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Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 28 Nov 2011 03:57:09 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/28/t1322470762qqovyswcew0eng0.htm/, Retrieved Fri, 29 Mar 2024 05:14:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147635, Retrieved Fri, 29 Mar 2024 05:14:04 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact105
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2011-11-28 08:57:09] [12e812fb765cb1bc3c59e8b2f53785ec] [Current]
- R P     [Multiple Regression] [] [2011-11-28 09:08:09] [c6dda33d269efe9a48a310f0c0798534]
- R  D      [Multiple Regression] [WS8- Multiple Lin...] [2011-11-29 12:56:45] [8b13b85c94b9a060d82f72930775ea89]
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Dataseries X:
235.1
280.7
264.6
240.7
201.4
240.8
241.1
223.8
206.1
174.7
203.3
220.5
299.5
347.4
338.3
327.7
351.6
396.6
438.8
395.6
363.5
378.8
357
369
464.8
479.1
431.3
366.5
326.3
355.1
331.6
261.3
249
205.5
235.6
240.9
264.9
253.8
232.3
193.8
177
213.2
207.2
180.6
188.6
175.4
199
179.6
225.8
234
200.2
183.6
178.2
203.2
208.5
191.8
172.8
148
159.4
154.5
213.2
196.4
182.8
176.4
153.6
173.2
171
151.2
161.9
157.2
201.7
236.4
356.1
398.3
403.7
384.6
365.8
368.1
367.9
347
343.3
292.9
311.5
300.9
366.9
356.9
329.7
316.2
269
289.3
266.2
253.6
233.8
228.4
253.6
260.1
306.6
309.2
309.5
271
279.9
317.9
298.4
246.7
227.3
209.1
259.9
266
320.6
308.5
282.2
262.7
263.5
313.1
284.3
252.6
250.3
246.5
312.7
333.2
446.4
511.6
515.5
506.4
483.2
522.3
509.8
460.7
405.8
375
378.5
406.8
467.8
469.8
429.8
355.8
332.7
378
360.5
334.7
319.5
323.1
363.6
352.1
411.9
388.6
416.4
360.7
338
417.2
388.4
371.1
331.5
353.7
396.7
447
533.5
565.4
542.3
488.7
467.1
531.3
496.1
444
403.4
386.3
394.1
404.1
462.1
448.1
432.3
386.3
395.2
421.9
382.9
384.2
345.5
323.4
372.6
376
462.7
487
444.2
399.3
394.9
455.4
414
375.5
347
339.4
385.8
378.8
451.8
446.1
422.5
383.1
352.8
445.3
367.5
355.1
326.2
319.8
331.8
340.9
394.1
417.2
369.9
349.2
321.4
405.7
342.9
316.5
284.2
270.9
288.8
278.8
324.4
310.9
299
273
279.3
359.2
305
282.1
250.3
246.5
257.9
266.5
315.9
318.4
295.4
266.4
245.8
362.8
324.9
294.2
289.5
295.2
290.3
272
307.4
328.7
292.9
249.1
230.4
361.5
321.7
277.2
260.7
251
257.6
241.8
287.5
292.3
274.7
254.2
230
339
318.2
287
295.8
284
271
262.7
340.6
379.4
373.3
355.2
338.4
466.9
451
422
429.2
425.9
460.7
463.6
541.4
544.2
517.5
469.4
439.4
549
533
506.1
484
457
481.5
469.5
544.7
541.2
521.5
469.7
434.4
542.6
517.3
485.7
465.8
447
426.6
411.6
467.5
484.5
451.2
417.4
379.9
484.7
455
420.8
416.5
376.3
405.6
405.8
500.8
514
475.5
430.1
414.4
538
526
488.5
520.2
504.4
568.5
610.6
818
830.9
835.9
782
762.3
856.9
820.9
769.6
752.2
724.4
723.1
719.5
817.4
803.3
752.5
689
630.4
765.5
757.7
732.2
702.6
683.3
709.5
702.2
784.8
810.9
755.6
656.8
615.1
745.3
694.1
675.7
643.7
622.1
634.6
588
689.7
673.9
647.9
568.8
545.7
632.6
643.8
593.1
579.7
546
562.9
572.5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 11 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147635&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]11 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147635&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147635&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Unempl[t] = + 371.996774193548 + 61.0322580645162M1[t] + 70.9290322580645M2[t] + 48.6612903225807M3[t] + 9.73870967741936M4[t] -10.8M5[t] + 61.9258064516129M6[t] + 39.1548387096774M7[t] + 8.00967741935485M8[t] -9.09677419354837M9[t] -24.5387096774193M10[t] -2.46774193548386M11[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Unempl[t] =  +  371.996774193548 +  61.0322580645162M1[t] +  70.9290322580645M2[t] +  48.6612903225807M3[t] +  9.73870967741936M4[t] -10.8M5[t] +  61.9258064516129M6[t] +  39.1548387096774M7[t] +  8.00967741935485M8[t] -9.09677419354837M9[t] -24.5387096774193M10[t] -2.46774193548386M11[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147635&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Unempl[t] =  +  371.996774193548 +  61.0322580645162M1[t] +  70.9290322580645M2[t] +  48.6612903225807M3[t] +  9.73870967741936M4[t] -10.8M5[t] +  61.9258064516129M6[t] +  39.1548387096774M7[t] +  8.00967741935485M8[t] -9.09677419354837M9[t] -24.5387096774193M10[t] -2.46774193548386M11[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147635&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147635&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Estimated Regression Equation
Unempl[t] = + 371.996774193548 + 61.0322580645162M1[t] + 70.9290322580645M2[t] + 48.6612903225807M3[t] + 9.73870967741936M4[t] -10.8M5[t] + 61.9258064516129M6[t] + 39.1548387096774M7[t] + 8.00967741935485M8[t] -9.09677419354837M9[t] -24.5387096774193M10[t] -2.46774193548386M11[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)371.99677419354827.66716913.445400
M161.032258064516239.1272861.55980.1196770.059838
M270.929032258064539.1272861.81280.0706990.03535
M348.661290322580739.1272861.24370.2144320.107216
M49.7387096774193639.1272860.24890.8035810.401791
M5-10.839.127286-0.2760.7826890.391345
M661.925806451612939.1272861.58270.1143730.057187
M739.154838709677439.1272861.00070.3176420.158821
M88.0096774193548539.1272860.20470.8379160.418958
M9-9.0967741935483739.127286-0.23250.8162880.408144
M10-24.538709677419339.127286-0.62720.5309580.265479
M11-2.4677419354838639.127286-0.06310.9497460.474873

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 371.996774193548 & 27.667169 & 13.4454 & 0 & 0 \tabularnewline
M1 & 61.0322580645162 & 39.127286 & 1.5598 & 0.119677 & 0.059838 \tabularnewline
M2 & 70.9290322580645 & 39.127286 & 1.8128 & 0.070699 & 0.03535 \tabularnewline
M3 & 48.6612903225807 & 39.127286 & 1.2437 & 0.214432 & 0.107216 \tabularnewline
M4 & 9.73870967741936 & 39.127286 & 0.2489 & 0.803581 & 0.401791 \tabularnewline
M5 & -10.8 & 39.127286 & -0.276 & 0.782689 & 0.391345 \tabularnewline
M6 & 61.9258064516129 & 39.127286 & 1.5827 & 0.114373 & 0.057187 \tabularnewline
M7 & 39.1548387096774 & 39.127286 & 1.0007 & 0.317642 & 0.158821 \tabularnewline
M8 & 8.00967741935485 & 39.127286 & 0.2047 & 0.837916 & 0.418958 \tabularnewline
M9 & -9.09677419354837 & 39.127286 & -0.2325 & 0.816288 & 0.408144 \tabularnewline
M10 & -24.5387096774193 & 39.127286 & -0.6272 & 0.530958 & 0.265479 \tabularnewline
M11 & -2.46774193548386 & 39.127286 & -0.0631 & 0.949746 & 0.474873 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147635&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]371.996774193548[/C][C]27.667169[/C][C]13.4454[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]M1[/C][C]61.0322580645162[/C][C]39.127286[/C][C]1.5598[/C][C]0.119677[/C][C]0.059838[/C][/ROW]
[ROW][C]M2[/C][C]70.9290322580645[/C][C]39.127286[/C][C]1.8128[/C][C]0.070699[/C][C]0.03535[/C][/ROW]
[ROW][C]M3[/C][C]48.6612903225807[/C][C]39.127286[/C][C]1.2437[/C][C]0.214432[/C][C]0.107216[/C][/ROW]
[ROW][C]M4[/C][C]9.73870967741936[/C][C]39.127286[/C][C]0.2489[/C][C]0.803581[/C][C]0.401791[/C][/ROW]
[ROW][C]M5[/C][C]-10.8[/C][C]39.127286[/C][C]-0.276[/C][C]0.782689[/C][C]0.391345[/C][/ROW]
[ROW][C]M6[/C][C]61.9258064516129[/C][C]39.127286[/C][C]1.5827[/C][C]0.114373[/C][C]0.057187[/C][/ROW]
[ROW][C]M7[/C][C]39.1548387096774[/C][C]39.127286[/C][C]1.0007[/C][C]0.317642[/C][C]0.158821[/C][/ROW]
[ROW][C]M8[/C][C]8.00967741935485[/C][C]39.127286[/C][C]0.2047[/C][C]0.837916[/C][C]0.418958[/C][/ROW]
[ROW][C]M9[/C][C]-9.09677419354837[/C][C]39.127286[/C][C]-0.2325[/C][C]0.816288[/C][C]0.408144[/C][/ROW]
[ROW][C]M10[/C][C]-24.5387096774193[/C][C]39.127286[/C][C]-0.6272[/C][C]0.530958[/C][C]0.265479[/C][/ROW]
[ROW][C]M11[/C][C]-2.46774193548386[/C][C]39.127286[/C][C]-0.0631[/C][C]0.949746[/C][C]0.474873[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147635&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147635&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)371.99677419354827.66716913.445400
M161.032258064516239.1272861.55980.1196770.059838
M270.929032258064539.1272861.81280.0706990.03535
M348.661290322580739.1272861.24370.2144320.107216
M49.7387096774193639.1272860.24890.8035810.401791
M5-10.839.127286-0.2760.7826890.391345
M661.925806451612939.1272861.58270.1143730.057187
M739.154838709677439.1272861.00070.3176420.158821
M88.0096774193548539.1272860.20470.8379160.418958
M9-9.0967741935483739.127286-0.23250.8162880.408144
M10-24.538709677419339.127286-0.62720.5309580.265479
M11-2.4677419354838639.127286-0.06310.9497460.474873







Multiple Linear Regression - Regression Statistics
Multiple R0.205441285799401
R-squared0.042206121910911
Adjusted R-squared0.0129401978581889
F-TEST (value)1.44215920996983
F-TEST (DF numerator)11
F-TEST (DF denominator)360
p-value0.151968787365977
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation154.04427987784
Sum Squared Residuals8542670.45870968

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.205441285799401 \tabularnewline
R-squared & 0.042206121910911 \tabularnewline
Adjusted R-squared & 0.0129401978581889 \tabularnewline
F-TEST (value) & 1.44215920996983 \tabularnewline
F-TEST (DF numerator) & 11 \tabularnewline
F-TEST (DF denominator) & 360 \tabularnewline
p-value & 0.151968787365977 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 154.04427987784 \tabularnewline
Sum Squared Residuals & 8542670.45870968 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147635&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.205441285799401[/C][/ROW]
[ROW][C]R-squared[/C][C]0.042206121910911[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0129401978581889[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]1.44215920996983[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]11[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]360[/C][/ROW]
[ROW][C]p-value[/C][C]0.151968787365977[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]154.04427987784[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]8542670.45870968[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147635&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147635&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R0.205441285799401
R-squared0.042206121910911
Adjusted R-squared0.0129401978581889
F-TEST (value)1.44215920996983
F-TEST (DF numerator)11
F-TEST (DF denominator)360
p-value0.151968787365977
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation154.04427987784
Sum Squared Residuals8542670.45870968







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1235.1433.029032258064-197.929032258064
2280.7442.925806451613-162.225806451613
3264.6420.658064516129-156.058064516129
4240.7381.735483870968-141.035483870968
5201.4361.196774193548-159.796774193548
6240.8433.922580645161-193.122580645161
7241.1411.151612903226-170.051612903226
8223.8380.006451612903-156.206451612903
9206.1362.9-156.8
10174.7347.458064516129-172.758064516129
11203.3369.529032258064-166.229032258065
12220.5371.996774193548-151.496774193548
13299.5433.029032258064-133.529032258065
14347.4442.925806451613-95.5258064516129
15338.3420.658064516129-82.358064516129
16327.7381.735483870968-54.0354838709677
17351.6361.196774193548-9.59677419354836
18396.6433.922580645161-37.3225806451613
19438.8411.15161290322627.6483870967742
20395.6380.00645161290315.5935483870968
21363.5362.90.600000000000004
22378.8347.45806451612931.341935483871
23357369.529032258065-12.5290322580645
24369371.996774193548-2.99677419354836
25464.8433.02903225806531.7709677419355
26479.1442.92580645161336.1741935483871
27431.3420.65806451612910.641935483871
28366.5381.735483870968-15.2354838709677
29326.3361.196774193548-34.8967741935484
30355.1433.922580645161-78.8225806451613
31331.6411.151612903226-79.5516129032258
32261.3380.006451612903-118.706451612903
33249362.9-113.9
34205.5347.458064516129-141.958064516129
35235.6369.529032258064-133.929032258065
36240.9371.996774193548-131.096774193548
37264.9433.029032258064-168.129032258065
38253.8442.925806451613-189.125806451613
39232.3420.658064516129-188.358064516129
40193.8381.735483870968-187.935483870968
41177361.196774193548-184.196774193548
42213.2433.922580645161-220.722580645161
43207.2411.151612903226-203.951612903226
44180.6380.006451612903-199.406451612903
45188.6362.9-174.3
46175.4347.458064516129-172.058064516129
47199369.529032258065-170.529032258065
48179.6371.996774193548-192.396774193548
49225.8433.029032258064-207.229032258065
50234442.925806451613-208.925806451613
51200.2420.658064516129-220.458064516129
52183.6381.735483870968-198.135483870968
53178.2361.196774193548-182.996774193548
54203.2433.922580645161-230.722580645161
55208.5411.151612903226-202.651612903226
56191.8380.006451612903-188.206451612903
57172.8362.9-190.1
58148347.458064516129-199.458064516129
59159.4369.529032258065-210.129032258065
60154.5371.996774193548-217.496774193548
61213.2433.029032258064-219.829032258065
62196.4442.925806451613-246.525806451613
63182.8420.658064516129-237.858064516129
64176.4381.735483870968-205.335483870968
65153.6361.196774193548-207.596774193548
66173.2433.922580645161-260.722580645161
67171411.151612903226-240.151612903226
68151.2380.006451612903-228.806451612903
69161.9362.9-201
70157.2347.458064516129-190.258064516129
71201.7369.529032258065-167.829032258065
72236.4371.996774193548-135.596774193548
73356.1433.029032258065-76.9290322580645
74398.3442.925806451613-44.6258064516129
75403.7420.658064516129-16.958064516129
76384.6381.7354838709682.86451612903229
77365.8361.1967741935484.60322580645163
78368.1433.922580645161-65.8225806451613
79367.9411.151612903226-43.2516129032258
80347380.006451612903-33.0064516129032
81343.3362.9-19.6
82292.9347.458064516129-54.5580645161291
83311.5369.529032258064-58.0290322580645
84300.9371.996774193548-71.0967741935484
85366.9433.029032258065-66.1290322580646
86356.9442.925806451613-86.0258064516129
87329.7420.658064516129-90.958064516129
88316.2381.735483870968-65.5354838709678
89269361.196774193548-92.1967741935484
90289.3433.922580645161-144.622580645161
91266.2411.151612903226-144.951612903226
92253.6380.006451612903-126.406451612903
93233.8362.9-129.1
94228.4347.458064516129-119.058064516129
95253.6369.529032258064-115.929032258065
96260.1371.996774193548-111.896774193548
97306.6433.029032258064-126.429032258064
98309.2442.925806451613-133.725806451613
99309.5420.658064516129-111.158064516129
100271381.735483870968-110.735483870968
101279.9361.196774193548-81.2967741935484
102317.9433.922580645161-116.022580645161
103298.4411.151612903226-112.751612903226
104246.7380.006451612903-133.306451612903
105227.3362.9-135.6
106209.1347.458064516129-138.358064516129
107259.9369.529032258064-109.629032258065
108266371.996774193548-105.996774193548
109320.6433.029032258064-112.429032258064
110308.5442.925806451613-134.425806451613
111282.2420.658064516129-138.458064516129
112262.7381.735483870968-119.035483870968
113263.5361.196774193548-97.6967741935484
114313.1433.922580645161-120.822580645161
115284.3411.151612903226-126.851612903226
116252.6380.006451612903-127.406451612903
117250.3362.9-112.6
118246.5347.458064516129-100.958064516129
119312.7369.529032258065-56.8290322580645
120333.2371.996774193548-38.7967741935484
121446.4433.02903225806513.3709677419354
122511.6442.92580645161368.6741935483871
123515.5420.65806451612994.841935483871
124506.4381.735483870968124.664516129032
125483.2361.196774193548122.003225806452
126522.3433.92258064516188.3774193548387
127509.8411.15161290322698.6483870967742
128460.7380.00645161290380.6935483870968
129405.8362.942.9
130375347.45806451612927.541935483871
131378.5369.5290322580648.97096774193549
132406.8371.99677419354834.8032258064516
133467.8433.02903225806534.7709677419355
134469.8442.92580645161326.8741935483871
135429.8420.6580645161299.14193548387101
136355.8381.735483870968-25.9354838709677
137332.7361.196774193548-28.4967741935484
138378433.922580645161-55.9225806451613
139360.5411.151612903226-50.6516129032258
140334.7380.006451612903-45.3064516129032
141319.5362.9-43.4
142323.1347.458064516129-24.358064516129
143363.6369.529032258064-5.92903225806449
144352.1371.996774193548-19.8967741935483
145411.9433.029032258065-21.1290322580645
146388.6442.925806451613-54.3258064516129
147416.4420.658064516129-4.25806451612903
148360.7381.735483870968-21.0354838709677
149338361.196774193548-23.1967741935484
150417.2433.922580645161-16.7225806451613
151388.4411.151612903226-22.7516129032258
152371.1380.006451612903-8.90645161290322
153331.5362.9-31.4
154353.7347.4580645161296.24193548387097
155396.7369.52903225806427.1709677419355
156447371.99677419354875.0032258064516
157533.5433.029032258065100.470967741935
158565.4442.925806451613122.474193548387
159542.3420.658064516129121.641935483871
160488.7381.735483870968106.964516129032
161467.1361.196774193548105.903225806452
162531.3433.92258064516197.3774193548387
163496.1411.15161290322684.9483870967742
164444380.00645161290363.9935483870968
165403.4362.940.5
166386.3347.45806451612938.841935483871
167394.1369.52903225806424.5709677419355
168404.1371.99677419354832.1032258064516
169462.1433.02903225806529.0709677419355
170448.1442.9258064516135.17419354838711
171432.3420.65806451612911.641935483871
172386.3381.7354838709684.56451612903227
173395.2361.19677419354834.0032258064516
174421.9433.922580645161-12.0225806451613
175382.9411.151612903226-28.2516129032258
176384.2380.0064516129034.19354838709675
177345.5362.9-17.4
178323.4347.458064516129-24.0580645161291
179372.6369.5290322580643.07096774193551
180376371.9967741935484.00322580645163
181462.7433.02903225806529.6709677419355
182487442.92580645161344.0741935483871
183444.2420.65806451612923.541935483871
184399.3381.73548387096817.5645161290323
185394.9361.19677419354833.7032258064516
186455.4433.92258064516121.4774193548387
187414411.1516129032262.8483870967742
188375.5380.006451612903-4.50645161290324
189347362.9-15.9
190339.4347.458064516129-8.05806451612904
191385.8369.52903225806416.2709677419355
192378.8371.9967741935486.80322580645164
193451.8433.02903225806518.7709677419355
194446.1442.9258064516133.17419354838711
195422.5420.6580645161291.84193548387099
196383.1381.7354838709681.36451612903228
197352.8361.196774193548-8.39677419354837
198445.3433.92258064516111.3774193548387
199367.5411.151612903226-43.6516129032258
200355.1380.006451612903-24.9064516129032
201326.2362.9-36.7
202319.8347.458064516129-27.658064516129
203331.8369.529032258064-37.7290322580645
204340.9371.996774193548-31.0967741935484
205394.1433.029032258065-38.9290322580645
206417.2442.925806451613-25.7258064516129
207369.9420.658064516129-50.758064516129
208349.2381.735483870968-32.5354838709677
209321.4361.196774193548-39.7967741935484
210405.7433.922580645161-28.2225806451613
211342.9411.151612903226-68.2516129032258
212316.5380.006451612903-63.5064516129032
213284.2362.9-78.7
214270.9347.458064516129-76.558064516129
215288.8369.529032258064-80.7290322580645
216278.8371.996774193548-93.1967741935483
217324.4433.029032258065-108.629032258065
218310.9442.925806451613-132.025806451613
219299420.658064516129-121.658064516129
220273381.735483870968-108.735483870968
221279.3361.196774193548-81.8967741935484
222359.2433.922580645161-74.7225806451613
223305411.151612903226-106.151612903226
224282.1380.006451612903-97.9064516129032
225250.3362.9-112.6
226246.5347.458064516129-100.958064516129
227257.9369.529032258064-111.629032258065
228266.5371.996774193548-105.496774193548
229315.9433.029032258064-117.129032258065
230318.4442.925806451613-124.525806451613
231295.4420.658064516129-125.258064516129
232266.4381.735483870968-115.335483870968
233245.8361.196774193548-115.396774193548
234362.8433.922580645161-71.1225806451613
235324.9411.151612903226-86.2516129032258
236294.2380.006451612903-85.8064516129032
237289.5362.9-73.4
238295.2347.458064516129-52.258064516129
239290.3369.529032258064-79.2290322580645
240272371.996774193548-99.9967741935483
241307.4433.029032258064-125.629032258065
242328.7442.925806451613-114.225806451613
243292.9420.658064516129-127.758064516129
244249.1381.735483870968-132.635483870968
245230.4361.196774193548-130.796774193548
246361.5433.922580645161-72.4225806451613
247321.7411.151612903226-89.4516129032258
248277.2380.006451612903-102.806451612903
249260.7362.9-102.2
250251347.458064516129-96.458064516129
251257.6369.529032258064-111.929032258064
252241.8371.996774193548-130.196774193548
253287.5433.029032258064-145.529032258065
254292.3442.925806451613-150.625806451613
255274.7420.658064516129-145.958064516129
256254.2381.735483870968-127.535483870968
257230361.196774193548-131.196774193548
258339433.922580645161-94.9225806451613
259318.2411.151612903226-92.9516129032258
260287380.006451612903-93.0064516129032
261295.8362.9-67.1
262284347.458064516129-63.458064516129
263271369.529032258064-98.5290322580645
264262.7371.996774193548-109.296774193548
265340.6433.029032258065-92.4290322580645
266379.4442.925806451613-63.5258064516129
267373.3420.658064516129-47.358064516129
268355.2381.735483870968-26.5354838709677
269338.4361.196774193548-22.7967741935484
270466.9433.92258064516132.9774193548387
271451411.15161290322639.8483870967742
272422380.00645161290341.9935483870968
273429.2362.966.3
274425.9347.45806451612978.4419354838709
275460.7369.52903225806591.1709677419355
276463.6371.99677419354891.6032258064516
277541.4433.029032258065108.370967741935
278544.2442.925806451613101.274193548387
279517.5420.65806451612996.841935483871
280469.4381.73548387096887.6645161290322
281439.4361.19677419354878.2032258064516
282549433.922580645161115.077419354839
283533411.151612903226121.848387096774
284506.1380.006451612903126.093548387097
285484362.9121.1
286457347.458064516129109.541935483871
287481.5369.529032258064111.970967741935
288469.5371.99677419354897.5032258064516
289544.7433.029032258065111.670967741935
290541.2442.92580645161398.2741935483871
291521.5420.658064516129100.841935483871
292469.7381.73548387096887.9645161290322
293434.4361.19677419354873.2032258064516
294542.6433.922580645161108.677419354839
295517.3411.151612903226106.148387096774
296485.7380.006451612903105.693548387097
297465.8362.9102.9
298447347.45806451612999.541935483871
299426.6369.52903225806457.0709677419355
300411.6371.99677419354839.6032258064517
301467.5433.02903225806534.4709677419355
302484.5442.92580645161341.5741935483871
303451.2420.65806451612930.541935483871
304417.4381.73548387096835.6645161290322
305379.9361.19677419354818.7032258064516
306484.7433.92258064516150.7774193548387
307455411.15161290322643.8483870967742
308420.8380.00645161290340.7935483870968
309416.5362.953.6
310376.3347.45806451612928.841935483871
311405.6369.52903225806536.0709677419355
312405.8371.99677419354833.8032258064516
313500.8433.02903225806467.7709677419355
314514442.92580645161371.0741935483871
315475.5420.65806451612954.841935483871
316430.1381.73548387096848.3645161290323
317414.4361.19677419354853.2032258064516
318538433.922580645161104.077419354839
319526411.151612903226114.848387096774
320488.5380.006451612903108.493548387097
321520.2362.9157.3
322504.4347.458064516129156.941935483871
323568.5369.529032258065198.970967741935
324610.6371.996774193548238.603225806452
325818433.029032258065384.970967741935
326830.9442.925806451613387.974193548387
327835.9420.658064516129415.241935483871
328782381.735483870968400.264516129032
329762.3361.196774193548401.103225806452
330856.9433.922580645161422.977419354839
331820.9411.151612903226409.748387096774
332769.6380.006451612903389.593548387097
333752.2362.9389.3
334724.4347.458064516129376.941935483871
335723.1369.529032258065353.570967741935
336719.5371.996774193548347.503225806452
337817.4433.029032258065384.370967741935
338803.3442.925806451613360.374193548387
339752.5420.658064516129331.841935483871
340689381.735483870968307.264516129032
341630.4361.196774193548269.203225806452
342765.5433.922580645161331.577419354839
343757.7411.151612903226346.548387096774
344732.2380.006451612903352.193548387097
345702.6362.9339.7
346683.3347.458064516129335.841935483871
347709.5369.529032258065339.970967741935
348702.2371.996774193548330.203225806452
349784.8433.029032258065351.770967741935
350810.9442.925806451613367.974193548387
351755.6420.658064516129334.941935483871
352656.8381.735483870968275.064516129032
353615.1361.196774193548253.903225806452
354745.3433.922580645161311.377419354839
355694.1411.151612903226282.948387096774
356675.7380.006451612903295.693548387097
357643.7362.9280.8
358622.1347.458064516129274.641935483871
359634.6369.529032258065265.070967741935
360588371.996774193548216.003225806452
361689.7433.029032258064256.670967741936
362673.9442.925806451613230.974193548387
363647.9420.658064516129227.241935483871
364568.8381.735483870968187.064516129032
365545.7361.196774193548184.503225806452
366632.6433.922580645161198.677419354839
367643.8411.151612903226232.648387096774
368593.1380.006451612903213.093548387097
369579.7362.9216.8
370546347.458064516129198.541935483871
371562.9369.529032258065193.370967741935
372572.5371.996774193548200.503225806452

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 235.1 & 433.029032258064 & -197.929032258064 \tabularnewline
2 & 280.7 & 442.925806451613 & -162.225806451613 \tabularnewline
3 & 264.6 & 420.658064516129 & -156.058064516129 \tabularnewline
4 & 240.7 & 381.735483870968 & -141.035483870968 \tabularnewline
5 & 201.4 & 361.196774193548 & -159.796774193548 \tabularnewline
6 & 240.8 & 433.922580645161 & -193.122580645161 \tabularnewline
7 & 241.1 & 411.151612903226 & -170.051612903226 \tabularnewline
8 & 223.8 & 380.006451612903 & -156.206451612903 \tabularnewline
9 & 206.1 & 362.9 & -156.8 \tabularnewline
10 & 174.7 & 347.458064516129 & -172.758064516129 \tabularnewline
11 & 203.3 & 369.529032258064 & -166.229032258065 \tabularnewline
12 & 220.5 & 371.996774193548 & -151.496774193548 \tabularnewline
13 & 299.5 & 433.029032258064 & -133.529032258065 \tabularnewline
14 & 347.4 & 442.925806451613 & -95.5258064516129 \tabularnewline
15 & 338.3 & 420.658064516129 & -82.358064516129 \tabularnewline
16 & 327.7 & 381.735483870968 & -54.0354838709677 \tabularnewline
17 & 351.6 & 361.196774193548 & -9.59677419354836 \tabularnewline
18 & 396.6 & 433.922580645161 & -37.3225806451613 \tabularnewline
19 & 438.8 & 411.151612903226 & 27.6483870967742 \tabularnewline
20 & 395.6 & 380.006451612903 & 15.5935483870968 \tabularnewline
21 & 363.5 & 362.9 & 0.600000000000004 \tabularnewline
22 & 378.8 & 347.458064516129 & 31.341935483871 \tabularnewline
23 & 357 & 369.529032258065 & -12.5290322580645 \tabularnewline
24 & 369 & 371.996774193548 & -2.99677419354836 \tabularnewline
25 & 464.8 & 433.029032258065 & 31.7709677419355 \tabularnewline
26 & 479.1 & 442.925806451613 & 36.1741935483871 \tabularnewline
27 & 431.3 & 420.658064516129 & 10.641935483871 \tabularnewline
28 & 366.5 & 381.735483870968 & -15.2354838709677 \tabularnewline
29 & 326.3 & 361.196774193548 & -34.8967741935484 \tabularnewline
30 & 355.1 & 433.922580645161 & -78.8225806451613 \tabularnewline
31 & 331.6 & 411.151612903226 & -79.5516129032258 \tabularnewline
32 & 261.3 & 380.006451612903 & -118.706451612903 \tabularnewline
33 & 249 & 362.9 & -113.9 \tabularnewline
34 & 205.5 & 347.458064516129 & -141.958064516129 \tabularnewline
35 & 235.6 & 369.529032258064 & -133.929032258065 \tabularnewline
36 & 240.9 & 371.996774193548 & -131.096774193548 \tabularnewline
37 & 264.9 & 433.029032258064 & -168.129032258065 \tabularnewline
38 & 253.8 & 442.925806451613 & -189.125806451613 \tabularnewline
39 & 232.3 & 420.658064516129 & -188.358064516129 \tabularnewline
40 & 193.8 & 381.735483870968 & -187.935483870968 \tabularnewline
41 & 177 & 361.196774193548 & -184.196774193548 \tabularnewline
42 & 213.2 & 433.922580645161 & -220.722580645161 \tabularnewline
43 & 207.2 & 411.151612903226 & -203.951612903226 \tabularnewline
44 & 180.6 & 380.006451612903 & -199.406451612903 \tabularnewline
45 & 188.6 & 362.9 & -174.3 \tabularnewline
46 & 175.4 & 347.458064516129 & -172.058064516129 \tabularnewline
47 & 199 & 369.529032258065 & -170.529032258065 \tabularnewline
48 & 179.6 & 371.996774193548 & -192.396774193548 \tabularnewline
49 & 225.8 & 433.029032258064 & -207.229032258065 \tabularnewline
50 & 234 & 442.925806451613 & -208.925806451613 \tabularnewline
51 & 200.2 & 420.658064516129 & -220.458064516129 \tabularnewline
52 & 183.6 & 381.735483870968 & -198.135483870968 \tabularnewline
53 & 178.2 & 361.196774193548 & -182.996774193548 \tabularnewline
54 & 203.2 & 433.922580645161 & -230.722580645161 \tabularnewline
55 & 208.5 & 411.151612903226 & -202.651612903226 \tabularnewline
56 & 191.8 & 380.006451612903 & -188.206451612903 \tabularnewline
57 & 172.8 & 362.9 & -190.1 \tabularnewline
58 & 148 & 347.458064516129 & -199.458064516129 \tabularnewline
59 & 159.4 & 369.529032258065 & -210.129032258065 \tabularnewline
60 & 154.5 & 371.996774193548 & -217.496774193548 \tabularnewline
61 & 213.2 & 433.029032258064 & -219.829032258065 \tabularnewline
62 & 196.4 & 442.925806451613 & -246.525806451613 \tabularnewline
63 & 182.8 & 420.658064516129 & -237.858064516129 \tabularnewline
64 & 176.4 & 381.735483870968 & -205.335483870968 \tabularnewline
65 & 153.6 & 361.196774193548 & -207.596774193548 \tabularnewline
66 & 173.2 & 433.922580645161 & -260.722580645161 \tabularnewline
67 & 171 & 411.151612903226 & -240.151612903226 \tabularnewline
68 & 151.2 & 380.006451612903 & -228.806451612903 \tabularnewline
69 & 161.9 & 362.9 & -201 \tabularnewline
70 & 157.2 & 347.458064516129 & -190.258064516129 \tabularnewline
71 & 201.7 & 369.529032258065 & -167.829032258065 \tabularnewline
72 & 236.4 & 371.996774193548 & -135.596774193548 \tabularnewline
73 & 356.1 & 433.029032258065 & -76.9290322580645 \tabularnewline
74 & 398.3 & 442.925806451613 & -44.6258064516129 \tabularnewline
75 & 403.7 & 420.658064516129 & -16.958064516129 \tabularnewline
76 & 384.6 & 381.735483870968 & 2.86451612903229 \tabularnewline
77 & 365.8 & 361.196774193548 & 4.60322580645163 \tabularnewline
78 & 368.1 & 433.922580645161 & -65.8225806451613 \tabularnewline
79 & 367.9 & 411.151612903226 & -43.2516129032258 \tabularnewline
80 & 347 & 380.006451612903 & -33.0064516129032 \tabularnewline
81 & 343.3 & 362.9 & -19.6 \tabularnewline
82 & 292.9 & 347.458064516129 & -54.5580645161291 \tabularnewline
83 & 311.5 & 369.529032258064 & -58.0290322580645 \tabularnewline
84 & 300.9 & 371.996774193548 & -71.0967741935484 \tabularnewline
85 & 366.9 & 433.029032258065 & -66.1290322580646 \tabularnewline
86 & 356.9 & 442.925806451613 & -86.0258064516129 \tabularnewline
87 & 329.7 & 420.658064516129 & -90.958064516129 \tabularnewline
88 & 316.2 & 381.735483870968 & -65.5354838709678 \tabularnewline
89 & 269 & 361.196774193548 & -92.1967741935484 \tabularnewline
90 & 289.3 & 433.922580645161 & -144.622580645161 \tabularnewline
91 & 266.2 & 411.151612903226 & -144.951612903226 \tabularnewline
92 & 253.6 & 380.006451612903 & -126.406451612903 \tabularnewline
93 & 233.8 & 362.9 & -129.1 \tabularnewline
94 & 228.4 & 347.458064516129 & -119.058064516129 \tabularnewline
95 & 253.6 & 369.529032258064 & -115.929032258065 \tabularnewline
96 & 260.1 & 371.996774193548 & -111.896774193548 \tabularnewline
97 & 306.6 & 433.029032258064 & -126.429032258064 \tabularnewline
98 & 309.2 & 442.925806451613 & -133.725806451613 \tabularnewline
99 & 309.5 & 420.658064516129 & -111.158064516129 \tabularnewline
100 & 271 & 381.735483870968 & -110.735483870968 \tabularnewline
101 & 279.9 & 361.196774193548 & -81.2967741935484 \tabularnewline
102 & 317.9 & 433.922580645161 & -116.022580645161 \tabularnewline
103 & 298.4 & 411.151612903226 & -112.751612903226 \tabularnewline
104 & 246.7 & 380.006451612903 & -133.306451612903 \tabularnewline
105 & 227.3 & 362.9 & -135.6 \tabularnewline
106 & 209.1 & 347.458064516129 & -138.358064516129 \tabularnewline
107 & 259.9 & 369.529032258064 & -109.629032258065 \tabularnewline
108 & 266 & 371.996774193548 & -105.996774193548 \tabularnewline
109 & 320.6 & 433.029032258064 & -112.429032258064 \tabularnewline
110 & 308.5 & 442.925806451613 & -134.425806451613 \tabularnewline
111 & 282.2 & 420.658064516129 & -138.458064516129 \tabularnewline
112 & 262.7 & 381.735483870968 & -119.035483870968 \tabularnewline
113 & 263.5 & 361.196774193548 & -97.6967741935484 \tabularnewline
114 & 313.1 & 433.922580645161 & -120.822580645161 \tabularnewline
115 & 284.3 & 411.151612903226 & -126.851612903226 \tabularnewline
116 & 252.6 & 380.006451612903 & -127.406451612903 \tabularnewline
117 & 250.3 & 362.9 & -112.6 \tabularnewline
118 & 246.5 & 347.458064516129 & -100.958064516129 \tabularnewline
119 & 312.7 & 369.529032258065 & -56.8290322580645 \tabularnewline
120 & 333.2 & 371.996774193548 & -38.7967741935484 \tabularnewline
121 & 446.4 & 433.029032258065 & 13.3709677419354 \tabularnewline
122 & 511.6 & 442.925806451613 & 68.6741935483871 \tabularnewline
123 & 515.5 & 420.658064516129 & 94.841935483871 \tabularnewline
124 & 506.4 & 381.735483870968 & 124.664516129032 \tabularnewline
125 & 483.2 & 361.196774193548 & 122.003225806452 \tabularnewline
126 & 522.3 & 433.922580645161 & 88.3774193548387 \tabularnewline
127 & 509.8 & 411.151612903226 & 98.6483870967742 \tabularnewline
128 & 460.7 & 380.006451612903 & 80.6935483870968 \tabularnewline
129 & 405.8 & 362.9 & 42.9 \tabularnewline
130 & 375 & 347.458064516129 & 27.541935483871 \tabularnewline
131 & 378.5 & 369.529032258064 & 8.97096774193549 \tabularnewline
132 & 406.8 & 371.996774193548 & 34.8032258064516 \tabularnewline
133 & 467.8 & 433.029032258065 & 34.7709677419355 \tabularnewline
134 & 469.8 & 442.925806451613 & 26.8741935483871 \tabularnewline
135 & 429.8 & 420.658064516129 & 9.14193548387101 \tabularnewline
136 & 355.8 & 381.735483870968 & -25.9354838709677 \tabularnewline
137 & 332.7 & 361.196774193548 & -28.4967741935484 \tabularnewline
138 & 378 & 433.922580645161 & -55.9225806451613 \tabularnewline
139 & 360.5 & 411.151612903226 & -50.6516129032258 \tabularnewline
140 & 334.7 & 380.006451612903 & -45.3064516129032 \tabularnewline
141 & 319.5 & 362.9 & -43.4 \tabularnewline
142 & 323.1 & 347.458064516129 & -24.358064516129 \tabularnewline
143 & 363.6 & 369.529032258064 & -5.92903225806449 \tabularnewline
144 & 352.1 & 371.996774193548 & -19.8967741935483 \tabularnewline
145 & 411.9 & 433.029032258065 & -21.1290322580645 \tabularnewline
146 & 388.6 & 442.925806451613 & -54.3258064516129 \tabularnewline
147 & 416.4 & 420.658064516129 & -4.25806451612903 \tabularnewline
148 & 360.7 & 381.735483870968 & -21.0354838709677 \tabularnewline
149 & 338 & 361.196774193548 & -23.1967741935484 \tabularnewline
150 & 417.2 & 433.922580645161 & -16.7225806451613 \tabularnewline
151 & 388.4 & 411.151612903226 & -22.7516129032258 \tabularnewline
152 & 371.1 & 380.006451612903 & -8.90645161290322 \tabularnewline
153 & 331.5 & 362.9 & -31.4 \tabularnewline
154 & 353.7 & 347.458064516129 & 6.24193548387097 \tabularnewline
155 & 396.7 & 369.529032258064 & 27.1709677419355 \tabularnewline
156 & 447 & 371.996774193548 & 75.0032258064516 \tabularnewline
157 & 533.5 & 433.029032258065 & 100.470967741935 \tabularnewline
158 & 565.4 & 442.925806451613 & 122.474193548387 \tabularnewline
159 & 542.3 & 420.658064516129 & 121.641935483871 \tabularnewline
160 & 488.7 & 381.735483870968 & 106.964516129032 \tabularnewline
161 & 467.1 & 361.196774193548 & 105.903225806452 \tabularnewline
162 & 531.3 & 433.922580645161 & 97.3774193548387 \tabularnewline
163 & 496.1 & 411.151612903226 & 84.9483870967742 \tabularnewline
164 & 444 & 380.006451612903 & 63.9935483870968 \tabularnewline
165 & 403.4 & 362.9 & 40.5 \tabularnewline
166 & 386.3 & 347.458064516129 & 38.841935483871 \tabularnewline
167 & 394.1 & 369.529032258064 & 24.5709677419355 \tabularnewline
168 & 404.1 & 371.996774193548 & 32.1032258064516 \tabularnewline
169 & 462.1 & 433.029032258065 & 29.0709677419355 \tabularnewline
170 & 448.1 & 442.925806451613 & 5.17419354838711 \tabularnewline
171 & 432.3 & 420.658064516129 & 11.641935483871 \tabularnewline
172 & 386.3 & 381.735483870968 & 4.56451612903227 \tabularnewline
173 & 395.2 & 361.196774193548 & 34.0032258064516 \tabularnewline
174 & 421.9 & 433.922580645161 & -12.0225806451613 \tabularnewline
175 & 382.9 & 411.151612903226 & -28.2516129032258 \tabularnewline
176 & 384.2 & 380.006451612903 & 4.19354838709675 \tabularnewline
177 & 345.5 & 362.9 & -17.4 \tabularnewline
178 & 323.4 & 347.458064516129 & -24.0580645161291 \tabularnewline
179 & 372.6 & 369.529032258064 & 3.07096774193551 \tabularnewline
180 & 376 & 371.996774193548 & 4.00322580645163 \tabularnewline
181 & 462.7 & 433.029032258065 & 29.6709677419355 \tabularnewline
182 & 487 & 442.925806451613 & 44.0741935483871 \tabularnewline
183 & 444.2 & 420.658064516129 & 23.541935483871 \tabularnewline
184 & 399.3 & 381.735483870968 & 17.5645161290323 \tabularnewline
185 & 394.9 & 361.196774193548 & 33.7032258064516 \tabularnewline
186 & 455.4 & 433.922580645161 & 21.4774193548387 \tabularnewline
187 & 414 & 411.151612903226 & 2.8483870967742 \tabularnewline
188 & 375.5 & 380.006451612903 & -4.50645161290324 \tabularnewline
189 & 347 & 362.9 & -15.9 \tabularnewline
190 & 339.4 & 347.458064516129 & -8.05806451612904 \tabularnewline
191 & 385.8 & 369.529032258064 & 16.2709677419355 \tabularnewline
192 & 378.8 & 371.996774193548 & 6.80322580645164 \tabularnewline
193 & 451.8 & 433.029032258065 & 18.7709677419355 \tabularnewline
194 & 446.1 & 442.925806451613 & 3.17419354838711 \tabularnewline
195 & 422.5 & 420.658064516129 & 1.84193548387099 \tabularnewline
196 & 383.1 & 381.735483870968 & 1.36451612903228 \tabularnewline
197 & 352.8 & 361.196774193548 & -8.39677419354837 \tabularnewline
198 & 445.3 & 433.922580645161 & 11.3774193548387 \tabularnewline
199 & 367.5 & 411.151612903226 & -43.6516129032258 \tabularnewline
200 & 355.1 & 380.006451612903 & -24.9064516129032 \tabularnewline
201 & 326.2 & 362.9 & -36.7 \tabularnewline
202 & 319.8 & 347.458064516129 & -27.658064516129 \tabularnewline
203 & 331.8 & 369.529032258064 & -37.7290322580645 \tabularnewline
204 & 340.9 & 371.996774193548 & -31.0967741935484 \tabularnewline
205 & 394.1 & 433.029032258065 & -38.9290322580645 \tabularnewline
206 & 417.2 & 442.925806451613 & -25.7258064516129 \tabularnewline
207 & 369.9 & 420.658064516129 & -50.758064516129 \tabularnewline
208 & 349.2 & 381.735483870968 & -32.5354838709677 \tabularnewline
209 & 321.4 & 361.196774193548 & -39.7967741935484 \tabularnewline
210 & 405.7 & 433.922580645161 & -28.2225806451613 \tabularnewline
211 & 342.9 & 411.151612903226 & -68.2516129032258 \tabularnewline
212 & 316.5 & 380.006451612903 & -63.5064516129032 \tabularnewline
213 & 284.2 & 362.9 & -78.7 \tabularnewline
214 & 270.9 & 347.458064516129 & -76.558064516129 \tabularnewline
215 & 288.8 & 369.529032258064 & -80.7290322580645 \tabularnewline
216 & 278.8 & 371.996774193548 & -93.1967741935483 \tabularnewline
217 & 324.4 & 433.029032258065 & -108.629032258065 \tabularnewline
218 & 310.9 & 442.925806451613 & -132.025806451613 \tabularnewline
219 & 299 & 420.658064516129 & -121.658064516129 \tabularnewline
220 & 273 & 381.735483870968 & -108.735483870968 \tabularnewline
221 & 279.3 & 361.196774193548 & -81.8967741935484 \tabularnewline
222 & 359.2 & 433.922580645161 & -74.7225806451613 \tabularnewline
223 & 305 & 411.151612903226 & -106.151612903226 \tabularnewline
224 & 282.1 & 380.006451612903 & -97.9064516129032 \tabularnewline
225 & 250.3 & 362.9 & -112.6 \tabularnewline
226 & 246.5 & 347.458064516129 & -100.958064516129 \tabularnewline
227 & 257.9 & 369.529032258064 & -111.629032258065 \tabularnewline
228 & 266.5 & 371.996774193548 & -105.496774193548 \tabularnewline
229 & 315.9 & 433.029032258064 & -117.129032258065 \tabularnewline
230 & 318.4 & 442.925806451613 & -124.525806451613 \tabularnewline
231 & 295.4 & 420.658064516129 & -125.258064516129 \tabularnewline
232 & 266.4 & 381.735483870968 & -115.335483870968 \tabularnewline
233 & 245.8 & 361.196774193548 & -115.396774193548 \tabularnewline
234 & 362.8 & 433.922580645161 & -71.1225806451613 \tabularnewline
235 & 324.9 & 411.151612903226 & -86.2516129032258 \tabularnewline
236 & 294.2 & 380.006451612903 & -85.8064516129032 \tabularnewline
237 & 289.5 & 362.9 & -73.4 \tabularnewline
238 & 295.2 & 347.458064516129 & -52.258064516129 \tabularnewline
239 & 290.3 & 369.529032258064 & -79.2290322580645 \tabularnewline
240 & 272 & 371.996774193548 & -99.9967741935483 \tabularnewline
241 & 307.4 & 433.029032258064 & -125.629032258065 \tabularnewline
242 & 328.7 & 442.925806451613 & -114.225806451613 \tabularnewline
243 & 292.9 & 420.658064516129 & -127.758064516129 \tabularnewline
244 & 249.1 & 381.735483870968 & -132.635483870968 \tabularnewline
245 & 230.4 & 361.196774193548 & -130.796774193548 \tabularnewline
246 & 361.5 & 433.922580645161 & -72.4225806451613 \tabularnewline
247 & 321.7 & 411.151612903226 & -89.4516129032258 \tabularnewline
248 & 277.2 & 380.006451612903 & -102.806451612903 \tabularnewline
249 & 260.7 & 362.9 & -102.2 \tabularnewline
250 & 251 & 347.458064516129 & -96.458064516129 \tabularnewline
251 & 257.6 & 369.529032258064 & -111.929032258064 \tabularnewline
252 & 241.8 & 371.996774193548 & -130.196774193548 \tabularnewline
253 & 287.5 & 433.029032258064 & -145.529032258065 \tabularnewline
254 & 292.3 & 442.925806451613 & -150.625806451613 \tabularnewline
255 & 274.7 & 420.658064516129 & -145.958064516129 \tabularnewline
256 & 254.2 & 381.735483870968 & -127.535483870968 \tabularnewline
257 & 230 & 361.196774193548 & -131.196774193548 \tabularnewline
258 & 339 & 433.922580645161 & -94.9225806451613 \tabularnewline
259 & 318.2 & 411.151612903226 & -92.9516129032258 \tabularnewline
260 & 287 & 380.006451612903 & -93.0064516129032 \tabularnewline
261 & 295.8 & 362.9 & -67.1 \tabularnewline
262 & 284 & 347.458064516129 & -63.458064516129 \tabularnewline
263 & 271 & 369.529032258064 & -98.5290322580645 \tabularnewline
264 & 262.7 & 371.996774193548 & -109.296774193548 \tabularnewline
265 & 340.6 & 433.029032258065 & -92.4290322580645 \tabularnewline
266 & 379.4 & 442.925806451613 & -63.5258064516129 \tabularnewline
267 & 373.3 & 420.658064516129 & -47.358064516129 \tabularnewline
268 & 355.2 & 381.735483870968 & -26.5354838709677 \tabularnewline
269 & 338.4 & 361.196774193548 & -22.7967741935484 \tabularnewline
270 & 466.9 & 433.922580645161 & 32.9774193548387 \tabularnewline
271 & 451 & 411.151612903226 & 39.8483870967742 \tabularnewline
272 & 422 & 380.006451612903 & 41.9935483870968 \tabularnewline
273 & 429.2 & 362.9 & 66.3 \tabularnewline
274 & 425.9 & 347.458064516129 & 78.4419354838709 \tabularnewline
275 & 460.7 & 369.529032258065 & 91.1709677419355 \tabularnewline
276 & 463.6 & 371.996774193548 & 91.6032258064516 \tabularnewline
277 & 541.4 & 433.029032258065 & 108.370967741935 \tabularnewline
278 & 544.2 & 442.925806451613 & 101.274193548387 \tabularnewline
279 & 517.5 & 420.658064516129 & 96.841935483871 \tabularnewline
280 & 469.4 & 381.735483870968 & 87.6645161290322 \tabularnewline
281 & 439.4 & 361.196774193548 & 78.2032258064516 \tabularnewline
282 & 549 & 433.922580645161 & 115.077419354839 \tabularnewline
283 & 533 & 411.151612903226 & 121.848387096774 \tabularnewline
284 & 506.1 & 380.006451612903 & 126.093548387097 \tabularnewline
285 & 484 & 362.9 & 121.1 \tabularnewline
286 & 457 & 347.458064516129 & 109.541935483871 \tabularnewline
287 & 481.5 & 369.529032258064 & 111.970967741935 \tabularnewline
288 & 469.5 & 371.996774193548 & 97.5032258064516 \tabularnewline
289 & 544.7 & 433.029032258065 & 111.670967741935 \tabularnewline
290 & 541.2 & 442.925806451613 & 98.2741935483871 \tabularnewline
291 & 521.5 & 420.658064516129 & 100.841935483871 \tabularnewline
292 & 469.7 & 381.735483870968 & 87.9645161290322 \tabularnewline
293 & 434.4 & 361.196774193548 & 73.2032258064516 \tabularnewline
294 & 542.6 & 433.922580645161 & 108.677419354839 \tabularnewline
295 & 517.3 & 411.151612903226 & 106.148387096774 \tabularnewline
296 & 485.7 & 380.006451612903 & 105.693548387097 \tabularnewline
297 & 465.8 & 362.9 & 102.9 \tabularnewline
298 & 447 & 347.458064516129 & 99.541935483871 \tabularnewline
299 & 426.6 & 369.529032258064 & 57.0709677419355 \tabularnewline
300 & 411.6 & 371.996774193548 & 39.6032258064517 \tabularnewline
301 & 467.5 & 433.029032258065 & 34.4709677419355 \tabularnewline
302 & 484.5 & 442.925806451613 & 41.5741935483871 \tabularnewline
303 & 451.2 & 420.658064516129 & 30.541935483871 \tabularnewline
304 & 417.4 & 381.735483870968 & 35.6645161290322 \tabularnewline
305 & 379.9 & 361.196774193548 & 18.7032258064516 \tabularnewline
306 & 484.7 & 433.922580645161 & 50.7774193548387 \tabularnewline
307 & 455 & 411.151612903226 & 43.8483870967742 \tabularnewline
308 & 420.8 & 380.006451612903 & 40.7935483870968 \tabularnewline
309 & 416.5 & 362.9 & 53.6 \tabularnewline
310 & 376.3 & 347.458064516129 & 28.841935483871 \tabularnewline
311 & 405.6 & 369.529032258065 & 36.0709677419355 \tabularnewline
312 & 405.8 & 371.996774193548 & 33.8032258064516 \tabularnewline
313 & 500.8 & 433.029032258064 & 67.7709677419355 \tabularnewline
314 & 514 & 442.925806451613 & 71.0741935483871 \tabularnewline
315 & 475.5 & 420.658064516129 & 54.841935483871 \tabularnewline
316 & 430.1 & 381.735483870968 & 48.3645161290323 \tabularnewline
317 & 414.4 & 361.196774193548 & 53.2032258064516 \tabularnewline
318 & 538 & 433.922580645161 & 104.077419354839 \tabularnewline
319 & 526 & 411.151612903226 & 114.848387096774 \tabularnewline
320 & 488.5 & 380.006451612903 & 108.493548387097 \tabularnewline
321 & 520.2 & 362.9 & 157.3 \tabularnewline
322 & 504.4 & 347.458064516129 & 156.941935483871 \tabularnewline
323 & 568.5 & 369.529032258065 & 198.970967741935 \tabularnewline
324 & 610.6 & 371.996774193548 & 238.603225806452 \tabularnewline
325 & 818 & 433.029032258065 & 384.970967741935 \tabularnewline
326 & 830.9 & 442.925806451613 & 387.974193548387 \tabularnewline
327 & 835.9 & 420.658064516129 & 415.241935483871 \tabularnewline
328 & 782 & 381.735483870968 & 400.264516129032 \tabularnewline
329 & 762.3 & 361.196774193548 & 401.103225806452 \tabularnewline
330 & 856.9 & 433.922580645161 & 422.977419354839 \tabularnewline
331 & 820.9 & 411.151612903226 & 409.748387096774 \tabularnewline
332 & 769.6 & 380.006451612903 & 389.593548387097 \tabularnewline
333 & 752.2 & 362.9 & 389.3 \tabularnewline
334 & 724.4 & 347.458064516129 & 376.941935483871 \tabularnewline
335 & 723.1 & 369.529032258065 & 353.570967741935 \tabularnewline
336 & 719.5 & 371.996774193548 & 347.503225806452 \tabularnewline
337 & 817.4 & 433.029032258065 & 384.370967741935 \tabularnewline
338 & 803.3 & 442.925806451613 & 360.374193548387 \tabularnewline
339 & 752.5 & 420.658064516129 & 331.841935483871 \tabularnewline
340 & 689 & 381.735483870968 & 307.264516129032 \tabularnewline
341 & 630.4 & 361.196774193548 & 269.203225806452 \tabularnewline
342 & 765.5 & 433.922580645161 & 331.577419354839 \tabularnewline
343 & 757.7 & 411.151612903226 & 346.548387096774 \tabularnewline
344 & 732.2 & 380.006451612903 & 352.193548387097 \tabularnewline
345 & 702.6 & 362.9 & 339.7 \tabularnewline
346 & 683.3 & 347.458064516129 & 335.841935483871 \tabularnewline
347 & 709.5 & 369.529032258065 & 339.970967741935 \tabularnewline
348 & 702.2 & 371.996774193548 & 330.203225806452 \tabularnewline
349 & 784.8 & 433.029032258065 & 351.770967741935 \tabularnewline
350 & 810.9 & 442.925806451613 & 367.974193548387 \tabularnewline
351 & 755.6 & 420.658064516129 & 334.941935483871 \tabularnewline
352 & 656.8 & 381.735483870968 & 275.064516129032 \tabularnewline
353 & 615.1 & 361.196774193548 & 253.903225806452 \tabularnewline
354 & 745.3 & 433.922580645161 & 311.377419354839 \tabularnewline
355 & 694.1 & 411.151612903226 & 282.948387096774 \tabularnewline
356 & 675.7 & 380.006451612903 & 295.693548387097 \tabularnewline
357 & 643.7 & 362.9 & 280.8 \tabularnewline
358 & 622.1 & 347.458064516129 & 274.641935483871 \tabularnewline
359 & 634.6 & 369.529032258065 & 265.070967741935 \tabularnewline
360 & 588 & 371.996774193548 & 216.003225806452 \tabularnewline
361 & 689.7 & 433.029032258064 & 256.670967741936 \tabularnewline
362 & 673.9 & 442.925806451613 & 230.974193548387 \tabularnewline
363 & 647.9 & 420.658064516129 & 227.241935483871 \tabularnewline
364 & 568.8 & 381.735483870968 & 187.064516129032 \tabularnewline
365 & 545.7 & 361.196774193548 & 184.503225806452 \tabularnewline
366 & 632.6 & 433.922580645161 & 198.677419354839 \tabularnewline
367 & 643.8 & 411.151612903226 & 232.648387096774 \tabularnewline
368 & 593.1 & 380.006451612903 & 213.093548387097 \tabularnewline
369 & 579.7 & 362.9 & 216.8 \tabularnewline
370 & 546 & 347.458064516129 & 198.541935483871 \tabularnewline
371 & 562.9 & 369.529032258065 & 193.370967741935 \tabularnewline
372 & 572.5 & 371.996774193548 & 200.503225806452 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147635&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]235.1[/C][C]433.029032258064[/C][C]-197.929032258064[/C][/ROW]
[ROW][C]2[/C][C]280.7[/C][C]442.925806451613[/C][C]-162.225806451613[/C][/ROW]
[ROW][C]3[/C][C]264.6[/C][C]420.658064516129[/C][C]-156.058064516129[/C][/ROW]
[ROW][C]4[/C][C]240.7[/C][C]381.735483870968[/C][C]-141.035483870968[/C][/ROW]
[ROW][C]5[/C][C]201.4[/C][C]361.196774193548[/C][C]-159.796774193548[/C][/ROW]
[ROW][C]6[/C][C]240.8[/C][C]433.922580645161[/C][C]-193.122580645161[/C][/ROW]
[ROW][C]7[/C][C]241.1[/C][C]411.151612903226[/C][C]-170.051612903226[/C][/ROW]
[ROW][C]8[/C][C]223.8[/C][C]380.006451612903[/C][C]-156.206451612903[/C][/ROW]
[ROW][C]9[/C][C]206.1[/C][C]362.9[/C][C]-156.8[/C][/ROW]
[ROW][C]10[/C][C]174.7[/C][C]347.458064516129[/C][C]-172.758064516129[/C][/ROW]
[ROW][C]11[/C][C]203.3[/C][C]369.529032258064[/C][C]-166.229032258065[/C][/ROW]
[ROW][C]12[/C][C]220.5[/C][C]371.996774193548[/C][C]-151.496774193548[/C][/ROW]
[ROW][C]13[/C][C]299.5[/C][C]433.029032258064[/C][C]-133.529032258065[/C][/ROW]
[ROW][C]14[/C][C]347.4[/C][C]442.925806451613[/C][C]-95.5258064516129[/C][/ROW]
[ROW][C]15[/C][C]338.3[/C][C]420.658064516129[/C][C]-82.358064516129[/C][/ROW]
[ROW][C]16[/C][C]327.7[/C][C]381.735483870968[/C][C]-54.0354838709677[/C][/ROW]
[ROW][C]17[/C][C]351.6[/C][C]361.196774193548[/C][C]-9.59677419354836[/C][/ROW]
[ROW][C]18[/C][C]396.6[/C][C]433.922580645161[/C][C]-37.3225806451613[/C][/ROW]
[ROW][C]19[/C][C]438.8[/C][C]411.151612903226[/C][C]27.6483870967742[/C][/ROW]
[ROW][C]20[/C][C]395.6[/C][C]380.006451612903[/C][C]15.5935483870968[/C][/ROW]
[ROW][C]21[/C][C]363.5[/C][C]362.9[/C][C]0.600000000000004[/C][/ROW]
[ROW][C]22[/C][C]378.8[/C][C]347.458064516129[/C][C]31.341935483871[/C][/ROW]
[ROW][C]23[/C][C]357[/C][C]369.529032258065[/C][C]-12.5290322580645[/C][/ROW]
[ROW][C]24[/C][C]369[/C][C]371.996774193548[/C][C]-2.99677419354836[/C][/ROW]
[ROW][C]25[/C][C]464.8[/C][C]433.029032258065[/C][C]31.7709677419355[/C][/ROW]
[ROW][C]26[/C][C]479.1[/C][C]442.925806451613[/C][C]36.1741935483871[/C][/ROW]
[ROW][C]27[/C][C]431.3[/C][C]420.658064516129[/C][C]10.641935483871[/C][/ROW]
[ROW][C]28[/C][C]366.5[/C][C]381.735483870968[/C][C]-15.2354838709677[/C][/ROW]
[ROW][C]29[/C][C]326.3[/C][C]361.196774193548[/C][C]-34.8967741935484[/C][/ROW]
[ROW][C]30[/C][C]355.1[/C][C]433.922580645161[/C][C]-78.8225806451613[/C][/ROW]
[ROW][C]31[/C][C]331.6[/C][C]411.151612903226[/C][C]-79.5516129032258[/C][/ROW]
[ROW][C]32[/C][C]261.3[/C][C]380.006451612903[/C][C]-118.706451612903[/C][/ROW]
[ROW][C]33[/C][C]249[/C][C]362.9[/C][C]-113.9[/C][/ROW]
[ROW][C]34[/C][C]205.5[/C][C]347.458064516129[/C][C]-141.958064516129[/C][/ROW]
[ROW][C]35[/C][C]235.6[/C][C]369.529032258064[/C][C]-133.929032258065[/C][/ROW]
[ROW][C]36[/C][C]240.9[/C][C]371.996774193548[/C][C]-131.096774193548[/C][/ROW]
[ROW][C]37[/C][C]264.9[/C][C]433.029032258064[/C][C]-168.129032258065[/C][/ROW]
[ROW][C]38[/C][C]253.8[/C][C]442.925806451613[/C][C]-189.125806451613[/C][/ROW]
[ROW][C]39[/C][C]232.3[/C][C]420.658064516129[/C][C]-188.358064516129[/C][/ROW]
[ROW][C]40[/C][C]193.8[/C][C]381.735483870968[/C][C]-187.935483870968[/C][/ROW]
[ROW][C]41[/C][C]177[/C][C]361.196774193548[/C][C]-184.196774193548[/C][/ROW]
[ROW][C]42[/C][C]213.2[/C][C]433.922580645161[/C][C]-220.722580645161[/C][/ROW]
[ROW][C]43[/C][C]207.2[/C][C]411.151612903226[/C][C]-203.951612903226[/C][/ROW]
[ROW][C]44[/C][C]180.6[/C][C]380.006451612903[/C][C]-199.406451612903[/C][/ROW]
[ROW][C]45[/C][C]188.6[/C][C]362.9[/C][C]-174.3[/C][/ROW]
[ROW][C]46[/C][C]175.4[/C][C]347.458064516129[/C][C]-172.058064516129[/C][/ROW]
[ROW][C]47[/C][C]199[/C][C]369.529032258065[/C][C]-170.529032258065[/C][/ROW]
[ROW][C]48[/C][C]179.6[/C][C]371.996774193548[/C][C]-192.396774193548[/C][/ROW]
[ROW][C]49[/C][C]225.8[/C][C]433.029032258064[/C][C]-207.229032258065[/C][/ROW]
[ROW][C]50[/C][C]234[/C][C]442.925806451613[/C][C]-208.925806451613[/C][/ROW]
[ROW][C]51[/C][C]200.2[/C][C]420.658064516129[/C][C]-220.458064516129[/C][/ROW]
[ROW][C]52[/C][C]183.6[/C][C]381.735483870968[/C][C]-198.135483870968[/C][/ROW]
[ROW][C]53[/C][C]178.2[/C][C]361.196774193548[/C][C]-182.996774193548[/C][/ROW]
[ROW][C]54[/C][C]203.2[/C][C]433.922580645161[/C][C]-230.722580645161[/C][/ROW]
[ROW][C]55[/C][C]208.5[/C][C]411.151612903226[/C][C]-202.651612903226[/C][/ROW]
[ROW][C]56[/C][C]191.8[/C][C]380.006451612903[/C][C]-188.206451612903[/C][/ROW]
[ROW][C]57[/C][C]172.8[/C][C]362.9[/C][C]-190.1[/C][/ROW]
[ROW][C]58[/C][C]148[/C][C]347.458064516129[/C][C]-199.458064516129[/C][/ROW]
[ROW][C]59[/C][C]159.4[/C][C]369.529032258065[/C][C]-210.129032258065[/C][/ROW]
[ROW][C]60[/C][C]154.5[/C][C]371.996774193548[/C][C]-217.496774193548[/C][/ROW]
[ROW][C]61[/C][C]213.2[/C][C]433.029032258064[/C][C]-219.829032258065[/C][/ROW]
[ROW][C]62[/C][C]196.4[/C][C]442.925806451613[/C][C]-246.525806451613[/C][/ROW]
[ROW][C]63[/C][C]182.8[/C][C]420.658064516129[/C][C]-237.858064516129[/C][/ROW]
[ROW][C]64[/C][C]176.4[/C][C]381.735483870968[/C][C]-205.335483870968[/C][/ROW]
[ROW][C]65[/C][C]153.6[/C][C]361.196774193548[/C][C]-207.596774193548[/C][/ROW]
[ROW][C]66[/C][C]173.2[/C][C]433.922580645161[/C][C]-260.722580645161[/C][/ROW]
[ROW][C]67[/C][C]171[/C][C]411.151612903226[/C][C]-240.151612903226[/C][/ROW]
[ROW][C]68[/C][C]151.2[/C][C]380.006451612903[/C][C]-228.806451612903[/C][/ROW]
[ROW][C]69[/C][C]161.9[/C][C]362.9[/C][C]-201[/C][/ROW]
[ROW][C]70[/C][C]157.2[/C][C]347.458064516129[/C][C]-190.258064516129[/C][/ROW]
[ROW][C]71[/C][C]201.7[/C][C]369.529032258065[/C][C]-167.829032258065[/C][/ROW]
[ROW][C]72[/C][C]236.4[/C][C]371.996774193548[/C][C]-135.596774193548[/C][/ROW]
[ROW][C]73[/C][C]356.1[/C][C]433.029032258065[/C][C]-76.9290322580645[/C][/ROW]
[ROW][C]74[/C][C]398.3[/C][C]442.925806451613[/C][C]-44.6258064516129[/C][/ROW]
[ROW][C]75[/C][C]403.7[/C][C]420.658064516129[/C][C]-16.958064516129[/C][/ROW]
[ROW][C]76[/C][C]384.6[/C][C]381.735483870968[/C][C]2.86451612903229[/C][/ROW]
[ROW][C]77[/C][C]365.8[/C][C]361.196774193548[/C][C]4.60322580645163[/C][/ROW]
[ROW][C]78[/C][C]368.1[/C][C]433.922580645161[/C][C]-65.8225806451613[/C][/ROW]
[ROW][C]79[/C][C]367.9[/C][C]411.151612903226[/C][C]-43.2516129032258[/C][/ROW]
[ROW][C]80[/C][C]347[/C][C]380.006451612903[/C][C]-33.0064516129032[/C][/ROW]
[ROW][C]81[/C][C]343.3[/C][C]362.9[/C][C]-19.6[/C][/ROW]
[ROW][C]82[/C][C]292.9[/C][C]347.458064516129[/C][C]-54.5580645161291[/C][/ROW]
[ROW][C]83[/C][C]311.5[/C][C]369.529032258064[/C][C]-58.0290322580645[/C][/ROW]
[ROW][C]84[/C][C]300.9[/C][C]371.996774193548[/C][C]-71.0967741935484[/C][/ROW]
[ROW][C]85[/C][C]366.9[/C][C]433.029032258065[/C][C]-66.1290322580646[/C][/ROW]
[ROW][C]86[/C][C]356.9[/C][C]442.925806451613[/C][C]-86.0258064516129[/C][/ROW]
[ROW][C]87[/C][C]329.7[/C][C]420.658064516129[/C][C]-90.958064516129[/C][/ROW]
[ROW][C]88[/C][C]316.2[/C][C]381.735483870968[/C][C]-65.5354838709678[/C][/ROW]
[ROW][C]89[/C][C]269[/C][C]361.196774193548[/C][C]-92.1967741935484[/C][/ROW]
[ROW][C]90[/C][C]289.3[/C][C]433.922580645161[/C][C]-144.622580645161[/C][/ROW]
[ROW][C]91[/C][C]266.2[/C][C]411.151612903226[/C][C]-144.951612903226[/C][/ROW]
[ROW][C]92[/C][C]253.6[/C][C]380.006451612903[/C][C]-126.406451612903[/C][/ROW]
[ROW][C]93[/C][C]233.8[/C][C]362.9[/C][C]-129.1[/C][/ROW]
[ROW][C]94[/C][C]228.4[/C][C]347.458064516129[/C][C]-119.058064516129[/C][/ROW]
[ROW][C]95[/C][C]253.6[/C][C]369.529032258064[/C][C]-115.929032258065[/C][/ROW]
[ROW][C]96[/C][C]260.1[/C][C]371.996774193548[/C][C]-111.896774193548[/C][/ROW]
[ROW][C]97[/C][C]306.6[/C][C]433.029032258064[/C][C]-126.429032258064[/C][/ROW]
[ROW][C]98[/C][C]309.2[/C][C]442.925806451613[/C][C]-133.725806451613[/C][/ROW]
[ROW][C]99[/C][C]309.5[/C][C]420.658064516129[/C][C]-111.158064516129[/C][/ROW]
[ROW][C]100[/C][C]271[/C][C]381.735483870968[/C][C]-110.735483870968[/C][/ROW]
[ROW][C]101[/C][C]279.9[/C][C]361.196774193548[/C][C]-81.2967741935484[/C][/ROW]
[ROW][C]102[/C][C]317.9[/C][C]433.922580645161[/C][C]-116.022580645161[/C][/ROW]
[ROW][C]103[/C][C]298.4[/C][C]411.151612903226[/C][C]-112.751612903226[/C][/ROW]
[ROW][C]104[/C][C]246.7[/C][C]380.006451612903[/C][C]-133.306451612903[/C][/ROW]
[ROW][C]105[/C][C]227.3[/C][C]362.9[/C][C]-135.6[/C][/ROW]
[ROW][C]106[/C][C]209.1[/C][C]347.458064516129[/C][C]-138.358064516129[/C][/ROW]
[ROW][C]107[/C][C]259.9[/C][C]369.529032258064[/C][C]-109.629032258065[/C][/ROW]
[ROW][C]108[/C][C]266[/C][C]371.996774193548[/C][C]-105.996774193548[/C][/ROW]
[ROW][C]109[/C][C]320.6[/C][C]433.029032258064[/C][C]-112.429032258064[/C][/ROW]
[ROW][C]110[/C][C]308.5[/C][C]442.925806451613[/C][C]-134.425806451613[/C][/ROW]
[ROW][C]111[/C][C]282.2[/C][C]420.658064516129[/C][C]-138.458064516129[/C][/ROW]
[ROW][C]112[/C][C]262.7[/C][C]381.735483870968[/C][C]-119.035483870968[/C][/ROW]
[ROW][C]113[/C][C]263.5[/C][C]361.196774193548[/C][C]-97.6967741935484[/C][/ROW]
[ROW][C]114[/C][C]313.1[/C][C]433.922580645161[/C][C]-120.822580645161[/C][/ROW]
[ROW][C]115[/C][C]284.3[/C][C]411.151612903226[/C][C]-126.851612903226[/C][/ROW]
[ROW][C]116[/C][C]252.6[/C][C]380.006451612903[/C][C]-127.406451612903[/C][/ROW]
[ROW][C]117[/C][C]250.3[/C][C]362.9[/C][C]-112.6[/C][/ROW]
[ROW][C]118[/C][C]246.5[/C][C]347.458064516129[/C][C]-100.958064516129[/C][/ROW]
[ROW][C]119[/C][C]312.7[/C][C]369.529032258065[/C][C]-56.8290322580645[/C][/ROW]
[ROW][C]120[/C][C]333.2[/C][C]371.996774193548[/C][C]-38.7967741935484[/C][/ROW]
[ROW][C]121[/C][C]446.4[/C][C]433.029032258065[/C][C]13.3709677419354[/C][/ROW]
[ROW][C]122[/C][C]511.6[/C][C]442.925806451613[/C][C]68.6741935483871[/C][/ROW]
[ROW][C]123[/C][C]515.5[/C][C]420.658064516129[/C][C]94.841935483871[/C][/ROW]
[ROW][C]124[/C][C]506.4[/C][C]381.735483870968[/C][C]124.664516129032[/C][/ROW]
[ROW][C]125[/C][C]483.2[/C][C]361.196774193548[/C][C]122.003225806452[/C][/ROW]
[ROW][C]126[/C][C]522.3[/C][C]433.922580645161[/C][C]88.3774193548387[/C][/ROW]
[ROW][C]127[/C][C]509.8[/C][C]411.151612903226[/C][C]98.6483870967742[/C][/ROW]
[ROW][C]128[/C][C]460.7[/C][C]380.006451612903[/C][C]80.6935483870968[/C][/ROW]
[ROW][C]129[/C][C]405.8[/C][C]362.9[/C][C]42.9[/C][/ROW]
[ROW][C]130[/C][C]375[/C][C]347.458064516129[/C][C]27.541935483871[/C][/ROW]
[ROW][C]131[/C][C]378.5[/C][C]369.529032258064[/C][C]8.97096774193549[/C][/ROW]
[ROW][C]132[/C][C]406.8[/C][C]371.996774193548[/C][C]34.8032258064516[/C][/ROW]
[ROW][C]133[/C][C]467.8[/C][C]433.029032258065[/C][C]34.7709677419355[/C][/ROW]
[ROW][C]134[/C][C]469.8[/C][C]442.925806451613[/C][C]26.8741935483871[/C][/ROW]
[ROW][C]135[/C][C]429.8[/C][C]420.658064516129[/C][C]9.14193548387101[/C][/ROW]
[ROW][C]136[/C][C]355.8[/C][C]381.735483870968[/C][C]-25.9354838709677[/C][/ROW]
[ROW][C]137[/C][C]332.7[/C][C]361.196774193548[/C][C]-28.4967741935484[/C][/ROW]
[ROW][C]138[/C][C]378[/C][C]433.922580645161[/C][C]-55.9225806451613[/C][/ROW]
[ROW][C]139[/C][C]360.5[/C][C]411.151612903226[/C][C]-50.6516129032258[/C][/ROW]
[ROW][C]140[/C][C]334.7[/C][C]380.006451612903[/C][C]-45.3064516129032[/C][/ROW]
[ROW][C]141[/C][C]319.5[/C][C]362.9[/C][C]-43.4[/C][/ROW]
[ROW][C]142[/C][C]323.1[/C][C]347.458064516129[/C][C]-24.358064516129[/C][/ROW]
[ROW][C]143[/C][C]363.6[/C][C]369.529032258064[/C][C]-5.92903225806449[/C][/ROW]
[ROW][C]144[/C][C]352.1[/C][C]371.996774193548[/C][C]-19.8967741935483[/C][/ROW]
[ROW][C]145[/C][C]411.9[/C][C]433.029032258065[/C][C]-21.1290322580645[/C][/ROW]
[ROW][C]146[/C][C]388.6[/C][C]442.925806451613[/C][C]-54.3258064516129[/C][/ROW]
[ROW][C]147[/C][C]416.4[/C][C]420.658064516129[/C][C]-4.25806451612903[/C][/ROW]
[ROW][C]148[/C][C]360.7[/C][C]381.735483870968[/C][C]-21.0354838709677[/C][/ROW]
[ROW][C]149[/C][C]338[/C][C]361.196774193548[/C][C]-23.1967741935484[/C][/ROW]
[ROW][C]150[/C][C]417.2[/C][C]433.922580645161[/C][C]-16.7225806451613[/C][/ROW]
[ROW][C]151[/C][C]388.4[/C][C]411.151612903226[/C][C]-22.7516129032258[/C][/ROW]
[ROW][C]152[/C][C]371.1[/C][C]380.006451612903[/C][C]-8.90645161290322[/C][/ROW]
[ROW][C]153[/C][C]331.5[/C][C]362.9[/C][C]-31.4[/C][/ROW]
[ROW][C]154[/C][C]353.7[/C][C]347.458064516129[/C][C]6.24193548387097[/C][/ROW]
[ROW][C]155[/C][C]396.7[/C][C]369.529032258064[/C][C]27.1709677419355[/C][/ROW]
[ROW][C]156[/C][C]447[/C][C]371.996774193548[/C][C]75.0032258064516[/C][/ROW]
[ROW][C]157[/C][C]533.5[/C][C]433.029032258065[/C][C]100.470967741935[/C][/ROW]
[ROW][C]158[/C][C]565.4[/C][C]442.925806451613[/C][C]122.474193548387[/C][/ROW]
[ROW][C]159[/C][C]542.3[/C][C]420.658064516129[/C][C]121.641935483871[/C][/ROW]
[ROW][C]160[/C][C]488.7[/C][C]381.735483870968[/C][C]106.964516129032[/C][/ROW]
[ROW][C]161[/C][C]467.1[/C][C]361.196774193548[/C][C]105.903225806452[/C][/ROW]
[ROW][C]162[/C][C]531.3[/C][C]433.922580645161[/C][C]97.3774193548387[/C][/ROW]
[ROW][C]163[/C][C]496.1[/C][C]411.151612903226[/C][C]84.9483870967742[/C][/ROW]
[ROW][C]164[/C][C]444[/C][C]380.006451612903[/C][C]63.9935483870968[/C][/ROW]
[ROW][C]165[/C][C]403.4[/C][C]362.9[/C][C]40.5[/C][/ROW]
[ROW][C]166[/C][C]386.3[/C][C]347.458064516129[/C][C]38.841935483871[/C][/ROW]
[ROW][C]167[/C][C]394.1[/C][C]369.529032258064[/C][C]24.5709677419355[/C][/ROW]
[ROW][C]168[/C][C]404.1[/C][C]371.996774193548[/C][C]32.1032258064516[/C][/ROW]
[ROW][C]169[/C][C]462.1[/C][C]433.029032258065[/C][C]29.0709677419355[/C][/ROW]
[ROW][C]170[/C][C]448.1[/C][C]442.925806451613[/C][C]5.17419354838711[/C][/ROW]
[ROW][C]171[/C][C]432.3[/C][C]420.658064516129[/C][C]11.641935483871[/C][/ROW]
[ROW][C]172[/C][C]386.3[/C][C]381.735483870968[/C][C]4.56451612903227[/C][/ROW]
[ROW][C]173[/C][C]395.2[/C][C]361.196774193548[/C][C]34.0032258064516[/C][/ROW]
[ROW][C]174[/C][C]421.9[/C][C]433.922580645161[/C][C]-12.0225806451613[/C][/ROW]
[ROW][C]175[/C][C]382.9[/C][C]411.151612903226[/C][C]-28.2516129032258[/C][/ROW]
[ROW][C]176[/C][C]384.2[/C][C]380.006451612903[/C][C]4.19354838709675[/C][/ROW]
[ROW][C]177[/C][C]345.5[/C][C]362.9[/C][C]-17.4[/C][/ROW]
[ROW][C]178[/C][C]323.4[/C][C]347.458064516129[/C][C]-24.0580645161291[/C][/ROW]
[ROW][C]179[/C][C]372.6[/C][C]369.529032258064[/C][C]3.07096774193551[/C][/ROW]
[ROW][C]180[/C][C]376[/C][C]371.996774193548[/C][C]4.00322580645163[/C][/ROW]
[ROW][C]181[/C][C]462.7[/C][C]433.029032258065[/C][C]29.6709677419355[/C][/ROW]
[ROW][C]182[/C][C]487[/C][C]442.925806451613[/C][C]44.0741935483871[/C][/ROW]
[ROW][C]183[/C][C]444.2[/C][C]420.658064516129[/C][C]23.541935483871[/C][/ROW]
[ROW][C]184[/C][C]399.3[/C][C]381.735483870968[/C][C]17.5645161290323[/C][/ROW]
[ROW][C]185[/C][C]394.9[/C][C]361.196774193548[/C][C]33.7032258064516[/C][/ROW]
[ROW][C]186[/C][C]455.4[/C][C]433.922580645161[/C][C]21.4774193548387[/C][/ROW]
[ROW][C]187[/C][C]414[/C][C]411.151612903226[/C][C]2.8483870967742[/C][/ROW]
[ROW][C]188[/C][C]375.5[/C][C]380.006451612903[/C][C]-4.50645161290324[/C][/ROW]
[ROW][C]189[/C][C]347[/C][C]362.9[/C][C]-15.9[/C][/ROW]
[ROW][C]190[/C][C]339.4[/C][C]347.458064516129[/C][C]-8.05806451612904[/C][/ROW]
[ROW][C]191[/C][C]385.8[/C][C]369.529032258064[/C][C]16.2709677419355[/C][/ROW]
[ROW][C]192[/C][C]378.8[/C][C]371.996774193548[/C][C]6.80322580645164[/C][/ROW]
[ROW][C]193[/C][C]451.8[/C][C]433.029032258065[/C][C]18.7709677419355[/C][/ROW]
[ROW][C]194[/C][C]446.1[/C][C]442.925806451613[/C][C]3.17419354838711[/C][/ROW]
[ROW][C]195[/C][C]422.5[/C][C]420.658064516129[/C][C]1.84193548387099[/C][/ROW]
[ROW][C]196[/C][C]383.1[/C][C]381.735483870968[/C][C]1.36451612903228[/C][/ROW]
[ROW][C]197[/C][C]352.8[/C][C]361.196774193548[/C][C]-8.39677419354837[/C][/ROW]
[ROW][C]198[/C][C]445.3[/C][C]433.922580645161[/C][C]11.3774193548387[/C][/ROW]
[ROW][C]199[/C][C]367.5[/C][C]411.151612903226[/C][C]-43.6516129032258[/C][/ROW]
[ROW][C]200[/C][C]355.1[/C][C]380.006451612903[/C][C]-24.9064516129032[/C][/ROW]
[ROW][C]201[/C][C]326.2[/C][C]362.9[/C][C]-36.7[/C][/ROW]
[ROW][C]202[/C][C]319.8[/C][C]347.458064516129[/C][C]-27.658064516129[/C][/ROW]
[ROW][C]203[/C][C]331.8[/C][C]369.529032258064[/C][C]-37.7290322580645[/C][/ROW]
[ROW][C]204[/C][C]340.9[/C][C]371.996774193548[/C][C]-31.0967741935484[/C][/ROW]
[ROW][C]205[/C][C]394.1[/C][C]433.029032258065[/C][C]-38.9290322580645[/C][/ROW]
[ROW][C]206[/C][C]417.2[/C][C]442.925806451613[/C][C]-25.7258064516129[/C][/ROW]
[ROW][C]207[/C][C]369.9[/C][C]420.658064516129[/C][C]-50.758064516129[/C][/ROW]
[ROW][C]208[/C][C]349.2[/C][C]381.735483870968[/C][C]-32.5354838709677[/C][/ROW]
[ROW][C]209[/C][C]321.4[/C][C]361.196774193548[/C][C]-39.7967741935484[/C][/ROW]
[ROW][C]210[/C][C]405.7[/C][C]433.922580645161[/C][C]-28.2225806451613[/C][/ROW]
[ROW][C]211[/C][C]342.9[/C][C]411.151612903226[/C][C]-68.2516129032258[/C][/ROW]
[ROW][C]212[/C][C]316.5[/C][C]380.006451612903[/C][C]-63.5064516129032[/C][/ROW]
[ROW][C]213[/C][C]284.2[/C][C]362.9[/C][C]-78.7[/C][/ROW]
[ROW][C]214[/C][C]270.9[/C][C]347.458064516129[/C][C]-76.558064516129[/C][/ROW]
[ROW][C]215[/C][C]288.8[/C][C]369.529032258064[/C][C]-80.7290322580645[/C][/ROW]
[ROW][C]216[/C][C]278.8[/C][C]371.996774193548[/C][C]-93.1967741935483[/C][/ROW]
[ROW][C]217[/C][C]324.4[/C][C]433.029032258065[/C][C]-108.629032258065[/C][/ROW]
[ROW][C]218[/C][C]310.9[/C][C]442.925806451613[/C][C]-132.025806451613[/C][/ROW]
[ROW][C]219[/C][C]299[/C][C]420.658064516129[/C][C]-121.658064516129[/C][/ROW]
[ROW][C]220[/C][C]273[/C][C]381.735483870968[/C][C]-108.735483870968[/C][/ROW]
[ROW][C]221[/C][C]279.3[/C][C]361.196774193548[/C][C]-81.8967741935484[/C][/ROW]
[ROW][C]222[/C][C]359.2[/C][C]433.922580645161[/C][C]-74.7225806451613[/C][/ROW]
[ROW][C]223[/C][C]305[/C][C]411.151612903226[/C][C]-106.151612903226[/C][/ROW]
[ROW][C]224[/C][C]282.1[/C][C]380.006451612903[/C][C]-97.9064516129032[/C][/ROW]
[ROW][C]225[/C][C]250.3[/C][C]362.9[/C][C]-112.6[/C][/ROW]
[ROW][C]226[/C][C]246.5[/C][C]347.458064516129[/C][C]-100.958064516129[/C][/ROW]
[ROW][C]227[/C][C]257.9[/C][C]369.529032258064[/C][C]-111.629032258065[/C][/ROW]
[ROW][C]228[/C][C]266.5[/C][C]371.996774193548[/C][C]-105.496774193548[/C][/ROW]
[ROW][C]229[/C][C]315.9[/C][C]433.029032258064[/C][C]-117.129032258065[/C][/ROW]
[ROW][C]230[/C][C]318.4[/C][C]442.925806451613[/C][C]-124.525806451613[/C][/ROW]
[ROW][C]231[/C][C]295.4[/C][C]420.658064516129[/C][C]-125.258064516129[/C][/ROW]
[ROW][C]232[/C][C]266.4[/C][C]381.735483870968[/C][C]-115.335483870968[/C][/ROW]
[ROW][C]233[/C][C]245.8[/C][C]361.196774193548[/C][C]-115.396774193548[/C][/ROW]
[ROW][C]234[/C][C]362.8[/C][C]433.922580645161[/C][C]-71.1225806451613[/C][/ROW]
[ROW][C]235[/C][C]324.9[/C][C]411.151612903226[/C][C]-86.2516129032258[/C][/ROW]
[ROW][C]236[/C][C]294.2[/C][C]380.006451612903[/C][C]-85.8064516129032[/C][/ROW]
[ROW][C]237[/C][C]289.5[/C][C]362.9[/C][C]-73.4[/C][/ROW]
[ROW][C]238[/C][C]295.2[/C][C]347.458064516129[/C][C]-52.258064516129[/C][/ROW]
[ROW][C]239[/C][C]290.3[/C][C]369.529032258064[/C][C]-79.2290322580645[/C][/ROW]
[ROW][C]240[/C][C]272[/C][C]371.996774193548[/C][C]-99.9967741935483[/C][/ROW]
[ROW][C]241[/C][C]307.4[/C][C]433.029032258064[/C][C]-125.629032258065[/C][/ROW]
[ROW][C]242[/C][C]328.7[/C][C]442.925806451613[/C][C]-114.225806451613[/C][/ROW]
[ROW][C]243[/C][C]292.9[/C][C]420.658064516129[/C][C]-127.758064516129[/C][/ROW]
[ROW][C]244[/C][C]249.1[/C][C]381.735483870968[/C][C]-132.635483870968[/C][/ROW]
[ROW][C]245[/C][C]230.4[/C][C]361.196774193548[/C][C]-130.796774193548[/C][/ROW]
[ROW][C]246[/C][C]361.5[/C][C]433.922580645161[/C][C]-72.4225806451613[/C][/ROW]
[ROW][C]247[/C][C]321.7[/C][C]411.151612903226[/C][C]-89.4516129032258[/C][/ROW]
[ROW][C]248[/C][C]277.2[/C][C]380.006451612903[/C][C]-102.806451612903[/C][/ROW]
[ROW][C]249[/C][C]260.7[/C][C]362.9[/C][C]-102.2[/C][/ROW]
[ROW][C]250[/C][C]251[/C][C]347.458064516129[/C][C]-96.458064516129[/C][/ROW]
[ROW][C]251[/C][C]257.6[/C][C]369.529032258064[/C][C]-111.929032258064[/C][/ROW]
[ROW][C]252[/C][C]241.8[/C][C]371.996774193548[/C][C]-130.196774193548[/C][/ROW]
[ROW][C]253[/C][C]287.5[/C][C]433.029032258064[/C][C]-145.529032258065[/C][/ROW]
[ROW][C]254[/C][C]292.3[/C][C]442.925806451613[/C][C]-150.625806451613[/C][/ROW]
[ROW][C]255[/C][C]274.7[/C][C]420.658064516129[/C][C]-145.958064516129[/C][/ROW]
[ROW][C]256[/C][C]254.2[/C][C]381.735483870968[/C][C]-127.535483870968[/C][/ROW]
[ROW][C]257[/C][C]230[/C][C]361.196774193548[/C][C]-131.196774193548[/C][/ROW]
[ROW][C]258[/C][C]339[/C][C]433.922580645161[/C][C]-94.9225806451613[/C][/ROW]
[ROW][C]259[/C][C]318.2[/C][C]411.151612903226[/C][C]-92.9516129032258[/C][/ROW]
[ROW][C]260[/C][C]287[/C][C]380.006451612903[/C][C]-93.0064516129032[/C][/ROW]
[ROW][C]261[/C][C]295.8[/C][C]362.9[/C][C]-67.1[/C][/ROW]
[ROW][C]262[/C][C]284[/C][C]347.458064516129[/C][C]-63.458064516129[/C][/ROW]
[ROW][C]263[/C][C]271[/C][C]369.529032258064[/C][C]-98.5290322580645[/C][/ROW]
[ROW][C]264[/C][C]262.7[/C][C]371.996774193548[/C][C]-109.296774193548[/C][/ROW]
[ROW][C]265[/C][C]340.6[/C][C]433.029032258065[/C][C]-92.4290322580645[/C][/ROW]
[ROW][C]266[/C][C]379.4[/C][C]442.925806451613[/C][C]-63.5258064516129[/C][/ROW]
[ROW][C]267[/C][C]373.3[/C][C]420.658064516129[/C][C]-47.358064516129[/C][/ROW]
[ROW][C]268[/C][C]355.2[/C][C]381.735483870968[/C][C]-26.5354838709677[/C][/ROW]
[ROW][C]269[/C][C]338.4[/C][C]361.196774193548[/C][C]-22.7967741935484[/C][/ROW]
[ROW][C]270[/C][C]466.9[/C][C]433.922580645161[/C][C]32.9774193548387[/C][/ROW]
[ROW][C]271[/C][C]451[/C][C]411.151612903226[/C][C]39.8483870967742[/C][/ROW]
[ROW][C]272[/C][C]422[/C][C]380.006451612903[/C][C]41.9935483870968[/C][/ROW]
[ROW][C]273[/C][C]429.2[/C][C]362.9[/C][C]66.3[/C][/ROW]
[ROW][C]274[/C][C]425.9[/C][C]347.458064516129[/C][C]78.4419354838709[/C][/ROW]
[ROW][C]275[/C][C]460.7[/C][C]369.529032258065[/C][C]91.1709677419355[/C][/ROW]
[ROW][C]276[/C][C]463.6[/C][C]371.996774193548[/C][C]91.6032258064516[/C][/ROW]
[ROW][C]277[/C][C]541.4[/C][C]433.029032258065[/C][C]108.370967741935[/C][/ROW]
[ROW][C]278[/C][C]544.2[/C][C]442.925806451613[/C][C]101.274193548387[/C][/ROW]
[ROW][C]279[/C][C]517.5[/C][C]420.658064516129[/C][C]96.841935483871[/C][/ROW]
[ROW][C]280[/C][C]469.4[/C][C]381.735483870968[/C][C]87.6645161290322[/C][/ROW]
[ROW][C]281[/C][C]439.4[/C][C]361.196774193548[/C][C]78.2032258064516[/C][/ROW]
[ROW][C]282[/C][C]549[/C][C]433.922580645161[/C][C]115.077419354839[/C][/ROW]
[ROW][C]283[/C][C]533[/C][C]411.151612903226[/C][C]121.848387096774[/C][/ROW]
[ROW][C]284[/C][C]506.1[/C][C]380.006451612903[/C][C]126.093548387097[/C][/ROW]
[ROW][C]285[/C][C]484[/C][C]362.9[/C][C]121.1[/C][/ROW]
[ROW][C]286[/C][C]457[/C][C]347.458064516129[/C][C]109.541935483871[/C][/ROW]
[ROW][C]287[/C][C]481.5[/C][C]369.529032258064[/C][C]111.970967741935[/C][/ROW]
[ROW][C]288[/C][C]469.5[/C][C]371.996774193548[/C][C]97.5032258064516[/C][/ROW]
[ROW][C]289[/C][C]544.7[/C][C]433.029032258065[/C][C]111.670967741935[/C][/ROW]
[ROW][C]290[/C][C]541.2[/C][C]442.925806451613[/C][C]98.2741935483871[/C][/ROW]
[ROW][C]291[/C][C]521.5[/C][C]420.658064516129[/C][C]100.841935483871[/C][/ROW]
[ROW][C]292[/C][C]469.7[/C][C]381.735483870968[/C][C]87.9645161290322[/C][/ROW]
[ROW][C]293[/C][C]434.4[/C][C]361.196774193548[/C][C]73.2032258064516[/C][/ROW]
[ROW][C]294[/C][C]542.6[/C][C]433.922580645161[/C][C]108.677419354839[/C][/ROW]
[ROW][C]295[/C][C]517.3[/C][C]411.151612903226[/C][C]106.148387096774[/C][/ROW]
[ROW][C]296[/C][C]485.7[/C][C]380.006451612903[/C][C]105.693548387097[/C][/ROW]
[ROW][C]297[/C][C]465.8[/C][C]362.9[/C][C]102.9[/C][/ROW]
[ROW][C]298[/C][C]447[/C][C]347.458064516129[/C][C]99.541935483871[/C][/ROW]
[ROW][C]299[/C][C]426.6[/C][C]369.529032258064[/C][C]57.0709677419355[/C][/ROW]
[ROW][C]300[/C][C]411.6[/C][C]371.996774193548[/C][C]39.6032258064517[/C][/ROW]
[ROW][C]301[/C][C]467.5[/C][C]433.029032258065[/C][C]34.4709677419355[/C][/ROW]
[ROW][C]302[/C][C]484.5[/C][C]442.925806451613[/C][C]41.5741935483871[/C][/ROW]
[ROW][C]303[/C][C]451.2[/C][C]420.658064516129[/C][C]30.541935483871[/C][/ROW]
[ROW][C]304[/C][C]417.4[/C][C]381.735483870968[/C][C]35.6645161290322[/C][/ROW]
[ROW][C]305[/C][C]379.9[/C][C]361.196774193548[/C][C]18.7032258064516[/C][/ROW]
[ROW][C]306[/C][C]484.7[/C][C]433.922580645161[/C][C]50.7774193548387[/C][/ROW]
[ROW][C]307[/C][C]455[/C][C]411.151612903226[/C][C]43.8483870967742[/C][/ROW]
[ROW][C]308[/C][C]420.8[/C][C]380.006451612903[/C][C]40.7935483870968[/C][/ROW]
[ROW][C]309[/C][C]416.5[/C][C]362.9[/C][C]53.6[/C][/ROW]
[ROW][C]310[/C][C]376.3[/C][C]347.458064516129[/C][C]28.841935483871[/C][/ROW]
[ROW][C]311[/C][C]405.6[/C][C]369.529032258065[/C][C]36.0709677419355[/C][/ROW]
[ROW][C]312[/C][C]405.8[/C][C]371.996774193548[/C][C]33.8032258064516[/C][/ROW]
[ROW][C]313[/C][C]500.8[/C][C]433.029032258064[/C][C]67.7709677419355[/C][/ROW]
[ROW][C]314[/C][C]514[/C][C]442.925806451613[/C][C]71.0741935483871[/C][/ROW]
[ROW][C]315[/C][C]475.5[/C][C]420.658064516129[/C][C]54.841935483871[/C][/ROW]
[ROW][C]316[/C][C]430.1[/C][C]381.735483870968[/C][C]48.3645161290323[/C][/ROW]
[ROW][C]317[/C][C]414.4[/C][C]361.196774193548[/C][C]53.2032258064516[/C][/ROW]
[ROW][C]318[/C][C]538[/C][C]433.922580645161[/C][C]104.077419354839[/C][/ROW]
[ROW][C]319[/C][C]526[/C][C]411.151612903226[/C][C]114.848387096774[/C][/ROW]
[ROW][C]320[/C][C]488.5[/C][C]380.006451612903[/C][C]108.493548387097[/C][/ROW]
[ROW][C]321[/C][C]520.2[/C][C]362.9[/C][C]157.3[/C][/ROW]
[ROW][C]322[/C][C]504.4[/C][C]347.458064516129[/C][C]156.941935483871[/C][/ROW]
[ROW][C]323[/C][C]568.5[/C][C]369.529032258065[/C][C]198.970967741935[/C][/ROW]
[ROW][C]324[/C][C]610.6[/C][C]371.996774193548[/C][C]238.603225806452[/C][/ROW]
[ROW][C]325[/C][C]818[/C][C]433.029032258065[/C][C]384.970967741935[/C][/ROW]
[ROW][C]326[/C][C]830.9[/C][C]442.925806451613[/C][C]387.974193548387[/C][/ROW]
[ROW][C]327[/C][C]835.9[/C][C]420.658064516129[/C][C]415.241935483871[/C][/ROW]
[ROW][C]328[/C][C]782[/C][C]381.735483870968[/C][C]400.264516129032[/C][/ROW]
[ROW][C]329[/C][C]762.3[/C][C]361.196774193548[/C][C]401.103225806452[/C][/ROW]
[ROW][C]330[/C][C]856.9[/C][C]433.922580645161[/C][C]422.977419354839[/C][/ROW]
[ROW][C]331[/C][C]820.9[/C][C]411.151612903226[/C][C]409.748387096774[/C][/ROW]
[ROW][C]332[/C][C]769.6[/C][C]380.006451612903[/C][C]389.593548387097[/C][/ROW]
[ROW][C]333[/C][C]752.2[/C][C]362.9[/C][C]389.3[/C][/ROW]
[ROW][C]334[/C][C]724.4[/C][C]347.458064516129[/C][C]376.941935483871[/C][/ROW]
[ROW][C]335[/C][C]723.1[/C][C]369.529032258065[/C][C]353.570967741935[/C][/ROW]
[ROW][C]336[/C][C]719.5[/C][C]371.996774193548[/C][C]347.503225806452[/C][/ROW]
[ROW][C]337[/C][C]817.4[/C][C]433.029032258065[/C][C]384.370967741935[/C][/ROW]
[ROW][C]338[/C][C]803.3[/C][C]442.925806451613[/C][C]360.374193548387[/C][/ROW]
[ROW][C]339[/C][C]752.5[/C][C]420.658064516129[/C][C]331.841935483871[/C][/ROW]
[ROW][C]340[/C][C]689[/C][C]381.735483870968[/C][C]307.264516129032[/C][/ROW]
[ROW][C]341[/C][C]630.4[/C][C]361.196774193548[/C][C]269.203225806452[/C][/ROW]
[ROW][C]342[/C][C]765.5[/C][C]433.922580645161[/C][C]331.577419354839[/C][/ROW]
[ROW][C]343[/C][C]757.7[/C][C]411.151612903226[/C][C]346.548387096774[/C][/ROW]
[ROW][C]344[/C][C]732.2[/C][C]380.006451612903[/C][C]352.193548387097[/C][/ROW]
[ROW][C]345[/C][C]702.6[/C][C]362.9[/C][C]339.7[/C][/ROW]
[ROW][C]346[/C][C]683.3[/C][C]347.458064516129[/C][C]335.841935483871[/C][/ROW]
[ROW][C]347[/C][C]709.5[/C][C]369.529032258065[/C][C]339.970967741935[/C][/ROW]
[ROW][C]348[/C][C]702.2[/C][C]371.996774193548[/C][C]330.203225806452[/C][/ROW]
[ROW][C]349[/C][C]784.8[/C][C]433.029032258065[/C][C]351.770967741935[/C][/ROW]
[ROW][C]350[/C][C]810.9[/C][C]442.925806451613[/C][C]367.974193548387[/C][/ROW]
[ROW][C]351[/C][C]755.6[/C][C]420.658064516129[/C][C]334.941935483871[/C][/ROW]
[ROW][C]352[/C][C]656.8[/C][C]381.735483870968[/C][C]275.064516129032[/C][/ROW]
[ROW][C]353[/C][C]615.1[/C][C]361.196774193548[/C][C]253.903225806452[/C][/ROW]
[ROW][C]354[/C][C]745.3[/C][C]433.922580645161[/C][C]311.377419354839[/C][/ROW]
[ROW][C]355[/C][C]694.1[/C][C]411.151612903226[/C][C]282.948387096774[/C][/ROW]
[ROW][C]356[/C][C]675.7[/C][C]380.006451612903[/C][C]295.693548387097[/C][/ROW]
[ROW][C]357[/C][C]643.7[/C][C]362.9[/C][C]280.8[/C][/ROW]
[ROW][C]358[/C][C]622.1[/C][C]347.458064516129[/C][C]274.641935483871[/C][/ROW]
[ROW][C]359[/C][C]634.6[/C][C]369.529032258065[/C][C]265.070967741935[/C][/ROW]
[ROW][C]360[/C][C]588[/C][C]371.996774193548[/C][C]216.003225806452[/C][/ROW]
[ROW][C]361[/C][C]689.7[/C][C]433.029032258064[/C][C]256.670967741936[/C][/ROW]
[ROW][C]362[/C][C]673.9[/C][C]442.925806451613[/C][C]230.974193548387[/C][/ROW]
[ROW][C]363[/C][C]647.9[/C][C]420.658064516129[/C][C]227.241935483871[/C][/ROW]
[ROW][C]364[/C][C]568.8[/C][C]381.735483870968[/C][C]187.064516129032[/C][/ROW]
[ROW][C]365[/C][C]545.7[/C][C]361.196774193548[/C][C]184.503225806452[/C][/ROW]
[ROW][C]366[/C][C]632.6[/C][C]433.922580645161[/C][C]198.677419354839[/C][/ROW]
[ROW][C]367[/C][C]643.8[/C][C]411.151612903226[/C][C]232.648387096774[/C][/ROW]
[ROW][C]368[/C][C]593.1[/C][C]380.006451612903[/C][C]213.093548387097[/C][/ROW]
[ROW][C]369[/C][C]579.7[/C][C]362.9[/C][C]216.8[/C][/ROW]
[ROW][C]370[/C][C]546[/C][C]347.458064516129[/C][C]198.541935483871[/C][/ROW]
[ROW][C]371[/C][C]562.9[/C][C]369.529032258065[/C][C]193.370967741935[/C][/ROW]
[ROW][C]372[/C][C]572.5[/C][C]371.996774193548[/C][C]200.503225806452[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147635&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147635&T=4

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1235.1433.029032258064-197.929032258064
2280.7442.925806451613-162.225806451613
3264.6420.658064516129-156.058064516129
4240.7381.735483870968-141.035483870968
5201.4361.196774193548-159.796774193548
6240.8433.922580645161-193.122580645161
7241.1411.151612903226-170.051612903226
8223.8380.006451612903-156.206451612903
9206.1362.9-156.8
10174.7347.458064516129-172.758064516129
11203.3369.529032258064-166.229032258065
12220.5371.996774193548-151.496774193548
13299.5433.029032258064-133.529032258065
14347.4442.925806451613-95.5258064516129
15338.3420.658064516129-82.358064516129
16327.7381.735483870968-54.0354838709677
17351.6361.196774193548-9.59677419354836
18396.6433.922580645161-37.3225806451613
19438.8411.15161290322627.6483870967742
20395.6380.00645161290315.5935483870968
21363.5362.90.600000000000004
22378.8347.45806451612931.341935483871
23357369.529032258065-12.5290322580645
24369371.996774193548-2.99677419354836
25464.8433.02903225806531.7709677419355
26479.1442.92580645161336.1741935483871
27431.3420.65806451612910.641935483871
28366.5381.735483870968-15.2354838709677
29326.3361.196774193548-34.8967741935484
30355.1433.922580645161-78.8225806451613
31331.6411.151612903226-79.5516129032258
32261.3380.006451612903-118.706451612903
33249362.9-113.9
34205.5347.458064516129-141.958064516129
35235.6369.529032258064-133.929032258065
36240.9371.996774193548-131.096774193548
37264.9433.029032258064-168.129032258065
38253.8442.925806451613-189.125806451613
39232.3420.658064516129-188.358064516129
40193.8381.735483870968-187.935483870968
41177361.196774193548-184.196774193548
42213.2433.922580645161-220.722580645161
43207.2411.151612903226-203.951612903226
44180.6380.006451612903-199.406451612903
45188.6362.9-174.3
46175.4347.458064516129-172.058064516129
47199369.529032258065-170.529032258065
48179.6371.996774193548-192.396774193548
49225.8433.029032258064-207.229032258065
50234442.925806451613-208.925806451613
51200.2420.658064516129-220.458064516129
52183.6381.735483870968-198.135483870968
53178.2361.196774193548-182.996774193548
54203.2433.922580645161-230.722580645161
55208.5411.151612903226-202.651612903226
56191.8380.006451612903-188.206451612903
57172.8362.9-190.1
58148347.458064516129-199.458064516129
59159.4369.529032258065-210.129032258065
60154.5371.996774193548-217.496774193548
61213.2433.029032258064-219.829032258065
62196.4442.925806451613-246.525806451613
63182.8420.658064516129-237.858064516129
64176.4381.735483870968-205.335483870968
65153.6361.196774193548-207.596774193548
66173.2433.922580645161-260.722580645161
67171411.151612903226-240.151612903226
68151.2380.006451612903-228.806451612903
69161.9362.9-201
70157.2347.458064516129-190.258064516129
71201.7369.529032258065-167.829032258065
72236.4371.996774193548-135.596774193548
73356.1433.029032258065-76.9290322580645
74398.3442.925806451613-44.6258064516129
75403.7420.658064516129-16.958064516129
76384.6381.7354838709682.86451612903229
77365.8361.1967741935484.60322580645163
78368.1433.922580645161-65.8225806451613
79367.9411.151612903226-43.2516129032258
80347380.006451612903-33.0064516129032
81343.3362.9-19.6
82292.9347.458064516129-54.5580645161291
83311.5369.529032258064-58.0290322580645
84300.9371.996774193548-71.0967741935484
85366.9433.029032258065-66.1290322580646
86356.9442.925806451613-86.0258064516129
87329.7420.658064516129-90.958064516129
88316.2381.735483870968-65.5354838709678
89269361.196774193548-92.1967741935484
90289.3433.922580645161-144.622580645161
91266.2411.151612903226-144.951612903226
92253.6380.006451612903-126.406451612903
93233.8362.9-129.1
94228.4347.458064516129-119.058064516129
95253.6369.529032258064-115.929032258065
96260.1371.996774193548-111.896774193548
97306.6433.029032258064-126.429032258064
98309.2442.925806451613-133.725806451613
99309.5420.658064516129-111.158064516129
100271381.735483870968-110.735483870968
101279.9361.196774193548-81.2967741935484
102317.9433.922580645161-116.022580645161
103298.4411.151612903226-112.751612903226
104246.7380.006451612903-133.306451612903
105227.3362.9-135.6
106209.1347.458064516129-138.358064516129
107259.9369.529032258064-109.629032258065
108266371.996774193548-105.996774193548
109320.6433.029032258064-112.429032258064
110308.5442.925806451613-134.425806451613
111282.2420.658064516129-138.458064516129
112262.7381.735483870968-119.035483870968
113263.5361.196774193548-97.6967741935484
114313.1433.922580645161-120.822580645161
115284.3411.151612903226-126.851612903226
116252.6380.006451612903-127.406451612903
117250.3362.9-112.6
118246.5347.458064516129-100.958064516129
119312.7369.529032258065-56.8290322580645
120333.2371.996774193548-38.7967741935484
121446.4433.02903225806513.3709677419354
122511.6442.92580645161368.6741935483871
123515.5420.65806451612994.841935483871
124506.4381.735483870968124.664516129032
125483.2361.196774193548122.003225806452
126522.3433.92258064516188.3774193548387
127509.8411.15161290322698.6483870967742
128460.7380.00645161290380.6935483870968
129405.8362.942.9
130375347.45806451612927.541935483871
131378.5369.5290322580648.97096774193549
132406.8371.99677419354834.8032258064516
133467.8433.02903225806534.7709677419355
134469.8442.92580645161326.8741935483871
135429.8420.6580645161299.14193548387101
136355.8381.735483870968-25.9354838709677
137332.7361.196774193548-28.4967741935484
138378433.922580645161-55.9225806451613
139360.5411.151612903226-50.6516129032258
140334.7380.006451612903-45.3064516129032
141319.5362.9-43.4
142323.1347.458064516129-24.358064516129
143363.6369.529032258064-5.92903225806449
144352.1371.996774193548-19.8967741935483
145411.9433.029032258065-21.1290322580645
146388.6442.925806451613-54.3258064516129
147416.4420.658064516129-4.25806451612903
148360.7381.735483870968-21.0354838709677
149338361.196774193548-23.1967741935484
150417.2433.922580645161-16.7225806451613
151388.4411.151612903226-22.7516129032258
152371.1380.006451612903-8.90645161290322
153331.5362.9-31.4
154353.7347.4580645161296.24193548387097
155396.7369.52903225806427.1709677419355
156447371.99677419354875.0032258064516
157533.5433.029032258065100.470967741935
158565.4442.925806451613122.474193548387
159542.3420.658064516129121.641935483871
160488.7381.735483870968106.964516129032
161467.1361.196774193548105.903225806452
162531.3433.92258064516197.3774193548387
163496.1411.15161290322684.9483870967742
164444380.00645161290363.9935483870968
165403.4362.940.5
166386.3347.45806451612938.841935483871
167394.1369.52903225806424.5709677419355
168404.1371.99677419354832.1032258064516
169462.1433.02903225806529.0709677419355
170448.1442.9258064516135.17419354838711
171432.3420.65806451612911.641935483871
172386.3381.7354838709684.56451612903227
173395.2361.19677419354834.0032258064516
174421.9433.922580645161-12.0225806451613
175382.9411.151612903226-28.2516129032258
176384.2380.0064516129034.19354838709675
177345.5362.9-17.4
178323.4347.458064516129-24.0580645161291
179372.6369.5290322580643.07096774193551
180376371.9967741935484.00322580645163
181462.7433.02903225806529.6709677419355
182487442.92580645161344.0741935483871
183444.2420.65806451612923.541935483871
184399.3381.73548387096817.5645161290323
185394.9361.19677419354833.7032258064516
186455.4433.92258064516121.4774193548387
187414411.1516129032262.8483870967742
188375.5380.006451612903-4.50645161290324
189347362.9-15.9
190339.4347.458064516129-8.05806451612904
191385.8369.52903225806416.2709677419355
192378.8371.9967741935486.80322580645164
193451.8433.02903225806518.7709677419355
194446.1442.9258064516133.17419354838711
195422.5420.6580645161291.84193548387099
196383.1381.7354838709681.36451612903228
197352.8361.196774193548-8.39677419354837
198445.3433.92258064516111.3774193548387
199367.5411.151612903226-43.6516129032258
200355.1380.006451612903-24.9064516129032
201326.2362.9-36.7
202319.8347.458064516129-27.658064516129
203331.8369.529032258064-37.7290322580645
204340.9371.996774193548-31.0967741935484
205394.1433.029032258065-38.9290322580645
206417.2442.925806451613-25.7258064516129
207369.9420.658064516129-50.758064516129
208349.2381.735483870968-32.5354838709677
209321.4361.196774193548-39.7967741935484
210405.7433.922580645161-28.2225806451613
211342.9411.151612903226-68.2516129032258
212316.5380.006451612903-63.5064516129032
213284.2362.9-78.7
214270.9347.458064516129-76.558064516129
215288.8369.529032258064-80.7290322580645
216278.8371.996774193548-93.1967741935483
217324.4433.029032258065-108.629032258065
218310.9442.925806451613-132.025806451613
219299420.658064516129-121.658064516129
220273381.735483870968-108.735483870968
221279.3361.196774193548-81.8967741935484
222359.2433.922580645161-74.7225806451613
223305411.151612903226-106.151612903226
224282.1380.006451612903-97.9064516129032
225250.3362.9-112.6
226246.5347.458064516129-100.958064516129
227257.9369.529032258064-111.629032258065
228266.5371.996774193548-105.496774193548
229315.9433.029032258064-117.129032258065
230318.4442.925806451613-124.525806451613
231295.4420.658064516129-125.258064516129
232266.4381.735483870968-115.335483870968
233245.8361.196774193548-115.396774193548
234362.8433.922580645161-71.1225806451613
235324.9411.151612903226-86.2516129032258
236294.2380.006451612903-85.8064516129032
237289.5362.9-73.4
238295.2347.458064516129-52.258064516129
239290.3369.529032258064-79.2290322580645
240272371.996774193548-99.9967741935483
241307.4433.029032258064-125.629032258065
242328.7442.925806451613-114.225806451613
243292.9420.658064516129-127.758064516129
244249.1381.735483870968-132.635483870968
245230.4361.196774193548-130.796774193548
246361.5433.922580645161-72.4225806451613
247321.7411.151612903226-89.4516129032258
248277.2380.006451612903-102.806451612903
249260.7362.9-102.2
250251347.458064516129-96.458064516129
251257.6369.529032258064-111.929032258064
252241.8371.996774193548-130.196774193548
253287.5433.029032258064-145.529032258065
254292.3442.925806451613-150.625806451613
255274.7420.658064516129-145.958064516129
256254.2381.735483870968-127.535483870968
257230361.196774193548-131.196774193548
258339433.922580645161-94.9225806451613
259318.2411.151612903226-92.9516129032258
260287380.006451612903-93.0064516129032
261295.8362.9-67.1
262284347.458064516129-63.458064516129
263271369.529032258064-98.5290322580645
264262.7371.996774193548-109.296774193548
265340.6433.029032258065-92.4290322580645
266379.4442.925806451613-63.5258064516129
267373.3420.658064516129-47.358064516129
268355.2381.735483870968-26.5354838709677
269338.4361.196774193548-22.7967741935484
270466.9433.92258064516132.9774193548387
271451411.15161290322639.8483870967742
272422380.00645161290341.9935483870968
273429.2362.966.3
274425.9347.45806451612978.4419354838709
275460.7369.52903225806591.1709677419355
276463.6371.99677419354891.6032258064516
277541.4433.029032258065108.370967741935
278544.2442.925806451613101.274193548387
279517.5420.65806451612996.841935483871
280469.4381.73548387096887.6645161290322
281439.4361.19677419354878.2032258064516
282549433.922580645161115.077419354839
283533411.151612903226121.848387096774
284506.1380.006451612903126.093548387097
285484362.9121.1
286457347.458064516129109.541935483871
287481.5369.529032258064111.970967741935
288469.5371.99677419354897.5032258064516
289544.7433.029032258065111.670967741935
290541.2442.92580645161398.2741935483871
291521.5420.658064516129100.841935483871
292469.7381.73548387096887.9645161290322
293434.4361.19677419354873.2032258064516
294542.6433.922580645161108.677419354839
295517.3411.151612903226106.148387096774
296485.7380.006451612903105.693548387097
297465.8362.9102.9
298447347.45806451612999.541935483871
299426.6369.52903225806457.0709677419355
300411.6371.99677419354839.6032258064517
301467.5433.02903225806534.4709677419355
302484.5442.92580645161341.5741935483871
303451.2420.65806451612930.541935483871
304417.4381.73548387096835.6645161290322
305379.9361.19677419354818.7032258064516
306484.7433.92258064516150.7774193548387
307455411.15161290322643.8483870967742
308420.8380.00645161290340.7935483870968
309416.5362.953.6
310376.3347.45806451612928.841935483871
311405.6369.52903225806536.0709677419355
312405.8371.99677419354833.8032258064516
313500.8433.02903225806467.7709677419355
314514442.92580645161371.0741935483871
315475.5420.65806451612954.841935483871
316430.1381.73548387096848.3645161290323
317414.4361.19677419354853.2032258064516
318538433.922580645161104.077419354839
319526411.151612903226114.848387096774
320488.5380.006451612903108.493548387097
321520.2362.9157.3
322504.4347.458064516129156.941935483871
323568.5369.529032258065198.970967741935
324610.6371.996774193548238.603225806452
325818433.029032258065384.970967741935
326830.9442.925806451613387.974193548387
327835.9420.658064516129415.241935483871
328782381.735483870968400.264516129032
329762.3361.196774193548401.103225806452
330856.9433.922580645161422.977419354839
331820.9411.151612903226409.748387096774
332769.6380.006451612903389.593548387097
333752.2362.9389.3
334724.4347.458064516129376.941935483871
335723.1369.529032258065353.570967741935
336719.5371.996774193548347.503225806452
337817.4433.029032258065384.370967741935
338803.3442.925806451613360.374193548387
339752.5420.658064516129331.841935483871
340689381.735483870968307.264516129032
341630.4361.196774193548269.203225806452
342765.5433.922580645161331.577419354839
343757.7411.151612903226346.548387096774
344732.2380.006451612903352.193548387097
345702.6362.9339.7
346683.3347.458064516129335.841935483871
347709.5369.529032258065339.970967741935
348702.2371.996774193548330.203225806452
349784.8433.029032258065351.770967741935
350810.9442.925806451613367.974193548387
351755.6420.658064516129334.941935483871
352656.8381.735483870968275.064516129032
353615.1361.196774193548253.903225806452
354745.3433.922580645161311.377419354839
355694.1411.151612903226282.948387096774
356675.7380.006451612903295.693548387097
357643.7362.9280.8
358622.1347.458064516129274.641935483871
359634.6369.529032258065265.070967741935
360588371.996774193548216.003225806452
361689.7433.029032258064256.670967741936
362673.9442.925806451613230.974193548387
363647.9420.658064516129227.241935483871
364568.8381.735483870968187.064516129032
365545.7361.196774193548184.503225806452
366632.6433.922580645161198.677419354839
367643.8411.151612903226232.648387096774
368593.1380.006451612903213.093548387097
369579.7362.9216.8
370546347.458064516129198.541935483871
371562.9369.529032258065193.370967741935
372572.5371.996774193548200.503225806452







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
150.03936652503036190.07873305006072380.960633474969638
160.02239020817400230.04478041634800470.977609791825998
170.03206729659407790.06413459318815590.967932703405922
180.03662302487162770.07324604974325550.963376975128372
190.05572175564953380.1114435112990680.944278244350466
200.05771933656618910.1154386731323780.942280663433811
210.05272827433555470.1054565486711090.947271725664445
220.06412046176575710.1282409235315140.935879538234243
230.05611936069924120.1122387213984820.943880639300759
240.04792170121618750.0958434024323750.952078298783812
250.06261404152546330.1252280830509270.937385958474537
260.06390555412091030.1278111082418210.93609444587909
270.05479928429074540.1095985685814910.945200715709255
280.0397231422527350.079446284505470.960276857747265
290.02638933002211880.05277866004423760.973610669977881
300.01689379128314470.03378758256628930.983106208716855
310.0103152631412450.020630526282490.989684736858755
320.006534442465057220.01306888493011440.993465557534943
330.003972396905296640.007944793810593270.996027603094703
340.002638168582222270.005276337164444550.997361831417778
350.001600649007140980.003201298014281950.998399350992859
360.0009830918331852730.001966183666370550.999016908166815
370.0006499017133201810.001299803426640360.99935009828668
380.0005731870333244350.001146374066648870.999426812966676
390.0004957546923006590.0009915093846013190.999504245307699
400.0004463207295141410.0008926414590282820.999553679270486
410.0003963548789853210.0007927097579706410.999603645121015
420.0003644178379453380.0007288356758906750.999635582162055
430.0003630771827082870.0007261543654165730.999636922817292
440.0003199213452916380.0006398426905832760.999680078654708
450.00023624046390510.0004724809278101990.999763759536095
460.000168866943313430.0003377338866268610.999831133056687
470.0001148027589159720.0002296055178319450.999885197241084
489.23437044384587e-050.0001846874088769170.999907656295562
497.39529022262269e-050.0001479058044524540.999926047097774
506.58853106233205e-050.0001317706212466410.999934114689377
516.39748433494816e-050.0001279496866989630.99993602515665
525.4053447239423e-050.0001081068944788460.999945946552761
534.19875102345845e-058.39750204691689e-050.999958012489765
543.68606975992089e-057.37213951984177e-050.999963139302401
553.11614139922284e-056.23228279844567e-050.999968838586008
562.30773344871356e-054.61546689742711e-050.999976922665513
571.76166627624149e-053.52333255248298e-050.999982383337238
581.41018173721189e-052.82036347442378e-050.999985898182628
591.1711964437022e-052.34239288740439e-050.999988288035563
601.03887421695051e-052.07774843390102e-050.99998961125783
618.74291856913948e-061.7485837138279e-050.999991257081431
629.96889748441653e-061.99377949688331e-050.999990031102516
631.02622630574208e-052.05245261148416e-050.999989737736943
648.6759019422475e-061.7351803884495e-050.999991324098058
657.704891003685e-061.540978200737e-050.999992295108996
668.27676829543204e-061.65535365908641e-050.999991723231705
678.98086841534638e-061.79617368306928e-050.999991019131585
688.69862507641854e-061.73972501528371e-050.999991301374924
697.08338595112202e-061.4166771902244e-050.999992916614049
705.36081303894685e-061.07216260778937e-050.999994639186961
713.62651323645373e-067.25302647290745e-060.999996373486764
722.29583160806133e-064.59166321612266e-060.999997704168392
731.66685978338069e-063.33371956676138e-060.999998333140217
741.40070824286479e-062.80141648572958e-060.999998599291757
751.46501117036576e-062.93002234073151e-060.99999853498883
761.6208008167148e-063.2416016334296e-060.999998379199183
771.74355322122792e-063.48710644245585e-060.999998256446779
781.52809493347263e-063.05618986694526e-060.999998471905067
791.28936054878595e-062.57872109757191e-060.999998710639451
801.17087449025716e-062.34174898051431e-060.99999882912551
811.10841929304302e-062.21683858608604e-060.999998891580707
828.55720698999593e-071.71144139799919e-060.999999144279301
836.58905052165118e-071.31781010433024e-060.999999341094948
844.67405193374397e-079.34810386748794e-070.999999532594807
853.40980215752385e-076.8196043150477e-070.999999659019784
862.25245215458828e-074.50490430917656e-070.999999774754785
871.45757259063212e-072.91514518126423e-070.999999854242741
889.49044728155475e-081.89808945631095e-070.999999905095527
895.86413717159294e-081.17282743431859e-070.999999941358628
903.89765172611583e-087.79530345223165e-080.999999961023483
912.56816670685541e-085.13633341371082e-080.999999974318333
921.62972473964117e-083.25944947928234e-080.999999983702753
931.03330302727504e-082.06660605455008e-080.99999998966697
946.46583295911455e-091.29316659182291e-080.999999993534167
954.04323668967714e-098.08647337935427e-090.999999995956763
962.50877093170103e-095.01754186340207e-090.999999997491229
971.58844949833786e-093.17689899667572e-090.999999998411551
981.01645321406304e-092.03290642812609e-090.999999998983547
996.26129641113498e-101.252259282227e-090.99999999937387
1003.79181069126984e-107.58362138253968e-100.999999999620819
1012.26751668106203e-104.53503336212406e-100.999999999773248
1021.50776341731646e-103.01552683463291e-100.999999999849224
1039.37034412591121e-111.87406882518224e-100.999999999906297
1045.93180547387998e-111.186361094776e-100.999999999940682
1053.77742692518733e-117.55485385037466e-110.999999999962226
1062.42144158327187e-114.84288316654375e-110.999999999975786
1071.48680257248412e-112.97360514496824e-110.999999999985132
1089.05500511054761e-121.81100102210952e-110.999999999990945
1095.63125931115526e-121.12625186223105e-110.999999999994369
1103.62050404584048e-127.24100809168096e-120.999999999996379
1112.36678534411197e-124.73357068822394e-120.999999999997633
1121.45096957804e-122.90193915608e-120.999999999998549
1138.46853312786835e-131.69370662557367e-120.999999999999153
1145.61391609857746e-131.12278321971549e-120.999999999999439
1153.54869035102248e-137.09738070204495e-130.999999999999645
1162.24634794081214e-134.49269588162428e-130.999999999999775
1171.37504426979885e-132.75008853959769e-130.999999999999862
1188.50851080200036e-141.70170216040007e-130.999999999999915
1196.08544872515071e-141.21708974503014e-130.999999999999939
1204.82313418259092e-149.64626836518183e-140.999999999999952
1217.27205220847782e-141.45441044169556e-130.999999999999927
1222.67843689299419e-135.35687378598838e-130.999999999999732
1231.39762087566206e-122.79524175132412e-120.999999999998602
1248.79131348946805e-121.75826269789361e-110.999999999991209
1254.03754001776561e-118.07508003553123e-110.999999999959625
1261.81210202327339e-103.62420404654677e-100.99999999981879
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1302.69815956538022e-095.39631913076044e-090.99999999730184
1312.68945506962627e-095.37891013925255e-090.999999997310545
1323.14412775621834e-096.28825551243667e-090.999999996855872
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1343.73500913077274e-097.47001826154548e-090.999999996264991
1353.27427918685115e-096.54855837370231e-090.999999996725721
1362.2836724097586e-094.5673448195172e-090.999999997716328
1371.55348113322368e-093.10696226644737e-090.999999998446519
1381.18810504804444e-092.37621009608887e-090.999999998811895
1398.50570934522887e-101.70114186904577e-090.999999999149429
1406.19143196987382e-101.23828639397476e-090.999999999380857
1414.4721115033108e-108.94422300662161e-100.999999999552789
1423.49228039464913e-106.98456078929825e-100.999999999650772
1432.89744181131039e-105.79488362262078e-100.999999999710256
1442.17364373328838e-104.34728746657677e-100.999999999782636
1451.64159228008155e-103.2831845601631e-100.999999999835841
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1493.90809235189151e-117.81618470378303e-110.999999999960919
1503.34290566902406e-116.68581133804813e-110.999999999966571
1512.51360873006647e-115.02721746013294e-110.999999999974864
1522.01175427995373e-114.02350855990746e-110.999999999979882
1531.45702157927305e-112.91404315854611e-110.99999999998543
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1551.19288964670124e-112.38577929340247e-110.999999999988071
1561.6456675958123e-113.29133519162459e-110.999999999983543
1572.9876618336051e-115.97532366721021e-110.999999999970123
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1612.75122569167444e-105.50245138334889e-100.999999999724877
1624.86773398896795e-109.7354679779359e-100.999999999513227
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1693.64623895265881e-107.29247790531762e-100.999999999635376
1702.671625798233e-105.343251596466e-100.999999999732837
1711.93288646447437e-103.86577292894873e-100.999999999806711
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1739.8905151680526e-111.97810303361052e-100.999999999901095
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1755.23625154102927e-111.04725030820585e-100.999999999947637
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1772.79310114641256e-115.58620229282513e-110.999999999972069
1781.95853335195258e-113.91706670390516e-110.999999999980415
1791.42084168104039e-112.84168336208078e-110.999999999985792
1809.92968934057614e-121.98593786811523e-110.99999999999007
1817.66703871922109e-121.53340774384422e-110.999999999992333
1826.26641061485436e-121.25328212297087e-110.999999999993734
1834.50114105474595e-129.00228210949191e-120.999999999995499
1843.068029553501e-126.136059107002e-120.999999999996932
1852.16160404288651e-124.32320808577303e-120.999999999997838
1861.76497939148101e-123.52995878296202e-120.999999999998235
1871.26741438522346e-122.53482877044693e-120.999999999998733
1888.87761469238177e-131.77552293847635e-120.999999999999112
1896.1585388064782e-131.23170776129564e-120.999999999999384
1904.31167048855417e-138.62334097710835e-130.999999999999569
1913.11850620029016e-136.23701240058032e-130.999999999999688
1922.10246077023056e-134.20492154046112e-130.99999999999979
1931.47506133582802e-132.95012267165604e-130.999999999999852
1949.77047215433379e-141.95409443086676e-130.999999999999902
1956.29047627748877e-141.25809525549775e-130.999999999999937
1963.93699929876923e-147.87399859753845e-140.999999999999961
1972.37450579060562e-144.74901158121124e-140.999999999999976
1981.77076864622104e-143.54153729244208e-140.999999999999982
1991.17918340400114e-142.35836680800228e-140.999999999999988
2007.78022599124275e-151.55604519824855e-140.999999999999992
2015.20644656982544e-151.04128931396509e-140.999999999999995
2023.4582773338732e-156.91655466774641e-150.999999999999997
2032.22015124592241e-154.44030249184481e-150.999999999999998
2041.37806943850231e-152.75613887700462e-150.999999999999999
2058.75141617124187e-161.75028323424837e-150.999999999999999
2065.44913409550121e-161.08982681910024e-150.999999999999999
2073.43707803156409e-166.87415606312819e-161
2082.05216249396173e-164.10432498792346e-161
2091.21515742459843e-162.43031484919686e-161
2108.23386636943619e-171.64677327388724e-161
2115.83466048291402e-171.1669320965828e-161
2124.04117334581099e-178.08234669162197e-171
2133.02172731346335e-176.04345462692671e-171
2142.22640820354439e-174.45281640708879e-171
2151.6271105559428e-173.2542211118856e-171
2161.24405761149603e-172.48811522299207e-171
2171.11680591733524e-172.23361183467048e-171
2181.23036601482928e-172.46073202965855e-171
2191.22457505698889e-172.44915011397779e-171
2201.07333042263577e-172.14666084527155e-171
2217.69002603993602e-181.5380052079872e-171
2226.15282737581192e-181.23056547516238e-171
2235.94313751644961e-181.18862750328992e-171
2245.38259198906864e-181.07651839781373e-171
2255.65413787847905e-181.13082757569581e-171
2265.40969690328144e-181.08193938065629e-171
2275.48514080755495e-181.09702816151099e-171
2285.16149534553543e-181.03229906910709e-171
2295.91251074596058e-181.18250214919212e-171
2307.33813193160511e-181.46762638632102e-171
2319.06788586644434e-181.81357717328887e-171
2329.79552638977121e-181.95910527795424e-171
2331.03422276364001e-172.06844552728003e-171
2349.54203055791519e-181.90840611158304e-171
2359.75399272103126e-181.95079854420625e-171
2369.8294006208099e-181.96588012416198e-171
2379.64545619186814e-181.92909123837363e-171
2388.32693035176075e-181.66538607035215e-171
2398.03163240405179e-181.60632648081036e-171
2408.76724548277293e-181.75344909655459e-171
2411.46074922995853e-172.92149845991706e-171
2422.16010836054715e-174.32021672109429e-171
2433.67399848023115e-177.3479969604623e-171
2446.26428269127021e-171.25285653825404e-161
2451.00350197206353e-162.00700394412705e-161
2461.19717604402028e-162.39435208804057e-161
2471.68383908502417e-163.36767817004835e-161
2482.67944345536286e-165.35888691072573e-161
2494.59868458318406e-169.19736916636812e-161
2507.2270097713225e-161.4454019542645e-150.999999999999999
2511.31161606385028e-152.62323212770057e-150.999999999999999
2522.88927618516539e-155.77855237033077e-150.999999999999997
2531.07495144281679e-142.14990288563359e-140.999999999999989
2544.41940123055673e-148.83880246111347e-140.999999999999956
2551.6548512375222e-133.30970247504439e-130.999999999999834
2564.24651709355111e-138.49303418710222e-130.999999999999575
2571.07294321001281e-122.14588642002562e-120.999999999998927
2582.55932760503307e-125.11865521006614e-120.999999999997441
2596.2881648591617e-121.25763297183234e-110.999999999993712
2601.54540538104084e-113.09081076208168e-110.999999999984546
2613.1782563740438e-116.35651274808759e-110.999999999968217
2625.99782364963765e-111.19956472992753e-100.999999999940022
2631.6436987372596e-103.28739747451919e-100.99999999983563
2644.97975831434805e-109.95951662869609e-100.999999999502024
2651.83289100087952e-093.66578200175904e-090.999999998167109
2664.71913628383929e-099.43827256767857e-090.999999995280864
2679.76549888727999e-091.953099777456e-080.999999990234501
2681.44534351937131e-082.89068703874263e-080.999999985546565
2691.90634131094729e-083.81268262189458e-080.999999980936587
2702.72388872361156e-085.44777744722311e-080.999999972761113
2713.89046319455933e-087.78092638911865e-080.999999961095368
2725.37920408841517e-081.07584081768303e-070.999999946207959
2737.39652757200093e-081.47930551440019e-070.999999926034724
2749.41449984126179e-081.88289996825236e-070.999999905855002
2751.18167046567228e-072.36334093134456e-070.999999881832953
2761.41427531052415e-072.82855062104831e-070.999999858572469
2772.03450453601115e-074.06900907202231e-070.999999796549546
2782.78071016654072e-075.56142033308144e-070.999999721928983
2793.54755485707925e-077.09510971415851e-070.999999645244514
2803.94242882583172e-077.88485765166345e-070.999999605757117
2814.0697216000813e-078.13944320016259e-070.99999959302784
2825.31370119172069e-071.06274023834414e-060.999999468629881
2836.96809259817672e-071.39361851963534e-060.99999930319074
2848.87428678751715e-071.77485735750343e-060.999999112571321
2851.13362384159016e-062.26724768318032e-060.999998866376158
2861.34169685071932e-062.68339370143863e-060.999998658303149
2871.54700319371116e-063.09400638742232e-060.999998452996806
2881.70716700392266e-063.41433400784532e-060.999998292832996
2892.27673267448952e-064.55346534897904e-060.999997723267326
2902.99048355036283e-065.98096710072566e-060.99999700951645
2913.64698236566476e-067.29396473132951e-060.999996353017634
2923.94736721013042e-067.89473442026084e-060.99999605263279
2934.08337438180394e-068.16674876360787e-060.999995916625618
2944.99109219677291e-069.98218439354582e-060.999995008907803
2956.13882047740952e-061.2277640954819e-050.999993861179523
2967.29340572866156e-061.45868114573231e-050.999992706594271
2978.95887957751251e-061.7917759155025e-050.999991041120422
2981.03408228119974e-052.06816456239949e-050.999989659177188
2991.3604271064537e-052.7208542129074e-050.999986395728935
3001.89511460953642e-053.79022921907285e-050.999981048853905
3014.36314144738007e-058.72628289476015e-050.999956368585526
3029.10238175689402e-050.000182047635137880.999908976182431
3030.0001864718389522240.0003729436779044480.999813528161048
3040.0002921284371217540.0005842568742435070.999707871562878
3050.0004687143763591270.0009374287527182540.999531285623641
3060.0008499893424609440.001699978684921890.999150010657539
3070.001652029796497140.003304059592994270.998347970203503
3080.003113448453778180.006226896907556360.996886551546222
3090.005583523333823020.0111670466676460.994416476666177
3100.01089217981299320.02178435962598630.989107820187007
3110.02019855745678650.04039711491357290.979801442543214
3120.03632046334105460.07264092668210920.963679536658945
3130.08438177519105350.1687635503821070.915618224808947
3140.1680827124515960.3361654249031930.831917287548404
3150.3131736529824840.6263473059649670.686826347017516
3160.4638632892519360.9277265785038720.536136710748064
3170.6020581175910360.7958837648179270.397941882408963
3180.7292895626259140.5414208747481720.270710437374086
3190.830889127671420.338221744657160.16911087232858
3200.9092479284413580.1815041431172840.0907520715586419
3210.937337300554220.1253253988915590.0626626994457795
3220.9554405893226410.08911882135471710.0445594106773586
3230.9594504522290890.0810990955418220.040549547770911
3240.9574531385160140.08509372296797150.0425468614839857
3250.9658880725420080.06822385491598310.0341119274579915
3260.9731260514317130.05374789713657490.0268739485682874
3270.9839987934526910.03200241309461720.0160012065473086
3280.9920877227302220.01582455453955520.00791227726977758
3290.9971081831433180.00578363371336480.0028918168566824
3300.9987835705747670.002432858850466480.00121642942523324
3310.9993492783013270.001301443397345610.000650721698672805
3320.9995449701419150.0009100597161703510.000455029858085175
3330.9997033695613340.0005932608773316150.000296630438665808
3340.9997935430153420.0004129139693163090.000206456984658154
3350.9998095269821230.0003809460357535990.0001904730178768
3360.99984106768160.0003178646368000570.000158932318400029
3370.9998322043869560.0003355912260880250.000167795613044012
3380.999780532646140.0004389347077192830.000219467353859642
3390.9996775101487110.0006449797025785390.000322489851289269
3400.9995866717483460.0008266565033080480.000413328251654024
3410.9993375185723140.001324962855372910.000662481427686454
3420.999147349411910.001705301176179160.00085265058808958
3430.9990083460445630.001983307910873770.000991653955436884
3440.9989343810673070.002131237865386480.00106561893269324
3450.9987389346108440.002522130778311520.00126106538915576
3460.998615641965110.002768716069780770.00138435803489039
3470.9986908057710530.002618388457894530.00130919422894727
3480.998994668776560.002010662446879510.00100533122343975
3490.9986402727119410.002719454576117950.00135972728805898
3500.999019724063440.001960551873120170.000980275936560085
3510.9989109682687530.00217806346249430.00108903173124715
3520.998344177096090.003311645807819220.00165582290390961
3530.9967204600720610.006559079855877440.00327953992793872
3540.9969723341079210.006055331784158420.00302766589207921
3550.9920913943073250.01581721138535070.00790860569267536
3560.9869092390880040.02618152182399150.0130907609119957
3570.9694510964010.06109780719800030.0305489035990001

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
15 & 0.0393665250303619 & 0.0787330500607238 & 0.960633474969638 \tabularnewline
16 & 0.0223902081740023 & 0.0447804163480047 & 0.977609791825998 \tabularnewline
17 & 0.0320672965940779 & 0.0641345931881559 & 0.967932703405922 \tabularnewline
18 & 0.0366230248716277 & 0.0732460497432555 & 0.963376975128372 \tabularnewline
19 & 0.0557217556495338 & 0.111443511299068 & 0.944278244350466 \tabularnewline
20 & 0.0577193365661891 & 0.115438673132378 & 0.942280663433811 \tabularnewline
21 & 0.0527282743355547 & 0.105456548671109 & 0.947271725664445 \tabularnewline
22 & 0.0641204617657571 & 0.128240923531514 & 0.935879538234243 \tabularnewline
23 & 0.0561193606992412 & 0.112238721398482 & 0.943880639300759 \tabularnewline
24 & 0.0479217012161875 & 0.095843402432375 & 0.952078298783812 \tabularnewline
25 & 0.0626140415254633 & 0.125228083050927 & 0.937385958474537 \tabularnewline
26 & 0.0639055541209103 & 0.127811108241821 & 0.93609444587909 \tabularnewline
27 & 0.0547992842907454 & 0.109598568581491 & 0.945200715709255 \tabularnewline
28 & 0.039723142252735 & 0.07944628450547 & 0.960276857747265 \tabularnewline
29 & 0.0263893300221188 & 0.0527786600442376 & 0.973610669977881 \tabularnewline
30 & 0.0168937912831447 & 0.0337875825662893 & 0.983106208716855 \tabularnewline
31 & 0.010315263141245 & 0.02063052628249 & 0.989684736858755 \tabularnewline
32 & 0.00653444246505722 & 0.0130688849301144 & 0.993465557534943 \tabularnewline
33 & 0.00397239690529664 & 0.00794479381059327 & 0.996027603094703 \tabularnewline
34 & 0.00263816858222227 & 0.00527633716444455 & 0.997361831417778 \tabularnewline
35 & 0.00160064900714098 & 0.00320129801428195 & 0.998399350992859 \tabularnewline
36 & 0.000983091833185273 & 0.00196618366637055 & 0.999016908166815 \tabularnewline
37 & 0.000649901713320181 & 0.00129980342664036 & 0.99935009828668 \tabularnewline
38 & 0.000573187033324435 & 0.00114637406664887 & 0.999426812966676 \tabularnewline
39 & 0.000495754692300659 & 0.000991509384601319 & 0.999504245307699 \tabularnewline
40 & 0.000446320729514141 & 0.000892641459028282 & 0.999553679270486 \tabularnewline
41 & 0.000396354878985321 & 0.000792709757970641 & 0.999603645121015 \tabularnewline
42 & 0.000364417837945338 & 0.000728835675890675 & 0.999635582162055 \tabularnewline
43 & 0.000363077182708287 & 0.000726154365416573 & 0.999636922817292 \tabularnewline
44 & 0.000319921345291638 & 0.000639842690583276 & 0.999680078654708 \tabularnewline
45 & 0.0002362404639051 & 0.000472480927810199 & 0.999763759536095 \tabularnewline
46 & 0.00016886694331343 & 0.000337733886626861 & 0.999831133056687 \tabularnewline
47 & 0.000114802758915972 & 0.000229605517831945 & 0.999885197241084 \tabularnewline
48 & 9.23437044384587e-05 & 0.000184687408876917 & 0.999907656295562 \tabularnewline
49 & 7.39529022262269e-05 & 0.000147905804452454 & 0.999926047097774 \tabularnewline
50 & 6.58853106233205e-05 & 0.000131770621246641 & 0.999934114689377 \tabularnewline
51 & 6.39748433494816e-05 & 0.000127949686698963 & 0.99993602515665 \tabularnewline
52 & 5.4053447239423e-05 & 0.000108106894478846 & 0.999945946552761 \tabularnewline
53 & 4.19875102345845e-05 & 8.39750204691689e-05 & 0.999958012489765 \tabularnewline
54 & 3.68606975992089e-05 & 7.37213951984177e-05 & 0.999963139302401 \tabularnewline
55 & 3.11614139922284e-05 & 6.23228279844567e-05 & 0.999968838586008 \tabularnewline
56 & 2.30773344871356e-05 & 4.61546689742711e-05 & 0.999976922665513 \tabularnewline
57 & 1.76166627624149e-05 & 3.52333255248298e-05 & 0.999982383337238 \tabularnewline
58 & 1.41018173721189e-05 & 2.82036347442378e-05 & 0.999985898182628 \tabularnewline
59 & 1.1711964437022e-05 & 2.34239288740439e-05 & 0.999988288035563 \tabularnewline
60 & 1.03887421695051e-05 & 2.07774843390102e-05 & 0.99998961125783 \tabularnewline
61 & 8.74291856913948e-06 & 1.7485837138279e-05 & 0.999991257081431 \tabularnewline
62 & 9.96889748441653e-06 & 1.99377949688331e-05 & 0.999990031102516 \tabularnewline
63 & 1.02622630574208e-05 & 2.05245261148416e-05 & 0.999989737736943 \tabularnewline
64 & 8.6759019422475e-06 & 1.7351803884495e-05 & 0.999991324098058 \tabularnewline
65 & 7.704891003685e-06 & 1.540978200737e-05 & 0.999992295108996 \tabularnewline
66 & 8.27676829543204e-06 & 1.65535365908641e-05 & 0.999991723231705 \tabularnewline
67 & 8.98086841534638e-06 & 1.79617368306928e-05 & 0.999991019131585 \tabularnewline
68 & 8.69862507641854e-06 & 1.73972501528371e-05 & 0.999991301374924 \tabularnewline
69 & 7.08338595112202e-06 & 1.4166771902244e-05 & 0.999992916614049 \tabularnewline
70 & 5.36081303894685e-06 & 1.07216260778937e-05 & 0.999994639186961 \tabularnewline
71 & 3.62651323645373e-06 & 7.25302647290745e-06 & 0.999996373486764 \tabularnewline
72 & 2.29583160806133e-06 & 4.59166321612266e-06 & 0.999997704168392 \tabularnewline
73 & 1.66685978338069e-06 & 3.33371956676138e-06 & 0.999998333140217 \tabularnewline
74 & 1.40070824286479e-06 & 2.80141648572958e-06 & 0.999998599291757 \tabularnewline
75 & 1.46501117036576e-06 & 2.93002234073151e-06 & 0.99999853498883 \tabularnewline
76 & 1.6208008167148e-06 & 3.2416016334296e-06 & 0.999998379199183 \tabularnewline
77 & 1.74355322122792e-06 & 3.48710644245585e-06 & 0.999998256446779 \tabularnewline
78 & 1.52809493347263e-06 & 3.05618986694526e-06 & 0.999998471905067 \tabularnewline
79 & 1.28936054878595e-06 & 2.57872109757191e-06 & 0.999998710639451 \tabularnewline
80 & 1.17087449025716e-06 & 2.34174898051431e-06 & 0.99999882912551 \tabularnewline
81 & 1.10841929304302e-06 & 2.21683858608604e-06 & 0.999998891580707 \tabularnewline
82 & 8.55720698999593e-07 & 1.71144139799919e-06 & 0.999999144279301 \tabularnewline
83 & 6.58905052165118e-07 & 1.31781010433024e-06 & 0.999999341094948 \tabularnewline
84 & 4.67405193374397e-07 & 9.34810386748794e-07 & 0.999999532594807 \tabularnewline
85 & 3.40980215752385e-07 & 6.8196043150477e-07 & 0.999999659019784 \tabularnewline
86 & 2.25245215458828e-07 & 4.50490430917656e-07 & 0.999999774754785 \tabularnewline
87 & 1.45757259063212e-07 & 2.91514518126423e-07 & 0.999999854242741 \tabularnewline
88 & 9.49044728155475e-08 & 1.89808945631095e-07 & 0.999999905095527 \tabularnewline
89 & 5.86413717159294e-08 & 1.17282743431859e-07 & 0.999999941358628 \tabularnewline
90 & 3.89765172611583e-08 & 7.79530345223165e-08 & 0.999999961023483 \tabularnewline
91 & 2.56816670685541e-08 & 5.13633341371082e-08 & 0.999999974318333 \tabularnewline
92 & 1.62972473964117e-08 & 3.25944947928234e-08 & 0.999999983702753 \tabularnewline
93 & 1.03330302727504e-08 & 2.06660605455008e-08 & 0.99999998966697 \tabularnewline
94 & 6.46583295911455e-09 & 1.29316659182291e-08 & 0.999999993534167 \tabularnewline
95 & 4.04323668967714e-09 & 8.08647337935427e-09 & 0.999999995956763 \tabularnewline
96 & 2.50877093170103e-09 & 5.01754186340207e-09 & 0.999999997491229 \tabularnewline
97 & 1.58844949833786e-09 & 3.17689899667572e-09 & 0.999999998411551 \tabularnewline
98 & 1.01645321406304e-09 & 2.03290642812609e-09 & 0.999999998983547 \tabularnewline
99 & 6.26129641113498e-10 & 1.252259282227e-09 & 0.99999999937387 \tabularnewline
100 & 3.79181069126984e-10 & 7.58362138253968e-10 & 0.999999999620819 \tabularnewline
101 & 2.26751668106203e-10 & 4.53503336212406e-10 & 0.999999999773248 \tabularnewline
102 & 1.50776341731646e-10 & 3.01552683463291e-10 & 0.999999999849224 \tabularnewline
103 & 9.37034412591121e-11 & 1.87406882518224e-10 & 0.999999999906297 \tabularnewline
104 & 5.93180547387998e-11 & 1.186361094776e-10 & 0.999999999940682 \tabularnewline
105 & 3.77742692518733e-11 & 7.55485385037466e-11 & 0.999999999962226 \tabularnewline
106 & 2.42144158327187e-11 & 4.84288316654375e-11 & 0.999999999975786 \tabularnewline
107 & 1.48680257248412e-11 & 2.97360514496824e-11 & 0.999999999985132 \tabularnewline
108 & 9.05500511054761e-12 & 1.81100102210952e-11 & 0.999999999990945 \tabularnewline
109 & 5.63125931115526e-12 & 1.12625186223105e-11 & 0.999999999994369 \tabularnewline
110 & 3.62050404584048e-12 & 7.24100809168096e-12 & 0.999999999996379 \tabularnewline
111 & 2.36678534411197e-12 & 4.73357068822394e-12 & 0.999999999997633 \tabularnewline
112 & 1.45096957804e-12 & 2.90193915608e-12 & 0.999999999998549 \tabularnewline
113 & 8.46853312786835e-13 & 1.69370662557367e-12 & 0.999999999999153 \tabularnewline
114 & 5.61391609857746e-13 & 1.12278321971549e-12 & 0.999999999999439 \tabularnewline
115 & 3.54869035102248e-13 & 7.09738070204495e-13 & 0.999999999999645 \tabularnewline
116 & 2.24634794081214e-13 & 4.49269588162428e-13 & 0.999999999999775 \tabularnewline
117 & 1.37504426979885e-13 & 2.75008853959769e-13 & 0.999999999999862 \tabularnewline
118 & 8.50851080200036e-14 & 1.70170216040007e-13 & 0.999999999999915 \tabularnewline
119 & 6.08544872515071e-14 & 1.21708974503014e-13 & 0.999999999999939 \tabularnewline
120 & 4.82313418259092e-14 & 9.64626836518183e-14 & 0.999999999999952 \tabularnewline
121 & 7.27205220847782e-14 & 1.45441044169556e-13 & 0.999999999999927 \tabularnewline
122 & 2.67843689299419e-13 & 5.35687378598838e-13 & 0.999999999999732 \tabularnewline
123 & 1.39762087566206e-12 & 2.79524175132412e-12 & 0.999999999998602 \tabularnewline
124 & 8.79131348946805e-12 & 1.75826269789361e-11 & 0.999999999991209 \tabularnewline
125 & 4.03754001776561e-11 & 8.07508003553123e-11 & 0.999999999959625 \tabularnewline
126 & 1.81210202327339e-10 & 3.62420404654677e-10 & 0.99999999981879 \tabularnewline
127 & 6.40428555161331e-10 & 1.28085711032266e-09 & 0.999999999359571 \tabularnewline
128 & 1.57865269274423e-09 & 3.15730538548845e-09 & 0.999999998421347 \tabularnewline
129 & 2.20747958156887e-09 & 4.41495916313775e-09 & 0.99999999779252 \tabularnewline
130 & 2.69815956538022e-09 & 5.39631913076044e-09 & 0.99999999730184 \tabularnewline
131 & 2.68945506962627e-09 & 5.37891013925255e-09 & 0.999999997310545 \tabularnewline
132 & 3.14412775621834e-09 & 6.28825551243667e-09 & 0.999999996855872 \tabularnewline
133 & 3.63794567092302e-09 & 7.27589134184604e-09 & 0.999999996362054 \tabularnewline
134 & 3.73500913077274e-09 & 7.47001826154548e-09 & 0.999999996264991 \tabularnewline
135 & 3.27427918685115e-09 & 6.54855837370231e-09 & 0.999999996725721 \tabularnewline
136 & 2.2836724097586e-09 & 4.5673448195172e-09 & 0.999999997716328 \tabularnewline
137 & 1.55348113322368e-09 & 3.10696226644737e-09 & 0.999999998446519 \tabularnewline
138 & 1.18810504804444e-09 & 2.37621009608887e-09 & 0.999999998811895 \tabularnewline
139 & 8.50570934522887e-10 & 1.70114186904577e-09 & 0.999999999149429 \tabularnewline
140 & 6.19143196987382e-10 & 1.23828639397476e-09 & 0.999999999380857 \tabularnewline
141 & 4.4721115033108e-10 & 8.94422300662161e-10 & 0.999999999552789 \tabularnewline
142 & 3.49228039464913e-10 & 6.98456078929825e-10 & 0.999999999650772 \tabularnewline
143 & 2.89744181131039e-10 & 5.79488362262078e-10 & 0.999999999710256 \tabularnewline
144 & 2.17364373328838e-10 & 4.34728746657677e-10 & 0.999999999782636 \tabularnewline
145 & 1.64159228008155e-10 & 3.2831845601631e-10 & 0.999999999835841 \tabularnewline
146 & 1.1237608692757e-10 & 2.24752173855139e-10 & 0.999999999887624 \tabularnewline
147 & 8.62437533146602e-11 & 1.7248750662932e-10 & 0.999999999913756 \tabularnewline
148 & 5.87423340046412e-11 & 1.17484668009282e-10 & 0.999999999941258 \tabularnewline
149 & 3.90809235189151e-11 & 7.81618470378303e-11 & 0.999999999960919 \tabularnewline
150 & 3.34290566902406e-11 & 6.68581133804813e-11 & 0.999999999966571 \tabularnewline
151 & 2.51360873006647e-11 & 5.02721746013294e-11 & 0.999999999974864 \tabularnewline
152 & 2.01175427995373e-11 & 4.02350855990746e-11 & 0.999999999979882 \tabularnewline
153 & 1.45702157927305e-11 & 2.91404315854611e-11 & 0.99999999998543 \tabularnewline
154 & 1.25584522408521e-11 & 2.51169044817041e-11 & 0.999999999987442 \tabularnewline
155 & 1.19288964670124e-11 & 2.38577929340247e-11 & 0.999999999988071 \tabularnewline
156 & 1.6456675958123e-11 & 3.29133519162459e-11 & 0.999999999983543 \tabularnewline
157 & 2.9876618336051e-11 & 5.97532366721021e-11 & 0.999999999970123 \tabularnewline
158 & 6.71038631460685e-11 & 1.34207726292137e-10 & 0.999999999932896 \tabularnewline
159 & 1.32032012881635e-10 & 2.6406402576327e-10 & 0.999999999867968 \tabularnewline
160 & 1.96063337017922e-10 & 3.92126674035844e-10 & 0.999999999803937 \tabularnewline
161 & 2.75122569167444e-10 & 5.50245138334889e-10 & 0.999999999724877 \tabularnewline
162 & 4.86773398896795e-10 & 9.7354679779359e-10 & 0.999999999513227 \tabularnewline
163 & 6.55310755063836e-10 & 1.31062151012767e-09 & 0.999999999344689 \tabularnewline
164 & 7.34540250902404e-10 & 1.46908050180481e-09 & 0.99999999926546 \tabularnewline
165 & 6.98771566174517e-10 & 1.39754313234903e-09 & 0.999999999301228 \tabularnewline
166 & 6.51113181948235e-10 & 1.30222636389647e-09 & 0.999999999348887 \tabularnewline
167 & 5.42576526599469e-10 & 1.08515305319894e-09 & 0.999999999457423 \tabularnewline
168 & 4.47209350572969e-10 & 8.94418701145938e-10 & 0.999999999552791 \tabularnewline
169 & 3.64623895265881e-10 & 7.29247790531762e-10 & 0.999999999635376 \tabularnewline
170 & 2.671625798233e-10 & 5.343251596466e-10 & 0.999999999732837 \tabularnewline
171 & 1.93288646447437e-10 & 3.86577292894873e-10 & 0.999999999806711 \tabularnewline
172 & 1.32721080845178e-10 & 2.65442161690356e-10 & 0.999999999867279 \tabularnewline
173 & 9.8905151680526e-11 & 1.97810303361052e-10 & 0.999999999901095 \tabularnewline
174 & 7.50917420002014e-11 & 1.50183484000403e-10 & 0.999999999924908 \tabularnewline
175 & 5.23625154102927e-11 & 1.04725030820585e-10 & 0.999999999947637 \tabularnewline
176 & 3.91727218809132e-11 & 7.83454437618264e-11 & 0.999999999960827 \tabularnewline
177 & 2.79310114641256e-11 & 5.58620229282513e-11 & 0.999999999972069 \tabularnewline
178 & 1.95853335195258e-11 & 3.91706670390516e-11 & 0.999999999980415 \tabularnewline
179 & 1.42084168104039e-11 & 2.84168336208078e-11 & 0.999999999985792 \tabularnewline
180 & 9.92968934057614e-12 & 1.98593786811523e-11 & 0.99999999999007 \tabularnewline
181 & 7.66703871922109e-12 & 1.53340774384422e-11 & 0.999999999992333 \tabularnewline
182 & 6.26641061485436e-12 & 1.25328212297087e-11 & 0.999999999993734 \tabularnewline
183 & 4.50114105474595e-12 & 9.00228210949191e-12 & 0.999999999995499 \tabularnewline
184 & 3.068029553501e-12 & 6.136059107002e-12 & 0.999999999996932 \tabularnewline
185 & 2.16160404288651e-12 & 4.32320808577303e-12 & 0.999999999997838 \tabularnewline
186 & 1.76497939148101e-12 & 3.52995878296202e-12 & 0.999999999998235 \tabularnewline
187 & 1.26741438522346e-12 & 2.53482877044693e-12 & 0.999999999998733 \tabularnewline
188 & 8.87761469238177e-13 & 1.77552293847635e-12 & 0.999999999999112 \tabularnewline
189 & 6.1585388064782e-13 & 1.23170776129564e-12 & 0.999999999999384 \tabularnewline
190 & 4.31167048855417e-13 & 8.62334097710835e-13 & 0.999999999999569 \tabularnewline
191 & 3.11850620029016e-13 & 6.23701240058032e-13 & 0.999999999999688 \tabularnewline
192 & 2.10246077023056e-13 & 4.20492154046112e-13 & 0.99999999999979 \tabularnewline
193 & 1.47506133582802e-13 & 2.95012267165604e-13 & 0.999999999999852 \tabularnewline
194 & 9.77047215433379e-14 & 1.95409443086676e-13 & 0.999999999999902 \tabularnewline
195 & 6.29047627748877e-14 & 1.25809525549775e-13 & 0.999999999999937 \tabularnewline
196 & 3.93699929876923e-14 & 7.87399859753845e-14 & 0.999999999999961 \tabularnewline
197 & 2.37450579060562e-14 & 4.74901158121124e-14 & 0.999999999999976 \tabularnewline
198 & 1.77076864622104e-14 & 3.54153729244208e-14 & 0.999999999999982 \tabularnewline
199 & 1.17918340400114e-14 & 2.35836680800228e-14 & 0.999999999999988 \tabularnewline
200 & 7.78022599124275e-15 & 1.55604519824855e-14 & 0.999999999999992 \tabularnewline
201 & 5.20644656982544e-15 & 1.04128931396509e-14 & 0.999999999999995 \tabularnewline
202 & 3.4582773338732e-15 & 6.91655466774641e-15 & 0.999999999999997 \tabularnewline
203 & 2.22015124592241e-15 & 4.44030249184481e-15 & 0.999999999999998 \tabularnewline
204 & 1.37806943850231e-15 & 2.75613887700462e-15 & 0.999999999999999 \tabularnewline
205 & 8.75141617124187e-16 & 1.75028323424837e-15 & 0.999999999999999 \tabularnewline
206 & 5.44913409550121e-16 & 1.08982681910024e-15 & 0.999999999999999 \tabularnewline
207 & 3.43707803156409e-16 & 6.87415606312819e-16 & 1 \tabularnewline
208 & 2.05216249396173e-16 & 4.10432498792346e-16 & 1 \tabularnewline
209 & 1.21515742459843e-16 & 2.43031484919686e-16 & 1 \tabularnewline
210 & 8.23386636943619e-17 & 1.64677327388724e-16 & 1 \tabularnewline
211 & 5.83466048291402e-17 & 1.1669320965828e-16 & 1 \tabularnewline
212 & 4.04117334581099e-17 & 8.08234669162197e-17 & 1 \tabularnewline
213 & 3.02172731346335e-17 & 6.04345462692671e-17 & 1 \tabularnewline
214 & 2.22640820354439e-17 & 4.45281640708879e-17 & 1 \tabularnewline
215 & 1.6271105559428e-17 & 3.2542211118856e-17 & 1 \tabularnewline
216 & 1.24405761149603e-17 & 2.48811522299207e-17 & 1 \tabularnewline
217 & 1.11680591733524e-17 & 2.23361183467048e-17 & 1 \tabularnewline
218 & 1.23036601482928e-17 & 2.46073202965855e-17 & 1 \tabularnewline
219 & 1.22457505698889e-17 & 2.44915011397779e-17 & 1 \tabularnewline
220 & 1.07333042263577e-17 & 2.14666084527155e-17 & 1 \tabularnewline
221 & 7.69002603993602e-18 & 1.5380052079872e-17 & 1 \tabularnewline
222 & 6.15282737581192e-18 & 1.23056547516238e-17 & 1 \tabularnewline
223 & 5.94313751644961e-18 & 1.18862750328992e-17 & 1 \tabularnewline
224 & 5.38259198906864e-18 & 1.07651839781373e-17 & 1 \tabularnewline
225 & 5.65413787847905e-18 & 1.13082757569581e-17 & 1 \tabularnewline
226 & 5.40969690328144e-18 & 1.08193938065629e-17 & 1 \tabularnewline
227 & 5.48514080755495e-18 & 1.09702816151099e-17 & 1 \tabularnewline
228 & 5.16149534553543e-18 & 1.03229906910709e-17 & 1 \tabularnewline
229 & 5.91251074596058e-18 & 1.18250214919212e-17 & 1 \tabularnewline
230 & 7.33813193160511e-18 & 1.46762638632102e-17 & 1 \tabularnewline
231 & 9.06788586644434e-18 & 1.81357717328887e-17 & 1 \tabularnewline
232 & 9.79552638977121e-18 & 1.95910527795424e-17 & 1 \tabularnewline
233 & 1.03422276364001e-17 & 2.06844552728003e-17 & 1 \tabularnewline
234 & 9.54203055791519e-18 & 1.90840611158304e-17 & 1 \tabularnewline
235 & 9.75399272103126e-18 & 1.95079854420625e-17 & 1 \tabularnewline
236 & 9.8294006208099e-18 & 1.96588012416198e-17 & 1 \tabularnewline
237 & 9.64545619186814e-18 & 1.92909123837363e-17 & 1 \tabularnewline
238 & 8.32693035176075e-18 & 1.66538607035215e-17 & 1 \tabularnewline
239 & 8.03163240405179e-18 & 1.60632648081036e-17 & 1 \tabularnewline
240 & 8.76724548277293e-18 & 1.75344909655459e-17 & 1 \tabularnewline
241 & 1.46074922995853e-17 & 2.92149845991706e-17 & 1 \tabularnewline
242 & 2.16010836054715e-17 & 4.32021672109429e-17 & 1 \tabularnewline
243 & 3.67399848023115e-17 & 7.3479969604623e-17 & 1 \tabularnewline
244 & 6.26428269127021e-17 & 1.25285653825404e-16 & 1 \tabularnewline
245 & 1.00350197206353e-16 & 2.00700394412705e-16 & 1 \tabularnewline
246 & 1.19717604402028e-16 & 2.39435208804057e-16 & 1 \tabularnewline
247 & 1.68383908502417e-16 & 3.36767817004835e-16 & 1 \tabularnewline
248 & 2.67944345536286e-16 & 5.35888691072573e-16 & 1 \tabularnewline
249 & 4.59868458318406e-16 & 9.19736916636812e-16 & 1 \tabularnewline
250 & 7.2270097713225e-16 & 1.4454019542645e-15 & 0.999999999999999 \tabularnewline
251 & 1.31161606385028e-15 & 2.62323212770057e-15 & 0.999999999999999 \tabularnewline
252 & 2.88927618516539e-15 & 5.77855237033077e-15 & 0.999999999999997 \tabularnewline
253 & 1.07495144281679e-14 & 2.14990288563359e-14 & 0.999999999999989 \tabularnewline
254 & 4.41940123055673e-14 & 8.83880246111347e-14 & 0.999999999999956 \tabularnewline
255 & 1.6548512375222e-13 & 3.30970247504439e-13 & 0.999999999999834 \tabularnewline
256 & 4.24651709355111e-13 & 8.49303418710222e-13 & 0.999999999999575 \tabularnewline
257 & 1.07294321001281e-12 & 2.14588642002562e-12 & 0.999999999998927 \tabularnewline
258 & 2.55932760503307e-12 & 5.11865521006614e-12 & 0.999999999997441 \tabularnewline
259 & 6.2881648591617e-12 & 1.25763297183234e-11 & 0.999999999993712 \tabularnewline
260 & 1.54540538104084e-11 & 3.09081076208168e-11 & 0.999999999984546 \tabularnewline
261 & 3.1782563740438e-11 & 6.35651274808759e-11 & 0.999999999968217 \tabularnewline
262 & 5.99782364963765e-11 & 1.19956472992753e-10 & 0.999999999940022 \tabularnewline
263 & 1.6436987372596e-10 & 3.28739747451919e-10 & 0.99999999983563 \tabularnewline
264 & 4.97975831434805e-10 & 9.95951662869609e-10 & 0.999999999502024 \tabularnewline
265 & 1.83289100087952e-09 & 3.66578200175904e-09 & 0.999999998167109 \tabularnewline
266 & 4.71913628383929e-09 & 9.43827256767857e-09 & 0.999999995280864 \tabularnewline
267 & 9.76549888727999e-09 & 1.953099777456e-08 & 0.999999990234501 \tabularnewline
268 & 1.44534351937131e-08 & 2.89068703874263e-08 & 0.999999985546565 \tabularnewline
269 & 1.90634131094729e-08 & 3.81268262189458e-08 & 0.999999980936587 \tabularnewline
270 & 2.72388872361156e-08 & 5.44777744722311e-08 & 0.999999972761113 \tabularnewline
271 & 3.89046319455933e-08 & 7.78092638911865e-08 & 0.999999961095368 \tabularnewline
272 & 5.37920408841517e-08 & 1.07584081768303e-07 & 0.999999946207959 \tabularnewline
273 & 7.39652757200093e-08 & 1.47930551440019e-07 & 0.999999926034724 \tabularnewline
274 & 9.41449984126179e-08 & 1.88289996825236e-07 & 0.999999905855002 \tabularnewline
275 & 1.18167046567228e-07 & 2.36334093134456e-07 & 0.999999881832953 \tabularnewline
276 & 1.41427531052415e-07 & 2.82855062104831e-07 & 0.999999858572469 \tabularnewline
277 & 2.03450453601115e-07 & 4.06900907202231e-07 & 0.999999796549546 \tabularnewline
278 & 2.78071016654072e-07 & 5.56142033308144e-07 & 0.999999721928983 \tabularnewline
279 & 3.54755485707925e-07 & 7.09510971415851e-07 & 0.999999645244514 \tabularnewline
280 & 3.94242882583172e-07 & 7.88485765166345e-07 & 0.999999605757117 \tabularnewline
281 & 4.0697216000813e-07 & 8.13944320016259e-07 & 0.99999959302784 \tabularnewline
282 & 5.31370119172069e-07 & 1.06274023834414e-06 & 0.999999468629881 \tabularnewline
283 & 6.96809259817672e-07 & 1.39361851963534e-06 & 0.99999930319074 \tabularnewline
284 & 8.87428678751715e-07 & 1.77485735750343e-06 & 0.999999112571321 \tabularnewline
285 & 1.13362384159016e-06 & 2.26724768318032e-06 & 0.999998866376158 \tabularnewline
286 & 1.34169685071932e-06 & 2.68339370143863e-06 & 0.999998658303149 \tabularnewline
287 & 1.54700319371116e-06 & 3.09400638742232e-06 & 0.999998452996806 \tabularnewline
288 & 1.70716700392266e-06 & 3.41433400784532e-06 & 0.999998292832996 \tabularnewline
289 & 2.27673267448952e-06 & 4.55346534897904e-06 & 0.999997723267326 \tabularnewline
290 & 2.99048355036283e-06 & 5.98096710072566e-06 & 0.99999700951645 \tabularnewline
291 & 3.64698236566476e-06 & 7.29396473132951e-06 & 0.999996353017634 \tabularnewline
292 & 3.94736721013042e-06 & 7.89473442026084e-06 & 0.99999605263279 \tabularnewline
293 & 4.08337438180394e-06 & 8.16674876360787e-06 & 0.999995916625618 \tabularnewline
294 & 4.99109219677291e-06 & 9.98218439354582e-06 & 0.999995008907803 \tabularnewline
295 & 6.13882047740952e-06 & 1.2277640954819e-05 & 0.999993861179523 \tabularnewline
296 & 7.29340572866156e-06 & 1.45868114573231e-05 & 0.999992706594271 \tabularnewline
297 & 8.95887957751251e-06 & 1.7917759155025e-05 & 0.999991041120422 \tabularnewline
298 & 1.03408228119974e-05 & 2.06816456239949e-05 & 0.999989659177188 \tabularnewline
299 & 1.3604271064537e-05 & 2.7208542129074e-05 & 0.999986395728935 \tabularnewline
300 & 1.89511460953642e-05 & 3.79022921907285e-05 & 0.999981048853905 \tabularnewline
301 & 4.36314144738007e-05 & 8.72628289476015e-05 & 0.999956368585526 \tabularnewline
302 & 9.10238175689402e-05 & 0.00018204763513788 & 0.999908976182431 \tabularnewline
303 & 0.000186471838952224 & 0.000372943677904448 & 0.999813528161048 \tabularnewline
304 & 0.000292128437121754 & 0.000584256874243507 & 0.999707871562878 \tabularnewline
305 & 0.000468714376359127 & 0.000937428752718254 & 0.999531285623641 \tabularnewline
306 & 0.000849989342460944 & 0.00169997868492189 & 0.999150010657539 \tabularnewline
307 & 0.00165202979649714 & 0.00330405959299427 & 0.998347970203503 \tabularnewline
308 & 0.00311344845377818 & 0.00622689690755636 & 0.996886551546222 \tabularnewline
309 & 0.00558352333382302 & 0.011167046667646 & 0.994416476666177 \tabularnewline
310 & 0.0108921798129932 & 0.0217843596259863 & 0.989107820187007 \tabularnewline
311 & 0.0201985574567865 & 0.0403971149135729 & 0.979801442543214 \tabularnewline
312 & 0.0363204633410546 & 0.0726409266821092 & 0.963679536658945 \tabularnewline
313 & 0.0843817751910535 & 0.168763550382107 & 0.915618224808947 \tabularnewline
314 & 0.168082712451596 & 0.336165424903193 & 0.831917287548404 \tabularnewline
315 & 0.313173652982484 & 0.626347305964967 & 0.686826347017516 \tabularnewline
316 & 0.463863289251936 & 0.927726578503872 & 0.536136710748064 \tabularnewline
317 & 0.602058117591036 & 0.795883764817927 & 0.397941882408963 \tabularnewline
318 & 0.729289562625914 & 0.541420874748172 & 0.270710437374086 \tabularnewline
319 & 0.83088912767142 & 0.33822174465716 & 0.16911087232858 \tabularnewline
320 & 0.909247928441358 & 0.181504143117284 & 0.0907520715586419 \tabularnewline
321 & 0.93733730055422 & 0.125325398891559 & 0.0626626994457795 \tabularnewline
322 & 0.955440589322641 & 0.0891188213547171 & 0.0445594106773586 \tabularnewline
323 & 0.959450452229089 & 0.081099095541822 & 0.040549547770911 \tabularnewline
324 & 0.957453138516014 & 0.0850937229679715 & 0.0425468614839857 \tabularnewline
325 & 0.965888072542008 & 0.0682238549159831 & 0.0341119274579915 \tabularnewline
326 & 0.973126051431713 & 0.0537478971365749 & 0.0268739485682874 \tabularnewline
327 & 0.983998793452691 & 0.0320024130946172 & 0.0160012065473086 \tabularnewline
328 & 0.992087722730222 & 0.0158245545395552 & 0.00791227726977758 \tabularnewline
329 & 0.997108183143318 & 0.0057836337133648 & 0.0028918168566824 \tabularnewline
330 & 0.998783570574767 & 0.00243285885046648 & 0.00121642942523324 \tabularnewline
331 & 0.999349278301327 & 0.00130144339734561 & 0.000650721698672805 \tabularnewline
332 & 0.999544970141915 & 0.000910059716170351 & 0.000455029858085175 \tabularnewline
333 & 0.999703369561334 & 0.000593260877331615 & 0.000296630438665808 \tabularnewline
334 & 0.999793543015342 & 0.000412913969316309 & 0.000206456984658154 \tabularnewline
335 & 0.999809526982123 & 0.000380946035753599 & 0.0001904730178768 \tabularnewline
336 & 0.9998410676816 & 0.000317864636800057 & 0.000158932318400029 \tabularnewline
337 & 0.999832204386956 & 0.000335591226088025 & 0.000167795613044012 \tabularnewline
338 & 0.99978053264614 & 0.000438934707719283 & 0.000219467353859642 \tabularnewline
339 & 0.999677510148711 & 0.000644979702578539 & 0.000322489851289269 \tabularnewline
340 & 0.999586671748346 & 0.000826656503308048 & 0.000413328251654024 \tabularnewline
341 & 0.999337518572314 & 0.00132496285537291 & 0.000662481427686454 \tabularnewline
342 & 0.99914734941191 & 0.00170530117617916 & 0.00085265058808958 \tabularnewline
343 & 0.999008346044563 & 0.00198330791087377 & 0.000991653955436884 \tabularnewline
344 & 0.998934381067307 & 0.00213123786538648 & 0.00106561893269324 \tabularnewline
345 & 0.998738934610844 & 0.00252213077831152 & 0.00126106538915576 \tabularnewline
346 & 0.99861564196511 & 0.00276871606978077 & 0.00138435803489039 \tabularnewline
347 & 0.998690805771053 & 0.00261838845789453 & 0.00130919422894727 \tabularnewline
348 & 0.99899466877656 & 0.00201066244687951 & 0.00100533122343975 \tabularnewline
349 & 0.998640272711941 & 0.00271945457611795 & 0.00135972728805898 \tabularnewline
350 & 0.99901972406344 & 0.00196055187312017 & 0.000980275936560085 \tabularnewline
351 & 0.998910968268753 & 0.0021780634624943 & 0.00108903173124715 \tabularnewline
352 & 0.99834417709609 & 0.00331164580781922 & 0.00165582290390961 \tabularnewline
353 & 0.996720460072061 & 0.00655907985587744 & 0.00327953992793872 \tabularnewline
354 & 0.996972334107921 & 0.00605533178415842 & 0.00302766589207921 \tabularnewline
355 & 0.992091394307325 & 0.0158172113853507 & 0.00790860569267536 \tabularnewline
356 & 0.986909239088004 & 0.0261815218239915 & 0.0130907609119957 \tabularnewline
357 & 0.969451096401 & 0.0610978071980003 & 0.0305489035990001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147635&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]15[/C][C]0.0393665250303619[/C][C]0.0787330500607238[/C][C]0.960633474969638[/C][/ROW]
[ROW][C]16[/C][C]0.0223902081740023[/C][C]0.0447804163480047[/C][C]0.977609791825998[/C][/ROW]
[ROW][C]17[/C][C]0.0320672965940779[/C][C]0.0641345931881559[/C][C]0.967932703405922[/C][/ROW]
[ROW][C]18[/C][C]0.0366230248716277[/C][C]0.0732460497432555[/C][C]0.963376975128372[/C][/ROW]
[ROW][C]19[/C][C]0.0557217556495338[/C][C]0.111443511299068[/C][C]0.944278244350466[/C][/ROW]
[ROW][C]20[/C][C]0.0577193365661891[/C][C]0.115438673132378[/C][C]0.942280663433811[/C][/ROW]
[ROW][C]21[/C][C]0.0527282743355547[/C][C]0.105456548671109[/C][C]0.947271725664445[/C][/ROW]
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[ROW][C]161[/C][C]2.75122569167444e-10[/C][C]5.50245138334889e-10[/C][C]0.999999999724877[/C][/ROW]
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[ROW][C]163[/C][C]6.55310755063836e-10[/C][C]1.31062151012767e-09[/C][C]0.999999999344689[/C][/ROW]
[ROW][C]164[/C][C]7.34540250902404e-10[/C][C]1.46908050180481e-09[/C][C]0.99999999926546[/C][/ROW]
[ROW][C]165[/C][C]6.98771566174517e-10[/C][C]1.39754313234903e-09[/C][C]0.999999999301228[/C][/ROW]
[ROW][C]166[/C][C]6.51113181948235e-10[/C][C]1.30222636389647e-09[/C][C]0.999999999348887[/C][/ROW]
[ROW][C]167[/C][C]5.42576526599469e-10[/C][C]1.08515305319894e-09[/C][C]0.999999999457423[/C][/ROW]
[ROW][C]168[/C][C]4.47209350572969e-10[/C][C]8.94418701145938e-10[/C][C]0.999999999552791[/C][/ROW]
[ROW][C]169[/C][C]3.64623895265881e-10[/C][C]7.29247790531762e-10[/C][C]0.999999999635376[/C][/ROW]
[ROW][C]170[/C][C]2.671625798233e-10[/C][C]5.343251596466e-10[/C][C]0.999999999732837[/C][/ROW]
[ROW][C]171[/C][C]1.93288646447437e-10[/C][C]3.86577292894873e-10[/C][C]0.999999999806711[/C][/ROW]
[ROW][C]172[/C][C]1.32721080845178e-10[/C][C]2.65442161690356e-10[/C][C]0.999999999867279[/C][/ROW]
[ROW][C]173[/C][C]9.8905151680526e-11[/C][C]1.97810303361052e-10[/C][C]0.999999999901095[/C][/ROW]
[ROW][C]174[/C][C]7.50917420002014e-11[/C][C]1.50183484000403e-10[/C][C]0.999999999924908[/C][/ROW]
[ROW][C]175[/C][C]5.23625154102927e-11[/C][C]1.04725030820585e-10[/C][C]0.999999999947637[/C][/ROW]
[ROW][C]176[/C][C]3.91727218809132e-11[/C][C]7.83454437618264e-11[/C][C]0.999999999960827[/C][/ROW]
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[ROW][C]183[/C][C]4.50114105474595e-12[/C][C]9.00228210949191e-12[/C][C]0.999999999995499[/C][/ROW]
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[ROW][C]187[/C][C]1.26741438522346e-12[/C][C]2.53482877044693e-12[/C][C]0.999999999998733[/C][/ROW]
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[ROW][C]207[/C][C]3.43707803156409e-16[/C][C]6.87415606312819e-16[/C][C]1[/C][/ROW]
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[ROW][C]209[/C][C]1.21515742459843e-16[/C][C]2.43031484919686e-16[/C][C]1[/C][/ROW]
[ROW][C]210[/C][C]8.23386636943619e-17[/C][C]1.64677327388724e-16[/C][C]1[/C][/ROW]
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[ROW][C]250[/C][C]7.2270097713225e-16[/C][C]1.4454019542645e-15[/C][C]0.999999999999999[/C][/ROW]
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[ROW][C]306[/C][C]0.000849989342460944[/C][C]0.00169997868492189[/C][C]0.999150010657539[/C][/ROW]
[ROW][C]307[/C][C]0.00165202979649714[/C][C]0.00330405959299427[/C][C]0.998347970203503[/C][/ROW]
[ROW][C]308[/C][C]0.00311344845377818[/C][C]0.00622689690755636[/C][C]0.996886551546222[/C][/ROW]
[ROW][C]309[/C][C]0.00558352333382302[/C][C]0.011167046667646[/C][C]0.994416476666177[/C][/ROW]
[ROW][C]310[/C][C]0.0108921798129932[/C][C]0.0217843596259863[/C][C]0.989107820187007[/C][/ROW]
[ROW][C]311[/C][C]0.0201985574567865[/C][C]0.0403971149135729[/C][C]0.979801442543214[/C][/ROW]
[ROW][C]312[/C][C]0.0363204633410546[/C][C]0.0726409266821092[/C][C]0.963679536658945[/C][/ROW]
[ROW][C]313[/C][C]0.0843817751910535[/C][C]0.168763550382107[/C][C]0.915618224808947[/C][/ROW]
[ROW][C]314[/C][C]0.168082712451596[/C][C]0.336165424903193[/C][C]0.831917287548404[/C][/ROW]
[ROW][C]315[/C][C]0.313173652982484[/C][C]0.626347305964967[/C][C]0.686826347017516[/C][/ROW]
[ROW][C]316[/C][C]0.463863289251936[/C][C]0.927726578503872[/C][C]0.536136710748064[/C][/ROW]
[ROW][C]317[/C][C]0.602058117591036[/C][C]0.795883764817927[/C][C]0.397941882408963[/C][/ROW]
[ROW][C]318[/C][C]0.729289562625914[/C][C]0.541420874748172[/C][C]0.270710437374086[/C][/ROW]
[ROW][C]319[/C][C]0.83088912767142[/C][C]0.33822174465716[/C][C]0.16911087232858[/C][/ROW]
[ROW][C]320[/C][C]0.909247928441358[/C][C]0.181504143117284[/C][C]0.0907520715586419[/C][/ROW]
[ROW][C]321[/C][C]0.93733730055422[/C][C]0.125325398891559[/C][C]0.0626626994457795[/C][/ROW]
[ROW][C]322[/C][C]0.955440589322641[/C][C]0.0891188213547171[/C][C]0.0445594106773586[/C][/ROW]
[ROW][C]323[/C][C]0.959450452229089[/C][C]0.081099095541822[/C][C]0.040549547770911[/C][/ROW]
[ROW][C]324[/C][C]0.957453138516014[/C][C]0.0850937229679715[/C][C]0.0425468614839857[/C][/ROW]
[ROW][C]325[/C][C]0.965888072542008[/C][C]0.0682238549159831[/C][C]0.0341119274579915[/C][/ROW]
[ROW][C]326[/C][C]0.973126051431713[/C][C]0.0537478971365749[/C][C]0.0268739485682874[/C][/ROW]
[ROW][C]327[/C][C]0.983998793452691[/C][C]0.0320024130946172[/C][C]0.0160012065473086[/C][/ROW]
[ROW][C]328[/C][C]0.992087722730222[/C][C]0.0158245545395552[/C][C]0.00791227726977758[/C][/ROW]
[ROW][C]329[/C][C]0.997108183143318[/C][C]0.0057836337133648[/C][C]0.0028918168566824[/C][/ROW]
[ROW][C]330[/C][C]0.998783570574767[/C][C]0.00243285885046648[/C][C]0.00121642942523324[/C][/ROW]
[ROW][C]331[/C][C]0.999349278301327[/C][C]0.00130144339734561[/C][C]0.000650721698672805[/C][/ROW]
[ROW][C]332[/C][C]0.999544970141915[/C][C]0.000910059716170351[/C][C]0.000455029858085175[/C][/ROW]
[ROW][C]333[/C][C]0.999703369561334[/C][C]0.000593260877331615[/C][C]0.000296630438665808[/C][/ROW]
[ROW][C]334[/C][C]0.999793543015342[/C][C]0.000412913969316309[/C][C]0.000206456984658154[/C][/ROW]
[ROW][C]335[/C][C]0.999809526982123[/C][C]0.000380946035753599[/C][C]0.0001904730178768[/C][/ROW]
[ROW][C]336[/C][C]0.9998410676816[/C][C]0.000317864636800057[/C][C]0.000158932318400029[/C][/ROW]
[ROW][C]337[/C][C]0.999832204386956[/C][C]0.000335591226088025[/C][C]0.000167795613044012[/C][/ROW]
[ROW][C]338[/C][C]0.99978053264614[/C][C]0.000438934707719283[/C][C]0.000219467353859642[/C][/ROW]
[ROW][C]339[/C][C]0.999677510148711[/C][C]0.000644979702578539[/C][C]0.000322489851289269[/C][/ROW]
[ROW][C]340[/C][C]0.999586671748346[/C][C]0.000826656503308048[/C][C]0.000413328251654024[/C][/ROW]
[ROW][C]341[/C][C]0.999337518572314[/C][C]0.00132496285537291[/C][C]0.000662481427686454[/C][/ROW]
[ROW][C]342[/C][C]0.99914734941191[/C][C]0.00170530117617916[/C][C]0.00085265058808958[/C][/ROW]
[ROW][C]343[/C][C]0.999008346044563[/C][C]0.00198330791087377[/C][C]0.000991653955436884[/C][/ROW]
[ROW][C]344[/C][C]0.998934381067307[/C][C]0.00213123786538648[/C][C]0.00106561893269324[/C][/ROW]
[ROW][C]345[/C][C]0.998738934610844[/C][C]0.00252213077831152[/C][C]0.00126106538915576[/C][/ROW]
[ROW][C]346[/C][C]0.99861564196511[/C][C]0.00276871606978077[/C][C]0.00138435803489039[/C][/ROW]
[ROW][C]347[/C][C]0.998690805771053[/C][C]0.00261838845789453[/C][C]0.00130919422894727[/C][/ROW]
[ROW][C]348[/C][C]0.99899466877656[/C][C]0.00201066244687951[/C][C]0.00100533122343975[/C][/ROW]
[ROW][C]349[/C][C]0.998640272711941[/C][C]0.00271945457611795[/C][C]0.00135972728805898[/C][/ROW]
[ROW][C]350[/C][C]0.99901972406344[/C][C]0.00196055187312017[/C][C]0.000980275936560085[/C][/ROW]
[ROW][C]351[/C][C]0.998910968268753[/C][C]0.0021780634624943[/C][C]0.00108903173124715[/C][/ROW]
[ROW][C]352[/C][C]0.99834417709609[/C][C]0.00331164580781922[/C][C]0.00165582290390961[/C][/ROW]
[ROW][C]353[/C][C]0.996720460072061[/C][C]0.00655907985587744[/C][C]0.00327953992793872[/C][/ROW]
[ROW][C]354[/C][C]0.996972334107921[/C][C]0.00605533178415842[/C][C]0.00302766589207921[/C][/ROW]
[ROW][C]355[/C][C]0.992091394307325[/C][C]0.0158172113853507[/C][C]0.00790860569267536[/C][/ROW]
[ROW][C]356[/C][C]0.986909239088004[/C][C]0.0261815218239915[/C][C]0.0130907609119957[/C][/ROW]
[ROW][C]357[/C][C]0.969451096401[/C][C]0.0610978071980003[/C][C]0.0305489035990001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147635&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147635&T=5

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
150.03936652503036190.07873305006072380.960633474969638
160.02239020817400230.04478041634800470.977609791825998
170.03206729659407790.06413459318815590.967932703405922
180.03662302487162770.07324604974325550.963376975128372
190.05572175564953380.1114435112990680.944278244350466
200.05771933656618910.1154386731323780.942280663433811
210.05272827433555470.1054565486711090.947271725664445
220.06412046176575710.1282409235315140.935879538234243
230.05611936069924120.1122387213984820.943880639300759
240.04792170121618750.0958434024323750.952078298783812
250.06261404152546330.1252280830509270.937385958474537
260.06390555412091030.1278111082418210.93609444587909
270.05479928429074540.1095985685814910.945200715709255
280.0397231422527350.079446284505470.960276857747265
290.02638933002211880.05277866004423760.973610669977881
300.01689379128314470.03378758256628930.983106208716855
310.0103152631412450.020630526282490.989684736858755
320.006534442465057220.01306888493011440.993465557534943
330.003972396905296640.007944793810593270.996027603094703
340.002638168582222270.005276337164444550.997361831417778
350.001600649007140980.003201298014281950.998399350992859
360.0009830918331852730.001966183666370550.999016908166815
370.0006499017133201810.001299803426640360.99935009828668
380.0005731870333244350.001146374066648870.999426812966676
390.0004957546923006590.0009915093846013190.999504245307699
400.0004463207295141410.0008926414590282820.999553679270486
410.0003963548789853210.0007927097579706410.999603645121015
420.0003644178379453380.0007288356758906750.999635582162055
430.0003630771827082870.0007261543654165730.999636922817292
440.0003199213452916380.0006398426905832760.999680078654708
450.00023624046390510.0004724809278101990.999763759536095
460.000168866943313430.0003377338866268610.999831133056687
470.0001148027589159720.0002296055178319450.999885197241084
489.23437044384587e-050.0001846874088769170.999907656295562
497.39529022262269e-050.0001479058044524540.999926047097774
506.58853106233205e-050.0001317706212466410.999934114689377
516.39748433494816e-050.0001279496866989630.99993602515665
525.4053447239423e-050.0001081068944788460.999945946552761
534.19875102345845e-058.39750204691689e-050.999958012489765
543.68606975992089e-057.37213951984177e-050.999963139302401
553.11614139922284e-056.23228279844567e-050.999968838586008
562.30773344871356e-054.61546689742711e-050.999976922665513
571.76166627624149e-053.52333255248298e-050.999982383337238
581.41018173721189e-052.82036347442378e-050.999985898182628
591.1711964437022e-052.34239288740439e-050.999988288035563
601.03887421695051e-052.07774843390102e-050.99998961125783
618.74291856913948e-061.7485837138279e-050.999991257081431
629.96889748441653e-061.99377949688331e-050.999990031102516
631.02622630574208e-052.05245261148416e-050.999989737736943
648.6759019422475e-061.7351803884495e-050.999991324098058
657.704891003685e-061.540978200737e-050.999992295108996
668.27676829543204e-061.65535365908641e-050.999991723231705
678.98086841534638e-061.79617368306928e-050.999991019131585
688.69862507641854e-061.73972501528371e-050.999991301374924
697.08338595112202e-061.4166771902244e-050.999992916614049
705.36081303894685e-061.07216260778937e-050.999994639186961
713.62651323645373e-067.25302647290745e-060.999996373486764
722.29583160806133e-064.59166321612266e-060.999997704168392
731.66685978338069e-063.33371956676138e-060.999998333140217
741.40070824286479e-062.80141648572958e-060.999998599291757
751.46501117036576e-062.93002234073151e-060.99999853498883
761.6208008167148e-063.2416016334296e-060.999998379199183
771.74355322122792e-063.48710644245585e-060.999998256446779
781.52809493347263e-063.05618986694526e-060.999998471905067
791.28936054878595e-062.57872109757191e-060.999998710639451
801.17087449025716e-062.34174898051431e-060.99999882912551
811.10841929304302e-062.21683858608604e-060.999998891580707
828.55720698999593e-071.71144139799919e-060.999999144279301
836.58905052165118e-071.31781010433024e-060.999999341094948
844.67405193374397e-079.34810386748794e-070.999999532594807
853.40980215752385e-076.8196043150477e-070.999999659019784
862.25245215458828e-074.50490430917656e-070.999999774754785
871.45757259063212e-072.91514518126423e-070.999999854242741
889.49044728155475e-081.89808945631095e-070.999999905095527
895.86413717159294e-081.17282743431859e-070.999999941358628
903.89765172611583e-087.79530345223165e-080.999999961023483
912.56816670685541e-085.13633341371082e-080.999999974318333
921.62972473964117e-083.25944947928234e-080.999999983702753
931.03330302727504e-082.06660605455008e-080.99999998966697
946.46583295911455e-091.29316659182291e-080.999999993534167
954.04323668967714e-098.08647337935427e-090.999999995956763
962.50877093170103e-095.01754186340207e-090.999999997491229
971.58844949833786e-093.17689899667572e-090.999999998411551
981.01645321406304e-092.03290642812609e-090.999999998983547
996.26129641113498e-101.252259282227e-090.99999999937387
1003.79181069126984e-107.58362138253968e-100.999999999620819
1012.26751668106203e-104.53503336212406e-100.999999999773248
1021.50776341731646e-103.01552683463291e-100.999999999849224
1039.37034412591121e-111.87406882518224e-100.999999999906297
1045.93180547387998e-111.186361094776e-100.999999999940682
1053.77742692518733e-117.55485385037466e-110.999999999962226
1062.42144158327187e-114.84288316654375e-110.999999999975786
1071.48680257248412e-112.97360514496824e-110.999999999985132
1089.05500511054761e-121.81100102210952e-110.999999999990945
1095.63125931115526e-121.12625186223105e-110.999999999994369
1103.62050404584048e-127.24100809168096e-120.999999999996379
1112.36678534411197e-124.73357068822394e-120.999999999997633
1121.45096957804e-122.90193915608e-120.999999999998549
1138.46853312786835e-131.69370662557367e-120.999999999999153
1145.61391609857746e-131.12278321971549e-120.999999999999439
1153.54869035102248e-137.09738070204495e-130.999999999999645
1162.24634794081214e-134.49269588162428e-130.999999999999775
1171.37504426979885e-132.75008853959769e-130.999999999999862
1188.50851080200036e-141.70170216040007e-130.999999999999915
1196.08544872515071e-141.21708974503014e-130.999999999999939
1204.82313418259092e-149.64626836518183e-140.999999999999952
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1222.67843689299419e-135.35687378598838e-130.999999999999732
1231.39762087566206e-122.79524175132412e-120.999999999998602
1248.79131348946805e-121.75826269789361e-110.999999999991209
1254.03754001776561e-118.07508003553123e-110.999999999959625
1261.81210202327339e-103.62420404654677e-100.99999999981879
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1292.20747958156887e-094.41495916313775e-090.99999999779252
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1371.55348113322368e-093.10696226644737e-090.999999998446519
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1398.50570934522887e-101.70114186904577e-090.999999999149429
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1414.4721115033108e-108.94422300662161e-100.999999999552789
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1432.89744181131039e-105.79488362262078e-100.999999999710256
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1451.64159228008155e-103.2831845601631e-100.999999999835841
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1503.34290566902406e-116.68581133804813e-110.999999999966571
1512.51360873006647e-115.02721746013294e-110.999999999974864
1522.01175427995373e-114.02350855990746e-110.999999999979882
1531.45702157927305e-112.91404315854611e-110.99999999998543
1541.25584522408521e-112.51169044817041e-110.999999999987442
1551.19288964670124e-112.38577929340247e-110.999999999988071
1561.6456675958123e-113.29133519162459e-110.999999999983543
1572.9876618336051e-115.97532366721021e-110.999999999970123
1586.71038631460685e-111.34207726292137e-100.999999999932896
1591.32032012881635e-102.6406402576327e-100.999999999867968
1601.96063337017922e-103.92126674035844e-100.999999999803937
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1624.86773398896795e-109.7354679779359e-100.999999999513227
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1647.34540250902404e-101.46908050180481e-090.99999999926546
1656.98771566174517e-101.39754313234903e-090.999999999301228
1666.51113181948235e-101.30222636389647e-090.999999999348887
1675.42576526599469e-101.08515305319894e-090.999999999457423
1684.47209350572969e-108.94418701145938e-100.999999999552791
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1702.671625798233e-105.343251596466e-100.999999999732837
1711.93288646447437e-103.86577292894873e-100.999999999806711
1721.32721080845178e-102.65442161690356e-100.999999999867279
1739.8905151680526e-111.97810303361052e-100.999999999901095
1747.50917420002014e-111.50183484000403e-100.999999999924908
1755.23625154102927e-111.04725030820585e-100.999999999947637
1763.91727218809132e-117.83454437618264e-110.999999999960827
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1809.92968934057614e-121.98593786811523e-110.99999999999007
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1826.26641061485436e-121.25328212297087e-110.999999999993734
1834.50114105474595e-129.00228210949191e-120.999999999995499
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1888.87761469238177e-131.77552293847635e-120.999999999999112
1896.1585388064782e-131.23170776129564e-120.999999999999384
1904.31167048855417e-138.62334097710835e-130.999999999999569
1913.11850620029016e-136.23701240058032e-130.999999999999688
1922.10246077023056e-134.20492154046112e-130.99999999999979
1931.47506133582802e-132.95012267165604e-130.999999999999852
1949.77047215433379e-141.95409443086676e-130.999999999999902
1956.29047627748877e-141.25809525549775e-130.999999999999937
1963.93699929876923e-147.87399859753845e-140.999999999999961
1972.37450579060562e-144.74901158121124e-140.999999999999976
1981.77076864622104e-143.54153729244208e-140.999999999999982
1991.17918340400114e-142.35836680800228e-140.999999999999988
2007.78022599124275e-151.55604519824855e-140.999999999999992
2015.20644656982544e-151.04128931396509e-140.999999999999995
2023.4582773338732e-156.91655466774641e-150.999999999999997
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2082.05216249396173e-164.10432498792346e-161
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2142.22640820354439e-174.45281640708879e-171
2151.6271105559428e-173.2542211118856e-171
2161.24405761149603e-172.48811522299207e-171
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2295.91251074596058e-181.18250214919212e-171
2307.33813193160511e-181.46762638632102e-171
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2329.79552638977121e-181.95910527795424e-171
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2494.59868458318406e-169.19736916636812e-161
2507.2270097713225e-161.4454019542645e-150.999999999999999
2511.31161606385028e-152.62323212770057e-150.999999999999999
2522.88927618516539e-155.77855237033077e-150.999999999999997
2531.07495144281679e-142.14990288563359e-140.999999999999989
2544.41940123055673e-148.83880246111347e-140.999999999999956
2551.6548512375222e-133.30970247504439e-130.999999999999834
2564.24651709355111e-138.49303418710222e-130.999999999999575
2571.07294321001281e-122.14588642002562e-120.999999999998927
2582.55932760503307e-125.11865521006614e-120.999999999997441
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2601.54540538104084e-113.09081076208168e-110.999999999984546
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2713.89046319455933e-087.78092638911865e-080.999999961095368
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2944.99109219677291e-069.98218439354582e-060.999995008907803
2956.13882047740952e-061.2277640954819e-050.999993861179523
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3001.89511460953642e-053.79022921907285e-050.999981048853905
3014.36314144738007e-058.72628289476015e-050.999956368585526
3029.10238175689402e-050.000182047635137880.999908976182431
3030.0001864718389522240.0003729436779044480.999813528161048
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3120.03632046334105460.07264092668210920.963679536658945
3130.08438177519105350.1687635503821070.915618224808947
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3160.4638632892519360.9277265785038720.536136710748064
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3190.830889127671420.338221744657160.16911087232858
3200.9092479284413580.1815041431172840.0907520715586419
3210.937337300554220.1253253988915590.0626626994457795
3220.9554405893226410.08911882135471710.0445594106773586
3230.9594504522290890.0810990955418220.040549547770911
3240.9574531385160140.08509372296797150.0425468614839857
3250.9658880725420080.06822385491598310.0341119274579915
3260.9731260514317130.05374789713657490.0268739485682874
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3280.9920877227302220.01582455453955520.00791227726977758
3290.9971081831433180.00578363371336480.0028918168566824
3300.9987835705747670.002432858850466480.00121642942523324
3310.9993492783013270.001301443397345610.000650721698672805
3320.9995449701419150.0009100597161703510.000455029858085175
3330.9997033695613340.0005932608773316150.000296630438665808
3340.9997935430153420.0004129139693163090.000206456984658154
3350.9998095269821230.0003809460357535990.0001904730178768
3360.99984106768160.0003178646368000570.000158932318400029
3370.9998322043869560.0003355912260880250.000167795613044012
3380.999780532646140.0004389347077192830.000219467353859642
3390.9996775101487110.0006449797025785390.000322489851289269
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3410.9993375185723140.001324962855372910.000662481427686454
3420.999147349411910.001705301176179160.00085265058808958
3430.9990083460445630.001983307910873770.000991653955436884
3440.9989343810673070.002131237865386480.00106561893269324
3450.9987389346108440.002522130778311520.00126106538915576
3460.998615641965110.002768716069780770.00138435803489039
3470.9986908057710530.002618388457894530.00130919422894727
3480.998994668776560.002010662446879510.00100533122343975
3490.9986402727119410.002719454576117950.00135972728805898
3500.999019724063440.001960551873120170.000980275936560085
3510.9989109682687530.00217806346249430.00108903173124715
3520.998344177096090.003311645807819220.00165582290390961
3530.9967204600720610.006559079855877440.00327953992793872
3540.9969723341079210.006055331784158420.00302766589207921
3550.9920913943073250.01581721138535070.00790860569267536
3560.9869092390880040.02618152182399150.0130907609119957
3570.9694510964010.06109780719800030.0305489035990001







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level3020.880466472303207NOK
5% type I error level3130.912536443148688NOK
10% type I error level3260.950437317784257NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 302 & 0.880466472303207 & NOK \tabularnewline
5% type I error level & 313 & 0.912536443148688 & NOK \tabularnewline
10% type I error level & 326 & 0.950437317784257 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147635&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]302[/C][C]0.880466472303207[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]313[/C][C]0.912536443148688[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]326[/C][C]0.950437317784257[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147635&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147635&T=6

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level3020.880466472303207NOK
5% type I error level3130.912536443148688NOK
10% type I error level3260.950437317784257NOK



Parameters (Session):
par1 = 1 ; par2 = Include Monthly Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Include Monthly Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}