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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 14 Dec 2014 21:04:24 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/14/t1418591340m2gnj2jntt1vz0i.htm/, Retrieved Sun, 12 May 2024 22:08:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267881, Retrieved Sun, 12 May 2024 22:08:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Monthly US soldie...] [2010-11-02 12:07:39] [b98453cac15ba1066b407e146608df68]
- RMP   [Classical Decomposition] [Soldiers] [2010-11-30 14:03:31] [b98453cac15ba1066b407e146608df68]
- RM      [Classical Decomposition] [WS8 CD] [2014-11-19 16:56:27] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD        [Multiple Regression] [P MR motcon] [2014-12-14 21:04:24] [9772ee27deeac3d50cc1fb84835cd7d6] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
26 50 4 12
57 62 4 8
37 54 5 11
67 71 4 13
43 54 4 11
52 65 9 10
52 73 8 7
43 52 11 10
84 84 4 15
67 42 4 12
49 66 6 12
70 65 4 10
52 78 8 10
58 73 4 14
68 75 4 6
62 72 11 12
43 66 4 14
56 70 4 11
56 61 6 8
74 81 6 12
65 71 4 15
63 69 8 13
58 71 5 11
57 72 4 12
63 68 9 7
53 70 4 11
57 68 7 7
51 61 10 12
64 67 4 12
53 76 4 13
29 70 7 9
54 60 12 11
58 72 7 12
43 69 5 15
51 71 8 12
53 62 5 6
54 70 4 5
56 64 9 13
61 58 7 11
47 76 4 6
39 52 4 12
48 59 4 10
50 68 4 6
35 76 4 12
30 65 7 11
68 67 4 6
49 59 7 12
61 69 4 12
67 76 4 8
47 63 4 10
56 75 4 11
50 63 8 7
43 60 4 12
67 73 4 13
62 63 4 14
57 70 4 12
41 75 7 6
54 66 12 14
45 63 4 10
48 63 4 12
61 64 4 11
56 70 5 10
41 75 15 7
43 61 5 12
53 60 10 7
44 62 9 12
66 73 8 12
58 61 4 10
46 66 5 10
37 64 4 12
51 59 9 12
51 64 4 12
56 60 10 8
66 56 4 10
37 78 4 5
59 53 6 10
42 67 7 10
38 59 5 12
66 66 4 11
34 68 4 9
53 71 4 12
49 66 4 11
55 73 4 10
49 72 4 12
59 71 6 10
40 59 10 9
58 64 7 11
60 66 4 12
63 78 4 7
56 68 7 11
54 73 4 12
52 62 8 6
34 65 11 9
69 68 6 15
32 65 14 10
48 60 5 11
67 71 4 12
58 65 8 12
57 68 9 12
42 64 4 11
64 74 4 9
58 69 5 11
66 76 4 12
26 68 5 12
61 72 4 14
52 67 4 8
51 63 7 10
55 59 10 9
50 73 4 10
60 66 5 9
56 62 4 10
63 69 4 12
61 66 4 11
52 51 6 9
16 56 4 11
46 67 8 12
56 69 5 12
52 57 4 7
55 56 17 12
50 55 4 12
59 63 4 12
60 67 8 10
52 65 4 15
44 47 7 10
67 76 4 15
52 64 4 10
55 68 5 15
37 64 7 9
54 65 4 15
72 71 4 12
51 63 7 13
48 60 11 12
60 68 7 12
50 72 4 8
63 70 4 9
33 61 4 15
67 61 4 12
46 62 4 12
54 71 4 15
59 71 6 11
61 51 8 12
33 56 23 6
47 70 4 14
69 73 8 12
52 76 6 12
55 68 4 12
41 48 7 11
73 52 4 12
52 60 4 12
50 59 4 12
51 57 10 12
60 79 6 8
56 60 5 8
56 60 5 12
29 59 4 12
66 62 4 11
66 59 5 10
73 61 5 11
55 71 5 12
64 57 5 13
40 66 4 12
46 63 6 12
58 69 4 10
43 58 4 10
61 59 4 11
51 48 9 8
50 66 18 12
52 73 6 9
54 67 5 12
66 61 4 9
61 68 11 11
80 75 4 15
51 62 10 8
56 69 6 8
56 58 8 11
56 60 8 11
53 74 6 11
47 55 8 13
25 62 4 7
47 63 4 12
46 69 9 8
50 58 9 8
39 58 5 4
51 68 4 11
58 72 4 10
35 62 15 7
58 62 10 12
60 65 9 11
62 69 7 9
63 66 9 10
53 72 6 8
46 62 4 8
67 75 7 11
59 58 4 12
64 66 7 10
38 55 4 10
50 47 15 12
48 72 4 8
48 62 9 11
47 64 4 8
66 64 4 10
47 19 28 14
63 50 4 9
58 68 4 9
44 70 4 10
51 79 5 13
43 69 4 12
55 71 4 13
38 48 12 8
45 73 4 3
50 74 6 8
54 66 6 12
57 71 5 11
60 74 4 9
55 78 4 12
56 75 4 12
49 53 10 12
37 60 7 10
59 70 4 13
46 69 7 9
51 65 4 12
58 78 4 11
64 78 12 14
53 59 5 11
48 72 8 9
51 70 6 12
47 63 17 8
59 63 4 15
62 71 5 12
62 74 4 14
51 67 5 12
64 66 5 9
52 62 6 9
67 80 4 13
50 73 4 13
54 67 4 15
58 61 6 11
56 73 8 7
63 74 10 10
31 32 4 11
65 69 5 14
71 69 4 14
50 84 4 13
57 64 4 12
47 58 16 8
47 59 7 13
57 78 4 9
43 57 4 12
41 60 14 13
63 68 5 11
63 68 5 11
56 73 5 13
51 69 5 12
50 67 7 12
22 60 19 10
41 65 16 9
59 66 4 10
56 74 4 13
66 81 7 13
53 72 9 9
42 55 5 11
52 49 14 12
54 74 4 8
44 53 16 12
62 64 10 12
53 65 5 12
50 57 6 9
36 51 4 12
76 80 4 12
66 67 4 11
62 70 5 12
59 74 4 6
47 75 4 7
55 70 5 10
58 69 4 12
60 65 4 10
44 55 5 12
57 71 8 9
45 65 15 3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 8 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267881&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267881&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267881&T=0

As an alternative you can also use a QR Code:  
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 time8 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
CONFSOFTTOT[t] = + 10.8719 + 0.0456043AMS.I[t] -0.0313425AMS.E[t] -0.0806869AMS.A[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
CONFSOFTTOT[t] =  +  10.8719 +  0.0456043AMS.I[t] -0.0313425AMS.E[t] -0.0806869AMS.A[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267881&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]CONFSOFTTOT[t] =  +  10.8719 +  0.0456043AMS.I[t] -0.0313425AMS.E[t] -0.0806869AMS.A[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267881&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267881&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Estimated Regression Equation
CONFSOFTTOT[t] = + 10.8719 + 0.0456043AMS.I[t] -0.0313425AMS.E[t] -0.0806869AMS.A[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)10.87191.322018.2247.90127e-153.95063e-15
AMS.I0.04560430.01396673.2650.001232350.000616177
AMS.E-0.03134250.0181302-1.7290.08497760.0424888
AMS.A-0.08068690.0412341-1.9570.05138250.0256913

\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) & 10.8719 & 1.32201 & 8.224 & 7.90127e-15 & 3.95063e-15 \tabularnewline
AMS.I & 0.0456043 & 0.0139667 & 3.265 & 0.00123235 & 0.000616177 \tabularnewline
AMS.E & -0.0313425 & 0.0181302 & -1.729 & 0.0849776 & 0.0424888 \tabularnewline
AMS.A & -0.0806869 & 0.0412341 & -1.957 & 0.0513825 & 0.0256913 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267881&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]10.8719[/C][C]1.32201[/C][C]8.224[/C][C]7.90127e-15[/C][C]3.95063e-15[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.0456043[/C][C]0.0139667[/C][C]3.265[/C][C]0.00123235[/C][C]0.000616177[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0313425[/C][C]0.0181302[/C][C]-1.729[/C][C]0.0849776[/C][C]0.0424888[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0806869[/C][C]0.0412341[/C][C]-1.957[/C][C]0.0513825[/C][C]0.0256913[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267881&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267881&T=2

As an alternative you can also use a QR Code:  
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)10.87191.322018.2247.90127e-153.95063e-15
AMS.I0.04560430.01396673.2650.001232350.000616177
AMS.E-0.03134250.0181302-1.7290.08497760.0424888
AMS.A-0.08068690.0412341-1.9570.05138250.0256913






Multiple Linear Regression - Regression Statistics
Multiple R0.237614
R-squared0.0564605
Adjusted R-squared0.0461674
F-TEST (value)5.48525
F-TEST (DF numerator)3
F-TEST (DF denominator)275
p-value0.00112807
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.2304
Sum Squared Residuals1368.04

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.237614 \tabularnewline
R-squared & 0.0564605 \tabularnewline
Adjusted R-squared & 0.0461674 \tabularnewline
F-TEST (value) & 5.48525 \tabularnewline
F-TEST (DF numerator) & 3 \tabularnewline
F-TEST (DF denominator) & 275 \tabularnewline
p-value & 0.00112807 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.2304 \tabularnewline
Sum Squared Residuals & 1368.04 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267881&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.237614[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0564605[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0461674[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]5.48525[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]3[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]275[/C][/ROW]
[ROW][C]p-value[/C][C]0.00112807[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.2304[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1368.04[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267881&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267881&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Regression Statistics
Multiple R0.237614
R-squared0.0564605
Adjusted R-squared0.0461674
F-TEST (value)5.48525
F-TEST (DF numerator)3
F-TEST (DF denominator)275
p-value0.00112807
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.2304
Sum Squared Residuals1368.04






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11210.16771.83225
2811.2054-3.20537
31110.46330.536659
41311.37931.62066
51110.81770.182346
61010.4799-0.479891
7710.3098-3.30984
81010.3155-0.31553
91511.74723.25284
101212.2883-0.288268
111210.55381.4462
121011.7042-1.7042
131010.1531-0.153125
141410.90623.09379
15611.2996-5.29957
161210.55521.44484
171410.44153.55846
181110.9090.09097
19811.0297-3.02974
201211.22380.776233
211511.28813.71187
221310.93692.06314
231110.88820.111791
241210.89191.10805
25710.8875-3.88751
261110.77220.227783
27710.7753-3.77526
281210.4791.52103
291211.36790.632108
301310.58422.41584
3199.43565-0.435652
321110.48580.514249
331210.69551.30451
341510.26684.73317
351210.32691.67308
36610.9423-4.94227
37510.8178-5.81782
381310.69372.30635
391111.2711-0.271101
40610.3105-4.31054
411210.69791.30208
421010.889-0.888963
43610.6981-4.69809
44129.763282.23672
45119.637971.36203
46611.5503-5.55031
471210.69251.30749
481211.16840.831606
49811.2226-3.22262
501010.718-0.717988
511110.75230.247682
52710.5321-3.53205
531210.62961.3704
541311.31671.68335
551411.40212.59795
561210.95461.04537
5769.82619-3.82619
581410.29773.7023
591010.6268-0.62678
601210.76361.23641
611111.3251-0.325107
621010.8283-0.828343
6379.1807-2.1807
641210.51761.48243
65710.6015-3.60152
661210.20911.79092
671210.94831.0517
681011.2823-1.28232
691010.4977-0.49767
701210.23061.7694
711210.62231.37766
721210.86911.13094
73810.7383-2.73833
741011.8039-1.80387
7559.79181-4.79181
761011.4173-1.41729
771010.1225-0.122536
781210.35221.64777
791111.4904-0.490443
8099.96842-0.96842
811210.74091.25913
821110.71520.28483
831010.7694-0.769398
841210.52711.47289
851010.8531-0.853127
86910.04-1.04001
871110.94620.053767
881211.21680.783183
89710.9775-3.97752
901110.72970.270346
911210.72381.27621
92610.6546-4.65461
9399.49764-0.497639
941511.40323.5968
95109.164370.835631
961110.77690.223067
971211.37930.620665
981210.83421.1658
991210.61391.38612
1001110.45860.541376
101911.1485-2.14849
1021110.95090.0491057
1031211.1770.822982
104129.52292.4771
1051411.07442.92563
106810.8206-2.82064
1071010.6583-0.658345
108910.7241-1.72407
1091010.5414-0.541376
110911.1361-2.13613
1111011.1598-1.15977
1121211.25960.740397
1131111.2624-0.262422
114911.1607-2.16075
115119.523651.47635
1161210.22431.77573
1171210.85971.14031
118711.1341-4.13407
1191210.25331.74671
1201211.10550.894459
1211211.26520.734759
1221010.8627-0.862727
1231510.88334.11667
1241010.8406-0.840595
1251511.22263.77738
1261010.9147-0.914668
1271510.84544.15458
12899.98854-0.988542
1291510.97454.02547
1301211.60740.392643
1311310.65832.34165
1321210.29281.70719
1331210.91211.08793
134810.5727-2.57272
135911.2283-2.22826
1361510.14224.85779
1371211.69280.30724
1381210.70371.29627
1391510.78654.21352
1401110.85310.146873
1411211.40980.590188
14268.76587-2.76587
1431410.49863.50141
1441211.08510.914889
1451210.37721.62282
1461210.92611.07389
1471110.67240.327561
1481212.2485-0.248469
1491211.040.959962
1501210.98021.01983
1511210.60431.39566
152810.648-2.64799
153811.1418-3.14177
1541211.14180.858232
1551210.02251.97752
1561111.6158-0.615813
1571011.6292-1.62915
1581111.8857-0.885699
1591210.75141.2486
1601311.60061.39937
1611210.30471.69527
1621210.5111.48899
1631011.0316-1.03158
1641010.6923-0.692284
1651111.4818-0.481819
166810.9671-2.96711
167129.631162.36884
168910.4712-1.47121
1691210.83121.16884
170911.6472-2.64716
1711110.63490.365072
1721511.84683.15318
173810.4476-2.44763
174810.779-2.779
1751110.96240.0376076
1761110.89970.100293
1771110.48550.514527
1781310.6462.35402
17979.74604-2.74604
1801210.7181.28201
181810.0809-2.08089
182810.6081-2.60808
183410.4292-6.42918
1841110.74370.256307
1851010.9376-0.937554
18679.31452-2.31452
1871210.76691.23314
1881110.84470.155275
189910.9719-1.97194
1901010.9502-0.950196
191810.5482-2.54816
192810.7037-2.70373
1931111.0119-0.0119046
1941211.4220.578047
1951011.1572-1.15717
1961010.5583-0.558289
1971210.46871.53127
198810.4815-2.48151
1991110.39150.608499
200810.6866-2.68665
2011011.5531-1.55313
2021410.16063.83943
203911.8551-2.85511
204911.0629-2.06292
2051010.3618-0.361778
2061310.31822.68176
2071210.34751.65248
2081310.83212.16792
209810.1322-2.13219
210310.3134-7.31335
211810.3487-2.34866
2121210.78181.21818
2131110.84260.157395
214910.9661-1.96608
2151210.61271.38731
2161210.75231.24768
2171210.63851.3615
2181010.1139-0.113912
2191311.04581.95416
220910.2423-1.24227
2211210.83771.16228
2221110.74950.250501
2231410.37763.62237
2241111.0363-0.0362975
225910.1588-1.15876
2261210.51961.48037
22789.66906-1.66906
2281511.26523.73476
2291211.07060.929373
2301411.05732.94271
2311210.69431.30565
232911.3185-2.31855
233910.816-1.81598
2341311.09731.90275
2351310.54142.45862
2361510.91184.08815
2371111.1209-0.120947
238710.4923-3.49225
2391010.6188-0.618769
2401110.95990.0400636
2411411.27012.72988
2421411.62442.37556
2431310.19662.80339
2441211.14270.857311
24589.90646-1.90646
2461310.60132.3987
247910.7039-1.70389
2481210.72361.27637
249139.731523.26848
2501111.2103-0.210258
2511111.2103-0.210258
2521310.73432.26568
2531210.63171.36834
2541210.48741.51263
255108.46161.5384
25699.41343-0.413435
2571011.1712-1.17121
2581310.78372.21634
2591310.77822.22175
260910.3061-1.3061
2611110.660.33998
2621210.57791.42206
263810.6925-2.69245
264129.926362.07364
2651210.88661.11341
2661210.84821.15176
267910.8815-1.88148
2681210.59251.40755
2691211.50770.492308
2701111.4591-0.459101
2711211.1020.898031
272610.9205-4.92047
273710.3419-3.34188
2741010.7827-0.782739
2751211.03160.968419
2761011.2482-1.24816
2771210.75121.24877
278910.6005-1.60054
27939.67654-6.67654

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 10.1677 & 1.83225 \tabularnewline
2 & 8 & 11.2054 & -3.20537 \tabularnewline
3 & 11 & 10.4633 & 0.536659 \tabularnewline
4 & 13 & 11.3793 & 1.62066 \tabularnewline
5 & 11 & 10.8177 & 0.182346 \tabularnewline
6 & 10 & 10.4799 & -0.479891 \tabularnewline
7 & 7 & 10.3098 & -3.30984 \tabularnewline
8 & 10 & 10.3155 & -0.31553 \tabularnewline
9 & 15 & 11.7472 & 3.25284 \tabularnewline
10 & 12 & 12.2883 & -0.288268 \tabularnewline
11 & 12 & 10.5538 & 1.4462 \tabularnewline
12 & 10 & 11.7042 & -1.7042 \tabularnewline
13 & 10 & 10.1531 & -0.153125 \tabularnewline
14 & 14 & 10.9062 & 3.09379 \tabularnewline
15 & 6 & 11.2996 & -5.29957 \tabularnewline
16 & 12 & 10.5552 & 1.44484 \tabularnewline
17 & 14 & 10.4415 & 3.55846 \tabularnewline
18 & 11 & 10.909 & 0.09097 \tabularnewline
19 & 8 & 11.0297 & -3.02974 \tabularnewline
20 & 12 & 11.2238 & 0.776233 \tabularnewline
21 & 15 & 11.2881 & 3.71187 \tabularnewline
22 & 13 & 10.9369 & 2.06314 \tabularnewline
23 & 11 & 10.8882 & 0.111791 \tabularnewline
24 & 12 & 10.8919 & 1.10805 \tabularnewline
25 & 7 & 10.8875 & -3.88751 \tabularnewline
26 & 11 & 10.7722 & 0.227783 \tabularnewline
27 & 7 & 10.7753 & -3.77526 \tabularnewline
28 & 12 & 10.479 & 1.52103 \tabularnewline
29 & 12 & 11.3679 & 0.632108 \tabularnewline
30 & 13 & 10.5842 & 2.41584 \tabularnewline
31 & 9 & 9.43565 & -0.435652 \tabularnewline
32 & 11 & 10.4858 & 0.514249 \tabularnewline
33 & 12 & 10.6955 & 1.30451 \tabularnewline
34 & 15 & 10.2668 & 4.73317 \tabularnewline
35 & 12 & 10.3269 & 1.67308 \tabularnewline
36 & 6 & 10.9423 & -4.94227 \tabularnewline
37 & 5 & 10.8178 & -5.81782 \tabularnewline
38 & 13 & 10.6937 & 2.30635 \tabularnewline
39 & 11 & 11.2711 & -0.271101 \tabularnewline
40 & 6 & 10.3105 & -4.31054 \tabularnewline
41 & 12 & 10.6979 & 1.30208 \tabularnewline
42 & 10 & 10.889 & -0.888963 \tabularnewline
43 & 6 & 10.6981 & -4.69809 \tabularnewline
44 & 12 & 9.76328 & 2.23672 \tabularnewline
45 & 11 & 9.63797 & 1.36203 \tabularnewline
46 & 6 & 11.5503 & -5.55031 \tabularnewline
47 & 12 & 10.6925 & 1.30749 \tabularnewline
48 & 12 & 11.1684 & 0.831606 \tabularnewline
49 & 8 & 11.2226 & -3.22262 \tabularnewline
50 & 10 & 10.718 & -0.717988 \tabularnewline
51 & 11 & 10.7523 & 0.247682 \tabularnewline
52 & 7 & 10.5321 & -3.53205 \tabularnewline
53 & 12 & 10.6296 & 1.3704 \tabularnewline
54 & 13 & 11.3167 & 1.68335 \tabularnewline
55 & 14 & 11.4021 & 2.59795 \tabularnewline
56 & 12 & 10.9546 & 1.04537 \tabularnewline
57 & 6 & 9.82619 & -3.82619 \tabularnewline
58 & 14 & 10.2977 & 3.7023 \tabularnewline
59 & 10 & 10.6268 & -0.62678 \tabularnewline
60 & 12 & 10.7636 & 1.23641 \tabularnewline
61 & 11 & 11.3251 & -0.325107 \tabularnewline
62 & 10 & 10.8283 & -0.828343 \tabularnewline
63 & 7 & 9.1807 & -2.1807 \tabularnewline
64 & 12 & 10.5176 & 1.48243 \tabularnewline
65 & 7 & 10.6015 & -3.60152 \tabularnewline
66 & 12 & 10.2091 & 1.79092 \tabularnewline
67 & 12 & 10.9483 & 1.0517 \tabularnewline
68 & 10 & 11.2823 & -1.28232 \tabularnewline
69 & 10 & 10.4977 & -0.49767 \tabularnewline
70 & 12 & 10.2306 & 1.7694 \tabularnewline
71 & 12 & 10.6223 & 1.37766 \tabularnewline
72 & 12 & 10.8691 & 1.13094 \tabularnewline
73 & 8 & 10.7383 & -2.73833 \tabularnewline
74 & 10 & 11.8039 & -1.80387 \tabularnewline
75 & 5 & 9.79181 & -4.79181 \tabularnewline
76 & 10 & 11.4173 & -1.41729 \tabularnewline
77 & 10 & 10.1225 & -0.122536 \tabularnewline
78 & 12 & 10.3522 & 1.64777 \tabularnewline
79 & 11 & 11.4904 & -0.490443 \tabularnewline
80 & 9 & 9.96842 & -0.96842 \tabularnewline
81 & 12 & 10.7409 & 1.25913 \tabularnewline
82 & 11 & 10.7152 & 0.28483 \tabularnewline
83 & 10 & 10.7694 & -0.769398 \tabularnewline
84 & 12 & 10.5271 & 1.47289 \tabularnewline
85 & 10 & 10.8531 & -0.853127 \tabularnewline
86 & 9 & 10.04 & -1.04001 \tabularnewline
87 & 11 & 10.9462 & 0.053767 \tabularnewline
88 & 12 & 11.2168 & 0.783183 \tabularnewline
89 & 7 & 10.9775 & -3.97752 \tabularnewline
90 & 11 & 10.7297 & 0.270346 \tabularnewline
91 & 12 & 10.7238 & 1.27621 \tabularnewline
92 & 6 & 10.6546 & -4.65461 \tabularnewline
93 & 9 & 9.49764 & -0.497639 \tabularnewline
94 & 15 & 11.4032 & 3.5968 \tabularnewline
95 & 10 & 9.16437 & 0.835631 \tabularnewline
96 & 11 & 10.7769 & 0.223067 \tabularnewline
97 & 12 & 11.3793 & 0.620665 \tabularnewline
98 & 12 & 10.8342 & 1.1658 \tabularnewline
99 & 12 & 10.6139 & 1.38612 \tabularnewline
100 & 11 & 10.4586 & 0.541376 \tabularnewline
101 & 9 & 11.1485 & -2.14849 \tabularnewline
102 & 11 & 10.9509 & 0.0491057 \tabularnewline
103 & 12 & 11.177 & 0.822982 \tabularnewline
104 & 12 & 9.5229 & 2.4771 \tabularnewline
105 & 14 & 11.0744 & 2.92563 \tabularnewline
106 & 8 & 10.8206 & -2.82064 \tabularnewline
107 & 10 & 10.6583 & -0.658345 \tabularnewline
108 & 9 & 10.7241 & -1.72407 \tabularnewline
109 & 10 & 10.5414 & -0.541376 \tabularnewline
110 & 9 & 11.1361 & -2.13613 \tabularnewline
111 & 10 & 11.1598 & -1.15977 \tabularnewline
112 & 12 & 11.2596 & 0.740397 \tabularnewline
113 & 11 & 11.2624 & -0.262422 \tabularnewline
114 & 9 & 11.1607 & -2.16075 \tabularnewline
115 & 11 & 9.52365 & 1.47635 \tabularnewline
116 & 12 & 10.2243 & 1.77573 \tabularnewline
117 & 12 & 10.8597 & 1.14031 \tabularnewline
118 & 7 & 11.1341 & -4.13407 \tabularnewline
119 & 12 & 10.2533 & 1.74671 \tabularnewline
120 & 12 & 11.1055 & 0.894459 \tabularnewline
121 & 12 & 11.2652 & 0.734759 \tabularnewline
122 & 10 & 10.8627 & -0.862727 \tabularnewline
123 & 15 & 10.8833 & 4.11667 \tabularnewline
124 & 10 & 10.8406 & -0.840595 \tabularnewline
125 & 15 & 11.2226 & 3.77738 \tabularnewline
126 & 10 & 10.9147 & -0.914668 \tabularnewline
127 & 15 & 10.8454 & 4.15458 \tabularnewline
128 & 9 & 9.98854 & -0.988542 \tabularnewline
129 & 15 & 10.9745 & 4.02547 \tabularnewline
130 & 12 & 11.6074 & 0.392643 \tabularnewline
131 & 13 & 10.6583 & 2.34165 \tabularnewline
132 & 12 & 10.2928 & 1.70719 \tabularnewline
133 & 12 & 10.9121 & 1.08793 \tabularnewline
134 & 8 & 10.5727 & -2.57272 \tabularnewline
135 & 9 & 11.2283 & -2.22826 \tabularnewline
136 & 15 & 10.1422 & 4.85779 \tabularnewline
137 & 12 & 11.6928 & 0.30724 \tabularnewline
138 & 12 & 10.7037 & 1.29627 \tabularnewline
139 & 15 & 10.7865 & 4.21352 \tabularnewline
140 & 11 & 10.8531 & 0.146873 \tabularnewline
141 & 12 & 11.4098 & 0.590188 \tabularnewline
142 & 6 & 8.76587 & -2.76587 \tabularnewline
143 & 14 & 10.4986 & 3.50141 \tabularnewline
144 & 12 & 11.0851 & 0.914889 \tabularnewline
145 & 12 & 10.3772 & 1.62282 \tabularnewline
146 & 12 & 10.9261 & 1.07389 \tabularnewline
147 & 11 & 10.6724 & 0.327561 \tabularnewline
148 & 12 & 12.2485 & -0.248469 \tabularnewline
149 & 12 & 11.04 & 0.959962 \tabularnewline
150 & 12 & 10.9802 & 1.01983 \tabularnewline
151 & 12 & 10.6043 & 1.39566 \tabularnewline
152 & 8 & 10.648 & -2.64799 \tabularnewline
153 & 8 & 11.1418 & -3.14177 \tabularnewline
154 & 12 & 11.1418 & 0.858232 \tabularnewline
155 & 12 & 10.0225 & 1.97752 \tabularnewline
156 & 11 & 11.6158 & -0.615813 \tabularnewline
157 & 10 & 11.6292 & -1.62915 \tabularnewline
158 & 11 & 11.8857 & -0.885699 \tabularnewline
159 & 12 & 10.7514 & 1.2486 \tabularnewline
160 & 13 & 11.6006 & 1.39937 \tabularnewline
161 & 12 & 10.3047 & 1.69527 \tabularnewline
162 & 12 & 10.511 & 1.48899 \tabularnewline
163 & 10 & 11.0316 & -1.03158 \tabularnewline
164 & 10 & 10.6923 & -0.692284 \tabularnewline
165 & 11 & 11.4818 & -0.481819 \tabularnewline
166 & 8 & 10.9671 & -2.96711 \tabularnewline
167 & 12 & 9.63116 & 2.36884 \tabularnewline
168 & 9 & 10.4712 & -1.47121 \tabularnewline
169 & 12 & 10.8312 & 1.16884 \tabularnewline
170 & 9 & 11.6472 & -2.64716 \tabularnewline
171 & 11 & 10.6349 & 0.365072 \tabularnewline
172 & 15 & 11.8468 & 3.15318 \tabularnewline
173 & 8 & 10.4476 & -2.44763 \tabularnewline
174 & 8 & 10.779 & -2.779 \tabularnewline
175 & 11 & 10.9624 & 0.0376076 \tabularnewline
176 & 11 & 10.8997 & 0.100293 \tabularnewline
177 & 11 & 10.4855 & 0.514527 \tabularnewline
178 & 13 & 10.646 & 2.35402 \tabularnewline
179 & 7 & 9.74604 & -2.74604 \tabularnewline
180 & 12 & 10.718 & 1.28201 \tabularnewline
181 & 8 & 10.0809 & -2.08089 \tabularnewline
182 & 8 & 10.6081 & -2.60808 \tabularnewline
183 & 4 & 10.4292 & -6.42918 \tabularnewline
184 & 11 & 10.7437 & 0.256307 \tabularnewline
185 & 10 & 10.9376 & -0.937554 \tabularnewline
186 & 7 & 9.31452 & -2.31452 \tabularnewline
187 & 12 & 10.7669 & 1.23314 \tabularnewline
188 & 11 & 10.8447 & 0.155275 \tabularnewline
189 & 9 & 10.9719 & -1.97194 \tabularnewline
190 & 10 & 10.9502 & -0.950196 \tabularnewline
191 & 8 & 10.5482 & -2.54816 \tabularnewline
192 & 8 & 10.7037 & -2.70373 \tabularnewline
193 & 11 & 11.0119 & -0.0119046 \tabularnewline
194 & 12 & 11.422 & 0.578047 \tabularnewline
195 & 10 & 11.1572 & -1.15717 \tabularnewline
196 & 10 & 10.5583 & -0.558289 \tabularnewline
197 & 12 & 10.4687 & 1.53127 \tabularnewline
198 & 8 & 10.4815 & -2.48151 \tabularnewline
199 & 11 & 10.3915 & 0.608499 \tabularnewline
200 & 8 & 10.6866 & -2.68665 \tabularnewline
201 & 10 & 11.5531 & -1.55313 \tabularnewline
202 & 14 & 10.1606 & 3.83943 \tabularnewline
203 & 9 & 11.8551 & -2.85511 \tabularnewline
204 & 9 & 11.0629 & -2.06292 \tabularnewline
205 & 10 & 10.3618 & -0.361778 \tabularnewline
206 & 13 & 10.3182 & 2.68176 \tabularnewline
207 & 12 & 10.3475 & 1.65248 \tabularnewline
208 & 13 & 10.8321 & 2.16792 \tabularnewline
209 & 8 & 10.1322 & -2.13219 \tabularnewline
210 & 3 & 10.3134 & -7.31335 \tabularnewline
211 & 8 & 10.3487 & -2.34866 \tabularnewline
212 & 12 & 10.7818 & 1.21818 \tabularnewline
213 & 11 & 10.8426 & 0.157395 \tabularnewline
214 & 9 & 10.9661 & -1.96608 \tabularnewline
215 & 12 & 10.6127 & 1.38731 \tabularnewline
216 & 12 & 10.7523 & 1.24768 \tabularnewline
217 & 12 & 10.6385 & 1.3615 \tabularnewline
218 & 10 & 10.1139 & -0.113912 \tabularnewline
219 & 13 & 11.0458 & 1.95416 \tabularnewline
220 & 9 & 10.2423 & -1.24227 \tabularnewline
221 & 12 & 10.8377 & 1.16228 \tabularnewline
222 & 11 & 10.7495 & 0.250501 \tabularnewline
223 & 14 & 10.3776 & 3.62237 \tabularnewline
224 & 11 & 11.0363 & -0.0362975 \tabularnewline
225 & 9 & 10.1588 & -1.15876 \tabularnewline
226 & 12 & 10.5196 & 1.48037 \tabularnewline
227 & 8 & 9.66906 & -1.66906 \tabularnewline
228 & 15 & 11.2652 & 3.73476 \tabularnewline
229 & 12 & 11.0706 & 0.929373 \tabularnewline
230 & 14 & 11.0573 & 2.94271 \tabularnewline
231 & 12 & 10.6943 & 1.30565 \tabularnewline
232 & 9 & 11.3185 & -2.31855 \tabularnewline
233 & 9 & 10.816 & -1.81598 \tabularnewline
234 & 13 & 11.0973 & 1.90275 \tabularnewline
235 & 13 & 10.5414 & 2.45862 \tabularnewline
236 & 15 & 10.9118 & 4.08815 \tabularnewline
237 & 11 & 11.1209 & -0.120947 \tabularnewline
238 & 7 & 10.4923 & -3.49225 \tabularnewline
239 & 10 & 10.6188 & -0.618769 \tabularnewline
240 & 11 & 10.9599 & 0.0400636 \tabularnewline
241 & 14 & 11.2701 & 2.72988 \tabularnewline
242 & 14 & 11.6244 & 2.37556 \tabularnewline
243 & 13 & 10.1966 & 2.80339 \tabularnewline
244 & 12 & 11.1427 & 0.857311 \tabularnewline
245 & 8 & 9.90646 & -1.90646 \tabularnewline
246 & 13 & 10.6013 & 2.3987 \tabularnewline
247 & 9 & 10.7039 & -1.70389 \tabularnewline
248 & 12 & 10.7236 & 1.27637 \tabularnewline
249 & 13 & 9.73152 & 3.26848 \tabularnewline
250 & 11 & 11.2103 & -0.210258 \tabularnewline
251 & 11 & 11.2103 & -0.210258 \tabularnewline
252 & 13 & 10.7343 & 2.26568 \tabularnewline
253 & 12 & 10.6317 & 1.36834 \tabularnewline
254 & 12 & 10.4874 & 1.51263 \tabularnewline
255 & 10 & 8.4616 & 1.5384 \tabularnewline
256 & 9 & 9.41343 & -0.413435 \tabularnewline
257 & 10 & 11.1712 & -1.17121 \tabularnewline
258 & 13 & 10.7837 & 2.21634 \tabularnewline
259 & 13 & 10.7782 & 2.22175 \tabularnewline
260 & 9 & 10.3061 & -1.3061 \tabularnewline
261 & 11 & 10.66 & 0.33998 \tabularnewline
262 & 12 & 10.5779 & 1.42206 \tabularnewline
263 & 8 & 10.6925 & -2.69245 \tabularnewline
264 & 12 & 9.92636 & 2.07364 \tabularnewline
265 & 12 & 10.8866 & 1.11341 \tabularnewline
266 & 12 & 10.8482 & 1.15176 \tabularnewline
267 & 9 & 10.8815 & -1.88148 \tabularnewline
268 & 12 & 10.5925 & 1.40755 \tabularnewline
269 & 12 & 11.5077 & 0.492308 \tabularnewline
270 & 11 & 11.4591 & -0.459101 \tabularnewline
271 & 12 & 11.102 & 0.898031 \tabularnewline
272 & 6 & 10.9205 & -4.92047 \tabularnewline
273 & 7 & 10.3419 & -3.34188 \tabularnewline
274 & 10 & 10.7827 & -0.782739 \tabularnewline
275 & 12 & 11.0316 & 0.968419 \tabularnewline
276 & 10 & 11.2482 & -1.24816 \tabularnewline
277 & 12 & 10.7512 & 1.24877 \tabularnewline
278 & 9 & 10.6005 & -1.60054 \tabularnewline
279 & 3 & 9.67654 & -6.67654 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267881&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]12[/C][C]10.1677[/C][C]1.83225[/C][/ROW]
[ROW][C]2[/C][C]8[/C][C]11.2054[/C][C]-3.20537[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]10.4633[/C][C]0.536659[/C][/ROW]
[ROW][C]4[/C][C]13[/C][C]11.3793[/C][C]1.62066[/C][/ROW]
[ROW][C]5[/C][C]11[/C][C]10.8177[/C][C]0.182346[/C][/ROW]
[ROW][C]6[/C][C]10[/C][C]10.4799[/C][C]-0.479891[/C][/ROW]
[ROW][C]7[/C][C]7[/C][C]10.3098[/C][C]-3.30984[/C][/ROW]
[ROW][C]8[/C][C]10[/C][C]10.3155[/C][C]-0.31553[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]11.7472[/C][C]3.25284[/C][/ROW]
[ROW][C]10[/C][C]12[/C][C]12.2883[/C][C]-0.288268[/C][/ROW]
[ROW][C]11[/C][C]12[/C][C]10.5538[/C][C]1.4462[/C][/ROW]
[ROW][C]12[/C][C]10[/C][C]11.7042[/C][C]-1.7042[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]10.1531[/C][C]-0.153125[/C][/ROW]
[ROW][C]14[/C][C]14[/C][C]10.9062[/C][C]3.09379[/C][/ROW]
[ROW][C]15[/C][C]6[/C][C]11.2996[/C][C]-5.29957[/C][/ROW]
[ROW][C]16[/C][C]12[/C][C]10.5552[/C][C]1.44484[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]10.4415[/C][C]3.55846[/C][/ROW]
[ROW][C]18[/C][C]11[/C][C]10.909[/C][C]0.09097[/C][/ROW]
[ROW][C]19[/C][C]8[/C][C]11.0297[/C][C]-3.02974[/C][/ROW]
[ROW][C]20[/C][C]12[/C][C]11.2238[/C][C]0.776233[/C][/ROW]
[ROW][C]21[/C][C]15[/C][C]11.2881[/C][C]3.71187[/C][/ROW]
[ROW][C]22[/C][C]13[/C][C]10.9369[/C][C]2.06314[/C][/ROW]
[ROW][C]23[/C][C]11[/C][C]10.8882[/C][C]0.111791[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]10.8919[/C][C]1.10805[/C][/ROW]
[ROW][C]25[/C][C]7[/C][C]10.8875[/C][C]-3.88751[/C][/ROW]
[ROW][C]26[/C][C]11[/C][C]10.7722[/C][C]0.227783[/C][/ROW]
[ROW][C]27[/C][C]7[/C][C]10.7753[/C][C]-3.77526[/C][/ROW]
[ROW][C]28[/C][C]12[/C][C]10.479[/C][C]1.52103[/C][/ROW]
[ROW][C]29[/C][C]12[/C][C]11.3679[/C][C]0.632108[/C][/ROW]
[ROW][C]30[/C][C]13[/C][C]10.5842[/C][C]2.41584[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]9.43565[/C][C]-0.435652[/C][/ROW]
[ROW][C]32[/C][C]11[/C][C]10.4858[/C][C]0.514249[/C][/ROW]
[ROW][C]33[/C][C]12[/C][C]10.6955[/C][C]1.30451[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]10.2668[/C][C]4.73317[/C][/ROW]
[ROW][C]35[/C][C]12[/C][C]10.3269[/C][C]1.67308[/C][/ROW]
[ROW][C]36[/C][C]6[/C][C]10.9423[/C][C]-4.94227[/C][/ROW]
[ROW][C]37[/C][C]5[/C][C]10.8178[/C][C]-5.81782[/C][/ROW]
[ROW][C]38[/C][C]13[/C][C]10.6937[/C][C]2.30635[/C][/ROW]
[ROW][C]39[/C][C]11[/C][C]11.2711[/C][C]-0.271101[/C][/ROW]
[ROW][C]40[/C][C]6[/C][C]10.3105[/C][C]-4.31054[/C][/ROW]
[ROW][C]41[/C][C]12[/C][C]10.6979[/C][C]1.30208[/C][/ROW]
[ROW][C]42[/C][C]10[/C][C]10.889[/C][C]-0.888963[/C][/ROW]
[ROW][C]43[/C][C]6[/C][C]10.6981[/C][C]-4.69809[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]9.76328[/C][C]2.23672[/C][/ROW]
[ROW][C]45[/C][C]11[/C][C]9.63797[/C][C]1.36203[/C][/ROW]
[ROW][C]46[/C][C]6[/C][C]11.5503[/C][C]-5.55031[/C][/ROW]
[ROW][C]47[/C][C]12[/C][C]10.6925[/C][C]1.30749[/C][/ROW]
[ROW][C]48[/C][C]12[/C][C]11.1684[/C][C]0.831606[/C][/ROW]
[ROW][C]49[/C][C]8[/C][C]11.2226[/C][C]-3.22262[/C][/ROW]
[ROW][C]50[/C][C]10[/C][C]10.718[/C][C]-0.717988[/C][/ROW]
[ROW][C]51[/C][C]11[/C][C]10.7523[/C][C]0.247682[/C][/ROW]
[ROW][C]52[/C][C]7[/C][C]10.5321[/C][C]-3.53205[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]10.6296[/C][C]1.3704[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]11.3167[/C][C]1.68335[/C][/ROW]
[ROW][C]55[/C][C]14[/C][C]11.4021[/C][C]2.59795[/C][/ROW]
[ROW][C]56[/C][C]12[/C][C]10.9546[/C][C]1.04537[/C][/ROW]
[ROW][C]57[/C][C]6[/C][C]9.82619[/C][C]-3.82619[/C][/ROW]
[ROW][C]58[/C][C]14[/C][C]10.2977[/C][C]3.7023[/C][/ROW]
[ROW][C]59[/C][C]10[/C][C]10.6268[/C][C]-0.62678[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]10.7636[/C][C]1.23641[/C][/ROW]
[ROW][C]61[/C][C]11[/C][C]11.3251[/C][C]-0.325107[/C][/ROW]
[ROW][C]62[/C][C]10[/C][C]10.8283[/C][C]-0.828343[/C][/ROW]
[ROW][C]63[/C][C]7[/C][C]9.1807[/C][C]-2.1807[/C][/ROW]
[ROW][C]64[/C][C]12[/C][C]10.5176[/C][C]1.48243[/C][/ROW]
[ROW][C]65[/C][C]7[/C][C]10.6015[/C][C]-3.60152[/C][/ROW]
[ROW][C]66[/C][C]12[/C][C]10.2091[/C][C]1.79092[/C][/ROW]
[ROW][C]67[/C][C]12[/C][C]10.9483[/C][C]1.0517[/C][/ROW]
[ROW][C]68[/C][C]10[/C][C]11.2823[/C][C]-1.28232[/C][/ROW]
[ROW][C]69[/C][C]10[/C][C]10.4977[/C][C]-0.49767[/C][/ROW]
[ROW][C]70[/C][C]12[/C][C]10.2306[/C][C]1.7694[/C][/ROW]
[ROW][C]71[/C][C]12[/C][C]10.6223[/C][C]1.37766[/C][/ROW]
[ROW][C]72[/C][C]12[/C][C]10.8691[/C][C]1.13094[/C][/ROW]
[ROW][C]73[/C][C]8[/C][C]10.7383[/C][C]-2.73833[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]11.8039[/C][C]-1.80387[/C][/ROW]
[ROW][C]75[/C][C]5[/C][C]9.79181[/C][C]-4.79181[/C][/ROW]
[ROW][C]76[/C][C]10[/C][C]11.4173[/C][C]-1.41729[/C][/ROW]
[ROW][C]77[/C][C]10[/C][C]10.1225[/C][C]-0.122536[/C][/ROW]
[ROW][C]78[/C][C]12[/C][C]10.3522[/C][C]1.64777[/C][/ROW]
[ROW][C]79[/C][C]11[/C][C]11.4904[/C][C]-0.490443[/C][/ROW]
[ROW][C]80[/C][C]9[/C][C]9.96842[/C][C]-0.96842[/C][/ROW]
[ROW][C]81[/C][C]12[/C][C]10.7409[/C][C]1.25913[/C][/ROW]
[ROW][C]82[/C][C]11[/C][C]10.7152[/C][C]0.28483[/C][/ROW]
[ROW][C]83[/C][C]10[/C][C]10.7694[/C][C]-0.769398[/C][/ROW]
[ROW][C]84[/C][C]12[/C][C]10.5271[/C][C]1.47289[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]10.8531[/C][C]-0.853127[/C][/ROW]
[ROW][C]86[/C][C]9[/C][C]10.04[/C][C]-1.04001[/C][/ROW]
[ROW][C]87[/C][C]11[/C][C]10.9462[/C][C]0.053767[/C][/ROW]
[ROW][C]88[/C][C]12[/C][C]11.2168[/C][C]0.783183[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.9775[/C][C]-3.97752[/C][/ROW]
[ROW][C]90[/C][C]11[/C][C]10.7297[/C][C]0.270346[/C][/ROW]
[ROW][C]91[/C][C]12[/C][C]10.7238[/C][C]1.27621[/C][/ROW]
[ROW][C]92[/C][C]6[/C][C]10.6546[/C][C]-4.65461[/C][/ROW]
[ROW][C]93[/C][C]9[/C][C]9.49764[/C][C]-0.497639[/C][/ROW]
[ROW][C]94[/C][C]15[/C][C]11.4032[/C][C]3.5968[/C][/ROW]
[ROW][C]95[/C][C]10[/C][C]9.16437[/C][C]0.835631[/C][/ROW]
[ROW][C]96[/C][C]11[/C][C]10.7769[/C][C]0.223067[/C][/ROW]
[ROW][C]97[/C][C]12[/C][C]11.3793[/C][C]0.620665[/C][/ROW]
[ROW][C]98[/C][C]12[/C][C]10.8342[/C][C]1.1658[/C][/ROW]
[ROW][C]99[/C][C]12[/C][C]10.6139[/C][C]1.38612[/C][/ROW]
[ROW][C]100[/C][C]11[/C][C]10.4586[/C][C]0.541376[/C][/ROW]
[ROW][C]101[/C][C]9[/C][C]11.1485[/C][C]-2.14849[/C][/ROW]
[ROW][C]102[/C][C]11[/C][C]10.9509[/C][C]0.0491057[/C][/ROW]
[ROW][C]103[/C][C]12[/C][C]11.177[/C][C]0.822982[/C][/ROW]
[ROW][C]104[/C][C]12[/C][C]9.5229[/C][C]2.4771[/C][/ROW]
[ROW][C]105[/C][C]14[/C][C]11.0744[/C][C]2.92563[/C][/ROW]
[ROW][C]106[/C][C]8[/C][C]10.8206[/C][C]-2.82064[/C][/ROW]
[ROW][C]107[/C][C]10[/C][C]10.6583[/C][C]-0.658345[/C][/ROW]
[ROW][C]108[/C][C]9[/C][C]10.7241[/C][C]-1.72407[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]10.5414[/C][C]-0.541376[/C][/ROW]
[ROW][C]110[/C][C]9[/C][C]11.1361[/C][C]-2.13613[/C][/ROW]
[ROW][C]111[/C][C]10[/C][C]11.1598[/C][C]-1.15977[/C][/ROW]
[ROW][C]112[/C][C]12[/C][C]11.2596[/C][C]0.740397[/C][/ROW]
[ROW][C]113[/C][C]11[/C][C]11.2624[/C][C]-0.262422[/C][/ROW]
[ROW][C]114[/C][C]9[/C][C]11.1607[/C][C]-2.16075[/C][/ROW]
[ROW][C]115[/C][C]11[/C][C]9.52365[/C][C]1.47635[/C][/ROW]
[ROW][C]116[/C][C]12[/C][C]10.2243[/C][C]1.77573[/C][/ROW]
[ROW][C]117[/C][C]12[/C][C]10.8597[/C][C]1.14031[/C][/ROW]
[ROW][C]118[/C][C]7[/C][C]11.1341[/C][C]-4.13407[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]10.2533[/C][C]1.74671[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]11.1055[/C][C]0.894459[/C][/ROW]
[ROW][C]121[/C][C]12[/C][C]11.2652[/C][C]0.734759[/C][/ROW]
[ROW][C]122[/C][C]10[/C][C]10.8627[/C][C]-0.862727[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]10.8833[/C][C]4.11667[/C][/ROW]
[ROW][C]124[/C][C]10[/C][C]10.8406[/C][C]-0.840595[/C][/ROW]
[ROW][C]125[/C][C]15[/C][C]11.2226[/C][C]3.77738[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]10.9147[/C][C]-0.914668[/C][/ROW]
[ROW][C]127[/C][C]15[/C][C]10.8454[/C][C]4.15458[/C][/ROW]
[ROW][C]128[/C][C]9[/C][C]9.98854[/C][C]-0.988542[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]10.9745[/C][C]4.02547[/C][/ROW]
[ROW][C]130[/C][C]12[/C][C]11.6074[/C][C]0.392643[/C][/ROW]
[ROW][C]131[/C][C]13[/C][C]10.6583[/C][C]2.34165[/C][/ROW]
[ROW][C]132[/C][C]12[/C][C]10.2928[/C][C]1.70719[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]10.9121[/C][C]1.08793[/C][/ROW]
[ROW][C]134[/C][C]8[/C][C]10.5727[/C][C]-2.57272[/C][/ROW]
[ROW][C]135[/C][C]9[/C][C]11.2283[/C][C]-2.22826[/C][/ROW]
[ROW][C]136[/C][C]15[/C][C]10.1422[/C][C]4.85779[/C][/ROW]
[ROW][C]137[/C][C]12[/C][C]11.6928[/C][C]0.30724[/C][/ROW]
[ROW][C]138[/C][C]12[/C][C]10.7037[/C][C]1.29627[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]10.7865[/C][C]4.21352[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]10.8531[/C][C]0.146873[/C][/ROW]
[ROW][C]141[/C][C]12[/C][C]11.4098[/C][C]0.590188[/C][/ROW]
[ROW][C]142[/C][C]6[/C][C]8.76587[/C][C]-2.76587[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]10.4986[/C][C]3.50141[/C][/ROW]
[ROW][C]144[/C][C]12[/C][C]11.0851[/C][C]0.914889[/C][/ROW]
[ROW][C]145[/C][C]12[/C][C]10.3772[/C][C]1.62282[/C][/ROW]
[ROW][C]146[/C][C]12[/C][C]10.9261[/C][C]1.07389[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]10.6724[/C][C]0.327561[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]12.2485[/C][C]-0.248469[/C][/ROW]
[ROW][C]149[/C][C]12[/C][C]11.04[/C][C]0.959962[/C][/ROW]
[ROW][C]150[/C][C]12[/C][C]10.9802[/C][C]1.01983[/C][/ROW]
[ROW][C]151[/C][C]12[/C][C]10.6043[/C][C]1.39566[/C][/ROW]
[ROW][C]152[/C][C]8[/C][C]10.648[/C][C]-2.64799[/C][/ROW]
[ROW][C]153[/C][C]8[/C][C]11.1418[/C][C]-3.14177[/C][/ROW]
[ROW][C]154[/C][C]12[/C][C]11.1418[/C][C]0.858232[/C][/ROW]
[ROW][C]155[/C][C]12[/C][C]10.0225[/C][C]1.97752[/C][/ROW]
[ROW][C]156[/C][C]11[/C][C]11.6158[/C][C]-0.615813[/C][/ROW]
[ROW][C]157[/C][C]10[/C][C]11.6292[/C][C]-1.62915[/C][/ROW]
[ROW][C]158[/C][C]11[/C][C]11.8857[/C][C]-0.885699[/C][/ROW]
[ROW][C]159[/C][C]12[/C][C]10.7514[/C][C]1.2486[/C][/ROW]
[ROW][C]160[/C][C]13[/C][C]11.6006[/C][C]1.39937[/C][/ROW]
[ROW][C]161[/C][C]12[/C][C]10.3047[/C][C]1.69527[/C][/ROW]
[ROW][C]162[/C][C]12[/C][C]10.511[/C][C]1.48899[/C][/ROW]
[ROW][C]163[/C][C]10[/C][C]11.0316[/C][C]-1.03158[/C][/ROW]
[ROW][C]164[/C][C]10[/C][C]10.6923[/C][C]-0.692284[/C][/ROW]
[ROW][C]165[/C][C]11[/C][C]11.4818[/C][C]-0.481819[/C][/ROW]
[ROW][C]166[/C][C]8[/C][C]10.9671[/C][C]-2.96711[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]9.63116[/C][C]2.36884[/C][/ROW]
[ROW][C]168[/C][C]9[/C][C]10.4712[/C][C]-1.47121[/C][/ROW]
[ROW][C]169[/C][C]12[/C][C]10.8312[/C][C]1.16884[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.6472[/C][C]-2.64716[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.6349[/C][C]0.365072[/C][/ROW]
[ROW][C]172[/C][C]15[/C][C]11.8468[/C][C]3.15318[/C][/ROW]
[ROW][C]173[/C][C]8[/C][C]10.4476[/C][C]-2.44763[/C][/ROW]
[ROW][C]174[/C][C]8[/C][C]10.779[/C][C]-2.779[/C][/ROW]
[ROW][C]175[/C][C]11[/C][C]10.9624[/C][C]0.0376076[/C][/ROW]
[ROW][C]176[/C][C]11[/C][C]10.8997[/C][C]0.100293[/C][/ROW]
[ROW][C]177[/C][C]11[/C][C]10.4855[/C][C]0.514527[/C][/ROW]
[ROW][C]178[/C][C]13[/C][C]10.646[/C][C]2.35402[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]9.74604[/C][C]-2.74604[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]10.718[/C][C]1.28201[/C][/ROW]
[ROW][C]181[/C][C]8[/C][C]10.0809[/C][C]-2.08089[/C][/ROW]
[ROW][C]182[/C][C]8[/C][C]10.6081[/C][C]-2.60808[/C][/ROW]
[ROW][C]183[/C][C]4[/C][C]10.4292[/C][C]-6.42918[/C][/ROW]
[ROW][C]184[/C][C]11[/C][C]10.7437[/C][C]0.256307[/C][/ROW]
[ROW][C]185[/C][C]10[/C][C]10.9376[/C][C]-0.937554[/C][/ROW]
[ROW][C]186[/C][C]7[/C][C]9.31452[/C][C]-2.31452[/C][/ROW]
[ROW][C]187[/C][C]12[/C][C]10.7669[/C][C]1.23314[/C][/ROW]
[ROW][C]188[/C][C]11[/C][C]10.8447[/C][C]0.155275[/C][/ROW]
[ROW][C]189[/C][C]9[/C][C]10.9719[/C][C]-1.97194[/C][/ROW]
[ROW][C]190[/C][C]10[/C][C]10.9502[/C][C]-0.950196[/C][/ROW]
[ROW][C]191[/C][C]8[/C][C]10.5482[/C][C]-2.54816[/C][/ROW]
[ROW][C]192[/C][C]8[/C][C]10.7037[/C][C]-2.70373[/C][/ROW]
[ROW][C]193[/C][C]11[/C][C]11.0119[/C][C]-0.0119046[/C][/ROW]
[ROW][C]194[/C][C]12[/C][C]11.422[/C][C]0.578047[/C][/ROW]
[ROW][C]195[/C][C]10[/C][C]11.1572[/C][C]-1.15717[/C][/ROW]
[ROW][C]196[/C][C]10[/C][C]10.5583[/C][C]-0.558289[/C][/ROW]
[ROW][C]197[/C][C]12[/C][C]10.4687[/C][C]1.53127[/C][/ROW]
[ROW][C]198[/C][C]8[/C][C]10.4815[/C][C]-2.48151[/C][/ROW]
[ROW][C]199[/C][C]11[/C][C]10.3915[/C][C]0.608499[/C][/ROW]
[ROW][C]200[/C][C]8[/C][C]10.6866[/C][C]-2.68665[/C][/ROW]
[ROW][C]201[/C][C]10[/C][C]11.5531[/C][C]-1.55313[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]10.1606[/C][C]3.83943[/C][/ROW]
[ROW][C]203[/C][C]9[/C][C]11.8551[/C][C]-2.85511[/C][/ROW]
[ROW][C]204[/C][C]9[/C][C]11.0629[/C][C]-2.06292[/C][/ROW]
[ROW][C]205[/C][C]10[/C][C]10.3618[/C][C]-0.361778[/C][/ROW]
[ROW][C]206[/C][C]13[/C][C]10.3182[/C][C]2.68176[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]10.3475[/C][C]1.65248[/C][/ROW]
[ROW][C]208[/C][C]13[/C][C]10.8321[/C][C]2.16792[/C][/ROW]
[ROW][C]209[/C][C]8[/C][C]10.1322[/C][C]-2.13219[/C][/ROW]
[ROW][C]210[/C][C]3[/C][C]10.3134[/C][C]-7.31335[/C][/ROW]
[ROW][C]211[/C][C]8[/C][C]10.3487[/C][C]-2.34866[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]10.7818[/C][C]1.21818[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]10.8426[/C][C]0.157395[/C][/ROW]
[ROW][C]214[/C][C]9[/C][C]10.9661[/C][C]-1.96608[/C][/ROW]
[ROW][C]215[/C][C]12[/C][C]10.6127[/C][C]1.38731[/C][/ROW]
[ROW][C]216[/C][C]12[/C][C]10.7523[/C][C]1.24768[/C][/ROW]
[ROW][C]217[/C][C]12[/C][C]10.6385[/C][C]1.3615[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]10.1139[/C][C]-0.113912[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.0458[/C][C]1.95416[/C][/ROW]
[ROW][C]220[/C][C]9[/C][C]10.2423[/C][C]-1.24227[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]10.8377[/C][C]1.16228[/C][/ROW]
[ROW][C]222[/C][C]11[/C][C]10.7495[/C][C]0.250501[/C][/ROW]
[ROW][C]223[/C][C]14[/C][C]10.3776[/C][C]3.62237[/C][/ROW]
[ROW][C]224[/C][C]11[/C][C]11.0363[/C][C]-0.0362975[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]10.1588[/C][C]-1.15876[/C][/ROW]
[ROW][C]226[/C][C]12[/C][C]10.5196[/C][C]1.48037[/C][/ROW]
[ROW][C]227[/C][C]8[/C][C]9.66906[/C][C]-1.66906[/C][/ROW]
[ROW][C]228[/C][C]15[/C][C]11.2652[/C][C]3.73476[/C][/ROW]
[ROW][C]229[/C][C]12[/C][C]11.0706[/C][C]0.929373[/C][/ROW]
[ROW][C]230[/C][C]14[/C][C]11.0573[/C][C]2.94271[/C][/ROW]
[ROW][C]231[/C][C]12[/C][C]10.6943[/C][C]1.30565[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]11.3185[/C][C]-2.31855[/C][/ROW]
[ROW][C]233[/C][C]9[/C][C]10.816[/C][C]-1.81598[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]11.0973[/C][C]1.90275[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]10.5414[/C][C]2.45862[/C][/ROW]
[ROW][C]236[/C][C]15[/C][C]10.9118[/C][C]4.08815[/C][/ROW]
[ROW][C]237[/C][C]11[/C][C]11.1209[/C][C]-0.120947[/C][/ROW]
[ROW][C]238[/C][C]7[/C][C]10.4923[/C][C]-3.49225[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]10.6188[/C][C]-0.618769[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]10.9599[/C][C]0.0400636[/C][/ROW]
[ROW][C]241[/C][C]14[/C][C]11.2701[/C][C]2.72988[/C][/ROW]
[ROW][C]242[/C][C]14[/C][C]11.6244[/C][C]2.37556[/C][/ROW]
[ROW][C]243[/C][C]13[/C][C]10.1966[/C][C]2.80339[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]11.1427[/C][C]0.857311[/C][/ROW]
[ROW][C]245[/C][C]8[/C][C]9.90646[/C][C]-1.90646[/C][/ROW]
[ROW][C]246[/C][C]13[/C][C]10.6013[/C][C]2.3987[/C][/ROW]
[ROW][C]247[/C][C]9[/C][C]10.7039[/C][C]-1.70389[/C][/ROW]
[ROW][C]248[/C][C]12[/C][C]10.7236[/C][C]1.27637[/C][/ROW]
[ROW][C]249[/C][C]13[/C][C]9.73152[/C][C]3.26848[/C][/ROW]
[ROW][C]250[/C][C]11[/C][C]11.2103[/C][C]-0.210258[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.2103[/C][C]-0.210258[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]10.7343[/C][C]2.26568[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]10.6317[/C][C]1.36834[/C][/ROW]
[ROW][C]254[/C][C]12[/C][C]10.4874[/C][C]1.51263[/C][/ROW]
[ROW][C]255[/C][C]10[/C][C]8.4616[/C][C]1.5384[/C][/ROW]
[ROW][C]256[/C][C]9[/C][C]9.41343[/C][C]-0.413435[/C][/ROW]
[ROW][C]257[/C][C]10[/C][C]11.1712[/C][C]-1.17121[/C][/ROW]
[ROW][C]258[/C][C]13[/C][C]10.7837[/C][C]2.21634[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]10.7782[/C][C]2.22175[/C][/ROW]
[ROW][C]260[/C][C]9[/C][C]10.3061[/C][C]-1.3061[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]10.66[/C][C]0.33998[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]10.5779[/C][C]1.42206[/C][/ROW]
[ROW][C]263[/C][C]8[/C][C]10.6925[/C][C]-2.69245[/C][/ROW]
[ROW][C]264[/C][C]12[/C][C]9.92636[/C][C]2.07364[/C][/ROW]
[ROW][C]265[/C][C]12[/C][C]10.8866[/C][C]1.11341[/C][/ROW]
[ROW][C]266[/C][C]12[/C][C]10.8482[/C][C]1.15176[/C][/ROW]
[ROW][C]267[/C][C]9[/C][C]10.8815[/C][C]-1.88148[/C][/ROW]
[ROW][C]268[/C][C]12[/C][C]10.5925[/C][C]1.40755[/C][/ROW]
[ROW][C]269[/C][C]12[/C][C]11.5077[/C][C]0.492308[/C][/ROW]
[ROW][C]270[/C][C]11[/C][C]11.4591[/C][C]-0.459101[/C][/ROW]
[ROW][C]271[/C][C]12[/C][C]11.102[/C][C]0.898031[/C][/ROW]
[ROW][C]272[/C][C]6[/C][C]10.9205[/C][C]-4.92047[/C][/ROW]
[ROW][C]273[/C][C]7[/C][C]10.3419[/C][C]-3.34188[/C][/ROW]
[ROW][C]274[/C][C]10[/C][C]10.7827[/C][C]-0.782739[/C][/ROW]
[ROW][C]275[/C][C]12[/C][C]11.0316[/C][C]0.968419[/C][/ROW]
[ROW][C]276[/C][C]10[/C][C]11.2482[/C][C]-1.24816[/C][/ROW]
[ROW][C]277[/C][C]12[/C][C]10.7512[/C][C]1.24877[/C][/ROW]
[ROW][C]278[/C][C]9[/C][C]10.6005[/C][C]-1.60054[/C][/ROW]
[ROW][C]279[/C][C]3[/C][C]9.67654[/C][C]-6.67654[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267881&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267881&T=4

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11210.16771.83225
2811.2054-3.20537
31110.46330.536659
41311.37931.62066
51110.81770.182346
61010.4799-0.479891
7710.3098-3.30984
81010.3155-0.31553
91511.74723.25284
101212.2883-0.288268
111210.55381.4462
121011.7042-1.7042
131010.1531-0.153125
141410.90623.09379
15611.2996-5.29957
161210.55521.44484
171410.44153.55846
181110.9090.09097
19811.0297-3.02974
201211.22380.776233
211511.28813.71187
221310.93692.06314
231110.88820.111791
241210.89191.10805
25710.8875-3.88751
261110.77220.227783
27710.7753-3.77526
281210.4791.52103
291211.36790.632108
301310.58422.41584
3199.43565-0.435652
321110.48580.514249
331210.69551.30451
341510.26684.73317
351210.32691.67308
36610.9423-4.94227
37510.8178-5.81782
381310.69372.30635
391111.2711-0.271101
40610.3105-4.31054
411210.69791.30208
421010.889-0.888963
43610.6981-4.69809
44129.763282.23672
45119.637971.36203
46611.5503-5.55031
471210.69251.30749
481211.16840.831606
49811.2226-3.22262
501010.718-0.717988
511110.75230.247682
52710.5321-3.53205
531210.62961.3704
541311.31671.68335
551411.40212.59795
561210.95461.04537
5769.82619-3.82619
581410.29773.7023
591010.6268-0.62678
601210.76361.23641
611111.3251-0.325107
621010.8283-0.828343
6379.1807-2.1807
641210.51761.48243
65710.6015-3.60152
661210.20911.79092
671210.94831.0517
681011.2823-1.28232
691010.4977-0.49767
701210.23061.7694
711210.62231.37766
721210.86911.13094
73810.7383-2.73833
741011.8039-1.80387
7559.79181-4.79181
761011.4173-1.41729
771010.1225-0.122536
781210.35221.64777
791111.4904-0.490443
8099.96842-0.96842
811210.74091.25913
821110.71520.28483
831010.7694-0.769398
841210.52711.47289
851010.8531-0.853127
86910.04-1.04001
871110.94620.053767
881211.21680.783183
89710.9775-3.97752
901110.72970.270346
911210.72381.27621
92610.6546-4.65461
9399.49764-0.497639
941511.40323.5968
95109.164370.835631
961110.77690.223067
971211.37930.620665
981210.83421.1658
991210.61391.38612
1001110.45860.541376
101911.1485-2.14849
1021110.95090.0491057
1031211.1770.822982
104129.52292.4771
1051411.07442.92563
106810.8206-2.82064
1071010.6583-0.658345
108910.7241-1.72407
1091010.5414-0.541376
110911.1361-2.13613
1111011.1598-1.15977
1121211.25960.740397
1131111.2624-0.262422
114911.1607-2.16075
115119.523651.47635
1161210.22431.77573
1171210.85971.14031
118711.1341-4.13407
1191210.25331.74671
1201211.10550.894459
1211211.26520.734759
1221010.8627-0.862727
1231510.88334.11667
1241010.8406-0.840595
1251511.22263.77738
1261010.9147-0.914668
1271510.84544.15458
12899.98854-0.988542
1291510.97454.02547
1301211.60740.392643
1311310.65832.34165
1321210.29281.70719
1331210.91211.08793
134810.5727-2.57272
135911.2283-2.22826
1361510.14224.85779
1371211.69280.30724
1381210.70371.29627
1391510.78654.21352
1401110.85310.146873
1411211.40980.590188
14268.76587-2.76587
1431410.49863.50141
1441211.08510.914889
1451210.37721.62282
1461210.92611.07389
1471110.67240.327561
1481212.2485-0.248469
1491211.040.959962
1501210.98021.01983
1511210.60431.39566
152810.648-2.64799
153811.1418-3.14177
1541211.14180.858232
1551210.02251.97752
1561111.6158-0.615813
1571011.6292-1.62915
1581111.8857-0.885699
1591210.75141.2486
1601311.60061.39937
1611210.30471.69527
1621210.5111.48899
1631011.0316-1.03158
1641010.6923-0.692284
1651111.4818-0.481819
166810.9671-2.96711
167129.631162.36884
168910.4712-1.47121
1691210.83121.16884
170911.6472-2.64716
1711110.63490.365072
1721511.84683.15318
173810.4476-2.44763
174810.779-2.779
1751110.96240.0376076
1761110.89970.100293
1771110.48550.514527
1781310.6462.35402
17979.74604-2.74604
1801210.7181.28201
181810.0809-2.08089
182810.6081-2.60808
183410.4292-6.42918
1841110.74370.256307
1851010.9376-0.937554
18679.31452-2.31452
1871210.76691.23314
1881110.84470.155275
189910.9719-1.97194
1901010.9502-0.950196
191810.5482-2.54816
192810.7037-2.70373
1931111.0119-0.0119046
1941211.4220.578047
1951011.1572-1.15717
1961010.5583-0.558289
1971210.46871.53127
198810.4815-2.48151
1991110.39150.608499
200810.6866-2.68665
2011011.5531-1.55313
2021410.16063.83943
203911.8551-2.85511
204911.0629-2.06292
2051010.3618-0.361778
2061310.31822.68176
2071210.34751.65248
2081310.83212.16792
209810.1322-2.13219
210310.3134-7.31335
211810.3487-2.34866
2121210.78181.21818
2131110.84260.157395
214910.9661-1.96608
2151210.61271.38731
2161210.75231.24768
2171210.63851.3615
2181010.1139-0.113912
2191311.04581.95416
220910.2423-1.24227
2211210.83771.16228
2221110.74950.250501
2231410.37763.62237
2241111.0363-0.0362975
225910.1588-1.15876
2261210.51961.48037
22789.66906-1.66906
2281511.26523.73476
2291211.07060.929373
2301411.05732.94271
2311210.69431.30565
232911.3185-2.31855
233910.816-1.81598
2341311.09731.90275
2351310.54142.45862
2361510.91184.08815
2371111.1209-0.120947
238710.4923-3.49225
2391010.6188-0.618769
2401110.95990.0400636
2411411.27012.72988
2421411.62442.37556
2431310.19662.80339
2441211.14270.857311
24589.90646-1.90646
2461310.60132.3987
247910.7039-1.70389
2481210.72361.27637
249139.731523.26848
2501111.2103-0.210258
2511111.2103-0.210258
2521310.73432.26568
2531210.63171.36834
2541210.48741.51263
255108.46161.5384
25699.41343-0.413435
2571011.1712-1.17121
2581310.78372.21634
2591310.77822.22175
260910.3061-1.3061
2611110.660.33998
2621210.57791.42206
263810.6925-2.69245
264129.926362.07364
2651210.88661.11341
2661210.84821.15176
267910.8815-1.88148
2681210.59251.40755
2691211.50770.492308
2701111.4591-0.459101
2711211.1020.898031
272610.9205-4.92047
273710.3419-3.34188
2741010.7827-0.782739
2751211.03160.968419
2761011.2482-1.24816
2771210.75121.24877
278910.6005-1.60054
27939.67654-6.67654






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.7287990.5424030.271201
80.5849430.8301140.415057
90.7272940.5454120.272706
100.6396360.7207280.360364
110.5657480.8685030.434252
120.5482780.9034440.451722
130.4458430.8916860.554157
140.448950.8978990.55105
150.8350040.3299920.164996
160.8253640.3492720.174636
170.8490030.3019950.150997
180.8009050.3981910.199095
190.8197630.3604740.180237
200.7761250.447750.223875
210.8296430.3407150.170357
220.8250070.3499860.174993
230.7803450.439310.219655
240.7309770.5380470.269023
250.7846040.4307920.215396
260.7396250.5207510.260375
270.8026030.3947940.197397
280.8039790.3920420.196021
290.7629930.4740150.237007
300.7355640.5288710.264436
310.7053910.5892190.294609
320.6802290.6395430.319771
330.6424290.7151420.357571
340.7351170.5297670.264883
350.7048810.5902380.295119
360.8520560.2958880.147944
370.9641210.07175780.0358789
380.9650890.06982290.0349114
390.9546980.09060350.0453017
400.9798710.04025720.0201286
410.9755740.0488530.0244265
420.968940.06211930.0310596
430.9856620.0286760.014338
440.9840630.03187410.0159371
450.9798550.04029060.0201453
460.9926140.01477270.00738636
470.9909520.01809690.00904846
480.9886630.0226740.011337
490.9900180.0199650.00998249
500.9869380.02612480.0130624
510.9829080.03418470.0170924
520.9877320.02453530.0122676
530.9853750.02925060.0146253
540.9845170.03096650.0154832
550.9868380.02632480.0131624
560.9838350.0323290.0161645
570.9904340.01913260.0095663
580.993490.01301990.00650997
590.9914880.01702470.00851233
600.9897150.02057020.0102851
610.9866140.02677270.0133864
620.9831320.03373570.0168679
630.9835170.03296550.0164828
640.9807760.03844870.0192244
650.9855730.02885420.0144271
660.9841090.03178120.0158906
670.9811770.03764560.0188228
680.9774760.04504760.0225238
690.9719750.05605080.0280254
700.9686450.062710.031355
710.9642710.07145710.0357286
720.958090.08381910.0419096
730.9599270.08014680.0400734
740.9550810.08983710.0449185
750.978980.04203990.0210199
760.9754460.04910760.0245538
770.9694570.06108560.0305428
780.965930.06814050.0340702
790.95840.08320040.0416002
800.9512470.09750550.0487527
810.944770.110460.0552298
820.9337790.1324420.066221
830.9220810.1558380.0779192
840.9142240.1715520.0857758
850.9004110.1991770.0995886
860.8866930.2266140.113307
870.8682260.2635470.131774
880.8509520.2980970.149048
890.8859370.2281260.114063
900.8680630.2638740.131937
910.8554340.2891320.144566
920.9084420.1831160.091558
930.8931940.2136110.106806
940.9201430.1597140.0798571
950.908460.1830790.0915396
960.8929540.2140920.107046
970.8776120.2447750.122388
980.8648640.2702720.135136
990.8536050.292790.146395
1000.8333660.3332680.166634
1010.8293030.3413940.170697
1020.8059450.388110.194055
1030.7853550.429290.214645
1040.7887780.4224430.211222
1050.8073620.3852760.192638
1060.8200490.3599020.179951
1070.7977880.4044250.202212
1080.7855460.4289080.214454
1090.7605210.4789580.239479
1100.75620.4875990.2438
1110.7349110.5301780.265089
1120.7096340.5807330.290366
1130.6794160.6411670.320584
1140.6746560.6506870.325344
1150.6561030.6877950.343897
1160.6451310.7097380.354869
1170.6215040.7569910.378496
1180.6941890.6116220.305811
1190.6849370.6301260.315063
1200.6597880.6804250.340212
1210.6321270.7357460.367873
1220.6037340.7925320.396266
1230.6819540.6360930.318046
1240.6543880.6912240.345612
1250.7113410.5773180.288659
1260.6860020.6279960.313998
1270.7563710.4872590.243629
1280.7339650.532070.266035
1290.7928850.414230.207115
1300.7683260.4633480.231674
1310.7712320.4575360.228768
1320.7608510.4782980.239149
1330.7399180.5201650.260082
1340.7486110.5027780.251389
1350.7483450.503310.251655
1360.8411340.3177320.158866
1370.820120.3597590.17988
1380.8054120.3891750.194588
1390.8606630.2786730.139337
1400.8407190.3185620.159281
1410.8207680.3584650.179232
1420.8288190.3423620.171181
1430.8609180.2781640.139082
1440.8443270.3113460.155673
1450.8352180.3295630.164782
1460.8186540.3626920.181346
1470.7960780.4078440.203922
1480.7723120.4553750.227688
1490.7511470.4977060.248853
1500.7300810.5398380.269919
1510.7135750.5728490.286425
1520.7257520.5484960.274248
1530.7529880.4940230.247012
1540.7292350.541530.270765
1550.7347570.5304860.265243
1560.7087510.5824990.291249
1570.6980170.6039650.301983
1580.6774640.6450730.322536
1590.6566380.6867240.343362
1600.6350060.7299870.364994
1610.6319440.7361130.368056
1620.6188190.7623610.381181
1630.5923740.8152530.407626
1640.5612330.8775340.438767
1650.5289130.9421740.471087
1660.5574750.8850490.442525
1670.5643110.8713770.435689
1680.5425720.9148550.457428
1690.5183170.9633660.481683
1700.5460840.9078310.453916
1710.5120050.975990.487995
1720.5293480.9413040.470652
1730.5358940.9282130.464106
1740.5558330.8883330.444167
1750.5210640.9578720.478936
1760.4858360.9716730.514164
1770.4537090.9074180.546291
1780.4600270.9200540.539973
1790.4601230.9202450.539877
1800.4408330.8816660.559167
1810.4300820.8601630.569918
1820.4426980.8853960.557302
1830.6774490.6451010.322551
1840.6449420.7101160.355058
1850.6166320.7667360.383368
1860.6118410.7763180.388159
1870.5849810.8300380.415019
1880.5491530.9016930.450847
1890.546060.907880.45394
1900.5210380.9579230.478962
1910.5307310.9385390.469269
1920.5449430.9101140.455057
1930.5084380.9831250.491562
1940.4722720.9445450.527728
1950.4518680.9037370.548132
1960.4159820.8319640.584018
1970.3921710.7843410.607829
1980.3958460.7916920.604154
1990.3617660.7235320.638234
2000.3766110.7532220.623389
2010.3684960.7369920.631504
2020.4159310.8318620.584069
2030.4661630.9323250.533837
2040.4715980.9431960.528402
2050.4335730.8671460.566427
2060.45550.9110010.5445
2070.44210.88420.5579
2080.4357230.8714450.564277
2090.4362840.8725680.563716
2100.7896150.4207690.210385
2110.7972180.4055650.202782
2120.7725920.4548170.227408
2130.7405130.5189740.259487
2140.7448850.510230.255115
2150.7198130.5603740.280187
2160.6907750.6184510.309225
2170.6621160.6757690.337884
2180.6230970.7538050.376903
2190.6033180.7933650.396682
2200.5778840.8442330.422116
2210.5409620.9180770.459038
2220.4979590.9959190.502041
2230.5825720.8348560.417428
2240.542160.915680.45784
2250.5109590.9780820.489041
2260.4802420.9604830.519758
2270.4504290.9008570.549571
2280.5042320.9915350.495768
2290.4635920.9271850.536408
2300.4878140.9756270.512186
2310.452010.904020.54799
2320.4644440.9288870.535556
2330.4600170.9200340.539983
2340.4457120.8914240.554288
2350.451070.9021390.54893
2360.5507350.8985310.449265
2370.5034350.993130.496565
2380.566420.8671590.43358
2390.5191620.9616750.480838
2400.486780.9735590.51322
2410.5029310.9941380.497069
2420.509650.98070.49035
2430.5997330.8005350.400267
2440.550270.8994590.44973
2450.5561560.8876890.443844
2460.5442810.9114370.455719
2470.4970540.9941070.502946
2480.449410.8988190.55059
2490.5064540.9870920.493546
2500.4478270.8956530.552173
2510.3896840.7793690.610316
2520.4241240.8482480.575876
2530.4082070.8164130.591793
2540.3962440.7924870.603756
2550.4837240.9674490.516276
2560.4685450.937090.531455
2570.4348440.8696880.565156
2580.5489740.9020530.451026
2590.7778220.4443560.222178
2600.758280.4834390.24172
2610.6908690.6182620.309131
2620.6246340.7507320.375366
2630.547150.9057010.45285
2640.6902570.6194860.309743
2650.7128870.5742260.287113
2660.6998020.6003950.300198
2670.7007820.5984350.299218
2680.6059390.7881210.394061
2690.5585220.8829550.441478
2700.4626630.9253250.537337
2710.4303580.8607150.569642
2720.6417490.7165020.358251

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
7 & 0.728799 & 0.542403 & 0.271201 \tabularnewline
8 & 0.584943 & 0.830114 & 0.415057 \tabularnewline
9 & 0.727294 & 0.545412 & 0.272706 \tabularnewline
10 & 0.639636 & 0.720728 & 0.360364 \tabularnewline
11 & 0.565748 & 0.868503 & 0.434252 \tabularnewline
12 & 0.548278 & 0.903444 & 0.451722 \tabularnewline
13 & 0.445843 & 0.891686 & 0.554157 \tabularnewline
14 & 0.44895 & 0.897899 & 0.55105 \tabularnewline
15 & 0.835004 & 0.329992 & 0.164996 \tabularnewline
16 & 0.825364 & 0.349272 & 0.174636 \tabularnewline
17 & 0.849003 & 0.301995 & 0.150997 \tabularnewline
18 & 0.800905 & 0.398191 & 0.199095 \tabularnewline
19 & 0.819763 & 0.360474 & 0.180237 \tabularnewline
20 & 0.776125 & 0.44775 & 0.223875 \tabularnewline
21 & 0.829643 & 0.340715 & 0.170357 \tabularnewline
22 & 0.825007 & 0.349986 & 0.174993 \tabularnewline
23 & 0.780345 & 0.43931 & 0.219655 \tabularnewline
24 & 0.730977 & 0.538047 & 0.269023 \tabularnewline
25 & 0.784604 & 0.430792 & 0.215396 \tabularnewline
26 & 0.739625 & 0.520751 & 0.260375 \tabularnewline
27 & 0.802603 & 0.394794 & 0.197397 \tabularnewline
28 & 0.803979 & 0.392042 & 0.196021 \tabularnewline
29 & 0.762993 & 0.474015 & 0.237007 \tabularnewline
30 & 0.735564 & 0.528871 & 0.264436 \tabularnewline
31 & 0.705391 & 0.589219 & 0.294609 \tabularnewline
32 & 0.680229 & 0.639543 & 0.319771 \tabularnewline
33 & 0.642429 & 0.715142 & 0.357571 \tabularnewline
34 & 0.735117 & 0.529767 & 0.264883 \tabularnewline
35 & 0.704881 & 0.590238 & 0.295119 \tabularnewline
36 & 0.852056 & 0.295888 & 0.147944 \tabularnewline
37 & 0.964121 & 0.0717578 & 0.0358789 \tabularnewline
38 & 0.965089 & 0.0698229 & 0.0349114 \tabularnewline
39 & 0.954698 & 0.0906035 & 0.0453017 \tabularnewline
40 & 0.979871 & 0.0402572 & 0.0201286 \tabularnewline
41 & 0.975574 & 0.048853 & 0.0244265 \tabularnewline
42 & 0.96894 & 0.0621193 & 0.0310596 \tabularnewline
43 & 0.985662 & 0.028676 & 0.014338 \tabularnewline
44 & 0.984063 & 0.0318741 & 0.0159371 \tabularnewline
45 & 0.979855 & 0.0402906 & 0.0201453 \tabularnewline
46 & 0.992614 & 0.0147727 & 0.00738636 \tabularnewline
47 & 0.990952 & 0.0180969 & 0.00904846 \tabularnewline
48 & 0.988663 & 0.022674 & 0.011337 \tabularnewline
49 & 0.990018 & 0.019965 & 0.00998249 \tabularnewline
50 & 0.986938 & 0.0261248 & 0.0130624 \tabularnewline
51 & 0.982908 & 0.0341847 & 0.0170924 \tabularnewline
52 & 0.987732 & 0.0245353 & 0.0122676 \tabularnewline
53 & 0.985375 & 0.0292506 & 0.0146253 \tabularnewline
54 & 0.984517 & 0.0309665 & 0.0154832 \tabularnewline
55 & 0.986838 & 0.0263248 & 0.0131624 \tabularnewline
56 & 0.983835 & 0.032329 & 0.0161645 \tabularnewline
57 & 0.990434 & 0.0191326 & 0.0095663 \tabularnewline
58 & 0.99349 & 0.0130199 & 0.00650997 \tabularnewline
59 & 0.991488 & 0.0170247 & 0.00851233 \tabularnewline
60 & 0.989715 & 0.0205702 & 0.0102851 \tabularnewline
61 & 0.986614 & 0.0267727 & 0.0133864 \tabularnewline
62 & 0.983132 & 0.0337357 & 0.0168679 \tabularnewline
63 & 0.983517 & 0.0329655 & 0.0164828 \tabularnewline
64 & 0.980776 & 0.0384487 & 0.0192244 \tabularnewline
65 & 0.985573 & 0.0288542 & 0.0144271 \tabularnewline
66 & 0.984109 & 0.0317812 & 0.0158906 \tabularnewline
67 & 0.981177 & 0.0376456 & 0.0188228 \tabularnewline
68 & 0.977476 & 0.0450476 & 0.0225238 \tabularnewline
69 & 0.971975 & 0.0560508 & 0.0280254 \tabularnewline
70 & 0.968645 & 0.06271 & 0.031355 \tabularnewline
71 & 0.964271 & 0.0714571 & 0.0357286 \tabularnewline
72 & 0.95809 & 0.0838191 & 0.0419096 \tabularnewline
73 & 0.959927 & 0.0801468 & 0.0400734 \tabularnewline
74 & 0.955081 & 0.0898371 & 0.0449185 \tabularnewline
75 & 0.97898 & 0.0420399 & 0.0210199 \tabularnewline
76 & 0.975446 & 0.0491076 & 0.0245538 \tabularnewline
77 & 0.969457 & 0.0610856 & 0.0305428 \tabularnewline
78 & 0.96593 & 0.0681405 & 0.0340702 \tabularnewline
79 & 0.9584 & 0.0832004 & 0.0416002 \tabularnewline
80 & 0.951247 & 0.0975055 & 0.0487527 \tabularnewline
81 & 0.94477 & 0.11046 & 0.0552298 \tabularnewline
82 & 0.933779 & 0.132442 & 0.066221 \tabularnewline
83 & 0.922081 & 0.155838 & 0.0779192 \tabularnewline
84 & 0.914224 & 0.171552 & 0.0857758 \tabularnewline
85 & 0.900411 & 0.199177 & 0.0995886 \tabularnewline
86 & 0.886693 & 0.226614 & 0.113307 \tabularnewline
87 & 0.868226 & 0.263547 & 0.131774 \tabularnewline
88 & 0.850952 & 0.298097 & 0.149048 \tabularnewline
89 & 0.885937 & 0.228126 & 0.114063 \tabularnewline
90 & 0.868063 & 0.263874 & 0.131937 \tabularnewline
91 & 0.855434 & 0.289132 & 0.144566 \tabularnewline
92 & 0.908442 & 0.183116 & 0.091558 \tabularnewline
93 & 0.893194 & 0.213611 & 0.106806 \tabularnewline
94 & 0.920143 & 0.159714 & 0.0798571 \tabularnewline
95 & 0.90846 & 0.183079 & 0.0915396 \tabularnewline
96 & 0.892954 & 0.214092 & 0.107046 \tabularnewline
97 & 0.877612 & 0.244775 & 0.122388 \tabularnewline
98 & 0.864864 & 0.270272 & 0.135136 \tabularnewline
99 & 0.853605 & 0.29279 & 0.146395 \tabularnewline
100 & 0.833366 & 0.333268 & 0.166634 \tabularnewline
101 & 0.829303 & 0.341394 & 0.170697 \tabularnewline
102 & 0.805945 & 0.38811 & 0.194055 \tabularnewline
103 & 0.785355 & 0.42929 & 0.214645 \tabularnewline
104 & 0.788778 & 0.422443 & 0.211222 \tabularnewline
105 & 0.807362 & 0.385276 & 0.192638 \tabularnewline
106 & 0.820049 & 0.359902 & 0.179951 \tabularnewline
107 & 0.797788 & 0.404425 & 0.202212 \tabularnewline
108 & 0.785546 & 0.428908 & 0.214454 \tabularnewline
109 & 0.760521 & 0.478958 & 0.239479 \tabularnewline
110 & 0.7562 & 0.487599 & 0.2438 \tabularnewline
111 & 0.734911 & 0.530178 & 0.265089 \tabularnewline
112 & 0.709634 & 0.580733 & 0.290366 \tabularnewline
113 & 0.679416 & 0.641167 & 0.320584 \tabularnewline
114 & 0.674656 & 0.650687 & 0.325344 \tabularnewline
115 & 0.656103 & 0.687795 & 0.343897 \tabularnewline
116 & 0.645131 & 0.709738 & 0.354869 \tabularnewline
117 & 0.621504 & 0.756991 & 0.378496 \tabularnewline
118 & 0.694189 & 0.611622 & 0.305811 \tabularnewline
119 & 0.684937 & 0.630126 & 0.315063 \tabularnewline
120 & 0.659788 & 0.680425 & 0.340212 \tabularnewline
121 & 0.632127 & 0.735746 & 0.367873 \tabularnewline
122 & 0.603734 & 0.792532 & 0.396266 \tabularnewline
123 & 0.681954 & 0.636093 & 0.318046 \tabularnewline
124 & 0.654388 & 0.691224 & 0.345612 \tabularnewline
125 & 0.711341 & 0.577318 & 0.288659 \tabularnewline
126 & 0.686002 & 0.627996 & 0.313998 \tabularnewline
127 & 0.756371 & 0.487259 & 0.243629 \tabularnewline
128 & 0.733965 & 0.53207 & 0.266035 \tabularnewline
129 & 0.792885 & 0.41423 & 0.207115 \tabularnewline
130 & 0.768326 & 0.463348 & 0.231674 \tabularnewline
131 & 0.771232 & 0.457536 & 0.228768 \tabularnewline
132 & 0.760851 & 0.478298 & 0.239149 \tabularnewline
133 & 0.739918 & 0.520165 & 0.260082 \tabularnewline
134 & 0.748611 & 0.502778 & 0.251389 \tabularnewline
135 & 0.748345 & 0.50331 & 0.251655 \tabularnewline
136 & 0.841134 & 0.317732 & 0.158866 \tabularnewline
137 & 0.82012 & 0.359759 & 0.17988 \tabularnewline
138 & 0.805412 & 0.389175 & 0.194588 \tabularnewline
139 & 0.860663 & 0.278673 & 0.139337 \tabularnewline
140 & 0.840719 & 0.318562 & 0.159281 \tabularnewline
141 & 0.820768 & 0.358465 & 0.179232 \tabularnewline
142 & 0.828819 & 0.342362 & 0.171181 \tabularnewline
143 & 0.860918 & 0.278164 & 0.139082 \tabularnewline
144 & 0.844327 & 0.311346 & 0.155673 \tabularnewline
145 & 0.835218 & 0.329563 & 0.164782 \tabularnewline
146 & 0.818654 & 0.362692 & 0.181346 \tabularnewline
147 & 0.796078 & 0.407844 & 0.203922 \tabularnewline
148 & 0.772312 & 0.455375 & 0.227688 \tabularnewline
149 & 0.751147 & 0.497706 & 0.248853 \tabularnewline
150 & 0.730081 & 0.539838 & 0.269919 \tabularnewline
151 & 0.713575 & 0.572849 & 0.286425 \tabularnewline
152 & 0.725752 & 0.548496 & 0.274248 \tabularnewline
153 & 0.752988 & 0.494023 & 0.247012 \tabularnewline
154 & 0.729235 & 0.54153 & 0.270765 \tabularnewline
155 & 0.734757 & 0.530486 & 0.265243 \tabularnewline
156 & 0.708751 & 0.582499 & 0.291249 \tabularnewline
157 & 0.698017 & 0.603965 & 0.301983 \tabularnewline
158 & 0.677464 & 0.645073 & 0.322536 \tabularnewline
159 & 0.656638 & 0.686724 & 0.343362 \tabularnewline
160 & 0.635006 & 0.729987 & 0.364994 \tabularnewline
161 & 0.631944 & 0.736113 & 0.368056 \tabularnewline
162 & 0.618819 & 0.762361 & 0.381181 \tabularnewline
163 & 0.592374 & 0.815253 & 0.407626 \tabularnewline
164 & 0.561233 & 0.877534 & 0.438767 \tabularnewline
165 & 0.528913 & 0.942174 & 0.471087 \tabularnewline
166 & 0.557475 & 0.885049 & 0.442525 \tabularnewline
167 & 0.564311 & 0.871377 & 0.435689 \tabularnewline
168 & 0.542572 & 0.914855 & 0.457428 \tabularnewline
169 & 0.518317 & 0.963366 & 0.481683 \tabularnewline
170 & 0.546084 & 0.907831 & 0.453916 \tabularnewline
171 & 0.512005 & 0.97599 & 0.487995 \tabularnewline
172 & 0.529348 & 0.941304 & 0.470652 \tabularnewline
173 & 0.535894 & 0.928213 & 0.464106 \tabularnewline
174 & 0.555833 & 0.888333 & 0.444167 \tabularnewline
175 & 0.521064 & 0.957872 & 0.478936 \tabularnewline
176 & 0.485836 & 0.971673 & 0.514164 \tabularnewline
177 & 0.453709 & 0.907418 & 0.546291 \tabularnewline
178 & 0.460027 & 0.920054 & 0.539973 \tabularnewline
179 & 0.460123 & 0.920245 & 0.539877 \tabularnewline
180 & 0.440833 & 0.881666 & 0.559167 \tabularnewline
181 & 0.430082 & 0.860163 & 0.569918 \tabularnewline
182 & 0.442698 & 0.885396 & 0.557302 \tabularnewline
183 & 0.677449 & 0.645101 & 0.322551 \tabularnewline
184 & 0.644942 & 0.710116 & 0.355058 \tabularnewline
185 & 0.616632 & 0.766736 & 0.383368 \tabularnewline
186 & 0.611841 & 0.776318 & 0.388159 \tabularnewline
187 & 0.584981 & 0.830038 & 0.415019 \tabularnewline
188 & 0.549153 & 0.901693 & 0.450847 \tabularnewline
189 & 0.54606 & 0.90788 & 0.45394 \tabularnewline
190 & 0.521038 & 0.957923 & 0.478962 \tabularnewline
191 & 0.530731 & 0.938539 & 0.469269 \tabularnewline
192 & 0.544943 & 0.910114 & 0.455057 \tabularnewline
193 & 0.508438 & 0.983125 & 0.491562 \tabularnewline
194 & 0.472272 & 0.944545 & 0.527728 \tabularnewline
195 & 0.451868 & 0.903737 & 0.548132 \tabularnewline
196 & 0.415982 & 0.831964 & 0.584018 \tabularnewline
197 & 0.392171 & 0.784341 & 0.607829 \tabularnewline
198 & 0.395846 & 0.791692 & 0.604154 \tabularnewline
199 & 0.361766 & 0.723532 & 0.638234 \tabularnewline
200 & 0.376611 & 0.753222 & 0.623389 \tabularnewline
201 & 0.368496 & 0.736992 & 0.631504 \tabularnewline
202 & 0.415931 & 0.831862 & 0.584069 \tabularnewline
203 & 0.466163 & 0.932325 & 0.533837 \tabularnewline
204 & 0.471598 & 0.943196 & 0.528402 \tabularnewline
205 & 0.433573 & 0.867146 & 0.566427 \tabularnewline
206 & 0.4555 & 0.911001 & 0.5445 \tabularnewline
207 & 0.4421 & 0.8842 & 0.5579 \tabularnewline
208 & 0.435723 & 0.871445 & 0.564277 \tabularnewline
209 & 0.436284 & 0.872568 & 0.563716 \tabularnewline
210 & 0.789615 & 0.420769 & 0.210385 \tabularnewline
211 & 0.797218 & 0.405565 & 0.202782 \tabularnewline
212 & 0.772592 & 0.454817 & 0.227408 \tabularnewline
213 & 0.740513 & 0.518974 & 0.259487 \tabularnewline
214 & 0.744885 & 0.51023 & 0.255115 \tabularnewline
215 & 0.719813 & 0.560374 & 0.280187 \tabularnewline
216 & 0.690775 & 0.618451 & 0.309225 \tabularnewline
217 & 0.662116 & 0.675769 & 0.337884 \tabularnewline
218 & 0.623097 & 0.753805 & 0.376903 \tabularnewline
219 & 0.603318 & 0.793365 & 0.396682 \tabularnewline
220 & 0.577884 & 0.844233 & 0.422116 \tabularnewline
221 & 0.540962 & 0.918077 & 0.459038 \tabularnewline
222 & 0.497959 & 0.995919 & 0.502041 \tabularnewline
223 & 0.582572 & 0.834856 & 0.417428 \tabularnewline
224 & 0.54216 & 0.91568 & 0.45784 \tabularnewline
225 & 0.510959 & 0.978082 & 0.489041 \tabularnewline
226 & 0.480242 & 0.960483 & 0.519758 \tabularnewline
227 & 0.450429 & 0.900857 & 0.549571 \tabularnewline
228 & 0.504232 & 0.991535 & 0.495768 \tabularnewline
229 & 0.463592 & 0.927185 & 0.536408 \tabularnewline
230 & 0.487814 & 0.975627 & 0.512186 \tabularnewline
231 & 0.45201 & 0.90402 & 0.54799 \tabularnewline
232 & 0.464444 & 0.928887 & 0.535556 \tabularnewline
233 & 0.460017 & 0.920034 & 0.539983 \tabularnewline
234 & 0.445712 & 0.891424 & 0.554288 \tabularnewline
235 & 0.45107 & 0.902139 & 0.54893 \tabularnewline
236 & 0.550735 & 0.898531 & 0.449265 \tabularnewline
237 & 0.503435 & 0.99313 & 0.496565 \tabularnewline
238 & 0.56642 & 0.867159 & 0.43358 \tabularnewline
239 & 0.519162 & 0.961675 & 0.480838 \tabularnewline
240 & 0.48678 & 0.973559 & 0.51322 \tabularnewline
241 & 0.502931 & 0.994138 & 0.497069 \tabularnewline
242 & 0.50965 & 0.9807 & 0.49035 \tabularnewline
243 & 0.599733 & 0.800535 & 0.400267 \tabularnewline
244 & 0.55027 & 0.899459 & 0.44973 \tabularnewline
245 & 0.556156 & 0.887689 & 0.443844 \tabularnewline
246 & 0.544281 & 0.911437 & 0.455719 \tabularnewline
247 & 0.497054 & 0.994107 & 0.502946 \tabularnewline
248 & 0.44941 & 0.898819 & 0.55059 \tabularnewline
249 & 0.506454 & 0.987092 & 0.493546 \tabularnewline
250 & 0.447827 & 0.895653 & 0.552173 \tabularnewline
251 & 0.389684 & 0.779369 & 0.610316 \tabularnewline
252 & 0.424124 & 0.848248 & 0.575876 \tabularnewline
253 & 0.408207 & 0.816413 & 0.591793 \tabularnewline
254 & 0.396244 & 0.792487 & 0.603756 \tabularnewline
255 & 0.483724 & 0.967449 & 0.516276 \tabularnewline
256 & 0.468545 & 0.93709 & 0.531455 \tabularnewline
257 & 0.434844 & 0.869688 & 0.565156 \tabularnewline
258 & 0.548974 & 0.902053 & 0.451026 \tabularnewline
259 & 0.777822 & 0.444356 & 0.222178 \tabularnewline
260 & 0.75828 & 0.483439 & 0.24172 \tabularnewline
261 & 0.690869 & 0.618262 & 0.309131 \tabularnewline
262 & 0.624634 & 0.750732 & 0.375366 \tabularnewline
263 & 0.54715 & 0.905701 & 0.45285 \tabularnewline
264 & 0.690257 & 0.619486 & 0.309743 \tabularnewline
265 & 0.712887 & 0.574226 & 0.287113 \tabularnewline
266 & 0.699802 & 0.600395 & 0.300198 \tabularnewline
267 & 0.700782 & 0.598435 & 0.299218 \tabularnewline
268 & 0.605939 & 0.788121 & 0.394061 \tabularnewline
269 & 0.558522 & 0.882955 & 0.441478 \tabularnewline
270 & 0.462663 & 0.925325 & 0.537337 \tabularnewline
271 & 0.430358 & 0.860715 & 0.569642 \tabularnewline
272 & 0.641749 & 0.716502 & 0.358251 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267881&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]7[/C][C]0.728799[/C][C]0.542403[/C][C]0.271201[/C][/ROW]
[ROW][C]8[/C][C]0.584943[/C][C]0.830114[/C][C]0.415057[/C][/ROW]
[ROW][C]9[/C][C]0.727294[/C][C]0.545412[/C][C]0.272706[/C][/ROW]
[ROW][C]10[/C][C]0.639636[/C][C]0.720728[/C][C]0.360364[/C][/ROW]
[ROW][C]11[/C][C]0.565748[/C][C]0.868503[/C][C]0.434252[/C][/ROW]
[ROW][C]12[/C][C]0.548278[/C][C]0.903444[/C][C]0.451722[/C][/ROW]
[ROW][C]13[/C][C]0.445843[/C][C]0.891686[/C][C]0.554157[/C][/ROW]
[ROW][C]14[/C][C]0.44895[/C][C]0.897899[/C][C]0.55105[/C][/ROW]
[ROW][C]15[/C][C]0.835004[/C][C]0.329992[/C][C]0.164996[/C][/ROW]
[ROW][C]16[/C][C]0.825364[/C][C]0.349272[/C][C]0.174636[/C][/ROW]
[ROW][C]17[/C][C]0.849003[/C][C]0.301995[/C][C]0.150997[/C][/ROW]
[ROW][C]18[/C][C]0.800905[/C][C]0.398191[/C][C]0.199095[/C][/ROW]
[ROW][C]19[/C][C]0.819763[/C][C]0.360474[/C][C]0.180237[/C][/ROW]
[ROW][C]20[/C][C]0.776125[/C][C]0.44775[/C][C]0.223875[/C][/ROW]
[ROW][C]21[/C][C]0.829643[/C][C]0.340715[/C][C]0.170357[/C][/ROW]
[ROW][C]22[/C][C]0.825007[/C][C]0.349986[/C][C]0.174993[/C][/ROW]
[ROW][C]23[/C][C]0.780345[/C][C]0.43931[/C][C]0.219655[/C][/ROW]
[ROW][C]24[/C][C]0.730977[/C][C]0.538047[/C][C]0.269023[/C][/ROW]
[ROW][C]25[/C][C]0.784604[/C][C]0.430792[/C][C]0.215396[/C][/ROW]
[ROW][C]26[/C][C]0.739625[/C][C]0.520751[/C][C]0.260375[/C][/ROW]
[ROW][C]27[/C][C]0.802603[/C][C]0.394794[/C][C]0.197397[/C][/ROW]
[ROW][C]28[/C][C]0.803979[/C][C]0.392042[/C][C]0.196021[/C][/ROW]
[ROW][C]29[/C][C]0.762993[/C][C]0.474015[/C][C]0.237007[/C][/ROW]
[ROW][C]30[/C][C]0.735564[/C][C]0.528871[/C][C]0.264436[/C][/ROW]
[ROW][C]31[/C][C]0.705391[/C][C]0.589219[/C][C]0.294609[/C][/ROW]
[ROW][C]32[/C][C]0.680229[/C][C]0.639543[/C][C]0.319771[/C][/ROW]
[ROW][C]33[/C][C]0.642429[/C][C]0.715142[/C][C]0.357571[/C][/ROW]
[ROW][C]34[/C][C]0.735117[/C][C]0.529767[/C][C]0.264883[/C][/ROW]
[ROW][C]35[/C][C]0.704881[/C][C]0.590238[/C][C]0.295119[/C][/ROW]
[ROW][C]36[/C][C]0.852056[/C][C]0.295888[/C][C]0.147944[/C][/ROW]
[ROW][C]37[/C][C]0.964121[/C][C]0.0717578[/C][C]0.0358789[/C][/ROW]
[ROW][C]38[/C][C]0.965089[/C][C]0.0698229[/C][C]0.0349114[/C][/ROW]
[ROW][C]39[/C][C]0.954698[/C][C]0.0906035[/C][C]0.0453017[/C][/ROW]
[ROW][C]40[/C][C]0.979871[/C][C]0.0402572[/C][C]0.0201286[/C][/ROW]
[ROW][C]41[/C][C]0.975574[/C][C]0.048853[/C][C]0.0244265[/C][/ROW]
[ROW][C]42[/C][C]0.96894[/C][C]0.0621193[/C][C]0.0310596[/C][/ROW]
[ROW][C]43[/C][C]0.985662[/C][C]0.028676[/C][C]0.014338[/C][/ROW]
[ROW][C]44[/C][C]0.984063[/C][C]0.0318741[/C][C]0.0159371[/C][/ROW]
[ROW][C]45[/C][C]0.979855[/C][C]0.0402906[/C][C]0.0201453[/C][/ROW]
[ROW][C]46[/C][C]0.992614[/C][C]0.0147727[/C][C]0.00738636[/C][/ROW]
[ROW][C]47[/C][C]0.990952[/C][C]0.0180969[/C][C]0.00904846[/C][/ROW]
[ROW][C]48[/C][C]0.988663[/C][C]0.022674[/C][C]0.011337[/C][/ROW]
[ROW][C]49[/C][C]0.990018[/C][C]0.019965[/C][C]0.00998249[/C][/ROW]
[ROW][C]50[/C][C]0.986938[/C][C]0.0261248[/C][C]0.0130624[/C][/ROW]
[ROW][C]51[/C][C]0.982908[/C][C]0.0341847[/C][C]0.0170924[/C][/ROW]
[ROW][C]52[/C][C]0.987732[/C][C]0.0245353[/C][C]0.0122676[/C][/ROW]
[ROW][C]53[/C][C]0.985375[/C][C]0.0292506[/C][C]0.0146253[/C][/ROW]
[ROW][C]54[/C][C]0.984517[/C][C]0.0309665[/C][C]0.0154832[/C][/ROW]
[ROW][C]55[/C][C]0.986838[/C][C]0.0263248[/C][C]0.0131624[/C][/ROW]
[ROW][C]56[/C][C]0.983835[/C][C]0.032329[/C][C]0.0161645[/C][/ROW]
[ROW][C]57[/C][C]0.990434[/C][C]0.0191326[/C][C]0.0095663[/C][/ROW]
[ROW][C]58[/C][C]0.99349[/C][C]0.0130199[/C][C]0.00650997[/C][/ROW]
[ROW][C]59[/C][C]0.991488[/C][C]0.0170247[/C][C]0.00851233[/C][/ROW]
[ROW][C]60[/C][C]0.989715[/C][C]0.0205702[/C][C]0.0102851[/C][/ROW]
[ROW][C]61[/C][C]0.986614[/C][C]0.0267727[/C][C]0.0133864[/C][/ROW]
[ROW][C]62[/C][C]0.983132[/C][C]0.0337357[/C][C]0.0168679[/C][/ROW]
[ROW][C]63[/C][C]0.983517[/C][C]0.0329655[/C][C]0.0164828[/C][/ROW]
[ROW][C]64[/C][C]0.980776[/C][C]0.0384487[/C][C]0.0192244[/C][/ROW]
[ROW][C]65[/C][C]0.985573[/C][C]0.0288542[/C][C]0.0144271[/C][/ROW]
[ROW][C]66[/C][C]0.984109[/C][C]0.0317812[/C][C]0.0158906[/C][/ROW]
[ROW][C]67[/C][C]0.981177[/C][C]0.0376456[/C][C]0.0188228[/C][/ROW]
[ROW][C]68[/C][C]0.977476[/C][C]0.0450476[/C][C]0.0225238[/C][/ROW]
[ROW][C]69[/C][C]0.971975[/C][C]0.0560508[/C][C]0.0280254[/C][/ROW]
[ROW][C]70[/C][C]0.968645[/C][C]0.06271[/C][C]0.031355[/C][/ROW]
[ROW][C]71[/C][C]0.964271[/C][C]0.0714571[/C][C]0.0357286[/C][/ROW]
[ROW][C]72[/C][C]0.95809[/C][C]0.0838191[/C][C]0.0419096[/C][/ROW]
[ROW][C]73[/C][C]0.959927[/C][C]0.0801468[/C][C]0.0400734[/C][/ROW]
[ROW][C]74[/C][C]0.955081[/C][C]0.0898371[/C][C]0.0449185[/C][/ROW]
[ROW][C]75[/C][C]0.97898[/C][C]0.0420399[/C][C]0.0210199[/C][/ROW]
[ROW][C]76[/C][C]0.975446[/C][C]0.0491076[/C][C]0.0245538[/C][/ROW]
[ROW][C]77[/C][C]0.969457[/C][C]0.0610856[/C][C]0.0305428[/C][/ROW]
[ROW][C]78[/C][C]0.96593[/C][C]0.0681405[/C][C]0.0340702[/C][/ROW]
[ROW][C]79[/C][C]0.9584[/C][C]0.0832004[/C][C]0.0416002[/C][/ROW]
[ROW][C]80[/C][C]0.951247[/C][C]0.0975055[/C][C]0.0487527[/C][/ROW]
[ROW][C]81[/C][C]0.94477[/C][C]0.11046[/C][C]0.0552298[/C][/ROW]
[ROW][C]82[/C][C]0.933779[/C][C]0.132442[/C][C]0.066221[/C][/ROW]
[ROW][C]83[/C][C]0.922081[/C][C]0.155838[/C][C]0.0779192[/C][/ROW]
[ROW][C]84[/C][C]0.914224[/C][C]0.171552[/C][C]0.0857758[/C][/ROW]
[ROW][C]85[/C][C]0.900411[/C][C]0.199177[/C][C]0.0995886[/C][/ROW]
[ROW][C]86[/C][C]0.886693[/C][C]0.226614[/C][C]0.113307[/C][/ROW]
[ROW][C]87[/C][C]0.868226[/C][C]0.263547[/C][C]0.131774[/C][/ROW]
[ROW][C]88[/C][C]0.850952[/C][C]0.298097[/C][C]0.149048[/C][/ROW]
[ROW][C]89[/C][C]0.885937[/C][C]0.228126[/C][C]0.114063[/C][/ROW]
[ROW][C]90[/C][C]0.868063[/C][C]0.263874[/C][C]0.131937[/C][/ROW]
[ROW][C]91[/C][C]0.855434[/C][C]0.289132[/C][C]0.144566[/C][/ROW]
[ROW][C]92[/C][C]0.908442[/C][C]0.183116[/C][C]0.091558[/C][/ROW]
[ROW][C]93[/C][C]0.893194[/C][C]0.213611[/C][C]0.106806[/C][/ROW]
[ROW][C]94[/C][C]0.920143[/C][C]0.159714[/C][C]0.0798571[/C][/ROW]
[ROW][C]95[/C][C]0.90846[/C][C]0.183079[/C][C]0.0915396[/C][/ROW]
[ROW][C]96[/C][C]0.892954[/C][C]0.214092[/C][C]0.107046[/C][/ROW]
[ROW][C]97[/C][C]0.877612[/C][C]0.244775[/C][C]0.122388[/C][/ROW]
[ROW][C]98[/C][C]0.864864[/C][C]0.270272[/C][C]0.135136[/C][/ROW]
[ROW][C]99[/C][C]0.853605[/C][C]0.29279[/C][C]0.146395[/C][/ROW]
[ROW][C]100[/C][C]0.833366[/C][C]0.333268[/C][C]0.166634[/C][/ROW]
[ROW][C]101[/C][C]0.829303[/C][C]0.341394[/C][C]0.170697[/C][/ROW]
[ROW][C]102[/C][C]0.805945[/C][C]0.38811[/C][C]0.194055[/C][/ROW]
[ROW][C]103[/C][C]0.785355[/C][C]0.42929[/C][C]0.214645[/C][/ROW]
[ROW][C]104[/C][C]0.788778[/C][C]0.422443[/C][C]0.211222[/C][/ROW]
[ROW][C]105[/C][C]0.807362[/C][C]0.385276[/C][C]0.192638[/C][/ROW]
[ROW][C]106[/C][C]0.820049[/C][C]0.359902[/C][C]0.179951[/C][/ROW]
[ROW][C]107[/C][C]0.797788[/C][C]0.404425[/C][C]0.202212[/C][/ROW]
[ROW][C]108[/C][C]0.785546[/C][C]0.428908[/C][C]0.214454[/C][/ROW]
[ROW][C]109[/C][C]0.760521[/C][C]0.478958[/C][C]0.239479[/C][/ROW]
[ROW][C]110[/C][C]0.7562[/C][C]0.487599[/C][C]0.2438[/C][/ROW]
[ROW][C]111[/C][C]0.734911[/C][C]0.530178[/C][C]0.265089[/C][/ROW]
[ROW][C]112[/C][C]0.709634[/C][C]0.580733[/C][C]0.290366[/C][/ROW]
[ROW][C]113[/C][C]0.679416[/C][C]0.641167[/C][C]0.320584[/C][/ROW]
[ROW][C]114[/C][C]0.674656[/C][C]0.650687[/C][C]0.325344[/C][/ROW]
[ROW][C]115[/C][C]0.656103[/C][C]0.687795[/C][C]0.343897[/C][/ROW]
[ROW][C]116[/C][C]0.645131[/C][C]0.709738[/C][C]0.354869[/C][/ROW]
[ROW][C]117[/C][C]0.621504[/C][C]0.756991[/C][C]0.378496[/C][/ROW]
[ROW][C]118[/C][C]0.694189[/C][C]0.611622[/C][C]0.305811[/C][/ROW]
[ROW][C]119[/C][C]0.684937[/C][C]0.630126[/C][C]0.315063[/C][/ROW]
[ROW][C]120[/C][C]0.659788[/C][C]0.680425[/C][C]0.340212[/C][/ROW]
[ROW][C]121[/C][C]0.632127[/C][C]0.735746[/C][C]0.367873[/C][/ROW]
[ROW][C]122[/C][C]0.603734[/C][C]0.792532[/C][C]0.396266[/C][/ROW]
[ROW][C]123[/C][C]0.681954[/C][C]0.636093[/C][C]0.318046[/C][/ROW]
[ROW][C]124[/C][C]0.654388[/C][C]0.691224[/C][C]0.345612[/C][/ROW]
[ROW][C]125[/C][C]0.711341[/C][C]0.577318[/C][C]0.288659[/C][/ROW]
[ROW][C]126[/C][C]0.686002[/C][C]0.627996[/C][C]0.313998[/C][/ROW]
[ROW][C]127[/C][C]0.756371[/C][C]0.487259[/C][C]0.243629[/C][/ROW]
[ROW][C]128[/C][C]0.733965[/C][C]0.53207[/C][C]0.266035[/C][/ROW]
[ROW][C]129[/C][C]0.792885[/C][C]0.41423[/C][C]0.207115[/C][/ROW]
[ROW][C]130[/C][C]0.768326[/C][C]0.463348[/C][C]0.231674[/C][/ROW]
[ROW][C]131[/C][C]0.771232[/C][C]0.457536[/C][C]0.228768[/C][/ROW]
[ROW][C]132[/C][C]0.760851[/C][C]0.478298[/C][C]0.239149[/C][/ROW]
[ROW][C]133[/C][C]0.739918[/C][C]0.520165[/C][C]0.260082[/C][/ROW]
[ROW][C]134[/C][C]0.748611[/C][C]0.502778[/C][C]0.251389[/C][/ROW]
[ROW][C]135[/C][C]0.748345[/C][C]0.50331[/C][C]0.251655[/C][/ROW]
[ROW][C]136[/C][C]0.841134[/C][C]0.317732[/C][C]0.158866[/C][/ROW]
[ROW][C]137[/C][C]0.82012[/C][C]0.359759[/C][C]0.17988[/C][/ROW]
[ROW][C]138[/C][C]0.805412[/C][C]0.389175[/C][C]0.194588[/C][/ROW]
[ROW][C]139[/C][C]0.860663[/C][C]0.278673[/C][C]0.139337[/C][/ROW]
[ROW][C]140[/C][C]0.840719[/C][C]0.318562[/C][C]0.159281[/C][/ROW]
[ROW][C]141[/C][C]0.820768[/C][C]0.358465[/C][C]0.179232[/C][/ROW]
[ROW][C]142[/C][C]0.828819[/C][C]0.342362[/C][C]0.171181[/C][/ROW]
[ROW][C]143[/C][C]0.860918[/C][C]0.278164[/C][C]0.139082[/C][/ROW]
[ROW][C]144[/C][C]0.844327[/C][C]0.311346[/C][C]0.155673[/C][/ROW]
[ROW][C]145[/C][C]0.835218[/C][C]0.329563[/C][C]0.164782[/C][/ROW]
[ROW][C]146[/C][C]0.818654[/C][C]0.362692[/C][C]0.181346[/C][/ROW]
[ROW][C]147[/C][C]0.796078[/C][C]0.407844[/C][C]0.203922[/C][/ROW]
[ROW][C]148[/C][C]0.772312[/C][C]0.455375[/C][C]0.227688[/C][/ROW]
[ROW][C]149[/C][C]0.751147[/C][C]0.497706[/C][C]0.248853[/C][/ROW]
[ROW][C]150[/C][C]0.730081[/C][C]0.539838[/C][C]0.269919[/C][/ROW]
[ROW][C]151[/C][C]0.713575[/C][C]0.572849[/C][C]0.286425[/C][/ROW]
[ROW][C]152[/C][C]0.725752[/C][C]0.548496[/C][C]0.274248[/C][/ROW]
[ROW][C]153[/C][C]0.752988[/C][C]0.494023[/C][C]0.247012[/C][/ROW]
[ROW][C]154[/C][C]0.729235[/C][C]0.54153[/C][C]0.270765[/C][/ROW]
[ROW][C]155[/C][C]0.734757[/C][C]0.530486[/C][C]0.265243[/C][/ROW]
[ROW][C]156[/C][C]0.708751[/C][C]0.582499[/C][C]0.291249[/C][/ROW]
[ROW][C]157[/C][C]0.698017[/C][C]0.603965[/C][C]0.301983[/C][/ROW]
[ROW][C]158[/C][C]0.677464[/C][C]0.645073[/C][C]0.322536[/C][/ROW]
[ROW][C]159[/C][C]0.656638[/C][C]0.686724[/C][C]0.343362[/C][/ROW]
[ROW][C]160[/C][C]0.635006[/C][C]0.729987[/C][C]0.364994[/C][/ROW]
[ROW][C]161[/C][C]0.631944[/C][C]0.736113[/C][C]0.368056[/C][/ROW]
[ROW][C]162[/C][C]0.618819[/C][C]0.762361[/C][C]0.381181[/C][/ROW]
[ROW][C]163[/C][C]0.592374[/C][C]0.815253[/C][C]0.407626[/C][/ROW]
[ROW][C]164[/C][C]0.561233[/C][C]0.877534[/C][C]0.438767[/C][/ROW]
[ROW][C]165[/C][C]0.528913[/C][C]0.942174[/C][C]0.471087[/C][/ROW]
[ROW][C]166[/C][C]0.557475[/C][C]0.885049[/C][C]0.442525[/C][/ROW]
[ROW][C]167[/C][C]0.564311[/C][C]0.871377[/C][C]0.435689[/C][/ROW]
[ROW][C]168[/C][C]0.542572[/C][C]0.914855[/C][C]0.457428[/C][/ROW]
[ROW][C]169[/C][C]0.518317[/C][C]0.963366[/C][C]0.481683[/C][/ROW]
[ROW][C]170[/C][C]0.546084[/C][C]0.907831[/C][C]0.453916[/C][/ROW]
[ROW][C]171[/C][C]0.512005[/C][C]0.97599[/C][C]0.487995[/C][/ROW]
[ROW][C]172[/C][C]0.529348[/C][C]0.941304[/C][C]0.470652[/C][/ROW]
[ROW][C]173[/C][C]0.535894[/C][C]0.928213[/C][C]0.464106[/C][/ROW]
[ROW][C]174[/C][C]0.555833[/C][C]0.888333[/C][C]0.444167[/C][/ROW]
[ROW][C]175[/C][C]0.521064[/C][C]0.957872[/C][C]0.478936[/C][/ROW]
[ROW][C]176[/C][C]0.485836[/C][C]0.971673[/C][C]0.514164[/C][/ROW]
[ROW][C]177[/C][C]0.453709[/C][C]0.907418[/C][C]0.546291[/C][/ROW]
[ROW][C]178[/C][C]0.460027[/C][C]0.920054[/C][C]0.539973[/C][/ROW]
[ROW][C]179[/C][C]0.460123[/C][C]0.920245[/C][C]0.539877[/C][/ROW]
[ROW][C]180[/C][C]0.440833[/C][C]0.881666[/C][C]0.559167[/C][/ROW]
[ROW][C]181[/C][C]0.430082[/C][C]0.860163[/C][C]0.569918[/C][/ROW]
[ROW][C]182[/C][C]0.442698[/C][C]0.885396[/C][C]0.557302[/C][/ROW]
[ROW][C]183[/C][C]0.677449[/C][C]0.645101[/C][C]0.322551[/C][/ROW]
[ROW][C]184[/C][C]0.644942[/C][C]0.710116[/C][C]0.355058[/C][/ROW]
[ROW][C]185[/C][C]0.616632[/C][C]0.766736[/C][C]0.383368[/C][/ROW]
[ROW][C]186[/C][C]0.611841[/C][C]0.776318[/C][C]0.388159[/C][/ROW]
[ROW][C]187[/C][C]0.584981[/C][C]0.830038[/C][C]0.415019[/C][/ROW]
[ROW][C]188[/C][C]0.549153[/C][C]0.901693[/C][C]0.450847[/C][/ROW]
[ROW][C]189[/C][C]0.54606[/C][C]0.90788[/C][C]0.45394[/C][/ROW]
[ROW][C]190[/C][C]0.521038[/C][C]0.957923[/C][C]0.478962[/C][/ROW]
[ROW][C]191[/C][C]0.530731[/C][C]0.938539[/C][C]0.469269[/C][/ROW]
[ROW][C]192[/C][C]0.544943[/C][C]0.910114[/C][C]0.455057[/C][/ROW]
[ROW][C]193[/C][C]0.508438[/C][C]0.983125[/C][C]0.491562[/C][/ROW]
[ROW][C]194[/C][C]0.472272[/C][C]0.944545[/C][C]0.527728[/C][/ROW]
[ROW][C]195[/C][C]0.451868[/C][C]0.903737[/C][C]0.548132[/C][/ROW]
[ROW][C]196[/C][C]0.415982[/C][C]0.831964[/C][C]0.584018[/C][/ROW]
[ROW][C]197[/C][C]0.392171[/C][C]0.784341[/C][C]0.607829[/C][/ROW]
[ROW][C]198[/C][C]0.395846[/C][C]0.791692[/C][C]0.604154[/C][/ROW]
[ROW][C]199[/C][C]0.361766[/C][C]0.723532[/C][C]0.638234[/C][/ROW]
[ROW][C]200[/C][C]0.376611[/C][C]0.753222[/C][C]0.623389[/C][/ROW]
[ROW][C]201[/C][C]0.368496[/C][C]0.736992[/C][C]0.631504[/C][/ROW]
[ROW][C]202[/C][C]0.415931[/C][C]0.831862[/C][C]0.584069[/C][/ROW]
[ROW][C]203[/C][C]0.466163[/C][C]0.932325[/C][C]0.533837[/C][/ROW]
[ROW][C]204[/C][C]0.471598[/C][C]0.943196[/C][C]0.528402[/C][/ROW]
[ROW][C]205[/C][C]0.433573[/C][C]0.867146[/C][C]0.566427[/C][/ROW]
[ROW][C]206[/C][C]0.4555[/C][C]0.911001[/C][C]0.5445[/C][/ROW]
[ROW][C]207[/C][C]0.4421[/C][C]0.8842[/C][C]0.5579[/C][/ROW]
[ROW][C]208[/C][C]0.435723[/C][C]0.871445[/C][C]0.564277[/C][/ROW]
[ROW][C]209[/C][C]0.436284[/C][C]0.872568[/C][C]0.563716[/C][/ROW]
[ROW][C]210[/C][C]0.789615[/C][C]0.420769[/C][C]0.210385[/C][/ROW]
[ROW][C]211[/C][C]0.797218[/C][C]0.405565[/C][C]0.202782[/C][/ROW]
[ROW][C]212[/C][C]0.772592[/C][C]0.454817[/C][C]0.227408[/C][/ROW]
[ROW][C]213[/C][C]0.740513[/C][C]0.518974[/C][C]0.259487[/C][/ROW]
[ROW][C]214[/C][C]0.744885[/C][C]0.51023[/C][C]0.255115[/C][/ROW]
[ROW][C]215[/C][C]0.719813[/C][C]0.560374[/C][C]0.280187[/C][/ROW]
[ROW][C]216[/C][C]0.690775[/C][C]0.618451[/C][C]0.309225[/C][/ROW]
[ROW][C]217[/C][C]0.662116[/C][C]0.675769[/C][C]0.337884[/C][/ROW]
[ROW][C]218[/C][C]0.623097[/C][C]0.753805[/C][C]0.376903[/C][/ROW]
[ROW][C]219[/C][C]0.603318[/C][C]0.793365[/C][C]0.396682[/C][/ROW]
[ROW][C]220[/C][C]0.577884[/C][C]0.844233[/C][C]0.422116[/C][/ROW]
[ROW][C]221[/C][C]0.540962[/C][C]0.918077[/C][C]0.459038[/C][/ROW]
[ROW][C]222[/C][C]0.497959[/C][C]0.995919[/C][C]0.502041[/C][/ROW]
[ROW][C]223[/C][C]0.582572[/C][C]0.834856[/C][C]0.417428[/C][/ROW]
[ROW][C]224[/C][C]0.54216[/C][C]0.91568[/C][C]0.45784[/C][/ROW]
[ROW][C]225[/C][C]0.510959[/C][C]0.978082[/C][C]0.489041[/C][/ROW]
[ROW][C]226[/C][C]0.480242[/C][C]0.960483[/C][C]0.519758[/C][/ROW]
[ROW][C]227[/C][C]0.450429[/C][C]0.900857[/C][C]0.549571[/C][/ROW]
[ROW][C]228[/C][C]0.504232[/C][C]0.991535[/C][C]0.495768[/C][/ROW]
[ROW][C]229[/C][C]0.463592[/C][C]0.927185[/C][C]0.536408[/C][/ROW]
[ROW][C]230[/C][C]0.487814[/C][C]0.975627[/C][C]0.512186[/C][/ROW]
[ROW][C]231[/C][C]0.45201[/C][C]0.90402[/C][C]0.54799[/C][/ROW]
[ROW][C]232[/C][C]0.464444[/C][C]0.928887[/C][C]0.535556[/C][/ROW]
[ROW][C]233[/C][C]0.460017[/C][C]0.920034[/C][C]0.539983[/C][/ROW]
[ROW][C]234[/C][C]0.445712[/C][C]0.891424[/C][C]0.554288[/C][/ROW]
[ROW][C]235[/C][C]0.45107[/C][C]0.902139[/C][C]0.54893[/C][/ROW]
[ROW][C]236[/C][C]0.550735[/C][C]0.898531[/C][C]0.449265[/C][/ROW]
[ROW][C]237[/C][C]0.503435[/C][C]0.99313[/C][C]0.496565[/C][/ROW]
[ROW][C]238[/C][C]0.56642[/C][C]0.867159[/C][C]0.43358[/C][/ROW]
[ROW][C]239[/C][C]0.519162[/C][C]0.961675[/C][C]0.480838[/C][/ROW]
[ROW][C]240[/C][C]0.48678[/C][C]0.973559[/C][C]0.51322[/C][/ROW]
[ROW][C]241[/C][C]0.502931[/C][C]0.994138[/C][C]0.497069[/C][/ROW]
[ROW][C]242[/C][C]0.50965[/C][C]0.9807[/C][C]0.49035[/C][/ROW]
[ROW][C]243[/C][C]0.599733[/C][C]0.800535[/C][C]0.400267[/C][/ROW]
[ROW][C]244[/C][C]0.55027[/C][C]0.899459[/C][C]0.44973[/C][/ROW]
[ROW][C]245[/C][C]0.556156[/C][C]0.887689[/C][C]0.443844[/C][/ROW]
[ROW][C]246[/C][C]0.544281[/C][C]0.911437[/C][C]0.455719[/C][/ROW]
[ROW][C]247[/C][C]0.497054[/C][C]0.994107[/C][C]0.502946[/C][/ROW]
[ROW][C]248[/C][C]0.44941[/C][C]0.898819[/C][C]0.55059[/C][/ROW]
[ROW][C]249[/C][C]0.506454[/C][C]0.987092[/C][C]0.493546[/C][/ROW]
[ROW][C]250[/C][C]0.447827[/C][C]0.895653[/C][C]0.552173[/C][/ROW]
[ROW][C]251[/C][C]0.389684[/C][C]0.779369[/C][C]0.610316[/C][/ROW]
[ROW][C]252[/C][C]0.424124[/C][C]0.848248[/C][C]0.575876[/C][/ROW]
[ROW][C]253[/C][C]0.408207[/C][C]0.816413[/C][C]0.591793[/C][/ROW]
[ROW][C]254[/C][C]0.396244[/C][C]0.792487[/C][C]0.603756[/C][/ROW]
[ROW][C]255[/C][C]0.483724[/C][C]0.967449[/C][C]0.516276[/C][/ROW]
[ROW][C]256[/C][C]0.468545[/C][C]0.93709[/C][C]0.531455[/C][/ROW]
[ROW][C]257[/C][C]0.434844[/C][C]0.869688[/C][C]0.565156[/C][/ROW]
[ROW][C]258[/C][C]0.548974[/C][C]0.902053[/C][C]0.451026[/C][/ROW]
[ROW][C]259[/C][C]0.777822[/C][C]0.444356[/C][C]0.222178[/C][/ROW]
[ROW][C]260[/C][C]0.75828[/C][C]0.483439[/C][C]0.24172[/C][/ROW]
[ROW][C]261[/C][C]0.690869[/C][C]0.618262[/C][C]0.309131[/C][/ROW]
[ROW][C]262[/C][C]0.624634[/C][C]0.750732[/C][C]0.375366[/C][/ROW]
[ROW][C]263[/C][C]0.54715[/C][C]0.905701[/C][C]0.45285[/C][/ROW]
[ROW][C]264[/C][C]0.690257[/C][C]0.619486[/C][C]0.309743[/C][/ROW]
[ROW][C]265[/C][C]0.712887[/C][C]0.574226[/C][C]0.287113[/C][/ROW]
[ROW][C]266[/C][C]0.699802[/C][C]0.600395[/C][C]0.300198[/C][/ROW]
[ROW][C]267[/C][C]0.700782[/C][C]0.598435[/C][C]0.299218[/C][/ROW]
[ROW][C]268[/C][C]0.605939[/C][C]0.788121[/C][C]0.394061[/C][/ROW]
[ROW][C]269[/C][C]0.558522[/C][C]0.882955[/C][C]0.441478[/C][/ROW]
[ROW][C]270[/C][C]0.462663[/C][C]0.925325[/C][C]0.537337[/C][/ROW]
[ROW][C]271[/C][C]0.430358[/C][C]0.860715[/C][C]0.569642[/C][/ROW]
[ROW][C]272[/C][C]0.641749[/C][C]0.716502[/C][C]0.358251[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267881&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267881&T=5

As an alternative you can also use a QR Code:  
QR Code


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.7287990.5424030.271201
80.5849430.8301140.415057
90.7272940.5454120.272706
100.6396360.7207280.360364
110.5657480.8685030.434252
120.5482780.9034440.451722
130.4458430.8916860.554157
140.448950.8978990.55105
150.8350040.3299920.164996
160.8253640.3492720.174636
170.8490030.3019950.150997
180.8009050.3981910.199095
190.8197630.3604740.180237
200.7761250.447750.223875
210.8296430.3407150.170357
220.8250070.3499860.174993
230.7803450.439310.219655
240.7309770.5380470.269023
250.7846040.4307920.215396
260.7396250.5207510.260375
270.8026030.3947940.197397
280.8039790.3920420.196021
290.7629930.4740150.237007
300.7355640.5288710.264436
310.7053910.5892190.294609
320.6802290.6395430.319771
330.6424290.7151420.357571
340.7351170.5297670.264883
350.7048810.5902380.295119
360.8520560.2958880.147944
370.9641210.07175780.0358789
380.9650890.06982290.0349114
390.9546980.09060350.0453017
400.9798710.04025720.0201286
410.9755740.0488530.0244265
420.968940.06211930.0310596
430.9856620.0286760.014338
440.9840630.03187410.0159371
450.9798550.04029060.0201453
460.9926140.01477270.00738636
470.9909520.01809690.00904846
480.9886630.0226740.011337
490.9900180.0199650.00998249
500.9869380.02612480.0130624
510.9829080.03418470.0170924
520.9877320.02453530.0122676
530.9853750.02925060.0146253
540.9845170.03096650.0154832
550.9868380.02632480.0131624
560.9838350.0323290.0161645
570.9904340.01913260.0095663
580.993490.01301990.00650997
590.9914880.01702470.00851233
600.9897150.02057020.0102851
610.9866140.02677270.0133864
620.9831320.03373570.0168679
630.9835170.03296550.0164828
640.9807760.03844870.0192244
650.9855730.02885420.0144271
660.9841090.03178120.0158906
670.9811770.03764560.0188228
680.9774760.04504760.0225238
690.9719750.05605080.0280254
700.9686450.062710.031355
710.9642710.07145710.0357286
720.958090.08381910.0419096
730.9599270.08014680.0400734
740.9550810.08983710.0449185
750.978980.04203990.0210199
760.9754460.04910760.0245538
770.9694570.06108560.0305428
780.965930.06814050.0340702
790.95840.08320040.0416002
800.9512470.09750550.0487527
810.944770.110460.0552298
820.9337790.1324420.066221
830.9220810.1558380.0779192
840.9142240.1715520.0857758
850.9004110.1991770.0995886
860.8866930.2266140.113307
870.8682260.2635470.131774
880.8509520.2980970.149048
890.8859370.2281260.114063
900.8680630.2638740.131937
910.8554340.2891320.144566
920.9084420.1831160.091558
930.8931940.2136110.106806
940.9201430.1597140.0798571
950.908460.1830790.0915396
960.8929540.2140920.107046
970.8776120.2447750.122388
980.8648640.2702720.135136
990.8536050.292790.146395
1000.8333660.3332680.166634
1010.8293030.3413940.170697
1020.8059450.388110.194055
1030.7853550.429290.214645
1040.7887780.4224430.211222
1050.8073620.3852760.192638
1060.8200490.3599020.179951
1070.7977880.4044250.202212
1080.7855460.4289080.214454
1090.7605210.4789580.239479
1100.75620.4875990.2438
1110.7349110.5301780.265089
1120.7096340.5807330.290366
1130.6794160.6411670.320584
1140.6746560.6506870.325344
1150.6561030.6877950.343897
1160.6451310.7097380.354869
1170.6215040.7569910.378496
1180.6941890.6116220.305811
1190.6849370.6301260.315063
1200.6597880.6804250.340212
1210.6321270.7357460.367873
1220.6037340.7925320.396266
1230.6819540.6360930.318046
1240.6543880.6912240.345612
1250.7113410.5773180.288659
1260.6860020.6279960.313998
1270.7563710.4872590.243629
1280.7339650.532070.266035
1290.7928850.414230.207115
1300.7683260.4633480.231674
1310.7712320.4575360.228768
1320.7608510.4782980.239149
1330.7399180.5201650.260082
1340.7486110.5027780.251389
1350.7483450.503310.251655
1360.8411340.3177320.158866
1370.820120.3597590.17988
1380.8054120.3891750.194588
1390.8606630.2786730.139337
1400.8407190.3185620.159281
1410.8207680.3584650.179232
1420.8288190.3423620.171181
1430.8609180.2781640.139082
1440.8443270.3113460.155673
1450.8352180.3295630.164782
1460.8186540.3626920.181346
1470.7960780.4078440.203922
1480.7723120.4553750.227688
1490.7511470.4977060.248853
1500.7300810.5398380.269919
1510.7135750.5728490.286425
1520.7257520.5484960.274248
1530.7529880.4940230.247012
1540.7292350.541530.270765
1550.7347570.5304860.265243
1560.7087510.5824990.291249
1570.6980170.6039650.301983
1580.6774640.6450730.322536
1590.6566380.6867240.343362
1600.6350060.7299870.364994
1610.6319440.7361130.368056
1620.6188190.7623610.381181
1630.5923740.8152530.407626
1640.5612330.8775340.438767
1650.5289130.9421740.471087
1660.5574750.8850490.442525
1670.5643110.8713770.435689
1680.5425720.9148550.457428
1690.5183170.9633660.481683
1700.5460840.9078310.453916
1710.5120050.975990.487995
1720.5293480.9413040.470652
1730.5358940.9282130.464106
1740.5558330.8883330.444167
1750.5210640.9578720.478936
1760.4858360.9716730.514164
1770.4537090.9074180.546291
1780.4600270.9200540.539973
1790.4601230.9202450.539877
1800.4408330.8816660.559167
1810.4300820.8601630.569918
1820.4426980.8853960.557302
1830.6774490.6451010.322551
1840.6449420.7101160.355058
1850.6166320.7667360.383368
1860.6118410.7763180.388159
1870.5849810.8300380.415019
1880.5491530.9016930.450847
1890.546060.907880.45394
1900.5210380.9579230.478962
1910.5307310.9385390.469269
1920.5449430.9101140.455057
1930.5084380.9831250.491562
1940.4722720.9445450.527728
1950.4518680.9037370.548132
1960.4159820.8319640.584018
1970.3921710.7843410.607829
1980.3958460.7916920.604154
1990.3617660.7235320.638234
2000.3766110.7532220.623389
2010.3684960.7369920.631504
2020.4159310.8318620.584069
2030.4661630.9323250.533837
2040.4715980.9431960.528402
2050.4335730.8671460.566427
2060.45550.9110010.5445
2070.44210.88420.5579
2080.4357230.8714450.564277
2090.4362840.8725680.563716
2100.7896150.4207690.210385
2110.7972180.4055650.202782
2120.7725920.4548170.227408
2130.7405130.5189740.259487
2140.7448850.510230.255115
2150.7198130.5603740.280187
2160.6907750.6184510.309225
2170.6621160.6757690.337884
2180.6230970.7538050.376903
2190.6033180.7933650.396682
2200.5778840.8442330.422116
2210.5409620.9180770.459038
2220.4979590.9959190.502041
2230.5825720.8348560.417428
2240.542160.915680.45784
2250.5109590.9780820.489041
2260.4802420.9604830.519758
2270.4504290.9008570.549571
2280.5042320.9915350.495768
2290.4635920.9271850.536408
2300.4878140.9756270.512186
2310.452010.904020.54799
2320.4644440.9288870.535556
2330.4600170.9200340.539983
2340.4457120.8914240.554288
2350.451070.9021390.54893
2360.5507350.8985310.449265
2370.5034350.993130.496565
2380.566420.8671590.43358
2390.5191620.9616750.480838
2400.486780.9735590.51322
2410.5029310.9941380.497069
2420.509650.98070.49035
2430.5997330.8005350.400267
2440.550270.8994590.44973
2450.5561560.8876890.443844
2460.5442810.9114370.455719
2470.4970540.9941070.502946
2480.449410.8988190.55059
2490.5064540.9870920.493546
2500.4478270.8956530.552173
2510.3896840.7793690.610316
2520.4241240.8482480.575876
2530.4082070.8164130.591793
2540.3962440.7924870.603756
2550.4837240.9674490.516276
2560.4685450.937090.531455
2570.4348440.8696880.565156
2580.5489740.9020530.451026
2590.7778220.4443560.222178
2600.758280.4834390.24172
2610.6908690.6182620.309131
2620.6246340.7507320.375366
2630.547150.9057010.45285
2640.6902570.6194860.309743
2650.7128870.5742260.287113
2660.6998020.6003950.300198
2670.7007820.5984350.299218
2680.6059390.7881210.394061
2690.5585220.8829550.441478
2700.4626630.9253250.537337
2710.4303580.8607150.569642
2720.6417490.7165020.358251






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level300.112782NOK
10% type I error level440.165414NOK

\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 & 0 & 0 & OK \tabularnewline
5% type I error level & 30 & 0.112782 & NOK \tabularnewline
10% type I error level & 44 & 0.165414 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267881&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]30[/C][C]0.112782[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]44[/C][C]0.165414[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267881&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267881&T=6

As an alternative you can also use a QR Code:  
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 level00OK
5% type I error level300.112782NOK
10% type I error level440.165414NOK


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 4
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

Parameters (Session):
par1 = 8 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 4 ; par2 = Do not include Seasonal 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$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), 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,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
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, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
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,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
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,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
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,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
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,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
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')
}