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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 computationFri, 18 Nov 2011 12:47:39 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/18/t1321638477j8c4pvd88ofmlr6.htm/, Retrieved Wed, 24 Apr 2024 06:52:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=145480, Retrieved Wed, 24 Apr 2024 06:52:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact73

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Decreasing Compet...] [2010-11-17 09:04:39] [b98453cac15ba1066b407e146608df68]
-    D    [Multiple Regression] [] [2011-11-18 17:47:39] [f8ac047da1b1db86cbd9837decfb2b34] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9	41	38	14	12
9	39	32	18	11
9	30	35	11	14
9	31	33	12	12
9	34	37	16	21
9	35	29	18	12
9	39	31	14	22
9	34	36	14	11
9	36	35	15	10
9	37	38	15	13
9	38	31	17	10
9	36	34	19	8
9	38	35	10	15
9	39	38	16	14
9	33	37	18	10
9	32	33	14	14
9	36	32	14	14
9	38	38	17	11
9	39	38	14	10
9	32	32	16	13
9	32	33	18	9.5
9	31	31	11	14
9	39	38	14	12
9	37	39	12	14
9	39	32	17	11
9	41	32	9	9
9	36	35	16	11
9	33	37	14	15
9	33	33	15	14
9	34	33	11	13
9	31	31	16	9
9	27	32	13	15
9	37	31	17	10
9	34	37	15	11
9	34	30	14	13
9	32	33	16	8
9	29	31	9	20
9	36	33	15	12
9	29	31	17	10
9	35	33	13	10
9	37	32	15	9
9	34	33	16	14
9	38	32	16	8
9	35	33	12	14
9	38	28	15	11
9	37	35	11	13
9	38	39	15	9
9	33	34	15	11
9	36	38	17	15
9	38	32	13	11
9	32	38	16	10
9	32	30	14	14
9	32	33	11	18
9	34	38	12	14
9	32	32	12	11
9	37	35	15	14.5
9	39	34	16	13
9	29	34	15	9
9	37	36	12	10
9	35	34	12	15
9	30	28	8	20
9	38	34	13	12
9	34	35	11	12
9	31	35	14	14
9	34	31	15	13
10	35	37	10	11
10	36	35	11	17
10	30	27	12	12
10	39	40	15	13
10	35	37	15	14
10	38	36	14	13
10	31	38	16	15
10	34	39	15	13
10	38	41	15	10
10	34	27	13	11
10	39	30	12	19
10	37	37	17	13
10	34	31	13	17
10	28	31	15	13
10	37	27	13	9
10	33	36	15	11
10	35	37	15	9
10	37	33	16	12
10	32	34	15	12
10	33	31	14	13
10	38	39	15	13
10	33	34	14	12
10	29	32	13	15
10	33	33	7	22
10	31	36	17	13
10	36	32	13	15
10	35	41	15	13
10	32	28	14	15
10	29	30	13	12.5
10	39	36	16	11
10	37	35	12	16
10	35	31	14	11
10	37	34	17	11
10	32	36	15	10
10	38	36	17	10
10	37	35	12	16
10	36	37	16	12
10	32	28	11	11
10	33	39	15	16
10	40	32	9	19
10	38	35	16	11
10	41	39	15	16
10	36	35	10	15
10	43	42	10	24
10	30	34	15	14
10	31	33	11	15
10	32	41	13	11
10	32	33	14	15
10	37	34	18	12
10	37	32	16	10
10	33	40	14	14
10	34	40	14	13
10	33	35	14	9
10	38	36	14	15
10	33	37	12	15
10	31	27	14	14
10	38	39	15	11
10	37	38	15	8
10	36	31	15	11
10	31	33	13	11
10	39	32	17	8
10	44	39	17	10
10	33	36	19	11
10	35	33	15	13
10	32	33	13	11
10	28	32	9	20
10	40	37	15	10
10	27	30	15	15
10	37	38	15	12
10	32	29	16	14
10	28	22	11	23
10	34	35	14	14
10	30	35	11	16
10	35	34	15	11
10	31	35	13	12
10	32	34	15	10
10	30	37	16	14
10	30	35	14	12
10	31	23	15	12
10	40	31	16	11
10	32	27	16	12
10	36	36	11	13
10	32	31	12	11
10	35	32	9	19
10	38	39	16	12
10	42	37	13	17
10	34	38	16	9
10	35	39	12	12
9	38	34	9	19
10	33	31	13	18
10	36	32	13	15
10	32	37	14	14
10	33	36	19	11
10	34	32	13	9
10	32	38	12	18
10	34	36	13	16
11	27	26	10	24
11	31	26	14	14
11	38	33	16	20
11	34	39	10	18
11	24	30	11	23
11	30	33	14	12
11	26	25	12	14
11	34	38	9	16
11	27	37	9	18
11	37	31	11	20
11	36	37	16	12
11	41	35	9	12
11	29	25	13	17
11	36	28	16	13
11	32	35	13	9
11	37	33	9	16
11	30	30	12	18
11	31	31	16	10
11	38	37	11	14
11	36	36	14	11
11	35	30	13	9
11	31	36	15	11
11	38	32	14	10
11	22	28	16	11
11	32	36	13	19
11	36	34	14	14
11	39	31	15	12
11	28	28	13	14
11	32	36	11	21
11	32	36	11	13
11	38	40	14	10
11	32	33	15	15
11	35	37	11	16
11	32	32	15	14
11	37	38	12	12
11	34	31	14	19
11	33	37	14	15
11	33	33	8	19
11	26	32	13	13
11	30	30	9	17
11	24	30	15	12
11	34	31	17	11
11	34	32	13	14
11	33	34	15	11
11	34	36	15	13
11	35	37	14	12
11	35	36	16	15
11	36	33	13	14
11	34	33	16	12
11	34	33	9	17
11	41	44	16	11
11	32	39	11	18
11	30	32	10	13
11	35	35	11	17
11	28	25	15	13
11	33	35	17	11
11	39	34	14	12
11	36	35	8	22
11	36	39	15	14
11	35	33	11	12
11	38	36	16	12
11	33	32	10	17
11	31	32	15	9
11	34	36	9	21
11	32	36	16	10
11	31	32	19	11
11	33	34	12	12
11	34	33	8	23
11	34	35	11	13
11	34	30	14	12
11	33	38	9	16
11	32	34	15	9
11	41	33	13	17
11	34	32	16	9
11	36	31	11	14
11	37	30	12	17
11	36	27	13	13
11	29	31	10	11
11	37	30	11	12
11	27	32	12	10
11	35	35	8	19
11	28	28	12	16
11	35	33	12	16
11	37	31	15	14
11	29	35	11	20
11	32	35	13	15
11	36	32	14	23
11	19	21	10	20
11	21	20	12	16
11	31	34	15	14
11	33	32	13	17
11	36	34	13	11
11	33	32	13	13
11	37	33	12	17
11	34	33	12	15
11	35	37	9	21
11	31	32	9	18
11	37	34	15	15
11	35	30	10	8
11	27	30	14	12
11	34	38	15	12
11	40	36	7	22
11	29	32	14	12

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 seconds
R Server'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 11 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145480&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]11 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145480&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145480&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 time11 seconds
R Server'George Udny Yule' @ yule.wessa.net






Multiple Linear Regression - Estimated Regression Equation
depression[t] = + 21.6884186699997 + 0.385686977493418tijd[t] -0.0373398660702173connected[t] -0.0091467791263336separated[t] -0.770373465470964happiness[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
depression[t] =  +  21.6884186699997 +  0.385686977493418tijd[t] -0.0373398660702173connected[t] -0.0091467791263336separated[t] -0.770373465470964happiness[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145480&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]depression[t] =  +  21.6884186699997 +  0.385686977493418tijd[t] -0.0373398660702173connected[t] -0.0091467791263336separated[t] -0.770373465470964happiness[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145480&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145480&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
depression[t] = + 21.6884186699997 + 0.385686977493418tijd[t] -0.0373398660702173connected[t] -0.0091467791263336separated[t] -0.770373465470964happiness[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)21.68841866999973.463796.261500
tijd0.3856869774934180.2306511.67220.0956990.04785
connected-0.03733986607021730.052198-0.71540.4750370.237518
separated-0.00914677912633360.052768-0.17330.8625190.43126
happiness-0.7703734654709640.072131-10.680200

\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) & 21.6884186699997 & 3.46379 & 6.2615 & 0 & 0 \tabularnewline
tijd & 0.385686977493418 & 0.230651 & 1.6722 & 0.095699 & 0.04785 \tabularnewline
connected & -0.0373398660702173 & 0.052198 & -0.7154 & 0.475037 & 0.237518 \tabularnewline
separated & -0.0091467791263336 & 0.052768 & -0.1733 & 0.862519 & 0.43126 \tabularnewline
happiness & -0.770373465470964 & 0.072131 & -10.6802 & 0 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145480&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]21.6884186699997[/C][C]3.46379[/C][C]6.2615[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]tijd[/C][C]0.385686977493418[/C][C]0.230651[/C][C]1.6722[/C][C]0.095699[/C][C]0.04785[/C][/ROW]
[ROW][C]connected[/C][C]-0.0373398660702173[/C][C]0.052198[/C][C]-0.7154[/C][C]0.475037[/C][C]0.237518[/C][/ROW]
[ROW][C]separated[/C][C]-0.0091467791263336[/C][C]0.052768[/C][C]-0.1733[/C][C]0.862519[/C][C]0.43126[/C][/ROW]
[ROW][C]happiness[/C][C]-0.770373465470964[/C][C]0.072131[/C][C]-10.6802[/C][C]0[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145480&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145480&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)21.68841866999973.463796.261500
tijd0.3856869774934180.2306511.67220.0956990.04785
connected-0.03733986607021730.052198-0.71540.4750370.237518
separated-0.00914677912633360.052768-0.17330.8625190.43126
happiness-0.7703734654709640.072131-10.680200






Multiple Linear Regression - Regression Statistics
Multiple R0.591997389026897
R-squared0.350460908614663
Adjusted R-squared0.340429416855816
F-TEST (value)34.9360710290757
F-TEST (DF numerator)4
F-TEST (DF denominator)259
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.81776673236503
Sum Squared Residuals2056.41062372799

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.591997389026897 \tabularnewline
R-squared & 0.350460908614663 \tabularnewline
Adjusted R-squared & 0.340429416855816 \tabularnewline
F-TEST (value) & 34.9360710290757 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 259 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.81776673236503 \tabularnewline
Sum Squared Residuals & 2056.41062372799 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145480&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.591997389026897[/C][/ROW]
[ROW][C]R-squared[/C][C]0.350460908614663[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.340429416855816[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]34.9360710290757[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]259[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.81776673236503[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2056.41062372799[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145480&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145480&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 R0.591997389026897
R-squared0.350460908614663
Adjusted R-squared0.340429416855816
F-TEST (value)34.9360710290757
F-TEST (DF numerator)4
F-TEST (DF denominator)259
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.81776673236503
Sum Squared Residuals2056.41062372799






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11212.4958608351674-0.495860835167416
2119.5439273801821.45607261981801
31415.2451600957317-1.2451600957317
41214.4557403224432-2.45574032244319
52111.22563974584339.77436025415666
6129.720727181841862.27927281815814
72212.63456802119229.36543197880782
81112.7755334559116-1.7755334559116
91011.9396270374265-1.93962703742654
101311.87484683397731.12515316602268
111010.3607874908495-0.36078749084951
1288.86727995466902-0.867279954669015
131515.7168146326409-0.716814632640927
141411.02979363636592.97020636363408
15109.722232680971630.27776731902837
161412.8776535254311.12234647456896
171412.73744084027651.2625591597235
181110.29676003696520.703239963034825
191012.5705405673078-2.57054056730785
201311.34605337361541.65394662638456
219.59.79615966354718-0.296159663547182
221415.2444073461668-1.24440734616682
231212.5705405673079-0.570540567307851
241414.1768204512639-0.176820451263881
251110.3143008456530.68569915434704
26916.4026088372802-7.40260883728024
271111.1692535719556-0.169253571955575
281512.80372654285552.19627345714451
291412.06994019388991.93005980611014
301315.1140941897035-2.1140941897035
31911.392540018812-2.392540018812
321513.84387310037941.15612689962058
331010.3981273569197-0.398127356919727
341111.9960132113143-0.996013211314307
351312.83041413066960.169585869330394
36811.3369065944891-3.33690659448911
372016.85983400924923.14016599075082
381211.95792059567920.0420794043207937
391010.6968462854815-0.696846285481465
401013.5360073926914-3.53600739269135
41911.9297275087353-2.92972750873532
421411.26222686234872.73777313765132
43811.1220141771941-3.12201417719414
441414.3063808581623-0.306380858162317
451111.9289747591704-0.92897475917044
461314.9837810332402-1.98378103324018
47911.8283601887808-2.82836018878077
481112.0607934147635-1.06079341476352
491510.37143976910564.62856023089439
501113.433134573607-2.43313457360703
511011.2911726988574-1.29117269885744
521412.905093862811.09490613718996
531815.18877392184392.81122607815607
541414.2979868286009-0.297986828600866
551114.4275472354993-3.4275472354993
5614.511.90228717135632.59771282864368
571311.06638075287131.93361924712874
58912.2101528790444-3.21015287904439
591014.2042607886429-4.20426078864288
601514.2972340790360.702765920964017
612017.62030794602892.37969205397107
621213.4148410153544-1.41484101535437
631215.0958006314508-3.09580063145083
641412.89669983324861.10330016675141
651312.05089388607230.949106113927692
661116.1962276500923-5.19622765009233
671715.40680787680381.59319212319619
681214.9336478407648-2.93364784076482
691312.16756052107760.832439478922363
701412.34436032273751.65563967726249
711313.0118609691242-0.0118609691241534
721511.71419954242113.28580045757892
731312.36340663055510.636593369444943
741012.1957536080215-2.19575360802152
751114.013914911013-3.01391491101299
761914.57014870875394.42985129124613
771310.72893365965512.27106634034486
781713.97732779450773.02267220549235
791312.6606200599870.339379940012971
80913.9018953128023-4.90189531280234
811112.4281868340043-1.42818683400428
82912.3443603227375-3.34436032273751
831211.53589424163140.464105758368557
841212.4838202583272-0.48382025832716
851313.2442941951069-0.244294195106908
861312.21404716627420.785952833725812
871213.2168538577279-1.21685385772791
881514.15488034573240.845119654267592
892218.6186148951513.38138510484901
901310.96211963520282.03788036479722
911513.89350128324091.10649871675911
921312.30777320623220.692226793767827
931513.30907439855611.69092560144387
9412.514.1731739039851-1.67317390398507
951111.433774172112-0.433774172112007
961614.59909454526261.40090545473737
971113.1696144629665-2.16961446296647
981110.75637399703410.243626002965856
991012.4655267000745-2.46552670007449
1001010.7007405727113-0.70074057271126
1011614.59909454526261.40090545473737
1021211.53664699119630.463353008803674
1031115.620194794969-4.62019479496902
1041612.40074649662533.59925350337473
1051916.82563568084392.17436431915612
1061111.4802608173086-0.480260817308558
1071612.10202756806353.89797243193646
1081516.1771813422748-1.17718134227478
1092415.85177482589898.14822517410108
1101412.55849999046761.44150000953241
1111515.6118007654076-0.611800765407569
1121113.9605397353848-2.96053973538475
1131513.26334050292451.73665949707554
114129.986000531563182.01399946843682
1151011.5450410207578-1.54504102075778
1161413.16197318296990.838026817030095
1171313.1246333168997-0.124633316899688
118913.2077070786016-4.20770707860157
1191513.01186096912421.98813903087585
1201514.73016045129080.269839548709165
1211413.35556104375270.644438956247324
1221112.2140471662742-1.21404716627419
123812.2605338114707-4.26053381147074
1241112.3619011314253-1.36190113142529
1251114.0710538344656-3.07105383446564
126810.6999878231464-2.69998782314638
1271010.449261038911-0.449261038910956
128119.346692972120421.65330702787958
1291312.38094743924280.619052560757159
1301114.0337139683954-3.03371396839542
1312017.27371407368652.72628592631352
1321012.1576609923864-2.15766099238642
1331512.70710670518362.29289329481642
1341212.2605338114707-0.260533811470739
1351411.75918068848792.24081931151214
1362315.82443493400797.17556506599211
1371413.17036721253140.829632787468644
1381615.63084707322510.369152926774881
1391112.3718006601165-1.37180066011651
1401214.052760276213-2.05276027621297
1411012.4838202583272-2.48382025832716
1421411.76068618761762.23931381238237
1431213.3197266768122-1.31972667681222
1441212.621774694787-0.621774694787046
1451111.4421682016735-0.442168201673458
1461211.77747424674050.22252575325947
1471315.3976610976775-2.39766109767748
1481114.8223809921191-3.82238099211905
1491917.0123350111951.98766498880504
1501211.44367370080320.556326299196776
1511713.62372819118793.37627180881208
152911.6021799442104-2.60217994421043
1531214.6371871608977-2.63718716089773
1541916.49633487723822.50366512276177
1551814.01466766057793.98533233942213
1561513.89350128324091.10649871675911
1571413.22675338641910.773246613580877
158119.346692972120421.65330702787958
159913.9681810153813-4.96818101538132
1601814.75835353823473.24164646176528
1611613.9315938988762.06840610112401
1622416.98124812653727.01875187346284
1631413.75039480037240.249605199627572
1642011.88424135305468.11575864694536
1651816.60096093540331.3990390645967
1662316.28630714277156.71369285722849
1671213.7237072125583-1.72370721255831
1681415.4869878407918-1.48698784079178
1691617.3804811800006-1.3804811800006
1701817.65100702161850.34899297838155
1712015.79174210473244.20825789526765
1721211.92233396868970.077666031310257
1731217.1465424548881-5.14654245488808
1741714.60459477711022.39540522288984
1751312.00465498082670.995345019173255
176914.4011073876362-5.40110738763617
1771617.3141954774216-1.31419547742161
1781815.29189448087922.70810551912076
1791012.1639139737988-2.16391397379883
1801415.6995215639041-1.69952156390413
1811113.472227678758-2.47222767875801
182914.3348216850572-5.33482168505719
1831112.8885535436381-1.88855354363813
1841013.4341350631229-3.43413506312291
1851112.5274131058098-1.52741310580979
1861914.39196060850984.60803939149016
1871413.49052123701070.509478762989327
1881212.6355685107081-0.635568510708058
1891414.6144943058014-0.614494305801377
1902115.93270753945185.06729246054823
1911315.9327075394518-2.93270753945177
1921013.3609608301122-3.36096083011224
1931512.87865401494692.12134598505309
1941615.81154116211480.188458837885217
1951412.88780079407321.11219920592676
1961214.9573411853771-2.95734118537705
1971913.59264130653015.40735869346989
1981513.57510049784231.42489950215768
1991918.23392840717340.766071592826555
2001314.6525869214365-1.65258692143648
2011717.6030148772921-0.603014877292134
2021213.2048132808876-1.20481328088765
2031111.2815209101172-0.281520910117214
2041414.3538679928747-0.353867992874739
2051112.8321673697504-1.83216736975036
2061312.77653394542750.223466054572524
2071213.5004207657019-1.50042076570189
2081511.96882061388633.03117938611371
2091414.270041481608-0.270041481607971
2101212.0336008173355-0.033600817335512
2111717.4262150756323-0.426215075632264
2121111.6716071844543-0.671607184454322
2131815.90526720207282.09473279792723
2141316.8143478535685-3.8143478535685
2151715.82983472036741.17016527963255
2161313.1011877122384-0.101187712238448
2171111.2822736596821-0.282273659682097
2181213.3785016388-1.37850163880002
2192218.10361525071013.89638474928987
2201412.6744138759081.32558612409196
2211215.8481282786201-3.84812827862012
2221211.85680101567560.143198984324358
2231716.70232825535780.29767174464215
224912.9251406601435-3.92514066014346
2252117.39877473825333.60122526174674
2261012.0808402120969-2.08084021209695
227119.84364679825961.1563532017404
2281215.1432877661633-3.14328776616325
2292318.19658854110324.80341145889677
2301315.8671745864377-2.86717458643767
2311213.6017880856564-1.60178808565644
2321617.4178210460708-1.41782104607081
233912.8695072358206-3.86950723582058
2341714.08334215125692.91665784874312
235912.0427475964618-3.04274759646185
2361415.8290819708026-1.82908197080257
2371715.03051541838771.96948458161228
2381314.324922156366-1.32492215636597
2391116.8608344987651-5.86083449876505
2401215.8008888838587-3.80088888385868
2411015.3856205208372-5.38562052083723
2421918.14095511678030.859044883219656
2431615.38486777127230.615132228727659
2441615.07775481314920.922245186850847
2451412.71024824284851.28975175715151
2462016.05387391678883.94612608321125
2471514.40110738763620.598892612363827
2482313.50881479526339.49118520473666
2492017.32570095073062.67429904926944
2501615.71942106677450.280578933225469
2511412.90684710189081.09315289810921
2521714.3912078589452.60879214105504
2531114.2608947024816-3.26089470248164
2541314.391207858945-1.39120785894496
2551715.00307508100871.99692491899128
2561515.1150946792194-0.11509467921937
2572117.35228809305673.64771190694329
2581817.54738145296930.45261854703075
2591512.68280790546952.31719209453051
260816.6459420814701-8.64594208147008
2611213.863167148148-1.86316714814796
2621212.7582403871748-0.758240387174809
2632218.71548247277393.28451752722611
2641213.7701938577549-1.77019385775486

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 12.4958608351674 & -0.495860835167416 \tabularnewline
2 & 11 & 9.543927380182 & 1.45607261981801 \tabularnewline
3 & 14 & 15.2451600957317 & -1.2451600957317 \tabularnewline
4 & 12 & 14.4557403224432 & -2.45574032244319 \tabularnewline
5 & 21 & 11.2256397458433 & 9.77436025415666 \tabularnewline
6 & 12 & 9.72072718184186 & 2.27927281815814 \tabularnewline
7 & 22 & 12.6345680211922 & 9.36543197880782 \tabularnewline
8 & 11 & 12.7755334559116 & -1.7755334559116 \tabularnewline
9 & 10 & 11.9396270374265 & -1.93962703742654 \tabularnewline
10 & 13 & 11.8748468339773 & 1.12515316602268 \tabularnewline
11 & 10 & 10.3607874908495 & -0.36078749084951 \tabularnewline
12 & 8 & 8.86727995466902 & -0.867279954669015 \tabularnewline
13 & 15 & 15.7168146326409 & -0.716814632640927 \tabularnewline
14 & 14 & 11.0297936363659 & 2.97020636363408 \tabularnewline
15 & 10 & 9.72223268097163 & 0.27776731902837 \tabularnewline
16 & 14 & 12.877653525431 & 1.12234647456896 \tabularnewline
17 & 14 & 12.7374408402765 & 1.2625591597235 \tabularnewline
18 & 11 & 10.2967600369652 & 0.703239963034825 \tabularnewline
19 & 10 & 12.5705405673078 & -2.57054056730785 \tabularnewline
20 & 13 & 11.3460533736154 & 1.65394662638456 \tabularnewline
21 & 9.5 & 9.79615966354718 & -0.296159663547182 \tabularnewline
22 & 14 & 15.2444073461668 & -1.24440734616682 \tabularnewline
23 & 12 & 12.5705405673079 & -0.570540567307851 \tabularnewline
24 & 14 & 14.1768204512639 & -0.176820451263881 \tabularnewline
25 & 11 & 10.314300845653 & 0.68569915434704 \tabularnewline
26 & 9 & 16.4026088372802 & -7.40260883728024 \tabularnewline
27 & 11 & 11.1692535719556 & -0.169253571955575 \tabularnewline
28 & 15 & 12.8037265428555 & 2.19627345714451 \tabularnewline
29 & 14 & 12.0699401938899 & 1.93005980611014 \tabularnewline
30 & 13 & 15.1140941897035 & -2.1140941897035 \tabularnewline
31 & 9 & 11.392540018812 & -2.392540018812 \tabularnewline
32 & 15 & 13.8438731003794 & 1.15612689962058 \tabularnewline
33 & 10 & 10.3981273569197 & -0.398127356919727 \tabularnewline
34 & 11 & 11.9960132113143 & -0.996013211314307 \tabularnewline
35 & 13 & 12.8304141306696 & 0.169585869330394 \tabularnewline
36 & 8 & 11.3369065944891 & -3.33690659448911 \tabularnewline
37 & 20 & 16.8598340092492 & 3.14016599075082 \tabularnewline
38 & 12 & 11.9579205956792 & 0.0420794043207937 \tabularnewline
39 & 10 & 10.6968462854815 & -0.696846285481465 \tabularnewline
40 & 10 & 13.5360073926914 & -3.53600739269135 \tabularnewline
41 & 9 & 11.9297275087353 & -2.92972750873532 \tabularnewline
42 & 14 & 11.2622268623487 & 2.73777313765132 \tabularnewline
43 & 8 & 11.1220141771941 & -3.12201417719414 \tabularnewline
44 & 14 & 14.3063808581623 & -0.306380858162317 \tabularnewline
45 & 11 & 11.9289747591704 & -0.92897475917044 \tabularnewline
46 & 13 & 14.9837810332402 & -1.98378103324018 \tabularnewline
47 & 9 & 11.8283601887808 & -2.82836018878077 \tabularnewline
48 & 11 & 12.0607934147635 & -1.06079341476352 \tabularnewline
49 & 15 & 10.3714397691056 & 4.62856023089439 \tabularnewline
50 & 11 & 13.433134573607 & -2.43313457360703 \tabularnewline
51 & 10 & 11.2911726988574 & -1.29117269885744 \tabularnewline
52 & 14 & 12.90509386281 & 1.09490613718996 \tabularnewline
53 & 18 & 15.1887739218439 & 2.81122607815607 \tabularnewline
54 & 14 & 14.2979868286009 & -0.297986828600866 \tabularnewline
55 & 11 & 14.4275472354993 & -3.4275472354993 \tabularnewline
56 & 14.5 & 11.9022871713563 & 2.59771282864368 \tabularnewline
57 & 13 & 11.0663807528713 & 1.93361924712874 \tabularnewline
58 & 9 & 12.2101528790444 & -3.21015287904439 \tabularnewline
59 & 10 & 14.2042607886429 & -4.20426078864288 \tabularnewline
60 & 15 & 14.297234079036 & 0.702765920964017 \tabularnewline
61 & 20 & 17.6203079460289 & 2.37969205397107 \tabularnewline
62 & 12 & 13.4148410153544 & -1.41484101535437 \tabularnewline
63 & 12 & 15.0958006314508 & -3.09580063145083 \tabularnewline
64 & 14 & 12.8966998332486 & 1.10330016675141 \tabularnewline
65 & 13 & 12.0508938860723 & 0.949106113927692 \tabularnewline
66 & 11 & 16.1962276500923 & -5.19622765009233 \tabularnewline
67 & 17 & 15.4068078768038 & 1.59319212319619 \tabularnewline
68 & 12 & 14.9336478407648 & -2.93364784076482 \tabularnewline
69 & 13 & 12.1675605210776 & 0.832439478922363 \tabularnewline
70 & 14 & 12.3443603227375 & 1.65563967726249 \tabularnewline
71 & 13 & 13.0118609691242 & -0.0118609691241534 \tabularnewline
72 & 15 & 11.7141995424211 & 3.28580045757892 \tabularnewline
73 & 13 & 12.3634066305551 & 0.636593369444943 \tabularnewline
74 & 10 & 12.1957536080215 & -2.19575360802152 \tabularnewline
75 & 11 & 14.013914911013 & -3.01391491101299 \tabularnewline
76 & 19 & 14.5701487087539 & 4.42985129124613 \tabularnewline
77 & 13 & 10.7289336596551 & 2.27106634034486 \tabularnewline
78 & 17 & 13.9773277945077 & 3.02267220549235 \tabularnewline
79 & 13 & 12.660620059987 & 0.339379940012971 \tabularnewline
80 & 9 & 13.9018953128023 & -4.90189531280234 \tabularnewline
81 & 11 & 12.4281868340043 & -1.42818683400428 \tabularnewline
82 & 9 & 12.3443603227375 & -3.34436032273751 \tabularnewline
83 & 12 & 11.5358942416314 & 0.464105758368557 \tabularnewline
84 & 12 & 12.4838202583272 & -0.48382025832716 \tabularnewline
85 & 13 & 13.2442941951069 & -0.244294195106908 \tabularnewline
86 & 13 & 12.2140471662742 & 0.785952833725812 \tabularnewline
87 & 12 & 13.2168538577279 & -1.21685385772791 \tabularnewline
88 & 15 & 14.1548803457324 & 0.845119654267592 \tabularnewline
89 & 22 & 18.618614895151 & 3.38138510484901 \tabularnewline
90 & 13 & 10.9621196352028 & 2.03788036479722 \tabularnewline
91 & 15 & 13.8935012832409 & 1.10649871675911 \tabularnewline
92 & 13 & 12.3077732062322 & 0.692226793767827 \tabularnewline
93 & 15 & 13.3090743985561 & 1.69092560144387 \tabularnewline
94 & 12.5 & 14.1731739039851 & -1.67317390398507 \tabularnewline
95 & 11 & 11.433774172112 & -0.433774172112007 \tabularnewline
96 & 16 & 14.5990945452626 & 1.40090545473737 \tabularnewline
97 & 11 & 13.1696144629665 & -2.16961446296647 \tabularnewline
98 & 11 & 10.7563739970341 & 0.243626002965856 \tabularnewline
99 & 10 & 12.4655267000745 & -2.46552670007449 \tabularnewline
100 & 10 & 10.7007405727113 & -0.70074057271126 \tabularnewline
101 & 16 & 14.5990945452626 & 1.40090545473737 \tabularnewline
102 & 12 & 11.5366469911963 & 0.463353008803674 \tabularnewline
103 & 11 & 15.620194794969 & -4.62019479496902 \tabularnewline
104 & 16 & 12.4007464966253 & 3.59925350337473 \tabularnewline
105 & 19 & 16.8256356808439 & 2.17436431915612 \tabularnewline
106 & 11 & 11.4802608173086 & -0.480260817308558 \tabularnewline
107 & 16 & 12.1020275680635 & 3.89797243193646 \tabularnewline
108 & 15 & 16.1771813422748 & -1.17718134227478 \tabularnewline
109 & 24 & 15.8517748258989 & 8.14822517410108 \tabularnewline
110 & 14 & 12.5584999904676 & 1.44150000953241 \tabularnewline
111 & 15 & 15.6118007654076 & -0.611800765407569 \tabularnewline
112 & 11 & 13.9605397353848 & -2.96053973538475 \tabularnewline
113 & 15 & 13.2633405029245 & 1.73665949707554 \tabularnewline
114 & 12 & 9.98600053156318 & 2.01399946843682 \tabularnewline
115 & 10 & 11.5450410207578 & -1.54504102075778 \tabularnewline
116 & 14 & 13.1619731829699 & 0.838026817030095 \tabularnewline
117 & 13 & 13.1246333168997 & -0.124633316899688 \tabularnewline
118 & 9 & 13.2077070786016 & -4.20770707860157 \tabularnewline
119 & 15 & 13.0118609691242 & 1.98813903087585 \tabularnewline
120 & 15 & 14.7301604512908 & 0.269839548709165 \tabularnewline
121 & 14 & 13.3555610437527 & 0.644438956247324 \tabularnewline
122 & 11 & 12.2140471662742 & -1.21404716627419 \tabularnewline
123 & 8 & 12.2605338114707 & -4.26053381147074 \tabularnewline
124 & 11 & 12.3619011314253 & -1.36190113142529 \tabularnewline
125 & 11 & 14.0710538344656 & -3.07105383446564 \tabularnewline
126 & 8 & 10.6999878231464 & -2.69998782314638 \tabularnewline
127 & 10 & 10.449261038911 & -0.449261038910956 \tabularnewline
128 & 11 & 9.34669297212042 & 1.65330702787958 \tabularnewline
129 & 13 & 12.3809474392428 & 0.619052560757159 \tabularnewline
130 & 11 & 14.0337139683954 & -3.03371396839542 \tabularnewline
131 & 20 & 17.2737140736865 & 2.72628592631352 \tabularnewline
132 & 10 & 12.1576609923864 & -2.15766099238642 \tabularnewline
133 & 15 & 12.7071067051836 & 2.29289329481642 \tabularnewline
134 & 12 & 12.2605338114707 & -0.260533811470739 \tabularnewline
135 & 14 & 11.7591806884879 & 2.24081931151214 \tabularnewline
136 & 23 & 15.8244349340079 & 7.17556506599211 \tabularnewline
137 & 14 & 13.1703672125314 & 0.829632787468644 \tabularnewline
138 & 16 & 15.6308470732251 & 0.369152926774881 \tabularnewline
139 & 11 & 12.3718006601165 & -1.37180066011651 \tabularnewline
140 & 12 & 14.052760276213 & -2.05276027621297 \tabularnewline
141 & 10 & 12.4838202583272 & -2.48382025832716 \tabularnewline
142 & 14 & 11.7606861876176 & 2.23931381238237 \tabularnewline
143 & 12 & 13.3197266768122 & -1.31972667681222 \tabularnewline
144 & 12 & 12.621774694787 & -0.621774694787046 \tabularnewline
145 & 11 & 11.4421682016735 & -0.442168201673458 \tabularnewline
146 & 12 & 11.7774742467405 & 0.22252575325947 \tabularnewline
147 & 13 & 15.3976610976775 & -2.39766109767748 \tabularnewline
148 & 11 & 14.8223809921191 & -3.82238099211905 \tabularnewline
149 & 19 & 17.012335011195 & 1.98766498880504 \tabularnewline
150 & 12 & 11.4436737008032 & 0.556326299196776 \tabularnewline
151 & 17 & 13.6237281911879 & 3.37627180881208 \tabularnewline
152 & 9 & 11.6021799442104 & -2.60217994421043 \tabularnewline
153 & 12 & 14.6371871608977 & -2.63718716089773 \tabularnewline
154 & 19 & 16.4963348772382 & 2.50366512276177 \tabularnewline
155 & 18 & 14.0146676605779 & 3.98533233942213 \tabularnewline
156 & 15 & 13.8935012832409 & 1.10649871675911 \tabularnewline
157 & 14 & 13.2267533864191 & 0.773246613580877 \tabularnewline
158 & 11 & 9.34669297212042 & 1.65330702787958 \tabularnewline
159 & 9 & 13.9681810153813 & -4.96818101538132 \tabularnewline
160 & 18 & 14.7583535382347 & 3.24164646176528 \tabularnewline
161 & 16 & 13.931593898876 & 2.06840610112401 \tabularnewline
162 & 24 & 16.9812481265372 & 7.01875187346284 \tabularnewline
163 & 14 & 13.7503948003724 & 0.249605199627572 \tabularnewline
164 & 20 & 11.8842413530546 & 8.11575864694536 \tabularnewline
165 & 18 & 16.6009609354033 & 1.3990390645967 \tabularnewline
166 & 23 & 16.2863071427715 & 6.71369285722849 \tabularnewline
167 & 12 & 13.7237072125583 & -1.72370721255831 \tabularnewline
168 & 14 & 15.4869878407918 & -1.48698784079178 \tabularnewline
169 & 16 & 17.3804811800006 & -1.3804811800006 \tabularnewline
170 & 18 & 17.6510070216185 & 0.34899297838155 \tabularnewline
171 & 20 & 15.7917421047324 & 4.20825789526765 \tabularnewline
172 & 12 & 11.9223339686897 & 0.077666031310257 \tabularnewline
173 & 12 & 17.1465424548881 & -5.14654245488808 \tabularnewline
174 & 17 & 14.6045947771102 & 2.39540522288984 \tabularnewline
175 & 13 & 12.0046549808267 & 0.995345019173255 \tabularnewline
176 & 9 & 14.4011073876362 & -5.40110738763617 \tabularnewline
177 & 16 & 17.3141954774216 & -1.31419547742161 \tabularnewline
178 & 18 & 15.2918944808792 & 2.70810551912076 \tabularnewline
179 & 10 & 12.1639139737988 & -2.16391397379883 \tabularnewline
180 & 14 & 15.6995215639041 & -1.69952156390413 \tabularnewline
181 & 11 & 13.472227678758 & -2.47222767875801 \tabularnewline
182 & 9 & 14.3348216850572 & -5.33482168505719 \tabularnewline
183 & 11 & 12.8885535436381 & -1.88855354363813 \tabularnewline
184 & 10 & 13.4341350631229 & -3.43413506312291 \tabularnewline
185 & 11 & 12.5274131058098 & -1.52741310580979 \tabularnewline
186 & 19 & 14.3919606085098 & 4.60803939149016 \tabularnewline
187 & 14 & 13.4905212370107 & 0.509478762989327 \tabularnewline
188 & 12 & 12.6355685107081 & -0.635568510708058 \tabularnewline
189 & 14 & 14.6144943058014 & -0.614494305801377 \tabularnewline
190 & 21 & 15.9327075394518 & 5.06729246054823 \tabularnewline
191 & 13 & 15.9327075394518 & -2.93270753945177 \tabularnewline
192 & 10 & 13.3609608301122 & -3.36096083011224 \tabularnewline
193 & 15 & 12.8786540149469 & 2.12134598505309 \tabularnewline
194 & 16 & 15.8115411621148 & 0.188458837885217 \tabularnewline
195 & 14 & 12.8878007940732 & 1.11219920592676 \tabularnewline
196 & 12 & 14.9573411853771 & -2.95734118537705 \tabularnewline
197 & 19 & 13.5926413065301 & 5.40735869346989 \tabularnewline
198 & 15 & 13.5751004978423 & 1.42489950215768 \tabularnewline
199 & 19 & 18.2339284071734 & 0.766071592826555 \tabularnewline
200 & 13 & 14.6525869214365 & -1.65258692143648 \tabularnewline
201 & 17 & 17.6030148772921 & -0.603014877292134 \tabularnewline
202 & 12 & 13.2048132808876 & -1.20481328088765 \tabularnewline
203 & 11 & 11.2815209101172 & -0.281520910117214 \tabularnewline
204 & 14 & 14.3538679928747 & -0.353867992874739 \tabularnewline
205 & 11 & 12.8321673697504 & -1.83216736975036 \tabularnewline
206 & 13 & 12.7765339454275 & 0.223466054572524 \tabularnewline
207 & 12 & 13.5004207657019 & -1.50042076570189 \tabularnewline
208 & 15 & 11.9688206138863 & 3.03117938611371 \tabularnewline
209 & 14 & 14.270041481608 & -0.270041481607971 \tabularnewline
210 & 12 & 12.0336008173355 & -0.033600817335512 \tabularnewline
211 & 17 & 17.4262150756323 & -0.426215075632264 \tabularnewline
212 & 11 & 11.6716071844543 & -0.671607184454322 \tabularnewline
213 & 18 & 15.9052672020728 & 2.09473279792723 \tabularnewline
214 & 13 & 16.8143478535685 & -3.8143478535685 \tabularnewline
215 & 17 & 15.8298347203674 & 1.17016527963255 \tabularnewline
216 & 13 & 13.1011877122384 & -0.101187712238448 \tabularnewline
217 & 11 & 11.2822736596821 & -0.282273659682097 \tabularnewline
218 & 12 & 13.3785016388 & -1.37850163880002 \tabularnewline
219 & 22 & 18.1036152507101 & 3.89638474928987 \tabularnewline
220 & 14 & 12.674413875908 & 1.32558612409196 \tabularnewline
221 & 12 & 15.8481282786201 & -3.84812827862012 \tabularnewline
222 & 12 & 11.8568010156756 & 0.143198984324358 \tabularnewline
223 & 17 & 16.7023282553578 & 0.29767174464215 \tabularnewline
224 & 9 & 12.9251406601435 & -3.92514066014346 \tabularnewline
225 & 21 & 17.3987747382533 & 3.60122526174674 \tabularnewline
226 & 10 & 12.0808402120969 & -2.08084021209695 \tabularnewline
227 & 11 & 9.8436467982596 & 1.1563532017404 \tabularnewline
228 & 12 & 15.1432877661633 & -3.14328776616325 \tabularnewline
229 & 23 & 18.1965885411032 & 4.80341145889677 \tabularnewline
230 & 13 & 15.8671745864377 & -2.86717458643767 \tabularnewline
231 & 12 & 13.6017880856564 & -1.60178808565644 \tabularnewline
232 & 16 & 17.4178210460708 & -1.41782104607081 \tabularnewline
233 & 9 & 12.8695072358206 & -3.86950723582058 \tabularnewline
234 & 17 & 14.0833421512569 & 2.91665784874312 \tabularnewline
235 & 9 & 12.0427475964618 & -3.04274759646185 \tabularnewline
236 & 14 & 15.8290819708026 & -1.82908197080257 \tabularnewline
237 & 17 & 15.0305154183877 & 1.96948458161228 \tabularnewline
238 & 13 & 14.324922156366 & -1.32492215636597 \tabularnewline
239 & 11 & 16.8608344987651 & -5.86083449876505 \tabularnewline
240 & 12 & 15.8008888838587 & -3.80088888385868 \tabularnewline
241 & 10 & 15.3856205208372 & -5.38562052083723 \tabularnewline
242 & 19 & 18.1409551167803 & 0.859044883219656 \tabularnewline
243 & 16 & 15.3848677712723 & 0.615132228727659 \tabularnewline
244 & 16 & 15.0777548131492 & 0.922245186850847 \tabularnewline
245 & 14 & 12.7102482428485 & 1.28975175715151 \tabularnewline
246 & 20 & 16.0538739167888 & 3.94612608321125 \tabularnewline
247 & 15 & 14.4011073876362 & 0.598892612363827 \tabularnewline
248 & 23 & 13.5088147952633 & 9.49118520473666 \tabularnewline
249 & 20 & 17.3257009507306 & 2.67429904926944 \tabularnewline
250 & 16 & 15.7194210667745 & 0.280578933225469 \tabularnewline
251 & 14 & 12.9068471018908 & 1.09315289810921 \tabularnewline
252 & 17 & 14.391207858945 & 2.60879214105504 \tabularnewline
253 & 11 & 14.2608947024816 & -3.26089470248164 \tabularnewline
254 & 13 & 14.391207858945 & -1.39120785894496 \tabularnewline
255 & 17 & 15.0030750810087 & 1.99692491899128 \tabularnewline
256 & 15 & 15.1150946792194 & -0.11509467921937 \tabularnewline
257 & 21 & 17.3522880930567 & 3.64771190694329 \tabularnewline
258 & 18 & 17.5473814529693 & 0.45261854703075 \tabularnewline
259 & 15 & 12.6828079054695 & 2.31719209453051 \tabularnewline
260 & 8 & 16.6459420814701 & -8.64594208147008 \tabularnewline
261 & 12 & 13.863167148148 & -1.86316714814796 \tabularnewline
262 & 12 & 12.7582403871748 & -0.758240387174809 \tabularnewline
263 & 22 & 18.7154824727739 & 3.28451752722611 \tabularnewline
264 & 12 & 13.7701938577549 & -1.77019385775486 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145480&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]12.4958608351674[/C][C]-0.495860835167416[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]9.543927380182[/C][C]1.45607261981801[/C][/ROW]
[ROW][C]3[/C][C]14[/C][C]15.2451600957317[/C][C]-1.2451600957317[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.4557403224432[/C][C]-2.45574032244319[/C][/ROW]
[ROW][C]5[/C][C]21[/C][C]11.2256397458433[/C][C]9.77436025415666[/C][/ROW]
[ROW][C]6[/C][C]12[/C][C]9.72072718184186[/C][C]2.27927281815814[/C][/ROW]
[ROW][C]7[/C][C]22[/C][C]12.6345680211922[/C][C]9.36543197880782[/C][/ROW]
[ROW][C]8[/C][C]11[/C][C]12.7755334559116[/C][C]-1.7755334559116[/C][/ROW]
[ROW][C]9[/C][C]10[/C][C]11.9396270374265[/C][C]-1.93962703742654[/C][/ROW]
[ROW][C]10[/C][C]13[/C][C]11.8748468339773[/C][C]1.12515316602268[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]10.3607874908495[/C][C]-0.36078749084951[/C][/ROW]
[ROW][C]12[/C][C]8[/C][C]8.86727995466902[/C][C]-0.867279954669015[/C][/ROW]
[ROW][C]13[/C][C]15[/C][C]15.7168146326409[/C][C]-0.716814632640927[/C][/ROW]
[ROW][C]14[/C][C]14[/C][C]11.0297936363659[/C][C]2.97020636363408[/C][/ROW]
[ROW][C]15[/C][C]10[/C][C]9.72223268097163[/C][C]0.27776731902837[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]12.877653525431[/C][C]1.12234647456896[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]12.7374408402765[/C][C]1.2625591597235[/C][/ROW]
[ROW][C]18[/C][C]11[/C][C]10.2967600369652[/C][C]0.703239963034825[/C][/ROW]
[ROW][C]19[/C][C]10[/C][C]12.5705405673078[/C][C]-2.57054056730785[/C][/ROW]
[ROW][C]20[/C][C]13[/C][C]11.3460533736154[/C][C]1.65394662638456[/C][/ROW]
[ROW][C]21[/C][C]9.5[/C][C]9.79615966354718[/C][C]-0.296159663547182[/C][/ROW]
[ROW][C]22[/C][C]14[/C][C]15.2444073461668[/C][C]-1.24440734616682[/C][/ROW]
[ROW][C]23[/C][C]12[/C][C]12.5705405673079[/C][C]-0.570540567307851[/C][/ROW]
[ROW][C]24[/C][C]14[/C][C]14.1768204512639[/C][C]-0.176820451263881[/C][/ROW]
[ROW][C]25[/C][C]11[/C][C]10.314300845653[/C][C]0.68569915434704[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]16.4026088372802[/C][C]-7.40260883728024[/C][/ROW]
[ROW][C]27[/C][C]11[/C][C]11.1692535719556[/C][C]-0.169253571955575[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]12.8037265428555[/C][C]2.19627345714451[/C][/ROW]
[ROW][C]29[/C][C]14[/C][C]12.0699401938899[/C][C]1.93005980611014[/C][/ROW]
[ROW][C]30[/C][C]13[/C][C]15.1140941897035[/C][C]-2.1140941897035[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]11.392540018812[/C][C]-2.392540018812[/C][/ROW]
[ROW][C]32[/C][C]15[/C][C]13.8438731003794[/C][C]1.15612689962058[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.3981273569197[/C][C]-0.398127356919727[/C][/ROW]
[ROW][C]34[/C][C]11[/C][C]11.9960132113143[/C][C]-0.996013211314307[/C][/ROW]
[ROW][C]35[/C][C]13[/C][C]12.8304141306696[/C][C]0.169585869330394[/C][/ROW]
[ROW][C]36[/C][C]8[/C][C]11.3369065944891[/C][C]-3.33690659448911[/C][/ROW]
[ROW][C]37[/C][C]20[/C][C]16.8598340092492[/C][C]3.14016599075082[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]11.9579205956792[/C][C]0.0420794043207937[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]10.6968462854815[/C][C]-0.696846285481465[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]13.5360073926914[/C][C]-3.53600739269135[/C][/ROW]
[ROW][C]41[/C][C]9[/C][C]11.9297275087353[/C][C]-2.92972750873532[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]11.2622268623487[/C][C]2.73777313765132[/C][/ROW]
[ROW][C]43[/C][C]8[/C][C]11.1220141771941[/C][C]-3.12201417719414[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.3063808581623[/C][C]-0.306380858162317[/C][/ROW]
[ROW][C]45[/C][C]11[/C][C]11.9289747591704[/C][C]-0.92897475917044[/C][/ROW]
[ROW][C]46[/C][C]13[/C][C]14.9837810332402[/C][C]-1.98378103324018[/C][/ROW]
[ROW][C]47[/C][C]9[/C][C]11.8283601887808[/C][C]-2.82836018878077[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]12.0607934147635[/C][C]-1.06079341476352[/C][/ROW]
[ROW][C]49[/C][C]15[/C][C]10.3714397691056[/C][C]4.62856023089439[/C][/ROW]
[ROW][C]50[/C][C]11[/C][C]13.433134573607[/C][C]-2.43313457360703[/C][/ROW]
[ROW][C]51[/C][C]10[/C][C]11.2911726988574[/C][C]-1.29117269885744[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]12.90509386281[/C][C]1.09490613718996[/C][/ROW]
[ROW][C]53[/C][C]18[/C][C]15.1887739218439[/C][C]2.81122607815607[/C][/ROW]
[ROW][C]54[/C][C]14[/C][C]14.2979868286009[/C][C]-0.297986828600866[/C][/ROW]
[ROW][C]55[/C][C]11[/C][C]14.4275472354993[/C][C]-3.4275472354993[/C][/ROW]
[ROW][C]56[/C][C]14.5[/C][C]11.9022871713563[/C][C]2.59771282864368[/C][/ROW]
[ROW][C]57[/C][C]13[/C][C]11.0663807528713[/C][C]1.93361924712874[/C][/ROW]
[ROW][C]58[/C][C]9[/C][C]12.2101528790444[/C][C]-3.21015287904439[/C][/ROW]
[ROW][C]59[/C][C]10[/C][C]14.2042607886429[/C][C]-4.20426078864288[/C][/ROW]
[ROW][C]60[/C][C]15[/C][C]14.297234079036[/C][C]0.702765920964017[/C][/ROW]
[ROW][C]61[/C][C]20[/C][C]17.6203079460289[/C][C]2.37969205397107[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]13.4148410153544[/C][C]-1.41484101535437[/C][/ROW]
[ROW][C]63[/C][C]12[/C][C]15.0958006314508[/C][C]-3.09580063145083[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]12.8966998332486[/C][C]1.10330016675141[/C][/ROW]
[ROW][C]65[/C][C]13[/C][C]12.0508938860723[/C][C]0.949106113927692[/C][/ROW]
[ROW][C]66[/C][C]11[/C][C]16.1962276500923[/C][C]-5.19622765009233[/C][/ROW]
[ROW][C]67[/C][C]17[/C][C]15.4068078768038[/C][C]1.59319212319619[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.9336478407648[/C][C]-2.93364784076482[/C][/ROW]
[ROW][C]69[/C][C]13[/C][C]12.1675605210776[/C][C]0.832439478922363[/C][/ROW]
[ROW][C]70[/C][C]14[/C][C]12.3443603227375[/C][C]1.65563967726249[/C][/ROW]
[ROW][C]71[/C][C]13[/C][C]13.0118609691242[/C][C]-0.0118609691241534[/C][/ROW]
[ROW][C]72[/C][C]15[/C][C]11.7141995424211[/C][C]3.28580045757892[/C][/ROW]
[ROW][C]73[/C][C]13[/C][C]12.3634066305551[/C][C]0.636593369444943[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]12.1957536080215[/C][C]-2.19575360802152[/C][/ROW]
[ROW][C]75[/C][C]11[/C][C]14.013914911013[/C][C]-3.01391491101299[/C][/ROW]
[ROW][C]76[/C][C]19[/C][C]14.5701487087539[/C][C]4.42985129124613[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]10.7289336596551[/C][C]2.27106634034486[/C][/ROW]
[ROW][C]78[/C][C]17[/C][C]13.9773277945077[/C][C]3.02267220549235[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]12.660620059987[/C][C]0.339379940012971[/C][/ROW]
[ROW][C]80[/C][C]9[/C][C]13.9018953128023[/C][C]-4.90189531280234[/C][/ROW]
[ROW][C]81[/C][C]11[/C][C]12.4281868340043[/C][C]-1.42818683400428[/C][/ROW]
[ROW][C]82[/C][C]9[/C][C]12.3443603227375[/C][C]-3.34436032273751[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]11.5358942416314[/C][C]0.464105758368557[/C][/ROW]
[ROW][C]84[/C][C]12[/C][C]12.4838202583272[/C][C]-0.48382025832716[/C][/ROW]
[ROW][C]85[/C][C]13[/C][C]13.2442941951069[/C][C]-0.244294195106908[/C][/ROW]
[ROW][C]86[/C][C]13[/C][C]12.2140471662742[/C][C]0.785952833725812[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]13.2168538577279[/C][C]-1.21685385772791[/C][/ROW]
[ROW][C]88[/C][C]15[/C][C]14.1548803457324[/C][C]0.845119654267592[/C][/ROW]
[ROW][C]89[/C][C]22[/C][C]18.618614895151[/C][C]3.38138510484901[/C][/ROW]
[ROW][C]90[/C][C]13[/C][C]10.9621196352028[/C][C]2.03788036479722[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]13.8935012832409[/C][C]1.10649871675911[/C][/ROW]
[ROW][C]92[/C][C]13[/C][C]12.3077732062322[/C][C]0.692226793767827[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]13.3090743985561[/C][C]1.69092560144387[/C][/ROW]
[ROW][C]94[/C][C]12.5[/C][C]14.1731739039851[/C][C]-1.67317390398507[/C][/ROW]
[ROW][C]95[/C][C]11[/C][C]11.433774172112[/C][C]-0.433774172112007[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]14.5990945452626[/C][C]1.40090545473737[/C][/ROW]
[ROW][C]97[/C][C]11[/C][C]13.1696144629665[/C][C]-2.16961446296647[/C][/ROW]
[ROW][C]98[/C][C]11[/C][C]10.7563739970341[/C][C]0.243626002965856[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]12.4655267000745[/C][C]-2.46552670007449[/C][/ROW]
[ROW][C]100[/C][C]10[/C][C]10.7007405727113[/C][C]-0.70074057271126[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.5990945452626[/C][C]1.40090545473737[/C][/ROW]
[ROW][C]102[/C][C]12[/C][C]11.5366469911963[/C][C]0.463353008803674[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]15.620194794969[/C][C]-4.62019479496902[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]12.4007464966253[/C][C]3.59925350337473[/C][/ROW]
[ROW][C]105[/C][C]19[/C][C]16.8256356808439[/C][C]2.17436431915612[/C][/ROW]
[ROW][C]106[/C][C]11[/C][C]11.4802608173086[/C][C]-0.480260817308558[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]12.1020275680635[/C][C]3.89797243193646[/C][/ROW]
[ROW][C]108[/C][C]15[/C][C]16.1771813422748[/C][C]-1.17718134227478[/C][/ROW]
[ROW][C]109[/C][C]24[/C][C]15.8517748258989[/C][C]8.14822517410108[/C][/ROW]
[ROW][C]110[/C][C]14[/C][C]12.5584999904676[/C][C]1.44150000953241[/C][/ROW]
[ROW][C]111[/C][C]15[/C][C]15.6118007654076[/C][C]-0.611800765407569[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]13.9605397353848[/C][C]-2.96053973538475[/C][/ROW]
[ROW][C]113[/C][C]15[/C][C]13.2633405029245[/C][C]1.73665949707554[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]9.98600053156318[/C][C]2.01399946843682[/C][/ROW]
[ROW][C]115[/C][C]10[/C][C]11.5450410207578[/C][C]-1.54504102075778[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.1619731829699[/C][C]0.838026817030095[/C][/ROW]
[ROW][C]117[/C][C]13[/C][C]13.1246333168997[/C][C]-0.124633316899688[/C][/ROW]
[ROW][C]118[/C][C]9[/C][C]13.2077070786016[/C][C]-4.20770707860157[/C][/ROW]
[ROW][C]119[/C][C]15[/C][C]13.0118609691242[/C][C]1.98813903087585[/C][/ROW]
[ROW][C]120[/C][C]15[/C][C]14.7301604512908[/C][C]0.269839548709165[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.3555610437527[/C][C]0.644438956247324[/C][/ROW]
[ROW][C]122[/C][C]11[/C][C]12.2140471662742[/C][C]-1.21404716627419[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]12.2605338114707[/C][C]-4.26053381147074[/C][/ROW]
[ROW][C]124[/C][C]11[/C][C]12.3619011314253[/C][C]-1.36190113142529[/C][/ROW]
[ROW][C]125[/C][C]11[/C][C]14.0710538344656[/C][C]-3.07105383446564[/C][/ROW]
[ROW][C]126[/C][C]8[/C][C]10.6999878231464[/C][C]-2.69998782314638[/C][/ROW]
[ROW][C]127[/C][C]10[/C][C]10.449261038911[/C][C]-0.449261038910956[/C][/ROW]
[ROW][C]128[/C][C]11[/C][C]9.34669297212042[/C][C]1.65330702787958[/C][/ROW]
[ROW][C]129[/C][C]13[/C][C]12.3809474392428[/C][C]0.619052560757159[/C][/ROW]
[ROW][C]130[/C][C]11[/C][C]14.0337139683954[/C][C]-3.03371396839542[/C][/ROW]
[ROW][C]131[/C][C]20[/C][C]17.2737140736865[/C][C]2.72628592631352[/C][/ROW]
[ROW][C]132[/C][C]10[/C][C]12.1576609923864[/C][C]-2.15766099238642[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.7071067051836[/C][C]2.29289329481642[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]12.2605338114707[/C][C]-0.260533811470739[/C][/ROW]
[ROW][C]135[/C][C]14[/C][C]11.7591806884879[/C][C]2.24081931151214[/C][/ROW]
[ROW][C]136[/C][C]23[/C][C]15.8244349340079[/C][C]7.17556506599211[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.1703672125314[/C][C]0.829632787468644[/C][/ROW]
[ROW][C]138[/C][C]16[/C][C]15.6308470732251[/C][C]0.369152926774881[/C][/ROW]
[ROW][C]139[/C][C]11[/C][C]12.3718006601165[/C][C]-1.37180066011651[/C][/ROW]
[ROW][C]140[/C][C]12[/C][C]14.052760276213[/C][C]-2.05276027621297[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]12.4838202583272[/C][C]-2.48382025832716[/C][/ROW]
[ROW][C]142[/C][C]14[/C][C]11.7606861876176[/C][C]2.23931381238237[/C][/ROW]
[ROW][C]143[/C][C]12[/C][C]13.3197266768122[/C][C]-1.31972667681222[/C][/ROW]
[ROW][C]144[/C][C]12[/C][C]12.621774694787[/C][C]-0.621774694787046[/C][/ROW]
[ROW][C]145[/C][C]11[/C][C]11.4421682016735[/C][C]-0.442168201673458[/C][/ROW]
[ROW][C]146[/C][C]12[/C][C]11.7774742467405[/C][C]0.22252575325947[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.3976610976775[/C][C]-2.39766109767748[/C][/ROW]
[ROW][C]148[/C][C]11[/C][C]14.8223809921191[/C][C]-3.82238099211905[/C][/ROW]
[ROW][C]149[/C][C]19[/C][C]17.012335011195[/C][C]1.98766498880504[/C][/ROW]
[ROW][C]150[/C][C]12[/C][C]11.4436737008032[/C][C]0.556326299196776[/C][/ROW]
[ROW][C]151[/C][C]17[/C][C]13.6237281911879[/C][C]3.37627180881208[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.6021799442104[/C][C]-2.60217994421043[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.6371871608977[/C][C]-2.63718716089773[/C][/ROW]
[ROW][C]154[/C][C]19[/C][C]16.4963348772382[/C][C]2.50366512276177[/C][/ROW]
[ROW][C]155[/C][C]18[/C][C]14.0146676605779[/C][C]3.98533233942213[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]13.8935012832409[/C][C]1.10649871675911[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.2267533864191[/C][C]0.773246613580877[/C][/ROW]
[ROW][C]158[/C][C]11[/C][C]9.34669297212042[/C][C]1.65330702787958[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]13.9681810153813[/C][C]-4.96818101538132[/C][/ROW]
[ROW][C]160[/C][C]18[/C][C]14.7583535382347[/C][C]3.24164646176528[/C][/ROW]
[ROW][C]161[/C][C]16[/C][C]13.931593898876[/C][C]2.06840610112401[/C][/ROW]
[ROW][C]162[/C][C]24[/C][C]16.9812481265372[/C][C]7.01875187346284[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.7503948003724[/C][C]0.249605199627572[/C][/ROW]
[ROW][C]164[/C][C]20[/C][C]11.8842413530546[/C][C]8.11575864694536[/C][/ROW]
[ROW][C]165[/C][C]18[/C][C]16.6009609354033[/C][C]1.3990390645967[/C][/ROW]
[ROW][C]166[/C][C]23[/C][C]16.2863071427715[/C][C]6.71369285722849[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]13.7237072125583[/C][C]-1.72370721255831[/C][/ROW]
[ROW][C]168[/C][C]14[/C][C]15.4869878407918[/C][C]-1.48698784079178[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]17.3804811800006[/C][C]-1.3804811800006[/C][/ROW]
[ROW][C]170[/C][C]18[/C][C]17.6510070216185[/C][C]0.34899297838155[/C][/ROW]
[ROW][C]171[/C][C]20[/C][C]15.7917421047324[/C][C]4.20825789526765[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.9223339686897[/C][C]0.077666031310257[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]17.1465424548881[/C][C]-5.14654245488808[/C][/ROW]
[ROW][C]174[/C][C]17[/C][C]14.6045947771102[/C][C]2.39540522288984[/C][/ROW]
[ROW][C]175[/C][C]13[/C][C]12.0046549808267[/C][C]0.995345019173255[/C][/ROW]
[ROW][C]176[/C][C]9[/C][C]14.4011073876362[/C][C]-5.40110738763617[/C][/ROW]
[ROW][C]177[/C][C]16[/C][C]17.3141954774216[/C][C]-1.31419547742161[/C][/ROW]
[ROW][C]178[/C][C]18[/C][C]15.2918944808792[/C][C]2.70810551912076[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]12.1639139737988[/C][C]-2.16391397379883[/C][/ROW]
[ROW][C]180[/C][C]14[/C][C]15.6995215639041[/C][C]-1.69952156390413[/C][/ROW]
[ROW][C]181[/C][C]11[/C][C]13.472227678758[/C][C]-2.47222767875801[/C][/ROW]
[ROW][C]182[/C][C]9[/C][C]14.3348216850572[/C][C]-5.33482168505719[/C][/ROW]
[ROW][C]183[/C][C]11[/C][C]12.8885535436381[/C][C]-1.88855354363813[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]13.4341350631229[/C][C]-3.43413506312291[/C][/ROW]
[ROW][C]185[/C][C]11[/C][C]12.5274131058098[/C][C]-1.52741310580979[/C][/ROW]
[ROW][C]186[/C][C]19[/C][C]14.3919606085098[/C][C]4.60803939149016[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.4905212370107[/C][C]0.509478762989327[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.6355685107081[/C][C]-0.635568510708058[/C][/ROW]
[ROW][C]189[/C][C]14[/C][C]14.6144943058014[/C][C]-0.614494305801377[/C][/ROW]
[ROW][C]190[/C][C]21[/C][C]15.9327075394518[/C][C]5.06729246054823[/C][/ROW]
[ROW][C]191[/C][C]13[/C][C]15.9327075394518[/C][C]-2.93270753945177[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]13.3609608301122[/C][C]-3.36096083011224[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.8786540149469[/C][C]2.12134598505309[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]15.8115411621148[/C][C]0.188458837885217[/C][/ROW]
[ROW][C]195[/C][C]14[/C][C]12.8878007940732[/C][C]1.11219920592676[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.9573411853771[/C][C]-2.95734118537705[/C][/ROW]
[ROW][C]197[/C][C]19[/C][C]13.5926413065301[/C][C]5.40735869346989[/C][/ROW]
[ROW][C]198[/C][C]15[/C][C]13.5751004978423[/C][C]1.42489950215768[/C][/ROW]
[ROW][C]199[/C][C]19[/C][C]18.2339284071734[/C][C]0.766071592826555[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]14.6525869214365[/C][C]-1.65258692143648[/C][/ROW]
[ROW][C]201[/C][C]17[/C][C]17.6030148772921[/C][C]-0.603014877292134[/C][/ROW]
[ROW][C]202[/C][C]12[/C][C]13.2048132808876[/C][C]-1.20481328088765[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]11.2815209101172[/C][C]-0.281520910117214[/C][/ROW]
[ROW][C]204[/C][C]14[/C][C]14.3538679928747[/C][C]-0.353867992874739[/C][/ROW]
[ROW][C]205[/C][C]11[/C][C]12.8321673697504[/C][C]-1.83216736975036[/C][/ROW]
[ROW][C]206[/C][C]13[/C][C]12.7765339454275[/C][C]0.223466054572524[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]13.5004207657019[/C][C]-1.50042076570189[/C][/ROW]
[ROW][C]208[/C][C]15[/C][C]11.9688206138863[/C][C]3.03117938611371[/C][/ROW]
[ROW][C]209[/C][C]14[/C][C]14.270041481608[/C][C]-0.270041481607971[/C][/ROW]
[ROW][C]210[/C][C]12[/C][C]12.0336008173355[/C][C]-0.033600817335512[/C][/ROW]
[ROW][C]211[/C][C]17[/C][C]17.4262150756323[/C][C]-0.426215075632264[/C][/ROW]
[ROW][C]212[/C][C]11[/C][C]11.6716071844543[/C][C]-0.671607184454322[/C][/ROW]
[ROW][C]213[/C][C]18[/C][C]15.9052672020728[/C][C]2.09473279792723[/C][/ROW]
[ROW][C]214[/C][C]13[/C][C]16.8143478535685[/C][C]-3.8143478535685[/C][/ROW]
[ROW][C]215[/C][C]17[/C][C]15.8298347203674[/C][C]1.17016527963255[/C][/ROW]
[ROW][C]216[/C][C]13[/C][C]13.1011877122384[/C][C]-0.101187712238448[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]11.2822736596821[/C][C]-0.282273659682097[/C][/ROW]
[ROW][C]218[/C][C]12[/C][C]13.3785016388[/C][C]-1.37850163880002[/C][/ROW]
[ROW][C]219[/C][C]22[/C][C]18.1036152507101[/C][C]3.89638474928987[/C][/ROW]
[ROW][C]220[/C][C]14[/C][C]12.674413875908[/C][C]1.32558612409196[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]15.8481282786201[/C][C]-3.84812827862012[/C][/ROW]
[ROW][C]222[/C][C]12[/C][C]11.8568010156756[/C][C]0.143198984324358[/C][/ROW]
[ROW][C]223[/C][C]17[/C][C]16.7023282553578[/C][C]0.29767174464215[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]12.9251406601435[/C][C]-3.92514066014346[/C][/ROW]
[ROW][C]225[/C][C]21[/C][C]17.3987747382533[/C][C]3.60122526174674[/C][/ROW]
[ROW][C]226[/C][C]10[/C][C]12.0808402120969[/C][C]-2.08084021209695[/C][/ROW]
[ROW][C]227[/C][C]11[/C][C]9.8436467982596[/C][C]1.1563532017404[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]15.1432877661633[/C][C]-3.14328776616325[/C][/ROW]
[ROW][C]229[/C][C]23[/C][C]18.1965885411032[/C][C]4.80341145889677[/C][/ROW]
[ROW][C]230[/C][C]13[/C][C]15.8671745864377[/C][C]-2.86717458643767[/C][/ROW]
[ROW][C]231[/C][C]12[/C][C]13.6017880856564[/C][C]-1.60178808565644[/C][/ROW]
[ROW][C]232[/C][C]16[/C][C]17.4178210460708[/C][C]-1.41782104607081[/C][/ROW]
[ROW][C]233[/C][C]9[/C][C]12.8695072358206[/C][C]-3.86950723582058[/C][/ROW]
[ROW][C]234[/C][C]17[/C][C]14.0833421512569[/C][C]2.91665784874312[/C][/ROW]
[ROW][C]235[/C][C]9[/C][C]12.0427475964618[/C][C]-3.04274759646185[/C][/ROW]
[ROW][C]236[/C][C]14[/C][C]15.8290819708026[/C][C]-1.82908197080257[/C][/ROW]
[ROW][C]237[/C][C]17[/C][C]15.0305154183877[/C][C]1.96948458161228[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.324922156366[/C][C]-1.32492215636597[/C][/ROW]
[ROW][C]239[/C][C]11[/C][C]16.8608344987651[/C][C]-5.86083449876505[/C][/ROW]
[ROW][C]240[/C][C]12[/C][C]15.8008888838587[/C][C]-3.80088888385868[/C][/ROW]
[ROW][C]241[/C][C]10[/C][C]15.3856205208372[/C][C]-5.38562052083723[/C][/ROW]
[ROW][C]242[/C][C]19[/C][C]18.1409551167803[/C][C]0.859044883219656[/C][/ROW]
[ROW][C]243[/C][C]16[/C][C]15.3848677712723[/C][C]0.615132228727659[/C][/ROW]
[ROW][C]244[/C][C]16[/C][C]15.0777548131492[/C][C]0.922245186850847[/C][/ROW]
[ROW][C]245[/C][C]14[/C][C]12.7102482428485[/C][C]1.28975175715151[/C][/ROW]
[ROW][C]246[/C][C]20[/C][C]16.0538739167888[/C][C]3.94612608321125[/C][/ROW]
[ROW][C]247[/C][C]15[/C][C]14.4011073876362[/C][C]0.598892612363827[/C][/ROW]
[ROW][C]248[/C][C]23[/C][C]13.5088147952633[/C][C]9.49118520473666[/C][/ROW]
[ROW][C]249[/C][C]20[/C][C]17.3257009507306[/C][C]2.67429904926944[/C][/ROW]
[ROW][C]250[/C][C]16[/C][C]15.7194210667745[/C][C]0.280578933225469[/C][/ROW]
[ROW][C]251[/C][C]14[/C][C]12.9068471018908[/C][C]1.09315289810921[/C][/ROW]
[ROW][C]252[/C][C]17[/C][C]14.391207858945[/C][C]2.60879214105504[/C][/ROW]
[ROW][C]253[/C][C]11[/C][C]14.2608947024816[/C][C]-3.26089470248164[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]14.391207858945[/C][C]-1.39120785894496[/C][/ROW]
[ROW][C]255[/C][C]17[/C][C]15.0030750810087[/C][C]1.99692491899128[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]15.1150946792194[/C][C]-0.11509467921937[/C][/ROW]
[ROW][C]257[/C][C]21[/C][C]17.3522880930567[/C][C]3.64771190694329[/C][/ROW]
[ROW][C]258[/C][C]18[/C][C]17.5473814529693[/C][C]0.45261854703075[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.6828079054695[/C][C]2.31719209453051[/C][/ROW]
[ROW][C]260[/C][C]8[/C][C]16.6459420814701[/C][C]-8.64594208147008[/C][/ROW]
[ROW][C]261[/C][C]12[/C][C]13.863167148148[/C][C]-1.86316714814796[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]12.7582403871748[/C][C]-0.758240387174809[/C][/ROW]
[ROW][C]263[/C][C]22[/C][C]18.7154824727739[/C][C]3.28451752722611[/C][/ROW]
[ROW][C]264[/C][C]12[/C][C]13.7701938577549[/C][C]-1.77019385775486[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145480&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145480&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
11212.4958608351674-0.495860835167416
2119.5439273801821.45607261981801
31415.2451600957317-1.2451600957317
41214.4557403224432-2.45574032244319
52111.22563974584339.77436025415666
6129.720727181841862.27927281815814
72212.63456802119229.36543197880782
81112.7755334559116-1.7755334559116
91011.9396270374265-1.93962703742654
101311.87484683397731.12515316602268
111010.3607874908495-0.36078749084951
1288.86727995466902-0.867279954669015
131515.7168146326409-0.716814632640927
141411.02979363636592.97020636363408
15109.722232680971630.27776731902837
161412.8776535254311.12234647456896
171412.73744084027651.2625591597235
181110.29676003696520.703239963034825
191012.5705405673078-2.57054056730785
201311.34605337361541.65394662638456
219.59.79615966354718-0.296159663547182
221415.2444073461668-1.24440734616682
231212.5705405673079-0.570540567307851
241414.1768204512639-0.176820451263881
251110.3143008456530.68569915434704
26916.4026088372802-7.40260883728024
271111.1692535719556-0.169253571955575
281512.80372654285552.19627345714451
291412.06994019388991.93005980611014
301315.1140941897035-2.1140941897035
31911.392540018812-2.392540018812
321513.84387310037941.15612689962058
331010.3981273569197-0.398127356919727
341111.9960132113143-0.996013211314307
351312.83041413066960.169585869330394
36811.3369065944891-3.33690659448911
372016.85983400924923.14016599075082
381211.95792059567920.0420794043207937
391010.6968462854815-0.696846285481465
401013.5360073926914-3.53600739269135
41911.9297275087353-2.92972750873532
421411.26222686234872.73777313765132
43811.1220141771941-3.12201417719414
441414.3063808581623-0.306380858162317
451111.9289747591704-0.92897475917044
461314.9837810332402-1.98378103324018
47911.8283601887808-2.82836018878077
481112.0607934147635-1.06079341476352
491510.37143976910564.62856023089439
501113.433134573607-2.43313457360703
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551114.4275472354993-3.4275472354993
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58912.2101528790444-3.21015287904439
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601514.2972340790360.702765920964017
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721511.71419954242113.28580045757892
731312.36340663055510.636593369444943
741012.1957536080215-2.19575360802152
751114.013914911013-3.01391491101299
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771310.72893365965512.27106634034486
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1021211.53664699119630.463353008803674
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1121113.9605397353848-2.96053973538475
1131513.26334050292451.73665949707554
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1161413.16197318296990.838026817030095
1171313.1246333168997-0.124633316899688
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1191513.01186096912421.98813903087585
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1211413.35556104375270.644438956247324
1221112.2140471662742-1.21404716627419
123812.2605338114707-4.26053381147074
1241112.3619011314253-1.36190113142529
1251114.0710538344656-3.07105383446564
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1271010.449261038911-0.449261038910956
128119.346692972120421.65330702787958
1291312.38094743924280.619052560757159
1301114.0337139683954-3.03371396839542
1312017.27371407368652.72628592631352
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1331512.70710670518362.29289329481642
1341212.2605338114707-0.260533811470739
1351411.75918068848792.24081931151214
1362315.82443493400797.17556506599211
1371413.17036721253140.829632787468644
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1391112.3718006601165-1.37180066011651
1401214.052760276213-2.05276027621297
1411012.4838202583272-2.48382025832716
1421411.76068618761762.23931381238237
1431213.3197266768122-1.31972667681222
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1471315.3976610976775-2.39766109767748
1481114.8223809921191-3.82238099211905
1491917.0123350111951.98766498880504
1501211.44367370080320.556326299196776
1511713.62372819118793.37627180881208
152911.6021799442104-2.60217994421043
1531214.6371871608977-2.63718716089773
1541916.49633487723822.50366512276177
1551814.01466766057793.98533233942213
1561513.89350128324091.10649871675911
1571413.22675338641910.773246613580877
158119.346692972120421.65330702787958
159913.9681810153813-4.96818101538132
1601814.75835353823473.24164646176528
1611613.9315938988762.06840610112401
1622416.98124812653727.01875187346284
1631413.75039480037240.249605199627572
1642011.88424135305468.11575864694536
1651816.60096093540331.3990390645967
1662316.28630714277156.71369285722849
1671213.7237072125583-1.72370721255831
1681415.4869878407918-1.48698784079178
1691617.3804811800006-1.3804811800006
1701817.65100702161850.34899297838155
1712015.79174210473244.20825789526765
1721211.92233396868970.077666031310257
1731217.1465424548881-5.14654245488808
1741714.60459477711022.39540522288984
1751312.00465498082670.995345019173255
176914.4011073876362-5.40110738763617
1771617.3141954774216-1.31419547742161
1781815.29189448087922.70810551912076
1791012.1639139737988-2.16391397379883
1801415.6995215639041-1.69952156390413
1811113.472227678758-2.47222767875801
182914.3348216850572-5.33482168505719
1831112.8885535436381-1.88855354363813
1841013.4341350631229-3.43413506312291
1851112.5274131058098-1.52741310580979
1861914.39196060850984.60803939149016
1871413.49052123701070.509478762989327
1881212.6355685107081-0.635568510708058
1891414.6144943058014-0.614494305801377
1902115.93270753945185.06729246054823
1911315.9327075394518-2.93270753945177
1921013.3609608301122-3.36096083011224
1931512.87865401494692.12134598505309
1941615.81154116211480.188458837885217
1951412.88780079407321.11219920592676
1961214.9573411853771-2.95734118537705
1971913.59264130653015.40735869346989
1981513.57510049784231.42489950215768
1991918.23392840717340.766071592826555
2001314.6525869214365-1.65258692143648
2011717.6030148772921-0.603014877292134
2021213.2048132808876-1.20481328088765
2031111.2815209101172-0.281520910117214
2041414.3538679928747-0.353867992874739
2051112.8321673697504-1.83216736975036
2061312.77653394542750.223466054572524
2071213.5004207657019-1.50042076570189
2081511.96882061388633.03117938611371
2091414.270041481608-0.270041481607971
2101212.0336008173355-0.033600817335512
2111717.4262150756323-0.426215075632264
2121111.6716071844543-0.671607184454322
2131815.90526720207282.09473279792723
2141316.8143478535685-3.8143478535685
2151715.82983472036741.17016527963255
2161313.1011877122384-0.101187712238448
2171111.2822736596821-0.282273659682097
2181213.3785016388-1.37850163880002
2192218.10361525071013.89638474928987
2201412.6744138759081.32558612409196
2211215.8481282786201-3.84812827862012
2221211.85680101567560.143198984324358
2231716.70232825535780.29767174464215
224912.9251406601435-3.92514066014346
2252117.39877473825333.60122526174674
2261012.0808402120969-2.08084021209695
227119.84364679825961.1563532017404
2281215.1432877661633-3.14328776616325
2292318.19658854110324.80341145889677
2301315.8671745864377-2.86717458643767
2311213.6017880856564-1.60178808565644
2321617.4178210460708-1.41782104607081
233912.8695072358206-3.86950723582058
2341714.08334215125692.91665784874312
235912.0427475964618-3.04274759646185
2361415.8290819708026-1.82908197080257
2371715.03051541838771.96948458161228
2381314.324922156366-1.32492215636597
2391116.8608344987651-5.86083449876505
2401215.8008888838587-3.80088888385868
2411015.3856205208372-5.38562052083723
2421918.14095511678030.859044883219656
2431615.38486777127230.615132228727659
2441615.07775481314920.922245186850847
2451412.71024824284851.28975175715151
2462016.05387391678883.94612608321125
2471514.40110738763620.598892612363827
2482313.50881479526339.49118520473666
2492017.32570095073062.67429904926944
2501615.71942106677450.280578933225469
2511412.90684710189081.09315289810921
2521714.3912078589452.60879214105504
2531114.2608947024816-3.26089470248164
2541314.391207858945-1.39120785894496
2551715.00307508100871.99692491899128
2561515.1150946792194-0.11509467921937
2572117.35228809305673.64771190694329
2581817.54738145296930.45261854703075
2591512.68280790546952.31719209453051
260816.6459420814701-8.64594208147008
2611213.863167148148-1.86316714814796
2621212.7582403871748-0.758240387174809
2632218.71548247277393.28451752722611
2641213.7701938577549-1.77019385775486






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.9996072048344770.0007855903310451820.000392795165522591
90.9995580261047160.0008839477905685220.000441973895284261
100.9988870866132660.002225826773468490.00111291338673425
110.9986644945580750.002671010883849290.00133550544192464
120.9981839983460320.003632003307936720.00181600165396836
130.9967677771671570.006464445665686350.00323222283284318
140.99460331825620.01079336348760060.00539668174380031
150.9905980705644530.01880385887109430.00940192943554715
160.9848333808772960.03033323824540850.0151666191227042
170.9758737518124360.04825249637512750.0241262481875637
180.9641237471608740.07175250567825180.0358762528391259
190.9652602673010840.06947946539783180.0347397326989159
200.950322201335960.0993555973280780.049677798664039
210.934423368102080.1311532637958410.0655766318979205
220.9130109059847430.1739781880305140.086989094015257
230.8872564333639960.2254871332720080.112743566636004
240.8527332812172660.2945334375654680.147266718782734
250.8214850184100660.3570299631798690.178514981589934
260.9281246579943930.1437506840112140.0718753420056072
270.9079582164993460.1840835670013070.0920417835006537
280.893094126205710.213811747588580.10690587379429
290.8697456294196650.2605087411606710.130254370580335
300.8413573546147320.3172852907705350.158642645385268
310.8491897296508640.3016205406982720.150810270349136
320.8214436263308810.3571127473382380.178556373669119
330.7906670670081940.4186658659836120.209332932991806
340.7620309901591070.4759380196817860.237969009840893
350.7183585841537640.5632828316924720.281641415846236
360.758326716009540.483346567980920.24167328399046
370.8094897682702520.3810204634594960.190510231729748
380.7722107458263950.4555785083472090.227789254173605
390.7457827726089980.5084344547820040.254217227391002
400.7558044248228420.4883911503543150.244195575177158
410.7546707671042810.4906584657914380.245329232895719
420.7409598925058460.5180802149883080.259040107494154
430.7474146928440290.5051706143119430.252585307155971
440.707735040791010.5845299184179810.292264959208991
450.6655286158658020.6689427682683960.334471384134198
460.6285762374383910.7428475251232180.371423762561609
470.6321704805817370.7356590388365260.367829519418263
480.5962127267827330.8075745464345340.403787273217267
490.6361884286577420.7276231426845150.363811571342258
500.6069949086540710.7860101826918580.393005091345929
510.5899260989273910.8201478021452170.410073901072609
520.5534832186934960.8930335626130070.446516781306504
530.5733282745111450.853343450977710.426671725488855
540.5286522631202150.942695473759570.471347736879785
550.536270913557960.927458172884080.46372908644204
560.5292699556610670.9414600886778650.470730044338933
570.5047271209167140.9905457581665730.495272879083286
580.5341175743290490.93176485134190.46588242567095
590.5630587484796520.8738825030406970.436941251520348
600.5303773088480640.9392453823038710.469622691151936
610.5571535505622790.8856928988754430.442846449437721
620.5209165388423190.9581669223153620.479083461157681
630.5154081980030340.9691836039939330.484591801996966
640.4775567225627950.955113445125590.522443277437205
650.4386737818984570.8773475637969130.561326218101543
660.4370045000895660.8740090001791320.562995499910434
670.4843975247562780.9687950495125560.515602475243722
680.4670634079590910.9341268159181820.532936592040909
690.4409752331011830.8819504662023650.559024766898817
700.4184810671019550.836962134203910.581518932898045
710.3800437256186340.7600874512372680.619956274381366
720.3771304700077510.7542609400155020.622869529992249
730.339864266934350.6797285338686990.66013573306565
740.329006188917150.65801237783430.67099381108285
750.3222299315092890.6444598630185770.677770068490711
760.417499190707760.834998381415520.58250080929224
770.3935750177457780.7871500354915560.606424982254222
780.396253913111990.7925078262239810.60374608688801
790.3608681690275580.7217363380551170.639131830972442
800.434120808598540.868241617197080.56587919140146
810.4114228477296830.8228456954593660.588577152270317
820.4325073016793960.8650146033587920.567492698320604
830.3953006814465550.790601362893110.604699318553445
840.3603472151432150.720694430286430.639652784856785
850.3251948122452180.6503896244904350.674805187754782
860.2939995991027780.5879991982055560.706000400897222
870.2672374685190790.5344749370381580.732762531480921
880.2404600557963240.4809201115926490.759539944203676
890.2900774133238440.5801548266476880.709922586676156
900.2684693786676520.5369387573353040.731530621332348
910.2441034243582080.4882068487164160.755896575641792
920.2163324745118320.4326649490236640.783667525488168
930.1975162623751030.3950325247502060.802483737624897
940.1830695858147310.3661391716294620.816930414185269
950.1603919867759250.320783973551850.839608013224075
960.1458090092839740.2916180185679480.854190990716026
970.1383186333619670.2766372667239340.861681366638033
980.1189123244474890.2378246488949770.881087675552511
990.118287423482020.236574846964040.88171257651798
1000.1028689836474230.2057379672948460.897131016352577
1010.09261758228684320.1852351645736860.907382417713157
1020.07833318148643060.1566663629728610.92166681851357
1030.1010783037566480.2021566075132960.898921696243352
1040.1089487051914780.2178974103829570.891051294808522
1050.1101702338768210.2203404677536410.88982976612318
1060.0948106543597430.1896213087194860.905189345640257
1070.1070624417756310.2141248835512610.89293755822437
1080.09381806971635520.187636139432710.906181930283645
1090.2474891428187850.494978285637570.752510857181215
1100.2260612965907770.4521225931815530.773938703409223
1110.2010510811096560.4021021622193120.798948918890344
1120.2113750763004380.4227501526008760.788624923699562
1130.1952139694595240.3904279389190480.804786030540476
1140.1809774018187750.361954803637550.819022598181225
1150.1667172772811180.3334345545622360.833282722718882
1160.1468221766564820.2936443533129650.853177823343518
1170.1282015453907290.2564030907814580.871798454609271
1180.1554532600394060.3109065200788120.844546739960594
1190.1432505803549530.2865011607099070.856749419645047
1200.1240212474393470.2480424948786950.875978752560653
1210.1085596925912920.2171193851825840.891440307408708
1220.0978391904941310.1956783809882620.902160809505869
1230.1244556527963210.2489113055926420.875544347203679
1240.1114551092427530.2229102184855050.888544890757247
1250.1147163754739210.2294327509478420.885283624526079
1260.1158010065949560.2316020131899130.884198993405044
1270.1011879043476740.2023758086953490.898812095652326
1280.09063002323973840.1812600464794770.909369976760262
1290.07743929951041180.1548785990208240.922560700489588
1300.08001256210030550.1600251242006110.919987437899695
1310.08108830699979270.1621766139995850.918911693000207
1320.07716450427327290.1543290085465460.922835495726727
1330.072815365575510.145630731151020.92718463442449
1340.0615520620700860.1231041241401720.938447937929914
1350.05731295909028370.1146259181805670.942687040909716
1360.1344783591628730.2689567183257470.865521640837127
1370.1173472311382810.2346944622765620.88265276886172
1380.1008906515355390.2017813030710770.899109348464461
1390.08984602182263570.1796920436452710.910153978177364
1400.08397044778430410.1679408955686080.916029552215696
1410.08210989805173130.1642197961034630.917890101948269
1420.07616863765538790.1523372753107760.923831362344612
1430.06719315123161910.1343863024632380.932806848768381
1440.0573385394866670.1146770789733340.942661460513333
1450.04825944368876060.09651888737752120.95174055631124
1460.03997556118167340.07995112236334680.960024438818327
1470.0387624294132940.07752485882658790.961237570586706
1480.04842877127011570.09685754254023140.951571228729884
1490.04339629588946140.08679259177892280.956603704110539
1500.035840915248330.07168183049665990.96415908475167
1510.03713745297034610.07427490594069220.962862547029654
1520.03735416308947770.07470832617895540.962645836910522
1530.03872050898899210.07744101797798420.961279491011008
1540.03511502818861030.07023005637722050.96488497181139
1550.03892813670109820.07785627340219640.961071863298902
1560.03245710022365810.06491420044731610.967542899776342
1570.02664988761451810.05329977522903620.973350112385482
1580.0229723240798750.045944648159750.977027675920125
1590.04174409588830390.08348819177660770.958255904111696
1600.03909119308203120.07818238616406250.960908806917969
1610.03356643733015740.06713287466031480.966433562669843
1620.07858055777607490.157161115552150.921419442223925
1630.06630712477444120.1326142495488820.933692875225559
1640.1881663414070710.3763326828141420.811833658592929
1650.1679651731934180.3359303463868360.832034826806582
1660.2777442397354790.5554884794709590.72225576026452
1670.2639112786601630.5278225573203270.736088721339837
1680.2472515066303560.4945030132607120.752748493369644
1690.2287210451762380.4574420903524760.771278954823762
1700.2023296698421270.4046593396842530.797670330157873
1710.2274337537541190.4548675075082380.772566246245881
1720.2018927367195110.4037854734390220.798107263280489
1730.2795124403993880.5590248807987760.720487559600612
1740.2714009332563960.5428018665127920.728599066743604
1750.2473862841532880.4947725683065760.752613715846712
1760.3358046842648730.6716093685297470.664195315735127
1770.3120854654730490.6241709309460980.687914534526951
1780.3098749630259040.6197499260518070.690125036974096
1790.2950026719393540.5900053438787090.704997328060646
1800.2776472841112410.5552945682224810.722352715888759
1810.2709587096245980.5419174192491960.729041290375402
1820.3536739879374880.7073479758749760.646326012062512
1830.3323863445296920.6647726890593840.667613655470308
1840.3496483300054540.6992966600109090.650351669994546
1850.3215456526947830.6430913053895650.678454347305217
1860.382340502687620.764681005375240.61765949731238
1870.34647807184190.69295614368380.6535219281581
1880.3135783022960080.6271566045920170.686421697703992
1890.2806484399280530.5612968798561060.719351560071947
1900.3598867611188250.719773522237650.640113238881175
1910.3587939821179820.7175879642359640.641206017882018
1920.3771859933799660.7543719867599310.622814006620034
1930.3647257544426160.7294515088852310.635274245557384
1940.3274492057127220.6548984114254430.672550794287278
1950.2998398882052170.5996797764104340.700160111794783
1960.3089901596298570.6179803192597130.691009840370143
1970.4145665294691490.8291330589382970.585433470530851
1980.386253053819920.772506107639840.61374694618008
1990.3484998690908720.6969997381817450.651500130909128
2000.3179311825497090.6358623650994180.682068817450291
2010.2827998304230870.5655996608461740.717200169576913
2020.2518164170565680.5036328341131360.748183582943432
2030.220106690388720.440213380777440.77989330961128
2040.190220648063710.380441296127420.80977935193629
2050.170509931957890.3410198639157810.82949006804211
2060.1452053871366550.2904107742733110.854794612863345
2070.1278510792872020.2557021585744040.872148920712798
2080.1331679714350380.2663359428700750.866832028564962
2090.1112872517825770.2225745035651550.888712748217423
2100.09241748703360240.1848349740672050.907582512966398
2110.07644087629952340.1528817525990470.923559123700477
2120.06321862797877710.1264372559575540.936781372021223
2130.05624365524510630.1124873104902130.943756344754894
2140.06385211554897270.1277042310979450.936147884451027
2150.05214372145934650.1042874429186930.947856278540653
2160.04225143903600890.08450287807201770.95774856096399
2170.03322780711089060.06645561422178110.96677219288911
2180.02731288275057610.05462576550115230.972687117249424
2190.02906357336866880.05812714673733770.970936426631331
2200.02367806291920010.04735612583840030.9763219370808
2210.02894068248517430.05788136497034860.971059317514826
2220.02195144031081810.04390288062163620.978048559689182
2230.0163747461188180.0327494922376360.983625253881182
2240.01759835123535550.03519670247071110.982401648764644
2250.01893551593767460.03787103187534930.981064484062325
2260.01518719940741860.03037439881483710.984812800592581
2270.01249805773056530.02499611546113070.987501942269435
2280.01226989982544430.02453979965088850.987730100174556
2290.01808914861851520.03617829723703040.981910851381485
2300.01709583167218850.03419166334437690.982904168327812
2310.0132847538830490.0265695077660980.98671524611695
2320.01015695700573120.02031391401146240.989843042994269
2330.01215631368542980.02431262737085950.98784368631457
2340.01066922244244740.02133844488489470.989330777557553
2350.01099026757501210.02198053515002420.989009732424988
2360.008607089284437660.01721417856887530.991392910715562
2370.006601507754743760.01320301550948750.993398492245256
2380.004646036001210980.009292072002421970.99535396399879
2390.01166462777482290.02332925554964580.988335372225177
2400.01609770406450330.03219540812900660.983902295935497
2410.03679100057031360.07358200114062710.963208999429686
2420.0256423669698610.05128473393972190.97435763303014
2430.01723629147921710.03447258295843430.982763708520783
2440.01124115745808860.02248231491617710.988758842541911
2450.007358561779319680.01471712355863940.99264143822068
2460.007016590584511690.01403318116902340.992983409415488
2470.004163437327544420.008326874655088850.995836562672456
2480.1325759585665150.2651519171330290.867424041433485
2490.1224307423854710.2448614847709420.877569257614529
2500.2065311971340260.4130623942680510.793468802865974
2510.1509060948606460.3018121897212920.849093905139354
2520.199256927279940.398513854559880.80074307272006
2530.1992780324176180.3985560648352360.800721967582382
2540.1272190554149230.2544381108298460.872780944585077
2550.1128930216283530.2257860432567060.887106978371647
2560.0611320346664580.1222640693329160.938867965333542

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.999607204834477 & 0.000785590331045182 & 0.000392795165522591 \tabularnewline
9 & 0.999558026104716 & 0.000883947790568522 & 0.000441973895284261 \tabularnewline
10 & 0.998887086613266 & 0.00222582677346849 & 0.00111291338673425 \tabularnewline
11 & 0.998664494558075 & 0.00267101088384929 & 0.00133550544192464 \tabularnewline
12 & 0.998183998346032 & 0.00363200330793672 & 0.00181600165396836 \tabularnewline
13 & 0.996767777167157 & 0.00646444566568635 & 0.00323222283284318 \tabularnewline
14 & 0.9946033182562 & 0.0107933634876006 & 0.00539668174380031 \tabularnewline
15 & 0.990598070564453 & 0.0188038588710943 & 0.00940192943554715 \tabularnewline
16 & 0.984833380877296 & 0.0303332382454085 & 0.0151666191227042 \tabularnewline
17 & 0.975873751812436 & 0.0482524963751275 & 0.0241262481875637 \tabularnewline
18 & 0.964123747160874 & 0.0717525056782518 & 0.0358762528391259 \tabularnewline
19 & 0.965260267301084 & 0.0694794653978318 & 0.0347397326989159 \tabularnewline
20 & 0.95032220133596 & 0.099355597328078 & 0.049677798664039 \tabularnewline
21 & 0.93442336810208 & 0.131153263795841 & 0.0655766318979205 \tabularnewline
22 & 0.913010905984743 & 0.173978188030514 & 0.086989094015257 \tabularnewline
23 & 0.887256433363996 & 0.225487133272008 & 0.112743566636004 \tabularnewline
24 & 0.852733281217266 & 0.294533437565468 & 0.147266718782734 \tabularnewline
25 & 0.821485018410066 & 0.357029963179869 & 0.178514981589934 \tabularnewline
26 & 0.928124657994393 & 0.143750684011214 & 0.0718753420056072 \tabularnewline
27 & 0.907958216499346 & 0.184083567001307 & 0.0920417835006537 \tabularnewline
28 & 0.89309412620571 & 0.21381174758858 & 0.10690587379429 \tabularnewline
29 & 0.869745629419665 & 0.260508741160671 & 0.130254370580335 \tabularnewline
30 & 0.841357354614732 & 0.317285290770535 & 0.158642645385268 \tabularnewline
31 & 0.849189729650864 & 0.301620540698272 & 0.150810270349136 \tabularnewline
32 & 0.821443626330881 & 0.357112747338238 & 0.178556373669119 \tabularnewline
33 & 0.790667067008194 & 0.418665865983612 & 0.209332932991806 \tabularnewline
34 & 0.762030990159107 & 0.475938019681786 & 0.237969009840893 \tabularnewline
35 & 0.718358584153764 & 0.563282831692472 & 0.281641415846236 \tabularnewline
36 & 0.75832671600954 & 0.48334656798092 & 0.24167328399046 \tabularnewline
37 & 0.809489768270252 & 0.381020463459496 & 0.190510231729748 \tabularnewline
38 & 0.772210745826395 & 0.455578508347209 & 0.227789254173605 \tabularnewline
39 & 0.745782772608998 & 0.508434454782004 & 0.254217227391002 \tabularnewline
40 & 0.755804424822842 & 0.488391150354315 & 0.244195575177158 \tabularnewline
41 & 0.754670767104281 & 0.490658465791438 & 0.245329232895719 \tabularnewline
42 & 0.740959892505846 & 0.518080214988308 & 0.259040107494154 \tabularnewline
43 & 0.747414692844029 & 0.505170614311943 & 0.252585307155971 \tabularnewline
44 & 0.70773504079101 & 0.584529918417981 & 0.292264959208991 \tabularnewline
45 & 0.665528615865802 & 0.668942768268396 & 0.334471384134198 \tabularnewline
46 & 0.628576237438391 & 0.742847525123218 & 0.371423762561609 \tabularnewline
47 & 0.632170480581737 & 0.735659038836526 & 0.367829519418263 \tabularnewline
48 & 0.596212726782733 & 0.807574546434534 & 0.403787273217267 \tabularnewline
49 & 0.636188428657742 & 0.727623142684515 & 0.363811571342258 \tabularnewline
50 & 0.606994908654071 & 0.786010182691858 & 0.393005091345929 \tabularnewline
51 & 0.589926098927391 & 0.820147802145217 & 0.410073901072609 \tabularnewline
52 & 0.553483218693496 & 0.893033562613007 & 0.446516781306504 \tabularnewline
53 & 0.573328274511145 & 0.85334345097771 & 0.426671725488855 \tabularnewline
54 & 0.528652263120215 & 0.94269547375957 & 0.471347736879785 \tabularnewline
55 & 0.53627091355796 & 0.92745817288408 & 0.46372908644204 \tabularnewline
56 & 0.529269955661067 & 0.941460088677865 & 0.470730044338933 \tabularnewline
57 & 0.504727120916714 & 0.990545758166573 & 0.495272879083286 \tabularnewline
58 & 0.534117574329049 & 0.9317648513419 & 0.46588242567095 \tabularnewline
59 & 0.563058748479652 & 0.873882503040697 & 0.436941251520348 \tabularnewline
60 & 0.530377308848064 & 0.939245382303871 & 0.469622691151936 \tabularnewline
61 & 0.557153550562279 & 0.885692898875443 & 0.442846449437721 \tabularnewline
62 & 0.520916538842319 & 0.958166922315362 & 0.479083461157681 \tabularnewline
63 & 0.515408198003034 & 0.969183603993933 & 0.484591801996966 \tabularnewline
64 & 0.477556722562795 & 0.95511344512559 & 0.522443277437205 \tabularnewline
65 & 0.438673781898457 & 0.877347563796913 & 0.561326218101543 \tabularnewline
66 & 0.437004500089566 & 0.874009000179132 & 0.562995499910434 \tabularnewline
67 & 0.484397524756278 & 0.968795049512556 & 0.515602475243722 \tabularnewline
68 & 0.467063407959091 & 0.934126815918182 & 0.532936592040909 \tabularnewline
69 & 0.440975233101183 & 0.881950466202365 & 0.559024766898817 \tabularnewline
70 & 0.418481067101955 & 0.83696213420391 & 0.581518932898045 \tabularnewline
71 & 0.380043725618634 & 0.760087451237268 & 0.619956274381366 \tabularnewline
72 & 0.377130470007751 & 0.754260940015502 & 0.622869529992249 \tabularnewline
73 & 0.33986426693435 & 0.679728533868699 & 0.66013573306565 \tabularnewline
74 & 0.32900618891715 & 0.6580123778343 & 0.67099381108285 \tabularnewline
75 & 0.322229931509289 & 0.644459863018577 & 0.677770068490711 \tabularnewline
76 & 0.41749919070776 & 0.83499838141552 & 0.58250080929224 \tabularnewline
77 & 0.393575017745778 & 0.787150035491556 & 0.606424982254222 \tabularnewline
78 & 0.39625391311199 & 0.792507826223981 & 0.60374608688801 \tabularnewline
79 & 0.360868169027558 & 0.721736338055117 & 0.639131830972442 \tabularnewline
80 & 0.43412080859854 & 0.86824161719708 & 0.56587919140146 \tabularnewline
81 & 0.411422847729683 & 0.822845695459366 & 0.588577152270317 \tabularnewline
82 & 0.432507301679396 & 0.865014603358792 & 0.567492698320604 \tabularnewline
83 & 0.395300681446555 & 0.79060136289311 & 0.604699318553445 \tabularnewline
84 & 0.360347215143215 & 0.72069443028643 & 0.639652784856785 \tabularnewline
85 & 0.325194812245218 & 0.650389624490435 & 0.674805187754782 \tabularnewline
86 & 0.293999599102778 & 0.587999198205556 & 0.706000400897222 \tabularnewline
87 & 0.267237468519079 & 0.534474937038158 & 0.732762531480921 \tabularnewline
88 & 0.240460055796324 & 0.480920111592649 & 0.759539944203676 \tabularnewline
89 & 0.290077413323844 & 0.580154826647688 & 0.709922586676156 \tabularnewline
90 & 0.268469378667652 & 0.536938757335304 & 0.731530621332348 \tabularnewline
91 & 0.244103424358208 & 0.488206848716416 & 0.755896575641792 \tabularnewline
92 & 0.216332474511832 & 0.432664949023664 & 0.783667525488168 \tabularnewline
93 & 0.197516262375103 & 0.395032524750206 & 0.802483737624897 \tabularnewline
94 & 0.183069585814731 & 0.366139171629462 & 0.816930414185269 \tabularnewline
95 & 0.160391986775925 & 0.32078397355185 & 0.839608013224075 \tabularnewline
96 & 0.145809009283974 & 0.291618018567948 & 0.854190990716026 \tabularnewline
97 & 0.138318633361967 & 0.276637266723934 & 0.861681366638033 \tabularnewline
98 & 0.118912324447489 & 0.237824648894977 & 0.881087675552511 \tabularnewline
99 & 0.11828742348202 & 0.23657484696404 & 0.88171257651798 \tabularnewline
100 & 0.102868983647423 & 0.205737967294846 & 0.897131016352577 \tabularnewline
101 & 0.0926175822868432 & 0.185235164573686 & 0.907382417713157 \tabularnewline
102 & 0.0783331814864306 & 0.156666362972861 & 0.92166681851357 \tabularnewline
103 & 0.101078303756648 & 0.202156607513296 & 0.898921696243352 \tabularnewline
104 & 0.108948705191478 & 0.217897410382957 & 0.891051294808522 \tabularnewline
105 & 0.110170233876821 & 0.220340467753641 & 0.88982976612318 \tabularnewline
106 & 0.094810654359743 & 0.189621308719486 & 0.905189345640257 \tabularnewline
107 & 0.107062441775631 & 0.214124883551261 & 0.89293755822437 \tabularnewline
108 & 0.0938180697163552 & 0.18763613943271 & 0.906181930283645 \tabularnewline
109 & 0.247489142818785 & 0.49497828563757 & 0.752510857181215 \tabularnewline
110 & 0.226061296590777 & 0.452122593181553 & 0.773938703409223 \tabularnewline
111 & 0.201051081109656 & 0.402102162219312 & 0.798948918890344 \tabularnewline
112 & 0.211375076300438 & 0.422750152600876 & 0.788624923699562 \tabularnewline
113 & 0.195213969459524 & 0.390427938919048 & 0.804786030540476 \tabularnewline
114 & 0.180977401818775 & 0.36195480363755 & 0.819022598181225 \tabularnewline
115 & 0.166717277281118 & 0.333434554562236 & 0.833282722718882 \tabularnewline
116 & 0.146822176656482 & 0.293644353312965 & 0.853177823343518 \tabularnewline
117 & 0.128201545390729 & 0.256403090781458 & 0.871798454609271 \tabularnewline
118 & 0.155453260039406 & 0.310906520078812 & 0.844546739960594 \tabularnewline
119 & 0.143250580354953 & 0.286501160709907 & 0.856749419645047 \tabularnewline
120 & 0.124021247439347 & 0.248042494878695 & 0.875978752560653 \tabularnewline
121 & 0.108559692591292 & 0.217119385182584 & 0.891440307408708 \tabularnewline
122 & 0.097839190494131 & 0.195678380988262 & 0.902160809505869 \tabularnewline
123 & 0.124455652796321 & 0.248911305592642 & 0.875544347203679 \tabularnewline
124 & 0.111455109242753 & 0.222910218485505 & 0.888544890757247 \tabularnewline
125 & 0.114716375473921 & 0.229432750947842 & 0.885283624526079 \tabularnewline
126 & 0.115801006594956 & 0.231602013189913 & 0.884198993405044 \tabularnewline
127 & 0.101187904347674 & 0.202375808695349 & 0.898812095652326 \tabularnewline
128 & 0.0906300232397384 & 0.181260046479477 & 0.909369976760262 \tabularnewline
129 & 0.0774392995104118 & 0.154878599020824 & 0.922560700489588 \tabularnewline
130 & 0.0800125621003055 & 0.160025124200611 & 0.919987437899695 \tabularnewline
131 & 0.0810883069997927 & 0.162176613999585 & 0.918911693000207 \tabularnewline
132 & 0.0771645042732729 & 0.154329008546546 & 0.922835495726727 \tabularnewline
133 & 0.07281536557551 & 0.14563073115102 & 0.92718463442449 \tabularnewline
134 & 0.061552062070086 & 0.123104124140172 & 0.938447937929914 \tabularnewline
135 & 0.0573129590902837 & 0.114625918180567 & 0.942687040909716 \tabularnewline
136 & 0.134478359162873 & 0.268956718325747 & 0.865521640837127 \tabularnewline
137 & 0.117347231138281 & 0.234694462276562 & 0.88265276886172 \tabularnewline
138 & 0.100890651535539 & 0.201781303071077 & 0.899109348464461 \tabularnewline
139 & 0.0898460218226357 & 0.179692043645271 & 0.910153978177364 \tabularnewline
140 & 0.0839704477843041 & 0.167940895568608 & 0.916029552215696 \tabularnewline
141 & 0.0821098980517313 & 0.164219796103463 & 0.917890101948269 \tabularnewline
142 & 0.0761686376553879 & 0.152337275310776 & 0.923831362344612 \tabularnewline
143 & 0.0671931512316191 & 0.134386302463238 & 0.932806848768381 \tabularnewline
144 & 0.057338539486667 & 0.114677078973334 & 0.942661460513333 \tabularnewline
145 & 0.0482594436887606 & 0.0965188873775212 & 0.95174055631124 \tabularnewline
146 & 0.0399755611816734 & 0.0799511223633468 & 0.960024438818327 \tabularnewline
147 & 0.038762429413294 & 0.0775248588265879 & 0.961237570586706 \tabularnewline
148 & 0.0484287712701157 & 0.0968575425402314 & 0.951571228729884 \tabularnewline
149 & 0.0433962958894614 & 0.0867925917789228 & 0.956603704110539 \tabularnewline
150 & 0.03584091524833 & 0.0716818304966599 & 0.96415908475167 \tabularnewline
151 & 0.0371374529703461 & 0.0742749059406922 & 0.962862547029654 \tabularnewline
152 & 0.0373541630894777 & 0.0747083261789554 & 0.962645836910522 \tabularnewline
153 & 0.0387205089889921 & 0.0774410179779842 & 0.961279491011008 \tabularnewline
154 & 0.0351150281886103 & 0.0702300563772205 & 0.96488497181139 \tabularnewline
155 & 0.0389281367010982 & 0.0778562734021964 & 0.961071863298902 \tabularnewline
156 & 0.0324571002236581 & 0.0649142004473161 & 0.967542899776342 \tabularnewline
157 & 0.0266498876145181 & 0.0532997752290362 & 0.973350112385482 \tabularnewline
158 & 0.022972324079875 & 0.04594464815975 & 0.977027675920125 \tabularnewline
159 & 0.0417440958883039 & 0.0834881917766077 & 0.958255904111696 \tabularnewline
160 & 0.0390911930820312 & 0.0781823861640625 & 0.960908806917969 \tabularnewline
161 & 0.0335664373301574 & 0.0671328746603148 & 0.966433562669843 \tabularnewline
162 & 0.0785805577760749 & 0.15716111555215 & 0.921419442223925 \tabularnewline
163 & 0.0663071247744412 & 0.132614249548882 & 0.933692875225559 \tabularnewline
164 & 0.188166341407071 & 0.376332682814142 & 0.811833658592929 \tabularnewline
165 & 0.167965173193418 & 0.335930346386836 & 0.832034826806582 \tabularnewline
166 & 0.277744239735479 & 0.555488479470959 & 0.72225576026452 \tabularnewline
167 & 0.263911278660163 & 0.527822557320327 & 0.736088721339837 \tabularnewline
168 & 0.247251506630356 & 0.494503013260712 & 0.752748493369644 \tabularnewline
169 & 0.228721045176238 & 0.457442090352476 & 0.771278954823762 \tabularnewline
170 & 0.202329669842127 & 0.404659339684253 & 0.797670330157873 \tabularnewline
171 & 0.227433753754119 & 0.454867507508238 & 0.772566246245881 \tabularnewline
172 & 0.201892736719511 & 0.403785473439022 & 0.798107263280489 \tabularnewline
173 & 0.279512440399388 & 0.559024880798776 & 0.720487559600612 \tabularnewline
174 & 0.271400933256396 & 0.542801866512792 & 0.728599066743604 \tabularnewline
175 & 0.247386284153288 & 0.494772568306576 & 0.752613715846712 \tabularnewline
176 & 0.335804684264873 & 0.671609368529747 & 0.664195315735127 \tabularnewline
177 & 0.312085465473049 & 0.624170930946098 & 0.687914534526951 \tabularnewline
178 & 0.309874963025904 & 0.619749926051807 & 0.690125036974096 \tabularnewline
179 & 0.295002671939354 & 0.590005343878709 & 0.704997328060646 \tabularnewline
180 & 0.277647284111241 & 0.555294568222481 & 0.722352715888759 \tabularnewline
181 & 0.270958709624598 & 0.541917419249196 & 0.729041290375402 \tabularnewline
182 & 0.353673987937488 & 0.707347975874976 & 0.646326012062512 \tabularnewline
183 & 0.332386344529692 & 0.664772689059384 & 0.667613655470308 \tabularnewline
184 & 0.349648330005454 & 0.699296660010909 & 0.650351669994546 \tabularnewline
185 & 0.321545652694783 & 0.643091305389565 & 0.678454347305217 \tabularnewline
186 & 0.38234050268762 & 0.76468100537524 & 0.61765949731238 \tabularnewline
187 & 0.3464780718419 & 0.6929561436838 & 0.6535219281581 \tabularnewline
188 & 0.313578302296008 & 0.627156604592017 & 0.686421697703992 \tabularnewline
189 & 0.280648439928053 & 0.561296879856106 & 0.719351560071947 \tabularnewline
190 & 0.359886761118825 & 0.71977352223765 & 0.640113238881175 \tabularnewline
191 & 0.358793982117982 & 0.717587964235964 & 0.641206017882018 \tabularnewline
192 & 0.377185993379966 & 0.754371986759931 & 0.622814006620034 \tabularnewline
193 & 0.364725754442616 & 0.729451508885231 & 0.635274245557384 \tabularnewline
194 & 0.327449205712722 & 0.654898411425443 & 0.672550794287278 \tabularnewline
195 & 0.299839888205217 & 0.599679776410434 & 0.700160111794783 \tabularnewline
196 & 0.308990159629857 & 0.617980319259713 & 0.691009840370143 \tabularnewline
197 & 0.414566529469149 & 0.829133058938297 & 0.585433470530851 \tabularnewline
198 & 0.38625305381992 & 0.77250610763984 & 0.61374694618008 \tabularnewline
199 & 0.348499869090872 & 0.696999738181745 & 0.651500130909128 \tabularnewline
200 & 0.317931182549709 & 0.635862365099418 & 0.682068817450291 \tabularnewline
201 & 0.282799830423087 & 0.565599660846174 & 0.717200169576913 \tabularnewline
202 & 0.251816417056568 & 0.503632834113136 & 0.748183582943432 \tabularnewline
203 & 0.22010669038872 & 0.44021338077744 & 0.77989330961128 \tabularnewline
204 & 0.19022064806371 & 0.38044129612742 & 0.80977935193629 \tabularnewline
205 & 0.17050993195789 & 0.341019863915781 & 0.82949006804211 \tabularnewline
206 & 0.145205387136655 & 0.290410774273311 & 0.854794612863345 \tabularnewline
207 & 0.127851079287202 & 0.255702158574404 & 0.872148920712798 \tabularnewline
208 & 0.133167971435038 & 0.266335942870075 & 0.866832028564962 \tabularnewline
209 & 0.111287251782577 & 0.222574503565155 & 0.888712748217423 \tabularnewline
210 & 0.0924174870336024 & 0.184834974067205 & 0.907582512966398 \tabularnewline
211 & 0.0764408762995234 & 0.152881752599047 & 0.923559123700477 \tabularnewline
212 & 0.0632186279787771 & 0.126437255957554 & 0.936781372021223 \tabularnewline
213 & 0.0562436552451063 & 0.112487310490213 & 0.943756344754894 \tabularnewline
214 & 0.0638521155489727 & 0.127704231097945 & 0.936147884451027 \tabularnewline
215 & 0.0521437214593465 & 0.104287442918693 & 0.947856278540653 \tabularnewline
216 & 0.0422514390360089 & 0.0845028780720177 & 0.95774856096399 \tabularnewline
217 & 0.0332278071108906 & 0.0664556142217811 & 0.96677219288911 \tabularnewline
218 & 0.0273128827505761 & 0.0546257655011523 & 0.972687117249424 \tabularnewline
219 & 0.0290635733686688 & 0.0581271467373377 & 0.970936426631331 \tabularnewline
220 & 0.0236780629192001 & 0.0473561258384003 & 0.9763219370808 \tabularnewline
221 & 0.0289406824851743 & 0.0578813649703486 & 0.971059317514826 \tabularnewline
222 & 0.0219514403108181 & 0.0439028806216362 & 0.978048559689182 \tabularnewline
223 & 0.016374746118818 & 0.032749492237636 & 0.983625253881182 \tabularnewline
224 & 0.0175983512353555 & 0.0351967024707111 & 0.982401648764644 \tabularnewline
225 & 0.0189355159376746 & 0.0378710318753493 & 0.981064484062325 \tabularnewline
226 & 0.0151871994074186 & 0.0303743988148371 & 0.984812800592581 \tabularnewline
227 & 0.0124980577305653 & 0.0249961154611307 & 0.987501942269435 \tabularnewline
228 & 0.0122698998254443 & 0.0245397996508885 & 0.987730100174556 \tabularnewline
229 & 0.0180891486185152 & 0.0361782972370304 & 0.981910851381485 \tabularnewline
230 & 0.0170958316721885 & 0.0341916633443769 & 0.982904168327812 \tabularnewline
231 & 0.013284753883049 & 0.026569507766098 & 0.98671524611695 \tabularnewline
232 & 0.0101569570057312 & 0.0203139140114624 & 0.989843042994269 \tabularnewline
233 & 0.0121563136854298 & 0.0243126273708595 & 0.98784368631457 \tabularnewline
234 & 0.0106692224424474 & 0.0213384448848947 & 0.989330777557553 \tabularnewline
235 & 0.0109902675750121 & 0.0219805351500242 & 0.989009732424988 \tabularnewline
236 & 0.00860708928443766 & 0.0172141785688753 & 0.991392910715562 \tabularnewline
237 & 0.00660150775474376 & 0.0132030155094875 & 0.993398492245256 \tabularnewline
238 & 0.00464603600121098 & 0.00929207200242197 & 0.99535396399879 \tabularnewline
239 & 0.0116646277748229 & 0.0233292555496458 & 0.988335372225177 \tabularnewline
240 & 0.0160977040645033 & 0.0321954081290066 & 0.983902295935497 \tabularnewline
241 & 0.0367910005703136 & 0.0735820011406271 & 0.963208999429686 \tabularnewline
242 & 0.025642366969861 & 0.0512847339397219 & 0.97435763303014 \tabularnewline
243 & 0.0172362914792171 & 0.0344725829584343 & 0.982763708520783 \tabularnewline
244 & 0.0112411574580886 & 0.0224823149161771 & 0.988758842541911 \tabularnewline
245 & 0.00735856177931968 & 0.0147171235586394 & 0.99264143822068 \tabularnewline
246 & 0.00701659058451169 & 0.0140331811690234 & 0.992983409415488 \tabularnewline
247 & 0.00416343732754442 & 0.00832687465508885 & 0.995836562672456 \tabularnewline
248 & 0.132575958566515 & 0.265151917133029 & 0.867424041433485 \tabularnewline
249 & 0.122430742385471 & 0.244861484770942 & 0.877569257614529 \tabularnewline
250 & 0.206531197134026 & 0.413062394268051 & 0.793468802865974 \tabularnewline
251 & 0.150906094860646 & 0.301812189721292 & 0.849093905139354 \tabularnewline
252 & 0.19925692727994 & 0.39851385455988 & 0.80074307272006 \tabularnewline
253 & 0.199278032417618 & 0.398556064835236 & 0.800721967582382 \tabularnewline
254 & 0.127219055414923 & 0.254438110829846 & 0.872780944585077 \tabularnewline
255 & 0.112893021628353 & 0.225786043256706 & 0.887106978371647 \tabularnewline
256 & 0.061132034666458 & 0.122264069332916 & 0.938867965333542 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145480&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]8[/C][C]0.999607204834477[/C][C]0.000785590331045182[/C][C]0.000392795165522591[/C][/ROW]
[ROW][C]9[/C][C]0.999558026104716[/C][C]0.000883947790568522[/C][C]0.000441973895284261[/C][/ROW]
[ROW][C]10[/C][C]0.998887086613266[/C][C]0.00222582677346849[/C][C]0.00111291338673425[/C][/ROW]
[ROW][C]11[/C][C]0.998664494558075[/C][C]0.00267101088384929[/C][C]0.00133550544192464[/C][/ROW]
[ROW][C]12[/C][C]0.998183998346032[/C][C]0.00363200330793672[/C][C]0.00181600165396836[/C][/ROW]
[ROW][C]13[/C][C]0.996767777167157[/C][C]0.00646444566568635[/C][C]0.00323222283284318[/C][/ROW]
[ROW][C]14[/C][C]0.9946033182562[/C][C]0.0107933634876006[/C][C]0.00539668174380031[/C][/ROW]
[ROW][C]15[/C][C]0.990598070564453[/C][C]0.0188038588710943[/C][C]0.00940192943554715[/C][/ROW]
[ROW][C]16[/C][C]0.984833380877296[/C][C]0.0303332382454085[/C][C]0.0151666191227042[/C][/ROW]
[ROW][C]17[/C][C]0.975873751812436[/C][C]0.0482524963751275[/C][C]0.0241262481875637[/C][/ROW]
[ROW][C]18[/C][C]0.964123747160874[/C][C]0.0717525056782518[/C][C]0.0358762528391259[/C][/ROW]
[ROW][C]19[/C][C]0.965260267301084[/C][C]0.0694794653978318[/C][C]0.0347397326989159[/C][/ROW]
[ROW][C]20[/C][C]0.95032220133596[/C][C]0.099355597328078[/C][C]0.049677798664039[/C][/ROW]
[ROW][C]21[/C][C]0.93442336810208[/C][C]0.131153263795841[/C][C]0.0655766318979205[/C][/ROW]
[ROW][C]22[/C][C]0.913010905984743[/C][C]0.173978188030514[/C][C]0.086989094015257[/C][/ROW]
[ROW][C]23[/C][C]0.887256433363996[/C][C]0.225487133272008[/C][C]0.112743566636004[/C][/ROW]
[ROW][C]24[/C][C]0.852733281217266[/C][C]0.294533437565468[/C][C]0.147266718782734[/C][/ROW]
[ROW][C]25[/C][C]0.821485018410066[/C][C]0.357029963179869[/C][C]0.178514981589934[/C][/ROW]
[ROW][C]26[/C][C]0.928124657994393[/C][C]0.143750684011214[/C][C]0.0718753420056072[/C][/ROW]
[ROW][C]27[/C][C]0.907958216499346[/C][C]0.184083567001307[/C][C]0.0920417835006537[/C][/ROW]
[ROW][C]28[/C][C]0.89309412620571[/C][C]0.21381174758858[/C][C]0.10690587379429[/C][/ROW]
[ROW][C]29[/C][C]0.869745629419665[/C][C]0.260508741160671[/C][C]0.130254370580335[/C][/ROW]
[ROW][C]30[/C][C]0.841357354614732[/C][C]0.317285290770535[/C][C]0.158642645385268[/C][/ROW]
[ROW][C]31[/C][C]0.849189729650864[/C][C]0.301620540698272[/C][C]0.150810270349136[/C][/ROW]
[ROW][C]32[/C][C]0.821443626330881[/C][C]0.357112747338238[/C][C]0.178556373669119[/C][/ROW]
[ROW][C]33[/C][C]0.790667067008194[/C][C]0.418665865983612[/C][C]0.209332932991806[/C][/ROW]
[ROW][C]34[/C][C]0.762030990159107[/C][C]0.475938019681786[/C][C]0.237969009840893[/C][/ROW]
[ROW][C]35[/C][C]0.718358584153764[/C][C]0.563282831692472[/C][C]0.281641415846236[/C][/ROW]
[ROW][C]36[/C][C]0.75832671600954[/C][C]0.48334656798092[/C][C]0.24167328399046[/C][/ROW]
[ROW][C]37[/C][C]0.809489768270252[/C][C]0.381020463459496[/C][C]0.190510231729748[/C][/ROW]
[ROW][C]38[/C][C]0.772210745826395[/C][C]0.455578508347209[/C][C]0.227789254173605[/C][/ROW]
[ROW][C]39[/C][C]0.745782772608998[/C][C]0.508434454782004[/C][C]0.254217227391002[/C][/ROW]
[ROW][C]40[/C][C]0.755804424822842[/C][C]0.488391150354315[/C][C]0.244195575177158[/C][/ROW]
[ROW][C]41[/C][C]0.754670767104281[/C][C]0.490658465791438[/C][C]0.245329232895719[/C][/ROW]
[ROW][C]42[/C][C]0.740959892505846[/C][C]0.518080214988308[/C][C]0.259040107494154[/C][/ROW]
[ROW][C]43[/C][C]0.747414692844029[/C][C]0.505170614311943[/C][C]0.252585307155971[/C][/ROW]
[ROW][C]44[/C][C]0.70773504079101[/C][C]0.584529918417981[/C][C]0.292264959208991[/C][/ROW]
[ROW][C]45[/C][C]0.665528615865802[/C][C]0.668942768268396[/C][C]0.334471384134198[/C][/ROW]
[ROW][C]46[/C][C]0.628576237438391[/C][C]0.742847525123218[/C][C]0.371423762561609[/C][/ROW]
[ROW][C]47[/C][C]0.632170480581737[/C][C]0.735659038836526[/C][C]0.367829519418263[/C][/ROW]
[ROW][C]48[/C][C]0.596212726782733[/C][C]0.807574546434534[/C][C]0.403787273217267[/C][/ROW]
[ROW][C]49[/C][C]0.636188428657742[/C][C]0.727623142684515[/C][C]0.363811571342258[/C][/ROW]
[ROW][C]50[/C][C]0.606994908654071[/C][C]0.786010182691858[/C][C]0.393005091345929[/C][/ROW]
[ROW][C]51[/C][C]0.589926098927391[/C][C]0.820147802145217[/C][C]0.410073901072609[/C][/ROW]
[ROW][C]52[/C][C]0.553483218693496[/C][C]0.893033562613007[/C][C]0.446516781306504[/C][/ROW]
[ROW][C]53[/C][C]0.573328274511145[/C][C]0.85334345097771[/C][C]0.426671725488855[/C][/ROW]
[ROW][C]54[/C][C]0.528652263120215[/C][C]0.94269547375957[/C][C]0.471347736879785[/C][/ROW]
[ROW][C]55[/C][C]0.53627091355796[/C][C]0.92745817288408[/C][C]0.46372908644204[/C][/ROW]
[ROW][C]56[/C][C]0.529269955661067[/C][C]0.941460088677865[/C][C]0.470730044338933[/C][/ROW]
[ROW][C]57[/C][C]0.504727120916714[/C][C]0.990545758166573[/C][C]0.495272879083286[/C][/ROW]
[ROW][C]58[/C][C]0.534117574329049[/C][C]0.9317648513419[/C][C]0.46588242567095[/C][/ROW]
[ROW][C]59[/C][C]0.563058748479652[/C][C]0.873882503040697[/C][C]0.436941251520348[/C][/ROW]
[ROW][C]60[/C][C]0.530377308848064[/C][C]0.939245382303871[/C][C]0.469622691151936[/C][/ROW]
[ROW][C]61[/C][C]0.557153550562279[/C][C]0.885692898875443[/C][C]0.442846449437721[/C][/ROW]
[ROW][C]62[/C][C]0.520916538842319[/C][C]0.958166922315362[/C][C]0.479083461157681[/C][/ROW]
[ROW][C]63[/C][C]0.515408198003034[/C][C]0.969183603993933[/C][C]0.484591801996966[/C][/ROW]
[ROW][C]64[/C][C]0.477556722562795[/C][C]0.95511344512559[/C][C]0.522443277437205[/C][/ROW]
[ROW][C]65[/C][C]0.438673781898457[/C][C]0.877347563796913[/C][C]0.561326218101543[/C][/ROW]
[ROW][C]66[/C][C]0.437004500089566[/C][C]0.874009000179132[/C][C]0.562995499910434[/C][/ROW]
[ROW][C]67[/C][C]0.484397524756278[/C][C]0.968795049512556[/C][C]0.515602475243722[/C][/ROW]
[ROW][C]68[/C][C]0.467063407959091[/C][C]0.934126815918182[/C][C]0.532936592040909[/C][/ROW]
[ROW][C]69[/C][C]0.440975233101183[/C][C]0.881950466202365[/C][C]0.559024766898817[/C][/ROW]
[ROW][C]70[/C][C]0.418481067101955[/C][C]0.83696213420391[/C][C]0.581518932898045[/C][/ROW]
[ROW][C]71[/C][C]0.380043725618634[/C][C]0.760087451237268[/C][C]0.619956274381366[/C][/ROW]
[ROW][C]72[/C][C]0.377130470007751[/C][C]0.754260940015502[/C][C]0.622869529992249[/C][/ROW]
[ROW][C]73[/C][C]0.33986426693435[/C][C]0.679728533868699[/C][C]0.66013573306565[/C][/ROW]
[ROW][C]74[/C][C]0.32900618891715[/C][C]0.6580123778343[/C][C]0.67099381108285[/C][/ROW]
[ROW][C]75[/C][C]0.322229931509289[/C][C]0.644459863018577[/C][C]0.677770068490711[/C][/ROW]
[ROW][C]76[/C][C]0.41749919070776[/C][C]0.83499838141552[/C][C]0.58250080929224[/C][/ROW]
[ROW][C]77[/C][C]0.393575017745778[/C][C]0.787150035491556[/C][C]0.606424982254222[/C][/ROW]
[ROW][C]78[/C][C]0.39625391311199[/C][C]0.792507826223981[/C][C]0.60374608688801[/C][/ROW]
[ROW][C]79[/C][C]0.360868169027558[/C][C]0.721736338055117[/C][C]0.639131830972442[/C][/ROW]
[ROW][C]80[/C][C]0.43412080859854[/C][C]0.86824161719708[/C][C]0.56587919140146[/C][/ROW]
[ROW][C]81[/C][C]0.411422847729683[/C][C]0.822845695459366[/C][C]0.588577152270317[/C][/ROW]
[ROW][C]82[/C][C]0.432507301679396[/C][C]0.865014603358792[/C][C]0.567492698320604[/C][/ROW]
[ROW][C]83[/C][C]0.395300681446555[/C][C]0.79060136289311[/C][C]0.604699318553445[/C][/ROW]
[ROW][C]84[/C][C]0.360347215143215[/C][C]0.72069443028643[/C][C]0.639652784856785[/C][/ROW]
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[ROW][C]220[/C][C]0.0236780629192001[/C][C]0.0473561258384003[/C][C]0.9763219370808[/C][/ROW]
[ROW][C]221[/C][C]0.0289406824851743[/C][C]0.0578813649703486[/C][C]0.971059317514826[/C][/ROW]
[ROW][C]222[/C][C]0.0219514403108181[/C][C]0.0439028806216362[/C][C]0.978048559689182[/C][/ROW]
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[ROW][C]224[/C][C]0.0175983512353555[/C][C]0.0351967024707111[/C][C]0.982401648764644[/C][/ROW]
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[ROW][C]227[/C][C]0.0124980577305653[/C][C]0.0249961154611307[/C][C]0.987501942269435[/C][/ROW]
[ROW][C]228[/C][C]0.0122698998254443[/C][C]0.0245397996508885[/C][C]0.987730100174556[/C][/ROW]
[ROW][C]229[/C][C]0.0180891486185152[/C][C]0.0361782972370304[/C][C]0.981910851381485[/C][/ROW]
[ROW][C]230[/C][C]0.0170958316721885[/C][C]0.0341916633443769[/C][C]0.982904168327812[/C][/ROW]
[ROW][C]231[/C][C]0.013284753883049[/C][C]0.026569507766098[/C][C]0.98671524611695[/C][/ROW]
[ROW][C]232[/C][C]0.0101569570057312[/C][C]0.0203139140114624[/C][C]0.989843042994269[/C][/ROW]
[ROW][C]233[/C][C]0.0121563136854298[/C][C]0.0243126273708595[/C][C]0.98784368631457[/C][/ROW]
[ROW][C]234[/C][C]0.0106692224424474[/C][C]0.0213384448848947[/C][C]0.989330777557553[/C][/ROW]
[ROW][C]235[/C][C]0.0109902675750121[/C][C]0.0219805351500242[/C][C]0.989009732424988[/C][/ROW]
[ROW][C]236[/C][C]0.00860708928443766[/C][C]0.0172141785688753[/C][C]0.991392910715562[/C][/ROW]
[ROW][C]237[/C][C]0.00660150775474376[/C][C]0.0132030155094875[/C][C]0.993398492245256[/C][/ROW]
[ROW][C]238[/C][C]0.00464603600121098[/C][C]0.00929207200242197[/C][C]0.99535396399879[/C][/ROW]
[ROW][C]239[/C][C]0.0116646277748229[/C][C]0.0233292555496458[/C][C]0.988335372225177[/C][/ROW]
[ROW][C]240[/C][C]0.0160977040645033[/C][C]0.0321954081290066[/C][C]0.983902295935497[/C][/ROW]
[ROW][C]241[/C][C]0.0367910005703136[/C][C]0.0735820011406271[/C][C]0.963208999429686[/C][/ROW]
[ROW][C]242[/C][C]0.025642366969861[/C][C]0.0512847339397219[/C][C]0.97435763303014[/C][/ROW]
[ROW][C]243[/C][C]0.0172362914792171[/C][C]0.0344725829584343[/C][C]0.982763708520783[/C][/ROW]
[ROW][C]244[/C][C]0.0112411574580886[/C][C]0.0224823149161771[/C][C]0.988758842541911[/C][/ROW]
[ROW][C]245[/C][C]0.00735856177931968[/C][C]0.0147171235586394[/C][C]0.99264143822068[/C][/ROW]
[ROW][C]246[/C][C]0.00701659058451169[/C][C]0.0140331811690234[/C][C]0.992983409415488[/C][/ROW]
[ROW][C]247[/C][C]0.00416343732754442[/C][C]0.00832687465508885[/C][C]0.995836562672456[/C][/ROW]
[ROW][C]248[/C][C]0.132575958566515[/C][C]0.265151917133029[/C][C]0.867424041433485[/C][/ROW]
[ROW][C]249[/C][C]0.122430742385471[/C][C]0.244861484770942[/C][C]0.877569257614529[/C][/ROW]
[ROW][C]250[/C][C]0.206531197134026[/C][C]0.413062394268051[/C][C]0.793468802865974[/C][/ROW]
[ROW][C]251[/C][C]0.150906094860646[/C][C]0.301812189721292[/C][C]0.849093905139354[/C][/ROW]
[ROW][C]252[/C][C]0.19925692727994[/C][C]0.39851385455988[/C][C]0.80074307272006[/C][/ROW]
[ROW][C]253[/C][C]0.199278032417618[/C][C]0.398556064835236[/C][C]0.800721967582382[/C][/ROW]
[ROW][C]254[/C][C]0.127219055414923[/C][C]0.254438110829846[/C][C]0.872780944585077[/C][/ROW]
[ROW][C]255[/C][C]0.112893021628353[/C][C]0.225786043256706[/C][C]0.887106978371647[/C][/ROW]
[ROW][C]256[/C][C]0.061132034666458[/C][C]0.122264069332916[/C][C]0.938867965333542[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145480&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145480&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
80.9996072048344770.0007855903310451820.000392795165522591
90.9995580261047160.0008839477905685220.000441973895284261
100.9988870866132660.002225826773468490.00111291338673425
110.9986644945580750.002671010883849290.00133550544192464
120.9981839983460320.003632003307936720.00181600165396836
130.9967677771671570.006464445665686350.00323222283284318
140.99460331825620.01079336348760060.00539668174380031
150.9905980705644530.01880385887109430.00940192943554715
160.9848333808772960.03033323824540850.0151666191227042
170.9758737518124360.04825249637512750.0241262481875637
180.9641237471608740.07175250567825180.0358762528391259
190.9652602673010840.06947946539783180.0347397326989159
200.950322201335960.0993555973280780.049677798664039
210.934423368102080.1311532637958410.0655766318979205
220.9130109059847430.1739781880305140.086989094015257
230.8872564333639960.2254871332720080.112743566636004
240.8527332812172660.2945334375654680.147266718782734
250.8214850184100660.3570299631798690.178514981589934
260.9281246579943930.1437506840112140.0718753420056072
270.9079582164993460.1840835670013070.0920417835006537
280.893094126205710.213811747588580.10690587379429
290.8697456294196650.2605087411606710.130254370580335
300.8413573546147320.3172852907705350.158642645385268
310.8491897296508640.3016205406982720.150810270349136
320.8214436263308810.3571127473382380.178556373669119
330.7906670670081940.4186658659836120.209332932991806
340.7620309901591070.4759380196817860.237969009840893
350.7183585841537640.5632828316924720.281641415846236
360.758326716009540.483346567980920.24167328399046
370.8094897682702520.3810204634594960.190510231729748
380.7722107458263950.4555785083472090.227789254173605
390.7457827726089980.5084344547820040.254217227391002
400.7558044248228420.4883911503543150.244195575177158
410.7546707671042810.4906584657914380.245329232895719
420.7409598925058460.5180802149883080.259040107494154
430.7474146928440290.5051706143119430.252585307155971
440.707735040791010.5845299184179810.292264959208991
450.6655286158658020.6689427682683960.334471384134198
460.6285762374383910.7428475251232180.371423762561609
470.6321704805817370.7356590388365260.367829519418263
480.5962127267827330.8075745464345340.403787273217267
490.6361884286577420.7276231426845150.363811571342258
500.6069949086540710.7860101826918580.393005091345929
510.5899260989273910.8201478021452170.410073901072609
520.5534832186934960.8930335626130070.446516781306504
530.5733282745111450.853343450977710.426671725488855
540.5286522631202150.942695473759570.471347736879785
550.536270913557960.927458172884080.46372908644204
560.5292699556610670.9414600886778650.470730044338933
570.5047271209167140.9905457581665730.495272879083286
580.5341175743290490.93176485134190.46588242567095
590.5630587484796520.8738825030406970.436941251520348
600.5303773088480640.9392453823038710.469622691151936
610.5571535505622790.8856928988754430.442846449437721
620.5209165388423190.9581669223153620.479083461157681
630.5154081980030340.9691836039939330.484591801996966
640.4775567225627950.955113445125590.522443277437205
650.4386737818984570.8773475637969130.561326218101543
660.4370045000895660.8740090001791320.562995499910434
670.4843975247562780.9687950495125560.515602475243722
680.4670634079590910.9341268159181820.532936592040909
690.4409752331011830.8819504662023650.559024766898817
700.4184810671019550.836962134203910.581518932898045
710.3800437256186340.7600874512372680.619956274381366
720.3771304700077510.7542609400155020.622869529992249
730.339864266934350.6797285338686990.66013573306565
740.329006188917150.65801237783430.67099381108285
750.3222299315092890.6444598630185770.677770068490711
760.417499190707760.834998381415520.58250080929224
770.3935750177457780.7871500354915560.606424982254222
780.396253913111990.7925078262239810.60374608688801
790.3608681690275580.7217363380551170.639131830972442
800.434120808598540.868241617197080.56587919140146
810.4114228477296830.8228456954593660.588577152270317
820.4325073016793960.8650146033587920.567492698320604
830.3953006814465550.790601362893110.604699318553445
840.3603472151432150.720694430286430.639652784856785
850.3251948122452180.6503896244904350.674805187754782
860.2939995991027780.5879991982055560.706000400897222
870.2672374685190790.5344749370381580.732762531480921
880.2404600557963240.4809201115926490.759539944203676
890.2900774133238440.5801548266476880.709922586676156
900.2684693786676520.5369387573353040.731530621332348
910.2441034243582080.4882068487164160.755896575641792
920.2163324745118320.4326649490236640.783667525488168
930.1975162623751030.3950325247502060.802483737624897
940.1830695858147310.3661391716294620.816930414185269
950.1603919867759250.320783973551850.839608013224075
960.1458090092839740.2916180185679480.854190990716026
970.1383186333619670.2766372667239340.861681366638033
980.1189123244474890.2378246488949770.881087675552511
990.118287423482020.236574846964040.88171257651798
1000.1028689836474230.2057379672948460.897131016352577
1010.09261758228684320.1852351645736860.907382417713157
1020.07833318148643060.1566663629728610.92166681851357
1030.1010783037566480.2021566075132960.898921696243352
1040.1089487051914780.2178974103829570.891051294808522
1050.1101702338768210.2203404677536410.88982976612318
1060.0948106543597430.1896213087194860.905189345640257
1070.1070624417756310.2141248835512610.89293755822437
1080.09381806971635520.187636139432710.906181930283645
1090.2474891428187850.494978285637570.752510857181215
1100.2260612965907770.4521225931815530.773938703409223
1110.2010510811096560.4021021622193120.798948918890344
1120.2113750763004380.4227501526008760.788624923699562
1130.1952139694595240.3904279389190480.804786030540476
1140.1809774018187750.361954803637550.819022598181225
1150.1667172772811180.3334345545622360.833282722718882
1160.1468221766564820.2936443533129650.853177823343518
1170.1282015453907290.2564030907814580.871798454609271
1180.1554532600394060.3109065200788120.844546739960594
1190.1432505803549530.2865011607099070.856749419645047
1200.1240212474393470.2480424948786950.875978752560653
1210.1085596925912920.2171193851825840.891440307408708
1220.0978391904941310.1956783809882620.902160809505869
1230.1244556527963210.2489113055926420.875544347203679
1240.1114551092427530.2229102184855050.888544890757247
1250.1147163754739210.2294327509478420.885283624526079
1260.1158010065949560.2316020131899130.884198993405044
1270.1011879043476740.2023758086953490.898812095652326
1280.09063002323973840.1812600464794770.909369976760262
1290.07743929951041180.1548785990208240.922560700489588
1300.08001256210030550.1600251242006110.919987437899695
1310.08108830699979270.1621766139995850.918911693000207
1320.07716450427327290.1543290085465460.922835495726727
1330.072815365575510.145630731151020.92718463442449
1340.0615520620700860.1231041241401720.938447937929914
1350.05731295909028370.1146259181805670.942687040909716
1360.1344783591628730.2689567183257470.865521640837127
1370.1173472311382810.2346944622765620.88265276886172
1380.1008906515355390.2017813030710770.899109348464461
1390.08984602182263570.1796920436452710.910153978177364
1400.08397044778430410.1679408955686080.916029552215696
1410.08210989805173130.1642197961034630.917890101948269
1420.07616863765538790.1523372753107760.923831362344612
1430.06719315123161910.1343863024632380.932806848768381
1440.0573385394866670.1146770789733340.942661460513333
1450.04825944368876060.09651888737752120.95174055631124
1460.03997556118167340.07995112236334680.960024438818327
1470.0387624294132940.07752485882658790.961237570586706
1480.04842877127011570.09685754254023140.951571228729884
1490.04339629588946140.08679259177892280.956603704110539
1500.035840915248330.07168183049665990.96415908475167
1510.03713745297034610.07427490594069220.962862547029654
1520.03735416308947770.07470832617895540.962645836910522
1530.03872050898899210.07744101797798420.961279491011008
1540.03511502818861030.07023005637722050.96488497181139
1550.03892813670109820.07785627340219640.961071863298902
1560.03245710022365810.06491420044731610.967542899776342
1570.02664988761451810.05329977522903620.973350112385482
1580.0229723240798750.045944648159750.977027675920125
1590.04174409588830390.08348819177660770.958255904111696
1600.03909119308203120.07818238616406250.960908806917969
1610.03356643733015740.06713287466031480.966433562669843
1620.07858055777607490.157161115552150.921419442223925
1630.06630712477444120.1326142495488820.933692875225559
1640.1881663414070710.3763326828141420.811833658592929
1650.1679651731934180.3359303463868360.832034826806582
1660.2777442397354790.5554884794709590.72225576026452
1670.2639112786601630.5278225573203270.736088721339837
1680.2472515066303560.4945030132607120.752748493369644
1690.2287210451762380.4574420903524760.771278954823762
1700.2023296698421270.4046593396842530.797670330157873
1710.2274337537541190.4548675075082380.772566246245881
1720.2018927367195110.4037854734390220.798107263280489
1730.2795124403993880.5590248807987760.720487559600612
1740.2714009332563960.5428018665127920.728599066743604
1750.2473862841532880.4947725683065760.752613715846712
1760.3358046842648730.6716093685297470.664195315735127
1770.3120854654730490.6241709309460980.687914534526951
1780.3098749630259040.6197499260518070.690125036974096
1790.2950026719393540.5900053438787090.704997328060646
1800.2776472841112410.5552945682224810.722352715888759
1810.2709587096245980.5419174192491960.729041290375402
1820.3536739879374880.7073479758749760.646326012062512
1830.3323863445296920.6647726890593840.667613655470308
1840.3496483300054540.6992966600109090.650351669994546
1850.3215456526947830.6430913053895650.678454347305217
1860.382340502687620.764681005375240.61765949731238
1870.34647807184190.69295614368380.6535219281581
1880.3135783022960080.6271566045920170.686421697703992
1890.2806484399280530.5612968798561060.719351560071947
1900.3598867611188250.719773522237650.640113238881175
1910.3587939821179820.7175879642359640.641206017882018
1920.3771859933799660.7543719867599310.622814006620034
1930.3647257544426160.7294515088852310.635274245557384
1940.3274492057127220.6548984114254430.672550794287278
1950.2998398882052170.5996797764104340.700160111794783
1960.3089901596298570.6179803192597130.691009840370143
1970.4145665294691490.8291330589382970.585433470530851
1980.386253053819920.772506107639840.61374694618008
1990.3484998690908720.6969997381817450.651500130909128
2000.3179311825497090.6358623650994180.682068817450291
2010.2827998304230870.5655996608461740.717200169576913
2020.2518164170565680.5036328341131360.748183582943432
2030.220106690388720.440213380777440.77989330961128
2040.190220648063710.380441296127420.80977935193629
2050.170509931957890.3410198639157810.82949006804211
2060.1452053871366550.2904107742733110.854794612863345
2070.1278510792872020.2557021585744040.872148920712798
2080.1331679714350380.2663359428700750.866832028564962
2090.1112872517825770.2225745035651550.888712748217423
2100.09241748703360240.1848349740672050.907582512966398
2110.07644087629952340.1528817525990470.923559123700477
2120.06321862797877710.1264372559575540.936781372021223
2130.05624365524510630.1124873104902130.943756344754894
2140.06385211554897270.1277042310979450.936147884451027
2150.05214372145934650.1042874429186930.947856278540653
2160.04225143903600890.08450287807201770.95774856096399
2170.03322780711089060.06645561422178110.96677219288911
2180.02731288275057610.05462576550115230.972687117249424
2190.02906357336866880.05812714673733770.970936426631331
2200.02367806291920010.04735612583840030.9763219370808
2210.02894068248517430.05788136497034860.971059317514826
2220.02195144031081810.04390288062163620.978048559689182
2230.0163747461188180.0327494922376360.983625253881182
2240.01759835123535550.03519670247071110.982401648764644
2250.01893551593767460.03787103187534930.981064484062325
2260.01518719940741860.03037439881483710.984812800592581
2270.01249805773056530.02499611546113070.987501942269435
2280.01226989982544430.02453979965088850.987730100174556
2290.01808914861851520.03617829723703040.981910851381485
2300.01709583167218850.03419166334437690.982904168327812
2310.0132847538830490.0265695077660980.98671524611695
2320.01015695700573120.02031391401146240.989843042994269
2330.01215631368542980.02431262737085950.98784368631457
2340.01066922244244740.02133844488489470.989330777557553
2350.01099026757501210.02198053515002420.989009732424988
2360.008607089284437660.01721417856887530.991392910715562
2370.006601507754743760.01320301550948750.993398492245256
2380.004646036001210980.009292072002421970.99535396399879
2390.01166462777482290.02332925554964580.988335372225177
2400.01609770406450330.03219540812900660.983902295935497
2410.03679100057031360.07358200114062710.963208999429686
2420.0256423669698610.05128473393972190.97435763303014
2430.01723629147921710.03447258295843430.982763708520783
2440.01124115745808860.02248231491617710.988758842541911
2450.007358561779319680.01471712355863940.99264143822068
2460.007016590584511690.01403318116902340.992983409415488
2470.004163437327544420.008326874655088850.995836562672456
2480.1325759585665150.2651519171330290.867424041433485
2490.1224307423854710.2448614847709420.877569257614529
2500.2065311971340260.4130623942680510.793468802865974
2510.1509060948606460.3018121897212920.849093905139354
2520.199256927279940.398513854559880.80074307272006
2530.1992780324176180.3985560648352360.800721967582382
2540.1272190554149230.2544381108298460.872780944585077
2550.1128930216283530.2257860432567060.887106978371647
2560.0611320346664580.1222640693329160.938867965333542






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level80.0321285140562249NOK
5% type I error level360.144578313253012NOK
10% type I error level620.248995983935743NOK

\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 & 8 & 0.0321285140562249 & NOK \tabularnewline
5% type I error level & 36 & 0.144578313253012 & NOK \tabularnewline
10% type I error level & 62 & 0.248995983935743 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145480&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]8[/C][C]0.0321285140562249[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]36[/C][C]0.144578313253012[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]62[/C][C]0.248995983935743[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145480&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145480&T=6

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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 level80.0321285140562249NOK
5% type I error level360.144578313253012NOK
10% type I error level620.248995983935743NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 5 ; 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$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}