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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 computationMon, 29 Oct 2012 16:32:19 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Oct/29/t1351542977g52isgpp8lp1aiz.htm/, Retrieved Sat, 27 Apr 2024 05:29:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=184814, Retrieved Sat, 27 Apr 2024 05:29:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Multiple Regression] [2012-10-29 20:32:19] [b56d37e2149957721e352fc03d1fa989] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	1	41	38	13	12	14
1	1	39	32	16	11	18
1	1	30	35	19	15	11
1	0	31	33	15	6	12
1	1	34	37	14	13	16
1	1	35	29	13	10	18
1	1	39	31	19	12	14
1	1	34	36	15	14	14
1	1	36	35	14	12	15
1	1	37	38	15	9	15
1	0	38	31	16	10	17
1	1	36	34	16	12	19
1	0	38	35	16	12	10
1	1	39	38	16	11	16
1	1	33	37	17	15	18
1	0	32	33	15	12	14
1	0	36	32	15	10	14
1	1	38	38	20	12	17
1	0	39	38	18	11	14
1	1	32	32	16	12	16
1	0	32	33	16	11	18
1	1	31	31	16	12	11
1	1	39	38	19	13	14
1	1	37	39	16	11	12
1	0	39	32	17	12	17
1	1	41	32	17	13	9
1	0	36	35	16	10	16
1	1	33	37	15	14	14
1	1	33	33	16	12	15
1	0	34	33	14	10	11
1	1	31	31	15	12	16
1	0	27	32	12	8	13
1	1	37	31	14	10	17
1	1	34	37	16	12	15
1	0	34	30	14	12	14
1	0	32	33	10	7	16
1	0	29	31	10	9	9
1	0	36	33	14	12	15
1	1	29	31	16	10	17
1	0	35	33	16	10	13
1	0	37	32	16	10	15
1	1	34	33	14	12	16
1	0	38	32	20	15	16
1	0	35	33	14	10	12
1	1	38	28	14	10	15
1	1	37	35	11	12	11
1	1	38	39	14	13	15
1	1	33	34	15	11	15
1	1	36	38	16	11	17
1	0	38	32	14	12	13
1	1	32	38	16	14	16
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1	0	32	33	12	12	11
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1	1	37	35	14	6	15
1	1	39	34	16	12	16
1	1	29	34	16	12	15
1	0	37	36	15	11	12
1	1	35	34	16	10	12
1	0	30	28	12	7	8
1	0	38	34	16	12	13
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1	1	34	31	16	12	15
1	0	35	37	17	13	10
1	1	36	35	18	14	11
1	0	30	27	18	11	12
1	1	39	40	12	12	15
1	0	35	37	16	12	15
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1	1	34	39	18	14	15
1	0	38	41	18	14	15
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1	1	35	37	16	12	15
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1	1	32	34	15	11	15
1	1	33	31	16	10	14
1	0	38	39	14	9	15
1	1	33	34	16	12	14
1	1	29	32	16	12	13
1	1	33	33	15	12	7
1	1	31	36	12	9	17
1	1	36	32	17	15	13
1	1	35	41	16	12	15
1	1	32	28	15	12	14
1	1	29	30	13	12	13
1	1	39	36	16	10	16
1	1	37	35	16	13	12
1	1	35	31	16	9	14
1	0	37	34	16	12	17
1	0	32	36	14	10	15
1	1	38	36	16	14	17
1	0	37	35	16	11	12
1	1	36	37	20	15	16
1	0	32	28	15	11	11
1	1	33	39	16	11	15
1	0	40	32	13	12	9
1	1	38	35	17	12	16
1	0	41	39	16	12	15
1	0	36	35	16	11	10
1	1	43	42	12	7	10
1	1	30	34	16	12	15
1	1	31	33	16	14	11
1	1	32	41	17	11	13
1	1	37	34	12	10	18
1	0	37	32	18	13	16
1	1	33	40	14	13	14
1	1	34	40	14	8	14
1	1	33	35	13	11	14
1	1	38	36	16	12	14
1	0	33	37	13	11	12
1	1	31	27	16	13	14
1	1	38	39	13	12	15
1	1	37	38	16	14	15
1	1	36	31	15	13	15
1	1	31	33	16	15	13
1	0	39	32	15	10	17
1	1	44	39	17	11	17
1	1	33	36	15	9	19
1	1	35	33	12	11	15
1	0	32	33	16	10	13
1	0	28	32	10	11	9
1	1	40	37	16	8	15
1	0	27	30	12	11	15
1	0	37	38	14	12	15
1	1	32	29	15	12	16
1	0	28	22	13	9	11
1	0	34	35	15	11	14
1	1	30	35	11	10	11
1	1	35	34	12	8	15
1	0	31	35	11	9	13
1	1	32	34	16	8	15
1	0	30	37	15	9	16
1	1	30	35	17	15	14
1	0	31	23	16	11	15
1	1	40	31	10	8	16
1	1	32	27	18	13	16
1	0	36	36	13	12	11
1	0	32	31	16	12	12
1	0	35	32	13	9	9
1	1	38	39	10	7	16
1	1	42	37	15	13	13
1	0	34	38	16	9	16
1	1	35	39	16	6	12
1	1	38	34	14	8	9
1	1	33	31	10	8	13
1	1	32	37	13	6	14
1	1	33	36	15	9	19
1	1	34	32	16	11	13
1	1	32	38	12	8	12
0	0	27	26	13	10	10
0	0	31	26	12	8	14
0	0	38	33	17	14	16
0	1	34	39	15	10	10
0	0	24	30	10	8	11
0	0	30	33	14	11	14
0	1	26	25	11	12	12
0	1	34	38	13	12	9
0	0	27	37	16	12	9
0	0	37	31	12	5	11
0	1	36	37	16	12	16
0	0	41	35	12	10	9
0	1	29	25	9	7	13
0	1	36	28	12	12	16
0	0	32	35	15	11	13
0	1	37	33	12	8	9
0	0	30	30	12	9	12
0	1	31	31	14	10	16
0	1	38	37	12	9	11
0	1	36	36	16	12	14
0	0	35	30	11	6	13
0	0	31	36	19	15	15
0	0	38	32	15	12	14
0	1	22	28	8	12	16
0	1	32	36	16	12	13
0	0	36	34	17	11	14
0	1	39	31	12	7	15
0	0	28	28	11	7	13
0	0	32	36	11	5	11
0	1	32	36	14	12	11
0	1	38	40	16	12	14
0	1	32	33	12	3	15
0	1	35	37	16	11	11
0	1	32	32	13	10	15
0	0	37	38	15	12	12
0	1	34	31	16	9	14
0	1	33	37	16	12	14
0	0	33	33	14	9	8
0	0	30	30	16	12	9
0	0	24	30	14	10	15
0	0	34	31	11	9	17
0	0	34	32	12	12	13
0	1	33	34	15	8	15
0	1	34	36	15	11	15
0	1	35	37	16	11	14
0	0	35	36	16	12	16
0	0	36	33	11	10	13
0	0	34	33	15	10	16
0	1	34	33	12	12	9
0	0	41	44	12	12	16
0	0	32	39	15	11	11
0	0	30	32	15	8	10
0	1	35	35	16	12	11
0	0	28	25	14	10	15
0	1	33	35	17	11	17
0	1	39	34	14	10	14
0	0	36	35	13	8	8
0	1	36	39	15	12	15
0	0	35	33	13	12	11
0	0	38	36	14	10	16
0	1	33	32	15	12	10
0	0	31	32	12	9	15
0	1	32	36	8	6	16
0	0	31	32	14	10	19
0	0	33	34	14	9	12
0	0	34	33	11	9	8
0	0	34	35	12	9	11
0	1	34	30	13	6	14
0	0	33	38	10	10	9
0	0	32	34	16	6	15
0	1	41	33	18	14	13
0	1	34	32	13	10	16
0	0	36	31	11	10	11
0	0	37	30	4	6	12
0	0	36	27	13	12	13
0	1	29	31	16	12	10
0	0	37	30	10	7	11
0	0	27	32	12	8	12
0	0	35	35	12	11	8
0	0	28	28	10	3	12
0	0	35	33	13	6	12
0	0	29	35	12	8	11
0	0	32	35	14	9	13
0	1	36	32	10	9	14
0	1	19	21	12	8	10
0	1	21	20	12	9	12
0	0	31	34	11	7	15
0	0	33	32	10	7	13
0	1	36	34	12	6	13
0	1	33	32	16	9	13
0	0	37	33	12	10	12
0	0	34	33	14	11	12
0	0	35	37	16	12	9
0	1	31	32	14	8	9
0	1	37	34	13	11	15
0	1	35	30	4	3	10
0	1	27	30	15	11	14
0	0	34	38	11	12	15
0	0	40	36	11	7	7
0	0	29	32	14	9	14
0	0	38	34	15	12	8
0	1	34	33	14	8	10
0	0	21	27	13	11	13
0	0	36	32	11	8	13
0	1	38	34	15	10	13
0	0	30	29	11	8	8
0	0	35	35	13	7	12
0	1	30	27	13	8	13
0	1	36	33	16	10	12
0	0	34	38	13	8	10
0	1	35	36	16	12	13
0	0	34	33	16	14	12
0	0	32	39	12	7	9
0	1	33	29	7	6	15
0	0	33	32	16	11	13
0	1	26	34	5	4	13
0	0	35	38	16	9	13
0	0	21	17	4	5	15
0	0	38	35	12	9	15
0	0	35	32	15	11	14
0	1	33	34	14	12	15
0	0	37	36	11	9	11
0	0	38	31	16	12	15
0	1	34	35	15	10	14
0	0	27	29	12	9	13
0	1	16	22	6	6	12
0	0	40	41	16	10	16
0	0	36	36	10	9	16
0	1	42	42	15	13	9
0	1	30	33	14	12	14

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time17 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 17 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184814&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]17 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184814&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184814&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 time17 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 11.37897344705 + 0.56594884567317Populatie[t] + 0.794072465790861Geslacht[t] + 0.0254836607336381Connected[t] -0.0129324071563781Seperate[t] + 0.112588656507544Learning[t] -0.0231412870773671Software[t] -0.00314978394761436t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  11.37897344705 +  0.56594884567317Populatie[t] +  0.794072465790861Geslacht[t] +  0.0254836607336381Connected[t] -0.0129324071563781Seperate[t] +  0.112588656507544Learning[t] -0.0231412870773671Software[t] -0.00314978394761436t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184814&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  11.37897344705 +  0.56594884567317Populatie[t] +  0.794072465790861Geslacht[t] +  0.0254836607336381Connected[t] -0.0129324071563781Seperate[t] +  0.112588656507544Learning[t] -0.0231412870773671Software[t] -0.00314978394761436t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184814&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184814&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
Happiness[t] = + 11.37897344705 + 0.56594884567317Populatie[t] + 0.794072465790861Geslacht[t] + 0.0254836607336381Connected[t] -0.0129324071563781Seperate[t] + 0.112588656507544Learning[t] -0.0231412870773671Software[t] -0.00314978394761436t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)11.378973447051.6746836.794700
Populatie0.565948845673170.5579191.01440.3112720.155636
Geslacht0.7940724657908610.2887952.74960.0063550.003178
Connected0.02548366073363810.0413590.61620.5382950.269147
Seperate-0.01293240715637810.04309-0.30010.7643030.382152
Learning0.1125886565075440.0743931.51340.1312980.065649
Software-0.02314128707736710.079769-0.29010.771950.385975
t-0.003149783947614360.00339-0.92910.353620.17681

\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) & 11.37897344705 & 1.674683 & 6.7947 & 0 & 0 \tabularnewline
Populatie & 0.56594884567317 & 0.557919 & 1.0144 & 0.311272 & 0.155636 \tabularnewline
Geslacht & 0.794072465790861 & 0.288795 & 2.7496 & 0.006355 & 0.003178 \tabularnewline
Connected & 0.0254836607336381 & 0.041359 & 0.6162 & 0.538295 & 0.269147 \tabularnewline
Seperate & -0.0129324071563781 & 0.04309 & -0.3001 & 0.764303 & 0.382152 \tabularnewline
Learning & 0.112588656507544 & 0.074393 & 1.5134 & 0.131298 & 0.065649 \tabularnewline
Software & -0.0231412870773671 & 0.079769 & -0.2901 & 0.77195 & 0.385975 \tabularnewline
t & -0.00314978394761436 & 0.00339 & -0.9291 & 0.35362 & 0.17681 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184814&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]11.37897344705[/C][C]1.674683[/C][C]6.7947[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Populatie[/C][C]0.56594884567317[/C][C]0.557919[/C][C]1.0144[/C][C]0.311272[/C][C]0.155636[/C][/ROW]
[ROW][C]Geslacht[/C][C]0.794072465790861[/C][C]0.288795[/C][C]2.7496[/C][C]0.006355[/C][C]0.003178[/C][/ROW]
[ROW][C]Connected[/C][C]0.0254836607336381[/C][C]0.041359[/C][C]0.6162[/C][C]0.538295[/C][C]0.269147[/C][/ROW]
[ROW][C]Seperate[/C][C]-0.0129324071563781[/C][C]0.04309[/C][C]-0.3001[/C][C]0.764303[/C][C]0.382152[/C][/ROW]
[ROW][C]Learning[/C][C]0.112588656507544[/C][C]0.074393[/C][C]1.5134[/C][C]0.131298[/C][C]0.065649[/C][/ROW]
[ROW][C]Software[/C][C]-0.0231412870773671[/C][C]0.079769[/C][C]-0.2901[/C][C]0.77195[/C][C]0.385975[/C][/ROW]
[ROW][C]t[/C][C]-0.00314978394761436[/C][C]0.00339[/C][C]-0.9291[/C][C]0.35362[/C][C]0.17681[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184814&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184814&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)11.378973447051.6746836.794700
Populatie0.565948845673170.5579191.01440.3112720.155636
Geslacht0.7940724657908610.2887952.74960.0063550.003178
Connected0.02548366073363810.0413590.61620.5382950.269147
Seperate-0.01293240715637810.04309-0.30010.7643030.382152
Learning0.1125886565075440.0743931.51340.1312980.065649
Software-0.02314128707736710.079769-0.29010.771950.385975
t-0.003149783947614360.00339-0.92910.353620.17681






Multiple Linear Regression - Regression Statistics
Multiple R0.345631177661747
R-squared0.119460910971846
Adjusted R-squared0.0974474337461426
F-TEST (value)5.42671699463994
F-TEST (DF numerator)7
F-TEST (DF denominator)280
p-value7.45462774376371e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.36910100619533
Sum Squared Residuals1571.5390817156

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.345631177661747 \tabularnewline
R-squared & 0.119460910971846 \tabularnewline
Adjusted R-squared & 0.0974474337461426 \tabularnewline
F-TEST (value) & 5.42671699463994 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 280 \tabularnewline
p-value & 7.45462774376371e-06 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.36910100619533 \tabularnewline
Sum Squared Residuals & 1571.5390817156 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184814&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.345631177661747[/C][/ROW]
[ROW][C]R-squared[/C][C]0.119460910971846[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0974474337461426[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]5.42671699463994[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]280[/C][/ROW]
[ROW][C]p-value[/C][C]7.45462774376371e-06[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.36910100619533[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1571.5390817156[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184814&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184814&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 R0.345631177661747
R-squared0.119460910971846
Adjusted R-squared0.0974474337461426
F-TEST (value)5.42671699463994
F-TEST (DF numerator)7
F-TEST (DF denominator)280
p-value7.45462774376371e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.36910100619533
Sum Squared Residuals1571.5390817156






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.4752006823728-0.475200682372824
21814.85958527649623.14041472350379
31114.8334861456899-3.83348614568988
41213.8455293286639-1.84552932866393
51614.38659569803351.61340430196654
61814.46922403679513.53077596320493
71415.1713934463598-1.17139344635978
81414.4795261227772-0.479526122777177
91514.47396998510040.526030014899593
101514.63951915815690.360480841843058
111714.04775478867692.95224521132307
121914.7026303534294.29736964657097
131013.9434430180015-3.94344301800145
141614.74419342618661.25580657381343
151814.62109759319163.37890240680842
161413.6943678595620.305632140438007
171413.852367699860.147632300139957
181715.13332396861531.86667603138472
191414.1595493536727-0.159549353672725
201614.60136225322631.39863774677368
211813.81434888340884.18565111659117
221114.5825114317538-3.58251143175383
231415.0073287660259-1.00732876602594
241214.6487958580868-2.64879585808677
251714.08251514934042.9174848506596
26914.9012638655736-5.90126386557355
271613.89466129542232.10533870457769
281414.3781143759349-0.378114375934873
291514.58556545127510.414434548724951
301113.6349321234099-2.63493212340986
311614.44157471971781.55842528028224
321313.2842845986752-0.284284598675187
331714.52187103387152.47812896612845
341514.54357056364510.456429436354897
351413.61169785098620.388302149013814
361613.18413533345882.81586466654118
37913.0841168074683-4.08411680746832
381513.61441859914151.38558140085851
391714.52428035733182.47571964266816
401313.8540952576824-0.854095257682441
411513.91484520235851.08515479764152
421614.34492460767461.65507539232539
431614.26867748584021.73132251415977
441213.6163188088769-1.6163188088769
451514.54835450870290.451645491297053
461114.0451456702497-3.04514567024968
471514.33037460085550.669625399144542
481514.42333977968380.576660220316178
491714.55750000581922.44249999418085
501313.6405209203938-0.640520920393767
511614.37984193375731.62015806624273
521413.55346677656420.4465332234358
531113.2400598839776-2.24005988397763
541214.4445011904591-2.44450119045907
551213.0709157632577-1.07091576325772
561514.49026152276040.509738477239627
571614.63734105798731.3626589420127
581514.37935466670330.620645333296697
591213.670689519091-1.670689519091
601214.5722396373646-2.57223963736464
61813.3442627620982-5.34426276209816
621313.8020360117247-0.802036011724726
631114.4318090693223-3.43180906932231
641414.1964548513908-0.196454851390794
651514.52352170420730.476478295792673
661013.7636360416944-3.7636360416944
671114.6953545680142-3.69535456801422
681213.918113472357-1.91811347235704
691514.07159458164750.928405418352519
701513.66158953647381.33841046352624
711413.16485635114760.835143648852354
721614.13245935834071.86754064165925
731514.57375891423570.426241085764259
741513.85260649311911.14739350688094
751313.7496810275658-0.749681027565834
761214.8112373093478-2.81123730934778
771714.46143954902122.53856045097877
781314.5057157999657-1.50571579996571
791513.19468432922541.8053156707746
801313.8103830900287-0.810383090028677
811513.58890699873911.41109300126089
821514.41786459489330.582135405106748
831613.610750638742.38924936125998
841514.28446389683610.715536103163933
851414.4813249386761-0.481324938676136
861513.50602570941711.49397429058289
871414.389945575157-0.389945575157039
881314.3107259625876-1.31072596258763
89714.2839897579106-7.28398975791064
901713.92273332273613.07726667726391
911314.5228270311557-1.52282703115569
921514.33463712679160.665362873208403
931414.3105689971684-0.310568997168439
941313.9799261036921-0.979926103692066
951614.53806702781991.46193297218007
961214.4274584683293-2.42745846832932
971414.5176361398494-0.517636139849407
981713.6631601288773.33683987112303
991513.32783248808811.67216751191194
1001714.40426929903882.59573070096125
1011213.6639196569551-1.66391965695512
1021614.76128334147271.23871665852732
1031113.5081399789788-2.5081399789788
1041514.29487849934310.705121500656929
105913.4056614682347-4.40566146823471
1061614.55717423317171.44282576682828
1071513.67208468050111.3279153194989
1081013.6163875085882-3.61638750858818
1091014.1373794877515-4.13737948775154
1101514.2410495621610.758950437839006
1111114.2300332719487-3.23003327194866
1121314.3309204092233-1.33092040922331
1131814.00591378357823.99408621642182
1141613.84066442596562.15933557403438
1151413.97583858159310.0241614184068868
1161414.113878893766-0.113878893765973
1171413.9678949671270.0321050328730349
1181414.3938557621364-0.393855762136428
1191213.1416581191281-1.14165811912812
1201414.3024209464358-0.302420946435768
1211514.00784321930180.992156780698181
1221514.28362557714480.716374422855158
1231514.25607161312810.743928386871941
1241314.1659447935523-1.16594479355231
1251713.58864201571863.41135798428139
1261714.61849217707312.38150782292688
1271914.19492460766434.80507539233573
1281513.89749082297571.1025091770243
1291313.4973135041438-0.497313504143849
130912.7064882582954-3.70648825829543
1311514.48350863343780.516491366562192
1321512.92574715699442.07425284300559
1331513.27601074906991.72398925093013
1341614.16849544815991.83150455184013
1351113.2041119537985-2.2041119537985
1361413.36463758008020.635362419919843
1371113.626412280036-2.62641228003604
1381513.92248443757531.07751556242472
1391312.8746651941610.125334805839042
1401514.29008851350930.709911486490692
1411613.26737177724952.73262822275049
1421414.1704888639564-0.1704888639564
1431513.533915652631.46608434736998
1441613.84462394601182.15537605398817
1451614.47433732149411.52566267850586
1461113.1228560548225-2.12285605482246
1471213.4201996332448-1.42019963324481
148913.2122263160512-4.2122263160512
1491613.69758973463282.30241026536718
1501314.246334968006-1.24633496800603
1511613.43746483005912.56253516994091
1521214.3103626267117-2.31036262671169
153914.1768659735771-5.17686597357706
1541313.6347404814002-0.634740481400216
1551413.91256113745810.0874388625419389
1561914.10358087318344.89641912681655
1571314.2439504609478-1.2439504609478
1581213.7313081477966-1.73130814779656
1591012.4622137169461-2.46221371694607
1601412.49469249358021.5053075064198
1611613.00349704474692.99650295525308
1621013.4822784760117-3.48227847601173
1631112.0299505749613-1.02995057496129
1641412.52183629874441.47816370125555
1651212.9533763383042-0.953376338304166
166913.2111518602078-4.21115186020783
167912.5862423620129-3.5862423620129
1681112.6271580118513-1.62715801185133
1691613.60336820651132.39663179348873
170912.5553570228783-3.5553570228783
1711312.90145773919110.0985422608088584
1721613.25995589304572.74004410695435
1731312.6311794068780.36882059312202
174913.3070430984116-4.30704309841164
1751212.3470911579295-0.347091157929468
1761613.35260111928772.6473988807123
1771113.2482064915996-2.24820649159956
1781413.58795255813910.412047441860879
1791312.41874553053180.581254469468242
1801512.92850432907542.07149567092463
1811412.77453903409071.22546096590934
1821612.42133217726843.5786678227316
1831313.4702689954665-0.470268995466497
1841412.93657614656021.06342385343976
1851513.37236889784531.62763110215472
1861312.22103494499840.77896505500162
1871112.262643120889-1.26264312088903
1881113.2293427627133-2.22934276271334
1891413.55254262755710.447457372442873
1901513.24493468696851.75506531303154
1911113.5317305860075-2.53173058600749
1921513.20216717319561.79783282680442
1931212.6336635230474-0.633663523047382
1941413.6206745905240.379325409475993
1951413.44502284167240.554977158327615
196812.5437767687764-4.54377676877644
197912.65872667588-3.65872667588003
1981512.32378018867022.67621981132977
1991712.24790992245744.75209007754265
2001312.27499252662880.725007473371196
2011513.44489785125781.55510214874224
2021513.37194305249891.62805694750108
2031413.49393317863610.506066821363887
2041612.68650204897663.31349795102335
2051312.23097243884880.76902756115118
2061612.62720995946413.37279004053589
207913.03408409763-4.03408409762999
2081612.27299099430683.72700900569318
2091112.4660575561384-1.46605755613835
2101012.5718911620502-2.57189116205021
2111113.4714584342906-2.47145843429059
2121512.44627989212012.55372010787993
2131713.5499214885133.45007851148701
2141413.39798139367830.60201860632168
215812.4450696722297-4.44506967222974
2161513.31687489015311.6831251098469
2171112.3465861096042-1.34658610960416
2181612.53996131705063.46003868294939
2191013.321501406204-3.32150140620399
2201512.20496972670772.7950302732923
2211612.5887156758613.411284324139
2221912.40070618475026.5992938152498
2231212.4458001950345-0.445800195034469
224812.1433005094542-4.14330050945424
2251112.2268745677014-1.22687456770141
2261413.26447180306620.735528196933805
227911.907975517511-2.90797551751096
2281512.69916878880992.30083121119005
2291313.7724238408085-0.772423840808467
2301613.13344270465352.86655729534649
2311112.1749428705236-1.1749428705236
2321211.51465370722270.485346292777334
2331312.39926767011420.600732329885759
2341013.2978410677191-3.29784106771914
2351112.1575950073477-1.15759500734772
2361212.0757798276887-0.0757798276886893
237812.1682782469089-4.16827824690894
2381212.0372226715244-0.0372226715243585
2391212.4161385852209-0.416138585220851
2401112.0753507918964-1.07535079189637
2411312.35068801608740.649311983912606
2421412.83198793630421.16801206369585
2431012.7861909986973-2.7861909986973
2441212.823799656296-0.823799656295977
2451512.03405423135182.96594576864822
2461311.99514792667671.00485207332335
2471313.0849753765005-0.0849753765005133
2481313.4121701894628-0.412170189462815
2491212.230454262395-0.230454262394971
2501212.3528895221842-0.352889522184163
251912.5255297962824-3.5255297962824
252913.1465677062674-4.14656770626736
2531513.08844255466921.91155744533083
2541012.2578874659308-2.25788746593084
2551413.10421332107820.895786678921836
2561511.90842152611663.09157847388341
257712.1997449562704-5.19974495627039
2581412.25948792824621.74051207175383
259812.502991071864-4.50299107186398
2601013.184888009731-3.18488800973098
2611311.95196009565381.04803990434617
2621312.11064973514590.889350264854086
2631313.3307469760191-0.330746976019123
264811.990245424318-3.99024542431799
2651212.2852381011928-0.285238101192754
2661313.0290604495415-0.0290604495414684
2671213.3927015824253-1.39270158242531
2681012.1883665800698-2.18836658006977
2691313.2758385581726-0.275838558172576
2701212.4456472950149-0.445647295014863
271912.0255701301731-3.0255701301731
2721512.43149854885342.56850145114659
2731312.49307055082690.506929449173139
2741312.00325658118050.996743418819528
2751312.50642643561540.493573564384626
2761511.15958722189973.84041277810029
2771512.165020445362.83497955463998
2781412.41570029604851.58429970395148
2791512.99406089852682.00593910147317
2801112.0045663691196-1.00456636911961
2811512.58508170299312.41491829700685
2821413.15603403092350.84396596907648
2831311.94339591654261.05660408345742
2841211.93841710259730.0615828974027059
2851612.54040839126093.45959160873908
2861611.84759534819274.15240465180725
287913.1842036857278-4.18420368572781
2881412.90219426795381.09780573204624

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 14.4752006823728 & -0.475200682372824 \tabularnewline
2 & 18 & 14.8595852764962 & 3.14041472350379 \tabularnewline
3 & 11 & 14.8334861456899 & -3.83348614568988 \tabularnewline
4 & 12 & 13.8455293286639 & -1.84552932866393 \tabularnewline
5 & 16 & 14.3865956980335 & 1.61340430196654 \tabularnewline
6 & 18 & 14.4692240367951 & 3.53077596320493 \tabularnewline
7 & 14 & 15.1713934463598 & -1.17139344635978 \tabularnewline
8 & 14 & 14.4795261227772 & -0.479526122777177 \tabularnewline
9 & 15 & 14.4739699851004 & 0.526030014899593 \tabularnewline
10 & 15 & 14.6395191581569 & 0.360480841843058 \tabularnewline
11 & 17 & 14.0477547886769 & 2.95224521132307 \tabularnewline
12 & 19 & 14.702630353429 & 4.29736964657097 \tabularnewline
13 & 10 & 13.9434430180015 & -3.94344301800145 \tabularnewline
14 & 16 & 14.7441934261866 & 1.25580657381343 \tabularnewline
15 & 18 & 14.6210975931916 & 3.37890240680842 \tabularnewline
16 & 14 & 13.694367859562 & 0.305632140438007 \tabularnewline
17 & 14 & 13.85236769986 & 0.147632300139957 \tabularnewline
18 & 17 & 15.1333239686153 & 1.86667603138472 \tabularnewline
19 & 14 & 14.1595493536727 & -0.159549353672725 \tabularnewline
20 & 16 & 14.6013622532263 & 1.39863774677368 \tabularnewline
21 & 18 & 13.8143488834088 & 4.18565111659117 \tabularnewline
22 & 11 & 14.5825114317538 & -3.58251143175383 \tabularnewline
23 & 14 & 15.0073287660259 & -1.00732876602594 \tabularnewline
24 & 12 & 14.6487958580868 & -2.64879585808677 \tabularnewline
25 & 17 & 14.0825151493404 & 2.9174848506596 \tabularnewline
26 & 9 & 14.9012638655736 & -5.90126386557355 \tabularnewline
27 & 16 & 13.8946612954223 & 2.10533870457769 \tabularnewline
28 & 14 & 14.3781143759349 & -0.378114375934873 \tabularnewline
29 & 15 & 14.5855654512751 & 0.414434548724951 \tabularnewline
30 & 11 & 13.6349321234099 & -2.63493212340986 \tabularnewline
31 & 16 & 14.4415747197178 & 1.55842528028224 \tabularnewline
32 & 13 & 13.2842845986752 & -0.284284598675187 \tabularnewline
33 & 17 & 14.5218710338715 & 2.47812896612845 \tabularnewline
34 & 15 & 14.5435705636451 & 0.456429436354897 \tabularnewline
35 & 14 & 13.6116978509862 & 0.388302149013814 \tabularnewline
36 & 16 & 13.1841353334588 & 2.81586466654118 \tabularnewline
37 & 9 & 13.0841168074683 & -4.08411680746832 \tabularnewline
38 & 15 & 13.6144185991415 & 1.38558140085851 \tabularnewline
39 & 17 & 14.5242803573318 & 2.47571964266816 \tabularnewline
40 & 13 & 13.8540952576824 & -0.854095257682441 \tabularnewline
41 & 15 & 13.9148452023585 & 1.08515479764152 \tabularnewline
42 & 16 & 14.3449246076746 & 1.65507539232539 \tabularnewline
43 & 16 & 14.2686774858402 & 1.73132251415977 \tabularnewline
44 & 12 & 13.6163188088769 & -1.6163188088769 \tabularnewline
45 & 15 & 14.5483545087029 & 0.451645491297053 \tabularnewline
46 & 11 & 14.0451456702497 & -3.04514567024968 \tabularnewline
47 & 15 & 14.3303746008555 & 0.669625399144542 \tabularnewline
48 & 15 & 14.4233397796838 & 0.576660220316178 \tabularnewline
49 & 17 & 14.5575000058192 & 2.44249999418085 \tabularnewline
50 & 13 & 13.6405209203938 & -0.640520920393767 \tabularnewline
51 & 16 & 14.3798419337573 & 1.62015806624273 \tabularnewline
52 & 14 & 13.5534667765642 & 0.4465332234358 \tabularnewline
53 & 11 & 13.2400598839776 & -2.24005988397763 \tabularnewline
54 & 12 & 14.4445011904591 & -2.44450119045907 \tabularnewline
55 & 12 & 13.0709157632577 & -1.07091576325772 \tabularnewline
56 & 15 & 14.4902615227604 & 0.509738477239627 \tabularnewline
57 & 16 & 14.6373410579873 & 1.3626589420127 \tabularnewline
58 & 15 & 14.3793546667033 & 0.620645333296697 \tabularnewline
59 & 12 & 13.670689519091 & -1.670689519091 \tabularnewline
60 & 12 & 14.5722396373646 & -2.57223963736464 \tabularnewline
61 & 8 & 13.3442627620982 & -5.34426276209816 \tabularnewline
62 & 13 & 13.8020360117247 & -0.802036011724726 \tabularnewline
63 & 11 & 14.4318090693223 & -3.43180906932231 \tabularnewline
64 & 14 & 14.1964548513908 & -0.196454851390794 \tabularnewline
65 & 15 & 14.5235217042073 & 0.476478295792673 \tabularnewline
66 & 10 & 13.7636360416944 & -3.7636360416944 \tabularnewline
67 & 11 & 14.6953545680142 & -3.69535456801422 \tabularnewline
68 & 12 & 13.918113472357 & -1.91811347235704 \tabularnewline
69 & 15 & 14.0715945816475 & 0.928405418352519 \tabularnewline
70 & 15 & 13.6615895364738 & 1.33841046352624 \tabularnewline
71 & 14 & 13.1648563511476 & 0.835143648852354 \tabularnewline
72 & 16 & 14.1324593583407 & 1.86754064165925 \tabularnewline
73 & 15 & 14.5737589142357 & 0.426241085764259 \tabularnewline
74 & 15 & 13.8526064931191 & 1.14739350688094 \tabularnewline
75 & 13 & 13.7496810275658 & -0.749681027565834 \tabularnewline
76 & 12 & 14.8112373093478 & -2.81123730934778 \tabularnewline
77 & 17 & 14.4614395490212 & 2.53856045097877 \tabularnewline
78 & 13 & 14.5057157999657 & -1.50571579996571 \tabularnewline
79 & 15 & 13.1946843292254 & 1.8053156707746 \tabularnewline
80 & 13 & 13.8103830900287 & -0.810383090028677 \tabularnewline
81 & 15 & 13.5889069987391 & 1.41109300126089 \tabularnewline
82 & 15 & 14.4178645948933 & 0.582135405106748 \tabularnewline
83 & 16 & 13.61075063874 & 2.38924936125998 \tabularnewline
84 & 15 & 14.2844638968361 & 0.715536103163933 \tabularnewline
85 & 14 & 14.4813249386761 & -0.481324938676136 \tabularnewline
86 & 15 & 13.5060257094171 & 1.49397429058289 \tabularnewline
87 & 14 & 14.389945575157 & -0.389945575157039 \tabularnewline
88 & 13 & 14.3107259625876 & -1.31072596258763 \tabularnewline
89 & 7 & 14.2839897579106 & -7.28398975791064 \tabularnewline
90 & 17 & 13.9227333227361 & 3.07726667726391 \tabularnewline
91 & 13 & 14.5228270311557 & -1.52282703115569 \tabularnewline
92 & 15 & 14.3346371267916 & 0.665362873208403 \tabularnewline
93 & 14 & 14.3105689971684 & -0.310568997168439 \tabularnewline
94 & 13 & 13.9799261036921 & -0.979926103692066 \tabularnewline
95 & 16 & 14.5380670278199 & 1.46193297218007 \tabularnewline
96 & 12 & 14.4274584683293 & -2.42745846832932 \tabularnewline
97 & 14 & 14.5176361398494 & -0.517636139849407 \tabularnewline
98 & 17 & 13.663160128877 & 3.33683987112303 \tabularnewline
99 & 15 & 13.3278324880881 & 1.67216751191194 \tabularnewline
100 & 17 & 14.4042692990388 & 2.59573070096125 \tabularnewline
101 & 12 & 13.6639196569551 & -1.66391965695512 \tabularnewline
102 & 16 & 14.7612833414727 & 1.23871665852732 \tabularnewline
103 & 11 & 13.5081399789788 & -2.5081399789788 \tabularnewline
104 & 15 & 14.2948784993431 & 0.705121500656929 \tabularnewline
105 & 9 & 13.4056614682347 & -4.40566146823471 \tabularnewline
106 & 16 & 14.5571742331717 & 1.44282576682828 \tabularnewline
107 & 15 & 13.6720846805011 & 1.3279153194989 \tabularnewline
108 & 10 & 13.6163875085882 & -3.61638750858818 \tabularnewline
109 & 10 & 14.1373794877515 & -4.13737948775154 \tabularnewline
110 & 15 & 14.241049562161 & 0.758950437839006 \tabularnewline
111 & 11 & 14.2300332719487 & -3.23003327194866 \tabularnewline
112 & 13 & 14.3309204092233 & -1.33092040922331 \tabularnewline
113 & 18 & 14.0059137835782 & 3.99408621642182 \tabularnewline
114 & 16 & 13.8406644259656 & 2.15933557403438 \tabularnewline
115 & 14 & 13.9758385815931 & 0.0241614184068868 \tabularnewline
116 & 14 & 14.113878893766 & -0.113878893765973 \tabularnewline
117 & 14 & 13.967894967127 & 0.0321050328730349 \tabularnewline
118 & 14 & 14.3938557621364 & -0.393855762136428 \tabularnewline
119 & 12 & 13.1416581191281 & -1.14165811912812 \tabularnewline
120 & 14 & 14.3024209464358 & -0.302420946435768 \tabularnewline
121 & 15 & 14.0078432193018 & 0.992156780698181 \tabularnewline
122 & 15 & 14.2836255771448 & 0.716374422855158 \tabularnewline
123 & 15 & 14.2560716131281 & 0.743928386871941 \tabularnewline
124 & 13 & 14.1659447935523 & -1.16594479355231 \tabularnewline
125 & 17 & 13.5886420157186 & 3.41135798428139 \tabularnewline
126 & 17 & 14.6184921770731 & 2.38150782292688 \tabularnewline
127 & 19 & 14.1949246076643 & 4.80507539233573 \tabularnewline
128 & 15 & 13.8974908229757 & 1.1025091770243 \tabularnewline
129 & 13 & 13.4973135041438 & -0.497313504143849 \tabularnewline
130 & 9 & 12.7064882582954 & -3.70648825829543 \tabularnewline
131 & 15 & 14.4835086334378 & 0.516491366562192 \tabularnewline
132 & 15 & 12.9257471569944 & 2.07425284300559 \tabularnewline
133 & 15 & 13.2760107490699 & 1.72398925093013 \tabularnewline
134 & 16 & 14.1684954481599 & 1.83150455184013 \tabularnewline
135 & 11 & 13.2041119537985 & -2.2041119537985 \tabularnewline
136 & 14 & 13.3646375800802 & 0.635362419919843 \tabularnewline
137 & 11 & 13.626412280036 & -2.62641228003604 \tabularnewline
138 & 15 & 13.9224844375753 & 1.07751556242472 \tabularnewline
139 & 13 & 12.874665194161 & 0.125334805839042 \tabularnewline
140 & 15 & 14.2900885135093 & 0.709911486490692 \tabularnewline
141 & 16 & 13.2673717772495 & 2.73262822275049 \tabularnewline
142 & 14 & 14.1704888639564 & -0.1704888639564 \tabularnewline
143 & 15 & 13.53391565263 & 1.46608434736998 \tabularnewline
144 & 16 & 13.8446239460118 & 2.15537605398817 \tabularnewline
145 & 16 & 14.4743373214941 & 1.52566267850586 \tabularnewline
146 & 11 & 13.1228560548225 & -2.12285605482246 \tabularnewline
147 & 12 & 13.4201996332448 & -1.42019963324481 \tabularnewline
148 & 9 & 13.2122263160512 & -4.2122263160512 \tabularnewline
149 & 16 & 13.6975897346328 & 2.30241026536718 \tabularnewline
150 & 13 & 14.246334968006 & -1.24633496800603 \tabularnewline
151 & 16 & 13.4374648300591 & 2.56253516994091 \tabularnewline
152 & 12 & 14.3103626267117 & -2.31036262671169 \tabularnewline
153 & 9 & 14.1768659735771 & -5.17686597357706 \tabularnewline
154 & 13 & 13.6347404814002 & -0.634740481400216 \tabularnewline
155 & 14 & 13.9125611374581 & 0.0874388625419389 \tabularnewline
156 & 19 & 14.1035808731834 & 4.89641912681655 \tabularnewline
157 & 13 & 14.2439504609478 & -1.2439504609478 \tabularnewline
158 & 12 & 13.7313081477966 & -1.73130814779656 \tabularnewline
159 & 10 & 12.4622137169461 & -2.46221371694607 \tabularnewline
160 & 14 & 12.4946924935802 & 1.5053075064198 \tabularnewline
161 & 16 & 13.0034970447469 & 2.99650295525308 \tabularnewline
162 & 10 & 13.4822784760117 & -3.48227847601173 \tabularnewline
163 & 11 & 12.0299505749613 & -1.02995057496129 \tabularnewline
164 & 14 & 12.5218362987444 & 1.47816370125555 \tabularnewline
165 & 12 & 12.9533763383042 & -0.953376338304166 \tabularnewline
166 & 9 & 13.2111518602078 & -4.21115186020783 \tabularnewline
167 & 9 & 12.5862423620129 & -3.5862423620129 \tabularnewline
168 & 11 & 12.6271580118513 & -1.62715801185133 \tabularnewline
169 & 16 & 13.6033682065113 & 2.39663179348873 \tabularnewline
170 & 9 & 12.5553570228783 & -3.5553570228783 \tabularnewline
171 & 13 & 12.9014577391911 & 0.0985422608088584 \tabularnewline
172 & 16 & 13.2599558930457 & 2.74004410695435 \tabularnewline
173 & 13 & 12.631179406878 & 0.36882059312202 \tabularnewline
174 & 9 & 13.3070430984116 & -4.30704309841164 \tabularnewline
175 & 12 & 12.3470911579295 & -0.347091157929468 \tabularnewline
176 & 16 & 13.3526011192877 & 2.6473988807123 \tabularnewline
177 & 11 & 13.2482064915996 & -2.24820649159956 \tabularnewline
178 & 14 & 13.5879525581391 & 0.412047441860879 \tabularnewline
179 & 13 & 12.4187455305318 & 0.581254469468242 \tabularnewline
180 & 15 & 12.9285043290754 & 2.07149567092463 \tabularnewline
181 & 14 & 12.7745390340907 & 1.22546096590934 \tabularnewline
182 & 16 & 12.4213321772684 & 3.5786678227316 \tabularnewline
183 & 13 & 13.4702689954665 & -0.470268995466497 \tabularnewline
184 & 14 & 12.9365761465602 & 1.06342385343976 \tabularnewline
185 & 15 & 13.3723688978453 & 1.62763110215472 \tabularnewline
186 & 13 & 12.2210349449984 & 0.77896505500162 \tabularnewline
187 & 11 & 12.262643120889 & -1.26264312088903 \tabularnewline
188 & 11 & 13.2293427627133 & -2.22934276271334 \tabularnewline
189 & 14 & 13.5525426275571 & 0.447457372442873 \tabularnewline
190 & 15 & 13.2449346869685 & 1.75506531303154 \tabularnewline
191 & 11 & 13.5317305860075 & -2.53173058600749 \tabularnewline
192 & 15 & 13.2021671731956 & 1.79783282680442 \tabularnewline
193 & 12 & 12.6336635230474 & -0.633663523047382 \tabularnewline
194 & 14 & 13.620674590524 & 0.379325409475993 \tabularnewline
195 & 14 & 13.4450228416724 & 0.554977158327615 \tabularnewline
196 & 8 & 12.5437767687764 & -4.54377676877644 \tabularnewline
197 & 9 & 12.65872667588 & -3.65872667588003 \tabularnewline
198 & 15 & 12.3237801886702 & 2.67621981132977 \tabularnewline
199 & 17 & 12.2479099224574 & 4.75209007754265 \tabularnewline
200 & 13 & 12.2749925266288 & 0.725007473371196 \tabularnewline
201 & 15 & 13.4448978512578 & 1.55510214874224 \tabularnewline
202 & 15 & 13.3719430524989 & 1.62805694750108 \tabularnewline
203 & 14 & 13.4939331786361 & 0.506066821363887 \tabularnewline
204 & 16 & 12.6865020489766 & 3.31349795102335 \tabularnewline
205 & 13 & 12.2309724388488 & 0.76902756115118 \tabularnewline
206 & 16 & 12.6272099594641 & 3.37279004053589 \tabularnewline
207 & 9 & 13.03408409763 & -4.03408409762999 \tabularnewline
208 & 16 & 12.2729909943068 & 3.72700900569318 \tabularnewline
209 & 11 & 12.4660575561384 & -1.46605755613835 \tabularnewline
210 & 10 & 12.5718911620502 & -2.57189116205021 \tabularnewline
211 & 11 & 13.4714584342906 & -2.47145843429059 \tabularnewline
212 & 15 & 12.4462798921201 & 2.55372010787993 \tabularnewline
213 & 17 & 13.549921488513 & 3.45007851148701 \tabularnewline
214 & 14 & 13.3979813936783 & 0.60201860632168 \tabularnewline
215 & 8 & 12.4450696722297 & -4.44506967222974 \tabularnewline
216 & 15 & 13.3168748901531 & 1.6831251098469 \tabularnewline
217 & 11 & 12.3465861096042 & -1.34658610960416 \tabularnewline
218 & 16 & 12.5399613170506 & 3.46003868294939 \tabularnewline
219 & 10 & 13.321501406204 & -3.32150140620399 \tabularnewline
220 & 15 & 12.2049697267077 & 2.7950302732923 \tabularnewline
221 & 16 & 12.588715675861 & 3.411284324139 \tabularnewline
222 & 19 & 12.4007061847502 & 6.5992938152498 \tabularnewline
223 & 12 & 12.4458001950345 & -0.445800195034469 \tabularnewline
224 & 8 & 12.1433005094542 & -4.14330050945424 \tabularnewline
225 & 11 & 12.2268745677014 & -1.22687456770141 \tabularnewline
226 & 14 & 13.2644718030662 & 0.735528196933805 \tabularnewline
227 & 9 & 11.907975517511 & -2.90797551751096 \tabularnewline
228 & 15 & 12.6991687888099 & 2.30083121119005 \tabularnewline
229 & 13 & 13.7724238408085 & -0.772423840808467 \tabularnewline
230 & 16 & 13.1334427046535 & 2.86655729534649 \tabularnewline
231 & 11 & 12.1749428705236 & -1.1749428705236 \tabularnewline
232 & 12 & 11.5146537072227 & 0.485346292777334 \tabularnewline
233 & 13 & 12.3992676701142 & 0.600732329885759 \tabularnewline
234 & 10 & 13.2978410677191 & -3.29784106771914 \tabularnewline
235 & 11 & 12.1575950073477 & -1.15759500734772 \tabularnewline
236 & 12 & 12.0757798276887 & -0.0757798276886893 \tabularnewline
237 & 8 & 12.1682782469089 & -4.16827824690894 \tabularnewline
238 & 12 & 12.0372226715244 & -0.0372226715243585 \tabularnewline
239 & 12 & 12.4161385852209 & -0.416138585220851 \tabularnewline
240 & 11 & 12.0753507918964 & -1.07535079189637 \tabularnewline
241 & 13 & 12.3506880160874 & 0.649311983912606 \tabularnewline
242 & 14 & 12.8319879363042 & 1.16801206369585 \tabularnewline
243 & 10 & 12.7861909986973 & -2.7861909986973 \tabularnewline
244 & 12 & 12.823799656296 & -0.823799656295977 \tabularnewline
245 & 15 & 12.0340542313518 & 2.96594576864822 \tabularnewline
246 & 13 & 11.9951479266767 & 1.00485207332335 \tabularnewline
247 & 13 & 13.0849753765005 & -0.0849753765005133 \tabularnewline
248 & 13 & 13.4121701894628 & -0.412170189462815 \tabularnewline
249 & 12 & 12.230454262395 & -0.230454262394971 \tabularnewline
250 & 12 & 12.3528895221842 & -0.352889522184163 \tabularnewline
251 & 9 & 12.5255297962824 & -3.5255297962824 \tabularnewline
252 & 9 & 13.1465677062674 & -4.14656770626736 \tabularnewline
253 & 15 & 13.0884425546692 & 1.91155744533083 \tabularnewline
254 & 10 & 12.2578874659308 & -2.25788746593084 \tabularnewline
255 & 14 & 13.1042133210782 & 0.895786678921836 \tabularnewline
256 & 15 & 11.9084215261166 & 3.09157847388341 \tabularnewline
257 & 7 & 12.1997449562704 & -5.19974495627039 \tabularnewline
258 & 14 & 12.2594879282462 & 1.74051207175383 \tabularnewline
259 & 8 & 12.502991071864 & -4.50299107186398 \tabularnewline
260 & 10 & 13.184888009731 & -3.18488800973098 \tabularnewline
261 & 13 & 11.9519600956538 & 1.04803990434617 \tabularnewline
262 & 13 & 12.1106497351459 & 0.889350264854086 \tabularnewline
263 & 13 & 13.3307469760191 & -0.330746976019123 \tabularnewline
264 & 8 & 11.990245424318 & -3.99024542431799 \tabularnewline
265 & 12 & 12.2852381011928 & -0.285238101192754 \tabularnewline
266 & 13 & 13.0290604495415 & -0.0290604495414684 \tabularnewline
267 & 12 & 13.3927015824253 & -1.39270158242531 \tabularnewline
268 & 10 & 12.1883665800698 & -2.18836658006977 \tabularnewline
269 & 13 & 13.2758385581726 & -0.275838558172576 \tabularnewline
270 & 12 & 12.4456472950149 & -0.445647295014863 \tabularnewline
271 & 9 & 12.0255701301731 & -3.0255701301731 \tabularnewline
272 & 15 & 12.4314985488534 & 2.56850145114659 \tabularnewline
273 & 13 & 12.4930705508269 & 0.506929449173139 \tabularnewline
274 & 13 & 12.0032565811805 & 0.996743418819528 \tabularnewline
275 & 13 & 12.5064264356154 & 0.493573564384626 \tabularnewline
276 & 15 & 11.1595872218997 & 3.84041277810029 \tabularnewline
277 & 15 & 12.16502044536 & 2.83497955463998 \tabularnewline
278 & 14 & 12.4157002960485 & 1.58429970395148 \tabularnewline
279 & 15 & 12.9940608985268 & 2.00593910147317 \tabularnewline
280 & 11 & 12.0045663691196 & -1.00456636911961 \tabularnewline
281 & 15 & 12.5850817029931 & 2.41491829700685 \tabularnewline
282 & 14 & 13.1560340309235 & 0.84396596907648 \tabularnewline
283 & 13 & 11.9433959165426 & 1.05660408345742 \tabularnewline
284 & 12 & 11.9384171025973 & 0.0615828974027059 \tabularnewline
285 & 16 & 12.5404083912609 & 3.45959160873908 \tabularnewline
286 & 16 & 11.8475953481927 & 4.15240465180725 \tabularnewline
287 & 9 & 13.1842036857278 & -4.18420368572781 \tabularnewline
288 & 14 & 12.9021942679538 & 1.09780573204624 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184814&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]14[/C][C]14.4752006823728[/C][C]-0.475200682372824[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]14.8595852764962[/C][C]3.14041472350379[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]14.8334861456899[/C][C]-3.83348614568988[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]13.8455293286639[/C][C]-1.84552932866393[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]14.3865956980335[/C][C]1.61340430196654[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.4692240367951[/C][C]3.53077596320493[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]15.1713934463598[/C][C]-1.17139344635978[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]14.4795261227772[/C][C]-0.479526122777177[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]14.4739699851004[/C][C]0.526030014899593[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.6395191581569[/C][C]0.360480841843058[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]14.0477547886769[/C][C]2.95224521132307[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]14.702630353429[/C][C]4.29736964657097[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.9434430180015[/C][C]-3.94344301800145[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]14.7441934261866[/C][C]1.25580657381343[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]14.6210975931916[/C][C]3.37890240680842[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.694367859562[/C][C]0.305632140438007[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.85236769986[/C][C]0.147632300139957[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.1333239686153[/C][C]1.86667603138472[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]14.1595493536727[/C][C]-0.159549353672725[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]14.6013622532263[/C][C]1.39863774677368[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]13.8143488834088[/C][C]4.18565111659117[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]14.5825114317538[/C][C]-3.58251143175383[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]15.0073287660259[/C][C]-1.00732876602594[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]14.6487958580868[/C][C]-2.64879585808677[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]14.0825151493404[/C][C]2.9174848506596[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]14.9012638655736[/C][C]-5.90126386557355[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]13.8946612954223[/C][C]2.10533870457769[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]14.3781143759349[/C][C]-0.378114375934873[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]14.5855654512751[/C][C]0.414434548724951[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]13.6349321234099[/C][C]-2.63493212340986[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]14.4415747197178[/C][C]1.55842528028224[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]13.2842845986752[/C][C]-0.284284598675187[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]14.5218710338715[/C][C]2.47812896612845[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]14.5435705636451[/C][C]0.456429436354897[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]13.6116978509862[/C][C]0.388302149013814[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]13.1841353334588[/C][C]2.81586466654118[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]13.0841168074683[/C][C]-4.08411680746832[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]13.6144185991415[/C][C]1.38558140085851[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]14.5242803573318[/C][C]2.47571964266816[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]13.8540952576824[/C][C]-0.854095257682441[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]13.9148452023585[/C][C]1.08515479764152[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]14.3449246076746[/C][C]1.65507539232539[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]14.2686774858402[/C][C]1.73132251415977[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.6163188088769[/C][C]-1.6163188088769[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.5483545087029[/C][C]0.451645491297053[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]14.0451456702497[/C][C]-3.04514567024968[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]14.3303746008555[/C][C]0.669625399144542[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.4233397796838[/C][C]0.576660220316178[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]14.5575000058192[/C][C]2.44249999418085[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]13.6405209203938[/C][C]-0.640520920393767[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]14.3798419337573[/C][C]1.62015806624273[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.5534667765642[/C][C]0.4465332234358[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]13.2400598839776[/C][C]-2.24005988397763[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]14.4445011904591[/C][C]-2.44450119045907[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]13.0709157632577[/C][C]-1.07091576325772[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]14.4902615227604[/C][C]0.509738477239627[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.6373410579873[/C][C]1.3626589420127[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]14.3793546667033[/C][C]0.620645333296697[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]13.670689519091[/C][C]-1.670689519091[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]14.5722396373646[/C][C]-2.57223963736464[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]13.3442627620982[/C][C]-5.34426276209816[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]13.8020360117247[/C][C]-0.802036011724726[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.4318090693223[/C][C]-3.43180906932231[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.1964548513908[/C][C]-0.196454851390794[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]14.5235217042073[/C][C]0.476478295792673[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]13.7636360416944[/C][C]-3.7636360416944[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]14.6953545680142[/C][C]-3.69535456801422[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]13.918113472357[/C][C]-1.91811347235704[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]14.0715945816475[/C][C]0.928405418352519[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.6615895364738[/C][C]1.33841046352624[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.1648563511476[/C][C]0.835143648852354[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]14.1324593583407[/C][C]1.86754064165925[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.5737589142357[/C][C]0.426241085764259[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]13.8526064931191[/C][C]1.14739350688094[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]13.7496810275658[/C][C]-0.749681027565834[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]14.8112373093478[/C][C]-2.81123730934778[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]14.4614395490212[/C][C]2.53856045097877[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]14.5057157999657[/C][C]-1.50571579996571[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.1946843292254[/C][C]1.8053156707746[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]13.8103830900287[/C][C]-0.810383090028677[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]13.5889069987391[/C][C]1.41109300126089[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]14.4178645948933[/C][C]0.582135405106748[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]13.61075063874[/C][C]2.38924936125998[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.2844638968361[/C][C]0.715536103163933[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.4813249386761[/C][C]-0.481324938676136[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.5060257094171[/C][C]1.49397429058289[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.389945575157[/C][C]-0.389945575157039[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]14.3107259625876[/C][C]-1.31072596258763[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]14.2839897579106[/C][C]-7.28398975791064[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.9227333227361[/C][C]3.07726667726391[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]14.5228270311557[/C][C]-1.52282703115569[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.3346371267916[/C][C]0.665362873208403[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]14.3105689971684[/C][C]-0.310568997168439[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.9799261036921[/C][C]-0.979926103692066[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.5380670278199[/C][C]1.46193297218007[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]14.4274584683293[/C][C]-2.42745846832932[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.5176361398494[/C][C]-0.517636139849407[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]13.663160128877[/C][C]3.33683987112303[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]13.3278324880881[/C][C]1.67216751191194[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]14.4042692990388[/C][C]2.59573070096125[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]13.6639196569551[/C][C]-1.66391965695512[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]14.7612833414727[/C][C]1.23871665852732[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]13.5081399789788[/C][C]-2.5081399789788[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]14.2948784993431[/C][C]0.705121500656929[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]13.4056614682347[/C][C]-4.40566146823471[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.5571742331717[/C][C]1.44282576682828[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]13.6720846805011[/C][C]1.3279153194989[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]13.6163875085882[/C][C]-3.61638750858818[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]14.1373794877515[/C][C]-4.13737948775154[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]14.241049562161[/C][C]0.758950437839006[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]14.2300332719487[/C][C]-3.23003327194866[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]14.3309204092233[/C][C]-1.33092040922331[/C][/ROW]
[ROW][C]113[/C][C]18[/C][C]14.0059137835782[/C][C]3.99408621642182[/C][/ROW]
[ROW][C]114[/C][C]16[/C][C]13.8406644259656[/C][C]2.15933557403438[/C][/ROW]
[ROW][C]115[/C][C]14[/C][C]13.9758385815931[/C][C]0.0241614184068868[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]14.113878893766[/C][C]-0.113878893765973[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.967894967127[/C][C]0.0321050328730349[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]14.3938557621364[/C][C]-0.393855762136428[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]13.1416581191281[/C][C]-1.14165811912812[/C][/ROW]
[ROW][C]120[/C][C]14[/C][C]14.3024209464358[/C][C]-0.302420946435768[/C][/ROW]
[ROW][C]121[/C][C]15[/C][C]14.0078432193018[/C][C]0.992156780698181[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.2836255771448[/C][C]0.716374422855158[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]14.2560716131281[/C][C]0.743928386871941[/C][/ROW]
[ROW][C]124[/C][C]13[/C][C]14.1659447935523[/C][C]-1.16594479355231[/C][/ROW]
[ROW][C]125[/C][C]17[/C][C]13.5886420157186[/C][C]3.41135798428139[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]14.6184921770731[/C][C]2.38150782292688[/C][/ROW]
[ROW][C]127[/C][C]19[/C][C]14.1949246076643[/C][C]4.80507539233573[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]13.8974908229757[/C][C]1.1025091770243[/C][/ROW]
[ROW][C]129[/C][C]13[/C][C]13.4973135041438[/C][C]-0.497313504143849[/C][/ROW]
[ROW][C]130[/C][C]9[/C][C]12.7064882582954[/C][C]-3.70648825829543[/C][/ROW]
[ROW][C]131[/C][C]15[/C][C]14.4835086334378[/C][C]0.516491366562192[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]12.9257471569944[/C][C]2.07425284300559[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]13.2760107490699[/C][C]1.72398925093013[/C][/ROW]
[ROW][C]134[/C][C]16[/C][C]14.1684954481599[/C][C]1.83150455184013[/C][/ROW]
[ROW][C]135[/C][C]11[/C][C]13.2041119537985[/C][C]-2.2041119537985[/C][/ROW]
[ROW][C]136[/C][C]14[/C][C]13.3646375800802[/C][C]0.635362419919843[/C][/ROW]
[ROW][C]137[/C][C]11[/C][C]13.626412280036[/C][C]-2.62641228003604[/C][/ROW]
[ROW][C]138[/C][C]15[/C][C]13.9224844375753[/C][C]1.07751556242472[/C][/ROW]
[ROW][C]139[/C][C]13[/C][C]12.874665194161[/C][C]0.125334805839042[/C][/ROW]
[ROW][C]140[/C][C]15[/C][C]14.2900885135093[/C][C]0.709911486490692[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]13.2673717772495[/C][C]2.73262822275049[/C][/ROW]
[ROW][C]142[/C][C]14[/C][C]14.1704888639564[/C][C]-0.1704888639564[/C][/ROW]
[ROW][C]143[/C][C]15[/C][C]13.53391565263[/C][C]1.46608434736998[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]13.8446239460118[/C][C]2.15537605398817[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.4743373214941[/C][C]1.52566267850586[/C][/ROW]
[ROW][C]146[/C][C]11[/C][C]13.1228560548225[/C][C]-2.12285605482246[/C][/ROW]
[ROW][C]147[/C][C]12[/C][C]13.4201996332448[/C][C]-1.42019963324481[/C][/ROW]
[ROW][C]148[/C][C]9[/C][C]13.2122263160512[/C][C]-4.2122263160512[/C][/ROW]
[ROW][C]149[/C][C]16[/C][C]13.6975897346328[/C][C]2.30241026536718[/C][/ROW]
[ROW][C]150[/C][C]13[/C][C]14.246334968006[/C][C]-1.24633496800603[/C][/ROW]
[ROW][C]151[/C][C]16[/C][C]13.4374648300591[/C][C]2.56253516994091[/C][/ROW]
[ROW][C]152[/C][C]12[/C][C]14.3103626267117[/C][C]-2.31036262671169[/C][/ROW]
[ROW][C]153[/C][C]9[/C][C]14.1768659735771[/C][C]-5.17686597357706[/C][/ROW]
[ROW][C]154[/C][C]13[/C][C]13.6347404814002[/C][C]-0.634740481400216[/C][/ROW]
[ROW][C]155[/C][C]14[/C][C]13.9125611374581[/C][C]0.0874388625419389[/C][/ROW]
[ROW][C]156[/C][C]19[/C][C]14.1035808731834[/C][C]4.89641912681655[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]14.2439504609478[/C][C]-1.2439504609478[/C][/ROW]
[ROW][C]158[/C][C]12[/C][C]13.7313081477966[/C][C]-1.73130814779656[/C][/ROW]
[ROW][C]159[/C][C]10[/C][C]12.4622137169461[/C][C]-2.46221371694607[/C][/ROW]
[ROW][C]160[/C][C]14[/C][C]12.4946924935802[/C][C]1.5053075064198[/C][/ROW]
[ROW][C]161[/C][C]16[/C][C]13.0034970447469[/C][C]2.99650295525308[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]13.4822784760117[/C][C]-3.48227847601173[/C][/ROW]
[ROW][C]163[/C][C]11[/C][C]12.0299505749613[/C][C]-1.02995057496129[/C][/ROW]
[ROW][C]164[/C][C]14[/C][C]12.5218362987444[/C][C]1.47816370125555[/C][/ROW]
[ROW][C]165[/C][C]12[/C][C]12.9533763383042[/C][C]-0.953376338304166[/C][/ROW]
[ROW][C]166[/C][C]9[/C][C]13.2111518602078[/C][C]-4.21115186020783[/C][/ROW]
[ROW][C]167[/C][C]9[/C][C]12.5862423620129[/C][C]-3.5862423620129[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]12.6271580118513[/C][C]-1.62715801185133[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]13.6033682065113[/C][C]2.39663179348873[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]12.5553570228783[/C][C]-3.5553570228783[/C][/ROW]
[ROW][C]171[/C][C]13[/C][C]12.9014577391911[/C][C]0.0985422608088584[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]13.2599558930457[/C][C]2.74004410695435[/C][/ROW]
[ROW][C]173[/C][C]13[/C][C]12.631179406878[/C][C]0.36882059312202[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]13.3070430984116[/C][C]-4.30704309841164[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]12.3470911579295[/C][C]-0.347091157929468[/C][/ROW]
[ROW][C]176[/C][C]16[/C][C]13.3526011192877[/C][C]2.6473988807123[/C][/ROW]
[ROW][C]177[/C][C]11[/C][C]13.2482064915996[/C][C]-2.24820649159956[/C][/ROW]
[ROW][C]178[/C][C]14[/C][C]13.5879525581391[/C][C]0.412047441860879[/C][/ROW]
[ROW][C]179[/C][C]13[/C][C]12.4187455305318[/C][C]0.581254469468242[/C][/ROW]
[ROW][C]180[/C][C]15[/C][C]12.9285043290754[/C][C]2.07149567092463[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]12.7745390340907[/C][C]1.22546096590934[/C][/ROW]
[ROW][C]182[/C][C]16[/C][C]12.4213321772684[/C][C]3.5786678227316[/C][/ROW]
[ROW][C]183[/C][C]13[/C][C]13.4702689954665[/C][C]-0.470268995466497[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]12.9365761465602[/C][C]1.06342385343976[/C][/ROW]
[ROW][C]185[/C][C]15[/C][C]13.3723688978453[/C][C]1.62763110215472[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]12.2210349449984[/C][C]0.77896505500162[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]12.262643120889[/C][C]-1.26264312088903[/C][/ROW]
[ROW][C]188[/C][C]11[/C][C]13.2293427627133[/C][C]-2.22934276271334[/C][/ROW]
[ROW][C]189[/C][C]14[/C][C]13.5525426275571[/C][C]0.447457372442873[/C][/ROW]
[ROW][C]190[/C][C]15[/C][C]13.2449346869685[/C][C]1.75506531303154[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]13.5317305860075[/C][C]-2.53173058600749[/C][/ROW]
[ROW][C]192[/C][C]15[/C][C]13.2021671731956[/C][C]1.79783282680442[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]12.6336635230474[/C][C]-0.633663523047382[/C][/ROW]
[ROW][C]194[/C][C]14[/C][C]13.620674590524[/C][C]0.379325409475993[/C][/ROW]
[ROW][C]195[/C][C]14[/C][C]13.4450228416724[/C][C]0.554977158327615[/C][/ROW]
[ROW][C]196[/C][C]8[/C][C]12.5437767687764[/C][C]-4.54377676877644[/C][/ROW]
[ROW][C]197[/C][C]9[/C][C]12.65872667588[/C][C]-3.65872667588003[/C][/ROW]
[ROW][C]198[/C][C]15[/C][C]12.3237801886702[/C][C]2.67621981132977[/C][/ROW]
[ROW][C]199[/C][C]17[/C][C]12.2479099224574[/C][C]4.75209007754265[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]12.2749925266288[/C][C]0.725007473371196[/C][/ROW]
[ROW][C]201[/C][C]15[/C][C]13.4448978512578[/C][C]1.55510214874224[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.3719430524989[/C][C]1.62805694750108[/C][/ROW]
[ROW][C]203[/C][C]14[/C][C]13.4939331786361[/C][C]0.506066821363887[/C][/ROW]
[ROW][C]204[/C][C]16[/C][C]12.6865020489766[/C][C]3.31349795102335[/C][/ROW]
[ROW][C]205[/C][C]13[/C][C]12.2309724388488[/C][C]0.76902756115118[/C][/ROW]
[ROW][C]206[/C][C]16[/C][C]12.6272099594641[/C][C]3.37279004053589[/C][/ROW]
[ROW][C]207[/C][C]9[/C][C]13.03408409763[/C][C]-4.03408409762999[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.2729909943068[/C][C]3.72700900569318[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]12.4660575561384[/C][C]-1.46605755613835[/C][/ROW]
[ROW][C]210[/C][C]10[/C][C]12.5718911620502[/C][C]-2.57189116205021[/C][/ROW]
[ROW][C]211[/C][C]11[/C][C]13.4714584342906[/C][C]-2.47145843429059[/C][/ROW]
[ROW][C]212[/C][C]15[/C][C]12.4462798921201[/C][C]2.55372010787993[/C][/ROW]
[ROW][C]213[/C][C]17[/C][C]13.549921488513[/C][C]3.45007851148701[/C][/ROW]
[ROW][C]214[/C][C]14[/C][C]13.3979813936783[/C][C]0.60201860632168[/C][/ROW]
[ROW][C]215[/C][C]8[/C][C]12.4450696722297[/C][C]-4.44506967222974[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.3168748901531[/C][C]1.6831251098469[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]12.3465861096042[/C][C]-1.34658610960416[/C][/ROW]
[ROW][C]218[/C][C]16[/C][C]12.5399613170506[/C][C]3.46003868294939[/C][/ROW]
[ROW][C]219[/C][C]10[/C][C]13.321501406204[/C][C]-3.32150140620399[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]12.2049697267077[/C][C]2.7950302732923[/C][/ROW]
[ROW][C]221[/C][C]16[/C][C]12.588715675861[/C][C]3.411284324139[/C][/ROW]
[ROW][C]222[/C][C]19[/C][C]12.4007061847502[/C][C]6.5992938152498[/C][/ROW]
[ROW][C]223[/C][C]12[/C][C]12.4458001950345[/C][C]-0.445800195034469[/C][/ROW]
[ROW][C]224[/C][C]8[/C][C]12.1433005094542[/C][C]-4.14330050945424[/C][/ROW]
[ROW][C]225[/C][C]11[/C][C]12.2268745677014[/C][C]-1.22687456770141[/C][/ROW]
[ROW][C]226[/C][C]14[/C][C]13.2644718030662[/C][C]0.735528196933805[/C][/ROW]
[ROW][C]227[/C][C]9[/C][C]11.907975517511[/C][C]-2.90797551751096[/C][/ROW]
[ROW][C]228[/C][C]15[/C][C]12.6991687888099[/C][C]2.30083121119005[/C][/ROW]
[ROW][C]229[/C][C]13[/C][C]13.7724238408085[/C][C]-0.772423840808467[/C][/ROW]
[ROW][C]230[/C][C]16[/C][C]13.1334427046535[/C][C]2.86655729534649[/C][/ROW]
[ROW][C]231[/C][C]11[/C][C]12.1749428705236[/C][C]-1.1749428705236[/C][/ROW]
[ROW][C]232[/C][C]12[/C][C]11.5146537072227[/C][C]0.485346292777334[/C][/ROW]
[ROW][C]233[/C][C]13[/C][C]12.3992676701142[/C][C]0.600732329885759[/C][/ROW]
[ROW][C]234[/C][C]10[/C][C]13.2978410677191[/C][C]-3.29784106771914[/C][/ROW]
[ROW][C]235[/C][C]11[/C][C]12.1575950073477[/C][C]-1.15759500734772[/C][/ROW]
[ROW][C]236[/C][C]12[/C][C]12.0757798276887[/C][C]-0.0757798276886893[/C][/ROW]
[ROW][C]237[/C][C]8[/C][C]12.1682782469089[/C][C]-4.16827824690894[/C][/ROW]
[ROW][C]238[/C][C]12[/C][C]12.0372226715244[/C][C]-0.0372226715243585[/C][/ROW]
[ROW][C]239[/C][C]12[/C][C]12.4161385852209[/C][C]-0.416138585220851[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]12.0753507918964[/C][C]-1.07535079189637[/C][/ROW]
[ROW][C]241[/C][C]13[/C][C]12.3506880160874[/C][C]0.649311983912606[/C][/ROW]
[ROW][C]242[/C][C]14[/C][C]12.8319879363042[/C][C]1.16801206369585[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]12.7861909986973[/C][C]-2.7861909986973[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.823799656296[/C][C]-0.823799656295977[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]12.0340542313518[/C][C]2.96594576864822[/C][/ROW]
[ROW][C]246[/C][C]13[/C][C]11.9951479266767[/C][C]1.00485207332335[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]13.0849753765005[/C][C]-0.0849753765005133[/C][/ROW]
[ROW][C]248[/C][C]13[/C][C]13.4121701894628[/C][C]-0.412170189462815[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]12.230454262395[/C][C]-0.230454262394971[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]12.3528895221842[/C][C]-0.352889522184163[/C][/ROW]
[ROW][C]251[/C][C]9[/C][C]12.5255297962824[/C][C]-3.5255297962824[/C][/ROW]
[ROW][C]252[/C][C]9[/C][C]13.1465677062674[/C][C]-4.14656770626736[/C][/ROW]
[ROW][C]253[/C][C]15[/C][C]13.0884425546692[/C][C]1.91155744533083[/C][/ROW]
[ROW][C]254[/C][C]10[/C][C]12.2578874659308[/C][C]-2.25788746593084[/C][/ROW]
[ROW][C]255[/C][C]14[/C][C]13.1042133210782[/C][C]0.895786678921836[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]11.9084215261166[/C][C]3.09157847388341[/C][/ROW]
[ROW][C]257[/C][C]7[/C][C]12.1997449562704[/C][C]-5.19974495627039[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]12.2594879282462[/C][C]1.74051207175383[/C][/ROW]
[ROW][C]259[/C][C]8[/C][C]12.502991071864[/C][C]-4.50299107186398[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]13.184888009731[/C][C]-3.18488800973098[/C][/ROW]
[ROW][C]261[/C][C]13[/C][C]11.9519600956538[/C][C]1.04803990434617[/C][/ROW]
[ROW][C]262[/C][C]13[/C][C]12.1106497351459[/C][C]0.889350264854086[/C][/ROW]
[ROW][C]263[/C][C]13[/C][C]13.3307469760191[/C][C]-0.330746976019123[/C][/ROW]
[ROW][C]264[/C][C]8[/C][C]11.990245424318[/C][C]-3.99024542431799[/C][/ROW]
[ROW][C]265[/C][C]12[/C][C]12.2852381011928[/C][C]-0.285238101192754[/C][/ROW]
[ROW][C]266[/C][C]13[/C][C]13.0290604495415[/C][C]-0.0290604495414684[/C][/ROW]
[ROW][C]267[/C][C]12[/C][C]13.3927015824253[/C][C]-1.39270158242531[/C][/ROW]
[ROW][C]268[/C][C]10[/C][C]12.1883665800698[/C][C]-2.18836658006977[/C][/ROW]
[ROW][C]269[/C][C]13[/C][C]13.2758385581726[/C][C]-0.275838558172576[/C][/ROW]
[ROW][C]270[/C][C]12[/C][C]12.4456472950149[/C][C]-0.445647295014863[/C][/ROW]
[ROW][C]271[/C][C]9[/C][C]12.0255701301731[/C][C]-3.0255701301731[/C][/ROW]
[ROW][C]272[/C][C]15[/C][C]12.4314985488534[/C][C]2.56850145114659[/C][/ROW]
[ROW][C]273[/C][C]13[/C][C]12.4930705508269[/C][C]0.506929449173139[/C][/ROW]
[ROW][C]274[/C][C]13[/C][C]12.0032565811805[/C][C]0.996743418819528[/C][/ROW]
[ROW][C]275[/C][C]13[/C][C]12.5064264356154[/C][C]0.493573564384626[/C][/ROW]
[ROW][C]276[/C][C]15[/C][C]11.1595872218997[/C][C]3.84041277810029[/C][/ROW]
[ROW][C]277[/C][C]15[/C][C]12.16502044536[/C][C]2.83497955463998[/C][/ROW]
[ROW][C]278[/C][C]14[/C][C]12.4157002960485[/C][C]1.58429970395148[/C][/ROW]
[ROW][C]279[/C][C]15[/C][C]12.9940608985268[/C][C]2.00593910147317[/C][/ROW]
[ROW][C]280[/C][C]11[/C][C]12.0045663691196[/C][C]-1.00456636911961[/C][/ROW]
[ROW][C]281[/C][C]15[/C][C]12.5850817029931[/C][C]2.41491829700685[/C][/ROW]
[ROW][C]282[/C][C]14[/C][C]13.1560340309235[/C][C]0.84396596907648[/C][/ROW]
[ROW][C]283[/C][C]13[/C][C]11.9433959165426[/C][C]1.05660408345742[/C][/ROW]
[ROW][C]284[/C][C]12[/C][C]11.9384171025973[/C][C]0.0615828974027059[/C][/ROW]
[ROW][C]285[/C][C]16[/C][C]12.5404083912609[/C][C]3.45959160873908[/C][/ROW]
[ROW][C]286[/C][C]16[/C][C]11.8475953481927[/C][C]4.15240465180725[/C][/ROW]
[ROW][C]287[/C][C]9[/C][C]13.1842036857278[/C][C]-4.18420368572781[/C][/ROW]
[ROW][C]288[/C][C]14[/C][C]12.9021942679538[/C][C]1.09780573204624[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184814&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184814&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
11414.4752006823728-0.475200682372824
21814.85958527649623.14041472350379
31114.8334861456899-3.83348614568988
41213.8455293286639-1.84552932866393
51614.38659569803351.61340430196654
61814.46922403679513.53077596320493
71415.1713934463598-1.17139344635978
81414.4795261227772-0.479526122777177
91514.47396998510040.526030014899593
101514.63951915815690.360480841843058
111714.04775478867692.95224521132307
121914.7026303534294.29736964657097
131013.9434430180015-3.94344301800145
141614.74419342618661.25580657381343
151814.62109759319163.37890240680842
161413.6943678595620.305632140438007
171413.852367699860.147632300139957
181715.13332396861531.86667603138472
191414.1595493536727-0.159549353672725
201614.60136225322631.39863774677368
211813.81434888340884.18565111659117
221114.5825114317538-3.58251143175383
231415.0073287660259-1.00732876602594
241214.6487958580868-2.64879585808677
251714.08251514934042.9174848506596
26914.9012638655736-5.90126386557355
271613.89466129542232.10533870457769
281414.3781143759349-0.378114375934873
291514.58556545127510.414434548724951
301113.6349321234099-2.63493212340986
311614.44157471971781.55842528028224
321313.2842845986752-0.284284598675187
331714.52187103387152.47812896612845
341514.54357056364510.456429436354897
351413.61169785098620.388302149013814
361613.18413533345882.81586466654118
37913.0841168074683-4.08411680746832
381513.61441859914151.38558140085851
391714.52428035733182.47571964266816
401313.8540952576824-0.854095257682441
411513.91484520235851.08515479764152
421614.34492460767461.65507539232539
431614.26867748584021.73132251415977
441213.6163188088769-1.6163188088769
451514.54835450870290.451645491297053
461114.0451456702497-3.04514567024968
471514.33037460085550.669625399144542
481514.42333977968380.576660220316178
491714.55750000581922.44249999418085
501313.6405209203938-0.640520920393767
511614.37984193375731.62015806624273
521413.55346677656420.4465332234358
531113.2400598839776-2.24005988397763
541214.4445011904591-2.44450119045907
551213.0709157632577-1.07091576325772
561514.49026152276040.509738477239627
571614.63734105798731.3626589420127
581514.37935466670330.620645333296697
591213.670689519091-1.670689519091
601214.5722396373646-2.57223963736464
61813.3442627620982-5.34426276209816
621313.8020360117247-0.802036011724726
631114.4318090693223-3.43180906932231
641414.1964548513908-0.196454851390794
651514.52352170420730.476478295792673
661013.7636360416944-3.7636360416944
671114.6953545680142-3.69535456801422
681213.918113472357-1.91811347235704
691514.07159458164750.928405418352519
701513.66158953647381.33841046352624
711413.16485635114760.835143648852354
721614.13245935834071.86754064165925
731514.57375891423570.426241085764259
741513.85260649311911.14739350688094
751313.7496810275658-0.749681027565834
761214.8112373093478-2.81123730934778
771714.46143954902122.53856045097877
781314.5057157999657-1.50571579996571
791513.19468432922541.8053156707746
801313.8103830900287-0.810383090028677
811513.58890699873911.41109300126089
821514.41786459489330.582135405106748
831613.610750638742.38924936125998
841514.28446389683610.715536103163933
851414.4813249386761-0.481324938676136
861513.50602570941711.49397429058289
871414.389945575157-0.389945575157039
881314.3107259625876-1.31072596258763
89714.2839897579106-7.28398975791064
901713.92273332273613.07726667726391
911314.5228270311557-1.52282703115569
921514.33463712679160.665362873208403
931414.3105689971684-0.310568997168439
941313.9799261036921-0.979926103692066
951614.53806702781991.46193297218007
961214.4274584683293-2.42745846832932
971414.5176361398494-0.517636139849407
981713.6631601288773.33683987112303
991513.32783248808811.67216751191194
1001714.40426929903882.59573070096125
1011213.6639196569551-1.66391965695512
1021614.76128334147271.23871665852732
1031113.5081399789788-2.5081399789788
1041514.29487849934310.705121500656929
105913.4056614682347-4.40566146823471
1061614.55717423317171.44282576682828
1071513.67208468050111.3279153194989
1081013.6163875085882-3.61638750858818
1091014.1373794877515-4.13737948775154
1101514.2410495621610.758950437839006
1111114.2300332719487-3.23003327194866
1121314.3309204092233-1.33092040922331
1131814.00591378357823.99408621642182
1141613.84066442596562.15933557403438
1151413.97583858159310.0241614184068868
1161414.113878893766-0.113878893765973
1171413.9678949671270.0321050328730349
1181414.3938557621364-0.393855762136428
1191213.1416581191281-1.14165811912812
1201414.3024209464358-0.302420946435768
1211514.00784321930180.992156780698181
1221514.28362557714480.716374422855158
1231514.25607161312810.743928386871941
1241314.1659447935523-1.16594479355231
1251713.58864201571863.41135798428139
1261714.61849217707312.38150782292688
1271914.19492460766434.80507539233573
1281513.89749082297571.1025091770243
1291313.4973135041438-0.497313504143849
130912.7064882582954-3.70648825829543
1311514.48350863343780.516491366562192
1321512.92574715699442.07425284300559
1331513.27601074906991.72398925093013
1341614.16849544815991.83150455184013
1351113.2041119537985-2.2041119537985
1361413.36463758008020.635362419919843
1371113.626412280036-2.62641228003604
1381513.92248443757531.07751556242472
1391312.8746651941610.125334805839042
1401514.29008851350930.709911486490692
1411613.26737177724952.73262822275049
1421414.1704888639564-0.1704888639564
1431513.533915652631.46608434736998
1441613.84462394601182.15537605398817
1451614.47433732149411.52566267850586
1461113.1228560548225-2.12285605482246
1471213.4201996332448-1.42019963324481
148913.2122263160512-4.2122263160512
1491613.69758973463282.30241026536718
1501314.246334968006-1.24633496800603
1511613.43746483005912.56253516994091
1521214.3103626267117-2.31036262671169
153914.1768659735771-5.17686597357706
1541313.6347404814002-0.634740481400216
1551413.91256113745810.0874388625419389
1561914.10358087318344.89641912681655
1571314.2439504609478-1.2439504609478
1581213.7313081477966-1.73130814779656
1591012.4622137169461-2.46221371694607
1601412.49469249358021.5053075064198
1611613.00349704474692.99650295525308
1621013.4822784760117-3.48227847601173
1631112.0299505749613-1.02995057496129
1641412.52183629874441.47816370125555
1651212.9533763383042-0.953376338304166
166913.2111518602078-4.21115186020783
167912.5862423620129-3.5862423620129
1681112.6271580118513-1.62715801185133
1691613.60336820651132.39663179348873
170912.5553570228783-3.5553570228783
1711312.90145773919110.0985422608088584
1721613.25995589304572.74004410695435
1731312.6311794068780.36882059312202
174913.3070430984116-4.30704309841164
1751212.3470911579295-0.347091157929468
1761613.35260111928772.6473988807123
1771113.2482064915996-2.24820649159956
1781413.58795255813910.412047441860879
1791312.41874553053180.581254469468242
1801512.92850432907542.07149567092463
1811412.77453903409071.22546096590934
1821612.42133217726843.5786678227316
1831313.4702689954665-0.470268995466497
1841412.93657614656021.06342385343976
1851513.37236889784531.62763110215472
1861312.22103494499840.77896505500162
1871112.262643120889-1.26264312088903
1881113.2293427627133-2.22934276271334
1891413.55254262755710.447457372442873
1901513.24493468696851.75506531303154
1911113.5317305860075-2.53173058600749
1921513.20216717319561.79783282680442
1931212.6336635230474-0.633663523047382
1941413.6206745905240.379325409475993
1951413.44502284167240.554977158327615
196812.5437767687764-4.54377676877644
197912.65872667588-3.65872667588003
1981512.32378018867022.67621981132977
1991712.24790992245744.75209007754265
2001312.27499252662880.725007473371196
2011513.44489785125781.55510214874224
2021513.37194305249891.62805694750108
2031413.49393317863610.506066821363887
2041612.68650204897663.31349795102335
2051312.23097243884880.76902756115118
2061612.62720995946413.37279004053589
207913.03408409763-4.03408409762999
2081612.27299099430683.72700900569318
2091112.4660575561384-1.46605755613835
2101012.5718911620502-2.57189116205021
2111113.4714584342906-2.47145843429059
2121512.44627989212012.55372010787993
2131713.5499214885133.45007851148701
2141413.39798139367830.60201860632168
215812.4450696722297-4.44506967222974
2161513.31687489015311.6831251098469
2171112.3465861096042-1.34658610960416
2181612.53996131705063.46003868294939
2191013.321501406204-3.32150140620399
2201512.20496972670772.7950302732923
2211612.5887156758613.411284324139
2221912.40070618475026.5992938152498
2231212.4458001950345-0.445800195034469
224812.1433005094542-4.14330050945424
2251112.2268745677014-1.22687456770141
2261413.26447180306620.735528196933805
227911.907975517511-2.90797551751096
2281512.69916878880992.30083121119005
2291313.7724238408085-0.772423840808467
2301613.13344270465352.86655729534649
2311112.1749428705236-1.1749428705236
2321211.51465370722270.485346292777334
2331312.39926767011420.600732329885759
2341013.2978410677191-3.29784106771914
2351112.1575950073477-1.15759500734772
2361212.0757798276887-0.0757798276886893
237812.1682782469089-4.16827824690894
2381212.0372226715244-0.0372226715243585
2391212.4161385852209-0.416138585220851
2401112.0753507918964-1.07535079189637
2411312.35068801608740.649311983912606
2421412.83198793630421.16801206369585
2431012.7861909986973-2.7861909986973
2441212.823799656296-0.823799656295977
2451512.03405423135182.96594576864822
2461311.99514792667671.00485207332335
2471313.0849753765005-0.0849753765005133
2481313.4121701894628-0.412170189462815
2491212.230454262395-0.230454262394971
2501212.3528895221842-0.352889522184163
251912.5255297962824-3.5255297962824
252913.1465677062674-4.14656770626736
2531513.08844255466921.91155744533083
2541012.2578874659308-2.25788746593084
2551413.10421332107820.895786678921836
2561511.90842152611663.09157847388341
257712.1997449562704-5.19974495627039
2581412.25948792824621.74051207175383
259812.502991071864-4.50299107186398
2601013.184888009731-3.18488800973098
2611311.95196009565381.04803990434617
2621312.11064973514590.889350264854086
2631313.3307469760191-0.330746976019123
264811.990245424318-3.99024542431799
2651212.2852381011928-0.285238101192754
2661313.0290604495415-0.0290604495414684
2671213.3927015824253-1.39270158242531
2681012.1883665800698-2.18836658006977
2691313.2758385581726-0.275838558172576
2701212.4456472950149-0.445647295014863
271912.0255701301731-3.0255701301731
2721512.43149854885342.56850145114659
2731312.49307055082690.506929449173139
2741312.00325658118050.996743418819528
2751312.50642643561540.493573564384626
2761511.15958722189973.84041277810029
2771512.165020445362.83497955463998
2781412.41570029604851.58429970395148
2791512.99406089852682.00593910147317
2801112.0045663691196-1.00456636911961
2811512.58508170299312.41491829700685
2821413.15603403092350.84396596907648
2831311.94339591654261.05660408345742
2841211.93841710259730.0615828974027059
2851612.54040839126093.45959160873908
2861611.84759534819274.15240465180725
287913.1842036857278-4.18420368572781
2881412.90219426795381.09780573204624






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.554617678474080.890764643051840.44538232152592
120.589648098029570.820703803940860.41035190197043
130.713662398615420.5726752027691610.28633760138458
140.6030344954053210.7939310091893580.396965504594679
150.657523487917170.684953024165660.34247651208283
160.5597334500664130.8805330998671730.440266549933587
170.4946761105024010.9893522210048020.505323889497599
180.423241798323260.846483596646520.57675820167674
190.3567543378809530.7135086757619050.643245662119047
200.3967051084849840.7934102169699680.603294891515016
210.4675781812607780.9351563625215560.532421818739222
220.8581369837810260.2837260324379490.141863016218974
230.8402214077700820.3195571844598370.159778592229918
240.8677912254381610.2644175491236780.132208774561839
250.8422565788332440.3154868423335120.157743421166756
260.9750780737648710.04984385247025760.0249219262351288
270.9697746929139020.06045061417219590.030225307086098
280.9575166711538050.08496665769239090.0424833288461954
290.9422879012407380.1154241975185250.0577120987592624
300.9489469108098010.1021061783803970.0510530891901985
310.9386802494613680.1226395010772640.061319750538632
320.9209292483717490.1581415032565020.0790707516282512
330.9127495843546730.1745008312906530.0872504156453266
340.8902380759905290.2195238480189430.109761924009471
350.8619058266698770.2761883466602460.138094173330123
360.8454027356608650.3091945286782710.154597264339135
370.9114494301942660.1771011396114670.0885505698057336
380.8963861262427290.2072277475145430.103613873757271
390.8914904568275520.2170190863448970.108509543172448
400.8691215182549020.2617569634901960.130878481745098
410.8437485248224370.3125029503551260.156251475177563
420.8206653159012880.3586693681974250.179334684098712
430.8047610077498510.3904779845002980.195238992250149
440.7897705356626160.4204589286747670.210229464337384
450.7578655716711040.4842688566577920.242134428328896
460.7695982752096160.4608034495807690.230401724790384
470.7427659341868630.5144681316262730.257234065813137
480.7042979373717850.5914041252564290.295702062628215
490.7017413345703180.5965173308593640.298258665429682
500.6616007905650580.6767984188698830.338399209434942
510.6390573816813540.7218852366372920.360942618318646
520.5954998518561270.8090002962877460.404500148143873
530.5755527440212420.8488945119575150.424447255978758
540.5752846786861010.8494306426277970.424715321313898
550.538467497996520.9230650040069590.46153250200348
560.495190168331910.9903803366638210.50480983166809
570.4614029709767160.9228059419534320.538597029023284
580.4191974548052040.8383949096104080.580802545194796
590.3884120054052990.7768240108105980.611587994594701
600.4070388885993020.8140777771986040.592961111400698
610.5550525217932320.8898949564135360.444947478206768
620.5127664910562680.9744670178874630.487233508943732
630.5331162906217980.9337674187564040.466883709378202
640.4929436158687780.9858872317375560.507056384131222
650.4554883378914610.9109766757829230.544511662108539
660.4715726381587480.9431452763174960.528427361841252
670.4972019619298810.9944039238597620.502798038070119
680.4664569844631480.9329139689262960.533543015536852
690.4519483715006360.9038967430012720.548051628499364
700.4579988159513060.9159976319026120.542001184048694
710.433315793978250.86663158795650.56668420602175
720.4381831961368370.8763663922736730.561816803863163
730.4063662050494350.812732410098870.593633794950565
740.3897733357082910.7795466714165830.610226664291709
750.353914492928010.7078289858560210.64608550707199
760.3564769832073720.7129539664147440.643523016792628
770.3766303774591890.7532607549183780.623369622540811
780.3455211478494460.6910422956988910.654478852150554
790.3562983424078340.7125966848156670.643701657592166
800.3222913032348130.6445826064696270.677708696765187
810.309302658490220.618605316980440.69069734150978
820.2798294258904230.5596588517808460.720170574109577
830.2932193094855460.5864386189710910.706780690514454
840.2668029934509990.5336059869019980.733197006549001
850.2362357468543430.4724714937086860.763764253145657
860.2187343736191450.4374687472382890.781265626380856
870.1915246320785890.3830492641571780.808475367921411
880.169825458413390.3396509168267790.83017454158661
890.3967957731136130.7935915462272270.603204226886387
900.4334744766552490.8669489533104980.566525523344751
910.4032920101940960.8065840203881920.596707989805904
920.3701291139003360.7402582278006720.629870886099664
930.3396962406643230.6793924813286450.660303759335677
940.3083547633550240.6167095267100470.691645236644976
950.2899301819734620.5798603639469240.710069818026538
960.2836435638558660.5672871277117320.716356436144134
970.2539411375655140.5078822751310270.746058862434486
980.2958278157427430.5916556314854860.704172184257257
990.281297089371210.562594178742420.71870291062879
1000.2922216544640960.5844433089281910.707778345535904
1010.2759957735267740.5519915470535480.724004226473226
1020.2561909245398320.5123818490796640.743809075460168
1030.2476379253334610.4952758506669220.752362074666539
1040.2218692040500160.4437384081000330.778130795949984
1050.27825209586760.55650419173520.7217479041324
1060.2619090469621540.5238180939243080.738090953037846
1070.2400890419962950.4801780839925890.759910958003705
1080.2747972520027270.5495945040054540.725202747997273
1090.3500429978561750.700085995712350.649957002143825
1100.3243448843101050.648689768620210.675655115689895
1110.3391458486614840.6782916973229670.660854151338516
1120.3179735006329250.6359470012658490.682026499367075
1130.3994249959148570.7988499918297150.600575004085143
1140.4040059663279740.8080119326559480.595994033672026
1150.3703048246421030.7406096492842050.629695175357897
1160.3375887789225580.6751775578451150.662411221077442
1170.3070063681590270.6140127363180550.692993631840973
1180.2773640017329490.5547280034658980.722635998267051
1190.2535070671763120.5070141343526240.746492932823688
1200.2294937923720060.4589875847440110.770506207627994
1210.2089539407059060.4179078814118110.791046059294094
1220.1873321560568460.3746643121136920.812667843943154
1230.1697978412306660.3395956824613320.830202158769334
1240.1522552802878350.304510560575670.847744719712165
1250.1801700590256540.3603401180513080.819829940974346
1260.1767314630702760.3534629261405530.823268536929724
1270.2574375104608680.5148750209217360.742562489539132
1280.2379309610143590.4758619220287180.762069038985641
1290.2125433776156530.4250867552313060.787456622384347
1300.237952698599830.4759053971996610.76204730140017
1310.2139060304601670.4278120609203350.786093969539833
1320.2181752062613110.4363504125226220.781824793738689
1330.2061960672933380.4123921345866760.793803932706662
1340.2006868555363590.4013737110727190.799313144463641
1350.1932641703914140.3865283407828270.806735829608586
1360.1722099339512920.3444198679025840.827790066048708
1370.1738717294306980.3477434588613960.826128270569302
1380.1572793080719080.3145586161438170.842720691928092
1390.1377256888170960.2754513776341910.862274311182904
1400.1214029986901920.2428059973803830.878597001309808
1410.1273654642452070.2547309284904130.872634535754793
1420.1102736290486270.2205472580972530.889726370951373
1430.1036250575344990.2072501150689980.896374942465501
1440.1026955538908030.2053911077816060.897304446109197
1450.09631924672752910.1926384934550580.903680753272471
1460.09153483319716030.1830696663943210.90846516680284
1470.0816032598292840.1632065196585680.918396740170716
1480.1122309118017520.2244618236035030.887769088198248
1490.111809417701820.223618835403640.88819058229818
1500.1008109148408360.2016218296816720.899189085159164
1510.1035941672547330.2071883345094660.896405832745267
1520.1058879380236130.2117758760472260.894112061976387
1530.1761075696519510.3522151393039020.823892430348049
1540.1580261403467810.3160522806935610.841973859653219
1550.1382146697423080.2764293394846160.861785330257692
1560.2142426591456460.4284853182912930.785757340854354
1570.1928379278611050.385675855722210.807162072138895
1580.1768583068935650.353716613787130.823141693106435
1590.1725719781070550.345143956214110.827428021892945
1600.1664226291615320.3328452583230640.833577370838468
1610.170434303872130.340868607744260.82956569612787
1620.1991590269716050.398318053943210.800840973028395
1630.1798858831270120.3597717662540240.820114116872988
1640.1669063897006920.3338127794013840.833093610299308
1650.1508576247861910.3017152495723820.849142375213809
1660.1924302795777110.3848605591554220.807569720422289
1670.2210996938832380.4421993877664770.778900306116762
1680.2023518644387150.404703728877430.797648135561285
1690.2088295881361680.4176591762723360.791170411863832
1700.2339340331586460.4678680663172910.766065966841354
1710.2130135206870130.4260270413740260.786986479312987
1720.2257442047911740.4514884095823480.774255795208826
1730.2020142467797090.4040284935594180.797985753220291
1740.2529634655384410.5059269310768810.747036534461559
1750.2297398566968760.4594797133937520.770260143303124
1760.2388234599253110.4776469198506220.761176540074689
1770.2331886949877590.4663773899755180.766811305012241
1780.2083730619617360.4167461239234720.791626938038264
1790.1867159895095410.3734319790190820.813284010490459
1800.1801364315831080.3602728631662160.819863568416892
1810.1631500701952170.3263001403904330.836849929804783
1820.1894347404259250.3788694808518490.810565259574075
1830.166822633879830.3336452677596610.83317736612017
1840.1495165271396190.2990330542792380.850483472860381
1850.1391947894518520.2783895789037040.860805210548148
1860.1222470742802560.2444941485605120.877752925719744
1870.1102743161800940.2205486323601880.889725683819906
1880.1074753057084660.2149506114169330.892524694291534
1890.09251915379114650.1850383075822930.907480846208853
1900.08637877541000940.1727575508200190.913621224589991
1910.08639395620202240.1727879124040450.913606043797978
1920.08016792531309140.1603358506261830.919832074686909
1930.0684103610671850.136820722134370.931589638932815
1940.05784988859058220.1156997771811640.942150111409418
1950.04864939918759630.09729879837519250.951350600812404
1960.07696292127352710.1539258425470540.923037078726473
1970.09989446473249640.1997889294649930.900105535267504
1980.09921589934270430.1984317986854090.900784100657296
1990.146240216310860.2924804326217190.85375978368914
2000.1272201978376220.2544403956752450.872779802162378
2010.1177663237729810.2355326475459610.882233676227019
2020.1096454067229720.2192908134459450.890354593277028
2030.09495248890291670.1899049778058330.905047511097083
2040.1097030618567550.219406123713510.890296938143245
2050.09457285065934440.1891457013186890.905427149340656
2060.1131916482878520.2263832965757040.886808351712148
2070.14263124640410.2852624928081990.8573687535959
2080.1799544148328360.3599088296656730.820045585167164
2090.1613473049039930.3226946098079860.838652695096007
2100.1607503789269750.321500757853950.839249621073025
2110.1557253441481320.3114506882962650.844274655851868
2120.1565647648543470.3131295297086930.843435235145653
2130.196866321603830.3937326432076590.80313367839617
2140.1781927970716390.3563855941432790.821807202928361
2150.231209763746470.4624195274929410.768790236253529
2160.2323356728773240.4646713457546480.767664327122676
2170.208736040900230.417472081800460.79126395909977
2180.2572187649090220.5144375298180430.742781235090978
2190.2641850456279190.5283700912558390.735814954372081
2200.2834174165129440.5668348330258870.716582583487056
2210.3650769549835390.7301539099670780.634923045016461
2220.7106051229889060.5787897540221880.289394877011094
2230.678995878943490.6420082421130210.32100412105651
2240.7176952883398090.5646094233203810.282304711660191
2250.6824574277508040.6350851444983920.317542572249196
2260.6669279304239440.6661441391521120.333072069576056
2270.6566179202976120.6867641594047760.343382079702388
2280.7224214863326820.5551570273346350.277578513667318
2290.6909491355089790.6181017289820420.309050864491021
2300.7840611746232820.4318776507534370.215938825376718
2310.7517643371704960.4964713256590070.248235662829504
2320.7158069234579660.5683861530840680.284193076542034
2330.6848691427978380.6302617144043230.315130857202162
2340.6685660433641080.6628679132717840.331433956635892
2350.6277221923598740.7445556152802520.372277807640126
2360.5887253942791060.8225492114417890.411274605720894
2370.6533314628283370.6933370743433270.346668537171663
2380.6170308668571240.7659382662857520.382969133142876
2390.5813134177977120.8373731644045750.418686582202288
2400.5346454797434250.930709040513150.465354520256575
2410.5136416258771530.9727167482456930.486358374122847
2420.4975319954926370.9950639909852750.502468004507363
2430.4895616271568160.9791232543136310.510438372843184
2440.4450054814848730.8900109629697460.554994518515127
2450.5406848609948150.9186302780103710.459315139005185
2460.5287521162967960.9424957674064090.471247883703204
2470.5339827444260140.9320345111479720.466017255573986
2480.524912955338560.950174089322880.47508704466144
2490.4764159234730510.9528318469461030.523584076526949
2500.427967894712360.855935789424720.57203210528764
2510.4212641429402720.8425282858805440.578735857059728
2520.416908777381090.833817554762180.58309122261891
2530.4618859503195650.9237719006391290.538114049680435
2540.4103520629571220.8207041259142440.589647937042878
2550.4008257166971440.8016514333942880.599174283302856
2560.6264657320067020.7470685359865950.373534267993298
2570.7013507838387780.5972984323224440.298649216161222
2580.7656235029085990.4687529941828020.234376497091401
2590.8124319041596020.3751361916807960.187568095840398
2600.7950989662858120.4098020674283760.204901033714188
2610.8502737559822280.2994524880355440.149726244017772
2620.8169165515812240.3661668968375530.183083448418776
2630.7687573325748910.4624853348502180.231242667425109
2640.8643442237971210.2713115524057580.135655776202879
2650.8166032570396580.3667934859206840.183396742960342
2660.7634508188907140.4730983622185730.236549181109286
2670.7414727966522730.5170544066954550.258527203347727
2680.7011744657406240.5976510685187520.298825534259376
2690.6315996495406710.7368007009186580.368400350459329
2700.5654078868125120.8691842263749760.434592113187488
2710.588660363241430.822679273517140.41133963675857
2720.4954121395082270.9908242790164540.504587860491773
2730.3996087595248350.799217519049670.600391240475165
2740.3158040567155550.631608113431110.684195943284445
2750.2435705863863810.4871411727727620.756429413613619
2760.1665166390257960.3330332780515920.833483360974204
2770.1063360412607590.2126720825215180.893663958739241

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.55461767847408 & 0.89076464305184 & 0.44538232152592 \tabularnewline
12 & 0.58964809802957 & 0.82070380394086 & 0.41035190197043 \tabularnewline
13 & 0.71366239861542 & 0.572675202769161 & 0.28633760138458 \tabularnewline
14 & 0.603034495405321 & 0.793931009189358 & 0.396965504594679 \tabularnewline
15 & 0.65752348791717 & 0.68495302416566 & 0.34247651208283 \tabularnewline
16 & 0.559733450066413 & 0.880533099867173 & 0.440266549933587 \tabularnewline
17 & 0.494676110502401 & 0.989352221004802 & 0.505323889497599 \tabularnewline
18 & 0.42324179832326 & 0.84648359664652 & 0.57675820167674 \tabularnewline
19 & 0.356754337880953 & 0.713508675761905 & 0.643245662119047 \tabularnewline
20 & 0.396705108484984 & 0.793410216969968 & 0.603294891515016 \tabularnewline
21 & 0.467578181260778 & 0.935156362521556 & 0.532421818739222 \tabularnewline
22 & 0.858136983781026 & 0.283726032437949 & 0.141863016218974 \tabularnewline
23 & 0.840221407770082 & 0.319557184459837 & 0.159778592229918 \tabularnewline
24 & 0.867791225438161 & 0.264417549123678 & 0.132208774561839 \tabularnewline
25 & 0.842256578833244 & 0.315486842333512 & 0.157743421166756 \tabularnewline
26 & 0.975078073764871 & 0.0498438524702576 & 0.0249219262351288 \tabularnewline
27 & 0.969774692913902 & 0.0604506141721959 & 0.030225307086098 \tabularnewline
28 & 0.957516671153805 & 0.0849666576923909 & 0.0424833288461954 \tabularnewline
29 & 0.942287901240738 & 0.115424197518525 & 0.0577120987592624 \tabularnewline
30 & 0.948946910809801 & 0.102106178380397 & 0.0510530891901985 \tabularnewline
31 & 0.938680249461368 & 0.122639501077264 & 0.061319750538632 \tabularnewline
32 & 0.920929248371749 & 0.158141503256502 & 0.0790707516282512 \tabularnewline
33 & 0.912749584354673 & 0.174500831290653 & 0.0872504156453266 \tabularnewline
34 & 0.890238075990529 & 0.219523848018943 & 0.109761924009471 \tabularnewline
35 & 0.861905826669877 & 0.276188346660246 & 0.138094173330123 \tabularnewline
36 & 0.845402735660865 & 0.309194528678271 & 0.154597264339135 \tabularnewline
37 & 0.911449430194266 & 0.177101139611467 & 0.0885505698057336 \tabularnewline
38 & 0.896386126242729 & 0.207227747514543 & 0.103613873757271 \tabularnewline
39 & 0.891490456827552 & 0.217019086344897 & 0.108509543172448 \tabularnewline
40 & 0.869121518254902 & 0.261756963490196 & 0.130878481745098 \tabularnewline
41 & 0.843748524822437 & 0.312502950355126 & 0.156251475177563 \tabularnewline
42 & 0.820665315901288 & 0.358669368197425 & 0.179334684098712 \tabularnewline
43 & 0.804761007749851 & 0.390477984500298 & 0.195238992250149 \tabularnewline
44 & 0.789770535662616 & 0.420458928674767 & 0.210229464337384 \tabularnewline
45 & 0.757865571671104 & 0.484268856657792 & 0.242134428328896 \tabularnewline
46 & 0.769598275209616 & 0.460803449580769 & 0.230401724790384 \tabularnewline
47 & 0.742765934186863 & 0.514468131626273 & 0.257234065813137 \tabularnewline
48 & 0.704297937371785 & 0.591404125256429 & 0.295702062628215 \tabularnewline
49 & 0.701741334570318 & 0.596517330859364 & 0.298258665429682 \tabularnewline
50 & 0.661600790565058 & 0.676798418869883 & 0.338399209434942 \tabularnewline
51 & 0.639057381681354 & 0.721885236637292 & 0.360942618318646 \tabularnewline
52 & 0.595499851856127 & 0.809000296287746 & 0.404500148143873 \tabularnewline
53 & 0.575552744021242 & 0.848894511957515 & 0.424447255978758 \tabularnewline
54 & 0.575284678686101 & 0.849430642627797 & 0.424715321313898 \tabularnewline
55 & 0.53846749799652 & 0.923065004006959 & 0.46153250200348 \tabularnewline
56 & 0.49519016833191 & 0.990380336663821 & 0.50480983166809 \tabularnewline
57 & 0.461402970976716 & 0.922805941953432 & 0.538597029023284 \tabularnewline
58 & 0.419197454805204 & 0.838394909610408 & 0.580802545194796 \tabularnewline
59 & 0.388412005405299 & 0.776824010810598 & 0.611587994594701 \tabularnewline
60 & 0.407038888599302 & 0.814077777198604 & 0.592961111400698 \tabularnewline
61 & 0.555052521793232 & 0.889894956413536 & 0.444947478206768 \tabularnewline
62 & 0.512766491056268 & 0.974467017887463 & 0.487233508943732 \tabularnewline
63 & 0.533116290621798 & 0.933767418756404 & 0.466883709378202 \tabularnewline
64 & 0.492943615868778 & 0.985887231737556 & 0.507056384131222 \tabularnewline
65 & 0.455488337891461 & 0.910976675782923 & 0.544511662108539 \tabularnewline
66 & 0.471572638158748 & 0.943145276317496 & 0.528427361841252 \tabularnewline
67 & 0.497201961929881 & 0.994403923859762 & 0.502798038070119 \tabularnewline
68 & 0.466456984463148 & 0.932913968926296 & 0.533543015536852 \tabularnewline
69 & 0.451948371500636 & 0.903896743001272 & 0.548051628499364 \tabularnewline
70 & 0.457998815951306 & 0.915997631902612 & 0.542001184048694 \tabularnewline
71 & 0.43331579397825 & 0.8666315879565 & 0.56668420602175 \tabularnewline
72 & 0.438183196136837 & 0.876366392273673 & 0.561816803863163 \tabularnewline
73 & 0.406366205049435 & 0.81273241009887 & 0.593633794950565 \tabularnewline
74 & 0.389773335708291 & 0.779546671416583 & 0.610226664291709 \tabularnewline
75 & 0.35391449292801 & 0.707828985856021 & 0.64608550707199 \tabularnewline
76 & 0.356476983207372 & 0.712953966414744 & 0.643523016792628 \tabularnewline
77 & 0.376630377459189 & 0.753260754918378 & 0.623369622540811 \tabularnewline
78 & 0.345521147849446 & 0.691042295698891 & 0.654478852150554 \tabularnewline
79 & 0.356298342407834 & 0.712596684815667 & 0.643701657592166 \tabularnewline
80 & 0.322291303234813 & 0.644582606469627 & 0.677708696765187 \tabularnewline
81 & 0.30930265849022 & 0.61860531698044 & 0.69069734150978 \tabularnewline
82 & 0.279829425890423 & 0.559658851780846 & 0.720170574109577 \tabularnewline
83 & 0.293219309485546 & 0.586438618971091 & 0.706780690514454 \tabularnewline
84 & 0.266802993450999 & 0.533605986901998 & 0.733197006549001 \tabularnewline
85 & 0.236235746854343 & 0.472471493708686 & 0.763764253145657 \tabularnewline
86 & 0.218734373619145 & 0.437468747238289 & 0.781265626380856 \tabularnewline
87 & 0.191524632078589 & 0.383049264157178 & 0.808475367921411 \tabularnewline
88 & 0.16982545841339 & 0.339650916826779 & 0.83017454158661 \tabularnewline
89 & 0.396795773113613 & 0.793591546227227 & 0.603204226886387 \tabularnewline
90 & 0.433474476655249 & 0.866948953310498 & 0.566525523344751 \tabularnewline
91 & 0.403292010194096 & 0.806584020388192 & 0.596707989805904 \tabularnewline
92 & 0.370129113900336 & 0.740258227800672 & 0.629870886099664 \tabularnewline
93 & 0.339696240664323 & 0.679392481328645 & 0.660303759335677 \tabularnewline
94 & 0.308354763355024 & 0.616709526710047 & 0.691645236644976 \tabularnewline
95 & 0.289930181973462 & 0.579860363946924 & 0.710069818026538 \tabularnewline
96 & 0.283643563855866 & 0.567287127711732 & 0.716356436144134 \tabularnewline
97 & 0.253941137565514 & 0.507882275131027 & 0.746058862434486 \tabularnewline
98 & 0.295827815742743 & 0.591655631485486 & 0.704172184257257 \tabularnewline
99 & 0.28129708937121 & 0.56259417874242 & 0.71870291062879 \tabularnewline
100 & 0.292221654464096 & 0.584443308928191 & 0.707778345535904 \tabularnewline
101 & 0.275995773526774 & 0.551991547053548 & 0.724004226473226 \tabularnewline
102 & 0.256190924539832 & 0.512381849079664 & 0.743809075460168 \tabularnewline
103 & 0.247637925333461 & 0.495275850666922 & 0.752362074666539 \tabularnewline
104 & 0.221869204050016 & 0.443738408100033 & 0.778130795949984 \tabularnewline
105 & 0.2782520958676 & 0.5565041917352 & 0.7217479041324 \tabularnewline
106 & 0.261909046962154 & 0.523818093924308 & 0.738090953037846 \tabularnewline
107 & 0.240089041996295 & 0.480178083992589 & 0.759910958003705 \tabularnewline
108 & 0.274797252002727 & 0.549594504005454 & 0.725202747997273 \tabularnewline
109 & 0.350042997856175 & 0.70008599571235 & 0.649957002143825 \tabularnewline
110 & 0.324344884310105 & 0.64868976862021 & 0.675655115689895 \tabularnewline
111 & 0.339145848661484 & 0.678291697322967 & 0.660854151338516 \tabularnewline
112 & 0.317973500632925 & 0.635947001265849 & 0.682026499367075 \tabularnewline
113 & 0.399424995914857 & 0.798849991829715 & 0.600575004085143 \tabularnewline
114 & 0.404005966327974 & 0.808011932655948 & 0.595994033672026 \tabularnewline
115 & 0.370304824642103 & 0.740609649284205 & 0.629695175357897 \tabularnewline
116 & 0.337588778922558 & 0.675177557845115 & 0.662411221077442 \tabularnewline
117 & 0.307006368159027 & 0.614012736318055 & 0.692993631840973 \tabularnewline
118 & 0.277364001732949 & 0.554728003465898 & 0.722635998267051 \tabularnewline
119 & 0.253507067176312 & 0.507014134352624 & 0.746492932823688 \tabularnewline
120 & 0.229493792372006 & 0.458987584744011 & 0.770506207627994 \tabularnewline
121 & 0.208953940705906 & 0.417907881411811 & 0.791046059294094 \tabularnewline
122 & 0.187332156056846 & 0.374664312113692 & 0.812667843943154 \tabularnewline
123 & 0.169797841230666 & 0.339595682461332 & 0.830202158769334 \tabularnewline
124 & 0.152255280287835 & 0.30451056057567 & 0.847744719712165 \tabularnewline
125 & 0.180170059025654 & 0.360340118051308 & 0.819829940974346 \tabularnewline
126 & 0.176731463070276 & 0.353462926140553 & 0.823268536929724 \tabularnewline
127 & 0.257437510460868 & 0.514875020921736 & 0.742562489539132 \tabularnewline
128 & 0.237930961014359 & 0.475861922028718 & 0.762069038985641 \tabularnewline
129 & 0.212543377615653 & 0.425086755231306 & 0.787456622384347 \tabularnewline
130 & 0.23795269859983 & 0.475905397199661 & 0.76204730140017 \tabularnewline
131 & 0.213906030460167 & 0.427812060920335 & 0.786093969539833 \tabularnewline
132 & 0.218175206261311 & 0.436350412522622 & 0.781824793738689 \tabularnewline
133 & 0.206196067293338 & 0.412392134586676 & 0.793803932706662 \tabularnewline
134 & 0.200686855536359 & 0.401373711072719 & 0.799313144463641 \tabularnewline
135 & 0.193264170391414 & 0.386528340782827 & 0.806735829608586 \tabularnewline
136 & 0.172209933951292 & 0.344419867902584 & 0.827790066048708 \tabularnewline
137 & 0.173871729430698 & 0.347743458861396 & 0.826128270569302 \tabularnewline
138 & 0.157279308071908 & 0.314558616143817 & 0.842720691928092 \tabularnewline
139 & 0.137725688817096 & 0.275451377634191 & 0.862274311182904 \tabularnewline
140 & 0.121402998690192 & 0.242805997380383 & 0.878597001309808 \tabularnewline
141 & 0.127365464245207 & 0.254730928490413 & 0.872634535754793 \tabularnewline
142 & 0.110273629048627 & 0.220547258097253 & 0.889726370951373 \tabularnewline
143 & 0.103625057534499 & 0.207250115068998 & 0.896374942465501 \tabularnewline
144 & 0.102695553890803 & 0.205391107781606 & 0.897304446109197 \tabularnewline
145 & 0.0963192467275291 & 0.192638493455058 & 0.903680753272471 \tabularnewline
146 & 0.0915348331971603 & 0.183069666394321 & 0.90846516680284 \tabularnewline
147 & 0.081603259829284 & 0.163206519658568 & 0.918396740170716 \tabularnewline
148 & 0.112230911801752 & 0.224461823603503 & 0.887769088198248 \tabularnewline
149 & 0.11180941770182 & 0.22361883540364 & 0.88819058229818 \tabularnewline
150 & 0.100810914840836 & 0.201621829681672 & 0.899189085159164 \tabularnewline
151 & 0.103594167254733 & 0.207188334509466 & 0.896405832745267 \tabularnewline
152 & 0.105887938023613 & 0.211775876047226 & 0.894112061976387 \tabularnewline
153 & 0.176107569651951 & 0.352215139303902 & 0.823892430348049 \tabularnewline
154 & 0.158026140346781 & 0.316052280693561 & 0.841973859653219 \tabularnewline
155 & 0.138214669742308 & 0.276429339484616 & 0.861785330257692 \tabularnewline
156 & 0.214242659145646 & 0.428485318291293 & 0.785757340854354 \tabularnewline
157 & 0.192837927861105 & 0.38567585572221 & 0.807162072138895 \tabularnewline
158 & 0.176858306893565 & 0.35371661378713 & 0.823141693106435 \tabularnewline
159 & 0.172571978107055 & 0.34514395621411 & 0.827428021892945 \tabularnewline
160 & 0.166422629161532 & 0.332845258323064 & 0.833577370838468 \tabularnewline
161 & 0.17043430387213 & 0.34086860774426 & 0.82956569612787 \tabularnewline
162 & 0.199159026971605 & 0.39831805394321 & 0.800840973028395 \tabularnewline
163 & 0.179885883127012 & 0.359771766254024 & 0.820114116872988 \tabularnewline
164 & 0.166906389700692 & 0.333812779401384 & 0.833093610299308 \tabularnewline
165 & 0.150857624786191 & 0.301715249572382 & 0.849142375213809 \tabularnewline
166 & 0.192430279577711 & 0.384860559155422 & 0.807569720422289 \tabularnewline
167 & 0.221099693883238 & 0.442199387766477 & 0.778900306116762 \tabularnewline
168 & 0.202351864438715 & 0.40470372887743 & 0.797648135561285 \tabularnewline
169 & 0.208829588136168 & 0.417659176272336 & 0.791170411863832 \tabularnewline
170 & 0.233934033158646 & 0.467868066317291 & 0.766065966841354 \tabularnewline
171 & 0.213013520687013 & 0.426027041374026 & 0.786986479312987 \tabularnewline
172 & 0.225744204791174 & 0.451488409582348 & 0.774255795208826 \tabularnewline
173 & 0.202014246779709 & 0.404028493559418 & 0.797985753220291 \tabularnewline
174 & 0.252963465538441 & 0.505926931076881 & 0.747036534461559 \tabularnewline
175 & 0.229739856696876 & 0.459479713393752 & 0.770260143303124 \tabularnewline
176 & 0.238823459925311 & 0.477646919850622 & 0.761176540074689 \tabularnewline
177 & 0.233188694987759 & 0.466377389975518 & 0.766811305012241 \tabularnewline
178 & 0.208373061961736 & 0.416746123923472 & 0.791626938038264 \tabularnewline
179 & 0.186715989509541 & 0.373431979019082 & 0.813284010490459 \tabularnewline
180 & 0.180136431583108 & 0.360272863166216 & 0.819863568416892 \tabularnewline
181 & 0.163150070195217 & 0.326300140390433 & 0.836849929804783 \tabularnewline
182 & 0.189434740425925 & 0.378869480851849 & 0.810565259574075 \tabularnewline
183 & 0.16682263387983 & 0.333645267759661 & 0.83317736612017 \tabularnewline
184 & 0.149516527139619 & 0.299033054279238 & 0.850483472860381 \tabularnewline
185 & 0.139194789451852 & 0.278389578903704 & 0.860805210548148 \tabularnewline
186 & 0.122247074280256 & 0.244494148560512 & 0.877752925719744 \tabularnewline
187 & 0.110274316180094 & 0.220548632360188 & 0.889725683819906 \tabularnewline
188 & 0.107475305708466 & 0.214950611416933 & 0.892524694291534 \tabularnewline
189 & 0.0925191537911465 & 0.185038307582293 & 0.907480846208853 \tabularnewline
190 & 0.0863787754100094 & 0.172757550820019 & 0.913621224589991 \tabularnewline
191 & 0.0863939562020224 & 0.172787912404045 & 0.913606043797978 \tabularnewline
192 & 0.0801679253130914 & 0.160335850626183 & 0.919832074686909 \tabularnewline
193 & 0.068410361067185 & 0.13682072213437 & 0.931589638932815 \tabularnewline
194 & 0.0578498885905822 & 0.115699777181164 & 0.942150111409418 \tabularnewline
195 & 0.0486493991875963 & 0.0972987983751925 & 0.951350600812404 \tabularnewline
196 & 0.0769629212735271 & 0.153925842547054 & 0.923037078726473 \tabularnewline
197 & 0.0998944647324964 & 0.199788929464993 & 0.900105535267504 \tabularnewline
198 & 0.0992158993427043 & 0.198431798685409 & 0.900784100657296 \tabularnewline
199 & 0.14624021631086 & 0.292480432621719 & 0.85375978368914 \tabularnewline
200 & 0.127220197837622 & 0.254440395675245 & 0.872779802162378 \tabularnewline
201 & 0.117766323772981 & 0.235532647545961 & 0.882233676227019 \tabularnewline
202 & 0.109645406722972 & 0.219290813445945 & 0.890354593277028 \tabularnewline
203 & 0.0949524889029167 & 0.189904977805833 & 0.905047511097083 \tabularnewline
204 & 0.109703061856755 & 0.21940612371351 & 0.890296938143245 \tabularnewline
205 & 0.0945728506593444 & 0.189145701318689 & 0.905427149340656 \tabularnewline
206 & 0.113191648287852 & 0.226383296575704 & 0.886808351712148 \tabularnewline
207 & 0.1426312464041 & 0.285262492808199 & 0.8573687535959 \tabularnewline
208 & 0.179954414832836 & 0.359908829665673 & 0.820045585167164 \tabularnewline
209 & 0.161347304903993 & 0.322694609807986 & 0.838652695096007 \tabularnewline
210 & 0.160750378926975 & 0.32150075785395 & 0.839249621073025 \tabularnewline
211 & 0.155725344148132 & 0.311450688296265 & 0.844274655851868 \tabularnewline
212 & 0.156564764854347 & 0.313129529708693 & 0.843435235145653 \tabularnewline
213 & 0.19686632160383 & 0.393732643207659 & 0.80313367839617 \tabularnewline
214 & 0.178192797071639 & 0.356385594143279 & 0.821807202928361 \tabularnewline
215 & 0.23120976374647 & 0.462419527492941 & 0.768790236253529 \tabularnewline
216 & 0.232335672877324 & 0.464671345754648 & 0.767664327122676 \tabularnewline
217 & 0.20873604090023 & 0.41747208180046 & 0.79126395909977 \tabularnewline
218 & 0.257218764909022 & 0.514437529818043 & 0.742781235090978 \tabularnewline
219 & 0.264185045627919 & 0.528370091255839 & 0.735814954372081 \tabularnewline
220 & 0.283417416512944 & 0.566834833025887 & 0.716582583487056 \tabularnewline
221 & 0.365076954983539 & 0.730153909967078 & 0.634923045016461 \tabularnewline
222 & 0.710605122988906 & 0.578789754022188 & 0.289394877011094 \tabularnewline
223 & 0.67899587894349 & 0.642008242113021 & 0.32100412105651 \tabularnewline
224 & 0.717695288339809 & 0.564609423320381 & 0.282304711660191 \tabularnewline
225 & 0.682457427750804 & 0.635085144498392 & 0.317542572249196 \tabularnewline
226 & 0.666927930423944 & 0.666144139152112 & 0.333072069576056 \tabularnewline
227 & 0.656617920297612 & 0.686764159404776 & 0.343382079702388 \tabularnewline
228 & 0.722421486332682 & 0.555157027334635 & 0.277578513667318 \tabularnewline
229 & 0.690949135508979 & 0.618101728982042 & 0.309050864491021 \tabularnewline
230 & 0.784061174623282 & 0.431877650753437 & 0.215938825376718 \tabularnewline
231 & 0.751764337170496 & 0.496471325659007 & 0.248235662829504 \tabularnewline
232 & 0.715806923457966 & 0.568386153084068 & 0.284193076542034 \tabularnewline
233 & 0.684869142797838 & 0.630261714404323 & 0.315130857202162 \tabularnewline
234 & 0.668566043364108 & 0.662867913271784 & 0.331433956635892 \tabularnewline
235 & 0.627722192359874 & 0.744555615280252 & 0.372277807640126 \tabularnewline
236 & 0.588725394279106 & 0.822549211441789 & 0.411274605720894 \tabularnewline
237 & 0.653331462828337 & 0.693337074343327 & 0.346668537171663 \tabularnewline
238 & 0.617030866857124 & 0.765938266285752 & 0.382969133142876 \tabularnewline
239 & 0.581313417797712 & 0.837373164404575 & 0.418686582202288 \tabularnewline
240 & 0.534645479743425 & 0.93070904051315 & 0.465354520256575 \tabularnewline
241 & 0.513641625877153 & 0.972716748245693 & 0.486358374122847 \tabularnewline
242 & 0.497531995492637 & 0.995063990985275 & 0.502468004507363 \tabularnewline
243 & 0.489561627156816 & 0.979123254313631 & 0.510438372843184 \tabularnewline
244 & 0.445005481484873 & 0.890010962969746 & 0.554994518515127 \tabularnewline
245 & 0.540684860994815 & 0.918630278010371 & 0.459315139005185 \tabularnewline
246 & 0.528752116296796 & 0.942495767406409 & 0.471247883703204 \tabularnewline
247 & 0.533982744426014 & 0.932034511147972 & 0.466017255573986 \tabularnewline
248 & 0.52491295533856 & 0.95017408932288 & 0.47508704466144 \tabularnewline
249 & 0.476415923473051 & 0.952831846946103 & 0.523584076526949 \tabularnewline
250 & 0.42796789471236 & 0.85593578942472 & 0.57203210528764 \tabularnewline
251 & 0.421264142940272 & 0.842528285880544 & 0.578735857059728 \tabularnewline
252 & 0.41690877738109 & 0.83381755476218 & 0.58309122261891 \tabularnewline
253 & 0.461885950319565 & 0.923771900639129 & 0.538114049680435 \tabularnewline
254 & 0.410352062957122 & 0.820704125914244 & 0.589647937042878 \tabularnewline
255 & 0.400825716697144 & 0.801651433394288 & 0.599174283302856 \tabularnewline
256 & 0.626465732006702 & 0.747068535986595 & 0.373534267993298 \tabularnewline
257 & 0.701350783838778 & 0.597298432322444 & 0.298649216161222 \tabularnewline
258 & 0.765623502908599 & 0.468752994182802 & 0.234376497091401 \tabularnewline
259 & 0.812431904159602 & 0.375136191680796 & 0.187568095840398 \tabularnewline
260 & 0.795098966285812 & 0.409802067428376 & 0.204901033714188 \tabularnewline
261 & 0.850273755982228 & 0.299452488035544 & 0.149726244017772 \tabularnewline
262 & 0.816916551581224 & 0.366166896837553 & 0.183083448418776 \tabularnewline
263 & 0.768757332574891 & 0.462485334850218 & 0.231242667425109 \tabularnewline
264 & 0.864344223797121 & 0.271311552405758 & 0.135655776202879 \tabularnewline
265 & 0.816603257039658 & 0.366793485920684 & 0.183396742960342 \tabularnewline
266 & 0.763450818890714 & 0.473098362218573 & 0.236549181109286 \tabularnewline
267 & 0.741472796652273 & 0.517054406695455 & 0.258527203347727 \tabularnewline
268 & 0.701174465740624 & 0.597651068518752 & 0.298825534259376 \tabularnewline
269 & 0.631599649540671 & 0.736800700918658 & 0.368400350459329 \tabularnewline
270 & 0.565407886812512 & 0.869184226374976 & 0.434592113187488 \tabularnewline
271 & 0.58866036324143 & 0.82267927351714 & 0.41133963675857 \tabularnewline
272 & 0.495412139508227 & 0.990824279016454 & 0.504587860491773 \tabularnewline
273 & 0.399608759524835 & 0.79921751904967 & 0.600391240475165 \tabularnewline
274 & 0.315804056715555 & 0.63160811343111 & 0.684195943284445 \tabularnewline
275 & 0.243570586386381 & 0.487141172772762 & 0.756429413613619 \tabularnewline
276 & 0.166516639025796 & 0.333033278051592 & 0.833483360974204 \tabularnewline
277 & 0.106336041260759 & 0.212672082521518 & 0.893663958739241 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184814&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]11[/C][C]0.55461767847408[/C][C]0.89076464305184[/C][C]0.44538232152592[/C][/ROW]
[ROW][C]12[/C][C]0.58964809802957[/C][C]0.82070380394086[/C][C]0.41035190197043[/C][/ROW]
[ROW][C]13[/C][C]0.71366239861542[/C][C]0.572675202769161[/C][C]0.28633760138458[/C][/ROW]
[ROW][C]14[/C][C]0.603034495405321[/C][C]0.793931009189358[/C][C]0.396965504594679[/C][/ROW]
[ROW][C]15[/C][C]0.65752348791717[/C][C]0.68495302416566[/C][C]0.34247651208283[/C][/ROW]
[ROW][C]16[/C][C]0.559733450066413[/C][C]0.880533099867173[/C][C]0.440266549933587[/C][/ROW]
[ROW][C]17[/C][C]0.494676110502401[/C][C]0.989352221004802[/C][C]0.505323889497599[/C][/ROW]
[ROW][C]18[/C][C]0.42324179832326[/C][C]0.84648359664652[/C][C]0.57675820167674[/C][/ROW]
[ROW][C]19[/C][C]0.356754337880953[/C][C]0.713508675761905[/C][C]0.643245662119047[/C][/ROW]
[ROW][C]20[/C][C]0.396705108484984[/C][C]0.793410216969968[/C][C]0.603294891515016[/C][/ROW]
[ROW][C]21[/C][C]0.467578181260778[/C][C]0.935156362521556[/C][C]0.532421818739222[/C][/ROW]
[ROW][C]22[/C][C]0.858136983781026[/C][C]0.283726032437949[/C][C]0.141863016218974[/C][/ROW]
[ROW][C]23[/C][C]0.840221407770082[/C][C]0.319557184459837[/C][C]0.159778592229918[/C][/ROW]
[ROW][C]24[/C][C]0.867791225438161[/C][C]0.264417549123678[/C][C]0.132208774561839[/C][/ROW]
[ROW][C]25[/C][C]0.842256578833244[/C][C]0.315486842333512[/C][C]0.157743421166756[/C][/ROW]
[ROW][C]26[/C][C]0.975078073764871[/C][C]0.0498438524702576[/C][C]0.0249219262351288[/C][/ROW]
[ROW][C]27[/C][C]0.969774692913902[/C][C]0.0604506141721959[/C][C]0.030225307086098[/C][/ROW]
[ROW][C]28[/C][C]0.957516671153805[/C][C]0.0849666576923909[/C][C]0.0424833288461954[/C][/ROW]
[ROW][C]29[/C][C]0.942287901240738[/C][C]0.115424197518525[/C][C]0.0577120987592624[/C][/ROW]
[ROW][C]30[/C][C]0.948946910809801[/C][C]0.102106178380397[/C][C]0.0510530891901985[/C][/ROW]
[ROW][C]31[/C][C]0.938680249461368[/C][C]0.122639501077264[/C][C]0.061319750538632[/C][/ROW]
[ROW][C]32[/C][C]0.920929248371749[/C][C]0.158141503256502[/C][C]0.0790707516282512[/C][/ROW]
[ROW][C]33[/C][C]0.912749584354673[/C][C]0.174500831290653[/C][C]0.0872504156453266[/C][/ROW]
[ROW][C]34[/C][C]0.890238075990529[/C][C]0.219523848018943[/C][C]0.109761924009471[/C][/ROW]
[ROW][C]35[/C][C]0.861905826669877[/C][C]0.276188346660246[/C][C]0.138094173330123[/C][/ROW]
[ROW][C]36[/C][C]0.845402735660865[/C][C]0.309194528678271[/C][C]0.154597264339135[/C][/ROW]
[ROW][C]37[/C][C]0.911449430194266[/C][C]0.177101139611467[/C][C]0.0885505698057336[/C][/ROW]
[ROW][C]38[/C][C]0.896386126242729[/C][C]0.207227747514543[/C][C]0.103613873757271[/C][/ROW]
[ROW][C]39[/C][C]0.891490456827552[/C][C]0.217019086344897[/C][C]0.108509543172448[/C][/ROW]
[ROW][C]40[/C][C]0.869121518254902[/C][C]0.261756963490196[/C][C]0.130878481745098[/C][/ROW]
[ROW][C]41[/C][C]0.843748524822437[/C][C]0.312502950355126[/C][C]0.156251475177563[/C][/ROW]
[ROW][C]42[/C][C]0.820665315901288[/C][C]0.358669368197425[/C][C]0.179334684098712[/C][/ROW]
[ROW][C]43[/C][C]0.804761007749851[/C][C]0.390477984500298[/C][C]0.195238992250149[/C][/ROW]
[ROW][C]44[/C][C]0.789770535662616[/C][C]0.420458928674767[/C][C]0.210229464337384[/C][/ROW]
[ROW][C]45[/C][C]0.757865571671104[/C][C]0.484268856657792[/C][C]0.242134428328896[/C][/ROW]
[ROW][C]46[/C][C]0.769598275209616[/C][C]0.460803449580769[/C][C]0.230401724790384[/C][/ROW]
[ROW][C]47[/C][C]0.742765934186863[/C][C]0.514468131626273[/C][C]0.257234065813137[/C][/ROW]
[ROW][C]48[/C][C]0.704297937371785[/C][C]0.591404125256429[/C][C]0.295702062628215[/C][/ROW]
[ROW][C]49[/C][C]0.701741334570318[/C][C]0.596517330859364[/C][C]0.298258665429682[/C][/ROW]
[ROW][C]50[/C][C]0.661600790565058[/C][C]0.676798418869883[/C][C]0.338399209434942[/C][/ROW]
[ROW][C]51[/C][C]0.639057381681354[/C][C]0.721885236637292[/C][C]0.360942618318646[/C][/ROW]
[ROW][C]52[/C][C]0.595499851856127[/C][C]0.809000296287746[/C][C]0.404500148143873[/C][/ROW]
[ROW][C]53[/C][C]0.575552744021242[/C][C]0.848894511957515[/C][C]0.424447255978758[/C][/ROW]
[ROW][C]54[/C][C]0.575284678686101[/C][C]0.849430642627797[/C][C]0.424715321313898[/C][/ROW]
[ROW][C]55[/C][C]0.53846749799652[/C][C]0.923065004006959[/C][C]0.46153250200348[/C][/ROW]
[ROW][C]56[/C][C]0.49519016833191[/C][C]0.990380336663821[/C][C]0.50480983166809[/C][/ROW]
[ROW][C]57[/C][C]0.461402970976716[/C][C]0.922805941953432[/C][C]0.538597029023284[/C][/ROW]
[ROW][C]58[/C][C]0.419197454805204[/C][C]0.838394909610408[/C][C]0.580802545194796[/C][/ROW]
[ROW][C]59[/C][C]0.388412005405299[/C][C]0.776824010810598[/C][C]0.611587994594701[/C][/ROW]
[ROW][C]60[/C][C]0.407038888599302[/C][C]0.814077777198604[/C][C]0.592961111400698[/C][/ROW]
[ROW][C]61[/C][C]0.555052521793232[/C][C]0.889894956413536[/C][C]0.444947478206768[/C][/ROW]
[ROW][C]62[/C][C]0.512766491056268[/C][C]0.974467017887463[/C][C]0.487233508943732[/C][/ROW]
[ROW][C]63[/C][C]0.533116290621798[/C][C]0.933767418756404[/C][C]0.466883709378202[/C][/ROW]
[ROW][C]64[/C][C]0.492943615868778[/C][C]0.985887231737556[/C][C]0.507056384131222[/C][/ROW]
[ROW][C]65[/C][C]0.455488337891461[/C][C]0.910976675782923[/C][C]0.544511662108539[/C][/ROW]
[ROW][C]66[/C][C]0.471572638158748[/C][C]0.943145276317496[/C][C]0.528427361841252[/C][/ROW]
[ROW][C]67[/C][C]0.497201961929881[/C][C]0.994403923859762[/C][C]0.502798038070119[/C][/ROW]
[ROW][C]68[/C][C]0.466456984463148[/C][C]0.932913968926296[/C][C]0.533543015536852[/C][/ROW]
[ROW][C]69[/C][C]0.451948371500636[/C][C]0.903896743001272[/C][C]0.548051628499364[/C][/ROW]
[ROW][C]70[/C][C]0.457998815951306[/C][C]0.915997631902612[/C][C]0.542001184048694[/C][/ROW]
[ROW][C]71[/C][C]0.43331579397825[/C][C]0.8666315879565[/C][C]0.56668420602175[/C][/ROW]
[ROW][C]72[/C][C]0.438183196136837[/C][C]0.876366392273673[/C][C]0.561816803863163[/C][/ROW]
[ROW][C]73[/C][C]0.406366205049435[/C][C]0.81273241009887[/C][C]0.593633794950565[/C][/ROW]
[ROW][C]74[/C][C]0.389773335708291[/C][C]0.779546671416583[/C][C]0.610226664291709[/C][/ROW]
[ROW][C]75[/C][C]0.35391449292801[/C][C]0.707828985856021[/C][C]0.64608550707199[/C][/ROW]
[ROW][C]76[/C][C]0.356476983207372[/C][C]0.712953966414744[/C][C]0.643523016792628[/C][/ROW]
[ROW][C]77[/C][C]0.376630377459189[/C][C]0.753260754918378[/C][C]0.623369622540811[/C][/ROW]
[ROW][C]78[/C][C]0.345521147849446[/C][C]0.691042295698891[/C][C]0.654478852150554[/C][/ROW]
[ROW][C]79[/C][C]0.356298342407834[/C][C]0.712596684815667[/C][C]0.643701657592166[/C][/ROW]
[ROW][C]80[/C][C]0.322291303234813[/C][C]0.644582606469627[/C][C]0.677708696765187[/C][/ROW]
[ROW][C]81[/C][C]0.30930265849022[/C][C]0.61860531698044[/C][C]0.69069734150978[/C][/ROW]
[ROW][C]82[/C][C]0.279829425890423[/C][C]0.559658851780846[/C][C]0.720170574109577[/C][/ROW]
[ROW][C]83[/C][C]0.293219309485546[/C][C]0.586438618971091[/C][C]0.706780690514454[/C][/ROW]
[ROW][C]84[/C][C]0.266802993450999[/C][C]0.533605986901998[/C][C]0.733197006549001[/C][/ROW]
[ROW][C]85[/C][C]0.236235746854343[/C][C]0.472471493708686[/C][C]0.763764253145657[/C][/ROW]
[ROW][C]86[/C][C]0.218734373619145[/C][C]0.437468747238289[/C][C]0.781265626380856[/C][/ROW]
[ROW][C]87[/C][C]0.191524632078589[/C][C]0.383049264157178[/C][C]0.808475367921411[/C][/ROW]
[ROW][C]88[/C][C]0.16982545841339[/C][C]0.339650916826779[/C][C]0.83017454158661[/C][/ROW]
[ROW][C]89[/C][C]0.396795773113613[/C][C]0.793591546227227[/C][C]0.603204226886387[/C][/ROW]
[ROW][C]90[/C][C]0.433474476655249[/C][C]0.866948953310498[/C][C]0.566525523344751[/C][/ROW]
[ROW][C]91[/C][C]0.403292010194096[/C][C]0.806584020388192[/C][C]0.596707989805904[/C][/ROW]
[ROW][C]92[/C][C]0.370129113900336[/C][C]0.740258227800672[/C][C]0.629870886099664[/C][/ROW]
[ROW][C]93[/C][C]0.339696240664323[/C][C]0.679392481328645[/C][C]0.660303759335677[/C][/ROW]
[ROW][C]94[/C][C]0.308354763355024[/C][C]0.616709526710047[/C][C]0.691645236644976[/C][/ROW]
[ROW][C]95[/C][C]0.289930181973462[/C][C]0.579860363946924[/C][C]0.710069818026538[/C][/ROW]
[ROW][C]96[/C][C]0.283643563855866[/C][C]0.567287127711732[/C][C]0.716356436144134[/C][/ROW]
[ROW][C]97[/C][C]0.253941137565514[/C][C]0.507882275131027[/C][C]0.746058862434486[/C][/ROW]
[ROW][C]98[/C][C]0.295827815742743[/C][C]0.591655631485486[/C][C]0.704172184257257[/C][/ROW]
[ROW][C]99[/C][C]0.28129708937121[/C][C]0.56259417874242[/C][C]0.71870291062879[/C][/ROW]
[ROW][C]100[/C][C]0.292221654464096[/C][C]0.584443308928191[/C][C]0.707778345535904[/C][/ROW]
[ROW][C]101[/C][C]0.275995773526774[/C][C]0.551991547053548[/C][C]0.724004226473226[/C][/ROW]
[ROW][C]102[/C][C]0.256190924539832[/C][C]0.512381849079664[/C][C]0.743809075460168[/C][/ROW]
[ROW][C]103[/C][C]0.247637925333461[/C][C]0.495275850666922[/C][C]0.752362074666539[/C][/ROW]
[ROW][C]104[/C][C]0.221869204050016[/C][C]0.443738408100033[/C][C]0.778130795949984[/C][/ROW]
[ROW][C]105[/C][C]0.2782520958676[/C][C]0.5565041917352[/C][C]0.7217479041324[/C][/ROW]
[ROW][C]106[/C][C]0.261909046962154[/C][C]0.523818093924308[/C][C]0.738090953037846[/C][/ROW]
[ROW][C]107[/C][C]0.240089041996295[/C][C]0.480178083992589[/C][C]0.759910958003705[/C][/ROW]
[ROW][C]108[/C][C]0.274797252002727[/C][C]0.549594504005454[/C][C]0.725202747997273[/C][/ROW]
[ROW][C]109[/C][C]0.350042997856175[/C][C]0.70008599571235[/C][C]0.649957002143825[/C][/ROW]
[ROW][C]110[/C][C]0.324344884310105[/C][C]0.64868976862021[/C][C]0.675655115689895[/C][/ROW]
[ROW][C]111[/C][C]0.339145848661484[/C][C]0.678291697322967[/C][C]0.660854151338516[/C][/ROW]
[ROW][C]112[/C][C]0.317973500632925[/C][C]0.635947001265849[/C][C]0.682026499367075[/C][/ROW]
[ROW][C]113[/C][C]0.399424995914857[/C][C]0.798849991829715[/C][C]0.600575004085143[/C][/ROW]
[ROW][C]114[/C][C]0.404005966327974[/C][C]0.808011932655948[/C][C]0.595994033672026[/C][/ROW]
[ROW][C]115[/C][C]0.370304824642103[/C][C]0.740609649284205[/C][C]0.629695175357897[/C][/ROW]
[ROW][C]116[/C][C]0.337588778922558[/C][C]0.675177557845115[/C][C]0.662411221077442[/C][/ROW]
[ROW][C]117[/C][C]0.307006368159027[/C][C]0.614012736318055[/C][C]0.692993631840973[/C][/ROW]
[ROW][C]118[/C][C]0.277364001732949[/C][C]0.554728003465898[/C][C]0.722635998267051[/C][/ROW]
[ROW][C]119[/C][C]0.253507067176312[/C][C]0.507014134352624[/C][C]0.746492932823688[/C][/ROW]
[ROW][C]120[/C][C]0.229493792372006[/C][C]0.458987584744011[/C][C]0.770506207627994[/C][/ROW]
[ROW][C]121[/C][C]0.208953940705906[/C][C]0.417907881411811[/C][C]0.791046059294094[/C][/ROW]
[ROW][C]122[/C][C]0.187332156056846[/C][C]0.374664312113692[/C][C]0.812667843943154[/C][/ROW]
[ROW][C]123[/C][C]0.169797841230666[/C][C]0.339595682461332[/C][C]0.830202158769334[/C][/ROW]
[ROW][C]124[/C][C]0.152255280287835[/C][C]0.30451056057567[/C][C]0.847744719712165[/C][/ROW]
[ROW][C]125[/C][C]0.180170059025654[/C][C]0.360340118051308[/C][C]0.819829940974346[/C][/ROW]
[ROW][C]126[/C][C]0.176731463070276[/C][C]0.353462926140553[/C][C]0.823268536929724[/C][/ROW]
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[ROW][C]273[/C][C]0.399608759524835[/C][C]0.79921751904967[/C][C]0.600391240475165[/C][/ROW]
[ROW][C]274[/C][C]0.315804056715555[/C][C]0.63160811343111[/C][C]0.684195943284445[/C][/ROW]
[ROW][C]275[/C][C]0.243570586386381[/C][C]0.487141172772762[/C][C]0.756429413613619[/C][/ROW]
[ROW][C]276[/C][C]0.166516639025796[/C][C]0.333033278051592[/C][C]0.833483360974204[/C][/ROW]
[ROW][C]277[/C][C]0.106336041260759[/C][C]0.212672082521518[/C][C]0.893663958739241[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184814&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184814&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
110.554617678474080.890764643051840.44538232152592
120.589648098029570.820703803940860.41035190197043
130.713662398615420.5726752027691610.28633760138458
140.6030344954053210.7939310091893580.396965504594679
150.657523487917170.684953024165660.34247651208283
160.5597334500664130.8805330998671730.440266549933587
170.4946761105024010.9893522210048020.505323889497599
180.423241798323260.846483596646520.57675820167674
190.3567543378809530.7135086757619050.643245662119047
200.3967051084849840.7934102169699680.603294891515016
210.4675781812607780.9351563625215560.532421818739222
220.8581369837810260.2837260324379490.141863016218974
230.8402214077700820.3195571844598370.159778592229918
240.8677912254381610.2644175491236780.132208774561839
250.8422565788332440.3154868423335120.157743421166756
260.9750780737648710.04984385247025760.0249219262351288
270.9697746929139020.06045061417219590.030225307086098
280.9575166711538050.08496665769239090.0424833288461954
290.9422879012407380.1154241975185250.0577120987592624
300.9489469108098010.1021061783803970.0510530891901985
310.9386802494613680.1226395010772640.061319750538632
320.9209292483717490.1581415032565020.0790707516282512
330.9127495843546730.1745008312906530.0872504156453266
340.8902380759905290.2195238480189430.109761924009471
350.8619058266698770.2761883466602460.138094173330123
360.8454027356608650.3091945286782710.154597264339135
370.9114494301942660.1771011396114670.0885505698057336
380.8963861262427290.2072277475145430.103613873757271
390.8914904568275520.2170190863448970.108509543172448
400.8691215182549020.2617569634901960.130878481745098
410.8437485248224370.3125029503551260.156251475177563
420.8206653159012880.3586693681974250.179334684098712
430.8047610077498510.3904779845002980.195238992250149
440.7897705356626160.4204589286747670.210229464337384
450.7578655716711040.4842688566577920.242134428328896
460.7695982752096160.4608034495807690.230401724790384
470.7427659341868630.5144681316262730.257234065813137
480.7042979373717850.5914041252564290.295702062628215
490.7017413345703180.5965173308593640.298258665429682
500.6616007905650580.6767984188698830.338399209434942
510.6390573816813540.7218852366372920.360942618318646
520.5954998518561270.8090002962877460.404500148143873
530.5755527440212420.8488945119575150.424447255978758
540.5752846786861010.8494306426277970.424715321313898
550.538467497996520.9230650040069590.46153250200348
560.495190168331910.9903803366638210.50480983166809
570.4614029709767160.9228059419534320.538597029023284
580.4191974548052040.8383949096104080.580802545194796
590.3884120054052990.7768240108105980.611587994594701
600.4070388885993020.8140777771986040.592961111400698
610.5550525217932320.8898949564135360.444947478206768
620.5127664910562680.9744670178874630.487233508943732
630.5331162906217980.9337674187564040.466883709378202
640.4929436158687780.9858872317375560.507056384131222
650.4554883378914610.9109766757829230.544511662108539
660.4715726381587480.9431452763174960.528427361841252
670.4972019619298810.9944039238597620.502798038070119
680.4664569844631480.9329139689262960.533543015536852
690.4519483715006360.9038967430012720.548051628499364
700.4579988159513060.9159976319026120.542001184048694
710.433315793978250.86663158795650.56668420602175
720.4381831961368370.8763663922736730.561816803863163
730.4063662050494350.812732410098870.593633794950565
740.3897733357082910.7795466714165830.610226664291709
750.353914492928010.7078289858560210.64608550707199
760.3564769832073720.7129539664147440.643523016792628
770.3766303774591890.7532607549183780.623369622540811
780.3455211478494460.6910422956988910.654478852150554
790.3562983424078340.7125966848156670.643701657592166
800.3222913032348130.6445826064696270.677708696765187
810.309302658490220.618605316980440.69069734150978
820.2798294258904230.5596588517808460.720170574109577
830.2932193094855460.5864386189710910.706780690514454
840.2668029934509990.5336059869019980.733197006549001
850.2362357468543430.4724714937086860.763764253145657
860.2187343736191450.4374687472382890.781265626380856
870.1915246320785890.3830492641571780.808475367921411
880.169825458413390.3396509168267790.83017454158661
890.3967957731136130.7935915462272270.603204226886387
900.4334744766552490.8669489533104980.566525523344751
910.4032920101940960.8065840203881920.596707989805904
920.3701291139003360.7402582278006720.629870886099664
930.3396962406643230.6793924813286450.660303759335677
940.3083547633550240.6167095267100470.691645236644976
950.2899301819734620.5798603639469240.710069818026538
960.2836435638558660.5672871277117320.716356436144134
970.2539411375655140.5078822751310270.746058862434486
980.2958278157427430.5916556314854860.704172184257257
990.281297089371210.562594178742420.71870291062879
1000.2922216544640960.5844433089281910.707778345535904
1010.2759957735267740.5519915470535480.724004226473226
1020.2561909245398320.5123818490796640.743809075460168
1030.2476379253334610.4952758506669220.752362074666539
1040.2218692040500160.4437384081000330.778130795949984
1050.27825209586760.55650419173520.7217479041324
1060.2619090469621540.5238180939243080.738090953037846
1070.2400890419962950.4801780839925890.759910958003705
1080.2747972520027270.5495945040054540.725202747997273
1090.3500429978561750.700085995712350.649957002143825
1100.3243448843101050.648689768620210.675655115689895
1110.3391458486614840.6782916973229670.660854151338516
1120.3179735006329250.6359470012658490.682026499367075
1130.3994249959148570.7988499918297150.600575004085143
1140.4040059663279740.8080119326559480.595994033672026
1150.3703048246421030.7406096492842050.629695175357897
1160.3375887789225580.6751775578451150.662411221077442
1170.3070063681590270.6140127363180550.692993631840973
1180.2773640017329490.5547280034658980.722635998267051
1190.2535070671763120.5070141343526240.746492932823688
1200.2294937923720060.4589875847440110.770506207627994
1210.2089539407059060.4179078814118110.791046059294094
1220.1873321560568460.3746643121136920.812667843943154
1230.1697978412306660.3395956824613320.830202158769334
1240.1522552802878350.304510560575670.847744719712165
1250.1801700590256540.3603401180513080.819829940974346
1260.1767314630702760.3534629261405530.823268536929724
1270.2574375104608680.5148750209217360.742562489539132
1280.2379309610143590.4758619220287180.762069038985641
1290.2125433776156530.4250867552313060.787456622384347
1300.237952698599830.4759053971996610.76204730140017
1310.2139060304601670.4278120609203350.786093969539833
1320.2181752062613110.4363504125226220.781824793738689
1330.2061960672933380.4123921345866760.793803932706662
1340.2006868555363590.4013737110727190.799313144463641
1350.1932641703914140.3865283407828270.806735829608586
1360.1722099339512920.3444198679025840.827790066048708
1370.1738717294306980.3477434588613960.826128270569302
1380.1572793080719080.3145586161438170.842720691928092
1390.1377256888170960.2754513776341910.862274311182904
1400.1214029986901920.2428059973803830.878597001309808
1410.1273654642452070.2547309284904130.872634535754793
1420.1102736290486270.2205472580972530.889726370951373
1430.1036250575344990.2072501150689980.896374942465501
1440.1026955538908030.2053911077816060.897304446109197
1450.09631924672752910.1926384934550580.903680753272471
1460.09153483319716030.1830696663943210.90846516680284
1470.0816032598292840.1632065196585680.918396740170716
1480.1122309118017520.2244618236035030.887769088198248
1490.111809417701820.223618835403640.88819058229818
1500.1008109148408360.2016218296816720.899189085159164
1510.1035941672547330.2071883345094660.896405832745267
1520.1058879380236130.2117758760472260.894112061976387
1530.1761075696519510.3522151393039020.823892430348049
1540.1580261403467810.3160522806935610.841973859653219
1550.1382146697423080.2764293394846160.861785330257692
1560.2142426591456460.4284853182912930.785757340854354
1570.1928379278611050.385675855722210.807162072138895
1580.1768583068935650.353716613787130.823141693106435
1590.1725719781070550.345143956214110.827428021892945
1600.1664226291615320.3328452583230640.833577370838468
1610.170434303872130.340868607744260.82956569612787
1620.1991590269716050.398318053943210.800840973028395
1630.1798858831270120.3597717662540240.820114116872988
1640.1669063897006920.3338127794013840.833093610299308
1650.1508576247861910.3017152495723820.849142375213809
1660.1924302795777110.3848605591554220.807569720422289
1670.2210996938832380.4421993877664770.778900306116762
1680.2023518644387150.404703728877430.797648135561285
1690.2088295881361680.4176591762723360.791170411863832
1700.2339340331586460.4678680663172910.766065966841354
1710.2130135206870130.4260270413740260.786986479312987
1720.2257442047911740.4514884095823480.774255795208826
1730.2020142467797090.4040284935594180.797985753220291
1740.2529634655384410.5059269310768810.747036534461559
1750.2297398566968760.4594797133937520.770260143303124
1760.2388234599253110.4776469198506220.761176540074689
1770.2331886949877590.4663773899755180.766811305012241
1780.2083730619617360.4167461239234720.791626938038264
1790.1867159895095410.3734319790190820.813284010490459
1800.1801364315831080.3602728631662160.819863568416892
1810.1631500701952170.3263001403904330.836849929804783
1820.1894347404259250.3788694808518490.810565259574075
1830.166822633879830.3336452677596610.83317736612017
1840.1495165271396190.2990330542792380.850483472860381
1850.1391947894518520.2783895789037040.860805210548148
1860.1222470742802560.2444941485605120.877752925719744
1870.1102743161800940.2205486323601880.889725683819906
1880.1074753057084660.2149506114169330.892524694291534
1890.09251915379114650.1850383075822930.907480846208853
1900.08637877541000940.1727575508200190.913621224589991
1910.08639395620202240.1727879124040450.913606043797978
1920.08016792531309140.1603358506261830.919832074686909
1930.0684103610671850.136820722134370.931589638932815
1940.05784988859058220.1156997771811640.942150111409418
1950.04864939918759630.09729879837519250.951350600812404
1960.07696292127352710.1539258425470540.923037078726473
1970.09989446473249640.1997889294649930.900105535267504
1980.09921589934270430.1984317986854090.900784100657296
1990.146240216310860.2924804326217190.85375978368914
2000.1272201978376220.2544403956752450.872779802162378
2010.1177663237729810.2355326475459610.882233676227019
2020.1096454067229720.2192908134459450.890354593277028
2030.09495248890291670.1899049778058330.905047511097083
2040.1097030618567550.219406123713510.890296938143245
2050.09457285065934440.1891457013186890.905427149340656
2060.1131916482878520.2263832965757040.886808351712148
2070.14263124640410.2852624928081990.8573687535959
2080.1799544148328360.3599088296656730.820045585167164
2090.1613473049039930.3226946098079860.838652695096007
2100.1607503789269750.321500757853950.839249621073025
2110.1557253441481320.3114506882962650.844274655851868
2120.1565647648543470.3131295297086930.843435235145653
2130.196866321603830.3937326432076590.80313367839617
2140.1781927970716390.3563855941432790.821807202928361
2150.231209763746470.4624195274929410.768790236253529
2160.2323356728773240.4646713457546480.767664327122676
2170.208736040900230.417472081800460.79126395909977
2180.2572187649090220.5144375298180430.742781235090978
2190.2641850456279190.5283700912558390.735814954372081
2200.2834174165129440.5668348330258870.716582583487056
2210.3650769549835390.7301539099670780.634923045016461
2220.7106051229889060.5787897540221880.289394877011094
2230.678995878943490.6420082421130210.32100412105651
2240.7176952883398090.5646094233203810.282304711660191
2250.6824574277508040.6350851444983920.317542572249196
2260.6669279304239440.6661441391521120.333072069576056
2270.6566179202976120.6867641594047760.343382079702388
2280.7224214863326820.5551570273346350.277578513667318
2290.6909491355089790.6181017289820420.309050864491021
2300.7840611746232820.4318776507534370.215938825376718
2310.7517643371704960.4964713256590070.248235662829504
2320.7158069234579660.5683861530840680.284193076542034
2330.6848691427978380.6302617144043230.315130857202162
2340.6685660433641080.6628679132717840.331433956635892
2350.6277221923598740.7445556152802520.372277807640126
2360.5887253942791060.8225492114417890.411274605720894
2370.6533314628283370.6933370743433270.346668537171663
2380.6170308668571240.7659382662857520.382969133142876
2390.5813134177977120.8373731644045750.418686582202288
2400.5346454797434250.930709040513150.465354520256575
2410.5136416258771530.9727167482456930.486358374122847
2420.4975319954926370.9950639909852750.502468004507363
2430.4895616271568160.9791232543136310.510438372843184
2440.4450054814848730.8900109629697460.554994518515127
2450.5406848609948150.9186302780103710.459315139005185
2460.5287521162967960.9424957674064090.471247883703204
2470.5339827444260140.9320345111479720.466017255573986
2480.524912955338560.950174089322880.47508704466144
2490.4764159234730510.9528318469461030.523584076526949
2500.427967894712360.855935789424720.57203210528764
2510.4212641429402720.8425282858805440.578735857059728
2520.416908777381090.833817554762180.58309122261891
2530.4618859503195650.9237719006391290.538114049680435
2540.4103520629571220.8207041259142440.589647937042878
2550.4008257166971440.8016514333942880.599174283302856
2560.6264657320067020.7470685359865950.373534267993298
2570.7013507838387780.5972984323224440.298649216161222
2580.7656235029085990.4687529941828020.234376497091401
2590.8124319041596020.3751361916807960.187568095840398
2600.7950989662858120.4098020674283760.204901033714188
2610.8502737559822280.2994524880355440.149726244017772
2620.8169165515812240.3661668968375530.183083448418776
2630.7687573325748910.4624853348502180.231242667425109
2640.8643442237971210.2713115524057580.135655776202879
2650.8166032570396580.3667934859206840.183396742960342
2660.7634508188907140.4730983622185730.236549181109286
2670.7414727966522730.5170544066954550.258527203347727
2680.7011744657406240.5976510685187520.298825534259376
2690.6315996495406710.7368007009186580.368400350459329
2700.5654078868125120.8691842263749760.434592113187488
2710.588660363241430.822679273517140.41133963675857
2720.4954121395082270.9908242790164540.504587860491773
2730.3996087595248350.799217519049670.600391240475165
2740.3158040567155550.631608113431110.684195943284445
2750.2435705863863810.4871411727727620.756429413613619
2760.1665166390257960.3330332780515920.833483360974204
2770.1063360412607590.2126720825215180.893663958739241






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level10.00374531835205993OK
10% type I error level40.0149812734082397OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 1 & 0.00374531835205993 & OK \tabularnewline
10% type I error level & 4 & 0.0149812734082397 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184814&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]1[/C][C]0.00374531835205993[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]4[/C][C]0.0149812734082397[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184814&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184814&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level10.00374531835205993OK
10% type I error level40.0149812734082397OK


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 3
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Figure 4
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

Parameters (Session):
par1 = 7 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 7 ; par2 = Do not include Seasonal Dummies ; par3 = 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')
}