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Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 17 Dec 2014 11:11:31 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/17/t1418815271fbx11droytii5jo.htm/, Retrieved Thu, 31 Oct 2024 23:26:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270042, Retrieved Thu, 31 Oct 2024 23:26:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact112
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Multiple Regressi...] [2014-12-17 11:11:31] [9636d26fd774798d33054b538c301d75] [Current]
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Dataseries X:
12.9 1 11 8 7 18 12 20 4
12.2 1 19 18 20 23 20 19 4
12.8 1 16 12 9 22 14 18 5
7.4 1 24 24 19 22 25 24 4
6.7 1 15 16 12 19 15 20 4
12.6 1 17 19 16 25 20 20 9
14.8 1 19 16 17 28 21 24 8
13.3 1 19 15 9 16 15 21 11
11.1 1 28 28 28 28 28 28 4
8.2 1 26 21 20 21 11 10 4
11.4 1 15 18 16 22 22 22 6
6.4 1 26 22 22 24 22 19 4
10.6 1 16 19 17 24 27 27 8
12 1 24 22 12 26 24 23 4
6.3 1 25 25 18 28 23 24 4
11.3 0 22 20 20 24 24 24 11
11.9 1 15 16 12 20 21 25 4
9.3 1 21 19 16 26 20 24 4
9.6 0 22 18 16 21 19 21 6
10 1 27 26 21 28 25 28 6
6.4 1 26 24 15 27 16 28 4
13.8 1 26 20 17 23 24 22 8
10.8 1 22 19 17 24 21 26 5
13.8 1 21 19 17 24 22 26 4
11.7 1 22 23 18 22 25 21 9
10.9 1 20 18 15 21 23 26 4
16.1 0 21 16 20 25 20 23 7
13.4 0 20 18 13 20 21 20 10
9.9 1 22 21 21 21 22 24 4
11.5 1 21 20 12 26 25 25 4
8.3 1 8 15 6 23 23 24 7
11.7 1 22 19 13 21 19 20 12
9 1 20 19 19 27 21 24 7
9.7 1 24 7 12 25 19 25 5
10.8 1 17 20 14 23 25 23 8
10.3 1 20 20 13 25 16 21 5
10.4 1 23 19 12 23 24 23 4
12.7 0 20 19 17 19 24 21 9
9.3 1 22 20 19 22 18 18 7
11.8 1 19 18 10 24 28 24 4
5.9 1 15 14 10 19 15 18 4
11.4 1 20 17 11 21 17 21 4
13 1 22 17 11 27 18 23 4
10.8 1 17 8 10 25 26 25 4
12.3 0 14 9 7 25 18 22 7
11.3 1 24 22 22 23 22 22 4
11.8 1 17 20 12 17 19 23 7
7.9 0 23 20 18 28 17 24 4
12.7 1 25 22 20 25 26 25 4
12.3 0 16 22 9 20 21 22 4
11.6 0 18 22 16 25 26 24 4
6.7 0 20 16 14 21 21 21 8
10.9 1 18 14 11 24 12 24 4
12.1 0 23 24 20 28 20 25 4
13.3 1 24 21 17 20 20 23 4
10.1 1 23 20 14 19 24 27 4
5.7 0 13 20 8 24 24 27 7
14.3 1 20 18 16 21 22 23 12
8 0 20 14 11 24 21 18 4
13.3 0 19 19 10 23 20 20 4
9.3 1 22 24 15 18 23 23 4
12.5 1 22 19 15 27 19 24 5
7.6 1 15 16 10 25 24 26 15
15.9 1 17 16 10 20 21 20 5
9.2 1 19 16 18 21 16 23 10
9.1 0 20 14 10 23 17 22 9
11.1 1 22 22 22 27 23 23 8
13 1 21 21 16 24 20 17 4
14.5 1 21 15 10 27 19 20 5
12.2 0 16 14 7 24 18 22 4
12.3 1 20 15 16 23 18 18 9
11.4 1 21 14 16 24 21 19 4
8.8 0 20 20 16 21 20 19 10
14.6 0 23 21 22 23 17 16 4
12.6 1 18 14 5 27 25 26 4
13 1 16 16 10 25 17 25 7
12.6 0 17 13 8 19 17 23 5
13.2 1 24 26 16 24 24 18 4
9.9 0 13 13 8 25 21 22 4
7.7 1 19 18 16 23 22 26 4
10.5 0 20 15 14 23 18 25 4
13.4 0 22 18 15 25 22 26 4
10.9 0 19 21 9 26 20 26 4
4.3 0 21 17 21 26 21 24 6
10.3 0 15 18 7 16 21 22 10
11.8 0 21 20 17 23 20 21 7
11.2 0 24 18 18 26 18 22 4
11.4 0 22 25 16 25 25 28 4
8.6 0 20 20 16 23 23 22 7
13.2 0 21 19 14 26 21 26 4
12.6 0 19 18 15 22 20 20 8
5.6 0 14 12 8 20 21 24 11
9.9 0 25 22 22 27 20 21 6
8.8 0 11 16 5 20 22 23 14
7.7 0 17 18 13 22 15 23 5
9 0 22 23 22 24 24 23 4
7.3 0 20 20 18 21 22 22 8
11.4 0 22 20 15 24 21 23 9
13.6 0 15 16 11 26 17 21 4
7.9 0 23 22 19 24 23 27 4
10.7 0 20 19 19 24 22 23 5
10.3 0 22 23 21 27 23 26 4
8.3 0 16 6 4 25 16 27 5
9.6 0 25 19 17 27 18 27 4
14.2 0 18 24 10 19 25 23 4
8.5 0 19 19 13 22 18 23 7
13.5 0 25 15 15 22 14 23 10
4.9 0 21 18 11 25 20 28 4
6.4 0 22 18 20 23 19 24 5
9.6 0 21 22 13 24 18 20 4
11.6 0 22 23 18 24 22 23 4
11.1 0 23 18 20 23 21 22 4
4.35 1 20 17 15 22 14 15 6
12.7 1 6 6 4 24 5 27 4
18.1 1 15 22 9 19 25 23 8
17.85 1 18 20 18 25 21 23 5
16.6 0 24 16 12 26 11 20 4
12.6 0 22 16 17 18 20 18 17
17.1 1 21 17 12 24 9 22 4
19.1 1 23 20 16 28 15 20 4
16.1 1 20 23 17 23 23 21 8
13.35 1 20 18 14 19 21 25 4
18.4 1 18 13 13 19 9 19 7
14.7 1 25 22 20 27 24 25 4
10.6 1 16 20 16 24 16 24 4
12.6 1 20 20 15 26 20 22 5
16.2 1 14 13 10 21 15 28 7
13.6 1 22 16 16 25 18 22 4
18.9 0 26 25 21 28 22 21 4
14.1 1 20 16 15 19 21 23 7
14.5 1 17 15 16 20 21 19 11
16.15 1 22 19 19 26 21 21 7
14.75 1 22 19 9 27 20 25 4
14.8 1 20 24 19 23 24 23 4
12.45 1 17 9 7 18 15 28 4
12.65 1 22 22 23 23 24 14 4
17.35 1 17 15 14 21 18 23 4
8.6 1 22 22 10 23 24 24 4
18.4 1 21 22 16 22 24 25 6
16.1 1 25 24 12 21 15 15 8
11.6 0 11 12 10 14 19 23 23
17.75 1 19 21 7 24 20 26 4
15.25 1 24 25 20 26 26 21 8
17.65 1 17 26 9 24 26 26 6
16.35 1 22 21 12 22 23 23 4
17.65 1 17 14 10 20 13 15 7
13.6 1 26 28 19 20 16 16 4
14.35 1 20 21 11 18 22 20 4
14.75 1 19 16 15 18 21 20 4
18.25 1 21 16 14 25 11 21 10
9.9 1 24 25 11 28 23 28 6
16 1 21 21 14 23 18 19 5
18.25 1 19 22 15 20 19 21 5
16.85 1 13 9 7 22 15 22 4
14.6 0 24 20 22 27 8 27 4
13.85 0 28 19 19 24 15 20 5
18.95 1 27 24 22 23 21 17 5
15.6 1 22 22 11 20 25 26 5
14.85 0 23 22 19 22 14 21 5
11.75 0 19 12 9 21 21 24 4
18.45 0 18 17 11 24 18 21 6
15.9 0 23 18 17 26 18 25 4
17.1 1 21 10 12 24 12 22 4
16.1 1 22 22 17 18 24 17 4
19.9 0 17 24 10 17 17 14 9
10.95 0 15 18 17 23 20 23 18
18.45 0 21 18 13 21 24 28 6
15.1 0 20 23 11 21 22 24 5
15 0 26 21 19 24 15 22 4
11.35 0 19 21 21 22 22 24 11
15.95 0 28 28 24 24 26 25 4
18.1 0 21 17 13 24 17 21 10
14.6 0 19 21 16 24 23 22 6
15.4 1 22 21 13 23 19 16 8
15.4 1 21 20 15 21 21 18 8
17.6 0 20 18 15 24 23 27 6
13.35 1 19 17 11 19 19 17 8
19.1 1 11 7 7 19 18 25 4
15.35 0 17 17 13 23 16 24 4
7.6 1 19 14 13 25 23 21 9
13.4 0 20 18 12 24 13 21 9
13.9 0 17 14 8 21 18 19 5
19.1 1 21 23 7 18 23 27 4
15.25 0 21 20 17 23 21 28 4
12.9 0 12 14 9 20 23 19 15
16.1 0 23 17 18 23 16 23 10
17.35 0 22 21 17 23 17 25 9
13.15 0 22 23 17 23 20 26 7
12.15 0 21 24 18 23 18 25 9
12.6 0 20 21 12 27 20 25 6
10.35 0 18 14 14 19 19 24 4
15.4 0 21 24 22 25 26 24 7
9.6 0 24 16 19 25 9 24 4
18.2 0 22 21 21 21 23 22 7
13.6 0 20 8 10 25 9 21 4
14.85 0 17 17 16 17 13 17 15
14.75 1 19 18 11 22 27 23 4
14.1 0 16 17 15 23 22 17 9
14.9 0 19 16 12 27 12 25 4
16.25 0 23 22 21 27 18 19 4
19.25 1 8 17 22 5 6 8 28
13.6 0 22 21 20 19 17 14 4
13.6 1 23 20 15 24 22 22 4
15.65 0 15 20 9 23 22 25 4
12.75 1 17 19 15 28 23 28 5
14.6 0 21 8 14 25 19 25 4
9.85 1 25 19 11 27 20 24 4
12.65 0 18 11 9 16 17 15 12
19.2 0 20 13 12 25 24 24 4
16.6 0 21 18 11 26 20 28 6
11.2 0 21 19 14 24 18 24 6
15.25 1 24 23 10 23 23 25 5
11.9 1 22 20 18 24 27 23 4
13.2 0 22 22 11 27 25 26 4
16.35 1 23 19 14 25 24 26 4
12.4 1 17 16 16 19 12 22 10
15.85 0 15 11 11 19 16 25 7
18.15 1 22 21 16 24 24 22 4
11.15 0 19 14 13 20 23 26 7
15.65 0 18 21 12 21 24 20 4
17.75 1 21 20 17 28 24 26 4
7.65 0 20 21 23 26 26 26 12
12.35 1 19 20 14 19 19 21 5
15.6 1 19 19 10 23 28 21 8
19.3 1 16 19 16 23 23 24 6
15.2 0 18 18 11 21 21 21 17
17.1 1 23 20 16 26 19 18 4
15.6 0 22 21 19 25 23 23 5
18.4 1 23 22 17 25 23 26 4
19.05 1 20 19 12 24 20 23 5
18.55 1 24 23 17 23 18 25 5
19.1 1 25 16 11 22 20 20 6
13.1 0 25 23 19 27 28 25 4
12.85 1 20 18 12 26 21 26 4
9.5 1 23 23 8 23 25 19 4
4.5 1 21 20 17 22 18 21 6
11.85 0 23 20 13 26 24 23 8
13.6 1 23 23 17 22 28 24 10
11.7 1 11 13 7 17 9 6 4
12.4 0 21 21 23 25 22 22 5
13.35 1 27 26 18 22 26 21 4
11.4 0 19 18 13 28 28 28 4
14.9 0 21 19 17 22 18 24 4
19.9 0 16 18 13 21 23 14 16
11.2 0 21 18 8 24 15 20 7
14.6 0 22 19 16 26 24 28 4
17.6 1 16 13 14 26 12 19 4
14.05 1 18 10 13 24 12 24 14
16.1 1 23 21 19 27 20 21 5
13.35 1 24 24 15 22 25 21 5
11.85 1 20 21 15 23 24 26 5
11.95 1 20 23 8 22 23 24 5
14.75 0 18 18 14 23 18 26 7
15.15 0 4 11 7 15 20 25 19
13.2 1 14 16 11 20 22 23 16
16.85 0 22 20 17 22 20 24 4
7.85 0 17 20 19 25 25 24 4
7.7 1 23 26 17 27 28 26 7
12.6 0 20 21 12 24 25 23 9
7.85 0 18 12 12 21 14 20 5
10.95 0 19 15 18 17 16 16 14
12.35 0 20 18 16 26 24 24 4
9.95 0 15 14 15 20 13 20 16
14.9 0 24 18 20 22 19 23 10
16.65 0 21 16 16 24 18 23 5
13.4 0 19 19 12 23 16 18 6
13.95 0 19 7 10 22 8 21 4
15.7 0 27 21 28 28 27 25 4
16.85 0 23 24 19 21 23 23 4
10.95 0 23 21 18 24 20 26 5
15.35 0 20 20 19 28 20 26 4
12.2 0 17 22 8 25 26 24 4
15.1 0 21 17 17 24 23 23 5
17.75 0 23 19 16 24 24 21 4
15.2 0 22 20 18 21 21 23 4
14.6 1 16 16 12 20 15 20 5
16.65 0 20 20 17 26 22 23 8
8.1 0 16 16 13 16 25 24 15




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 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 & 10 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270042&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]10 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=270042&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270042&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 15.1593 + 0.345847groupN[t] + 0.0536449AMS.I1[t] + 0.0824024AMS.I2[t] -0.055485AMS.I3[t] -0.0563992AMS.E1[t] -0.0713734AMS.E2[t] -0.0635831AMS.E3[t] + 0.000195765AMS.A[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  15.1593 +  0.345847groupN[t] +  0.0536449AMS.I1[t] +  0.0824024AMS.I2[t] -0.055485AMS.I3[t] -0.0563992AMS.E1[t] -0.0713734AMS.E2[t] -0.0635831AMS.E3[t] +  0.000195765AMS.A[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270042&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  15.1593 +  0.345847groupN[t] +  0.0536449AMS.I1[t] +  0.0824024AMS.I2[t] -0.055485AMS.I3[t] -0.0563992AMS.E1[t] -0.0713734AMS.E2[t] -0.0635831AMS.E3[t] +  0.000195765AMS.A[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270042&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270042&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 15.1593 + 0.345847groupN[t] + 0.0536449AMS.I1[t] + 0.0824024AMS.I2[t] -0.055485AMS.I3[t] -0.0563992AMS.E1[t] -0.0713734AMS.E2[t] -0.0635831AMS.E3[t] + 0.000195765AMS.A[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.15932.407196.2971.22702e-096.13509e-10
groupN0.3458470.4205790.82230.4116280.205814
AMS.I10.05364490.08437310.63580.5254440.262722
AMS.I20.08240240.07227211.140.255230.127615
AMS.I3-0.0554850.06284-0.8830.3780480.189024
AMS.E1-0.05639920.0865466-0.65170.5151750.257587
AMS.E2-0.07137340.0590523-1.2090.2278590.11393
AMS.E3-0.06358310.0718879-0.88450.377230.188615
AMS.A0.0001957650.07196520.002720.9978320.498916

\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) & 15.1593 & 2.40719 & 6.297 & 1.22702e-09 & 6.13509e-10 \tabularnewline
groupN & 0.345847 & 0.420579 & 0.8223 & 0.411628 & 0.205814 \tabularnewline
AMS.I1 & 0.0536449 & 0.0843731 & 0.6358 & 0.525444 & 0.262722 \tabularnewline
AMS.I2 & 0.0824024 & 0.0722721 & 1.14 & 0.25523 & 0.127615 \tabularnewline
AMS.I3 & -0.055485 & 0.06284 & -0.883 & 0.378048 & 0.189024 \tabularnewline
AMS.E1 & -0.0563992 & 0.0865466 & -0.6517 & 0.515175 & 0.257587 \tabularnewline
AMS.E2 & -0.0713734 & 0.0590523 & -1.209 & 0.227859 & 0.11393 \tabularnewline
AMS.E3 & -0.0635831 & 0.0718879 & -0.8845 & 0.37723 & 0.188615 \tabularnewline
AMS.A & 0.000195765 & 0.0719652 & 0.00272 & 0.997832 & 0.498916 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270042&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]15.1593[/C][C]2.40719[/C][C]6.297[/C][C]1.22702e-09[/C][C]6.13509e-10[/C][/ROW]
[ROW][C]groupN[/C][C]0.345847[/C][C]0.420579[/C][C]0.8223[/C][C]0.411628[/C][C]0.205814[/C][/ROW]
[ROW][C]AMS.I1[/C][C]0.0536449[/C][C]0.0843731[/C][C]0.6358[/C][C]0.525444[/C][C]0.262722[/C][/ROW]
[ROW][C]AMS.I2[/C][C]0.0824024[/C][C]0.0722721[/C][C]1.14[/C][C]0.25523[/C][C]0.127615[/C][/ROW]
[ROW][C]AMS.I3[/C][C]-0.055485[/C][C]0.06284[/C][C]-0.883[/C][C]0.378048[/C][C]0.189024[/C][/ROW]
[ROW][C]AMS.E1[/C][C]-0.0563992[/C][C]0.0865466[/C][C]-0.6517[/C][C]0.515175[/C][C]0.257587[/C][/ROW]
[ROW][C]AMS.E2[/C][C]-0.0713734[/C][C]0.0590523[/C][C]-1.209[/C][C]0.227859[/C][C]0.11393[/C][/ROW]
[ROW][C]AMS.E3[/C][C]-0.0635831[/C][C]0.0718879[/C][C]-0.8845[/C][C]0.37723[/C][C]0.188615[/C][/ROW]
[ROW][C]AMS.A[/C][C]0.000195765[/C][C]0.0719652[/C][C]0.00272[/C][C]0.997832[/C][C]0.498916[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270042&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270042&T=2

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.15932.407196.2971.22702e-096.13509e-10
groupN0.3458470.4205790.82230.4116280.205814
AMS.I10.05364490.08437310.63580.5254440.262722
AMS.I20.08240240.07227211.140.255230.127615
AMS.I3-0.0554850.06284-0.8830.3780480.189024
AMS.E1-0.05639920.0865466-0.65170.5151750.257587
AMS.E2-0.07137340.0590523-1.2090.2278590.11393
AMS.E3-0.06358310.0718879-0.88450.377230.188615
AMS.A0.0001957650.07196520.002720.9978320.498916







Multiple Linear Regression - Regression Statistics
Multiple R0.166218
R-squared0.0276285
Adjusted R-squared-0.00128961
F-TEST (value)0.955405
F-TEST (DF numerator)8
F-TEST (DF denominator)269
p-value0.471414
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.39655
Sum Squared Residuals3103.33

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.166218 \tabularnewline
R-squared & 0.0276285 \tabularnewline
Adjusted R-squared & -0.00128961 \tabularnewline
F-TEST (value) & 0.955405 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 269 \tabularnewline
p-value & 0.471414 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.39655 \tabularnewline
Sum Squared Residuals & 3103.33 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270042&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.166218[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0276285[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]-0.00128961[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]0.955405[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]269[/C][/ROW]
[ROW][C]p-value[/C][C]0.471414[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.39655[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3103.33[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270042&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270042&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.166218
R-squared0.0276285
Adjusted R-squared-0.00128961
F-TEST (value)0.955405
F-TEST (DF numerator)8
F-TEST (DF denominator)269
p-value0.471414
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.39655
Sum Squared Residuals3103.33







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.2235-0.323488
212.212.966-0.765966
312.813.4694-0.66937
47.413.1657-5.76571
56.713.5493-6.84934
612.612.9876-0.387616
714.812.29712.50289
813.313.955-0.654959
911.112.4037-1.30368
108.214.9161-6.71609
1111.412.6966-1.29662
126.413.361-6.96097
1310.611.99-1.38999
141213.2987-1.29866
156.313.1616-6.86159
1611.312.2874-0.98742
1711.912.7468-0.846787
189.312.8905-3.59048
199.613.0604-3.46039
201012.7881-2.78814
216.413.601-7.20097
2213.813.19730.60272
2310.812.8031-2.0031
2413.812.67791.12211
2511.713.2232-1.52323
2610.912.7506-1.85063
2716.112.19613.90394
2813.413.09760.302426
299.912.9708-3.07076
3011.512.7744-1.27438
318.312.374-4.07401
3211.713.7199-2.01985
33912.5432-3.5432
349.712.3489-2.64892
3510.812.746-1.94597
3610.313.6185-3.31854
3710.413.167-2.767
3812.712.7365-0.0365364
399.313.6105-4.31051
4011.812.5755-0.775514
415.913.6227-7.72267
4211.413.6363-2.23633
431313.2067-0.206681
4410.811.667-0.866964
4512.312.17140.128636
4611.313.1193-1.81933
4711.813.6234-1.82338
487.912.7247-4.82468
4912.712.69490.005093
5012.313.3062-1.0062
5111.612.2591-0.659069
526.712.7569-6.05691
5310.913.2787-2.37875
5412.112.6656-0.565618
5513.313.5627-0.262718
5610.113.1097-3.0097
575.712.2789-6.5789
5814.312.95881.34116
59812.7793-4.77933
6013.313.19380.106212
619.313.7123-4.41228
6212.513.0148-0.514785
637.612.3002-4.70021
6415.913.28322.61684
659.213.0573-3.85727
669.112.9234-3.82335
6711.112.6523-1.55227
681313.6132-0.61317
6914.513.16331.33671
7012.212.7465-0.546477
7112.313.2017-0.901652
7211.412.8378-1.43781
738.813.1745-4.37448
7414.613.37581.2242
7512.612.38740.212559
761312.91550.0845132
7712.612.9522-0.352217
7813.213.837-0.637039
799.912.1771-2.27714
807.712.6001-4.90008
8110.512.5207-2.02071
8213.412.35791.04215
8310.912.8634-1.96338
844.312.0314-7.73143
8510.313.2607-2.96069
8611.812.9321-1.13209
8711.212.7821-1.58211
8811.412.5379-1.1379
898.612.6562-4.05623
9013.212.45710.742932
9112.612.8911-0.291143
925.612.3046-6.70458
939.912.8083-2.90826
948.812.6325-3.83251
957.713.0604-5.36035
96912.4859-3.48587
977.312.7296-5.42962
9811.412.8422-1.44216
9913.612.65790.942145
1007.912.4406-4.54061
10110.712.3584-1.65837
10210.312.2528-1.95278
1038.312.0223-3.72234
1049.612.5993-2.99933
10514.213.23010.969865
1068.513.0363-4.53632
10713.513.20370.296312
1084.912.5417-7.64173
1096.412.5347-6.13471
1109.613.4682-3.86818
11111.612.8506-1.25056
11211.112.5726-1.47258
1134.3513.954-9.604
11412.712.67310.026949
11518.113.30654.79349
11617.8512.74985.10021
11716.613.5773.023
11812.613.1308-0.530827
11917.113.97273.12731
12019.113.57865.52142
12116.113.25762.84243
12213.3513.12520.224755
12318.413.94.5
12414.712.72491.97514
12510.613.103-2.50295
12612.613.1021-0.502089
12716.212.73863.46142
12813.613.02320.576765
12918.912.96515.93494
13014.113.03271.06729
13114.512.93261.5674
13216.1512.89763.25236
13314.7513.21251.53746
13414.813.02971.77032
13512.4512.905-0.454975
13612.6513.3225-0.672477
13717.3512.94564.40441
1388.613.408-4.80795
13918.413.01465.3854
14016.114.95091.14909
14111.612.5797-0.979748
14217.7513.4334.317
14315.2513.08722.16281
14417.6513.19894.4511
14516.3513.40592.94407
14617.6514.00763.64235
14713.614.8664-1.26643
14814.3513.84180.508151
14914.7513.22561.52437
15018.2513.64494.60507
1519.913.2424-3.3424
1521613.79632.20368
15318.2513.68664.5634
15416.8512.84634.0037
15514.613.06441.5356
15613.8513.47790.37211
15718.9513.83465.11544
15815.613.32332.27668
15914.8513.57751.27254
16011.7512.4595-0.709549
16118.4512.9435.50699
16215.912.59323.3068
16317.113.18183.91824
16416.113.74662.35337
16519.914.43355.4665
16610.9512.3204-1.3704
16718.4512.37136.07875
16815.113.23751.86253
1691513.4081.59196
17011.3512.4089-1.05895
17115.9512.83893.11113
17218.113.06515.03487
17314.612.62841.97161
17415.414.02541.37459
17515.413.62131.77872
17617.612.17245.4276
17713.3513.8078-0.457848
17819.112.33856.76147
17915.3512.78642.5636
1807.612.5716-4.97165
18113.413.4347-0.0346707
18213.913.10480.79522
18319.113.76585.33422
18415.2512.4152.83495
18512.912.48260.41744
18616.112.89563.2044
18717.3513.02834.32168
18813.1512.9150.234974
18912.1513.095-0.94502
19012.612.7581-0.158147
19110.3512.5488-2.19883
19215.412.25253.14751
1939.613.1334-3.53342
19418.212.68135.51871
19513.612.94970.650267
19614.8513.61971.2303
19714.7512.76781.98222
19814.112.63961.4604
19914.912.86312.03691
20016.2513.0263.22403
20119.2514.9014.34897
20213.613.7859-0.185893
20313.613.23290.36712
20415.6512.65642.99357
20512.7512.15030.599665
20614.611.81342.78663
2079.8513.3261-3.47609
20812.6513.4648-0.814805
20919.211.98947.21058
21016.612.48574.11428
21111.212.9115-1.71154
21215.2513.60561.64437
21311.912.5923-0.69233
21413.212.58250.617518
21516.3512.75253.59752
21612.413.5228-1.12282
21715.8512.45833.39173
21818.1513.06345.08659
21911.1512.1895-1.03949
22015.6513.02132.62872
22117.7512.39195.35806
2227.6511.7136-4.06356
22312.3513.6337-1.28368
22415.612.90582.69415
22519.312.57776.72227
22615.212.98262.21736
22717.113.5333.56695
22815.612.50273.09731
22918.412.90465.49539
23019.0513.23545.81464
23118.5513.57414.9759
23219.113.61565.4844
23313.112.23140.868598
23412.8512.77780.0721622
2359.513.9015-4.40151
2364.513.4769-8.97689
23711.8512.6797-0.829657
23813.612.92770.672317
23911.714.7962-3.09618
24012.412.36210.0379385
24113.3513.6663-0.316306
24211.411.5833-0.183282
24314.912.85752.0425
24419.913.06656.83348
24511.213.6307-2.4307
24614.612.05852.54154
24717.613.12774.47228
24814.0512.84011.20987
24916.113.13072.96933
25013.3513.5786-0.228591
25111.8512.8139-0.963863
25211.9513.622-1.672
25314.7512.59762.15236
25415.1512.03263.11744
25513.212.80680.393231
25616.8512.85083.9992
2577.8511.9455-4.09554
2587.712.7651-5.06514
25912.612.6982-0.0982305
2607.8512.9936-5.14359
26110.9513.3005-2.35048
26212.3512.12310.226904
2639.9512.9609-3.01093
26414.912.7632.13704
26516.6512.61684.03325
26613.413.4959-0.095869
26713.9513.05430.895744
26815.711.68954.0105
26916.8513.02893.82106
27010.9512.6916-1.74159
27115.3512.1673.18302
27212.212.6493-0.449304
27315.112.28682.8132
27417.7512.675.08002
27515.212.84392.35608
27614.613.54681.05322
27716.6512.43954.21047
2788.112.4049-4.30494

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.2235 & -0.323488 \tabularnewline
2 & 12.2 & 12.966 & -0.765966 \tabularnewline
3 & 12.8 & 13.4694 & -0.66937 \tabularnewline
4 & 7.4 & 13.1657 & -5.76571 \tabularnewline
5 & 6.7 & 13.5493 & -6.84934 \tabularnewline
6 & 12.6 & 12.9876 & -0.387616 \tabularnewline
7 & 14.8 & 12.2971 & 2.50289 \tabularnewline
8 & 13.3 & 13.955 & -0.654959 \tabularnewline
9 & 11.1 & 12.4037 & -1.30368 \tabularnewline
10 & 8.2 & 14.9161 & -6.71609 \tabularnewline
11 & 11.4 & 12.6966 & -1.29662 \tabularnewline
12 & 6.4 & 13.361 & -6.96097 \tabularnewline
13 & 10.6 & 11.99 & -1.38999 \tabularnewline
14 & 12 & 13.2987 & -1.29866 \tabularnewline
15 & 6.3 & 13.1616 & -6.86159 \tabularnewline
16 & 11.3 & 12.2874 & -0.98742 \tabularnewline
17 & 11.9 & 12.7468 & -0.846787 \tabularnewline
18 & 9.3 & 12.8905 & -3.59048 \tabularnewline
19 & 9.6 & 13.0604 & -3.46039 \tabularnewline
20 & 10 & 12.7881 & -2.78814 \tabularnewline
21 & 6.4 & 13.601 & -7.20097 \tabularnewline
22 & 13.8 & 13.1973 & 0.60272 \tabularnewline
23 & 10.8 & 12.8031 & -2.0031 \tabularnewline
24 & 13.8 & 12.6779 & 1.12211 \tabularnewline
25 & 11.7 & 13.2232 & -1.52323 \tabularnewline
26 & 10.9 & 12.7506 & -1.85063 \tabularnewline
27 & 16.1 & 12.1961 & 3.90394 \tabularnewline
28 & 13.4 & 13.0976 & 0.302426 \tabularnewline
29 & 9.9 & 12.9708 & -3.07076 \tabularnewline
30 & 11.5 & 12.7744 & -1.27438 \tabularnewline
31 & 8.3 & 12.374 & -4.07401 \tabularnewline
32 & 11.7 & 13.7199 & -2.01985 \tabularnewline
33 & 9 & 12.5432 & -3.5432 \tabularnewline
34 & 9.7 & 12.3489 & -2.64892 \tabularnewline
35 & 10.8 & 12.746 & -1.94597 \tabularnewline
36 & 10.3 & 13.6185 & -3.31854 \tabularnewline
37 & 10.4 & 13.167 & -2.767 \tabularnewline
38 & 12.7 & 12.7365 & -0.0365364 \tabularnewline
39 & 9.3 & 13.6105 & -4.31051 \tabularnewline
40 & 11.8 & 12.5755 & -0.775514 \tabularnewline
41 & 5.9 & 13.6227 & -7.72267 \tabularnewline
42 & 11.4 & 13.6363 & -2.23633 \tabularnewline
43 & 13 & 13.2067 & -0.206681 \tabularnewline
44 & 10.8 & 11.667 & -0.866964 \tabularnewline
45 & 12.3 & 12.1714 & 0.128636 \tabularnewline
46 & 11.3 & 13.1193 & -1.81933 \tabularnewline
47 & 11.8 & 13.6234 & -1.82338 \tabularnewline
48 & 7.9 & 12.7247 & -4.82468 \tabularnewline
49 & 12.7 & 12.6949 & 0.005093 \tabularnewline
50 & 12.3 & 13.3062 & -1.0062 \tabularnewline
51 & 11.6 & 12.2591 & -0.659069 \tabularnewline
52 & 6.7 & 12.7569 & -6.05691 \tabularnewline
53 & 10.9 & 13.2787 & -2.37875 \tabularnewline
54 & 12.1 & 12.6656 & -0.565618 \tabularnewline
55 & 13.3 & 13.5627 & -0.262718 \tabularnewline
56 & 10.1 & 13.1097 & -3.0097 \tabularnewline
57 & 5.7 & 12.2789 & -6.5789 \tabularnewline
58 & 14.3 & 12.9588 & 1.34116 \tabularnewline
59 & 8 & 12.7793 & -4.77933 \tabularnewline
60 & 13.3 & 13.1938 & 0.106212 \tabularnewline
61 & 9.3 & 13.7123 & -4.41228 \tabularnewline
62 & 12.5 & 13.0148 & -0.514785 \tabularnewline
63 & 7.6 & 12.3002 & -4.70021 \tabularnewline
64 & 15.9 & 13.2832 & 2.61684 \tabularnewline
65 & 9.2 & 13.0573 & -3.85727 \tabularnewline
66 & 9.1 & 12.9234 & -3.82335 \tabularnewline
67 & 11.1 & 12.6523 & -1.55227 \tabularnewline
68 & 13 & 13.6132 & -0.61317 \tabularnewline
69 & 14.5 & 13.1633 & 1.33671 \tabularnewline
70 & 12.2 & 12.7465 & -0.546477 \tabularnewline
71 & 12.3 & 13.2017 & -0.901652 \tabularnewline
72 & 11.4 & 12.8378 & -1.43781 \tabularnewline
73 & 8.8 & 13.1745 & -4.37448 \tabularnewline
74 & 14.6 & 13.3758 & 1.2242 \tabularnewline
75 & 12.6 & 12.3874 & 0.212559 \tabularnewline
76 & 13 & 12.9155 & 0.0845132 \tabularnewline
77 & 12.6 & 12.9522 & -0.352217 \tabularnewline
78 & 13.2 & 13.837 & -0.637039 \tabularnewline
79 & 9.9 & 12.1771 & -2.27714 \tabularnewline
80 & 7.7 & 12.6001 & -4.90008 \tabularnewline
81 & 10.5 & 12.5207 & -2.02071 \tabularnewline
82 & 13.4 & 12.3579 & 1.04215 \tabularnewline
83 & 10.9 & 12.8634 & -1.96338 \tabularnewline
84 & 4.3 & 12.0314 & -7.73143 \tabularnewline
85 & 10.3 & 13.2607 & -2.96069 \tabularnewline
86 & 11.8 & 12.9321 & -1.13209 \tabularnewline
87 & 11.2 & 12.7821 & -1.58211 \tabularnewline
88 & 11.4 & 12.5379 & -1.1379 \tabularnewline
89 & 8.6 & 12.6562 & -4.05623 \tabularnewline
90 & 13.2 & 12.4571 & 0.742932 \tabularnewline
91 & 12.6 & 12.8911 & -0.291143 \tabularnewline
92 & 5.6 & 12.3046 & -6.70458 \tabularnewline
93 & 9.9 & 12.8083 & -2.90826 \tabularnewline
94 & 8.8 & 12.6325 & -3.83251 \tabularnewline
95 & 7.7 & 13.0604 & -5.36035 \tabularnewline
96 & 9 & 12.4859 & -3.48587 \tabularnewline
97 & 7.3 & 12.7296 & -5.42962 \tabularnewline
98 & 11.4 & 12.8422 & -1.44216 \tabularnewline
99 & 13.6 & 12.6579 & 0.942145 \tabularnewline
100 & 7.9 & 12.4406 & -4.54061 \tabularnewline
101 & 10.7 & 12.3584 & -1.65837 \tabularnewline
102 & 10.3 & 12.2528 & -1.95278 \tabularnewline
103 & 8.3 & 12.0223 & -3.72234 \tabularnewline
104 & 9.6 & 12.5993 & -2.99933 \tabularnewline
105 & 14.2 & 13.2301 & 0.969865 \tabularnewline
106 & 8.5 & 13.0363 & -4.53632 \tabularnewline
107 & 13.5 & 13.2037 & 0.296312 \tabularnewline
108 & 4.9 & 12.5417 & -7.64173 \tabularnewline
109 & 6.4 & 12.5347 & -6.13471 \tabularnewline
110 & 9.6 & 13.4682 & -3.86818 \tabularnewline
111 & 11.6 & 12.8506 & -1.25056 \tabularnewline
112 & 11.1 & 12.5726 & -1.47258 \tabularnewline
113 & 4.35 & 13.954 & -9.604 \tabularnewline
114 & 12.7 & 12.6731 & 0.026949 \tabularnewline
115 & 18.1 & 13.3065 & 4.79349 \tabularnewline
116 & 17.85 & 12.7498 & 5.10021 \tabularnewline
117 & 16.6 & 13.577 & 3.023 \tabularnewline
118 & 12.6 & 13.1308 & -0.530827 \tabularnewline
119 & 17.1 & 13.9727 & 3.12731 \tabularnewline
120 & 19.1 & 13.5786 & 5.52142 \tabularnewline
121 & 16.1 & 13.2576 & 2.84243 \tabularnewline
122 & 13.35 & 13.1252 & 0.224755 \tabularnewline
123 & 18.4 & 13.9 & 4.5 \tabularnewline
124 & 14.7 & 12.7249 & 1.97514 \tabularnewline
125 & 10.6 & 13.103 & -2.50295 \tabularnewline
126 & 12.6 & 13.1021 & -0.502089 \tabularnewline
127 & 16.2 & 12.7386 & 3.46142 \tabularnewline
128 & 13.6 & 13.0232 & 0.576765 \tabularnewline
129 & 18.9 & 12.9651 & 5.93494 \tabularnewline
130 & 14.1 & 13.0327 & 1.06729 \tabularnewline
131 & 14.5 & 12.9326 & 1.5674 \tabularnewline
132 & 16.15 & 12.8976 & 3.25236 \tabularnewline
133 & 14.75 & 13.2125 & 1.53746 \tabularnewline
134 & 14.8 & 13.0297 & 1.77032 \tabularnewline
135 & 12.45 & 12.905 & -0.454975 \tabularnewline
136 & 12.65 & 13.3225 & -0.672477 \tabularnewline
137 & 17.35 & 12.9456 & 4.40441 \tabularnewline
138 & 8.6 & 13.408 & -4.80795 \tabularnewline
139 & 18.4 & 13.0146 & 5.3854 \tabularnewline
140 & 16.1 & 14.9509 & 1.14909 \tabularnewline
141 & 11.6 & 12.5797 & -0.979748 \tabularnewline
142 & 17.75 & 13.433 & 4.317 \tabularnewline
143 & 15.25 & 13.0872 & 2.16281 \tabularnewline
144 & 17.65 & 13.1989 & 4.4511 \tabularnewline
145 & 16.35 & 13.4059 & 2.94407 \tabularnewline
146 & 17.65 & 14.0076 & 3.64235 \tabularnewline
147 & 13.6 & 14.8664 & -1.26643 \tabularnewline
148 & 14.35 & 13.8418 & 0.508151 \tabularnewline
149 & 14.75 & 13.2256 & 1.52437 \tabularnewline
150 & 18.25 & 13.6449 & 4.60507 \tabularnewline
151 & 9.9 & 13.2424 & -3.3424 \tabularnewline
152 & 16 & 13.7963 & 2.20368 \tabularnewline
153 & 18.25 & 13.6866 & 4.5634 \tabularnewline
154 & 16.85 & 12.8463 & 4.0037 \tabularnewline
155 & 14.6 & 13.0644 & 1.5356 \tabularnewline
156 & 13.85 & 13.4779 & 0.37211 \tabularnewline
157 & 18.95 & 13.8346 & 5.11544 \tabularnewline
158 & 15.6 & 13.3233 & 2.27668 \tabularnewline
159 & 14.85 & 13.5775 & 1.27254 \tabularnewline
160 & 11.75 & 12.4595 & -0.709549 \tabularnewline
161 & 18.45 & 12.943 & 5.50699 \tabularnewline
162 & 15.9 & 12.5932 & 3.3068 \tabularnewline
163 & 17.1 & 13.1818 & 3.91824 \tabularnewline
164 & 16.1 & 13.7466 & 2.35337 \tabularnewline
165 & 19.9 & 14.4335 & 5.4665 \tabularnewline
166 & 10.95 & 12.3204 & -1.3704 \tabularnewline
167 & 18.45 & 12.3713 & 6.07875 \tabularnewline
168 & 15.1 & 13.2375 & 1.86253 \tabularnewline
169 & 15 & 13.408 & 1.59196 \tabularnewline
170 & 11.35 & 12.4089 & -1.05895 \tabularnewline
171 & 15.95 & 12.8389 & 3.11113 \tabularnewline
172 & 18.1 & 13.0651 & 5.03487 \tabularnewline
173 & 14.6 & 12.6284 & 1.97161 \tabularnewline
174 & 15.4 & 14.0254 & 1.37459 \tabularnewline
175 & 15.4 & 13.6213 & 1.77872 \tabularnewline
176 & 17.6 & 12.1724 & 5.4276 \tabularnewline
177 & 13.35 & 13.8078 & -0.457848 \tabularnewline
178 & 19.1 & 12.3385 & 6.76147 \tabularnewline
179 & 15.35 & 12.7864 & 2.5636 \tabularnewline
180 & 7.6 & 12.5716 & -4.97165 \tabularnewline
181 & 13.4 & 13.4347 & -0.0346707 \tabularnewline
182 & 13.9 & 13.1048 & 0.79522 \tabularnewline
183 & 19.1 & 13.7658 & 5.33422 \tabularnewline
184 & 15.25 & 12.415 & 2.83495 \tabularnewline
185 & 12.9 & 12.4826 & 0.41744 \tabularnewline
186 & 16.1 & 12.8956 & 3.2044 \tabularnewline
187 & 17.35 & 13.0283 & 4.32168 \tabularnewline
188 & 13.15 & 12.915 & 0.234974 \tabularnewline
189 & 12.15 & 13.095 & -0.94502 \tabularnewline
190 & 12.6 & 12.7581 & -0.158147 \tabularnewline
191 & 10.35 & 12.5488 & -2.19883 \tabularnewline
192 & 15.4 & 12.2525 & 3.14751 \tabularnewline
193 & 9.6 & 13.1334 & -3.53342 \tabularnewline
194 & 18.2 & 12.6813 & 5.51871 \tabularnewline
195 & 13.6 & 12.9497 & 0.650267 \tabularnewline
196 & 14.85 & 13.6197 & 1.2303 \tabularnewline
197 & 14.75 & 12.7678 & 1.98222 \tabularnewline
198 & 14.1 & 12.6396 & 1.4604 \tabularnewline
199 & 14.9 & 12.8631 & 2.03691 \tabularnewline
200 & 16.25 & 13.026 & 3.22403 \tabularnewline
201 & 19.25 & 14.901 & 4.34897 \tabularnewline
202 & 13.6 & 13.7859 & -0.185893 \tabularnewline
203 & 13.6 & 13.2329 & 0.36712 \tabularnewline
204 & 15.65 & 12.6564 & 2.99357 \tabularnewline
205 & 12.75 & 12.1503 & 0.599665 \tabularnewline
206 & 14.6 & 11.8134 & 2.78663 \tabularnewline
207 & 9.85 & 13.3261 & -3.47609 \tabularnewline
208 & 12.65 & 13.4648 & -0.814805 \tabularnewline
209 & 19.2 & 11.9894 & 7.21058 \tabularnewline
210 & 16.6 & 12.4857 & 4.11428 \tabularnewline
211 & 11.2 & 12.9115 & -1.71154 \tabularnewline
212 & 15.25 & 13.6056 & 1.64437 \tabularnewline
213 & 11.9 & 12.5923 & -0.69233 \tabularnewline
214 & 13.2 & 12.5825 & 0.617518 \tabularnewline
215 & 16.35 & 12.7525 & 3.59752 \tabularnewline
216 & 12.4 & 13.5228 & -1.12282 \tabularnewline
217 & 15.85 & 12.4583 & 3.39173 \tabularnewline
218 & 18.15 & 13.0634 & 5.08659 \tabularnewline
219 & 11.15 & 12.1895 & -1.03949 \tabularnewline
220 & 15.65 & 13.0213 & 2.62872 \tabularnewline
221 & 17.75 & 12.3919 & 5.35806 \tabularnewline
222 & 7.65 & 11.7136 & -4.06356 \tabularnewline
223 & 12.35 & 13.6337 & -1.28368 \tabularnewline
224 & 15.6 & 12.9058 & 2.69415 \tabularnewline
225 & 19.3 & 12.5777 & 6.72227 \tabularnewline
226 & 15.2 & 12.9826 & 2.21736 \tabularnewline
227 & 17.1 & 13.533 & 3.56695 \tabularnewline
228 & 15.6 & 12.5027 & 3.09731 \tabularnewline
229 & 18.4 & 12.9046 & 5.49539 \tabularnewline
230 & 19.05 & 13.2354 & 5.81464 \tabularnewline
231 & 18.55 & 13.5741 & 4.9759 \tabularnewline
232 & 19.1 & 13.6156 & 5.4844 \tabularnewline
233 & 13.1 & 12.2314 & 0.868598 \tabularnewline
234 & 12.85 & 12.7778 & 0.0721622 \tabularnewline
235 & 9.5 & 13.9015 & -4.40151 \tabularnewline
236 & 4.5 & 13.4769 & -8.97689 \tabularnewline
237 & 11.85 & 12.6797 & -0.829657 \tabularnewline
238 & 13.6 & 12.9277 & 0.672317 \tabularnewline
239 & 11.7 & 14.7962 & -3.09618 \tabularnewline
240 & 12.4 & 12.3621 & 0.0379385 \tabularnewline
241 & 13.35 & 13.6663 & -0.316306 \tabularnewline
242 & 11.4 & 11.5833 & -0.183282 \tabularnewline
243 & 14.9 & 12.8575 & 2.0425 \tabularnewline
244 & 19.9 & 13.0665 & 6.83348 \tabularnewline
245 & 11.2 & 13.6307 & -2.4307 \tabularnewline
246 & 14.6 & 12.0585 & 2.54154 \tabularnewline
247 & 17.6 & 13.1277 & 4.47228 \tabularnewline
248 & 14.05 & 12.8401 & 1.20987 \tabularnewline
249 & 16.1 & 13.1307 & 2.96933 \tabularnewline
250 & 13.35 & 13.5786 & -0.228591 \tabularnewline
251 & 11.85 & 12.8139 & -0.963863 \tabularnewline
252 & 11.95 & 13.622 & -1.672 \tabularnewline
253 & 14.75 & 12.5976 & 2.15236 \tabularnewline
254 & 15.15 & 12.0326 & 3.11744 \tabularnewline
255 & 13.2 & 12.8068 & 0.393231 \tabularnewline
256 & 16.85 & 12.8508 & 3.9992 \tabularnewline
257 & 7.85 & 11.9455 & -4.09554 \tabularnewline
258 & 7.7 & 12.7651 & -5.06514 \tabularnewline
259 & 12.6 & 12.6982 & -0.0982305 \tabularnewline
260 & 7.85 & 12.9936 & -5.14359 \tabularnewline
261 & 10.95 & 13.3005 & -2.35048 \tabularnewline
262 & 12.35 & 12.1231 & 0.226904 \tabularnewline
263 & 9.95 & 12.9609 & -3.01093 \tabularnewline
264 & 14.9 & 12.763 & 2.13704 \tabularnewline
265 & 16.65 & 12.6168 & 4.03325 \tabularnewline
266 & 13.4 & 13.4959 & -0.095869 \tabularnewline
267 & 13.95 & 13.0543 & 0.895744 \tabularnewline
268 & 15.7 & 11.6895 & 4.0105 \tabularnewline
269 & 16.85 & 13.0289 & 3.82106 \tabularnewline
270 & 10.95 & 12.6916 & -1.74159 \tabularnewline
271 & 15.35 & 12.167 & 3.18302 \tabularnewline
272 & 12.2 & 12.6493 & -0.449304 \tabularnewline
273 & 15.1 & 12.2868 & 2.8132 \tabularnewline
274 & 17.75 & 12.67 & 5.08002 \tabularnewline
275 & 15.2 & 12.8439 & 2.35608 \tabularnewline
276 & 14.6 & 13.5468 & 1.05322 \tabularnewline
277 & 16.65 & 12.4395 & 4.21047 \tabularnewline
278 & 8.1 & 12.4049 & -4.30494 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270042&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]13.2235[/C][C]-0.323488[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]12.966[/C][C]-0.765966[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]13.4694[/C][C]-0.66937[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]13.1657[/C][C]-5.76571[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]13.5493[/C][C]-6.84934[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]12.9876[/C][C]-0.387616[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.2971[/C][C]2.50289[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]13.955[/C][C]-0.654959[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.4037[/C][C]-1.30368[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.9161[/C][C]-6.71609[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]12.6966[/C][C]-1.29662[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]13.361[/C][C]-6.96097[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]11.99[/C][C]-1.38999[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.2987[/C][C]-1.29866[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]13.1616[/C][C]-6.86159[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]12.2874[/C][C]-0.98742[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]12.7468[/C][C]-0.846787[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.8905[/C][C]-3.59048[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]13.0604[/C][C]-3.46039[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]12.7881[/C][C]-2.78814[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]13.601[/C][C]-7.20097[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]13.1973[/C][C]0.60272[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]12.8031[/C][C]-2.0031[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.6779[/C][C]1.12211[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]13.2232[/C][C]-1.52323[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.7506[/C][C]-1.85063[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]12.1961[/C][C]3.90394[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]13.0976[/C][C]0.302426[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]12.9708[/C][C]-3.07076[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]12.7744[/C][C]-1.27438[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]12.374[/C][C]-4.07401[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.7199[/C][C]-2.01985[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.5432[/C][C]-3.5432[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]12.3489[/C][C]-2.64892[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.746[/C][C]-1.94597[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]13.6185[/C][C]-3.31854[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]13.167[/C][C]-2.767[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.7365[/C][C]-0.0365364[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]13.6105[/C][C]-4.31051[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.5755[/C][C]-0.775514[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]13.6227[/C][C]-7.72267[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.6363[/C][C]-2.23633[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]13.2067[/C][C]-0.206681[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]11.667[/C][C]-0.866964[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]12.1714[/C][C]0.128636[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.1193[/C][C]-1.81933[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]13.6234[/C][C]-1.82338[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]12.7247[/C][C]-4.82468[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]12.6949[/C][C]0.005093[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]13.3062[/C][C]-1.0062[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]12.2591[/C][C]-0.659069[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]12.7569[/C][C]-6.05691[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.2787[/C][C]-2.37875[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.6656[/C][C]-0.565618[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.5627[/C][C]-0.262718[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.1097[/C][C]-3.0097[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]12.2789[/C][C]-6.5789[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.9588[/C][C]1.34116[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]12.7793[/C][C]-4.77933[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]13.1938[/C][C]0.106212[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]13.7123[/C][C]-4.41228[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]13.0148[/C][C]-0.514785[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]12.3002[/C][C]-4.70021[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.2832[/C][C]2.61684[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.0573[/C][C]-3.85727[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]12.9234[/C][C]-3.82335[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.6523[/C][C]-1.55227[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.6132[/C][C]-0.61317[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]13.1633[/C][C]1.33671[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.7465[/C][C]-0.546477[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.2017[/C][C]-0.901652[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]12.8378[/C][C]-1.43781[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]13.1745[/C][C]-4.37448[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]13.3758[/C][C]1.2242[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]12.3874[/C][C]0.212559[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]12.9155[/C][C]0.0845132[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]12.9522[/C][C]-0.352217[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]13.837[/C][C]-0.637039[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]12.1771[/C][C]-2.27714[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]12.6001[/C][C]-4.90008[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]12.5207[/C][C]-2.02071[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]12.3579[/C][C]1.04215[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]12.8634[/C][C]-1.96338[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]12.0314[/C][C]-7.73143[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]13.2607[/C][C]-2.96069[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]12.9321[/C][C]-1.13209[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]12.7821[/C][C]-1.58211[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]12.5379[/C][C]-1.1379[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]12.6562[/C][C]-4.05623[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]12.4571[/C][C]0.742932[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]12.8911[/C][C]-0.291143[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]12.3046[/C][C]-6.70458[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]12.8083[/C][C]-2.90826[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]12.6325[/C][C]-3.83251[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]13.0604[/C][C]-5.36035[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]12.4859[/C][C]-3.48587[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]12.7296[/C][C]-5.42962[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]12.8422[/C][C]-1.44216[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]12.6579[/C][C]0.942145[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]12.4406[/C][C]-4.54061[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]12.3584[/C][C]-1.65837[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]12.2528[/C][C]-1.95278[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]12.0223[/C][C]-3.72234[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]12.5993[/C][C]-2.99933[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]13.2301[/C][C]0.969865[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]13.0363[/C][C]-4.53632[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]13.2037[/C][C]0.296312[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]12.5417[/C][C]-7.64173[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]12.5347[/C][C]-6.13471[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]13.4682[/C][C]-3.86818[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]12.8506[/C][C]-1.25056[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]12.5726[/C][C]-1.47258[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]13.954[/C][C]-9.604[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]12.6731[/C][C]0.026949[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]13.3065[/C][C]4.79349[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]12.7498[/C][C]5.10021[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]13.577[/C][C]3.023[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]13.1308[/C][C]-0.530827[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]13.9727[/C][C]3.12731[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]13.5786[/C][C]5.52142[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]13.2576[/C][C]2.84243[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]13.1252[/C][C]0.224755[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]13.9[/C][C]4.5[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]12.7249[/C][C]1.97514[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]13.103[/C][C]-2.50295[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]13.1021[/C][C]-0.502089[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]12.7386[/C][C]3.46142[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]13.0232[/C][C]0.576765[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]12.9651[/C][C]5.93494[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]13.0327[/C][C]1.06729[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]12.9326[/C][C]1.5674[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]12.8976[/C][C]3.25236[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]13.2125[/C][C]1.53746[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]13.0297[/C][C]1.77032[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]12.905[/C][C]-0.454975[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]13.3225[/C][C]-0.672477[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]12.9456[/C][C]4.40441[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]13.408[/C][C]-4.80795[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]13.0146[/C][C]5.3854[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]14.9509[/C][C]1.14909[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]12.5797[/C][C]-0.979748[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]13.433[/C][C]4.317[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]13.0872[/C][C]2.16281[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]13.1989[/C][C]4.4511[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]13.4059[/C][C]2.94407[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]14.0076[/C][C]3.64235[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]14.8664[/C][C]-1.26643[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]13.8418[/C][C]0.508151[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]13.2256[/C][C]1.52437[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]13.6449[/C][C]4.60507[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]13.2424[/C][C]-3.3424[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.7963[/C][C]2.20368[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]13.6866[/C][C]4.5634[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]12.8463[/C][C]4.0037[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]13.0644[/C][C]1.5356[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]13.4779[/C][C]0.37211[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]13.8346[/C][C]5.11544[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]13.3233[/C][C]2.27668[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]13.5775[/C][C]1.27254[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]12.4595[/C][C]-0.709549[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]12.943[/C][C]5.50699[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]12.5932[/C][C]3.3068[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]13.1818[/C][C]3.91824[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]13.7466[/C][C]2.35337[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]14.4335[/C][C]5.4665[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]12.3204[/C][C]-1.3704[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]12.3713[/C][C]6.07875[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]13.2375[/C][C]1.86253[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]13.408[/C][C]1.59196[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]12.4089[/C][C]-1.05895[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]12.8389[/C][C]3.11113[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]13.0651[/C][C]5.03487[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]12.6284[/C][C]1.97161[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]14.0254[/C][C]1.37459[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]13.6213[/C][C]1.77872[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]12.1724[/C][C]5.4276[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]13.8078[/C][C]-0.457848[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]12.3385[/C][C]6.76147[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]12.7864[/C][C]2.5636[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]12.5716[/C][C]-4.97165[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]13.4347[/C][C]-0.0346707[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]13.1048[/C][C]0.79522[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]13.7658[/C][C]5.33422[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]12.415[/C][C]2.83495[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]12.4826[/C][C]0.41744[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]12.8956[/C][C]3.2044[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]13.0283[/C][C]4.32168[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]12.915[/C][C]0.234974[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]13.095[/C][C]-0.94502[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]12.7581[/C][C]-0.158147[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]12.5488[/C][C]-2.19883[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]12.2525[/C][C]3.14751[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]13.1334[/C][C]-3.53342[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]12.6813[/C][C]5.51871[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]12.9497[/C][C]0.650267[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]13.6197[/C][C]1.2303[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]12.7678[/C][C]1.98222[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]12.6396[/C][C]1.4604[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]12.8631[/C][C]2.03691[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]13.026[/C][C]3.22403[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]14.901[/C][C]4.34897[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]13.7859[/C][C]-0.185893[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]13.2329[/C][C]0.36712[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]12.6564[/C][C]2.99357[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]12.1503[/C][C]0.599665[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]11.8134[/C][C]2.78663[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]13.3261[/C][C]-3.47609[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]13.4648[/C][C]-0.814805[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]11.9894[/C][C]7.21058[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]12.4857[/C][C]4.11428[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]12.9115[/C][C]-1.71154[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]13.6056[/C][C]1.64437[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]12.5923[/C][C]-0.69233[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]12.5825[/C][C]0.617518[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]12.7525[/C][C]3.59752[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]13.5228[/C][C]-1.12282[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]12.4583[/C][C]3.39173[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]13.0634[/C][C]5.08659[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]12.1895[/C][C]-1.03949[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]13.0213[/C][C]2.62872[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]12.3919[/C][C]5.35806[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]11.7136[/C][C]-4.06356[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]13.6337[/C][C]-1.28368[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]12.9058[/C][C]2.69415[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]12.5777[/C][C]6.72227[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]12.9826[/C][C]2.21736[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]13.533[/C][C]3.56695[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]12.5027[/C][C]3.09731[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]12.9046[/C][C]5.49539[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]13.2354[/C][C]5.81464[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]13.5741[/C][C]4.9759[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]13.6156[/C][C]5.4844[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]12.2314[/C][C]0.868598[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]12.7778[/C][C]0.0721622[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]13.9015[/C][C]-4.40151[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]13.4769[/C][C]-8.97689[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]12.6797[/C][C]-0.829657[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]12.9277[/C][C]0.672317[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]14.7962[/C][C]-3.09618[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]12.3621[/C][C]0.0379385[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]13.6663[/C][C]-0.316306[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]11.5833[/C][C]-0.183282[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]12.8575[/C][C]2.0425[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]13.0665[/C][C]6.83348[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]13.6307[/C][C]-2.4307[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]12.0585[/C][C]2.54154[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]13.1277[/C][C]4.47228[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]12.8401[/C][C]1.20987[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]13.1307[/C][C]2.96933[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]13.5786[/C][C]-0.228591[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]12.8139[/C][C]-0.963863[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]13.622[/C][C]-1.672[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]12.5976[/C][C]2.15236[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]12.0326[/C][C]3.11744[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]12.8068[/C][C]0.393231[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]12.8508[/C][C]3.9992[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]11.9455[/C][C]-4.09554[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]12.7651[/C][C]-5.06514[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]12.6982[/C][C]-0.0982305[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]12.9936[/C][C]-5.14359[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]13.3005[/C][C]-2.35048[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]12.1231[/C][C]0.226904[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]12.9609[/C][C]-3.01093[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]12.763[/C][C]2.13704[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]12.6168[/C][C]4.03325[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]13.4959[/C][C]-0.095869[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]13.0543[/C][C]0.895744[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]11.6895[/C][C]4.0105[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]13.0289[/C][C]3.82106[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]12.6916[/C][C]-1.74159[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]12.167[/C][C]3.18302[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]12.6493[/C][C]-0.449304[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]12.2868[/C][C]2.8132[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]12.67[/C][C]5.08002[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]12.8439[/C][C]2.35608[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]13.5468[/C][C]1.05322[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]12.4395[/C][C]4.21047[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]12.4049[/C][C]-4.30494[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270042&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270042&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.2235-0.323488
212.212.966-0.765966
312.813.4694-0.66937
47.413.1657-5.76571
56.713.5493-6.84934
612.612.9876-0.387616
714.812.29712.50289
813.313.955-0.654959
911.112.4037-1.30368
108.214.9161-6.71609
1111.412.6966-1.29662
126.413.361-6.96097
1310.611.99-1.38999
141213.2987-1.29866
156.313.1616-6.86159
1611.312.2874-0.98742
1711.912.7468-0.846787
189.312.8905-3.59048
199.613.0604-3.46039
201012.7881-2.78814
216.413.601-7.20097
2213.813.19730.60272
2310.812.8031-2.0031
2413.812.67791.12211
2511.713.2232-1.52323
2610.912.7506-1.85063
2716.112.19613.90394
2813.413.09760.302426
299.912.9708-3.07076
3011.512.7744-1.27438
318.312.374-4.07401
3211.713.7199-2.01985
33912.5432-3.5432
349.712.3489-2.64892
3510.812.746-1.94597
3610.313.6185-3.31854
3710.413.167-2.767
3812.712.7365-0.0365364
399.313.6105-4.31051
4011.812.5755-0.775514
415.913.6227-7.72267
4211.413.6363-2.23633
431313.2067-0.206681
4410.811.667-0.866964
4512.312.17140.128636
4611.313.1193-1.81933
4711.813.6234-1.82338
487.912.7247-4.82468
4912.712.69490.005093
5012.313.3062-1.0062
5111.612.2591-0.659069
526.712.7569-6.05691
5310.913.2787-2.37875
5412.112.6656-0.565618
5513.313.5627-0.262718
5610.113.1097-3.0097
575.712.2789-6.5789
5814.312.95881.34116
59812.7793-4.77933
6013.313.19380.106212
619.313.7123-4.41228
6212.513.0148-0.514785
637.612.3002-4.70021
6415.913.28322.61684
659.213.0573-3.85727
669.112.9234-3.82335
6711.112.6523-1.55227
681313.6132-0.61317
6914.513.16331.33671
7012.212.7465-0.546477
7112.313.2017-0.901652
7211.412.8378-1.43781
738.813.1745-4.37448
7414.613.37581.2242
7512.612.38740.212559
761312.91550.0845132
7712.612.9522-0.352217
7813.213.837-0.637039
799.912.1771-2.27714
807.712.6001-4.90008
8110.512.5207-2.02071
8213.412.35791.04215
8310.912.8634-1.96338
844.312.0314-7.73143
8510.313.2607-2.96069
8611.812.9321-1.13209
8711.212.7821-1.58211
8811.412.5379-1.1379
898.612.6562-4.05623
9013.212.45710.742932
9112.612.8911-0.291143
925.612.3046-6.70458
939.912.8083-2.90826
948.812.6325-3.83251
957.713.0604-5.36035
96912.4859-3.48587
977.312.7296-5.42962
9811.412.8422-1.44216
9913.612.65790.942145
1007.912.4406-4.54061
10110.712.3584-1.65837
10210.312.2528-1.95278
1038.312.0223-3.72234
1049.612.5993-2.99933
10514.213.23010.969865
1068.513.0363-4.53632
10713.513.20370.296312
1084.912.5417-7.64173
1096.412.5347-6.13471
1109.613.4682-3.86818
11111.612.8506-1.25056
11211.112.5726-1.47258
1134.3513.954-9.604
11412.712.67310.026949
11518.113.30654.79349
11617.8512.74985.10021
11716.613.5773.023
11812.613.1308-0.530827
11917.113.97273.12731
12019.113.57865.52142
12116.113.25762.84243
12213.3513.12520.224755
12318.413.94.5
12414.712.72491.97514
12510.613.103-2.50295
12612.613.1021-0.502089
12716.212.73863.46142
12813.613.02320.576765
12918.912.96515.93494
13014.113.03271.06729
13114.512.93261.5674
13216.1512.89763.25236
13314.7513.21251.53746
13414.813.02971.77032
13512.4512.905-0.454975
13612.6513.3225-0.672477
13717.3512.94564.40441
1388.613.408-4.80795
13918.413.01465.3854
14016.114.95091.14909
14111.612.5797-0.979748
14217.7513.4334.317
14315.2513.08722.16281
14417.6513.19894.4511
14516.3513.40592.94407
14617.6514.00763.64235
14713.614.8664-1.26643
14814.3513.84180.508151
14914.7513.22561.52437
15018.2513.64494.60507
1519.913.2424-3.3424
1521613.79632.20368
15318.2513.68664.5634
15416.8512.84634.0037
15514.613.06441.5356
15613.8513.47790.37211
15718.9513.83465.11544
15815.613.32332.27668
15914.8513.57751.27254
16011.7512.4595-0.709549
16118.4512.9435.50699
16215.912.59323.3068
16317.113.18183.91824
16416.113.74662.35337
16519.914.43355.4665
16610.9512.3204-1.3704
16718.4512.37136.07875
16815.113.23751.86253
1691513.4081.59196
17011.3512.4089-1.05895
17115.9512.83893.11113
17218.113.06515.03487
17314.612.62841.97161
17415.414.02541.37459
17515.413.62131.77872
17617.612.17245.4276
17713.3513.8078-0.457848
17819.112.33856.76147
17915.3512.78642.5636
1807.612.5716-4.97165
18113.413.4347-0.0346707
18213.913.10480.79522
18319.113.76585.33422
18415.2512.4152.83495
18512.912.48260.41744
18616.112.89563.2044
18717.3513.02834.32168
18813.1512.9150.234974
18912.1513.095-0.94502
19012.612.7581-0.158147
19110.3512.5488-2.19883
19215.412.25253.14751
1939.613.1334-3.53342
19418.212.68135.51871
19513.612.94970.650267
19614.8513.61971.2303
19714.7512.76781.98222
19814.112.63961.4604
19914.912.86312.03691
20016.2513.0263.22403
20119.2514.9014.34897
20213.613.7859-0.185893
20313.613.23290.36712
20415.6512.65642.99357
20512.7512.15030.599665
20614.611.81342.78663
2079.8513.3261-3.47609
20812.6513.4648-0.814805
20919.211.98947.21058
21016.612.48574.11428
21111.212.9115-1.71154
21215.2513.60561.64437
21311.912.5923-0.69233
21413.212.58250.617518
21516.3512.75253.59752
21612.413.5228-1.12282
21715.8512.45833.39173
21818.1513.06345.08659
21911.1512.1895-1.03949
22015.6513.02132.62872
22117.7512.39195.35806
2227.6511.7136-4.06356
22312.3513.6337-1.28368
22415.612.90582.69415
22519.312.57776.72227
22615.212.98262.21736
22717.113.5333.56695
22815.612.50273.09731
22918.412.90465.49539
23019.0513.23545.81464
23118.5513.57414.9759
23219.113.61565.4844
23313.112.23140.868598
23412.8512.77780.0721622
2359.513.9015-4.40151
2364.513.4769-8.97689
23711.8512.6797-0.829657
23813.612.92770.672317
23911.714.7962-3.09618
24012.412.36210.0379385
24113.3513.6663-0.316306
24211.411.5833-0.183282
24314.912.85752.0425
24419.913.06656.83348
24511.213.6307-2.4307
24614.612.05852.54154
24717.613.12774.47228
24814.0512.84011.20987
24916.113.13072.96933
25013.3513.5786-0.228591
25111.8512.8139-0.963863
25211.9513.622-1.672
25314.7512.59762.15236
25415.1512.03263.11744
25513.212.80680.393231
25616.8512.85083.9992
2577.8511.9455-4.09554
2587.712.7651-5.06514
25912.612.6982-0.0982305
2607.8512.9936-5.14359
26110.9513.3005-2.35048
26212.3512.12310.226904
2639.9512.9609-3.01093
26414.912.7632.13704
26516.6512.61684.03325
26613.413.4959-0.095869
26713.9513.05430.895744
26815.711.68954.0105
26916.8513.02893.82106
27010.9512.6916-1.74159
27115.3512.1673.18302
27212.212.6493-0.449304
27315.112.28682.8132
27417.7512.675.08002
27515.212.84392.35608
27614.613.54681.05322
27716.6512.43954.21047
2788.112.4049-4.30494







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.3807990.7615980.619201
130.2767270.5534540.723273
140.2488920.4977840.751108
150.277830.5556610.72217
160.1816650.363330.818335
170.1348240.2696470.865176
180.09725690.1945140.902743
190.06127420.1225480.938726
200.03638170.07276340.963618
210.02356110.04712230.976439
220.01298780.02597570.987012
230.007067960.01413590.992932
240.008504250.01700850.991496
250.005039050.01007810.994961
260.002749740.005499480.99725
270.004036270.008072550.995964
280.002843480.005686970.997157
290.001618820.003237630.998381
300.0008675910.001735180.999132
310.0008389420.001677880.999161
320.0005102410.001020480.99949
330.0007421240.001484250.999258
340.01578610.03157220.984214
350.01072680.02145350.989273
360.007864920.01572980.992135
370.005226320.01045260.994774
380.003278660.006557320.996721
390.002491480.004982960.997509
400.001607330.003214650.998393
410.00360870.00721740.996391
420.002988640.005977290.997011
430.002954940.005909880.997045
440.00281260.005625190.997187
450.001930840.003861680.998069
460.001475530.002951060.998524
470.00111490.00222980.998885
480.001016140.002032290.998984
490.0008845460.001769090.999115
500.0008490360.001698070.999151
510.0005512940.001102590.999449
520.002354330.004708660.997646
530.001738690.003477380.998261
540.001470560.002941110.998529
550.001652770.003305540.998347
560.001249530.002499050.99875
570.003656230.007312470.996344
580.002801240.005602490.997199
590.002738520.005477040.997261
600.003468430.006936860.996532
610.002968280.005936570.997032
620.002491330.004982650.997509
630.005382410.01076480.994618
640.009527130.01905430.990473
650.009449740.01889950.99055
660.008612390.01722480.991388
670.006645060.01329010.993355
680.006087270.01217450.993913
690.006530550.01306110.993469
700.005167420.01033480.994833
710.003888170.007776340.996112
720.002972340.005944690.997028
730.00286910.00573820.997131
740.003345270.006690540.996655
750.002568440.005136890.997432
760.002349810.004699610.99765
770.001833160.003666310.998167
780.001624480.003248970.998376
790.001292220.002584430.998708
800.001678080.003356170.998322
810.001248170.002496350.998752
820.001128130.002256260.998872
830.0008417960.001683590.999158
840.003952890.007905780.996047
850.003156430.006312870.996844
860.00244560.004891190.997554
870.001861920.003723840.998138
880.001466280.002932560.998534
890.001488210.002976420.998512
900.001360960.002721920.998639
910.001063760.002127520.998936
920.002856310.005712620.997144
930.002389960.004779920.99761
940.002194410.004388820.997806
950.002508540.005017080.997491
960.002329640.004659280.99767
970.003137740.006275480.996862
980.002476280.004952550.997524
990.002408960.004817910.997591
1000.002671720.005343440.997328
1010.002169250.00433850.997831
1020.001809050.00361810.998191
1030.001921480.003842960.998079
1040.001673280.003346550.998327
1050.001747660.003495330.998252
1060.001885750.00377150.998114
1070.001911840.003823690.998088
1080.006252270.01250450.993748
1090.01098380.02196750.989016
1100.01124720.02249440.988753
1110.009987990.0199760.990012
1120.008719120.01743820.991281
1130.0546480.1092960.945352
1140.06077080.1215420.939229
1150.1066350.213270.893365
1160.1728530.3457060.827147
1170.224380.448760.77562
1180.2067990.4135990.793201
1190.2535310.5070620.746469
1200.354010.708020.64599
1210.3702920.7405840.629708
1220.3591450.718290.640855
1230.4368120.8736240.563188
1240.4302930.8605860.569707
1250.4351870.8703730.564813
1260.4103870.8207740.589613
1270.4355160.8710310.564484
1280.411040.8220810.58896
1290.5451620.9096760.454838
1300.5299960.9400070.470004
1310.5122130.9755750.487787
1320.51680.96640.4832
1330.4929650.9859290.507035
1340.4811090.9622180.518891
1350.4651950.930390.534805
1360.4432120.8864230.556788
1370.4803770.9607550.519623
1380.540790.9184210.45921
1390.615990.768020.38401
1400.5935870.8128260.406413
1410.5655170.8689670.434483
1420.5960190.8079620.403981
1430.5777530.8444940.422247
1440.6037990.7924020.396201
1450.5989420.8021150.401058
1460.6067270.7865450.393273
1470.5837740.8324520.416226
1480.5557690.8884630.444231
1490.5368270.9263450.463173
1500.5723950.855210.427605
1510.5855170.8289660.414483
1520.5636980.8726050.436302
1530.5898330.8203340.410167
1540.5957340.8085320.404266
1550.5806330.8387330.419367
1560.5560990.8878010.443901
1570.6000880.7998240.399912
1580.5822560.8354880.417744
1590.5601880.8796230.439812
1600.5438220.9123560.456178
1610.6166140.7667720.383386
1620.6234280.7531450.376572
1630.6253770.7492460.374623
1640.6052790.7894420.394721
1650.6737270.6525450.326273
1660.6500710.6998580.349929
1670.7299560.5400880.270044
1680.7108490.5783030.289151
1690.6877650.6244690.312235
1700.6715360.6569270.328464
1710.6687770.6624450.331223
1720.71540.56920.2846
1730.6960620.6078760.303938
1740.6686150.662770.331385
1750.6411310.7177380.358869
1760.6884060.6231880.311594
1770.6576860.6846290.342314
1780.725870.5482590.27413
1790.7094640.5810720.290536
1800.774090.4518190.22591
1810.7451640.5096730.254836
1820.7160180.5679640.283982
1830.7678550.464290.232145
1840.7568580.4862840.243142
1850.7301680.5396650.269832
1860.7223870.5552270.277613
1870.7437990.5124010.256201
1880.7125330.5749350.287467
1890.6817960.6364080.318204
1900.6479530.7040930.352047
1910.6412730.7174540.358727
1920.6285150.7429690.371485
1930.651090.6978210.34891
1940.6918470.6163070.308153
1950.660310.6793790.33969
1960.6272140.7455720.372786
1970.5968220.8063560.403178
1980.5637140.8725730.436286
1990.5326570.9346850.467343
2000.5164840.9670310.483516
2010.5907310.8185370.409269
2020.5512140.8975710.448786
2030.5140060.9719870.485994
2040.5005880.9988240.499412
2050.4703390.9406790.529661
2060.4509520.9019050.549048
2070.5012360.9975290.498764
2080.4644990.9289980.535501
2090.5251910.9496190.474809
2100.523320.9533610.47668
2110.4985010.9970020.501499
2120.4633250.9266510.536675
2130.4489080.8978160.551092
2140.4081490.8162980.591851
2150.3849610.7699220.615039
2160.3501790.7003570.649821
2170.337070.6741410.66293
2180.3516680.7033360.648332
2190.3261130.6522260.673887
2200.3134480.6268950.686552
2210.3200550.640110.679945
2220.3987690.7975380.601231
2230.3596950.719390.640305
2240.3318790.6637590.668121
2250.4215050.8430110.578495
2260.3916560.7833120.608344
2270.3719150.743830.628085
2280.3448940.6897880.655106
2290.3870290.7740580.612971
2300.4764090.9528170.523591
2310.5710010.8579980.428999
2320.6602920.6794150.339708
2330.6156590.7686810.384341
2340.5664330.8671330.433567
2350.5523360.8953270.447664
2360.8180280.3639440.181972
2370.7907360.4185270.209264
2380.7501040.4997930.249896
2390.7494740.5010530.250526
2400.7336520.5326970.266348
2410.6841020.6317950.315898
2420.6416570.7166870.358343
2430.5980160.8039690.401984
2440.7470210.5059580.252979
2450.7086910.5826180.291309
2460.6584310.6831380.341569
2470.6500950.6998110.349905
2480.5937080.8125850.406292
2490.5817940.8364120.418206
2500.5210040.9579920.478996
2510.4560120.9120240.543988
2520.3890090.7780180.610991
2530.3265310.6530620.673469
2540.4909140.9818270.509086
2550.6325240.7349510.367476
2560.589370.8212590.41063
2570.707330.585340.29267
2580.8719080.2561840.128092
2590.8261560.3476880.173844
2600.9196590.1606810.0803405
2610.9027170.1945660.0972832
2620.8875260.2249480.112474
2630.8238360.3523280.176164
2640.7634860.4730270.236514
2650.7067490.5865010.293251
2660.9929370.0141260.007063

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.380799 & 0.761598 & 0.619201 \tabularnewline
13 & 0.276727 & 0.553454 & 0.723273 \tabularnewline
14 & 0.248892 & 0.497784 & 0.751108 \tabularnewline
15 & 0.27783 & 0.555661 & 0.72217 \tabularnewline
16 & 0.181665 & 0.36333 & 0.818335 \tabularnewline
17 & 0.134824 & 0.269647 & 0.865176 \tabularnewline
18 & 0.0972569 & 0.194514 & 0.902743 \tabularnewline
19 & 0.0612742 & 0.122548 & 0.938726 \tabularnewline
20 & 0.0363817 & 0.0727634 & 0.963618 \tabularnewline
21 & 0.0235611 & 0.0471223 & 0.976439 \tabularnewline
22 & 0.0129878 & 0.0259757 & 0.987012 \tabularnewline
23 & 0.00706796 & 0.0141359 & 0.992932 \tabularnewline
24 & 0.00850425 & 0.0170085 & 0.991496 \tabularnewline
25 & 0.00503905 & 0.0100781 & 0.994961 \tabularnewline
26 & 0.00274974 & 0.00549948 & 0.99725 \tabularnewline
27 & 0.00403627 & 0.00807255 & 0.995964 \tabularnewline
28 & 0.00284348 & 0.00568697 & 0.997157 \tabularnewline
29 & 0.00161882 & 0.00323763 & 0.998381 \tabularnewline
30 & 0.000867591 & 0.00173518 & 0.999132 \tabularnewline
31 & 0.000838942 & 0.00167788 & 0.999161 \tabularnewline
32 & 0.000510241 & 0.00102048 & 0.99949 \tabularnewline
33 & 0.000742124 & 0.00148425 & 0.999258 \tabularnewline
34 & 0.0157861 & 0.0315722 & 0.984214 \tabularnewline
35 & 0.0107268 & 0.0214535 & 0.989273 \tabularnewline
36 & 0.00786492 & 0.0157298 & 0.992135 \tabularnewline
37 & 0.00522632 & 0.0104526 & 0.994774 \tabularnewline
38 & 0.00327866 & 0.00655732 & 0.996721 \tabularnewline
39 & 0.00249148 & 0.00498296 & 0.997509 \tabularnewline
40 & 0.00160733 & 0.00321465 & 0.998393 \tabularnewline
41 & 0.0036087 & 0.0072174 & 0.996391 \tabularnewline
42 & 0.00298864 & 0.00597729 & 0.997011 \tabularnewline
43 & 0.00295494 & 0.00590988 & 0.997045 \tabularnewline
44 & 0.0028126 & 0.00562519 & 0.997187 \tabularnewline
45 & 0.00193084 & 0.00386168 & 0.998069 \tabularnewline
46 & 0.00147553 & 0.00295106 & 0.998524 \tabularnewline
47 & 0.0011149 & 0.0022298 & 0.998885 \tabularnewline
48 & 0.00101614 & 0.00203229 & 0.998984 \tabularnewline
49 & 0.000884546 & 0.00176909 & 0.999115 \tabularnewline
50 & 0.000849036 & 0.00169807 & 0.999151 \tabularnewline
51 & 0.000551294 & 0.00110259 & 0.999449 \tabularnewline
52 & 0.00235433 & 0.00470866 & 0.997646 \tabularnewline
53 & 0.00173869 & 0.00347738 & 0.998261 \tabularnewline
54 & 0.00147056 & 0.00294111 & 0.998529 \tabularnewline
55 & 0.00165277 & 0.00330554 & 0.998347 \tabularnewline
56 & 0.00124953 & 0.00249905 & 0.99875 \tabularnewline
57 & 0.00365623 & 0.00731247 & 0.996344 \tabularnewline
58 & 0.00280124 & 0.00560249 & 0.997199 \tabularnewline
59 & 0.00273852 & 0.00547704 & 0.997261 \tabularnewline
60 & 0.00346843 & 0.00693686 & 0.996532 \tabularnewline
61 & 0.00296828 & 0.00593657 & 0.997032 \tabularnewline
62 & 0.00249133 & 0.00498265 & 0.997509 \tabularnewline
63 & 0.00538241 & 0.0107648 & 0.994618 \tabularnewline
64 & 0.00952713 & 0.0190543 & 0.990473 \tabularnewline
65 & 0.00944974 & 0.0188995 & 0.99055 \tabularnewline
66 & 0.00861239 & 0.0172248 & 0.991388 \tabularnewline
67 & 0.00664506 & 0.0132901 & 0.993355 \tabularnewline
68 & 0.00608727 & 0.0121745 & 0.993913 \tabularnewline
69 & 0.00653055 & 0.0130611 & 0.993469 \tabularnewline
70 & 0.00516742 & 0.0103348 & 0.994833 \tabularnewline
71 & 0.00388817 & 0.00777634 & 0.996112 \tabularnewline
72 & 0.00297234 & 0.00594469 & 0.997028 \tabularnewline
73 & 0.0028691 & 0.0057382 & 0.997131 \tabularnewline
74 & 0.00334527 & 0.00669054 & 0.996655 \tabularnewline
75 & 0.00256844 & 0.00513689 & 0.997432 \tabularnewline
76 & 0.00234981 & 0.00469961 & 0.99765 \tabularnewline
77 & 0.00183316 & 0.00366631 & 0.998167 \tabularnewline
78 & 0.00162448 & 0.00324897 & 0.998376 \tabularnewline
79 & 0.00129222 & 0.00258443 & 0.998708 \tabularnewline
80 & 0.00167808 & 0.00335617 & 0.998322 \tabularnewline
81 & 0.00124817 & 0.00249635 & 0.998752 \tabularnewline
82 & 0.00112813 & 0.00225626 & 0.998872 \tabularnewline
83 & 0.000841796 & 0.00168359 & 0.999158 \tabularnewline
84 & 0.00395289 & 0.00790578 & 0.996047 \tabularnewline
85 & 0.00315643 & 0.00631287 & 0.996844 \tabularnewline
86 & 0.0024456 & 0.00489119 & 0.997554 \tabularnewline
87 & 0.00186192 & 0.00372384 & 0.998138 \tabularnewline
88 & 0.00146628 & 0.00293256 & 0.998534 \tabularnewline
89 & 0.00148821 & 0.00297642 & 0.998512 \tabularnewline
90 & 0.00136096 & 0.00272192 & 0.998639 \tabularnewline
91 & 0.00106376 & 0.00212752 & 0.998936 \tabularnewline
92 & 0.00285631 & 0.00571262 & 0.997144 \tabularnewline
93 & 0.00238996 & 0.00477992 & 0.99761 \tabularnewline
94 & 0.00219441 & 0.00438882 & 0.997806 \tabularnewline
95 & 0.00250854 & 0.00501708 & 0.997491 \tabularnewline
96 & 0.00232964 & 0.00465928 & 0.99767 \tabularnewline
97 & 0.00313774 & 0.00627548 & 0.996862 \tabularnewline
98 & 0.00247628 & 0.00495255 & 0.997524 \tabularnewline
99 & 0.00240896 & 0.00481791 & 0.997591 \tabularnewline
100 & 0.00267172 & 0.00534344 & 0.997328 \tabularnewline
101 & 0.00216925 & 0.0043385 & 0.997831 \tabularnewline
102 & 0.00180905 & 0.0036181 & 0.998191 \tabularnewline
103 & 0.00192148 & 0.00384296 & 0.998079 \tabularnewline
104 & 0.00167328 & 0.00334655 & 0.998327 \tabularnewline
105 & 0.00174766 & 0.00349533 & 0.998252 \tabularnewline
106 & 0.00188575 & 0.0037715 & 0.998114 \tabularnewline
107 & 0.00191184 & 0.00382369 & 0.998088 \tabularnewline
108 & 0.00625227 & 0.0125045 & 0.993748 \tabularnewline
109 & 0.0109838 & 0.0219675 & 0.989016 \tabularnewline
110 & 0.0112472 & 0.0224944 & 0.988753 \tabularnewline
111 & 0.00998799 & 0.019976 & 0.990012 \tabularnewline
112 & 0.00871912 & 0.0174382 & 0.991281 \tabularnewline
113 & 0.054648 & 0.109296 & 0.945352 \tabularnewline
114 & 0.0607708 & 0.121542 & 0.939229 \tabularnewline
115 & 0.106635 & 0.21327 & 0.893365 \tabularnewline
116 & 0.172853 & 0.345706 & 0.827147 \tabularnewline
117 & 0.22438 & 0.44876 & 0.77562 \tabularnewline
118 & 0.206799 & 0.413599 & 0.793201 \tabularnewline
119 & 0.253531 & 0.507062 & 0.746469 \tabularnewline
120 & 0.35401 & 0.70802 & 0.64599 \tabularnewline
121 & 0.370292 & 0.740584 & 0.629708 \tabularnewline
122 & 0.359145 & 0.71829 & 0.640855 \tabularnewline
123 & 0.436812 & 0.873624 & 0.563188 \tabularnewline
124 & 0.430293 & 0.860586 & 0.569707 \tabularnewline
125 & 0.435187 & 0.870373 & 0.564813 \tabularnewline
126 & 0.410387 & 0.820774 & 0.589613 \tabularnewline
127 & 0.435516 & 0.871031 & 0.564484 \tabularnewline
128 & 0.41104 & 0.822081 & 0.58896 \tabularnewline
129 & 0.545162 & 0.909676 & 0.454838 \tabularnewline
130 & 0.529996 & 0.940007 & 0.470004 \tabularnewline
131 & 0.512213 & 0.975575 & 0.487787 \tabularnewline
132 & 0.5168 & 0.9664 & 0.4832 \tabularnewline
133 & 0.492965 & 0.985929 & 0.507035 \tabularnewline
134 & 0.481109 & 0.962218 & 0.518891 \tabularnewline
135 & 0.465195 & 0.93039 & 0.534805 \tabularnewline
136 & 0.443212 & 0.886423 & 0.556788 \tabularnewline
137 & 0.480377 & 0.960755 & 0.519623 \tabularnewline
138 & 0.54079 & 0.918421 & 0.45921 \tabularnewline
139 & 0.61599 & 0.76802 & 0.38401 \tabularnewline
140 & 0.593587 & 0.812826 & 0.406413 \tabularnewline
141 & 0.565517 & 0.868967 & 0.434483 \tabularnewline
142 & 0.596019 & 0.807962 & 0.403981 \tabularnewline
143 & 0.577753 & 0.844494 & 0.422247 \tabularnewline
144 & 0.603799 & 0.792402 & 0.396201 \tabularnewline
145 & 0.598942 & 0.802115 & 0.401058 \tabularnewline
146 & 0.606727 & 0.786545 & 0.393273 \tabularnewline
147 & 0.583774 & 0.832452 & 0.416226 \tabularnewline
148 & 0.555769 & 0.888463 & 0.444231 \tabularnewline
149 & 0.536827 & 0.926345 & 0.463173 \tabularnewline
150 & 0.572395 & 0.85521 & 0.427605 \tabularnewline
151 & 0.585517 & 0.828966 & 0.414483 \tabularnewline
152 & 0.563698 & 0.872605 & 0.436302 \tabularnewline
153 & 0.589833 & 0.820334 & 0.410167 \tabularnewline
154 & 0.595734 & 0.808532 & 0.404266 \tabularnewline
155 & 0.580633 & 0.838733 & 0.419367 \tabularnewline
156 & 0.556099 & 0.887801 & 0.443901 \tabularnewline
157 & 0.600088 & 0.799824 & 0.399912 \tabularnewline
158 & 0.582256 & 0.835488 & 0.417744 \tabularnewline
159 & 0.560188 & 0.879623 & 0.439812 \tabularnewline
160 & 0.543822 & 0.912356 & 0.456178 \tabularnewline
161 & 0.616614 & 0.766772 & 0.383386 \tabularnewline
162 & 0.623428 & 0.753145 & 0.376572 \tabularnewline
163 & 0.625377 & 0.749246 & 0.374623 \tabularnewline
164 & 0.605279 & 0.789442 & 0.394721 \tabularnewline
165 & 0.673727 & 0.652545 & 0.326273 \tabularnewline
166 & 0.650071 & 0.699858 & 0.349929 \tabularnewline
167 & 0.729956 & 0.540088 & 0.270044 \tabularnewline
168 & 0.710849 & 0.578303 & 0.289151 \tabularnewline
169 & 0.687765 & 0.624469 & 0.312235 \tabularnewline
170 & 0.671536 & 0.656927 & 0.328464 \tabularnewline
171 & 0.668777 & 0.662445 & 0.331223 \tabularnewline
172 & 0.7154 & 0.5692 & 0.2846 \tabularnewline
173 & 0.696062 & 0.607876 & 0.303938 \tabularnewline
174 & 0.668615 & 0.66277 & 0.331385 \tabularnewline
175 & 0.641131 & 0.717738 & 0.358869 \tabularnewline
176 & 0.688406 & 0.623188 & 0.311594 \tabularnewline
177 & 0.657686 & 0.684629 & 0.342314 \tabularnewline
178 & 0.72587 & 0.548259 & 0.27413 \tabularnewline
179 & 0.709464 & 0.581072 & 0.290536 \tabularnewline
180 & 0.77409 & 0.451819 & 0.22591 \tabularnewline
181 & 0.745164 & 0.509673 & 0.254836 \tabularnewline
182 & 0.716018 & 0.567964 & 0.283982 \tabularnewline
183 & 0.767855 & 0.46429 & 0.232145 \tabularnewline
184 & 0.756858 & 0.486284 & 0.243142 \tabularnewline
185 & 0.730168 & 0.539665 & 0.269832 \tabularnewline
186 & 0.722387 & 0.555227 & 0.277613 \tabularnewline
187 & 0.743799 & 0.512401 & 0.256201 \tabularnewline
188 & 0.712533 & 0.574935 & 0.287467 \tabularnewline
189 & 0.681796 & 0.636408 & 0.318204 \tabularnewline
190 & 0.647953 & 0.704093 & 0.352047 \tabularnewline
191 & 0.641273 & 0.717454 & 0.358727 \tabularnewline
192 & 0.628515 & 0.742969 & 0.371485 \tabularnewline
193 & 0.65109 & 0.697821 & 0.34891 \tabularnewline
194 & 0.691847 & 0.616307 & 0.308153 \tabularnewline
195 & 0.66031 & 0.679379 & 0.33969 \tabularnewline
196 & 0.627214 & 0.745572 & 0.372786 \tabularnewline
197 & 0.596822 & 0.806356 & 0.403178 \tabularnewline
198 & 0.563714 & 0.872573 & 0.436286 \tabularnewline
199 & 0.532657 & 0.934685 & 0.467343 \tabularnewline
200 & 0.516484 & 0.967031 & 0.483516 \tabularnewline
201 & 0.590731 & 0.818537 & 0.409269 \tabularnewline
202 & 0.551214 & 0.897571 & 0.448786 \tabularnewline
203 & 0.514006 & 0.971987 & 0.485994 \tabularnewline
204 & 0.500588 & 0.998824 & 0.499412 \tabularnewline
205 & 0.470339 & 0.940679 & 0.529661 \tabularnewline
206 & 0.450952 & 0.901905 & 0.549048 \tabularnewline
207 & 0.501236 & 0.997529 & 0.498764 \tabularnewline
208 & 0.464499 & 0.928998 & 0.535501 \tabularnewline
209 & 0.525191 & 0.949619 & 0.474809 \tabularnewline
210 & 0.52332 & 0.953361 & 0.47668 \tabularnewline
211 & 0.498501 & 0.997002 & 0.501499 \tabularnewline
212 & 0.463325 & 0.926651 & 0.536675 \tabularnewline
213 & 0.448908 & 0.897816 & 0.551092 \tabularnewline
214 & 0.408149 & 0.816298 & 0.591851 \tabularnewline
215 & 0.384961 & 0.769922 & 0.615039 \tabularnewline
216 & 0.350179 & 0.700357 & 0.649821 \tabularnewline
217 & 0.33707 & 0.674141 & 0.66293 \tabularnewline
218 & 0.351668 & 0.703336 & 0.648332 \tabularnewline
219 & 0.326113 & 0.652226 & 0.673887 \tabularnewline
220 & 0.313448 & 0.626895 & 0.686552 \tabularnewline
221 & 0.320055 & 0.64011 & 0.679945 \tabularnewline
222 & 0.398769 & 0.797538 & 0.601231 \tabularnewline
223 & 0.359695 & 0.71939 & 0.640305 \tabularnewline
224 & 0.331879 & 0.663759 & 0.668121 \tabularnewline
225 & 0.421505 & 0.843011 & 0.578495 \tabularnewline
226 & 0.391656 & 0.783312 & 0.608344 \tabularnewline
227 & 0.371915 & 0.74383 & 0.628085 \tabularnewline
228 & 0.344894 & 0.689788 & 0.655106 \tabularnewline
229 & 0.387029 & 0.774058 & 0.612971 \tabularnewline
230 & 0.476409 & 0.952817 & 0.523591 \tabularnewline
231 & 0.571001 & 0.857998 & 0.428999 \tabularnewline
232 & 0.660292 & 0.679415 & 0.339708 \tabularnewline
233 & 0.615659 & 0.768681 & 0.384341 \tabularnewline
234 & 0.566433 & 0.867133 & 0.433567 \tabularnewline
235 & 0.552336 & 0.895327 & 0.447664 \tabularnewline
236 & 0.818028 & 0.363944 & 0.181972 \tabularnewline
237 & 0.790736 & 0.418527 & 0.209264 \tabularnewline
238 & 0.750104 & 0.499793 & 0.249896 \tabularnewline
239 & 0.749474 & 0.501053 & 0.250526 \tabularnewline
240 & 0.733652 & 0.532697 & 0.266348 \tabularnewline
241 & 0.684102 & 0.631795 & 0.315898 \tabularnewline
242 & 0.641657 & 0.716687 & 0.358343 \tabularnewline
243 & 0.598016 & 0.803969 & 0.401984 \tabularnewline
244 & 0.747021 & 0.505958 & 0.252979 \tabularnewline
245 & 0.708691 & 0.582618 & 0.291309 \tabularnewline
246 & 0.658431 & 0.683138 & 0.341569 \tabularnewline
247 & 0.650095 & 0.699811 & 0.349905 \tabularnewline
248 & 0.593708 & 0.812585 & 0.406292 \tabularnewline
249 & 0.581794 & 0.836412 & 0.418206 \tabularnewline
250 & 0.521004 & 0.957992 & 0.478996 \tabularnewline
251 & 0.456012 & 0.912024 & 0.543988 \tabularnewline
252 & 0.389009 & 0.778018 & 0.610991 \tabularnewline
253 & 0.326531 & 0.653062 & 0.673469 \tabularnewline
254 & 0.490914 & 0.981827 & 0.509086 \tabularnewline
255 & 0.632524 & 0.734951 & 0.367476 \tabularnewline
256 & 0.58937 & 0.821259 & 0.41063 \tabularnewline
257 & 0.70733 & 0.58534 & 0.29267 \tabularnewline
258 & 0.871908 & 0.256184 & 0.128092 \tabularnewline
259 & 0.826156 & 0.347688 & 0.173844 \tabularnewline
260 & 0.919659 & 0.160681 & 0.0803405 \tabularnewline
261 & 0.902717 & 0.194566 & 0.0972832 \tabularnewline
262 & 0.887526 & 0.224948 & 0.112474 \tabularnewline
263 & 0.823836 & 0.352328 & 0.176164 \tabularnewline
264 & 0.763486 & 0.473027 & 0.236514 \tabularnewline
265 & 0.706749 & 0.586501 & 0.293251 \tabularnewline
266 & 0.992937 & 0.014126 & 0.007063 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270042&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]12[/C][C]0.380799[/C][C]0.761598[/C][C]0.619201[/C][/ROW]
[ROW][C]13[/C][C]0.276727[/C][C]0.553454[/C][C]0.723273[/C][/ROW]
[ROW][C]14[/C][C]0.248892[/C][C]0.497784[/C][C]0.751108[/C][/ROW]
[ROW][C]15[/C][C]0.27783[/C][C]0.555661[/C][C]0.72217[/C][/ROW]
[ROW][C]16[/C][C]0.181665[/C][C]0.36333[/C][C]0.818335[/C][/ROW]
[ROW][C]17[/C][C]0.134824[/C][C]0.269647[/C][C]0.865176[/C][/ROW]
[ROW][C]18[/C][C]0.0972569[/C][C]0.194514[/C][C]0.902743[/C][/ROW]
[ROW][C]19[/C][C]0.0612742[/C][C]0.122548[/C][C]0.938726[/C][/ROW]
[ROW][C]20[/C][C]0.0363817[/C][C]0.0727634[/C][C]0.963618[/C][/ROW]
[ROW][C]21[/C][C]0.0235611[/C][C]0.0471223[/C][C]0.976439[/C][/ROW]
[ROW][C]22[/C][C]0.0129878[/C][C]0.0259757[/C][C]0.987012[/C][/ROW]
[ROW][C]23[/C][C]0.00706796[/C][C]0.0141359[/C][C]0.992932[/C][/ROW]
[ROW][C]24[/C][C]0.00850425[/C][C]0.0170085[/C][C]0.991496[/C][/ROW]
[ROW][C]25[/C][C]0.00503905[/C][C]0.0100781[/C][C]0.994961[/C][/ROW]
[ROW][C]26[/C][C]0.00274974[/C][C]0.00549948[/C][C]0.99725[/C][/ROW]
[ROW][C]27[/C][C]0.00403627[/C][C]0.00807255[/C][C]0.995964[/C][/ROW]
[ROW][C]28[/C][C]0.00284348[/C][C]0.00568697[/C][C]0.997157[/C][/ROW]
[ROW][C]29[/C][C]0.00161882[/C][C]0.00323763[/C][C]0.998381[/C][/ROW]
[ROW][C]30[/C][C]0.000867591[/C][C]0.00173518[/C][C]0.999132[/C][/ROW]
[ROW][C]31[/C][C]0.000838942[/C][C]0.00167788[/C][C]0.999161[/C][/ROW]
[ROW][C]32[/C][C]0.000510241[/C][C]0.00102048[/C][C]0.99949[/C][/ROW]
[ROW][C]33[/C][C]0.000742124[/C][C]0.00148425[/C][C]0.999258[/C][/ROW]
[ROW][C]34[/C][C]0.0157861[/C][C]0.0315722[/C][C]0.984214[/C][/ROW]
[ROW][C]35[/C][C]0.0107268[/C][C]0.0214535[/C][C]0.989273[/C][/ROW]
[ROW][C]36[/C][C]0.00786492[/C][C]0.0157298[/C][C]0.992135[/C][/ROW]
[ROW][C]37[/C][C]0.00522632[/C][C]0.0104526[/C][C]0.994774[/C][/ROW]
[ROW][C]38[/C][C]0.00327866[/C][C]0.00655732[/C][C]0.996721[/C][/ROW]
[ROW][C]39[/C][C]0.00249148[/C][C]0.00498296[/C][C]0.997509[/C][/ROW]
[ROW][C]40[/C][C]0.00160733[/C][C]0.00321465[/C][C]0.998393[/C][/ROW]
[ROW][C]41[/C][C]0.0036087[/C][C]0.0072174[/C][C]0.996391[/C][/ROW]
[ROW][C]42[/C][C]0.00298864[/C][C]0.00597729[/C][C]0.997011[/C][/ROW]
[ROW][C]43[/C][C]0.00295494[/C][C]0.00590988[/C][C]0.997045[/C][/ROW]
[ROW][C]44[/C][C]0.0028126[/C][C]0.00562519[/C][C]0.997187[/C][/ROW]
[ROW][C]45[/C][C]0.00193084[/C][C]0.00386168[/C][C]0.998069[/C][/ROW]
[ROW][C]46[/C][C]0.00147553[/C][C]0.00295106[/C][C]0.998524[/C][/ROW]
[ROW][C]47[/C][C]0.0011149[/C][C]0.0022298[/C][C]0.998885[/C][/ROW]
[ROW][C]48[/C][C]0.00101614[/C][C]0.00203229[/C][C]0.998984[/C][/ROW]
[ROW][C]49[/C][C]0.000884546[/C][C]0.00176909[/C][C]0.999115[/C][/ROW]
[ROW][C]50[/C][C]0.000849036[/C][C]0.00169807[/C][C]0.999151[/C][/ROW]
[ROW][C]51[/C][C]0.000551294[/C][C]0.00110259[/C][C]0.999449[/C][/ROW]
[ROW][C]52[/C][C]0.00235433[/C][C]0.00470866[/C][C]0.997646[/C][/ROW]
[ROW][C]53[/C][C]0.00173869[/C][C]0.00347738[/C][C]0.998261[/C][/ROW]
[ROW][C]54[/C][C]0.00147056[/C][C]0.00294111[/C][C]0.998529[/C][/ROW]
[ROW][C]55[/C][C]0.00165277[/C][C]0.00330554[/C][C]0.998347[/C][/ROW]
[ROW][C]56[/C][C]0.00124953[/C][C]0.00249905[/C][C]0.99875[/C][/ROW]
[ROW][C]57[/C][C]0.00365623[/C][C]0.00731247[/C][C]0.996344[/C][/ROW]
[ROW][C]58[/C][C]0.00280124[/C][C]0.00560249[/C][C]0.997199[/C][/ROW]
[ROW][C]59[/C][C]0.00273852[/C][C]0.00547704[/C][C]0.997261[/C][/ROW]
[ROW][C]60[/C][C]0.00346843[/C][C]0.00693686[/C][C]0.996532[/C][/ROW]
[ROW][C]61[/C][C]0.00296828[/C][C]0.00593657[/C][C]0.997032[/C][/ROW]
[ROW][C]62[/C][C]0.00249133[/C][C]0.00498265[/C][C]0.997509[/C][/ROW]
[ROW][C]63[/C][C]0.00538241[/C][C]0.0107648[/C][C]0.994618[/C][/ROW]
[ROW][C]64[/C][C]0.00952713[/C][C]0.0190543[/C][C]0.990473[/C][/ROW]
[ROW][C]65[/C][C]0.00944974[/C][C]0.0188995[/C][C]0.99055[/C][/ROW]
[ROW][C]66[/C][C]0.00861239[/C][C]0.0172248[/C][C]0.991388[/C][/ROW]
[ROW][C]67[/C][C]0.00664506[/C][C]0.0132901[/C][C]0.993355[/C][/ROW]
[ROW][C]68[/C][C]0.00608727[/C][C]0.0121745[/C][C]0.993913[/C][/ROW]
[ROW][C]69[/C][C]0.00653055[/C][C]0.0130611[/C][C]0.993469[/C][/ROW]
[ROW][C]70[/C][C]0.00516742[/C][C]0.0103348[/C][C]0.994833[/C][/ROW]
[ROW][C]71[/C][C]0.00388817[/C][C]0.00777634[/C][C]0.996112[/C][/ROW]
[ROW][C]72[/C][C]0.00297234[/C][C]0.00594469[/C][C]0.997028[/C][/ROW]
[ROW][C]73[/C][C]0.0028691[/C][C]0.0057382[/C][C]0.997131[/C][/ROW]
[ROW][C]74[/C][C]0.00334527[/C][C]0.00669054[/C][C]0.996655[/C][/ROW]
[ROW][C]75[/C][C]0.00256844[/C][C]0.00513689[/C][C]0.997432[/C][/ROW]
[ROW][C]76[/C][C]0.00234981[/C][C]0.00469961[/C][C]0.99765[/C][/ROW]
[ROW][C]77[/C][C]0.00183316[/C][C]0.00366631[/C][C]0.998167[/C][/ROW]
[ROW][C]78[/C][C]0.00162448[/C][C]0.00324897[/C][C]0.998376[/C][/ROW]
[ROW][C]79[/C][C]0.00129222[/C][C]0.00258443[/C][C]0.998708[/C][/ROW]
[ROW][C]80[/C][C]0.00167808[/C][C]0.00335617[/C][C]0.998322[/C][/ROW]
[ROW][C]81[/C][C]0.00124817[/C][C]0.00249635[/C][C]0.998752[/C][/ROW]
[ROW][C]82[/C][C]0.00112813[/C][C]0.00225626[/C][C]0.998872[/C][/ROW]
[ROW][C]83[/C][C]0.000841796[/C][C]0.00168359[/C][C]0.999158[/C][/ROW]
[ROW][C]84[/C][C]0.00395289[/C][C]0.00790578[/C][C]0.996047[/C][/ROW]
[ROW][C]85[/C][C]0.00315643[/C][C]0.00631287[/C][C]0.996844[/C][/ROW]
[ROW][C]86[/C][C]0.0024456[/C][C]0.00489119[/C][C]0.997554[/C][/ROW]
[ROW][C]87[/C][C]0.00186192[/C][C]0.00372384[/C][C]0.998138[/C][/ROW]
[ROW][C]88[/C][C]0.00146628[/C][C]0.00293256[/C][C]0.998534[/C][/ROW]
[ROW][C]89[/C][C]0.00148821[/C][C]0.00297642[/C][C]0.998512[/C][/ROW]
[ROW][C]90[/C][C]0.00136096[/C][C]0.00272192[/C][C]0.998639[/C][/ROW]
[ROW][C]91[/C][C]0.00106376[/C][C]0.00212752[/C][C]0.998936[/C][/ROW]
[ROW][C]92[/C][C]0.00285631[/C][C]0.00571262[/C][C]0.997144[/C][/ROW]
[ROW][C]93[/C][C]0.00238996[/C][C]0.00477992[/C][C]0.99761[/C][/ROW]
[ROW][C]94[/C][C]0.00219441[/C][C]0.00438882[/C][C]0.997806[/C][/ROW]
[ROW][C]95[/C][C]0.00250854[/C][C]0.00501708[/C][C]0.997491[/C][/ROW]
[ROW][C]96[/C][C]0.00232964[/C][C]0.00465928[/C][C]0.99767[/C][/ROW]
[ROW][C]97[/C][C]0.00313774[/C][C]0.00627548[/C][C]0.996862[/C][/ROW]
[ROW][C]98[/C][C]0.00247628[/C][C]0.00495255[/C][C]0.997524[/C][/ROW]
[ROW][C]99[/C][C]0.00240896[/C][C]0.00481791[/C][C]0.997591[/C][/ROW]
[ROW][C]100[/C][C]0.00267172[/C][C]0.00534344[/C][C]0.997328[/C][/ROW]
[ROW][C]101[/C][C]0.00216925[/C][C]0.0043385[/C][C]0.997831[/C][/ROW]
[ROW][C]102[/C][C]0.00180905[/C][C]0.0036181[/C][C]0.998191[/C][/ROW]
[ROW][C]103[/C][C]0.00192148[/C][C]0.00384296[/C][C]0.998079[/C][/ROW]
[ROW][C]104[/C][C]0.00167328[/C][C]0.00334655[/C][C]0.998327[/C][/ROW]
[ROW][C]105[/C][C]0.00174766[/C][C]0.00349533[/C][C]0.998252[/C][/ROW]
[ROW][C]106[/C][C]0.00188575[/C][C]0.0037715[/C][C]0.998114[/C][/ROW]
[ROW][C]107[/C][C]0.00191184[/C][C]0.00382369[/C][C]0.998088[/C][/ROW]
[ROW][C]108[/C][C]0.00625227[/C][C]0.0125045[/C][C]0.993748[/C][/ROW]
[ROW][C]109[/C][C]0.0109838[/C][C]0.0219675[/C][C]0.989016[/C][/ROW]
[ROW][C]110[/C][C]0.0112472[/C][C]0.0224944[/C][C]0.988753[/C][/ROW]
[ROW][C]111[/C][C]0.00998799[/C][C]0.019976[/C][C]0.990012[/C][/ROW]
[ROW][C]112[/C][C]0.00871912[/C][C]0.0174382[/C][C]0.991281[/C][/ROW]
[ROW][C]113[/C][C]0.054648[/C][C]0.109296[/C][C]0.945352[/C][/ROW]
[ROW][C]114[/C][C]0.0607708[/C][C]0.121542[/C][C]0.939229[/C][/ROW]
[ROW][C]115[/C][C]0.106635[/C][C]0.21327[/C][C]0.893365[/C][/ROW]
[ROW][C]116[/C][C]0.172853[/C][C]0.345706[/C][C]0.827147[/C][/ROW]
[ROW][C]117[/C][C]0.22438[/C][C]0.44876[/C][C]0.77562[/C][/ROW]
[ROW][C]118[/C][C]0.206799[/C][C]0.413599[/C][C]0.793201[/C][/ROW]
[ROW][C]119[/C][C]0.253531[/C][C]0.507062[/C][C]0.746469[/C][/ROW]
[ROW][C]120[/C][C]0.35401[/C][C]0.70802[/C][C]0.64599[/C][/ROW]
[ROW][C]121[/C][C]0.370292[/C][C]0.740584[/C][C]0.629708[/C][/ROW]
[ROW][C]122[/C][C]0.359145[/C][C]0.71829[/C][C]0.640855[/C][/ROW]
[ROW][C]123[/C][C]0.436812[/C][C]0.873624[/C][C]0.563188[/C][/ROW]
[ROW][C]124[/C][C]0.430293[/C][C]0.860586[/C][C]0.569707[/C][/ROW]
[ROW][C]125[/C][C]0.435187[/C][C]0.870373[/C][C]0.564813[/C][/ROW]
[ROW][C]126[/C][C]0.410387[/C][C]0.820774[/C][C]0.589613[/C][/ROW]
[ROW][C]127[/C][C]0.435516[/C][C]0.871031[/C][C]0.564484[/C][/ROW]
[ROW][C]128[/C][C]0.41104[/C][C]0.822081[/C][C]0.58896[/C][/ROW]
[ROW][C]129[/C][C]0.545162[/C][C]0.909676[/C][C]0.454838[/C][/ROW]
[ROW][C]130[/C][C]0.529996[/C][C]0.940007[/C][C]0.470004[/C][/ROW]
[ROW][C]131[/C][C]0.512213[/C][C]0.975575[/C][C]0.487787[/C][/ROW]
[ROW][C]132[/C][C]0.5168[/C][C]0.9664[/C][C]0.4832[/C][/ROW]
[ROW][C]133[/C][C]0.492965[/C][C]0.985929[/C][C]0.507035[/C][/ROW]
[ROW][C]134[/C][C]0.481109[/C][C]0.962218[/C][C]0.518891[/C][/ROW]
[ROW][C]135[/C][C]0.465195[/C][C]0.93039[/C][C]0.534805[/C][/ROW]
[ROW][C]136[/C][C]0.443212[/C][C]0.886423[/C][C]0.556788[/C][/ROW]
[ROW][C]137[/C][C]0.480377[/C][C]0.960755[/C][C]0.519623[/C][/ROW]
[ROW][C]138[/C][C]0.54079[/C][C]0.918421[/C][C]0.45921[/C][/ROW]
[ROW][C]139[/C][C]0.61599[/C][C]0.76802[/C][C]0.38401[/C][/ROW]
[ROW][C]140[/C][C]0.593587[/C][C]0.812826[/C][C]0.406413[/C][/ROW]
[ROW][C]141[/C][C]0.565517[/C][C]0.868967[/C][C]0.434483[/C][/ROW]
[ROW][C]142[/C][C]0.596019[/C][C]0.807962[/C][C]0.403981[/C][/ROW]
[ROW][C]143[/C][C]0.577753[/C][C]0.844494[/C][C]0.422247[/C][/ROW]
[ROW][C]144[/C][C]0.603799[/C][C]0.792402[/C][C]0.396201[/C][/ROW]
[ROW][C]145[/C][C]0.598942[/C][C]0.802115[/C][C]0.401058[/C][/ROW]
[ROW][C]146[/C][C]0.606727[/C][C]0.786545[/C][C]0.393273[/C][/ROW]
[ROW][C]147[/C][C]0.583774[/C][C]0.832452[/C][C]0.416226[/C][/ROW]
[ROW][C]148[/C][C]0.555769[/C][C]0.888463[/C][C]0.444231[/C][/ROW]
[ROW][C]149[/C][C]0.536827[/C][C]0.926345[/C][C]0.463173[/C][/ROW]
[ROW][C]150[/C][C]0.572395[/C][C]0.85521[/C][C]0.427605[/C][/ROW]
[ROW][C]151[/C][C]0.585517[/C][C]0.828966[/C][C]0.414483[/C][/ROW]
[ROW][C]152[/C][C]0.563698[/C][C]0.872605[/C][C]0.436302[/C][/ROW]
[ROW][C]153[/C][C]0.589833[/C][C]0.820334[/C][C]0.410167[/C][/ROW]
[ROW][C]154[/C][C]0.595734[/C][C]0.808532[/C][C]0.404266[/C][/ROW]
[ROW][C]155[/C][C]0.580633[/C][C]0.838733[/C][C]0.419367[/C][/ROW]
[ROW][C]156[/C][C]0.556099[/C][C]0.887801[/C][C]0.443901[/C][/ROW]
[ROW][C]157[/C][C]0.600088[/C][C]0.799824[/C][C]0.399912[/C][/ROW]
[ROW][C]158[/C][C]0.582256[/C][C]0.835488[/C][C]0.417744[/C][/ROW]
[ROW][C]159[/C][C]0.560188[/C][C]0.879623[/C][C]0.439812[/C][/ROW]
[ROW][C]160[/C][C]0.543822[/C][C]0.912356[/C][C]0.456178[/C][/ROW]
[ROW][C]161[/C][C]0.616614[/C][C]0.766772[/C][C]0.383386[/C][/ROW]
[ROW][C]162[/C][C]0.623428[/C][C]0.753145[/C][C]0.376572[/C][/ROW]
[ROW][C]163[/C][C]0.625377[/C][C]0.749246[/C][C]0.374623[/C][/ROW]
[ROW][C]164[/C][C]0.605279[/C][C]0.789442[/C][C]0.394721[/C][/ROW]
[ROW][C]165[/C][C]0.673727[/C][C]0.652545[/C][C]0.326273[/C][/ROW]
[ROW][C]166[/C][C]0.650071[/C][C]0.699858[/C][C]0.349929[/C][/ROW]
[ROW][C]167[/C][C]0.729956[/C][C]0.540088[/C][C]0.270044[/C][/ROW]
[ROW][C]168[/C][C]0.710849[/C][C]0.578303[/C][C]0.289151[/C][/ROW]
[ROW][C]169[/C][C]0.687765[/C][C]0.624469[/C][C]0.312235[/C][/ROW]
[ROW][C]170[/C][C]0.671536[/C][C]0.656927[/C][C]0.328464[/C][/ROW]
[ROW][C]171[/C][C]0.668777[/C][C]0.662445[/C][C]0.331223[/C][/ROW]
[ROW][C]172[/C][C]0.7154[/C][C]0.5692[/C][C]0.2846[/C][/ROW]
[ROW][C]173[/C][C]0.696062[/C][C]0.607876[/C][C]0.303938[/C][/ROW]
[ROW][C]174[/C][C]0.668615[/C][C]0.66277[/C][C]0.331385[/C][/ROW]
[ROW][C]175[/C][C]0.641131[/C][C]0.717738[/C][C]0.358869[/C][/ROW]
[ROW][C]176[/C][C]0.688406[/C][C]0.623188[/C][C]0.311594[/C][/ROW]
[ROW][C]177[/C][C]0.657686[/C][C]0.684629[/C][C]0.342314[/C][/ROW]
[ROW][C]178[/C][C]0.72587[/C][C]0.548259[/C][C]0.27413[/C][/ROW]
[ROW][C]179[/C][C]0.709464[/C][C]0.581072[/C][C]0.290536[/C][/ROW]
[ROW][C]180[/C][C]0.77409[/C][C]0.451819[/C][C]0.22591[/C][/ROW]
[ROW][C]181[/C][C]0.745164[/C][C]0.509673[/C][C]0.254836[/C][/ROW]
[ROW][C]182[/C][C]0.716018[/C][C]0.567964[/C][C]0.283982[/C][/ROW]
[ROW][C]183[/C][C]0.767855[/C][C]0.46429[/C][C]0.232145[/C][/ROW]
[ROW][C]184[/C][C]0.756858[/C][C]0.486284[/C][C]0.243142[/C][/ROW]
[ROW][C]185[/C][C]0.730168[/C][C]0.539665[/C][C]0.269832[/C][/ROW]
[ROW][C]186[/C][C]0.722387[/C][C]0.555227[/C][C]0.277613[/C][/ROW]
[ROW][C]187[/C][C]0.743799[/C][C]0.512401[/C][C]0.256201[/C][/ROW]
[ROW][C]188[/C][C]0.712533[/C][C]0.574935[/C][C]0.287467[/C][/ROW]
[ROW][C]189[/C][C]0.681796[/C][C]0.636408[/C][C]0.318204[/C][/ROW]
[ROW][C]190[/C][C]0.647953[/C][C]0.704093[/C][C]0.352047[/C][/ROW]
[ROW][C]191[/C][C]0.641273[/C][C]0.717454[/C][C]0.358727[/C][/ROW]
[ROW][C]192[/C][C]0.628515[/C][C]0.742969[/C][C]0.371485[/C][/ROW]
[ROW][C]193[/C][C]0.65109[/C][C]0.697821[/C][C]0.34891[/C][/ROW]
[ROW][C]194[/C][C]0.691847[/C][C]0.616307[/C][C]0.308153[/C][/ROW]
[ROW][C]195[/C][C]0.66031[/C][C]0.679379[/C][C]0.33969[/C][/ROW]
[ROW][C]196[/C][C]0.627214[/C][C]0.745572[/C][C]0.372786[/C][/ROW]
[ROW][C]197[/C][C]0.596822[/C][C]0.806356[/C][C]0.403178[/C][/ROW]
[ROW][C]198[/C][C]0.563714[/C][C]0.872573[/C][C]0.436286[/C][/ROW]
[ROW][C]199[/C][C]0.532657[/C][C]0.934685[/C][C]0.467343[/C][/ROW]
[ROW][C]200[/C][C]0.516484[/C][C]0.967031[/C][C]0.483516[/C][/ROW]
[ROW][C]201[/C][C]0.590731[/C][C]0.818537[/C][C]0.409269[/C][/ROW]
[ROW][C]202[/C][C]0.551214[/C][C]0.897571[/C][C]0.448786[/C][/ROW]
[ROW][C]203[/C][C]0.514006[/C][C]0.971987[/C][C]0.485994[/C][/ROW]
[ROW][C]204[/C][C]0.500588[/C][C]0.998824[/C][C]0.499412[/C][/ROW]
[ROW][C]205[/C][C]0.470339[/C][C]0.940679[/C][C]0.529661[/C][/ROW]
[ROW][C]206[/C][C]0.450952[/C][C]0.901905[/C][C]0.549048[/C][/ROW]
[ROW][C]207[/C][C]0.501236[/C][C]0.997529[/C][C]0.498764[/C][/ROW]
[ROW][C]208[/C][C]0.464499[/C][C]0.928998[/C][C]0.535501[/C][/ROW]
[ROW][C]209[/C][C]0.525191[/C][C]0.949619[/C][C]0.474809[/C][/ROW]
[ROW][C]210[/C][C]0.52332[/C][C]0.953361[/C][C]0.47668[/C][/ROW]
[ROW][C]211[/C][C]0.498501[/C][C]0.997002[/C][C]0.501499[/C][/ROW]
[ROW][C]212[/C][C]0.463325[/C][C]0.926651[/C][C]0.536675[/C][/ROW]
[ROW][C]213[/C][C]0.448908[/C][C]0.897816[/C][C]0.551092[/C][/ROW]
[ROW][C]214[/C][C]0.408149[/C][C]0.816298[/C][C]0.591851[/C][/ROW]
[ROW][C]215[/C][C]0.384961[/C][C]0.769922[/C][C]0.615039[/C][/ROW]
[ROW][C]216[/C][C]0.350179[/C][C]0.700357[/C][C]0.649821[/C][/ROW]
[ROW][C]217[/C][C]0.33707[/C][C]0.674141[/C][C]0.66293[/C][/ROW]
[ROW][C]218[/C][C]0.351668[/C][C]0.703336[/C][C]0.648332[/C][/ROW]
[ROW][C]219[/C][C]0.326113[/C][C]0.652226[/C][C]0.673887[/C][/ROW]
[ROW][C]220[/C][C]0.313448[/C][C]0.626895[/C][C]0.686552[/C][/ROW]
[ROW][C]221[/C][C]0.320055[/C][C]0.64011[/C][C]0.679945[/C][/ROW]
[ROW][C]222[/C][C]0.398769[/C][C]0.797538[/C][C]0.601231[/C][/ROW]
[ROW][C]223[/C][C]0.359695[/C][C]0.71939[/C][C]0.640305[/C][/ROW]
[ROW][C]224[/C][C]0.331879[/C][C]0.663759[/C][C]0.668121[/C][/ROW]
[ROW][C]225[/C][C]0.421505[/C][C]0.843011[/C][C]0.578495[/C][/ROW]
[ROW][C]226[/C][C]0.391656[/C][C]0.783312[/C][C]0.608344[/C][/ROW]
[ROW][C]227[/C][C]0.371915[/C][C]0.74383[/C][C]0.628085[/C][/ROW]
[ROW][C]228[/C][C]0.344894[/C][C]0.689788[/C][C]0.655106[/C][/ROW]
[ROW][C]229[/C][C]0.387029[/C][C]0.774058[/C][C]0.612971[/C][/ROW]
[ROW][C]230[/C][C]0.476409[/C][C]0.952817[/C][C]0.523591[/C][/ROW]
[ROW][C]231[/C][C]0.571001[/C][C]0.857998[/C][C]0.428999[/C][/ROW]
[ROW][C]232[/C][C]0.660292[/C][C]0.679415[/C][C]0.339708[/C][/ROW]
[ROW][C]233[/C][C]0.615659[/C][C]0.768681[/C][C]0.384341[/C][/ROW]
[ROW][C]234[/C][C]0.566433[/C][C]0.867133[/C][C]0.433567[/C][/ROW]
[ROW][C]235[/C][C]0.552336[/C][C]0.895327[/C][C]0.447664[/C][/ROW]
[ROW][C]236[/C][C]0.818028[/C][C]0.363944[/C][C]0.181972[/C][/ROW]
[ROW][C]237[/C][C]0.790736[/C][C]0.418527[/C][C]0.209264[/C][/ROW]
[ROW][C]238[/C][C]0.750104[/C][C]0.499793[/C][C]0.249896[/C][/ROW]
[ROW][C]239[/C][C]0.749474[/C][C]0.501053[/C][C]0.250526[/C][/ROW]
[ROW][C]240[/C][C]0.733652[/C][C]0.532697[/C][C]0.266348[/C][/ROW]
[ROW][C]241[/C][C]0.684102[/C][C]0.631795[/C][C]0.315898[/C][/ROW]
[ROW][C]242[/C][C]0.641657[/C][C]0.716687[/C][C]0.358343[/C][/ROW]
[ROW][C]243[/C][C]0.598016[/C][C]0.803969[/C][C]0.401984[/C][/ROW]
[ROW][C]244[/C][C]0.747021[/C][C]0.505958[/C][C]0.252979[/C][/ROW]
[ROW][C]245[/C][C]0.708691[/C][C]0.582618[/C][C]0.291309[/C][/ROW]
[ROW][C]246[/C][C]0.658431[/C][C]0.683138[/C][C]0.341569[/C][/ROW]
[ROW][C]247[/C][C]0.650095[/C][C]0.699811[/C][C]0.349905[/C][/ROW]
[ROW][C]248[/C][C]0.593708[/C][C]0.812585[/C][C]0.406292[/C][/ROW]
[ROW][C]249[/C][C]0.581794[/C][C]0.836412[/C][C]0.418206[/C][/ROW]
[ROW][C]250[/C][C]0.521004[/C][C]0.957992[/C][C]0.478996[/C][/ROW]
[ROW][C]251[/C][C]0.456012[/C][C]0.912024[/C][C]0.543988[/C][/ROW]
[ROW][C]252[/C][C]0.389009[/C][C]0.778018[/C][C]0.610991[/C][/ROW]
[ROW][C]253[/C][C]0.326531[/C][C]0.653062[/C][C]0.673469[/C][/ROW]
[ROW][C]254[/C][C]0.490914[/C][C]0.981827[/C][C]0.509086[/C][/ROW]
[ROW][C]255[/C][C]0.632524[/C][C]0.734951[/C][C]0.367476[/C][/ROW]
[ROW][C]256[/C][C]0.58937[/C][C]0.821259[/C][C]0.41063[/C][/ROW]
[ROW][C]257[/C][C]0.70733[/C][C]0.58534[/C][C]0.29267[/C][/ROW]
[ROW][C]258[/C][C]0.871908[/C][C]0.256184[/C][C]0.128092[/C][/ROW]
[ROW][C]259[/C][C]0.826156[/C][C]0.347688[/C][C]0.173844[/C][/ROW]
[ROW][C]260[/C][C]0.919659[/C][C]0.160681[/C][C]0.0803405[/C][/ROW]
[ROW][C]261[/C][C]0.902717[/C][C]0.194566[/C][C]0.0972832[/C][/ROW]
[ROW][C]262[/C][C]0.887526[/C][C]0.224948[/C][C]0.112474[/C][/ROW]
[ROW][C]263[/C][C]0.823836[/C][C]0.352328[/C][C]0.176164[/C][/ROW]
[ROW][C]264[/C][C]0.763486[/C][C]0.473027[/C][C]0.236514[/C][/ROW]
[ROW][C]265[/C][C]0.706749[/C][C]0.586501[/C][C]0.293251[/C][/ROW]
[ROW][C]266[/C][C]0.992937[/C][C]0.014126[/C][C]0.007063[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270042&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270042&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.3807990.7615980.619201
130.2767270.5534540.723273
140.2488920.4977840.751108
150.277830.5556610.72217
160.1816650.363330.818335
170.1348240.2696470.865176
180.09725690.1945140.902743
190.06127420.1225480.938726
200.03638170.07276340.963618
210.02356110.04712230.976439
220.01298780.02597570.987012
230.007067960.01413590.992932
240.008504250.01700850.991496
250.005039050.01007810.994961
260.002749740.005499480.99725
270.004036270.008072550.995964
280.002843480.005686970.997157
290.001618820.003237630.998381
300.0008675910.001735180.999132
310.0008389420.001677880.999161
320.0005102410.001020480.99949
330.0007421240.001484250.999258
340.01578610.03157220.984214
350.01072680.02145350.989273
360.007864920.01572980.992135
370.005226320.01045260.994774
380.003278660.006557320.996721
390.002491480.004982960.997509
400.001607330.003214650.998393
410.00360870.00721740.996391
420.002988640.005977290.997011
430.002954940.005909880.997045
440.00281260.005625190.997187
450.001930840.003861680.998069
460.001475530.002951060.998524
470.00111490.00222980.998885
480.001016140.002032290.998984
490.0008845460.001769090.999115
500.0008490360.001698070.999151
510.0005512940.001102590.999449
520.002354330.004708660.997646
530.001738690.003477380.998261
540.001470560.002941110.998529
550.001652770.003305540.998347
560.001249530.002499050.99875
570.003656230.007312470.996344
580.002801240.005602490.997199
590.002738520.005477040.997261
600.003468430.006936860.996532
610.002968280.005936570.997032
620.002491330.004982650.997509
630.005382410.01076480.994618
640.009527130.01905430.990473
650.009449740.01889950.99055
660.008612390.01722480.991388
670.006645060.01329010.993355
680.006087270.01217450.993913
690.006530550.01306110.993469
700.005167420.01033480.994833
710.003888170.007776340.996112
720.002972340.005944690.997028
730.00286910.00573820.997131
740.003345270.006690540.996655
750.002568440.005136890.997432
760.002349810.004699610.99765
770.001833160.003666310.998167
780.001624480.003248970.998376
790.001292220.002584430.998708
800.001678080.003356170.998322
810.001248170.002496350.998752
820.001128130.002256260.998872
830.0008417960.001683590.999158
840.003952890.007905780.996047
850.003156430.006312870.996844
860.00244560.004891190.997554
870.001861920.003723840.998138
880.001466280.002932560.998534
890.001488210.002976420.998512
900.001360960.002721920.998639
910.001063760.002127520.998936
920.002856310.005712620.997144
930.002389960.004779920.99761
940.002194410.004388820.997806
950.002508540.005017080.997491
960.002329640.004659280.99767
970.003137740.006275480.996862
980.002476280.004952550.997524
990.002408960.004817910.997591
1000.002671720.005343440.997328
1010.002169250.00433850.997831
1020.001809050.00361810.998191
1030.001921480.003842960.998079
1040.001673280.003346550.998327
1050.001747660.003495330.998252
1060.001885750.00377150.998114
1070.001911840.003823690.998088
1080.006252270.01250450.993748
1090.01098380.02196750.989016
1100.01124720.02249440.988753
1110.009987990.0199760.990012
1120.008719120.01743820.991281
1130.0546480.1092960.945352
1140.06077080.1215420.939229
1150.1066350.213270.893365
1160.1728530.3457060.827147
1170.224380.448760.77562
1180.2067990.4135990.793201
1190.2535310.5070620.746469
1200.354010.708020.64599
1210.3702920.7405840.629708
1220.3591450.718290.640855
1230.4368120.8736240.563188
1240.4302930.8605860.569707
1250.4351870.8703730.564813
1260.4103870.8207740.589613
1270.4355160.8710310.564484
1280.411040.8220810.58896
1290.5451620.9096760.454838
1300.5299960.9400070.470004
1310.5122130.9755750.487787
1320.51680.96640.4832
1330.4929650.9859290.507035
1340.4811090.9622180.518891
1350.4651950.930390.534805
1360.4432120.8864230.556788
1370.4803770.9607550.519623
1380.540790.9184210.45921
1390.615990.768020.38401
1400.5935870.8128260.406413
1410.5655170.8689670.434483
1420.5960190.8079620.403981
1430.5777530.8444940.422247
1440.6037990.7924020.396201
1450.5989420.8021150.401058
1460.6067270.7865450.393273
1470.5837740.8324520.416226
1480.5557690.8884630.444231
1490.5368270.9263450.463173
1500.5723950.855210.427605
1510.5855170.8289660.414483
1520.5636980.8726050.436302
1530.5898330.8203340.410167
1540.5957340.8085320.404266
1550.5806330.8387330.419367
1560.5560990.8878010.443901
1570.6000880.7998240.399912
1580.5822560.8354880.417744
1590.5601880.8796230.439812
1600.5438220.9123560.456178
1610.6166140.7667720.383386
1620.6234280.7531450.376572
1630.6253770.7492460.374623
1640.6052790.7894420.394721
1650.6737270.6525450.326273
1660.6500710.6998580.349929
1670.7299560.5400880.270044
1680.7108490.5783030.289151
1690.6877650.6244690.312235
1700.6715360.6569270.328464
1710.6687770.6624450.331223
1720.71540.56920.2846
1730.6960620.6078760.303938
1740.6686150.662770.331385
1750.6411310.7177380.358869
1760.6884060.6231880.311594
1770.6576860.6846290.342314
1780.725870.5482590.27413
1790.7094640.5810720.290536
1800.774090.4518190.22591
1810.7451640.5096730.254836
1820.7160180.5679640.283982
1830.7678550.464290.232145
1840.7568580.4862840.243142
1850.7301680.5396650.269832
1860.7223870.5552270.277613
1870.7437990.5124010.256201
1880.7125330.5749350.287467
1890.6817960.6364080.318204
1900.6479530.7040930.352047
1910.6412730.7174540.358727
1920.6285150.7429690.371485
1930.651090.6978210.34891
1940.6918470.6163070.308153
1950.660310.6793790.33969
1960.6272140.7455720.372786
1970.5968220.8063560.403178
1980.5637140.8725730.436286
1990.5326570.9346850.467343
2000.5164840.9670310.483516
2010.5907310.8185370.409269
2020.5512140.8975710.448786
2030.5140060.9719870.485994
2040.5005880.9988240.499412
2050.4703390.9406790.529661
2060.4509520.9019050.549048
2070.5012360.9975290.498764
2080.4644990.9289980.535501
2090.5251910.9496190.474809
2100.523320.9533610.47668
2110.4985010.9970020.501499
2120.4633250.9266510.536675
2130.4489080.8978160.551092
2140.4081490.8162980.591851
2150.3849610.7699220.615039
2160.3501790.7003570.649821
2170.337070.6741410.66293
2180.3516680.7033360.648332
2190.3261130.6522260.673887
2200.3134480.6268950.686552
2210.3200550.640110.679945
2220.3987690.7975380.601231
2230.3596950.719390.640305
2240.3318790.6637590.668121
2250.4215050.8430110.578495
2260.3916560.7833120.608344
2270.3719150.743830.628085
2280.3448940.6897880.655106
2290.3870290.7740580.612971
2300.4764090.9528170.523591
2310.5710010.8579980.428999
2320.6602920.6794150.339708
2330.6156590.7686810.384341
2340.5664330.8671330.433567
2350.5523360.8953270.447664
2360.8180280.3639440.181972
2370.7907360.4185270.209264
2380.7501040.4997930.249896
2390.7494740.5010530.250526
2400.7336520.5326970.266348
2410.6841020.6317950.315898
2420.6416570.7166870.358343
2430.5980160.8039690.401984
2440.7470210.5059580.252979
2450.7086910.5826180.291309
2460.6584310.6831380.341569
2470.6500950.6998110.349905
2480.5937080.8125850.406292
2490.5817940.8364120.418206
2500.5210040.9579920.478996
2510.4560120.9120240.543988
2520.3890090.7780180.610991
2530.3265310.6530620.673469
2540.4909140.9818270.509086
2550.6325240.7349510.367476
2560.589370.8212590.41063
2570.707330.585340.29267
2580.8719080.2561840.128092
2590.8261560.3476880.173844
2600.9196590.1606810.0803405
2610.9027170.1945660.0972832
2620.8875260.2249480.112474
2630.8238360.3523280.176164
2640.7634860.4730270.236514
2650.7067490.5865010.293251
2660.9929370.0141260.007063







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level700.27451NOK
5% type I error level930.364706NOK
10% type I error level940.368627NOK

\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 & 70 & 0.27451 & NOK \tabularnewline
5% type I error level & 93 & 0.364706 & NOK \tabularnewline
10% type I error level & 94 & 0.368627 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270042&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]70[/C][C]0.27451[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]93[/C][C]0.364706[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]94[/C][C]0.368627[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270042&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270042&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level700.27451NOK
5% type I error level930.364706NOK
10% type I error level940.368627NOK



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