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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationFri, 21 Dec 2012 04:21:03 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/21/t1356081797697k5xas4xmvxzz.htm/, Retrieved Fri, 29 Mar 2024 09:22:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=203364, Retrieved Fri, 29 Mar 2024 09:22:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact76
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2012-12-21 09:21:03] [90f4fc95bc23bd40c615363dd079f863] [Current]
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Dataseries X:
1	4
1	3
1	3
1	3
1	3
1	3
1	3
1	4
1	3
1	3
1	4
1	3
1	3
1	4
1	3
1	4
2	4
1	4
1	3
2	4
1	3
1	3
1	3
1	3
1	4
1	3
1	3
1	3
1	3
1	3
1	3
1	3
1	3
1	4
1	3
1	3
1	4
1	3
1	3
1	4
2	3
1	3
1	3
1	4
1	3
1	3
1	3
1	3
1	3
1	3
1	4
2	4
1	3
2	3
1	3
1	4
1	3
1	3
1	3
2	4
1	4
1	3
1	3
1	4
1	3
1	3
2	4
1	3
1	3
1	3
1	3
1	3
1	3
1	3
1	3
1	4
1	3
1	3
2	4
1	4
1	3
1	3
1	3
2	3
1	3
1	3
1	3
1	4
1	3
1	3
1	3
1	4
1	3
1	3
1	4
1	3
1	4
1	3
1	3
1	3
1	3
1	3
1	3
1	3
1	4
1	3
1	3
1	4
1	3
1	3
1	4
1	4
1	3
1	4
1	3
1	3
1	3
1	3
1	3
1	3
1	3
1	3
1	4
1	3
1	3
1	4
1	3
1	3
1	3
1	3
1	3
1	3
1	3
1	3
1	3
1	3
1	3
1	4
1	4
1	3
2	3
1	4
1	3
1	3
1	3
1	4
1	4
1	4
1	3
1	3
1	3
2	3
2	3
1	3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 10 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203364&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203364&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203364&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'George Udny Yule' @ yule.wessa.net







Multiple Linear Regression - Estimated Regression Equation
CorrectAnalysis[t] = + 0.760526315789473 + 0.0973684210526316T40T20[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
CorrectAnalysis[t] =  +  0.760526315789473 +  0.0973684210526316T40T20[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203364&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]CorrectAnalysis[t] =  +  0.760526315789473 +  0.0973684210526316T40T20[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203364&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203364&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
CorrectAnalysis[t] = + 0.760526315789473 + 0.0973684210526316T40T20[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)0.7605263157894730.1610014.72375e-063e-06
T40T200.09736842105263160.048951.98920.0484790.02424

\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) & 0.760526315789473 & 0.161001 & 4.7237 & 5e-06 & 3e-06 \tabularnewline
T40T20 & 0.0973684210526316 & 0.04895 & 1.9892 & 0.048479 & 0.02424 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203364&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]0.760526315789473[/C][C]0.161001[/C][C]4.7237[/C][C]5e-06[/C][C]3e-06[/C][/ROW]
[ROW][C]T40T20[/C][C]0.0973684210526316[/C][C]0.04895[/C][C]1.9892[/C][C]0.048479[/C][C]0.02424[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203364&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203364&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)0.7605263157894730.1610014.72375e-063e-06
T40T200.09736842105263160.048951.98920.0484790.02424







Multiple Linear Regression - Regression Statistics
Multiple R0.159281652810876
R-squared0.0253706449221646
Adjusted R-squared0.0189586096913894
F-TEST (value)3.95672263315016
F-TEST (DF numerator)1
F-TEST (DF denominator)152
p-value0.0484790762148585
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.266362072117266
Sum Squared Residuals10.7842105263158

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.159281652810876 \tabularnewline
R-squared & 0.0253706449221646 \tabularnewline
Adjusted R-squared & 0.0189586096913894 \tabularnewline
F-TEST (value) & 3.95672263315016 \tabularnewline
F-TEST (DF numerator) & 1 \tabularnewline
F-TEST (DF denominator) & 152 \tabularnewline
p-value & 0.0484790762148585 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.266362072117266 \tabularnewline
Sum Squared Residuals & 10.7842105263158 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203364&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.159281652810876[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0253706449221646[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0189586096913894[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]3.95672263315016[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]1[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]152[/C][/ROW]
[ROW][C]p-value[/C][C]0.0484790762148585[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.266362072117266[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]10.7842105263158[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203364&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203364&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 R0.159281652810876
R-squared0.0253706449221646
Adjusted R-squared0.0189586096913894
F-TEST (value)3.95672263315016
F-TEST (DF numerator)1
F-TEST (DF denominator)152
p-value0.0484790762148585
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.266362072117266
Sum Squared Residuals10.7842105263158







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
111.15-0.15
211.05263157894737-0.0526315789473685
311.05263157894737-0.0526315789473684
411.05263157894737-0.0526315789473684
511.05263157894737-0.0526315789473684
611.05263157894737-0.0526315789473684
711.05263157894737-0.0526315789473684
811.15-0.15
911.05263157894737-0.0526315789473684
1011.05263157894737-0.0526315789473684
1111.15-0.15
1211.05263157894737-0.0526315789473684
1311.05263157894737-0.0526315789473684
1411.15-0.15
1511.05263157894737-0.0526315789473684
1611.15-0.15
1721.150.85
1811.15-0.15
1911.05263157894737-0.0526315789473684
2021.150.85
2111.05263157894737-0.0526315789473684
2211.05263157894737-0.0526315789473684
2311.05263157894737-0.0526315789473684
2411.05263157894737-0.0526315789473684
2511.15-0.15
2611.05263157894737-0.0526315789473684
2711.05263157894737-0.0526315789473684
2811.05263157894737-0.0526315789473684
2911.05263157894737-0.0526315789473684
3011.05263157894737-0.0526315789473684
3111.05263157894737-0.0526315789473684
3211.05263157894737-0.0526315789473684
3311.05263157894737-0.0526315789473684
3411.15-0.15
3511.05263157894737-0.0526315789473684
3611.05263157894737-0.0526315789473684
3711.15-0.15
3811.05263157894737-0.0526315789473684
3911.05263157894737-0.0526315789473684
4011.15-0.15
4121.052631578947370.947368421052632
4211.05263157894737-0.0526315789473684
4311.05263157894737-0.0526315789473684
4411.15-0.15
4511.05263157894737-0.0526315789473684
4611.05263157894737-0.0526315789473684
4711.05263157894737-0.0526315789473684
4811.05263157894737-0.0526315789473684
4911.05263157894737-0.0526315789473684
5011.05263157894737-0.0526315789473684
5111.15-0.15
5221.150.85
5311.05263157894737-0.0526315789473684
5421.052631578947370.947368421052632
5511.05263157894737-0.0526315789473684
5611.15-0.15
5711.05263157894737-0.0526315789473684
5811.05263157894737-0.0526315789473684
5911.05263157894737-0.0526315789473684
6021.150.85
6111.15-0.15
6211.05263157894737-0.0526315789473684
6311.05263157894737-0.0526315789473684
6411.15-0.15
6511.05263157894737-0.0526315789473684
6611.05263157894737-0.0526315789473684
6721.150.85
6811.05263157894737-0.0526315789473684
6911.05263157894737-0.0526315789473684
7011.05263157894737-0.0526315789473684
7111.05263157894737-0.0526315789473684
7211.05263157894737-0.0526315789473684
7311.05263157894737-0.0526315789473684
7411.05263157894737-0.0526315789473684
7511.05263157894737-0.0526315789473684
7611.15-0.15
7711.05263157894737-0.0526315789473684
7811.05263157894737-0.0526315789473684
7921.150.85
8011.15-0.15
8111.05263157894737-0.0526315789473684
8211.05263157894737-0.0526315789473684
8311.05263157894737-0.0526315789473684
8421.052631578947370.947368421052632
8511.05263157894737-0.0526315789473684
8611.05263157894737-0.0526315789473684
8711.05263157894737-0.0526315789473684
8811.15-0.15
8911.05263157894737-0.0526315789473684
9011.05263157894737-0.0526315789473684
9111.05263157894737-0.0526315789473684
9211.15-0.15
9311.05263157894737-0.0526315789473684
9411.05263157894737-0.0526315789473684
9511.15-0.15
9611.05263157894737-0.0526315789473684
9711.15-0.15
9811.05263157894737-0.0526315789473684
9911.05263157894737-0.0526315789473684
10011.05263157894737-0.0526315789473684
10111.05263157894737-0.0526315789473684
10211.05263157894737-0.0526315789473684
10311.05263157894737-0.0526315789473684
10411.05263157894737-0.0526315789473684
10511.15-0.15
10611.05263157894737-0.0526315789473684
10711.05263157894737-0.0526315789473684
10811.15-0.15
10911.05263157894737-0.0526315789473684
11011.05263157894737-0.0526315789473684
11111.15-0.15
11211.15-0.15
11311.05263157894737-0.0526315789473684
11411.15-0.15
11511.05263157894737-0.0526315789473684
11611.05263157894737-0.0526315789473684
11711.05263157894737-0.0526315789473684
11811.05263157894737-0.0526315789473684
11911.05263157894737-0.0526315789473684
12011.05263157894737-0.0526315789473684
12111.05263157894737-0.0526315789473684
12211.05263157894737-0.0526315789473684
12311.15-0.15
12411.05263157894737-0.0526315789473684
12511.05263157894737-0.0526315789473684
12611.15-0.15
12711.05263157894737-0.0526315789473684
12811.05263157894737-0.0526315789473684
12911.05263157894737-0.0526315789473684
13011.05263157894737-0.0526315789473684
13111.05263157894737-0.0526315789473684
13211.05263157894737-0.0526315789473684
13311.05263157894737-0.0526315789473684
13411.05263157894737-0.0526315789473684
13511.05263157894737-0.0526315789473684
13611.05263157894737-0.0526315789473684
13711.05263157894737-0.0526315789473684
13811.15-0.15
13911.15-0.15
14011.05263157894737-0.0526315789473684
14121.052631578947370.947368421052632
14211.15-0.15
14311.05263157894737-0.0526315789473684
14411.05263157894737-0.0526315789473684
14511.05263157894737-0.0526315789473684
14611.15-0.15
14711.15-0.15
14811.15-0.15
14911.05263157894737-0.0526315789473684
15011.05263157894737-0.0526315789473684
15111.05263157894737-0.0526315789473684
15221.052631578947370.947368421052632
15321.052631578947370.947368421052632
15411.05263157894737-0.0526315789473684

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1 & 1.15 & -0.15 \tabularnewline
2 & 1 & 1.05263157894737 & -0.0526315789473685 \tabularnewline
3 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
4 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
5 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
6 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
7 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
8 & 1 & 1.15 & -0.15 \tabularnewline
9 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
10 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
11 & 1 & 1.15 & -0.15 \tabularnewline
12 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
13 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
14 & 1 & 1.15 & -0.15 \tabularnewline
15 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
16 & 1 & 1.15 & -0.15 \tabularnewline
17 & 2 & 1.15 & 0.85 \tabularnewline
18 & 1 & 1.15 & -0.15 \tabularnewline
19 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
20 & 2 & 1.15 & 0.85 \tabularnewline
21 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
22 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
23 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
24 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
25 & 1 & 1.15 & -0.15 \tabularnewline
26 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
27 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
28 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
29 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
30 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
31 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
32 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
33 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
34 & 1 & 1.15 & -0.15 \tabularnewline
35 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
36 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
37 & 1 & 1.15 & -0.15 \tabularnewline
38 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
39 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
40 & 1 & 1.15 & -0.15 \tabularnewline
41 & 2 & 1.05263157894737 & 0.947368421052632 \tabularnewline
42 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
43 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
44 & 1 & 1.15 & -0.15 \tabularnewline
45 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
46 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
47 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
48 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
49 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
50 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
51 & 1 & 1.15 & -0.15 \tabularnewline
52 & 2 & 1.15 & 0.85 \tabularnewline
53 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
54 & 2 & 1.05263157894737 & 0.947368421052632 \tabularnewline
55 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
56 & 1 & 1.15 & -0.15 \tabularnewline
57 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
58 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
59 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
60 & 2 & 1.15 & 0.85 \tabularnewline
61 & 1 & 1.15 & -0.15 \tabularnewline
62 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
63 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
64 & 1 & 1.15 & -0.15 \tabularnewline
65 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
66 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
67 & 2 & 1.15 & 0.85 \tabularnewline
68 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
69 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
70 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
71 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
72 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
73 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
74 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
75 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
76 & 1 & 1.15 & -0.15 \tabularnewline
77 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
78 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
79 & 2 & 1.15 & 0.85 \tabularnewline
80 & 1 & 1.15 & -0.15 \tabularnewline
81 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
82 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
83 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
84 & 2 & 1.05263157894737 & 0.947368421052632 \tabularnewline
85 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
86 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
87 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
88 & 1 & 1.15 & -0.15 \tabularnewline
89 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
90 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
91 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
92 & 1 & 1.15 & -0.15 \tabularnewline
93 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
94 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
95 & 1 & 1.15 & -0.15 \tabularnewline
96 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
97 & 1 & 1.15 & -0.15 \tabularnewline
98 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
99 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
100 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
101 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
102 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
103 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
104 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
105 & 1 & 1.15 & -0.15 \tabularnewline
106 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
107 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
108 & 1 & 1.15 & -0.15 \tabularnewline
109 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
110 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
111 & 1 & 1.15 & -0.15 \tabularnewline
112 & 1 & 1.15 & -0.15 \tabularnewline
113 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
114 & 1 & 1.15 & -0.15 \tabularnewline
115 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
116 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
117 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
118 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
119 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
120 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
121 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
122 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
123 & 1 & 1.15 & -0.15 \tabularnewline
124 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
125 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
126 & 1 & 1.15 & -0.15 \tabularnewline
127 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
128 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
129 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
130 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
131 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
132 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
133 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
134 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
135 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
136 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
137 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
138 & 1 & 1.15 & -0.15 \tabularnewline
139 & 1 & 1.15 & -0.15 \tabularnewline
140 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
141 & 2 & 1.05263157894737 & 0.947368421052632 \tabularnewline
142 & 1 & 1.15 & -0.15 \tabularnewline
143 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
144 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
145 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
146 & 1 & 1.15 & -0.15 \tabularnewline
147 & 1 & 1.15 & -0.15 \tabularnewline
148 & 1 & 1.15 & -0.15 \tabularnewline
149 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
150 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
151 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
152 & 2 & 1.05263157894737 & 0.947368421052632 \tabularnewline
153 & 2 & 1.05263157894737 & 0.947368421052632 \tabularnewline
154 & 1 & 1.05263157894737 & -0.0526315789473684 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203364&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]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473685[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]7[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]11[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]14[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]15[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]16[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]17[/C][C]2[/C][C]1.15[/C][C]0.85[/C][/ROW]
[ROW][C]18[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]20[/C][C]2[/C][C]1.15[/C][C]0.85[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]25[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]28[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]30[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]31[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]32[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]33[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]34[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]35[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]36[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]37[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]40[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]41[/C][C]2[/C][C]1.05263157894737[/C][C]0.947368421052632[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]43[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]44[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]45[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]46[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]47[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]49[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]51[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]52[/C][C]2[/C][C]1.15[/C][C]0.85[/C][/ROW]
[ROW][C]53[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]54[/C][C]2[/C][C]1.05263157894737[/C][C]0.947368421052632[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]59[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]60[/C][C]2[/C][C]1.15[/C][C]0.85[/C][/ROW]
[ROW][C]61[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]62[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]63[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]64[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]65[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]66[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]67[/C][C]2[/C][C]1.15[/C][C]0.85[/C][/ROW]
[ROW][C]68[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]69[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]70[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]71[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]72[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]73[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]75[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]79[/C][C]2[/C][C]1.15[/C][C]0.85[/C][/ROW]
[ROW][C]80[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]81[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]82[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]83[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]84[/C][C]2[/C][C]1.05263157894737[/C][C]0.947368421052632[/C][/ROW]
[ROW][C]85[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]86[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]87[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]88[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]89[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]90[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]91[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]92[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]93[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]94[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]95[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]97[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]98[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]99[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]102[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]103[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]105[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]106[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]107[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]108[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]111[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]112[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]114[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]121[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]133[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]141[/C][C]2[/C][C]1.05263157894737[/C][C]0.947368421052632[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]146[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]147[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]1.15[/C][C]-0.15[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[ROW][C]152[/C][C]2[/C][C]1.05263157894737[/C][C]0.947368421052632[/C][/ROW]
[ROW][C]153[/C][C]2[/C][C]1.05263157894737[/C][C]0.947368421052632[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]1.05263157894737[/C][C]-0.0526315789473684[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203364&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203364&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
111.15-0.15
211.05263157894737-0.0526315789473685
311.05263157894737-0.0526315789473684
411.05263157894737-0.0526315789473684
511.05263157894737-0.0526315789473684
611.05263157894737-0.0526315789473684
711.05263157894737-0.0526315789473684
811.15-0.15
911.05263157894737-0.0526315789473684
1011.05263157894737-0.0526315789473684
1111.15-0.15
1211.05263157894737-0.0526315789473684
1311.05263157894737-0.0526315789473684
1411.15-0.15
1511.05263157894737-0.0526315789473684
1611.15-0.15
1721.150.85
1811.15-0.15
1911.05263157894737-0.0526315789473684
2021.150.85
2111.05263157894737-0.0526315789473684
2211.05263157894737-0.0526315789473684
2311.05263157894737-0.0526315789473684
2411.05263157894737-0.0526315789473684
2511.15-0.15
2611.05263157894737-0.0526315789473684
2711.05263157894737-0.0526315789473684
2811.05263157894737-0.0526315789473684
2911.05263157894737-0.0526315789473684
3011.05263157894737-0.0526315789473684
3111.05263157894737-0.0526315789473684
3211.05263157894737-0.0526315789473684
3311.05263157894737-0.0526315789473684
3411.15-0.15
3511.05263157894737-0.0526315789473684
3611.05263157894737-0.0526315789473684
3711.15-0.15
3811.05263157894737-0.0526315789473684
3911.05263157894737-0.0526315789473684
4011.15-0.15
4121.052631578947370.947368421052632
4211.05263157894737-0.0526315789473684
4311.05263157894737-0.0526315789473684
4411.15-0.15
4511.05263157894737-0.0526315789473684
4611.05263157894737-0.0526315789473684
4711.05263157894737-0.0526315789473684
4811.05263157894737-0.0526315789473684
4911.05263157894737-0.0526315789473684
5011.05263157894737-0.0526315789473684
5111.15-0.15
5221.150.85
5311.05263157894737-0.0526315789473684
5421.052631578947370.947368421052632
5511.05263157894737-0.0526315789473684
5611.15-0.15
5711.05263157894737-0.0526315789473684
5811.05263157894737-0.0526315789473684
5911.05263157894737-0.0526315789473684
6021.150.85
6111.15-0.15
6211.05263157894737-0.0526315789473684
6311.05263157894737-0.0526315789473684
6411.15-0.15
6511.05263157894737-0.0526315789473684
6611.05263157894737-0.0526315789473684
6721.150.85
6811.05263157894737-0.0526315789473684
6911.05263157894737-0.0526315789473684
7011.05263157894737-0.0526315789473684
7111.05263157894737-0.0526315789473684
7211.05263157894737-0.0526315789473684
7311.05263157894737-0.0526315789473684
7411.05263157894737-0.0526315789473684
7511.05263157894737-0.0526315789473684
7611.15-0.15
7711.05263157894737-0.0526315789473684
7811.05263157894737-0.0526315789473684
7921.150.85
8011.15-0.15
8111.05263157894737-0.0526315789473684
8211.05263157894737-0.0526315789473684
8311.05263157894737-0.0526315789473684
8421.052631578947370.947368421052632
8511.05263157894737-0.0526315789473684
8611.05263157894737-0.0526315789473684
8711.05263157894737-0.0526315789473684
8811.15-0.15
8911.05263157894737-0.0526315789473684
9011.05263157894737-0.0526315789473684
9111.05263157894737-0.0526315789473684
9211.15-0.15
9311.05263157894737-0.0526315789473684
9411.05263157894737-0.0526315789473684
9511.15-0.15
9611.05263157894737-0.0526315789473684
9711.15-0.15
9811.05263157894737-0.0526315789473684
9911.05263157894737-0.0526315789473684
10011.05263157894737-0.0526315789473684
10111.05263157894737-0.0526315789473684
10211.05263157894737-0.0526315789473684
10311.05263157894737-0.0526315789473684
10411.05263157894737-0.0526315789473684
10511.15-0.15
10611.05263157894737-0.0526315789473684
10711.05263157894737-0.0526315789473684
10811.15-0.15
10911.05263157894737-0.0526315789473684
11011.05263157894737-0.0526315789473684
11111.15-0.15
11211.15-0.15
11311.05263157894737-0.0526315789473684
11411.15-0.15
11511.05263157894737-0.0526315789473684
11611.05263157894737-0.0526315789473684
11711.05263157894737-0.0526315789473684
11811.05263157894737-0.0526315789473684
11911.05263157894737-0.0526315789473684
12011.05263157894737-0.0526315789473684
12111.05263157894737-0.0526315789473684
12211.05263157894737-0.0526315789473684
12311.15-0.15
12411.05263157894737-0.0526315789473684
12511.05263157894737-0.0526315789473684
12611.15-0.15
12711.05263157894737-0.0526315789473684
12811.05263157894737-0.0526315789473684
12911.05263157894737-0.0526315789473684
13011.05263157894737-0.0526315789473684
13111.05263157894737-0.0526315789473684
13211.05263157894737-0.0526315789473684
13311.05263157894737-0.0526315789473684
13411.05263157894737-0.0526315789473684
13511.05263157894737-0.0526315789473684
13611.05263157894737-0.0526315789473684
13711.05263157894737-0.0526315789473684
13811.15-0.15
13911.15-0.15
14011.05263157894737-0.0526315789473684
14121.052631578947370.947368421052632
14211.15-0.15
14311.05263157894737-0.0526315789473684
14411.05263157894737-0.0526315789473684
14511.05263157894737-0.0526315789473684
14611.15-0.15
14711.15-0.15
14811.15-0.15
14911.05263157894737-0.0526315789473684
15011.05263157894737-0.0526315789473684
15111.05263157894737-0.0526315789473684
15221.052631578947370.947368421052632
15321.052631578947370.947368421052632
15411.05263157894737-0.0526315789473684







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
5001
67.20813905825587e-1281.44162781165117e-1271
77.58003760833375e-1621.51600752166675e-1611
82.19972755282718e-924.39945510565436e-921
92.19989326159289e-1104.39978652318578e-1101
104.47975901180034e-1268.95951802360067e-1261
117.19299095226655e-1481.43859819045331e-1471
121.65839512745184e-1533.31679025490368e-1531
131.35196442089683e-1912.70392884179367e-1911
141.8905536112752e-1823.78110722255041e-1821
158.04568822984911e-1981.60913764596982e-1971
16001
170.2769984395782930.5539968791565870.723001560421707
180.2360283047661330.4720566095322650.763971695233867
190.180131591725960.360263183451920.81986840827404
200.731999040496550.5360019190068990.26800095950345
210.6718749321126890.6562501357746220.328125067887311
220.6079768715964920.7840462568070170.392023128403508
230.5420291324060450.915941735187910.457970867593955
240.4758484799633140.9516969599266280.524151520036686
250.4564318029267130.9128636058534260.543568197073287
260.3933802402883620.7867604805767240.606619759711638
270.3337252891996050.667450578399210.666274710800395
280.2786273675894940.5572547351789880.721372632410506
290.2289101964477410.4578203928954820.771089803552259
300.1850492885579480.3700985771158970.814950711442051
310.14719260981150.2943852196230010.8528073901885
320.1152056153263510.2304112306527010.884794384673649
330.08873136797558730.1774627359511750.911268632024413
340.08059814498788740.1611962899757750.919401855012113
350.06090106502403630.1218021300480730.939098934975964
360.04530429219168680.09060858438337370.954695707808313
370.03946083025571790.07892166051143580.960539169744282
380.0287650670448950.05753013408979010.971234932955105
390.02065295870322940.04130591740645880.979347041296771
400.01727318319484070.03454636638968150.982726816805159
410.3946317187412970.7892634374825950.605368281258703
420.345616889855170.691233779710340.65438311014483
430.2993054103863760.5986108207727510.700694589613624
440.270357691426940.540715382853880.72964230857306
450.2298143063541180.4596286127082360.770185693645882
460.1930920886548040.3861841773096070.806907911345196
470.1603433740017980.3206867480035960.839656625998202
480.1315820300874040.2631640601748080.868417969912596
490.1067013259119740.2134026518239480.893298674088026
500.08549624653056130.1709924930611230.914503753469439
510.07299560497448350.1459912099489670.927004395025516
520.3817635362125780.7635270724251570.618236463787422
530.3367784461645150.673556892329030.663221553835485
540.8377203390258940.3245593219482130.162279660974106
550.8075549316509360.3848901366981270.192445068349064
560.7866907315192890.4266185369614230.213309268480711
570.7515558911281480.4968882177437030.248444108871852
580.7136357917207920.5727284165584160.286364208279208
590.6732545709856560.6534908580286880.326745429014344
600.9287495040343290.1425009919313420.0712504959656711
610.919182403465640.1616351930687210.0808175965343604
620.9008128863048870.1983742273902270.0991871136951133
630.8795981853987270.2408036292025470.120401814601273
640.8648029739002770.2703940521994460.135197026099723
650.8387385359328440.3225229281343120.161261464067156
660.8096414237473540.3807171525052920.190358576252646
670.9748590754361950.05028184912760980.0251409245638049
680.9675371131675670.06492577366486530.0324628868324326
690.9585499389416450.08290012211671070.0414500610583554
700.9476574508633920.1046850982732160.0523425491366079
710.9346210359797370.1307579280405260.0653789640202629
720.9192134550916950.1615730898166090.0807865449083045
730.9012299979690270.1975400040619450.0987700020309725
740.8805004031784290.2389991936431420.119499596821571
750.8569008895346510.2861982209306980.143099110465349
760.8407764711221650.3184470577556690.159223528877835
770.8123882580619710.3752234838760590.187611741938029
780.7810961538851920.4378076922296150.218903846114808
790.978485327595750.04302934480849980.0215146724042499
800.9746515911786430.05069681764271420.0253484088213571
810.9673669300557490.06526613988850180.0326330699442509
820.9584422854185030.08311542916299410.041557714581497
830.9476425274821170.1047149450357660.0523574725178828
840.9992596655721890.001480668855622680.000740334427811342
850.9989116973556610.002176605288678320.00108830264433916
860.998418807190440.003162385619119590.00158119280955979
870.997729396159110.004541207681780.00227060384089
880.9970533925422550.005893214915490610.00294660745774531
890.9958504183087640.00829916338247130.00414958169123565
900.994223959093230.01155208181354020.00577604090677009
910.9920528521266080.01589429574678310.00794714787339155
920.9898969770509430.02020604589811360.0101030229490568
930.9863714180879390.02725716382412190.0136285819120609
940.9818265392835410.03634692143291710.0181734607164585
950.9772612965464640.04547740690707130.0227387034535357
960.9702775367512760.05944492649744860.0297224632487243
970.9631741501321640.07365169973567280.0368258498678364
980.9528235754079740.09435284918405250.0471764245920263
990.9402459202638950.119508159472210.0597540797361049
1000.9251639556280380.1496720887439230.0748360443719615
1010.907319217025530.1853615659489410.0926807829744703
1020.8864874057153720.2270251885692550.113512594284628
1030.8624947332607750.2750105334784490.137505266739225
1040.8352341618841730.3295316762316540.164765838115827
1050.8085509212263290.3828981575473420.191449078773671
1060.7749770654109410.4500458691781180.225022934589059
1070.7382769907908880.5234460184182230.261723009209112
1080.7025465313090150.594906937381970.297453468690985
1090.6604507141868330.6790985716263340.339549285813167
1100.6162337354815830.7675325290368340.383766264518417
1110.573567808109950.8528643837801010.42643219189005
1120.5291305602643170.9417388794713660.470869439735683
1130.4814017382906710.9628034765813420.518598261709329
1140.4356581736662360.8713163473324710.564341826333765
1150.388724445263210.7774488905264210.61127555473679
1160.3433455240711790.6866910481423570.656654475928821
1170.3001208114760890.6002416229521780.699879188523911
1180.2595613304249490.5191226608498970.740438669575051
1190.2220714025887270.4441428051774540.777928597411273
1200.1879374958984810.3758749917969610.812062504101519
1210.1573246877216370.3146493754432740.842675312278363
1220.1302804936495840.2605609872991670.869719506350416
1230.1054155922044490.2108311844088980.894584407795551
1240.08509033833327180.1701806766665440.914909661666728
1250.06794629566040640.1358925913208130.932053704339594
1260.05231616981712860.1046323396342570.947683830182871
1270.04065458581896640.08130917163793270.959345414181034
1280.03127499958274690.06254999916549390.968725000417253
1290.02384245411566720.04768490823133440.976157545884333
1300.01803804824812040.03607609649624070.98196195175188
1310.01356917749954020.02713835499908050.98643082250046
1320.01017607441990340.02035214883980680.989823925580097
1330.007635045534628530.01527009106925710.992364954465371
1340.00575903586827850.0115180717365570.994240964131721
1350.004396309613104380.008792619226208750.995603690386896
1360.003428173881459670.006856347762919330.99657182611854
1370.002766940182735920.005533880365471850.997233059817264
1380.001656774645683390.003313549291366780.998343225354317
1390.0009534765168070270.001906953033614050.999046523483193
1400.0007728636299353910.001545727259870780.999227136370065
1410.01642011740220730.03284023480441460.983579882597793
1420.009881408373273410.01976281674654680.990118591626727
1430.007284575621522440.01456915124304490.992715424378478
1440.005654119258973140.01130823851794630.994345880741027
1450.004859628576350880.009719257152701770.995140371423649
1460.0023816617758080.0047633235516160.997618338224192
1470.001057286272219410.002114572544438820.998942713727781
1480.0004147927449494390.0008295854898988780.999585207255051
1490.0003384572405281540.0006769144810563090.999661542759472

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
5 & 0 & 0 & 1 \tabularnewline
6 & 7.20813905825587e-128 & 1.44162781165117e-127 & 1 \tabularnewline
7 & 7.58003760833375e-162 & 1.51600752166675e-161 & 1 \tabularnewline
8 & 2.19972755282718e-92 & 4.39945510565436e-92 & 1 \tabularnewline
9 & 2.19989326159289e-110 & 4.39978652318578e-110 & 1 \tabularnewline
10 & 4.47975901180034e-126 & 8.95951802360067e-126 & 1 \tabularnewline
11 & 7.19299095226655e-148 & 1.43859819045331e-147 & 1 \tabularnewline
12 & 1.65839512745184e-153 & 3.31679025490368e-153 & 1 \tabularnewline
13 & 1.35196442089683e-191 & 2.70392884179367e-191 & 1 \tabularnewline
14 & 1.8905536112752e-182 & 3.78110722255041e-182 & 1 \tabularnewline
15 & 8.04568822984911e-198 & 1.60913764596982e-197 & 1 \tabularnewline
16 & 0 & 0 & 1 \tabularnewline
17 & 0.276998439578293 & 0.553996879156587 & 0.723001560421707 \tabularnewline
18 & 0.236028304766133 & 0.472056609532265 & 0.763971695233867 \tabularnewline
19 & 0.18013159172596 & 0.36026318345192 & 0.81986840827404 \tabularnewline
20 & 0.73199904049655 & 0.536001919006899 & 0.26800095950345 \tabularnewline
21 & 0.671874932112689 & 0.656250135774622 & 0.328125067887311 \tabularnewline
22 & 0.607976871596492 & 0.784046256807017 & 0.392023128403508 \tabularnewline
23 & 0.542029132406045 & 0.91594173518791 & 0.457970867593955 \tabularnewline
24 & 0.475848479963314 & 0.951696959926628 & 0.524151520036686 \tabularnewline
25 & 0.456431802926713 & 0.912863605853426 & 0.543568197073287 \tabularnewline
26 & 0.393380240288362 & 0.786760480576724 & 0.606619759711638 \tabularnewline
27 & 0.333725289199605 & 0.66745057839921 & 0.666274710800395 \tabularnewline
28 & 0.278627367589494 & 0.557254735178988 & 0.721372632410506 \tabularnewline
29 & 0.228910196447741 & 0.457820392895482 & 0.771089803552259 \tabularnewline
30 & 0.185049288557948 & 0.370098577115897 & 0.814950711442051 \tabularnewline
31 & 0.1471926098115 & 0.294385219623001 & 0.8528073901885 \tabularnewline
32 & 0.115205615326351 & 0.230411230652701 & 0.884794384673649 \tabularnewline
33 & 0.0887313679755873 & 0.177462735951175 & 0.911268632024413 \tabularnewline
34 & 0.0805981449878874 & 0.161196289975775 & 0.919401855012113 \tabularnewline
35 & 0.0609010650240363 & 0.121802130048073 & 0.939098934975964 \tabularnewline
36 & 0.0453042921916868 & 0.0906085843833737 & 0.954695707808313 \tabularnewline
37 & 0.0394608302557179 & 0.0789216605114358 & 0.960539169744282 \tabularnewline
38 & 0.028765067044895 & 0.0575301340897901 & 0.971234932955105 \tabularnewline
39 & 0.0206529587032294 & 0.0413059174064588 & 0.979347041296771 \tabularnewline
40 & 0.0172731831948407 & 0.0345463663896815 & 0.982726816805159 \tabularnewline
41 & 0.394631718741297 & 0.789263437482595 & 0.605368281258703 \tabularnewline
42 & 0.34561688985517 & 0.69123377971034 & 0.65438311014483 \tabularnewline
43 & 0.299305410386376 & 0.598610820772751 & 0.700694589613624 \tabularnewline
44 & 0.27035769142694 & 0.54071538285388 & 0.72964230857306 \tabularnewline
45 & 0.229814306354118 & 0.459628612708236 & 0.770185693645882 \tabularnewline
46 & 0.193092088654804 & 0.386184177309607 & 0.806907911345196 \tabularnewline
47 & 0.160343374001798 & 0.320686748003596 & 0.839656625998202 \tabularnewline
48 & 0.131582030087404 & 0.263164060174808 & 0.868417969912596 \tabularnewline
49 & 0.106701325911974 & 0.213402651823948 & 0.893298674088026 \tabularnewline
50 & 0.0854962465305613 & 0.170992493061123 & 0.914503753469439 \tabularnewline
51 & 0.0729956049744835 & 0.145991209948967 & 0.927004395025516 \tabularnewline
52 & 0.381763536212578 & 0.763527072425157 & 0.618236463787422 \tabularnewline
53 & 0.336778446164515 & 0.67355689232903 & 0.663221553835485 \tabularnewline
54 & 0.837720339025894 & 0.324559321948213 & 0.162279660974106 \tabularnewline
55 & 0.807554931650936 & 0.384890136698127 & 0.192445068349064 \tabularnewline
56 & 0.786690731519289 & 0.426618536961423 & 0.213309268480711 \tabularnewline
57 & 0.751555891128148 & 0.496888217743703 & 0.248444108871852 \tabularnewline
58 & 0.713635791720792 & 0.572728416558416 & 0.286364208279208 \tabularnewline
59 & 0.673254570985656 & 0.653490858028688 & 0.326745429014344 \tabularnewline
60 & 0.928749504034329 & 0.142500991931342 & 0.0712504959656711 \tabularnewline
61 & 0.91918240346564 & 0.161635193068721 & 0.0808175965343604 \tabularnewline
62 & 0.900812886304887 & 0.198374227390227 & 0.0991871136951133 \tabularnewline
63 & 0.879598185398727 & 0.240803629202547 & 0.120401814601273 \tabularnewline
64 & 0.864802973900277 & 0.270394052199446 & 0.135197026099723 \tabularnewline
65 & 0.838738535932844 & 0.322522928134312 & 0.161261464067156 \tabularnewline
66 & 0.809641423747354 & 0.380717152505292 & 0.190358576252646 \tabularnewline
67 & 0.974859075436195 & 0.0502818491276098 & 0.0251409245638049 \tabularnewline
68 & 0.967537113167567 & 0.0649257736648653 & 0.0324628868324326 \tabularnewline
69 & 0.958549938941645 & 0.0829001221167107 & 0.0414500610583554 \tabularnewline
70 & 0.947657450863392 & 0.104685098273216 & 0.0523425491366079 \tabularnewline
71 & 0.934621035979737 & 0.130757928040526 & 0.0653789640202629 \tabularnewline
72 & 0.919213455091695 & 0.161573089816609 & 0.0807865449083045 \tabularnewline
73 & 0.901229997969027 & 0.197540004061945 & 0.0987700020309725 \tabularnewline
74 & 0.880500403178429 & 0.238999193643142 & 0.119499596821571 \tabularnewline
75 & 0.856900889534651 & 0.286198220930698 & 0.143099110465349 \tabularnewline
76 & 0.840776471122165 & 0.318447057755669 & 0.159223528877835 \tabularnewline
77 & 0.812388258061971 & 0.375223483876059 & 0.187611741938029 \tabularnewline
78 & 0.781096153885192 & 0.437807692229615 & 0.218903846114808 \tabularnewline
79 & 0.97848532759575 & 0.0430293448084998 & 0.0215146724042499 \tabularnewline
80 & 0.974651591178643 & 0.0506968176427142 & 0.0253484088213571 \tabularnewline
81 & 0.967366930055749 & 0.0652661398885018 & 0.0326330699442509 \tabularnewline
82 & 0.958442285418503 & 0.0831154291629941 & 0.041557714581497 \tabularnewline
83 & 0.947642527482117 & 0.104714945035766 & 0.0523574725178828 \tabularnewline
84 & 0.999259665572189 & 0.00148066885562268 & 0.000740334427811342 \tabularnewline
85 & 0.998911697355661 & 0.00217660528867832 & 0.00108830264433916 \tabularnewline
86 & 0.99841880719044 & 0.00316238561911959 & 0.00158119280955979 \tabularnewline
87 & 0.99772939615911 & 0.00454120768178 & 0.00227060384089 \tabularnewline
88 & 0.997053392542255 & 0.00589321491549061 & 0.00294660745774531 \tabularnewline
89 & 0.995850418308764 & 0.0082991633824713 & 0.00414958169123565 \tabularnewline
90 & 0.99422395909323 & 0.0115520818135402 & 0.00577604090677009 \tabularnewline
91 & 0.992052852126608 & 0.0158942957467831 & 0.00794714787339155 \tabularnewline
92 & 0.989896977050943 & 0.0202060458981136 & 0.0101030229490568 \tabularnewline
93 & 0.986371418087939 & 0.0272571638241219 & 0.0136285819120609 \tabularnewline
94 & 0.981826539283541 & 0.0363469214329171 & 0.0181734607164585 \tabularnewline
95 & 0.977261296546464 & 0.0454774069070713 & 0.0227387034535357 \tabularnewline
96 & 0.970277536751276 & 0.0594449264974486 & 0.0297224632487243 \tabularnewline
97 & 0.963174150132164 & 0.0736516997356728 & 0.0368258498678364 \tabularnewline
98 & 0.952823575407974 & 0.0943528491840525 & 0.0471764245920263 \tabularnewline
99 & 0.940245920263895 & 0.11950815947221 & 0.0597540797361049 \tabularnewline
100 & 0.925163955628038 & 0.149672088743923 & 0.0748360443719615 \tabularnewline
101 & 0.90731921702553 & 0.185361565948941 & 0.0926807829744703 \tabularnewline
102 & 0.886487405715372 & 0.227025188569255 & 0.113512594284628 \tabularnewline
103 & 0.862494733260775 & 0.275010533478449 & 0.137505266739225 \tabularnewline
104 & 0.835234161884173 & 0.329531676231654 & 0.164765838115827 \tabularnewline
105 & 0.808550921226329 & 0.382898157547342 & 0.191449078773671 \tabularnewline
106 & 0.774977065410941 & 0.450045869178118 & 0.225022934589059 \tabularnewline
107 & 0.738276990790888 & 0.523446018418223 & 0.261723009209112 \tabularnewline
108 & 0.702546531309015 & 0.59490693738197 & 0.297453468690985 \tabularnewline
109 & 0.660450714186833 & 0.679098571626334 & 0.339549285813167 \tabularnewline
110 & 0.616233735481583 & 0.767532529036834 & 0.383766264518417 \tabularnewline
111 & 0.57356780810995 & 0.852864383780101 & 0.42643219189005 \tabularnewline
112 & 0.529130560264317 & 0.941738879471366 & 0.470869439735683 \tabularnewline
113 & 0.481401738290671 & 0.962803476581342 & 0.518598261709329 \tabularnewline
114 & 0.435658173666236 & 0.871316347332471 & 0.564341826333765 \tabularnewline
115 & 0.38872444526321 & 0.777448890526421 & 0.61127555473679 \tabularnewline
116 & 0.343345524071179 & 0.686691048142357 & 0.656654475928821 \tabularnewline
117 & 0.300120811476089 & 0.600241622952178 & 0.699879188523911 \tabularnewline
118 & 0.259561330424949 & 0.519122660849897 & 0.740438669575051 \tabularnewline
119 & 0.222071402588727 & 0.444142805177454 & 0.777928597411273 \tabularnewline
120 & 0.187937495898481 & 0.375874991796961 & 0.812062504101519 \tabularnewline
121 & 0.157324687721637 & 0.314649375443274 & 0.842675312278363 \tabularnewline
122 & 0.130280493649584 & 0.260560987299167 & 0.869719506350416 \tabularnewline
123 & 0.105415592204449 & 0.210831184408898 & 0.894584407795551 \tabularnewline
124 & 0.0850903383332718 & 0.170180676666544 & 0.914909661666728 \tabularnewline
125 & 0.0679462956604064 & 0.135892591320813 & 0.932053704339594 \tabularnewline
126 & 0.0523161698171286 & 0.104632339634257 & 0.947683830182871 \tabularnewline
127 & 0.0406545858189664 & 0.0813091716379327 & 0.959345414181034 \tabularnewline
128 & 0.0312749995827469 & 0.0625499991654939 & 0.968725000417253 \tabularnewline
129 & 0.0238424541156672 & 0.0476849082313344 & 0.976157545884333 \tabularnewline
130 & 0.0180380482481204 & 0.0360760964962407 & 0.98196195175188 \tabularnewline
131 & 0.0135691774995402 & 0.0271383549990805 & 0.98643082250046 \tabularnewline
132 & 0.0101760744199034 & 0.0203521488398068 & 0.989823925580097 \tabularnewline
133 & 0.00763504553462853 & 0.0152700910692571 & 0.992364954465371 \tabularnewline
134 & 0.0057590358682785 & 0.011518071736557 & 0.994240964131721 \tabularnewline
135 & 0.00439630961310438 & 0.00879261922620875 & 0.995603690386896 \tabularnewline
136 & 0.00342817388145967 & 0.00685634776291933 & 0.99657182611854 \tabularnewline
137 & 0.00276694018273592 & 0.00553388036547185 & 0.997233059817264 \tabularnewline
138 & 0.00165677464568339 & 0.00331354929136678 & 0.998343225354317 \tabularnewline
139 & 0.000953476516807027 & 0.00190695303361405 & 0.999046523483193 \tabularnewline
140 & 0.000772863629935391 & 0.00154572725987078 & 0.999227136370065 \tabularnewline
141 & 0.0164201174022073 & 0.0328402348044146 & 0.983579882597793 \tabularnewline
142 & 0.00988140837327341 & 0.0197628167465468 & 0.990118591626727 \tabularnewline
143 & 0.00728457562152244 & 0.0145691512430449 & 0.992715424378478 \tabularnewline
144 & 0.00565411925897314 & 0.0113082385179463 & 0.994345880741027 \tabularnewline
145 & 0.00485962857635088 & 0.00971925715270177 & 0.995140371423649 \tabularnewline
146 & 0.002381661775808 & 0.004763323551616 & 0.997618338224192 \tabularnewline
147 & 0.00105728627221941 & 0.00211457254443882 & 0.998942713727781 \tabularnewline
148 & 0.000414792744949439 & 0.000829585489898878 & 0.999585207255051 \tabularnewline
149 & 0.000338457240528154 & 0.000676914481056309 & 0.999661542759472 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203364&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]5[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]6[/C][C]7.20813905825587e-128[/C][C]1.44162781165117e-127[/C][C]1[/C][/ROW]
[ROW][C]7[/C][C]7.58003760833375e-162[/C][C]1.51600752166675e-161[/C][C]1[/C][/ROW]
[ROW][C]8[/C][C]2.19972755282718e-92[/C][C]4.39945510565436e-92[/C][C]1[/C][/ROW]
[ROW][C]9[/C][C]2.19989326159289e-110[/C][C]4.39978652318578e-110[/C][C]1[/C][/ROW]
[ROW][C]10[/C][C]4.47975901180034e-126[/C][C]8.95951802360067e-126[/C][C]1[/C][/ROW]
[ROW][C]11[/C][C]7.19299095226655e-148[/C][C]1.43859819045331e-147[/C][C]1[/C][/ROW]
[ROW][C]12[/C][C]1.65839512745184e-153[/C][C]3.31679025490368e-153[/C][C]1[/C][/ROW]
[ROW][C]13[/C][C]1.35196442089683e-191[/C][C]2.70392884179367e-191[/C][C]1[/C][/ROW]
[ROW][C]14[/C][C]1.8905536112752e-182[/C][C]3.78110722255041e-182[/C][C]1[/C][/ROW]
[ROW][C]15[/C][C]8.04568822984911e-198[/C][C]1.60913764596982e-197[/C][C]1[/C][/ROW]
[ROW][C]16[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]17[/C][C]0.276998439578293[/C][C]0.553996879156587[/C][C]0.723001560421707[/C][/ROW]
[ROW][C]18[/C][C]0.236028304766133[/C][C]0.472056609532265[/C][C]0.763971695233867[/C][/ROW]
[ROW][C]19[/C][C]0.18013159172596[/C][C]0.36026318345192[/C][C]0.81986840827404[/C][/ROW]
[ROW][C]20[/C][C]0.73199904049655[/C][C]0.536001919006899[/C][C]0.26800095950345[/C][/ROW]
[ROW][C]21[/C][C]0.671874932112689[/C][C]0.656250135774622[/C][C]0.328125067887311[/C][/ROW]
[ROW][C]22[/C][C]0.607976871596492[/C][C]0.784046256807017[/C][C]0.392023128403508[/C][/ROW]
[ROW][C]23[/C][C]0.542029132406045[/C][C]0.91594173518791[/C][C]0.457970867593955[/C][/ROW]
[ROW][C]24[/C][C]0.475848479963314[/C][C]0.951696959926628[/C][C]0.524151520036686[/C][/ROW]
[ROW][C]25[/C][C]0.456431802926713[/C][C]0.912863605853426[/C][C]0.543568197073287[/C][/ROW]
[ROW][C]26[/C][C]0.393380240288362[/C][C]0.786760480576724[/C][C]0.606619759711638[/C][/ROW]
[ROW][C]27[/C][C]0.333725289199605[/C][C]0.66745057839921[/C][C]0.666274710800395[/C][/ROW]
[ROW][C]28[/C][C]0.278627367589494[/C][C]0.557254735178988[/C][C]0.721372632410506[/C][/ROW]
[ROW][C]29[/C][C]0.228910196447741[/C][C]0.457820392895482[/C][C]0.771089803552259[/C][/ROW]
[ROW][C]30[/C][C]0.185049288557948[/C][C]0.370098577115897[/C][C]0.814950711442051[/C][/ROW]
[ROW][C]31[/C][C]0.1471926098115[/C][C]0.294385219623001[/C][C]0.8528073901885[/C][/ROW]
[ROW][C]32[/C][C]0.115205615326351[/C][C]0.230411230652701[/C][C]0.884794384673649[/C][/ROW]
[ROW][C]33[/C][C]0.0887313679755873[/C][C]0.177462735951175[/C][C]0.911268632024413[/C][/ROW]
[ROW][C]34[/C][C]0.0805981449878874[/C][C]0.161196289975775[/C][C]0.919401855012113[/C][/ROW]
[ROW][C]35[/C][C]0.0609010650240363[/C][C]0.121802130048073[/C][C]0.939098934975964[/C][/ROW]
[ROW][C]36[/C][C]0.0453042921916868[/C][C]0.0906085843833737[/C][C]0.954695707808313[/C][/ROW]
[ROW][C]37[/C][C]0.0394608302557179[/C][C]0.0789216605114358[/C][C]0.960539169744282[/C][/ROW]
[ROW][C]38[/C][C]0.028765067044895[/C][C]0.0575301340897901[/C][C]0.971234932955105[/C][/ROW]
[ROW][C]39[/C][C]0.0206529587032294[/C][C]0.0413059174064588[/C][C]0.979347041296771[/C][/ROW]
[ROW][C]40[/C][C]0.0172731831948407[/C][C]0.0345463663896815[/C][C]0.982726816805159[/C][/ROW]
[ROW][C]41[/C][C]0.394631718741297[/C][C]0.789263437482595[/C][C]0.605368281258703[/C][/ROW]
[ROW][C]42[/C][C]0.34561688985517[/C][C]0.69123377971034[/C][C]0.65438311014483[/C][/ROW]
[ROW][C]43[/C][C]0.299305410386376[/C][C]0.598610820772751[/C][C]0.700694589613624[/C][/ROW]
[ROW][C]44[/C][C]0.27035769142694[/C][C]0.54071538285388[/C][C]0.72964230857306[/C][/ROW]
[ROW][C]45[/C][C]0.229814306354118[/C][C]0.459628612708236[/C][C]0.770185693645882[/C][/ROW]
[ROW][C]46[/C][C]0.193092088654804[/C][C]0.386184177309607[/C][C]0.806907911345196[/C][/ROW]
[ROW][C]47[/C][C]0.160343374001798[/C][C]0.320686748003596[/C][C]0.839656625998202[/C][/ROW]
[ROW][C]48[/C][C]0.131582030087404[/C][C]0.263164060174808[/C][C]0.868417969912596[/C][/ROW]
[ROW][C]49[/C][C]0.106701325911974[/C][C]0.213402651823948[/C][C]0.893298674088026[/C][/ROW]
[ROW][C]50[/C][C]0.0854962465305613[/C][C]0.170992493061123[/C][C]0.914503753469439[/C][/ROW]
[ROW][C]51[/C][C]0.0729956049744835[/C][C]0.145991209948967[/C][C]0.927004395025516[/C][/ROW]
[ROW][C]52[/C][C]0.381763536212578[/C][C]0.763527072425157[/C][C]0.618236463787422[/C][/ROW]
[ROW][C]53[/C][C]0.336778446164515[/C][C]0.67355689232903[/C][C]0.663221553835485[/C][/ROW]
[ROW][C]54[/C][C]0.837720339025894[/C][C]0.324559321948213[/C][C]0.162279660974106[/C][/ROW]
[ROW][C]55[/C][C]0.807554931650936[/C][C]0.384890136698127[/C][C]0.192445068349064[/C][/ROW]
[ROW][C]56[/C][C]0.786690731519289[/C][C]0.426618536961423[/C][C]0.213309268480711[/C][/ROW]
[ROW][C]57[/C][C]0.751555891128148[/C][C]0.496888217743703[/C][C]0.248444108871852[/C][/ROW]
[ROW][C]58[/C][C]0.713635791720792[/C][C]0.572728416558416[/C][C]0.286364208279208[/C][/ROW]
[ROW][C]59[/C][C]0.673254570985656[/C][C]0.653490858028688[/C][C]0.326745429014344[/C][/ROW]
[ROW][C]60[/C][C]0.928749504034329[/C][C]0.142500991931342[/C][C]0.0712504959656711[/C][/ROW]
[ROW][C]61[/C][C]0.91918240346564[/C][C]0.161635193068721[/C][C]0.0808175965343604[/C][/ROW]
[ROW][C]62[/C][C]0.900812886304887[/C][C]0.198374227390227[/C][C]0.0991871136951133[/C][/ROW]
[ROW][C]63[/C][C]0.879598185398727[/C][C]0.240803629202547[/C][C]0.120401814601273[/C][/ROW]
[ROW][C]64[/C][C]0.864802973900277[/C][C]0.270394052199446[/C][C]0.135197026099723[/C][/ROW]
[ROW][C]65[/C][C]0.838738535932844[/C][C]0.322522928134312[/C][C]0.161261464067156[/C][/ROW]
[ROW][C]66[/C][C]0.809641423747354[/C][C]0.380717152505292[/C][C]0.190358576252646[/C][/ROW]
[ROW][C]67[/C][C]0.974859075436195[/C][C]0.0502818491276098[/C][C]0.0251409245638049[/C][/ROW]
[ROW][C]68[/C][C]0.967537113167567[/C][C]0.0649257736648653[/C][C]0.0324628868324326[/C][/ROW]
[ROW][C]69[/C][C]0.958549938941645[/C][C]0.0829001221167107[/C][C]0.0414500610583554[/C][/ROW]
[ROW][C]70[/C][C]0.947657450863392[/C][C]0.104685098273216[/C][C]0.0523425491366079[/C][/ROW]
[ROW][C]71[/C][C]0.934621035979737[/C][C]0.130757928040526[/C][C]0.0653789640202629[/C][/ROW]
[ROW][C]72[/C][C]0.919213455091695[/C][C]0.161573089816609[/C][C]0.0807865449083045[/C][/ROW]
[ROW][C]73[/C][C]0.901229997969027[/C][C]0.197540004061945[/C][C]0.0987700020309725[/C][/ROW]
[ROW][C]74[/C][C]0.880500403178429[/C][C]0.238999193643142[/C][C]0.119499596821571[/C][/ROW]
[ROW][C]75[/C][C]0.856900889534651[/C][C]0.286198220930698[/C][C]0.143099110465349[/C][/ROW]
[ROW][C]76[/C][C]0.840776471122165[/C][C]0.318447057755669[/C][C]0.159223528877835[/C][/ROW]
[ROW][C]77[/C][C]0.812388258061971[/C][C]0.375223483876059[/C][C]0.187611741938029[/C][/ROW]
[ROW][C]78[/C][C]0.781096153885192[/C][C]0.437807692229615[/C][C]0.218903846114808[/C][/ROW]
[ROW][C]79[/C][C]0.97848532759575[/C][C]0.0430293448084998[/C][C]0.0215146724042499[/C][/ROW]
[ROW][C]80[/C][C]0.974651591178643[/C][C]0.0506968176427142[/C][C]0.0253484088213571[/C][/ROW]
[ROW][C]81[/C][C]0.967366930055749[/C][C]0.0652661398885018[/C][C]0.0326330699442509[/C][/ROW]
[ROW][C]82[/C][C]0.958442285418503[/C][C]0.0831154291629941[/C][C]0.041557714581497[/C][/ROW]
[ROW][C]83[/C][C]0.947642527482117[/C][C]0.104714945035766[/C][C]0.0523574725178828[/C][/ROW]
[ROW][C]84[/C][C]0.999259665572189[/C][C]0.00148066885562268[/C][C]0.000740334427811342[/C][/ROW]
[ROW][C]85[/C][C]0.998911697355661[/C][C]0.00217660528867832[/C][C]0.00108830264433916[/C][/ROW]
[ROW][C]86[/C][C]0.99841880719044[/C][C]0.00316238561911959[/C][C]0.00158119280955979[/C][/ROW]
[ROW][C]87[/C][C]0.99772939615911[/C][C]0.00454120768178[/C][C]0.00227060384089[/C][/ROW]
[ROW][C]88[/C][C]0.997053392542255[/C][C]0.00589321491549061[/C][C]0.00294660745774531[/C][/ROW]
[ROW][C]89[/C][C]0.995850418308764[/C][C]0.0082991633824713[/C][C]0.00414958169123565[/C][/ROW]
[ROW][C]90[/C][C]0.99422395909323[/C][C]0.0115520818135402[/C][C]0.00577604090677009[/C][/ROW]
[ROW][C]91[/C][C]0.992052852126608[/C][C]0.0158942957467831[/C][C]0.00794714787339155[/C][/ROW]
[ROW][C]92[/C][C]0.989896977050943[/C][C]0.0202060458981136[/C][C]0.0101030229490568[/C][/ROW]
[ROW][C]93[/C][C]0.986371418087939[/C][C]0.0272571638241219[/C][C]0.0136285819120609[/C][/ROW]
[ROW][C]94[/C][C]0.981826539283541[/C][C]0.0363469214329171[/C][C]0.0181734607164585[/C][/ROW]
[ROW][C]95[/C][C]0.977261296546464[/C][C]0.0454774069070713[/C][C]0.0227387034535357[/C][/ROW]
[ROW][C]96[/C][C]0.970277536751276[/C][C]0.0594449264974486[/C][C]0.0297224632487243[/C][/ROW]
[ROW][C]97[/C][C]0.963174150132164[/C][C]0.0736516997356728[/C][C]0.0368258498678364[/C][/ROW]
[ROW][C]98[/C][C]0.952823575407974[/C][C]0.0943528491840525[/C][C]0.0471764245920263[/C][/ROW]
[ROW][C]99[/C][C]0.940245920263895[/C][C]0.11950815947221[/C][C]0.0597540797361049[/C][/ROW]
[ROW][C]100[/C][C]0.925163955628038[/C][C]0.149672088743923[/C][C]0.0748360443719615[/C][/ROW]
[ROW][C]101[/C][C]0.90731921702553[/C][C]0.185361565948941[/C][C]0.0926807829744703[/C][/ROW]
[ROW][C]102[/C][C]0.886487405715372[/C][C]0.227025188569255[/C][C]0.113512594284628[/C][/ROW]
[ROW][C]103[/C][C]0.862494733260775[/C][C]0.275010533478449[/C][C]0.137505266739225[/C][/ROW]
[ROW][C]104[/C][C]0.835234161884173[/C][C]0.329531676231654[/C][C]0.164765838115827[/C][/ROW]
[ROW][C]105[/C][C]0.808550921226329[/C][C]0.382898157547342[/C][C]0.191449078773671[/C][/ROW]
[ROW][C]106[/C][C]0.774977065410941[/C][C]0.450045869178118[/C][C]0.225022934589059[/C][/ROW]
[ROW][C]107[/C][C]0.738276990790888[/C][C]0.523446018418223[/C][C]0.261723009209112[/C][/ROW]
[ROW][C]108[/C][C]0.702546531309015[/C][C]0.59490693738197[/C][C]0.297453468690985[/C][/ROW]
[ROW][C]109[/C][C]0.660450714186833[/C][C]0.679098571626334[/C][C]0.339549285813167[/C][/ROW]
[ROW][C]110[/C][C]0.616233735481583[/C][C]0.767532529036834[/C][C]0.383766264518417[/C][/ROW]
[ROW][C]111[/C][C]0.57356780810995[/C][C]0.852864383780101[/C][C]0.42643219189005[/C][/ROW]
[ROW][C]112[/C][C]0.529130560264317[/C][C]0.941738879471366[/C][C]0.470869439735683[/C][/ROW]
[ROW][C]113[/C][C]0.481401738290671[/C][C]0.962803476581342[/C][C]0.518598261709329[/C][/ROW]
[ROW][C]114[/C][C]0.435658173666236[/C][C]0.871316347332471[/C][C]0.564341826333765[/C][/ROW]
[ROW][C]115[/C][C]0.38872444526321[/C][C]0.777448890526421[/C][C]0.61127555473679[/C][/ROW]
[ROW][C]116[/C][C]0.343345524071179[/C][C]0.686691048142357[/C][C]0.656654475928821[/C][/ROW]
[ROW][C]117[/C][C]0.300120811476089[/C][C]0.600241622952178[/C][C]0.699879188523911[/C][/ROW]
[ROW][C]118[/C][C]0.259561330424949[/C][C]0.519122660849897[/C][C]0.740438669575051[/C][/ROW]
[ROW][C]119[/C][C]0.222071402588727[/C][C]0.444142805177454[/C][C]0.777928597411273[/C][/ROW]
[ROW][C]120[/C][C]0.187937495898481[/C][C]0.375874991796961[/C][C]0.812062504101519[/C][/ROW]
[ROW][C]121[/C][C]0.157324687721637[/C][C]0.314649375443274[/C][C]0.842675312278363[/C][/ROW]
[ROW][C]122[/C][C]0.130280493649584[/C][C]0.260560987299167[/C][C]0.869719506350416[/C][/ROW]
[ROW][C]123[/C][C]0.105415592204449[/C][C]0.210831184408898[/C][C]0.894584407795551[/C][/ROW]
[ROW][C]124[/C][C]0.0850903383332718[/C][C]0.170180676666544[/C][C]0.914909661666728[/C][/ROW]
[ROW][C]125[/C][C]0.0679462956604064[/C][C]0.135892591320813[/C][C]0.932053704339594[/C][/ROW]
[ROW][C]126[/C][C]0.0523161698171286[/C][C]0.104632339634257[/C][C]0.947683830182871[/C][/ROW]
[ROW][C]127[/C][C]0.0406545858189664[/C][C]0.0813091716379327[/C][C]0.959345414181034[/C][/ROW]
[ROW][C]128[/C][C]0.0312749995827469[/C][C]0.0625499991654939[/C][C]0.968725000417253[/C][/ROW]
[ROW][C]129[/C][C]0.0238424541156672[/C][C]0.0476849082313344[/C][C]0.976157545884333[/C][/ROW]
[ROW][C]130[/C][C]0.0180380482481204[/C][C]0.0360760964962407[/C][C]0.98196195175188[/C][/ROW]
[ROW][C]131[/C][C]0.0135691774995402[/C][C]0.0271383549990805[/C][C]0.98643082250046[/C][/ROW]
[ROW][C]132[/C][C]0.0101760744199034[/C][C]0.0203521488398068[/C][C]0.989823925580097[/C][/ROW]
[ROW][C]133[/C][C]0.00763504553462853[/C][C]0.0152700910692571[/C][C]0.992364954465371[/C][/ROW]
[ROW][C]134[/C][C]0.0057590358682785[/C][C]0.011518071736557[/C][C]0.994240964131721[/C][/ROW]
[ROW][C]135[/C][C]0.00439630961310438[/C][C]0.00879261922620875[/C][C]0.995603690386896[/C][/ROW]
[ROW][C]136[/C][C]0.00342817388145967[/C][C]0.00685634776291933[/C][C]0.99657182611854[/C][/ROW]
[ROW][C]137[/C][C]0.00276694018273592[/C][C]0.00553388036547185[/C][C]0.997233059817264[/C][/ROW]
[ROW][C]138[/C][C]0.00165677464568339[/C][C]0.00331354929136678[/C][C]0.998343225354317[/C][/ROW]
[ROW][C]139[/C][C]0.000953476516807027[/C][C]0.00190695303361405[/C][C]0.999046523483193[/C][/ROW]
[ROW][C]140[/C][C]0.000772863629935391[/C][C]0.00154572725987078[/C][C]0.999227136370065[/C][/ROW]
[ROW][C]141[/C][C]0.0164201174022073[/C][C]0.0328402348044146[/C][C]0.983579882597793[/C][/ROW]
[ROW][C]142[/C][C]0.00988140837327341[/C][C]0.0197628167465468[/C][C]0.990118591626727[/C][/ROW]
[ROW][C]143[/C][C]0.00728457562152244[/C][C]0.0145691512430449[/C][C]0.992715424378478[/C][/ROW]
[ROW][C]144[/C][C]0.00565411925897314[/C][C]0.0113082385179463[/C][C]0.994345880741027[/C][/ROW]
[ROW][C]145[/C][C]0.00485962857635088[/C][C]0.00971925715270177[/C][C]0.995140371423649[/C][/ROW]
[ROW][C]146[/C][C]0.002381661775808[/C][C]0.004763323551616[/C][C]0.997618338224192[/C][/ROW]
[ROW][C]147[/C][C]0.00105728627221941[/C][C]0.00211457254443882[/C][C]0.998942713727781[/C][/ROW]
[ROW][C]148[/C][C]0.000414792744949439[/C][C]0.000829585489898878[/C][C]0.999585207255051[/C][/ROW]
[ROW][C]149[/C][C]0.000338457240528154[/C][C]0.000676914481056309[/C][C]0.999661542759472[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203364&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203364&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
5001
67.20813905825587e-1281.44162781165117e-1271
77.58003760833375e-1621.51600752166675e-1611
82.19972755282718e-924.39945510565436e-921
92.19989326159289e-1104.39978652318578e-1101
104.47975901180034e-1268.95951802360067e-1261
117.19299095226655e-1481.43859819045331e-1471
121.65839512745184e-1533.31679025490368e-1531
131.35196442089683e-1912.70392884179367e-1911
141.8905536112752e-1823.78110722255041e-1821
158.04568822984911e-1981.60913764596982e-1971
16001
170.2769984395782930.5539968791565870.723001560421707
180.2360283047661330.4720566095322650.763971695233867
190.180131591725960.360263183451920.81986840827404
200.731999040496550.5360019190068990.26800095950345
210.6718749321126890.6562501357746220.328125067887311
220.6079768715964920.7840462568070170.392023128403508
230.5420291324060450.915941735187910.457970867593955
240.4758484799633140.9516969599266280.524151520036686
250.4564318029267130.9128636058534260.543568197073287
260.3933802402883620.7867604805767240.606619759711638
270.3337252891996050.667450578399210.666274710800395
280.2786273675894940.5572547351789880.721372632410506
290.2289101964477410.4578203928954820.771089803552259
300.1850492885579480.3700985771158970.814950711442051
310.14719260981150.2943852196230010.8528073901885
320.1152056153263510.2304112306527010.884794384673649
330.08873136797558730.1774627359511750.911268632024413
340.08059814498788740.1611962899757750.919401855012113
350.06090106502403630.1218021300480730.939098934975964
360.04530429219168680.09060858438337370.954695707808313
370.03946083025571790.07892166051143580.960539169744282
380.0287650670448950.05753013408979010.971234932955105
390.02065295870322940.04130591740645880.979347041296771
400.01727318319484070.03454636638968150.982726816805159
410.3946317187412970.7892634374825950.605368281258703
420.345616889855170.691233779710340.65438311014483
430.2993054103863760.5986108207727510.700694589613624
440.270357691426940.540715382853880.72964230857306
450.2298143063541180.4596286127082360.770185693645882
460.1930920886548040.3861841773096070.806907911345196
470.1603433740017980.3206867480035960.839656625998202
480.1315820300874040.2631640601748080.868417969912596
490.1067013259119740.2134026518239480.893298674088026
500.08549624653056130.1709924930611230.914503753469439
510.07299560497448350.1459912099489670.927004395025516
520.3817635362125780.7635270724251570.618236463787422
530.3367784461645150.673556892329030.663221553835485
540.8377203390258940.3245593219482130.162279660974106
550.8075549316509360.3848901366981270.192445068349064
560.7866907315192890.4266185369614230.213309268480711
570.7515558911281480.4968882177437030.248444108871852
580.7136357917207920.5727284165584160.286364208279208
590.6732545709856560.6534908580286880.326745429014344
600.9287495040343290.1425009919313420.0712504959656711
610.919182403465640.1616351930687210.0808175965343604
620.9008128863048870.1983742273902270.0991871136951133
630.8795981853987270.2408036292025470.120401814601273
640.8648029739002770.2703940521994460.135197026099723
650.8387385359328440.3225229281343120.161261464067156
660.8096414237473540.3807171525052920.190358576252646
670.9748590754361950.05028184912760980.0251409245638049
680.9675371131675670.06492577366486530.0324628868324326
690.9585499389416450.08290012211671070.0414500610583554
700.9476574508633920.1046850982732160.0523425491366079
710.9346210359797370.1307579280405260.0653789640202629
720.9192134550916950.1615730898166090.0807865449083045
730.9012299979690270.1975400040619450.0987700020309725
740.8805004031784290.2389991936431420.119499596821571
750.8569008895346510.2861982209306980.143099110465349
760.8407764711221650.3184470577556690.159223528877835
770.8123882580619710.3752234838760590.187611741938029
780.7810961538851920.4378076922296150.218903846114808
790.978485327595750.04302934480849980.0215146724042499
800.9746515911786430.05069681764271420.0253484088213571
810.9673669300557490.06526613988850180.0326330699442509
820.9584422854185030.08311542916299410.041557714581497
830.9476425274821170.1047149450357660.0523574725178828
840.9992596655721890.001480668855622680.000740334427811342
850.9989116973556610.002176605288678320.00108830264433916
860.998418807190440.003162385619119590.00158119280955979
870.997729396159110.004541207681780.00227060384089
880.9970533925422550.005893214915490610.00294660745774531
890.9958504183087640.00829916338247130.00414958169123565
900.994223959093230.01155208181354020.00577604090677009
910.9920528521266080.01589429574678310.00794714787339155
920.9898969770509430.02020604589811360.0101030229490568
930.9863714180879390.02725716382412190.0136285819120609
940.9818265392835410.03634692143291710.0181734607164585
950.9772612965464640.04547740690707130.0227387034535357
960.9702775367512760.05944492649744860.0297224632487243
970.9631741501321640.07365169973567280.0368258498678364
980.9528235754079740.09435284918405250.0471764245920263
990.9402459202638950.119508159472210.0597540797361049
1000.9251639556280380.1496720887439230.0748360443719615
1010.907319217025530.1853615659489410.0926807829744703
1020.8864874057153720.2270251885692550.113512594284628
1030.8624947332607750.2750105334784490.137505266739225
1040.8352341618841730.3295316762316540.164765838115827
1050.8085509212263290.3828981575473420.191449078773671
1060.7749770654109410.4500458691781180.225022934589059
1070.7382769907908880.5234460184182230.261723009209112
1080.7025465313090150.594906937381970.297453468690985
1090.6604507141868330.6790985716263340.339549285813167
1100.6162337354815830.7675325290368340.383766264518417
1110.573567808109950.8528643837801010.42643219189005
1120.5291305602643170.9417388794713660.470869439735683
1130.4814017382906710.9628034765813420.518598261709329
1140.4356581736662360.8713163473324710.564341826333765
1150.388724445263210.7774488905264210.61127555473679
1160.3433455240711790.6866910481423570.656654475928821
1170.3001208114760890.6002416229521780.699879188523911
1180.2595613304249490.5191226608498970.740438669575051
1190.2220714025887270.4441428051774540.777928597411273
1200.1879374958984810.3758749917969610.812062504101519
1210.1573246877216370.3146493754432740.842675312278363
1220.1302804936495840.2605609872991670.869719506350416
1230.1054155922044490.2108311844088980.894584407795551
1240.08509033833327180.1701806766665440.914909661666728
1250.06794629566040640.1358925913208130.932053704339594
1260.05231616981712860.1046323396342570.947683830182871
1270.04065458581896640.08130917163793270.959345414181034
1280.03127499958274690.06254999916549390.968725000417253
1290.02384245411566720.04768490823133440.976157545884333
1300.01803804824812040.03607609649624070.98196195175188
1310.01356917749954020.02713835499908050.98643082250046
1320.01017607441990340.02035214883980680.989823925580097
1330.007635045534628530.01527009106925710.992364954465371
1340.00575903586827850.0115180717365570.994240964131721
1350.004396309613104380.008792619226208750.995603690386896
1360.003428173881459670.006856347762919330.99657182611854
1370.002766940182735920.005533880365471850.997233059817264
1380.001656774645683390.003313549291366780.998343225354317
1390.0009534765168070270.001906953033614050.999046523483193
1400.0007728636299353910.001545727259870780.999227136370065
1410.01642011740220730.03284023480441460.983579882597793
1420.009881408373273410.01976281674654680.990118591626727
1430.007284575621522440.01456915124304490.992715424378478
1440.005654119258973140.01130823851794630.994345880741027
1450.004859628576350880.009719257152701770.995140371423649
1460.0023816617758080.0047633235516160.997618338224192
1470.001057286272219410.002114572544438820.998942713727781
1480.0004147927449494390.0008295854898988780.999585207255051
1490.0003384572405281540.0006769144810563090.999661542759472







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level290.2NOK
5% type I error level480.331034482758621NOK
10% type I error level620.427586206896552NOK

\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 & 29 & 0.2 & NOK \tabularnewline
5% type I error level & 48 & 0.331034482758621 & NOK \tabularnewline
10% type I error level & 62 & 0.427586206896552 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203364&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]29[/C][C]0.2[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]48[/C][C]0.331034482758621[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]62[/C][C]0.427586206896552[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203364&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203364&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 level290.2NOK
5% type I error level480.331034482758621NOK
10% type I error level620.427586206896552NOK



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$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}