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*The author of this computation has been verified*

R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Wed, 03 Dec 2014 14:56:20 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/03/t1417618709uld0tfch2npdecm.htm/, Retrieved Sun, 19 May 2024 10:21:07 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=262963, Retrieved Sun, 19 May 2024 10:21:07 +0000

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No (this computation is public)

User-defined keywords

Estimated Impact

122

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Multiple Regression] [] [2014-12-03 14:56:20] [72ee53c6f28232e74174360ca89644de] [Current]

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Dataseries X:

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1	0.5	0.67	0.67	0	12.9
0.89	0.5	0.83	0.33	0.5	12.2
0.89	0.4	1	0.67	0	12.8
0.89	0.5	0.83	0	0	7.4
0.89	0.7	0.67	0	1	6.7
0.78	0.3	0	0	0.5	12.6
0.89	0.4	0.83	0.67	0.5	14.8
1	0.4	0.5	0.67	1	13.3
0.89	0.7	0.83	0	0.5	11.1
0.78	0.6	0.33	0.67	0.5	8.2
1	0.6	0.5	1	0	11.4
0.78	0.2	0.67	0	0.5	6.4
0.89	0.4	1	0	0.5	10.6
0.89	0.4	0.5	0.67	0	12
0.89	0.5	0.67	0.33	0	6.3
0.89	0.3	0.17	0.67	0	11.3
0.89	0.4	0.83	0.33	0.5	11.9
0.67	0.7	0.67	0.33	0.5	9.3
1	0.5	0.67	0.33	0	9.6
0.78	0.2	0.67	0	0	10
0.78	0.3	0.5	0.67	0	6.4
0.89	0.6	1	0.33	0	13.8
0.78	0.6	0.83	0.33	0	10.8
0.89	0.2	0.83	0.33	0	13.8
0.89	0.7	1	0.67	1	11.7
0.33	0.2	0.67	0	0	10.9
1	1	1	0.33	1	16.1
0.89	0.4	0.83	0.67	0	13.4
0.89	0.4	1	1	0	9.9
0.67	0.2	0.83	0.67	0	11.5
0.56	0.4	0.67	0.33	0	8.3
0.89	0.4	0.67	0	0.5	11.7
0.89	0.7	1	0.67	0.5	9
1	0.2	0.67	0.67	0	9.7
0.78	0.6	1	1	0	10.8
0.78	0.3	1	1	0.5	10.3
0.33	0.3	0.5	0.33	0	10.4
0.78	0.2	0.67	0	0.5	12.7
0.89	0.5	0.83	0.67	0.5	9.3
0.89	0.7	1	0.67	0.5	11.8
0.78	0.6	1	0.67	0.5	5.9
0.89	0.4	1	0.67	0.5	11.4
0.89	0.6	1	0.33	0.5	13
1	0.4	1	1	0	10.8
0.67	0.3	0.83	0.67	0	12.3
1	0.5	0.83	0.67	0.5	11.3
0.89	0.2	0.5	0	0	11.8
0.89	0.3	0.83	0	0.5	7.9
0.89	0.5	0.17	0	0	12.7
0.78	0.7	0.83	1	0.5	12.3
0.89	0.4	1	0.67	1	11.6
0.78	0.3	1	0	0	6.7
0.78	0.2	0.67	0.67	1	10.9
1	0.5	1	0	0	12.1
0.78	0.4	1	0	0.5	13.3
1	0.6	1	0.67	1	10.1
0.78	0.4	0.83	1	0	5.7
0.67	0.4	0.33	0	0	14.3
0.33	0.2	0.33	0.33	0	8
1	0.9	1	0.67	0.5	13.3
1	0.8	1	0.67	1	9.3
0.78	0.8	0.83	0	0.5	12.5
0.67	0.3	1	1	0.5	7.6
1	0.2	0.83	0.67	0	15.9
0.89	0.4	0.67	0	0.5	9.2
0.89	0.2	0.83	1	0	9.1
0.78	0.2	0.67	0.67	0.5	11.1
1	0.1	0.83	0.67	0	13
0.56	0.4	0.67	1	0.5	14.5
0.67	0.5	1	0	0.5	12.2
0.89	0.8	0.83	0.33	0.5	12.3
0.89	0.4	0.67	0.67	0	11.4
0.89	0.6	0.83	0.33	0.5	8.8
0.89	0.5	0.83	0.67	0.5	14.6
0.78	0.3	0.67	0	0	12.6
1	0.4	0.33	0	0.5	13
1	0.6	0.83	0.67	0.5	12.6
0.89	0.4	1	0.33	0	13.2
0.44	0.3	0.83	0	0	9.9
0.78	0.8	0.83	0	1	7.7
0.89	0.6	0.5	0.33	1	10.5
0.67	0.3	0.5	0	0	13.4
0.78	0.5	0.83	0.67	0.5	10.9
0.78	0.4	1	0.33	0	4.3
0.33	0.3	0.33	0.67	0	10.3
0.89	0.7	1	0.33	0	11.8
0.89	0.2	0.67	0.33	0.5	11.2
0.89	0.4	0.83	1	0	11.4
0.89	0.6	1	0.67	0.5	8.6
0.56	0.6	0.83	0	0	13.2
0.67	0.6	0.83	0.67	0.5	12.6
0.67	0.4	1	0.33	0.5	5.6
0.78	0.6	0.83	0	0	9.9
0.78	0.5	1	0.33	0.5	8.8
0.78	0.5	0.83	0	0	7.7
0.89	0.6	0.67	0	0	9
1	0.8	0.83	0.33	0.5	7.3
0.89	0.5	0.83	0.67	1	11.4
0.89	0.6	0.83	0.67	0.5	13.6
0.78	0.4	0.83	0.67	0.5	7.9
1	0.3	0.67	0.67	0.5	10.7
0.78	0.3	0.83	1	0	10.3
0.67	0.2	0	0	0	8.3
0.78	0.4	0.83	0	0	9.6
0.89	0.5	1	0	0	14.2
0.67	0.3	0.17	0	0.5	8.5
0.22	0.4	0.17	0	0.5	13.5
0.44	0.5	0.5	1	0	4.9
0.89	0.3	0.5	0.67	0	6.4
0.67	0.5	1	0	0	9.6
0.89	0.4	0.67	0.67	0	11.6
0.67	0.4	0.83	0.67	0	11.1
0.78	0.6	1	0	1	4.35
0.78	0.3	1	0.67	1	12.7
0.78	0.4	1	0.33	1	18.1
1	0.3	1	1	1	17.85
0.78	1	1	1	1	16.6
0.67	0.4	1	0	0	12.6
0.89	0.8	0.83	1	0.5	17.1
0.89	0.3	1	0.67	1	19.1
1	0.5	0.83	0.67	0	16.1
0.78	0.4	1	0	0	13.35
0.67	0.3	0.83	0.67	0	18.4
0.89	0.5	0.83	1	0	14.7
0.67	0.3	1	0.67	0	10.6
0.67	0.3	0.67	0	0	12.6
1	0.4	0.83	0	0	16.2
0.67	0.3	1	0	0	13.6
1	0.6	1	0.33	0.5	18.9
0.89	0.6	0.83	0.67	1	14.1
0.89	0.4	1	1	1	14.5
1	0.4	1	0	0	16.15
0.67	0.4	1	0.67	0	14.75
0.44	0.3	0.67	0.67	0.5	14.8
0.89	0.2	1	0.33	1	12.45
0.56	0.5	0.83	0.67	0	12.65
0.78	0.4	1	0.67	1	17.35
1	0.4	1	0.67	0	8.6
1	0.4	0.83	0.67	0	18.4
0.89	0.3	0.67	0.67	0.5	16.1
0.67	0.4	0.83	0.67	1	11.6
0.89	0.2	1	0.33	0.5	17.75
0.33	0	0	0	0	15.25
0.89	0.4	1	0.67	0.5	17.65
0.78	0.6	1	0	1	16.35
1	0.4	0.67	0.67	0	17.65
0.44	0.4	1	0	0	13.6
0.67	0.4	0.83	0	0.5	14.35
0.33	0.2	0.17	0	0.5	14.75
0.89	0.4	0.83	1	1	18.25
0.89	0.3	0.83	0	0	9.9
1	0.6	0.83	0.67	1	16
0.89	0.6	0.83	1	0	18.25
0.89	0.4	0.83	0	0	16.85
1	0.5	1	0.67	1	14.6
0.89	0.4	0.83	0	0.5	13.85
1	0.6	1	1	1	18.95
0.78	0.6	0.83	0.67	0.5	15.6
0.78	0.9	1	0.67	0.5	14.85
0.67	0.4	0.83	0.67	0.5	11.75
0.89	0.8	1	1	0.5	18.45
0.67	0.5	0.83	1	0	15.9
0.78	0.4	0.83	1	0	17.1
0.89	0.4	1	0.67	1	16.1
0.89	0.7	1	1	1	19.9
0.78	0.4	1	0.33	1	10.95
1	0.8	1	0.67	0.5	18.45
1	0.4	1	1	1	15.1
1	0.3	1	0.67	0	15
0.67	0.5	1	0.67	0.5	11.35
0.89	0.8	1	0.67	1	15.95
1	0.4	0.83	0.33	0	18.1
1	1	1	1	0.5	14.6
0.89	0.5	1	0.67	1	15.4
0.89	0.5	1	0.67	1	15.4
0.89	0.3	1	0.33	0	17.6
0.89	0.3	0.83	0.33	0.5	13.35
0.89	0.3	0.5	0	0	19.1
1	0.4	0.67	0.33	0.5	15.35
0.67	0.5	1	0.33	0	7.6
1	0.5	0.67	0.67	0.5	13.4
0.89	0.4	1	0	0	13.9
0.89	0.7	1	1	0.5	19.1
0.89	0.5	0.5	0.33	0	15.25
0.89	0.4	0.67	0.33	1	12.9
1	0.7	0.67	1	0	16.1
1	0.7	0.67	1	0	17.35
1	0.7	0.67	1	0	13.15
0.89	0.7	0.67	1	0	12.15
0.89	0.7	0.67	0	0	12.6
0.89	0.7	1	0.67	0.5	10.35
0.33	0.1	0.67	0.33	0.5	15.4
0.67	0.2	0.67	0.67	0.5	9.6
0.56	0.3	0.33	0.33	0	18.2
0.44	0.6	0.83	0.33	0	13.6
1	0.8	1	1	1	14.85
0.89	0.8	1	0.33	0.5	14.75
0.33	0	0.17	0	0	14.1
0.67	0.3	0.67	0.33	0	14.9
0.67	0.6	0.83	0.33	0.5	16.25
1	0.5	0.83	0.67	0	19.25
0.78	0.7	1	0.33	0	13.6
0.67	0.3	0.83	0	0.5	13.6
1	0.3	1	0.67	0	15.65
0.78	0.4	1	0.67	0	12.75
0.89	0.4	0.83	1	0	14.6
0.89	0.1	0.83	0	0	9.85
0.89	0.5	1	0.67	0	12.65
0	0	0	0	0	19.2
0.67	0.4	1	0.33	0.5	16.6
1	0.6	0.83	0.67	1	11.2
1	0.4	1	0.33	0.5	15.25
0.67	0.1	0.33	0	0.5	11.9
0.89	0.3	0.83	0	0	13.2
0.89	0.7	0.83	0.67	0	16.35
0.56	0.3	0.17	0	0	12.4
0.67	0.5	0.83	0.33	0.5	15.85
1	0.3	0.83	0.67	1	18.15
1	0.6	0.67	0.67	0.5	11.15
1	0.9	1	1	0	15.65
0.67	0.4	0.83	0	0.5	17.75
0.44	0.3	1	0	0.5	7.65
0.89	0.9	1	0.67	1	12.35
0.44	0.5	1	0	0.5	15.6
0.56	0.3	1	1	0.5	19.3
0.89	0.6	0.83	0.67	0	15.2
0.67	0.2	1	0.33	0	17.1
0.89	0.4	0.83	1	0.5	15.6
1	0.5	0.83	0.67	0.5	18.4
0.78	0.4	0.83	0.67	0	19.05
0.44	0	0	0	0	18.55
0.89	0.2	1	0.33	0.5	19.1
0.89	0.5	1	0.67	0.5	13.1
0.89	0.3	1	0.67	0	12.85
0.44	0	0	0	0	9.5
1	0.5	0.83	1	0	4.5
0.89	0.6	0.83	0.33	0	11.85
0.67	0.3	0.83	0	0.5	13.6
0.33	0	0	0	0	11.7
0.78	0.3	0.67	0	0.5	12.4
0.89	0.5	1	0.67	0.5	13.35
0.78	0.4	0.67	0	0	11.4
0.78	0.5	0.83	0.67	0	14.9
0.89	0.7	1	1	1	19.9
0.78	0.8	1	0.67	0.5	11.2
0.78	0.6	1	0.33	0.5	14.6
0.67	0.4	0.83	0.33	0	17.6
0.89	0.5	0.83	0.33	0.5	14.05
0.89	0.5	1	0	0.5	16.1
0.78	0.3	1	0.33	0	13.35
1	0.6	1	0	0.5	11.85
1	0.3	0.67	0.67	0	11.95
0.78	0.6	0.83	1	0.5	14.75
0.78	0.3	0.33	0.33	0	15.15
0.89	0.7	1	0.67	1	13.2
0.89	0.7	1	1	0	16.85
0.67	0.6	0.67	1	0.5	7.85
1	0.5	1	0.33	0.5	7.7
0.67	0.5	0.83	0.33	0	12.6
0.56	0.4	0.67	0	0	7.85
0.78	0.4	1	0.33	1	10.95
1	0.7	1	1	0	12.35
0.67	0.2	0.17	0	0.5	9.95
0.78	0.5	0.83	0.67	0	14.9
0.56	0.4	0.83	0.67	0.5	16.65
1	0.2	1	0.67	1	13.4
0.89	0.5	0.67	0.67	0	13.95
0.44	0.4	0.5	0	0	15.7
1	0.7	0.67	1	1	16.85
0.89	0.6	0.83	0.67	1	10.95
0.78	0.4	0.83	0	0	15.35
0.89	0.5	1	0.67	1	12.2
0.11	0	0.17	0	0	15.1
0.89	0.7	1	0.67	0.5	17.75
0.89	0.4	0.67	0.67	0	15.2
1	0.5	0.67	1	0	14.6
0.89	0.6	0.83	0.67	0	16.65
1	0.8	0.5	0.67	0.5	8.1

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	9 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262963&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262963&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262963&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	9 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Multiple Linear Regression - Estimated Regression Equation
TOTAL[t] = + 11.695 + 0.123088Calculation[t] -1.01876Algebraic_Reasoning[t] + 0.941365Graphical_Interpretation[t] + 1.5109Proportionality_and_Ratio[t] + 0.53153Probability_and_Sampling[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOTAL[t] =  +  11.695 +  0.123088Calculation[t] -1.01876Algebraic_Reasoning[t] +  0.941365Graphical_Interpretation[t] +  1.5109Proportionality_and_Ratio[t] +  0.53153Probability_and_Sampling[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262963&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOTAL[t] =  +  11.695 +  0.123088Calculation[t] -1.01876Algebraic_Reasoning[t] +  0.941365Graphical_Interpretation[t] +  1.5109Proportionality_and_Ratio[t] +  0.53153Probability_and_Sampling[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262963&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262963&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
TOTAL[t] = + 11.695 + 0.123088Calculation[t] -1.01876Algebraic_Reasoning[t] + 0.941365Graphical_Interpretation[t] + 1.5109Proportionality_and_Ratio[t] + 0.53153Probability_and_Sampling[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	11.695	0.981177	11.92	1.23849e-26	6.19244e-27
Calculation	0.123088	1.33641	0.0921	0.926684	0.463342
Algebraic_Reasoning	-1.01876	1.24456	-0.8186	0.413748	0.206874
Graphical_Interpretation	0.941365	0.994546	0.9465	0.34472	0.17236
Proportionality_and_Ratio	1.5109	0.630139	2.398	0.0171714	0.00858568
Probability_and_Sampling	0.53153	0.579652	0.917	0.359965	0.179982

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 11.695 & 0.981177 & 11.92 & 1.23849e-26 & 6.19244e-27 \tabularnewline
Calculation & 0.123088 & 1.33641 & 0.0921 & 0.926684 & 0.463342 \tabularnewline
Algebraic_Reasoning & -1.01876 & 1.24456 & -0.8186 & 0.413748 & 0.206874 \tabularnewline
Graphical_Interpretation & 0.941365 & 0.994546 & 0.9465 & 0.34472 & 0.17236 \tabularnewline
Proportionality_and_Ratio & 1.5109 & 0.630139 & 2.398 & 0.0171714 & 0.00858568 \tabularnewline
Probability_and_Sampling & 0.53153 & 0.579652 & 0.917 & 0.359965 & 0.179982 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262963&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]11.695[/C][C]0.981177[/C][C]11.92[/C][C]1.23849e-26[/C][C]6.19244e-27[/C][/ROW]
[ROW][C]Calculation[/C][C]0.123088[/C][C]1.33641[/C][C]0.0921[/C][C]0.926684[/C][C]0.463342[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]-1.01876[/C][C]1.24456[/C][C]-0.8186[/C][C]0.413748[/C][C]0.206874[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]0.941365[/C][C]0.994546[/C][C]0.9465[/C][C]0.34472[/C][C]0.17236[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]1.5109[/C][C]0.630139[/C][C]2.398[/C][C]0.0171714[/C][C]0.00858568[/C][/ROW]
[ROW][C]Probability_and_Sampling[/C][C]0.53153[/C][C]0.579652[/C][C]0.917[/C][C]0.359965[/C][C]0.179982[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262963&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262963&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
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	11.695	0.981177	11.92	1.23849e-26	6.19244e-27
Calculation	0.123088	1.33641	0.0921	0.926684	0.463342
Algebraic_Reasoning	-1.01876	1.24456	-0.8186	0.413748	0.206874
Graphical_Interpretation	0.941365	0.994546	0.9465	0.34472	0.17236
Proportionality_and_Ratio	1.5109	0.630139	2.398	0.0171714	0.00858568
Probability_and_Sampling	0.53153	0.579652	0.917	0.359965	0.179982

Multiple Linear Regression - Regression Statistics
Multiple R	0.192783
R-squared	0.0371653
Adjusted R-squared	0.0194661
F-TEST (value)	2.09983
F-TEST (DF numerator)	5
F-TEST (DF denominator)	272
p-value	0.0657013
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	3.36116
Sum Squared Residuals	3072.89

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.192783 \tabularnewline
R-squared & 0.0371653 \tabularnewline
Adjusted R-squared & 0.0194661 \tabularnewline
F-TEST (value) & 2.09983 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 272 \tabularnewline
p-value & 0.0657013 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.36116 \tabularnewline
Sum Squared Residuals & 3072.89 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262963&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.192783[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0371653[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0194661[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]2.09983[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]272[/C][/ROW]
[ROW][C]p-value[/C][C]0.0657013[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.36116[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3072.89[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262963&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262963&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 R	0.192783
R-squared	0.0371653
Adjusted R-squared	0.0194661
F-TEST (value)	2.09983
F-TEST (DF numerator)	5
F-TEST (DF denominator)	272
p-value	0.0657013
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	3.36116
Sum Squared Residuals	3072.89

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	12.9517	-0.0516856
2	12.2	12.8408	-0.640822
3	12.8	13.3507	-0.550673
4	7.4	12.0765	-4.67646
5	6.7	12.2536	-5.55362
6	12.6	11.7511	0.848897
7	14.8	13.4564	1.34359
8	13.3	13.4251	-0.12506
9	11.1	12.1385	-1.03847
10	8.2	12.7684	-4.56843
11	11.4	13.1884	-1.78838
12	6.4	12.4837	-6.08369
13	10.6	12.6041	-2.00413
14	12	12.88	-0.87999
15	6.3	12.4244	-6.12444
16	11.3	12.6712	-1.37122
17	11.9	12.9427	-1.0427
18	9.3	12.4594	-3.15937
19	9.6	12.438	-2.83798
20	10	12.2179	-2.21793
21	6.4	12.9683	-6.56833
22	13.8	12.6332	1.16679
23	10.8	12.4596	-1.65964
24	13.8	12.8807	0.919315
25	11.7	13.5766	-1.87657
26	10.9	12.1625	-1.26254
27	16.1	12.7708	3.32922
28	13.4	13.1906	0.20936
29	9.9	13.8493	-3.94927
30	11.5	13.3673	-1.86731
31	8.3	12.4857	-4.1857
32	11.7	12.2935	-0.593481
33	9	13.3108	-4.31081
34	9.7	13.2573	-3.55731
35	10.8	13.632	-2.83198
36	10.3	14.2034	-3.90337
37	10.4	12.3992	-1.99923
38	12.7	12.4837	0.216306
39	9.3	13.3545	-4.05453
40	11.8	13.3108	-1.51081
41	5.9	13.3991	-7.49915
42	11.4	13.6164	-2.21644
43	13	12.899	0.101022
44	10.8	13.8628	-3.06281
45	12.3	13.2654	-0.965437
46	11.3	13.3681	-2.06807
47	11.8	12.0714	-0.271436
48	7.9	12.546	-4.64598
49	12.7	11.4552	1.24484
50	12.3	13.6358	-1.33584
51	11.6	13.8822	-2.2822
52	6.7	12.4267	-5.7267
53	10.9	13.7618	-2.86176
54	12.1	12.25	-0.15003
55	13.3	12.5906	0.709408
56	10.1	13.692	-3.59199
57	5.7	13.6757	-7.9757
58	14.3	11.6806	2.61943
59	8	12.3411	-4.34107
60	13.3	13.1206	0.179403
61	9.3	13.4882	-4.18824
62	12.5	12.0231	0.476945
63	7.6	14.1898	-6.58983
64	15.9	13.4079	2.49207
65	9.2	12.2935	-3.09348
66	9.1	13.893	-4.79299
67	11.1	13.496	-2.396
68	13	13.5098	-0.509808
69	14.5	13.7638	0.736233
70	12.2	12.4752	-0.275176
71	12.3	12.5352	-0.235194
72	11.4	13.04	-1.64002
73	8.8	12.7389	-3.93895
74	14.6	13.3545	1.24547
75	12.6	12.1161	0.483948
76	13	11.987	1.01304
77	12.6	13.2662	-0.666193
78	13.2	12.837	0.363035
79	9.9	12.2248	-2.32482
80	7.7	12.2888	-4.58882
81	10.5	12.6941	-2.19406
82	13.4	11.9425	1.45752
83	10.9	13.341	-2.44099
84	4.3	12.8234	-8.52343
85	10.3	12.7529	-2.4529
86	11.8	12.5313	-0.731337
87	11.2	12.9958	-1.79583
88	11.4	13.6892	-2.28924
89	8.6	13.4127	-4.81269
90	13.2	11.934	1.26604
91	12.6	13.2256	-0.625574
92	5.6	13.0757	-7.47565
93	9.9	11.961	-2.06104
94	8.8	12.9873	-4.18731
95	7.7	12.0629	-4.36292
96	9	11.824	-2.82396
97	7.3	12.5487	-5.24873
98	11.4	13.6203	-2.22029
99	13.6	13.2527	0.347347
100	7.9	13.4429	-5.54287
101	10.7	13.4212	-2.7212
102	10.3	13.7776	-3.47758
103	8.3	11.5737	-3.27367
104	9.6	12.1648	-2.56479
105	14.2	12.2365	1.96351
106	8.5	11.8976	-3.3976
107	13.5	11.7403	1.75967
108	4.9	13.2213	-8.32132
109	6.4	12.9819	-6.58187
110	9.6	12.2094	-2.60941
111	11.6	13.04	-1.44002
112	11.1	13.1636	-2.06356
113	4.35	12.6526	-8.3026
114	12.7	13.9705	-1.27054
115	18.1	13.355	4.74504
116	17.85	14.4962	3.35378
117	16.6	13.756	2.844
118	12.6	12.3113	0.288713
119	17.1	13.5475	3.5525
120	19.1	13.9841	5.11592
121	16.1	13.1023	2.9977
122	13.35	12.3248	1.02517
123	18.4	13.2654	5.13456
124	14.7	13.5874	1.11264
125	10.6	13.4255	-2.82547
126	12.6	12.1025	0.497487
127	16.2	12.1919	4.00813
128	13.6	12.4132	1.18684
129	18.9	12.9125	5.98748
130	14.1	13.5184	0.581581
131	14.5	14.3808	0.119199
132	16.15	12.3519	3.79809
133	14.75	13.3236	1.42641
134	14.8	13.3523	1.44773
135	12.45	13.5722	-1.12225
136	12.65	13.0481	-0.398145
137	17.35	13.8687	3.48134
138	8.6	13.3642	-4.76421
139	18.4	13.2042	5.19582
140	16.1	13.4077	2.69234
141	11.6	13.6951	-2.09509
142	17.75	13.3065	4.44352
143	15.25	11.7356	3.51442
144	17.65	13.6164	4.03356
145	16.35	12.6526	3.6974
146	17.65	13.0536	4.59644
147	13.6	12.283	1.31702
148	14.35	12.417	1.93298
149	14.75	11.9576	2.79238
150	18.25	14.2208	4.02923
151	9.9	12.2802	-2.38021
152	16	13.532	2.46804
153	18.25	13.4855	4.76451
154	16.85	12.1783	4.67167
155	14.6	13.7939	0.806134
156	13.85	12.4441	1.4059
157	18.95	14.1906	4.75941
158	15.6	13.2391	2.36089
159	14.85	13.0935	1.75648
160	11.75	13.4293	-1.67933
161	18.45	13.7075	4.74247
162	15.9	13.5603	2.33972
163	17.1	13.6757	3.4243
164	16.1	13.8822	2.2178
165	19.9	14.0752	5.82483
166	10.95	13.355	-2.40496
167	18.45	13.2225	5.22753
168	15.1	14.3943	0.705659
169	15	13.4661	1.53391
170	11.35	13.4875	-2.13748
171	15.95	13.4747	2.4753
172	18.1	12.6905	5.40953
173	14.6	13.5173	1.08268
174	15.4	13.7803	1.61967
175	15.4	13.7803	1.61967
176	17.6	12.9388	4.66116
177	13.35	13.0446	0.305426
178	19.1	11.9696	7.13044
179	15.35	12.8056	2.54438
180	7.6	12.708	-5.10801
181	13.4	13.2175	0.182549
182	13.9	12.3384	1.56163
183	19.1	13.8094	5.29059
184	15.25	12.2644	2.98559
185	12.9	13.0578	-0.157845
186	16.1	13.2465	2.85347
187	17.35	13.2465	4.10347
188	13.15	13.2465	-0.0965319
189	12.15	13.233	-1.08299
190	12.6	11.7221	0.877912
191	10.35	13.3108	-2.96081
192	15.4	13.0288	2.37122
193	9.6	13.4825	-3.88246
194	18.2	12.2675	5.93249
195	13.6	12.4178	1.18221
196	14.85	13.9868	0.863163
197	14.75	12.6952	2.05477
198	14.1	11.8956	2.20439
199	14.9	12.6011	2.29889
200	16.25	12.7119	3.53813
201	19.25	13.1023	6.1477
202	13.6	12.5178	1.0822
203	13.6	12.5189	1.0811
204	15.65	13.4661	2.18391
205	12.75	13.3371	-0.587133
206	14.6	13.6892	0.910761
207	9.85	12.484	-2.63396
208	12.65	13.2488	-0.598796
209	19.2	11.695	7.50504
210	16.6	13.0757	3.52435
211	11.2	13.532	-2.33196
212	15.25	13.1163	2.13373
213	11.9	12.252	-0.351966
214	13.2	12.2802	0.919789
215	16.35	12.885	3.46499
216	12.4	11.6183	0.781709
217	15.85	12.8137	3.03626
218	18.15	13.8376	4.31241
219	11.15	13.1156	-1.96557
220	15.65	13.3534	2.29657
221	17.75	12.417	5.33298
222	7.65	12.6506	-5.00062
223	12.35	13.3728	-1.02282
224	15.6	12.4469	3.15313
225	19.3	14.1763	5.12371
226	15.2	12.9869	2.21311
227	17.1	13.0136	4.08636
228	15.6	13.955	1.645
229	18.4	13.3681	5.03193
230	19.05	13.1771	5.8729
231	18.55	11.7491	6.80088
232	19.1	13.3065	5.79352
233	13.1	13.5146	-0.414562
234	12.85	13.4525	-0.602549
235	9.5	11.7491	-2.24912
236	4.5	13.6009	-9.1009
237	11.85	12.4732	-0.623181
238	13.6	12.5189	1.0811
239	11.7	11.7356	-0.0355766
240	12.4	12.3818	0.0181824
241	13.35	13.5146	-0.164562
242	11.4	12.0142	-0.614176
243	14.9	13.0752	1.82478
244	19.9	14.0752	5.82483
245	11.2	13.1954	-1.99539
246	14.6	12.8854	1.71456
247	17.6	12.6499	4.95015
248	14.05	12.8408	1.20918
249	16.1	12.5023	3.59774
250	13.35	12.9253	0.424699
251	11.85	12.4139	-0.563919
252	11.95	13.1554	-1.20544
253	14.75	13.7377	1.01229
254	15.15	12.2946	2.85541
255	13.2	13.5766	-0.376574
256	16.85	13.5436	3.30636
257	7.85	13.5736	-5.72355
258	7.7	13.0144	-5.31439
259	12.6	12.548	0.0520225
260	7.85	11.9871	-4.1371
261	10.95	13.355	-2.40496
262	12.35	13.5572	-1.20718
263	9.95	11.9995	-2.04947
264	14.9	13.0752	1.82478
265	16.65	13.4158	3.23421
266	13.4	14.0995	-0.699495
267	13.95	12.9381	1.01185
268	15.7	11.8123	3.88771
269	16.85	13.7781	3.07194
270	10.95	13.5184	-2.56842
271	15.35	12.1648	3.18521
272	12.2	13.7803	-1.58033
273	15.1	11.8685	3.23147
274	17.75	13.3108	4.43919
275	15.2	13.04	2.15998
276	14.6	13.4503	1.14972
277	16.65	12.9869	3.66311
278	8.1	12.7518	-4.65179

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.9517 & -0.0516856 \tabularnewline
2 & 12.2 & 12.8408 & -0.640822 \tabularnewline
3 & 12.8 & 13.3507 & -0.550673 \tabularnewline
4 & 7.4 & 12.0765 & -4.67646 \tabularnewline
5 & 6.7 & 12.2536 & -5.55362 \tabularnewline
6 & 12.6 & 11.7511 & 0.848897 \tabularnewline
7 & 14.8 & 13.4564 & 1.34359 \tabularnewline
8 & 13.3 & 13.4251 & -0.12506 \tabularnewline
9 & 11.1 & 12.1385 & -1.03847 \tabularnewline
10 & 8.2 & 12.7684 & -4.56843 \tabularnewline
11 & 11.4 & 13.1884 & -1.78838 \tabularnewline
12 & 6.4 & 12.4837 & -6.08369 \tabularnewline
13 & 10.6 & 12.6041 & -2.00413 \tabularnewline
14 & 12 & 12.88 & -0.87999 \tabularnewline
15 & 6.3 & 12.4244 & -6.12444 \tabularnewline
16 & 11.3 & 12.6712 & -1.37122 \tabularnewline
17 & 11.9 & 12.9427 & -1.0427 \tabularnewline
18 & 9.3 & 12.4594 & -3.15937 \tabularnewline
19 & 9.6 & 12.438 & -2.83798 \tabularnewline
20 & 10 & 12.2179 & -2.21793 \tabularnewline
21 & 6.4 & 12.9683 & -6.56833 \tabularnewline
22 & 13.8 & 12.6332 & 1.16679 \tabularnewline
23 & 10.8 & 12.4596 & -1.65964 \tabularnewline
24 & 13.8 & 12.8807 & 0.919315 \tabularnewline
25 & 11.7 & 13.5766 & -1.87657 \tabularnewline
26 & 10.9 & 12.1625 & -1.26254 \tabularnewline
27 & 16.1 & 12.7708 & 3.32922 \tabularnewline
28 & 13.4 & 13.1906 & 0.20936 \tabularnewline
29 & 9.9 & 13.8493 & -3.94927 \tabularnewline
30 & 11.5 & 13.3673 & -1.86731 \tabularnewline
31 & 8.3 & 12.4857 & -4.1857 \tabularnewline
32 & 11.7 & 12.2935 & -0.593481 \tabularnewline
33 & 9 & 13.3108 & -4.31081 \tabularnewline
34 & 9.7 & 13.2573 & -3.55731 \tabularnewline
35 & 10.8 & 13.632 & -2.83198 \tabularnewline
36 & 10.3 & 14.2034 & -3.90337 \tabularnewline
37 & 10.4 & 12.3992 & -1.99923 \tabularnewline
38 & 12.7 & 12.4837 & 0.216306 \tabularnewline
39 & 9.3 & 13.3545 & -4.05453 \tabularnewline
40 & 11.8 & 13.3108 & -1.51081 \tabularnewline
41 & 5.9 & 13.3991 & -7.49915 \tabularnewline
42 & 11.4 & 13.6164 & -2.21644 \tabularnewline
43 & 13 & 12.899 & 0.101022 \tabularnewline
44 & 10.8 & 13.8628 & -3.06281 \tabularnewline
45 & 12.3 & 13.2654 & -0.965437 \tabularnewline
46 & 11.3 & 13.3681 & -2.06807 \tabularnewline
47 & 11.8 & 12.0714 & -0.271436 \tabularnewline
48 & 7.9 & 12.546 & -4.64598 \tabularnewline
49 & 12.7 & 11.4552 & 1.24484 \tabularnewline
50 & 12.3 & 13.6358 & -1.33584 \tabularnewline
51 & 11.6 & 13.8822 & -2.2822 \tabularnewline
52 & 6.7 & 12.4267 & -5.7267 \tabularnewline
53 & 10.9 & 13.7618 & -2.86176 \tabularnewline
54 & 12.1 & 12.25 & -0.15003 \tabularnewline
55 & 13.3 & 12.5906 & 0.709408 \tabularnewline
56 & 10.1 & 13.692 & -3.59199 \tabularnewline
57 & 5.7 & 13.6757 & -7.9757 \tabularnewline
58 & 14.3 & 11.6806 & 2.61943 \tabularnewline
59 & 8 & 12.3411 & -4.34107 \tabularnewline
60 & 13.3 & 13.1206 & 0.179403 \tabularnewline
61 & 9.3 & 13.4882 & -4.18824 \tabularnewline
62 & 12.5 & 12.0231 & 0.476945 \tabularnewline
63 & 7.6 & 14.1898 & -6.58983 \tabularnewline
64 & 15.9 & 13.4079 & 2.49207 \tabularnewline
65 & 9.2 & 12.2935 & -3.09348 \tabularnewline
66 & 9.1 & 13.893 & -4.79299 \tabularnewline
67 & 11.1 & 13.496 & -2.396 \tabularnewline
68 & 13 & 13.5098 & -0.509808 \tabularnewline
69 & 14.5 & 13.7638 & 0.736233 \tabularnewline
70 & 12.2 & 12.4752 & -0.275176 \tabularnewline
71 & 12.3 & 12.5352 & -0.235194 \tabularnewline
72 & 11.4 & 13.04 & -1.64002 \tabularnewline
73 & 8.8 & 12.7389 & -3.93895 \tabularnewline
74 & 14.6 & 13.3545 & 1.24547 \tabularnewline
75 & 12.6 & 12.1161 & 0.483948 \tabularnewline
76 & 13 & 11.987 & 1.01304 \tabularnewline
77 & 12.6 & 13.2662 & -0.666193 \tabularnewline
78 & 13.2 & 12.837 & 0.363035 \tabularnewline
79 & 9.9 & 12.2248 & -2.32482 \tabularnewline
80 & 7.7 & 12.2888 & -4.58882 \tabularnewline
81 & 10.5 & 12.6941 & -2.19406 \tabularnewline
82 & 13.4 & 11.9425 & 1.45752 \tabularnewline
83 & 10.9 & 13.341 & -2.44099 \tabularnewline
84 & 4.3 & 12.8234 & -8.52343 \tabularnewline
85 & 10.3 & 12.7529 & -2.4529 \tabularnewline
86 & 11.8 & 12.5313 & -0.731337 \tabularnewline
87 & 11.2 & 12.9958 & -1.79583 \tabularnewline
88 & 11.4 & 13.6892 & -2.28924 \tabularnewline
89 & 8.6 & 13.4127 & -4.81269 \tabularnewline
90 & 13.2 & 11.934 & 1.26604 \tabularnewline
91 & 12.6 & 13.2256 & -0.625574 \tabularnewline
92 & 5.6 & 13.0757 & -7.47565 \tabularnewline
93 & 9.9 & 11.961 & -2.06104 \tabularnewline
94 & 8.8 & 12.9873 & -4.18731 \tabularnewline
95 & 7.7 & 12.0629 & -4.36292 \tabularnewline
96 & 9 & 11.824 & -2.82396 \tabularnewline
97 & 7.3 & 12.5487 & -5.24873 \tabularnewline
98 & 11.4 & 13.6203 & -2.22029 \tabularnewline
99 & 13.6 & 13.2527 & 0.347347 \tabularnewline
100 & 7.9 & 13.4429 & -5.54287 \tabularnewline
101 & 10.7 & 13.4212 & -2.7212 \tabularnewline
102 & 10.3 & 13.7776 & -3.47758 \tabularnewline
103 & 8.3 & 11.5737 & -3.27367 \tabularnewline
104 & 9.6 & 12.1648 & -2.56479 \tabularnewline
105 & 14.2 & 12.2365 & 1.96351 \tabularnewline
106 & 8.5 & 11.8976 & -3.3976 \tabularnewline
107 & 13.5 & 11.7403 & 1.75967 \tabularnewline
108 & 4.9 & 13.2213 & -8.32132 \tabularnewline
109 & 6.4 & 12.9819 & -6.58187 \tabularnewline
110 & 9.6 & 12.2094 & -2.60941 \tabularnewline
111 & 11.6 & 13.04 & -1.44002 \tabularnewline
112 & 11.1 & 13.1636 & -2.06356 \tabularnewline
113 & 4.35 & 12.6526 & -8.3026 \tabularnewline
114 & 12.7 & 13.9705 & -1.27054 \tabularnewline
115 & 18.1 & 13.355 & 4.74504 \tabularnewline
116 & 17.85 & 14.4962 & 3.35378 \tabularnewline
117 & 16.6 & 13.756 & 2.844 \tabularnewline
118 & 12.6 & 12.3113 & 0.288713 \tabularnewline
119 & 17.1 & 13.5475 & 3.5525 \tabularnewline
120 & 19.1 & 13.9841 & 5.11592 \tabularnewline
121 & 16.1 & 13.1023 & 2.9977 \tabularnewline
122 & 13.35 & 12.3248 & 1.02517 \tabularnewline
123 & 18.4 & 13.2654 & 5.13456 \tabularnewline
124 & 14.7 & 13.5874 & 1.11264 \tabularnewline
125 & 10.6 & 13.4255 & -2.82547 \tabularnewline
126 & 12.6 & 12.1025 & 0.497487 \tabularnewline
127 & 16.2 & 12.1919 & 4.00813 \tabularnewline
128 & 13.6 & 12.4132 & 1.18684 \tabularnewline
129 & 18.9 & 12.9125 & 5.98748 \tabularnewline
130 & 14.1 & 13.5184 & 0.581581 \tabularnewline
131 & 14.5 & 14.3808 & 0.119199 \tabularnewline
132 & 16.15 & 12.3519 & 3.79809 \tabularnewline
133 & 14.75 & 13.3236 & 1.42641 \tabularnewline
134 & 14.8 & 13.3523 & 1.44773 \tabularnewline
135 & 12.45 & 13.5722 & -1.12225 \tabularnewline
136 & 12.65 & 13.0481 & -0.398145 \tabularnewline
137 & 17.35 & 13.8687 & 3.48134 \tabularnewline
138 & 8.6 & 13.3642 & -4.76421 \tabularnewline
139 & 18.4 & 13.2042 & 5.19582 \tabularnewline
140 & 16.1 & 13.4077 & 2.69234 \tabularnewline
141 & 11.6 & 13.6951 & -2.09509 \tabularnewline
142 & 17.75 & 13.3065 & 4.44352 \tabularnewline
143 & 15.25 & 11.7356 & 3.51442 \tabularnewline
144 & 17.65 & 13.6164 & 4.03356 \tabularnewline
145 & 16.35 & 12.6526 & 3.6974 \tabularnewline
146 & 17.65 & 13.0536 & 4.59644 \tabularnewline
147 & 13.6 & 12.283 & 1.31702 \tabularnewline
148 & 14.35 & 12.417 & 1.93298 \tabularnewline
149 & 14.75 & 11.9576 & 2.79238 \tabularnewline
150 & 18.25 & 14.2208 & 4.02923 \tabularnewline
151 & 9.9 & 12.2802 & -2.38021 \tabularnewline
152 & 16 & 13.532 & 2.46804 \tabularnewline
153 & 18.25 & 13.4855 & 4.76451 \tabularnewline
154 & 16.85 & 12.1783 & 4.67167 \tabularnewline
155 & 14.6 & 13.7939 & 0.806134 \tabularnewline
156 & 13.85 & 12.4441 & 1.4059 \tabularnewline
157 & 18.95 & 14.1906 & 4.75941 \tabularnewline
158 & 15.6 & 13.2391 & 2.36089 \tabularnewline
159 & 14.85 & 13.0935 & 1.75648 \tabularnewline
160 & 11.75 & 13.4293 & -1.67933 \tabularnewline
161 & 18.45 & 13.7075 & 4.74247 \tabularnewline
162 & 15.9 & 13.5603 & 2.33972 \tabularnewline
163 & 17.1 & 13.6757 & 3.4243 \tabularnewline
164 & 16.1 & 13.8822 & 2.2178 \tabularnewline
165 & 19.9 & 14.0752 & 5.82483 \tabularnewline
166 & 10.95 & 13.355 & -2.40496 \tabularnewline
167 & 18.45 & 13.2225 & 5.22753 \tabularnewline
168 & 15.1 & 14.3943 & 0.705659 \tabularnewline
169 & 15 & 13.4661 & 1.53391 \tabularnewline
170 & 11.35 & 13.4875 & -2.13748 \tabularnewline
171 & 15.95 & 13.4747 & 2.4753 \tabularnewline
172 & 18.1 & 12.6905 & 5.40953 \tabularnewline
173 & 14.6 & 13.5173 & 1.08268 \tabularnewline
174 & 15.4 & 13.7803 & 1.61967 \tabularnewline
175 & 15.4 & 13.7803 & 1.61967 \tabularnewline
176 & 17.6 & 12.9388 & 4.66116 \tabularnewline
177 & 13.35 & 13.0446 & 0.305426 \tabularnewline
178 & 19.1 & 11.9696 & 7.13044 \tabularnewline
179 & 15.35 & 12.8056 & 2.54438 \tabularnewline
180 & 7.6 & 12.708 & -5.10801 \tabularnewline
181 & 13.4 & 13.2175 & 0.182549 \tabularnewline
182 & 13.9 & 12.3384 & 1.56163 \tabularnewline
183 & 19.1 & 13.8094 & 5.29059 \tabularnewline
184 & 15.25 & 12.2644 & 2.98559 \tabularnewline
185 & 12.9 & 13.0578 & -0.157845 \tabularnewline
186 & 16.1 & 13.2465 & 2.85347 \tabularnewline
187 & 17.35 & 13.2465 & 4.10347 \tabularnewline
188 & 13.15 & 13.2465 & -0.0965319 \tabularnewline
189 & 12.15 & 13.233 & -1.08299 \tabularnewline
190 & 12.6 & 11.7221 & 0.877912 \tabularnewline
191 & 10.35 & 13.3108 & -2.96081 \tabularnewline
192 & 15.4 & 13.0288 & 2.37122 \tabularnewline
193 & 9.6 & 13.4825 & -3.88246 \tabularnewline
194 & 18.2 & 12.2675 & 5.93249 \tabularnewline
195 & 13.6 & 12.4178 & 1.18221 \tabularnewline
196 & 14.85 & 13.9868 & 0.863163 \tabularnewline
197 & 14.75 & 12.6952 & 2.05477 \tabularnewline
198 & 14.1 & 11.8956 & 2.20439 \tabularnewline
199 & 14.9 & 12.6011 & 2.29889 \tabularnewline
200 & 16.25 & 12.7119 & 3.53813 \tabularnewline
201 & 19.25 & 13.1023 & 6.1477 \tabularnewline
202 & 13.6 & 12.5178 & 1.0822 \tabularnewline
203 & 13.6 & 12.5189 & 1.0811 \tabularnewline
204 & 15.65 & 13.4661 & 2.18391 \tabularnewline
205 & 12.75 & 13.3371 & -0.587133 \tabularnewline
206 & 14.6 & 13.6892 & 0.910761 \tabularnewline
207 & 9.85 & 12.484 & -2.63396 \tabularnewline
208 & 12.65 & 13.2488 & -0.598796 \tabularnewline
209 & 19.2 & 11.695 & 7.50504 \tabularnewline
210 & 16.6 & 13.0757 & 3.52435 \tabularnewline
211 & 11.2 & 13.532 & -2.33196 \tabularnewline
212 & 15.25 & 13.1163 & 2.13373 \tabularnewline
213 & 11.9 & 12.252 & -0.351966 \tabularnewline
214 & 13.2 & 12.2802 & 0.919789 \tabularnewline
215 & 16.35 & 12.885 & 3.46499 \tabularnewline
216 & 12.4 & 11.6183 & 0.781709 \tabularnewline
217 & 15.85 & 12.8137 & 3.03626 \tabularnewline
218 & 18.15 & 13.8376 & 4.31241 \tabularnewline
219 & 11.15 & 13.1156 & -1.96557 \tabularnewline
220 & 15.65 & 13.3534 & 2.29657 \tabularnewline
221 & 17.75 & 12.417 & 5.33298 \tabularnewline
222 & 7.65 & 12.6506 & -5.00062 \tabularnewline
223 & 12.35 & 13.3728 & -1.02282 \tabularnewline
224 & 15.6 & 12.4469 & 3.15313 \tabularnewline
225 & 19.3 & 14.1763 & 5.12371 \tabularnewline
226 & 15.2 & 12.9869 & 2.21311 \tabularnewline
227 & 17.1 & 13.0136 & 4.08636 \tabularnewline
228 & 15.6 & 13.955 & 1.645 \tabularnewline
229 & 18.4 & 13.3681 & 5.03193 \tabularnewline
230 & 19.05 & 13.1771 & 5.8729 \tabularnewline
231 & 18.55 & 11.7491 & 6.80088 \tabularnewline
232 & 19.1 & 13.3065 & 5.79352 \tabularnewline
233 & 13.1 & 13.5146 & -0.414562 \tabularnewline
234 & 12.85 & 13.4525 & -0.602549 \tabularnewline
235 & 9.5 & 11.7491 & -2.24912 \tabularnewline
236 & 4.5 & 13.6009 & -9.1009 \tabularnewline
237 & 11.85 & 12.4732 & -0.623181 \tabularnewline
238 & 13.6 & 12.5189 & 1.0811 \tabularnewline
239 & 11.7 & 11.7356 & -0.0355766 \tabularnewline
240 & 12.4 & 12.3818 & 0.0181824 \tabularnewline
241 & 13.35 & 13.5146 & -0.164562 \tabularnewline
242 & 11.4 & 12.0142 & -0.614176 \tabularnewline
243 & 14.9 & 13.0752 & 1.82478 \tabularnewline
244 & 19.9 & 14.0752 & 5.82483 \tabularnewline
245 & 11.2 & 13.1954 & -1.99539 \tabularnewline
246 & 14.6 & 12.8854 & 1.71456 \tabularnewline
247 & 17.6 & 12.6499 & 4.95015 \tabularnewline
248 & 14.05 & 12.8408 & 1.20918 \tabularnewline
249 & 16.1 & 12.5023 & 3.59774 \tabularnewline
250 & 13.35 & 12.9253 & 0.424699 \tabularnewline
251 & 11.85 & 12.4139 & -0.563919 \tabularnewline
252 & 11.95 & 13.1554 & -1.20544 \tabularnewline
253 & 14.75 & 13.7377 & 1.01229 \tabularnewline
254 & 15.15 & 12.2946 & 2.85541 \tabularnewline
255 & 13.2 & 13.5766 & -0.376574 \tabularnewline
256 & 16.85 & 13.5436 & 3.30636 \tabularnewline
257 & 7.85 & 13.5736 & -5.72355 \tabularnewline
258 & 7.7 & 13.0144 & -5.31439 \tabularnewline
259 & 12.6 & 12.548 & 0.0520225 \tabularnewline
260 & 7.85 & 11.9871 & -4.1371 \tabularnewline
261 & 10.95 & 13.355 & -2.40496 \tabularnewline
262 & 12.35 & 13.5572 & -1.20718 \tabularnewline
263 & 9.95 & 11.9995 & -2.04947 \tabularnewline
264 & 14.9 & 13.0752 & 1.82478 \tabularnewline
265 & 16.65 & 13.4158 & 3.23421 \tabularnewline
266 & 13.4 & 14.0995 & -0.699495 \tabularnewline
267 & 13.95 & 12.9381 & 1.01185 \tabularnewline
268 & 15.7 & 11.8123 & 3.88771 \tabularnewline
269 & 16.85 & 13.7781 & 3.07194 \tabularnewline
270 & 10.95 & 13.5184 & -2.56842 \tabularnewline
271 & 15.35 & 12.1648 & 3.18521 \tabularnewline
272 & 12.2 & 13.7803 & -1.58033 \tabularnewline
273 & 15.1 & 11.8685 & 3.23147 \tabularnewline
274 & 17.75 & 13.3108 & 4.43919 \tabularnewline
275 & 15.2 & 13.04 & 2.15998 \tabularnewline
276 & 14.6 & 13.4503 & 1.14972 \tabularnewline
277 & 16.65 & 12.9869 & 3.66311 \tabularnewline
278 & 8.1 & 12.7518 & -4.65179 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262963&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]12.9517[/C][C]-0.0516856[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]12.8408[/C][C]-0.640822[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]13.3507[/C][C]-0.550673[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]12.0765[/C][C]-4.67646[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]12.2536[/C][C]-5.55362[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]11.7511[/C][C]0.848897[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]13.4564[/C][C]1.34359[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]13.4251[/C][C]-0.12506[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.1385[/C][C]-1.03847[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]12.7684[/C][C]-4.56843[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]13.1884[/C][C]-1.78838[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]12.4837[/C][C]-6.08369[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]12.6041[/C][C]-2.00413[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]12.88[/C][C]-0.87999[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]12.4244[/C][C]-6.12444[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]12.6712[/C][C]-1.37122[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]12.9427[/C][C]-1.0427[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.4594[/C][C]-3.15937[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.438[/C][C]-2.83798[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]12.2179[/C][C]-2.21793[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]12.9683[/C][C]-6.56833[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.6332[/C][C]1.16679[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]12.4596[/C][C]-1.65964[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.8807[/C][C]0.919315[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]13.5766[/C][C]-1.87657[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.1625[/C][C]-1.26254[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]12.7708[/C][C]3.32922[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]13.1906[/C][C]0.20936[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]13.8493[/C][C]-3.94927[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]13.3673[/C][C]-1.86731[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]12.4857[/C][C]-4.1857[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]12.2935[/C][C]-0.593481[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]13.3108[/C][C]-4.31081[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]13.2573[/C][C]-3.55731[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]13.632[/C][C]-2.83198[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]14.2034[/C][C]-3.90337[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]12.3992[/C][C]-1.99923[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.4837[/C][C]0.216306[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]13.3545[/C][C]-4.05453[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]13.3108[/C][C]-1.51081[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]13.3991[/C][C]-7.49915[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.6164[/C][C]-2.21644[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]12.899[/C][C]0.101022[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]13.8628[/C][C]-3.06281[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]13.2654[/C][C]-0.965437[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.3681[/C][C]-2.06807[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]12.0714[/C][C]-0.271436[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]12.546[/C][C]-4.64598[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]11.4552[/C][C]1.24484[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]13.6358[/C][C]-1.33584[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]13.8822[/C][C]-2.2822[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]12.4267[/C][C]-5.7267[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.7618[/C][C]-2.86176[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.25[/C][C]-0.15003[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]12.5906[/C][C]0.709408[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.692[/C][C]-3.59199[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]13.6757[/C][C]-7.9757[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]11.6806[/C][C]2.61943[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]12.3411[/C][C]-4.34107[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]13.1206[/C][C]0.179403[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]13.4882[/C][C]-4.18824[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]12.0231[/C][C]0.476945[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]14.1898[/C][C]-6.58983[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.4079[/C][C]2.49207[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]12.2935[/C][C]-3.09348[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]13.893[/C][C]-4.79299[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]13.496[/C][C]-2.396[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.5098[/C][C]-0.509808[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]13.7638[/C][C]0.736233[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.4752[/C][C]-0.275176[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]12.5352[/C][C]-0.235194[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]13.04[/C][C]-1.64002[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]12.7389[/C][C]-3.93895[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]13.3545[/C][C]1.24547[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]12.1161[/C][C]0.483948[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]11.987[/C][C]1.01304[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]13.2662[/C][C]-0.666193[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]12.837[/C][C]0.363035[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]12.2248[/C][C]-2.32482[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]12.2888[/C][C]-4.58882[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]12.6941[/C][C]-2.19406[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]11.9425[/C][C]1.45752[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]13.341[/C][C]-2.44099[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]12.8234[/C][C]-8.52343[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]12.7529[/C][C]-2.4529[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]12.5313[/C][C]-0.731337[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]12.9958[/C][C]-1.79583[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]13.6892[/C][C]-2.28924[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]13.4127[/C][C]-4.81269[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]11.934[/C][C]1.26604[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]13.2256[/C][C]-0.625574[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]13.0757[/C][C]-7.47565[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]11.961[/C][C]-2.06104[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]12.9873[/C][C]-4.18731[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]12.0629[/C][C]-4.36292[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]11.824[/C][C]-2.82396[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]12.5487[/C][C]-5.24873[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]13.6203[/C][C]-2.22029[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]13.2527[/C][C]0.347347[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]13.4429[/C][C]-5.54287[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]13.4212[/C][C]-2.7212[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]13.7776[/C][C]-3.47758[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]11.5737[/C][C]-3.27367[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]12.1648[/C][C]-2.56479[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]12.2365[/C][C]1.96351[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]11.8976[/C][C]-3.3976[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]11.7403[/C][C]1.75967[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]13.2213[/C][C]-8.32132[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]12.9819[/C][C]-6.58187[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]12.2094[/C][C]-2.60941[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]13.04[/C][C]-1.44002[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]13.1636[/C][C]-2.06356[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]12.6526[/C][C]-8.3026[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]13.9705[/C][C]-1.27054[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]13.355[/C][C]4.74504[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]14.4962[/C][C]3.35378[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]13.756[/C][C]2.844[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]12.3113[/C][C]0.288713[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]13.5475[/C][C]3.5525[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]13.9841[/C][C]5.11592[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]13.1023[/C][C]2.9977[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]12.3248[/C][C]1.02517[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]13.2654[/C][C]5.13456[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]13.5874[/C][C]1.11264[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]13.4255[/C][C]-2.82547[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]12.1025[/C][C]0.497487[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]12.1919[/C][C]4.00813[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]12.4132[/C][C]1.18684[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]12.9125[/C][C]5.98748[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]13.5184[/C][C]0.581581[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]14.3808[/C][C]0.119199[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]12.3519[/C][C]3.79809[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]13.3236[/C][C]1.42641[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]13.3523[/C][C]1.44773[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]13.5722[/C][C]-1.12225[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]13.0481[/C][C]-0.398145[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]13.8687[/C][C]3.48134[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]13.3642[/C][C]-4.76421[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]13.2042[/C][C]5.19582[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]13.4077[/C][C]2.69234[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]13.6951[/C][C]-2.09509[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]13.3065[/C][C]4.44352[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]11.7356[/C][C]3.51442[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]13.6164[/C][C]4.03356[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]12.6526[/C][C]3.6974[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]13.0536[/C][C]4.59644[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]12.283[/C][C]1.31702[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]12.417[/C][C]1.93298[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]11.9576[/C][C]2.79238[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]14.2208[/C][C]4.02923[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]12.2802[/C][C]-2.38021[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.532[/C][C]2.46804[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]13.4855[/C][C]4.76451[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]12.1783[/C][C]4.67167[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]13.7939[/C][C]0.806134[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]12.4441[/C][C]1.4059[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]14.1906[/C][C]4.75941[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]13.2391[/C][C]2.36089[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]13.0935[/C][C]1.75648[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]13.4293[/C][C]-1.67933[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]13.7075[/C][C]4.74247[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]13.5603[/C][C]2.33972[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]13.6757[/C][C]3.4243[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]13.8822[/C][C]2.2178[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]14.0752[/C][C]5.82483[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]13.355[/C][C]-2.40496[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]13.2225[/C][C]5.22753[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]14.3943[/C][C]0.705659[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]13.4661[/C][C]1.53391[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]13.4875[/C][C]-2.13748[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]13.4747[/C][C]2.4753[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]12.6905[/C][C]5.40953[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]13.5173[/C][C]1.08268[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]13.7803[/C][C]1.61967[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]13.7803[/C][C]1.61967[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]12.9388[/C][C]4.66116[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]13.0446[/C][C]0.305426[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]11.9696[/C][C]7.13044[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]12.8056[/C][C]2.54438[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]12.708[/C][C]-5.10801[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]13.2175[/C][C]0.182549[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]12.3384[/C][C]1.56163[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]13.8094[/C][C]5.29059[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]12.2644[/C][C]2.98559[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]13.0578[/C][C]-0.157845[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]13.2465[/C][C]2.85347[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]13.2465[/C][C]4.10347[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]13.2465[/C][C]-0.0965319[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]13.233[/C][C]-1.08299[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]11.7221[/C][C]0.877912[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]13.3108[/C][C]-2.96081[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]13.0288[/C][C]2.37122[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]13.4825[/C][C]-3.88246[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]12.2675[/C][C]5.93249[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]12.4178[/C][C]1.18221[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]13.9868[/C][C]0.863163[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]12.6952[/C][C]2.05477[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]11.8956[/C][C]2.20439[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]12.6011[/C][C]2.29889[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]12.7119[/C][C]3.53813[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]13.1023[/C][C]6.1477[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]12.5178[/C][C]1.0822[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]12.5189[/C][C]1.0811[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]13.4661[/C][C]2.18391[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]13.3371[/C][C]-0.587133[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]13.6892[/C][C]0.910761[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]12.484[/C][C]-2.63396[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]13.2488[/C][C]-0.598796[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]11.695[/C][C]7.50504[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]13.0757[/C][C]3.52435[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]13.532[/C][C]-2.33196[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]13.1163[/C][C]2.13373[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]12.252[/C][C]-0.351966[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]12.2802[/C][C]0.919789[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]12.885[/C][C]3.46499[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]11.6183[/C][C]0.781709[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]12.8137[/C][C]3.03626[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]13.8376[/C][C]4.31241[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]13.1156[/C][C]-1.96557[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]13.3534[/C][C]2.29657[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]12.417[/C][C]5.33298[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]12.6506[/C][C]-5.00062[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]13.3728[/C][C]-1.02282[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]12.4469[/C][C]3.15313[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]14.1763[/C][C]5.12371[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]12.9869[/C][C]2.21311[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]13.0136[/C][C]4.08636[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]13.955[/C][C]1.645[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]13.3681[/C][C]5.03193[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]13.1771[/C][C]5.8729[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]11.7491[/C][C]6.80088[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]13.3065[/C][C]5.79352[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]13.5146[/C][C]-0.414562[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]13.4525[/C][C]-0.602549[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]11.7491[/C][C]-2.24912[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]13.6009[/C][C]-9.1009[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]12.4732[/C][C]-0.623181[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]12.5189[/C][C]1.0811[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]11.7356[/C][C]-0.0355766[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]12.3818[/C][C]0.0181824[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]13.5146[/C][C]-0.164562[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]12.0142[/C][C]-0.614176[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]13.0752[/C][C]1.82478[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]14.0752[/C][C]5.82483[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]13.1954[/C][C]-1.99539[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]12.8854[/C][C]1.71456[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]12.6499[/C][C]4.95015[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]12.8408[/C][C]1.20918[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]12.5023[/C][C]3.59774[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]12.9253[/C][C]0.424699[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]12.4139[/C][C]-0.563919[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]13.1554[/C][C]-1.20544[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]13.7377[/C][C]1.01229[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]12.2946[/C][C]2.85541[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]13.5766[/C][C]-0.376574[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]13.5436[/C][C]3.30636[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]13.5736[/C][C]-5.72355[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]13.0144[/C][C]-5.31439[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]12.548[/C][C]0.0520225[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]11.9871[/C][C]-4.1371[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]13.355[/C][C]-2.40496[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]13.5572[/C][C]-1.20718[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]11.9995[/C][C]-2.04947[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]13.0752[/C][C]1.82478[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]13.4158[/C][C]3.23421[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]14.0995[/C][C]-0.699495[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]12.9381[/C][C]1.01185[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]11.8123[/C][C]3.88771[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]13.7781[/C][C]3.07194[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]13.5184[/C][C]-2.56842[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]12.1648[/C][C]3.18521[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]13.7803[/C][C]-1.58033[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]11.8685[/C][C]3.23147[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]13.3108[/C][C]4.43919[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]13.04[/C][C]2.15998[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]13.4503[/C][C]1.14972[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]12.9869[/C][C]3.66311[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]12.7518[/C][C]-4.65179[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262963&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262963&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 Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	12.9517	-0.0516856
2	12.2	12.8408	-0.640822
3	12.8	13.3507	-0.550673
4	7.4	12.0765	-4.67646
5	6.7	12.2536	-5.55362
6	12.6	11.7511	0.848897
7	14.8	13.4564	1.34359
8	13.3	13.4251	-0.12506
9	11.1	12.1385	-1.03847
10	8.2	12.7684	-4.56843
11	11.4	13.1884	-1.78838
12	6.4	12.4837	-6.08369
13	10.6	12.6041	-2.00413
14	12	12.88	-0.87999
15	6.3	12.4244	-6.12444
16	11.3	12.6712	-1.37122
17	11.9	12.9427	-1.0427
18	9.3	12.4594	-3.15937
19	9.6	12.438	-2.83798
20	10	12.2179	-2.21793
21	6.4	12.9683	-6.56833
22	13.8	12.6332	1.16679
23	10.8	12.4596	-1.65964
24	13.8	12.8807	0.919315
25	11.7	13.5766	-1.87657
26	10.9	12.1625	-1.26254
27	16.1	12.7708	3.32922
28	13.4	13.1906	0.20936
29	9.9	13.8493	-3.94927
30	11.5	13.3673	-1.86731
31	8.3	12.4857	-4.1857
32	11.7	12.2935	-0.593481
33	9	13.3108	-4.31081
34	9.7	13.2573	-3.55731
35	10.8	13.632	-2.83198
36	10.3	14.2034	-3.90337
37	10.4	12.3992	-1.99923
38	12.7	12.4837	0.216306
39	9.3	13.3545	-4.05453
40	11.8	13.3108	-1.51081
41	5.9	13.3991	-7.49915
42	11.4	13.6164	-2.21644
43	13	12.899	0.101022
44	10.8	13.8628	-3.06281
45	12.3	13.2654	-0.965437
46	11.3	13.3681	-2.06807
47	11.8	12.0714	-0.271436
48	7.9	12.546	-4.64598
49	12.7	11.4552	1.24484
50	12.3	13.6358	-1.33584
51	11.6	13.8822	-2.2822
52	6.7	12.4267	-5.7267
53	10.9	13.7618	-2.86176
54	12.1	12.25	-0.15003
55	13.3	12.5906	0.709408
56	10.1	13.692	-3.59199
57	5.7	13.6757	-7.9757
58	14.3	11.6806	2.61943
59	8	12.3411	-4.34107
60	13.3	13.1206	0.179403
61	9.3	13.4882	-4.18824
62	12.5	12.0231	0.476945
63	7.6	14.1898	-6.58983
64	15.9	13.4079	2.49207
65	9.2	12.2935	-3.09348
66	9.1	13.893	-4.79299
67	11.1	13.496	-2.396
68	13	13.5098	-0.509808
69	14.5	13.7638	0.736233
70	12.2	12.4752	-0.275176
71	12.3	12.5352	-0.235194
72	11.4	13.04	-1.64002
73	8.8	12.7389	-3.93895
74	14.6	13.3545	1.24547
75	12.6	12.1161	0.483948
76	13	11.987	1.01304
77	12.6	13.2662	-0.666193
78	13.2	12.837	0.363035
79	9.9	12.2248	-2.32482
80	7.7	12.2888	-4.58882
81	10.5	12.6941	-2.19406
82	13.4	11.9425	1.45752
83	10.9	13.341	-2.44099
84	4.3	12.8234	-8.52343
85	10.3	12.7529	-2.4529
86	11.8	12.5313	-0.731337
87	11.2	12.9958	-1.79583
88	11.4	13.6892	-2.28924
89	8.6	13.4127	-4.81269
90	13.2	11.934	1.26604
91	12.6	13.2256	-0.625574
92	5.6	13.0757	-7.47565
93	9.9	11.961	-2.06104
94	8.8	12.9873	-4.18731
95	7.7	12.0629	-4.36292
96	9	11.824	-2.82396
97	7.3	12.5487	-5.24873
98	11.4	13.6203	-2.22029
99	13.6	13.2527	0.347347
100	7.9	13.4429	-5.54287
101	10.7	13.4212	-2.7212
102	10.3	13.7776	-3.47758
103	8.3	11.5737	-3.27367
104	9.6	12.1648	-2.56479
105	14.2	12.2365	1.96351
106	8.5	11.8976	-3.3976
107	13.5	11.7403	1.75967
108	4.9	13.2213	-8.32132
109	6.4	12.9819	-6.58187
110	9.6	12.2094	-2.60941
111	11.6	13.04	-1.44002
112	11.1	13.1636	-2.06356
113	4.35	12.6526	-8.3026
114	12.7	13.9705	-1.27054
115	18.1	13.355	4.74504
116	17.85	14.4962	3.35378
117	16.6	13.756	2.844
118	12.6	12.3113	0.288713
119	17.1	13.5475	3.5525
120	19.1	13.9841	5.11592
121	16.1	13.1023	2.9977
122	13.35	12.3248	1.02517
123	18.4	13.2654	5.13456
124	14.7	13.5874	1.11264
125	10.6	13.4255	-2.82547
126	12.6	12.1025	0.497487
127	16.2	12.1919	4.00813
128	13.6	12.4132	1.18684
129	18.9	12.9125	5.98748
130	14.1	13.5184	0.581581
131	14.5	14.3808	0.119199
132	16.15	12.3519	3.79809
133	14.75	13.3236	1.42641
134	14.8	13.3523	1.44773
135	12.45	13.5722	-1.12225
136	12.65	13.0481	-0.398145
137	17.35	13.8687	3.48134
138	8.6	13.3642	-4.76421
139	18.4	13.2042	5.19582
140	16.1	13.4077	2.69234
141	11.6	13.6951	-2.09509
142	17.75	13.3065	4.44352
143	15.25	11.7356	3.51442
144	17.65	13.6164	4.03356
145	16.35	12.6526	3.6974
146	17.65	13.0536	4.59644
147	13.6	12.283	1.31702
148	14.35	12.417	1.93298
149	14.75	11.9576	2.79238
150	18.25	14.2208	4.02923
151	9.9	12.2802	-2.38021
152	16	13.532	2.46804
153	18.25	13.4855	4.76451
154	16.85	12.1783	4.67167
155	14.6	13.7939	0.806134
156	13.85	12.4441	1.4059
157	18.95	14.1906	4.75941
158	15.6	13.2391	2.36089
159	14.85	13.0935	1.75648
160	11.75	13.4293	-1.67933
161	18.45	13.7075	4.74247
162	15.9	13.5603	2.33972
163	17.1	13.6757	3.4243
164	16.1	13.8822	2.2178
165	19.9	14.0752	5.82483
166	10.95	13.355	-2.40496
167	18.45	13.2225	5.22753
168	15.1	14.3943	0.705659
169	15	13.4661	1.53391
170	11.35	13.4875	-2.13748
171	15.95	13.4747	2.4753
172	18.1	12.6905	5.40953
173	14.6	13.5173	1.08268
174	15.4	13.7803	1.61967
175	15.4	13.7803	1.61967
176	17.6	12.9388	4.66116
177	13.35	13.0446	0.305426
178	19.1	11.9696	7.13044
179	15.35	12.8056	2.54438
180	7.6	12.708	-5.10801
181	13.4	13.2175	0.182549
182	13.9	12.3384	1.56163
183	19.1	13.8094	5.29059
184	15.25	12.2644	2.98559
185	12.9	13.0578	-0.157845
186	16.1	13.2465	2.85347
187	17.35	13.2465	4.10347
188	13.15	13.2465	-0.0965319
189	12.15	13.233	-1.08299
190	12.6	11.7221	0.877912
191	10.35	13.3108	-2.96081
192	15.4	13.0288	2.37122
193	9.6	13.4825	-3.88246
194	18.2	12.2675	5.93249
195	13.6	12.4178	1.18221
196	14.85	13.9868	0.863163
197	14.75	12.6952	2.05477
198	14.1	11.8956	2.20439
199	14.9	12.6011	2.29889
200	16.25	12.7119	3.53813
201	19.25	13.1023	6.1477
202	13.6	12.5178	1.0822
203	13.6	12.5189	1.0811
204	15.65	13.4661	2.18391
205	12.75	13.3371	-0.587133
206	14.6	13.6892	0.910761
207	9.85	12.484	-2.63396
208	12.65	13.2488	-0.598796
209	19.2	11.695	7.50504
210	16.6	13.0757	3.52435
211	11.2	13.532	-2.33196
212	15.25	13.1163	2.13373
213	11.9	12.252	-0.351966
214	13.2	12.2802	0.919789
215	16.35	12.885	3.46499
216	12.4	11.6183	0.781709
217	15.85	12.8137	3.03626
218	18.15	13.8376	4.31241
219	11.15	13.1156	-1.96557
220	15.65	13.3534	2.29657
221	17.75	12.417	5.33298
222	7.65	12.6506	-5.00062
223	12.35	13.3728	-1.02282
224	15.6	12.4469	3.15313
225	19.3	14.1763	5.12371
226	15.2	12.9869	2.21311
227	17.1	13.0136	4.08636
228	15.6	13.955	1.645
229	18.4	13.3681	5.03193
230	19.05	13.1771	5.8729
231	18.55	11.7491	6.80088
232	19.1	13.3065	5.79352
233	13.1	13.5146	-0.414562
234	12.85	13.4525	-0.602549
235	9.5	11.7491	-2.24912
236	4.5	13.6009	-9.1009
237	11.85	12.4732	-0.623181
238	13.6	12.5189	1.0811
239	11.7	11.7356	-0.0355766
240	12.4	12.3818	0.0181824
241	13.35	13.5146	-0.164562
242	11.4	12.0142	-0.614176
243	14.9	13.0752	1.82478
244	19.9	14.0752	5.82483
245	11.2	13.1954	-1.99539
246	14.6	12.8854	1.71456
247	17.6	12.6499	4.95015
248	14.05	12.8408	1.20918
249	16.1	12.5023	3.59774
250	13.35	12.9253	0.424699
251	11.85	12.4139	-0.563919
252	11.95	13.1554	-1.20544
253	14.75	13.7377	1.01229
254	15.15	12.2946	2.85541
255	13.2	13.5766	-0.376574
256	16.85	13.5436	3.30636
257	7.85	13.5736	-5.72355
258	7.7	13.0144	-5.31439
259	12.6	12.548	0.0520225
260	7.85	11.9871	-4.1371
261	10.95	13.355	-2.40496
262	12.35	13.5572	-1.20718
263	9.95	11.9995	-2.04947
264	14.9	13.0752	1.82478
265	16.65	13.4158	3.23421
266	13.4	14.0995	-0.699495
267	13.95	12.9381	1.01185
268	15.7	11.8123	3.88771
269	16.85	13.7781	3.07194
270	10.95	13.5184	-2.56842
271	15.35	12.1648	3.18521
272	12.2	13.7803	-1.58033
273	15.1	11.8685	3.23147
274	17.75	13.3108	4.43919
275	15.2	13.04	2.15998
276	14.6	13.4503	1.14972
277	16.65	12.9869	3.66311
278	8.1	12.7518	-4.65179

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
9	0.261163	0.522326	0.738837
10	0.321693	0.643386	0.678307
11	0.196219	0.392437	0.803781
12	0.417723	0.835445	0.582277
13	0.305602	0.611203	0.694398
14	0.211944	0.423888	0.788056
15	0.255903	0.511806	0.744097
16	0.183511	0.367023	0.816489
17	0.127725	0.25545	0.872275
18	0.0981792	0.196358	0.901821
19	0.065943	0.131886	0.934057
20	0.0430935	0.086187	0.956906
21	0.0835453	0.167091	0.916455
22	0.111575	0.223151	0.888425
23	0.0875799	0.17516	0.91242
24	0.0762538	0.152508	0.923746
25	0.0538113	0.107623	0.946189
26	0.0506365	0.101273	0.949363
27	0.0930229	0.186046	0.906977
28	0.0718517	0.143703	0.928148
29	0.0772399	0.15448	0.92276
30	0.0564875	0.112975	0.943513
31	0.0441751	0.0883502	0.955825
32	0.0328278	0.0656555	0.967172
33	0.0342501	0.0685002	0.96575
34	0.0299558	0.0599116	0.970044
35	0.0217387	0.0434774	0.978261
36	0.0180564	0.0361128	0.981944
37	0.014607	0.0292139	0.985393
38	0.0119684	0.0239368	0.988032
39	0.0106894	0.0213788	0.989311
40	0.00736647	0.0147329	0.992634
41	0.0184137	0.0368273	0.981586
42	0.0132757	0.0265513	0.986724
43	0.0107472	0.0214945	0.989253
44	0.00802651	0.016053	0.991973
45	0.00652847	0.0130569	0.993472
46	0.00458272	0.00916544	0.995417
47	0.00326189	0.00652378	0.996738
48	0.00394935	0.00789871	0.996051
49	0.00343486	0.00686972	0.996565
50	0.00258339	0.00516679	0.997417
51	0.00178934	0.00357867	0.998211
52	0.00250453	0.00500907	0.997495
53	0.00178845	0.0035769	0.998212
54	0.00130925	0.0026185	0.998691
55	0.00128385	0.00256769	0.998716
56	0.00105104	0.00210207	0.998949
57	0.00298467	0.00596933	0.997015
58	0.00405136	0.00810272	0.995949
59	0.00341467	0.00682933	0.996585
60	0.00269739	0.00539478	0.997303
61	0.00259556	0.00519112	0.997404
62	0.00197914	0.00395828	0.998021
63	0.00225654	0.00451309	0.997743
64	0.00378923	0.00757847	0.996211
65	0.0033533	0.0067066	0.996647
66	0.00322927	0.00645854	0.996771
67	0.00252582	0.00505165	0.997474
68	0.00204271	0.00408542	0.997957
69	0.00333884	0.00667768	0.996661
70	0.0027259	0.00545179	0.997274
71	0.00202727	0.00405455	0.997973
72	0.00150916	0.00301832	0.998491
73	0.0014803	0.0029606	0.99852
74	0.00163558	0.00327115	0.998364
75	0.00131453	0.00262905	0.998685
76	0.000983142	0.00196628	0.999017
77	0.000726087	0.00145217	0.999274
78	0.000600906	0.00120181	0.999399
79	0.000443878	0.000887756	0.999556
80	0.00052468	0.00104936	0.999475
81	0.000391122	0.000782245	0.999609
82	0.000367026	0.000734051	0.999633
83	0.0002753	0.0005506	0.999725
84	0.0016537	0.00330739	0.998346
85	0.00133425	0.0026685	0.998666
86	0.000994731	0.00198946	0.999005
87	0.000754633	0.00150927	0.999245
88	0.000596869	0.00119374	0.999403
89	0.000671117	0.00134223	0.999329
90	0.000667893	0.00133579	0.999332
91	0.000568694	0.00113739	0.999431
92	0.00147545	0.00295089	0.998525
93	0.00117848	0.00235696	0.998822
94	0.00117249	0.00234497	0.998828
95	0.00144718	0.00289436	0.998553
96	0.0013864	0.00277281	0.998614
97	0.00230077	0.00460154	0.997699
98	0.00188039	0.00376078	0.99812
99	0.00170373	0.00340746	0.998296
100	0.00237706	0.00475413	0.997623
101	0.0020818	0.00416359	0.997918
102	0.0019694	0.0039388	0.998031
103	0.00217473	0.00434946	0.997825
104	0.0019056	0.00381119	0.998094
105	0.00202848	0.00405695	0.997972
106	0.00210504	0.00421008	0.997895
107	0.00253917	0.00507835	0.997461
108	0.0094927	0.0189854	0.990507
109	0.0223484	0.0446968	0.977652
110	0.0203887	0.0407774	0.979611
111	0.0182447	0.0364894	0.981755
112	0.0170283	0.0340565	0.982972
113	0.056127	0.112254	0.943873
114	0.0543573	0.108715	0.945643
115	0.112242	0.224483	0.887758
116	0.152462	0.304924	0.847538
117	0.188026	0.376053	0.811974
118	0.177935	0.35587	0.822065
119	0.21832	0.436641	0.78168
120	0.317884	0.635768	0.682116
121	0.341483	0.682966	0.658517
122	0.329274	0.658548	0.670726
123	0.449489	0.898977	0.550511
124	0.438487	0.876974	0.561513
125	0.438432	0.876864	0.561568
126	0.419444	0.838889	0.580556
127	0.451553	0.903106	0.548447
128	0.436573	0.873146	0.563427
129	0.549695	0.900611	0.450305
130	0.524955	0.95009	0.475045
131	0.500433	0.999134	0.499567
132	0.518325	0.96335	0.481675
133	0.51095	0.9781	0.48905
134	0.513041	0.973918	0.486959
135	0.486662	0.973324	0.513338
136	0.469677	0.939353	0.530323
137	0.493441	0.986881	0.506559
138	0.558463	0.883074	0.441537
139	0.626074	0.747853	0.373926
140	0.624919	0.750162	0.375081
141	0.61471	0.770579	0.38529
142	0.647808	0.704384	0.352192
143	0.670371	0.659258	0.329629
144	0.694084	0.611833	0.305916
145	0.709042	0.581916	0.290958
146	0.742628	0.514745	0.257372
147	0.726377	0.547246	0.273623
148	0.709026	0.581949	0.290974
149	0.705703	0.588594	0.294297
150	0.724985	0.55003	0.275015
151	0.722112	0.555775	0.277888
152	0.71145	0.5771	0.28855
153	0.753382	0.493235	0.246618
154	0.778896	0.442207	0.221104
155	0.753839	0.492323	0.246161
156	0.729694	0.540611	0.270306
157	0.763695	0.47261	0.236305
158	0.7528	0.494401	0.2472
159	0.736422	0.527157	0.263578
160	0.725108	0.549785	0.274892
161	0.757468	0.485064	0.242532
162	0.747091	0.505818	0.252909
163	0.747263	0.505475	0.252737
164	0.72961	0.540779	0.27039
165	0.788842	0.422316	0.211158
166	0.781251	0.437499	0.218749
167	0.817372	0.365256	0.182628
168	0.793252	0.413495	0.206748
169	0.771352	0.457296	0.228648
170	0.766053	0.467894	0.233947
171	0.753752	0.492496	0.246248
172	0.79152	0.41696	0.20848
173	0.766731	0.466537	0.233269
174	0.743746	0.512509	0.256254
175	0.719755	0.560489	0.280245
176	0.738788	0.522424	0.261212
177	0.709206	0.581588	0.290794
178	0.808366	0.383268	0.191634
179	0.798144	0.403712	0.201856
180	0.862211	0.275578	0.137789
181	0.84083	0.31834	0.15917
182	0.820809	0.358381	0.179191
183	0.84895	0.302101	0.15105
184	0.843223	0.313554	0.156777
185	0.819746	0.360509	0.180254
186	0.809566	0.380868	0.190434
187	0.819614	0.360772	0.180386
188	0.794122	0.411756	0.205878
189	0.774386	0.451228	0.225614
190	0.746647	0.506706	0.253353
191	0.751304	0.497393	0.248696
192	0.737576	0.524849	0.262424
193	0.780249	0.439503	0.219751
194	0.824965	0.350069	0.175035
195	0.808063	0.383873	0.191937
196	0.782006	0.435988	0.217994
197	0.763197	0.473606	0.236803
198	0.744206	0.511588	0.255794
199	0.720509	0.558982	0.279491
200	0.715192	0.569617	0.284808
201	0.785669	0.428662	0.214331
202	0.757048	0.485903	0.242952
203	0.72711	0.545779	0.27289
204	0.700863	0.598275	0.299137
205	0.68203	0.63594	0.31797
206	0.647399	0.705202	0.352601
207	0.650969	0.698061	0.349031
208	0.625018	0.749964	0.374982
209	0.704798	0.590405	0.295202
210	0.68902	0.621959	0.31098
211	0.665626	0.668748	0.334374
212	0.636739	0.726521	0.363261
213	0.598776	0.802448	0.401224
214	0.558674	0.882652	0.441326
215	0.553139	0.893722	0.446861
216	0.512148	0.975704	0.487852
217	0.491672	0.983343	0.508328
218	0.514522	0.970955	0.485478
219	0.48084	0.961679	0.51916
220	0.45286	0.90572	0.54714
221	0.499132	0.998265	0.500868
222	0.657082	0.685836	0.342918
223	0.616042	0.767916	0.383958
224	0.582929	0.834142	0.417071
225	0.571781	0.856439	0.428219
226	0.539643	0.920714	0.460357
227	0.513485	0.97303	0.486515
228	0.471874	0.943748	0.528126
229	0.541552	0.916895	0.458448
230	0.596856	0.806289	0.403144
231	0.723832	0.552336	0.276168
232	0.79438	0.411239	0.20562
233	0.75841	0.483181	0.24159
234	0.721793	0.556413	0.278207
235	0.695697	0.608606	0.304303
236	0.935334	0.129332	0.0646662
237	0.919447	0.161107	0.0805533
238	0.898029	0.203941	0.101971
239	0.873084	0.253832	0.126916
240	0.842271	0.315458	0.157729
241	0.809074	0.381852	0.190926
242	0.772873	0.454254	0.227127
243	0.72926	0.541479	0.27074
244	0.845613	0.308773	0.154387
245	0.831297	0.337406	0.168703
246	0.795805	0.408391	0.204195
247	0.799498	0.401004	0.200502
248	0.762668	0.474663	0.237332
249	0.796338	0.407325	0.203662
250	0.751865	0.496271	0.248135
251	0.704281	0.591439	0.295719
252	0.672423	0.655153	0.327577
253	0.608659	0.782682	0.391341
254	0.577725	0.84455	0.422275
255	0.517394	0.965212	0.482606
256	0.463898	0.927797	0.536102
257	0.771722	0.456556	0.228278
258	0.78336	0.433279	0.21664
259	0.732466	0.535067	0.267534
260	0.882449	0.235102	0.117551
261	0.875632	0.248737	0.124368
262	0.918973	0.162053	0.0810267
263	0.874724	0.250552	0.125276
264	0.846413	0.307173	0.153587
265	0.79309	0.413819	0.20691
266	0.703963	0.592074	0.296037
267	0.591299	0.817401	0.408701
268	0.452088	0.904175	0.547912
269	0.975642	0.0487157	0.0243578

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.261163 & 0.522326 & 0.738837 \tabularnewline
10 & 0.321693 & 0.643386 & 0.678307 \tabularnewline
11 & 0.196219 & 0.392437 & 0.803781 \tabularnewline
12 & 0.417723 & 0.835445 & 0.582277 \tabularnewline
13 & 0.305602 & 0.611203 & 0.694398 \tabularnewline
14 & 0.211944 & 0.423888 & 0.788056 \tabularnewline
15 & 0.255903 & 0.511806 & 0.744097 \tabularnewline
16 & 0.183511 & 0.367023 & 0.816489 \tabularnewline
17 & 0.127725 & 0.25545 & 0.872275 \tabularnewline
18 & 0.0981792 & 0.196358 & 0.901821 \tabularnewline
19 & 0.065943 & 0.131886 & 0.934057 \tabularnewline
20 & 0.0430935 & 0.086187 & 0.956906 \tabularnewline
21 & 0.0835453 & 0.167091 & 0.916455 \tabularnewline
22 & 0.111575 & 0.223151 & 0.888425 \tabularnewline
23 & 0.0875799 & 0.17516 & 0.91242 \tabularnewline
24 & 0.0762538 & 0.152508 & 0.923746 \tabularnewline
25 & 0.0538113 & 0.107623 & 0.946189 \tabularnewline
26 & 0.0506365 & 0.101273 & 0.949363 \tabularnewline
27 & 0.0930229 & 0.186046 & 0.906977 \tabularnewline
28 & 0.0718517 & 0.143703 & 0.928148 \tabularnewline
29 & 0.0772399 & 0.15448 & 0.92276 \tabularnewline
30 & 0.0564875 & 0.112975 & 0.943513 \tabularnewline
31 & 0.0441751 & 0.0883502 & 0.955825 \tabularnewline
32 & 0.0328278 & 0.0656555 & 0.967172 \tabularnewline
33 & 0.0342501 & 0.0685002 & 0.96575 \tabularnewline
34 & 0.0299558 & 0.0599116 & 0.970044 \tabularnewline
35 & 0.0217387 & 0.0434774 & 0.978261 \tabularnewline
36 & 0.0180564 & 0.0361128 & 0.981944 \tabularnewline
37 & 0.014607 & 0.0292139 & 0.985393 \tabularnewline
38 & 0.0119684 & 0.0239368 & 0.988032 \tabularnewline
39 & 0.0106894 & 0.0213788 & 0.989311 \tabularnewline
40 & 0.00736647 & 0.0147329 & 0.992634 \tabularnewline
41 & 0.0184137 & 0.0368273 & 0.981586 \tabularnewline
42 & 0.0132757 & 0.0265513 & 0.986724 \tabularnewline
43 & 0.0107472 & 0.0214945 & 0.989253 \tabularnewline
44 & 0.00802651 & 0.016053 & 0.991973 \tabularnewline
45 & 0.00652847 & 0.0130569 & 0.993472 \tabularnewline
46 & 0.00458272 & 0.00916544 & 0.995417 \tabularnewline
47 & 0.00326189 & 0.00652378 & 0.996738 \tabularnewline
48 & 0.00394935 & 0.00789871 & 0.996051 \tabularnewline
49 & 0.00343486 & 0.00686972 & 0.996565 \tabularnewline
50 & 0.00258339 & 0.00516679 & 0.997417 \tabularnewline
51 & 0.00178934 & 0.00357867 & 0.998211 \tabularnewline
52 & 0.00250453 & 0.00500907 & 0.997495 \tabularnewline
53 & 0.00178845 & 0.0035769 & 0.998212 \tabularnewline
54 & 0.00130925 & 0.0026185 & 0.998691 \tabularnewline
55 & 0.00128385 & 0.00256769 & 0.998716 \tabularnewline
56 & 0.00105104 & 0.00210207 & 0.998949 \tabularnewline
57 & 0.00298467 & 0.00596933 & 0.997015 \tabularnewline
58 & 0.00405136 & 0.00810272 & 0.995949 \tabularnewline
59 & 0.00341467 & 0.00682933 & 0.996585 \tabularnewline
60 & 0.00269739 & 0.00539478 & 0.997303 \tabularnewline
61 & 0.00259556 & 0.00519112 & 0.997404 \tabularnewline
62 & 0.00197914 & 0.00395828 & 0.998021 \tabularnewline
63 & 0.00225654 & 0.00451309 & 0.997743 \tabularnewline
64 & 0.00378923 & 0.00757847 & 0.996211 \tabularnewline
65 & 0.0033533 & 0.0067066 & 0.996647 \tabularnewline
66 & 0.00322927 & 0.00645854 & 0.996771 \tabularnewline
67 & 0.00252582 & 0.00505165 & 0.997474 \tabularnewline
68 & 0.00204271 & 0.00408542 & 0.997957 \tabularnewline
69 & 0.00333884 & 0.00667768 & 0.996661 \tabularnewline
70 & 0.0027259 & 0.00545179 & 0.997274 \tabularnewline
71 & 0.00202727 & 0.00405455 & 0.997973 \tabularnewline
72 & 0.00150916 & 0.00301832 & 0.998491 \tabularnewline
73 & 0.0014803 & 0.0029606 & 0.99852 \tabularnewline
74 & 0.00163558 & 0.00327115 & 0.998364 \tabularnewline
75 & 0.00131453 & 0.00262905 & 0.998685 \tabularnewline
76 & 0.000983142 & 0.00196628 & 0.999017 \tabularnewline
77 & 0.000726087 & 0.00145217 & 0.999274 \tabularnewline
78 & 0.000600906 & 0.00120181 & 0.999399 \tabularnewline
79 & 0.000443878 & 0.000887756 & 0.999556 \tabularnewline
80 & 0.00052468 & 0.00104936 & 0.999475 \tabularnewline
81 & 0.000391122 & 0.000782245 & 0.999609 \tabularnewline
82 & 0.000367026 & 0.000734051 & 0.999633 \tabularnewline
83 & 0.0002753 & 0.0005506 & 0.999725 \tabularnewline
84 & 0.0016537 & 0.00330739 & 0.998346 \tabularnewline
85 & 0.00133425 & 0.0026685 & 0.998666 \tabularnewline
86 & 0.000994731 & 0.00198946 & 0.999005 \tabularnewline
87 & 0.000754633 & 0.00150927 & 0.999245 \tabularnewline
88 & 0.000596869 & 0.00119374 & 0.999403 \tabularnewline
89 & 0.000671117 & 0.00134223 & 0.999329 \tabularnewline
90 & 0.000667893 & 0.00133579 & 0.999332 \tabularnewline
91 & 0.000568694 & 0.00113739 & 0.999431 \tabularnewline
92 & 0.00147545 & 0.00295089 & 0.998525 \tabularnewline
93 & 0.00117848 & 0.00235696 & 0.998822 \tabularnewline
94 & 0.00117249 & 0.00234497 & 0.998828 \tabularnewline
95 & 0.00144718 & 0.00289436 & 0.998553 \tabularnewline
96 & 0.0013864 & 0.00277281 & 0.998614 \tabularnewline
97 & 0.00230077 & 0.00460154 & 0.997699 \tabularnewline
98 & 0.00188039 & 0.00376078 & 0.99812 \tabularnewline
99 & 0.00170373 & 0.00340746 & 0.998296 \tabularnewline
100 & 0.00237706 & 0.00475413 & 0.997623 \tabularnewline
101 & 0.0020818 & 0.00416359 & 0.997918 \tabularnewline
102 & 0.0019694 & 0.0039388 & 0.998031 \tabularnewline
103 & 0.00217473 & 0.00434946 & 0.997825 \tabularnewline
104 & 0.0019056 & 0.00381119 & 0.998094 \tabularnewline
105 & 0.00202848 & 0.00405695 & 0.997972 \tabularnewline
106 & 0.00210504 & 0.00421008 & 0.997895 \tabularnewline
107 & 0.00253917 & 0.00507835 & 0.997461 \tabularnewline
108 & 0.0094927 & 0.0189854 & 0.990507 \tabularnewline
109 & 0.0223484 & 0.0446968 & 0.977652 \tabularnewline
110 & 0.0203887 & 0.0407774 & 0.979611 \tabularnewline
111 & 0.0182447 & 0.0364894 & 0.981755 \tabularnewline
112 & 0.0170283 & 0.0340565 & 0.982972 \tabularnewline
113 & 0.056127 & 0.112254 & 0.943873 \tabularnewline
114 & 0.0543573 & 0.108715 & 0.945643 \tabularnewline
115 & 0.112242 & 0.224483 & 0.887758 \tabularnewline
116 & 0.152462 & 0.304924 & 0.847538 \tabularnewline
117 & 0.188026 & 0.376053 & 0.811974 \tabularnewline
118 & 0.177935 & 0.35587 & 0.822065 \tabularnewline
119 & 0.21832 & 0.436641 & 0.78168 \tabularnewline
120 & 0.317884 & 0.635768 & 0.682116 \tabularnewline
121 & 0.341483 & 0.682966 & 0.658517 \tabularnewline
122 & 0.329274 & 0.658548 & 0.670726 \tabularnewline
123 & 0.449489 & 0.898977 & 0.550511 \tabularnewline
124 & 0.438487 & 0.876974 & 0.561513 \tabularnewline
125 & 0.438432 & 0.876864 & 0.561568 \tabularnewline
126 & 0.419444 & 0.838889 & 0.580556 \tabularnewline
127 & 0.451553 & 0.903106 & 0.548447 \tabularnewline
128 & 0.436573 & 0.873146 & 0.563427 \tabularnewline
129 & 0.549695 & 0.900611 & 0.450305 \tabularnewline
130 & 0.524955 & 0.95009 & 0.475045 \tabularnewline
131 & 0.500433 & 0.999134 & 0.499567 \tabularnewline
132 & 0.518325 & 0.96335 & 0.481675 \tabularnewline
133 & 0.51095 & 0.9781 & 0.48905 \tabularnewline
134 & 0.513041 & 0.973918 & 0.486959 \tabularnewline
135 & 0.486662 & 0.973324 & 0.513338 \tabularnewline
136 & 0.469677 & 0.939353 & 0.530323 \tabularnewline
137 & 0.493441 & 0.986881 & 0.506559 \tabularnewline
138 & 0.558463 & 0.883074 & 0.441537 \tabularnewline
139 & 0.626074 & 0.747853 & 0.373926 \tabularnewline
140 & 0.624919 & 0.750162 & 0.375081 \tabularnewline
141 & 0.61471 & 0.770579 & 0.38529 \tabularnewline
142 & 0.647808 & 0.704384 & 0.352192 \tabularnewline
143 & 0.670371 & 0.659258 & 0.329629 \tabularnewline
144 & 0.694084 & 0.611833 & 0.305916 \tabularnewline
145 & 0.709042 & 0.581916 & 0.290958 \tabularnewline
146 & 0.742628 & 0.514745 & 0.257372 \tabularnewline
147 & 0.726377 & 0.547246 & 0.273623 \tabularnewline
148 & 0.709026 & 0.581949 & 0.290974 \tabularnewline
149 & 0.705703 & 0.588594 & 0.294297 \tabularnewline
150 & 0.724985 & 0.55003 & 0.275015 \tabularnewline
151 & 0.722112 & 0.555775 & 0.277888 \tabularnewline
152 & 0.71145 & 0.5771 & 0.28855 \tabularnewline
153 & 0.753382 & 0.493235 & 0.246618 \tabularnewline
154 & 0.778896 & 0.442207 & 0.221104 \tabularnewline
155 & 0.753839 & 0.492323 & 0.246161 \tabularnewline
156 & 0.729694 & 0.540611 & 0.270306 \tabularnewline
157 & 0.763695 & 0.47261 & 0.236305 \tabularnewline
158 & 0.7528 & 0.494401 & 0.2472 \tabularnewline
159 & 0.736422 & 0.527157 & 0.263578 \tabularnewline
160 & 0.725108 & 0.549785 & 0.274892 \tabularnewline
161 & 0.757468 & 0.485064 & 0.242532 \tabularnewline
162 & 0.747091 & 0.505818 & 0.252909 \tabularnewline
163 & 0.747263 & 0.505475 & 0.252737 \tabularnewline
164 & 0.72961 & 0.540779 & 0.27039 \tabularnewline
165 & 0.788842 & 0.422316 & 0.211158 \tabularnewline
166 & 0.781251 & 0.437499 & 0.218749 \tabularnewline
167 & 0.817372 & 0.365256 & 0.182628 \tabularnewline
168 & 0.793252 & 0.413495 & 0.206748 \tabularnewline
169 & 0.771352 & 0.457296 & 0.228648 \tabularnewline
170 & 0.766053 & 0.467894 & 0.233947 \tabularnewline
171 & 0.753752 & 0.492496 & 0.246248 \tabularnewline
172 & 0.79152 & 0.41696 & 0.20848 \tabularnewline
173 & 0.766731 & 0.466537 & 0.233269 \tabularnewline
174 & 0.743746 & 0.512509 & 0.256254 \tabularnewline
175 & 0.719755 & 0.560489 & 0.280245 \tabularnewline
176 & 0.738788 & 0.522424 & 0.261212 \tabularnewline
177 & 0.709206 & 0.581588 & 0.290794 \tabularnewline
178 & 0.808366 & 0.383268 & 0.191634 \tabularnewline
179 & 0.798144 & 0.403712 & 0.201856 \tabularnewline
180 & 0.862211 & 0.275578 & 0.137789 \tabularnewline
181 & 0.84083 & 0.31834 & 0.15917 \tabularnewline
182 & 0.820809 & 0.358381 & 0.179191 \tabularnewline
183 & 0.84895 & 0.302101 & 0.15105 \tabularnewline
184 & 0.843223 & 0.313554 & 0.156777 \tabularnewline
185 & 0.819746 & 0.360509 & 0.180254 \tabularnewline
186 & 0.809566 & 0.380868 & 0.190434 \tabularnewline
187 & 0.819614 & 0.360772 & 0.180386 \tabularnewline
188 & 0.794122 & 0.411756 & 0.205878 \tabularnewline
189 & 0.774386 & 0.451228 & 0.225614 \tabularnewline
190 & 0.746647 & 0.506706 & 0.253353 \tabularnewline
191 & 0.751304 & 0.497393 & 0.248696 \tabularnewline
192 & 0.737576 & 0.524849 & 0.262424 \tabularnewline
193 & 0.780249 & 0.439503 & 0.219751 \tabularnewline
194 & 0.824965 & 0.350069 & 0.175035 \tabularnewline
195 & 0.808063 & 0.383873 & 0.191937 \tabularnewline
196 & 0.782006 & 0.435988 & 0.217994 \tabularnewline
197 & 0.763197 & 0.473606 & 0.236803 \tabularnewline
198 & 0.744206 & 0.511588 & 0.255794 \tabularnewline
199 & 0.720509 & 0.558982 & 0.279491 \tabularnewline
200 & 0.715192 & 0.569617 & 0.284808 \tabularnewline
201 & 0.785669 & 0.428662 & 0.214331 \tabularnewline
202 & 0.757048 & 0.485903 & 0.242952 \tabularnewline
203 & 0.72711 & 0.545779 & 0.27289 \tabularnewline
204 & 0.700863 & 0.598275 & 0.299137 \tabularnewline
205 & 0.68203 & 0.63594 & 0.31797 \tabularnewline
206 & 0.647399 & 0.705202 & 0.352601 \tabularnewline
207 & 0.650969 & 0.698061 & 0.349031 \tabularnewline
208 & 0.625018 & 0.749964 & 0.374982 \tabularnewline
209 & 0.704798 & 0.590405 & 0.295202 \tabularnewline
210 & 0.68902 & 0.621959 & 0.31098 \tabularnewline
211 & 0.665626 & 0.668748 & 0.334374 \tabularnewline
212 & 0.636739 & 0.726521 & 0.363261 \tabularnewline
213 & 0.598776 & 0.802448 & 0.401224 \tabularnewline
214 & 0.558674 & 0.882652 & 0.441326 \tabularnewline
215 & 0.553139 & 0.893722 & 0.446861 \tabularnewline
216 & 0.512148 & 0.975704 & 0.487852 \tabularnewline
217 & 0.491672 & 0.983343 & 0.508328 \tabularnewline
218 & 0.514522 & 0.970955 & 0.485478 \tabularnewline
219 & 0.48084 & 0.961679 & 0.51916 \tabularnewline
220 & 0.45286 & 0.90572 & 0.54714 \tabularnewline
221 & 0.499132 & 0.998265 & 0.500868 \tabularnewline
222 & 0.657082 & 0.685836 & 0.342918 \tabularnewline
223 & 0.616042 & 0.767916 & 0.383958 \tabularnewline
224 & 0.582929 & 0.834142 & 0.417071 \tabularnewline
225 & 0.571781 & 0.856439 & 0.428219 \tabularnewline
226 & 0.539643 & 0.920714 & 0.460357 \tabularnewline
227 & 0.513485 & 0.97303 & 0.486515 \tabularnewline
228 & 0.471874 & 0.943748 & 0.528126 \tabularnewline
229 & 0.541552 & 0.916895 & 0.458448 \tabularnewline
230 & 0.596856 & 0.806289 & 0.403144 \tabularnewline
231 & 0.723832 & 0.552336 & 0.276168 \tabularnewline
232 & 0.79438 & 0.411239 & 0.20562 \tabularnewline
233 & 0.75841 & 0.483181 & 0.24159 \tabularnewline
234 & 0.721793 & 0.556413 & 0.278207 \tabularnewline
235 & 0.695697 & 0.608606 & 0.304303 \tabularnewline
236 & 0.935334 & 0.129332 & 0.0646662 \tabularnewline
237 & 0.919447 & 0.161107 & 0.0805533 \tabularnewline
238 & 0.898029 & 0.203941 & 0.101971 \tabularnewline
239 & 0.873084 & 0.253832 & 0.126916 \tabularnewline
240 & 0.842271 & 0.315458 & 0.157729 \tabularnewline
241 & 0.809074 & 0.381852 & 0.190926 \tabularnewline
242 & 0.772873 & 0.454254 & 0.227127 \tabularnewline
243 & 0.72926 & 0.541479 & 0.27074 \tabularnewline
244 & 0.845613 & 0.308773 & 0.154387 \tabularnewline
245 & 0.831297 & 0.337406 & 0.168703 \tabularnewline
246 & 0.795805 & 0.408391 & 0.204195 \tabularnewline
247 & 0.799498 & 0.401004 & 0.200502 \tabularnewline
248 & 0.762668 & 0.474663 & 0.237332 \tabularnewline
249 & 0.796338 & 0.407325 & 0.203662 \tabularnewline
250 & 0.751865 & 0.496271 & 0.248135 \tabularnewline
251 & 0.704281 & 0.591439 & 0.295719 \tabularnewline
252 & 0.672423 & 0.655153 & 0.327577 \tabularnewline
253 & 0.608659 & 0.782682 & 0.391341 \tabularnewline
254 & 0.577725 & 0.84455 & 0.422275 \tabularnewline
255 & 0.517394 & 0.965212 & 0.482606 \tabularnewline
256 & 0.463898 & 0.927797 & 0.536102 \tabularnewline
257 & 0.771722 & 0.456556 & 0.228278 \tabularnewline
258 & 0.78336 & 0.433279 & 0.21664 \tabularnewline
259 & 0.732466 & 0.535067 & 0.267534 \tabularnewline
260 & 0.882449 & 0.235102 & 0.117551 \tabularnewline
261 & 0.875632 & 0.248737 & 0.124368 \tabularnewline
262 & 0.918973 & 0.162053 & 0.0810267 \tabularnewline
263 & 0.874724 & 0.250552 & 0.125276 \tabularnewline
264 & 0.846413 & 0.307173 & 0.153587 \tabularnewline
265 & 0.79309 & 0.413819 & 0.20691 \tabularnewline
266 & 0.703963 & 0.592074 & 0.296037 \tabularnewline
267 & 0.591299 & 0.817401 & 0.408701 \tabularnewline
268 & 0.452088 & 0.904175 & 0.547912 \tabularnewline
269 & 0.975642 & 0.0487157 & 0.0243578 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262963&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]9[/C][C]0.261163[/C][C]0.522326[/C][C]0.738837[/C][/ROW]
[ROW][C]10[/C][C]0.321693[/C][C]0.643386[/C][C]0.678307[/C][/ROW]
[ROW][C]11[/C][C]0.196219[/C][C]0.392437[/C][C]0.803781[/C][/ROW]
[ROW][C]12[/C][C]0.417723[/C][C]0.835445[/C][C]0.582277[/C][/ROW]
[ROW][C]13[/C][C]0.305602[/C][C]0.611203[/C][C]0.694398[/C][/ROW]
[ROW][C]14[/C][C]0.211944[/C][C]0.423888[/C][C]0.788056[/C][/ROW]
[ROW][C]15[/C][C]0.255903[/C][C]0.511806[/C][C]0.744097[/C][/ROW]
[ROW][C]16[/C][C]0.183511[/C][C]0.367023[/C][C]0.816489[/C][/ROW]
[ROW][C]17[/C][C]0.127725[/C][C]0.25545[/C][C]0.872275[/C][/ROW]
[ROW][C]18[/C][C]0.0981792[/C][C]0.196358[/C][C]0.901821[/C][/ROW]
[ROW][C]19[/C][C]0.065943[/C][C]0.131886[/C][C]0.934057[/C][/ROW]
[ROW][C]20[/C][C]0.0430935[/C][C]0.086187[/C][C]0.956906[/C][/ROW]
[ROW][C]21[/C][C]0.0835453[/C][C]0.167091[/C][C]0.916455[/C][/ROW]
[ROW][C]22[/C][C]0.111575[/C][C]0.223151[/C][C]0.888425[/C][/ROW]
[ROW][C]23[/C][C]0.0875799[/C][C]0.17516[/C][C]0.91242[/C][/ROW]
[ROW][C]24[/C][C]0.0762538[/C][C]0.152508[/C][C]0.923746[/C][/ROW]
[ROW][C]25[/C][C]0.0538113[/C][C]0.107623[/C][C]0.946189[/C][/ROW]
[ROW][C]26[/C][C]0.0506365[/C][C]0.101273[/C][C]0.949363[/C][/ROW]
[ROW][C]27[/C][C]0.0930229[/C][C]0.186046[/C][C]0.906977[/C][/ROW]
[ROW][C]28[/C][C]0.0718517[/C][C]0.143703[/C][C]0.928148[/C][/ROW]
[ROW][C]29[/C][C]0.0772399[/C][C]0.15448[/C][C]0.92276[/C][/ROW]
[ROW][C]30[/C][C]0.0564875[/C][C]0.112975[/C][C]0.943513[/C][/ROW]
[ROW][C]31[/C][C]0.0441751[/C][C]0.0883502[/C][C]0.955825[/C][/ROW]
[ROW][C]32[/C][C]0.0328278[/C][C]0.0656555[/C][C]0.967172[/C][/ROW]
[ROW][C]33[/C][C]0.0342501[/C][C]0.0685002[/C][C]0.96575[/C][/ROW]
[ROW][C]34[/C][C]0.0299558[/C][C]0.0599116[/C][C]0.970044[/C][/ROW]
[ROW][C]35[/C][C]0.0217387[/C][C]0.0434774[/C][C]0.978261[/C][/ROW]
[ROW][C]36[/C][C]0.0180564[/C][C]0.0361128[/C][C]0.981944[/C][/ROW]
[ROW][C]37[/C][C]0.014607[/C][C]0.0292139[/C][C]0.985393[/C][/ROW]
[ROW][C]38[/C][C]0.0119684[/C][C]0.0239368[/C][C]0.988032[/C][/ROW]
[ROW][C]39[/C][C]0.0106894[/C][C]0.0213788[/C][C]0.989311[/C][/ROW]
[ROW][C]40[/C][C]0.00736647[/C][C]0.0147329[/C][C]0.992634[/C][/ROW]
[ROW][C]41[/C][C]0.0184137[/C][C]0.0368273[/C][C]0.981586[/C][/ROW]
[ROW][C]42[/C][C]0.0132757[/C][C]0.0265513[/C][C]0.986724[/C][/ROW]
[ROW][C]43[/C][C]0.0107472[/C][C]0.0214945[/C][C]0.989253[/C][/ROW]
[ROW][C]44[/C][C]0.00802651[/C][C]0.016053[/C][C]0.991973[/C][/ROW]
[ROW][C]45[/C][C]0.00652847[/C][C]0.0130569[/C][C]0.993472[/C][/ROW]
[ROW][C]46[/C][C]0.00458272[/C][C]0.00916544[/C][C]0.995417[/C][/ROW]
[ROW][C]47[/C][C]0.00326189[/C][C]0.00652378[/C][C]0.996738[/C][/ROW]
[ROW][C]48[/C][C]0.00394935[/C][C]0.00789871[/C][C]0.996051[/C][/ROW]
[ROW][C]49[/C][C]0.00343486[/C][C]0.00686972[/C][C]0.996565[/C][/ROW]
[ROW][C]50[/C][C]0.00258339[/C][C]0.00516679[/C][C]0.997417[/C][/ROW]
[ROW][C]51[/C][C]0.00178934[/C][C]0.00357867[/C][C]0.998211[/C][/ROW]
[ROW][C]52[/C][C]0.00250453[/C][C]0.00500907[/C][C]0.997495[/C][/ROW]
[ROW][C]53[/C][C]0.00178845[/C][C]0.0035769[/C][C]0.998212[/C][/ROW]
[ROW][C]54[/C][C]0.00130925[/C][C]0.0026185[/C][C]0.998691[/C][/ROW]
[ROW][C]55[/C][C]0.00128385[/C][C]0.00256769[/C][C]0.998716[/C][/ROW]
[ROW][C]56[/C][C]0.00105104[/C][C]0.00210207[/C][C]0.998949[/C][/ROW]
[ROW][C]57[/C][C]0.00298467[/C][C]0.00596933[/C][C]0.997015[/C][/ROW]
[ROW][C]58[/C][C]0.00405136[/C][C]0.00810272[/C][C]0.995949[/C][/ROW]
[ROW][C]59[/C][C]0.00341467[/C][C]0.00682933[/C][C]0.996585[/C][/ROW]
[ROW][C]60[/C][C]0.00269739[/C][C]0.00539478[/C][C]0.997303[/C][/ROW]
[ROW][C]61[/C][C]0.00259556[/C][C]0.00519112[/C][C]0.997404[/C][/ROW]
[ROW][C]62[/C][C]0.00197914[/C][C]0.00395828[/C][C]0.998021[/C][/ROW]
[ROW][C]63[/C][C]0.00225654[/C][C]0.00451309[/C][C]0.997743[/C][/ROW]
[ROW][C]64[/C][C]0.00378923[/C][C]0.00757847[/C][C]0.996211[/C][/ROW]
[ROW][C]65[/C][C]0.0033533[/C][C]0.0067066[/C][C]0.996647[/C][/ROW]
[ROW][C]66[/C][C]0.00322927[/C][C]0.00645854[/C][C]0.996771[/C][/ROW]
[ROW][C]67[/C][C]0.00252582[/C][C]0.00505165[/C][C]0.997474[/C][/ROW]
[ROW][C]68[/C][C]0.00204271[/C][C]0.00408542[/C][C]0.997957[/C][/ROW]
[ROW][C]69[/C][C]0.00333884[/C][C]0.00667768[/C][C]0.996661[/C][/ROW]
[ROW][C]70[/C][C]0.0027259[/C][C]0.00545179[/C][C]0.997274[/C][/ROW]
[ROW][C]71[/C][C]0.00202727[/C][C]0.00405455[/C][C]0.997973[/C][/ROW]
[ROW][C]72[/C][C]0.00150916[/C][C]0.00301832[/C][C]0.998491[/C][/ROW]
[ROW][C]73[/C][C]0.0014803[/C][C]0.0029606[/C][C]0.99852[/C][/ROW]
[ROW][C]74[/C][C]0.00163558[/C][C]0.00327115[/C][C]0.998364[/C][/ROW]
[ROW][C]75[/C][C]0.00131453[/C][C]0.00262905[/C][C]0.998685[/C][/ROW]
[ROW][C]76[/C][C]0.000983142[/C][C]0.00196628[/C][C]0.999017[/C][/ROW]
[ROW][C]77[/C][C]0.000726087[/C][C]0.00145217[/C][C]0.999274[/C][/ROW]
[ROW][C]78[/C][C]0.000600906[/C][C]0.00120181[/C][C]0.999399[/C][/ROW]
[ROW][C]79[/C][C]0.000443878[/C][C]0.000887756[/C][C]0.999556[/C][/ROW]
[ROW][C]80[/C][C]0.00052468[/C][C]0.00104936[/C][C]0.999475[/C][/ROW]
[ROW][C]81[/C][C]0.000391122[/C][C]0.000782245[/C][C]0.999609[/C][/ROW]
[ROW][C]82[/C][C]0.000367026[/C][C]0.000734051[/C][C]0.999633[/C][/ROW]
[ROW][C]83[/C][C]0.0002753[/C][C]0.0005506[/C][C]0.999725[/C][/ROW]
[ROW][C]84[/C][C]0.0016537[/C][C]0.00330739[/C][C]0.998346[/C][/ROW]
[ROW][C]85[/C][C]0.00133425[/C][C]0.0026685[/C][C]0.998666[/C][/ROW]
[ROW][C]86[/C][C]0.000994731[/C][C]0.00198946[/C][C]0.999005[/C][/ROW]
[ROW][C]87[/C][C]0.000754633[/C][C]0.00150927[/C][C]0.999245[/C][/ROW]
[ROW][C]88[/C][C]0.000596869[/C][C]0.00119374[/C][C]0.999403[/C][/ROW]
[ROW][C]89[/C][C]0.000671117[/C][C]0.00134223[/C][C]0.999329[/C][/ROW]
[ROW][C]90[/C][C]0.000667893[/C][C]0.00133579[/C][C]0.999332[/C][/ROW]
[ROW][C]91[/C][C]0.000568694[/C][C]0.00113739[/C][C]0.999431[/C][/ROW]
[ROW][C]92[/C][C]0.00147545[/C][C]0.00295089[/C][C]0.998525[/C][/ROW]
[ROW][C]93[/C][C]0.00117848[/C][C]0.00235696[/C][C]0.998822[/C][/ROW]
[ROW][C]94[/C][C]0.00117249[/C][C]0.00234497[/C][C]0.998828[/C][/ROW]
[ROW][C]95[/C][C]0.00144718[/C][C]0.00289436[/C][C]0.998553[/C][/ROW]
[ROW][C]96[/C][C]0.0013864[/C][C]0.00277281[/C][C]0.998614[/C][/ROW]
[ROW][C]97[/C][C]0.00230077[/C][C]0.00460154[/C][C]0.997699[/C][/ROW]
[ROW][C]98[/C][C]0.00188039[/C][C]0.00376078[/C][C]0.99812[/C][/ROW]
[ROW][C]99[/C][C]0.00170373[/C][C]0.00340746[/C][C]0.998296[/C][/ROW]
[ROW][C]100[/C][C]0.00237706[/C][C]0.00475413[/C][C]0.997623[/C][/ROW]
[ROW][C]101[/C][C]0.0020818[/C][C]0.00416359[/C][C]0.997918[/C][/ROW]
[ROW][C]102[/C][C]0.0019694[/C][C]0.0039388[/C][C]0.998031[/C][/ROW]
[ROW][C]103[/C][C]0.00217473[/C][C]0.00434946[/C][C]0.997825[/C][/ROW]
[ROW][C]104[/C][C]0.0019056[/C][C]0.00381119[/C][C]0.998094[/C][/ROW]
[ROW][C]105[/C][C]0.00202848[/C][C]0.00405695[/C][C]0.997972[/C][/ROW]
[ROW][C]106[/C][C]0.00210504[/C][C]0.00421008[/C][C]0.997895[/C][/ROW]
[ROW][C]107[/C][C]0.00253917[/C][C]0.00507835[/C][C]0.997461[/C][/ROW]
[ROW][C]108[/C][C]0.0094927[/C][C]0.0189854[/C][C]0.990507[/C][/ROW]
[ROW][C]109[/C][C]0.0223484[/C][C]0.0446968[/C][C]0.977652[/C][/ROW]
[ROW][C]110[/C][C]0.0203887[/C][C]0.0407774[/C][C]0.979611[/C][/ROW]
[ROW][C]111[/C][C]0.0182447[/C][C]0.0364894[/C][C]0.981755[/C][/ROW]
[ROW][C]112[/C][C]0.0170283[/C][C]0.0340565[/C][C]0.982972[/C][/ROW]
[ROW][C]113[/C][C]0.056127[/C][C]0.112254[/C][C]0.943873[/C][/ROW]
[ROW][C]114[/C][C]0.0543573[/C][C]0.108715[/C][C]0.945643[/C][/ROW]
[ROW][C]115[/C][C]0.112242[/C][C]0.224483[/C][C]0.887758[/C][/ROW]
[ROW][C]116[/C][C]0.152462[/C][C]0.304924[/C][C]0.847538[/C][/ROW]
[ROW][C]117[/C][C]0.188026[/C][C]0.376053[/C][C]0.811974[/C][/ROW]
[ROW][C]118[/C][C]0.177935[/C][C]0.35587[/C][C]0.822065[/C][/ROW]
[ROW][C]119[/C][C]0.21832[/C][C]0.436641[/C][C]0.78168[/C][/ROW]
[ROW][C]120[/C][C]0.317884[/C][C]0.635768[/C][C]0.682116[/C][/ROW]
[ROW][C]121[/C][C]0.341483[/C][C]0.682966[/C][C]0.658517[/C][/ROW]
[ROW][C]122[/C][C]0.329274[/C][C]0.658548[/C][C]0.670726[/C][/ROW]
[ROW][C]123[/C][C]0.449489[/C][C]0.898977[/C][C]0.550511[/C][/ROW]
[ROW][C]124[/C][C]0.438487[/C][C]0.876974[/C][C]0.561513[/C][/ROW]
[ROW][C]125[/C][C]0.438432[/C][C]0.876864[/C][C]0.561568[/C][/ROW]
[ROW][C]126[/C][C]0.419444[/C][C]0.838889[/C][C]0.580556[/C][/ROW]
[ROW][C]127[/C][C]0.451553[/C][C]0.903106[/C][C]0.548447[/C][/ROW]
[ROW][C]128[/C][C]0.436573[/C][C]0.873146[/C][C]0.563427[/C][/ROW]
[ROW][C]129[/C][C]0.549695[/C][C]0.900611[/C][C]0.450305[/C][/ROW]
[ROW][C]130[/C][C]0.524955[/C][C]0.95009[/C][C]0.475045[/C][/ROW]
[ROW][C]131[/C][C]0.500433[/C][C]0.999134[/C][C]0.499567[/C][/ROW]
[ROW][C]132[/C][C]0.518325[/C][C]0.96335[/C][C]0.481675[/C][/ROW]
[ROW][C]133[/C][C]0.51095[/C][C]0.9781[/C][C]0.48905[/C][/ROW]
[ROW][C]134[/C][C]0.513041[/C][C]0.973918[/C][C]0.486959[/C][/ROW]
[ROW][C]135[/C][C]0.486662[/C][C]0.973324[/C][C]0.513338[/C][/ROW]
[ROW][C]136[/C][C]0.469677[/C][C]0.939353[/C][C]0.530323[/C][/ROW]
[ROW][C]137[/C][C]0.493441[/C][C]0.986881[/C][C]0.506559[/C][/ROW]
[ROW][C]138[/C][C]0.558463[/C][C]0.883074[/C][C]0.441537[/C][/ROW]
[ROW][C]139[/C][C]0.626074[/C][C]0.747853[/C][C]0.373926[/C][/ROW]
[ROW][C]140[/C][C]0.624919[/C][C]0.750162[/C][C]0.375081[/C][/ROW]
[ROW][C]141[/C][C]0.61471[/C][C]0.770579[/C][C]0.38529[/C][/ROW]
[ROW][C]142[/C][C]0.647808[/C][C]0.704384[/C][C]0.352192[/C][/ROW]
[ROW][C]143[/C][C]0.670371[/C][C]0.659258[/C][C]0.329629[/C][/ROW]
[ROW][C]144[/C][C]0.694084[/C][C]0.611833[/C][C]0.305916[/C][/ROW]
[ROW][C]145[/C][C]0.709042[/C][C]0.581916[/C][C]0.290958[/C][/ROW]
[ROW][C]146[/C][C]0.742628[/C][C]0.514745[/C][C]0.257372[/C][/ROW]
[ROW][C]147[/C][C]0.726377[/C][C]0.547246[/C][C]0.273623[/C][/ROW]
[ROW][C]148[/C][C]0.709026[/C][C]0.581949[/C][C]0.290974[/C][/ROW]
[ROW][C]149[/C][C]0.705703[/C][C]0.588594[/C][C]0.294297[/C][/ROW]
[ROW][C]150[/C][C]0.724985[/C][C]0.55003[/C][C]0.275015[/C][/ROW]
[ROW][C]151[/C][C]0.722112[/C][C]0.555775[/C][C]0.277888[/C][/ROW]
[ROW][C]152[/C][C]0.71145[/C][C]0.5771[/C][C]0.28855[/C][/ROW]
[ROW][C]153[/C][C]0.753382[/C][C]0.493235[/C][C]0.246618[/C][/ROW]
[ROW][C]154[/C][C]0.778896[/C][C]0.442207[/C][C]0.221104[/C][/ROW]
[ROW][C]155[/C][C]0.753839[/C][C]0.492323[/C][C]0.246161[/C][/ROW]
[ROW][C]156[/C][C]0.729694[/C][C]0.540611[/C][C]0.270306[/C][/ROW]
[ROW][C]157[/C][C]0.763695[/C][C]0.47261[/C][C]0.236305[/C][/ROW]
[ROW][C]158[/C][C]0.7528[/C][C]0.494401[/C][C]0.2472[/C][/ROW]
[ROW][C]159[/C][C]0.736422[/C][C]0.527157[/C][C]0.263578[/C][/ROW]
[ROW][C]160[/C][C]0.725108[/C][C]0.549785[/C][C]0.274892[/C][/ROW]
[ROW][C]161[/C][C]0.757468[/C][C]0.485064[/C][C]0.242532[/C][/ROW]
[ROW][C]162[/C][C]0.747091[/C][C]0.505818[/C][C]0.252909[/C][/ROW]
[ROW][C]163[/C][C]0.747263[/C][C]0.505475[/C][C]0.252737[/C][/ROW]
[ROW][C]164[/C][C]0.72961[/C][C]0.540779[/C][C]0.27039[/C][/ROW]
[ROW][C]165[/C][C]0.788842[/C][C]0.422316[/C][C]0.211158[/C][/ROW]
[ROW][C]166[/C][C]0.781251[/C][C]0.437499[/C][C]0.218749[/C][/ROW]
[ROW][C]167[/C][C]0.817372[/C][C]0.365256[/C][C]0.182628[/C][/ROW]
[ROW][C]168[/C][C]0.793252[/C][C]0.413495[/C][C]0.206748[/C][/ROW]
[ROW][C]169[/C][C]0.771352[/C][C]0.457296[/C][C]0.228648[/C][/ROW]
[ROW][C]170[/C][C]0.766053[/C][C]0.467894[/C][C]0.233947[/C][/ROW]
[ROW][C]171[/C][C]0.753752[/C][C]0.492496[/C][C]0.246248[/C][/ROW]
[ROW][C]172[/C][C]0.79152[/C][C]0.41696[/C][C]0.20848[/C][/ROW]
[ROW][C]173[/C][C]0.766731[/C][C]0.466537[/C][C]0.233269[/C][/ROW]
[ROW][C]174[/C][C]0.743746[/C][C]0.512509[/C][C]0.256254[/C][/ROW]
[ROW][C]175[/C][C]0.719755[/C][C]0.560489[/C][C]0.280245[/C][/ROW]
[ROW][C]176[/C][C]0.738788[/C][C]0.522424[/C][C]0.261212[/C][/ROW]
[ROW][C]177[/C][C]0.709206[/C][C]0.581588[/C][C]0.290794[/C][/ROW]
[ROW][C]178[/C][C]0.808366[/C][C]0.383268[/C][C]0.191634[/C][/ROW]
[ROW][C]179[/C][C]0.798144[/C][C]0.403712[/C][C]0.201856[/C][/ROW]
[ROW][C]180[/C][C]0.862211[/C][C]0.275578[/C][C]0.137789[/C][/ROW]
[ROW][C]181[/C][C]0.84083[/C][C]0.31834[/C][C]0.15917[/C][/ROW]
[ROW][C]182[/C][C]0.820809[/C][C]0.358381[/C][C]0.179191[/C][/ROW]
[ROW][C]183[/C][C]0.84895[/C][C]0.302101[/C][C]0.15105[/C][/ROW]
[ROW][C]184[/C][C]0.843223[/C][C]0.313554[/C][C]0.156777[/C][/ROW]
[ROW][C]185[/C][C]0.819746[/C][C]0.360509[/C][C]0.180254[/C][/ROW]
[ROW][C]186[/C][C]0.809566[/C][C]0.380868[/C][C]0.190434[/C][/ROW]
[ROW][C]187[/C][C]0.819614[/C][C]0.360772[/C][C]0.180386[/C][/ROW]
[ROW][C]188[/C][C]0.794122[/C][C]0.411756[/C][C]0.205878[/C][/ROW]
[ROW][C]189[/C][C]0.774386[/C][C]0.451228[/C][C]0.225614[/C][/ROW]
[ROW][C]190[/C][C]0.746647[/C][C]0.506706[/C][C]0.253353[/C][/ROW]
[ROW][C]191[/C][C]0.751304[/C][C]0.497393[/C][C]0.248696[/C][/ROW]
[ROW][C]192[/C][C]0.737576[/C][C]0.524849[/C][C]0.262424[/C][/ROW]
[ROW][C]193[/C][C]0.780249[/C][C]0.439503[/C][C]0.219751[/C][/ROW]
[ROW][C]194[/C][C]0.824965[/C][C]0.350069[/C][C]0.175035[/C][/ROW]
[ROW][C]195[/C][C]0.808063[/C][C]0.383873[/C][C]0.191937[/C][/ROW]
[ROW][C]196[/C][C]0.782006[/C][C]0.435988[/C][C]0.217994[/C][/ROW]
[ROW][C]197[/C][C]0.763197[/C][C]0.473606[/C][C]0.236803[/C][/ROW]
[ROW][C]198[/C][C]0.744206[/C][C]0.511588[/C][C]0.255794[/C][/ROW]
[ROW][C]199[/C][C]0.720509[/C][C]0.558982[/C][C]0.279491[/C][/ROW]
[ROW][C]200[/C][C]0.715192[/C][C]0.569617[/C][C]0.284808[/C][/ROW]
[ROW][C]201[/C][C]0.785669[/C][C]0.428662[/C][C]0.214331[/C][/ROW]
[ROW][C]202[/C][C]0.757048[/C][C]0.485903[/C][C]0.242952[/C][/ROW]
[ROW][C]203[/C][C]0.72711[/C][C]0.545779[/C][C]0.27289[/C][/ROW]
[ROW][C]204[/C][C]0.700863[/C][C]0.598275[/C][C]0.299137[/C][/ROW]
[ROW][C]205[/C][C]0.68203[/C][C]0.63594[/C][C]0.31797[/C][/ROW]
[ROW][C]206[/C][C]0.647399[/C][C]0.705202[/C][C]0.352601[/C][/ROW]
[ROW][C]207[/C][C]0.650969[/C][C]0.698061[/C][C]0.349031[/C][/ROW]
[ROW][C]208[/C][C]0.625018[/C][C]0.749964[/C][C]0.374982[/C][/ROW]
[ROW][C]209[/C][C]0.704798[/C][C]0.590405[/C][C]0.295202[/C][/ROW]
[ROW][C]210[/C][C]0.68902[/C][C]0.621959[/C][C]0.31098[/C][/ROW]
[ROW][C]211[/C][C]0.665626[/C][C]0.668748[/C][C]0.334374[/C][/ROW]
[ROW][C]212[/C][C]0.636739[/C][C]0.726521[/C][C]0.363261[/C][/ROW]
[ROW][C]213[/C][C]0.598776[/C][C]0.802448[/C][C]0.401224[/C][/ROW]
[ROW][C]214[/C][C]0.558674[/C][C]0.882652[/C][C]0.441326[/C][/ROW]
[ROW][C]215[/C][C]0.553139[/C][C]0.893722[/C][C]0.446861[/C][/ROW]
[ROW][C]216[/C][C]0.512148[/C][C]0.975704[/C][C]0.487852[/C][/ROW]
[ROW][C]217[/C][C]0.491672[/C][C]0.983343[/C][C]0.508328[/C][/ROW]
[ROW][C]218[/C][C]0.514522[/C][C]0.970955[/C][C]0.485478[/C][/ROW]
[ROW][C]219[/C][C]0.48084[/C][C]0.961679[/C][C]0.51916[/C][/ROW]
[ROW][C]220[/C][C]0.45286[/C][C]0.90572[/C][C]0.54714[/C][/ROW]
[ROW][C]221[/C][C]0.499132[/C][C]0.998265[/C][C]0.500868[/C][/ROW]
[ROW][C]222[/C][C]0.657082[/C][C]0.685836[/C][C]0.342918[/C][/ROW]
[ROW][C]223[/C][C]0.616042[/C][C]0.767916[/C][C]0.383958[/C][/ROW]
[ROW][C]224[/C][C]0.582929[/C][C]0.834142[/C][C]0.417071[/C][/ROW]
[ROW][C]225[/C][C]0.571781[/C][C]0.856439[/C][C]0.428219[/C][/ROW]
[ROW][C]226[/C][C]0.539643[/C][C]0.920714[/C][C]0.460357[/C][/ROW]
[ROW][C]227[/C][C]0.513485[/C][C]0.97303[/C][C]0.486515[/C][/ROW]
[ROW][C]228[/C][C]0.471874[/C][C]0.943748[/C][C]0.528126[/C][/ROW]
[ROW][C]229[/C][C]0.541552[/C][C]0.916895[/C][C]0.458448[/C][/ROW]
[ROW][C]230[/C][C]0.596856[/C][C]0.806289[/C][C]0.403144[/C][/ROW]
[ROW][C]231[/C][C]0.723832[/C][C]0.552336[/C][C]0.276168[/C][/ROW]
[ROW][C]232[/C][C]0.79438[/C][C]0.411239[/C][C]0.20562[/C][/ROW]
[ROW][C]233[/C][C]0.75841[/C][C]0.483181[/C][C]0.24159[/C][/ROW]
[ROW][C]234[/C][C]0.721793[/C][C]0.556413[/C][C]0.278207[/C][/ROW]
[ROW][C]235[/C][C]0.695697[/C][C]0.608606[/C][C]0.304303[/C][/ROW]
[ROW][C]236[/C][C]0.935334[/C][C]0.129332[/C][C]0.0646662[/C][/ROW]
[ROW][C]237[/C][C]0.919447[/C][C]0.161107[/C][C]0.0805533[/C][/ROW]
[ROW][C]238[/C][C]0.898029[/C][C]0.203941[/C][C]0.101971[/C][/ROW]
[ROW][C]239[/C][C]0.873084[/C][C]0.253832[/C][C]0.126916[/C][/ROW]
[ROW][C]240[/C][C]0.842271[/C][C]0.315458[/C][C]0.157729[/C][/ROW]
[ROW][C]241[/C][C]0.809074[/C][C]0.381852[/C][C]0.190926[/C][/ROW]
[ROW][C]242[/C][C]0.772873[/C][C]0.454254[/C][C]0.227127[/C][/ROW]
[ROW][C]243[/C][C]0.72926[/C][C]0.541479[/C][C]0.27074[/C][/ROW]
[ROW][C]244[/C][C]0.845613[/C][C]0.308773[/C][C]0.154387[/C][/ROW]
[ROW][C]245[/C][C]0.831297[/C][C]0.337406[/C][C]0.168703[/C][/ROW]
[ROW][C]246[/C][C]0.795805[/C][C]0.408391[/C][C]0.204195[/C][/ROW]
[ROW][C]247[/C][C]0.799498[/C][C]0.401004[/C][C]0.200502[/C][/ROW]
[ROW][C]248[/C][C]0.762668[/C][C]0.474663[/C][C]0.237332[/C][/ROW]
[ROW][C]249[/C][C]0.796338[/C][C]0.407325[/C][C]0.203662[/C][/ROW]
[ROW][C]250[/C][C]0.751865[/C][C]0.496271[/C][C]0.248135[/C][/ROW]
[ROW][C]251[/C][C]0.704281[/C][C]0.591439[/C][C]0.295719[/C][/ROW]
[ROW][C]252[/C][C]0.672423[/C][C]0.655153[/C][C]0.327577[/C][/ROW]
[ROW][C]253[/C][C]0.608659[/C][C]0.782682[/C][C]0.391341[/C][/ROW]
[ROW][C]254[/C][C]0.577725[/C][C]0.84455[/C][C]0.422275[/C][/ROW]
[ROW][C]255[/C][C]0.517394[/C][C]0.965212[/C][C]0.482606[/C][/ROW]
[ROW][C]256[/C][C]0.463898[/C][C]0.927797[/C][C]0.536102[/C][/ROW]
[ROW][C]257[/C][C]0.771722[/C][C]0.456556[/C][C]0.228278[/C][/ROW]
[ROW][C]258[/C][C]0.78336[/C][C]0.433279[/C][C]0.21664[/C][/ROW]
[ROW][C]259[/C][C]0.732466[/C][C]0.535067[/C][C]0.267534[/C][/ROW]
[ROW][C]260[/C][C]0.882449[/C][C]0.235102[/C][C]0.117551[/C][/ROW]
[ROW][C]261[/C][C]0.875632[/C][C]0.248737[/C][C]0.124368[/C][/ROW]
[ROW][C]262[/C][C]0.918973[/C][C]0.162053[/C][C]0.0810267[/C][/ROW]
[ROW][C]263[/C][C]0.874724[/C][C]0.250552[/C][C]0.125276[/C][/ROW]
[ROW][C]264[/C][C]0.846413[/C][C]0.307173[/C][C]0.153587[/C][/ROW]
[ROW][C]265[/C][C]0.79309[/C][C]0.413819[/C][C]0.20691[/C][/ROW]
[ROW][C]266[/C][C]0.703963[/C][C]0.592074[/C][C]0.296037[/C][/ROW]
[ROW][C]267[/C][C]0.591299[/C][C]0.817401[/C][C]0.408701[/C][/ROW]
[ROW][C]268[/C][C]0.452088[/C][C]0.904175[/C][C]0.547912[/C][/ROW]
[ROW][C]269[/C][C]0.975642[/C][C]0.0487157[/C][C]0.0243578[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262963&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262963&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-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
9	0.261163	0.522326	0.738837
10	0.321693	0.643386	0.678307
11	0.196219	0.392437	0.803781
12	0.417723	0.835445	0.582277
13	0.305602	0.611203	0.694398
14	0.211944	0.423888	0.788056
15	0.255903	0.511806	0.744097
16	0.183511	0.367023	0.816489
17	0.127725	0.25545	0.872275
18	0.0981792	0.196358	0.901821
19	0.065943	0.131886	0.934057
20	0.0430935	0.086187	0.956906
21	0.0835453	0.167091	0.916455
22	0.111575	0.223151	0.888425
23	0.0875799	0.17516	0.91242
24	0.0762538	0.152508	0.923746
25	0.0538113	0.107623	0.946189
26	0.0506365	0.101273	0.949363
27	0.0930229	0.186046	0.906977
28	0.0718517	0.143703	0.928148
29	0.0772399	0.15448	0.92276
30	0.0564875	0.112975	0.943513
31	0.0441751	0.0883502	0.955825
32	0.0328278	0.0656555	0.967172
33	0.0342501	0.0685002	0.96575
34	0.0299558	0.0599116	0.970044
35	0.0217387	0.0434774	0.978261
36	0.0180564	0.0361128	0.981944
37	0.014607	0.0292139	0.985393
38	0.0119684	0.0239368	0.988032
39	0.0106894	0.0213788	0.989311
40	0.00736647	0.0147329	0.992634
41	0.0184137	0.0368273	0.981586
42	0.0132757	0.0265513	0.986724
43	0.0107472	0.0214945	0.989253
44	0.00802651	0.016053	0.991973
45	0.00652847	0.0130569	0.993472
46	0.00458272	0.00916544	0.995417
47	0.00326189	0.00652378	0.996738
48	0.00394935	0.00789871	0.996051
49	0.00343486	0.00686972	0.996565
50	0.00258339	0.00516679	0.997417
51	0.00178934	0.00357867	0.998211
52	0.00250453	0.00500907	0.997495
53	0.00178845	0.0035769	0.998212
54	0.00130925	0.0026185	0.998691
55	0.00128385	0.00256769	0.998716
56	0.00105104	0.00210207	0.998949
57	0.00298467	0.00596933	0.997015
58	0.00405136	0.00810272	0.995949
59	0.00341467	0.00682933	0.996585
60	0.00269739	0.00539478	0.997303
61	0.00259556	0.00519112	0.997404
62	0.00197914	0.00395828	0.998021
63	0.00225654	0.00451309	0.997743
64	0.00378923	0.00757847	0.996211
65	0.0033533	0.0067066	0.996647
66	0.00322927	0.00645854	0.996771
67	0.00252582	0.00505165	0.997474
68	0.00204271	0.00408542	0.997957
69	0.00333884	0.00667768	0.996661
70	0.0027259	0.00545179	0.997274
71	0.00202727	0.00405455	0.997973
72	0.00150916	0.00301832	0.998491
73	0.0014803	0.0029606	0.99852
74	0.00163558	0.00327115	0.998364
75	0.00131453	0.00262905	0.998685
76	0.000983142	0.00196628	0.999017
77	0.000726087	0.00145217	0.999274
78	0.000600906	0.00120181	0.999399
79	0.000443878	0.000887756	0.999556
80	0.00052468	0.00104936	0.999475
81	0.000391122	0.000782245	0.999609
82	0.000367026	0.000734051	0.999633
83	0.0002753	0.0005506	0.999725
84	0.0016537	0.00330739	0.998346
85	0.00133425	0.0026685	0.998666
86	0.000994731	0.00198946	0.999005
87	0.000754633	0.00150927	0.999245
88	0.000596869	0.00119374	0.999403
89	0.000671117	0.00134223	0.999329
90	0.000667893	0.00133579	0.999332
91	0.000568694	0.00113739	0.999431
92	0.00147545	0.00295089	0.998525
93	0.00117848	0.00235696	0.998822
94	0.00117249	0.00234497	0.998828
95	0.00144718	0.00289436	0.998553
96	0.0013864	0.00277281	0.998614
97	0.00230077	0.00460154	0.997699
98	0.00188039	0.00376078	0.99812
99	0.00170373	0.00340746	0.998296
100	0.00237706	0.00475413	0.997623
101	0.0020818	0.00416359	0.997918
102	0.0019694	0.0039388	0.998031
103	0.00217473	0.00434946	0.997825
104	0.0019056	0.00381119	0.998094
105	0.00202848	0.00405695	0.997972
106	0.00210504	0.00421008	0.997895
107	0.00253917	0.00507835	0.997461
108	0.0094927	0.0189854	0.990507
109	0.0223484	0.0446968	0.977652
110	0.0203887	0.0407774	0.979611
111	0.0182447	0.0364894	0.981755
112	0.0170283	0.0340565	0.982972
113	0.056127	0.112254	0.943873
114	0.0543573	0.108715	0.945643
115	0.112242	0.224483	0.887758
116	0.152462	0.304924	0.847538
117	0.188026	0.376053	0.811974
118	0.177935	0.35587	0.822065
119	0.21832	0.436641	0.78168
120	0.317884	0.635768	0.682116
121	0.341483	0.682966	0.658517
122	0.329274	0.658548	0.670726
123	0.449489	0.898977	0.550511
124	0.438487	0.876974	0.561513
125	0.438432	0.876864	0.561568
126	0.419444	0.838889	0.580556
127	0.451553	0.903106	0.548447
128	0.436573	0.873146	0.563427
129	0.549695	0.900611	0.450305
130	0.524955	0.95009	0.475045
131	0.500433	0.999134	0.499567
132	0.518325	0.96335	0.481675
133	0.51095	0.9781	0.48905
134	0.513041	0.973918	0.486959
135	0.486662	0.973324	0.513338
136	0.469677	0.939353	0.530323
137	0.493441	0.986881	0.506559
138	0.558463	0.883074	0.441537
139	0.626074	0.747853	0.373926
140	0.624919	0.750162	0.375081
141	0.61471	0.770579	0.38529
142	0.647808	0.704384	0.352192
143	0.670371	0.659258	0.329629
144	0.694084	0.611833	0.305916
145	0.709042	0.581916	0.290958
146	0.742628	0.514745	0.257372
147	0.726377	0.547246	0.273623
148	0.709026	0.581949	0.290974
149	0.705703	0.588594	0.294297
150	0.724985	0.55003	0.275015
151	0.722112	0.555775	0.277888
152	0.71145	0.5771	0.28855
153	0.753382	0.493235	0.246618
154	0.778896	0.442207	0.221104
155	0.753839	0.492323	0.246161
156	0.729694	0.540611	0.270306
157	0.763695	0.47261	0.236305
158	0.7528	0.494401	0.2472
159	0.736422	0.527157	0.263578
160	0.725108	0.549785	0.274892
161	0.757468	0.485064	0.242532
162	0.747091	0.505818	0.252909
163	0.747263	0.505475	0.252737
164	0.72961	0.540779	0.27039
165	0.788842	0.422316	0.211158
166	0.781251	0.437499	0.218749
167	0.817372	0.365256	0.182628
168	0.793252	0.413495	0.206748
169	0.771352	0.457296	0.228648
170	0.766053	0.467894	0.233947
171	0.753752	0.492496	0.246248
172	0.79152	0.41696	0.20848
173	0.766731	0.466537	0.233269
174	0.743746	0.512509	0.256254
175	0.719755	0.560489	0.280245
176	0.738788	0.522424	0.261212
177	0.709206	0.581588	0.290794
178	0.808366	0.383268	0.191634
179	0.798144	0.403712	0.201856
180	0.862211	0.275578	0.137789
181	0.84083	0.31834	0.15917
182	0.820809	0.358381	0.179191
183	0.84895	0.302101	0.15105
184	0.843223	0.313554	0.156777
185	0.819746	0.360509	0.180254
186	0.809566	0.380868	0.190434
187	0.819614	0.360772	0.180386
188	0.794122	0.411756	0.205878
189	0.774386	0.451228	0.225614
190	0.746647	0.506706	0.253353
191	0.751304	0.497393	0.248696
192	0.737576	0.524849	0.262424
193	0.780249	0.439503	0.219751
194	0.824965	0.350069	0.175035
195	0.808063	0.383873	0.191937
196	0.782006	0.435988	0.217994
197	0.763197	0.473606	0.236803
198	0.744206	0.511588	0.255794
199	0.720509	0.558982	0.279491
200	0.715192	0.569617	0.284808
201	0.785669	0.428662	0.214331
202	0.757048	0.485903	0.242952
203	0.72711	0.545779	0.27289
204	0.700863	0.598275	0.299137
205	0.68203	0.63594	0.31797
206	0.647399	0.705202	0.352601
207	0.650969	0.698061	0.349031
208	0.625018	0.749964	0.374982
209	0.704798	0.590405	0.295202
210	0.68902	0.621959	0.31098
211	0.665626	0.668748	0.334374
212	0.636739	0.726521	0.363261
213	0.598776	0.802448	0.401224
214	0.558674	0.882652	0.441326
215	0.553139	0.893722	0.446861
216	0.512148	0.975704	0.487852
217	0.491672	0.983343	0.508328
218	0.514522	0.970955	0.485478
219	0.48084	0.961679	0.51916
220	0.45286	0.90572	0.54714
221	0.499132	0.998265	0.500868
222	0.657082	0.685836	0.342918
223	0.616042	0.767916	0.383958
224	0.582929	0.834142	0.417071
225	0.571781	0.856439	0.428219
226	0.539643	0.920714	0.460357
227	0.513485	0.97303	0.486515
228	0.471874	0.943748	0.528126
229	0.541552	0.916895	0.458448
230	0.596856	0.806289	0.403144
231	0.723832	0.552336	0.276168
232	0.79438	0.411239	0.20562
233	0.75841	0.483181	0.24159
234	0.721793	0.556413	0.278207
235	0.695697	0.608606	0.304303
236	0.935334	0.129332	0.0646662
237	0.919447	0.161107	0.0805533
238	0.898029	0.203941	0.101971
239	0.873084	0.253832	0.126916
240	0.842271	0.315458	0.157729
241	0.809074	0.381852	0.190926
242	0.772873	0.454254	0.227127
243	0.72926	0.541479	0.27074
244	0.845613	0.308773	0.154387
245	0.831297	0.337406	0.168703
246	0.795805	0.408391	0.204195
247	0.799498	0.401004	0.200502
248	0.762668	0.474663	0.237332
249	0.796338	0.407325	0.203662
250	0.751865	0.496271	0.248135
251	0.704281	0.591439	0.295719
252	0.672423	0.655153	0.327577
253	0.608659	0.782682	0.391341
254	0.577725	0.84455	0.422275
255	0.517394	0.965212	0.482606
256	0.463898	0.927797	0.536102
257	0.771722	0.456556	0.228278
258	0.78336	0.433279	0.21664
259	0.732466	0.535067	0.267534
260	0.882449	0.235102	0.117551
261	0.875632	0.248737	0.124368
262	0.918973	0.162053	0.0810267
263	0.874724	0.250552	0.125276
264	0.846413	0.307173	0.153587
265	0.79309	0.413819	0.20691
266	0.703963	0.592074	0.296037
267	0.591299	0.817401	0.408701
268	0.452088	0.904175	0.547912
269	0.975642	0.0487157	0.0243578

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	62	0.237548	NOK
5% type I error level	79	0.302682	NOK
10% type I error level	84	0.321839	NOK

\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 & 62 & 0.237548 & NOK \tabularnewline
5% type I error level & 79 & 0.302682 & NOK \tabularnewline
10% type I error level & 84 & 0.321839 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262963&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]62[/C][C]0.237548[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]79[/C][C]0.302682[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]84[/C][C]0.321839[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262963&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262963&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 tests	OK/NOK
1% type I error level	62	0.237548	NOK
5% type I error level	79	0.302682	NOK
10% type I error level	84	0.321839	NOK

Figure 1

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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 6 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

par1 = 6 ; 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')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code