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Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationThu, 19 Dec 2013 05:16:44 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/19/t138744834091fbknquiygbxk7.htm/, Retrieved Fri, 29 Mar 2024 07:36:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232447, Retrieved Fri, 29 Mar 2024 07:36:22 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact156
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2013-12-19 10:16:44] [9e6a405f514733ea23d87e4507d39d29] [Current]
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Dataseries X:
0	1	1	4	4	2	5	1	11
0	1	1	3	2	3	4	1	13
0	0	1	4	4	3	5	0	7
0	0	1	3	3	2	2	0	10
0	0	1	5	4	1	3	0	10
0	0	1	3	3	3	2	0	5
1	0	1	5	3	2	2	1	7
0	1	1	3	3	2	4	1	9
0	0	2	5	4	3	3	0	14
1	0	1	3	3	4	3	1	8
0	1	1	4	4	1	5	1	14
0	1	1	4	3	2	5	1	11
0	1	2	4	4	4	2	0	9
0	0	1	3	2	2	2	0	12
0	1	1	5	4	3	5	1	16
0	0	1	4	3	3	4	0	10
0	0	1	3	3	1	2	0	8
0	1	1	3	4	3	2	1	9
0	0	2	3	3	3	4	0	7
0	0	1	4	3	2	5	0	13
0	1	2	5	5	2	5	1	10
1	1	1	4	4	2	1	0	12
1	1	4	5	4	2	4	1	10
0	1	1	3	3	4	5	1	3
1	1	1	4	5	3	4	1	8
1	0	1	2	2	1	1	0	15
1	1	1	5	4	2	5	0	13
0	0	1	2	3	1	2	0	9
0	1	1	3	2	3	4	1	12
0	1	1	3	3	2	1	0	12
0	1	1	3	4	1	4	1	9
0	1	1	3	4	3	4	1	9
0	0	1	4	1	2	3	0	10
0	0	1	3	2	3	4	1	8
0	1	1	5	5	1	5	0	8
0	0	1	2	2	3	2	1	8
0	1	1	3	4	3	4	0	12
1	1	1	3	3	2	5	1	9
1	1	1	4	1	3	4	0	8
0	1	1	5	3	3	3	1	15
0	1	1	3	4	3	4	1	9
0	0	3	3	3	3	3	0	6
0	0	2	3	4	3	4	1	13
0	1	1	3	1	3	4	1	9
1	1	1	3	4	2	4	1	12
0	0	1	4	3	1	3	0	17
0	0	1	3	4	3	3	0	13
0	0	1	2	3	3	2	1	11
0	1	1	3	3	1	4	1	10
1	0	1	3	1	1	2	1	7
0	1	1	3	2	1	4	0	14
0	1	1	4	5	4	4	1	11
0	1	1	2	4	3	2	0	9
0	0	1	5	3	1	5	0	8
0	1	1	4	3	2	5	1	12
0	0	2	2	3	4	5	1	13
0	1	1	3	4	3	5	1	2
0	0	1	4	3	2	4	0	18
0	1	1	3	4	3	2	1	11
0	0	1	3	3	3	5	1	10
0	1	1	4	3	2	4	1	13
0	0	1	3	4	3	4	1	6
0	0	1	3	4	1	3	0	8
0	1	1	4	3	3	3	1	12
0	0	1	2	3	2	2	1	12
0	0	1	2	4	2	2	1	14
0	0	1	4	3	4	1	0	8
0	0	1	2	4	2	2	0	7
0	1	1	4	3	3	2	1	10
1	1	1	3	4	2	2	1	10
0	1	1	5	5	4	4	1	14
0	1	1	3	2	2	4	1	16
0	1	1	3	2	3	2	1	14
0	1	2	4	4	3	4	1	6
0	0	1	3	2	1	5	0	10
0	0	1	3	4	2	5	1	8
0	0	1	4	2	2	5	1	9
0	1	1	3	4	3	3	1	7
0	0	1	3	3	1	2	0	11
0	1	3	3	3	2	3	1	13
0	0	1	3	4	3	4	0	12
0	1	2	5	3	2	2	0	12
0	1	1	3	3	3	5	1	11
0	1	1	5	4	4	5	1	6
0	0	1	4	4	3	4	0	10
0	1	1	3	4	3	3	1	5
1	0	1	3	4	3	4	1	8
0	1	1	5	4	2	3	1	13
0	0	1	4	4	3	3	0	18
0	1	2	5	4	3	4	1	15
0	1	3	4	4	3	1	1	13
0	0	1	2	4	3	4	0	7
0	1	1	5	4	2	1	0	9
0	1	1	4	3	2	4	1	9
0	0	1	2	4	4	3	1	7
0	1	1	2	2	2	1	1	13
1	0	1	3	4	1	1	0	6
0	0	1	4	4	3	3	0	7
0	0	1	2	5	2	3	1	15
0	0	1	4	1	1	1	0	11
0	1	1	3	2	3	1	1	11
0	1	1	3	3	2	1	1	7
0	1	3	3	3	2	3	1	8
0	1	1	4	4	3	4	1	7
0	1	1	3	3	2	2	1	13
0	0	3	3	4	3	3	1	9
1	1	2	4	4	1	1	1	15
0	1	1	3	3	3	3	1	10
0	0	1	4	4	2	3	0	11
0	1	1	3	4	3	5	0	15
0	1	2	4	3	2	4	0	8
0	1	3	4	4	2	4	0	9
1	1	1	3	3	3	1	0	8
0	1	1	5	4	2	3	1	19
0	0	1	3	3	2	2	1	8
0	1	1	4	2	2	2	0	10
0	1	1	4	4	3	4	1	15
0	1	1	2	4	2	4	1	8
0	1	1	4	3	4	5	0	7
0	1	1	4	4	1	4	1	15
0	1	1	4	4	3	1	1	9
0	0	1	3	4	1	5	0	8
0	1	1	5	3	2	2	0	11
0	1	1	4	3	4	2	1	9
1	0	3	3	4	3	4	1	11
1	0	2	3	4	2	1	1	10
0	0	1	4	4	1	2	0	8
0	1	1	5	4	2	5	0	7
0	0	1	3	4	3	2	0	8
0	1	1	3	4	2	3	1	9
0	1	1	2	3	3	3	1	11
1	1	1	5	4	3	5	1	12
0	0	1	3	4	3	4	1	14
0	1	1	3	3	3	2	0	10
0	1	1	4	3	3	2	0	10
0	1	1	2	3	1	2	1	9
0	0	2	4	4	3	1	1	12
1	1	1	3	3	4	3	1	5
0	0	1	3	1	3	1	0	14
1	0	1	5	1	2	4	0	14
0	1	1	5	3	5	5	0	13
0	1	1	3	3	2	3	1	17
0	1	1	4	4	1	2	0	11
0	1	1	5	3	2	3	0	8
0	1	1	2	4	2	5	1	10
0	0	1	4	3	1	1	0	5
1	0	2	2	3	1	3	0	6
0	0	1	4	4	2	1	0	5
0	0	1	3	2	2	2	1	10
0	0	1	4	4	4	1	0	9
0	0	1	4	4	1	5	0	10
0	1	1	4	4	1	5	1	9
0	1	1	5	5	3	3	0	8
0	0	1	5	5	3	4	1	7
0	1	1	4	3	4	5	1	13
0	0	1	3	4	2	3	1	11
0	0	1	4	4	3	3	0	11
0	0	2	5	1	1	2	0	11
0	1	1	4	3	4	5	1	12
0	1	1	5	5	5	2	0	11
0	1	1	4	4	2	2	1	10
0	0	1	2	2	3	5	0	9
0	1	1	2	1	2	3	1	13
1	1	1	5	4	2	3	1	10
0	1	1	3	4	4	3	1	7
0	1	1	3	3	3	2	1	10
1	1	1	3	3	2	3	1	11
0	0	1	3	4	2	1	0	14
0	1	1	4	4	1	2	1	10
0	0	1	4	2	3	2	0	12
0	0	1	3	4	2	3	0	13
0	0	1	5	2	2	4	0	8
0	1	1	3	4	3	4	0	8
0	0	1	4	4	2	4	0	8
0	0	1	3	4	2	1	1	11
0	0	1	4	4	2	3	1	11
0	1	1	5	4	1	4	0	9
0	0	1	3	4	1	5	0	12
0	1	1	5	4	1	5	1	7
1	1	1	3	3	3	3	1	7
0	0	1	4	2	3	3	0	9
1	0	1	5	3	2	2	0	11
0	0	1	4	3	2	4	0	8
0	1	1	4	2	5	5	1	10
1	0	1	3	4	3	1	0	7
0	1	1	5	1	2	4	1	6
0	1	1	4	4	1	2	0	8
0	1	1	4	4	3	4	1	11
0	1	1	3	3	2	2	1	11
0	0	1	5	4	2	3	0	13
0	1	1	3	3	2	4	1	13
1	1	1	4	4	3	2	0	11
0	1	3	4	4	3	2	1	7
0	1	1	3	4	2	5	0	7
0	1	1	3	4	4	5	1	10
0	0	1	5	1	1	3	0	8
0	0	1	4	4	1	3	0	8
0	0	1	4	3	1	5	0	9
0	0	1	3	1	1	3	0	9
0	0	1	5	3	1	4	0	17
0	1	1	2	3	3	2	1	11
0	0	1	3	4	1	5	0	11
0	0	1	3	4	1	3	0	11
1	0	1	4	4	3	4	1	12
0	0	2	2	2	2	2	0	10
0	1	1	4	4	4	3	1	8
0	0	1	2	4	2	4	0	6
0	0	1	4	4	3	5	0	10
0	1	1	4	4	3	4	0	10
0	0	1	5	4	2	5	0	4
0	1	1	5	4	2	2	0	10
1	0	1	2	2	1	4	0	7
0	1	1	3	4	3	5	1	12
0	0	1	4	3	2	4	0	7
1	1	1	4	2	3	3	0	12
0	1	1	4	4	3	5	1	9
0	0	1	3	4	2	3	0	10
0	1	1	3	2	3	5	1	11
0	1	1	3	4	2	3	0	12
0	1	1	3	2	1	3	1	12
0	1	2	2	2	3	4	1	2
0	1	3	3	3	3	3	1	9
0	0	1	4	3	3	2	0	9
0	1	1	3	3	2	2	0	4
0	1	1	5	5	4	5	1	9
0	0	1	2	3	2	1	1	8
1	1	1	2	4	4	1	0	7
0	0	1	4	3	3	4	0	10
0	0	1	4	3	2	3	1	14
0	1	1	4	3	4	2	1	11
0	0	1	4	2	1	2	0	8
0	1	1	5	4	2	5	0	8
0	1	4	5	4	3	4	0	13
0	0	1	5	4	3	4	0	6
0	0	1	3	3	1	2	0	10
0	1	1	3	3	1	4	0	9
0	0	1	4	4	2	2	0	11
0	0	1	4	4	4	5	1	8
0	0	1	4	4	2	2	0	6
0	0	1	4	3	2	2	1	9
0	0	1	3	2	1	4	0	8
1	0	1	5	2	3	4	1	11
0	0	1	2	4	2	3	1	10
0	1	1	4	4	3	5	0	7
0	0	1	5	2	2	3	0	7
0	1	1	2	4	3	4	1	8
0	0	1	2	4	4	1	1	7
0	0	3	3	1	3	3	0	10
0	1	1	5	4	2	1	1	9
1	1	1	4	1	3	1	1	13
0	0	1	4	5	3	3	0	11
0	0	1	5	5	1	5	0	6
0	1	1	2	3	3	2	0	8
0	1	1	3	4	2	1	1	8
0	0	1	5	3	1	1	0	7
0	1	1	3	4	4	1	1	11
0	0	1	4	3	2	4	0	10
0	1	1	3	3	3	3	1	8
0	0	1	4	4	3	4	1	7
0	0	1	5	5	1	4	1	7
0	1	1	4	3	3	2	1	9
0	1	1	4	4	4	2	1	11
0	0	2	4	4	3	5	1	11
0	1	1	4	4	3	2	0	11
0	0	1	3	3	3	3	1	10
0	1	1	3	4	2	4	0	10
0	1	1	4	3	4	2	1	10
0	0	1	5	5	5	5	1	8
0	1	1	3	3	3	2	1	11
0	1	1	4	4	4	4	1	8
0	1	1	3	1	3	2	1	4
0	1	1	3	4	4	2	1	6
0	0	3	3	3	4	2	1	11
0	0	3	3	3	2	2	0	7
0	1	1	3	3	3	3	1	6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time24 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 24 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232447&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]24 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232447&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232447&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time24 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Multiple Linear Regression - Estimated Regression Equation
score[t] = + 9.46356 -0.202712illness[t] + 0.258773sports.competition[t] + 0.0793029addictive.drugs[t] + 0.374337fruits[t] -0.182761fish[t] -0.278447high.alcohol[t] -0.0631215milk[t] + 0.625181Gender[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
score[t] =  +  9.46356 -0.202712illness[t] +  0.258773sports.competition[t] +  0.0793029addictive.drugs[t] +  0.374337fruits[t] -0.182761fish[t] -0.278447high.alcohol[t] -0.0631215milk[t] +  0.625181Gender[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232447&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]score[t] =  +  9.46356 -0.202712illness[t] +  0.258773sports.competition[t] +  0.0793029addictive.drugs[t] +  0.374337fruits[t] -0.182761fish[t] -0.278447high.alcohol[t] -0.0631215milk[t] +  0.625181Gender[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232447&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232447&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
score[t] = + 9.46356 -0.202712illness[t] + 0.258773sports.competition[t] + 0.0793029addictive.drugs[t] + 0.374337fruits[t] -0.182761fish[t] -0.278447high.alcohol[t] -0.0631215milk[t] + 0.625181Gender[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)9.463561.035149.1421.62941e-178.14707e-18
illness-0.2027120.522637-0.38790.6984270.349213
sports.competition0.2587730.3750340.690.4907970.245398
addictive.drugs0.07930290.3260730.24320.8080330.404017
fruits0.3743370.1985511.8850.06047260.0302363
fish-0.1827610.188353-0.97030.3327720.166386
high.alcohol-0.2784470.190071-1.4650.1441110.0720555
milk-0.06312150.136892-0.46110.6451010.322551
Gender0.6251810.3881961.610.108480.0542399

\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) & 9.46356 & 1.03514 & 9.142 & 1.62941e-17 & 8.14707e-18 \tabularnewline
illness & -0.202712 & 0.522637 & -0.3879 & 0.698427 & 0.349213 \tabularnewline
sports.competition & 0.258773 & 0.375034 & 0.69 & 0.490797 & 0.245398 \tabularnewline
addictive.drugs & 0.0793029 & 0.326073 & 0.2432 & 0.808033 & 0.404017 \tabularnewline
fruits & 0.374337 & 0.198551 & 1.885 & 0.0604726 & 0.0302363 \tabularnewline
fish & -0.182761 & 0.188353 & -0.9703 & 0.332772 & 0.166386 \tabularnewline
high.alcohol & -0.278447 & 0.190071 & -1.465 & 0.144111 & 0.0720555 \tabularnewline
milk & -0.0631215 & 0.136892 & -0.4611 & 0.645101 & 0.322551 \tabularnewline
Gender & 0.625181 & 0.388196 & 1.61 & 0.10848 & 0.0542399 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232447&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]9.46356[/C][C]1.03514[/C][C]9.142[/C][C]1.62941e-17[/C][C]8.14707e-18[/C][/ROW]
[ROW][C]illness[/C][C]-0.202712[/C][C]0.522637[/C][C]-0.3879[/C][C]0.698427[/C][C]0.349213[/C][/ROW]
[ROW][C]sports.competition[/C][C]0.258773[/C][C]0.375034[/C][C]0.69[/C][C]0.490797[/C][C]0.245398[/C][/ROW]
[ROW][C]addictive.drugs[/C][C]0.0793029[/C][C]0.326073[/C][C]0.2432[/C][C]0.808033[/C][C]0.404017[/C][/ROW]
[ROW][C]fruits[/C][C]0.374337[/C][C]0.198551[/C][C]1.885[/C][C]0.0604726[/C][C]0.0302363[/C][/ROW]
[ROW][C]fish[/C][C]-0.182761[/C][C]0.188353[/C][C]-0.9703[/C][C]0.332772[/C][C]0.166386[/C][/ROW]
[ROW][C]high.alcohol[/C][C]-0.278447[/C][C]0.190071[/C][C]-1.465[/C][C]0.144111[/C][C]0.0720555[/C][/ROW]
[ROW][C]milk[/C][C]-0.0631215[/C][C]0.136892[/C][C]-0.4611[/C][C]0.645101[/C][C]0.322551[/C][/ROW]
[ROW][C]Gender[/C][C]0.625181[/C][C]0.388196[/C][C]1.61[/C][C]0.10848[/C][C]0.0542399[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232447&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232447&T=2

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)9.463561.035149.1421.62941e-178.14707e-18
illness-0.2027120.522637-0.38790.6984270.349213
sports.competition0.2587730.3750340.690.4907970.245398
addictive.drugs0.07930290.3260730.24320.8080330.404017
fruits0.3743370.1985511.8850.06047260.0302363
fish-0.1827610.188353-0.97030.3327720.166386
high.alcohol-0.2784470.190071-1.4650.1441110.0720555
milk-0.06312150.136892-0.46110.6451010.322551
Gender0.6251810.3881961.610.108480.0542399







Multiple Linear Regression - Regression Statistics
Multiple R0.177383
R-squared0.0314647
Adjusted R-squared0.00233583
F-TEST (value)1.08019
F-TEST (DF numerator)8
F-TEST (DF denominator)266
p-value0.377201
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.82183
Sum Squared Residuals2118.08

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.177383 \tabularnewline
R-squared & 0.0314647 \tabularnewline
Adjusted R-squared & 0.00233583 \tabularnewline
F-TEST (value) & 1.08019 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 266 \tabularnewline
p-value & 0.377201 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.82183 \tabularnewline
Sum Squared Residuals & 2118.08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232447&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.177383[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0314647[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.00233583[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]1.08019[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]266[/C][/ROW]
[ROW][C]p-value[/C][C]0.377201[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.82183[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2118.08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232447&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232447&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.177383
R-squared0.0314647
Adjusted R-squared0.00233583
F-TEST (value)1.08019
F-TEST (DF numerator)8
F-TEST (DF denominator)266
p-value0.377201
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.82183
Sum Squared Residuals2118.08







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11110.32060.679382
21310.09652.90352
379.15822-2.15822
4109.434450.565547
51010.2157-0.215692
659.15601-4.15601
7710.6056-3.6056
8910.1922-1.19216
9149.73814.2619
1089.23691-1.23691
111410.59913.40093
121110.50340.49662
1399.40721-0.40721
14129.617212.38279
151610.41655.58349
16109.40410.5959
1789.7129-1.7129
1899.8572-0.857198
1979.10907-2.10907
20139.619433.38057
211010.5915-0.591497
22129.745212.25479
231010.7933-0.793274
2439.57215-6.57215
2589.71982-1.71982
26159.381735.61827
27139.867063.13294
2899.33856-0.338563
291210.09651.90352
30129.756352.24365
31910.2878-1.28785
3299.73096-0.730955
331010.1112-0.111192
3489.8377-1.8377
35810.1655-2.16546
3689.58961-1.58961
37129.105772.89423
3899.92633-0.92633
3989.82568-1.82568
401510.72554.27449
4199.73096-0.730955
4269.25149-3.25149
43139.551493.44851
44910.2792-1.27924
45129.806692.19331
461710.02416.97588
47138.910124.08988
48119.406851.59315
491010.4706-0.470611
50710.5009-3.50089
511410.02823.97181
52119.644081.35592
5398.857680.14232
54810.2722-2.27221
551210.50341.49662
56139.018343.98166
5729.66783-7.66783
58189.682558.31745
59119.85721.1428
60109.591820.408178
611310.56652.4335
6269.47218-3.47218
6389.46702-1.46702
641210.35121.64882
65129.68532.3147
66149.502544.49746
6789.31502-1.31502
6878.87735-1.87735
691010.4143-0.414297
70109.932930.0670667
711410.01843.98158
721610.37495.62507
731410.22273.77728
74610.1846-4.1846
75109.70630.293702
7689.68751-1.68751
77910.4274-1.42737
7879.79408-2.79408
79119.71291.2871
801310.41392.58611
81128.8473.153
821210.52121.4788
83119.85061.1494
84610.1381-4.13806
85109.221340.778661
8659.79408-4.79408
8789.26947-1.26947
881310.82122.1788
89189.284468.71554
901510.55894.44107
911310.45332.54674
9278.47266-1.47266
93910.3223-1.32226
94910.5665-1.5665
9578.88252-1.88252
961310.192.81005
9769.39055-3.39055
9879.28446-2.28446
99159.256655.74335
1001110.51590.484118
1011110.28580.714158
102710.3815-3.38153
103810.4139-2.41389
104710.1053-3.10529
1051310.31842.68159
10699.69391-0.69391
1071510.72814.27186
108109.976840.023162
109119.562911.43709
110159.042655.95735
111810.0206-2.02062
11299.91717-0.917165
11389.27519-1.27519
1141910.82128.1788
115810.0596-2.05963
1161010.2503-0.250325
1171510.10534.89471
11889.63507-1.63507
11979.3213-2.3213
1201510.66224.33781
121910.2947-1.29466
12289.34077-1.34077
1231110.44190.558099
124910.1358-1.13585
125119.428081.57192
126109.816580.183415
12789.90448-1.90448
128710.0698-3.06977
12988.97324-0.973245
130910.0725-1.07252
131119.60251.3975
1321210.21381.7862
133149.472184.52782
134109.414780.585221
135109.789120.210884
136910.2225-1.22252
1371210.11521.88481
13859.49568-4.49568
139149.584654.41535
1401410.21973.7803
141139.417193.58281
1421710.25536.74471
1431110.16320.83675
144810.3788-2.37878
145109.571940.428056
146510.1504-5.15036
14769.15203-3.15203
14859.68915-4.68915
1491010.2424-0.242395
15099.13226-0.132256
151109.715110.284888
152910.5991-1.59907
15389.73481-1.73481
154710.0381-3.0381
155139.946483.05352
156119.813751.18625
157119.284461.71554
1581110.90640.093599
159129.946482.05352
160119.241041.75896
1611010.51-0.509983
16298.775070.224935
1631310.24652.75353
1641010.6185-0.618486
16579.51563-2.51563
1661010.04-0.0399595
1671110.05260.947427
168149.314814.68519
1691010.7884-0.78843
170129.71312.2869
171139.188573.81143
172810.2396-2.23965
17389.10577-1.10577
17489.49979-1.49979
175119.939991.06001
1761110.18810.811912
177910.4113-1.41134
178129.340772.65923
179710.9734-3.9734
18079.77413-2.77413
18199.64998-0.649983
182119.980421.01958
18389.68255-1.68255
184109.85080.149201
18578.83365-1.83365
186611.3064-5.30636
187810.1632-2.16325
1881110.10530.894708
1891110.31840.681593
190139.937243.06276
1911310.19222.80784
192119.403641.59636
193710.3901-3.39014
19479.3211-2.3211
195109.389390.610614
196810.764-2.76398
19789.84136-1.84136
19899.89787-0.897873
199910.0153-1.0153
2001710.33536.66467
201119.665621.33438
202119.340771.65923
203119.467021.53298
204129.643812.35619
205109.322180.67782
20689.88997-1.88997
20768.75111-2.75111
208109.158220.841783
209109.480110.519888
21049.811-5.811
2111010.2591-0.259139
21279.19237-2.19237
213129.667832.33217
21479.68255-2.68255
215129.706042.29396
216910.0422-1.04217
217109.188570.81143
2181110.03340.966644
219129.447342.55266
2201210.71651.28351
22129.80144-7.80144
222910.1354-1.13544
22399.53034-0.530343
22449.69323-5.69323
22599.9553-0.955299
22689.74842-1.74842
22778.43964-1.43964
228109.40410.5959
2291410.37083.62915
2301110.13580.864151
231810.27-2.27
232810.0698-2.06977
2331310.09242.90764
23469.59568-3.59568
235109.71290.287099
23699.84543-0.845431
237119.626031.37397
23889.50495-1.50495
23969.62603-3.62603
240910.434-1.43397
24189.76942-1.76942
2421110.38370.616333
243109.439410.560586
24479.41699-2.41699
245710.3028-3.30277
24689.35662-1.35662
24779.00876-2.00876
248109.617010.382987
249910.9474-1.94744
2501310.64022.35977
251119.10171.8983
25269.90669-3.90669
25389.04044-1.04044
254810.1988-2.19877
255710.5247-3.5247
256119.641871.35813
257109.682550.317452
25889.97684-1.97684
25979.84652-2.84652
260710.595-3.59499
261910.4143-1.4143
262119.953091.04691
263119.86271.1373
264119.606351.39365
265109.718070.281935
266109.384220.615778
2671010.1358-0.135849
26889.41808-1.41808
2691110.040.96004
27089.82685-1.82685
271410.4055-6.40548
27269.57875-3.57875
273119.661351.33865
27479.59306-2.59306
27569.97684-3.97684

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 11 & 10.3206 & 0.679382 \tabularnewline
2 & 13 & 10.0965 & 2.90352 \tabularnewline
3 & 7 & 9.15822 & -2.15822 \tabularnewline
4 & 10 & 9.43445 & 0.565547 \tabularnewline
5 & 10 & 10.2157 & -0.215692 \tabularnewline
6 & 5 & 9.15601 & -4.15601 \tabularnewline
7 & 7 & 10.6056 & -3.6056 \tabularnewline
8 & 9 & 10.1922 & -1.19216 \tabularnewline
9 & 14 & 9.7381 & 4.2619 \tabularnewline
10 & 8 & 9.23691 & -1.23691 \tabularnewline
11 & 14 & 10.5991 & 3.40093 \tabularnewline
12 & 11 & 10.5034 & 0.49662 \tabularnewline
13 & 9 & 9.40721 & -0.40721 \tabularnewline
14 & 12 & 9.61721 & 2.38279 \tabularnewline
15 & 16 & 10.4165 & 5.58349 \tabularnewline
16 & 10 & 9.4041 & 0.5959 \tabularnewline
17 & 8 & 9.7129 & -1.7129 \tabularnewline
18 & 9 & 9.8572 & -0.857198 \tabularnewline
19 & 7 & 9.10907 & -2.10907 \tabularnewline
20 & 13 & 9.61943 & 3.38057 \tabularnewline
21 & 10 & 10.5915 & -0.591497 \tabularnewline
22 & 12 & 9.74521 & 2.25479 \tabularnewline
23 & 10 & 10.7933 & -0.793274 \tabularnewline
24 & 3 & 9.57215 & -6.57215 \tabularnewline
25 & 8 & 9.71982 & -1.71982 \tabularnewline
26 & 15 & 9.38173 & 5.61827 \tabularnewline
27 & 13 & 9.86706 & 3.13294 \tabularnewline
28 & 9 & 9.33856 & -0.338563 \tabularnewline
29 & 12 & 10.0965 & 1.90352 \tabularnewline
30 & 12 & 9.75635 & 2.24365 \tabularnewline
31 & 9 & 10.2878 & -1.28785 \tabularnewline
32 & 9 & 9.73096 & -0.730955 \tabularnewline
33 & 10 & 10.1112 & -0.111192 \tabularnewline
34 & 8 & 9.8377 & -1.8377 \tabularnewline
35 & 8 & 10.1655 & -2.16546 \tabularnewline
36 & 8 & 9.58961 & -1.58961 \tabularnewline
37 & 12 & 9.10577 & 2.89423 \tabularnewline
38 & 9 & 9.92633 & -0.92633 \tabularnewline
39 & 8 & 9.82568 & -1.82568 \tabularnewline
40 & 15 & 10.7255 & 4.27449 \tabularnewline
41 & 9 & 9.73096 & -0.730955 \tabularnewline
42 & 6 & 9.25149 & -3.25149 \tabularnewline
43 & 13 & 9.55149 & 3.44851 \tabularnewline
44 & 9 & 10.2792 & -1.27924 \tabularnewline
45 & 12 & 9.80669 & 2.19331 \tabularnewline
46 & 17 & 10.0241 & 6.97588 \tabularnewline
47 & 13 & 8.91012 & 4.08988 \tabularnewline
48 & 11 & 9.40685 & 1.59315 \tabularnewline
49 & 10 & 10.4706 & -0.470611 \tabularnewline
50 & 7 & 10.5009 & -3.50089 \tabularnewline
51 & 14 & 10.0282 & 3.97181 \tabularnewline
52 & 11 & 9.64408 & 1.35592 \tabularnewline
53 & 9 & 8.85768 & 0.14232 \tabularnewline
54 & 8 & 10.2722 & -2.27221 \tabularnewline
55 & 12 & 10.5034 & 1.49662 \tabularnewline
56 & 13 & 9.01834 & 3.98166 \tabularnewline
57 & 2 & 9.66783 & -7.66783 \tabularnewline
58 & 18 & 9.68255 & 8.31745 \tabularnewline
59 & 11 & 9.8572 & 1.1428 \tabularnewline
60 & 10 & 9.59182 & 0.408178 \tabularnewline
61 & 13 & 10.5665 & 2.4335 \tabularnewline
62 & 6 & 9.47218 & -3.47218 \tabularnewline
63 & 8 & 9.46702 & -1.46702 \tabularnewline
64 & 12 & 10.3512 & 1.64882 \tabularnewline
65 & 12 & 9.6853 & 2.3147 \tabularnewline
66 & 14 & 9.50254 & 4.49746 \tabularnewline
67 & 8 & 9.31502 & -1.31502 \tabularnewline
68 & 7 & 8.87735 & -1.87735 \tabularnewline
69 & 10 & 10.4143 & -0.414297 \tabularnewline
70 & 10 & 9.93293 & 0.0670667 \tabularnewline
71 & 14 & 10.0184 & 3.98158 \tabularnewline
72 & 16 & 10.3749 & 5.62507 \tabularnewline
73 & 14 & 10.2227 & 3.77728 \tabularnewline
74 & 6 & 10.1846 & -4.1846 \tabularnewline
75 & 10 & 9.7063 & 0.293702 \tabularnewline
76 & 8 & 9.68751 & -1.68751 \tabularnewline
77 & 9 & 10.4274 & -1.42737 \tabularnewline
78 & 7 & 9.79408 & -2.79408 \tabularnewline
79 & 11 & 9.7129 & 1.2871 \tabularnewline
80 & 13 & 10.4139 & 2.58611 \tabularnewline
81 & 12 & 8.847 & 3.153 \tabularnewline
82 & 12 & 10.5212 & 1.4788 \tabularnewline
83 & 11 & 9.8506 & 1.1494 \tabularnewline
84 & 6 & 10.1381 & -4.13806 \tabularnewline
85 & 10 & 9.22134 & 0.778661 \tabularnewline
86 & 5 & 9.79408 & -4.79408 \tabularnewline
87 & 8 & 9.26947 & -1.26947 \tabularnewline
88 & 13 & 10.8212 & 2.1788 \tabularnewline
89 & 18 & 9.28446 & 8.71554 \tabularnewline
90 & 15 & 10.5589 & 4.44107 \tabularnewline
91 & 13 & 10.4533 & 2.54674 \tabularnewline
92 & 7 & 8.47266 & -1.47266 \tabularnewline
93 & 9 & 10.3223 & -1.32226 \tabularnewline
94 & 9 & 10.5665 & -1.5665 \tabularnewline
95 & 7 & 8.88252 & -1.88252 \tabularnewline
96 & 13 & 10.19 & 2.81005 \tabularnewline
97 & 6 & 9.39055 & -3.39055 \tabularnewline
98 & 7 & 9.28446 & -2.28446 \tabularnewline
99 & 15 & 9.25665 & 5.74335 \tabularnewline
100 & 11 & 10.5159 & 0.484118 \tabularnewline
101 & 11 & 10.2858 & 0.714158 \tabularnewline
102 & 7 & 10.3815 & -3.38153 \tabularnewline
103 & 8 & 10.4139 & -2.41389 \tabularnewline
104 & 7 & 10.1053 & -3.10529 \tabularnewline
105 & 13 & 10.3184 & 2.68159 \tabularnewline
106 & 9 & 9.69391 & -0.69391 \tabularnewline
107 & 15 & 10.7281 & 4.27186 \tabularnewline
108 & 10 & 9.97684 & 0.023162 \tabularnewline
109 & 11 & 9.56291 & 1.43709 \tabularnewline
110 & 15 & 9.04265 & 5.95735 \tabularnewline
111 & 8 & 10.0206 & -2.02062 \tabularnewline
112 & 9 & 9.91717 & -0.917165 \tabularnewline
113 & 8 & 9.27519 & -1.27519 \tabularnewline
114 & 19 & 10.8212 & 8.1788 \tabularnewline
115 & 8 & 10.0596 & -2.05963 \tabularnewline
116 & 10 & 10.2503 & -0.250325 \tabularnewline
117 & 15 & 10.1053 & 4.89471 \tabularnewline
118 & 8 & 9.63507 & -1.63507 \tabularnewline
119 & 7 & 9.3213 & -2.3213 \tabularnewline
120 & 15 & 10.6622 & 4.33781 \tabularnewline
121 & 9 & 10.2947 & -1.29466 \tabularnewline
122 & 8 & 9.34077 & -1.34077 \tabularnewline
123 & 11 & 10.4419 & 0.558099 \tabularnewline
124 & 9 & 10.1358 & -1.13585 \tabularnewline
125 & 11 & 9.42808 & 1.57192 \tabularnewline
126 & 10 & 9.81658 & 0.183415 \tabularnewline
127 & 8 & 9.90448 & -1.90448 \tabularnewline
128 & 7 & 10.0698 & -3.06977 \tabularnewline
129 & 8 & 8.97324 & -0.973245 \tabularnewline
130 & 9 & 10.0725 & -1.07252 \tabularnewline
131 & 11 & 9.6025 & 1.3975 \tabularnewline
132 & 12 & 10.2138 & 1.7862 \tabularnewline
133 & 14 & 9.47218 & 4.52782 \tabularnewline
134 & 10 & 9.41478 & 0.585221 \tabularnewline
135 & 10 & 9.78912 & 0.210884 \tabularnewline
136 & 9 & 10.2225 & -1.22252 \tabularnewline
137 & 12 & 10.1152 & 1.88481 \tabularnewline
138 & 5 & 9.49568 & -4.49568 \tabularnewline
139 & 14 & 9.58465 & 4.41535 \tabularnewline
140 & 14 & 10.2197 & 3.7803 \tabularnewline
141 & 13 & 9.41719 & 3.58281 \tabularnewline
142 & 17 & 10.2553 & 6.74471 \tabularnewline
143 & 11 & 10.1632 & 0.83675 \tabularnewline
144 & 8 & 10.3788 & -2.37878 \tabularnewline
145 & 10 & 9.57194 & 0.428056 \tabularnewline
146 & 5 & 10.1504 & -5.15036 \tabularnewline
147 & 6 & 9.15203 & -3.15203 \tabularnewline
148 & 5 & 9.68915 & -4.68915 \tabularnewline
149 & 10 & 10.2424 & -0.242395 \tabularnewline
150 & 9 & 9.13226 & -0.132256 \tabularnewline
151 & 10 & 9.71511 & 0.284888 \tabularnewline
152 & 9 & 10.5991 & -1.59907 \tabularnewline
153 & 8 & 9.73481 & -1.73481 \tabularnewline
154 & 7 & 10.0381 & -3.0381 \tabularnewline
155 & 13 & 9.94648 & 3.05352 \tabularnewline
156 & 11 & 9.81375 & 1.18625 \tabularnewline
157 & 11 & 9.28446 & 1.71554 \tabularnewline
158 & 11 & 10.9064 & 0.093599 \tabularnewline
159 & 12 & 9.94648 & 2.05352 \tabularnewline
160 & 11 & 9.24104 & 1.75896 \tabularnewline
161 & 10 & 10.51 & -0.509983 \tabularnewline
162 & 9 & 8.77507 & 0.224935 \tabularnewline
163 & 13 & 10.2465 & 2.75353 \tabularnewline
164 & 10 & 10.6185 & -0.618486 \tabularnewline
165 & 7 & 9.51563 & -2.51563 \tabularnewline
166 & 10 & 10.04 & -0.0399595 \tabularnewline
167 & 11 & 10.0526 & 0.947427 \tabularnewline
168 & 14 & 9.31481 & 4.68519 \tabularnewline
169 & 10 & 10.7884 & -0.78843 \tabularnewline
170 & 12 & 9.7131 & 2.2869 \tabularnewline
171 & 13 & 9.18857 & 3.81143 \tabularnewline
172 & 8 & 10.2396 & -2.23965 \tabularnewline
173 & 8 & 9.10577 & -1.10577 \tabularnewline
174 & 8 & 9.49979 & -1.49979 \tabularnewline
175 & 11 & 9.93999 & 1.06001 \tabularnewline
176 & 11 & 10.1881 & 0.811912 \tabularnewline
177 & 9 & 10.4113 & -1.41134 \tabularnewline
178 & 12 & 9.34077 & 2.65923 \tabularnewline
179 & 7 & 10.9734 & -3.9734 \tabularnewline
180 & 7 & 9.77413 & -2.77413 \tabularnewline
181 & 9 & 9.64998 & -0.649983 \tabularnewline
182 & 11 & 9.98042 & 1.01958 \tabularnewline
183 & 8 & 9.68255 & -1.68255 \tabularnewline
184 & 10 & 9.8508 & 0.149201 \tabularnewline
185 & 7 & 8.83365 & -1.83365 \tabularnewline
186 & 6 & 11.3064 & -5.30636 \tabularnewline
187 & 8 & 10.1632 & -2.16325 \tabularnewline
188 & 11 & 10.1053 & 0.894708 \tabularnewline
189 & 11 & 10.3184 & 0.681593 \tabularnewline
190 & 13 & 9.93724 & 3.06276 \tabularnewline
191 & 13 & 10.1922 & 2.80784 \tabularnewline
192 & 11 & 9.40364 & 1.59636 \tabularnewline
193 & 7 & 10.3901 & -3.39014 \tabularnewline
194 & 7 & 9.3211 & -2.3211 \tabularnewline
195 & 10 & 9.38939 & 0.610614 \tabularnewline
196 & 8 & 10.764 & -2.76398 \tabularnewline
197 & 8 & 9.84136 & -1.84136 \tabularnewline
198 & 9 & 9.89787 & -0.897873 \tabularnewline
199 & 9 & 10.0153 & -1.0153 \tabularnewline
200 & 17 & 10.3353 & 6.66467 \tabularnewline
201 & 11 & 9.66562 & 1.33438 \tabularnewline
202 & 11 & 9.34077 & 1.65923 \tabularnewline
203 & 11 & 9.46702 & 1.53298 \tabularnewline
204 & 12 & 9.64381 & 2.35619 \tabularnewline
205 & 10 & 9.32218 & 0.67782 \tabularnewline
206 & 8 & 9.88997 & -1.88997 \tabularnewline
207 & 6 & 8.75111 & -2.75111 \tabularnewline
208 & 10 & 9.15822 & 0.841783 \tabularnewline
209 & 10 & 9.48011 & 0.519888 \tabularnewline
210 & 4 & 9.811 & -5.811 \tabularnewline
211 & 10 & 10.2591 & -0.259139 \tabularnewline
212 & 7 & 9.19237 & -2.19237 \tabularnewline
213 & 12 & 9.66783 & 2.33217 \tabularnewline
214 & 7 & 9.68255 & -2.68255 \tabularnewline
215 & 12 & 9.70604 & 2.29396 \tabularnewline
216 & 9 & 10.0422 & -1.04217 \tabularnewline
217 & 10 & 9.18857 & 0.81143 \tabularnewline
218 & 11 & 10.0334 & 0.966644 \tabularnewline
219 & 12 & 9.44734 & 2.55266 \tabularnewline
220 & 12 & 10.7165 & 1.28351 \tabularnewline
221 & 2 & 9.80144 & -7.80144 \tabularnewline
222 & 9 & 10.1354 & -1.13544 \tabularnewline
223 & 9 & 9.53034 & -0.530343 \tabularnewline
224 & 4 & 9.69323 & -5.69323 \tabularnewline
225 & 9 & 9.9553 & -0.955299 \tabularnewline
226 & 8 & 9.74842 & -1.74842 \tabularnewline
227 & 7 & 8.43964 & -1.43964 \tabularnewline
228 & 10 & 9.4041 & 0.5959 \tabularnewline
229 & 14 & 10.3708 & 3.62915 \tabularnewline
230 & 11 & 10.1358 & 0.864151 \tabularnewline
231 & 8 & 10.27 & -2.27 \tabularnewline
232 & 8 & 10.0698 & -2.06977 \tabularnewline
233 & 13 & 10.0924 & 2.90764 \tabularnewline
234 & 6 & 9.59568 & -3.59568 \tabularnewline
235 & 10 & 9.7129 & 0.287099 \tabularnewline
236 & 9 & 9.84543 & -0.845431 \tabularnewline
237 & 11 & 9.62603 & 1.37397 \tabularnewline
238 & 8 & 9.50495 & -1.50495 \tabularnewline
239 & 6 & 9.62603 & -3.62603 \tabularnewline
240 & 9 & 10.434 & -1.43397 \tabularnewline
241 & 8 & 9.76942 & -1.76942 \tabularnewline
242 & 11 & 10.3837 & 0.616333 \tabularnewline
243 & 10 & 9.43941 & 0.560586 \tabularnewline
244 & 7 & 9.41699 & -2.41699 \tabularnewline
245 & 7 & 10.3028 & -3.30277 \tabularnewline
246 & 8 & 9.35662 & -1.35662 \tabularnewline
247 & 7 & 9.00876 & -2.00876 \tabularnewline
248 & 10 & 9.61701 & 0.382987 \tabularnewline
249 & 9 & 10.9474 & -1.94744 \tabularnewline
250 & 13 & 10.6402 & 2.35977 \tabularnewline
251 & 11 & 9.1017 & 1.8983 \tabularnewline
252 & 6 & 9.90669 & -3.90669 \tabularnewline
253 & 8 & 9.04044 & -1.04044 \tabularnewline
254 & 8 & 10.1988 & -2.19877 \tabularnewline
255 & 7 & 10.5247 & -3.5247 \tabularnewline
256 & 11 & 9.64187 & 1.35813 \tabularnewline
257 & 10 & 9.68255 & 0.317452 \tabularnewline
258 & 8 & 9.97684 & -1.97684 \tabularnewline
259 & 7 & 9.84652 & -2.84652 \tabularnewline
260 & 7 & 10.595 & -3.59499 \tabularnewline
261 & 9 & 10.4143 & -1.4143 \tabularnewline
262 & 11 & 9.95309 & 1.04691 \tabularnewline
263 & 11 & 9.8627 & 1.1373 \tabularnewline
264 & 11 & 9.60635 & 1.39365 \tabularnewline
265 & 10 & 9.71807 & 0.281935 \tabularnewline
266 & 10 & 9.38422 & 0.615778 \tabularnewline
267 & 10 & 10.1358 & -0.135849 \tabularnewline
268 & 8 & 9.41808 & -1.41808 \tabularnewline
269 & 11 & 10.04 & 0.96004 \tabularnewline
270 & 8 & 9.82685 & -1.82685 \tabularnewline
271 & 4 & 10.4055 & -6.40548 \tabularnewline
272 & 6 & 9.57875 & -3.57875 \tabularnewline
273 & 11 & 9.66135 & 1.33865 \tabularnewline
274 & 7 & 9.59306 & -2.59306 \tabularnewline
275 & 6 & 9.97684 & -3.97684 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232447&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]11[/C][C]10.3206[/C][C]0.679382[/C][/ROW]
[ROW][C]2[/C][C]13[/C][C]10.0965[/C][C]2.90352[/C][/ROW]
[ROW][C]3[/C][C]7[/C][C]9.15822[/C][C]-2.15822[/C][/ROW]
[ROW][C]4[/C][C]10[/C][C]9.43445[/C][C]0.565547[/C][/ROW]
[ROW][C]5[/C][C]10[/C][C]10.2157[/C][C]-0.215692[/C][/ROW]
[ROW][C]6[/C][C]5[/C][C]9.15601[/C][C]-4.15601[/C][/ROW]
[ROW][C]7[/C][C]7[/C][C]10.6056[/C][C]-3.6056[/C][/ROW]
[ROW][C]8[/C][C]9[/C][C]10.1922[/C][C]-1.19216[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]9.7381[/C][C]4.2619[/C][/ROW]
[ROW][C]10[/C][C]8[/C][C]9.23691[/C][C]-1.23691[/C][/ROW]
[ROW][C]11[/C][C]14[/C][C]10.5991[/C][C]3.40093[/C][/ROW]
[ROW][C]12[/C][C]11[/C][C]10.5034[/C][C]0.49662[/C][/ROW]
[ROW][C]13[/C][C]9[/C][C]9.40721[/C][C]-0.40721[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]9.61721[/C][C]2.38279[/C][/ROW]
[ROW][C]15[/C][C]16[/C][C]10.4165[/C][C]5.58349[/C][/ROW]
[ROW][C]16[/C][C]10[/C][C]9.4041[/C][C]0.5959[/C][/ROW]
[ROW][C]17[/C][C]8[/C][C]9.7129[/C][C]-1.7129[/C][/ROW]
[ROW][C]18[/C][C]9[/C][C]9.8572[/C][C]-0.857198[/C][/ROW]
[ROW][C]19[/C][C]7[/C][C]9.10907[/C][C]-2.10907[/C][/ROW]
[ROW][C]20[/C][C]13[/C][C]9.61943[/C][C]3.38057[/C][/ROW]
[ROW][C]21[/C][C]10[/C][C]10.5915[/C][C]-0.591497[/C][/ROW]
[ROW][C]22[/C][C]12[/C][C]9.74521[/C][C]2.25479[/C][/ROW]
[ROW][C]23[/C][C]10[/C][C]10.7933[/C][C]-0.793274[/C][/ROW]
[ROW][C]24[/C][C]3[/C][C]9.57215[/C][C]-6.57215[/C][/ROW]
[ROW][C]25[/C][C]8[/C][C]9.71982[/C][C]-1.71982[/C][/ROW]
[ROW][C]26[/C][C]15[/C][C]9.38173[/C][C]5.61827[/C][/ROW]
[ROW][C]27[/C][C]13[/C][C]9.86706[/C][C]3.13294[/C][/ROW]
[ROW][C]28[/C][C]9[/C][C]9.33856[/C][C]-0.338563[/C][/ROW]
[ROW][C]29[/C][C]12[/C][C]10.0965[/C][C]1.90352[/C][/ROW]
[ROW][C]30[/C][C]12[/C][C]9.75635[/C][C]2.24365[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]10.2878[/C][C]-1.28785[/C][/ROW]
[ROW][C]32[/C][C]9[/C][C]9.73096[/C][C]-0.730955[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.1112[/C][C]-0.111192[/C][/ROW]
[ROW][C]34[/C][C]8[/C][C]9.8377[/C][C]-1.8377[/C][/ROW]
[ROW][C]35[/C][C]8[/C][C]10.1655[/C][C]-2.16546[/C][/ROW]
[ROW][C]36[/C][C]8[/C][C]9.58961[/C][C]-1.58961[/C][/ROW]
[ROW][C]37[/C][C]12[/C][C]9.10577[/C][C]2.89423[/C][/ROW]
[ROW][C]38[/C][C]9[/C][C]9.92633[/C][C]-0.92633[/C][/ROW]
[ROW][C]39[/C][C]8[/C][C]9.82568[/C][C]-1.82568[/C][/ROW]
[ROW][C]40[/C][C]15[/C][C]10.7255[/C][C]4.27449[/C][/ROW]
[ROW][C]41[/C][C]9[/C][C]9.73096[/C][C]-0.730955[/C][/ROW]
[ROW][C]42[/C][C]6[/C][C]9.25149[/C][C]-3.25149[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]9.55149[/C][C]3.44851[/C][/ROW]
[ROW][C]44[/C][C]9[/C][C]10.2792[/C][C]-1.27924[/C][/ROW]
[ROW][C]45[/C][C]12[/C][C]9.80669[/C][C]2.19331[/C][/ROW]
[ROW][C]46[/C][C]17[/C][C]10.0241[/C][C]6.97588[/C][/ROW]
[ROW][C]47[/C][C]13[/C][C]8.91012[/C][C]4.08988[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]9.40685[/C][C]1.59315[/C][/ROW]
[ROW][C]49[/C][C]10[/C][C]10.4706[/C][C]-0.470611[/C][/ROW]
[ROW][C]50[/C][C]7[/C][C]10.5009[/C][C]-3.50089[/C][/ROW]
[ROW][C]51[/C][C]14[/C][C]10.0282[/C][C]3.97181[/C][/ROW]
[ROW][C]52[/C][C]11[/C][C]9.64408[/C][C]1.35592[/C][/ROW]
[ROW][C]53[/C][C]9[/C][C]8.85768[/C][C]0.14232[/C][/ROW]
[ROW][C]54[/C][C]8[/C][C]10.2722[/C][C]-2.27221[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]10.5034[/C][C]1.49662[/C][/ROW]
[ROW][C]56[/C][C]13[/C][C]9.01834[/C][C]3.98166[/C][/ROW]
[ROW][C]57[/C][C]2[/C][C]9.66783[/C][C]-7.66783[/C][/ROW]
[ROW][C]58[/C][C]18[/C][C]9.68255[/C][C]8.31745[/C][/ROW]
[ROW][C]59[/C][C]11[/C][C]9.8572[/C][C]1.1428[/C][/ROW]
[ROW][C]60[/C][C]10[/C][C]9.59182[/C][C]0.408178[/C][/ROW]
[ROW][C]61[/C][C]13[/C][C]10.5665[/C][C]2.4335[/C][/ROW]
[ROW][C]62[/C][C]6[/C][C]9.47218[/C][C]-3.47218[/C][/ROW]
[ROW][C]63[/C][C]8[/C][C]9.46702[/C][C]-1.46702[/C][/ROW]
[ROW][C]64[/C][C]12[/C][C]10.3512[/C][C]1.64882[/C][/ROW]
[ROW][C]65[/C][C]12[/C][C]9.6853[/C][C]2.3147[/C][/ROW]
[ROW][C]66[/C][C]14[/C][C]9.50254[/C][C]4.49746[/C][/ROW]
[ROW][C]67[/C][C]8[/C][C]9.31502[/C][C]-1.31502[/C][/ROW]
[ROW][C]68[/C][C]7[/C][C]8.87735[/C][C]-1.87735[/C][/ROW]
[ROW][C]69[/C][C]10[/C][C]10.4143[/C][C]-0.414297[/C][/ROW]
[ROW][C]70[/C][C]10[/C][C]9.93293[/C][C]0.0670667[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]10.0184[/C][C]3.98158[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]10.3749[/C][C]5.62507[/C][/ROW]
[ROW][C]73[/C][C]14[/C][C]10.2227[/C][C]3.77728[/C][/ROW]
[ROW][C]74[/C][C]6[/C][C]10.1846[/C][C]-4.1846[/C][/ROW]
[ROW][C]75[/C][C]10[/C][C]9.7063[/C][C]0.293702[/C][/ROW]
[ROW][C]76[/C][C]8[/C][C]9.68751[/C][C]-1.68751[/C][/ROW]
[ROW][C]77[/C][C]9[/C][C]10.4274[/C][C]-1.42737[/C][/ROW]
[ROW][C]78[/C][C]7[/C][C]9.79408[/C][C]-2.79408[/C][/ROW]
[ROW][C]79[/C][C]11[/C][C]9.7129[/C][C]1.2871[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]10.4139[/C][C]2.58611[/C][/ROW]
[ROW][C]81[/C][C]12[/C][C]8.847[/C][C]3.153[/C][/ROW]
[ROW][C]82[/C][C]12[/C][C]10.5212[/C][C]1.4788[/C][/ROW]
[ROW][C]83[/C][C]11[/C][C]9.8506[/C][C]1.1494[/C][/ROW]
[ROW][C]84[/C][C]6[/C][C]10.1381[/C][C]-4.13806[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]9.22134[/C][C]0.778661[/C][/ROW]
[ROW][C]86[/C][C]5[/C][C]9.79408[/C][C]-4.79408[/C][/ROW]
[ROW][C]87[/C][C]8[/C][C]9.26947[/C][C]-1.26947[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]10.8212[/C][C]2.1788[/C][/ROW]
[ROW][C]89[/C][C]18[/C][C]9.28446[/C][C]8.71554[/C][/ROW]
[ROW][C]90[/C][C]15[/C][C]10.5589[/C][C]4.44107[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]10.4533[/C][C]2.54674[/C][/ROW]
[ROW][C]92[/C][C]7[/C][C]8.47266[/C][C]-1.47266[/C][/ROW]
[ROW][C]93[/C][C]9[/C][C]10.3223[/C][C]-1.32226[/C][/ROW]
[ROW][C]94[/C][C]9[/C][C]10.5665[/C][C]-1.5665[/C][/ROW]
[ROW][C]95[/C][C]7[/C][C]8.88252[/C][C]-1.88252[/C][/ROW]
[ROW][C]96[/C][C]13[/C][C]10.19[/C][C]2.81005[/C][/ROW]
[ROW][C]97[/C][C]6[/C][C]9.39055[/C][C]-3.39055[/C][/ROW]
[ROW][C]98[/C][C]7[/C][C]9.28446[/C][C]-2.28446[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]9.25665[/C][C]5.74335[/C][/ROW]
[ROW][C]100[/C][C]11[/C][C]10.5159[/C][C]0.484118[/C][/ROW]
[ROW][C]101[/C][C]11[/C][C]10.2858[/C][C]0.714158[/C][/ROW]
[ROW][C]102[/C][C]7[/C][C]10.3815[/C][C]-3.38153[/C][/ROW]
[ROW][C]103[/C][C]8[/C][C]10.4139[/C][C]-2.41389[/C][/ROW]
[ROW][C]104[/C][C]7[/C][C]10.1053[/C][C]-3.10529[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]10.3184[/C][C]2.68159[/C][/ROW]
[ROW][C]106[/C][C]9[/C][C]9.69391[/C][C]-0.69391[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]10.7281[/C][C]4.27186[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]9.97684[/C][C]0.023162[/C][/ROW]
[ROW][C]109[/C][C]11[/C][C]9.56291[/C][C]1.43709[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]9.04265[/C][C]5.95735[/C][/ROW]
[ROW][C]111[/C][C]8[/C][C]10.0206[/C][C]-2.02062[/C][/ROW]
[ROW][C]112[/C][C]9[/C][C]9.91717[/C][C]-0.917165[/C][/ROW]
[ROW][C]113[/C][C]8[/C][C]9.27519[/C][C]-1.27519[/C][/ROW]
[ROW][C]114[/C][C]19[/C][C]10.8212[/C][C]8.1788[/C][/ROW]
[ROW][C]115[/C][C]8[/C][C]10.0596[/C][C]-2.05963[/C][/ROW]
[ROW][C]116[/C][C]10[/C][C]10.2503[/C][C]-0.250325[/C][/ROW]
[ROW][C]117[/C][C]15[/C][C]10.1053[/C][C]4.89471[/C][/ROW]
[ROW][C]118[/C][C]8[/C][C]9.63507[/C][C]-1.63507[/C][/ROW]
[ROW][C]119[/C][C]7[/C][C]9.3213[/C][C]-2.3213[/C][/ROW]
[ROW][C]120[/C][C]15[/C][C]10.6622[/C][C]4.33781[/C][/ROW]
[ROW][C]121[/C][C]9[/C][C]10.2947[/C][C]-1.29466[/C][/ROW]
[ROW][C]122[/C][C]8[/C][C]9.34077[/C][C]-1.34077[/C][/ROW]
[ROW][C]123[/C][C]11[/C][C]10.4419[/C][C]0.558099[/C][/ROW]
[ROW][C]124[/C][C]9[/C][C]10.1358[/C][C]-1.13585[/C][/ROW]
[ROW][C]125[/C][C]11[/C][C]9.42808[/C][C]1.57192[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]9.81658[/C][C]0.183415[/C][/ROW]
[ROW][C]127[/C][C]8[/C][C]9.90448[/C][C]-1.90448[/C][/ROW]
[ROW][C]128[/C][C]7[/C][C]10.0698[/C][C]-3.06977[/C][/ROW]
[ROW][C]129[/C][C]8[/C][C]8.97324[/C][C]-0.973245[/C][/ROW]
[ROW][C]130[/C][C]9[/C][C]10.0725[/C][C]-1.07252[/C][/ROW]
[ROW][C]131[/C][C]11[/C][C]9.6025[/C][C]1.3975[/C][/ROW]
[ROW][C]132[/C][C]12[/C][C]10.2138[/C][C]1.7862[/C][/ROW]
[ROW][C]133[/C][C]14[/C][C]9.47218[/C][C]4.52782[/C][/ROW]
[ROW][C]134[/C][C]10[/C][C]9.41478[/C][C]0.585221[/C][/ROW]
[ROW][C]135[/C][C]10[/C][C]9.78912[/C][C]0.210884[/C][/ROW]
[ROW][C]136[/C][C]9[/C][C]10.2225[/C][C]-1.22252[/C][/ROW]
[ROW][C]137[/C][C]12[/C][C]10.1152[/C][C]1.88481[/C][/ROW]
[ROW][C]138[/C][C]5[/C][C]9.49568[/C][C]-4.49568[/C][/ROW]
[ROW][C]139[/C][C]14[/C][C]9.58465[/C][C]4.41535[/C][/ROW]
[ROW][C]140[/C][C]14[/C][C]10.2197[/C][C]3.7803[/C][/ROW]
[ROW][C]141[/C][C]13[/C][C]9.41719[/C][C]3.58281[/C][/ROW]
[ROW][C]142[/C][C]17[/C][C]10.2553[/C][C]6.74471[/C][/ROW]
[ROW][C]143[/C][C]11[/C][C]10.1632[/C][C]0.83675[/C][/ROW]
[ROW][C]144[/C][C]8[/C][C]10.3788[/C][C]-2.37878[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]9.57194[/C][C]0.428056[/C][/ROW]
[ROW][C]146[/C][C]5[/C][C]10.1504[/C][C]-5.15036[/C][/ROW]
[ROW][C]147[/C][C]6[/C][C]9.15203[/C][C]-3.15203[/C][/ROW]
[ROW][C]148[/C][C]5[/C][C]9.68915[/C][C]-4.68915[/C][/ROW]
[ROW][C]149[/C][C]10[/C][C]10.2424[/C][C]-0.242395[/C][/ROW]
[ROW][C]150[/C][C]9[/C][C]9.13226[/C][C]-0.132256[/C][/ROW]
[ROW][C]151[/C][C]10[/C][C]9.71511[/C][C]0.284888[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]10.5991[/C][C]-1.59907[/C][/ROW]
[ROW][C]153[/C][C]8[/C][C]9.73481[/C][C]-1.73481[/C][/ROW]
[ROW][C]154[/C][C]7[/C][C]10.0381[/C][C]-3.0381[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]9.94648[/C][C]3.05352[/C][/ROW]
[ROW][C]156[/C][C]11[/C][C]9.81375[/C][C]1.18625[/C][/ROW]
[ROW][C]157[/C][C]11[/C][C]9.28446[/C][C]1.71554[/C][/ROW]
[ROW][C]158[/C][C]11[/C][C]10.9064[/C][C]0.093599[/C][/ROW]
[ROW][C]159[/C][C]12[/C][C]9.94648[/C][C]2.05352[/C][/ROW]
[ROW][C]160[/C][C]11[/C][C]9.24104[/C][C]1.75896[/C][/ROW]
[ROW][C]161[/C][C]10[/C][C]10.51[/C][C]-0.509983[/C][/ROW]
[ROW][C]162[/C][C]9[/C][C]8.77507[/C][C]0.224935[/C][/ROW]
[ROW][C]163[/C][C]13[/C][C]10.2465[/C][C]2.75353[/C][/ROW]
[ROW][C]164[/C][C]10[/C][C]10.6185[/C][C]-0.618486[/C][/ROW]
[ROW][C]165[/C][C]7[/C][C]9.51563[/C][C]-2.51563[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]10.04[/C][C]-0.0399595[/C][/ROW]
[ROW][C]167[/C][C]11[/C][C]10.0526[/C][C]0.947427[/C][/ROW]
[ROW][C]168[/C][C]14[/C][C]9.31481[/C][C]4.68519[/C][/ROW]
[ROW][C]169[/C][C]10[/C][C]10.7884[/C][C]-0.78843[/C][/ROW]
[ROW][C]170[/C][C]12[/C][C]9.7131[/C][C]2.2869[/C][/ROW]
[ROW][C]171[/C][C]13[/C][C]9.18857[/C][C]3.81143[/C][/ROW]
[ROW][C]172[/C][C]8[/C][C]10.2396[/C][C]-2.23965[/C][/ROW]
[ROW][C]173[/C][C]8[/C][C]9.10577[/C][C]-1.10577[/C][/ROW]
[ROW][C]174[/C][C]8[/C][C]9.49979[/C][C]-1.49979[/C][/ROW]
[ROW][C]175[/C][C]11[/C][C]9.93999[/C][C]1.06001[/C][/ROW]
[ROW][C]176[/C][C]11[/C][C]10.1881[/C][C]0.811912[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]10.4113[/C][C]-1.41134[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]9.34077[/C][C]2.65923[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]10.9734[/C][C]-3.9734[/C][/ROW]
[ROW][C]180[/C][C]7[/C][C]9.77413[/C][C]-2.77413[/C][/ROW]
[ROW][C]181[/C][C]9[/C][C]9.64998[/C][C]-0.649983[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]9.98042[/C][C]1.01958[/C][/ROW]
[ROW][C]183[/C][C]8[/C][C]9.68255[/C][C]-1.68255[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]9.8508[/C][C]0.149201[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]8.83365[/C][C]-1.83365[/C][/ROW]
[ROW][C]186[/C][C]6[/C][C]11.3064[/C][C]-5.30636[/C][/ROW]
[ROW][C]187[/C][C]8[/C][C]10.1632[/C][C]-2.16325[/C][/ROW]
[ROW][C]188[/C][C]11[/C][C]10.1053[/C][C]0.894708[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]10.3184[/C][C]0.681593[/C][/ROW]
[ROW][C]190[/C][C]13[/C][C]9.93724[/C][C]3.06276[/C][/ROW]
[ROW][C]191[/C][C]13[/C][C]10.1922[/C][C]2.80784[/C][/ROW]
[ROW][C]192[/C][C]11[/C][C]9.40364[/C][C]1.59636[/C][/ROW]
[ROW][C]193[/C][C]7[/C][C]10.3901[/C][C]-3.39014[/C][/ROW]
[ROW][C]194[/C][C]7[/C][C]9.3211[/C][C]-2.3211[/C][/ROW]
[ROW][C]195[/C][C]10[/C][C]9.38939[/C][C]0.610614[/C][/ROW]
[ROW][C]196[/C][C]8[/C][C]10.764[/C][C]-2.76398[/C][/ROW]
[ROW][C]197[/C][C]8[/C][C]9.84136[/C][C]-1.84136[/C][/ROW]
[ROW][C]198[/C][C]9[/C][C]9.89787[/C][C]-0.897873[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]10.0153[/C][C]-1.0153[/C][/ROW]
[ROW][C]200[/C][C]17[/C][C]10.3353[/C][C]6.66467[/C][/ROW]
[ROW][C]201[/C][C]11[/C][C]9.66562[/C][C]1.33438[/C][/ROW]
[ROW][C]202[/C][C]11[/C][C]9.34077[/C][C]1.65923[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]9.46702[/C][C]1.53298[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]9.64381[/C][C]2.35619[/C][/ROW]
[ROW][C]205[/C][C]10[/C][C]9.32218[/C][C]0.67782[/C][/ROW]
[ROW][C]206[/C][C]8[/C][C]9.88997[/C][C]-1.88997[/C][/ROW]
[ROW][C]207[/C][C]6[/C][C]8.75111[/C][C]-2.75111[/C][/ROW]
[ROW][C]208[/C][C]10[/C][C]9.15822[/C][C]0.841783[/C][/ROW]
[ROW][C]209[/C][C]10[/C][C]9.48011[/C][C]0.519888[/C][/ROW]
[ROW][C]210[/C][C]4[/C][C]9.811[/C][C]-5.811[/C][/ROW]
[ROW][C]211[/C][C]10[/C][C]10.2591[/C][C]-0.259139[/C][/ROW]
[ROW][C]212[/C][C]7[/C][C]9.19237[/C][C]-2.19237[/C][/ROW]
[ROW][C]213[/C][C]12[/C][C]9.66783[/C][C]2.33217[/C][/ROW]
[ROW][C]214[/C][C]7[/C][C]9.68255[/C][C]-2.68255[/C][/ROW]
[ROW][C]215[/C][C]12[/C][C]9.70604[/C][C]2.29396[/C][/ROW]
[ROW][C]216[/C][C]9[/C][C]10.0422[/C][C]-1.04217[/C][/ROW]
[ROW][C]217[/C][C]10[/C][C]9.18857[/C][C]0.81143[/C][/ROW]
[ROW][C]218[/C][C]11[/C][C]10.0334[/C][C]0.966644[/C][/ROW]
[ROW][C]219[/C][C]12[/C][C]9.44734[/C][C]2.55266[/C][/ROW]
[ROW][C]220[/C][C]12[/C][C]10.7165[/C][C]1.28351[/C][/ROW]
[ROW][C]221[/C][C]2[/C][C]9.80144[/C][C]-7.80144[/C][/ROW]
[ROW][C]222[/C][C]9[/C][C]10.1354[/C][C]-1.13544[/C][/ROW]
[ROW][C]223[/C][C]9[/C][C]9.53034[/C][C]-0.530343[/C][/ROW]
[ROW][C]224[/C][C]4[/C][C]9.69323[/C][C]-5.69323[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.9553[/C][C]-0.955299[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]9.74842[/C][C]-1.74842[/C][/ROW]
[ROW][C]227[/C][C]7[/C][C]8.43964[/C][C]-1.43964[/C][/ROW]
[ROW][C]228[/C][C]10[/C][C]9.4041[/C][C]0.5959[/C][/ROW]
[ROW][C]229[/C][C]14[/C][C]10.3708[/C][C]3.62915[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]10.1358[/C][C]0.864151[/C][/ROW]
[ROW][C]231[/C][C]8[/C][C]10.27[/C][C]-2.27[/C][/ROW]
[ROW][C]232[/C][C]8[/C][C]10.0698[/C][C]-2.06977[/C][/ROW]
[ROW][C]233[/C][C]13[/C][C]10.0924[/C][C]2.90764[/C][/ROW]
[ROW][C]234[/C][C]6[/C][C]9.59568[/C][C]-3.59568[/C][/ROW]
[ROW][C]235[/C][C]10[/C][C]9.7129[/C][C]0.287099[/C][/ROW]
[ROW][C]236[/C][C]9[/C][C]9.84543[/C][C]-0.845431[/C][/ROW]
[ROW][C]237[/C][C]11[/C][C]9.62603[/C][C]1.37397[/C][/ROW]
[ROW][C]238[/C][C]8[/C][C]9.50495[/C][C]-1.50495[/C][/ROW]
[ROW][C]239[/C][C]6[/C][C]9.62603[/C][C]-3.62603[/C][/ROW]
[ROW][C]240[/C][C]9[/C][C]10.434[/C][C]-1.43397[/C][/ROW]
[ROW][C]241[/C][C]8[/C][C]9.76942[/C][C]-1.76942[/C][/ROW]
[ROW][C]242[/C][C]11[/C][C]10.3837[/C][C]0.616333[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]9.43941[/C][C]0.560586[/C][/ROW]
[ROW][C]244[/C][C]7[/C][C]9.41699[/C][C]-2.41699[/C][/ROW]
[ROW][C]245[/C][C]7[/C][C]10.3028[/C][C]-3.30277[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]9.35662[/C][C]-1.35662[/C][/ROW]
[ROW][C]247[/C][C]7[/C][C]9.00876[/C][C]-2.00876[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]9.61701[/C][C]0.382987[/C][/ROW]
[ROW][C]249[/C][C]9[/C][C]10.9474[/C][C]-1.94744[/C][/ROW]
[ROW][C]250[/C][C]13[/C][C]10.6402[/C][C]2.35977[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]9.1017[/C][C]1.8983[/C][/ROW]
[ROW][C]252[/C][C]6[/C][C]9.90669[/C][C]-3.90669[/C][/ROW]
[ROW][C]253[/C][C]8[/C][C]9.04044[/C][C]-1.04044[/C][/ROW]
[ROW][C]254[/C][C]8[/C][C]10.1988[/C][C]-2.19877[/C][/ROW]
[ROW][C]255[/C][C]7[/C][C]10.5247[/C][C]-3.5247[/C][/ROW]
[ROW][C]256[/C][C]11[/C][C]9.64187[/C][C]1.35813[/C][/ROW]
[ROW][C]257[/C][C]10[/C][C]9.68255[/C][C]0.317452[/C][/ROW]
[ROW][C]258[/C][C]8[/C][C]9.97684[/C][C]-1.97684[/C][/ROW]
[ROW][C]259[/C][C]7[/C][C]9.84652[/C][C]-2.84652[/C][/ROW]
[ROW][C]260[/C][C]7[/C][C]10.595[/C][C]-3.59499[/C][/ROW]
[ROW][C]261[/C][C]9[/C][C]10.4143[/C][C]-1.4143[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]9.95309[/C][C]1.04691[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]9.8627[/C][C]1.1373[/C][/ROW]
[ROW][C]264[/C][C]11[/C][C]9.60635[/C][C]1.39365[/C][/ROW]
[ROW][C]265[/C][C]10[/C][C]9.71807[/C][C]0.281935[/C][/ROW]
[ROW][C]266[/C][C]10[/C][C]9.38422[/C][C]0.615778[/C][/ROW]
[ROW][C]267[/C][C]10[/C][C]10.1358[/C][C]-0.135849[/C][/ROW]
[ROW][C]268[/C][C]8[/C][C]9.41808[/C][C]-1.41808[/C][/ROW]
[ROW][C]269[/C][C]11[/C][C]10.04[/C][C]0.96004[/C][/ROW]
[ROW][C]270[/C][C]8[/C][C]9.82685[/C][C]-1.82685[/C][/ROW]
[ROW][C]271[/C][C]4[/C][C]10.4055[/C][C]-6.40548[/C][/ROW]
[ROW][C]272[/C][C]6[/C][C]9.57875[/C][C]-3.57875[/C][/ROW]
[ROW][C]273[/C][C]11[/C][C]9.66135[/C][C]1.33865[/C][/ROW]
[ROW][C]274[/C][C]7[/C][C]9.59306[/C][C]-2.59306[/C][/ROW]
[ROW][C]275[/C][C]6[/C][C]9.97684[/C][C]-3.97684[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232447&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232447&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11110.32060.679382
21310.09652.90352
379.15822-2.15822
4109.434450.565547
51010.2157-0.215692
659.15601-4.15601
7710.6056-3.6056
8910.1922-1.19216
9149.73814.2619
1089.23691-1.23691
111410.59913.40093
121110.50340.49662
1399.40721-0.40721
14129.617212.38279
151610.41655.58349
16109.40410.5959
1789.7129-1.7129
1899.8572-0.857198
1979.10907-2.10907
20139.619433.38057
211010.5915-0.591497
22129.745212.25479
231010.7933-0.793274
2439.57215-6.57215
2589.71982-1.71982
26159.381735.61827
27139.867063.13294
2899.33856-0.338563
291210.09651.90352
30129.756352.24365
31910.2878-1.28785
3299.73096-0.730955
331010.1112-0.111192
3489.8377-1.8377
35810.1655-2.16546
3689.58961-1.58961
37129.105772.89423
3899.92633-0.92633
3989.82568-1.82568
401510.72554.27449
4199.73096-0.730955
4269.25149-3.25149
43139.551493.44851
44910.2792-1.27924
45129.806692.19331
461710.02416.97588
47138.910124.08988
48119.406851.59315
491010.4706-0.470611
50710.5009-3.50089
511410.02823.97181
52119.644081.35592
5398.857680.14232
54810.2722-2.27221
551210.50341.49662
56139.018343.98166
5729.66783-7.66783
58189.682558.31745
59119.85721.1428
60109.591820.408178
611310.56652.4335
6269.47218-3.47218
6389.46702-1.46702
641210.35121.64882
65129.68532.3147
66149.502544.49746
6789.31502-1.31502
6878.87735-1.87735
691010.4143-0.414297
70109.932930.0670667
711410.01843.98158
721610.37495.62507
731410.22273.77728
74610.1846-4.1846
75109.70630.293702
7689.68751-1.68751
77910.4274-1.42737
7879.79408-2.79408
79119.71291.2871
801310.41392.58611
81128.8473.153
821210.52121.4788
83119.85061.1494
84610.1381-4.13806
85109.221340.778661
8659.79408-4.79408
8789.26947-1.26947
881310.82122.1788
89189.284468.71554
901510.55894.44107
911310.45332.54674
9278.47266-1.47266
93910.3223-1.32226
94910.5665-1.5665
9578.88252-1.88252
961310.192.81005
9769.39055-3.39055
9879.28446-2.28446
99159.256655.74335
1001110.51590.484118
1011110.28580.714158
102710.3815-3.38153
103810.4139-2.41389
104710.1053-3.10529
1051310.31842.68159
10699.69391-0.69391
1071510.72814.27186
108109.976840.023162
109119.562911.43709
110159.042655.95735
111810.0206-2.02062
11299.91717-0.917165
11389.27519-1.27519
1141910.82128.1788
115810.0596-2.05963
1161010.2503-0.250325
1171510.10534.89471
11889.63507-1.63507
11979.3213-2.3213
1201510.66224.33781
121910.2947-1.29466
12289.34077-1.34077
1231110.44190.558099
124910.1358-1.13585
125119.428081.57192
126109.816580.183415
12789.90448-1.90448
128710.0698-3.06977
12988.97324-0.973245
130910.0725-1.07252
131119.60251.3975
1321210.21381.7862
133149.472184.52782
134109.414780.585221
135109.789120.210884
136910.2225-1.22252
1371210.11521.88481
13859.49568-4.49568
139149.584654.41535
1401410.21973.7803
141139.417193.58281
1421710.25536.74471
1431110.16320.83675
144810.3788-2.37878
145109.571940.428056
146510.1504-5.15036
14769.15203-3.15203
14859.68915-4.68915
1491010.2424-0.242395
15099.13226-0.132256
151109.715110.284888
152910.5991-1.59907
15389.73481-1.73481
154710.0381-3.0381
155139.946483.05352
156119.813751.18625
157119.284461.71554
1581110.90640.093599
159129.946482.05352
160119.241041.75896
1611010.51-0.509983
16298.775070.224935
1631310.24652.75353
1641010.6185-0.618486
16579.51563-2.51563
1661010.04-0.0399595
1671110.05260.947427
168149.314814.68519
1691010.7884-0.78843
170129.71312.2869
171139.188573.81143
172810.2396-2.23965
17389.10577-1.10577
17489.49979-1.49979
175119.939991.06001
1761110.18810.811912
177910.4113-1.41134
178129.340772.65923
179710.9734-3.9734
18079.77413-2.77413
18199.64998-0.649983
182119.980421.01958
18389.68255-1.68255
184109.85080.149201
18578.83365-1.83365
186611.3064-5.30636
187810.1632-2.16325
1881110.10530.894708
1891110.31840.681593
190139.937243.06276
1911310.19222.80784
192119.403641.59636
193710.3901-3.39014
19479.3211-2.3211
195109.389390.610614
196810.764-2.76398
19789.84136-1.84136
19899.89787-0.897873
199910.0153-1.0153
2001710.33536.66467
201119.665621.33438
202119.340771.65923
203119.467021.53298
204129.643812.35619
205109.322180.67782
20689.88997-1.88997
20768.75111-2.75111
208109.158220.841783
209109.480110.519888
21049.811-5.811
2111010.2591-0.259139
21279.19237-2.19237
213129.667832.33217
21479.68255-2.68255
215129.706042.29396
216910.0422-1.04217
217109.188570.81143
2181110.03340.966644
219129.447342.55266
2201210.71651.28351
22129.80144-7.80144
222910.1354-1.13544
22399.53034-0.530343
22449.69323-5.69323
22599.9553-0.955299
22689.74842-1.74842
22778.43964-1.43964
228109.40410.5959
2291410.37083.62915
2301110.13580.864151
231810.27-2.27
232810.0698-2.06977
2331310.09242.90764
23469.59568-3.59568
235109.71290.287099
23699.84543-0.845431
237119.626031.37397
23889.50495-1.50495
23969.62603-3.62603
240910.434-1.43397
24189.76942-1.76942
2421110.38370.616333
243109.439410.560586
24479.41699-2.41699
245710.3028-3.30277
24689.35662-1.35662
24779.00876-2.00876
248109.617010.382987
249910.9474-1.94744
2501310.64022.35977
251119.10171.8983
25269.90669-3.90669
25389.04044-1.04044
254810.1988-2.19877
255710.5247-3.5247
256119.641871.35813
257109.682550.317452
25889.97684-1.97684
25979.84652-2.84652
260710.595-3.59499
261910.4143-1.4143
262119.953091.04691
263119.86271.1373
264119.606351.39365
265109.718070.281935
266109.384220.615778
2671010.1358-0.135849
26889.41808-1.41808
2691110.040.96004
27089.82685-1.82685
271410.4055-6.40548
27269.57875-3.57875
273119.661351.33865
27479.59306-2.59306
27569.97684-3.97684







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.5678190.8643620.432181
130.3981980.7963970.601802
140.2643210.5286420.735679
150.6490430.7019150.350957
160.5374020.9251950.462598
170.4286930.8573850.571307
180.3320210.6640430.667979
190.3725330.7450670.627467
200.3759380.7518770.624062
210.3397670.6795330.660233
220.352510.7050190.64749
230.2785490.5570970.721451
240.6232250.753550.376775
250.5529880.8940230.447012
260.7162840.5674320.283716
270.6771140.6457710.322886
280.6138880.7722230.386112
290.5561810.8876390.443819
300.4946050.9892110.505395
310.4393140.8786290.560686
320.3882840.7765690.611716
330.414950.82990.58505
340.3586280.7172570.641372
350.4424380.8848770.557562
360.387610.7752190.61239
370.376980.753960.62302
380.3414890.6829790.658511
390.4218210.8436430.578179
400.4412780.8825560.558722
410.3883610.7767220.611639
420.3613560.7227130.638644
430.5028960.9942070.497104
440.4646590.9293180.535341
450.4486750.897350.551325
460.6027420.7945170.397258
470.6552590.6894830.344741
480.6320710.7358590.367929
490.5941580.8116850.405842
500.6168080.7663840.383192
510.6204590.7590830.379541
520.5824950.835010.417505
530.5393490.9213030.460651
540.5603550.8792890.439645
550.5223710.9552590.477629
560.6231390.7537220.376861
570.8404430.3191140.159557
580.9462390.1075230.0537615
590.934880.130240.06512
600.9206660.1586690.0793343
610.9124410.1751170.0875586
620.9172540.1654920.0827462
630.9111690.1776610.0888306
640.8964390.2071210.103561
650.8900260.2199470.109974
660.9112480.1775040.0887521
670.902370.1952590.0976296
680.897140.205720.10286
690.8797970.2404060.120203
700.8580330.2839340.141967
710.870720.258560.12928
720.9136030.1727940.0863972
730.9174470.1651060.0825529
740.9350770.1298450.0649226
750.9221780.1556440.0778222
760.911450.17710.08855
770.9001490.1997020.0998511
780.9019370.1961250.0980627
790.8860310.2279390.113969
800.8797520.2404960.120248
810.8836910.2326170.116309
820.8670170.2659650.132983
830.8487770.3024470.151223
840.8718950.2562090.128105
850.8518460.2963080.148154
860.890180.2196410.10982
870.8735980.2528050.126402
880.8602870.2794260.139713
890.9623350.07532950.0376647
900.9699890.0600220.030011
910.9670520.06589580.0329479
920.961350.07730040.0386502
930.9616390.07672250.0383613
940.9573310.08533810.042669
950.9514510.09709780.0485489
960.9492430.1015140.0507572
970.9549780.09004360.0450218
980.9534980.0930030.0465015
990.9749430.05011310.0250565
1000.9705750.05885060.0294253
1010.9644240.0711510.0355755
1020.9695140.06097220.0304861
1030.968560.06287960.0314398
1040.970170.05966080.0298304
1050.9689150.06217050.0310853
1060.9624250.07514970.0375749
1070.9700040.05999140.0299957
1080.9633710.07325860.0366293
1090.9572270.08554520.0427726
1100.9778020.04439630.0221981
1110.9766190.04676120.0233806
1120.9724190.05516180.0275809
1130.967490.06501950.0325097
1140.9930330.01393320.00696661
1150.9924470.0151050.00755252
1160.990750.01849910.00924955
1170.9943660.01126870.00563437
1180.9933340.01333210.00666604
1190.9927580.01448460.00724229
1200.9951020.009795840.00489792
1210.9942310.01153820.00576912
1220.993240.01352080.00676041
1230.9918930.0162140.00810699
1240.990090.01981990.00990993
1250.988880.02223980.0111199
1260.9860510.02789820.0139491
1270.9853440.02931130.0146556
1280.9862810.02743890.0137194
1290.9834660.03306780.0165339
1300.9802550.03948990.019745
1310.9771120.04577510.0228876
1320.9746620.05067560.0253378
1330.9819040.03619120.0180956
1340.9778350.04433050.0221653
1350.9728660.05426860.0271343
1360.9682450.06350980.0317549
1370.9652350.06953010.034765
1380.97430.05139990.0256999
1390.9809570.0380850.0190425
1400.9837410.03251740.0162587
1410.9860440.02791130.0139557
1420.9965510.006898310.00344916
1430.9959280.008144850.00407242
1440.9956720.008655040.00432752
1450.9945170.01096550.00548277
1460.9971910.005617680.00280884
1470.997480.005040640.00252032
1480.9985740.002852680.00142634
1490.9981240.003752110.00187605
1500.9975190.004962230.00248111
1510.9968020.006395770.00319788
1520.9961240.00775280.0038764
1530.9953750.009249730.00462487
1540.9956210.008758140.00437907
1550.9963070.007386850.00369343
1560.9954820.009036360.00451818
1570.9946850.01063080.00531538
1580.9934780.01304320.00652159
1590.9933930.01321350.00660673
1600.9924770.01504530.00752264
1610.9905270.01894520.0094726
1620.9879970.0240070.0120035
1630.9901240.01975220.00987611
1640.9875460.02490870.0124543
1650.9865450.02691080.0134554
1660.9833580.03328460.0166423
1670.9799260.04014750.0200738
1680.9873220.02535570.0126779
1690.9843460.0313070.0156535
1700.9845450.03090970.0154549
1710.9884520.0230950.0115475
1720.9869990.02600280.0130014
1730.9838640.03227290.0161364
1740.980760.03847930.0192396
1750.9775220.04495650.0224783
1760.9735310.05293820.0264691
1770.9683040.06339290.0316965
1780.970270.05946050.0297302
1790.973620.05276010.0263801
1800.9749720.05005590.025028
1810.9694070.06118690.0305934
1820.9626760.07464780.0373239
1830.9562260.0875480.043774
1840.9480940.1038120.0519059
1850.9475610.1048770.0524387
1860.9624310.07513710.0375686
1870.9575310.08493860.0424693
1880.9505750.09885080.0494254
1890.9432180.1135640.056782
1900.9512040.09759290.0487965
1910.9587770.08244540.0412227
1920.9506060.09878720.0493936
1930.9556860.08862710.0443135
1940.9502540.09949150.0497457
1950.9415860.1168290.0584143
1960.935580.1288390.0644196
1970.9258220.1483550.0741776
1980.9110260.1779480.0889741
1990.8947640.2104730.105236
2000.9767220.04655570.0232779
2010.9748080.0503850.0251925
2020.9750560.0498870.0249435
2030.975170.04966080.0248304
2040.9715130.05697420.0284871
2050.9670080.06598320.0329916
2060.9612840.0774320.038716
2070.9560990.08780210.0439011
2080.9503920.09921570.0496079
2090.9415770.1168460.058423
2100.9664980.06700340.0335017
2110.957830.08433950.0421698
2120.955270.08946040.0447302
2130.9609110.07817810.039089
2140.9550550.08988930.0449446
2150.9490330.1019350.0509674
2160.9362910.1274170.0637086
2170.9278530.1442940.0721472
2180.9299380.1401230.0700617
2190.9478540.1042930.0521463
2200.9615650.07687040.0384352
2210.9927230.01455330.00727663
2220.9907850.01842990.00921497
2230.9874760.0250490.0125245
2240.9935550.01289030.00644514
2250.9908690.01826260.0091313
2260.9876120.0247760.012388
2270.992160.01568070.00784033
2280.990850.01830070.00915036
2290.9988130.002374510.00118726
2300.9988150.002370290.00118515
2310.9982150.003569810.00178491
2320.9972720.00545550.00272775
2330.9966670.006666630.00333331
2340.996820.00636010.00318005
2350.9960520.007896080.00394804
2360.9946240.01075210.00537603
2370.9946530.01069320.0053466
2380.9919010.01619750.00809875
2390.9929930.01401350.00700676
2400.990320.01935990.00967996
2410.9868460.02630820.0131541
2420.9817840.03643220.0182161
2430.9819180.03616380.0180819
2440.9804480.03910470.0195524
2450.9721410.05571740.0278587
2460.9586390.08272240.0413612
2470.953490.093020.04651
2480.938450.1230990.0615497
2490.9150850.169830.0849151
2500.8812380.2375240.118762
2510.842710.314580.15729
2520.8314630.3370730.168537
2530.7904790.4190420.209521
2540.72790.5441990.2721
2550.6750020.6499970.324998
2560.6023040.7953920.397696
2570.546880.906240.45312
2580.4461950.892390.553805
2590.3636770.7273540.636323
2600.4637190.9274380.536281
2610.3859350.771870.614065
2620.2616550.523310.738345
2630.1543770.3087550.845623

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.567819 & 0.864362 & 0.432181 \tabularnewline
13 & 0.398198 & 0.796397 & 0.601802 \tabularnewline
14 & 0.264321 & 0.528642 & 0.735679 \tabularnewline
15 & 0.649043 & 0.701915 & 0.350957 \tabularnewline
16 & 0.537402 & 0.925195 & 0.462598 \tabularnewline
17 & 0.428693 & 0.857385 & 0.571307 \tabularnewline
18 & 0.332021 & 0.664043 & 0.667979 \tabularnewline
19 & 0.372533 & 0.745067 & 0.627467 \tabularnewline
20 & 0.375938 & 0.751877 & 0.624062 \tabularnewline
21 & 0.339767 & 0.679533 & 0.660233 \tabularnewline
22 & 0.35251 & 0.705019 & 0.64749 \tabularnewline
23 & 0.278549 & 0.557097 & 0.721451 \tabularnewline
24 & 0.623225 & 0.75355 & 0.376775 \tabularnewline
25 & 0.552988 & 0.894023 & 0.447012 \tabularnewline
26 & 0.716284 & 0.567432 & 0.283716 \tabularnewline
27 & 0.677114 & 0.645771 & 0.322886 \tabularnewline
28 & 0.613888 & 0.772223 & 0.386112 \tabularnewline
29 & 0.556181 & 0.887639 & 0.443819 \tabularnewline
30 & 0.494605 & 0.989211 & 0.505395 \tabularnewline
31 & 0.439314 & 0.878629 & 0.560686 \tabularnewline
32 & 0.388284 & 0.776569 & 0.611716 \tabularnewline
33 & 0.41495 & 0.8299 & 0.58505 \tabularnewline
34 & 0.358628 & 0.717257 & 0.641372 \tabularnewline
35 & 0.442438 & 0.884877 & 0.557562 \tabularnewline
36 & 0.38761 & 0.775219 & 0.61239 \tabularnewline
37 & 0.37698 & 0.75396 & 0.62302 \tabularnewline
38 & 0.341489 & 0.682979 & 0.658511 \tabularnewline
39 & 0.421821 & 0.843643 & 0.578179 \tabularnewline
40 & 0.441278 & 0.882556 & 0.558722 \tabularnewline
41 & 0.388361 & 0.776722 & 0.611639 \tabularnewline
42 & 0.361356 & 0.722713 & 0.638644 \tabularnewline
43 & 0.502896 & 0.994207 & 0.497104 \tabularnewline
44 & 0.464659 & 0.929318 & 0.535341 \tabularnewline
45 & 0.448675 & 0.89735 & 0.551325 \tabularnewline
46 & 0.602742 & 0.794517 & 0.397258 \tabularnewline
47 & 0.655259 & 0.689483 & 0.344741 \tabularnewline
48 & 0.632071 & 0.735859 & 0.367929 \tabularnewline
49 & 0.594158 & 0.811685 & 0.405842 \tabularnewline
50 & 0.616808 & 0.766384 & 0.383192 \tabularnewline
51 & 0.620459 & 0.759083 & 0.379541 \tabularnewline
52 & 0.582495 & 0.83501 & 0.417505 \tabularnewline
53 & 0.539349 & 0.921303 & 0.460651 \tabularnewline
54 & 0.560355 & 0.879289 & 0.439645 \tabularnewline
55 & 0.522371 & 0.955259 & 0.477629 \tabularnewline
56 & 0.623139 & 0.753722 & 0.376861 \tabularnewline
57 & 0.840443 & 0.319114 & 0.159557 \tabularnewline
58 & 0.946239 & 0.107523 & 0.0537615 \tabularnewline
59 & 0.93488 & 0.13024 & 0.06512 \tabularnewline
60 & 0.920666 & 0.158669 & 0.0793343 \tabularnewline
61 & 0.912441 & 0.175117 & 0.0875586 \tabularnewline
62 & 0.917254 & 0.165492 & 0.0827462 \tabularnewline
63 & 0.911169 & 0.177661 & 0.0888306 \tabularnewline
64 & 0.896439 & 0.207121 & 0.103561 \tabularnewline
65 & 0.890026 & 0.219947 & 0.109974 \tabularnewline
66 & 0.911248 & 0.177504 & 0.0887521 \tabularnewline
67 & 0.90237 & 0.195259 & 0.0976296 \tabularnewline
68 & 0.89714 & 0.20572 & 0.10286 \tabularnewline
69 & 0.879797 & 0.240406 & 0.120203 \tabularnewline
70 & 0.858033 & 0.283934 & 0.141967 \tabularnewline
71 & 0.87072 & 0.25856 & 0.12928 \tabularnewline
72 & 0.913603 & 0.172794 & 0.0863972 \tabularnewline
73 & 0.917447 & 0.165106 & 0.0825529 \tabularnewline
74 & 0.935077 & 0.129845 & 0.0649226 \tabularnewline
75 & 0.922178 & 0.155644 & 0.0778222 \tabularnewline
76 & 0.91145 & 0.1771 & 0.08855 \tabularnewline
77 & 0.900149 & 0.199702 & 0.0998511 \tabularnewline
78 & 0.901937 & 0.196125 & 0.0980627 \tabularnewline
79 & 0.886031 & 0.227939 & 0.113969 \tabularnewline
80 & 0.879752 & 0.240496 & 0.120248 \tabularnewline
81 & 0.883691 & 0.232617 & 0.116309 \tabularnewline
82 & 0.867017 & 0.265965 & 0.132983 \tabularnewline
83 & 0.848777 & 0.302447 & 0.151223 \tabularnewline
84 & 0.871895 & 0.256209 & 0.128105 \tabularnewline
85 & 0.851846 & 0.296308 & 0.148154 \tabularnewline
86 & 0.89018 & 0.219641 & 0.10982 \tabularnewline
87 & 0.873598 & 0.252805 & 0.126402 \tabularnewline
88 & 0.860287 & 0.279426 & 0.139713 \tabularnewline
89 & 0.962335 & 0.0753295 & 0.0376647 \tabularnewline
90 & 0.969989 & 0.060022 & 0.030011 \tabularnewline
91 & 0.967052 & 0.0658958 & 0.0329479 \tabularnewline
92 & 0.96135 & 0.0773004 & 0.0386502 \tabularnewline
93 & 0.961639 & 0.0767225 & 0.0383613 \tabularnewline
94 & 0.957331 & 0.0853381 & 0.042669 \tabularnewline
95 & 0.951451 & 0.0970978 & 0.0485489 \tabularnewline
96 & 0.949243 & 0.101514 & 0.0507572 \tabularnewline
97 & 0.954978 & 0.0900436 & 0.0450218 \tabularnewline
98 & 0.953498 & 0.093003 & 0.0465015 \tabularnewline
99 & 0.974943 & 0.0501131 & 0.0250565 \tabularnewline
100 & 0.970575 & 0.0588506 & 0.0294253 \tabularnewline
101 & 0.964424 & 0.071151 & 0.0355755 \tabularnewline
102 & 0.969514 & 0.0609722 & 0.0304861 \tabularnewline
103 & 0.96856 & 0.0628796 & 0.0314398 \tabularnewline
104 & 0.97017 & 0.0596608 & 0.0298304 \tabularnewline
105 & 0.968915 & 0.0621705 & 0.0310853 \tabularnewline
106 & 0.962425 & 0.0751497 & 0.0375749 \tabularnewline
107 & 0.970004 & 0.0599914 & 0.0299957 \tabularnewline
108 & 0.963371 & 0.0732586 & 0.0366293 \tabularnewline
109 & 0.957227 & 0.0855452 & 0.0427726 \tabularnewline
110 & 0.977802 & 0.0443963 & 0.0221981 \tabularnewline
111 & 0.976619 & 0.0467612 & 0.0233806 \tabularnewline
112 & 0.972419 & 0.0551618 & 0.0275809 \tabularnewline
113 & 0.96749 & 0.0650195 & 0.0325097 \tabularnewline
114 & 0.993033 & 0.0139332 & 0.00696661 \tabularnewline
115 & 0.992447 & 0.015105 & 0.00755252 \tabularnewline
116 & 0.99075 & 0.0184991 & 0.00924955 \tabularnewline
117 & 0.994366 & 0.0112687 & 0.00563437 \tabularnewline
118 & 0.993334 & 0.0133321 & 0.00666604 \tabularnewline
119 & 0.992758 & 0.0144846 & 0.00724229 \tabularnewline
120 & 0.995102 & 0.00979584 & 0.00489792 \tabularnewline
121 & 0.994231 & 0.0115382 & 0.00576912 \tabularnewline
122 & 0.99324 & 0.0135208 & 0.00676041 \tabularnewline
123 & 0.991893 & 0.016214 & 0.00810699 \tabularnewline
124 & 0.99009 & 0.0198199 & 0.00990993 \tabularnewline
125 & 0.98888 & 0.0222398 & 0.0111199 \tabularnewline
126 & 0.986051 & 0.0278982 & 0.0139491 \tabularnewline
127 & 0.985344 & 0.0293113 & 0.0146556 \tabularnewline
128 & 0.986281 & 0.0274389 & 0.0137194 \tabularnewline
129 & 0.983466 & 0.0330678 & 0.0165339 \tabularnewline
130 & 0.980255 & 0.0394899 & 0.019745 \tabularnewline
131 & 0.977112 & 0.0457751 & 0.0228876 \tabularnewline
132 & 0.974662 & 0.0506756 & 0.0253378 \tabularnewline
133 & 0.981904 & 0.0361912 & 0.0180956 \tabularnewline
134 & 0.977835 & 0.0443305 & 0.0221653 \tabularnewline
135 & 0.972866 & 0.0542686 & 0.0271343 \tabularnewline
136 & 0.968245 & 0.0635098 & 0.0317549 \tabularnewline
137 & 0.965235 & 0.0695301 & 0.034765 \tabularnewline
138 & 0.9743 & 0.0513999 & 0.0256999 \tabularnewline
139 & 0.980957 & 0.038085 & 0.0190425 \tabularnewline
140 & 0.983741 & 0.0325174 & 0.0162587 \tabularnewline
141 & 0.986044 & 0.0279113 & 0.0139557 \tabularnewline
142 & 0.996551 & 0.00689831 & 0.00344916 \tabularnewline
143 & 0.995928 & 0.00814485 & 0.00407242 \tabularnewline
144 & 0.995672 & 0.00865504 & 0.00432752 \tabularnewline
145 & 0.994517 & 0.0109655 & 0.00548277 \tabularnewline
146 & 0.997191 & 0.00561768 & 0.00280884 \tabularnewline
147 & 0.99748 & 0.00504064 & 0.00252032 \tabularnewline
148 & 0.998574 & 0.00285268 & 0.00142634 \tabularnewline
149 & 0.998124 & 0.00375211 & 0.00187605 \tabularnewline
150 & 0.997519 & 0.00496223 & 0.00248111 \tabularnewline
151 & 0.996802 & 0.00639577 & 0.00319788 \tabularnewline
152 & 0.996124 & 0.0077528 & 0.0038764 \tabularnewline
153 & 0.995375 & 0.00924973 & 0.00462487 \tabularnewline
154 & 0.995621 & 0.00875814 & 0.00437907 \tabularnewline
155 & 0.996307 & 0.00738685 & 0.00369343 \tabularnewline
156 & 0.995482 & 0.00903636 & 0.00451818 \tabularnewline
157 & 0.994685 & 0.0106308 & 0.00531538 \tabularnewline
158 & 0.993478 & 0.0130432 & 0.00652159 \tabularnewline
159 & 0.993393 & 0.0132135 & 0.00660673 \tabularnewline
160 & 0.992477 & 0.0150453 & 0.00752264 \tabularnewline
161 & 0.990527 & 0.0189452 & 0.0094726 \tabularnewline
162 & 0.987997 & 0.024007 & 0.0120035 \tabularnewline
163 & 0.990124 & 0.0197522 & 0.00987611 \tabularnewline
164 & 0.987546 & 0.0249087 & 0.0124543 \tabularnewline
165 & 0.986545 & 0.0269108 & 0.0134554 \tabularnewline
166 & 0.983358 & 0.0332846 & 0.0166423 \tabularnewline
167 & 0.979926 & 0.0401475 & 0.0200738 \tabularnewline
168 & 0.987322 & 0.0253557 & 0.0126779 \tabularnewline
169 & 0.984346 & 0.031307 & 0.0156535 \tabularnewline
170 & 0.984545 & 0.0309097 & 0.0154549 \tabularnewline
171 & 0.988452 & 0.023095 & 0.0115475 \tabularnewline
172 & 0.986999 & 0.0260028 & 0.0130014 \tabularnewline
173 & 0.983864 & 0.0322729 & 0.0161364 \tabularnewline
174 & 0.98076 & 0.0384793 & 0.0192396 \tabularnewline
175 & 0.977522 & 0.0449565 & 0.0224783 \tabularnewline
176 & 0.973531 & 0.0529382 & 0.0264691 \tabularnewline
177 & 0.968304 & 0.0633929 & 0.0316965 \tabularnewline
178 & 0.97027 & 0.0594605 & 0.0297302 \tabularnewline
179 & 0.97362 & 0.0527601 & 0.0263801 \tabularnewline
180 & 0.974972 & 0.0500559 & 0.025028 \tabularnewline
181 & 0.969407 & 0.0611869 & 0.0305934 \tabularnewline
182 & 0.962676 & 0.0746478 & 0.0373239 \tabularnewline
183 & 0.956226 & 0.087548 & 0.043774 \tabularnewline
184 & 0.948094 & 0.103812 & 0.0519059 \tabularnewline
185 & 0.947561 & 0.104877 & 0.0524387 \tabularnewline
186 & 0.962431 & 0.0751371 & 0.0375686 \tabularnewline
187 & 0.957531 & 0.0849386 & 0.0424693 \tabularnewline
188 & 0.950575 & 0.0988508 & 0.0494254 \tabularnewline
189 & 0.943218 & 0.113564 & 0.056782 \tabularnewline
190 & 0.951204 & 0.0975929 & 0.0487965 \tabularnewline
191 & 0.958777 & 0.0824454 & 0.0412227 \tabularnewline
192 & 0.950606 & 0.0987872 & 0.0493936 \tabularnewline
193 & 0.955686 & 0.0886271 & 0.0443135 \tabularnewline
194 & 0.950254 & 0.0994915 & 0.0497457 \tabularnewline
195 & 0.941586 & 0.116829 & 0.0584143 \tabularnewline
196 & 0.93558 & 0.128839 & 0.0644196 \tabularnewline
197 & 0.925822 & 0.148355 & 0.0741776 \tabularnewline
198 & 0.911026 & 0.177948 & 0.0889741 \tabularnewline
199 & 0.894764 & 0.210473 & 0.105236 \tabularnewline
200 & 0.976722 & 0.0465557 & 0.0232779 \tabularnewline
201 & 0.974808 & 0.050385 & 0.0251925 \tabularnewline
202 & 0.975056 & 0.049887 & 0.0249435 \tabularnewline
203 & 0.97517 & 0.0496608 & 0.0248304 \tabularnewline
204 & 0.971513 & 0.0569742 & 0.0284871 \tabularnewline
205 & 0.967008 & 0.0659832 & 0.0329916 \tabularnewline
206 & 0.961284 & 0.077432 & 0.038716 \tabularnewline
207 & 0.956099 & 0.0878021 & 0.0439011 \tabularnewline
208 & 0.950392 & 0.0992157 & 0.0496079 \tabularnewline
209 & 0.941577 & 0.116846 & 0.058423 \tabularnewline
210 & 0.966498 & 0.0670034 & 0.0335017 \tabularnewline
211 & 0.95783 & 0.0843395 & 0.0421698 \tabularnewline
212 & 0.95527 & 0.0894604 & 0.0447302 \tabularnewline
213 & 0.960911 & 0.0781781 & 0.039089 \tabularnewline
214 & 0.955055 & 0.0898893 & 0.0449446 \tabularnewline
215 & 0.949033 & 0.101935 & 0.0509674 \tabularnewline
216 & 0.936291 & 0.127417 & 0.0637086 \tabularnewline
217 & 0.927853 & 0.144294 & 0.0721472 \tabularnewline
218 & 0.929938 & 0.140123 & 0.0700617 \tabularnewline
219 & 0.947854 & 0.104293 & 0.0521463 \tabularnewline
220 & 0.961565 & 0.0768704 & 0.0384352 \tabularnewline
221 & 0.992723 & 0.0145533 & 0.00727663 \tabularnewline
222 & 0.990785 & 0.0184299 & 0.00921497 \tabularnewline
223 & 0.987476 & 0.025049 & 0.0125245 \tabularnewline
224 & 0.993555 & 0.0128903 & 0.00644514 \tabularnewline
225 & 0.990869 & 0.0182626 & 0.0091313 \tabularnewline
226 & 0.987612 & 0.024776 & 0.012388 \tabularnewline
227 & 0.99216 & 0.0156807 & 0.00784033 \tabularnewline
228 & 0.99085 & 0.0183007 & 0.00915036 \tabularnewline
229 & 0.998813 & 0.00237451 & 0.00118726 \tabularnewline
230 & 0.998815 & 0.00237029 & 0.00118515 \tabularnewline
231 & 0.998215 & 0.00356981 & 0.00178491 \tabularnewline
232 & 0.997272 & 0.0054555 & 0.00272775 \tabularnewline
233 & 0.996667 & 0.00666663 & 0.00333331 \tabularnewline
234 & 0.99682 & 0.0063601 & 0.00318005 \tabularnewline
235 & 0.996052 & 0.00789608 & 0.00394804 \tabularnewline
236 & 0.994624 & 0.0107521 & 0.00537603 \tabularnewline
237 & 0.994653 & 0.0106932 & 0.0053466 \tabularnewline
238 & 0.991901 & 0.0161975 & 0.00809875 \tabularnewline
239 & 0.992993 & 0.0140135 & 0.00700676 \tabularnewline
240 & 0.99032 & 0.0193599 & 0.00967996 \tabularnewline
241 & 0.986846 & 0.0263082 & 0.0131541 \tabularnewline
242 & 0.981784 & 0.0364322 & 0.0182161 \tabularnewline
243 & 0.981918 & 0.0361638 & 0.0180819 \tabularnewline
244 & 0.980448 & 0.0391047 & 0.0195524 \tabularnewline
245 & 0.972141 & 0.0557174 & 0.0278587 \tabularnewline
246 & 0.958639 & 0.0827224 & 0.0413612 \tabularnewline
247 & 0.95349 & 0.09302 & 0.04651 \tabularnewline
248 & 0.93845 & 0.123099 & 0.0615497 \tabularnewline
249 & 0.915085 & 0.16983 & 0.0849151 \tabularnewline
250 & 0.881238 & 0.237524 & 0.118762 \tabularnewline
251 & 0.84271 & 0.31458 & 0.15729 \tabularnewline
252 & 0.831463 & 0.337073 & 0.168537 \tabularnewline
253 & 0.790479 & 0.419042 & 0.209521 \tabularnewline
254 & 0.7279 & 0.544199 & 0.2721 \tabularnewline
255 & 0.675002 & 0.649997 & 0.324998 \tabularnewline
256 & 0.602304 & 0.795392 & 0.397696 \tabularnewline
257 & 0.54688 & 0.90624 & 0.45312 \tabularnewline
258 & 0.446195 & 0.89239 & 0.553805 \tabularnewline
259 & 0.363677 & 0.727354 & 0.636323 \tabularnewline
260 & 0.463719 & 0.927438 & 0.536281 \tabularnewline
261 & 0.385935 & 0.77187 & 0.614065 \tabularnewline
262 & 0.261655 & 0.52331 & 0.738345 \tabularnewline
263 & 0.154377 & 0.308755 & 0.845623 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232447&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]12[/C][C]0.567819[/C][C]0.864362[/C][C]0.432181[/C][/ROW]
[ROW][C]13[/C][C]0.398198[/C][C]0.796397[/C][C]0.601802[/C][/ROW]
[ROW][C]14[/C][C]0.264321[/C][C]0.528642[/C][C]0.735679[/C][/ROW]
[ROW][C]15[/C][C]0.649043[/C][C]0.701915[/C][C]0.350957[/C][/ROW]
[ROW][C]16[/C][C]0.537402[/C][C]0.925195[/C][C]0.462598[/C][/ROW]
[ROW][C]17[/C][C]0.428693[/C][C]0.857385[/C][C]0.571307[/C][/ROW]
[ROW][C]18[/C][C]0.332021[/C][C]0.664043[/C][C]0.667979[/C][/ROW]
[ROW][C]19[/C][C]0.372533[/C][C]0.745067[/C][C]0.627467[/C][/ROW]
[ROW][C]20[/C][C]0.375938[/C][C]0.751877[/C][C]0.624062[/C][/ROW]
[ROW][C]21[/C][C]0.339767[/C][C]0.679533[/C][C]0.660233[/C][/ROW]
[ROW][C]22[/C][C]0.35251[/C][C]0.705019[/C][C]0.64749[/C][/ROW]
[ROW][C]23[/C][C]0.278549[/C][C]0.557097[/C][C]0.721451[/C][/ROW]
[ROW][C]24[/C][C]0.623225[/C][C]0.75355[/C][C]0.376775[/C][/ROW]
[ROW][C]25[/C][C]0.552988[/C][C]0.894023[/C][C]0.447012[/C][/ROW]
[ROW][C]26[/C][C]0.716284[/C][C]0.567432[/C][C]0.283716[/C][/ROW]
[ROW][C]27[/C][C]0.677114[/C][C]0.645771[/C][C]0.322886[/C][/ROW]
[ROW][C]28[/C][C]0.613888[/C][C]0.772223[/C][C]0.386112[/C][/ROW]
[ROW][C]29[/C][C]0.556181[/C][C]0.887639[/C][C]0.443819[/C][/ROW]
[ROW][C]30[/C][C]0.494605[/C][C]0.989211[/C][C]0.505395[/C][/ROW]
[ROW][C]31[/C][C]0.439314[/C][C]0.878629[/C][C]0.560686[/C][/ROW]
[ROW][C]32[/C][C]0.388284[/C][C]0.776569[/C][C]0.611716[/C][/ROW]
[ROW][C]33[/C][C]0.41495[/C][C]0.8299[/C][C]0.58505[/C][/ROW]
[ROW][C]34[/C][C]0.358628[/C][C]0.717257[/C][C]0.641372[/C][/ROW]
[ROW][C]35[/C][C]0.442438[/C][C]0.884877[/C][C]0.557562[/C][/ROW]
[ROW][C]36[/C][C]0.38761[/C][C]0.775219[/C][C]0.61239[/C][/ROW]
[ROW][C]37[/C][C]0.37698[/C][C]0.75396[/C][C]0.62302[/C][/ROW]
[ROW][C]38[/C][C]0.341489[/C][C]0.682979[/C][C]0.658511[/C][/ROW]
[ROW][C]39[/C][C]0.421821[/C][C]0.843643[/C][C]0.578179[/C][/ROW]
[ROW][C]40[/C][C]0.441278[/C][C]0.882556[/C][C]0.558722[/C][/ROW]
[ROW][C]41[/C][C]0.388361[/C][C]0.776722[/C][C]0.611639[/C][/ROW]
[ROW][C]42[/C][C]0.361356[/C][C]0.722713[/C][C]0.638644[/C][/ROW]
[ROW][C]43[/C][C]0.502896[/C][C]0.994207[/C][C]0.497104[/C][/ROW]
[ROW][C]44[/C][C]0.464659[/C][C]0.929318[/C][C]0.535341[/C][/ROW]
[ROW][C]45[/C][C]0.448675[/C][C]0.89735[/C][C]0.551325[/C][/ROW]
[ROW][C]46[/C][C]0.602742[/C][C]0.794517[/C][C]0.397258[/C][/ROW]
[ROW][C]47[/C][C]0.655259[/C][C]0.689483[/C][C]0.344741[/C][/ROW]
[ROW][C]48[/C][C]0.632071[/C][C]0.735859[/C][C]0.367929[/C][/ROW]
[ROW][C]49[/C][C]0.594158[/C][C]0.811685[/C][C]0.405842[/C][/ROW]
[ROW][C]50[/C][C]0.616808[/C][C]0.766384[/C][C]0.383192[/C][/ROW]
[ROW][C]51[/C][C]0.620459[/C][C]0.759083[/C][C]0.379541[/C][/ROW]
[ROW][C]52[/C][C]0.582495[/C][C]0.83501[/C][C]0.417505[/C][/ROW]
[ROW][C]53[/C][C]0.539349[/C][C]0.921303[/C][C]0.460651[/C][/ROW]
[ROW][C]54[/C][C]0.560355[/C][C]0.879289[/C][C]0.439645[/C][/ROW]
[ROW][C]55[/C][C]0.522371[/C][C]0.955259[/C][C]0.477629[/C][/ROW]
[ROW][C]56[/C][C]0.623139[/C][C]0.753722[/C][C]0.376861[/C][/ROW]
[ROW][C]57[/C][C]0.840443[/C][C]0.319114[/C][C]0.159557[/C][/ROW]
[ROW][C]58[/C][C]0.946239[/C][C]0.107523[/C][C]0.0537615[/C][/ROW]
[ROW][C]59[/C][C]0.93488[/C][C]0.13024[/C][C]0.06512[/C][/ROW]
[ROW][C]60[/C][C]0.920666[/C][C]0.158669[/C][C]0.0793343[/C][/ROW]
[ROW][C]61[/C][C]0.912441[/C][C]0.175117[/C][C]0.0875586[/C][/ROW]
[ROW][C]62[/C][C]0.917254[/C][C]0.165492[/C][C]0.0827462[/C][/ROW]
[ROW][C]63[/C][C]0.911169[/C][C]0.177661[/C][C]0.0888306[/C][/ROW]
[ROW][C]64[/C][C]0.896439[/C][C]0.207121[/C][C]0.103561[/C][/ROW]
[ROW][C]65[/C][C]0.890026[/C][C]0.219947[/C][C]0.109974[/C][/ROW]
[ROW][C]66[/C][C]0.911248[/C][C]0.177504[/C][C]0.0887521[/C][/ROW]
[ROW][C]67[/C][C]0.90237[/C][C]0.195259[/C][C]0.0976296[/C][/ROW]
[ROW][C]68[/C][C]0.89714[/C][C]0.20572[/C][C]0.10286[/C][/ROW]
[ROW][C]69[/C][C]0.879797[/C][C]0.240406[/C][C]0.120203[/C][/ROW]
[ROW][C]70[/C][C]0.858033[/C][C]0.283934[/C][C]0.141967[/C][/ROW]
[ROW][C]71[/C][C]0.87072[/C][C]0.25856[/C][C]0.12928[/C][/ROW]
[ROW][C]72[/C][C]0.913603[/C][C]0.172794[/C][C]0.0863972[/C][/ROW]
[ROW][C]73[/C][C]0.917447[/C][C]0.165106[/C][C]0.0825529[/C][/ROW]
[ROW][C]74[/C][C]0.935077[/C][C]0.129845[/C][C]0.0649226[/C][/ROW]
[ROW][C]75[/C][C]0.922178[/C][C]0.155644[/C][C]0.0778222[/C][/ROW]
[ROW][C]76[/C][C]0.91145[/C][C]0.1771[/C][C]0.08855[/C][/ROW]
[ROW][C]77[/C][C]0.900149[/C][C]0.199702[/C][C]0.0998511[/C][/ROW]
[ROW][C]78[/C][C]0.901937[/C][C]0.196125[/C][C]0.0980627[/C][/ROW]
[ROW][C]79[/C][C]0.886031[/C][C]0.227939[/C][C]0.113969[/C][/ROW]
[ROW][C]80[/C][C]0.879752[/C][C]0.240496[/C][C]0.120248[/C][/ROW]
[ROW][C]81[/C][C]0.883691[/C][C]0.232617[/C][C]0.116309[/C][/ROW]
[ROW][C]82[/C][C]0.867017[/C][C]0.265965[/C][C]0.132983[/C][/ROW]
[ROW][C]83[/C][C]0.848777[/C][C]0.302447[/C][C]0.151223[/C][/ROW]
[ROW][C]84[/C][C]0.871895[/C][C]0.256209[/C][C]0.128105[/C][/ROW]
[ROW][C]85[/C][C]0.851846[/C][C]0.296308[/C][C]0.148154[/C][/ROW]
[ROW][C]86[/C][C]0.89018[/C][C]0.219641[/C][C]0.10982[/C][/ROW]
[ROW][C]87[/C][C]0.873598[/C][C]0.252805[/C][C]0.126402[/C][/ROW]
[ROW][C]88[/C][C]0.860287[/C][C]0.279426[/C][C]0.139713[/C][/ROW]
[ROW][C]89[/C][C]0.962335[/C][C]0.0753295[/C][C]0.0376647[/C][/ROW]
[ROW][C]90[/C][C]0.969989[/C][C]0.060022[/C][C]0.030011[/C][/ROW]
[ROW][C]91[/C][C]0.967052[/C][C]0.0658958[/C][C]0.0329479[/C][/ROW]
[ROW][C]92[/C][C]0.96135[/C][C]0.0773004[/C][C]0.0386502[/C][/ROW]
[ROW][C]93[/C][C]0.961639[/C][C]0.0767225[/C][C]0.0383613[/C][/ROW]
[ROW][C]94[/C][C]0.957331[/C][C]0.0853381[/C][C]0.042669[/C][/ROW]
[ROW][C]95[/C][C]0.951451[/C][C]0.0970978[/C][C]0.0485489[/C][/ROW]
[ROW][C]96[/C][C]0.949243[/C][C]0.101514[/C][C]0.0507572[/C][/ROW]
[ROW][C]97[/C][C]0.954978[/C][C]0.0900436[/C][C]0.0450218[/C][/ROW]
[ROW][C]98[/C][C]0.953498[/C][C]0.093003[/C][C]0.0465015[/C][/ROW]
[ROW][C]99[/C][C]0.974943[/C][C]0.0501131[/C][C]0.0250565[/C][/ROW]
[ROW][C]100[/C][C]0.970575[/C][C]0.0588506[/C][C]0.0294253[/C][/ROW]
[ROW][C]101[/C][C]0.964424[/C][C]0.071151[/C][C]0.0355755[/C][/ROW]
[ROW][C]102[/C][C]0.969514[/C][C]0.0609722[/C][C]0.0304861[/C][/ROW]
[ROW][C]103[/C][C]0.96856[/C][C]0.0628796[/C][C]0.0314398[/C][/ROW]
[ROW][C]104[/C][C]0.97017[/C][C]0.0596608[/C][C]0.0298304[/C][/ROW]
[ROW][C]105[/C][C]0.968915[/C][C]0.0621705[/C][C]0.0310853[/C][/ROW]
[ROW][C]106[/C][C]0.962425[/C][C]0.0751497[/C][C]0.0375749[/C][/ROW]
[ROW][C]107[/C][C]0.970004[/C][C]0.0599914[/C][C]0.0299957[/C][/ROW]
[ROW][C]108[/C][C]0.963371[/C][C]0.0732586[/C][C]0.0366293[/C][/ROW]
[ROW][C]109[/C][C]0.957227[/C][C]0.0855452[/C][C]0.0427726[/C][/ROW]
[ROW][C]110[/C][C]0.977802[/C][C]0.0443963[/C][C]0.0221981[/C][/ROW]
[ROW][C]111[/C][C]0.976619[/C][C]0.0467612[/C][C]0.0233806[/C][/ROW]
[ROW][C]112[/C][C]0.972419[/C][C]0.0551618[/C][C]0.0275809[/C][/ROW]
[ROW][C]113[/C][C]0.96749[/C][C]0.0650195[/C][C]0.0325097[/C][/ROW]
[ROW][C]114[/C][C]0.993033[/C][C]0.0139332[/C][C]0.00696661[/C][/ROW]
[ROW][C]115[/C][C]0.992447[/C][C]0.015105[/C][C]0.00755252[/C][/ROW]
[ROW][C]116[/C][C]0.99075[/C][C]0.0184991[/C][C]0.00924955[/C][/ROW]
[ROW][C]117[/C][C]0.994366[/C][C]0.0112687[/C][C]0.00563437[/C][/ROW]
[ROW][C]118[/C][C]0.993334[/C][C]0.0133321[/C][C]0.00666604[/C][/ROW]
[ROW][C]119[/C][C]0.992758[/C][C]0.0144846[/C][C]0.00724229[/C][/ROW]
[ROW][C]120[/C][C]0.995102[/C][C]0.00979584[/C][C]0.00489792[/C][/ROW]
[ROW][C]121[/C][C]0.994231[/C][C]0.0115382[/C][C]0.00576912[/C][/ROW]
[ROW][C]122[/C][C]0.99324[/C][C]0.0135208[/C][C]0.00676041[/C][/ROW]
[ROW][C]123[/C][C]0.991893[/C][C]0.016214[/C][C]0.00810699[/C][/ROW]
[ROW][C]124[/C][C]0.99009[/C][C]0.0198199[/C][C]0.00990993[/C][/ROW]
[ROW][C]125[/C][C]0.98888[/C][C]0.0222398[/C][C]0.0111199[/C][/ROW]
[ROW][C]126[/C][C]0.986051[/C][C]0.0278982[/C][C]0.0139491[/C][/ROW]
[ROW][C]127[/C][C]0.985344[/C][C]0.0293113[/C][C]0.0146556[/C][/ROW]
[ROW][C]128[/C][C]0.986281[/C][C]0.0274389[/C][C]0.0137194[/C][/ROW]
[ROW][C]129[/C][C]0.983466[/C][C]0.0330678[/C][C]0.0165339[/C][/ROW]
[ROW][C]130[/C][C]0.980255[/C][C]0.0394899[/C][C]0.019745[/C][/ROW]
[ROW][C]131[/C][C]0.977112[/C][C]0.0457751[/C][C]0.0228876[/C][/ROW]
[ROW][C]132[/C][C]0.974662[/C][C]0.0506756[/C][C]0.0253378[/C][/ROW]
[ROW][C]133[/C][C]0.981904[/C][C]0.0361912[/C][C]0.0180956[/C][/ROW]
[ROW][C]134[/C][C]0.977835[/C][C]0.0443305[/C][C]0.0221653[/C][/ROW]
[ROW][C]135[/C][C]0.972866[/C][C]0.0542686[/C][C]0.0271343[/C][/ROW]
[ROW][C]136[/C][C]0.968245[/C][C]0.0635098[/C][C]0.0317549[/C][/ROW]
[ROW][C]137[/C][C]0.965235[/C][C]0.0695301[/C][C]0.034765[/C][/ROW]
[ROW][C]138[/C][C]0.9743[/C][C]0.0513999[/C][C]0.0256999[/C][/ROW]
[ROW][C]139[/C][C]0.980957[/C][C]0.038085[/C][C]0.0190425[/C][/ROW]
[ROW][C]140[/C][C]0.983741[/C][C]0.0325174[/C][C]0.0162587[/C][/ROW]
[ROW][C]141[/C][C]0.986044[/C][C]0.0279113[/C][C]0.0139557[/C][/ROW]
[ROW][C]142[/C][C]0.996551[/C][C]0.00689831[/C][C]0.00344916[/C][/ROW]
[ROW][C]143[/C][C]0.995928[/C][C]0.00814485[/C][C]0.00407242[/C][/ROW]
[ROW][C]144[/C][C]0.995672[/C][C]0.00865504[/C][C]0.00432752[/C][/ROW]
[ROW][C]145[/C][C]0.994517[/C][C]0.0109655[/C][C]0.00548277[/C][/ROW]
[ROW][C]146[/C][C]0.997191[/C][C]0.00561768[/C][C]0.00280884[/C][/ROW]
[ROW][C]147[/C][C]0.99748[/C][C]0.00504064[/C][C]0.00252032[/C][/ROW]
[ROW][C]148[/C][C]0.998574[/C][C]0.00285268[/C][C]0.00142634[/C][/ROW]
[ROW][C]149[/C][C]0.998124[/C][C]0.00375211[/C][C]0.00187605[/C][/ROW]
[ROW][C]150[/C][C]0.997519[/C][C]0.00496223[/C][C]0.00248111[/C][/ROW]
[ROW][C]151[/C][C]0.996802[/C][C]0.00639577[/C][C]0.00319788[/C][/ROW]
[ROW][C]152[/C][C]0.996124[/C][C]0.0077528[/C][C]0.0038764[/C][/ROW]
[ROW][C]153[/C][C]0.995375[/C][C]0.00924973[/C][C]0.00462487[/C][/ROW]
[ROW][C]154[/C][C]0.995621[/C][C]0.00875814[/C][C]0.00437907[/C][/ROW]
[ROW][C]155[/C][C]0.996307[/C][C]0.00738685[/C][C]0.00369343[/C][/ROW]
[ROW][C]156[/C][C]0.995482[/C][C]0.00903636[/C][C]0.00451818[/C][/ROW]
[ROW][C]157[/C][C]0.994685[/C][C]0.0106308[/C][C]0.00531538[/C][/ROW]
[ROW][C]158[/C][C]0.993478[/C][C]0.0130432[/C][C]0.00652159[/C][/ROW]
[ROW][C]159[/C][C]0.993393[/C][C]0.0132135[/C][C]0.00660673[/C][/ROW]
[ROW][C]160[/C][C]0.992477[/C][C]0.0150453[/C][C]0.00752264[/C][/ROW]
[ROW][C]161[/C][C]0.990527[/C][C]0.0189452[/C][C]0.0094726[/C][/ROW]
[ROW][C]162[/C][C]0.987997[/C][C]0.024007[/C][C]0.0120035[/C][/ROW]
[ROW][C]163[/C][C]0.990124[/C][C]0.0197522[/C][C]0.00987611[/C][/ROW]
[ROW][C]164[/C][C]0.987546[/C][C]0.0249087[/C][C]0.0124543[/C][/ROW]
[ROW][C]165[/C][C]0.986545[/C][C]0.0269108[/C][C]0.0134554[/C][/ROW]
[ROW][C]166[/C][C]0.983358[/C][C]0.0332846[/C][C]0.0166423[/C][/ROW]
[ROW][C]167[/C][C]0.979926[/C][C]0.0401475[/C][C]0.0200738[/C][/ROW]
[ROW][C]168[/C][C]0.987322[/C][C]0.0253557[/C][C]0.0126779[/C][/ROW]
[ROW][C]169[/C][C]0.984346[/C][C]0.031307[/C][C]0.0156535[/C][/ROW]
[ROW][C]170[/C][C]0.984545[/C][C]0.0309097[/C][C]0.0154549[/C][/ROW]
[ROW][C]171[/C][C]0.988452[/C][C]0.023095[/C][C]0.0115475[/C][/ROW]
[ROW][C]172[/C][C]0.986999[/C][C]0.0260028[/C][C]0.0130014[/C][/ROW]
[ROW][C]173[/C][C]0.983864[/C][C]0.0322729[/C][C]0.0161364[/C][/ROW]
[ROW][C]174[/C][C]0.98076[/C][C]0.0384793[/C][C]0.0192396[/C][/ROW]
[ROW][C]175[/C][C]0.977522[/C][C]0.0449565[/C][C]0.0224783[/C][/ROW]
[ROW][C]176[/C][C]0.973531[/C][C]0.0529382[/C][C]0.0264691[/C][/ROW]
[ROW][C]177[/C][C]0.968304[/C][C]0.0633929[/C][C]0.0316965[/C][/ROW]
[ROW][C]178[/C][C]0.97027[/C][C]0.0594605[/C][C]0.0297302[/C][/ROW]
[ROW][C]179[/C][C]0.97362[/C][C]0.0527601[/C][C]0.0263801[/C][/ROW]
[ROW][C]180[/C][C]0.974972[/C][C]0.0500559[/C][C]0.025028[/C][/ROW]
[ROW][C]181[/C][C]0.969407[/C][C]0.0611869[/C][C]0.0305934[/C][/ROW]
[ROW][C]182[/C][C]0.962676[/C][C]0.0746478[/C][C]0.0373239[/C][/ROW]
[ROW][C]183[/C][C]0.956226[/C][C]0.087548[/C][C]0.043774[/C][/ROW]
[ROW][C]184[/C][C]0.948094[/C][C]0.103812[/C][C]0.0519059[/C][/ROW]
[ROW][C]185[/C][C]0.947561[/C][C]0.104877[/C][C]0.0524387[/C][/ROW]
[ROW][C]186[/C][C]0.962431[/C][C]0.0751371[/C][C]0.0375686[/C][/ROW]
[ROW][C]187[/C][C]0.957531[/C][C]0.0849386[/C][C]0.0424693[/C][/ROW]
[ROW][C]188[/C][C]0.950575[/C][C]0.0988508[/C][C]0.0494254[/C][/ROW]
[ROW][C]189[/C][C]0.943218[/C][C]0.113564[/C][C]0.056782[/C][/ROW]
[ROW][C]190[/C][C]0.951204[/C][C]0.0975929[/C][C]0.0487965[/C][/ROW]
[ROW][C]191[/C][C]0.958777[/C][C]0.0824454[/C][C]0.0412227[/C][/ROW]
[ROW][C]192[/C][C]0.950606[/C][C]0.0987872[/C][C]0.0493936[/C][/ROW]
[ROW][C]193[/C][C]0.955686[/C][C]0.0886271[/C][C]0.0443135[/C][/ROW]
[ROW][C]194[/C][C]0.950254[/C][C]0.0994915[/C][C]0.0497457[/C][/ROW]
[ROW][C]195[/C][C]0.941586[/C][C]0.116829[/C][C]0.0584143[/C][/ROW]
[ROW][C]196[/C][C]0.93558[/C][C]0.128839[/C][C]0.0644196[/C][/ROW]
[ROW][C]197[/C][C]0.925822[/C][C]0.148355[/C][C]0.0741776[/C][/ROW]
[ROW][C]198[/C][C]0.911026[/C][C]0.177948[/C][C]0.0889741[/C][/ROW]
[ROW][C]199[/C][C]0.894764[/C][C]0.210473[/C][C]0.105236[/C][/ROW]
[ROW][C]200[/C][C]0.976722[/C][C]0.0465557[/C][C]0.0232779[/C][/ROW]
[ROW][C]201[/C][C]0.974808[/C][C]0.050385[/C][C]0.0251925[/C][/ROW]
[ROW][C]202[/C][C]0.975056[/C][C]0.049887[/C][C]0.0249435[/C][/ROW]
[ROW][C]203[/C][C]0.97517[/C][C]0.0496608[/C][C]0.0248304[/C][/ROW]
[ROW][C]204[/C][C]0.971513[/C][C]0.0569742[/C][C]0.0284871[/C][/ROW]
[ROW][C]205[/C][C]0.967008[/C][C]0.0659832[/C][C]0.0329916[/C][/ROW]
[ROW][C]206[/C][C]0.961284[/C][C]0.077432[/C][C]0.038716[/C][/ROW]
[ROW][C]207[/C][C]0.956099[/C][C]0.0878021[/C][C]0.0439011[/C][/ROW]
[ROW][C]208[/C][C]0.950392[/C][C]0.0992157[/C][C]0.0496079[/C][/ROW]
[ROW][C]209[/C][C]0.941577[/C][C]0.116846[/C][C]0.058423[/C][/ROW]
[ROW][C]210[/C][C]0.966498[/C][C]0.0670034[/C][C]0.0335017[/C][/ROW]
[ROW][C]211[/C][C]0.95783[/C][C]0.0843395[/C][C]0.0421698[/C][/ROW]
[ROW][C]212[/C][C]0.95527[/C][C]0.0894604[/C][C]0.0447302[/C][/ROW]
[ROW][C]213[/C][C]0.960911[/C][C]0.0781781[/C][C]0.039089[/C][/ROW]
[ROW][C]214[/C][C]0.955055[/C][C]0.0898893[/C][C]0.0449446[/C][/ROW]
[ROW][C]215[/C][C]0.949033[/C][C]0.101935[/C][C]0.0509674[/C][/ROW]
[ROW][C]216[/C][C]0.936291[/C][C]0.127417[/C][C]0.0637086[/C][/ROW]
[ROW][C]217[/C][C]0.927853[/C][C]0.144294[/C][C]0.0721472[/C][/ROW]
[ROW][C]218[/C][C]0.929938[/C][C]0.140123[/C][C]0.0700617[/C][/ROW]
[ROW][C]219[/C][C]0.947854[/C][C]0.104293[/C][C]0.0521463[/C][/ROW]
[ROW][C]220[/C][C]0.961565[/C][C]0.0768704[/C][C]0.0384352[/C][/ROW]
[ROW][C]221[/C][C]0.992723[/C][C]0.0145533[/C][C]0.00727663[/C][/ROW]
[ROW][C]222[/C][C]0.990785[/C][C]0.0184299[/C][C]0.00921497[/C][/ROW]
[ROW][C]223[/C][C]0.987476[/C][C]0.025049[/C][C]0.0125245[/C][/ROW]
[ROW][C]224[/C][C]0.993555[/C][C]0.0128903[/C][C]0.00644514[/C][/ROW]
[ROW][C]225[/C][C]0.990869[/C][C]0.0182626[/C][C]0.0091313[/C][/ROW]
[ROW][C]226[/C][C]0.987612[/C][C]0.024776[/C][C]0.012388[/C][/ROW]
[ROW][C]227[/C][C]0.99216[/C][C]0.0156807[/C][C]0.00784033[/C][/ROW]
[ROW][C]228[/C][C]0.99085[/C][C]0.0183007[/C][C]0.00915036[/C][/ROW]
[ROW][C]229[/C][C]0.998813[/C][C]0.00237451[/C][C]0.00118726[/C][/ROW]
[ROW][C]230[/C][C]0.998815[/C][C]0.00237029[/C][C]0.00118515[/C][/ROW]
[ROW][C]231[/C][C]0.998215[/C][C]0.00356981[/C][C]0.00178491[/C][/ROW]
[ROW][C]232[/C][C]0.997272[/C][C]0.0054555[/C][C]0.00272775[/C][/ROW]
[ROW][C]233[/C][C]0.996667[/C][C]0.00666663[/C][C]0.00333331[/C][/ROW]
[ROW][C]234[/C][C]0.99682[/C][C]0.0063601[/C][C]0.00318005[/C][/ROW]
[ROW][C]235[/C][C]0.996052[/C][C]0.00789608[/C][C]0.00394804[/C][/ROW]
[ROW][C]236[/C][C]0.994624[/C][C]0.0107521[/C][C]0.00537603[/C][/ROW]
[ROW][C]237[/C][C]0.994653[/C][C]0.0106932[/C][C]0.0053466[/C][/ROW]
[ROW][C]238[/C][C]0.991901[/C][C]0.0161975[/C][C]0.00809875[/C][/ROW]
[ROW][C]239[/C][C]0.992993[/C][C]0.0140135[/C][C]0.00700676[/C][/ROW]
[ROW][C]240[/C][C]0.99032[/C][C]0.0193599[/C][C]0.00967996[/C][/ROW]
[ROW][C]241[/C][C]0.986846[/C][C]0.0263082[/C][C]0.0131541[/C][/ROW]
[ROW][C]242[/C][C]0.981784[/C][C]0.0364322[/C][C]0.0182161[/C][/ROW]
[ROW][C]243[/C][C]0.981918[/C][C]0.0361638[/C][C]0.0180819[/C][/ROW]
[ROW][C]244[/C][C]0.980448[/C][C]0.0391047[/C][C]0.0195524[/C][/ROW]
[ROW][C]245[/C][C]0.972141[/C][C]0.0557174[/C][C]0.0278587[/C][/ROW]
[ROW][C]246[/C][C]0.958639[/C][C]0.0827224[/C][C]0.0413612[/C][/ROW]
[ROW][C]247[/C][C]0.95349[/C][C]0.09302[/C][C]0.04651[/C][/ROW]
[ROW][C]248[/C][C]0.93845[/C][C]0.123099[/C][C]0.0615497[/C][/ROW]
[ROW][C]249[/C][C]0.915085[/C][C]0.16983[/C][C]0.0849151[/C][/ROW]
[ROW][C]250[/C][C]0.881238[/C][C]0.237524[/C][C]0.118762[/C][/ROW]
[ROW][C]251[/C][C]0.84271[/C][C]0.31458[/C][C]0.15729[/C][/ROW]
[ROW][C]252[/C][C]0.831463[/C][C]0.337073[/C][C]0.168537[/C][/ROW]
[ROW][C]253[/C][C]0.790479[/C][C]0.419042[/C][C]0.209521[/C][/ROW]
[ROW][C]254[/C][C]0.7279[/C][C]0.544199[/C][C]0.2721[/C][/ROW]
[ROW][C]255[/C][C]0.675002[/C][C]0.649997[/C][C]0.324998[/C][/ROW]
[ROW][C]256[/C][C]0.602304[/C][C]0.795392[/C][C]0.397696[/C][/ROW]
[ROW][C]257[/C][C]0.54688[/C][C]0.90624[/C][C]0.45312[/C][/ROW]
[ROW][C]258[/C][C]0.446195[/C][C]0.89239[/C][C]0.553805[/C][/ROW]
[ROW][C]259[/C][C]0.363677[/C][C]0.727354[/C][C]0.636323[/C][/ROW]
[ROW][C]260[/C][C]0.463719[/C][C]0.927438[/C][C]0.536281[/C][/ROW]
[ROW][C]261[/C][C]0.385935[/C][C]0.77187[/C][C]0.614065[/C][/ROW]
[ROW][C]262[/C][C]0.261655[/C][C]0.52331[/C][C]0.738345[/C][/ROW]
[ROW][C]263[/C][C]0.154377[/C][C]0.308755[/C][C]0.845623[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232447&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232447&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.5678190.8643620.432181
130.3981980.7963970.601802
140.2643210.5286420.735679
150.6490430.7019150.350957
160.5374020.9251950.462598
170.4286930.8573850.571307
180.3320210.6640430.667979
190.3725330.7450670.627467
200.3759380.7518770.624062
210.3397670.6795330.660233
220.352510.7050190.64749
230.2785490.5570970.721451
240.6232250.753550.376775
250.5529880.8940230.447012
260.7162840.5674320.283716
270.6771140.6457710.322886
280.6138880.7722230.386112
290.5561810.8876390.443819
300.4946050.9892110.505395
310.4393140.8786290.560686
320.3882840.7765690.611716
330.414950.82990.58505
340.3586280.7172570.641372
350.4424380.8848770.557562
360.387610.7752190.61239
370.376980.753960.62302
380.3414890.6829790.658511
390.4218210.8436430.578179
400.4412780.8825560.558722
410.3883610.7767220.611639
420.3613560.7227130.638644
430.5028960.9942070.497104
440.4646590.9293180.535341
450.4486750.897350.551325
460.6027420.7945170.397258
470.6552590.6894830.344741
480.6320710.7358590.367929
490.5941580.8116850.405842
500.6168080.7663840.383192
510.6204590.7590830.379541
520.5824950.835010.417505
530.5393490.9213030.460651
540.5603550.8792890.439645
550.5223710.9552590.477629
560.6231390.7537220.376861
570.8404430.3191140.159557
580.9462390.1075230.0537615
590.934880.130240.06512
600.9206660.1586690.0793343
610.9124410.1751170.0875586
620.9172540.1654920.0827462
630.9111690.1776610.0888306
640.8964390.2071210.103561
650.8900260.2199470.109974
660.9112480.1775040.0887521
670.902370.1952590.0976296
680.897140.205720.10286
690.8797970.2404060.120203
700.8580330.2839340.141967
710.870720.258560.12928
720.9136030.1727940.0863972
730.9174470.1651060.0825529
740.9350770.1298450.0649226
750.9221780.1556440.0778222
760.911450.17710.08855
770.9001490.1997020.0998511
780.9019370.1961250.0980627
790.8860310.2279390.113969
800.8797520.2404960.120248
810.8836910.2326170.116309
820.8670170.2659650.132983
830.8487770.3024470.151223
840.8718950.2562090.128105
850.8518460.2963080.148154
860.890180.2196410.10982
870.8735980.2528050.126402
880.8602870.2794260.139713
890.9623350.07532950.0376647
900.9699890.0600220.030011
910.9670520.06589580.0329479
920.961350.07730040.0386502
930.9616390.07672250.0383613
940.9573310.08533810.042669
950.9514510.09709780.0485489
960.9492430.1015140.0507572
970.9549780.09004360.0450218
980.9534980.0930030.0465015
990.9749430.05011310.0250565
1000.9705750.05885060.0294253
1010.9644240.0711510.0355755
1020.9695140.06097220.0304861
1030.968560.06287960.0314398
1040.970170.05966080.0298304
1050.9689150.06217050.0310853
1060.9624250.07514970.0375749
1070.9700040.05999140.0299957
1080.9633710.07325860.0366293
1090.9572270.08554520.0427726
1100.9778020.04439630.0221981
1110.9766190.04676120.0233806
1120.9724190.05516180.0275809
1130.967490.06501950.0325097
1140.9930330.01393320.00696661
1150.9924470.0151050.00755252
1160.990750.01849910.00924955
1170.9943660.01126870.00563437
1180.9933340.01333210.00666604
1190.9927580.01448460.00724229
1200.9951020.009795840.00489792
1210.9942310.01153820.00576912
1220.993240.01352080.00676041
1230.9918930.0162140.00810699
1240.990090.01981990.00990993
1250.988880.02223980.0111199
1260.9860510.02789820.0139491
1270.9853440.02931130.0146556
1280.9862810.02743890.0137194
1290.9834660.03306780.0165339
1300.9802550.03948990.019745
1310.9771120.04577510.0228876
1320.9746620.05067560.0253378
1330.9819040.03619120.0180956
1340.9778350.04433050.0221653
1350.9728660.05426860.0271343
1360.9682450.06350980.0317549
1370.9652350.06953010.034765
1380.97430.05139990.0256999
1390.9809570.0380850.0190425
1400.9837410.03251740.0162587
1410.9860440.02791130.0139557
1420.9965510.006898310.00344916
1430.9959280.008144850.00407242
1440.9956720.008655040.00432752
1450.9945170.01096550.00548277
1460.9971910.005617680.00280884
1470.997480.005040640.00252032
1480.9985740.002852680.00142634
1490.9981240.003752110.00187605
1500.9975190.004962230.00248111
1510.9968020.006395770.00319788
1520.9961240.00775280.0038764
1530.9953750.009249730.00462487
1540.9956210.008758140.00437907
1550.9963070.007386850.00369343
1560.9954820.009036360.00451818
1570.9946850.01063080.00531538
1580.9934780.01304320.00652159
1590.9933930.01321350.00660673
1600.9924770.01504530.00752264
1610.9905270.01894520.0094726
1620.9879970.0240070.0120035
1630.9901240.01975220.00987611
1640.9875460.02490870.0124543
1650.9865450.02691080.0134554
1660.9833580.03328460.0166423
1670.9799260.04014750.0200738
1680.9873220.02535570.0126779
1690.9843460.0313070.0156535
1700.9845450.03090970.0154549
1710.9884520.0230950.0115475
1720.9869990.02600280.0130014
1730.9838640.03227290.0161364
1740.980760.03847930.0192396
1750.9775220.04495650.0224783
1760.9735310.05293820.0264691
1770.9683040.06339290.0316965
1780.970270.05946050.0297302
1790.973620.05276010.0263801
1800.9749720.05005590.025028
1810.9694070.06118690.0305934
1820.9626760.07464780.0373239
1830.9562260.0875480.043774
1840.9480940.1038120.0519059
1850.9475610.1048770.0524387
1860.9624310.07513710.0375686
1870.9575310.08493860.0424693
1880.9505750.09885080.0494254
1890.9432180.1135640.056782
1900.9512040.09759290.0487965
1910.9587770.08244540.0412227
1920.9506060.09878720.0493936
1930.9556860.08862710.0443135
1940.9502540.09949150.0497457
1950.9415860.1168290.0584143
1960.935580.1288390.0644196
1970.9258220.1483550.0741776
1980.9110260.1779480.0889741
1990.8947640.2104730.105236
2000.9767220.04655570.0232779
2010.9748080.0503850.0251925
2020.9750560.0498870.0249435
2030.975170.04966080.0248304
2040.9715130.05697420.0284871
2050.9670080.06598320.0329916
2060.9612840.0774320.038716
2070.9560990.08780210.0439011
2080.9503920.09921570.0496079
2090.9415770.1168460.058423
2100.9664980.06700340.0335017
2110.957830.08433950.0421698
2120.955270.08946040.0447302
2130.9609110.07817810.039089
2140.9550550.08988930.0449446
2150.9490330.1019350.0509674
2160.9362910.1274170.0637086
2170.9278530.1442940.0721472
2180.9299380.1401230.0700617
2190.9478540.1042930.0521463
2200.9615650.07687040.0384352
2210.9927230.01455330.00727663
2220.9907850.01842990.00921497
2230.9874760.0250490.0125245
2240.9935550.01289030.00644514
2250.9908690.01826260.0091313
2260.9876120.0247760.012388
2270.992160.01568070.00784033
2280.990850.01830070.00915036
2290.9988130.002374510.00118726
2300.9988150.002370290.00118515
2310.9982150.003569810.00178491
2320.9972720.00545550.00272775
2330.9966670.006666630.00333331
2340.996820.00636010.00318005
2350.9960520.007896080.00394804
2360.9946240.01075210.00537603
2370.9946530.01069320.0053466
2380.9919010.01619750.00809875
2390.9929930.01401350.00700676
2400.990320.01935990.00967996
2410.9868460.02630820.0131541
2420.9817840.03643220.0182161
2430.9819180.03616380.0180819
2440.9804480.03910470.0195524
2450.9721410.05571740.0278587
2460.9586390.08272240.0413612
2470.953490.093020.04651
2480.938450.1230990.0615497
2490.9150850.169830.0849151
2500.8812380.2375240.118762
2510.842710.314580.15729
2520.8314630.3370730.168537
2530.7904790.4190420.209521
2540.72790.5441990.2721
2550.6750020.6499970.324998
2560.6023040.7953920.397696
2570.546880.906240.45312
2580.4461950.892390.553805
2590.3636770.7273540.636323
2600.4637190.9274380.536281
2610.3859350.771870.614065
2620.2616550.523310.738345
2630.1543770.3087550.845623







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level220.0873016NOK
5% type I error level860.34127NOK
10% type I error level1440.571429NOK

\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 & 22 & 0.0873016 & NOK \tabularnewline
5% type I error level & 86 & 0.34127 & NOK \tabularnewline
10% type I error level & 144 & 0.571429 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232447&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]22[/C][C]0.0873016[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]86[/C][C]0.34127[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]144[/C][C]0.571429[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232447&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232447&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level220.0873016NOK
5% type I error level860.34127NOK
10% type I error level1440.571429NOK



Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 3 ; par4 = TRUE ;
Parameters (R input):
par1 = 9 ; 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')
}