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R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Thu, 11 Dec 2014 10:57:18 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/11/t141829545973hmre70qdz8whp.htm/, Retrieved Thu, 16 May 2024 16:06:17 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265719, Retrieved Thu, 16 May 2024 16:06:17 +0000

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

-       [Multiple Regression] [] [2014-12-11 10:57:18] [6398a3f6f1f2f5e55f0ec79c736f94f8] [Current]

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Dataseries X:

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7.5 1.00 0.50 0.67 0.67 0.00 0.50
6.0 0.89 0.50 0.83 0.33 0.50 1.00
6.5 0.89 0.40 1.00 0.67 0.00 1.00
1.0 0.89 0.50 0.83 0.00 0.00 0.00
1.0 0.89 0.70 0.67 0.00 1.00 1.00
5.5 0.78 0.30 0.00 0.00 0.50 0.50
8.5 0.89 0.40 0.83 0.67 0.50 0.00
6.5 1.00 0.40 0.50 0.67 1.00 1.00
4.5 0.89 0.70 0.83 0.00 0.50 0.00
2.0 0.78 0.60 0.33 0.67 0.50 0.50
5.0 1.00 0.60 0.50 1.00 0.00 0.50
0.5 0.78 0.20 0.67 0.00 0.50 0.50
5.0 0.89 0.40 1.00 0.00 0.50 0.50
5.0 0.89 0.40 0.50 0.67 0.00 1.00
2.5 0.89 0.50 0.67 0.33 0.00 0.00
5.0 0.89 0.30 0.17 0.67 0.00 0.50
5.5 0.89 0.40 0.83 0.33 0.50 0.50
3.5 0.67 0.70 0.67 0.33 0.50 1.00
3.0 1.00 0.50 0.67 0.33 0.00 1.00
4.0 0.78 0.20 0.67 0.00 0.00 1.00
0.5 0.78 0.30 0.50 0.67 0.00 0.50
6.5 0.89 0.60 1.00 0.33 0.00 1.00
4.5 0.78 0.60 0.83 0.33 0.00 1.00
7.5 0.89 0.20 0.83 0.33 0.00 1.00
5.5 0.89 0.70 1.00 0.67 1.00 0.00
4.0 0.33 0.20 0.67 0.00 0.00 0.00
7.5 1.00 1.00 1.00 0.33 1.00 1.00
7.0 0.89 0.40 0.83 0.67 0.00 0.50
4.0 0.89 0.40 1.00 1.00 0.00 1.00
5.5 0.67 0.20 0.83 0.67 0.00 0.50
2.5 0.56 0.40 0.67 0.33 0.00 1.00
5.5 0.89 0.40 0.67 0.00 0.50 1.00
3.5 0.89 0.70 1.00 0.67 0.50 0.50
2.5 1.00 0.20 0.67 0.67 0.00 0.50
4.5 0.78 0.60 1.00 1.00 0.00 0.50
4.5 0.78 0.30 1.00 1.00 0.50 0.50
4.5 0.33 0.30 0.50 0.33 0.00 0.00
6.0 0.78 0.20 0.67 0.00 0.50 0.00
2.5 0.89 0.50 0.83 0.67 0.50 0.50
5.0 0.89 0.70 1.00 0.67 0.50 1.00
0.0 0.78 0.60 1.00 0.67 0.50 0.50
5.0 0.89 0.40 1.00 0.67 0.50 1.00
6.5 0.89 0.60 1.00 0.33 0.50 1.00
5.0 1.00 0.40 1.00 1.00 0.00 1.00
6.0 0.67 0.30 0.83 0.67 0.00 1.00
4.5 1.00 0.50 0.83 0.67 0.50 0.50
5.5 0.89 0.20 0.50 0.00 0.00 1.00
1.0 0.89 0.30 0.83 0.00 0.50 1.00
7.5 0.89 0.50 0.17 0.00 0.00 1.00
6.0 0.78 0.70 0.83 1.00 0.50 1.00
5.0 0.89 0.40 1.00 0.67 1.00 0.50
1.0 0.78 0.30 1.00 0.00 0.00 0.50
5.0 0.78 0.20 0.67 0.67 1.00 1.00
6.5 1.00 0.50 1.00 0.00 0.00 0.50
7.0 0.78 0.40 1.00 0.00 0.50 0.00
4.5 1.00 0.60 1.00 0.67 1.00 1.00
0.0 0.78 0.40 0.83 1.00 0.00 1.00
8.5 0.67 0.40 0.33 0.00 0.00 0.50
3.5 0.33 0.20 0.33 0.33 0.00 0.00
7.5 1.00 0.90 1.00 0.67 0.50 1.00
3.5 1.00 0.80 1.00 0.67 1.00 0.50
6.0 0.78 0.80 0.83 0.00 0.50 1.00
1.5 0.67 0.30 1.00 1.00 0.50 1.00
9.0 1.00 0.20 0.83 0.67 0.00 0.50
3.5 0.89 0.40 0.67 0.00 0.50 1.00
3.5 0.89 0.20 0.83 1.00 0.00 1.00
4.0 0.78 0.20 0.67 0.67 0.50 1.00
6.5 1.00 0.10 0.83 0.67 0.00 1.00
7.5 0.56 0.40 0.67 1.00 0.50 0.00
6.0 0.67 0.50 1.00 0.00 0.50 0.50
5.0 0.89 0.80 0.83 0.33 0.50 1.00
5.5 0.89 0.40 0.67 0.67 0.00 0.50
3.5 0.89 0.60 0.83 0.33 0.50 0.50
7.5 0.89 0.50 0.83 0.67 0.50 1.00
6.5 0.78 0.30 0.67 0.00 0.00 0.00
NA 0.89 0.80 1.00 1.00 0.50 1.00
6.5 1.00 0.40 0.33 0.00 0.50 0.00
6.5 1.00 0.60 0.83 0.67 0.50 0.50
7.0 0.89 0.40 1.00 0.33 0.00 0.50
3.5 0.44 0.30 0.83 0.00 0.00 0.00
1.5 0.78 0.80 0.83 0.00 1.00 1.00
4.0 0.89 0.60 0.50 0.33 1.00 1.00
7.5 0.67 0.30 0.50 0.00 0.00 0.00
4.5 0.78 0.50 0.83 0.67 0.50 1.00
0.0 0.78 0.40 1.00 0.33 0.00 1.00
3.5 0.33 0.30 0.33 0.67 0.00 0.00
5.5 0.89 0.70 1.00 0.33 0.00 0.50
5.0 0.89 0.20 0.67 0.33 0.50 0.50
4.5 0.89 0.40 0.83 1.00 0.00 1.00
2.5 0.89 0.60 1.00 0.67 0.50 0.50
7.5 0.56 0.60 0.83 0.00 0.00 1.00
7.0 0.67 0.60 0.83 0.67 0.50 0.50
0.0 0.67 0.40 1.00 0.33 0.50 1.00
4.5 0.78 0.60 0.83 0.00 0.00 1.00
3.0 0.78 0.50 1.00 0.33 0.50 1.00
1.5 0.78 0.50 0.83 0.00 0.00 1.00
3.5 0.89 0.60 0.67 0.00 0.00 1.00
2.5 1.00 0.80 0.83 0.33 0.50 1.00
5.5 0.89 0.50 0.83 0.67 1.00 0.50
8.0 0.89 0.60 0.83 0.67 0.50 1.00
1.0 0.78 0.40 0.83 0.67 0.50 1.00
5.0 1.00 0.30 0.67 0.67 0.50 1.00
4.5 0.78 0.30 0.83 1.00 0.00 0.50
3.0 0.67 0.20 0.00 0.00 0.00 0.00
3.0 0.78 0.40 0.83 0.00 0.00 0.50
8.0 0.89 0.50 1.00 0.00 0.00 0.50
2.5 0.67 0.30 0.17 0.00 0.50 0.00
7.0 0.22 0.40 0.17 0.00 0.50 0.00
0.0 0.44 0.50 0.50 1.00 0.00 0.00
1.0 0.89 0.30 0.50 0.67 0.00 1.00
3.5 0.67 0.50 1.00 0.00 0.00 0.50
5.5 0.89 0.40 0.67 0.67 0.00 0.50
5.5 0.67 0.40 0.83 0.67 0.00 1.00
0.5 0.78 0.60 1.00 0.00 1.00 1.00
7.5 0.78 0.30 1.00 0.67 1.00 1.00
9 0.78 0.40 1.00 0.33 1.00 0.50
9.5 1.00 0.30 1.00 1.00 1.00 1.00
8.5 0.78 1.00 1.00 1.00 1.00 1.00
7 0.67 0.40 1.00 0.00 0.00 0.50
8 0.89 0.80 0.83 1.00 0.50 1.00
10 0.89 0.30 1.00 0.67 1.00 1.00
7 1.00 0.50 0.83 0.67 0.00 1.00
8.5 0.78 0.40 1.00 0.00 0.00 0.50
9 0.67 0.30 0.83 0.67 0.00 1.00
9.5 0.89 0.50 0.83 1.00 0.00 1.00
4 0.67 0.30 1.00 0.67 0.00 1.00
6 0.67 0.30 0.67 0.00 0.00 1.00
8 1.00 0.40 0.83 0.00 0.00 1.00
5.5 0.67 0.30 1.00 0.00 0.00 0.50
9.5 1.00 0.60 1.00 0.33 0.50 0.50
7.5 0.89 0.60 0.83 0.67 1.00 1.00
7 0.89 0.40 1.00 1.00 1.00 1.00
7.5 1.00 0.40 1.00 0.00 0.00 0.00
8 0.67 0.40 1.00 0.67 0.00 0.50
7 0.44 0.30 0.67 0.67 0.50 1.00
7 0.89 0.20 1.00 0.33 1.00 0.00
6 0.56 0.50 0.83 0.67 0.00 1.00
10 0.78 0.40 1.00 0.67 1.00 1.00
2.5 1.00 0.40 1.00 0.67 0.00 0.00
9 1.00 0.40 0.83 0.67 0.00 1.00
8 0.89 0.30 0.67 0.67 0.50 0.50
6 0.67 0.40 0.83 0.67 1.00 0.50
8.5 0.89 0.20 1.00 0.33 0.50 1.00
6 0.33 0.00 0.00 0.00 0.00 0.00
9 0.89 0.40 1.00 0.67 0.50 1.00
8 0.78 0.60 1.00 0.00 1.00 1.00
9 1.00 0.40 0.67 0.67 0.00 0.50
5.5 0.44 0.40 1.00 0.00 0.00 0.50
7 0.67 0.40 0.83 0.00 0.50 0.00
5.5 0.33 0.20 0.17 0.00 0.50 0.00
9 0.89 0.40 0.83 1.00 1.00 1.00
2 0.89 0.30 0.83 0.00 0.00 0.50
8.5 1.00 0.60 0.83 0.67 1.00 0.00
9 0.89 0.60 0.83 1.00 0.00 1.00
8.5 0.89 0.40 0.83 0.00 0.00 1.00
9 1.00 0.50 1.00 0.67 1.00 0.50
7.5 0.89 0.40 0.83 0.00 0.50 1.00
10 1.00 0.60 1.00 1.00 1.00 1.00
9 0.78 0.60 0.83 0.67 0.50 1.00
7.5 0.78 0.90 1.00 0.67 0.50 1.00
6 0.67 0.40 0.83 0.67 0.50 0.00
10.5 0.89 0.80 1.00 1.00 0.50 1.00
8.5 0.67 0.50 0.83 1.00 0.00 1.00
8 0.78 0.40 0.83 1.00 0.00 0.00
10 0.89 0.40 1.00 0.67 1.00 0.50
10.5 0.89 0.70 1.00 1.00 1.00 0.50
6.5 0.78 0.40 1.00 0.33 1.00 1.00
9.5 1.00 0.80 1.00 0.67 0.50 1.00
8.5 1.00 0.40 1.00 1.00 1.00 0.50
7.5 1.00 0.30 1.00 0.67 0.00 0.50
5 0.67 0.50 1.00 0.67 0.50 1.00
8 0.89 0.80 1.00 0.67 1.00 1.00
10 1.00 0.40 0.83 0.33 0.00 0.50
7 1.00 1.00 1.00 1.00 0.50 0.00
7.5 0.89 0.50 1.00 0.67 1.00 1.00
7.5 0.89 0.50 1.00 0.67 1.00 1.00
9.5 0.89 0.30 1.00 0.33 0.00 1.00
6 0.89 0.30 0.83 0.33 0.50 1.00
10 0.89 0.30 0.50 0.00 0.00 1.00
7 1.00 0.40 0.67 0.33 0.50 0.50
3 0.67 0.50 1.00 0.33 0.00 1.00
6 1.00 0.50 0.67 0.67 0.50 1.00
7 0.89 0.40 1.00 0.00 0.00 0.00
10 0.89 0.70 1.00 1.00 0.50 0.00
7 0.89 0.50 0.50 0.33 0.00 0.50
3.5 0.89 0.40 0.67 0.33 1.00 0.00
8 1.00 0.70 0.67 1.00 0.00 1.00
10 1.00 0.70 0.67 1.00 0.00 1.00
5.5 1.00 0.70 0.67 1.00 0.00 1.00
6 0.89 0.70 0.67 1.00 0.00 1.00
6.5 0.89 0.70 0.67 0.00 0.00 0.00
6.5 0.89 0.70 1.00 0.67 0.50 1.00
8.5 0.33 0.10 0.67 0.33 0.50 0.00
4 0.67 0.20 0.67 0.67 0.50 1.00
9.5 0.56 0.30 0.33 0.33 0.00 1.00
8 0.44 0.60 0.83 0.33 0.00 0.50
8.5 1.00 0.80 1.00 1.00 1.00 1.00
5.5 0.89 0.80 1.00 0.33 0.50 0.50
7 0.33 0.00 0.17 0.00 0.00 0.00
9 0.67 0.30 0.67 0.33 0.00 1.00
8 0.67 0.60 0.83 0.33 0.50 1.00
10 1.00 0.50 0.83 0.67 0.00 1.00
8 0.78 0.70 1.00 0.33 0.00 0.50
6 0.67 0.30 0.83 0.00 0.50 1.00
8 1.00 0.30 1.00 0.67 0.00 0.00
5 0.78 0.40 1.00 0.67 0.00 0.50
9 0.89 0.40 0.83 1.00 0.00 1.00
4.5 0.89 0.10 0.83 0.00 0.00 1.00
8.5 0.89 0.50 1.00 0.67 0.00 1.00
9.5 0.00 0.00 0.00 0.00 0.00 0.00
8.5 0.67 0.40 1.00 0.33 0.50 0.00
7.5 1.00 0.60 0.83 0.67 1.00 0.50
7.5 1.00 0.40 1.00 0.33 0.50 1.00
5 0.67 0.10 0.33 0.00 0.50 1.00
7 0.89 0.30 0.83 0.00 0.00 1.00
8 0.89 0.70 0.83 0.67 0.00 1.00
5.5 0.56 0.30 0.17 0.00 0.00 1.00
8.5 0.67 0.50 0.83 0.33 0.50 0.00
9.5 1.00 0.30 0.83 0.67 1.00 1.00
7 1.00 0.60 0.67 0.67 0.50 1.00
8 1.00 0.90 1.00 1.00 0.00 1.00
8.5 0.67 0.40 0.83 0.00 0.50 1.00
3.5 0.44 0.30 1.00 0.00 0.50 0.50
6.5 0.89 0.90 1.00 0.67 1.00 1.00
6.5 0.44 0.50 1.00 0.00 0.50 0.00
10.5 0.56 0.30 1.00 1.00 0.50 0.50
8.5 0.89 0.60 0.83 0.67 0.00 0.50
8 0.67 0.20 1.00 0.33 0.00 0.50
10 0.89 0.40 0.83 1.00 0.50 1.00
10 1.00 0.50 0.83 0.67 0.50 0.50
9.5 0.78 0.40 0.83 0.67 0.00 0.50
9 0.44 0.00 0.00 0.00 0.00 0.00
10 0.89 0.20 1.00 0.33 0.50 1.00
7.5 0.89 0.50 1.00 0.67 0.50 1.00
4.5 0.89 0.30 1.00 0.67 0.00 0.50
4.5 0.44 0.00 0.00 0.00 0.00 0.00
0.5 1.00 0.50 0.83 1.00 0.00 1.00
6.5 0.89 0.60 0.83 0.33 0.00 1.00
4.5 0.67 0.30 0.83 0.00 0.50 0.50
5.5 0.33 0.00 0.00 0.00 0.00 0.00
5 0.78 0.30 0.67 0.00 0.50 0.00
6 0.89 0.50 1.00 0.67 0.50 1.00
4 0.78 0.40 0.67 0.00 0.00 1.00
8 0.78 0.50 0.83 0.67 0.00 0.50
10.5 0.89 0.70 1.00 1.00 1.00 0.50
6.5 0.78 0.80 1.00 0.67 0.50 1.00
8 0.78 0.60 1.00 0.33 0.50 1.00
8.5 0.67 0.40 0.83 0.33 0.00 0.50
5.5 0.89 0.50 0.83 0.33 0.50 0.00
7 0.89 0.50 1.00 0.00 0.50 1.00
5 0.78 0.30 1.00 0.33 0.00 1.00
3.5 1.00 0.60 1.00 0.00 0.50 1.00
5 1.00 0.30 0.67 0.67 0.00 0.50
9 0.78 0.60 0.83 1.00 0.50 0.50
8.5 0.78 0.30 0.33 0.33 0.00 1.00
5 0.89 0.70 1.00 0.67 1.00 1.00
9.5 0.89 0.70 1.00 1.00 0.00 1.00
3 0.67 0.60 0.67 1.00 0.50 1.00
1.5 1.00 0.50 1.00 0.33 0.50 0.00
6 0.67 0.50 0.83 0.33 0.00 0.50
0.5 0.56 0.40 0.67 0.00 0.00 1.00
6.5 0.78 0.40 1.00 0.33 1.00 1.00
7.5 1.00 0.70 1.00 1.00 0.00 1.00
4.5 0.67 0.20 0.17 0.00 0.50 0.00
8 0.78 0.50 0.83 0.67 0.00 0.50
9 0.56 0.40 0.83 0.67 0.50 0.00
7.5 1.00 0.20 1.00 0.67 1.00 1.00
8.5 0.89 0.50 0.67 0.67 0.00 0.00
7 0.44 0.40 0.50 0.00 0.00 1.00
9.5 1.00 0.70 0.67 1.00 1.00 1.00
6.5 0.89 0.60 0.83 0.67 1.00 0.00
9.5 0.78 0.40 0.83 0.00 0.00 0.00
6 0.89 0.50 1.00 0.67 1.00 1.00
8 0.11 0.00 0.17 0.00 0.00 0.00
9.5 0.89 0.70 1.00 0.67 0.50 1.00
8 0.89 0.40 0.67 0.67 0.00 1.00
8 1.00 0.50 0.67 1.00 0.00 1.00
9 0.89 0.60 0.83 0.67 0.00 0.50
5 1.00 0.80 0.50 0.67 0.50 0.50

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	10 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 10 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265719&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265719&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265719&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	10 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 4.87736 + 0.403322Calculation[t] -0.289335Algebraic_Reasoning[t] + 0.621705Graphical_Interpretation[t] + 1.42821Proportionality_and_Ratio[t] + 0.353074Probability_and_Sampling[t] -0.266296Estimation[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  4.87736 +  0.403322Calculation[t] -0.289335Algebraic_Reasoning[t] +  0.621705Graphical_Interpretation[t] +  1.42821Proportionality_and_Ratio[t] +  0.353074Probability_and_Sampling[t] -0.266296Estimation[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265719&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  4.87736 +  0.403322Calculation[t] -0.289335Algebraic_Reasoning[t] +  0.621705Graphical_Interpretation[t] +  1.42821Proportionality_and_Ratio[t] +  0.353074Probability_and_Sampling[t] -0.266296Estimation[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265719&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265719&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
Ex[t] = + 4.87736 + 0.403322Calculation[t] -0.289335Algebraic_Reasoning[t] + 0.621705Graphical_Interpretation[t] + 1.42821Proportionality_and_Ratio[t] + 0.353074Probability_and_Sampling[t] -0.266296Estimation[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	4.87736	0.726548	6.713	1.11306e-10	5.56531e-11
Calculation	0.403322	1.00788	0.4002	0.689347	0.344674
Algebraic_Reasoning	-0.289335	0.92381	-0.3132	0.754372	0.377186
Graphical_Interpretation	0.621705	0.741487	0.8385	0.402513	0.201256
Proportionality_and_Ratio	1.42821	0.468842	3.046	0.00254553	0.00127276
Probability_and_Sampling	0.353074	0.42926	0.8225	0.411505	0.205753
Estimation	-0.266296	0.416806	-0.6389	0.52343	0.261715

\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) & 4.87736 & 0.726548 & 6.713 & 1.11306e-10 & 5.56531e-11 \tabularnewline
Calculation & 0.403322 & 1.00788 & 0.4002 & 0.689347 & 0.344674 \tabularnewline
Algebraic_Reasoning & -0.289335 & 0.92381 & -0.3132 & 0.754372 & 0.377186 \tabularnewline
Graphical_Interpretation & 0.621705 & 0.741487 & 0.8385 & 0.402513 & 0.201256 \tabularnewline
Proportionality_and_Ratio & 1.42821 & 0.468842 & 3.046 & 0.00254553 & 0.00127276 \tabularnewline
Probability_and_Sampling & 0.353074 & 0.42926 & 0.8225 & 0.411505 & 0.205753 \tabularnewline
Estimation & -0.266296 & 0.416806 & -0.6389 & 0.52343 & 0.261715 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265719&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]4.87736[/C][C]0.726548[/C][C]6.713[/C][C]1.11306e-10[/C][C]5.56531e-11[/C][/ROW]
[ROW][C]Calculation[/C][C]0.403322[/C][C]1.00788[/C][C]0.4002[/C][C]0.689347[/C][C]0.344674[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]-0.289335[/C][C]0.92381[/C][C]-0.3132[/C][C]0.754372[/C][C]0.377186[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]0.621705[/C][C]0.741487[/C][C]0.8385[/C][C]0.402513[/C][C]0.201256[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]1.42821[/C][C]0.468842[/C][C]3.046[/C][C]0.00254553[/C][C]0.00127276[/C][/ROW]
[ROW][C]Probability_and_Sampling[/C][C]0.353074[/C][C]0.42926[/C][C]0.8225[/C][C]0.411505[/C][C]0.205753[/C][/ROW]
[ROW][C]Estimation[/C][C]-0.266296[/C][C]0.416806[/C][C]-0.6389[/C][C]0.52343[/C][C]0.261715[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265719&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265719&T=2

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	4.87736	0.726548	6.713	1.11306e-10	5.56531e-11
Calculation	0.403322	1.00788	0.4002	0.689347	0.344674
Algebraic_Reasoning	-0.289335	0.92381	-0.3132	0.754372	0.377186
Graphical_Interpretation	0.621705	0.741487	0.8385	0.402513	0.201256
Proportionality_and_Ratio	1.42821	0.468842	3.046	0.00254553	0.00127276
Probability_and_Sampling	0.353074	0.42926	0.8225	0.411505	0.205753
Estimation	-0.266296	0.416806	-0.6389	0.52343	0.261715

Multiple Linear Regression - Regression Statistics
Multiple R	0.236567
R-squared	0.0559641
Adjusted R-squared	0.0350629
F-TEST (value)	2.67756
F-TEST (DF numerator)	6
F-TEST (DF denominator)	271
p-value	0.0153294
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.48882
Sum Squared Residuals	1678.63

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.236567 \tabularnewline
R-squared & 0.0559641 \tabularnewline
Adjusted R-squared & 0.0350629 \tabularnewline
F-TEST (value) & 2.67756 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 271 \tabularnewline
p-value & 0.0153294 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.48882 \tabularnewline
Sum Squared Residuals & 1678.63 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265719&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.236567[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0559641[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0350629[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]2.67756[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]271[/C][/ROW]
[ROW][C]p-value[/C][C]0.0153294[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.48882[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1678.63[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265719&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265719&T=3

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Regression Statistics
Multiple R	0.236567
R-squared	0.0559641
Adjusted R-squared	0.0350629
F-TEST (value)	2.67756
F-TEST (DF numerator)	6
F-TEST (DF denominator)	271
p-value	0.0153294
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.48882
Sum Squared Residuals	1678.63

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	7.5	6.37632	1.12368
2	6	5.98922	0.010781
3	6.5	6.4329	0.0671018
4	1	5.60767	-4.60767
5	1	5.53711	-4.53711
6	5.5	5.14854	0.351458
7	8.5	6.77004	1.72996
8	6.5	6.51949	-0.0194852
9	4.5	5.72634	-1.22634
10	2	6.22381	-4.22381
11	5	6.713	-1.713
12	0.5	5.59402	-5.09402
13	5	5.78568	-0.785679
14	5	6.12205	-1.12205
15	2.5	5.9795	-3.4795
16	5	6.07896	-1.07896
17	5.5	6.1513	-0.6513
18	3.5	5.74315	-2.24315
19	3	5.75757	-2.75757
20	4	5.28433	-1.28433
21	0.5	6.23976	-5.73976
22	6.5	5.88944	0.610562
23	4.5	5.73938	-1.23938
24	7.5	5.89948	1.60052
25	5.5	6.96547	-1.46547
26	4	5.36913	-1.36913
27	7.5	6.17114	1.32886
28	7	6.46036	0.539644
29	4	6.90421	-2.90421
30	5.5	6.42949	-0.929492
31	2.5	5.60905	-3.10905
32	5.5	5.44737	0.0526312
33	3.5	6.65578	-3.15578
34	2.5	6.46312	-3.96312
35	4.5	6.93512	-2.43512
36	4.5	7.19846	-2.69846
37	4.5	5.70582	-1.20582
38	6	5.72717	0.272834
39	2.5	6.60796	-4.10796
40	5	6.52263	-1.52263
41	0	6.64035	-6.64035
42	5	6.60944	-1.60944
43	6.5	6.06598	0.434025
44	5	6.94857	-1.94857
45	6	6.26741	-0.267411
46	4.5	6.65233	-2.15233
47	5.5	5.22301	0.276991
48	1	5.57578	-4.57578
49	7.5	4.93105	2.56895
50	6	6.84389	-0.84389
51	5	6.91912	-1.91912
52	1	5.59371	-4.59371
53	5	6.59431	-1.59431
54	6.5	5.62457	0.875426
55	7	5.87446	1.12554
56	4.5	6.77247	-2.27247
57	0	6.75415	-6.75415
58	8.5	5.10387	3.39613
59	3.5	5.62907	-2.12907
60	7.5	6.50913	0.990867
61	3.5	6.84775	-3.34775
62	6	5.38674	0.613258
63	1.5	7.02095	-5.52095
64	9	6.56259	2.43741
65	3.5	5.44737	-1.94737
66	3.5	6.85639	-3.35639
67	4	6.41777	-2.41777
68	6.5	6.45837	0.0416259
69	7.5	7.00878	0.491217
70	6	5.66802	0.331985
71	5	5.90242	-0.902419
72	5.5	6.36088	-0.860883
73	3.5	6.09343	-2.59343
74	7.5	6.47481	1.02519
75	6.5	5.5217	0.978304
76	NA	NA	0.95335
77	6.5	6.62339	-0.123392
78	6.5	5.58045	0.919547
79	7	8.98404	-1.98404
80	3.5	7.56328	-4.06328
81	1.5	3.43166	-1.93166
82	4	1.87164	2.12836
83	7.5	9.43045	-1.93045
84	4.5	10.4029	-5.90294
85	0	2.58572	-2.58572
86	3.5	3.99365	-0.493653
87	5.5	6.60969	-1.10969
88	5	7.29852	-2.29852
89	4.5	8.68472	-4.18472
90	2.5	0.179341	2.32066
91	7.5	6.9903	0.509704
92	7	13.0351	-6.03511
93	0	0.768072	-0.768072
94	4.5	7.55054	-3.05054
95	3	6.79701	-3.79701
96	1.5	3.21296	-1.71296
97	3.5	6.94678	-3.44678
98	2.5	3.7845	-1.2845
99	5.5	3.94588	1.55412
100	8	13.4594	-5.45938
101	1	2.47757	-1.47757
102	5	7.41624	-2.41624
103	4.5	6.58972	-2.08972
104	3	5.45909	-2.45909
105	3	0.580209	2.41979
106	8	10.843	-2.84301
107	2.5	0.632586	1.86741
108	7	13.6492	-6.64922
109	0	5.15098	-5.15098
110	1	2.99148	-1.99148
111	3.5	4.36088	-0.860883
112	5.5	6.23848	-0.738478
113	5.5	10.7268	-5.22684
114	0.5	-0.22946	0.72946
115	7.5	4.88916	2.61084
116	9	6.83058	2.16942
117	9.5	8.03932	1.46068
118	8.5	7.02041	1.47959
119	7	5.85932	1.14068
120	8	4.81491	3.18509
121	10	9.34264	0.65736
122	7	4.06478	2.93522
123	8.5	5.76741	2.73259
124	9	6.26959	2.73041
125	9.5	11.8731	-2.3731
126	4	3.21103	0.788966
127	6	3.41467	2.58533
128	8	8.04934	-0.0493449
129	5.5	2.24349	3.25651
130	9.5	8.62242	0.877584
131	7.5	7.75728	-0.257283
132	7	5.28666	1.71334
133	7.5	5.97732	1.52268
134	8	7.25171	0.748289
135	7	6.62454	0.375458
136	7	7.16518	-0.165179
137	6	2.74161	3.25839
138	10	14.2436	-4.24356
139	2.5	-0.128426	2.62843
140	9	7.56635	1.43365
141	8	8.7247	-0.7247
142	6	3.68171	2.31829
143	8.5	7.51046	0.989541
144	6	3.60944	2.39056
145	9	6.72684	2.27316
146	8	5.40525	2.59475
147	9	8.92765	0.0723526
148	5.5	4.22441	1.27559
149	7	6.73482	0.265181
150	5.5	3.65159	1.84841
151	9	12.5324	-3.53239
152	2	0.433077	1.56692
153	8.5	6.24065	2.25935
154	9	5.8703	3.1297
155	8.5	6.43455	2.06545
156	9	7.04684	1.95316
157	7.5	4.74378	2.75622
158	10	7.40151	2.59849
159	9	7.9204	1.0796
160	7.5	8.18131	-0.68131
161	6	2.46501	3.53499
162	10.5	8.68085	1.81915
163	8.5	7.52045	0.97955
164	8	4.91912	3.08088
165	10	6.80363	3.19637
166	10.5	10.256	0.243986
167	6.5	3.53807	2.96193
168	9.5	8.4348	1.0652
169	8.5	7.63934	0.860655
170	7.5	8.99177	-1.49177
171	5	3.67024	1.32976
172	8	4.01913	3.98087
173	10	10.2178	-0.217806
174	7	6.25704	0.742961
175	7.5	6.75704	0.742961
176	7.5	3.97624	3.52376
177	9.5	9.54709	-0.0470859
178	6	1.19408	4.80592
179	10	9.09619	0.903807
180	7	9.82964	-2.82964
181	3	3.4197	-0.419705
182	6	4.74229	1.25771
183	7	4.26024	2.73976
184	10	8.74067	1.25933
185	7	9.86151	-2.86151
186	3.5	2.15661	1.34339
187	8	4.65661	3.34339
188	10	11.1566	-1.15661
189	5.5	6.11225	-0.612246
190	6	4.95033	1.04967
191	6.5	6.52263	-0.0226349
192	6.5	4.04592	2.45408
193	8.5	10.8734	-2.37341
194	4	-0.0733999	4.0734
195	9.5	7.2354	2.2646
196	8	6.68591	1.31409
197	8.5	9.14126	-0.641256
198	5.5	3.61615	1.88385
199	7	3.68235	3.31765
200	9	6.87155	2.12845
201	8	4.34264	3.65736
202	10	7.94929	2.05071
203	8	7.48704	0.512956
204	6	4.77249	1.22751
205	8	9.52168	-1.52168
206	5	2.79852	2.20148
207	9	9.9571	-0.957105
208	4.5	2.40396	2.09604
209	8.5	3.87736	4.62264
210	9.5	7.30141	2.19859
211	8.5	7.79993	0.700071
212	7.5	6.16821	1.33179
213	7.5	7.73406	-0.234059
214	5	3.39924	1.60076
215	7	5.24041	1.75959
216	8	7.35582	0.644184
217	5.5	3.16678	2.33322
218	8.5	5.75358	2.74642
219	9.5	8.89077	0.609229
220	7	5.80391	1.19609
221	8	4.95811	3.04189
222	8.5	10.6331	-2.13312
223	3.5	3.64131	-0.141305
224	6.5	5.7084	0.791601
225	6.5	3.10973	3.39027
226	10.5	8.40249	2.09751
227	8.5	6.54959	1.95041
228	8	4.97506	3.02494
229	10	6.65233	3.34767
230	10	6.91599	3.08401
231	9.5	5.55482	3.94518
232	9	5.18171	3.81829
233	10	9.0805	0.919498
234	7.5	9.59498	-2.09498
235	4.5	5.05482	-0.554824
236	4.5	10.814	-6.31395
237	0.5	-0.216252	0.716252
238	6.5	7.62019	-1.12019
239	4.5	4.01046	0.489541
240	5.5	6.19823	-0.698233
241	5	5.5805	-0.580502
242	6	7.22647	-1.22647
243	4	2.38706	1.61294
244	8	4.80363	3.19637
245	10.5	10.4493	0.050664
246	6.5	4.52161	1.97839
247	8	5.38603	2.61397
248	8.5	9.25551	-0.755515
249	5.5	4.1236	1.3764
250	7	7.93187	-0.931873
251	5	7.13903	-2.13903
252	3.5	4.93418	-1.43418
253	5	3.00597	1.99403
254	9	6.01533	2.98467
255	8.5	10.1992	-1.69917
256	5	2.31741	2.68259
257	9.5	13.229	-3.72899
258	3	7.90557	-4.90557
259	1.5	1.3571	0.142901
260	6	10.6377	-4.63774
261	0.5	0.256014	0.243986
262	6.5	5.86177	0.638226
263	7.5	8.37195	-0.871948
264	4.5	2.88706	1.61294
265	8	5.63694	2.36306
266	9	8.3882	0.611795
267	7.5	5.4651	2.0349
268	8.5	6.48365	2.01635
269	7	4.50969	2.49031
270	9.5	9.88871	-0.388711
271	6.5	2.59223	3.90777
272	9.5	10.257	-0.757039
273	6	3.02742	2.97258
274	8	5.02263	2.97737
275	9.5	7.72774	1.77226
276	8	6.71448	1.28552
277	8	5.40249	2.59751
278	9	10.3604	-1.36036
279	5	NA	NA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 6.37632 & 1.12368 \tabularnewline
2 & 6 & 5.98922 & 0.010781 \tabularnewline
3 & 6.5 & 6.4329 & 0.0671018 \tabularnewline
4 & 1 & 5.60767 & -4.60767 \tabularnewline
5 & 1 & 5.53711 & -4.53711 \tabularnewline
6 & 5.5 & 5.14854 & 0.351458 \tabularnewline
7 & 8.5 & 6.77004 & 1.72996 \tabularnewline
8 & 6.5 & 6.51949 & -0.0194852 \tabularnewline
9 & 4.5 & 5.72634 & -1.22634 \tabularnewline
10 & 2 & 6.22381 & -4.22381 \tabularnewline
11 & 5 & 6.713 & -1.713 \tabularnewline
12 & 0.5 & 5.59402 & -5.09402 \tabularnewline
13 & 5 & 5.78568 & -0.785679 \tabularnewline
14 & 5 & 6.12205 & -1.12205 \tabularnewline
15 & 2.5 & 5.9795 & -3.4795 \tabularnewline
16 & 5 & 6.07896 & -1.07896 \tabularnewline
17 & 5.5 & 6.1513 & -0.6513 \tabularnewline
18 & 3.5 & 5.74315 & -2.24315 \tabularnewline
19 & 3 & 5.75757 & -2.75757 \tabularnewline
20 & 4 & 5.28433 & -1.28433 \tabularnewline
21 & 0.5 & 6.23976 & -5.73976 \tabularnewline
22 & 6.5 & 5.88944 & 0.610562 \tabularnewline
23 & 4.5 & 5.73938 & -1.23938 \tabularnewline
24 & 7.5 & 5.89948 & 1.60052 \tabularnewline
25 & 5.5 & 6.96547 & -1.46547 \tabularnewline
26 & 4 & 5.36913 & -1.36913 \tabularnewline
27 & 7.5 & 6.17114 & 1.32886 \tabularnewline
28 & 7 & 6.46036 & 0.539644 \tabularnewline
29 & 4 & 6.90421 & -2.90421 \tabularnewline
30 & 5.5 & 6.42949 & -0.929492 \tabularnewline
31 & 2.5 & 5.60905 & -3.10905 \tabularnewline
32 & 5.5 & 5.44737 & 0.0526312 \tabularnewline
33 & 3.5 & 6.65578 & -3.15578 \tabularnewline
34 & 2.5 & 6.46312 & -3.96312 \tabularnewline
35 & 4.5 & 6.93512 & -2.43512 \tabularnewline
36 & 4.5 & 7.19846 & -2.69846 \tabularnewline
37 & 4.5 & 5.70582 & -1.20582 \tabularnewline
38 & 6 & 5.72717 & 0.272834 \tabularnewline
39 & 2.5 & 6.60796 & -4.10796 \tabularnewline
40 & 5 & 6.52263 & -1.52263 \tabularnewline
41 & 0 & 6.64035 & -6.64035 \tabularnewline
42 & 5 & 6.60944 & -1.60944 \tabularnewline
43 & 6.5 & 6.06598 & 0.434025 \tabularnewline
44 & 5 & 6.94857 & -1.94857 \tabularnewline
45 & 6 & 6.26741 & -0.267411 \tabularnewline
46 & 4.5 & 6.65233 & -2.15233 \tabularnewline
47 & 5.5 & 5.22301 & 0.276991 \tabularnewline
48 & 1 & 5.57578 & -4.57578 \tabularnewline
49 & 7.5 & 4.93105 & 2.56895 \tabularnewline
50 & 6 & 6.84389 & -0.84389 \tabularnewline
51 & 5 & 6.91912 & -1.91912 \tabularnewline
52 & 1 & 5.59371 & -4.59371 \tabularnewline
53 & 5 & 6.59431 & -1.59431 \tabularnewline
54 & 6.5 & 5.62457 & 0.875426 \tabularnewline
55 & 7 & 5.87446 & 1.12554 \tabularnewline
56 & 4.5 & 6.77247 & -2.27247 \tabularnewline
57 & 0 & 6.75415 & -6.75415 \tabularnewline
58 & 8.5 & 5.10387 & 3.39613 \tabularnewline
59 & 3.5 & 5.62907 & -2.12907 \tabularnewline
60 & 7.5 & 6.50913 & 0.990867 \tabularnewline
61 & 3.5 & 6.84775 & -3.34775 \tabularnewline
62 & 6 & 5.38674 & 0.613258 \tabularnewline
63 & 1.5 & 7.02095 & -5.52095 \tabularnewline
64 & 9 & 6.56259 & 2.43741 \tabularnewline
65 & 3.5 & 5.44737 & -1.94737 \tabularnewline
66 & 3.5 & 6.85639 & -3.35639 \tabularnewline
67 & 4 & 6.41777 & -2.41777 \tabularnewline
68 & 6.5 & 6.45837 & 0.0416259 \tabularnewline
69 & 7.5 & 7.00878 & 0.491217 \tabularnewline
70 & 6 & 5.66802 & 0.331985 \tabularnewline
71 & 5 & 5.90242 & -0.902419 \tabularnewline
72 & 5.5 & 6.36088 & -0.860883 \tabularnewline
73 & 3.5 & 6.09343 & -2.59343 \tabularnewline
74 & 7.5 & 6.47481 & 1.02519 \tabularnewline
75 & 6.5 & 5.5217 & 0.978304 \tabularnewline
76 & NA & NA & 0.95335 \tabularnewline
77 & 6.5 & 6.62339 & -0.123392 \tabularnewline
78 & 6.5 & 5.58045 & 0.919547 \tabularnewline
79 & 7 & 8.98404 & -1.98404 \tabularnewline
80 & 3.5 & 7.56328 & -4.06328 \tabularnewline
81 & 1.5 & 3.43166 & -1.93166 \tabularnewline
82 & 4 & 1.87164 & 2.12836 \tabularnewline
83 & 7.5 & 9.43045 & -1.93045 \tabularnewline
84 & 4.5 & 10.4029 & -5.90294 \tabularnewline
85 & 0 & 2.58572 & -2.58572 \tabularnewline
86 & 3.5 & 3.99365 & -0.493653 \tabularnewline
87 & 5.5 & 6.60969 & -1.10969 \tabularnewline
88 & 5 & 7.29852 & -2.29852 \tabularnewline
89 & 4.5 & 8.68472 & -4.18472 \tabularnewline
90 & 2.5 & 0.179341 & 2.32066 \tabularnewline
91 & 7.5 & 6.9903 & 0.509704 \tabularnewline
92 & 7 & 13.0351 & -6.03511 \tabularnewline
93 & 0 & 0.768072 & -0.768072 \tabularnewline
94 & 4.5 & 7.55054 & -3.05054 \tabularnewline
95 & 3 & 6.79701 & -3.79701 \tabularnewline
96 & 1.5 & 3.21296 & -1.71296 \tabularnewline
97 & 3.5 & 6.94678 & -3.44678 \tabularnewline
98 & 2.5 & 3.7845 & -1.2845 \tabularnewline
99 & 5.5 & 3.94588 & 1.55412 \tabularnewline
100 & 8 & 13.4594 & -5.45938 \tabularnewline
101 & 1 & 2.47757 & -1.47757 \tabularnewline
102 & 5 & 7.41624 & -2.41624 \tabularnewline
103 & 4.5 & 6.58972 & -2.08972 \tabularnewline
104 & 3 & 5.45909 & -2.45909 \tabularnewline
105 & 3 & 0.580209 & 2.41979 \tabularnewline
106 & 8 & 10.843 & -2.84301 \tabularnewline
107 & 2.5 & 0.632586 & 1.86741 \tabularnewline
108 & 7 & 13.6492 & -6.64922 \tabularnewline
109 & 0 & 5.15098 & -5.15098 \tabularnewline
110 & 1 & 2.99148 & -1.99148 \tabularnewline
111 & 3.5 & 4.36088 & -0.860883 \tabularnewline
112 & 5.5 & 6.23848 & -0.738478 \tabularnewline
113 & 5.5 & 10.7268 & -5.22684 \tabularnewline
114 & 0.5 & -0.22946 & 0.72946 \tabularnewline
115 & 7.5 & 4.88916 & 2.61084 \tabularnewline
116 & 9 & 6.83058 & 2.16942 \tabularnewline
117 & 9.5 & 8.03932 & 1.46068 \tabularnewline
118 & 8.5 & 7.02041 & 1.47959 \tabularnewline
119 & 7 & 5.85932 & 1.14068 \tabularnewline
120 & 8 & 4.81491 & 3.18509 \tabularnewline
121 & 10 & 9.34264 & 0.65736 \tabularnewline
122 & 7 & 4.06478 & 2.93522 \tabularnewline
123 & 8.5 & 5.76741 & 2.73259 \tabularnewline
124 & 9 & 6.26959 & 2.73041 \tabularnewline
125 & 9.5 & 11.8731 & -2.3731 \tabularnewline
126 & 4 & 3.21103 & 0.788966 \tabularnewline
127 & 6 & 3.41467 & 2.58533 \tabularnewline
128 & 8 & 8.04934 & -0.0493449 \tabularnewline
129 & 5.5 & 2.24349 & 3.25651 \tabularnewline
130 & 9.5 & 8.62242 & 0.877584 \tabularnewline
131 & 7.5 & 7.75728 & -0.257283 \tabularnewline
132 & 7 & 5.28666 & 1.71334 \tabularnewline
133 & 7.5 & 5.97732 & 1.52268 \tabularnewline
134 & 8 & 7.25171 & 0.748289 \tabularnewline
135 & 7 & 6.62454 & 0.375458 \tabularnewline
136 & 7 & 7.16518 & -0.165179 \tabularnewline
137 & 6 & 2.74161 & 3.25839 \tabularnewline
138 & 10 & 14.2436 & -4.24356 \tabularnewline
139 & 2.5 & -0.128426 & 2.62843 \tabularnewline
140 & 9 & 7.56635 & 1.43365 \tabularnewline
141 & 8 & 8.7247 & -0.7247 \tabularnewline
142 & 6 & 3.68171 & 2.31829 \tabularnewline
143 & 8.5 & 7.51046 & 0.989541 \tabularnewline
144 & 6 & 3.60944 & 2.39056 \tabularnewline
145 & 9 & 6.72684 & 2.27316 \tabularnewline
146 & 8 & 5.40525 & 2.59475 \tabularnewline
147 & 9 & 8.92765 & 0.0723526 \tabularnewline
148 & 5.5 & 4.22441 & 1.27559 \tabularnewline
149 & 7 & 6.73482 & 0.265181 \tabularnewline
150 & 5.5 & 3.65159 & 1.84841 \tabularnewline
151 & 9 & 12.5324 & -3.53239 \tabularnewline
152 & 2 & 0.433077 & 1.56692 \tabularnewline
153 & 8.5 & 6.24065 & 2.25935 \tabularnewline
154 & 9 & 5.8703 & 3.1297 \tabularnewline
155 & 8.5 & 6.43455 & 2.06545 \tabularnewline
156 & 9 & 7.04684 & 1.95316 \tabularnewline
157 & 7.5 & 4.74378 & 2.75622 \tabularnewline
158 & 10 & 7.40151 & 2.59849 \tabularnewline
159 & 9 & 7.9204 & 1.0796 \tabularnewline
160 & 7.5 & 8.18131 & -0.68131 \tabularnewline
161 & 6 & 2.46501 & 3.53499 \tabularnewline
162 & 10.5 & 8.68085 & 1.81915 \tabularnewline
163 & 8.5 & 7.52045 & 0.97955 \tabularnewline
164 & 8 & 4.91912 & 3.08088 \tabularnewline
165 & 10 & 6.80363 & 3.19637 \tabularnewline
166 & 10.5 & 10.256 & 0.243986 \tabularnewline
167 & 6.5 & 3.53807 & 2.96193 \tabularnewline
168 & 9.5 & 8.4348 & 1.0652 \tabularnewline
169 & 8.5 & 7.63934 & 0.860655 \tabularnewline
170 & 7.5 & 8.99177 & -1.49177 \tabularnewline
171 & 5 & 3.67024 & 1.32976 \tabularnewline
172 & 8 & 4.01913 & 3.98087 \tabularnewline
173 & 10 & 10.2178 & -0.217806 \tabularnewline
174 & 7 & 6.25704 & 0.742961 \tabularnewline
175 & 7.5 & 6.75704 & 0.742961 \tabularnewline
176 & 7.5 & 3.97624 & 3.52376 \tabularnewline
177 & 9.5 & 9.54709 & -0.0470859 \tabularnewline
178 & 6 & 1.19408 & 4.80592 \tabularnewline
179 & 10 & 9.09619 & 0.903807 \tabularnewline
180 & 7 & 9.82964 & -2.82964 \tabularnewline
181 & 3 & 3.4197 & -0.419705 \tabularnewline
182 & 6 & 4.74229 & 1.25771 \tabularnewline
183 & 7 & 4.26024 & 2.73976 \tabularnewline
184 & 10 & 8.74067 & 1.25933 \tabularnewline
185 & 7 & 9.86151 & -2.86151 \tabularnewline
186 & 3.5 & 2.15661 & 1.34339 \tabularnewline
187 & 8 & 4.65661 & 3.34339 \tabularnewline
188 & 10 & 11.1566 & -1.15661 \tabularnewline
189 & 5.5 & 6.11225 & -0.612246 \tabularnewline
190 & 6 & 4.95033 & 1.04967 \tabularnewline
191 & 6.5 & 6.52263 & -0.0226349 \tabularnewline
192 & 6.5 & 4.04592 & 2.45408 \tabularnewline
193 & 8.5 & 10.8734 & -2.37341 \tabularnewline
194 & 4 & -0.0733999 & 4.0734 \tabularnewline
195 & 9.5 & 7.2354 & 2.2646 \tabularnewline
196 & 8 & 6.68591 & 1.31409 \tabularnewline
197 & 8.5 & 9.14126 & -0.641256 \tabularnewline
198 & 5.5 & 3.61615 & 1.88385 \tabularnewline
199 & 7 & 3.68235 & 3.31765 \tabularnewline
200 & 9 & 6.87155 & 2.12845 \tabularnewline
201 & 8 & 4.34264 & 3.65736 \tabularnewline
202 & 10 & 7.94929 & 2.05071 \tabularnewline
203 & 8 & 7.48704 & 0.512956 \tabularnewline
204 & 6 & 4.77249 & 1.22751 \tabularnewline
205 & 8 & 9.52168 & -1.52168 \tabularnewline
206 & 5 & 2.79852 & 2.20148 \tabularnewline
207 & 9 & 9.9571 & -0.957105 \tabularnewline
208 & 4.5 & 2.40396 & 2.09604 \tabularnewline
209 & 8.5 & 3.87736 & 4.62264 \tabularnewline
210 & 9.5 & 7.30141 & 2.19859 \tabularnewline
211 & 8.5 & 7.79993 & 0.700071 \tabularnewline
212 & 7.5 & 6.16821 & 1.33179 \tabularnewline
213 & 7.5 & 7.73406 & -0.234059 \tabularnewline
214 & 5 & 3.39924 & 1.60076 \tabularnewline
215 & 7 & 5.24041 & 1.75959 \tabularnewline
216 & 8 & 7.35582 & 0.644184 \tabularnewline
217 & 5.5 & 3.16678 & 2.33322 \tabularnewline
218 & 8.5 & 5.75358 & 2.74642 \tabularnewline
219 & 9.5 & 8.89077 & 0.609229 \tabularnewline
220 & 7 & 5.80391 & 1.19609 \tabularnewline
221 & 8 & 4.95811 & 3.04189 \tabularnewline
222 & 8.5 & 10.6331 & -2.13312 \tabularnewline
223 & 3.5 & 3.64131 & -0.141305 \tabularnewline
224 & 6.5 & 5.7084 & 0.791601 \tabularnewline
225 & 6.5 & 3.10973 & 3.39027 \tabularnewline
226 & 10.5 & 8.40249 & 2.09751 \tabularnewline
227 & 8.5 & 6.54959 & 1.95041 \tabularnewline
228 & 8 & 4.97506 & 3.02494 \tabularnewline
229 & 10 & 6.65233 & 3.34767 \tabularnewline
230 & 10 & 6.91599 & 3.08401 \tabularnewline
231 & 9.5 & 5.55482 & 3.94518 \tabularnewline
232 & 9 & 5.18171 & 3.81829 \tabularnewline
233 & 10 & 9.0805 & 0.919498 \tabularnewline
234 & 7.5 & 9.59498 & -2.09498 \tabularnewline
235 & 4.5 & 5.05482 & -0.554824 \tabularnewline
236 & 4.5 & 10.814 & -6.31395 \tabularnewline
237 & 0.5 & -0.216252 & 0.716252 \tabularnewline
238 & 6.5 & 7.62019 & -1.12019 \tabularnewline
239 & 4.5 & 4.01046 & 0.489541 \tabularnewline
240 & 5.5 & 6.19823 & -0.698233 \tabularnewline
241 & 5 & 5.5805 & -0.580502 \tabularnewline
242 & 6 & 7.22647 & -1.22647 \tabularnewline
243 & 4 & 2.38706 & 1.61294 \tabularnewline
244 & 8 & 4.80363 & 3.19637 \tabularnewline
245 & 10.5 & 10.4493 & 0.050664 \tabularnewline
246 & 6.5 & 4.52161 & 1.97839 \tabularnewline
247 & 8 & 5.38603 & 2.61397 \tabularnewline
248 & 8.5 & 9.25551 & -0.755515 \tabularnewline
249 & 5.5 & 4.1236 & 1.3764 \tabularnewline
250 & 7 & 7.93187 & -0.931873 \tabularnewline
251 & 5 & 7.13903 & -2.13903 \tabularnewline
252 & 3.5 & 4.93418 & -1.43418 \tabularnewline
253 & 5 & 3.00597 & 1.99403 \tabularnewline
254 & 9 & 6.01533 & 2.98467 \tabularnewline
255 & 8.5 & 10.1992 & -1.69917 \tabularnewline
256 & 5 & 2.31741 & 2.68259 \tabularnewline
257 & 9.5 & 13.229 & -3.72899 \tabularnewline
258 & 3 & 7.90557 & -4.90557 \tabularnewline
259 & 1.5 & 1.3571 & 0.142901 \tabularnewline
260 & 6 & 10.6377 & -4.63774 \tabularnewline
261 & 0.5 & 0.256014 & 0.243986 \tabularnewline
262 & 6.5 & 5.86177 & 0.638226 \tabularnewline
263 & 7.5 & 8.37195 & -0.871948 \tabularnewline
264 & 4.5 & 2.88706 & 1.61294 \tabularnewline
265 & 8 & 5.63694 & 2.36306 \tabularnewline
266 & 9 & 8.3882 & 0.611795 \tabularnewline
267 & 7.5 & 5.4651 & 2.0349 \tabularnewline
268 & 8.5 & 6.48365 & 2.01635 \tabularnewline
269 & 7 & 4.50969 & 2.49031 \tabularnewline
270 & 9.5 & 9.88871 & -0.388711 \tabularnewline
271 & 6.5 & 2.59223 & 3.90777 \tabularnewline
272 & 9.5 & 10.257 & -0.757039 \tabularnewline
273 & 6 & 3.02742 & 2.97258 \tabularnewline
274 & 8 & 5.02263 & 2.97737 \tabularnewline
275 & 9.5 & 7.72774 & 1.77226 \tabularnewline
276 & 8 & 6.71448 & 1.28552 \tabularnewline
277 & 8 & 5.40249 & 2.59751 \tabularnewline
278 & 9 & 10.3604 & -1.36036 \tabularnewline
279 & 5 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265719&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]7.5[/C][C]6.37632[/C][C]1.12368[/C][/ROW]
[ROW][C]2[/C][C]6[/C][C]5.98922[/C][C]0.010781[/C][/ROW]
[ROW][C]3[/C][C]6.5[/C][C]6.4329[/C][C]0.0671018[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]5.60767[/C][C]-4.60767[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]5.53711[/C][C]-4.53711[/C][/ROW]
[ROW][C]6[/C][C]5.5[/C][C]5.14854[/C][C]0.351458[/C][/ROW]
[ROW][C]7[/C][C]8.5[/C][C]6.77004[/C][C]1.72996[/C][/ROW]
[ROW][C]8[/C][C]6.5[/C][C]6.51949[/C][C]-0.0194852[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]5.72634[/C][C]-1.22634[/C][/ROW]
[ROW][C]10[/C][C]2[/C][C]6.22381[/C][C]-4.22381[/C][/ROW]
[ROW][C]11[/C][C]5[/C][C]6.713[/C][C]-1.713[/C][/ROW]
[ROW][C]12[/C][C]0.5[/C][C]5.59402[/C][C]-5.09402[/C][/ROW]
[ROW][C]13[/C][C]5[/C][C]5.78568[/C][C]-0.785679[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]6.12205[/C][C]-1.12205[/C][/ROW]
[ROW][C]15[/C][C]2.5[/C][C]5.9795[/C][C]-3.4795[/C][/ROW]
[ROW][C]16[/C][C]5[/C][C]6.07896[/C][C]-1.07896[/C][/ROW]
[ROW][C]17[/C][C]5.5[/C][C]6.1513[/C][C]-0.6513[/C][/ROW]
[ROW][C]18[/C][C]3.5[/C][C]5.74315[/C][C]-2.24315[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]5.75757[/C][C]-2.75757[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]5.28433[/C][C]-1.28433[/C][/ROW]
[ROW][C]21[/C][C]0.5[/C][C]6.23976[/C][C]-5.73976[/C][/ROW]
[ROW][C]22[/C][C]6.5[/C][C]5.88944[/C][C]0.610562[/C][/ROW]
[ROW][C]23[/C][C]4.5[/C][C]5.73938[/C][C]-1.23938[/C][/ROW]
[ROW][C]24[/C][C]7.5[/C][C]5.89948[/C][C]1.60052[/C][/ROW]
[ROW][C]25[/C][C]5.5[/C][C]6.96547[/C][C]-1.46547[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]5.36913[/C][C]-1.36913[/C][/ROW]
[ROW][C]27[/C][C]7.5[/C][C]6.17114[/C][C]1.32886[/C][/ROW]
[ROW][C]28[/C][C]7[/C][C]6.46036[/C][C]0.539644[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]6.90421[/C][C]-2.90421[/C][/ROW]
[ROW][C]30[/C][C]5.5[/C][C]6.42949[/C][C]-0.929492[/C][/ROW]
[ROW][C]31[/C][C]2.5[/C][C]5.60905[/C][C]-3.10905[/C][/ROW]
[ROW][C]32[/C][C]5.5[/C][C]5.44737[/C][C]0.0526312[/C][/ROW]
[ROW][C]33[/C][C]3.5[/C][C]6.65578[/C][C]-3.15578[/C][/ROW]
[ROW][C]34[/C][C]2.5[/C][C]6.46312[/C][C]-3.96312[/C][/ROW]
[ROW][C]35[/C][C]4.5[/C][C]6.93512[/C][C]-2.43512[/C][/ROW]
[ROW][C]36[/C][C]4.5[/C][C]7.19846[/C][C]-2.69846[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]5.70582[/C][C]-1.20582[/C][/ROW]
[ROW][C]38[/C][C]6[/C][C]5.72717[/C][C]0.272834[/C][/ROW]
[ROW][C]39[/C][C]2.5[/C][C]6.60796[/C][C]-4.10796[/C][/ROW]
[ROW][C]40[/C][C]5[/C][C]6.52263[/C][C]-1.52263[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]6.64035[/C][C]-6.64035[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]6.60944[/C][C]-1.60944[/C][/ROW]
[ROW][C]43[/C][C]6.5[/C][C]6.06598[/C][C]0.434025[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]6.94857[/C][C]-1.94857[/C][/ROW]
[ROW][C]45[/C][C]6[/C][C]6.26741[/C][C]-0.267411[/C][/ROW]
[ROW][C]46[/C][C]4.5[/C][C]6.65233[/C][C]-2.15233[/C][/ROW]
[ROW][C]47[/C][C]5.5[/C][C]5.22301[/C][C]0.276991[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]5.57578[/C][C]-4.57578[/C][/ROW]
[ROW][C]49[/C][C]7.5[/C][C]4.93105[/C][C]2.56895[/C][/ROW]
[ROW][C]50[/C][C]6[/C][C]6.84389[/C][C]-0.84389[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]6.91912[/C][C]-1.91912[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]5.59371[/C][C]-4.59371[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]6.59431[/C][C]-1.59431[/C][/ROW]
[ROW][C]54[/C][C]6.5[/C][C]5.62457[/C][C]0.875426[/C][/ROW]
[ROW][C]55[/C][C]7[/C][C]5.87446[/C][C]1.12554[/C][/ROW]
[ROW][C]56[/C][C]4.5[/C][C]6.77247[/C][C]-2.27247[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]6.75415[/C][C]-6.75415[/C][/ROW]
[ROW][C]58[/C][C]8.5[/C][C]5.10387[/C][C]3.39613[/C][/ROW]
[ROW][C]59[/C][C]3.5[/C][C]5.62907[/C][C]-2.12907[/C][/ROW]
[ROW][C]60[/C][C]7.5[/C][C]6.50913[/C][C]0.990867[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]6.84775[/C][C]-3.34775[/C][/ROW]
[ROW][C]62[/C][C]6[/C][C]5.38674[/C][C]0.613258[/C][/ROW]
[ROW][C]63[/C][C]1.5[/C][C]7.02095[/C][C]-5.52095[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]6.56259[/C][C]2.43741[/C][/ROW]
[ROW][C]65[/C][C]3.5[/C][C]5.44737[/C][C]-1.94737[/C][/ROW]
[ROW][C]66[/C][C]3.5[/C][C]6.85639[/C][C]-3.35639[/C][/ROW]
[ROW][C]67[/C][C]4[/C][C]6.41777[/C][C]-2.41777[/C][/ROW]
[ROW][C]68[/C][C]6.5[/C][C]6.45837[/C][C]0.0416259[/C][/ROW]
[ROW][C]69[/C][C]7.5[/C][C]7.00878[/C][C]0.491217[/C][/ROW]
[ROW][C]70[/C][C]6[/C][C]5.66802[/C][C]0.331985[/C][/ROW]
[ROW][C]71[/C][C]5[/C][C]5.90242[/C][C]-0.902419[/C][/ROW]
[ROW][C]72[/C][C]5.5[/C][C]6.36088[/C][C]-0.860883[/C][/ROW]
[ROW][C]73[/C][C]3.5[/C][C]6.09343[/C][C]-2.59343[/C][/ROW]
[ROW][C]74[/C][C]7.5[/C][C]6.47481[/C][C]1.02519[/C][/ROW]
[ROW][C]75[/C][C]6.5[/C][C]5.5217[/C][C]0.978304[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]0.95335[/C][/ROW]
[ROW][C]77[/C][C]6.5[/C][C]6.62339[/C][C]-0.123392[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]5.58045[/C][C]0.919547[/C][/ROW]
[ROW][C]79[/C][C]7[/C][C]8.98404[/C][C]-1.98404[/C][/ROW]
[ROW][C]80[/C][C]3.5[/C][C]7.56328[/C][C]-4.06328[/C][/ROW]
[ROW][C]81[/C][C]1.5[/C][C]3.43166[/C][C]-1.93166[/C][/ROW]
[ROW][C]82[/C][C]4[/C][C]1.87164[/C][C]2.12836[/C][/ROW]
[ROW][C]83[/C][C]7.5[/C][C]9.43045[/C][C]-1.93045[/C][/ROW]
[ROW][C]84[/C][C]4.5[/C][C]10.4029[/C][C]-5.90294[/C][/ROW]
[ROW][C]85[/C][C]0[/C][C]2.58572[/C][C]-2.58572[/C][/ROW]
[ROW][C]86[/C][C]3.5[/C][C]3.99365[/C][C]-0.493653[/C][/ROW]
[ROW][C]87[/C][C]5.5[/C][C]6.60969[/C][C]-1.10969[/C][/ROW]
[ROW][C]88[/C][C]5[/C][C]7.29852[/C][C]-2.29852[/C][/ROW]
[ROW][C]89[/C][C]4.5[/C][C]8.68472[/C][C]-4.18472[/C][/ROW]
[ROW][C]90[/C][C]2.5[/C][C]0.179341[/C][C]2.32066[/C][/ROW]
[ROW][C]91[/C][C]7.5[/C][C]6.9903[/C][C]0.509704[/C][/ROW]
[ROW][C]92[/C][C]7[/C][C]13.0351[/C][C]-6.03511[/C][/ROW]
[ROW][C]93[/C][C]0[/C][C]0.768072[/C][C]-0.768072[/C][/ROW]
[ROW][C]94[/C][C]4.5[/C][C]7.55054[/C][C]-3.05054[/C][/ROW]
[ROW][C]95[/C][C]3[/C][C]6.79701[/C][C]-3.79701[/C][/ROW]
[ROW][C]96[/C][C]1.5[/C][C]3.21296[/C][C]-1.71296[/C][/ROW]
[ROW][C]97[/C][C]3.5[/C][C]6.94678[/C][C]-3.44678[/C][/ROW]
[ROW][C]98[/C][C]2.5[/C][C]3.7845[/C][C]-1.2845[/C][/ROW]
[ROW][C]99[/C][C]5.5[/C][C]3.94588[/C][C]1.55412[/C][/ROW]
[ROW][C]100[/C][C]8[/C][C]13.4594[/C][C]-5.45938[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]2.47757[/C][C]-1.47757[/C][/ROW]
[ROW][C]102[/C][C]5[/C][C]7.41624[/C][C]-2.41624[/C][/ROW]
[ROW][C]103[/C][C]4.5[/C][C]6.58972[/C][C]-2.08972[/C][/ROW]
[ROW][C]104[/C][C]3[/C][C]5.45909[/C][C]-2.45909[/C][/ROW]
[ROW][C]105[/C][C]3[/C][C]0.580209[/C][C]2.41979[/C][/ROW]
[ROW][C]106[/C][C]8[/C][C]10.843[/C][C]-2.84301[/C][/ROW]
[ROW][C]107[/C][C]2.5[/C][C]0.632586[/C][C]1.86741[/C][/ROW]
[ROW][C]108[/C][C]7[/C][C]13.6492[/C][C]-6.64922[/C][/ROW]
[ROW][C]109[/C][C]0[/C][C]5.15098[/C][C]-5.15098[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]2.99148[/C][C]-1.99148[/C][/ROW]
[ROW][C]111[/C][C]3.5[/C][C]4.36088[/C][C]-0.860883[/C][/ROW]
[ROW][C]112[/C][C]5.5[/C][C]6.23848[/C][C]-0.738478[/C][/ROW]
[ROW][C]113[/C][C]5.5[/C][C]10.7268[/C][C]-5.22684[/C][/ROW]
[ROW][C]114[/C][C]0.5[/C][C]-0.22946[/C][C]0.72946[/C][/ROW]
[ROW][C]115[/C][C]7.5[/C][C]4.88916[/C][C]2.61084[/C][/ROW]
[ROW][C]116[/C][C]9[/C][C]6.83058[/C][C]2.16942[/C][/ROW]
[ROW][C]117[/C][C]9.5[/C][C]8.03932[/C][C]1.46068[/C][/ROW]
[ROW][C]118[/C][C]8.5[/C][C]7.02041[/C][C]1.47959[/C][/ROW]
[ROW][C]119[/C][C]7[/C][C]5.85932[/C][C]1.14068[/C][/ROW]
[ROW][C]120[/C][C]8[/C][C]4.81491[/C][C]3.18509[/C][/ROW]
[ROW][C]121[/C][C]10[/C][C]9.34264[/C][C]0.65736[/C][/ROW]
[ROW][C]122[/C][C]7[/C][C]4.06478[/C][C]2.93522[/C][/ROW]
[ROW][C]123[/C][C]8.5[/C][C]5.76741[/C][C]2.73259[/C][/ROW]
[ROW][C]124[/C][C]9[/C][C]6.26959[/C][C]2.73041[/C][/ROW]
[ROW][C]125[/C][C]9.5[/C][C]11.8731[/C][C]-2.3731[/C][/ROW]
[ROW][C]126[/C][C]4[/C][C]3.21103[/C][C]0.788966[/C][/ROW]
[ROW][C]127[/C][C]6[/C][C]3.41467[/C][C]2.58533[/C][/ROW]
[ROW][C]128[/C][C]8[/C][C]8.04934[/C][C]-0.0493449[/C][/ROW]
[ROW][C]129[/C][C]5.5[/C][C]2.24349[/C][C]3.25651[/C][/ROW]
[ROW][C]130[/C][C]9.5[/C][C]8.62242[/C][C]0.877584[/C][/ROW]
[ROW][C]131[/C][C]7.5[/C][C]7.75728[/C][C]-0.257283[/C][/ROW]
[ROW][C]132[/C][C]7[/C][C]5.28666[/C][C]1.71334[/C][/ROW]
[ROW][C]133[/C][C]7.5[/C][C]5.97732[/C][C]1.52268[/C][/ROW]
[ROW][C]134[/C][C]8[/C][C]7.25171[/C][C]0.748289[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]6.62454[/C][C]0.375458[/C][/ROW]
[ROW][C]136[/C][C]7[/C][C]7.16518[/C][C]-0.165179[/C][/ROW]
[ROW][C]137[/C][C]6[/C][C]2.74161[/C][C]3.25839[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]14.2436[/C][C]-4.24356[/C][/ROW]
[ROW][C]139[/C][C]2.5[/C][C]-0.128426[/C][C]2.62843[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]7.56635[/C][C]1.43365[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]8.7247[/C][C]-0.7247[/C][/ROW]
[ROW][C]142[/C][C]6[/C][C]3.68171[/C][C]2.31829[/C][/ROW]
[ROW][C]143[/C][C]8.5[/C][C]7.51046[/C][C]0.989541[/C][/ROW]
[ROW][C]144[/C][C]6[/C][C]3.60944[/C][C]2.39056[/C][/ROW]
[ROW][C]145[/C][C]9[/C][C]6.72684[/C][C]2.27316[/C][/ROW]
[ROW][C]146[/C][C]8[/C][C]5.40525[/C][C]2.59475[/C][/ROW]
[ROW][C]147[/C][C]9[/C][C]8.92765[/C][C]0.0723526[/C][/ROW]
[ROW][C]148[/C][C]5.5[/C][C]4.22441[/C][C]1.27559[/C][/ROW]
[ROW][C]149[/C][C]7[/C][C]6.73482[/C][C]0.265181[/C][/ROW]
[ROW][C]150[/C][C]5.5[/C][C]3.65159[/C][C]1.84841[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]12.5324[/C][C]-3.53239[/C][/ROW]
[ROW][C]152[/C][C]2[/C][C]0.433077[/C][C]1.56692[/C][/ROW]
[ROW][C]153[/C][C]8.5[/C][C]6.24065[/C][C]2.25935[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]5.8703[/C][C]3.1297[/C][/ROW]
[ROW][C]155[/C][C]8.5[/C][C]6.43455[/C][C]2.06545[/C][/ROW]
[ROW][C]156[/C][C]9[/C][C]7.04684[/C][C]1.95316[/C][/ROW]
[ROW][C]157[/C][C]7.5[/C][C]4.74378[/C][C]2.75622[/C][/ROW]
[ROW][C]158[/C][C]10[/C][C]7.40151[/C][C]2.59849[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]7.9204[/C][C]1.0796[/C][/ROW]
[ROW][C]160[/C][C]7.5[/C][C]8.18131[/C][C]-0.68131[/C][/ROW]
[ROW][C]161[/C][C]6[/C][C]2.46501[/C][C]3.53499[/C][/ROW]
[ROW][C]162[/C][C]10.5[/C][C]8.68085[/C][C]1.81915[/C][/ROW]
[ROW][C]163[/C][C]8.5[/C][C]7.52045[/C][C]0.97955[/C][/ROW]
[ROW][C]164[/C][C]8[/C][C]4.91912[/C][C]3.08088[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]6.80363[/C][C]3.19637[/C][/ROW]
[ROW][C]166[/C][C]10.5[/C][C]10.256[/C][C]0.243986[/C][/ROW]
[ROW][C]167[/C][C]6.5[/C][C]3.53807[/C][C]2.96193[/C][/ROW]
[ROW][C]168[/C][C]9.5[/C][C]8.4348[/C][C]1.0652[/C][/ROW]
[ROW][C]169[/C][C]8.5[/C][C]7.63934[/C][C]0.860655[/C][/ROW]
[ROW][C]170[/C][C]7.5[/C][C]8.99177[/C][C]-1.49177[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]3.67024[/C][C]1.32976[/C][/ROW]
[ROW][C]172[/C][C]8[/C][C]4.01913[/C][C]3.98087[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]10.2178[/C][C]-0.217806[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]6.25704[/C][C]0.742961[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]6.75704[/C][C]0.742961[/C][/ROW]
[ROW][C]176[/C][C]7.5[/C][C]3.97624[/C][C]3.52376[/C][/ROW]
[ROW][C]177[/C][C]9.5[/C][C]9.54709[/C][C]-0.0470859[/C][/ROW]
[ROW][C]178[/C][C]6[/C][C]1.19408[/C][C]4.80592[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]9.09619[/C][C]0.903807[/C][/ROW]
[ROW][C]180[/C][C]7[/C][C]9.82964[/C][C]-2.82964[/C][/ROW]
[ROW][C]181[/C][C]3[/C][C]3.4197[/C][C]-0.419705[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]4.74229[/C][C]1.25771[/C][/ROW]
[ROW][C]183[/C][C]7[/C][C]4.26024[/C][C]2.73976[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]8.74067[/C][C]1.25933[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]9.86151[/C][C]-2.86151[/C][/ROW]
[ROW][C]186[/C][C]3.5[/C][C]2.15661[/C][C]1.34339[/C][/ROW]
[ROW][C]187[/C][C]8[/C][C]4.65661[/C][C]3.34339[/C][/ROW]
[ROW][C]188[/C][C]10[/C][C]11.1566[/C][C]-1.15661[/C][/ROW]
[ROW][C]189[/C][C]5.5[/C][C]6.11225[/C][C]-0.612246[/C][/ROW]
[ROW][C]190[/C][C]6[/C][C]4.95033[/C][C]1.04967[/C][/ROW]
[ROW][C]191[/C][C]6.5[/C][C]6.52263[/C][C]-0.0226349[/C][/ROW]
[ROW][C]192[/C][C]6.5[/C][C]4.04592[/C][C]2.45408[/C][/ROW]
[ROW][C]193[/C][C]8.5[/C][C]10.8734[/C][C]-2.37341[/C][/ROW]
[ROW][C]194[/C][C]4[/C][C]-0.0733999[/C][C]4.0734[/C][/ROW]
[ROW][C]195[/C][C]9.5[/C][C]7.2354[/C][C]2.2646[/C][/ROW]
[ROW][C]196[/C][C]8[/C][C]6.68591[/C][C]1.31409[/C][/ROW]
[ROW][C]197[/C][C]8.5[/C][C]9.14126[/C][C]-0.641256[/C][/ROW]
[ROW][C]198[/C][C]5.5[/C][C]3.61615[/C][C]1.88385[/C][/ROW]
[ROW][C]199[/C][C]7[/C][C]3.68235[/C][C]3.31765[/C][/ROW]
[ROW][C]200[/C][C]9[/C][C]6.87155[/C][C]2.12845[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]4.34264[/C][C]3.65736[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]7.94929[/C][C]2.05071[/C][/ROW]
[ROW][C]203[/C][C]8[/C][C]7.48704[/C][C]0.512956[/C][/ROW]
[ROW][C]204[/C][C]6[/C][C]4.77249[/C][C]1.22751[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]9.52168[/C][C]-1.52168[/C][/ROW]
[ROW][C]206[/C][C]5[/C][C]2.79852[/C][C]2.20148[/C][/ROW]
[ROW][C]207[/C][C]9[/C][C]9.9571[/C][C]-0.957105[/C][/ROW]
[ROW][C]208[/C][C]4.5[/C][C]2.40396[/C][C]2.09604[/C][/ROW]
[ROW][C]209[/C][C]8.5[/C][C]3.87736[/C][C]4.62264[/C][/ROW]
[ROW][C]210[/C][C]9.5[/C][C]7.30141[/C][C]2.19859[/C][/ROW]
[ROW][C]211[/C][C]8.5[/C][C]7.79993[/C][C]0.700071[/C][/ROW]
[ROW][C]212[/C][C]7.5[/C][C]6.16821[/C][C]1.33179[/C][/ROW]
[ROW][C]213[/C][C]7.5[/C][C]7.73406[/C][C]-0.234059[/C][/ROW]
[ROW][C]214[/C][C]5[/C][C]3.39924[/C][C]1.60076[/C][/ROW]
[ROW][C]215[/C][C]7[/C][C]5.24041[/C][C]1.75959[/C][/ROW]
[ROW][C]216[/C][C]8[/C][C]7.35582[/C][C]0.644184[/C][/ROW]
[ROW][C]217[/C][C]5.5[/C][C]3.16678[/C][C]2.33322[/C][/ROW]
[ROW][C]218[/C][C]8.5[/C][C]5.75358[/C][C]2.74642[/C][/ROW]
[ROW][C]219[/C][C]9.5[/C][C]8.89077[/C][C]0.609229[/C][/ROW]
[ROW][C]220[/C][C]7[/C][C]5.80391[/C][C]1.19609[/C][/ROW]
[ROW][C]221[/C][C]8[/C][C]4.95811[/C][C]3.04189[/C][/ROW]
[ROW][C]222[/C][C]8.5[/C][C]10.6331[/C][C]-2.13312[/C][/ROW]
[ROW][C]223[/C][C]3.5[/C][C]3.64131[/C][C]-0.141305[/C][/ROW]
[ROW][C]224[/C][C]6.5[/C][C]5.7084[/C][C]0.791601[/C][/ROW]
[ROW][C]225[/C][C]6.5[/C][C]3.10973[/C][C]3.39027[/C][/ROW]
[ROW][C]226[/C][C]10.5[/C][C]8.40249[/C][C]2.09751[/C][/ROW]
[ROW][C]227[/C][C]8.5[/C][C]6.54959[/C][C]1.95041[/C][/ROW]
[ROW][C]228[/C][C]8[/C][C]4.97506[/C][C]3.02494[/C][/ROW]
[ROW][C]229[/C][C]10[/C][C]6.65233[/C][C]3.34767[/C][/ROW]
[ROW][C]230[/C][C]10[/C][C]6.91599[/C][C]3.08401[/C][/ROW]
[ROW][C]231[/C][C]9.5[/C][C]5.55482[/C][C]3.94518[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]5.18171[/C][C]3.81829[/C][/ROW]
[ROW][C]233[/C][C]10[/C][C]9.0805[/C][C]0.919498[/C][/ROW]
[ROW][C]234[/C][C]7.5[/C][C]9.59498[/C][C]-2.09498[/C][/ROW]
[ROW][C]235[/C][C]4.5[/C][C]5.05482[/C][C]-0.554824[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]10.814[/C][C]-6.31395[/C][/ROW]
[ROW][C]237[/C][C]0.5[/C][C]-0.216252[/C][C]0.716252[/C][/ROW]
[ROW][C]238[/C][C]6.5[/C][C]7.62019[/C][C]-1.12019[/C][/ROW]
[ROW][C]239[/C][C]4.5[/C][C]4.01046[/C][C]0.489541[/C][/ROW]
[ROW][C]240[/C][C]5.5[/C][C]6.19823[/C][C]-0.698233[/C][/ROW]
[ROW][C]241[/C][C]5[/C][C]5.5805[/C][C]-0.580502[/C][/ROW]
[ROW][C]242[/C][C]6[/C][C]7.22647[/C][C]-1.22647[/C][/ROW]
[ROW][C]243[/C][C]4[/C][C]2.38706[/C][C]1.61294[/C][/ROW]
[ROW][C]244[/C][C]8[/C][C]4.80363[/C][C]3.19637[/C][/ROW]
[ROW][C]245[/C][C]10.5[/C][C]10.4493[/C][C]0.050664[/C][/ROW]
[ROW][C]246[/C][C]6.5[/C][C]4.52161[/C][C]1.97839[/C][/ROW]
[ROW][C]247[/C][C]8[/C][C]5.38603[/C][C]2.61397[/C][/ROW]
[ROW][C]248[/C][C]8.5[/C][C]9.25551[/C][C]-0.755515[/C][/ROW]
[ROW][C]249[/C][C]5.5[/C][C]4.1236[/C][C]1.3764[/C][/ROW]
[ROW][C]250[/C][C]7[/C][C]7.93187[/C][C]-0.931873[/C][/ROW]
[ROW][C]251[/C][C]5[/C][C]7.13903[/C][C]-2.13903[/C][/ROW]
[ROW][C]252[/C][C]3.5[/C][C]4.93418[/C][C]-1.43418[/C][/ROW]
[ROW][C]253[/C][C]5[/C][C]3.00597[/C][C]1.99403[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]6.01533[/C][C]2.98467[/C][/ROW]
[ROW][C]255[/C][C]8.5[/C][C]10.1992[/C][C]-1.69917[/C][/ROW]
[ROW][C]256[/C][C]5[/C][C]2.31741[/C][C]2.68259[/C][/ROW]
[ROW][C]257[/C][C]9.5[/C][C]13.229[/C][C]-3.72899[/C][/ROW]
[ROW][C]258[/C][C]3[/C][C]7.90557[/C][C]-4.90557[/C][/ROW]
[ROW][C]259[/C][C]1.5[/C][C]1.3571[/C][C]0.142901[/C][/ROW]
[ROW][C]260[/C][C]6[/C][C]10.6377[/C][C]-4.63774[/C][/ROW]
[ROW][C]261[/C][C]0.5[/C][C]0.256014[/C][C]0.243986[/C][/ROW]
[ROW][C]262[/C][C]6.5[/C][C]5.86177[/C][C]0.638226[/C][/ROW]
[ROW][C]263[/C][C]7.5[/C][C]8.37195[/C][C]-0.871948[/C][/ROW]
[ROW][C]264[/C][C]4.5[/C][C]2.88706[/C][C]1.61294[/C][/ROW]
[ROW][C]265[/C][C]8[/C][C]5.63694[/C][C]2.36306[/C][/ROW]
[ROW][C]266[/C][C]9[/C][C]8.3882[/C][C]0.611795[/C][/ROW]
[ROW][C]267[/C][C]7.5[/C][C]5.4651[/C][C]2.0349[/C][/ROW]
[ROW][C]268[/C][C]8.5[/C][C]6.48365[/C][C]2.01635[/C][/ROW]
[ROW][C]269[/C][C]7[/C][C]4.50969[/C][C]2.49031[/C][/ROW]
[ROW][C]270[/C][C]9.5[/C][C]9.88871[/C][C]-0.388711[/C][/ROW]
[ROW][C]271[/C][C]6.5[/C][C]2.59223[/C][C]3.90777[/C][/ROW]
[ROW][C]272[/C][C]9.5[/C][C]10.257[/C][C]-0.757039[/C][/ROW]
[ROW][C]273[/C][C]6[/C][C]3.02742[/C][C]2.97258[/C][/ROW]
[ROW][C]274[/C][C]8[/C][C]5.02263[/C][C]2.97737[/C][/ROW]
[ROW][C]275[/C][C]9.5[/C][C]7.72774[/C][C]1.77226[/C][/ROW]
[ROW][C]276[/C][C]8[/C][C]6.71448[/C][C]1.28552[/C][/ROW]
[ROW][C]277[/C][C]8[/C][C]5.40249[/C][C]2.59751[/C][/ROW]
[ROW][C]278[/C][C]9[/C][C]10.3604[/C][C]-1.36036[/C][/ROW]
[ROW][C]279[/C][C]5[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265719&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265719&T=4

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	7.5	6.37632	1.12368
2	6	5.98922	0.010781
3	6.5	6.4329	0.0671018
4	1	5.60767	-4.60767
5	1	5.53711	-4.53711
6	5.5	5.14854	0.351458
7	8.5	6.77004	1.72996
8	6.5	6.51949	-0.0194852
9	4.5	5.72634	-1.22634
10	2	6.22381	-4.22381
11	5	6.713	-1.713
12	0.5	5.59402	-5.09402
13	5	5.78568	-0.785679
14	5	6.12205	-1.12205
15	2.5	5.9795	-3.4795
16	5	6.07896	-1.07896
17	5.5	6.1513	-0.6513
18	3.5	5.74315	-2.24315
19	3	5.75757	-2.75757
20	4	5.28433	-1.28433
21	0.5	6.23976	-5.73976
22	6.5	5.88944	0.610562
23	4.5	5.73938	-1.23938
24	7.5	5.89948	1.60052
25	5.5	6.96547	-1.46547
26	4	5.36913	-1.36913
27	7.5	6.17114	1.32886
28	7	6.46036	0.539644
29	4	6.90421	-2.90421
30	5.5	6.42949	-0.929492
31	2.5	5.60905	-3.10905
32	5.5	5.44737	0.0526312
33	3.5	6.65578	-3.15578
34	2.5	6.46312	-3.96312
35	4.5	6.93512	-2.43512
36	4.5	7.19846	-2.69846
37	4.5	5.70582	-1.20582
38	6	5.72717	0.272834
39	2.5	6.60796	-4.10796
40	5	6.52263	-1.52263
41	0	6.64035	-6.64035
42	5	6.60944	-1.60944
43	6.5	6.06598	0.434025
44	5	6.94857	-1.94857
45	6	6.26741	-0.267411
46	4.5	6.65233	-2.15233
47	5.5	5.22301	0.276991
48	1	5.57578	-4.57578
49	7.5	4.93105	2.56895
50	6	6.84389	-0.84389
51	5	6.91912	-1.91912
52	1	5.59371	-4.59371
53	5	6.59431	-1.59431
54	6.5	5.62457	0.875426
55	7	5.87446	1.12554
56	4.5	6.77247	-2.27247
57	0	6.75415	-6.75415
58	8.5	5.10387	3.39613
59	3.5	5.62907	-2.12907
60	7.5	6.50913	0.990867
61	3.5	6.84775	-3.34775
62	6	5.38674	0.613258
63	1.5	7.02095	-5.52095
64	9	6.56259	2.43741
65	3.5	5.44737	-1.94737
66	3.5	6.85639	-3.35639
67	4	6.41777	-2.41777
68	6.5	6.45837	0.0416259
69	7.5	7.00878	0.491217
70	6	5.66802	0.331985
71	5	5.90242	-0.902419
72	5.5	6.36088	-0.860883
73	3.5	6.09343	-2.59343
74	7.5	6.47481	1.02519
75	6.5	5.5217	0.978304
76	NA	NA	0.95335
77	6.5	6.62339	-0.123392
78	6.5	5.58045	0.919547
79	7	8.98404	-1.98404
80	3.5	7.56328	-4.06328
81	1.5	3.43166	-1.93166
82	4	1.87164	2.12836
83	7.5	9.43045	-1.93045
84	4.5	10.4029	-5.90294
85	0	2.58572	-2.58572
86	3.5	3.99365	-0.493653
87	5.5	6.60969	-1.10969
88	5	7.29852	-2.29852
89	4.5	8.68472	-4.18472
90	2.5	0.179341	2.32066
91	7.5	6.9903	0.509704
92	7	13.0351	-6.03511
93	0	0.768072	-0.768072
94	4.5	7.55054	-3.05054
95	3	6.79701	-3.79701
96	1.5	3.21296	-1.71296
97	3.5	6.94678	-3.44678
98	2.5	3.7845	-1.2845
99	5.5	3.94588	1.55412
100	8	13.4594	-5.45938
101	1	2.47757	-1.47757
102	5	7.41624	-2.41624
103	4.5	6.58972	-2.08972
104	3	5.45909	-2.45909
105	3	0.580209	2.41979
106	8	10.843	-2.84301
107	2.5	0.632586	1.86741
108	7	13.6492	-6.64922
109	0	5.15098	-5.15098
110	1	2.99148	-1.99148
111	3.5	4.36088	-0.860883
112	5.5	6.23848	-0.738478
113	5.5	10.7268	-5.22684
114	0.5	-0.22946	0.72946
115	7.5	4.88916	2.61084
116	9	6.83058	2.16942
117	9.5	8.03932	1.46068
118	8.5	7.02041	1.47959
119	7	5.85932	1.14068
120	8	4.81491	3.18509
121	10	9.34264	0.65736
122	7	4.06478	2.93522
123	8.5	5.76741	2.73259
124	9	6.26959	2.73041
125	9.5	11.8731	-2.3731
126	4	3.21103	0.788966
127	6	3.41467	2.58533
128	8	8.04934	-0.0493449
129	5.5	2.24349	3.25651
130	9.5	8.62242	0.877584
131	7.5	7.75728	-0.257283
132	7	5.28666	1.71334
133	7.5	5.97732	1.52268
134	8	7.25171	0.748289
135	7	6.62454	0.375458
136	7	7.16518	-0.165179
137	6	2.74161	3.25839
138	10	14.2436	-4.24356
139	2.5	-0.128426	2.62843
140	9	7.56635	1.43365
141	8	8.7247	-0.7247
142	6	3.68171	2.31829
143	8.5	7.51046	0.989541
144	6	3.60944	2.39056
145	9	6.72684	2.27316
146	8	5.40525	2.59475
147	9	8.92765	0.0723526
148	5.5	4.22441	1.27559
149	7	6.73482	0.265181
150	5.5	3.65159	1.84841
151	9	12.5324	-3.53239
152	2	0.433077	1.56692
153	8.5	6.24065	2.25935
154	9	5.8703	3.1297
155	8.5	6.43455	2.06545
156	9	7.04684	1.95316
157	7.5	4.74378	2.75622
158	10	7.40151	2.59849
159	9	7.9204	1.0796
160	7.5	8.18131	-0.68131
161	6	2.46501	3.53499
162	10.5	8.68085	1.81915
163	8.5	7.52045	0.97955
164	8	4.91912	3.08088
165	10	6.80363	3.19637
166	10.5	10.256	0.243986
167	6.5	3.53807	2.96193
168	9.5	8.4348	1.0652
169	8.5	7.63934	0.860655
170	7.5	8.99177	-1.49177
171	5	3.67024	1.32976
172	8	4.01913	3.98087
173	10	10.2178	-0.217806
174	7	6.25704	0.742961
175	7.5	6.75704	0.742961
176	7.5	3.97624	3.52376
177	9.5	9.54709	-0.0470859
178	6	1.19408	4.80592
179	10	9.09619	0.903807
180	7	9.82964	-2.82964
181	3	3.4197	-0.419705
182	6	4.74229	1.25771
183	7	4.26024	2.73976
184	10	8.74067	1.25933
185	7	9.86151	-2.86151
186	3.5	2.15661	1.34339
187	8	4.65661	3.34339
188	10	11.1566	-1.15661
189	5.5	6.11225	-0.612246
190	6	4.95033	1.04967
191	6.5	6.52263	-0.0226349
192	6.5	4.04592	2.45408
193	8.5	10.8734	-2.37341
194	4	-0.0733999	4.0734
195	9.5	7.2354	2.2646
196	8	6.68591	1.31409
197	8.5	9.14126	-0.641256
198	5.5	3.61615	1.88385
199	7	3.68235	3.31765
200	9	6.87155	2.12845
201	8	4.34264	3.65736
202	10	7.94929	2.05071
203	8	7.48704	0.512956
204	6	4.77249	1.22751
205	8	9.52168	-1.52168
206	5	2.79852	2.20148
207	9	9.9571	-0.957105
208	4.5	2.40396	2.09604
209	8.5	3.87736	4.62264
210	9.5	7.30141	2.19859
211	8.5	7.79993	0.700071
212	7.5	6.16821	1.33179
213	7.5	7.73406	-0.234059
214	5	3.39924	1.60076
215	7	5.24041	1.75959
216	8	7.35582	0.644184
217	5.5	3.16678	2.33322
218	8.5	5.75358	2.74642
219	9.5	8.89077	0.609229
220	7	5.80391	1.19609
221	8	4.95811	3.04189
222	8.5	10.6331	-2.13312
223	3.5	3.64131	-0.141305
224	6.5	5.7084	0.791601
225	6.5	3.10973	3.39027
226	10.5	8.40249	2.09751
227	8.5	6.54959	1.95041
228	8	4.97506	3.02494
229	10	6.65233	3.34767
230	10	6.91599	3.08401
231	9.5	5.55482	3.94518
232	9	5.18171	3.81829
233	10	9.0805	0.919498
234	7.5	9.59498	-2.09498
235	4.5	5.05482	-0.554824
236	4.5	10.814	-6.31395
237	0.5	-0.216252	0.716252
238	6.5	7.62019	-1.12019
239	4.5	4.01046	0.489541
240	5.5	6.19823	-0.698233
241	5	5.5805	-0.580502
242	6	7.22647	-1.22647
243	4	2.38706	1.61294
244	8	4.80363	3.19637
245	10.5	10.4493	0.050664
246	6.5	4.52161	1.97839
247	8	5.38603	2.61397
248	8.5	9.25551	-0.755515
249	5.5	4.1236	1.3764
250	7	7.93187	-0.931873
251	5	7.13903	-2.13903
252	3.5	4.93418	-1.43418
253	5	3.00597	1.99403
254	9	6.01533	2.98467
255	8.5	10.1992	-1.69917
256	5	2.31741	2.68259
257	9.5	13.229	-3.72899
258	3	7.90557	-4.90557
259	1.5	1.3571	0.142901
260	6	10.6377	-4.63774
261	0.5	0.256014	0.243986
262	6.5	5.86177	0.638226
263	7.5	8.37195	-0.871948
264	4.5	2.88706	1.61294
265	8	5.63694	2.36306
266	9	8.3882	0.611795
267	7.5	5.4651	2.0349
268	8.5	6.48365	2.01635
269	7	4.50969	2.49031
270	9.5	9.88871	-0.388711
271	6.5	2.59223	3.90777
272	9.5	10.257	-0.757039
273	6	3.02742	2.97258
274	8	5.02263	2.97737
275	9.5	7.72774	1.77226
276	8	6.71448	1.28552
277	8	5.40249	2.59751
278	9	10.3604	-1.36036
279	5	NA	NA

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
10	0.711527	0.576947	0.288473
11	0.564913	0.870175	0.435087
12	0.789995	0.420011	0.210005
13	0.701139	0.597723	0.298861
14	0.595345	0.80931	0.404655
15	0.542148	0.915704	0.457852
16	0.44386	0.88772	0.55614
17	0.35042	0.700839	0.64958
18	0.327589	0.655178	0.672411
19	0.26647	0.532939	0.73353
20	0.209084	0.418168	0.790916
21	0.381147	0.762293	0.618853
22	0.379318	0.758637	0.620682
23	0.323792	0.647584	0.676208
24	0.302114	0.604229	0.697886
25	0.242699	0.485398	0.757301
26	0.241538	0.483075	0.758462
27	0.255405	0.510811	0.744595
28	0.215247	0.430494	0.784753
29	0.258743	0.517486	0.741257
30	0.209871	0.419742	0.790129
31	0.177546	0.355092	0.822454
32	0.147572	0.295143	0.852428
33	0.142464	0.284929	0.857536
34	0.180485	0.36097	0.819515
35	0.149982	0.299964	0.850018
36	0.133136	0.266272	0.866864
37	0.127035	0.254071	0.872965
38	0.113935	0.22787	0.886065
39	0.129846	0.259693	0.870154
40	0.10395	0.207899	0.89605
41	0.225295	0.450589	0.774705
42	0.189918	0.379837	0.810082
43	0.171635	0.343271	0.828365
44	0.145033	0.290066	0.854967
45	0.12698	0.25396	0.87302
46	0.106678	0.213356	0.893322
47	0.0871996	0.174399	0.9128
48	0.138587	0.277173	0.861413
49	0.164933	0.329865	0.835067
50	0.143893	0.287786	0.856107
51	0.121551	0.243102	0.878449
52	0.149803	0.299606	0.850197
53	0.125891	0.251781	0.874109
54	0.120565	0.241131	0.879435
55	0.135802	0.271604	0.864198
56	0.1183	0.2366	0.8817
57	0.231813	0.463626	0.768187
58	0.3153	0.6306	0.6847
59	0.284939	0.569877	0.715061
60	0.279868	0.559735	0.720132
61	0.273774	0.547548	0.726226
62	0.245547	0.491094	0.754453
63	0.285392	0.570785	0.714608
64	0.349327	0.698655	0.650673
65	0.327783	0.655567	0.672217
66	0.322055	0.64411	0.677945
67	0.299442	0.598884	0.700558
68	0.277125	0.55425	0.722875
69	0.317509	0.635018	0.682491
70	0.299688	0.599376	0.700312
71	0.26618	0.532359	0.73382
72	0.23793	0.47586	0.76207
73	0.227166	0.454332	0.772834
74	0.232123	0.464246	0.767877
75	0.214772	0.429544	0.785228
76	0.190146	0.380292	0.809854
77	0.169831	0.339662	0.830169
78	0.159447	0.318894	0.840553
79	0.142614	0.285229	0.857386
80	0.162546	0.325092	0.837454
81	0.14605	0.2921	0.85395
82	0.149947	0.299893	0.850053
83	0.135087	0.270174	0.864913
84	0.232009	0.464018	0.767991
85	0.220131	0.440261	0.779869
86	0.194289	0.388579	0.805711
87	0.172743	0.345487	0.827257
88	0.162475	0.32495	0.837525
89	0.18968	0.379359	0.81032
90	0.222868	0.445736	0.777132
91	0.224447	0.448893	0.775553
92	0.33743	0.674859	0.66257
93	0.30646	0.61292	0.69354
94	0.307099	0.614198	0.692901
95	0.353971	0.707943	0.646029
96	0.339737	0.679473	0.660263
97	0.371311	0.742621	0.628689
98	0.349523	0.699046	0.650477
99	0.372864	0.745729	0.627136
100	0.487075	0.97415	0.512925
101	0.466729	0.933458	0.533271
102	0.463398	0.926796	0.536602
103	0.470199	0.940399	0.529801
104	0.473574	0.947148	0.526426
105	0.491626	0.983251	0.508374
106	0.5132	0.973599	0.4868
107	0.541449	0.917102	0.458551
108	0.758135	0.483731	0.241865
109	0.863935	0.27213	0.136065
110	0.858499	0.283002	0.141501
111	0.847685	0.30463	0.152315
112	0.843149	0.313702	0.156851
113	0.90981	0.18038	0.0901902
114	0.919821	0.160358	0.0801791
115	0.939878	0.120244	0.0601219
116	0.952337	0.0953257	0.0476628
117	0.95866	0.0826802	0.0413401
118	0.957801	0.0843982	0.0421991
119	0.957975	0.0840493	0.0420246
120	0.971504	0.0569915	0.0284957
121	0.968303	0.0633931	0.0316965
122	0.974333	0.0513334	0.0256667
123	0.980915	0.0381701	0.0190851
124	0.984992	0.030017	0.0150085
125	0.986434	0.0271318	0.0135659
126	0.984369	0.0312624	0.0156312
127	0.985018	0.0299647	0.0149823
128	0.981962	0.0360751	0.0180375
129	0.986123	0.0277545	0.0138772
130	0.984447	0.0311064	0.0155532
131	0.982415	0.0351709	0.0175854
132	0.980433	0.0391345	0.0195673
133	0.979771	0.0404584	0.0202292
134	0.979384	0.0412313	0.0206157
135	0.97503	0.0499408	0.0249704
136	0.972929	0.054141	0.0270705
137	0.97905	0.0418993	0.0209496
138	0.98921	0.02158	0.01079
139	0.98996	0.0200791	0.0100396
140	0.988774	0.0224527	0.0112263
141	0.987285	0.0254295	0.0127147
142	0.98688	0.02624	0.01312
143	0.985156	0.0296881	0.014844
144	0.985331	0.0293385	0.0146693
145	0.985423	0.029155	0.0145775
146	0.986171	0.0276582	0.0138291
147	0.983462	0.0330766	0.0165383
148	0.980808	0.0383837	0.0191918
149	0.977593	0.0448148	0.0224074
150	0.975933	0.048134	0.024067
151	0.984038	0.0319244	0.0159622
152	0.982122	0.035755	0.0178775
153	0.982495	0.0350101	0.0175051
154	0.984778	0.0304441	0.0152221
155	0.983782	0.0324365	0.0162182
156	0.982349	0.0353013	0.0176506
157	0.983477	0.0330453	0.0165226
158	0.984107	0.0317863	0.0158932
159	0.981526	0.0369474	0.0184737
160	0.979504	0.0409915	0.0204958
161	0.984012	0.031977	0.0159885
162	0.982625	0.03475	0.017375
163	0.980189	0.0396211	0.0198105
164	0.98213	0.03574	0.01787
165	0.98443	0.031141	0.0155705
166	0.980554	0.0388914	0.0194457
167	0.982576	0.0348478	0.0174239
168	0.978757	0.0424851	0.0212426
169	0.974316	0.0513677	0.0256838
170	0.973652	0.0526958	0.0263479
171	0.969582	0.0608359	0.0304179
172	0.977865	0.04427	0.022135
173	0.973092	0.0538152	0.0269076
174	0.967234	0.0655324	0.0327662
175	0.960353	0.0792933	0.0396467
176	0.966642	0.0667156	0.0333578
177	0.959354	0.0812927	0.0406464
178	0.979375	0.0412495	0.0206248
179	0.97506	0.0498805	0.0249403
180	0.981927	0.0361451	0.0180725
181	0.977717	0.044566	0.022283
182	0.973594	0.0528117	0.0264058
183	0.972854	0.0542918	0.0271459
184	0.96797	0.0640601	0.03203
185	0.971664	0.0566713	0.0283356
186	0.966207	0.067586	0.033793
187	0.969472	0.0610567	0.0305283
188	0.96717	0.0656595	0.0328298
189	0.964119	0.0717628	0.0358814
190	0.957527	0.0849452	0.0424726
191	0.948803	0.102393	0.0511967
192	0.94579	0.108419	0.0542097
193	0.959584	0.0808327	0.0404164
194	0.967647	0.0647067	0.0323534
195	0.96393	0.0721399	0.0360699
196	0.956584	0.0868319	0.0434159
197	0.947481	0.105038	0.052519
198	0.940522	0.118956	0.059478
199	0.943565	0.112869	0.0564346
200	0.937893	0.124214	0.062107
201	0.94846	0.103079	0.0515397
202	0.943594	0.112812	0.056406
203	0.931316	0.137368	0.0686838
204	0.918235	0.163531	0.0817653
205	0.922219	0.155563	0.0777813
206	0.911075	0.177851	0.0889254
207	0.897341	0.205318	0.102659
208	0.885272	0.229457	0.114728
209	0.901943	0.196114	0.0980569
210	0.890832	0.218337	0.109168
211	0.870557	0.258886	0.129443
212	0.853165	0.29367	0.146835
213	0.828926	0.342149	0.171074
214	0.81393	0.37214	0.18607
215	0.793965	0.412071	0.206035
216	0.762483	0.475034	0.237517
217	0.74779	0.504419	0.25221
218	0.746674	0.506651	0.253326
219	0.711555	0.576891	0.288445
220	0.676041	0.647917	0.323959
221	0.701084	0.597831	0.298916
222	0.718479	0.563042	0.281521
223	0.678626	0.642749	0.321374
224	0.639212	0.721576	0.360788
225	0.616671	0.766659	0.383329
226	0.590699	0.818601	0.409301
227	0.553184	0.893631	0.446816
228	0.546718	0.906565	0.453282
229	0.583093	0.833814	0.416907
230	0.578727	0.842546	0.421273
231	0.619584	0.760833	0.380416
232	0.71232	0.575359	0.28768
233	0.67443	0.651139	0.32557
234	0.667407	0.665186	0.332593
235	0.627038	0.745925	0.372962
236	0.906372	0.187255	0.0936277
237	0.883377	0.233247	0.116623
238	0.859127	0.281746	0.140873
239	0.828864	0.342273	0.171136
240	0.792094	0.415812	0.207906
241	0.757872	0.484255	0.242128
242	0.720271	0.559458	0.279729
243	0.6726	0.654799	0.3274
244	0.689037	0.621926	0.310963
245	0.635972	0.728056	0.364028
246	0.618015	0.76397	0.381985
247	0.587941	0.824119	0.412059
248	0.530296	0.939408	0.469704
249	0.534501	0.930998	0.465499
250	0.494094	0.988187	0.505906
251	0.434043	0.868085	0.565957
252	0.467544	0.935089	0.532456
253	0.409431	0.818863	0.590569
254	0.388145	0.776291	0.611855
255	0.32753	0.65506	0.67247
256	0.281538	0.563076	0.718462
257	0.552147	0.895706	0.447853
258	0.768922	0.462155	0.231078
259	0.717996	0.564007	0.282004
260	0.980015	0.0399698	0.0199849
261	0.966548	0.0669042	0.0334521
262	0.964832	0.0703351	0.0351676
263	0.938983	0.122033	0.0610167
264	0.909648	0.180704	0.0903519
265	0.845539	0.308923	0.154461
266	0.746785	0.506429	0.253215
267	0.610781	0.778438	0.389219
268	0.47412	0.94824	0.52588
269	0.894879	0.210242	0.105121

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.711527 & 0.576947 & 0.288473 \tabularnewline
11 & 0.564913 & 0.870175 & 0.435087 \tabularnewline
12 & 0.789995 & 0.420011 & 0.210005 \tabularnewline
13 & 0.701139 & 0.597723 & 0.298861 \tabularnewline
14 & 0.595345 & 0.80931 & 0.404655 \tabularnewline
15 & 0.542148 & 0.915704 & 0.457852 \tabularnewline
16 & 0.44386 & 0.88772 & 0.55614 \tabularnewline
17 & 0.35042 & 0.700839 & 0.64958 \tabularnewline
18 & 0.327589 & 0.655178 & 0.672411 \tabularnewline
19 & 0.26647 & 0.532939 & 0.73353 \tabularnewline
20 & 0.209084 & 0.418168 & 0.790916 \tabularnewline
21 & 0.381147 & 0.762293 & 0.618853 \tabularnewline
22 & 0.379318 & 0.758637 & 0.620682 \tabularnewline
23 & 0.323792 & 0.647584 & 0.676208 \tabularnewline
24 & 0.302114 & 0.604229 & 0.697886 \tabularnewline
25 & 0.242699 & 0.485398 & 0.757301 \tabularnewline
26 & 0.241538 & 0.483075 & 0.758462 \tabularnewline
27 & 0.255405 & 0.510811 & 0.744595 \tabularnewline
28 & 0.215247 & 0.430494 & 0.784753 \tabularnewline
29 & 0.258743 & 0.517486 & 0.741257 \tabularnewline
30 & 0.209871 & 0.419742 & 0.790129 \tabularnewline
31 & 0.177546 & 0.355092 & 0.822454 \tabularnewline
32 & 0.147572 & 0.295143 & 0.852428 \tabularnewline
33 & 0.142464 & 0.284929 & 0.857536 \tabularnewline
34 & 0.180485 & 0.36097 & 0.819515 \tabularnewline
35 & 0.149982 & 0.299964 & 0.850018 \tabularnewline
36 & 0.133136 & 0.266272 & 0.866864 \tabularnewline
37 & 0.127035 & 0.254071 & 0.872965 \tabularnewline
38 & 0.113935 & 0.22787 & 0.886065 \tabularnewline
39 & 0.129846 & 0.259693 & 0.870154 \tabularnewline
40 & 0.10395 & 0.207899 & 0.89605 \tabularnewline
41 & 0.225295 & 0.450589 & 0.774705 \tabularnewline
42 & 0.189918 & 0.379837 & 0.810082 \tabularnewline
43 & 0.171635 & 0.343271 & 0.828365 \tabularnewline
44 & 0.145033 & 0.290066 & 0.854967 \tabularnewline
45 & 0.12698 & 0.25396 & 0.87302 \tabularnewline
46 & 0.106678 & 0.213356 & 0.893322 \tabularnewline
47 & 0.0871996 & 0.174399 & 0.9128 \tabularnewline
48 & 0.138587 & 0.277173 & 0.861413 \tabularnewline
49 & 0.164933 & 0.329865 & 0.835067 \tabularnewline
50 & 0.143893 & 0.287786 & 0.856107 \tabularnewline
51 & 0.121551 & 0.243102 & 0.878449 \tabularnewline
52 & 0.149803 & 0.299606 & 0.850197 \tabularnewline
53 & 0.125891 & 0.251781 & 0.874109 \tabularnewline
54 & 0.120565 & 0.241131 & 0.879435 \tabularnewline
55 & 0.135802 & 0.271604 & 0.864198 \tabularnewline
56 & 0.1183 & 0.2366 & 0.8817 \tabularnewline
57 & 0.231813 & 0.463626 & 0.768187 \tabularnewline
58 & 0.3153 & 0.6306 & 0.6847 \tabularnewline
59 & 0.284939 & 0.569877 & 0.715061 \tabularnewline
60 & 0.279868 & 0.559735 & 0.720132 \tabularnewline
61 & 0.273774 & 0.547548 & 0.726226 \tabularnewline
62 & 0.245547 & 0.491094 & 0.754453 \tabularnewline
63 & 0.285392 & 0.570785 & 0.714608 \tabularnewline
64 & 0.349327 & 0.698655 & 0.650673 \tabularnewline
65 & 0.327783 & 0.655567 & 0.672217 \tabularnewline
66 & 0.322055 & 0.64411 & 0.677945 \tabularnewline
67 & 0.299442 & 0.598884 & 0.700558 \tabularnewline
68 & 0.277125 & 0.55425 & 0.722875 \tabularnewline
69 & 0.317509 & 0.635018 & 0.682491 \tabularnewline
70 & 0.299688 & 0.599376 & 0.700312 \tabularnewline
71 & 0.26618 & 0.532359 & 0.73382 \tabularnewline
72 & 0.23793 & 0.47586 & 0.76207 \tabularnewline
73 & 0.227166 & 0.454332 & 0.772834 \tabularnewline
74 & 0.232123 & 0.464246 & 0.767877 \tabularnewline
75 & 0.214772 & 0.429544 & 0.785228 \tabularnewline
76 & 0.190146 & 0.380292 & 0.809854 \tabularnewline
77 & 0.169831 & 0.339662 & 0.830169 \tabularnewline
78 & 0.159447 & 0.318894 & 0.840553 \tabularnewline
79 & 0.142614 & 0.285229 & 0.857386 \tabularnewline
80 & 0.162546 & 0.325092 & 0.837454 \tabularnewline
81 & 0.14605 & 0.2921 & 0.85395 \tabularnewline
82 & 0.149947 & 0.299893 & 0.850053 \tabularnewline
83 & 0.135087 & 0.270174 & 0.864913 \tabularnewline
84 & 0.232009 & 0.464018 & 0.767991 \tabularnewline
85 & 0.220131 & 0.440261 & 0.779869 \tabularnewline
86 & 0.194289 & 0.388579 & 0.805711 \tabularnewline
87 & 0.172743 & 0.345487 & 0.827257 \tabularnewline
88 & 0.162475 & 0.32495 & 0.837525 \tabularnewline
89 & 0.18968 & 0.379359 & 0.81032 \tabularnewline
90 & 0.222868 & 0.445736 & 0.777132 \tabularnewline
91 & 0.224447 & 0.448893 & 0.775553 \tabularnewline
92 & 0.33743 & 0.674859 & 0.66257 \tabularnewline
93 & 0.30646 & 0.61292 & 0.69354 \tabularnewline
94 & 0.307099 & 0.614198 & 0.692901 \tabularnewline
95 & 0.353971 & 0.707943 & 0.646029 \tabularnewline
96 & 0.339737 & 0.679473 & 0.660263 \tabularnewline
97 & 0.371311 & 0.742621 & 0.628689 \tabularnewline
98 & 0.349523 & 0.699046 & 0.650477 \tabularnewline
99 & 0.372864 & 0.745729 & 0.627136 \tabularnewline
100 & 0.487075 & 0.97415 & 0.512925 \tabularnewline
101 & 0.466729 & 0.933458 & 0.533271 \tabularnewline
102 & 0.463398 & 0.926796 & 0.536602 \tabularnewline
103 & 0.470199 & 0.940399 & 0.529801 \tabularnewline
104 & 0.473574 & 0.947148 & 0.526426 \tabularnewline
105 & 0.491626 & 0.983251 & 0.508374 \tabularnewline
106 & 0.5132 & 0.973599 & 0.4868 \tabularnewline
107 & 0.541449 & 0.917102 & 0.458551 \tabularnewline
108 & 0.758135 & 0.483731 & 0.241865 \tabularnewline
109 & 0.863935 & 0.27213 & 0.136065 \tabularnewline
110 & 0.858499 & 0.283002 & 0.141501 \tabularnewline
111 & 0.847685 & 0.30463 & 0.152315 \tabularnewline
112 & 0.843149 & 0.313702 & 0.156851 \tabularnewline
113 & 0.90981 & 0.18038 & 0.0901902 \tabularnewline
114 & 0.919821 & 0.160358 & 0.0801791 \tabularnewline
115 & 0.939878 & 0.120244 & 0.0601219 \tabularnewline
116 & 0.952337 & 0.0953257 & 0.0476628 \tabularnewline
117 & 0.95866 & 0.0826802 & 0.0413401 \tabularnewline
118 & 0.957801 & 0.0843982 & 0.0421991 \tabularnewline
119 & 0.957975 & 0.0840493 & 0.0420246 \tabularnewline
120 & 0.971504 & 0.0569915 & 0.0284957 \tabularnewline
121 & 0.968303 & 0.0633931 & 0.0316965 \tabularnewline
122 & 0.974333 & 0.0513334 & 0.0256667 \tabularnewline
123 & 0.980915 & 0.0381701 & 0.0190851 \tabularnewline
124 & 0.984992 & 0.030017 & 0.0150085 \tabularnewline
125 & 0.986434 & 0.0271318 & 0.0135659 \tabularnewline
126 & 0.984369 & 0.0312624 & 0.0156312 \tabularnewline
127 & 0.985018 & 0.0299647 & 0.0149823 \tabularnewline
128 & 0.981962 & 0.0360751 & 0.0180375 \tabularnewline
129 & 0.986123 & 0.0277545 & 0.0138772 \tabularnewline
130 & 0.984447 & 0.0311064 & 0.0155532 \tabularnewline
131 & 0.982415 & 0.0351709 & 0.0175854 \tabularnewline
132 & 0.980433 & 0.0391345 & 0.0195673 \tabularnewline
133 & 0.979771 & 0.0404584 & 0.0202292 \tabularnewline
134 & 0.979384 & 0.0412313 & 0.0206157 \tabularnewline
135 & 0.97503 & 0.0499408 & 0.0249704 \tabularnewline
136 & 0.972929 & 0.054141 & 0.0270705 \tabularnewline
137 & 0.97905 & 0.0418993 & 0.0209496 \tabularnewline
138 & 0.98921 & 0.02158 & 0.01079 \tabularnewline
139 & 0.98996 & 0.0200791 & 0.0100396 \tabularnewline
140 & 0.988774 & 0.0224527 & 0.0112263 \tabularnewline
141 & 0.987285 & 0.0254295 & 0.0127147 \tabularnewline
142 & 0.98688 & 0.02624 & 0.01312 \tabularnewline
143 & 0.985156 & 0.0296881 & 0.014844 \tabularnewline
144 & 0.985331 & 0.0293385 & 0.0146693 \tabularnewline
145 & 0.985423 & 0.029155 & 0.0145775 \tabularnewline
146 & 0.986171 & 0.0276582 & 0.0138291 \tabularnewline
147 & 0.983462 & 0.0330766 & 0.0165383 \tabularnewline
148 & 0.980808 & 0.0383837 & 0.0191918 \tabularnewline
149 & 0.977593 & 0.0448148 & 0.0224074 \tabularnewline
150 & 0.975933 & 0.048134 & 0.024067 \tabularnewline
151 & 0.984038 & 0.0319244 & 0.0159622 \tabularnewline
152 & 0.982122 & 0.035755 & 0.0178775 \tabularnewline
153 & 0.982495 & 0.0350101 & 0.0175051 \tabularnewline
154 & 0.984778 & 0.0304441 & 0.0152221 \tabularnewline
155 & 0.983782 & 0.0324365 & 0.0162182 \tabularnewline
156 & 0.982349 & 0.0353013 & 0.0176506 \tabularnewline
157 & 0.983477 & 0.0330453 & 0.0165226 \tabularnewline
158 & 0.984107 & 0.0317863 & 0.0158932 \tabularnewline
159 & 0.981526 & 0.0369474 & 0.0184737 \tabularnewline
160 & 0.979504 & 0.0409915 & 0.0204958 \tabularnewline
161 & 0.984012 & 0.031977 & 0.0159885 \tabularnewline
162 & 0.982625 & 0.03475 & 0.017375 \tabularnewline
163 & 0.980189 & 0.0396211 & 0.0198105 \tabularnewline
164 & 0.98213 & 0.03574 & 0.01787 \tabularnewline
165 & 0.98443 & 0.031141 & 0.0155705 \tabularnewline
166 & 0.980554 & 0.0388914 & 0.0194457 \tabularnewline
167 & 0.982576 & 0.0348478 & 0.0174239 \tabularnewline
168 & 0.978757 & 0.0424851 & 0.0212426 \tabularnewline
169 & 0.974316 & 0.0513677 & 0.0256838 \tabularnewline
170 & 0.973652 & 0.0526958 & 0.0263479 \tabularnewline
171 & 0.969582 & 0.0608359 & 0.0304179 \tabularnewline
172 & 0.977865 & 0.04427 & 0.022135 \tabularnewline
173 & 0.973092 & 0.0538152 & 0.0269076 \tabularnewline
174 & 0.967234 & 0.0655324 & 0.0327662 \tabularnewline
175 & 0.960353 & 0.0792933 & 0.0396467 \tabularnewline
176 & 0.966642 & 0.0667156 & 0.0333578 \tabularnewline
177 & 0.959354 & 0.0812927 & 0.0406464 \tabularnewline
178 & 0.979375 & 0.0412495 & 0.0206248 \tabularnewline
179 & 0.97506 & 0.0498805 & 0.0249403 \tabularnewline
180 & 0.981927 & 0.0361451 & 0.0180725 \tabularnewline
181 & 0.977717 & 0.044566 & 0.022283 \tabularnewline
182 & 0.973594 & 0.0528117 & 0.0264058 \tabularnewline
183 & 0.972854 & 0.0542918 & 0.0271459 \tabularnewline
184 & 0.96797 & 0.0640601 & 0.03203 \tabularnewline
185 & 0.971664 & 0.0566713 & 0.0283356 \tabularnewline
186 & 0.966207 & 0.067586 & 0.033793 \tabularnewline
187 & 0.969472 & 0.0610567 & 0.0305283 \tabularnewline
188 & 0.96717 & 0.0656595 & 0.0328298 \tabularnewline
189 & 0.964119 & 0.0717628 & 0.0358814 \tabularnewline
190 & 0.957527 & 0.0849452 & 0.0424726 \tabularnewline
191 & 0.948803 & 0.102393 & 0.0511967 \tabularnewline
192 & 0.94579 & 0.108419 & 0.0542097 \tabularnewline
193 & 0.959584 & 0.0808327 & 0.0404164 \tabularnewline
194 & 0.967647 & 0.0647067 & 0.0323534 \tabularnewline
195 & 0.96393 & 0.0721399 & 0.0360699 \tabularnewline
196 & 0.956584 & 0.0868319 & 0.0434159 \tabularnewline
197 & 0.947481 & 0.105038 & 0.052519 \tabularnewline
198 & 0.940522 & 0.118956 & 0.059478 \tabularnewline
199 & 0.943565 & 0.112869 & 0.0564346 \tabularnewline
200 & 0.937893 & 0.124214 & 0.062107 \tabularnewline
201 & 0.94846 & 0.103079 & 0.0515397 \tabularnewline
202 & 0.943594 & 0.112812 & 0.056406 \tabularnewline
203 & 0.931316 & 0.137368 & 0.0686838 \tabularnewline
204 & 0.918235 & 0.163531 & 0.0817653 \tabularnewline
205 & 0.922219 & 0.155563 & 0.0777813 \tabularnewline
206 & 0.911075 & 0.177851 & 0.0889254 \tabularnewline
207 & 0.897341 & 0.205318 & 0.102659 \tabularnewline
208 & 0.885272 & 0.229457 & 0.114728 \tabularnewline
209 & 0.901943 & 0.196114 & 0.0980569 \tabularnewline
210 & 0.890832 & 0.218337 & 0.109168 \tabularnewline
211 & 0.870557 & 0.258886 & 0.129443 \tabularnewline
212 & 0.853165 & 0.29367 & 0.146835 \tabularnewline
213 & 0.828926 & 0.342149 & 0.171074 \tabularnewline
214 & 0.81393 & 0.37214 & 0.18607 \tabularnewline
215 & 0.793965 & 0.412071 & 0.206035 \tabularnewline
216 & 0.762483 & 0.475034 & 0.237517 \tabularnewline
217 & 0.74779 & 0.504419 & 0.25221 \tabularnewline
218 & 0.746674 & 0.506651 & 0.253326 \tabularnewline
219 & 0.711555 & 0.576891 & 0.288445 \tabularnewline
220 & 0.676041 & 0.647917 & 0.323959 \tabularnewline
221 & 0.701084 & 0.597831 & 0.298916 \tabularnewline
222 & 0.718479 & 0.563042 & 0.281521 \tabularnewline
223 & 0.678626 & 0.642749 & 0.321374 \tabularnewline
224 & 0.639212 & 0.721576 & 0.360788 \tabularnewline
225 & 0.616671 & 0.766659 & 0.383329 \tabularnewline
226 & 0.590699 & 0.818601 & 0.409301 \tabularnewline
227 & 0.553184 & 0.893631 & 0.446816 \tabularnewline
228 & 0.546718 & 0.906565 & 0.453282 \tabularnewline
229 & 0.583093 & 0.833814 & 0.416907 \tabularnewline
230 & 0.578727 & 0.842546 & 0.421273 \tabularnewline
231 & 0.619584 & 0.760833 & 0.380416 \tabularnewline
232 & 0.71232 & 0.575359 & 0.28768 \tabularnewline
233 & 0.67443 & 0.651139 & 0.32557 \tabularnewline
234 & 0.667407 & 0.665186 & 0.332593 \tabularnewline
235 & 0.627038 & 0.745925 & 0.372962 \tabularnewline
236 & 0.906372 & 0.187255 & 0.0936277 \tabularnewline
237 & 0.883377 & 0.233247 & 0.116623 \tabularnewline
238 & 0.859127 & 0.281746 & 0.140873 \tabularnewline
239 & 0.828864 & 0.342273 & 0.171136 \tabularnewline
240 & 0.792094 & 0.415812 & 0.207906 \tabularnewline
241 & 0.757872 & 0.484255 & 0.242128 \tabularnewline
242 & 0.720271 & 0.559458 & 0.279729 \tabularnewline
243 & 0.6726 & 0.654799 & 0.3274 \tabularnewline
244 & 0.689037 & 0.621926 & 0.310963 \tabularnewline
245 & 0.635972 & 0.728056 & 0.364028 \tabularnewline
246 & 0.618015 & 0.76397 & 0.381985 \tabularnewline
247 & 0.587941 & 0.824119 & 0.412059 \tabularnewline
248 & 0.530296 & 0.939408 & 0.469704 \tabularnewline
249 & 0.534501 & 0.930998 & 0.465499 \tabularnewline
250 & 0.494094 & 0.988187 & 0.505906 \tabularnewline
251 & 0.434043 & 0.868085 & 0.565957 \tabularnewline
252 & 0.467544 & 0.935089 & 0.532456 \tabularnewline
253 & 0.409431 & 0.818863 & 0.590569 \tabularnewline
254 & 0.388145 & 0.776291 & 0.611855 \tabularnewline
255 & 0.32753 & 0.65506 & 0.67247 \tabularnewline
256 & 0.281538 & 0.563076 & 0.718462 \tabularnewline
257 & 0.552147 & 0.895706 & 0.447853 \tabularnewline
258 & 0.768922 & 0.462155 & 0.231078 \tabularnewline
259 & 0.717996 & 0.564007 & 0.282004 \tabularnewline
260 & 0.980015 & 0.0399698 & 0.0199849 \tabularnewline
261 & 0.966548 & 0.0669042 & 0.0334521 \tabularnewline
262 & 0.964832 & 0.0703351 & 0.0351676 \tabularnewline
263 & 0.938983 & 0.122033 & 0.0610167 \tabularnewline
264 & 0.909648 & 0.180704 & 0.0903519 \tabularnewline
265 & 0.845539 & 0.308923 & 0.154461 \tabularnewline
266 & 0.746785 & 0.506429 & 0.253215 \tabularnewline
267 & 0.610781 & 0.778438 & 0.389219 \tabularnewline
268 & 0.47412 & 0.94824 & 0.52588 \tabularnewline
269 & 0.894879 & 0.210242 & 0.105121 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265719&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]10[/C][C]0.711527[/C][C]0.576947[/C][C]0.288473[/C][/ROW]
[ROW][C]11[/C][C]0.564913[/C][C]0.870175[/C][C]0.435087[/C][/ROW]
[ROW][C]12[/C][C]0.789995[/C][C]0.420011[/C][C]0.210005[/C][/ROW]
[ROW][C]13[/C][C]0.701139[/C][C]0.597723[/C][C]0.298861[/C][/ROW]
[ROW][C]14[/C][C]0.595345[/C][C]0.80931[/C][C]0.404655[/C][/ROW]
[ROW][C]15[/C][C]0.542148[/C][C]0.915704[/C][C]0.457852[/C][/ROW]
[ROW][C]16[/C][C]0.44386[/C][C]0.88772[/C][C]0.55614[/C][/ROW]
[ROW][C]17[/C][C]0.35042[/C][C]0.700839[/C][C]0.64958[/C][/ROW]
[ROW][C]18[/C][C]0.327589[/C][C]0.655178[/C][C]0.672411[/C][/ROW]
[ROW][C]19[/C][C]0.26647[/C][C]0.532939[/C][C]0.73353[/C][/ROW]
[ROW][C]20[/C][C]0.209084[/C][C]0.418168[/C][C]0.790916[/C][/ROW]
[ROW][C]21[/C][C]0.381147[/C][C]0.762293[/C][C]0.618853[/C][/ROW]
[ROW][C]22[/C][C]0.379318[/C][C]0.758637[/C][C]0.620682[/C][/ROW]
[ROW][C]23[/C][C]0.323792[/C][C]0.647584[/C][C]0.676208[/C][/ROW]
[ROW][C]24[/C][C]0.302114[/C][C]0.604229[/C][C]0.697886[/C][/ROW]
[ROW][C]25[/C][C]0.242699[/C][C]0.485398[/C][C]0.757301[/C][/ROW]
[ROW][C]26[/C][C]0.241538[/C][C]0.483075[/C][C]0.758462[/C][/ROW]
[ROW][C]27[/C][C]0.255405[/C][C]0.510811[/C][C]0.744595[/C][/ROW]
[ROW][C]28[/C][C]0.215247[/C][C]0.430494[/C][C]0.784753[/C][/ROW]
[ROW][C]29[/C][C]0.258743[/C][C]0.517486[/C][C]0.741257[/C][/ROW]
[ROW][C]30[/C][C]0.209871[/C][C]0.419742[/C][C]0.790129[/C][/ROW]
[ROW][C]31[/C][C]0.177546[/C][C]0.355092[/C][C]0.822454[/C][/ROW]
[ROW][C]32[/C][C]0.147572[/C][C]0.295143[/C][C]0.852428[/C][/ROW]
[ROW][C]33[/C][C]0.142464[/C][C]0.284929[/C][C]0.857536[/C][/ROW]
[ROW][C]34[/C][C]0.180485[/C][C]0.36097[/C][C]0.819515[/C][/ROW]
[ROW][C]35[/C][C]0.149982[/C][C]0.299964[/C][C]0.850018[/C][/ROW]
[ROW][C]36[/C][C]0.133136[/C][C]0.266272[/C][C]0.866864[/C][/ROW]
[ROW][C]37[/C][C]0.127035[/C][C]0.254071[/C][C]0.872965[/C][/ROW]
[ROW][C]38[/C][C]0.113935[/C][C]0.22787[/C][C]0.886065[/C][/ROW]
[ROW][C]39[/C][C]0.129846[/C][C]0.259693[/C][C]0.870154[/C][/ROW]
[ROW][C]40[/C][C]0.10395[/C][C]0.207899[/C][C]0.89605[/C][/ROW]
[ROW][C]41[/C][C]0.225295[/C][C]0.450589[/C][C]0.774705[/C][/ROW]
[ROW][C]42[/C][C]0.189918[/C][C]0.379837[/C][C]0.810082[/C][/ROW]
[ROW][C]43[/C][C]0.171635[/C][C]0.343271[/C][C]0.828365[/C][/ROW]
[ROW][C]44[/C][C]0.145033[/C][C]0.290066[/C][C]0.854967[/C][/ROW]
[ROW][C]45[/C][C]0.12698[/C][C]0.25396[/C][C]0.87302[/C][/ROW]
[ROW][C]46[/C][C]0.106678[/C][C]0.213356[/C][C]0.893322[/C][/ROW]
[ROW][C]47[/C][C]0.0871996[/C][C]0.174399[/C][C]0.9128[/C][/ROW]
[ROW][C]48[/C][C]0.138587[/C][C]0.277173[/C][C]0.861413[/C][/ROW]
[ROW][C]49[/C][C]0.164933[/C][C]0.329865[/C][C]0.835067[/C][/ROW]
[ROW][C]50[/C][C]0.143893[/C][C]0.287786[/C][C]0.856107[/C][/ROW]
[ROW][C]51[/C][C]0.121551[/C][C]0.243102[/C][C]0.878449[/C][/ROW]
[ROW][C]52[/C][C]0.149803[/C][C]0.299606[/C][C]0.850197[/C][/ROW]
[ROW][C]53[/C][C]0.125891[/C][C]0.251781[/C][C]0.874109[/C][/ROW]
[ROW][C]54[/C][C]0.120565[/C][C]0.241131[/C][C]0.879435[/C][/ROW]
[ROW][C]55[/C][C]0.135802[/C][C]0.271604[/C][C]0.864198[/C][/ROW]
[ROW][C]56[/C][C]0.1183[/C][C]0.2366[/C][C]0.8817[/C][/ROW]
[ROW][C]57[/C][C]0.231813[/C][C]0.463626[/C][C]0.768187[/C][/ROW]
[ROW][C]58[/C][C]0.3153[/C][C]0.6306[/C][C]0.6847[/C][/ROW]
[ROW][C]59[/C][C]0.284939[/C][C]0.569877[/C][C]0.715061[/C][/ROW]
[ROW][C]60[/C][C]0.279868[/C][C]0.559735[/C][C]0.720132[/C][/ROW]
[ROW][C]61[/C][C]0.273774[/C][C]0.547548[/C][C]0.726226[/C][/ROW]
[ROW][C]62[/C][C]0.245547[/C][C]0.491094[/C][C]0.754453[/C][/ROW]
[ROW][C]63[/C][C]0.285392[/C][C]0.570785[/C][C]0.714608[/C][/ROW]
[ROW][C]64[/C][C]0.349327[/C][C]0.698655[/C][C]0.650673[/C][/ROW]
[ROW][C]65[/C][C]0.327783[/C][C]0.655567[/C][C]0.672217[/C][/ROW]
[ROW][C]66[/C][C]0.322055[/C][C]0.64411[/C][C]0.677945[/C][/ROW]
[ROW][C]67[/C][C]0.299442[/C][C]0.598884[/C][C]0.700558[/C][/ROW]
[ROW][C]68[/C][C]0.277125[/C][C]0.55425[/C][C]0.722875[/C][/ROW]
[ROW][C]69[/C][C]0.317509[/C][C]0.635018[/C][C]0.682491[/C][/ROW]
[ROW][C]70[/C][C]0.299688[/C][C]0.599376[/C][C]0.700312[/C][/ROW]
[ROW][C]71[/C][C]0.26618[/C][C]0.532359[/C][C]0.73382[/C][/ROW]
[ROW][C]72[/C][C]0.23793[/C][C]0.47586[/C][C]0.76207[/C][/ROW]
[ROW][C]73[/C][C]0.227166[/C][C]0.454332[/C][C]0.772834[/C][/ROW]
[ROW][C]74[/C][C]0.232123[/C][C]0.464246[/C][C]0.767877[/C][/ROW]
[ROW][C]75[/C][C]0.214772[/C][C]0.429544[/C][C]0.785228[/C][/ROW]
[ROW][C]76[/C][C]0.190146[/C][C]0.380292[/C][C]0.809854[/C][/ROW]
[ROW][C]77[/C][C]0.169831[/C][C]0.339662[/C][C]0.830169[/C][/ROW]
[ROW][C]78[/C][C]0.159447[/C][C]0.318894[/C][C]0.840553[/C][/ROW]
[ROW][C]79[/C][C]0.142614[/C][C]0.285229[/C][C]0.857386[/C][/ROW]
[ROW][C]80[/C][C]0.162546[/C][C]0.325092[/C][C]0.837454[/C][/ROW]
[ROW][C]81[/C][C]0.14605[/C][C]0.2921[/C][C]0.85395[/C][/ROW]
[ROW][C]82[/C][C]0.149947[/C][C]0.299893[/C][C]0.850053[/C][/ROW]
[ROW][C]83[/C][C]0.135087[/C][C]0.270174[/C][C]0.864913[/C][/ROW]
[ROW][C]84[/C][C]0.232009[/C][C]0.464018[/C][C]0.767991[/C][/ROW]
[ROW][C]85[/C][C]0.220131[/C][C]0.440261[/C][C]0.779869[/C][/ROW]
[ROW][C]86[/C][C]0.194289[/C][C]0.388579[/C][C]0.805711[/C][/ROW]
[ROW][C]87[/C][C]0.172743[/C][C]0.345487[/C][C]0.827257[/C][/ROW]
[ROW][C]88[/C][C]0.162475[/C][C]0.32495[/C][C]0.837525[/C][/ROW]
[ROW][C]89[/C][C]0.18968[/C][C]0.379359[/C][C]0.81032[/C][/ROW]
[ROW][C]90[/C][C]0.222868[/C][C]0.445736[/C][C]0.777132[/C][/ROW]
[ROW][C]91[/C][C]0.224447[/C][C]0.448893[/C][C]0.775553[/C][/ROW]
[ROW][C]92[/C][C]0.33743[/C][C]0.674859[/C][C]0.66257[/C][/ROW]
[ROW][C]93[/C][C]0.30646[/C][C]0.61292[/C][C]0.69354[/C][/ROW]
[ROW][C]94[/C][C]0.307099[/C][C]0.614198[/C][C]0.692901[/C][/ROW]
[ROW][C]95[/C][C]0.353971[/C][C]0.707943[/C][C]0.646029[/C][/ROW]
[ROW][C]96[/C][C]0.339737[/C][C]0.679473[/C][C]0.660263[/C][/ROW]
[ROW][C]97[/C][C]0.371311[/C][C]0.742621[/C][C]0.628689[/C][/ROW]
[ROW][C]98[/C][C]0.349523[/C][C]0.699046[/C][C]0.650477[/C][/ROW]
[ROW][C]99[/C][C]0.372864[/C][C]0.745729[/C][C]0.627136[/C][/ROW]
[ROW][C]100[/C][C]0.487075[/C][C]0.97415[/C][C]0.512925[/C][/ROW]
[ROW][C]101[/C][C]0.466729[/C][C]0.933458[/C][C]0.533271[/C][/ROW]
[ROW][C]102[/C][C]0.463398[/C][C]0.926796[/C][C]0.536602[/C][/ROW]
[ROW][C]103[/C][C]0.470199[/C][C]0.940399[/C][C]0.529801[/C][/ROW]
[ROW][C]104[/C][C]0.473574[/C][C]0.947148[/C][C]0.526426[/C][/ROW]
[ROW][C]105[/C][C]0.491626[/C][C]0.983251[/C][C]0.508374[/C][/ROW]
[ROW][C]106[/C][C]0.5132[/C][C]0.973599[/C][C]0.4868[/C][/ROW]
[ROW][C]107[/C][C]0.541449[/C][C]0.917102[/C][C]0.458551[/C][/ROW]
[ROW][C]108[/C][C]0.758135[/C][C]0.483731[/C][C]0.241865[/C][/ROW]
[ROW][C]109[/C][C]0.863935[/C][C]0.27213[/C][C]0.136065[/C][/ROW]
[ROW][C]110[/C][C]0.858499[/C][C]0.283002[/C][C]0.141501[/C][/ROW]
[ROW][C]111[/C][C]0.847685[/C][C]0.30463[/C][C]0.152315[/C][/ROW]
[ROW][C]112[/C][C]0.843149[/C][C]0.313702[/C][C]0.156851[/C][/ROW]
[ROW][C]113[/C][C]0.90981[/C][C]0.18038[/C][C]0.0901902[/C][/ROW]
[ROW][C]114[/C][C]0.919821[/C][C]0.160358[/C][C]0.0801791[/C][/ROW]
[ROW][C]115[/C][C]0.939878[/C][C]0.120244[/C][C]0.0601219[/C][/ROW]
[ROW][C]116[/C][C]0.952337[/C][C]0.0953257[/C][C]0.0476628[/C][/ROW]
[ROW][C]117[/C][C]0.95866[/C][C]0.0826802[/C][C]0.0413401[/C][/ROW]
[ROW][C]118[/C][C]0.957801[/C][C]0.0843982[/C][C]0.0421991[/C][/ROW]
[ROW][C]119[/C][C]0.957975[/C][C]0.0840493[/C][C]0.0420246[/C][/ROW]
[ROW][C]120[/C][C]0.971504[/C][C]0.0569915[/C][C]0.0284957[/C][/ROW]
[ROW][C]121[/C][C]0.968303[/C][C]0.0633931[/C][C]0.0316965[/C][/ROW]
[ROW][C]122[/C][C]0.974333[/C][C]0.0513334[/C][C]0.0256667[/C][/ROW]
[ROW][C]123[/C][C]0.980915[/C][C]0.0381701[/C][C]0.0190851[/C][/ROW]
[ROW][C]124[/C][C]0.984992[/C][C]0.030017[/C][C]0.0150085[/C][/ROW]
[ROW][C]125[/C][C]0.986434[/C][C]0.0271318[/C][C]0.0135659[/C][/ROW]
[ROW][C]126[/C][C]0.984369[/C][C]0.0312624[/C][C]0.0156312[/C][/ROW]
[ROW][C]127[/C][C]0.985018[/C][C]0.0299647[/C][C]0.0149823[/C][/ROW]
[ROW][C]128[/C][C]0.981962[/C][C]0.0360751[/C][C]0.0180375[/C][/ROW]
[ROW][C]129[/C][C]0.986123[/C][C]0.0277545[/C][C]0.0138772[/C][/ROW]
[ROW][C]130[/C][C]0.984447[/C][C]0.0311064[/C][C]0.0155532[/C][/ROW]
[ROW][C]131[/C][C]0.982415[/C][C]0.0351709[/C][C]0.0175854[/C][/ROW]
[ROW][C]132[/C][C]0.980433[/C][C]0.0391345[/C][C]0.0195673[/C][/ROW]
[ROW][C]133[/C][C]0.979771[/C][C]0.0404584[/C][C]0.0202292[/C][/ROW]
[ROW][C]134[/C][C]0.979384[/C][C]0.0412313[/C][C]0.0206157[/C][/ROW]
[ROW][C]135[/C][C]0.97503[/C][C]0.0499408[/C][C]0.0249704[/C][/ROW]
[ROW][C]136[/C][C]0.972929[/C][C]0.054141[/C][C]0.0270705[/C][/ROW]
[ROW][C]137[/C][C]0.97905[/C][C]0.0418993[/C][C]0.0209496[/C][/ROW]
[ROW][C]138[/C][C]0.98921[/C][C]0.02158[/C][C]0.01079[/C][/ROW]
[ROW][C]139[/C][C]0.98996[/C][C]0.0200791[/C][C]0.0100396[/C][/ROW]
[ROW][C]140[/C][C]0.988774[/C][C]0.0224527[/C][C]0.0112263[/C][/ROW]
[ROW][C]141[/C][C]0.987285[/C][C]0.0254295[/C][C]0.0127147[/C][/ROW]
[ROW][C]142[/C][C]0.98688[/C][C]0.02624[/C][C]0.01312[/C][/ROW]
[ROW][C]143[/C][C]0.985156[/C][C]0.0296881[/C][C]0.014844[/C][/ROW]
[ROW][C]144[/C][C]0.985331[/C][C]0.0293385[/C][C]0.0146693[/C][/ROW]
[ROW][C]145[/C][C]0.985423[/C][C]0.029155[/C][C]0.0145775[/C][/ROW]
[ROW][C]146[/C][C]0.986171[/C][C]0.0276582[/C][C]0.0138291[/C][/ROW]
[ROW][C]147[/C][C]0.983462[/C][C]0.0330766[/C][C]0.0165383[/C][/ROW]
[ROW][C]148[/C][C]0.980808[/C][C]0.0383837[/C][C]0.0191918[/C][/ROW]
[ROW][C]149[/C][C]0.977593[/C][C]0.0448148[/C][C]0.0224074[/C][/ROW]
[ROW][C]150[/C][C]0.975933[/C][C]0.048134[/C][C]0.024067[/C][/ROW]
[ROW][C]151[/C][C]0.984038[/C][C]0.0319244[/C][C]0.0159622[/C][/ROW]
[ROW][C]152[/C][C]0.982122[/C][C]0.035755[/C][C]0.0178775[/C][/ROW]
[ROW][C]153[/C][C]0.982495[/C][C]0.0350101[/C][C]0.0175051[/C][/ROW]
[ROW][C]154[/C][C]0.984778[/C][C]0.0304441[/C][C]0.0152221[/C][/ROW]
[ROW][C]155[/C][C]0.983782[/C][C]0.0324365[/C][C]0.0162182[/C][/ROW]
[ROW][C]156[/C][C]0.982349[/C][C]0.0353013[/C][C]0.0176506[/C][/ROW]
[ROW][C]157[/C][C]0.983477[/C][C]0.0330453[/C][C]0.0165226[/C][/ROW]
[ROW][C]158[/C][C]0.984107[/C][C]0.0317863[/C][C]0.0158932[/C][/ROW]
[ROW][C]159[/C][C]0.981526[/C][C]0.0369474[/C][C]0.0184737[/C][/ROW]
[ROW][C]160[/C][C]0.979504[/C][C]0.0409915[/C][C]0.0204958[/C][/ROW]
[ROW][C]161[/C][C]0.984012[/C][C]0.031977[/C][C]0.0159885[/C][/ROW]
[ROW][C]162[/C][C]0.982625[/C][C]0.03475[/C][C]0.017375[/C][/ROW]
[ROW][C]163[/C][C]0.980189[/C][C]0.0396211[/C][C]0.0198105[/C][/ROW]
[ROW][C]164[/C][C]0.98213[/C][C]0.03574[/C][C]0.01787[/C][/ROW]
[ROW][C]165[/C][C]0.98443[/C][C]0.031141[/C][C]0.0155705[/C][/ROW]
[ROW][C]166[/C][C]0.980554[/C][C]0.0388914[/C][C]0.0194457[/C][/ROW]
[ROW][C]167[/C][C]0.982576[/C][C]0.0348478[/C][C]0.0174239[/C][/ROW]
[ROW][C]168[/C][C]0.978757[/C][C]0.0424851[/C][C]0.0212426[/C][/ROW]
[ROW][C]169[/C][C]0.974316[/C][C]0.0513677[/C][C]0.0256838[/C][/ROW]
[ROW][C]170[/C][C]0.973652[/C][C]0.0526958[/C][C]0.0263479[/C][/ROW]
[ROW][C]171[/C][C]0.969582[/C][C]0.0608359[/C][C]0.0304179[/C][/ROW]
[ROW][C]172[/C][C]0.977865[/C][C]0.04427[/C][C]0.022135[/C][/ROW]
[ROW][C]173[/C][C]0.973092[/C][C]0.0538152[/C][C]0.0269076[/C][/ROW]
[ROW][C]174[/C][C]0.967234[/C][C]0.0655324[/C][C]0.0327662[/C][/ROW]
[ROW][C]175[/C][C]0.960353[/C][C]0.0792933[/C][C]0.0396467[/C][/ROW]
[ROW][C]176[/C][C]0.966642[/C][C]0.0667156[/C][C]0.0333578[/C][/ROW]
[ROW][C]177[/C][C]0.959354[/C][C]0.0812927[/C][C]0.0406464[/C][/ROW]
[ROW][C]178[/C][C]0.979375[/C][C]0.0412495[/C][C]0.0206248[/C][/ROW]
[ROW][C]179[/C][C]0.97506[/C][C]0.0498805[/C][C]0.0249403[/C][/ROW]
[ROW][C]180[/C][C]0.981927[/C][C]0.0361451[/C][C]0.0180725[/C][/ROW]
[ROW][C]181[/C][C]0.977717[/C][C]0.044566[/C][C]0.022283[/C][/ROW]
[ROW][C]182[/C][C]0.973594[/C][C]0.0528117[/C][C]0.0264058[/C][/ROW]
[ROW][C]183[/C][C]0.972854[/C][C]0.0542918[/C][C]0.0271459[/C][/ROW]
[ROW][C]184[/C][C]0.96797[/C][C]0.0640601[/C][C]0.03203[/C][/ROW]
[ROW][C]185[/C][C]0.971664[/C][C]0.0566713[/C][C]0.0283356[/C][/ROW]
[ROW][C]186[/C][C]0.966207[/C][C]0.067586[/C][C]0.033793[/C][/ROW]
[ROW][C]187[/C][C]0.969472[/C][C]0.0610567[/C][C]0.0305283[/C][/ROW]
[ROW][C]188[/C][C]0.96717[/C][C]0.0656595[/C][C]0.0328298[/C][/ROW]
[ROW][C]189[/C][C]0.964119[/C][C]0.0717628[/C][C]0.0358814[/C][/ROW]
[ROW][C]190[/C][C]0.957527[/C][C]0.0849452[/C][C]0.0424726[/C][/ROW]
[ROW][C]191[/C][C]0.948803[/C][C]0.102393[/C][C]0.0511967[/C][/ROW]
[ROW][C]192[/C][C]0.94579[/C][C]0.108419[/C][C]0.0542097[/C][/ROW]
[ROW][C]193[/C][C]0.959584[/C][C]0.0808327[/C][C]0.0404164[/C][/ROW]
[ROW][C]194[/C][C]0.967647[/C][C]0.0647067[/C][C]0.0323534[/C][/ROW]
[ROW][C]195[/C][C]0.96393[/C][C]0.0721399[/C][C]0.0360699[/C][/ROW]
[ROW][C]196[/C][C]0.956584[/C][C]0.0868319[/C][C]0.0434159[/C][/ROW]
[ROW][C]197[/C][C]0.947481[/C][C]0.105038[/C][C]0.052519[/C][/ROW]
[ROW][C]198[/C][C]0.940522[/C][C]0.118956[/C][C]0.059478[/C][/ROW]
[ROW][C]199[/C][C]0.943565[/C][C]0.112869[/C][C]0.0564346[/C][/ROW]
[ROW][C]200[/C][C]0.937893[/C][C]0.124214[/C][C]0.062107[/C][/ROW]
[ROW][C]201[/C][C]0.94846[/C][C]0.103079[/C][C]0.0515397[/C][/ROW]
[ROW][C]202[/C][C]0.943594[/C][C]0.112812[/C][C]0.056406[/C][/ROW]
[ROW][C]203[/C][C]0.931316[/C][C]0.137368[/C][C]0.0686838[/C][/ROW]
[ROW][C]204[/C][C]0.918235[/C][C]0.163531[/C][C]0.0817653[/C][/ROW]
[ROW][C]205[/C][C]0.922219[/C][C]0.155563[/C][C]0.0777813[/C][/ROW]
[ROW][C]206[/C][C]0.911075[/C][C]0.177851[/C][C]0.0889254[/C][/ROW]
[ROW][C]207[/C][C]0.897341[/C][C]0.205318[/C][C]0.102659[/C][/ROW]
[ROW][C]208[/C][C]0.885272[/C][C]0.229457[/C][C]0.114728[/C][/ROW]
[ROW][C]209[/C][C]0.901943[/C][C]0.196114[/C][C]0.0980569[/C][/ROW]
[ROW][C]210[/C][C]0.890832[/C][C]0.218337[/C][C]0.109168[/C][/ROW]
[ROW][C]211[/C][C]0.870557[/C][C]0.258886[/C][C]0.129443[/C][/ROW]
[ROW][C]212[/C][C]0.853165[/C][C]0.29367[/C][C]0.146835[/C][/ROW]
[ROW][C]213[/C][C]0.828926[/C][C]0.342149[/C][C]0.171074[/C][/ROW]
[ROW][C]214[/C][C]0.81393[/C][C]0.37214[/C][C]0.18607[/C][/ROW]
[ROW][C]215[/C][C]0.793965[/C][C]0.412071[/C][C]0.206035[/C][/ROW]
[ROW][C]216[/C][C]0.762483[/C][C]0.475034[/C][C]0.237517[/C][/ROW]
[ROW][C]217[/C][C]0.74779[/C][C]0.504419[/C][C]0.25221[/C][/ROW]
[ROW][C]218[/C][C]0.746674[/C][C]0.506651[/C][C]0.253326[/C][/ROW]
[ROW][C]219[/C][C]0.711555[/C][C]0.576891[/C][C]0.288445[/C][/ROW]
[ROW][C]220[/C][C]0.676041[/C][C]0.647917[/C][C]0.323959[/C][/ROW]
[ROW][C]221[/C][C]0.701084[/C][C]0.597831[/C][C]0.298916[/C][/ROW]
[ROW][C]222[/C][C]0.718479[/C][C]0.563042[/C][C]0.281521[/C][/ROW]
[ROW][C]223[/C][C]0.678626[/C][C]0.642749[/C][C]0.321374[/C][/ROW]
[ROW][C]224[/C][C]0.639212[/C][C]0.721576[/C][C]0.360788[/C][/ROW]
[ROW][C]225[/C][C]0.616671[/C][C]0.766659[/C][C]0.383329[/C][/ROW]
[ROW][C]226[/C][C]0.590699[/C][C]0.818601[/C][C]0.409301[/C][/ROW]
[ROW][C]227[/C][C]0.553184[/C][C]0.893631[/C][C]0.446816[/C][/ROW]
[ROW][C]228[/C][C]0.546718[/C][C]0.906565[/C][C]0.453282[/C][/ROW]
[ROW][C]229[/C][C]0.583093[/C][C]0.833814[/C][C]0.416907[/C][/ROW]
[ROW][C]230[/C][C]0.578727[/C][C]0.842546[/C][C]0.421273[/C][/ROW]
[ROW][C]231[/C][C]0.619584[/C][C]0.760833[/C][C]0.380416[/C][/ROW]
[ROW][C]232[/C][C]0.71232[/C][C]0.575359[/C][C]0.28768[/C][/ROW]
[ROW][C]233[/C][C]0.67443[/C][C]0.651139[/C][C]0.32557[/C][/ROW]
[ROW][C]234[/C][C]0.667407[/C][C]0.665186[/C][C]0.332593[/C][/ROW]
[ROW][C]235[/C][C]0.627038[/C][C]0.745925[/C][C]0.372962[/C][/ROW]
[ROW][C]236[/C][C]0.906372[/C][C]0.187255[/C][C]0.0936277[/C][/ROW]
[ROW][C]237[/C][C]0.883377[/C][C]0.233247[/C][C]0.116623[/C][/ROW]
[ROW][C]238[/C][C]0.859127[/C][C]0.281746[/C][C]0.140873[/C][/ROW]
[ROW][C]239[/C][C]0.828864[/C][C]0.342273[/C][C]0.171136[/C][/ROW]
[ROW][C]240[/C][C]0.792094[/C][C]0.415812[/C][C]0.207906[/C][/ROW]
[ROW][C]241[/C][C]0.757872[/C][C]0.484255[/C][C]0.242128[/C][/ROW]
[ROW][C]242[/C][C]0.720271[/C][C]0.559458[/C][C]0.279729[/C][/ROW]
[ROW][C]243[/C][C]0.6726[/C][C]0.654799[/C][C]0.3274[/C][/ROW]
[ROW][C]244[/C][C]0.689037[/C][C]0.621926[/C][C]0.310963[/C][/ROW]
[ROW][C]245[/C][C]0.635972[/C][C]0.728056[/C][C]0.364028[/C][/ROW]
[ROW][C]246[/C][C]0.618015[/C][C]0.76397[/C][C]0.381985[/C][/ROW]
[ROW][C]247[/C][C]0.587941[/C][C]0.824119[/C][C]0.412059[/C][/ROW]
[ROW][C]248[/C][C]0.530296[/C][C]0.939408[/C][C]0.469704[/C][/ROW]
[ROW][C]249[/C][C]0.534501[/C][C]0.930998[/C][C]0.465499[/C][/ROW]
[ROW][C]250[/C][C]0.494094[/C][C]0.988187[/C][C]0.505906[/C][/ROW]
[ROW][C]251[/C][C]0.434043[/C][C]0.868085[/C][C]0.565957[/C][/ROW]
[ROW][C]252[/C][C]0.467544[/C][C]0.935089[/C][C]0.532456[/C][/ROW]
[ROW][C]253[/C][C]0.409431[/C][C]0.818863[/C][C]0.590569[/C][/ROW]
[ROW][C]254[/C][C]0.388145[/C][C]0.776291[/C][C]0.611855[/C][/ROW]
[ROW][C]255[/C][C]0.32753[/C][C]0.65506[/C][C]0.67247[/C][/ROW]
[ROW][C]256[/C][C]0.281538[/C][C]0.563076[/C][C]0.718462[/C][/ROW]
[ROW][C]257[/C][C]0.552147[/C][C]0.895706[/C][C]0.447853[/C][/ROW]
[ROW][C]258[/C][C]0.768922[/C][C]0.462155[/C][C]0.231078[/C][/ROW]
[ROW][C]259[/C][C]0.717996[/C][C]0.564007[/C][C]0.282004[/C][/ROW]
[ROW][C]260[/C][C]0.980015[/C][C]0.0399698[/C][C]0.0199849[/C][/ROW]
[ROW][C]261[/C][C]0.966548[/C][C]0.0669042[/C][C]0.0334521[/C][/ROW]
[ROW][C]262[/C][C]0.964832[/C][C]0.0703351[/C][C]0.0351676[/C][/ROW]
[ROW][C]263[/C][C]0.938983[/C][C]0.122033[/C][C]0.0610167[/C][/ROW]
[ROW][C]264[/C][C]0.909648[/C][C]0.180704[/C][C]0.0903519[/C][/ROW]
[ROW][C]265[/C][C]0.845539[/C][C]0.308923[/C][C]0.154461[/C][/ROW]
[ROW][C]266[/C][C]0.746785[/C][C]0.506429[/C][C]0.253215[/C][/ROW]
[ROW][C]267[/C][C]0.610781[/C][C]0.778438[/C][C]0.389219[/C][/ROW]
[ROW][C]268[/C][C]0.47412[/C][C]0.94824[/C][C]0.52588[/C][/ROW]
[ROW][C]269[/C][C]0.894879[/C][C]0.210242[/C][C]0.105121[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265719&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265719&T=5

As an alternative you can also use a QR Code:

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

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
10	0.711527	0.576947	0.288473
11	0.564913	0.870175	0.435087
12	0.789995	0.420011	0.210005
13	0.701139	0.597723	0.298861
14	0.595345	0.80931	0.404655
15	0.542148	0.915704	0.457852
16	0.44386	0.88772	0.55614
17	0.35042	0.700839	0.64958
18	0.327589	0.655178	0.672411
19	0.26647	0.532939	0.73353
20	0.209084	0.418168	0.790916
21	0.381147	0.762293	0.618853
22	0.379318	0.758637	0.620682
23	0.323792	0.647584	0.676208
24	0.302114	0.604229	0.697886
25	0.242699	0.485398	0.757301
26	0.241538	0.483075	0.758462
27	0.255405	0.510811	0.744595
28	0.215247	0.430494	0.784753
29	0.258743	0.517486	0.741257
30	0.209871	0.419742	0.790129
31	0.177546	0.355092	0.822454
32	0.147572	0.295143	0.852428
33	0.142464	0.284929	0.857536
34	0.180485	0.36097	0.819515
35	0.149982	0.299964	0.850018
36	0.133136	0.266272	0.866864
37	0.127035	0.254071	0.872965
38	0.113935	0.22787	0.886065
39	0.129846	0.259693	0.870154
40	0.10395	0.207899	0.89605
41	0.225295	0.450589	0.774705
42	0.189918	0.379837	0.810082
43	0.171635	0.343271	0.828365
44	0.145033	0.290066	0.854967
45	0.12698	0.25396	0.87302
46	0.106678	0.213356	0.893322
47	0.0871996	0.174399	0.9128
48	0.138587	0.277173	0.861413
49	0.164933	0.329865	0.835067
50	0.143893	0.287786	0.856107
51	0.121551	0.243102	0.878449
52	0.149803	0.299606	0.850197
53	0.125891	0.251781	0.874109
54	0.120565	0.241131	0.879435
55	0.135802	0.271604	0.864198
56	0.1183	0.2366	0.8817
57	0.231813	0.463626	0.768187
58	0.3153	0.6306	0.6847
59	0.284939	0.569877	0.715061
60	0.279868	0.559735	0.720132
61	0.273774	0.547548	0.726226
62	0.245547	0.491094	0.754453
63	0.285392	0.570785	0.714608
64	0.349327	0.698655	0.650673
65	0.327783	0.655567	0.672217
66	0.322055	0.64411	0.677945
67	0.299442	0.598884	0.700558
68	0.277125	0.55425	0.722875
69	0.317509	0.635018	0.682491
70	0.299688	0.599376	0.700312
71	0.26618	0.532359	0.73382
72	0.23793	0.47586	0.76207
73	0.227166	0.454332	0.772834
74	0.232123	0.464246	0.767877
75	0.214772	0.429544	0.785228
76	0.190146	0.380292	0.809854
77	0.169831	0.339662	0.830169
78	0.159447	0.318894	0.840553
79	0.142614	0.285229	0.857386
80	0.162546	0.325092	0.837454
81	0.14605	0.2921	0.85395
82	0.149947	0.299893	0.850053
83	0.135087	0.270174	0.864913
84	0.232009	0.464018	0.767991
85	0.220131	0.440261	0.779869
86	0.194289	0.388579	0.805711
87	0.172743	0.345487	0.827257
88	0.162475	0.32495	0.837525
89	0.18968	0.379359	0.81032
90	0.222868	0.445736	0.777132
91	0.224447	0.448893	0.775553
92	0.33743	0.674859	0.66257
93	0.30646	0.61292	0.69354
94	0.307099	0.614198	0.692901
95	0.353971	0.707943	0.646029
96	0.339737	0.679473	0.660263
97	0.371311	0.742621	0.628689
98	0.349523	0.699046	0.650477
99	0.372864	0.745729	0.627136
100	0.487075	0.97415	0.512925
101	0.466729	0.933458	0.533271
102	0.463398	0.926796	0.536602
103	0.470199	0.940399	0.529801
104	0.473574	0.947148	0.526426
105	0.491626	0.983251	0.508374
106	0.5132	0.973599	0.4868
107	0.541449	0.917102	0.458551
108	0.758135	0.483731	0.241865
109	0.863935	0.27213	0.136065
110	0.858499	0.283002	0.141501
111	0.847685	0.30463	0.152315
112	0.843149	0.313702	0.156851
113	0.90981	0.18038	0.0901902
114	0.919821	0.160358	0.0801791
115	0.939878	0.120244	0.0601219
116	0.952337	0.0953257	0.0476628
117	0.95866	0.0826802	0.0413401
118	0.957801	0.0843982	0.0421991
119	0.957975	0.0840493	0.0420246
120	0.971504	0.0569915	0.0284957
121	0.968303	0.0633931	0.0316965
122	0.974333	0.0513334	0.0256667
123	0.980915	0.0381701	0.0190851
124	0.984992	0.030017	0.0150085
125	0.986434	0.0271318	0.0135659
126	0.984369	0.0312624	0.0156312
127	0.985018	0.0299647	0.0149823
128	0.981962	0.0360751	0.0180375
129	0.986123	0.0277545	0.0138772
130	0.984447	0.0311064	0.0155532
131	0.982415	0.0351709	0.0175854
132	0.980433	0.0391345	0.0195673
133	0.979771	0.0404584	0.0202292
134	0.979384	0.0412313	0.0206157
135	0.97503	0.0499408	0.0249704
136	0.972929	0.054141	0.0270705
137	0.97905	0.0418993	0.0209496
138	0.98921	0.02158	0.01079
139	0.98996	0.0200791	0.0100396
140	0.988774	0.0224527	0.0112263
141	0.987285	0.0254295	0.0127147
142	0.98688	0.02624	0.01312
143	0.985156	0.0296881	0.014844
144	0.985331	0.0293385	0.0146693
145	0.985423	0.029155	0.0145775
146	0.986171	0.0276582	0.0138291
147	0.983462	0.0330766	0.0165383
148	0.980808	0.0383837	0.0191918
149	0.977593	0.0448148	0.0224074
150	0.975933	0.048134	0.024067
151	0.984038	0.0319244	0.0159622
152	0.982122	0.035755	0.0178775
153	0.982495	0.0350101	0.0175051
154	0.984778	0.0304441	0.0152221
155	0.983782	0.0324365	0.0162182
156	0.982349	0.0353013	0.0176506
157	0.983477	0.0330453	0.0165226
158	0.984107	0.0317863	0.0158932
159	0.981526	0.0369474	0.0184737
160	0.979504	0.0409915	0.0204958
161	0.984012	0.031977	0.0159885
162	0.982625	0.03475	0.017375
163	0.980189	0.0396211	0.0198105
164	0.98213	0.03574	0.01787
165	0.98443	0.031141	0.0155705
166	0.980554	0.0388914	0.0194457
167	0.982576	0.0348478	0.0174239
168	0.978757	0.0424851	0.0212426
169	0.974316	0.0513677	0.0256838
170	0.973652	0.0526958	0.0263479
171	0.969582	0.0608359	0.0304179
172	0.977865	0.04427	0.022135
173	0.973092	0.0538152	0.0269076
174	0.967234	0.0655324	0.0327662
175	0.960353	0.0792933	0.0396467
176	0.966642	0.0667156	0.0333578
177	0.959354	0.0812927	0.0406464
178	0.979375	0.0412495	0.0206248
179	0.97506	0.0498805	0.0249403
180	0.981927	0.0361451	0.0180725
181	0.977717	0.044566	0.022283
182	0.973594	0.0528117	0.0264058
183	0.972854	0.0542918	0.0271459
184	0.96797	0.0640601	0.03203
185	0.971664	0.0566713	0.0283356
186	0.966207	0.067586	0.033793
187	0.969472	0.0610567	0.0305283
188	0.96717	0.0656595	0.0328298
189	0.964119	0.0717628	0.0358814
190	0.957527	0.0849452	0.0424726
191	0.948803	0.102393	0.0511967
192	0.94579	0.108419	0.0542097
193	0.959584	0.0808327	0.0404164
194	0.967647	0.0647067	0.0323534
195	0.96393	0.0721399	0.0360699
196	0.956584	0.0868319	0.0434159
197	0.947481	0.105038	0.052519
198	0.940522	0.118956	0.059478
199	0.943565	0.112869	0.0564346
200	0.937893	0.124214	0.062107
201	0.94846	0.103079	0.0515397
202	0.943594	0.112812	0.056406
203	0.931316	0.137368	0.0686838
204	0.918235	0.163531	0.0817653
205	0.922219	0.155563	0.0777813
206	0.911075	0.177851	0.0889254
207	0.897341	0.205318	0.102659
208	0.885272	0.229457	0.114728
209	0.901943	0.196114	0.0980569
210	0.890832	0.218337	0.109168
211	0.870557	0.258886	0.129443
212	0.853165	0.29367	0.146835
213	0.828926	0.342149	0.171074
214	0.81393	0.37214	0.18607
215	0.793965	0.412071	0.206035
216	0.762483	0.475034	0.237517
217	0.74779	0.504419	0.25221
218	0.746674	0.506651	0.253326
219	0.711555	0.576891	0.288445
220	0.676041	0.647917	0.323959
221	0.701084	0.597831	0.298916
222	0.718479	0.563042	0.281521
223	0.678626	0.642749	0.321374
224	0.639212	0.721576	0.360788
225	0.616671	0.766659	0.383329
226	0.590699	0.818601	0.409301
227	0.553184	0.893631	0.446816
228	0.546718	0.906565	0.453282
229	0.583093	0.833814	0.416907
230	0.578727	0.842546	0.421273
231	0.619584	0.760833	0.380416
232	0.71232	0.575359	0.28768
233	0.67443	0.651139	0.32557
234	0.667407	0.665186	0.332593
235	0.627038	0.745925	0.372962
236	0.906372	0.187255	0.0936277
237	0.883377	0.233247	0.116623
238	0.859127	0.281746	0.140873
239	0.828864	0.342273	0.171136
240	0.792094	0.415812	0.207906
241	0.757872	0.484255	0.242128
242	0.720271	0.559458	0.279729
243	0.6726	0.654799	0.3274
244	0.689037	0.621926	0.310963
245	0.635972	0.728056	0.364028
246	0.618015	0.76397	0.381985
247	0.587941	0.824119	0.412059
248	0.530296	0.939408	0.469704
249	0.534501	0.930998	0.465499
250	0.494094	0.988187	0.505906
251	0.434043	0.868085	0.565957
252	0.467544	0.935089	0.532456
253	0.409431	0.818863	0.590569
254	0.388145	0.776291	0.611855
255	0.32753	0.65506	0.67247
256	0.281538	0.563076	0.718462
257	0.552147	0.895706	0.447853
258	0.768922	0.462155	0.231078
259	0.717996	0.564007	0.282004
260	0.980015	0.0399698	0.0199849
261	0.966548	0.0669042	0.0334521
262	0.964832	0.0703351	0.0351676
263	0.938983	0.122033	0.0610167
264	0.909648	0.180704	0.0903519
265	0.845539	0.308923	0.154461
266	0.746785	0.506429	0.253215
267	0.610781	0.778438	0.389219
268	0.47412	0.94824	0.52588
269	0.894879	0.210242	0.105121

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	51	0.196154	NOK
10% type I error level	82	0.315385	NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 51 & 0.196154 & NOK \tabularnewline
10% type I error level & 82 & 0.315385 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265719&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]51[/C][C]0.196154[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]82[/C][C]0.315385[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265719&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265719&T=6

As an alternative you can also use a QR Code:

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	51	0.196154	NOK
10% type I error level	82	0.315385	NOK

Figure 1

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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

R code (references can be found in the software module):

library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code