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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationThu, 11 Dec 2014 19:04:11 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/11/t1418324710q2jfsiwtf5ur02u.htm/, Retrieved Thu, 16 May 2024 19:20:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266292, Retrieved Thu, 16 May 2024 19:20:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact52

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-11 19:04:11] [6398a3f6f1f2f5e55f0ec79c736f94f8] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0 1.00 0.50 0.67 0.67 0.00 0.50
1 0.89 0.50 0.83 0.33 0.50 1.00
0 0.89 0.40 1.00 0.67 0.00 1.00
1 0.89 0.50 0.83 0.00 0.00 0.00
1 0.89 0.70 0.67 0.00 1.00 1.00
1 0.78 0.30 0.00 0.00 0.50 0.50
0 0.89 0.40 0.83 0.67 0.50 0.00
1 1.00 0.40 0.50 0.67 1.00 1.00
1 0.89 0.70 0.83 0.00 0.50 0.00
1 0.78 0.60 0.33 0.67 0.50 0.50
1 1.00 0.60 0.50 1.00 0.00 0.50
1 0.78 0.20 0.67 0.00 0.50 0.50
1 0.89 0.40 1.00 0.00 0.50 0.50
0 0.89 0.40 0.50 0.67 0.00 1.00
0 0.89 0.50 0.67 0.33 0.00 0.00
0 0.89 0.30 0.17 0.67 0.00 0.50
1 0.89 0.40 0.83 0.33 0.50 0.50
0 0.67 0.70 0.67 0.33 0.50 1.00
1 1.00 0.50 0.67 0.33 0.00 1.00
0 0.78 0.20 0.67 0.00 0.00 1.00
1 0.78 0.30 0.50 0.67 0.00 0.50
1 0.89 0.60 1.00 0.33 0.00 1.00
0 0.78 0.60 0.83 0.33 0.00 1.00
1 0.89 0.20 0.83 0.33 0.00 1.00
1 0.89 0.70 1.00 0.67 1.00 0.00
1 0.33 0.20 0.67 0.00 0.00 0.00
1 1.00 1.00 1.00 0.33 1.00 1.00
0 0.89 0.40 0.83 0.67 0.00 0.50
1 0.89 0.40 1.00 1.00 0.00 1.00
0 0.67 0.20 0.83 0.67 0.00 0.50
0 0.56 0.40 0.67 0.33 0.00 1.00
0 0.89 0.40 0.67 0.00 0.50 1.00
1 0.89 0.70 1.00 0.67 0.50 0.50
1 1.00 0.20 0.67 0.67 0.00 0.50
1 0.78 0.60 1.00 1.00 0.00 0.50
1 0.78 0.30 1.00 1.00 0.50 0.50
0 0.33 0.30 0.50 0.33 0.00 0.00
1 0.78 0.20 0.67 0.00 0.50 0.00
1 0.89 0.50 0.83 0.67 0.50 0.50
0 0.89 0.70 1.00 0.67 0.50 1.00
1 0.78 0.60 1.00 0.67 0.50 0.50
1 0.89 0.40 1.00 0.67 0.50 1.00
1 0.89 0.60 1.00 0.33 0.50 1.00
1 1.00 0.40 1.00 1.00 0.00 1.00
1 0.67 0.30 0.83 0.67 0.00 1.00
0 1.00 0.50 0.83 0.67 0.50 0.50
1 0.89 0.20 0.50 0.00 0.00 1.00
1 0.89 0.30 0.83 0.00 0.50 1.00
0 0.89 0.50 0.17 0.00 0.00 1.00
1 0.78 0.70 0.83 1.00 0.50 1.00
1 0.89 0.40 1.00 0.67 1.00 0.50
1 0.78 0.30 1.00 0.00 0.00 0.50
1 0.78 0.20 0.67 0.67 1.00 1.00
1 1.00 0.50 1.00 0.00 0.00 0.50
1 0.78 0.40 1.00 0.00 0.50 0.00
1 1.00 0.60 1.00 0.67 1.00 1.00
0 0.78 0.40 0.83 1.00 0.00 1.00
1 0.67 0.40 0.33 0.00 0.00 0.50
0 0.33 0.20 0.33 0.33 0.00 0.00
1 1.00 0.90 1.00 0.67 0.50 1.00
1 1.00 0.80 1.00 0.67 1.00 0.50
0 0.78 0.80 0.83 0.00 0.50 1.00
0 0.67 0.30 1.00 1.00 0.50 1.00
1 1.00 0.20 0.83 0.67 0.00 0.50
0 0.89 0.40 0.67 0.00 0.50 1.00
1 0.89 0.20 0.83 1.00 0.00 1.00
0 0.78 0.20 0.67 0.67 0.50 1.00
1 1.00 0.10 0.83 0.67 0.00 1.00
1 0.56 0.40 0.67 1.00 0.50 0.00
0 0.67 0.50 1.00 0.00 0.50 0.50
0 0.89 0.80 0.83 0.33 0.50 1.00
0 0.89 0.40 0.67 0.67 0.00 0.50
0 0.89 0.60 0.83 0.33 0.50 0.50
1 0.89 0.50 0.83 0.67 0.50 1.00
0 0.78 0.30 0.67 0.00 0.00 0.00
1 0.89 0.80 1.00 1.00 0.50 1.00
0 1.00 0.40 0.33 0.00 0.50 0.00
1 1.00 0.60 0.83 0.67 0.50 0.50
0 0.89 0.40 1.00 0.33 0.00 0.50
0 0.44 0.30 0.83 0.00 0.00 0.00
1 0.78 0.80 0.83 0.00 1.00 1.00
0 0.89 0.60 0.50 0.33 1.00 1.00
0 0.67 0.30 0.50 0.00 0.00 0.00
0 0.78 0.50 0.83 0.67 0.50 1.00
1 0.78 0.40 1.00 0.33 0.00 1.00
0 0.33 0.30 0.33 0.67 0.00 0.00
1 0.89 0.70 1.00 0.33 0.00 0.50
1 0.89 0.20 0.67 0.33 0.50 0.50
0 0.89 0.40 0.83 1.00 0.00 1.00
0 0.89 0.60 1.00 0.67 0.50 0.50
0 0.56 0.60 0.83 0.00 0.00 1.00
1 0.67 0.60 0.83 0.67 0.50 0.50
1 0.67 0.40 1.00 0.33 0.50 1.00
1 0.78 0.60 0.83 0.00 0.00 1.00
0 0.78 0.50 1.00 0.33 0.50 1.00
1 0.78 0.50 0.83 0.00 0.00 1.00
0 0.89 0.60 0.67 0.00 0.00 1.00
1 1.00 0.80 0.83 0.33 0.50 1.00
1 0.89 0.50 0.83 0.67 1.00 0.50
1 0.89 0.60 0.83 0.67 0.50 1.00
1 0.78 0.40 0.83 0.67 0.50 1.00
1 1.00 0.30 0.67 0.67 0.50 1.00
0 0.78 0.30 0.83 1.00 0.00 0.50
1 0.67 0.20 0.00 0.00 0.00 0.00
1 0.78 0.40 0.83 0.00 0.00 0.50
1 0.89 0.50 1.00 0.00 0.00 0.50
0 0.67 0.30 0.17 0.00 0.50 0.00
0 0.22 0.40 0.17 0.00 0.50 0.00
0 0.44 0.50 0.50 1.00 0.00 0.00
0 0.89 0.30 0.50 0.67 0.00 1.00
0 0.67 0.50 1.00 0.00 0.00 0.50
0 0.89 0.40 0.67 0.67 0.00 0.50
1 0.67 0.40 0.83 0.67 0.00 1.00
1 0.78 0.60 1.00 0.00 1.00 1.00
1 0.78 0.30 1.00 0.67 1.00 1.00
1 0.78 0.40 1.00 0.33 1.00 0.50
1 1.00 0.30 1.00 1.00 1.00 1.00
0 0.78 1.00 1.00 1.00 1.00 1.00
1 0.67 0.40 1.00 0.00 0.00 0.50
1 0.89 0.80 0.83 1.00 0.50 1.00
0 0.89 0.30 1.00 0.67 1.00 1.00
1 1.00 0.50 0.83 0.67 0.00 1.00
0 0.78 0.40 1.00 0.00 0.00 0.50
0 0.67 0.30 0.83 0.67 0.00 1.00
1 0.89 0.50 0.83 1.00 0.00 1.00
1 0.67 0.30 1.00 0.67 0.00 1.00
1 0.67 0.30 0.67 0.00 0.00 1.00
1 1.00 0.40 0.83 0.00 0.00 1.00
1 0.67 0.30 1.00 0.00 0.00 0.50
1 1.00 0.60 1.00 0.33 0.50 0.50
1 0.89 0.60 0.83 0.67 1.00 1.00
1 0.89 0.40 1.00 1.00 1.00 1.00
0 1.00 0.40 1.00 0.00 0.00 0.00
1 0.67 0.40 1.00 0.67 0.00 0.50
1 0.44 0.30 0.67 0.67 0.50 1.00
1 0.89 0.20 1.00 0.33 1.00 0.00
1 0.56 0.50 0.83 0.67 0.00 1.00
1 0.78 0.40 1.00 0.67 1.00 1.00
1 1.00 0.40 1.00 0.67 0.00 0.00
0 1.00 0.40 0.83 0.67 0.00 1.00
1 0.89 0.30 0.67 0.67 0.50 0.50
1 0.67 0.40 0.83 0.67 1.00 0.50
1 0.89 0.20 1.00 0.33 0.50 1.00
1 0.33 0.00 0.00 0.00 0.00 0.00
1 0.89 0.40 1.00 0.67 0.50 1.00
0 0.78 0.60 1.00 0.00 1.00 1.00
0 1.00 0.40 0.67 0.67 0.00 0.50
1 0.44 0.40 1.00 0.00 0.00 0.50
0 0.67 0.40 0.83 0.00 0.50 0.00
0 0.33 0.20 0.17 0.00 0.50 0.00
1 0.89 0.40 0.83 1.00 1.00 1.00
0 0.89 0.30 0.83 0.00 0.00 0.50
1 1.00 0.60 0.83 0.67 1.00 0.00
1 0.89 0.60 0.83 1.00 0.00 1.00
0 0.89 0.40 0.83 0.00 0.00 1.00
1 1.00 0.50 1.00 0.67 1.00 0.50
1 0.89 0.40 0.83 0.00 0.50 1.00
1 1.00 0.60 1.00 1.00 1.00 1.00
0 0.78 0.60 0.83 0.67 0.50 1.00
0 0.78 0.90 1.00 0.67 0.50 1.00
0 0.67 0.40 0.83 0.67 0.50 0.00
0 0.89 0.80 1.00 1.00 0.50 1.00
1 0.67 0.50 0.83 1.00 0.00 1.00
0 0.78 0.40 0.83 1.00 0.00 0.00
1 0.89 0.40 1.00 0.67 1.00 0.50
0 0.89 0.70 1.00 1.00 1.00 0.50
1 0.78 0.40 1.00 0.33 1.00 1.00
0 1.00 0.80 1.00 0.67 0.50 1.00
1 1.00 0.40 1.00 1.00 1.00 0.50
0 1.00 0.30 1.00 0.67 0.00 0.50
0 0.67 0.50 1.00 0.67 0.50 1.00
1 0.89 0.80 1.00 0.67 1.00 1.00
0 1.00 0.40 0.83 0.33 0.00 0.50
1 1.00 1.00 1.00 1.00 0.50 0.00
1 0.89 0.50 1.00 0.67 1.00 1.00
1 0.89 0.50 1.00 0.67 1.00 1.00
1 0.89 0.30 1.00 0.33 0.00 1.00
1 0.89 0.30 0.83 0.33 0.50 1.00
0 0.89 0.30 0.50 0.00 0.00 1.00
1 1.00 0.40 0.67 0.33 0.50 0.50
0 0.67 0.50 1.00 0.33 0.00 1.00
0 1.00 0.50 0.67 0.67 0.50 1.00
0 0.89 0.40 1.00 0.00 0.00 0.00
1 0.89 0.70 1.00 1.00 0.50 0.00
0 0.89 0.50 0.50 0.33 0.00 0.50
1 0.89 0.40 0.67 0.33 1.00 0.00
0 1.00 0.70 0.67 1.00 0.00 1.00
0 1.00 0.70 0.67 1.00 0.00 1.00
0 1.00 0.70 0.67 1.00 0.00 1.00
0 0.89 0.70 0.67 1.00 0.00 1.00
1 0.89 0.70 0.67 0.00 0.00 0.00
1 0.89 0.70 1.00 0.67 0.50 1.00
1 0.33 0.10 0.67 0.33 0.50 0.00
1 0.67 0.20 0.67 0.67 0.50 1.00
0 0.56 0.30 0.33 0.33 0.00 1.00
0 0.44 0.60 0.83 0.33 0.00 0.50
1 1.00 0.80 1.00 1.00 1.00 1.00
0 0.89 0.80 1.00 0.33 0.50 0.50
0 0.33 0.00 0.17 0.00 0.00 0.00
0 0.67 0.30 0.67 0.33 0.00 1.00
0 0.67 0.60 0.83 0.33 0.50 1.00
1 1.00 0.50 0.83 0.67 0.00 1.00
1 0.78 0.70 1.00 0.33 0.00 0.50
0 0.67 0.30 0.83 0.00 0.50 1.00
0 1.00 0.30 1.00 0.67 0.00 0.00
1 0.78 0.40 1.00 0.67 0.00 0.50
0 0.89 0.40 0.83 1.00 0.00 1.00
1 0.89 0.10 0.83 0.00 0.00 1.00
1 0.89 0.50 1.00 0.67 0.00 1.00
0 0.00 0.00 0.00 0.00 0.00 0.00
1 0.67 0.40 1.00 0.33 0.50 0.00
1 1.00 0.60 0.83 0.67 1.00 0.50
1 1.00 0.40 1.00 0.33 0.50 1.00
0 0.67 0.10 0.33 0.00 0.50 1.00
0 0.89 0.30 0.83 0.00 0.00 1.00
0 0.89 0.70 0.83 0.67 0.00 1.00
1 0.56 0.30 0.17 0.00 0.00 1.00
1 0.67 0.50 0.83 0.33 0.50 0.00
1 1.00 0.30 0.83 0.67 1.00 1.00
1 1.00 0.60 0.67 0.67 0.50 1.00
0 1.00 0.90 1.00 1.00 0.00 1.00
0 0.67 0.40 0.83 0.00 0.50 1.00
0 0.44 0.30 1.00 0.00 0.50 0.50
1 0.89 0.90 1.00 0.67 1.00 1.00
1 0.44 0.50 1.00 0.00 0.50 0.00
0 0.56 0.30 1.00 1.00 0.50 0.50
0 0.89 0.60 0.83 0.67 0.00 0.50
0 0.67 0.20 1.00 0.33 0.00 0.50
1 0.89 0.40 0.83 1.00 0.50 1.00
1 1.00 0.50 0.83 0.67 0.50 0.50
0 0.78 0.40 0.83 0.67 0.00 0.50
0 0.44 0.00 0.00 0.00 0.00 0.00
0 0.89 0.20 1.00 0.33 0.50 1.00
1 0.89 0.50 1.00 0.67 0.50 1.00
1 0.89 0.30 1.00 0.67 0.00 0.50
1 0.44 0.00 0.00 0.00 0.00 0.00
1 1.00 0.50 0.83 1.00 0.00 1.00
0 0.89 0.60 0.83 0.33 0.00 1.00
1 0.67 0.30 0.83 0.00 0.50 0.50
1 0.33 0.00 0.00 0.00 0.00 0.00
1 0.78 0.30 0.67 0.00 0.50 0.00
0 0.89 0.50 1.00 0.67 0.50 1.00
0 0.78 0.40 0.67 0.00 0.00 1.00
1 0.78 0.50 0.83 0.67 0.00 0.50
0 0.89 0.70 1.00 1.00 1.00 0.50
1 0.78 0.80 1.00 0.67 0.50 1.00
1 0.78 0.60 1.00 0.33 0.50 1.00
0 0.67 0.40 0.83 0.33 0.00 0.50
1 0.89 0.50 0.83 0.33 0.50 0.00
0 0.89 0.50 1.00 0.00 0.50 1.00
1 0.78 0.30 1.00 0.33 0.00 1.00
1 1.00 0.60 1.00 0.00 0.50 1.00
0 1.00 0.30 0.67 0.67 0.00 0.50
1 0.78 0.60 0.83 1.00 0.50 0.50
0 0.78 0.30 0.33 0.33 0.00 1.00
1 0.89 0.70 1.00 0.67 1.00 1.00
0 0.89 0.70 1.00 1.00 0.00 1.00
1 0.67 0.60 0.67 1.00 0.50 1.00
0 1.00 0.50 1.00 0.33 0.50 0.00
0 0.67 0.50 0.83 0.33 0.00 0.50
1 0.56 0.40 0.67 0.00 0.00 1.00
1 0.78 0.40 1.00 0.33 1.00 1.00
0 1.00 0.70 1.00 1.00 0.00 1.00
1 0.67 0.20 0.17 0.00 0.50 0.00
1 0.78 0.50 0.83 0.67 0.00 0.50
0 0.56 0.40 0.83 0.67 0.50 0.00
1 1.00 0.20 1.00 0.67 1.00 1.00
0 0.89 0.50 0.67 0.67 0.00 0.00
0 0.44 0.40 0.50 0.00 0.00 1.00
1 1.00 0.70 0.67 1.00 1.00 1.00
1 0.89 0.60 0.83 0.67 1.00 0.00
0 0.78 0.40 0.83 0.00 0.00 0.00
1 0.89 0.50 1.00 0.67 1.00 1.00
0 0.11 0.00 0.17 0.00 0.00 0.00
0 0.89 0.70 1.00 0.67 0.50 1.00
1 0.89 0.40 0.67 0.67 0.00 1.00
0 1.00 0.50 0.67 1.00 0.00 1.00
0 0.89 0.60 0.83 0.67 0.00 0.50
1 1.00 0.80 0.50 0.67 0.50 0.50

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266292&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266292&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266292&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
gender[t] = + 0.173674 + 0.34219Calculation[t] -0.399582Algebraic_Reasoning[t] + 0.214826Graphical_Interpretation[t] -0.00235574Proportionality_and_Ratio[t] + 0.3967Probability_and_Sampling[t] -0.00757385Estimation[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
gender[t] =  +  0.173674 +  0.34219Calculation[t] -0.399582Algebraic_Reasoning[t] +  0.214826Graphical_Interpretation[t] -0.00235574Proportionality_and_Ratio[t] +  0.3967Probability_and_Sampling[t] -0.00757385Estimation[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266292&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]gender[t] =  +  0.173674 +  0.34219Calculation[t] -0.399582Algebraic_Reasoning[t] +  0.214826Graphical_Interpretation[t] -0.00235574Proportionality_and_Ratio[t] +  0.3967Probability_and_Sampling[t] -0.00757385Estimation[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266292&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266292&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Estimated Regression Equation
gender[t] = + 0.173674 + 0.34219Calculation[t] -0.399582Algebraic_Reasoning[t] + 0.214826Graphical_Interpretation[t] -0.00235574Proportionality_and_Ratio[t] + 0.3967Probability_and_Sampling[t] -0.00757385Estimation[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)0.1736740.1369811.2680.2059270.102964
Calculation0.342190.1899131.8020.07268090.0363404
Algebraic_Reasoning-0.3995820.173609-2.3020.02211240.0110562
Graphical_Interpretation0.2148260.1398261.5360.1256070.0628035
Proportionality_and_Ratio-0.002355740.0882476-0.026690.9787230.489361
Probability_and_Sampling0.39670.08094594.9011.64199e-068.20993e-07
Estimation-0.007573850.0785772-0.096390.9232840.461642

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 0.173674 & 0.136981 & 1.268 & 0.205927 & 0.102964 \tabularnewline
Calculation & 0.34219 & 0.189913 & 1.802 & 0.0726809 & 0.0363404 \tabularnewline
Algebraic_Reasoning & -0.399582 & 0.173609 & -2.302 & 0.0221124 & 0.0110562 \tabularnewline
Graphical_Interpretation & 0.214826 & 0.139826 & 1.536 & 0.125607 & 0.0628035 \tabularnewline
Proportionality_and_Ratio & -0.00235574 & 0.0882476 & -0.02669 & 0.978723 & 0.489361 \tabularnewline
Probability_and_Sampling & 0.3967 & 0.0809459 & 4.901 & 1.64199e-06 & 8.20993e-07 \tabularnewline
Estimation & -0.00757385 & 0.0785772 & -0.09639 & 0.923284 & 0.461642 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266292&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]0.173674[/C][C]0.136981[/C][C]1.268[/C][C]0.205927[/C][C]0.102964[/C][/ROW]
[ROW][C]Calculation[/C][C]0.34219[/C][C]0.189913[/C][C]1.802[/C][C]0.0726809[/C][C]0.0363404[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]-0.399582[/C][C]0.173609[/C][C]-2.302[/C][C]0.0221124[/C][C]0.0110562[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]0.214826[/C][C]0.139826[/C][C]1.536[/C][C]0.125607[/C][C]0.0628035[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]-0.00235574[/C][C]0.0882476[/C][C]-0.02669[/C][C]0.978723[/C][C]0.489361[/C][/ROW]
[ROW][C]Probability_and_Sampling[/C][C]0.3967[/C][C]0.0809459[/C][C]4.901[/C][C]1.64199e-06[/C][C]8.20993e-07[/C][/ROW]
[ROW][C]Estimation[/C][C]-0.00757385[/C][C]0.0785772[/C][C]-0.09639[/C][C]0.923284[/C][C]0.461642[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266292&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266292&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)0.1736740.1369811.2680.2059270.102964
Calculation0.342190.1899131.8020.07268090.0363404
Algebraic_Reasoning-0.3995820.173609-2.3020.02211240.0110562
Graphical_Interpretation0.2148260.1398261.5360.1256070.0628035
Proportionality_and_Ratio-0.002355740.0882476-0.026690.9787230.489361
Probability_and_Sampling0.39670.08094594.9011.64199e-068.20993e-07
Estimation-0.007573850.0785772-0.096390.9232840.461642






Multiple Linear Regression - Regression Statistics
Multiple R0.351986
R-squared0.123894
Adjusted R-squared0.104568
F-TEST (value)6.41079
F-TEST (DF numerator)6
F-TEST (DF denominator)272
p-value2.4781e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.469333
Sum Squared Residuals59.9143

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.351986 \tabularnewline
R-squared & 0.123894 \tabularnewline
Adjusted R-squared & 0.104568 \tabularnewline
F-TEST (value) & 6.41079 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 272 \tabularnewline
p-value & 2.4781e-06 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.469333 \tabularnewline
Sum Squared Residuals & 59.9143 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266292&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.351986[/C][/ROW]
[ROW][C]R-squared[/C][C]0.123894[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.104568[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]6.41079[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]272[/C][/ROW]
[ROW][C]p-value[/C][C]2.4781e-06[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.469333[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]59.9143[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266292&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266292&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Regression Statistics
Multiple R0.351986
R-squared0.123894
Adjusted R-squared0.104568
F-TEST (value)6.41079
F-TEST (DF numerator)6
F-TEST (DF denominator)272
p-value2.4781e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.469333
Sum Squared Residuals59.9143






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
100.454641-0.454641
210.6467370.353263
300.524064-0.524064
410.4567380.543262
510.7315760.268424
610.5152710.484729
700.693468-0.693468
810.8509920.149008
910.5751710.424829
1010.464710.53529
1110.3773850.622615
1210.6991630.300837
1310.727780.27222
1400.416651-0.416651
1500.421588-0.421588
1600.389504-0.389504
1710.6904820.309518
1800.457166-0.457166
1910.4516550.548345
2000.497026-0.497026
2110.4227550.577245
2210.4449490.555051
2300.370787-0.370787
2410.5682610.431739
2510.8084640.191536
2610.3506140.649386
2710.7194570.280543
2800.491331-0.491331
2910.5232870.476713
3000.495965-0.495965
3100.34105-0.34105
3200.6531-0.6531
3310.6063270.393673
3410.5745160.425484
3510.4095170.590483
3610.7277410.272259
3700.273358-0.273358
3810.702950.29705
3910.6497230.350277
4000.60254-0.60254
4110.6086440.391356
4210.7224140.277586
4310.6432990.356701
4410.5609280.439072
4510.452220.54778
4600.687364-0.687364
4710.4981460.501854
4810.7274310.272569
4900.307379-0.307379
5010.5276010.472399
5110.9245510.0754485
5210.5317470.468253
5310.8921470.107853
5410.5271120.472888
5510.6939260.306074
5610.8784890.121511
5700.449126-0.449126
5810.3102140.689786
5900.276796-0.276796
6010.5602640.439736
6110.8023590.197641
6200.489999-0.489999
6300.686314-0.686314
6410.6088880.391112
6500.6531-0.6531
6610.5666830.433317
6700.693797-0.693797
6810.6450590.354941
6910.5453960.454604
7000.61254-0.61254
7100.526862-0.526862
7200.456959-0.456959
7300.610565-0.610565
7410.6459360.354064
7500.464641-0.464641
7610.5618040.438196
7700.625274-0.625274
7810.6474050.352595
7900.528652-0.528652
8000.382669-0.382669
8110.6883490.311651
8200.734236-0.734236
8300.39048-0.39048
8400.608295-0.608295
8510.4872240.512776
8600.236036-0.236036
8710.4087780.591222
8810.7360260.263974
8900.486766-0.486766
9000.646285-0.646285
9100.296283-0.296283
9210.5344830.465517
9310.6479340.352066
9410.3715650.628435
9500.645616-0.645616
9610.4115230.588477
9700.374834-0.374834
9810.5645030.435497
9910.8480730.151927
10010.6059780.394022
10110.6482530.351747
10210.7291210.270879
10300.492871-0.492871
10410.3230250.676975
10510.4552680.544732
10610.4894710.510529
10700.517937-0.517937
10800.323994-0.323994
10900.229504-0.229504
11000.456609-0.456609
11100.41419-0.41419
11200.456959-0.456959
11310.4122620.587738
11410.8047860.195214
11510.9230820.0769181
11610.8877120.112288
11710.9975860.00241372
11800.642597-0.642597
11910.4541480.545852
12010.5252840.474716
12100.960723-0.960723
12210.4852270.514773
12300.491789-0.491789
12400.45222-0.45222
12510.4468080.553192
12610.4887410.511259
12710.4194260.580574
12810.5267630.473237
12910.4941060.505894
13010.6847270.315273
13110.8043280.195672
13210.9199870.0800128
13300.570857-0.570857
13410.452570.54743
13510.5374950.462505
13611.00906-0.00905582
13710.3346630.665337
13810.8831240.116876
13910.5692790.430721
14000.525185-0.525185
14110.6952670.304733
14210.8127490.187251
14310.8031320.196868
14410.2865970.713403
14510.7224140.277586
14600.804786-0.804786
14700.494599-0.494599
14810.3754440.624556
14900.619764-0.619764
15000.441551-0.441551
15110.8834670.116533
15200.532867-0.532867
15310.8495420.150458
15410.406850.59315
15500.489122-0.489122
15610.9222340.0777659
15710.6874720.312528
15810.8777120.122288
15900.568337-0.568337
16000.484982-0.484982
16100.618186-0.618186
16200.561804-0.561804
16310.3715260.628474
16400.456699-0.456699
16510.9245510.0754485
16600.803899-0.803899
16710.8839250.116075
16800.600222-0.600222
16910.9614150.038585
17000.60545-0.60545
17100.607174-0.607174
17210.7609320.239068
17300.529773-0.529773
17410.5271020.472898
17510.8808060.119194
17610.8808060.119194
17710.5648240.435176
17810.7266530.273347
17900.458188-0.458188
18010.6937510.306249
18100.409625-0.409625
18200.649204-0.649204
18300.533217-0.533217
18410.6093360.390664
18500.381281-0.381281
18610.8582470.141753
18700.37016-0.37016
18800.37016-0.37016
18900.37016-0.37016
19000.33252-0.33252
19110.3424490.657551
19210.602540.39746
19310.5881450.411855
19410.6561560.343844
19500.307967-0.307967
19600.25823-0.25823
19710.7977950.202205
19800.567169-0.567169
19900.323117-0.323117
20000.418649-0.418649
20100.531497-0.531497
20210.4852270.514773
20310.3711370.628863
20400.652149-0.652149
20500.609237-0.609237
20610.490210.50979
20700.486766-0.486766
20810.6089970.391003
20910.4841060.515894
21000.173674-0.173674
21110.6555070.344493
21210.8457550.154245
21310.7608560.239144
21400.624652-0.624652
21500.52908-0.52908
21600.367669-0.367669
21710.2743720.725628
21810.5790290.420971
21910.9618430.0381568
22010.6092460.390754
22100.361137-0.361137
22200.612191-0.612191
22300.613753-0.613753
22410.7209730.279027
22510.5376230.462377
22600.65246-0.65246
22700.411414-0.411414
22800.533287-0.533287
22910.6851170.314883
23010.6873640.312636
23100.45369-0.45369
23200.324238-0.324238
23300.803132-0.803132
23410.6824560.317544
23510.567810.43219
23610.3242380.675762
23710.4844490.515551
23800.408428-0.408428
23910.6559360.344064
24010.2865970.713403
24110.6629910.337009
24200.682456-0.682456
24300.417109-0.417109
24410.4137320.586268
24500.803899-0.803899
24610.5249410.475059
24710.6056580.394342
24800.41685-0.41685
24910.6543110.345689
25000.684035-0.684035
25110.5271830.472817
25210.6817170.318283
25300.534558-0.534558
25410.5713460.428654
25500.383249-0.383249
25610.800890.19911
25700.403412-0.403412
25810.4955460.504454
25900.728472-0.728472
26000.376892-0.376892
26110.3418270.658173
26210.8839250.116075
26300.441053-0.441053
26410.5578950.442105
26510.4137320.586268
26600.580545-0.580545
26711.03832-0.0383219
26800.420787-0.420787
26900.264244-0.264244
27010.7668610.233139
27110.8119010.188099
27200.459055-0.459055
27310.8808060.119194
27400.247836-0.247836
27500.60254-0.60254
27610.4531720.546828
27700.450077-0.450077
27800.411414-0.411414
27910.4965960.503404

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 0 & 0.454641 & -0.454641 \tabularnewline
2 & 1 & 0.646737 & 0.353263 \tabularnewline
3 & 0 & 0.524064 & -0.524064 \tabularnewline
4 & 1 & 0.456738 & 0.543262 \tabularnewline
5 & 1 & 0.731576 & 0.268424 \tabularnewline
6 & 1 & 0.515271 & 0.484729 \tabularnewline
7 & 0 & 0.693468 & -0.693468 \tabularnewline
8 & 1 & 0.850992 & 0.149008 \tabularnewline
9 & 1 & 0.575171 & 0.424829 \tabularnewline
10 & 1 & 0.46471 & 0.53529 \tabularnewline
11 & 1 & 0.377385 & 0.622615 \tabularnewline
12 & 1 & 0.699163 & 0.300837 \tabularnewline
13 & 1 & 0.72778 & 0.27222 \tabularnewline
14 & 0 & 0.416651 & -0.416651 \tabularnewline
15 & 0 & 0.421588 & -0.421588 \tabularnewline
16 & 0 & 0.389504 & -0.389504 \tabularnewline
17 & 1 & 0.690482 & 0.309518 \tabularnewline
18 & 0 & 0.457166 & -0.457166 \tabularnewline
19 & 1 & 0.451655 & 0.548345 \tabularnewline
20 & 0 & 0.497026 & -0.497026 \tabularnewline
21 & 1 & 0.422755 & 0.577245 \tabularnewline
22 & 1 & 0.444949 & 0.555051 \tabularnewline
23 & 0 & 0.370787 & -0.370787 \tabularnewline
24 & 1 & 0.568261 & 0.431739 \tabularnewline
25 & 1 & 0.808464 & 0.191536 \tabularnewline
26 & 1 & 0.350614 & 0.649386 \tabularnewline
27 & 1 & 0.719457 & 0.280543 \tabularnewline
28 & 0 & 0.491331 & -0.491331 \tabularnewline
29 & 1 & 0.523287 & 0.476713 \tabularnewline
30 & 0 & 0.495965 & -0.495965 \tabularnewline
31 & 0 & 0.34105 & -0.34105 \tabularnewline
32 & 0 & 0.6531 & -0.6531 \tabularnewline
33 & 1 & 0.606327 & 0.393673 \tabularnewline
34 & 1 & 0.574516 & 0.425484 \tabularnewline
35 & 1 & 0.409517 & 0.590483 \tabularnewline
36 & 1 & 0.727741 & 0.272259 \tabularnewline
37 & 0 & 0.273358 & -0.273358 \tabularnewline
38 & 1 & 0.70295 & 0.29705 \tabularnewline
39 & 1 & 0.649723 & 0.350277 \tabularnewline
40 & 0 & 0.60254 & -0.60254 \tabularnewline
41 & 1 & 0.608644 & 0.391356 \tabularnewline
42 & 1 & 0.722414 & 0.277586 \tabularnewline
43 & 1 & 0.643299 & 0.356701 \tabularnewline
44 & 1 & 0.560928 & 0.439072 \tabularnewline
45 & 1 & 0.45222 & 0.54778 \tabularnewline
46 & 0 & 0.687364 & -0.687364 \tabularnewline
47 & 1 & 0.498146 & 0.501854 \tabularnewline
48 & 1 & 0.727431 & 0.272569 \tabularnewline
49 & 0 & 0.307379 & -0.307379 \tabularnewline
50 & 1 & 0.527601 & 0.472399 \tabularnewline
51 & 1 & 0.924551 & 0.0754485 \tabularnewline
52 & 1 & 0.531747 & 0.468253 \tabularnewline
53 & 1 & 0.892147 & 0.107853 \tabularnewline
54 & 1 & 0.527112 & 0.472888 \tabularnewline
55 & 1 & 0.693926 & 0.306074 \tabularnewline
56 & 1 & 0.878489 & 0.121511 \tabularnewline
57 & 0 & 0.449126 & -0.449126 \tabularnewline
58 & 1 & 0.310214 & 0.689786 \tabularnewline
59 & 0 & 0.276796 & -0.276796 \tabularnewline
60 & 1 & 0.560264 & 0.439736 \tabularnewline
61 & 1 & 0.802359 & 0.197641 \tabularnewline
62 & 0 & 0.489999 & -0.489999 \tabularnewline
63 & 0 & 0.686314 & -0.686314 \tabularnewline
64 & 1 & 0.608888 & 0.391112 \tabularnewline
65 & 0 & 0.6531 & -0.6531 \tabularnewline
66 & 1 & 0.566683 & 0.433317 \tabularnewline
67 & 0 & 0.693797 & -0.693797 \tabularnewline
68 & 1 & 0.645059 & 0.354941 \tabularnewline
69 & 1 & 0.545396 & 0.454604 \tabularnewline
70 & 0 & 0.61254 & -0.61254 \tabularnewline
71 & 0 & 0.526862 & -0.526862 \tabularnewline
72 & 0 & 0.456959 & -0.456959 \tabularnewline
73 & 0 & 0.610565 & -0.610565 \tabularnewline
74 & 1 & 0.645936 & 0.354064 \tabularnewline
75 & 0 & 0.464641 & -0.464641 \tabularnewline
76 & 1 & 0.561804 & 0.438196 \tabularnewline
77 & 0 & 0.625274 & -0.625274 \tabularnewline
78 & 1 & 0.647405 & 0.352595 \tabularnewline
79 & 0 & 0.528652 & -0.528652 \tabularnewline
80 & 0 & 0.382669 & -0.382669 \tabularnewline
81 & 1 & 0.688349 & 0.311651 \tabularnewline
82 & 0 & 0.734236 & -0.734236 \tabularnewline
83 & 0 & 0.39048 & -0.39048 \tabularnewline
84 & 0 & 0.608295 & -0.608295 \tabularnewline
85 & 1 & 0.487224 & 0.512776 \tabularnewline
86 & 0 & 0.236036 & -0.236036 \tabularnewline
87 & 1 & 0.408778 & 0.591222 \tabularnewline
88 & 1 & 0.736026 & 0.263974 \tabularnewline
89 & 0 & 0.486766 & -0.486766 \tabularnewline
90 & 0 & 0.646285 & -0.646285 \tabularnewline
91 & 0 & 0.296283 & -0.296283 \tabularnewline
92 & 1 & 0.534483 & 0.465517 \tabularnewline
93 & 1 & 0.647934 & 0.352066 \tabularnewline
94 & 1 & 0.371565 & 0.628435 \tabularnewline
95 & 0 & 0.645616 & -0.645616 \tabularnewline
96 & 1 & 0.411523 & 0.588477 \tabularnewline
97 & 0 & 0.374834 & -0.374834 \tabularnewline
98 & 1 & 0.564503 & 0.435497 \tabularnewline
99 & 1 & 0.848073 & 0.151927 \tabularnewline
100 & 1 & 0.605978 & 0.394022 \tabularnewline
101 & 1 & 0.648253 & 0.351747 \tabularnewline
102 & 1 & 0.729121 & 0.270879 \tabularnewline
103 & 0 & 0.492871 & -0.492871 \tabularnewline
104 & 1 & 0.323025 & 0.676975 \tabularnewline
105 & 1 & 0.455268 & 0.544732 \tabularnewline
106 & 1 & 0.489471 & 0.510529 \tabularnewline
107 & 0 & 0.517937 & -0.517937 \tabularnewline
108 & 0 & 0.323994 & -0.323994 \tabularnewline
109 & 0 & 0.229504 & -0.229504 \tabularnewline
110 & 0 & 0.456609 & -0.456609 \tabularnewline
111 & 0 & 0.41419 & -0.41419 \tabularnewline
112 & 0 & 0.456959 & -0.456959 \tabularnewline
113 & 1 & 0.412262 & 0.587738 \tabularnewline
114 & 1 & 0.804786 & 0.195214 \tabularnewline
115 & 1 & 0.923082 & 0.0769181 \tabularnewline
116 & 1 & 0.887712 & 0.112288 \tabularnewline
117 & 1 & 0.997586 & 0.00241372 \tabularnewline
118 & 0 & 0.642597 & -0.642597 \tabularnewline
119 & 1 & 0.454148 & 0.545852 \tabularnewline
120 & 1 & 0.525284 & 0.474716 \tabularnewline
121 & 0 & 0.960723 & -0.960723 \tabularnewline
122 & 1 & 0.485227 & 0.514773 \tabularnewline
123 & 0 & 0.491789 & -0.491789 \tabularnewline
124 & 0 & 0.45222 & -0.45222 \tabularnewline
125 & 1 & 0.446808 & 0.553192 \tabularnewline
126 & 1 & 0.488741 & 0.511259 \tabularnewline
127 & 1 & 0.419426 & 0.580574 \tabularnewline
128 & 1 & 0.526763 & 0.473237 \tabularnewline
129 & 1 & 0.494106 & 0.505894 \tabularnewline
130 & 1 & 0.684727 & 0.315273 \tabularnewline
131 & 1 & 0.804328 & 0.195672 \tabularnewline
132 & 1 & 0.919987 & 0.0800128 \tabularnewline
133 & 0 & 0.570857 & -0.570857 \tabularnewline
134 & 1 & 0.45257 & 0.54743 \tabularnewline
135 & 1 & 0.537495 & 0.462505 \tabularnewline
136 & 1 & 1.00906 & -0.00905582 \tabularnewline
137 & 1 & 0.334663 & 0.665337 \tabularnewline
138 & 1 & 0.883124 & 0.116876 \tabularnewline
139 & 1 & 0.569279 & 0.430721 \tabularnewline
140 & 0 & 0.525185 & -0.525185 \tabularnewline
141 & 1 & 0.695267 & 0.304733 \tabularnewline
142 & 1 & 0.812749 & 0.187251 \tabularnewline
143 & 1 & 0.803132 & 0.196868 \tabularnewline
144 & 1 & 0.286597 & 0.713403 \tabularnewline
145 & 1 & 0.722414 & 0.277586 \tabularnewline
146 & 0 & 0.804786 & -0.804786 \tabularnewline
147 & 0 & 0.494599 & -0.494599 \tabularnewline
148 & 1 & 0.375444 & 0.624556 \tabularnewline
149 & 0 & 0.619764 & -0.619764 \tabularnewline
150 & 0 & 0.441551 & -0.441551 \tabularnewline
151 & 1 & 0.883467 & 0.116533 \tabularnewline
152 & 0 & 0.532867 & -0.532867 \tabularnewline
153 & 1 & 0.849542 & 0.150458 \tabularnewline
154 & 1 & 0.40685 & 0.59315 \tabularnewline
155 & 0 & 0.489122 & -0.489122 \tabularnewline
156 & 1 & 0.922234 & 0.0777659 \tabularnewline
157 & 1 & 0.687472 & 0.312528 \tabularnewline
158 & 1 & 0.877712 & 0.122288 \tabularnewline
159 & 0 & 0.568337 & -0.568337 \tabularnewline
160 & 0 & 0.484982 & -0.484982 \tabularnewline
161 & 0 & 0.618186 & -0.618186 \tabularnewline
162 & 0 & 0.561804 & -0.561804 \tabularnewline
163 & 1 & 0.371526 & 0.628474 \tabularnewline
164 & 0 & 0.456699 & -0.456699 \tabularnewline
165 & 1 & 0.924551 & 0.0754485 \tabularnewline
166 & 0 & 0.803899 & -0.803899 \tabularnewline
167 & 1 & 0.883925 & 0.116075 \tabularnewline
168 & 0 & 0.600222 & -0.600222 \tabularnewline
169 & 1 & 0.961415 & 0.038585 \tabularnewline
170 & 0 & 0.60545 & -0.60545 \tabularnewline
171 & 0 & 0.607174 & -0.607174 \tabularnewline
172 & 1 & 0.760932 & 0.239068 \tabularnewline
173 & 0 & 0.529773 & -0.529773 \tabularnewline
174 & 1 & 0.527102 & 0.472898 \tabularnewline
175 & 1 & 0.880806 & 0.119194 \tabularnewline
176 & 1 & 0.880806 & 0.119194 \tabularnewline
177 & 1 & 0.564824 & 0.435176 \tabularnewline
178 & 1 & 0.726653 & 0.273347 \tabularnewline
179 & 0 & 0.458188 & -0.458188 \tabularnewline
180 & 1 & 0.693751 & 0.306249 \tabularnewline
181 & 0 & 0.409625 & -0.409625 \tabularnewline
182 & 0 & 0.649204 & -0.649204 \tabularnewline
183 & 0 & 0.533217 & -0.533217 \tabularnewline
184 & 1 & 0.609336 & 0.390664 \tabularnewline
185 & 0 & 0.381281 & -0.381281 \tabularnewline
186 & 1 & 0.858247 & 0.141753 \tabularnewline
187 & 0 & 0.37016 & -0.37016 \tabularnewline
188 & 0 & 0.37016 & -0.37016 \tabularnewline
189 & 0 & 0.37016 & -0.37016 \tabularnewline
190 & 0 & 0.33252 & -0.33252 \tabularnewline
191 & 1 & 0.342449 & 0.657551 \tabularnewline
192 & 1 & 0.60254 & 0.39746 \tabularnewline
193 & 1 & 0.588145 & 0.411855 \tabularnewline
194 & 1 & 0.656156 & 0.343844 \tabularnewline
195 & 0 & 0.307967 & -0.307967 \tabularnewline
196 & 0 & 0.25823 & -0.25823 \tabularnewline
197 & 1 & 0.797795 & 0.202205 \tabularnewline
198 & 0 & 0.567169 & -0.567169 \tabularnewline
199 & 0 & 0.323117 & -0.323117 \tabularnewline
200 & 0 & 0.418649 & -0.418649 \tabularnewline
201 & 0 & 0.531497 & -0.531497 \tabularnewline
202 & 1 & 0.485227 & 0.514773 \tabularnewline
203 & 1 & 0.371137 & 0.628863 \tabularnewline
204 & 0 & 0.652149 & -0.652149 \tabularnewline
205 & 0 & 0.609237 & -0.609237 \tabularnewline
206 & 1 & 0.49021 & 0.50979 \tabularnewline
207 & 0 & 0.486766 & -0.486766 \tabularnewline
208 & 1 & 0.608997 & 0.391003 \tabularnewline
209 & 1 & 0.484106 & 0.515894 \tabularnewline
210 & 0 & 0.173674 & -0.173674 \tabularnewline
211 & 1 & 0.655507 & 0.344493 \tabularnewline
212 & 1 & 0.845755 & 0.154245 \tabularnewline
213 & 1 & 0.760856 & 0.239144 \tabularnewline
214 & 0 & 0.624652 & -0.624652 \tabularnewline
215 & 0 & 0.52908 & -0.52908 \tabularnewline
216 & 0 & 0.367669 & -0.367669 \tabularnewline
217 & 1 & 0.274372 & 0.725628 \tabularnewline
218 & 1 & 0.579029 & 0.420971 \tabularnewline
219 & 1 & 0.961843 & 0.0381568 \tabularnewline
220 & 1 & 0.609246 & 0.390754 \tabularnewline
221 & 0 & 0.361137 & -0.361137 \tabularnewline
222 & 0 & 0.612191 & -0.612191 \tabularnewline
223 & 0 & 0.613753 & -0.613753 \tabularnewline
224 & 1 & 0.720973 & 0.279027 \tabularnewline
225 & 1 & 0.537623 & 0.462377 \tabularnewline
226 & 0 & 0.65246 & -0.65246 \tabularnewline
227 & 0 & 0.411414 & -0.411414 \tabularnewline
228 & 0 & 0.533287 & -0.533287 \tabularnewline
229 & 1 & 0.685117 & 0.314883 \tabularnewline
230 & 1 & 0.687364 & 0.312636 \tabularnewline
231 & 0 & 0.45369 & -0.45369 \tabularnewline
232 & 0 & 0.324238 & -0.324238 \tabularnewline
233 & 0 & 0.803132 & -0.803132 \tabularnewline
234 & 1 & 0.682456 & 0.317544 \tabularnewline
235 & 1 & 0.56781 & 0.43219 \tabularnewline
236 & 1 & 0.324238 & 0.675762 \tabularnewline
237 & 1 & 0.484449 & 0.515551 \tabularnewline
238 & 0 & 0.408428 & -0.408428 \tabularnewline
239 & 1 & 0.655936 & 0.344064 \tabularnewline
240 & 1 & 0.286597 & 0.713403 \tabularnewline
241 & 1 & 0.662991 & 0.337009 \tabularnewline
242 & 0 & 0.682456 & -0.682456 \tabularnewline
243 & 0 & 0.417109 & -0.417109 \tabularnewline
244 & 1 & 0.413732 & 0.586268 \tabularnewline
245 & 0 & 0.803899 & -0.803899 \tabularnewline
246 & 1 & 0.524941 & 0.475059 \tabularnewline
247 & 1 & 0.605658 & 0.394342 \tabularnewline
248 & 0 & 0.41685 & -0.41685 \tabularnewline
249 & 1 & 0.654311 & 0.345689 \tabularnewline
250 & 0 & 0.684035 & -0.684035 \tabularnewline
251 & 1 & 0.527183 & 0.472817 \tabularnewline
252 & 1 & 0.681717 & 0.318283 \tabularnewline
253 & 0 & 0.534558 & -0.534558 \tabularnewline
254 & 1 & 0.571346 & 0.428654 \tabularnewline
255 & 0 & 0.383249 & -0.383249 \tabularnewline
256 & 1 & 0.80089 & 0.19911 \tabularnewline
257 & 0 & 0.403412 & -0.403412 \tabularnewline
258 & 1 & 0.495546 & 0.504454 \tabularnewline
259 & 0 & 0.728472 & -0.728472 \tabularnewline
260 & 0 & 0.376892 & -0.376892 \tabularnewline
261 & 1 & 0.341827 & 0.658173 \tabularnewline
262 & 1 & 0.883925 & 0.116075 \tabularnewline
263 & 0 & 0.441053 & -0.441053 \tabularnewline
264 & 1 & 0.557895 & 0.442105 \tabularnewline
265 & 1 & 0.413732 & 0.586268 \tabularnewline
266 & 0 & 0.580545 & -0.580545 \tabularnewline
267 & 1 & 1.03832 & -0.0383219 \tabularnewline
268 & 0 & 0.420787 & -0.420787 \tabularnewline
269 & 0 & 0.264244 & -0.264244 \tabularnewline
270 & 1 & 0.766861 & 0.233139 \tabularnewline
271 & 1 & 0.811901 & 0.188099 \tabularnewline
272 & 0 & 0.459055 & -0.459055 \tabularnewline
273 & 1 & 0.880806 & 0.119194 \tabularnewline
274 & 0 & 0.247836 & -0.247836 \tabularnewline
275 & 0 & 0.60254 & -0.60254 \tabularnewline
276 & 1 & 0.453172 & 0.546828 \tabularnewline
277 & 0 & 0.450077 & -0.450077 \tabularnewline
278 & 0 & 0.411414 & -0.411414 \tabularnewline
279 & 1 & 0.496596 & 0.503404 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266292&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]0[/C][C]0.454641[/C][C]-0.454641[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]0.646737[/C][C]0.353263[/C][/ROW]
[ROW][C]3[/C][C]0[/C][C]0.524064[/C][C]-0.524064[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]0.456738[/C][C]0.543262[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]0.731576[/C][C]0.268424[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]0.515271[/C][C]0.484729[/C][/ROW]
[ROW][C]7[/C][C]0[/C][C]0.693468[/C][C]-0.693468[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]0.850992[/C][C]0.149008[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]0.575171[/C][C]0.424829[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]0.46471[/C][C]0.53529[/C][/ROW]
[ROW][C]11[/C][C]1[/C][C]0.377385[/C][C]0.622615[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]0.699163[/C][C]0.300837[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]0.72778[/C][C]0.27222[/C][/ROW]
[ROW][C]14[/C][C]0[/C][C]0.416651[/C][C]-0.416651[/C][/ROW]
[ROW][C]15[/C][C]0[/C][C]0.421588[/C][C]-0.421588[/C][/ROW]
[ROW][C]16[/C][C]0[/C][C]0.389504[/C][C]-0.389504[/C][/ROW]
[ROW][C]17[/C][C]1[/C][C]0.690482[/C][C]0.309518[/C][/ROW]
[ROW][C]18[/C][C]0[/C][C]0.457166[/C][C]-0.457166[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]0.451655[/C][C]0.548345[/C][/ROW]
[ROW][C]20[/C][C]0[/C][C]0.497026[/C][C]-0.497026[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]0.422755[/C][C]0.577245[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]0.444949[/C][C]0.555051[/C][/ROW]
[ROW][C]23[/C][C]0[/C][C]0.370787[/C][C]-0.370787[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]0.568261[/C][C]0.431739[/C][/ROW]
[ROW][C]25[/C][C]1[/C][C]0.808464[/C][C]0.191536[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]0.350614[/C][C]0.649386[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]0.719457[/C][C]0.280543[/C][/ROW]
[ROW][C]28[/C][C]0[/C][C]0.491331[/C][C]-0.491331[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]0.523287[/C][C]0.476713[/C][/ROW]
[ROW][C]30[/C][C]0[/C][C]0.495965[/C][C]-0.495965[/C][/ROW]
[ROW][C]31[/C][C]0[/C][C]0.34105[/C][C]-0.34105[/C][/ROW]
[ROW][C]32[/C][C]0[/C][C]0.6531[/C][C]-0.6531[/C][/ROW]
[ROW][C]33[/C][C]1[/C][C]0.606327[/C][C]0.393673[/C][/ROW]
[ROW][C]34[/C][C]1[/C][C]0.574516[/C][C]0.425484[/C][/ROW]
[ROW][C]35[/C][C]1[/C][C]0.409517[/C][C]0.590483[/C][/ROW]
[ROW][C]36[/C][C]1[/C][C]0.727741[/C][C]0.272259[/C][/ROW]
[ROW][C]37[/C][C]0[/C][C]0.273358[/C][C]-0.273358[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]0.70295[/C][C]0.29705[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]0.649723[/C][C]0.350277[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]0.60254[/C][C]-0.60254[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.608644[/C][C]0.391356[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]0.722414[/C][C]0.277586[/C][/ROW]
[ROW][C]43[/C][C]1[/C][C]0.643299[/C][C]0.356701[/C][/ROW]
[ROW][C]44[/C][C]1[/C][C]0.560928[/C][C]0.439072[/C][/ROW]
[ROW][C]45[/C][C]1[/C][C]0.45222[/C][C]0.54778[/C][/ROW]
[ROW][C]46[/C][C]0[/C][C]0.687364[/C][C]-0.687364[/C][/ROW]
[ROW][C]47[/C][C]1[/C][C]0.498146[/C][C]0.501854[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]0.727431[/C][C]0.272569[/C][/ROW]
[ROW][C]49[/C][C]0[/C][C]0.307379[/C][C]-0.307379[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]0.527601[/C][C]0.472399[/C][/ROW]
[ROW][C]51[/C][C]1[/C][C]0.924551[/C][C]0.0754485[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]0.531747[/C][C]0.468253[/C][/ROW]
[ROW][C]53[/C][C]1[/C][C]0.892147[/C][C]0.107853[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]0.527112[/C][C]0.472888[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]0.693926[/C][C]0.306074[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]0.878489[/C][C]0.121511[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]0.449126[/C][C]-0.449126[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]0.310214[/C][C]0.689786[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]0.276796[/C][C]-0.276796[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]0.560264[/C][C]0.439736[/C][/ROW]
[ROW][C]61[/C][C]1[/C][C]0.802359[/C][C]0.197641[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0.489999[/C][C]-0.489999[/C][/ROW]
[ROW][C]63[/C][C]0[/C][C]0.686314[/C][C]-0.686314[/C][/ROW]
[ROW][C]64[/C][C]1[/C][C]0.608888[/C][C]0.391112[/C][/ROW]
[ROW][C]65[/C][C]0[/C][C]0.6531[/C][C]-0.6531[/C][/ROW]
[ROW][C]66[/C][C]1[/C][C]0.566683[/C][C]0.433317[/C][/ROW]
[ROW][C]67[/C][C]0[/C][C]0.693797[/C][C]-0.693797[/C][/ROW]
[ROW][C]68[/C][C]1[/C][C]0.645059[/C][C]0.354941[/C][/ROW]
[ROW][C]69[/C][C]1[/C][C]0.545396[/C][C]0.454604[/C][/ROW]
[ROW][C]70[/C][C]0[/C][C]0.61254[/C][C]-0.61254[/C][/ROW]
[ROW][C]71[/C][C]0[/C][C]0.526862[/C][C]-0.526862[/C][/ROW]
[ROW][C]72[/C][C]0[/C][C]0.456959[/C][C]-0.456959[/C][/ROW]
[ROW][C]73[/C][C]0[/C][C]0.610565[/C][C]-0.610565[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]0.645936[/C][C]0.354064[/C][/ROW]
[ROW][C]75[/C][C]0[/C][C]0.464641[/C][C]-0.464641[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]0.561804[/C][C]0.438196[/C][/ROW]
[ROW][C]77[/C][C]0[/C][C]0.625274[/C][C]-0.625274[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]0.647405[/C][C]0.352595[/C][/ROW]
[ROW][C]79[/C][C]0[/C][C]0.528652[/C][C]-0.528652[/C][/ROW]
[ROW][C]80[/C][C]0[/C][C]0.382669[/C][C]-0.382669[/C][/ROW]
[ROW][C]81[/C][C]1[/C][C]0.688349[/C][C]0.311651[/C][/ROW]
[ROW][C]82[/C][C]0[/C][C]0.734236[/C][C]-0.734236[/C][/ROW]
[ROW][C]83[/C][C]0[/C][C]0.39048[/C][C]-0.39048[/C][/ROW]
[ROW][C]84[/C][C]0[/C][C]0.608295[/C][C]-0.608295[/C][/ROW]
[ROW][C]85[/C][C]1[/C][C]0.487224[/C][C]0.512776[/C][/ROW]
[ROW][C]86[/C][C]0[/C][C]0.236036[/C][C]-0.236036[/C][/ROW]
[ROW][C]87[/C][C]1[/C][C]0.408778[/C][C]0.591222[/C][/ROW]
[ROW][C]88[/C][C]1[/C][C]0.736026[/C][C]0.263974[/C][/ROW]
[ROW][C]89[/C][C]0[/C][C]0.486766[/C][C]-0.486766[/C][/ROW]
[ROW][C]90[/C][C]0[/C][C]0.646285[/C][C]-0.646285[/C][/ROW]
[ROW][C]91[/C][C]0[/C][C]0.296283[/C][C]-0.296283[/C][/ROW]
[ROW][C]92[/C][C]1[/C][C]0.534483[/C][C]0.465517[/C][/ROW]
[ROW][C]93[/C][C]1[/C][C]0.647934[/C][C]0.352066[/C][/ROW]
[ROW][C]94[/C][C]1[/C][C]0.371565[/C][C]0.628435[/C][/ROW]
[ROW][C]95[/C][C]0[/C][C]0.645616[/C][C]-0.645616[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]0.411523[/C][C]0.588477[/C][/ROW]
[ROW][C]97[/C][C]0[/C][C]0.374834[/C][C]-0.374834[/C][/ROW]
[ROW][C]98[/C][C]1[/C][C]0.564503[/C][C]0.435497[/C][/ROW]
[ROW][C]99[/C][C]1[/C][C]0.848073[/C][C]0.151927[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]0.605978[/C][C]0.394022[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]0.648253[/C][C]0.351747[/C][/ROW]
[ROW][C]102[/C][C]1[/C][C]0.729121[/C][C]0.270879[/C][/ROW]
[ROW][C]103[/C][C]0[/C][C]0.492871[/C][C]-0.492871[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]0.323025[/C][C]0.676975[/C][/ROW]
[ROW][C]105[/C][C]1[/C][C]0.455268[/C][C]0.544732[/C][/ROW]
[ROW][C]106[/C][C]1[/C][C]0.489471[/C][C]0.510529[/C][/ROW]
[ROW][C]107[/C][C]0[/C][C]0.517937[/C][C]-0.517937[/C][/ROW]
[ROW][C]108[/C][C]0[/C][C]0.323994[/C][C]-0.323994[/C][/ROW]
[ROW][C]109[/C][C]0[/C][C]0.229504[/C][C]-0.229504[/C][/ROW]
[ROW][C]110[/C][C]0[/C][C]0.456609[/C][C]-0.456609[/C][/ROW]
[ROW][C]111[/C][C]0[/C][C]0.41419[/C][C]-0.41419[/C][/ROW]
[ROW][C]112[/C][C]0[/C][C]0.456959[/C][C]-0.456959[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]0.412262[/C][C]0.587738[/C][/ROW]
[ROW][C]114[/C][C]1[/C][C]0.804786[/C][C]0.195214[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]0.923082[/C][C]0.0769181[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]0.887712[/C][C]0.112288[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]0.997586[/C][C]0.00241372[/C][/ROW]
[ROW][C]118[/C][C]0[/C][C]0.642597[/C][C]-0.642597[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]0.454148[/C][C]0.545852[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]0.525284[/C][C]0.474716[/C][/ROW]
[ROW][C]121[/C][C]0[/C][C]0.960723[/C][C]-0.960723[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]0.485227[/C][C]0.514773[/C][/ROW]
[ROW][C]123[/C][C]0[/C][C]0.491789[/C][C]-0.491789[/C][/ROW]
[ROW][C]124[/C][C]0[/C][C]0.45222[/C][C]-0.45222[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]0.446808[/C][C]0.553192[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]0.488741[/C][C]0.511259[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]0.419426[/C][C]0.580574[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]0.526763[/C][C]0.473237[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]0.494106[/C][C]0.505894[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]0.684727[/C][C]0.315273[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]0.804328[/C][C]0.195672[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]0.919987[/C][C]0.0800128[/C][/ROW]
[ROW][C]133[/C][C]0[/C][C]0.570857[/C][C]-0.570857[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]0.45257[/C][C]0.54743[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]0.537495[/C][C]0.462505[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]1.00906[/C][C]-0.00905582[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]0.334663[/C][C]0.665337[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]0.883124[/C][C]0.116876[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]0.569279[/C][C]0.430721[/C][/ROW]
[ROW][C]140[/C][C]0[/C][C]0.525185[/C][C]-0.525185[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]0.695267[/C][C]0.304733[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]0.812749[/C][C]0.187251[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]0.803132[/C][C]0.196868[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]0.286597[/C][C]0.713403[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]0.722414[/C][C]0.277586[/C][/ROW]
[ROW][C]146[/C][C]0[/C][C]0.804786[/C][C]-0.804786[/C][/ROW]
[ROW][C]147[/C][C]0[/C][C]0.494599[/C][C]-0.494599[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]0.375444[/C][C]0.624556[/C][/ROW]
[ROW][C]149[/C][C]0[/C][C]0.619764[/C][C]-0.619764[/C][/ROW]
[ROW][C]150[/C][C]0[/C][C]0.441551[/C][C]-0.441551[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]0.883467[/C][C]0.116533[/C][/ROW]
[ROW][C]152[/C][C]0[/C][C]0.532867[/C][C]-0.532867[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]0.849542[/C][C]0.150458[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]0.40685[/C][C]0.59315[/C][/ROW]
[ROW][C]155[/C][C]0[/C][C]0.489122[/C][C]-0.489122[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]0.922234[/C][C]0.0777659[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]0.687472[/C][C]0.312528[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]0.877712[/C][C]0.122288[/C][/ROW]
[ROW][C]159[/C][C]0[/C][C]0.568337[/C][C]-0.568337[/C][/ROW]
[ROW][C]160[/C][C]0[/C][C]0.484982[/C][C]-0.484982[/C][/ROW]
[ROW][C]161[/C][C]0[/C][C]0.618186[/C][C]-0.618186[/C][/ROW]
[ROW][C]162[/C][C]0[/C][C]0.561804[/C][C]-0.561804[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]0.371526[/C][C]0.628474[/C][/ROW]
[ROW][C]164[/C][C]0[/C][C]0.456699[/C][C]-0.456699[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]0.924551[/C][C]0.0754485[/C][/ROW]
[ROW][C]166[/C][C]0[/C][C]0.803899[/C][C]-0.803899[/C][/ROW]
[ROW][C]167[/C][C]1[/C][C]0.883925[/C][C]0.116075[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]0.600222[/C][C]-0.600222[/C][/ROW]
[ROW][C]169[/C][C]1[/C][C]0.961415[/C][C]0.038585[/C][/ROW]
[ROW][C]170[/C][C]0[/C][C]0.60545[/C][C]-0.60545[/C][/ROW]
[ROW][C]171[/C][C]0[/C][C]0.607174[/C][C]-0.607174[/C][/ROW]
[ROW][C]172[/C][C]1[/C][C]0.760932[/C][C]0.239068[/C][/ROW]
[ROW][C]173[/C][C]0[/C][C]0.529773[/C][C]-0.529773[/C][/ROW]
[ROW][C]174[/C][C]1[/C][C]0.527102[/C][C]0.472898[/C][/ROW]
[ROW][C]175[/C][C]1[/C][C]0.880806[/C][C]0.119194[/C][/ROW]
[ROW][C]176[/C][C]1[/C][C]0.880806[/C][C]0.119194[/C][/ROW]
[ROW][C]177[/C][C]1[/C][C]0.564824[/C][C]0.435176[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]0.726653[/C][C]0.273347[/C][/ROW]
[ROW][C]179[/C][C]0[/C][C]0.458188[/C][C]-0.458188[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]0.693751[/C][C]0.306249[/C][/ROW]
[ROW][C]181[/C][C]0[/C][C]0.409625[/C][C]-0.409625[/C][/ROW]
[ROW][C]182[/C][C]0[/C][C]0.649204[/C][C]-0.649204[/C][/ROW]
[ROW][C]183[/C][C]0[/C][C]0.533217[/C][C]-0.533217[/C][/ROW]
[ROW][C]184[/C][C]1[/C][C]0.609336[/C][C]0.390664[/C][/ROW]
[ROW][C]185[/C][C]0[/C][C]0.381281[/C][C]-0.381281[/C][/ROW]
[ROW][C]186[/C][C]1[/C][C]0.858247[/C][C]0.141753[/C][/ROW]
[ROW][C]187[/C][C]0[/C][C]0.37016[/C][C]-0.37016[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]0.37016[/C][C]-0.37016[/C][/ROW]
[ROW][C]189[/C][C]0[/C][C]0.37016[/C][C]-0.37016[/C][/ROW]
[ROW][C]190[/C][C]0[/C][C]0.33252[/C][C]-0.33252[/C][/ROW]
[ROW][C]191[/C][C]1[/C][C]0.342449[/C][C]0.657551[/C][/ROW]
[ROW][C]192[/C][C]1[/C][C]0.60254[/C][C]0.39746[/C][/ROW]
[ROW][C]193[/C][C]1[/C][C]0.588145[/C][C]0.411855[/C][/ROW]
[ROW][C]194[/C][C]1[/C][C]0.656156[/C][C]0.343844[/C][/ROW]
[ROW][C]195[/C][C]0[/C][C]0.307967[/C][C]-0.307967[/C][/ROW]
[ROW][C]196[/C][C]0[/C][C]0.25823[/C][C]-0.25823[/C][/ROW]
[ROW][C]197[/C][C]1[/C][C]0.797795[/C][C]0.202205[/C][/ROW]
[ROW][C]198[/C][C]0[/C][C]0.567169[/C][C]-0.567169[/C][/ROW]
[ROW][C]199[/C][C]0[/C][C]0.323117[/C][C]-0.323117[/C][/ROW]
[ROW][C]200[/C][C]0[/C][C]0.418649[/C][C]-0.418649[/C][/ROW]
[ROW][C]201[/C][C]0[/C][C]0.531497[/C][C]-0.531497[/C][/ROW]
[ROW][C]202[/C][C]1[/C][C]0.485227[/C][C]0.514773[/C][/ROW]
[ROW][C]203[/C][C]1[/C][C]0.371137[/C][C]0.628863[/C][/ROW]
[ROW][C]204[/C][C]0[/C][C]0.652149[/C][C]-0.652149[/C][/ROW]
[ROW][C]205[/C][C]0[/C][C]0.609237[/C][C]-0.609237[/C][/ROW]
[ROW][C]206[/C][C]1[/C][C]0.49021[/C][C]0.50979[/C][/ROW]
[ROW][C]207[/C][C]0[/C][C]0.486766[/C][C]-0.486766[/C][/ROW]
[ROW][C]208[/C][C]1[/C][C]0.608997[/C][C]0.391003[/C][/ROW]
[ROW][C]209[/C][C]1[/C][C]0.484106[/C][C]0.515894[/C][/ROW]
[ROW][C]210[/C][C]0[/C][C]0.173674[/C][C]-0.173674[/C][/ROW]
[ROW][C]211[/C][C]1[/C][C]0.655507[/C][C]0.344493[/C][/ROW]
[ROW][C]212[/C][C]1[/C][C]0.845755[/C][C]0.154245[/C][/ROW]
[ROW][C]213[/C][C]1[/C][C]0.760856[/C][C]0.239144[/C][/ROW]
[ROW][C]214[/C][C]0[/C][C]0.624652[/C][C]-0.624652[/C][/ROW]
[ROW][C]215[/C][C]0[/C][C]0.52908[/C][C]-0.52908[/C][/ROW]
[ROW][C]216[/C][C]0[/C][C]0.367669[/C][C]-0.367669[/C][/ROW]
[ROW][C]217[/C][C]1[/C][C]0.274372[/C][C]0.725628[/C][/ROW]
[ROW][C]218[/C][C]1[/C][C]0.579029[/C][C]0.420971[/C][/ROW]
[ROW][C]219[/C][C]1[/C][C]0.961843[/C][C]0.0381568[/C][/ROW]
[ROW][C]220[/C][C]1[/C][C]0.609246[/C][C]0.390754[/C][/ROW]
[ROW][C]221[/C][C]0[/C][C]0.361137[/C][C]-0.361137[/C][/ROW]
[ROW][C]222[/C][C]0[/C][C]0.612191[/C][C]-0.612191[/C][/ROW]
[ROW][C]223[/C][C]0[/C][C]0.613753[/C][C]-0.613753[/C][/ROW]
[ROW][C]224[/C][C]1[/C][C]0.720973[/C][C]0.279027[/C][/ROW]
[ROW][C]225[/C][C]1[/C][C]0.537623[/C][C]0.462377[/C][/ROW]
[ROW][C]226[/C][C]0[/C][C]0.65246[/C][C]-0.65246[/C][/ROW]
[ROW][C]227[/C][C]0[/C][C]0.411414[/C][C]-0.411414[/C][/ROW]
[ROW][C]228[/C][C]0[/C][C]0.533287[/C][C]-0.533287[/C][/ROW]
[ROW][C]229[/C][C]1[/C][C]0.685117[/C][C]0.314883[/C][/ROW]
[ROW][C]230[/C][C]1[/C][C]0.687364[/C][C]0.312636[/C][/ROW]
[ROW][C]231[/C][C]0[/C][C]0.45369[/C][C]-0.45369[/C][/ROW]
[ROW][C]232[/C][C]0[/C][C]0.324238[/C][C]-0.324238[/C][/ROW]
[ROW][C]233[/C][C]0[/C][C]0.803132[/C][C]-0.803132[/C][/ROW]
[ROW][C]234[/C][C]1[/C][C]0.682456[/C][C]0.317544[/C][/ROW]
[ROW][C]235[/C][C]1[/C][C]0.56781[/C][C]0.43219[/C][/ROW]
[ROW][C]236[/C][C]1[/C][C]0.324238[/C][C]0.675762[/C][/ROW]
[ROW][C]237[/C][C]1[/C][C]0.484449[/C][C]0.515551[/C][/ROW]
[ROW][C]238[/C][C]0[/C][C]0.408428[/C][C]-0.408428[/C][/ROW]
[ROW][C]239[/C][C]1[/C][C]0.655936[/C][C]0.344064[/C][/ROW]
[ROW][C]240[/C][C]1[/C][C]0.286597[/C][C]0.713403[/C][/ROW]
[ROW][C]241[/C][C]1[/C][C]0.662991[/C][C]0.337009[/C][/ROW]
[ROW][C]242[/C][C]0[/C][C]0.682456[/C][C]-0.682456[/C][/ROW]
[ROW][C]243[/C][C]0[/C][C]0.417109[/C][C]-0.417109[/C][/ROW]
[ROW][C]244[/C][C]1[/C][C]0.413732[/C][C]0.586268[/C][/ROW]
[ROW][C]245[/C][C]0[/C][C]0.803899[/C][C]-0.803899[/C][/ROW]
[ROW][C]246[/C][C]1[/C][C]0.524941[/C][C]0.475059[/C][/ROW]
[ROW][C]247[/C][C]1[/C][C]0.605658[/C][C]0.394342[/C][/ROW]
[ROW][C]248[/C][C]0[/C][C]0.41685[/C][C]-0.41685[/C][/ROW]
[ROW][C]249[/C][C]1[/C][C]0.654311[/C][C]0.345689[/C][/ROW]
[ROW][C]250[/C][C]0[/C][C]0.684035[/C][C]-0.684035[/C][/ROW]
[ROW][C]251[/C][C]1[/C][C]0.527183[/C][C]0.472817[/C][/ROW]
[ROW][C]252[/C][C]1[/C][C]0.681717[/C][C]0.318283[/C][/ROW]
[ROW][C]253[/C][C]0[/C][C]0.534558[/C][C]-0.534558[/C][/ROW]
[ROW][C]254[/C][C]1[/C][C]0.571346[/C][C]0.428654[/C][/ROW]
[ROW][C]255[/C][C]0[/C][C]0.383249[/C][C]-0.383249[/C][/ROW]
[ROW][C]256[/C][C]1[/C][C]0.80089[/C][C]0.19911[/C][/ROW]
[ROW][C]257[/C][C]0[/C][C]0.403412[/C][C]-0.403412[/C][/ROW]
[ROW][C]258[/C][C]1[/C][C]0.495546[/C][C]0.504454[/C][/ROW]
[ROW][C]259[/C][C]0[/C][C]0.728472[/C][C]-0.728472[/C][/ROW]
[ROW][C]260[/C][C]0[/C][C]0.376892[/C][C]-0.376892[/C][/ROW]
[ROW][C]261[/C][C]1[/C][C]0.341827[/C][C]0.658173[/C][/ROW]
[ROW][C]262[/C][C]1[/C][C]0.883925[/C][C]0.116075[/C][/ROW]
[ROW][C]263[/C][C]0[/C][C]0.441053[/C][C]-0.441053[/C][/ROW]
[ROW][C]264[/C][C]1[/C][C]0.557895[/C][C]0.442105[/C][/ROW]
[ROW][C]265[/C][C]1[/C][C]0.413732[/C][C]0.586268[/C][/ROW]
[ROW][C]266[/C][C]0[/C][C]0.580545[/C][C]-0.580545[/C][/ROW]
[ROW][C]267[/C][C]1[/C][C]1.03832[/C][C]-0.0383219[/C][/ROW]
[ROW][C]268[/C][C]0[/C][C]0.420787[/C][C]-0.420787[/C][/ROW]
[ROW][C]269[/C][C]0[/C][C]0.264244[/C][C]-0.264244[/C][/ROW]
[ROW][C]270[/C][C]1[/C][C]0.766861[/C][C]0.233139[/C][/ROW]
[ROW][C]271[/C][C]1[/C][C]0.811901[/C][C]0.188099[/C][/ROW]
[ROW][C]272[/C][C]0[/C][C]0.459055[/C][C]-0.459055[/C][/ROW]
[ROW][C]273[/C][C]1[/C][C]0.880806[/C][C]0.119194[/C][/ROW]
[ROW][C]274[/C][C]0[/C][C]0.247836[/C][C]-0.247836[/C][/ROW]
[ROW][C]275[/C][C]0[/C][C]0.60254[/C][C]-0.60254[/C][/ROW]
[ROW][C]276[/C][C]1[/C][C]0.453172[/C][C]0.546828[/C][/ROW]
[ROW][C]277[/C][C]0[/C][C]0.450077[/C][C]-0.450077[/C][/ROW]
[ROW][C]278[/C][C]0[/C][C]0.411414[/C][C]-0.411414[/C][/ROW]
[ROW][C]279[/C][C]1[/C][C]0.496596[/C][C]0.503404[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266292&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266292&T=4

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
100.454641-0.454641
210.6467370.353263
300.524064-0.524064
410.4567380.543262
510.7315760.268424
610.5152710.484729
700.693468-0.693468
810.8509920.149008
910.5751710.424829
1010.464710.53529
1110.3773850.622615
1210.6991630.300837
1310.727780.27222
1400.416651-0.416651
1500.421588-0.421588
1600.389504-0.389504
1710.6904820.309518
1800.457166-0.457166
1910.4516550.548345
2000.497026-0.497026
2110.4227550.577245
2210.4449490.555051
2300.370787-0.370787
2410.5682610.431739
2510.8084640.191536
2610.3506140.649386
2710.7194570.280543
2800.491331-0.491331
2910.5232870.476713
3000.495965-0.495965
3100.34105-0.34105
3200.6531-0.6531
3310.6063270.393673
3410.5745160.425484
3510.4095170.590483
3610.7277410.272259
3700.273358-0.273358
3810.702950.29705
3910.6497230.350277
4000.60254-0.60254
4110.6086440.391356
4210.7224140.277586
4310.6432990.356701
4410.5609280.439072
4510.452220.54778
4600.687364-0.687364
4710.4981460.501854
4810.7274310.272569
4900.307379-0.307379
5010.5276010.472399
5110.9245510.0754485
5210.5317470.468253
5310.8921470.107853
5410.5271120.472888
5510.6939260.306074
5610.8784890.121511
5700.449126-0.449126
5810.3102140.689786
5900.276796-0.276796
6010.5602640.439736
6110.8023590.197641
6200.489999-0.489999
6300.686314-0.686314
6410.6088880.391112
6500.6531-0.6531
6610.5666830.433317
6700.693797-0.693797
6810.6450590.354941
6910.5453960.454604
7000.61254-0.61254
7100.526862-0.526862
7200.456959-0.456959
7300.610565-0.610565
7410.6459360.354064
7500.464641-0.464641
7610.5618040.438196
7700.625274-0.625274
7810.6474050.352595
7900.528652-0.528652
8000.382669-0.382669
8110.6883490.311651
8200.734236-0.734236
8300.39048-0.39048
8400.608295-0.608295
8510.4872240.512776
8600.236036-0.236036
8710.4087780.591222
8810.7360260.263974
8900.486766-0.486766
9000.646285-0.646285
9100.296283-0.296283
9210.5344830.465517
9310.6479340.352066
9410.3715650.628435
9500.645616-0.645616
9610.4115230.588477
9700.374834-0.374834
9810.5645030.435497
9910.8480730.151927
10010.6059780.394022
10110.6482530.351747
10210.7291210.270879
10300.492871-0.492871
10410.3230250.676975
10510.4552680.544732
10610.4894710.510529
10700.517937-0.517937
10800.323994-0.323994
10900.229504-0.229504
11000.456609-0.456609
11100.41419-0.41419
11200.456959-0.456959
11310.4122620.587738
11410.8047860.195214
11510.9230820.0769181
11610.8877120.112288
11710.9975860.00241372
11800.642597-0.642597
11910.4541480.545852
12010.5252840.474716
12100.960723-0.960723
12210.4852270.514773
12300.491789-0.491789
12400.45222-0.45222
12510.4468080.553192
12610.4887410.511259
12710.4194260.580574
12810.5267630.473237
12910.4941060.505894
13010.6847270.315273
13110.8043280.195672
13210.9199870.0800128
13300.570857-0.570857
13410.452570.54743
13510.5374950.462505
13611.00906-0.00905582
13710.3346630.665337
13810.8831240.116876
13910.5692790.430721
14000.525185-0.525185
14110.6952670.304733
14210.8127490.187251
14310.8031320.196868
14410.2865970.713403
14510.7224140.277586
14600.804786-0.804786
14700.494599-0.494599
14810.3754440.624556
14900.619764-0.619764
15000.441551-0.441551
15110.8834670.116533
15200.532867-0.532867
15310.8495420.150458
15410.406850.59315
15500.489122-0.489122
15610.9222340.0777659
15710.6874720.312528
15810.8777120.122288
15900.568337-0.568337
16000.484982-0.484982
16100.618186-0.618186
16200.561804-0.561804
16310.3715260.628474
16400.456699-0.456699
16510.9245510.0754485
16600.803899-0.803899
16710.8839250.116075
16800.600222-0.600222
16910.9614150.038585
17000.60545-0.60545
17100.607174-0.607174
17210.7609320.239068
17300.529773-0.529773
17410.5271020.472898
17510.8808060.119194
17610.8808060.119194
17710.5648240.435176
17810.7266530.273347
17900.458188-0.458188
18010.6937510.306249
18100.409625-0.409625
18200.649204-0.649204
18300.533217-0.533217
18410.6093360.390664
18500.381281-0.381281
18610.8582470.141753
18700.37016-0.37016
18800.37016-0.37016
18900.37016-0.37016
19000.33252-0.33252
19110.3424490.657551
19210.602540.39746
19310.5881450.411855
19410.6561560.343844
19500.307967-0.307967
19600.25823-0.25823
19710.7977950.202205
19800.567169-0.567169
19900.323117-0.323117
20000.418649-0.418649
20100.531497-0.531497
20210.4852270.514773
20310.3711370.628863
20400.652149-0.652149
20500.609237-0.609237
20610.490210.50979
20700.486766-0.486766
20810.6089970.391003
20910.4841060.515894
21000.173674-0.173674
21110.6555070.344493
21210.8457550.154245
21310.7608560.239144
21400.624652-0.624652
21500.52908-0.52908
21600.367669-0.367669
21710.2743720.725628
21810.5790290.420971
21910.9618430.0381568
22010.6092460.390754
22100.361137-0.361137
22200.612191-0.612191
22300.613753-0.613753
22410.7209730.279027
22510.5376230.462377
22600.65246-0.65246
22700.411414-0.411414
22800.533287-0.533287
22910.6851170.314883
23010.6873640.312636
23100.45369-0.45369
23200.324238-0.324238
23300.803132-0.803132
23410.6824560.317544
23510.567810.43219
23610.3242380.675762
23710.4844490.515551
23800.408428-0.408428
23910.6559360.344064
24010.2865970.713403
24110.6629910.337009
24200.682456-0.682456
24300.417109-0.417109
24410.4137320.586268
24500.803899-0.803899
24610.5249410.475059
24710.6056580.394342
24800.41685-0.41685
24910.6543110.345689
25000.684035-0.684035
25110.5271830.472817
25210.6817170.318283
25300.534558-0.534558
25410.5713460.428654
25500.383249-0.383249
25610.800890.19911
25700.403412-0.403412
25810.4955460.504454
25900.728472-0.728472
26000.376892-0.376892
26110.3418270.658173
26210.8839250.116075
26300.441053-0.441053
26410.5578950.442105
26510.4137320.586268
26600.580545-0.580545
26711.03832-0.0383219
26800.420787-0.420787
26900.264244-0.264244
27010.7668610.233139
27110.8119010.188099
27200.459055-0.459055
27310.8808060.119194
27400.247836-0.247836
27500.60254-0.60254
27610.4531720.546828
27700.450077-0.450077
27800.411414-0.411414
27910.4965960.503404






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.6189390.7621210.381061
110.6093940.7812120.390606
120.5857840.8284320.414216
130.5090630.9818740.490937
140.5111240.9777510.488876
150.5538240.8923520.446176
160.5031930.9936140.496807
170.4584750.916950.541525
180.494890.989780.50511
190.4431190.8862390.556881
200.4040020.8080040.595998
210.636660.7266790.36334
220.6617190.6765620.338281
230.6252270.7495450.374773
240.6381070.7237860.361893
250.5799750.8400510.420025
260.657260.685480.34274
270.5979240.8041510.402076
280.5799190.8401630.420081
290.6479870.7040260.352013
300.6379650.724070.362035
310.6095380.7809240.390462
320.700630.598740.29937
330.6692520.6614970.330748
340.6617930.6764140.338207
350.6777220.6445550.322278
360.6365740.7268520.363426
370.6074920.7850160.392508
380.5608020.8783960.439198
390.5186060.9627870.481394
400.5702870.8594250.429713
410.537930.9241410.46207
420.4998620.9997230.500138
430.4671530.9343070.532847
440.4528380.9056760.547162
450.4753930.9507860.524607
460.5798410.8403170.420159
470.5782690.8434620.421731
480.5362080.9275850.463792
490.5073640.9852720.492636
500.4952960.9905910.504704
510.4530250.9060490.546975
520.4321280.8642550.567872
530.3873320.7746630.612668
540.3648990.7297980.635101
550.3273170.6546350.672683
560.2882430.5764870.711757
570.2902330.5804660.709767
580.3245870.6491740.675413
590.3028680.6057370.697132
600.2832610.5665220.716739
610.2494080.4988160.750592
620.2762750.552550.723725
630.3168440.6336890.683156
640.2921230.5842470.707877
650.3474520.6949030.652548
660.3390690.6781390.660931
670.3773740.7547480.622626
680.3529360.7058730.647064
690.3470970.6941940.652903
700.3892650.7785310.610735
710.4029340.8058680.597066
720.4227430.8454850.577257
730.4704660.9409330.529534
740.4524480.9048970.547552
750.4737280.9474560.526272
760.462780.9255590.53722
770.5076560.9846870.492344
780.4815760.9631510.518424
790.5083310.9833370.491669
800.4905140.9810290.509486
810.470830.941660.52917
820.5208830.9582340.479117
830.5049080.9901850.495092
840.5307230.9385540.469277
850.5339460.9321080.466054
860.5000920.9998150.499908
870.5056070.9887850.494393
880.4793480.9586970.520652
890.4912870.9825730.508713
900.5403330.9193350.459667
910.5134440.9731130.486556
920.5131540.9736920.486846
930.4981140.9962280.501886
940.5241090.9517820.475891
950.5590730.8818540.440927
960.5757190.8485610.424281
970.5650470.8699060.434953
980.554150.8916990.44585
990.5209950.958010.479005
1000.5071480.9857050.492852
1010.4909670.9819340.509033
1020.4653320.9306630.534668
1030.4745060.9490110.525494
1040.5266720.9466550.473328
1050.5342840.9314320.465716
1060.5331410.9337180.466859
1070.5324850.935030.467515
1080.5077480.9845040.492252
1090.4796280.9592570.520372
1100.4771280.9542560.522872
1110.4740410.9480810.525959
1120.4765380.9530750.523462
1130.4977540.9955080.502246
1140.4686750.9373490.531325
1150.434420.868840.56558
1160.4015530.8031050.598447
1170.3680810.7361620.631919
1180.3978930.7957860.602107
1190.4070280.8140570.592972
1200.4067340.8134680.593266
1210.5168560.9662870.483144
1220.5191210.9617580.480879
1230.5294680.9410640.470532
1240.5254230.9491550.474577
1250.5341940.9316120.465806
1260.5413880.9172230.458612
1270.5640830.8718340.435917
1280.5672490.8655010.432751
1290.5766540.8466920.423346
1300.55890.88220.4411
1310.5310590.9378820.468941
1320.4974880.9949760.502512
1330.5242080.9515840.475792
1340.537240.925520.46276
1350.5396060.9207880.460394
1360.5049220.9901550.495078
1370.541170.9176590.45883
1380.5088270.9823470.491173
1390.5065690.9868630.493431
1400.519010.9619810.48099
1410.4993760.9987510.500624
1420.4705180.9410360.529482
1430.4457050.891410.554295
1440.4966340.9932680.503366
1450.4767560.9535130.523244
1460.5449560.9100890.455044
1470.5481130.9037740.451887
1480.5871770.8256460.412823
1490.6098030.7803930.390197
1500.6119510.7760990.388049
1510.5800610.8398790.419939
1520.5860450.827910.413955
1530.5548780.8902440.445122
1540.5832130.8335740.416787
1550.5832880.8334250.416712
1560.5494660.9010690.450534
1570.5318340.9363320.468166
1580.4989810.9979620.501019
1590.5161640.9676730.483836
1600.5218460.9563090.478154
1610.5468760.9062470.453124
1620.5632490.8735030.436751
1630.6052920.7894170.394708
1640.5982170.8035660.401783
1650.5644730.8710550.435527
1660.6430480.7139040.356952
1670.6113150.7773710.388685
1680.6346080.7307840.365392
1690.6008440.7983120.399156
1700.6114430.7771150.388557
1710.6299980.7400040.370002
1720.6017790.7964420.398221
1730.6042310.7915370.395769
1740.5981290.8037420.401871
1750.5645160.8709690.435484
1760.5304130.9391750.469587
1770.5476170.9047660.452383
1780.5291650.941670.470835
1790.5217670.9564660.478233
1800.4996730.9993460.500327
1810.4831460.9662920.516854
1820.5180980.9638050.481902
1830.5190910.9618190.480909
1840.5052130.9895740.494787
1850.4956370.9912740.504363
1860.4618550.9237110.538145
1870.4469470.8938940.553053
1880.433250.8664990.56675
1890.4214310.8428630.578569
1900.4061370.8122730.593863
1910.4293360.8586730.570664
1920.4196270.8392550.580373
1930.4178830.8357670.582117
1940.4057310.8114610.594269
1950.3867650.773530.613235
1960.3581950.716390.641805
1970.3267330.6534670.673267
1980.3495010.6990010.650499
1990.3313540.6627070.668646
2000.317180.6343610.68282
2010.3306370.6612740.669363
2020.3439340.6878680.656066
2030.3787590.7575180.621241
2040.4055250.811050.594475
2050.4064040.8128070.593596
2060.444770.8895390.55523
2070.4323760.8647510.567624
2080.4506590.9013180.549341
2090.4959180.9918360.504082
2100.4773170.9546330.522683
2110.4740070.9480140.525993
2120.4344250.868850.565575
2130.423590.8471810.57641
2140.4934480.9868960.506552
2150.4803050.960610.519695
2160.4608650.921730.539135
2170.4702550.940510.529745
2180.4662080.9324160.533792
2190.4235430.8470870.576457
2200.3963960.7927920.603604
2210.3719080.7438170.628092
2220.4023430.8046860.597657
2230.4127680.8255360.587232
2240.3734420.7468830.626558
2250.3919760.7839520.608024
2260.4029520.8059050.597048
2270.378030.7560590.62197
2280.3558710.7117420.644129
2290.3279210.6558430.672079
2300.3099830.6199660.690017
2310.2907060.5814130.709294
2320.3077080.6154160.692292
2330.3714740.7429490.628526
2340.3490580.6981150.650942
2350.3923270.7846540.607673
2360.3825060.7650120.617494
2370.433850.8676990.56615
2380.409370.818740.59063
2390.3869180.7738360.613082
2400.3991260.7982510.600874
2410.3912470.7824940.608753
2420.425320.850640.57468
2430.4188190.8376370.581181
2440.5154730.9690540.484527
2450.6446580.7106850.355342
2460.6201160.7597670.379884
2470.5993210.8013590.400679
2480.5516620.8966760.448338
2490.5737110.8525780.426289
2500.6504560.6990890.349544
2510.7502840.4994310.249716
2520.7282680.5434630.271732
2530.684070.6318590.31593
2540.6954170.6091670.304583
2550.7681570.4636850.231843
2560.7097110.5805780.290289
2570.6464860.7070280.353514
2580.6324470.7351060.367553
2590.6400850.7198290.359915
2600.565080.8698410.43492
2610.6746280.6507450.325372
2620.5996740.8006510.400326
2630.5122560.9754880.487744
2640.4140210.8280420.585979
2650.8422710.3154590.157729
2660.7651710.4696580.234829
2670.7526780.4946430.247322
2680.6256690.7486630.374331
2690.4564070.9128130.543593

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.618939 & 0.762121 & 0.381061 \tabularnewline
11 & 0.609394 & 0.781212 & 0.390606 \tabularnewline
12 & 0.585784 & 0.828432 & 0.414216 \tabularnewline
13 & 0.509063 & 0.981874 & 0.490937 \tabularnewline
14 & 0.511124 & 0.977751 & 0.488876 \tabularnewline
15 & 0.553824 & 0.892352 & 0.446176 \tabularnewline
16 & 0.503193 & 0.993614 & 0.496807 \tabularnewline
17 & 0.458475 & 0.91695 & 0.541525 \tabularnewline
18 & 0.49489 & 0.98978 & 0.50511 \tabularnewline
19 & 0.443119 & 0.886239 & 0.556881 \tabularnewline
20 & 0.404002 & 0.808004 & 0.595998 \tabularnewline
21 & 0.63666 & 0.726679 & 0.36334 \tabularnewline
22 & 0.661719 & 0.676562 & 0.338281 \tabularnewline
23 & 0.625227 & 0.749545 & 0.374773 \tabularnewline
24 & 0.638107 & 0.723786 & 0.361893 \tabularnewline
25 & 0.579975 & 0.840051 & 0.420025 \tabularnewline
26 & 0.65726 & 0.68548 & 0.34274 \tabularnewline
27 & 0.597924 & 0.804151 & 0.402076 \tabularnewline
28 & 0.579919 & 0.840163 & 0.420081 \tabularnewline
29 & 0.647987 & 0.704026 & 0.352013 \tabularnewline
30 & 0.637965 & 0.72407 & 0.362035 \tabularnewline
31 & 0.609538 & 0.780924 & 0.390462 \tabularnewline
32 & 0.70063 & 0.59874 & 0.29937 \tabularnewline
33 & 0.669252 & 0.661497 & 0.330748 \tabularnewline
34 & 0.661793 & 0.676414 & 0.338207 \tabularnewline
35 & 0.677722 & 0.644555 & 0.322278 \tabularnewline
36 & 0.636574 & 0.726852 & 0.363426 \tabularnewline
37 & 0.607492 & 0.785016 & 0.392508 \tabularnewline
38 & 0.560802 & 0.878396 & 0.439198 \tabularnewline
39 & 0.518606 & 0.962787 & 0.481394 \tabularnewline
40 & 0.570287 & 0.859425 & 0.429713 \tabularnewline
41 & 0.53793 & 0.924141 & 0.46207 \tabularnewline
42 & 0.499862 & 0.999723 & 0.500138 \tabularnewline
43 & 0.467153 & 0.934307 & 0.532847 \tabularnewline
44 & 0.452838 & 0.905676 & 0.547162 \tabularnewline
45 & 0.475393 & 0.950786 & 0.524607 \tabularnewline
46 & 0.579841 & 0.840317 & 0.420159 \tabularnewline
47 & 0.578269 & 0.843462 & 0.421731 \tabularnewline
48 & 0.536208 & 0.927585 & 0.463792 \tabularnewline
49 & 0.507364 & 0.985272 & 0.492636 \tabularnewline
50 & 0.495296 & 0.990591 & 0.504704 \tabularnewline
51 & 0.453025 & 0.906049 & 0.546975 \tabularnewline
52 & 0.432128 & 0.864255 & 0.567872 \tabularnewline
53 & 0.387332 & 0.774663 & 0.612668 \tabularnewline
54 & 0.364899 & 0.729798 & 0.635101 \tabularnewline
55 & 0.327317 & 0.654635 & 0.672683 \tabularnewline
56 & 0.288243 & 0.576487 & 0.711757 \tabularnewline
57 & 0.290233 & 0.580466 & 0.709767 \tabularnewline
58 & 0.324587 & 0.649174 & 0.675413 \tabularnewline
59 & 0.302868 & 0.605737 & 0.697132 \tabularnewline
60 & 0.283261 & 0.566522 & 0.716739 \tabularnewline
61 & 0.249408 & 0.498816 & 0.750592 \tabularnewline
62 & 0.276275 & 0.55255 & 0.723725 \tabularnewline
63 & 0.316844 & 0.633689 & 0.683156 \tabularnewline
64 & 0.292123 & 0.584247 & 0.707877 \tabularnewline
65 & 0.347452 & 0.694903 & 0.652548 \tabularnewline
66 & 0.339069 & 0.678139 & 0.660931 \tabularnewline
67 & 0.377374 & 0.754748 & 0.622626 \tabularnewline
68 & 0.352936 & 0.705873 & 0.647064 \tabularnewline
69 & 0.347097 & 0.694194 & 0.652903 \tabularnewline
70 & 0.389265 & 0.778531 & 0.610735 \tabularnewline
71 & 0.402934 & 0.805868 & 0.597066 \tabularnewline
72 & 0.422743 & 0.845485 & 0.577257 \tabularnewline
73 & 0.470466 & 0.940933 & 0.529534 \tabularnewline
74 & 0.452448 & 0.904897 & 0.547552 \tabularnewline
75 & 0.473728 & 0.947456 & 0.526272 \tabularnewline
76 & 0.46278 & 0.925559 & 0.53722 \tabularnewline
77 & 0.507656 & 0.984687 & 0.492344 \tabularnewline
78 & 0.481576 & 0.963151 & 0.518424 \tabularnewline
79 & 0.508331 & 0.983337 & 0.491669 \tabularnewline
80 & 0.490514 & 0.981029 & 0.509486 \tabularnewline
81 & 0.47083 & 0.94166 & 0.52917 \tabularnewline
82 & 0.520883 & 0.958234 & 0.479117 \tabularnewline
83 & 0.504908 & 0.990185 & 0.495092 \tabularnewline
84 & 0.530723 & 0.938554 & 0.469277 \tabularnewline
85 & 0.533946 & 0.932108 & 0.466054 \tabularnewline
86 & 0.500092 & 0.999815 & 0.499908 \tabularnewline
87 & 0.505607 & 0.988785 & 0.494393 \tabularnewline
88 & 0.479348 & 0.958697 & 0.520652 \tabularnewline
89 & 0.491287 & 0.982573 & 0.508713 \tabularnewline
90 & 0.540333 & 0.919335 & 0.459667 \tabularnewline
91 & 0.513444 & 0.973113 & 0.486556 \tabularnewline
92 & 0.513154 & 0.973692 & 0.486846 \tabularnewline
93 & 0.498114 & 0.996228 & 0.501886 \tabularnewline
94 & 0.524109 & 0.951782 & 0.475891 \tabularnewline
95 & 0.559073 & 0.881854 & 0.440927 \tabularnewline
96 & 0.575719 & 0.848561 & 0.424281 \tabularnewline
97 & 0.565047 & 0.869906 & 0.434953 \tabularnewline
98 & 0.55415 & 0.891699 & 0.44585 \tabularnewline
99 & 0.520995 & 0.95801 & 0.479005 \tabularnewline
100 & 0.507148 & 0.985705 & 0.492852 \tabularnewline
101 & 0.490967 & 0.981934 & 0.509033 \tabularnewline
102 & 0.465332 & 0.930663 & 0.534668 \tabularnewline
103 & 0.474506 & 0.949011 & 0.525494 \tabularnewline
104 & 0.526672 & 0.946655 & 0.473328 \tabularnewline
105 & 0.534284 & 0.931432 & 0.465716 \tabularnewline
106 & 0.533141 & 0.933718 & 0.466859 \tabularnewline
107 & 0.532485 & 0.93503 & 0.467515 \tabularnewline
108 & 0.507748 & 0.984504 & 0.492252 \tabularnewline
109 & 0.479628 & 0.959257 & 0.520372 \tabularnewline
110 & 0.477128 & 0.954256 & 0.522872 \tabularnewline
111 & 0.474041 & 0.948081 & 0.525959 \tabularnewline
112 & 0.476538 & 0.953075 & 0.523462 \tabularnewline
113 & 0.497754 & 0.995508 & 0.502246 \tabularnewline
114 & 0.468675 & 0.937349 & 0.531325 \tabularnewline
115 & 0.43442 & 0.86884 & 0.56558 \tabularnewline
116 & 0.401553 & 0.803105 & 0.598447 \tabularnewline
117 & 0.368081 & 0.736162 & 0.631919 \tabularnewline
118 & 0.397893 & 0.795786 & 0.602107 \tabularnewline
119 & 0.407028 & 0.814057 & 0.592972 \tabularnewline
120 & 0.406734 & 0.813468 & 0.593266 \tabularnewline
121 & 0.516856 & 0.966287 & 0.483144 \tabularnewline
122 & 0.519121 & 0.961758 & 0.480879 \tabularnewline
123 & 0.529468 & 0.941064 & 0.470532 \tabularnewline
124 & 0.525423 & 0.949155 & 0.474577 \tabularnewline
125 & 0.534194 & 0.931612 & 0.465806 \tabularnewline
126 & 0.541388 & 0.917223 & 0.458612 \tabularnewline
127 & 0.564083 & 0.871834 & 0.435917 \tabularnewline
128 & 0.567249 & 0.865501 & 0.432751 \tabularnewline
129 & 0.576654 & 0.846692 & 0.423346 \tabularnewline
130 & 0.5589 & 0.8822 & 0.4411 \tabularnewline
131 & 0.531059 & 0.937882 & 0.468941 \tabularnewline
132 & 0.497488 & 0.994976 & 0.502512 \tabularnewline
133 & 0.524208 & 0.951584 & 0.475792 \tabularnewline
134 & 0.53724 & 0.92552 & 0.46276 \tabularnewline
135 & 0.539606 & 0.920788 & 0.460394 \tabularnewline
136 & 0.504922 & 0.990155 & 0.495078 \tabularnewline
137 & 0.54117 & 0.917659 & 0.45883 \tabularnewline
138 & 0.508827 & 0.982347 & 0.491173 \tabularnewline
139 & 0.506569 & 0.986863 & 0.493431 \tabularnewline
140 & 0.51901 & 0.961981 & 0.48099 \tabularnewline
141 & 0.499376 & 0.998751 & 0.500624 \tabularnewline
142 & 0.470518 & 0.941036 & 0.529482 \tabularnewline
143 & 0.445705 & 0.89141 & 0.554295 \tabularnewline
144 & 0.496634 & 0.993268 & 0.503366 \tabularnewline
145 & 0.476756 & 0.953513 & 0.523244 \tabularnewline
146 & 0.544956 & 0.910089 & 0.455044 \tabularnewline
147 & 0.548113 & 0.903774 & 0.451887 \tabularnewline
148 & 0.587177 & 0.825646 & 0.412823 \tabularnewline
149 & 0.609803 & 0.780393 & 0.390197 \tabularnewline
150 & 0.611951 & 0.776099 & 0.388049 \tabularnewline
151 & 0.580061 & 0.839879 & 0.419939 \tabularnewline
152 & 0.586045 & 0.82791 & 0.413955 \tabularnewline
153 & 0.554878 & 0.890244 & 0.445122 \tabularnewline
154 & 0.583213 & 0.833574 & 0.416787 \tabularnewline
155 & 0.583288 & 0.833425 & 0.416712 \tabularnewline
156 & 0.549466 & 0.901069 & 0.450534 \tabularnewline
157 & 0.531834 & 0.936332 & 0.468166 \tabularnewline
158 & 0.498981 & 0.997962 & 0.501019 \tabularnewline
159 & 0.516164 & 0.967673 & 0.483836 \tabularnewline
160 & 0.521846 & 0.956309 & 0.478154 \tabularnewline
161 & 0.546876 & 0.906247 & 0.453124 \tabularnewline
162 & 0.563249 & 0.873503 & 0.436751 \tabularnewline
163 & 0.605292 & 0.789417 & 0.394708 \tabularnewline
164 & 0.598217 & 0.803566 & 0.401783 \tabularnewline
165 & 0.564473 & 0.871055 & 0.435527 \tabularnewline
166 & 0.643048 & 0.713904 & 0.356952 \tabularnewline
167 & 0.611315 & 0.777371 & 0.388685 \tabularnewline
168 & 0.634608 & 0.730784 & 0.365392 \tabularnewline
169 & 0.600844 & 0.798312 & 0.399156 \tabularnewline
170 & 0.611443 & 0.777115 & 0.388557 \tabularnewline
171 & 0.629998 & 0.740004 & 0.370002 \tabularnewline
172 & 0.601779 & 0.796442 & 0.398221 \tabularnewline
173 & 0.604231 & 0.791537 & 0.395769 \tabularnewline
174 & 0.598129 & 0.803742 & 0.401871 \tabularnewline
175 & 0.564516 & 0.870969 & 0.435484 \tabularnewline
176 & 0.530413 & 0.939175 & 0.469587 \tabularnewline
177 & 0.547617 & 0.904766 & 0.452383 \tabularnewline
178 & 0.529165 & 0.94167 & 0.470835 \tabularnewline
179 & 0.521767 & 0.956466 & 0.478233 \tabularnewline
180 & 0.499673 & 0.999346 & 0.500327 \tabularnewline
181 & 0.483146 & 0.966292 & 0.516854 \tabularnewline
182 & 0.518098 & 0.963805 & 0.481902 \tabularnewline
183 & 0.519091 & 0.961819 & 0.480909 \tabularnewline
184 & 0.505213 & 0.989574 & 0.494787 \tabularnewline
185 & 0.495637 & 0.991274 & 0.504363 \tabularnewline
186 & 0.461855 & 0.923711 & 0.538145 \tabularnewline
187 & 0.446947 & 0.893894 & 0.553053 \tabularnewline
188 & 0.43325 & 0.866499 & 0.56675 \tabularnewline
189 & 0.421431 & 0.842863 & 0.578569 \tabularnewline
190 & 0.406137 & 0.812273 & 0.593863 \tabularnewline
191 & 0.429336 & 0.858673 & 0.570664 \tabularnewline
192 & 0.419627 & 0.839255 & 0.580373 \tabularnewline
193 & 0.417883 & 0.835767 & 0.582117 \tabularnewline
194 & 0.405731 & 0.811461 & 0.594269 \tabularnewline
195 & 0.386765 & 0.77353 & 0.613235 \tabularnewline
196 & 0.358195 & 0.71639 & 0.641805 \tabularnewline
197 & 0.326733 & 0.653467 & 0.673267 \tabularnewline
198 & 0.349501 & 0.699001 & 0.650499 \tabularnewline
199 & 0.331354 & 0.662707 & 0.668646 \tabularnewline
200 & 0.31718 & 0.634361 & 0.68282 \tabularnewline
201 & 0.330637 & 0.661274 & 0.669363 \tabularnewline
202 & 0.343934 & 0.687868 & 0.656066 \tabularnewline
203 & 0.378759 & 0.757518 & 0.621241 \tabularnewline
204 & 0.405525 & 0.81105 & 0.594475 \tabularnewline
205 & 0.406404 & 0.812807 & 0.593596 \tabularnewline
206 & 0.44477 & 0.889539 & 0.55523 \tabularnewline
207 & 0.432376 & 0.864751 & 0.567624 \tabularnewline
208 & 0.450659 & 0.901318 & 0.549341 \tabularnewline
209 & 0.495918 & 0.991836 & 0.504082 \tabularnewline
210 & 0.477317 & 0.954633 & 0.522683 \tabularnewline
211 & 0.474007 & 0.948014 & 0.525993 \tabularnewline
212 & 0.434425 & 0.86885 & 0.565575 \tabularnewline
213 & 0.42359 & 0.847181 & 0.57641 \tabularnewline
214 & 0.493448 & 0.986896 & 0.506552 \tabularnewline
215 & 0.480305 & 0.96061 & 0.519695 \tabularnewline
216 & 0.460865 & 0.92173 & 0.539135 \tabularnewline
217 & 0.470255 & 0.94051 & 0.529745 \tabularnewline
218 & 0.466208 & 0.932416 & 0.533792 \tabularnewline
219 & 0.423543 & 0.847087 & 0.576457 \tabularnewline
220 & 0.396396 & 0.792792 & 0.603604 \tabularnewline
221 & 0.371908 & 0.743817 & 0.628092 \tabularnewline
222 & 0.402343 & 0.804686 & 0.597657 \tabularnewline
223 & 0.412768 & 0.825536 & 0.587232 \tabularnewline
224 & 0.373442 & 0.746883 & 0.626558 \tabularnewline
225 & 0.391976 & 0.783952 & 0.608024 \tabularnewline
226 & 0.402952 & 0.805905 & 0.597048 \tabularnewline
227 & 0.37803 & 0.756059 & 0.62197 \tabularnewline
228 & 0.355871 & 0.711742 & 0.644129 \tabularnewline
229 & 0.327921 & 0.655843 & 0.672079 \tabularnewline
230 & 0.309983 & 0.619966 & 0.690017 \tabularnewline
231 & 0.290706 & 0.581413 & 0.709294 \tabularnewline
232 & 0.307708 & 0.615416 & 0.692292 \tabularnewline
233 & 0.371474 & 0.742949 & 0.628526 \tabularnewline
234 & 0.349058 & 0.698115 & 0.650942 \tabularnewline
235 & 0.392327 & 0.784654 & 0.607673 \tabularnewline
236 & 0.382506 & 0.765012 & 0.617494 \tabularnewline
237 & 0.43385 & 0.867699 & 0.56615 \tabularnewline
238 & 0.40937 & 0.81874 & 0.59063 \tabularnewline
239 & 0.386918 & 0.773836 & 0.613082 \tabularnewline
240 & 0.399126 & 0.798251 & 0.600874 \tabularnewline
241 & 0.391247 & 0.782494 & 0.608753 \tabularnewline
242 & 0.42532 & 0.85064 & 0.57468 \tabularnewline
243 & 0.418819 & 0.837637 & 0.581181 \tabularnewline
244 & 0.515473 & 0.969054 & 0.484527 \tabularnewline
245 & 0.644658 & 0.710685 & 0.355342 \tabularnewline
246 & 0.620116 & 0.759767 & 0.379884 \tabularnewline
247 & 0.599321 & 0.801359 & 0.400679 \tabularnewline
248 & 0.551662 & 0.896676 & 0.448338 \tabularnewline
249 & 0.573711 & 0.852578 & 0.426289 \tabularnewline
250 & 0.650456 & 0.699089 & 0.349544 \tabularnewline
251 & 0.750284 & 0.499431 & 0.249716 \tabularnewline
252 & 0.728268 & 0.543463 & 0.271732 \tabularnewline
253 & 0.68407 & 0.631859 & 0.31593 \tabularnewline
254 & 0.695417 & 0.609167 & 0.304583 \tabularnewline
255 & 0.768157 & 0.463685 & 0.231843 \tabularnewline
256 & 0.709711 & 0.580578 & 0.290289 \tabularnewline
257 & 0.646486 & 0.707028 & 0.353514 \tabularnewline
258 & 0.632447 & 0.735106 & 0.367553 \tabularnewline
259 & 0.640085 & 0.719829 & 0.359915 \tabularnewline
260 & 0.56508 & 0.869841 & 0.43492 \tabularnewline
261 & 0.674628 & 0.650745 & 0.325372 \tabularnewline
262 & 0.599674 & 0.800651 & 0.400326 \tabularnewline
263 & 0.512256 & 0.975488 & 0.487744 \tabularnewline
264 & 0.414021 & 0.828042 & 0.585979 \tabularnewline
265 & 0.842271 & 0.315459 & 0.157729 \tabularnewline
266 & 0.765171 & 0.469658 & 0.234829 \tabularnewline
267 & 0.752678 & 0.494643 & 0.247322 \tabularnewline
268 & 0.625669 & 0.748663 & 0.374331 \tabularnewline
269 & 0.456407 & 0.912813 & 0.543593 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266292&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]0.618939[/C][C]0.762121[/C][C]0.381061[/C][/ROW]
[ROW][C]11[/C][C]0.609394[/C][C]0.781212[/C][C]0.390606[/C][/ROW]
[ROW][C]12[/C][C]0.585784[/C][C]0.828432[/C][C]0.414216[/C][/ROW]
[ROW][C]13[/C][C]0.509063[/C][C]0.981874[/C][C]0.490937[/C][/ROW]
[ROW][C]14[/C][C]0.511124[/C][C]0.977751[/C][C]0.488876[/C][/ROW]
[ROW][C]15[/C][C]0.553824[/C][C]0.892352[/C][C]0.446176[/C][/ROW]
[ROW][C]16[/C][C]0.503193[/C][C]0.993614[/C][C]0.496807[/C][/ROW]
[ROW][C]17[/C][C]0.458475[/C][C]0.91695[/C][C]0.541525[/C][/ROW]
[ROW][C]18[/C][C]0.49489[/C][C]0.98978[/C][C]0.50511[/C][/ROW]
[ROW][C]19[/C][C]0.443119[/C][C]0.886239[/C][C]0.556881[/C][/ROW]
[ROW][C]20[/C][C]0.404002[/C][C]0.808004[/C][C]0.595998[/C][/ROW]
[ROW][C]21[/C][C]0.63666[/C][C]0.726679[/C][C]0.36334[/C][/ROW]
[ROW][C]22[/C][C]0.661719[/C][C]0.676562[/C][C]0.338281[/C][/ROW]
[ROW][C]23[/C][C]0.625227[/C][C]0.749545[/C][C]0.374773[/C][/ROW]
[ROW][C]24[/C][C]0.638107[/C][C]0.723786[/C][C]0.361893[/C][/ROW]
[ROW][C]25[/C][C]0.579975[/C][C]0.840051[/C][C]0.420025[/C][/ROW]
[ROW][C]26[/C][C]0.65726[/C][C]0.68548[/C][C]0.34274[/C][/ROW]
[ROW][C]27[/C][C]0.597924[/C][C]0.804151[/C][C]0.402076[/C][/ROW]
[ROW][C]28[/C][C]0.579919[/C][C]0.840163[/C][C]0.420081[/C][/ROW]
[ROW][C]29[/C][C]0.647987[/C][C]0.704026[/C][C]0.352013[/C][/ROW]
[ROW][C]30[/C][C]0.637965[/C][C]0.72407[/C][C]0.362035[/C][/ROW]
[ROW][C]31[/C][C]0.609538[/C][C]0.780924[/C][C]0.390462[/C][/ROW]
[ROW][C]32[/C][C]0.70063[/C][C]0.59874[/C][C]0.29937[/C][/ROW]
[ROW][C]33[/C][C]0.669252[/C][C]0.661497[/C][C]0.330748[/C][/ROW]
[ROW][C]34[/C][C]0.661793[/C][C]0.676414[/C][C]0.338207[/C][/ROW]
[ROW][C]35[/C][C]0.677722[/C][C]0.644555[/C][C]0.322278[/C][/ROW]
[ROW][C]36[/C][C]0.636574[/C][C]0.726852[/C][C]0.363426[/C][/ROW]
[ROW][C]37[/C][C]0.607492[/C][C]0.785016[/C][C]0.392508[/C][/ROW]
[ROW][C]38[/C][C]0.560802[/C][C]0.878396[/C][C]0.439198[/C][/ROW]
[ROW][C]39[/C][C]0.518606[/C][C]0.962787[/C][C]0.481394[/C][/ROW]
[ROW][C]40[/C][C]0.570287[/C][C]0.859425[/C][C]0.429713[/C][/ROW]
[ROW][C]41[/C][C]0.53793[/C][C]0.924141[/C][C]0.46207[/C][/ROW]
[ROW][C]42[/C][C]0.499862[/C][C]0.999723[/C][C]0.500138[/C][/ROW]
[ROW][C]43[/C][C]0.467153[/C][C]0.934307[/C][C]0.532847[/C][/ROW]
[ROW][C]44[/C][C]0.452838[/C][C]0.905676[/C][C]0.547162[/C][/ROW]
[ROW][C]45[/C][C]0.475393[/C][C]0.950786[/C][C]0.524607[/C][/ROW]
[ROW][C]46[/C][C]0.579841[/C][C]0.840317[/C][C]0.420159[/C][/ROW]
[ROW][C]47[/C][C]0.578269[/C][C]0.843462[/C][C]0.421731[/C][/ROW]
[ROW][C]48[/C][C]0.536208[/C][C]0.927585[/C][C]0.463792[/C][/ROW]
[ROW][C]49[/C][C]0.507364[/C][C]0.985272[/C][C]0.492636[/C][/ROW]
[ROW][C]50[/C][C]0.495296[/C][C]0.990591[/C][C]0.504704[/C][/ROW]
[ROW][C]51[/C][C]0.453025[/C][C]0.906049[/C][C]0.546975[/C][/ROW]
[ROW][C]52[/C][C]0.432128[/C][C]0.864255[/C][C]0.567872[/C][/ROW]
[ROW][C]53[/C][C]0.387332[/C][C]0.774663[/C][C]0.612668[/C][/ROW]
[ROW][C]54[/C][C]0.364899[/C][C]0.729798[/C][C]0.635101[/C][/ROW]
[ROW][C]55[/C][C]0.327317[/C][C]0.654635[/C][C]0.672683[/C][/ROW]
[ROW][C]56[/C][C]0.288243[/C][C]0.576487[/C][C]0.711757[/C][/ROW]
[ROW][C]57[/C][C]0.290233[/C][C]0.580466[/C][C]0.709767[/C][/ROW]
[ROW][C]58[/C][C]0.324587[/C][C]0.649174[/C][C]0.675413[/C][/ROW]
[ROW][C]59[/C][C]0.302868[/C][C]0.605737[/C][C]0.697132[/C][/ROW]
[ROW][C]60[/C][C]0.283261[/C][C]0.566522[/C][C]0.716739[/C][/ROW]
[ROW][C]61[/C][C]0.249408[/C][C]0.498816[/C][C]0.750592[/C][/ROW]
[ROW][C]62[/C][C]0.276275[/C][C]0.55255[/C][C]0.723725[/C][/ROW]
[ROW][C]63[/C][C]0.316844[/C][C]0.633689[/C][C]0.683156[/C][/ROW]
[ROW][C]64[/C][C]0.292123[/C][C]0.584247[/C][C]0.707877[/C][/ROW]
[ROW][C]65[/C][C]0.347452[/C][C]0.694903[/C][C]0.652548[/C][/ROW]
[ROW][C]66[/C][C]0.339069[/C][C]0.678139[/C][C]0.660931[/C][/ROW]
[ROW][C]67[/C][C]0.377374[/C][C]0.754748[/C][C]0.622626[/C][/ROW]
[ROW][C]68[/C][C]0.352936[/C][C]0.705873[/C][C]0.647064[/C][/ROW]
[ROW][C]69[/C][C]0.347097[/C][C]0.694194[/C][C]0.652903[/C][/ROW]
[ROW][C]70[/C][C]0.389265[/C][C]0.778531[/C][C]0.610735[/C][/ROW]
[ROW][C]71[/C][C]0.402934[/C][C]0.805868[/C][C]0.597066[/C][/ROW]
[ROW][C]72[/C][C]0.422743[/C][C]0.845485[/C][C]0.577257[/C][/ROW]
[ROW][C]73[/C][C]0.470466[/C][C]0.940933[/C][C]0.529534[/C][/ROW]
[ROW][C]74[/C][C]0.452448[/C][C]0.904897[/C][C]0.547552[/C][/ROW]
[ROW][C]75[/C][C]0.473728[/C][C]0.947456[/C][C]0.526272[/C][/ROW]
[ROW][C]76[/C][C]0.46278[/C][C]0.925559[/C][C]0.53722[/C][/ROW]
[ROW][C]77[/C][C]0.507656[/C][C]0.984687[/C][C]0.492344[/C][/ROW]
[ROW][C]78[/C][C]0.481576[/C][C]0.963151[/C][C]0.518424[/C][/ROW]
[ROW][C]79[/C][C]0.508331[/C][C]0.983337[/C][C]0.491669[/C][/ROW]
[ROW][C]80[/C][C]0.490514[/C][C]0.981029[/C][C]0.509486[/C][/ROW]
[ROW][C]81[/C][C]0.47083[/C][C]0.94166[/C][C]0.52917[/C][/ROW]
[ROW][C]82[/C][C]0.520883[/C][C]0.958234[/C][C]0.479117[/C][/ROW]
[ROW][C]83[/C][C]0.504908[/C][C]0.990185[/C][C]0.495092[/C][/ROW]
[ROW][C]84[/C][C]0.530723[/C][C]0.938554[/C][C]0.469277[/C][/ROW]
[ROW][C]85[/C][C]0.533946[/C][C]0.932108[/C][C]0.466054[/C][/ROW]
[ROW][C]86[/C][C]0.500092[/C][C]0.999815[/C][C]0.499908[/C][/ROW]
[ROW][C]87[/C][C]0.505607[/C][C]0.988785[/C][C]0.494393[/C][/ROW]
[ROW][C]88[/C][C]0.479348[/C][C]0.958697[/C][C]0.520652[/C][/ROW]
[ROW][C]89[/C][C]0.491287[/C][C]0.982573[/C][C]0.508713[/C][/ROW]
[ROW][C]90[/C][C]0.540333[/C][C]0.919335[/C][C]0.459667[/C][/ROW]
[ROW][C]91[/C][C]0.513444[/C][C]0.973113[/C][C]0.486556[/C][/ROW]
[ROW][C]92[/C][C]0.513154[/C][C]0.973692[/C][C]0.486846[/C][/ROW]
[ROW][C]93[/C][C]0.498114[/C][C]0.996228[/C][C]0.501886[/C][/ROW]
[ROW][C]94[/C][C]0.524109[/C][C]0.951782[/C][C]0.475891[/C][/ROW]
[ROW][C]95[/C][C]0.559073[/C][C]0.881854[/C][C]0.440927[/C][/ROW]
[ROW][C]96[/C][C]0.575719[/C][C]0.848561[/C][C]0.424281[/C][/ROW]
[ROW][C]97[/C][C]0.565047[/C][C]0.869906[/C][C]0.434953[/C][/ROW]
[ROW][C]98[/C][C]0.55415[/C][C]0.891699[/C][C]0.44585[/C][/ROW]
[ROW][C]99[/C][C]0.520995[/C][C]0.95801[/C][C]0.479005[/C][/ROW]
[ROW][C]100[/C][C]0.507148[/C][C]0.985705[/C][C]0.492852[/C][/ROW]
[ROW][C]101[/C][C]0.490967[/C][C]0.981934[/C][C]0.509033[/C][/ROW]
[ROW][C]102[/C][C]0.465332[/C][C]0.930663[/C][C]0.534668[/C][/ROW]
[ROW][C]103[/C][C]0.474506[/C][C]0.949011[/C][C]0.525494[/C][/ROW]
[ROW][C]104[/C][C]0.526672[/C][C]0.946655[/C][C]0.473328[/C][/ROW]
[ROW][C]105[/C][C]0.534284[/C][C]0.931432[/C][C]0.465716[/C][/ROW]
[ROW][C]106[/C][C]0.533141[/C][C]0.933718[/C][C]0.466859[/C][/ROW]
[ROW][C]107[/C][C]0.532485[/C][C]0.93503[/C][C]0.467515[/C][/ROW]
[ROW][C]108[/C][C]0.507748[/C][C]0.984504[/C][C]0.492252[/C][/ROW]
[ROW][C]109[/C][C]0.479628[/C][C]0.959257[/C][C]0.520372[/C][/ROW]
[ROW][C]110[/C][C]0.477128[/C][C]0.954256[/C][C]0.522872[/C][/ROW]
[ROW][C]111[/C][C]0.474041[/C][C]0.948081[/C][C]0.525959[/C][/ROW]
[ROW][C]112[/C][C]0.476538[/C][C]0.953075[/C][C]0.523462[/C][/ROW]
[ROW][C]113[/C][C]0.497754[/C][C]0.995508[/C][C]0.502246[/C][/ROW]
[ROW][C]114[/C][C]0.468675[/C][C]0.937349[/C][C]0.531325[/C][/ROW]
[ROW][C]115[/C][C]0.43442[/C][C]0.86884[/C][C]0.56558[/C][/ROW]
[ROW][C]116[/C][C]0.401553[/C][C]0.803105[/C][C]0.598447[/C][/ROW]
[ROW][C]117[/C][C]0.368081[/C][C]0.736162[/C][C]0.631919[/C][/ROW]
[ROW][C]118[/C][C]0.397893[/C][C]0.795786[/C][C]0.602107[/C][/ROW]
[ROW][C]119[/C][C]0.407028[/C][C]0.814057[/C][C]0.592972[/C][/ROW]
[ROW][C]120[/C][C]0.406734[/C][C]0.813468[/C][C]0.593266[/C][/ROW]
[ROW][C]121[/C][C]0.516856[/C][C]0.966287[/C][C]0.483144[/C][/ROW]
[ROW][C]122[/C][C]0.519121[/C][C]0.961758[/C][C]0.480879[/C][/ROW]
[ROW][C]123[/C][C]0.529468[/C][C]0.941064[/C][C]0.470532[/C][/ROW]
[ROW][C]124[/C][C]0.525423[/C][C]0.949155[/C][C]0.474577[/C][/ROW]
[ROW][C]125[/C][C]0.534194[/C][C]0.931612[/C][C]0.465806[/C][/ROW]
[ROW][C]126[/C][C]0.541388[/C][C]0.917223[/C][C]0.458612[/C][/ROW]
[ROW][C]127[/C][C]0.564083[/C][C]0.871834[/C][C]0.435917[/C][/ROW]
[ROW][C]128[/C][C]0.567249[/C][C]0.865501[/C][C]0.432751[/C][/ROW]
[ROW][C]129[/C][C]0.576654[/C][C]0.846692[/C][C]0.423346[/C][/ROW]
[ROW][C]130[/C][C]0.5589[/C][C]0.8822[/C][C]0.4411[/C][/ROW]
[ROW][C]131[/C][C]0.531059[/C][C]0.937882[/C][C]0.468941[/C][/ROW]
[ROW][C]132[/C][C]0.497488[/C][C]0.994976[/C][C]0.502512[/C][/ROW]
[ROW][C]133[/C][C]0.524208[/C][C]0.951584[/C][C]0.475792[/C][/ROW]
[ROW][C]134[/C][C]0.53724[/C][C]0.92552[/C][C]0.46276[/C][/ROW]
[ROW][C]135[/C][C]0.539606[/C][C]0.920788[/C][C]0.460394[/C][/ROW]
[ROW][C]136[/C][C]0.504922[/C][C]0.990155[/C][C]0.495078[/C][/ROW]
[ROW][C]137[/C][C]0.54117[/C][C]0.917659[/C][C]0.45883[/C][/ROW]
[ROW][C]138[/C][C]0.508827[/C][C]0.982347[/C][C]0.491173[/C][/ROW]
[ROW][C]139[/C][C]0.506569[/C][C]0.986863[/C][C]0.493431[/C][/ROW]
[ROW][C]140[/C][C]0.51901[/C][C]0.961981[/C][C]0.48099[/C][/ROW]
[ROW][C]141[/C][C]0.499376[/C][C]0.998751[/C][C]0.500624[/C][/ROW]
[ROW][C]142[/C][C]0.470518[/C][C]0.941036[/C][C]0.529482[/C][/ROW]
[ROW][C]143[/C][C]0.445705[/C][C]0.89141[/C][C]0.554295[/C][/ROW]
[ROW][C]144[/C][C]0.496634[/C][C]0.993268[/C][C]0.503366[/C][/ROW]
[ROW][C]145[/C][C]0.476756[/C][C]0.953513[/C][C]0.523244[/C][/ROW]
[ROW][C]146[/C][C]0.544956[/C][C]0.910089[/C][C]0.455044[/C][/ROW]
[ROW][C]147[/C][C]0.548113[/C][C]0.903774[/C][C]0.451887[/C][/ROW]
[ROW][C]148[/C][C]0.587177[/C][C]0.825646[/C][C]0.412823[/C][/ROW]
[ROW][C]149[/C][C]0.609803[/C][C]0.780393[/C][C]0.390197[/C][/ROW]
[ROW][C]150[/C][C]0.611951[/C][C]0.776099[/C][C]0.388049[/C][/ROW]
[ROW][C]151[/C][C]0.580061[/C][C]0.839879[/C][C]0.419939[/C][/ROW]
[ROW][C]152[/C][C]0.586045[/C][C]0.82791[/C][C]0.413955[/C][/ROW]
[ROW][C]153[/C][C]0.554878[/C][C]0.890244[/C][C]0.445122[/C][/ROW]
[ROW][C]154[/C][C]0.583213[/C][C]0.833574[/C][C]0.416787[/C][/ROW]
[ROW][C]155[/C][C]0.583288[/C][C]0.833425[/C][C]0.416712[/C][/ROW]
[ROW][C]156[/C][C]0.549466[/C][C]0.901069[/C][C]0.450534[/C][/ROW]
[ROW][C]157[/C][C]0.531834[/C][C]0.936332[/C][C]0.468166[/C][/ROW]
[ROW][C]158[/C][C]0.498981[/C][C]0.997962[/C][C]0.501019[/C][/ROW]
[ROW][C]159[/C][C]0.516164[/C][C]0.967673[/C][C]0.483836[/C][/ROW]
[ROW][C]160[/C][C]0.521846[/C][C]0.956309[/C][C]0.478154[/C][/ROW]
[ROW][C]161[/C][C]0.546876[/C][C]0.906247[/C][C]0.453124[/C][/ROW]
[ROW][C]162[/C][C]0.563249[/C][C]0.873503[/C][C]0.436751[/C][/ROW]
[ROW][C]163[/C][C]0.605292[/C][C]0.789417[/C][C]0.394708[/C][/ROW]
[ROW][C]164[/C][C]0.598217[/C][C]0.803566[/C][C]0.401783[/C][/ROW]
[ROW][C]165[/C][C]0.564473[/C][C]0.871055[/C][C]0.435527[/C][/ROW]
[ROW][C]166[/C][C]0.643048[/C][C]0.713904[/C][C]0.356952[/C][/ROW]
[ROW][C]167[/C][C]0.611315[/C][C]0.777371[/C][C]0.388685[/C][/ROW]
[ROW][C]168[/C][C]0.634608[/C][C]0.730784[/C][C]0.365392[/C][/ROW]
[ROW][C]169[/C][C]0.600844[/C][C]0.798312[/C][C]0.399156[/C][/ROW]
[ROW][C]170[/C][C]0.611443[/C][C]0.777115[/C][C]0.388557[/C][/ROW]
[ROW][C]171[/C][C]0.629998[/C][C]0.740004[/C][C]0.370002[/C][/ROW]
[ROW][C]172[/C][C]0.601779[/C][C]0.796442[/C][C]0.398221[/C][/ROW]
[ROW][C]173[/C][C]0.604231[/C][C]0.791537[/C][C]0.395769[/C][/ROW]
[ROW][C]174[/C][C]0.598129[/C][C]0.803742[/C][C]0.401871[/C][/ROW]
[ROW][C]175[/C][C]0.564516[/C][C]0.870969[/C][C]0.435484[/C][/ROW]
[ROW][C]176[/C][C]0.530413[/C][C]0.939175[/C][C]0.469587[/C][/ROW]
[ROW][C]177[/C][C]0.547617[/C][C]0.904766[/C][C]0.452383[/C][/ROW]
[ROW][C]178[/C][C]0.529165[/C][C]0.94167[/C][C]0.470835[/C][/ROW]
[ROW][C]179[/C][C]0.521767[/C][C]0.956466[/C][C]0.478233[/C][/ROW]
[ROW][C]180[/C][C]0.499673[/C][C]0.999346[/C][C]0.500327[/C][/ROW]
[ROW][C]181[/C][C]0.483146[/C][C]0.966292[/C][C]0.516854[/C][/ROW]
[ROW][C]182[/C][C]0.518098[/C][C]0.963805[/C][C]0.481902[/C][/ROW]
[ROW][C]183[/C][C]0.519091[/C][C]0.961819[/C][C]0.480909[/C][/ROW]
[ROW][C]184[/C][C]0.505213[/C][C]0.989574[/C][C]0.494787[/C][/ROW]
[ROW][C]185[/C][C]0.495637[/C][C]0.991274[/C][C]0.504363[/C][/ROW]
[ROW][C]186[/C][C]0.461855[/C][C]0.923711[/C][C]0.538145[/C][/ROW]
[ROW][C]187[/C][C]0.446947[/C][C]0.893894[/C][C]0.553053[/C][/ROW]
[ROW][C]188[/C][C]0.43325[/C][C]0.866499[/C][C]0.56675[/C][/ROW]
[ROW][C]189[/C][C]0.421431[/C][C]0.842863[/C][C]0.578569[/C][/ROW]
[ROW][C]190[/C][C]0.406137[/C][C]0.812273[/C][C]0.593863[/C][/ROW]
[ROW][C]191[/C][C]0.429336[/C][C]0.858673[/C][C]0.570664[/C][/ROW]
[ROW][C]192[/C][C]0.419627[/C][C]0.839255[/C][C]0.580373[/C][/ROW]
[ROW][C]193[/C][C]0.417883[/C][C]0.835767[/C][C]0.582117[/C][/ROW]
[ROW][C]194[/C][C]0.405731[/C][C]0.811461[/C][C]0.594269[/C][/ROW]
[ROW][C]195[/C][C]0.386765[/C][C]0.77353[/C][C]0.613235[/C][/ROW]
[ROW][C]196[/C][C]0.358195[/C][C]0.71639[/C][C]0.641805[/C][/ROW]
[ROW][C]197[/C][C]0.326733[/C][C]0.653467[/C][C]0.673267[/C][/ROW]
[ROW][C]198[/C][C]0.349501[/C][C]0.699001[/C][C]0.650499[/C][/ROW]
[ROW][C]199[/C][C]0.331354[/C][C]0.662707[/C][C]0.668646[/C][/ROW]
[ROW][C]200[/C][C]0.31718[/C][C]0.634361[/C][C]0.68282[/C][/ROW]
[ROW][C]201[/C][C]0.330637[/C][C]0.661274[/C][C]0.669363[/C][/ROW]
[ROW][C]202[/C][C]0.343934[/C][C]0.687868[/C][C]0.656066[/C][/ROW]
[ROW][C]203[/C][C]0.378759[/C][C]0.757518[/C][C]0.621241[/C][/ROW]
[ROW][C]204[/C][C]0.405525[/C][C]0.81105[/C][C]0.594475[/C][/ROW]
[ROW][C]205[/C][C]0.406404[/C][C]0.812807[/C][C]0.593596[/C][/ROW]
[ROW][C]206[/C][C]0.44477[/C][C]0.889539[/C][C]0.55523[/C][/ROW]
[ROW][C]207[/C][C]0.432376[/C][C]0.864751[/C][C]0.567624[/C][/ROW]
[ROW][C]208[/C][C]0.450659[/C][C]0.901318[/C][C]0.549341[/C][/ROW]
[ROW][C]209[/C][C]0.495918[/C][C]0.991836[/C][C]0.504082[/C][/ROW]
[ROW][C]210[/C][C]0.477317[/C][C]0.954633[/C][C]0.522683[/C][/ROW]
[ROW][C]211[/C][C]0.474007[/C][C]0.948014[/C][C]0.525993[/C][/ROW]
[ROW][C]212[/C][C]0.434425[/C][C]0.86885[/C][C]0.565575[/C][/ROW]
[ROW][C]213[/C][C]0.42359[/C][C]0.847181[/C][C]0.57641[/C][/ROW]
[ROW][C]214[/C][C]0.493448[/C][C]0.986896[/C][C]0.506552[/C][/ROW]
[ROW][C]215[/C][C]0.480305[/C][C]0.96061[/C][C]0.519695[/C][/ROW]
[ROW][C]216[/C][C]0.460865[/C][C]0.92173[/C][C]0.539135[/C][/ROW]
[ROW][C]217[/C][C]0.470255[/C][C]0.94051[/C][C]0.529745[/C][/ROW]
[ROW][C]218[/C][C]0.466208[/C][C]0.932416[/C][C]0.533792[/C][/ROW]
[ROW][C]219[/C][C]0.423543[/C][C]0.847087[/C][C]0.576457[/C][/ROW]
[ROW][C]220[/C][C]0.396396[/C][C]0.792792[/C][C]0.603604[/C][/ROW]
[ROW][C]221[/C][C]0.371908[/C][C]0.743817[/C][C]0.628092[/C][/ROW]
[ROW][C]222[/C][C]0.402343[/C][C]0.804686[/C][C]0.597657[/C][/ROW]
[ROW][C]223[/C][C]0.412768[/C][C]0.825536[/C][C]0.587232[/C][/ROW]
[ROW][C]224[/C][C]0.373442[/C][C]0.746883[/C][C]0.626558[/C][/ROW]
[ROW][C]225[/C][C]0.391976[/C][C]0.783952[/C][C]0.608024[/C][/ROW]
[ROW][C]226[/C][C]0.402952[/C][C]0.805905[/C][C]0.597048[/C][/ROW]
[ROW][C]227[/C][C]0.37803[/C][C]0.756059[/C][C]0.62197[/C][/ROW]
[ROW][C]228[/C][C]0.355871[/C][C]0.711742[/C][C]0.644129[/C][/ROW]
[ROW][C]229[/C][C]0.327921[/C][C]0.655843[/C][C]0.672079[/C][/ROW]
[ROW][C]230[/C][C]0.309983[/C][C]0.619966[/C][C]0.690017[/C][/ROW]
[ROW][C]231[/C][C]0.290706[/C][C]0.581413[/C][C]0.709294[/C][/ROW]
[ROW][C]232[/C][C]0.307708[/C][C]0.615416[/C][C]0.692292[/C][/ROW]
[ROW][C]233[/C][C]0.371474[/C][C]0.742949[/C][C]0.628526[/C][/ROW]
[ROW][C]234[/C][C]0.349058[/C][C]0.698115[/C][C]0.650942[/C][/ROW]
[ROW][C]235[/C][C]0.392327[/C][C]0.784654[/C][C]0.607673[/C][/ROW]
[ROW][C]236[/C][C]0.382506[/C][C]0.765012[/C][C]0.617494[/C][/ROW]
[ROW][C]237[/C][C]0.43385[/C][C]0.867699[/C][C]0.56615[/C][/ROW]
[ROW][C]238[/C][C]0.40937[/C][C]0.81874[/C][C]0.59063[/C][/ROW]
[ROW][C]239[/C][C]0.386918[/C][C]0.773836[/C][C]0.613082[/C][/ROW]
[ROW][C]240[/C][C]0.399126[/C][C]0.798251[/C][C]0.600874[/C][/ROW]
[ROW][C]241[/C][C]0.391247[/C][C]0.782494[/C][C]0.608753[/C][/ROW]
[ROW][C]242[/C][C]0.42532[/C][C]0.85064[/C][C]0.57468[/C][/ROW]
[ROW][C]243[/C][C]0.418819[/C][C]0.837637[/C][C]0.581181[/C][/ROW]
[ROW][C]244[/C][C]0.515473[/C][C]0.969054[/C][C]0.484527[/C][/ROW]
[ROW][C]245[/C][C]0.644658[/C][C]0.710685[/C][C]0.355342[/C][/ROW]
[ROW][C]246[/C][C]0.620116[/C][C]0.759767[/C][C]0.379884[/C][/ROW]
[ROW][C]247[/C][C]0.599321[/C][C]0.801359[/C][C]0.400679[/C][/ROW]
[ROW][C]248[/C][C]0.551662[/C][C]0.896676[/C][C]0.448338[/C][/ROW]
[ROW][C]249[/C][C]0.573711[/C][C]0.852578[/C][C]0.426289[/C][/ROW]
[ROW][C]250[/C][C]0.650456[/C][C]0.699089[/C][C]0.349544[/C][/ROW]
[ROW][C]251[/C][C]0.750284[/C][C]0.499431[/C][C]0.249716[/C][/ROW]
[ROW][C]252[/C][C]0.728268[/C][C]0.543463[/C][C]0.271732[/C][/ROW]
[ROW][C]253[/C][C]0.68407[/C][C]0.631859[/C][C]0.31593[/C][/ROW]
[ROW][C]254[/C][C]0.695417[/C][C]0.609167[/C][C]0.304583[/C][/ROW]
[ROW][C]255[/C][C]0.768157[/C][C]0.463685[/C][C]0.231843[/C][/ROW]
[ROW][C]256[/C][C]0.709711[/C][C]0.580578[/C][C]0.290289[/C][/ROW]
[ROW][C]257[/C][C]0.646486[/C][C]0.707028[/C][C]0.353514[/C][/ROW]
[ROW][C]258[/C][C]0.632447[/C][C]0.735106[/C][C]0.367553[/C][/ROW]
[ROW][C]259[/C][C]0.640085[/C][C]0.719829[/C][C]0.359915[/C][/ROW]
[ROW][C]260[/C][C]0.56508[/C][C]0.869841[/C][C]0.43492[/C][/ROW]
[ROW][C]261[/C][C]0.674628[/C][C]0.650745[/C][C]0.325372[/C][/ROW]
[ROW][C]262[/C][C]0.599674[/C][C]0.800651[/C][C]0.400326[/C][/ROW]
[ROW][C]263[/C][C]0.512256[/C][C]0.975488[/C][C]0.487744[/C][/ROW]
[ROW][C]264[/C][C]0.414021[/C][C]0.828042[/C][C]0.585979[/C][/ROW]
[ROW][C]265[/C][C]0.842271[/C][C]0.315459[/C][C]0.157729[/C][/ROW]
[ROW][C]266[/C][C]0.765171[/C][C]0.469658[/C][C]0.234829[/C][/ROW]
[ROW][C]267[/C][C]0.752678[/C][C]0.494643[/C][C]0.247322[/C][/ROW]
[ROW][C]268[/C][C]0.625669[/C][C]0.748663[/C][C]0.374331[/C][/ROW]
[ROW][C]269[/C][C]0.456407[/C][C]0.912813[/C][C]0.543593[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266292&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266292&T=5

As an alternative you can also use a QR Code:  
QR Code


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.6189390.7621210.381061
110.6093940.7812120.390606
120.5857840.8284320.414216
130.5090630.9818740.490937
140.5111240.9777510.488876
150.5538240.8923520.446176
160.5031930.9936140.496807
170.4584750.916950.541525
180.494890.989780.50511
190.4431190.8862390.556881
200.4040020.8080040.595998
210.636660.7266790.36334
220.6617190.6765620.338281
230.6252270.7495450.374773
240.6381070.7237860.361893
250.5799750.8400510.420025
260.657260.685480.34274
270.5979240.8041510.402076
280.5799190.8401630.420081
290.6479870.7040260.352013
300.6379650.724070.362035
310.6095380.7809240.390462
320.700630.598740.29937
330.6692520.6614970.330748
340.6617930.6764140.338207
350.6777220.6445550.322278
360.6365740.7268520.363426
370.6074920.7850160.392508
380.5608020.8783960.439198
390.5186060.9627870.481394
400.5702870.8594250.429713
410.537930.9241410.46207
420.4998620.9997230.500138
430.4671530.9343070.532847
440.4528380.9056760.547162
450.4753930.9507860.524607
460.5798410.8403170.420159
470.5782690.8434620.421731
480.5362080.9275850.463792
490.5073640.9852720.492636
500.4952960.9905910.504704
510.4530250.9060490.546975
520.4321280.8642550.567872
530.3873320.7746630.612668
540.3648990.7297980.635101
550.3273170.6546350.672683
560.2882430.5764870.711757
570.2902330.5804660.709767
580.3245870.6491740.675413
590.3028680.6057370.697132
600.2832610.5665220.716739
610.2494080.4988160.750592
620.2762750.552550.723725
630.3168440.6336890.683156
640.2921230.5842470.707877
650.3474520.6949030.652548
660.3390690.6781390.660931
670.3773740.7547480.622626
680.3529360.7058730.647064
690.3470970.6941940.652903
700.3892650.7785310.610735
710.4029340.8058680.597066
720.4227430.8454850.577257
730.4704660.9409330.529534
740.4524480.9048970.547552
750.4737280.9474560.526272
760.462780.9255590.53722
770.5076560.9846870.492344
780.4815760.9631510.518424
790.5083310.9833370.491669
800.4905140.9810290.509486
810.470830.941660.52917
820.5208830.9582340.479117
830.5049080.9901850.495092
840.5307230.9385540.469277
850.5339460.9321080.466054
860.5000920.9998150.499908
870.5056070.9887850.494393
880.4793480.9586970.520652
890.4912870.9825730.508713
900.5403330.9193350.459667
910.5134440.9731130.486556
920.5131540.9736920.486846
930.4981140.9962280.501886
940.5241090.9517820.475891
950.5590730.8818540.440927
960.5757190.8485610.424281
970.5650470.8699060.434953
980.554150.8916990.44585
990.5209950.958010.479005
1000.5071480.9857050.492852
1010.4909670.9819340.509033
1020.4653320.9306630.534668
1030.4745060.9490110.525494
1040.5266720.9466550.473328
1050.5342840.9314320.465716
1060.5331410.9337180.466859
1070.5324850.935030.467515
1080.5077480.9845040.492252
1090.4796280.9592570.520372
1100.4771280.9542560.522872
1110.4740410.9480810.525959
1120.4765380.9530750.523462
1130.4977540.9955080.502246
1140.4686750.9373490.531325
1150.434420.868840.56558
1160.4015530.8031050.598447
1170.3680810.7361620.631919
1180.3978930.7957860.602107
1190.4070280.8140570.592972
1200.4067340.8134680.593266
1210.5168560.9662870.483144
1220.5191210.9617580.480879
1230.5294680.9410640.470532
1240.5254230.9491550.474577
1250.5341940.9316120.465806
1260.5413880.9172230.458612
1270.5640830.8718340.435917
1280.5672490.8655010.432751
1290.5766540.8466920.423346
1300.55890.88220.4411
1310.5310590.9378820.468941
1320.4974880.9949760.502512
1330.5242080.9515840.475792
1340.537240.925520.46276
1350.5396060.9207880.460394
1360.5049220.9901550.495078
1370.541170.9176590.45883
1380.5088270.9823470.491173
1390.5065690.9868630.493431
1400.519010.9619810.48099
1410.4993760.9987510.500624
1420.4705180.9410360.529482
1430.4457050.891410.554295
1440.4966340.9932680.503366
1450.4767560.9535130.523244
1460.5449560.9100890.455044
1470.5481130.9037740.451887
1480.5871770.8256460.412823
1490.6098030.7803930.390197
1500.6119510.7760990.388049
1510.5800610.8398790.419939
1520.5860450.827910.413955
1530.5548780.8902440.445122
1540.5832130.8335740.416787
1550.5832880.8334250.416712
1560.5494660.9010690.450534
1570.5318340.9363320.468166
1580.4989810.9979620.501019
1590.5161640.9676730.483836
1600.5218460.9563090.478154
1610.5468760.9062470.453124
1620.5632490.8735030.436751
1630.6052920.7894170.394708
1640.5982170.8035660.401783
1650.5644730.8710550.435527
1660.6430480.7139040.356952
1670.6113150.7773710.388685
1680.6346080.7307840.365392
1690.6008440.7983120.399156
1700.6114430.7771150.388557
1710.6299980.7400040.370002
1720.6017790.7964420.398221
1730.6042310.7915370.395769
1740.5981290.8037420.401871
1750.5645160.8709690.435484
1760.5304130.9391750.469587
1770.5476170.9047660.452383
1780.5291650.941670.470835
1790.5217670.9564660.478233
1800.4996730.9993460.500327
1810.4831460.9662920.516854
1820.5180980.9638050.481902
1830.5190910.9618190.480909
1840.5052130.9895740.494787
1850.4956370.9912740.504363
1860.4618550.9237110.538145
1870.4469470.8938940.553053
1880.433250.8664990.56675
1890.4214310.8428630.578569
1900.4061370.8122730.593863
1910.4293360.8586730.570664
1920.4196270.8392550.580373
1930.4178830.8357670.582117
1940.4057310.8114610.594269
1950.3867650.773530.613235
1960.3581950.716390.641805
1970.3267330.6534670.673267
1980.3495010.6990010.650499
1990.3313540.6627070.668646
2000.317180.6343610.68282
2010.3306370.6612740.669363
2020.3439340.6878680.656066
2030.3787590.7575180.621241
2040.4055250.811050.594475
2050.4064040.8128070.593596
2060.444770.8895390.55523
2070.4323760.8647510.567624
2080.4506590.9013180.549341
2090.4959180.9918360.504082
2100.4773170.9546330.522683
2110.4740070.9480140.525993
2120.4344250.868850.565575
2130.423590.8471810.57641
2140.4934480.9868960.506552
2150.4803050.960610.519695
2160.4608650.921730.539135
2170.4702550.940510.529745
2180.4662080.9324160.533792
2190.4235430.8470870.576457
2200.3963960.7927920.603604
2210.3719080.7438170.628092
2220.4023430.8046860.597657
2230.4127680.8255360.587232
2240.3734420.7468830.626558
2250.3919760.7839520.608024
2260.4029520.8059050.597048
2270.378030.7560590.62197
2280.3558710.7117420.644129
2290.3279210.6558430.672079
2300.3099830.6199660.690017
2310.2907060.5814130.709294
2320.3077080.6154160.692292
2330.3714740.7429490.628526
2340.3490580.6981150.650942
2350.3923270.7846540.607673
2360.3825060.7650120.617494
2370.433850.8676990.56615
2380.409370.818740.59063
2390.3869180.7738360.613082
2400.3991260.7982510.600874
2410.3912470.7824940.608753
2420.425320.850640.57468
2430.4188190.8376370.581181
2440.5154730.9690540.484527
2450.6446580.7106850.355342
2460.6201160.7597670.379884
2470.5993210.8013590.400679
2480.5516620.8966760.448338
2490.5737110.8525780.426289
2500.6504560.6990890.349544
2510.7502840.4994310.249716
2520.7282680.5434630.271732
2530.684070.6318590.31593
2540.6954170.6091670.304583
2550.7681570.4636850.231843
2560.7097110.5805780.290289
2570.6464860.7070280.353514
2580.6324470.7351060.367553
2590.6400850.7198290.359915
2600.565080.8698410.43492
2610.6746280.6507450.325372
2620.5996740.8006510.400326
2630.5122560.9754880.487744
2640.4140210.8280420.585979
2650.8422710.3154590.157729
2660.7651710.4696580.234829
2670.7526780.4946430.247322
2680.6256690.7486630.374331
2690.4564070.9128130.543593






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level00OK

\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 & 0 & 0 & OK \tabularnewline
10% type I error level & 0 & 0 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266292&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266292&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266292&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level00OK


Figures (Output of Computation)

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Input Parameters & R Code

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')
}