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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 computationSun, 17 Nov 2013 12:29:19 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/17/t1384709378xl92tm3boh4v6n7.htm/, Retrieved Mon, 29 Apr 2024 07:24:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=225831, Retrieved Mon, 29 Apr 2024 07:24:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [time effect in su...] [2010-11-17 08:55:33] [b98453cac15ba1066b407e146608df68]
- RMPD    [Multiple Regression] [WS 7] [2013-11-17 17:29:19] [964acef360ea028b18952da197fdc0b8] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
38 12 14 12 53 32 9 41
32 11 18 11 83 51 9 39
35 15 11 14 66 42 9 30
33 6 12 12 67 41 9 31
37 13 16 21 76 46 9 34
29 10 18 12 78 47 9 35
31 12 14 22 53 37 9 39
36 14 14 11 80 49 9 34
35 12 15 10 74 45 9 36
38 9 15 13 76 47 9 37
31 10 17 10 79 49 9 38
34 12 19 8 54 33 9 36
35 12 10 15 67 42 9 38
38 11 16 14 54 33 9 39
37 15 18 10 87 53 9 33
33 12 14 14 58 36 9 32
32 10 14 14 75 45 9 36
38 12 17 11 88 54 9 38
38 11 14 10 64 41 9 39
32 12 16 13 57 36 9 32
33 11 18 9.5 66 41 9 32
31 12 11 14 68 44 9 31
38 13 14 12 54 33 9 39
39 11 12 14 56 37 9 37
32 12 17 11 86 52 9 39
32 13 9 9 80 47 9 41
35 10 16 11 76 43 9 36
37 14 14 15 69 44 9 33
33 12 15 14 78 45 9 33
33 10 11 13 67 44 9 34
31 12 16 9 80 49 9 31
32 8 13 15 54 33 9 27
31 10 17 10 71 43 9 37
37 12 15 11 84 54 9 34
30 12 14 13 74 42 9 34
33 7 16 8 71 44 9 32
31 9 9 20 63 37 9 29
33 12 15 12 71 43 9 36
31 10 17 10 76 46 9 29
33 10 13 10 69 42 9 35
32 10 15 9 74 45 9 37
33 12 16 14 75 44 9 34
32 15 16 8 54 33 9 38
33 10 12 14 52 31 9 35
28 10 15 11 69 42 9 38
35 12 11 13 68 40 9 37
39 13 15 9 65 43 9 38
34 11 15 11 75 46 9 33
38 11 17 15 74 42 9 36
32 12 13 11 75 45 9 38
38 14 16 10 72 44 9 32
30 10 14 14 67 40 9 32
33 12 11 18 63 37 9 32
38 13 12 14 62 46 9 34
32 5 12 11 63 36 9 32
35 6 15 14.5 76 47 9 37
34 12 16 13 74 45 9 39
34 12 15 9 67 42 9 29
36 11 12 10 73 43 9 37
34 10 12 15 70 43 9 35
28 7 8 20 53 32 9 30
34 12 13 12 77 45 9 38
35 14 11 12 80 48 9 34
35 11 14 14 52 31 9 31
31 12 15 13 54 33 9 34
37 13 10 11 80 49 10 35
35 14 11 17 66 42 10 36
27 11 12 12 73 41 10 30
40 12 15 13 63 38 10 39
37 12 15 14 69 42 10 35
36 8 14 13 67 44 10 38
38 11 16 15 54 33 10 31
39 14 15 13 81 48 10 34
41 14 15 10 69 40 10 38
27 12 13 11 84 50 10 34
30 9 12 19 80 49 10 39
37 13 17 13 70 43 10 37
31 11 13 17 69 44 10 34
31 12 15 13 77 47 10 28
27 12 13 9 54 33 10 37
36 12 15 11 79 46 10 33
37 12 15 9 71 45 10 35
33 12 16 12 73 43 10 37
34 11 15 12 72 44 10 32
31 10 14 13 77 47 10 33
39 9 15 13 75 45 10 38
34 12 14 12 69 42 10 33
32 12 13 15 54 33 10 29
33 12 7 22 70 43 10 33
36 9 17 13 73 46 10 31
32 15 13 15 54 33 10 36
41 12 15 13 77 46 10 35
28 12 14 15 82 48 10 32
30 12 13 12.5 80 47 10 29
36 10 16 11 80 47 10 39
35 13 12 16 69 43 10 37
31 9 14 11 78 46 10 35
34 12 17 11 81 48 10 37
36 10 15 10 76 46 10 32
36 14 17 10 76 45 10 38
35 11 12 16 73 45 10 37
37 15 16 12 85 52 10 36
28 11 11 11 66 42 10 32
39 11 15 16 79 47 10 33
32 12 9 19 68 41 10 40
35 12 16 11 76 47 10 38
39 12 15 16 71 43 10 41
35 11 10 15 54 33 10 36
42 7 10 24 46 30 10 43
34 12 15 14 85 52 10 30
33 14 11 15 74 44 10 31
41 11 13 11 88 55 10 32
33 11 14 15 38 11 10 32
34 10 18 12 76 47 10 37
32 13 16 10 86 53 10 37
40 13 14 14 54 33 10 33
40 8 14 13 67 44 10 34
35 11 14 9 69 42 10 33
36 12 14 15 90 55 10 38
37 11 12 15 54 33 10 33
27 13 14 14 76 46 10 31
39 12 15 11 89 54 10 38
38 14 15 8 76 47 10 37
31 13 15 11 73 45 10 36
33 15 13 11 79 47 10 31
32 10 17 8 90 55 10 39
39 11 17 10 74 44 10 44
36 9 19 11 81 53 10 33
33 11 15 13 72 44 10 35
33 10 13 11 71 42 10 32
32 11 9 20 66 40 10 28
37 8 15 10 77 46 10 40
30 11 15 15 65 40 10 27
38 12 15 12 74 46 10 37
29 12 16 14 85 53 10 32
22 9 11 23 54 33 10 28
35 11 14 14 63 42 10 34
35 10 11 16 54 35 10 30
34 8 15 11 64 40 10 35
35 9 13 12 69 41 10 31
34 8 15 10 54 33 10 32
37 9 16 14 84 51 10 30
35 15 14 12 86 53 10 30
23 11 15 12 77 46 10 31
31 8 16 11 89 55 10 40
27 13 16 12 76 47 10 32
36 12 11 13 60 38 10 36
31 12 12 11 75 46 10 32
32 9 9 19 73 46 10 35
39 7 16 12 85 53 10 38
37 13 13 17 79 47 10 42
38 9 16 9 71 41 10 34
39 6 12 12 72 44 10 35
34 8 9 19 69 43 9 38
31 8 13 18 78 51 10 33
32 15 13 15 54 33 10 36
37 6 14 14 69 43 10 32
36 9 19 11 81 53 10 33
32 11 13 9 84 51 10 34
38 8 12 18 84 50 10 32
36 8 13 16 69 46 10 34
26 10 10 24 66 43 11 27
26 8 14 14 81 47 11 31
33 14 16 20 82 50 11 38
39 10 10 18 72 43 11 34
30 8 11 23 54 33 11 24
33 11 14 12 78 48 11 30
25 12 12 14 74 44 11 26
38 12 9 16 82 50 11 34
37 12 9 18 73 41 11 27
31 5 11 20 55 34 11 37
37 12 16 12 72 44 11 36
35 10 9 12 78 47 11 41
25 7 13 17 59 35 11 29
28 12 16 13 72 44 11 36
35 11 13 9 78 44 11 32
33 8 9 16 68 43 11 37
30 9 12 18 69 41 11 30
31 10 16 10 67 41 11 31
37 9 11 14 74 42 11 38
36 12 14 11 54 33 11 36
30 6 13 9 67 41 11 35
36 15 15 11 70 44 11 31
32 12 14 10 80 48 11 38
28 12 16 11 89 55 11 22
36 12 13 19 76 44 11 32
34 11 14 14 74 43 11 36
31 7 15 12 87 52 11 39
28 7 13 14 54 30 11 28
36 5 11 21 61 39 11 32
36 12 11 13 38 11 11 32
40 12 14 10 75 44 11 38
33 3 15 15 69 42 11 32
37 11 11 16 62 41 11 35
32 10 15 14 72 44 11 32
38 12 12 12 70 44 11 37
31 9 14 19 79 48 11 34
37 12 14 15 87 53 11 33
33 9 8 19 62 37 11 33
32 12 13 13 77 44 11 26
30 12 9 17 69 44 11 30
30 10 15 12 69 40 11 24
31 9 17 11 75 42 11 34
32 12 13 14 54 35 11 34
34 8 15 11 72 43 11 33
36 11 15 13 74 45 11 34
37 11 14 12 85 55 11 35
36 12 16 15 52 31 11 35
33 10 13 14 70 44 11 36
33 10 16 12 84 50 11 34
33 12 9 17 64 40 11 34
44 12 16 11 84 53 11 41
39 11 11 18 87 54 11 32
32 8 10 13 79 49 11 30
35 12 11 17 67 40 11 35
25 10 15 13 65 41 11 28
35 11 17 11 85 52 11 33
34 10 14 12 83 52 11 39
35 8 8 22 61 36 11 36
39 12 15 14 82 52 11 36
33 12 11 12 76 46 11 35
36 10 16 12 58 31 11 38
32 12 10 17 72 44 11 33
32 9 15 9 72 44 11 31
36 9 9 21 38 11 11 34
36 6 16 10 78 46 11 32
32 10 19 11 54 33 11 31
34 9 12 12 63 34 11 33
33 9 8 23 66 42 11 34
35 9 11 13 70 43 11 34
30 6 14 12 71 43 11 34
38 10 9 16 67 44 11 33
34 6 15 9 58 36 11 32
33 14 13 17 72 46 11 41
32 10 16 9 72 44 11 34
31 10 11 14 70 43 11 36
30 6 12 17 76 50 11 37
27 12 13 13 50 33 11 36
31 12 10 11 72 43 11 29
30 7 11 12 72 44 11 37
32 8 12 10 88 53 11 27
35 11 8 19 53 34 11 35
28 3 12 16 58 35 11 28
33 6 12 16 66 40 11 35
31 10 15 14 82 53 11 37
35 8 11 20 69 42 11 29
35 9 13 15 68 43 11 32
32 9 14 23 44 29 11 36
21 8 10 20 56 36 11 19
20 9 12 16 53 30 11 21
34 7 15 14 70 42 11 31
32 7 13 17 78 47 11 33
34 6 13 11 71 44 11 36
32 9 13 13 72 45 11 33
33 10 12 17 68 44 11 37
33 11 12 15 67 43 11 34
37 12 9 21 75 43 11 35
32 8 9 18 62 40 11 31
34 11 15 15 67 41 11 37
30 3 10 8 83 52 11 35
30 11 14 12 64 38 11 27
38 12 15 12 68 41 11 34
36 7 7 22 62 39 11 40
32 9 14 12 72 43 11 29

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time17 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 17 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225831&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]17 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225831&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225831&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 time17 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Connected[t] = + 23.288 + 0.435274Separate[t] -0.000997004Software[t] + 0.0170942Happiness[t] -0.0458875Depression[t] -0.0522197Sport1[t] + 0.119644Sport2[t] -0.464043Month[t] -0.00194354t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Connected[t] =  +  23.288 +  0.435274Separate[t] -0.000997004Software[t] +  0.0170942Happiness[t] -0.0458875Depression[t] -0.0522197Sport1[t] +  0.119644Sport2[t] -0.464043Month[t] -0.00194354t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225831&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Connected[t] =  +  23.288 +  0.435274Separate[t] -0.000997004Software[t] +  0.0170942Happiness[t] -0.0458875Depression[t] -0.0522197Sport1[t] +  0.119644Sport2[t] -0.464043Month[t] -0.00194354t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225831&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225831&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
Connected[t] = + 23.288 + 0.435274Separate[t] -0.000997004Software[t] + 0.0170942Happiness[t] -0.0458875Depression[t] -0.0522197Sport1[t] + 0.119644Sport2[t] -0.464043Month[t] -0.00194354t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)23.2886.879243.3850.0008232450.000411623
Separate0.4352740.05742287.586.40537e-133.20268e-13
Software-0.0009970040.0987174-0.01010.991950.495975
Happiness0.01709420.1049270.16290.8707150.435357
Depression-0.04588750.0766212-0.59890.549780.27489
Sport1-0.05221970.0685118-0.76220.4466450.223322
Sport20.1196440.1016181.1770.2401370.120068
Month-0.4640430.737611-0.62910.5298360.264918
t-0.001943540.00782337-0.24840.8040030.402002

\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) & 23.288 & 6.87924 & 3.385 & 0.000823245 & 0.000411623 \tabularnewline
Separate & 0.435274 & 0.0574228 & 7.58 & 6.40537e-13 & 3.20268e-13 \tabularnewline
Software & -0.000997004 & 0.0987174 & -0.0101 & 0.99195 & 0.495975 \tabularnewline
Happiness & 0.0170942 & 0.104927 & 0.1629 & 0.870715 & 0.435357 \tabularnewline
Depression & -0.0458875 & 0.0766212 & -0.5989 & 0.54978 & 0.27489 \tabularnewline
Sport1 & -0.0522197 & 0.0685118 & -0.7622 & 0.446645 & 0.223322 \tabularnewline
Sport2 & 0.119644 & 0.101618 & 1.177 & 0.240137 & 0.120068 \tabularnewline
Month & -0.464043 & 0.737611 & -0.6291 & 0.529836 & 0.264918 \tabularnewline
t & -0.00194354 & 0.00782337 & -0.2484 & 0.804003 & 0.402002 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225831&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]23.288[/C][C]6.87924[/C][C]3.385[/C][C]0.000823245[/C][C]0.000411623[/C][/ROW]
[ROW][C]Separate[/C][C]0.435274[/C][C]0.0574228[/C][C]7.58[/C][C]6.40537e-13[/C][C]3.20268e-13[/C][/ROW]
[ROW][C]Software[/C][C]-0.000997004[/C][C]0.0987174[/C][C]-0.0101[/C][C]0.99195[/C][C]0.495975[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0170942[/C][C]0.104927[/C][C]0.1629[/C][C]0.870715[/C][C]0.435357[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0458875[/C][C]0.0766212[/C][C]-0.5989[/C][C]0.54978[/C][C]0.27489[/C][/ROW]
[ROW][C]Sport1[/C][C]-0.0522197[/C][C]0.0685118[/C][C]-0.7622[/C][C]0.446645[/C][C]0.223322[/C][/ROW]
[ROW][C]Sport2[/C][C]0.119644[/C][C]0.101618[/C][C]1.177[/C][C]0.240137[/C][C]0.120068[/C][/ROW]
[ROW][C]Month[/C][C]-0.464043[/C][C]0.737611[/C][C]-0.6291[/C][C]0.529836[/C][C]0.264918[/C][/ROW]
[ROW][C]t[/C][C]-0.00194354[/C][C]0.00782337[/C][C]-0.2484[/C][C]0.804003[/C][C]0.402002[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225831&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225831&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)23.2886.879243.3850.0008232450.000411623
Separate0.4352740.05742287.586.40537e-133.20268e-13
Software-0.0009970040.0987174-0.01010.991950.495975
Happiness0.01709420.1049270.16290.8707150.435357
Depression-0.04588750.0766212-0.59890.549780.27489
Sport1-0.05221970.0685118-0.76220.4466450.223322
Sport20.1196440.1016181.1770.2401370.120068
Month-0.4640430.737611-0.62910.5298360.264918
t-0.001943540.00782337-0.24840.8040030.402002






Multiple Linear Regression - Regression Statistics
Multiple R0.490694
R-squared0.240781
Adjusted R-squared0.216962
F-TEST (value)10.1089
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value3.03846e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.35949
Sum Squared Residuals2877.97

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.490694 \tabularnewline
R-squared & 0.240781 \tabularnewline
Adjusted R-squared & 0.216962 \tabularnewline
F-TEST (value) & 10.1089 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 255 \tabularnewline
p-value & 3.03846e-12 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.35949 \tabularnewline
Sum Squared Residuals & 2877.97 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225831&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.490694[/C][/ROW]
[ROW][C]R-squared[/C][C]0.240781[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.216962[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]10.1089[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]255[/C][/ROW]
[ROW][C]p-value[/C][C]3.03846e-12[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.35949[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2877.97[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225831&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225831&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 R0.490694
R-squared0.240781
Adjusted R-squared0.216962
F-TEST (value)10.1089
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value3.03846e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.35949
Sum Squared Residuals2877.97






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
14136.38784.61222
23934.59614.40391
33035.4496-5.4496
43134.5231-3.52309
53436.0389-2.03889
63533.02011.97988
73933.46855.53146
83436.1715-2.17153
93635.6340.36597
103736.93810.0619135
113834.14273.8573
123634.96171.03825
133835.3182.68204
143936.37332.62665
153336.8195-3.8195
163234.308-2.30796
173634.06181.93821
183837.25640.74362
193936.94792.05206
203233.9972-1.9972
213234.7546-2.75457
223133.8094-2.80941
233936.41142.58855
243737.0949-0.0949449
253934.49634.50372
264134.16356.83654
273635.22850.77148
283336.3606-3.36058
293334.3322-1.33218
303434.7645-0.764517
313134.0784-3.07841
322733.6325-6.63254
333733.79983.20016
343436.9647-2.9647
353432.89341.10656
363234.8619-2.86188
372932.8973-3.89733
383634.53271.46728
392933.886-4.88601
403534.57320.426795
413734.31392.6861
423434.361-0.361025
433833.97674.02333
443533.93641.06356
453832.37545.62458
463735.07121.92882
473837.57690.423146
483335.1455-2.14549
493636.3089-0.308929
503834.11623.88377
513236.8581-4.85812
523232.9428-0.942756
533233.8598-1.85976
543437.3628-3.36285
553233.6462-1.64624
563735.4771.52298
573934.98494.0151
582935.156-6.15602
593735.73481.26523
603534.79050.209499
613031.4537-1.45374
623834.81313.18687
633435.4125-1.41255
643134.8013-3.80131
653433.25510.744898
663535.9627-0.962655
673634.72451.27549
683031.0047-1.00471
693936.8292.171
703535.6406-0.640598
713835.57992.42011
723135.7507-4.75069
733436.6404-2.64043
743837.31620.683811
753431.55552.44454
763932.56746.43262
773735.77351.2265
783433.08180.918163
792833.2378-5.23781
803731.17025.82983
813335.278-2.27798
823536.1012-1.1012
833733.89393.10613
843234.483-2.48296
853333.211-0.211046
863836.57451.42546
873334.3764-1.37641
882933.0557-4.05567
893333.4261-0.426144
903135.5192-4.51922
913633.04682.95315
923537.4456-2.44564
933231.65450.345549
942932.6055-3.60548
953935.33733.66271
963734.69512.30489
973533.10861.89137
983734.54342.45657
993235.4475-3.44754
1003835.35622.64385
1013734.71782.28221
1023636.0452-0.0452037
1033231.88590.114067
1043336.4303-3.43031
1054032.99687.00322
1063835.08752.91248
1074136.36274.63734
1083634.27231.72766
1094336.96716.03286
1103034.618-4.61795
1113133.6817-2.68175
1123237.9677-5.96773
1133231.66380.3362
1143734.6272.37301
1153734.00482.99524
1163336.5454-3.54543
1173437.2316-3.23158
1183334.8901-1.8901
1193835.50592.49414
1203335.1538-2.15375
1213131.2837-0.283679
1223836.93911.06093
1233736.47890.521125
1243633.21072.78928
1253133.9691-2.96911
1263934.12564.87435
1274436.59737.40271
1283335.9911-2.99107
1293533.91431.08566
1303233.7839-1.78392
1312832.8861-4.88615
1324035.76854.23155
1332732.3959-5.39593
1343736.26070.739264
1353232.5297-0.529731
1362828.2113-0.211338
1373434.9371-0.937053
1383034.4255-4.42552
1393534.36410.635868
1403134.5749-3.57493
1413234.0908-2.09082
1423035.8142-5.81425
1433035.1282-5.12821
1443129.55651.44348
1454033.55296.4471
1463231.48070.519303
1473635.02460.975416
1483233.129-1.12899
1493533.25141.74863
1503836.95011.04992
1514235.38636.61366
1523435.9419-1.94194
1533536.4789-1.47894
1543834.42723.57281
1553333.2568-0.256816
1563632.92053.07948
1573235.58-3.58004
1583335.9328-2.93277
1593433.7810.219006
1603235.844-3.84396
1613435.3851-1.38506
1622729.9437-2.94368
1633130.16630.833738
1643833.27084.72917
1653435.5584-1.55842
1662431.1722-7.17218
1673033.5705-3.5705
1682629.6897-3.6897
1693435.5034-1.50337
1702734.3676-7.36756
1713731.80585.19419
1723635.16980.83019
1734134.22536.77473
1742929.269-0.268959
1753631.20064.79938
1763234.0655-2.06555
1773733.2093.79099
1783031.5682-1.56825
1793132.5405-1.5405
1803834.63633.36372
1813634.35261.64738
1823532.0982.90202
1833134.8434-3.8434
1843833.08854.91148
1852231.7013-9.70131
1863234.126-2.12595
1873633.48582.51422
1883932.68886.31119
1892830.3462-2.34617
1903234.1843-2.18427
1913232.3935-0.393479
1923836.33771.66231
1933233.1595-1.15949
1943535.0223-0.022295
1953232.8419-0.841862
1963735.59451.4055
1973432.27021.7298
1983335.2409-2.24093
1993332.6060.394046
2002632.5808-6.58075
2013031.8741-1.87409
2022431.7276-7.72757
2033432.16791.83206
2043432.65131.34865
2053333.713-0.712988
2063434.6217-0.621675
2073535.7058-0.705819
2083534.01590.984067
2093633.32022.67982
2103433.44810.551922
2113432.9431.057
2124138.6352.36497
2133236.014-4.01402
2143033-3.00003
2153533.68331.31669
2162829.8066-1.80662
2173334.5541-1.55407
2183934.12514.87488
2193633.23352.76646
2203636.2732-0.273152
2213533.27841.72158
2223833.81514.18494
2233332.56230.437684
2243133.0159-2.01593
2253431.92912.0709
2263234.6533-2.65331
2273132.6096-1.60958
2283332.96330.0366962
2293432.75341.24656
2303434.043-0.0429647
2313431.91262.08741
2323335.4484-2.44836
2333233.6459-1.64591
2344133.26487.73521
2353433.01070.989348
2363632.24333.75668
2373732.21374.78629
2383630.42445.57562
2392932.2516-3.25163
2403731.91025.08976
2412733.128-6.128
2423533.5021.49802
2432830.5257-2.52568
2443532.87762.12242
2453732.8644.13599
2462933.6242-4.62423
2473234.0568-2.05678
2483631.97734.02273
2491927.4685-8.46846
2502126.6868-5.68678
2513133.4717-2.47172
2523332.60780.392167
2533633.75942.24063
2543332.85950.140467
2553733.18053.81954
2563433.20190.798132
2573534.19570.80434
2583132.4789-1.47892
2593733.44333.55669
2603532.42452.57545
2612731.6166-4.61662
2623435.263-1.26302
2634033.87396.12608
2642932.6638-3.66379

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 41 & 36.3878 & 4.61222 \tabularnewline
2 & 39 & 34.5961 & 4.40391 \tabularnewline
3 & 30 & 35.4496 & -5.4496 \tabularnewline
4 & 31 & 34.5231 & -3.52309 \tabularnewline
5 & 34 & 36.0389 & -2.03889 \tabularnewline
6 & 35 & 33.0201 & 1.97988 \tabularnewline
7 & 39 & 33.4685 & 5.53146 \tabularnewline
8 & 34 & 36.1715 & -2.17153 \tabularnewline
9 & 36 & 35.634 & 0.36597 \tabularnewline
10 & 37 & 36.9381 & 0.0619135 \tabularnewline
11 & 38 & 34.1427 & 3.8573 \tabularnewline
12 & 36 & 34.9617 & 1.03825 \tabularnewline
13 & 38 & 35.318 & 2.68204 \tabularnewline
14 & 39 & 36.3733 & 2.62665 \tabularnewline
15 & 33 & 36.8195 & -3.8195 \tabularnewline
16 & 32 & 34.308 & -2.30796 \tabularnewline
17 & 36 & 34.0618 & 1.93821 \tabularnewline
18 & 38 & 37.2564 & 0.74362 \tabularnewline
19 & 39 & 36.9479 & 2.05206 \tabularnewline
20 & 32 & 33.9972 & -1.9972 \tabularnewline
21 & 32 & 34.7546 & -2.75457 \tabularnewline
22 & 31 & 33.8094 & -2.80941 \tabularnewline
23 & 39 & 36.4114 & 2.58855 \tabularnewline
24 & 37 & 37.0949 & -0.0949449 \tabularnewline
25 & 39 & 34.4963 & 4.50372 \tabularnewline
26 & 41 & 34.1635 & 6.83654 \tabularnewline
27 & 36 & 35.2285 & 0.77148 \tabularnewline
28 & 33 & 36.3606 & -3.36058 \tabularnewline
29 & 33 & 34.3322 & -1.33218 \tabularnewline
30 & 34 & 34.7645 & -0.764517 \tabularnewline
31 & 31 & 34.0784 & -3.07841 \tabularnewline
32 & 27 & 33.6325 & -6.63254 \tabularnewline
33 & 37 & 33.7998 & 3.20016 \tabularnewline
34 & 34 & 36.9647 & -2.9647 \tabularnewline
35 & 34 & 32.8934 & 1.10656 \tabularnewline
36 & 32 & 34.8619 & -2.86188 \tabularnewline
37 & 29 & 32.8973 & -3.89733 \tabularnewline
38 & 36 & 34.5327 & 1.46728 \tabularnewline
39 & 29 & 33.886 & -4.88601 \tabularnewline
40 & 35 & 34.5732 & 0.426795 \tabularnewline
41 & 37 & 34.3139 & 2.6861 \tabularnewline
42 & 34 & 34.361 & -0.361025 \tabularnewline
43 & 38 & 33.9767 & 4.02333 \tabularnewline
44 & 35 & 33.9364 & 1.06356 \tabularnewline
45 & 38 & 32.3754 & 5.62458 \tabularnewline
46 & 37 & 35.0712 & 1.92882 \tabularnewline
47 & 38 & 37.5769 & 0.423146 \tabularnewline
48 & 33 & 35.1455 & -2.14549 \tabularnewline
49 & 36 & 36.3089 & -0.308929 \tabularnewline
50 & 38 & 34.1162 & 3.88377 \tabularnewline
51 & 32 & 36.8581 & -4.85812 \tabularnewline
52 & 32 & 32.9428 & -0.942756 \tabularnewline
53 & 32 & 33.8598 & -1.85976 \tabularnewline
54 & 34 & 37.3628 & -3.36285 \tabularnewline
55 & 32 & 33.6462 & -1.64624 \tabularnewline
56 & 37 & 35.477 & 1.52298 \tabularnewline
57 & 39 & 34.9849 & 4.0151 \tabularnewline
58 & 29 & 35.156 & -6.15602 \tabularnewline
59 & 37 & 35.7348 & 1.26523 \tabularnewline
60 & 35 & 34.7905 & 0.209499 \tabularnewline
61 & 30 & 31.4537 & -1.45374 \tabularnewline
62 & 38 & 34.8131 & 3.18687 \tabularnewline
63 & 34 & 35.4125 & -1.41255 \tabularnewline
64 & 31 & 34.8013 & -3.80131 \tabularnewline
65 & 34 & 33.2551 & 0.744898 \tabularnewline
66 & 35 & 35.9627 & -0.962655 \tabularnewline
67 & 36 & 34.7245 & 1.27549 \tabularnewline
68 & 30 & 31.0047 & -1.00471 \tabularnewline
69 & 39 & 36.829 & 2.171 \tabularnewline
70 & 35 & 35.6406 & -0.640598 \tabularnewline
71 & 38 & 35.5799 & 2.42011 \tabularnewline
72 & 31 & 35.7507 & -4.75069 \tabularnewline
73 & 34 & 36.6404 & -2.64043 \tabularnewline
74 & 38 & 37.3162 & 0.683811 \tabularnewline
75 & 34 & 31.5555 & 2.44454 \tabularnewline
76 & 39 & 32.5674 & 6.43262 \tabularnewline
77 & 37 & 35.7735 & 1.2265 \tabularnewline
78 & 34 & 33.0818 & 0.918163 \tabularnewline
79 & 28 & 33.2378 & -5.23781 \tabularnewline
80 & 37 & 31.1702 & 5.82983 \tabularnewline
81 & 33 & 35.278 & -2.27798 \tabularnewline
82 & 35 & 36.1012 & -1.1012 \tabularnewline
83 & 37 & 33.8939 & 3.10613 \tabularnewline
84 & 32 & 34.483 & -2.48296 \tabularnewline
85 & 33 & 33.211 & -0.211046 \tabularnewline
86 & 38 & 36.5745 & 1.42546 \tabularnewline
87 & 33 & 34.3764 & -1.37641 \tabularnewline
88 & 29 & 33.0557 & -4.05567 \tabularnewline
89 & 33 & 33.4261 & -0.426144 \tabularnewline
90 & 31 & 35.5192 & -4.51922 \tabularnewline
91 & 36 & 33.0468 & 2.95315 \tabularnewline
92 & 35 & 37.4456 & -2.44564 \tabularnewline
93 & 32 & 31.6545 & 0.345549 \tabularnewline
94 & 29 & 32.6055 & -3.60548 \tabularnewline
95 & 39 & 35.3373 & 3.66271 \tabularnewline
96 & 37 & 34.6951 & 2.30489 \tabularnewline
97 & 35 & 33.1086 & 1.89137 \tabularnewline
98 & 37 & 34.5434 & 2.45657 \tabularnewline
99 & 32 & 35.4475 & -3.44754 \tabularnewline
100 & 38 & 35.3562 & 2.64385 \tabularnewline
101 & 37 & 34.7178 & 2.28221 \tabularnewline
102 & 36 & 36.0452 & -0.0452037 \tabularnewline
103 & 32 & 31.8859 & 0.114067 \tabularnewline
104 & 33 & 36.4303 & -3.43031 \tabularnewline
105 & 40 & 32.9968 & 7.00322 \tabularnewline
106 & 38 & 35.0875 & 2.91248 \tabularnewline
107 & 41 & 36.3627 & 4.63734 \tabularnewline
108 & 36 & 34.2723 & 1.72766 \tabularnewline
109 & 43 & 36.9671 & 6.03286 \tabularnewline
110 & 30 & 34.618 & -4.61795 \tabularnewline
111 & 31 & 33.6817 & -2.68175 \tabularnewline
112 & 32 & 37.9677 & -5.96773 \tabularnewline
113 & 32 & 31.6638 & 0.3362 \tabularnewline
114 & 37 & 34.627 & 2.37301 \tabularnewline
115 & 37 & 34.0048 & 2.99524 \tabularnewline
116 & 33 & 36.5454 & -3.54543 \tabularnewline
117 & 34 & 37.2316 & -3.23158 \tabularnewline
118 & 33 & 34.8901 & -1.8901 \tabularnewline
119 & 38 & 35.5059 & 2.49414 \tabularnewline
120 & 33 & 35.1538 & -2.15375 \tabularnewline
121 & 31 & 31.2837 & -0.283679 \tabularnewline
122 & 38 & 36.9391 & 1.06093 \tabularnewline
123 & 37 & 36.4789 & 0.521125 \tabularnewline
124 & 36 & 33.2107 & 2.78928 \tabularnewline
125 & 31 & 33.9691 & -2.96911 \tabularnewline
126 & 39 & 34.1256 & 4.87435 \tabularnewline
127 & 44 & 36.5973 & 7.40271 \tabularnewline
128 & 33 & 35.9911 & -2.99107 \tabularnewline
129 & 35 & 33.9143 & 1.08566 \tabularnewline
130 & 32 & 33.7839 & -1.78392 \tabularnewline
131 & 28 & 32.8861 & -4.88615 \tabularnewline
132 & 40 & 35.7685 & 4.23155 \tabularnewline
133 & 27 & 32.3959 & -5.39593 \tabularnewline
134 & 37 & 36.2607 & 0.739264 \tabularnewline
135 & 32 & 32.5297 & -0.529731 \tabularnewline
136 & 28 & 28.2113 & -0.211338 \tabularnewline
137 & 34 & 34.9371 & -0.937053 \tabularnewline
138 & 30 & 34.4255 & -4.42552 \tabularnewline
139 & 35 & 34.3641 & 0.635868 \tabularnewline
140 & 31 & 34.5749 & -3.57493 \tabularnewline
141 & 32 & 34.0908 & -2.09082 \tabularnewline
142 & 30 & 35.8142 & -5.81425 \tabularnewline
143 & 30 & 35.1282 & -5.12821 \tabularnewline
144 & 31 & 29.5565 & 1.44348 \tabularnewline
145 & 40 & 33.5529 & 6.4471 \tabularnewline
146 & 32 & 31.4807 & 0.519303 \tabularnewline
147 & 36 & 35.0246 & 0.975416 \tabularnewline
148 & 32 & 33.129 & -1.12899 \tabularnewline
149 & 35 & 33.2514 & 1.74863 \tabularnewline
150 & 38 & 36.9501 & 1.04992 \tabularnewline
151 & 42 & 35.3863 & 6.61366 \tabularnewline
152 & 34 & 35.9419 & -1.94194 \tabularnewline
153 & 35 & 36.4789 & -1.47894 \tabularnewline
154 & 38 & 34.4272 & 3.57281 \tabularnewline
155 & 33 & 33.2568 & -0.256816 \tabularnewline
156 & 36 & 32.9205 & 3.07948 \tabularnewline
157 & 32 & 35.58 & -3.58004 \tabularnewline
158 & 33 & 35.9328 & -2.93277 \tabularnewline
159 & 34 & 33.781 & 0.219006 \tabularnewline
160 & 32 & 35.844 & -3.84396 \tabularnewline
161 & 34 & 35.3851 & -1.38506 \tabularnewline
162 & 27 & 29.9437 & -2.94368 \tabularnewline
163 & 31 & 30.1663 & 0.833738 \tabularnewline
164 & 38 & 33.2708 & 4.72917 \tabularnewline
165 & 34 & 35.5584 & -1.55842 \tabularnewline
166 & 24 & 31.1722 & -7.17218 \tabularnewline
167 & 30 & 33.5705 & -3.5705 \tabularnewline
168 & 26 & 29.6897 & -3.6897 \tabularnewline
169 & 34 & 35.5034 & -1.50337 \tabularnewline
170 & 27 & 34.3676 & -7.36756 \tabularnewline
171 & 37 & 31.8058 & 5.19419 \tabularnewline
172 & 36 & 35.1698 & 0.83019 \tabularnewline
173 & 41 & 34.2253 & 6.77473 \tabularnewline
174 & 29 & 29.269 & -0.268959 \tabularnewline
175 & 36 & 31.2006 & 4.79938 \tabularnewline
176 & 32 & 34.0655 & -2.06555 \tabularnewline
177 & 37 & 33.209 & 3.79099 \tabularnewline
178 & 30 & 31.5682 & -1.56825 \tabularnewline
179 & 31 & 32.5405 & -1.5405 \tabularnewline
180 & 38 & 34.6363 & 3.36372 \tabularnewline
181 & 36 & 34.3526 & 1.64738 \tabularnewline
182 & 35 & 32.098 & 2.90202 \tabularnewline
183 & 31 & 34.8434 & -3.8434 \tabularnewline
184 & 38 & 33.0885 & 4.91148 \tabularnewline
185 & 22 & 31.7013 & -9.70131 \tabularnewline
186 & 32 & 34.126 & -2.12595 \tabularnewline
187 & 36 & 33.4858 & 2.51422 \tabularnewline
188 & 39 & 32.6888 & 6.31119 \tabularnewline
189 & 28 & 30.3462 & -2.34617 \tabularnewline
190 & 32 & 34.1843 & -2.18427 \tabularnewline
191 & 32 & 32.3935 & -0.393479 \tabularnewline
192 & 38 & 36.3377 & 1.66231 \tabularnewline
193 & 32 & 33.1595 & -1.15949 \tabularnewline
194 & 35 & 35.0223 & -0.022295 \tabularnewline
195 & 32 & 32.8419 & -0.841862 \tabularnewline
196 & 37 & 35.5945 & 1.4055 \tabularnewline
197 & 34 & 32.2702 & 1.7298 \tabularnewline
198 & 33 & 35.2409 & -2.24093 \tabularnewline
199 & 33 & 32.606 & 0.394046 \tabularnewline
200 & 26 & 32.5808 & -6.58075 \tabularnewline
201 & 30 & 31.8741 & -1.87409 \tabularnewline
202 & 24 & 31.7276 & -7.72757 \tabularnewline
203 & 34 & 32.1679 & 1.83206 \tabularnewline
204 & 34 & 32.6513 & 1.34865 \tabularnewline
205 & 33 & 33.713 & -0.712988 \tabularnewline
206 & 34 & 34.6217 & -0.621675 \tabularnewline
207 & 35 & 35.7058 & -0.705819 \tabularnewline
208 & 35 & 34.0159 & 0.984067 \tabularnewline
209 & 36 & 33.3202 & 2.67982 \tabularnewline
210 & 34 & 33.4481 & 0.551922 \tabularnewline
211 & 34 & 32.943 & 1.057 \tabularnewline
212 & 41 & 38.635 & 2.36497 \tabularnewline
213 & 32 & 36.014 & -4.01402 \tabularnewline
214 & 30 & 33 & -3.00003 \tabularnewline
215 & 35 & 33.6833 & 1.31669 \tabularnewline
216 & 28 & 29.8066 & -1.80662 \tabularnewline
217 & 33 & 34.5541 & -1.55407 \tabularnewline
218 & 39 & 34.1251 & 4.87488 \tabularnewline
219 & 36 & 33.2335 & 2.76646 \tabularnewline
220 & 36 & 36.2732 & -0.273152 \tabularnewline
221 & 35 & 33.2784 & 1.72158 \tabularnewline
222 & 38 & 33.8151 & 4.18494 \tabularnewline
223 & 33 & 32.5623 & 0.437684 \tabularnewline
224 & 31 & 33.0159 & -2.01593 \tabularnewline
225 & 34 & 31.9291 & 2.0709 \tabularnewline
226 & 32 & 34.6533 & -2.65331 \tabularnewline
227 & 31 & 32.6096 & -1.60958 \tabularnewline
228 & 33 & 32.9633 & 0.0366962 \tabularnewline
229 & 34 & 32.7534 & 1.24656 \tabularnewline
230 & 34 & 34.043 & -0.0429647 \tabularnewline
231 & 34 & 31.9126 & 2.08741 \tabularnewline
232 & 33 & 35.4484 & -2.44836 \tabularnewline
233 & 32 & 33.6459 & -1.64591 \tabularnewline
234 & 41 & 33.2648 & 7.73521 \tabularnewline
235 & 34 & 33.0107 & 0.989348 \tabularnewline
236 & 36 & 32.2433 & 3.75668 \tabularnewline
237 & 37 & 32.2137 & 4.78629 \tabularnewline
238 & 36 & 30.4244 & 5.57562 \tabularnewline
239 & 29 & 32.2516 & -3.25163 \tabularnewline
240 & 37 & 31.9102 & 5.08976 \tabularnewline
241 & 27 & 33.128 & -6.128 \tabularnewline
242 & 35 & 33.502 & 1.49802 \tabularnewline
243 & 28 & 30.5257 & -2.52568 \tabularnewline
244 & 35 & 32.8776 & 2.12242 \tabularnewline
245 & 37 & 32.864 & 4.13599 \tabularnewline
246 & 29 & 33.6242 & -4.62423 \tabularnewline
247 & 32 & 34.0568 & -2.05678 \tabularnewline
248 & 36 & 31.9773 & 4.02273 \tabularnewline
249 & 19 & 27.4685 & -8.46846 \tabularnewline
250 & 21 & 26.6868 & -5.68678 \tabularnewline
251 & 31 & 33.4717 & -2.47172 \tabularnewline
252 & 33 & 32.6078 & 0.392167 \tabularnewline
253 & 36 & 33.7594 & 2.24063 \tabularnewline
254 & 33 & 32.8595 & 0.140467 \tabularnewline
255 & 37 & 33.1805 & 3.81954 \tabularnewline
256 & 34 & 33.2019 & 0.798132 \tabularnewline
257 & 35 & 34.1957 & 0.80434 \tabularnewline
258 & 31 & 32.4789 & -1.47892 \tabularnewline
259 & 37 & 33.4433 & 3.55669 \tabularnewline
260 & 35 & 32.4245 & 2.57545 \tabularnewline
261 & 27 & 31.6166 & -4.61662 \tabularnewline
262 & 34 & 35.263 & -1.26302 \tabularnewline
263 & 40 & 33.8739 & 6.12608 \tabularnewline
264 & 29 & 32.6638 & -3.66379 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225831&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]41[/C][C]36.3878[/C][C]4.61222[/C][/ROW]
[ROW][C]2[/C][C]39[/C][C]34.5961[/C][C]4.40391[/C][/ROW]
[ROW][C]3[/C][C]30[/C][C]35.4496[/C][C]-5.4496[/C][/ROW]
[ROW][C]4[/C][C]31[/C][C]34.5231[/C][C]-3.52309[/C][/ROW]
[ROW][C]5[/C][C]34[/C][C]36.0389[/C][C]-2.03889[/C][/ROW]
[ROW][C]6[/C][C]35[/C][C]33.0201[/C][C]1.97988[/C][/ROW]
[ROW][C]7[/C][C]39[/C][C]33.4685[/C][C]5.53146[/C][/ROW]
[ROW][C]8[/C][C]34[/C][C]36.1715[/C][C]-2.17153[/C][/ROW]
[ROW][C]9[/C][C]36[/C][C]35.634[/C][C]0.36597[/C][/ROW]
[ROW][C]10[/C][C]37[/C][C]36.9381[/C][C]0.0619135[/C][/ROW]
[ROW][C]11[/C][C]38[/C][C]34.1427[/C][C]3.8573[/C][/ROW]
[ROW][C]12[/C][C]36[/C][C]34.9617[/C][C]1.03825[/C][/ROW]
[ROW][C]13[/C][C]38[/C][C]35.318[/C][C]2.68204[/C][/ROW]
[ROW][C]14[/C][C]39[/C][C]36.3733[/C][C]2.62665[/C][/ROW]
[ROW][C]15[/C][C]33[/C][C]36.8195[/C][C]-3.8195[/C][/ROW]
[ROW][C]16[/C][C]32[/C][C]34.308[/C][C]-2.30796[/C][/ROW]
[ROW][C]17[/C][C]36[/C][C]34.0618[/C][C]1.93821[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]37.2564[/C][C]0.74362[/C][/ROW]
[ROW][C]19[/C][C]39[/C][C]36.9479[/C][C]2.05206[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]33.9972[/C][C]-1.9972[/C][/ROW]
[ROW][C]21[/C][C]32[/C][C]34.7546[/C][C]-2.75457[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]33.8094[/C][C]-2.80941[/C][/ROW]
[ROW][C]23[/C][C]39[/C][C]36.4114[/C][C]2.58855[/C][/ROW]
[ROW][C]24[/C][C]37[/C][C]37.0949[/C][C]-0.0949449[/C][/ROW]
[ROW][C]25[/C][C]39[/C][C]34.4963[/C][C]4.50372[/C][/ROW]
[ROW][C]26[/C][C]41[/C][C]34.1635[/C][C]6.83654[/C][/ROW]
[ROW][C]27[/C][C]36[/C][C]35.2285[/C][C]0.77148[/C][/ROW]
[ROW][C]28[/C][C]33[/C][C]36.3606[/C][C]-3.36058[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]34.3322[/C][C]-1.33218[/C][/ROW]
[ROW][C]30[/C][C]34[/C][C]34.7645[/C][C]-0.764517[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]34.0784[/C][C]-3.07841[/C][/ROW]
[ROW][C]32[/C][C]27[/C][C]33.6325[/C][C]-6.63254[/C][/ROW]
[ROW][C]33[/C][C]37[/C][C]33.7998[/C][C]3.20016[/C][/ROW]
[ROW][C]34[/C][C]34[/C][C]36.9647[/C][C]-2.9647[/C][/ROW]
[ROW][C]35[/C][C]34[/C][C]32.8934[/C][C]1.10656[/C][/ROW]
[ROW][C]36[/C][C]32[/C][C]34.8619[/C][C]-2.86188[/C][/ROW]
[ROW][C]37[/C][C]29[/C][C]32.8973[/C][C]-3.89733[/C][/ROW]
[ROW][C]38[/C][C]36[/C][C]34.5327[/C][C]1.46728[/C][/ROW]
[ROW][C]39[/C][C]29[/C][C]33.886[/C][C]-4.88601[/C][/ROW]
[ROW][C]40[/C][C]35[/C][C]34.5732[/C][C]0.426795[/C][/ROW]
[ROW][C]41[/C][C]37[/C][C]34.3139[/C][C]2.6861[/C][/ROW]
[ROW][C]42[/C][C]34[/C][C]34.361[/C][C]-0.361025[/C][/ROW]
[ROW][C]43[/C][C]38[/C][C]33.9767[/C][C]4.02333[/C][/ROW]
[ROW][C]44[/C][C]35[/C][C]33.9364[/C][C]1.06356[/C][/ROW]
[ROW][C]45[/C][C]38[/C][C]32.3754[/C][C]5.62458[/C][/ROW]
[ROW][C]46[/C][C]37[/C][C]35.0712[/C][C]1.92882[/C][/ROW]
[ROW][C]47[/C][C]38[/C][C]37.5769[/C][C]0.423146[/C][/ROW]
[ROW][C]48[/C][C]33[/C][C]35.1455[/C][C]-2.14549[/C][/ROW]
[ROW][C]49[/C][C]36[/C][C]36.3089[/C][C]-0.308929[/C][/ROW]
[ROW][C]50[/C][C]38[/C][C]34.1162[/C][C]3.88377[/C][/ROW]
[ROW][C]51[/C][C]32[/C][C]36.8581[/C][C]-4.85812[/C][/ROW]
[ROW][C]52[/C][C]32[/C][C]32.9428[/C][C]-0.942756[/C][/ROW]
[ROW][C]53[/C][C]32[/C][C]33.8598[/C][C]-1.85976[/C][/ROW]
[ROW][C]54[/C][C]34[/C][C]37.3628[/C][C]-3.36285[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]33.6462[/C][C]-1.64624[/C][/ROW]
[ROW][C]56[/C][C]37[/C][C]35.477[/C][C]1.52298[/C][/ROW]
[ROW][C]57[/C][C]39[/C][C]34.9849[/C][C]4.0151[/C][/ROW]
[ROW][C]58[/C][C]29[/C][C]35.156[/C][C]-6.15602[/C][/ROW]
[ROW][C]59[/C][C]37[/C][C]35.7348[/C][C]1.26523[/C][/ROW]
[ROW][C]60[/C][C]35[/C][C]34.7905[/C][C]0.209499[/C][/ROW]
[ROW][C]61[/C][C]30[/C][C]31.4537[/C][C]-1.45374[/C][/ROW]
[ROW][C]62[/C][C]38[/C][C]34.8131[/C][C]3.18687[/C][/ROW]
[ROW][C]63[/C][C]34[/C][C]35.4125[/C][C]-1.41255[/C][/ROW]
[ROW][C]64[/C][C]31[/C][C]34.8013[/C][C]-3.80131[/C][/ROW]
[ROW][C]65[/C][C]34[/C][C]33.2551[/C][C]0.744898[/C][/ROW]
[ROW][C]66[/C][C]35[/C][C]35.9627[/C][C]-0.962655[/C][/ROW]
[ROW][C]67[/C][C]36[/C][C]34.7245[/C][C]1.27549[/C][/ROW]
[ROW][C]68[/C][C]30[/C][C]31.0047[/C][C]-1.00471[/C][/ROW]
[ROW][C]69[/C][C]39[/C][C]36.829[/C][C]2.171[/C][/ROW]
[ROW][C]70[/C][C]35[/C][C]35.6406[/C][C]-0.640598[/C][/ROW]
[ROW][C]71[/C][C]38[/C][C]35.5799[/C][C]2.42011[/C][/ROW]
[ROW][C]72[/C][C]31[/C][C]35.7507[/C][C]-4.75069[/C][/ROW]
[ROW][C]73[/C][C]34[/C][C]36.6404[/C][C]-2.64043[/C][/ROW]
[ROW][C]74[/C][C]38[/C][C]37.3162[/C][C]0.683811[/C][/ROW]
[ROW][C]75[/C][C]34[/C][C]31.5555[/C][C]2.44454[/C][/ROW]
[ROW][C]76[/C][C]39[/C][C]32.5674[/C][C]6.43262[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.7735[/C][C]1.2265[/C][/ROW]
[ROW][C]78[/C][C]34[/C][C]33.0818[/C][C]0.918163[/C][/ROW]
[ROW][C]79[/C][C]28[/C][C]33.2378[/C][C]-5.23781[/C][/ROW]
[ROW][C]80[/C][C]37[/C][C]31.1702[/C][C]5.82983[/C][/ROW]
[ROW][C]81[/C][C]33[/C][C]35.278[/C][C]-2.27798[/C][/ROW]
[ROW][C]82[/C][C]35[/C][C]36.1012[/C][C]-1.1012[/C][/ROW]
[ROW][C]83[/C][C]37[/C][C]33.8939[/C][C]3.10613[/C][/ROW]
[ROW][C]84[/C][C]32[/C][C]34.483[/C][C]-2.48296[/C][/ROW]
[ROW][C]85[/C][C]33[/C][C]33.211[/C][C]-0.211046[/C][/ROW]
[ROW][C]86[/C][C]38[/C][C]36.5745[/C][C]1.42546[/C][/ROW]
[ROW][C]87[/C][C]33[/C][C]34.3764[/C][C]-1.37641[/C][/ROW]
[ROW][C]88[/C][C]29[/C][C]33.0557[/C][C]-4.05567[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]33.4261[/C][C]-0.426144[/C][/ROW]
[ROW][C]90[/C][C]31[/C][C]35.5192[/C][C]-4.51922[/C][/ROW]
[ROW][C]91[/C][C]36[/C][C]33.0468[/C][C]2.95315[/C][/ROW]
[ROW][C]92[/C][C]35[/C][C]37.4456[/C][C]-2.44564[/C][/ROW]
[ROW][C]93[/C][C]32[/C][C]31.6545[/C][C]0.345549[/C][/ROW]
[ROW][C]94[/C][C]29[/C][C]32.6055[/C][C]-3.60548[/C][/ROW]
[ROW][C]95[/C][C]39[/C][C]35.3373[/C][C]3.66271[/C][/ROW]
[ROW][C]96[/C][C]37[/C][C]34.6951[/C][C]2.30489[/C][/ROW]
[ROW][C]97[/C][C]35[/C][C]33.1086[/C][C]1.89137[/C][/ROW]
[ROW][C]98[/C][C]37[/C][C]34.5434[/C][C]2.45657[/C][/ROW]
[ROW][C]99[/C][C]32[/C][C]35.4475[/C][C]-3.44754[/C][/ROW]
[ROW][C]100[/C][C]38[/C][C]35.3562[/C][C]2.64385[/C][/ROW]
[ROW][C]101[/C][C]37[/C][C]34.7178[/C][C]2.28221[/C][/ROW]
[ROW][C]102[/C][C]36[/C][C]36.0452[/C][C]-0.0452037[/C][/ROW]
[ROW][C]103[/C][C]32[/C][C]31.8859[/C][C]0.114067[/C][/ROW]
[ROW][C]104[/C][C]33[/C][C]36.4303[/C][C]-3.43031[/C][/ROW]
[ROW][C]105[/C][C]40[/C][C]32.9968[/C][C]7.00322[/C][/ROW]
[ROW][C]106[/C][C]38[/C][C]35.0875[/C][C]2.91248[/C][/ROW]
[ROW][C]107[/C][C]41[/C][C]36.3627[/C][C]4.63734[/C][/ROW]
[ROW][C]108[/C][C]36[/C][C]34.2723[/C][C]1.72766[/C][/ROW]
[ROW][C]109[/C][C]43[/C][C]36.9671[/C][C]6.03286[/C][/ROW]
[ROW][C]110[/C][C]30[/C][C]34.618[/C][C]-4.61795[/C][/ROW]
[ROW][C]111[/C][C]31[/C][C]33.6817[/C][C]-2.68175[/C][/ROW]
[ROW][C]112[/C][C]32[/C][C]37.9677[/C][C]-5.96773[/C][/ROW]
[ROW][C]113[/C][C]32[/C][C]31.6638[/C][C]0.3362[/C][/ROW]
[ROW][C]114[/C][C]37[/C][C]34.627[/C][C]2.37301[/C][/ROW]
[ROW][C]115[/C][C]37[/C][C]34.0048[/C][C]2.99524[/C][/ROW]
[ROW][C]116[/C][C]33[/C][C]36.5454[/C][C]-3.54543[/C][/ROW]
[ROW][C]117[/C][C]34[/C][C]37.2316[/C][C]-3.23158[/C][/ROW]
[ROW][C]118[/C][C]33[/C][C]34.8901[/C][C]-1.8901[/C][/ROW]
[ROW][C]119[/C][C]38[/C][C]35.5059[/C][C]2.49414[/C][/ROW]
[ROW][C]120[/C][C]33[/C][C]35.1538[/C][C]-2.15375[/C][/ROW]
[ROW][C]121[/C][C]31[/C][C]31.2837[/C][C]-0.283679[/C][/ROW]
[ROW][C]122[/C][C]38[/C][C]36.9391[/C][C]1.06093[/C][/ROW]
[ROW][C]123[/C][C]37[/C][C]36.4789[/C][C]0.521125[/C][/ROW]
[ROW][C]124[/C][C]36[/C][C]33.2107[/C][C]2.78928[/C][/ROW]
[ROW][C]125[/C][C]31[/C][C]33.9691[/C][C]-2.96911[/C][/ROW]
[ROW][C]126[/C][C]39[/C][C]34.1256[/C][C]4.87435[/C][/ROW]
[ROW][C]127[/C][C]44[/C][C]36.5973[/C][C]7.40271[/C][/ROW]
[ROW][C]128[/C][C]33[/C][C]35.9911[/C][C]-2.99107[/C][/ROW]
[ROW][C]129[/C][C]35[/C][C]33.9143[/C][C]1.08566[/C][/ROW]
[ROW][C]130[/C][C]32[/C][C]33.7839[/C][C]-1.78392[/C][/ROW]
[ROW][C]131[/C][C]28[/C][C]32.8861[/C][C]-4.88615[/C][/ROW]
[ROW][C]132[/C][C]40[/C][C]35.7685[/C][C]4.23155[/C][/ROW]
[ROW][C]133[/C][C]27[/C][C]32.3959[/C][C]-5.39593[/C][/ROW]
[ROW][C]134[/C][C]37[/C][C]36.2607[/C][C]0.739264[/C][/ROW]
[ROW][C]135[/C][C]32[/C][C]32.5297[/C][C]-0.529731[/C][/ROW]
[ROW][C]136[/C][C]28[/C][C]28.2113[/C][C]-0.211338[/C][/ROW]
[ROW][C]137[/C][C]34[/C][C]34.9371[/C][C]-0.937053[/C][/ROW]
[ROW][C]138[/C][C]30[/C][C]34.4255[/C][C]-4.42552[/C][/ROW]
[ROW][C]139[/C][C]35[/C][C]34.3641[/C][C]0.635868[/C][/ROW]
[ROW][C]140[/C][C]31[/C][C]34.5749[/C][C]-3.57493[/C][/ROW]
[ROW][C]141[/C][C]32[/C][C]34.0908[/C][C]-2.09082[/C][/ROW]
[ROW][C]142[/C][C]30[/C][C]35.8142[/C][C]-5.81425[/C][/ROW]
[ROW][C]143[/C][C]30[/C][C]35.1282[/C][C]-5.12821[/C][/ROW]
[ROW][C]144[/C][C]31[/C][C]29.5565[/C][C]1.44348[/C][/ROW]
[ROW][C]145[/C][C]40[/C][C]33.5529[/C][C]6.4471[/C][/ROW]
[ROW][C]146[/C][C]32[/C][C]31.4807[/C][C]0.519303[/C][/ROW]
[ROW][C]147[/C][C]36[/C][C]35.0246[/C][C]0.975416[/C][/ROW]
[ROW][C]148[/C][C]32[/C][C]33.129[/C][C]-1.12899[/C][/ROW]
[ROW][C]149[/C][C]35[/C][C]33.2514[/C][C]1.74863[/C][/ROW]
[ROW][C]150[/C][C]38[/C][C]36.9501[/C][C]1.04992[/C][/ROW]
[ROW][C]151[/C][C]42[/C][C]35.3863[/C][C]6.61366[/C][/ROW]
[ROW][C]152[/C][C]34[/C][C]35.9419[/C][C]-1.94194[/C][/ROW]
[ROW][C]153[/C][C]35[/C][C]36.4789[/C][C]-1.47894[/C][/ROW]
[ROW][C]154[/C][C]38[/C][C]34.4272[/C][C]3.57281[/C][/ROW]
[ROW][C]155[/C][C]33[/C][C]33.2568[/C][C]-0.256816[/C][/ROW]
[ROW][C]156[/C][C]36[/C][C]32.9205[/C][C]3.07948[/C][/ROW]
[ROW][C]157[/C][C]32[/C][C]35.58[/C][C]-3.58004[/C][/ROW]
[ROW][C]158[/C][C]33[/C][C]35.9328[/C][C]-2.93277[/C][/ROW]
[ROW][C]159[/C][C]34[/C][C]33.781[/C][C]0.219006[/C][/ROW]
[ROW][C]160[/C][C]32[/C][C]35.844[/C][C]-3.84396[/C][/ROW]
[ROW][C]161[/C][C]34[/C][C]35.3851[/C][C]-1.38506[/C][/ROW]
[ROW][C]162[/C][C]27[/C][C]29.9437[/C][C]-2.94368[/C][/ROW]
[ROW][C]163[/C][C]31[/C][C]30.1663[/C][C]0.833738[/C][/ROW]
[ROW][C]164[/C][C]38[/C][C]33.2708[/C][C]4.72917[/C][/ROW]
[ROW][C]165[/C][C]34[/C][C]35.5584[/C][C]-1.55842[/C][/ROW]
[ROW][C]166[/C][C]24[/C][C]31.1722[/C][C]-7.17218[/C][/ROW]
[ROW][C]167[/C][C]30[/C][C]33.5705[/C][C]-3.5705[/C][/ROW]
[ROW][C]168[/C][C]26[/C][C]29.6897[/C][C]-3.6897[/C][/ROW]
[ROW][C]169[/C][C]34[/C][C]35.5034[/C][C]-1.50337[/C][/ROW]
[ROW][C]170[/C][C]27[/C][C]34.3676[/C][C]-7.36756[/C][/ROW]
[ROW][C]171[/C][C]37[/C][C]31.8058[/C][C]5.19419[/C][/ROW]
[ROW][C]172[/C][C]36[/C][C]35.1698[/C][C]0.83019[/C][/ROW]
[ROW][C]173[/C][C]41[/C][C]34.2253[/C][C]6.77473[/C][/ROW]
[ROW][C]174[/C][C]29[/C][C]29.269[/C][C]-0.268959[/C][/ROW]
[ROW][C]175[/C][C]36[/C][C]31.2006[/C][C]4.79938[/C][/ROW]
[ROW][C]176[/C][C]32[/C][C]34.0655[/C][C]-2.06555[/C][/ROW]
[ROW][C]177[/C][C]37[/C][C]33.209[/C][C]3.79099[/C][/ROW]
[ROW][C]178[/C][C]30[/C][C]31.5682[/C][C]-1.56825[/C][/ROW]
[ROW][C]179[/C][C]31[/C][C]32.5405[/C][C]-1.5405[/C][/ROW]
[ROW][C]180[/C][C]38[/C][C]34.6363[/C][C]3.36372[/C][/ROW]
[ROW][C]181[/C][C]36[/C][C]34.3526[/C][C]1.64738[/C][/ROW]
[ROW][C]182[/C][C]35[/C][C]32.098[/C][C]2.90202[/C][/ROW]
[ROW][C]183[/C][C]31[/C][C]34.8434[/C][C]-3.8434[/C][/ROW]
[ROW][C]184[/C][C]38[/C][C]33.0885[/C][C]4.91148[/C][/ROW]
[ROW][C]185[/C][C]22[/C][C]31.7013[/C][C]-9.70131[/C][/ROW]
[ROW][C]186[/C][C]32[/C][C]34.126[/C][C]-2.12595[/C][/ROW]
[ROW][C]187[/C][C]36[/C][C]33.4858[/C][C]2.51422[/C][/ROW]
[ROW][C]188[/C][C]39[/C][C]32.6888[/C][C]6.31119[/C][/ROW]
[ROW][C]189[/C][C]28[/C][C]30.3462[/C][C]-2.34617[/C][/ROW]
[ROW][C]190[/C][C]32[/C][C]34.1843[/C][C]-2.18427[/C][/ROW]
[ROW][C]191[/C][C]32[/C][C]32.3935[/C][C]-0.393479[/C][/ROW]
[ROW][C]192[/C][C]38[/C][C]36.3377[/C][C]1.66231[/C][/ROW]
[ROW][C]193[/C][C]32[/C][C]33.1595[/C][C]-1.15949[/C][/ROW]
[ROW][C]194[/C][C]35[/C][C]35.0223[/C][C]-0.022295[/C][/ROW]
[ROW][C]195[/C][C]32[/C][C]32.8419[/C][C]-0.841862[/C][/ROW]
[ROW][C]196[/C][C]37[/C][C]35.5945[/C][C]1.4055[/C][/ROW]
[ROW][C]197[/C][C]34[/C][C]32.2702[/C][C]1.7298[/C][/ROW]
[ROW][C]198[/C][C]33[/C][C]35.2409[/C][C]-2.24093[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]32.606[/C][C]0.394046[/C][/ROW]
[ROW][C]200[/C][C]26[/C][C]32.5808[/C][C]-6.58075[/C][/ROW]
[ROW][C]201[/C][C]30[/C][C]31.8741[/C][C]-1.87409[/C][/ROW]
[ROW][C]202[/C][C]24[/C][C]31.7276[/C][C]-7.72757[/C][/ROW]
[ROW][C]203[/C][C]34[/C][C]32.1679[/C][C]1.83206[/C][/ROW]
[ROW][C]204[/C][C]34[/C][C]32.6513[/C][C]1.34865[/C][/ROW]
[ROW][C]205[/C][C]33[/C][C]33.713[/C][C]-0.712988[/C][/ROW]
[ROW][C]206[/C][C]34[/C][C]34.6217[/C][C]-0.621675[/C][/ROW]
[ROW][C]207[/C][C]35[/C][C]35.7058[/C][C]-0.705819[/C][/ROW]
[ROW][C]208[/C][C]35[/C][C]34.0159[/C][C]0.984067[/C][/ROW]
[ROW][C]209[/C][C]36[/C][C]33.3202[/C][C]2.67982[/C][/ROW]
[ROW][C]210[/C][C]34[/C][C]33.4481[/C][C]0.551922[/C][/ROW]
[ROW][C]211[/C][C]34[/C][C]32.943[/C][C]1.057[/C][/ROW]
[ROW][C]212[/C][C]41[/C][C]38.635[/C][C]2.36497[/C][/ROW]
[ROW][C]213[/C][C]32[/C][C]36.014[/C][C]-4.01402[/C][/ROW]
[ROW][C]214[/C][C]30[/C][C]33[/C][C]-3.00003[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]33.6833[/C][C]1.31669[/C][/ROW]
[ROW][C]216[/C][C]28[/C][C]29.8066[/C][C]-1.80662[/C][/ROW]
[ROW][C]217[/C][C]33[/C][C]34.5541[/C][C]-1.55407[/C][/ROW]
[ROW][C]218[/C][C]39[/C][C]34.1251[/C][C]4.87488[/C][/ROW]
[ROW][C]219[/C][C]36[/C][C]33.2335[/C][C]2.76646[/C][/ROW]
[ROW][C]220[/C][C]36[/C][C]36.2732[/C][C]-0.273152[/C][/ROW]
[ROW][C]221[/C][C]35[/C][C]33.2784[/C][C]1.72158[/C][/ROW]
[ROW][C]222[/C][C]38[/C][C]33.8151[/C][C]4.18494[/C][/ROW]
[ROW][C]223[/C][C]33[/C][C]32.5623[/C][C]0.437684[/C][/ROW]
[ROW][C]224[/C][C]31[/C][C]33.0159[/C][C]-2.01593[/C][/ROW]
[ROW][C]225[/C][C]34[/C][C]31.9291[/C][C]2.0709[/C][/ROW]
[ROW][C]226[/C][C]32[/C][C]34.6533[/C][C]-2.65331[/C][/ROW]
[ROW][C]227[/C][C]31[/C][C]32.6096[/C][C]-1.60958[/C][/ROW]
[ROW][C]228[/C][C]33[/C][C]32.9633[/C][C]0.0366962[/C][/ROW]
[ROW][C]229[/C][C]34[/C][C]32.7534[/C][C]1.24656[/C][/ROW]
[ROW][C]230[/C][C]34[/C][C]34.043[/C][C]-0.0429647[/C][/ROW]
[ROW][C]231[/C][C]34[/C][C]31.9126[/C][C]2.08741[/C][/ROW]
[ROW][C]232[/C][C]33[/C][C]35.4484[/C][C]-2.44836[/C][/ROW]
[ROW][C]233[/C][C]32[/C][C]33.6459[/C][C]-1.64591[/C][/ROW]
[ROW][C]234[/C][C]41[/C][C]33.2648[/C][C]7.73521[/C][/ROW]
[ROW][C]235[/C][C]34[/C][C]33.0107[/C][C]0.989348[/C][/ROW]
[ROW][C]236[/C][C]36[/C][C]32.2433[/C][C]3.75668[/C][/ROW]
[ROW][C]237[/C][C]37[/C][C]32.2137[/C][C]4.78629[/C][/ROW]
[ROW][C]238[/C][C]36[/C][C]30.4244[/C][C]5.57562[/C][/ROW]
[ROW][C]239[/C][C]29[/C][C]32.2516[/C][C]-3.25163[/C][/ROW]
[ROW][C]240[/C][C]37[/C][C]31.9102[/C][C]5.08976[/C][/ROW]
[ROW][C]241[/C][C]27[/C][C]33.128[/C][C]-6.128[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]33.502[/C][C]1.49802[/C][/ROW]
[ROW][C]243[/C][C]28[/C][C]30.5257[/C][C]-2.52568[/C][/ROW]
[ROW][C]244[/C][C]35[/C][C]32.8776[/C][C]2.12242[/C][/ROW]
[ROW][C]245[/C][C]37[/C][C]32.864[/C][C]4.13599[/C][/ROW]
[ROW][C]246[/C][C]29[/C][C]33.6242[/C][C]-4.62423[/C][/ROW]
[ROW][C]247[/C][C]32[/C][C]34.0568[/C][C]-2.05678[/C][/ROW]
[ROW][C]248[/C][C]36[/C][C]31.9773[/C][C]4.02273[/C][/ROW]
[ROW][C]249[/C][C]19[/C][C]27.4685[/C][C]-8.46846[/C][/ROW]
[ROW][C]250[/C][C]21[/C][C]26.6868[/C][C]-5.68678[/C][/ROW]
[ROW][C]251[/C][C]31[/C][C]33.4717[/C][C]-2.47172[/C][/ROW]
[ROW][C]252[/C][C]33[/C][C]32.6078[/C][C]0.392167[/C][/ROW]
[ROW][C]253[/C][C]36[/C][C]33.7594[/C][C]2.24063[/C][/ROW]
[ROW][C]254[/C][C]33[/C][C]32.8595[/C][C]0.140467[/C][/ROW]
[ROW][C]255[/C][C]37[/C][C]33.1805[/C][C]3.81954[/C][/ROW]
[ROW][C]256[/C][C]34[/C][C]33.2019[/C][C]0.798132[/C][/ROW]
[ROW][C]257[/C][C]35[/C][C]34.1957[/C][C]0.80434[/C][/ROW]
[ROW][C]258[/C][C]31[/C][C]32.4789[/C][C]-1.47892[/C][/ROW]
[ROW][C]259[/C][C]37[/C][C]33.4433[/C][C]3.55669[/C][/ROW]
[ROW][C]260[/C][C]35[/C][C]32.4245[/C][C]2.57545[/C][/ROW]
[ROW][C]261[/C][C]27[/C][C]31.6166[/C][C]-4.61662[/C][/ROW]
[ROW][C]262[/C][C]34[/C][C]35.263[/C][C]-1.26302[/C][/ROW]
[ROW][C]263[/C][C]40[/C][C]33.8739[/C][C]6.12608[/C][/ROW]
[ROW][C]264[/C][C]29[/C][C]32.6638[/C][C]-3.66379[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225831&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225831&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
14136.38784.61222
23934.59614.40391
33035.4496-5.4496
43134.5231-3.52309
53436.0389-2.03889
63533.02011.97988
73933.46855.53146
83436.1715-2.17153
93635.6340.36597
103736.93810.0619135
113834.14273.8573
123634.96171.03825
133835.3182.68204
143936.37332.62665
153336.8195-3.8195
163234.308-2.30796
173634.06181.93821
183837.25640.74362
193936.94792.05206
203233.9972-1.9972
213234.7546-2.75457
223133.8094-2.80941
233936.41142.58855
243737.0949-0.0949449
253934.49634.50372
264134.16356.83654
273635.22850.77148
283336.3606-3.36058
293334.3322-1.33218
303434.7645-0.764517
313134.0784-3.07841
322733.6325-6.63254
333733.79983.20016
343436.9647-2.9647
353432.89341.10656
363234.8619-2.86188
372932.8973-3.89733
383634.53271.46728
392933.886-4.88601
403534.57320.426795
413734.31392.6861
423434.361-0.361025
433833.97674.02333
443533.93641.06356
453832.37545.62458
463735.07121.92882
473837.57690.423146
483335.1455-2.14549
493636.3089-0.308929
503834.11623.88377
513236.8581-4.85812
523232.9428-0.942756
533233.8598-1.85976
543437.3628-3.36285
553233.6462-1.64624
563735.4771.52298
573934.98494.0151
582935.156-6.15602
593735.73481.26523
603534.79050.209499
613031.4537-1.45374
623834.81313.18687
633435.4125-1.41255
643134.8013-3.80131
653433.25510.744898
663535.9627-0.962655
673634.72451.27549
683031.0047-1.00471
693936.8292.171
703535.6406-0.640598
713835.57992.42011
723135.7507-4.75069
733436.6404-2.64043
743837.31620.683811
753431.55552.44454
763932.56746.43262
773735.77351.2265
783433.08180.918163
792833.2378-5.23781
803731.17025.82983
813335.278-2.27798
823536.1012-1.1012
833733.89393.10613
843234.483-2.48296
853333.211-0.211046
863836.57451.42546
873334.3764-1.37641
882933.0557-4.05567
893333.4261-0.426144
903135.5192-4.51922
913633.04682.95315
923537.4456-2.44564
933231.65450.345549
942932.6055-3.60548
953935.33733.66271
963734.69512.30489
973533.10861.89137
983734.54342.45657
993235.4475-3.44754
1003835.35622.64385
1013734.71782.28221
1023636.0452-0.0452037
1033231.88590.114067
1043336.4303-3.43031
1054032.99687.00322
1063835.08752.91248
1074136.36274.63734
1083634.27231.72766
1094336.96716.03286
1103034.618-4.61795
1113133.6817-2.68175
1123237.9677-5.96773
1133231.66380.3362
1143734.6272.37301
1153734.00482.99524
1163336.5454-3.54543
1173437.2316-3.23158
1183334.8901-1.8901
1193835.50592.49414
1203335.1538-2.15375
1213131.2837-0.283679
1223836.93911.06093
1233736.47890.521125
1243633.21072.78928
1253133.9691-2.96911
1263934.12564.87435
1274436.59737.40271
1283335.9911-2.99107
1293533.91431.08566
1303233.7839-1.78392
1312832.8861-4.88615
1324035.76854.23155
1332732.3959-5.39593
1343736.26070.739264
1353232.5297-0.529731
1362828.2113-0.211338
1373434.9371-0.937053
1383034.4255-4.42552
1393534.36410.635868
1403134.5749-3.57493
1413234.0908-2.09082
1423035.8142-5.81425
1433035.1282-5.12821
1443129.55651.44348
1454033.55296.4471
1463231.48070.519303
1473635.02460.975416
1483233.129-1.12899
1493533.25141.74863
1503836.95011.04992
1514235.38636.61366
1523435.9419-1.94194
1533536.4789-1.47894
1543834.42723.57281
1553333.2568-0.256816
1563632.92053.07948
1573235.58-3.58004
1583335.9328-2.93277
1593433.7810.219006
1603235.844-3.84396
1613435.3851-1.38506
1622729.9437-2.94368
1633130.16630.833738
1643833.27084.72917
1653435.5584-1.55842
1662431.1722-7.17218
1673033.5705-3.5705
1682629.6897-3.6897
1693435.5034-1.50337
1702734.3676-7.36756
1713731.80585.19419
1723635.16980.83019
1734134.22536.77473
1742929.269-0.268959
1753631.20064.79938
1763234.0655-2.06555
1773733.2093.79099
1783031.5682-1.56825
1793132.5405-1.5405
1803834.63633.36372
1813634.35261.64738
1823532.0982.90202
1833134.8434-3.8434
1843833.08854.91148
1852231.7013-9.70131
1863234.126-2.12595
1873633.48582.51422
1883932.68886.31119
1892830.3462-2.34617
1903234.1843-2.18427
1913232.3935-0.393479
1923836.33771.66231
1933233.1595-1.15949
1943535.0223-0.022295
1953232.8419-0.841862
1963735.59451.4055
1973432.27021.7298
1983335.2409-2.24093
1993332.6060.394046
2002632.5808-6.58075
2013031.8741-1.87409
2022431.7276-7.72757
2033432.16791.83206
2043432.65131.34865
2053333.713-0.712988
2063434.6217-0.621675
2073535.7058-0.705819
2083534.01590.984067
2093633.32022.67982
2103433.44810.551922
2113432.9431.057
2124138.6352.36497
2133236.014-4.01402
2143033-3.00003
2153533.68331.31669
2162829.8066-1.80662
2173334.5541-1.55407
2183934.12514.87488
2193633.23352.76646
2203636.2732-0.273152
2213533.27841.72158
2223833.81514.18494
2233332.56230.437684
2243133.0159-2.01593
2253431.92912.0709
2263234.6533-2.65331
2273132.6096-1.60958
2283332.96330.0366962
2293432.75341.24656
2303434.043-0.0429647
2313431.91262.08741
2323335.4484-2.44836
2333233.6459-1.64591
2344133.26487.73521
2353433.01070.989348
2363632.24333.75668
2373732.21374.78629
2383630.42445.57562
2392932.2516-3.25163
2403731.91025.08976
2412733.128-6.128
2423533.5021.49802
2432830.5257-2.52568
2443532.87762.12242
2453732.8644.13599
2462933.6242-4.62423
2473234.0568-2.05678
2483631.97734.02273
2491927.4685-8.46846
2502126.6868-5.68678
2513133.4717-2.47172
2523332.60780.392167
2533633.75942.24063
2543332.85950.140467
2553733.18053.81954
2563433.20190.798132
2573534.19570.80434
2583132.4789-1.47892
2593733.44333.55669
2603532.42452.57545
2612731.6166-4.61662
2623435.263-1.26302
2634033.87396.12608
2642932.6638-3.66379






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.7357940.5284120.264206
130.9084290.1831420.0915712
140.8446830.3106340.155317
150.8191610.3616780.180839
160.7879990.4240020.212001
170.7597690.4804620.240231
180.6883870.6232260.311613
190.6054830.7890340.394517
200.6169970.7660060.383003
210.6327980.7344040.367202
220.5607810.8784380.439219
230.5744230.8511530.425577
240.5013990.9972030.498601
250.602660.794680.39734
260.7877260.4245470.212274
270.7520170.4959660.247983
280.7370620.5258760.262938
290.7115260.5769490.288474
300.6585360.6829290.341464
310.6512320.6975370.348768
320.7830210.4339570.216979
330.7814510.4370970.218549
340.7437120.5125770.256288
350.6975650.6048710.302435
360.6642650.671470.335735
370.63980.7204010.3602
380.6124440.7751120.387556
390.6317510.7364990.368249
400.592140.8157210.40786
410.5960120.8079750.403988
420.5461790.9076420.453821
430.5386170.9227660.461383
440.4991320.9982640.500868
450.5770090.8459820.422991
460.5502970.8994050.449703
470.5083790.9832420.491621
480.4687620.9375230.531238
490.4238310.8476630.576169
500.4320310.8640610.567969
510.4682760.9365520.531724
520.4234180.8468350.576582
530.3825710.7651420.617429
540.3464880.6929750.653512
550.3074660.6149330.692534
560.3282010.6564030.671799
570.3646630.7293260.635337
580.4580280.9160560.541972
590.4265330.8530650.573467
600.389550.77910.61045
610.3503920.7007830.649608
620.3490910.6981820.650909
630.3136710.6273420.686329
640.3117530.6235060.688247
650.2765340.5530670.723466
660.2419080.4838150.758092
670.2179720.4359440.782028
680.2056890.4113780.794311
690.1950610.3901230.804939
700.1676920.3353840.832308
710.1620960.3241930.837904
720.1873810.3747610.812619
730.1728010.3456020.827199
740.149480.298960.85052
750.1323980.2647960.867602
760.1990170.3980340.800983
770.1745850.349170.825415
780.1501760.3003520.849824
790.2078140.4156270.792186
800.2377610.4755210.762239
810.2231410.4462820.776859
820.1963470.3926930.803653
830.1879990.3759990.812001
840.1772690.3545370.822731
850.1534990.3069970.846501
860.1410830.2821650.858917
870.1239730.2479450.876027
880.1353120.2706240.864688
890.1153290.2306580.884671
900.1217540.2435080.878246
910.1168090.2336190.883191
920.1030540.2061070.896946
930.08733250.1746650.912668
940.09306540.1861310.906935
950.1033510.2067030.896649
960.09950560.1990110.900494
970.08851740.1770350.911483
980.08260790.1652160.917392
990.08030530.1606110.919695
1000.07621040.1524210.92379
1010.0729350.145870.927065
1020.06079950.1215990.939201
1030.05054220.1010840.949458
1040.04725610.09451220.952744
1050.09241120.1848220.907589
1060.09134050.1826810.908659
1070.1151040.2302080.884896
1080.1033690.2067390.896631
1090.1606190.3212390.839381
1100.1787720.3575450.821228
1110.1713710.3427430.828629
1120.2034380.4068760.796562
1130.1878540.3757070.812146
1140.1784480.3568960.821552
1150.1762310.3524620.823769
1160.1740220.3480450.825978
1170.1659130.3318260.834087
1180.148580.2971610.85142
1190.143330.2866610.85667
1200.1298280.2596560.870172
1210.113540.227080.88646
1220.1013620.2027240.898638
1230.08782580.1756520.912174
1240.08402640.1680530.915974
1250.07978760.1595750.920212
1260.09892940.1978590.901071
1270.1838660.3677320.816134
1280.177670.355340.82233
1290.1585130.3170270.841487
1300.1426250.285250.857375
1310.1620220.3240440.837978
1320.1809230.3618450.819077
1330.2168580.4337170.783142
1340.1940650.3881310.805935
1350.1708530.3417070.829147
1360.1499350.2998710.850065
1370.1306990.2613980.869301
1380.1410690.2821380.858931
1390.1229190.2458380.877081
1400.1219920.2439830.878008
1410.1108590.2217180.889141
1420.1400210.2800420.859979
1430.1614540.3229080.838546
1440.146530.2930590.85347
1450.2226940.4453880.777306
1460.1994750.398950.800525
1470.1805330.3610660.819467
1480.15870.3174010.8413
1490.1466150.293230.853385
1500.1300310.2600610.869969
1510.2110450.4220890.788955
1520.1910460.3820920.808954
1530.1717210.3434420.828279
1540.1955370.3910750.804463
1550.174180.348360.82582
1560.1930980.3861970.806902
1570.1829940.3659870.817006
1580.1674490.3348980.832551
1590.1594680.3189350.840532
1600.1480350.296070.851965
1610.1277740.2555490.872226
1620.1203470.2406930.879653
1630.1103490.2206990.889651
1640.1435840.2871680.856416
1650.1293050.258610.870695
1660.2113520.4227050.788648
1670.2104560.4209120.789544
1680.2016450.403290.798355
1690.182540.3650790.81746
1700.2895450.5790910.710455
1710.3230320.6460650.676968
1720.292020.584040.70798
1730.3918190.7836380.608181
1740.3566840.7133670.643316
1750.4291150.858230.570885
1760.4006970.8013940.599303
1770.4046610.8093230.595339
1780.370980.741960.62902
1790.339460.678920.66054
1800.3385970.6771940.661403
1810.3084670.6169340.691533
1820.3073320.6146630.692668
1830.3188440.6376880.681156
1840.397050.7941010.60295
1850.5942870.8114250.405713
1860.5704160.8591680.429584
1870.5598890.8802230.440111
1880.7254080.5491850.274592
1890.6979210.6041580.302079
1900.6951280.6097450.304872
1910.6607380.6785240.339262
1920.631350.7372990.36865
1930.5963920.8072160.403608
1940.569160.861680.43084
1950.5280960.9438080.471904
1960.4897250.9794490.510275
1970.4733030.9466070.526697
1980.4434540.8869080.556546
1990.4021620.8043240.597838
2000.4622140.9244270.537786
2010.4309160.8618330.569084
2020.5746240.8507520.425376
2030.5662380.8675250.433762
2040.5260460.9479080.473954
2050.4827740.9655480.517226
2060.4439190.8878380.556081
2070.4132820.8265630.586718
2080.3767830.7535660.623217
2090.3498660.6997310.650134
2100.3142710.6285420.685729
2110.2763770.5527540.723623
2120.2450850.4901710.754915
2130.3084460.6168920.691554
2140.3089110.6178220.691089
2150.271360.5427210.72864
2160.2386710.4773420.761329
2170.2205870.4411750.779413
2180.2298030.4596060.770197
2190.2001350.4002690.799865
2200.1939180.3878360.806082
2210.1640940.3281880.835906
2220.1719460.3438920.828054
2230.1422550.284510.857745
2240.1234790.2469580.876521
2250.1845330.3690650.815467
2260.1689820.3379630.831018
2270.1519390.3038770.848061
2280.1486010.2972020.851399
2290.1211220.2422430.878878
2300.09587430.1917490.904126
2310.08592020.171840.91408
2320.1971270.3942550.802873
2330.1962020.3924040.803798
2340.2400870.4801740.759913
2350.193860.387720.80614
2360.2004520.4009030.799548
2370.1751940.3503890.824806
2380.2581340.5162690.741866
2390.2089830.4179660.791017
2400.458690.917380.54131
2410.4504020.9008040.549598
2420.4021560.8043120.597844
2430.3276820.6553650.672318
2440.338390.676780.66161
2450.3681450.736290.631855
2460.461180.922360.53882
2470.4568270.9136550.543173
2480.4184780.8369570.581522
2490.5934790.8130420.406521
2500.6137560.7724890.386244
2510.5418990.9162030.458101
2520.5330110.9339780.466989

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.735794 & 0.528412 & 0.264206 \tabularnewline
13 & 0.908429 & 0.183142 & 0.0915712 \tabularnewline
14 & 0.844683 & 0.310634 & 0.155317 \tabularnewline
15 & 0.819161 & 0.361678 & 0.180839 \tabularnewline
16 & 0.787999 & 0.424002 & 0.212001 \tabularnewline
17 & 0.759769 & 0.480462 & 0.240231 \tabularnewline
18 & 0.688387 & 0.623226 & 0.311613 \tabularnewline
19 & 0.605483 & 0.789034 & 0.394517 \tabularnewline
20 & 0.616997 & 0.766006 & 0.383003 \tabularnewline
21 & 0.632798 & 0.734404 & 0.367202 \tabularnewline
22 & 0.560781 & 0.878438 & 0.439219 \tabularnewline
23 & 0.574423 & 0.851153 & 0.425577 \tabularnewline
24 & 0.501399 & 0.997203 & 0.498601 \tabularnewline
25 & 0.60266 & 0.79468 & 0.39734 \tabularnewline
26 & 0.787726 & 0.424547 & 0.212274 \tabularnewline
27 & 0.752017 & 0.495966 & 0.247983 \tabularnewline
28 & 0.737062 & 0.525876 & 0.262938 \tabularnewline
29 & 0.711526 & 0.576949 & 0.288474 \tabularnewline
30 & 0.658536 & 0.682929 & 0.341464 \tabularnewline
31 & 0.651232 & 0.697537 & 0.348768 \tabularnewline
32 & 0.783021 & 0.433957 & 0.216979 \tabularnewline
33 & 0.781451 & 0.437097 & 0.218549 \tabularnewline
34 & 0.743712 & 0.512577 & 0.256288 \tabularnewline
35 & 0.697565 & 0.604871 & 0.302435 \tabularnewline
36 & 0.664265 & 0.67147 & 0.335735 \tabularnewline
37 & 0.6398 & 0.720401 & 0.3602 \tabularnewline
38 & 0.612444 & 0.775112 & 0.387556 \tabularnewline
39 & 0.631751 & 0.736499 & 0.368249 \tabularnewline
40 & 0.59214 & 0.815721 & 0.40786 \tabularnewline
41 & 0.596012 & 0.807975 & 0.403988 \tabularnewline
42 & 0.546179 & 0.907642 & 0.453821 \tabularnewline
43 & 0.538617 & 0.922766 & 0.461383 \tabularnewline
44 & 0.499132 & 0.998264 & 0.500868 \tabularnewline
45 & 0.577009 & 0.845982 & 0.422991 \tabularnewline
46 & 0.550297 & 0.899405 & 0.449703 \tabularnewline
47 & 0.508379 & 0.983242 & 0.491621 \tabularnewline
48 & 0.468762 & 0.937523 & 0.531238 \tabularnewline
49 & 0.423831 & 0.847663 & 0.576169 \tabularnewline
50 & 0.432031 & 0.864061 & 0.567969 \tabularnewline
51 & 0.468276 & 0.936552 & 0.531724 \tabularnewline
52 & 0.423418 & 0.846835 & 0.576582 \tabularnewline
53 & 0.382571 & 0.765142 & 0.617429 \tabularnewline
54 & 0.346488 & 0.692975 & 0.653512 \tabularnewline
55 & 0.307466 & 0.614933 & 0.692534 \tabularnewline
56 & 0.328201 & 0.656403 & 0.671799 \tabularnewline
57 & 0.364663 & 0.729326 & 0.635337 \tabularnewline
58 & 0.458028 & 0.916056 & 0.541972 \tabularnewline
59 & 0.426533 & 0.853065 & 0.573467 \tabularnewline
60 & 0.38955 & 0.7791 & 0.61045 \tabularnewline
61 & 0.350392 & 0.700783 & 0.649608 \tabularnewline
62 & 0.349091 & 0.698182 & 0.650909 \tabularnewline
63 & 0.313671 & 0.627342 & 0.686329 \tabularnewline
64 & 0.311753 & 0.623506 & 0.688247 \tabularnewline
65 & 0.276534 & 0.553067 & 0.723466 \tabularnewline
66 & 0.241908 & 0.483815 & 0.758092 \tabularnewline
67 & 0.217972 & 0.435944 & 0.782028 \tabularnewline
68 & 0.205689 & 0.411378 & 0.794311 \tabularnewline
69 & 0.195061 & 0.390123 & 0.804939 \tabularnewline
70 & 0.167692 & 0.335384 & 0.832308 \tabularnewline
71 & 0.162096 & 0.324193 & 0.837904 \tabularnewline
72 & 0.187381 & 0.374761 & 0.812619 \tabularnewline
73 & 0.172801 & 0.345602 & 0.827199 \tabularnewline
74 & 0.14948 & 0.29896 & 0.85052 \tabularnewline
75 & 0.132398 & 0.264796 & 0.867602 \tabularnewline
76 & 0.199017 & 0.398034 & 0.800983 \tabularnewline
77 & 0.174585 & 0.34917 & 0.825415 \tabularnewline
78 & 0.150176 & 0.300352 & 0.849824 \tabularnewline
79 & 0.207814 & 0.415627 & 0.792186 \tabularnewline
80 & 0.237761 & 0.475521 & 0.762239 \tabularnewline
81 & 0.223141 & 0.446282 & 0.776859 \tabularnewline
82 & 0.196347 & 0.392693 & 0.803653 \tabularnewline
83 & 0.187999 & 0.375999 & 0.812001 \tabularnewline
84 & 0.177269 & 0.354537 & 0.822731 \tabularnewline
85 & 0.153499 & 0.306997 & 0.846501 \tabularnewline
86 & 0.141083 & 0.282165 & 0.858917 \tabularnewline
87 & 0.123973 & 0.247945 & 0.876027 \tabularnewline
88 & 0.135312 & 0.270624 & 0.864688 \tabularnewline
89 & 0.115329 & 0.230658 & 0.884671 \tabularnewline
90 & 0.121754 & 0.243508 & 0.878246 \tabularnewline
91 & 0.116809 & 0.233619 & 0.883191 \tabularnewline
92 & 0.103054 & 0.206107 & 0.896946 \tabularnewline
93 & 0.0873325 & 0.174665 & 0.912668 \tabularnewline
94 & 0.0930654 & 0.186131 & 0.906935 \tabularnewline
95 & 0.103351 & 0.206703 & 0.896649 \tabularnewline
96 & 0.0995056 & 0.199011 & 0.900494 \tabularnewline
97 & 0.0885174 & 0.177035 & 0.911483 \tabularnewline
98 & 0.0826079 & 0.165216 & 0.917392 \tabularnewline
99 & 0.0803053 & 0.160611 & 0.919695 \tabularnewline
100 & 0.0762104 & 0.152421 & 0.92379 \tabularnewline
101 & 0.072935 & 0.14587 & 0.927065 \tabularnewline
102 & 0.0607995 & 0.121599 & 0.939201 \tabularnewline
103 & 0.0505422 & 0.101084 & 0.949458 \tabularnewline
104 & 0.0472561 & 0.0945122 & 0.952744 \tabularnewline
105 & 0.0924112 & 0.184822 & 0.907589 \tabularnewline
106 & 0.0913405 & 0.182681 & 0.908659 \tabularnewline
107 & 0.115104 & 0.230208 & 0.884896 \tabularnewline
108 & 0.103369 & 0.206739 & 0.896631 \tabularnewline
109 & 0.160619 & 0.321239 & 0.839381 \tabularnewline
110 & 0.178772 & 0.357545 & 0.821228 \tabularnewline
111 & 0.171371 & 0.342743 & 0.828629 \tabularnewline
112 & 0.203438 & 0.406876 & 0.796562 \tabularnewline
113 & 0.187854 & 0.375707 & 0.812146 \tabularnewline
114 & 0.178448 & 0.356896 & 0.821552 \tabularnewline
115 & 0.176231 & 0.352462 & 0.823769 \tabularnewline
116 & 0.174022 & 0.348045 & 0.825978 \tabularnewline
117 & 0.165913 & 0.331826 & 0.834087 \tabularnewline
118 & 0.14858 & 0.297161 & 0.85142 \tabularnewline
119 & 0.14333 & 0.286661 & 0.85667 \tabularnewline
120 & 0.129828 & 0.259656 & 0.870172 \tabularnewline
121 & 0.11354 & 0.22708 & 0.88646 \tabularnewline
122 & 0.101362 & 0.202724 & 0.898638 \tabularnewline
123 & 0.0878258 & 0.175652 & 0.912174 \tabularnewline
124 & 0.0840264 & 0.168053 & 0.915974 \tabularnewline
125 & 0.0797876 & 0.159575 & 0.920212 \tabularnewline
126 & 0.0989294 & 0.197859 & 0.901071 \tabularnewline
127 & 0.183866 & 0.367732 & 0.816134 \tabularnewline
128 & 0.17767 & 0.35534 & 0.82233 \tabularnewline
129 & 0.158513 & 0.317027 & 0.841487 \tabularnewline
130 & 0.142625 & 0.28525 & 0.857375 \tabularnewline
131 & 0.162022 & 0.324044 & 0.837978 \tabularnewline
132 & 0.180923 & 0.361845 & 0.819077 \tabularnewline
133 & 0.216858 & 0.433717 & 0.783142 \tabularnewline
134 & 0.194065 & 0.388131 & 0.805935 \tabularnewline
135 & 0.170853 & 0.341707 & 0.829147 \tabularnewline
136 & 0.149935 & 0.299871 & 0.850065 \tabularnewline
137 & 0.130699 & 0.261398 & 0.869301 \tabularnewline
138 & 0.141069 & 0.282138 & 0.858931 \tabularnewline
139 & 0.122919 & 0.245838 & 0.877081 \tabularnewline
140 & 0.121992 & 0.243983 & 0.878008 \tabularnewline
141 & 0.110859 & 0.221718 & 0.889141 \tabularnewline
142 & 0.140021 & 0.280042 & 0.859979 \tabularnewline
143 & 0.161454 & 0.322908 & 0.838546 \tabularnewline
144 & 0.14653 & 0.293059 & 0.85347 \tabularnewline
145 & 0.222694 & 0.445388 & 0.777306 \tabularnewline
146 & 0.199475 & 0.39895 & 0.800525 \tabularnewline
147 & 0.180533 & 0.361066 & 0.819467 \tabularnewline
148 & 0.1587 & 0.317401 & 0.8413 \tabularnewline
149 & 0.146615 & 0.29323 & 0.853385 \tabularnewline
150 & 0.130031 & 0.260061 & 0.869969 \tabularnewline
151 & 0.211045 & 0.422089 & 0.788955 \tabularnewline
152 & 0.191046 & 0.382092 & 0.808954 \tabularnewline
153 & 0.171721 & 0.343442 & 0.828279 \tabularnewline
154 & 0.195537 & 0.391075 & 0.804463 \tabularnewline
155 & 0.17418 & 0.34836 & 0.82582 \tabularnewline
156 & 0.193098 & 0.386197 & 0.806902 \tabularnewline
157 & 0.182994 & 0.365987 & 0.817006 \tabularnewline
158 & 0.167449 & 0.334898 & 0.832551 \tabularnewline
159 & 0.159468 & 0.318935 & 0.840532 \tabularnewline
160 & 0.148035 & 0.29607 & 0.851965 \tabularnewline
161 & 0.127774 & 0.255549 & 0.872226 \tabularnewline
162 & 0.120347 & 0.240693 & 0.879653 \tabularnewline
163 & 0.110349 & 0.220699 & 0.889651 \tabularnewline
164 & 0.143584 & 0.287168 & 0.856416 \tabularnewline
165 & 0.129305 & 0.25861 & 0.870695 \tabularnewline
166 & 0.211352 & 0.422705 & 0.788648 \tabularnewline
167 & 0.210456 & 0.420912 & 0.789544 \tabularnewline
168 & 0.201645 & 0.40329 & 0.798355 \tabularnewline
169 & 0.18254 & 0.365079 & 0.81746 \tabularnewline
170 & 0.289545 & 0.579091 & 0.710455 \tabularnewline
171 & 0.323032 & 0.646065 & 0.676968 \tabularnewline
172 & 0.29202 & 0.58404 & 0.70798 \tabularnewline
173 & 0.391819 & 0.783638 & 0.608181 \tabularnewline
174 & 0.356684 & 0.713367 & 0.643316 \tabularnewline
175 & 0.429115 & 0.85823 & 0.570885 \tabularnewline
176 & 0.400697 & 0.801394 & 0.599303 \tabularnewline
177 & 0.404661 & 0.809323 & 0.595339 \tabularnewline
178 & 0.37098 & 0.74196 & 0.62902 \tabularnewline
179 & 0.33946 & 0.67892 & 0.66054 \tabularnewline
180 & 0.338597 & 0.677194 & 0.661403 \tabularnewline
181 & 0.308467 & 0.616934 & 0.691533 \tabularnewline
182 & 0.307332 & 0.614663 & 0.692668 \tabularnewline
183 & 0.318844 & 0.637688 & 0.681156 \tabularnewline
184 & 0.39705 & 0.794101 & 0.60295 \tabularnewline
185 & 0.594287 & 0.811425 & 0.405713 \tabularnewline
186 & 0.570416 & 0.859168 & 0.429584 \tabularnewline
187 & 0.559889 & 0.880223 & 0.440111 \tabularnewline
188 & 0.725408 & 0.549185 & 0.274592 \tabularnewline
189 & 0.697921 & 0.604158 & 0.302079 \tabularnewline
190 & 0.695128 & 0.609745 & 0.304872 \tabularnewline
191 & 0.660738 & 0.678524 & 0.339262 \tabularnewline
192 & 0.63135 & 0.737299 & 0.36865 \tabularnewline
193 & 0.596392 & 0.807216 & 0.403608 \tabularnewline
194 & 0.56916 & 0.86168 & 0.43084 \tabularnewline
195 & 0.528096 & 0.943808 & 0.471904 \tabularnewline
196 & 0.489725 & 0.979449 & 0.510275 \tabularnewline
197 & 0.473303 & 0.946607 & 0.526697 \tabularnewline
198 & 0.443454 & 0.886908 & 0.556546 \tabularnewline
199 & 0.402162 & 0.804324 & 0.597838 \tabularnewline
200 & 0.462214 & 0.924427 & 0.537786 \tabularnewline
201 & 0.430916 & 0.861833 & 0.569084 \tabularnewline
202 & 0.574624 & 0.850752 & 0.425376 \tabularnewline
203 & 0.566238 & 0.867525 & 0.433762 \tabularnewline
204 & 0.526046 & 0.947908 & 0.473954 \tabularnewline
205 & 0.482774 & 0.965548 & 0.517226 \tabularnewline
206 & 0.443919 & 0.887838 & 0.556081 \tabularnewline
207 & 0.413282 & 0.826563 & 0.586718 \tabularnewline
208 & 0.376783 & 0.753566 & 0.623217 \tabularnewline
209 & 0.349866 & 0.699731 & 0.650134 \tabularnewline
210 & 0.314271 & 0.628542 & 0.685729 \tabularnewline
211 & 0.276377 & 0.552754 & 0.723623 \tabularnewline
212 & 0.245085 & 0.490171 & 0.754915 \tabularnewline
213 & 0.308446 & 0.616892 & 0.691554 \tabularnewline
214 & 0.308911 & 0.617822 & 0.691089 \tabularnewline
215 & 0.27136 & 0.542721 & 0.72864 \tabularnewline
216 & 0.238671 & 0.477342 & 0.761329 \tabularnewline
217 & 0.220587 & 0.441175 & 0.779413 \tabularnewline
218 & 0.229803 & 0.459606 & 0.770197 \tabularnewline
219 & 0.200135 & 0.400269 & 0.799865 \tabularnewline
220 & 0.193918 & 0.387836 & 0.806082 \tabularnewline
221 & 0.164094 & 0.328188 & 0.835906 \tabularnewline
222 & 0.171946 & 0.343892 & 0.828054 \tabularnewline
223 & 0.142255 & 0.28451 & 0.857745 \tabularnewline
224 & 0.123479 & 0.246958 & 0.876521 \tabularnewline
225 & 0.184533 & 0.369065 & 0.815467 \tabularnewline
226 & 0.168982 & 0.337963 & 0.831018 \tabularnewline
227 & 0.151939 & 0.303877 & 0.848061 \tabularnewline
228 & 0.148601 & 0.297202 & 0.851399 \tabularnewline
229 & 0.121122 & 0.242243 & 0.878878 \tabularnewline
230 & 0.0958743 & 0.191749 & 0.904126 \tabularnewline
231 & 0.0859202 & 0.17184 & 0.91408 \tabularnewline
232 & 0.197127 & 0.394255 & 0.802873 \tabularnewline
233 & 0.196202 & 0.392404 & 0.803798 \tabularnewline
234 & 0.240087 & 0.480174 & 0.759913 \tabularnewline
235 & 0.19386 & 0.38772 & 0.80614 \tabularnewline
236 & 0.200452 & 0.400903 & 0.799548 \tabularnewline
237 & 0.175194 & 0.350389 & 0.824806 \tabularnewline
238 & 0.258134 & 0.516269 & 0.741866 \tabularnewline
239 & 0.208983 & 0.417966 & 0.791017 \tabularnewline
240 & 0.45869 & 0.91738 & 0.54131 \tabularnewline
241 & 0.450402 & 0.900804 & 0.549598 \tabularnewline
242 & 0.402156 & 0.804312 & 0.597844 \tabularnewline
243 & 0.327682 & 0.655365 & 0.672318 \tabularnewline
244 & 0.33839 & 0.67678 & 0.66161 \tabularnewline
245 & 0.368145 & 0.73629 & 0.631855 \tabularnewline
246 & 0.46118 & 0.92236 & 0.53882 \tabularnewline
247 & 0.456827 & 0.913655 & 0.543173 \tabularnewline
248 & 0.418478 & 0.836957 & 0.581522 \tabularnewline
249 & 0.593479 & 0.813042 & 0.406521 \tabularnewline
250 & 0.613756 & 0.772489 & 0.386244 \tabularnewline
251 & 0.541899 & 0.916203 & 0.458101 \tabularnewline
252 & 0.533011 & 0.933978 & 0.466989 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225831&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]12[/C][C]0.735794[/C][C]0.528412[/C][C]0.264206[/C][/ROW]
[ROW][C]13[/C][C]0.908429[/C][C]0.183142[/C][C]0.0915712[/C][/ROW]
[ROW][C]14[/C][C]0.844683[/C][C]0.310634[/C][C]0.155317[/C][/ROW]
[ROW][C]15[/C][C]0.819161[/C][C]0.361678[/C][C]0.180839[/C][/ROW]
[ROW][C]16[/C][C]0.787999[/C][C]0.424002[/C][C]0.212001[/C][/ROW]
[ROW][C]17[/C][C]0.759769[/C][C]0.480462[/C][C]0.240231[/C][/ROW]
[ROW][C]18[/C][C]0.688387[/C][C]0.623226[/C][C]0.311613[/C][/ROW]
[ROW][C]19[/C][C]0.605483[/C][C]0.789034[/C][C]0.394517[/C][/ROW]
[ROW][C]20[/C][C]0.616997[/C][C]0.766006[/C][C]0.383003[/C][/ROW]
[ROW][C]21[/C][C]0.632798[/C][C]0.734404[/C][C]0.367202[/C][/ROW]
[ROW][C]22[/C][C]0.560781[/C][C]0.878438[/C][C]0.439219[/C][/ROW]
[ROW][C]23[/C][C]0.574423[/C][C]0.851153[/C][C]0.425577[/C][/ROW]
[ROW][C]24[/C][C]0.501399[/C][C]0.997203[/C][C]0.498601[/C][/ROW]
[ROW][C]25[/C][C]0.60266[/C][C]0.79468[/C][C]0.39734[/C][/ROW]
[ROW][C]26[/C][C]0.787726[/C][C]0.424547[/C][C]0.212274[/C][/ROW]
[ROW][C]27[/C][C]0.752017[/C][C]0.495966[/C][C]0.247983[/C][/ROW]
[ROW][C]28[/C][C]0.737062[/C][C]0.525876[/C][C]0.262938[/C][/ROW]
[ROW][C]29[/C][C]0.711526[/C][C]0.576949[/C][C]0.288474[/C][/ROW]
[ROW][C]30[/C][C]0.658536[/C][C]0.682929[/C][C]0.341464[/C][/ROW]
[ROW][C]31[/C][C]0.651232[/C][C]0.697537[/C][C]0.348768[/C][/ROW]
[ROW][C]32[/C][C]0.783021[/C][C]0.433957[/C][C]0.216979[/C][/ROW]
[ROW][C]33[/C][C]0.781451[/C][C]0.437097[/C][C]0.218549[/C][/ROW]
[ROW][C]34[/C][C]0.743712[/C][C]0.512577[/C][C]0.256288[/C][/ROW]
[ROW][C]35[/C][C]0.697565[/C][C]0.604871[/C][C]0.302435[/C][/ROW]
[ROW][C]36[/C][C]0.664265[/C][C]0.67147[/C][C]0.335735[/C][/ROW]
[ROW][C]37[/C][C]0.6398[/C][C]0.720401[/C][C]0.3602[/C][/ROW]
[ROW][C]38[/C][C]0.612444[/C][C]0.775112[/C][C]0.387556[/C][/ROW]
[ROW][C]39[/C][C]0.631751[/C][C]0.736499[/C][C]0.368249[/C][/ROW]
[ROW][C]40[/C][C]0.59214[/C][C]0.815721[/C][C]0.40786[/C][/ROW]
[ROW][C]41[/C][C]0.596012[/C][C]0.807975[/C][C]0.403988[/C][/ROW]
[ROW][C]42[/C][C]0.546179[/C][C]0.907642[/C][C]0.453821[/C][/ROW]
[ROW][C]43[/C][C]0.538617[/C][C]0.922766[/C][C]0.461383[/C][/ROW]
[ROW][C]44[/C][C]0.499132[/C][C]0.998264[/C][C]0.500868[/C][/ROW]
[ROW][C]45[/C][C]0.577009[/C][C]0.845982[/C][C]0.422991[/C][/ROW]
[ROW][C]46[/C][C]0.550297[/C][C]0.899405[/C][C]0.449703[/C][/ROW]
[ROW][C]47[/C][C]0.508379[/C][C]0.983242[/C][C]0.491621[/C][/ROW]
[ROW][C]48[/C][C]0.468762[/C][C]0.937523[/C][C]0.531238[/C][/ROW]
[ROW][C]49[/C][C]0.423831[/C][C]0.847663[/C][C]0.576169[/C][/ROW]
[ROW][C]50[/C][C]0.432031[/C][C]0.864061[/C][C]0.567969[/C][/ROW]
[ROW][C]51[/C][C]0.468276[/C][C]0.936552[/C][C]0.531724[/C][/ROW]
[ROW][C]52[/C][C]0.423418[/C][C]0.846835[/C][C]0.576582[/C][/ROW]
[ROW][C]53[/C][C]0.382571[/C][C]0.765142[/C][C]0.617429[/C][/ROW]
[ROW][C]54[/C][C]0.346488[/C][C]0.692975[/C][C]0.653512[/C][/ROW]
[ROW][C]55[/C][C]0.307466[/C][C]0.614933[/C][C]0.692534[/C][/ROW]
[ROW][C]56[/C][C]0.328201[/C][C]0.656403[/C][C]0.671799[/C][/ROW]
[ROW][C]57[/C][C]0.364663[/C][C]0.729326[/C][C]0.635337[/C][/ROW]
[ROW][C]58[/C][C]0.458028[/C][C]0.916056[/C][C]0.541972[/C][/ROW]
[ROW][C]59[/C][C]0.426533[/C][C]0.853065[/C][C]0.573467[/C][/ROW]
[ROW][C]60[/C][C]0.38955[/C][C]0.7791[/C][C]0.61045[/C][/ROW]
[ROW][C]61[/C][C]0.350392[/C][C]0.700783[/C][C]0.649608[/C][/ROW]
[ROW][C]62[/C][C]0.349091[/C][C]0.698182[/C][C]0.650909[/C][/ROW]
[ROW][C]63[/C][C]0.313671[/C][C]0.627342[/C][C]0.686329[/C][/ROW]
[ROW][C]64[/C][C]0.311753[/C][C]0.623506[/C][C]0.688247[/C][/ROW]
[ROW][C]65[/C][C]0.276534[/C][C]0.553067[/C][C]0.723466[/C][/ROW]
[ROW][C]66[/C][C]0.241908[/C][C]0.483815[/C][C]0.758092[/C][/ROW]
[ROW][C]67[/C][C]0.217972[/C][C]0.435944[/C][C]0.782028[/C][/ROW]
[ROW][C]68[/C][C]0.205689[/C][C]0.411378[/C][C]0.794311[/C][/ROW]
[ROW][C]69[/C][C]0.195061[/C][C]0.390123[/C][C]0.804939[/C][/ROW]
[ROW][C]70[/C][C]0.167692[/C][C]0.335384[/C][C]0.832308[/C][/ROW]
[ROW][C]71[/C][C]0.162096[/C][C]0.324193[/C][C]0.837904[/C][/ROW]
[ROW][C]72[/C][C]0.187381[/C][C]0.374761[/C][C]0.812619[/C][/ROW]
[ROW][C]73[/C][C]0.172801[/C][C]0.345602[/C][C]0.827199[/C][/ROW]
[ROW][C]74[/C][C]0.14948[/C][C]0.29896[/C][C]0.85052[/C][/ROW]
[ROW][C]75[/C][C]0.132398[/C][C]0.264796[/C][C]0.867602[/C][/ROW]
[ROW][C]76[/C][C]0.199017[/C][C]0.398034[/C][C]0.800983[/C][/ROW]
[ROW][C]77[/C][C]0.174585[/C][C]0.34917[/C][C]0.825415[/C][/ROW]
[ROW][C]78[/C][C]0.150176[/C][C]0.300352[/C][C]0.849824[/C][/ROW]
[ROW][C]79[/C][C]0.207814[/C][C]0.415627[/C][C]0.792186[/C][/ROW]
[ROW][C]80[/C][C]0.237761[/C][C]0.475521[/C][C]0.762239[/C][/ROW]
[ROW][C]81[/C][C]0.223141[/C][C]0.446282[/C][C]0.776859[/C][/ROW]
[ROW][C]82[/C][C]0.196347[/C][C]0.392693[/C][C]0.803653[/C][/ROW]
[ROW][C]83[/C][C]0.187999[/C][C]0.375999[/C][C]0.812001[/C][/ROW]
[ROW][C]84[/C][C]0.177269[/C][C]0.354537[/C][C]0.822731[/C][/ROW]
[ROW][C]85[/C][C]0.153499[/C][C]0.306997[/C][C]0.846501[/C][/ROW]
[ROW][C]86[/C][C]0.141083[/C][C]0.282165[/C][C]0.858917[/C][/ROW]
[ROW][C]87[/C][C]0.123973[/C][C]0.247945[/C][C]0.876027[/C][/ROW]
[ROW][C]88[/C][C]0.135312[/C][C]0.270624[/C][C]0.864688[/C][/ROW]
[ROW][C]89[/C][C]0.115329[/C][C]0.230658[/C][C]0.884671[/C][/ROW]
[ROW][C]90[/C][C]0.121754[/C][C]0.243508[/C][C]0.878246[/C][/ROW]
[ROW][C]91[/C][C]0.116809[/C][C]0.233619[/C][C]0.883191[/C][/ROW]
[ROW][C]92[/C][C]0.103054[/C][C]0.206107[/C][C]0.896946[/C][/ROW]
[ROW][C]93[/C][C]0.0873325[/C][C]0.174665[/C][C]0.912668[/C][/ROW]
[ROW][C]94[/C][C]0.0930654[/C][C]0.186131[/C][C]0.906935[/C][/ROW]
[ROW][C]95[/C][C]0.103351[/C][C]0.206703[/C][C]0.896649[/C][/ROW]
[ROW][C]96[/C][C]0.0995056[/C][C]0.199011[/C][C]0.900494[/C][/ROW]
[ROW][C]97[/C][C]0.0885174[/C][C]0.177035[/C][C]0.911483[/C][/ROW]
[ROW][C]98[/C][C]0.0826079[/C][C]0.165216[/C][C]0.917392[/C][/ROW]
[ROW][C]99[/C][C]0.0803053[/C][C]0.160611[/C][C]0.919695[/C][/ROW]
[ROW][C]100[/C][C]0.0762104[/C][C]0.152421[/C][C]0.92379[/C][/ROW]
[ROW][C]101[/C][C]0.072935[/C][C]0.14587[/C][C]0.927065[/C][/ROW]
[ROW][C]102[/C][C]0.0607995[/C][C]0.121599[/C][C]0.939201[/C][/ROW]
[ROW][C]103[/C][C]0.0505422[/C][C]0.101084[/C][C]0.949458[/C][/ROW]
[ROW][C]104[/C][C]0.0472561[/C][C]0.0945122[/C][C]0.952744[/C][/ROW]
[ROW][C]105[/C][C]0.0924112[/C][C]0.184822[/C][C]0.907589[/C][/ROW]
[ROW][C]106[/C][C]0.0913405[/C][C]0.182681[/C][C]0.908659[/C][/ROW]
[ROW][C]107[/C][C]0.115104[/C][C]0.230208[/C][C]0.884896[/C][/ROW]
[ROW][C]108[/C][C]0.103369[/C][C]0.206739[/C][C]0.896631[/C][/ROW]
[ROW][C]109[/C][C]0.160619[/C][C]0.321239[/C][C]0.839381[/C][/ROW]
[ROW][C]110[/C][C]0.178772[/C][C]0.357545[/C][C]0.821228[/C][/ROW]
[ROW][C]111[/C][C]0.171371[/C][C]0.342743[/C][C]0.828629[/C][/ROW]
[ROW][C]112[/C][C]0.203438[/C][C]0.406876[/C][C]0.796562[/C][/ROW]
[ROW][C]113[/C][C]0.187854[/C][C]0.375707[/C][C]0.812146[/C][/ROW]
[ROW][C]114[/C][C]0.178448[/C][C]0.356896[/C][C]0.821552[/C][/ROW]
[ROW][C]115[/C][C]0.176231[/C][C]0.352462[/C][C]0.823769[/C][/ROW]
[ROW][C]116[/C][C]0.174022[/C][C]0.348045[/C][C]0.825978[/C][/ROW]
[ROW][C]117[/C][C]0.165913[/C][C]0.331826[/C][C]0.834087[/C][/ROW]
[ROW][C]118[/C][C]0.14858[/C][C]0.297161[/C][C]0.85142[/C][/ROW]
[ROW][C]119[/C][C]0.14333[/C][C]0.286661[/C][C]0.85667[/C][/ROW]
[ROW][C]120[/C][C]0.129828[/C][C]0.259656[/C][C]0.870172[/C][/ROW]
[ROW][C]121[/C][C]0.11354[/C][C]0.22708[/C][C]0.88646[/C][/ROW]
[ROW][C]122[/C][C]0.101362[/C][C]0.202724[/C][C]0.898638[/C][/ROW]
[ROW][C]123[/C][C]0.0878258[/C][C]0.175652[/C][C]0.912174[/C][/ROW]
[ROW][C]124[/C][C]0.0840264[/C][C]0.168053[/C][C]0.915974[/C][/ROW]
[ROW][C]125[/C][C]0.0797876[/C][C]0.159575[/C][C]0.920212[/C][/ROW]
[ROW][C]126[/C][C]0.0989294[/C][C]0.197859[/C][C]0.901071[/C][/ROW]
[ROW][C]127[/C][C]0.183866[/C][C]0.367732[/C][C]0.816134[/C][/ROW]
[ROW][C]128[/C][C]0.17767[/C][C]0.35534[/C][C]0.82233[/C][/ROW]
[ROW][C]129[/C][C]0.158513[/C][C]0.317027[/C][C]0.841487[/C][/ROW]
[ROW][C]130[/C][C]0.142625[/C][C]0.28525[/C][C]0.857375[/C][/ROW]
[ROW][C]131[/C][C]0.162022[/C][C]0.324044[/C][C]0.837978[/C][/ROW]
[ROW][C]132[/C][C]0.180923[/C][C]0.361845[/C][C]0.819077[/C][/ROW]
[ROW][C]133[/C][C]0.216858[/C][C]0.433717[/C][C]0.783142[/C][/ROW]
[ROW][C]134[/C][C]0.194065[/C][C]0.388131[/C][C]0.805935[/C][/ROW]
[ROW][C]135[/C][C]0.170853[/C][C]0.341707[/C][C]0.829147[/C][/ROW]
[ROW][C]136[/C][C]0.149935[/C][C]0.299871[/C][C]0.850065[/C][/ROW]
[ROW][C]137[/C][C]0.130699[/C][C]0.261398[/C][C]0.869301[/C][/ROW]
[ROW][C]138[/C][C]0.141069[/C][C]0.282138[/C][C]0.858931[/C][/ROW]
[ROW][C]139[/C][C]0.122919[/C][C]0.245838[/C][C]0.877081[/C][/ROW]
[ROW][C]140[/C][C]0.121992[/C][C]0.243983[/C][C]0.878008[/C][/ROW]
[ROW][C]141[/C][C]0.110859[/C][C]0.221718[/C][C]0.889141[/C][/ROW]
[ROW][C]142[/C][C]0.140021[/C][C]0.280042[/C][C]0.859979[/C][/ROW]
[ROW][C]143[/C][C]0.161454[/C][C]0.322908[/C][C]0.838546[/C][/ROW]
[ROW][C]144[/C][C]0.14653[/C][C]0.293059[/C][C]0.85347[/C][/ROW]
[ROW][C]145[/C][C]0.222694[/C][C]0.445388[/C][C]0.777306[/C][/ROW]
[ROW][C]146[/C][C]0.199475[/C][C]0.39895[/C][C]0.800525[/C][/ROW]
[ROW][C]147[/C][C]0.180533[/C][C]0.361066[/C][C]0.819467[/C][/ROW]
[ROW][C]148[/C][C]0.1587[/C][C]0.317401[/C][C]0.8413[/C][/ROW]
[ROW][C]149[/C][C]0.146615[/C][C]0.29323[/C][C]0.853385[/C][/ROW]
[ROW][C]150[/C][C]0.130031[/C][C]0.260061[/C][C]0.869969[/C][/ROW]
[ROW][C]151[/C][C]0.211045[/C][C]0.422089[/C][C]0.788955[/C][/ROW]
[ROW][C]152[/C][C]0.191046[/C][C]0.382092[/C][C]0.808954[/C][/ROW]
[ROW][C]153[/C][C]0.171721[/C][C]0.343442[/C][C]0.828279[/C][/ROW]
[ROW][C]154[/C][C]0.195537[/C][C]0.391075[/C][C]0.804463[/C][/ROW]
[ROW][C]155[/C][C]0.17418[/C][C]0.34836[/C][C]0.82582[/C][/ROW]
[ROW][C]156[/C][C]0.193098[/C][C]0.386197[/C][C]0.806902[/C][/ROW]
[ROW][C]157[/C][C]0.182994[/C][C]0.365987[/C][C]0.817006[/C][/ROW]
[ROW][C]158[/C][C]0.167449[/C][C]0.334898[/C][C]0.832551[/C][/ROW]
[ROW][C]159[/C][C]0.159468[/C][C]0.318935[/C][C]0.840532[/C][/ROW]
[ROW][C]160[/C][C]0.148035[/C][C]0.29607[/C][C]0.851965[/C][/ROW]
[ROW][C]161[/C][C]0.127774[/C][C]0.255549[/C][C]0.872226[/C][/ROW]
[ROW][C]162[/C][C]0.120347[/C][C]0.240693[/C][C]0.879653[/C][/ROW]
[ROW][C]163[/C][C]0.110349[/C][C]0.220699[/C][C]0.889651[/C][/ROW]
[ROW][C]164[/C][C]0.143584[/C][C]0.287168[/C][C]0.856416[/C][/ROW]
[ROW][C]165[/C][C]0.129305[/C][C]0.25861[/C][C]0.870695[/C][/ROW]
[ROW][C]166[/C][C]0.211352[/C][C]0.422705[/C][C]0.788648[/C][/ROW]
[ROW][C]167[/C][C]0.210456[/C][C]0.420912[/C][C]0.789544[/C][/ROW]
[ROW][C]168[/C][C]0.201645[/C][C]0.40329[/C][C]0.798355[/C][/ROW]
[ROW][C]169[/C][C]0.18254[/C][C]0.365079[/C][C]0.81746[/C][/ROW]
[ROW][C]170[/C][C]0.289545[/C][C]0.579091[/C][C]0.710455[/C][/ROW]
[ROW][C]171[/C][C]0.323032[/C][C]0.646065[/C][C]0.676968[/C][/ROW]
[ROW][C]172[/C][C]0.29202[/C][C]0.58404[/C][C]0.70798[/C][/ROW]
[ROW][C]173[/C][C]0.391819[/C][C]0.783638[/C][C]0.608181[/C][/ROW]
[ROW][C]174[/C][C]0.356684[/C][C]0.713367[/C][C]0.643316[/C][/ROW]
[ROW][C]175[/C][C]0.429115[/C][C]0.85823[/C][C]0.570885[/C][/ROW]
[ROW][C]176[/C][C]0.400697[/C][C]0.801394[/C][C]0.599303[/C][/ROW]
[ROW][C]177[/C][C]0.404661[/C][C]0.809323[/C][C]0.595339[/C][/ROW]
[ROW][C]178[/C][C]0.37098[/C][C]0.74196[/C][C]0.62902[/C][/ROW]
[ROW][C]179[/C][C]0.33946[/C][C]0.67892[/C][C]0.66054[/C][/ROW]
[ROW][C]180[/C][C]0.338597[/C][C]0.677194[/C][C]0.661403[/C][/ROW]
[ROW][C]181[/C][C]0.308467[/C][C]0.616934[/C][C]0.691533[/C][/ROW]
[ROW][C]182[/C][C]0.307332[/C][C]0.614663[/C][C]0.692668[/C][/ROW]
[ROW][C]183[/C][C]0.318844[/C][C]0.637688[/C][C]0.681156[/C][/ROW]
[ROW][C]184[/C][C]0.39705[/C][C]0.794101[/C][C]0.60295[/C][/ROW]
[ROW][C]185[/C][C]0.594287[/C][C]0.811425[/C][C]0.405713[/C][/ROW]
[ROW][C]186[/C][C]0.570416[/C][C]0.859168[/C][C]0.429584[/C][/ROW]
[ROW][C]187[/C][C]0.559889[/C][C]0.880223[/C][C]0.440111[/C][/ROW]
[ROW][C]188[/C][C]0.725408[/C][C]0.549185[/C][C]0.274592[/C][/ROW]
[ROW][C]189[/C][C]0.697921[/C][C]0.604158[/C][C]0.302079[/C][/ROW]
[ROW][C]190[/C][C]0.695128[/C][C]0.609745[/C][C]0.304872[/C][/ROW]
[ROW][C]191[/C][C]0.660738[/C][C]0.678524[/C][C]0.339262[/C][/ROW]
[ROW][C]192[/C][C]0.63135[/C][C]0.737299[/C][C]0.36865[/C][/ROW]
[ROW][C]193[/C][C]0.596392[/C][C]0.807216[/C][C]0.403608[/C][/ROW]
[ROW][C]194[/C][C]0.56916[/C][C]0.86168[/C][C]0.43084[/C][/ROW]
[ROW][C]195[/C][C]0.528096[/C][C]0.943808[/C][C]0.471904[/C][/ROW]
[ROW][C]196[/C][C]0.489725[/C][C]0.979449[/C][C]0.510275[/C][/ROW]
[ROW][C]197[/C][C]0.473303[/C][C]0.946607[/C][C]0.526697[/C][/ROW]
[ROW][C]198[/C][C]0.443454[/C][C]0.886908[/C][C]0.556546[/C][/ROW]
[ROW][C]199[/C][C]0.402162[/C][C]0.804324[/C][C]0.597838[/C][/ROW]
[ROW][C]200[/C][C]0.462214[/C][C]0.924427[/C][C]0.537786[/C][/ROW]
[ROW][C]201[/C][C]0.430916[/C][C]0.861833[/C][C]0.569084[/C][/ROW]
[ROW][C]202[/C][C]0.574624[/C][C]0.850752[/C][C]0.425376[/C][/ROW]
[ROW][C]203[/C][C]0.566238[/C][C]0.867525[/C][C]0.433762[/C][/ROW]
[ROW][C]204[/C][C]0.526046[/C][C]0.947908[/C][C]0.473954[/C][/ROW]
[ROW][C]205[/C][C]0.482774[/C][C]0.965548[/C][C]0.517226[/C][/ROW]
[ROW][C]206[/C][C]0.443919[/C][C]0.887838[/C][C]0.556081[/C][/ROW]
[ROW][C]207[/C][C]0.413282[/C][C]0.826563[/C][C]0.586718[/C][/ROW]
[ROW][C]208[/C][C]0.376783[/C][C]0.753566[/C][C]0.623217[/C][/ROW]
[ROW][C]209[/C][C]0.349866[/C][C]0.699731[/C][C]0.650134[/C][/ROW]
[ROW][C]210[/C][C]0.314271[/C][C]0.628542[/C][C]0.685729[/C][/ROW]
[ROW][C]211[/C][C]0.276377[/C][C]0.552754[/C][C]0.723623[/C][/ROW]
[ROW][C]212[/C][C]0.245085[/C][C]0.490171[/C][C]0.754915[/C][/ROW]
[ROW][C]213[/C][C]0.308446[/C][C]0.616892[/C][C]0.691554[/C][/ROW]
[ROW][C]214[/C][C]0.308911[/C][C]0.617822[/C][C]0.691089[/C][/ROW]
[ROW][C]215[/C][C]0.27136[/C][C]0.542721[/C][C]0.72864[/C][/ROW]
[ROW][C]216[/C][C]0.238671[/C][C]0.477342[/C][C]0.761329[/C][/ROW]
[ROW][C]217[/C][C]0.220587[/C][C]0.441175[/C][C]0.779413[/C][/ROW]
[ROW][C]218[/C][C]0.229803[/C][C]0.459606[/C][C]0.770197[/C][/ROW]
[ROW][C]219[/C][C]0.200135[/C][C]0.400269[/C][C]0.799865[/C][/ROW]
[ROW][C]220[/C][C]0.193918[/C][C]0.387836[/C][C]0.806082[/C][/ROW]
[ROW][C]221[/C][C]0.164094[/C][C]0.328188[/C][C]0.835906[/C][/ROW]
[ROW][C]222[/C][C]0.171946[/C][C]0.343892[/C][C]0.828054[/C][/ROW]
[ROW][C]223[/C][C]0.142255[/C][C]0.28451[/C][C]0.857745[/C][/ROW]
[ROW][C]224[/C][C]0.123479[/C][C]0.246958[/C][C]0.876521[/C][/ROW]
[ROW][C]225[/C][C]0.184533[/C][C]0.369065[/C][C]0.815467[/C][/ROW]
[ROW][C]226[/C][C]0.168982[/C][C]0.337963[/C][C]0.831018[/C][/ROW]
[ROW][C]227[/C][C]0.151939[/C][C]0.303877[/C][C]0.848061[/C][/ROW]
[ROW][C]228[/C][C]0.148601[/C][C]0.297202[/C][C]0.851399[/C][/ROW]
[ROW][C]229[/C][C]0.121122[/C][C]0.242243[/C][C]0.878878[/C][/ROW]
[ROW][C]230[/C][C]0.0958743[/C][C]0.191749[/C][C]0.904126[/C][/ROW]
[ROW][C]231[/C][C]0.0859202[/C][C]0.17184[/C][C]0.91408[/C][/ROW]
[ROW][C]232[/C][C]0.197127[/C][C]0.394255[/C][C]0.802873[/C][/ROW]
[ROW][C]233[/C][C]0.196202[/C][C]0.392404[/C][C]0.803798[/C][/ROW]
[ROW][C]234[/C][C]0.240087[/C][C]0.480174[/C][C]0.759913[/C][/ROW]
[ROW][C]235[/C][C]0.19386[/C][C]0.38772[/C][C]0.80614[/C][/ROW]
[ROW][C]236[/C][C]0.200452[/C][C]0.400903[/C][C]0.799548[/C][/ROW]
[ROW][C]237[/C][C]0.175194[/C][C]0.350389[/C][C]0.824806[/C][/ROW]
[ROW][C]238[/C][C]0.258134[/C][C]0.516269[/C][C]0.741866[/C][/ROW]
[ROW][C]239[/C][C]0.208983[/C][C]0.417966[/C][C]0.791017[/C][/ROW]
[ROW][C]240[/C][C]0.45869[/C][C]0.91738[/C][C]0.54131[/C][/ROW]
[ROW][C]241[/C][C]0.450402[/C][C]0.900804[/C][C]0.549598[/C][/ROW]
[ROW][C]242[/C][C]0.402156[/C][C]0.804312[/C][C]0.597844[/C][/ROW]
[ROW][C]243[/C][C]0.327682[/C][C]0.655365[/C][C]0.672318[/C][/ROW]
[ROW][C]244[/C][C]0.33839[/C][C]0.67678[/C][C]0.66161[/C][/ROW]
[ROW][C]245[/C][C]0.368145[/C][C]0.73629[/C][C]0.631855[/C][/ROW]
[ROW][C]246[/C][C]0.46118[/C][C]0.92236[/C][C]0.53882[/C][/ROW]
[ROW][C]247[/C][C]0.456827[/C][C]0.913655[/C][C]0.543173[/C][/ROW]
[ROW][C]248[/C][C]0.418478[/C][C]0.836957[/C][C]0.581522[/C][/ROW]
[ROW][C]249[/C][C]0.593479[/C][C]0.813042[/C][C]0.406521[/C][/ROW]
[ROW][C]250[/C][C]0.613756[/C][C]0.772489[/C][C]0.386244[/C][/ROW]
[ROW][C]251[/C][C]0.541899[/C][C]0.916203[/C][C]0.458101[/C][/ROW]
[ROW][C]252[/C][C]0.533011[/C][C]0.933978[/C][C]0.466989[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225831&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225831&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
120.7357940.5284120.264206
130.9084290.1831420.0915712
140.8446830.3106340.155317
150.8191610.3616780.180839
160.7879990.4240020.212001
170.7597690.4804620.240231
180.6883870.6232260.311613
190.6054830.7890340.394517
200.6169970.7660060.383003
210.6327980.7344040.367202
220.5607810.8784380.439219
230.5744230.8511530.425577
240.5013990.9972030.498601
250.602660.794680.39734
260.7877260.4245470.212274
270.7520170.4959660.247983
280.7370620.5258760.262938
290.7115260.5769490.288474
300.6585360.6829290.341464
310.6512320.6975370.348768
320.7830210.4339570.216979
330.7814510.4370970.218549
340.7437120.5125770.256288
350.6975650.6048710.302435
360.6642650.671470.335735
370.63980.7204010.3602
380.6124440.7751120.387556
390.6317510.7364990.368249
400.592140.8157210.40786
410.5960120.8079750.403988
420.5461790.9076420.453821
430.5386170.9227660.461383
440.4991320.9982640.500868
450.5770090.8459820.422991
460.5502970.8994050.449703
470.5083790.9832420.491621
480.4687620.9375230.531238
490.4238310.8476630.576169
500.4320310.8640610.567969
510.4682760.9365520.531724
520.4234180.8468350.576582
530.3825710.7651420.617429
540.3464880.6929750.653512
550.3074660.6149330.692534
560.3282010.6564030.671799
570.3646630.7293260.635337
580.4580280.9160560.541972
590.4265330.8530650.573467
600.389550.77910.61045
610.3503920.7007830.649608
620.3490910.6981820.650909
630.3136710.6273420.686329
640.3117530.6235060.688247
650.2765340.5530670.723466
660.2419080.4838150.758092
670.2179720.4359440.782028
680.2056890.4113780.794311
690.1950610.3901230.804939
700.1676920.3353840.832308
710.1620960.3241930.837904
720.1873810.3747610.812619
730.1728010.3456020.827199
740.149480.298960.85052
750.1323980.2647960.867602
760.1990170.3980340.800983
770.1745850.349170.825415
780.1501760.3003520.849824
790.2078140.4156270.792186
800.2377610.4755210.762239
810.2231410.4462820.776859
820.1963470.3926930.803653
830.1879990.3759990.812001
840.1772690.3545370.822731
850.1534990.3069970.846501
860.1410830.2821650.858917
870.1239730.2479450.876027
880.1353120.2706240.864688
890.1153290.2306580.884671
900.1217540.2435080.878246
910.1168090.2336190.883191
920.1030540.2061070.896946
930.08733250.1746650.912668
940.09306540.1861310.906935
950.1033510.2067030.896649
960.09950560.1990110.900494
970.08851740.1770350.911483
980.08260790.1652160.917392
990.08030530.1606110.919695
1000.07621040.1524210.92379
1010.0729350.145870.927065
1020.06079950.1215990.939201
1030.05054220.1010840.949458
1040.04725610.09451220.952744
1050.09241120.1848220.907589
1060.09134050.1826810.908659
1070.1151040.2302080.884896
1080.1033690.2067390.896631
1090.1606190.3212390.839381
1100.1787720.3575450.821228
1110.1713710.3427430.828629
1120.2034380.4068760.796562
1130.1878540.3757070.812146
1140.1784480.3568960.821552
1150.1762310.3524620.823769
1160.1740220.3480450.825978
1170.1659130.3318260.834087
1180.148580.2971610.85142
1190.143330.2866610.85667
1200.1298280.2596560.870172
1210.113540.227080.88646
1220.1013620.2027240.898638
1230.08782580.1756520.912174
1240.08402640.1680530.915974
1250.07978760.1595750.920212
1260.09892940.1978590.901071
1270.1838660.3677320.816134
1280.177670.355340.82233
1290.1585130.3170270.841487
1300.1426250.285250.857375
1310.1620220.3240440.837978
1320.1809230.3618450.819077
1330.2168580.4337170.783142
1340.1940650.3881310.805935
1350.1708530.3417070.829147
1360.1499350.2998710.850065
1370.1306990.2613980.869301
1380.1410690.2821380.858931
1390.1229190.2458380.877081
1400.1219920.2439830.878008
1410.1108590.2217180.889141
1420.1400210.2800420.859979
1430.1614540.3229080.838546
1440.146530.2930590.85347
1450.2226940.4453880.777306
1460.1994750.398950.800525
1470.1805330.3610660.819467
1480.15870.3174010.8413
1490.1466150.293230.853385
1500.1300310.2600610.869969
1510.2110450.4220890.788955
1520.1910460.3820920.808954
1530.1717210.3434420.828279
1540.1955370.3910750.804463
1550.174180.348360.82582
1560.1930980.3861970.806902
1570.1829940.3659870.817006
1580.1674490.3348980.832551
1590.1594680.3189350.840532
1600.1480350.296070.851965
1610.1277740.2555490.872226
1620.1203470.2406930.879653
1630.1103490.2206990.889651
1640.1435840.2871680.856416
1650.1293050.258610.870695
1660.2113520.4227050.788648
1670.2104560.4209120.789544
1680.2016450.403290.798355
1690.182540.3650790.81746
1700.2895450.5790910.710455
1710.3230320.6460650.676968
1720.292020.584040.70798
1730.3918190.7836380.608181
1740.3566840.7133670.643316
1750.4291150.858230.570885
1760.4006970.8013940.599303
1770.4046610.8093230.595339
1780.370980.741960.62902
1790.339460.678920.66054
1800.3385970.6771940.661403
1810.3084670.6169340.691533
1820.3073320.6146630.692668
1830.3188440.6376880.681156
1840.397050.7941010.60295
1850.5942870.8114250.405713
1860.5704160.8591680.429584
1870.5598890.8802230.440111
1880.7254080.5491850.274592
1890.6979210.6041580.302079
1900.6951280.6097450.304872
1910.6607380.6785240.339262
1920.631350.7372990.36865
1930.5963920.8072160.403608
1940.569160.861680.43084
1950.5280960.9438080.471904
1960.4897250.9794490.510275
1970.4733030.9466070.526697
1980.4434540.8869080.556546
1990.4021620.8043240.597838
2000.4622140.9244270.537786
2010.4309160.8618330.569084
2020.5746240.8507520.425376
2030.5662380.8675250.433762
2040.5260460.9479080.473954
2050.4827740.9655480.517226
2060.4439190.8878380.556081
2070.4132820.8265630.586718
2080.3767830.7535660.623217
2090.3498660.6997310.650134
2100.3142710.6285420.685729
2110.2763770.5527540.723623
2120.2450850.4901710.754915
2130.3084460.6168920.691554
2140.3089110.6178220.691089
2150.271360.5427210.72864
2160.2386710.4773420.761329
2170.2205870.4411750.779413
2180.2298030.4596060.770197
2190.2001350.4002690.799865
2200.1939180.3878360.806082
2210.1640940.3281880.835906
2220.1719460.3438920.828054
2230.1422550.284510.857745
2240.1234790.2469580.876521
2250.1845330.3690650.815467
2260.1689820.3379630.831018
2270.1519390.3038770.848061
2280.1486010.2972020.851399
2290.1211220.2422430.878878
2300.09587430.1917490.904126
2310.08592020.171840.91408
2320.1971270.3942550.802873
2330.1962020.3924040.803798
2340.2400870.4801740.759913
2350.193860.387720.80614
2360.2004520.4009030.799548
2370.1751940.3503890.824806
2380.2581340.5162690.741866
2390.2089830.4179660.791017
2400.458690.917380.54131
2410.4504020.9008040.549598
2420.4021560.8043120.597844
2430.3276820.6553650.672318
2440.338390.676780.66161
2450.3681450.736290.631855
2460.461180.922360.53882
2470.4568270.9136550.543173
2480.4184780.8369570.581522
2490.5934790.8130420.406521
2500.6137560.7724890.386244
2510.5418990.9162030.458101
2520.5330110.9339780.466989






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 level10.00414938OK

\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 & 1 & 0.00414938 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225831&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]1[/C][C]0.00414938[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225831&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225831&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level10.00414938OK


Figures (Output of Computation)

Figure 1
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

Parameters (Session):
par1 = 8 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 8 ; par2 = Do not include Seasonal Dummies ; par3 = 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')
}