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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 12:00:40 -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/t13847077211g86wzilj437txf.htm/, Retrieved Mon, 29 Apr 2024 01:08:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=225827, Retrieved Mon, 29 Apr 2024 01:08:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact83

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 17:00:40] [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 time20 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 & 20 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225827&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]20 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=225827&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225827&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 time20 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Connected[t] = + 24.59 + 0.435581Separate[t] + 0.0056091Software[t] + 0.0201522Happiness[t] -0.0444458Depression[t] -0.0500754Sport1[t] + 0.116447Sport2[t] -0.633094Month[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Connected[t] =  +  24.59 +  0.435581Separate[t] +  0.0056091Software[t] +  0.0201522Happiness[t] -0.0444458Depression[t] -0.0500754Sport1[t] +  0.116447Sport2[t] -0.633094Month[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225827&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Connected[t] =  +  24.59 +  0.435581Separate[t] +  0.0056091Software[t] +  0.0201522Happiness[t] -0.0444458Depression[t] -0.0500754Sport1[t] +  0.116447Sport2[t] -0.633094Month[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225827&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225827&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] = + 24.59 + 0.435581Separate[t] + 0.0056091Software[t] + 0.0201522Happiness[t] -0.0444458Depression[t] -0.0500754Sport1[t] + 0.116447Sport2[t] -0.633094Month[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)24.594.447945.5287.95758e-083.97879e-08
Separate0.4355810.05730427.6015.5544e-132.7772e-13
Software0.00560910.09489410.059110.9529110.476456
Happiness0.02015220.1040120.19370.8465260.423263
Depression-0.04444580.076261-0.58280.5605330.280267
Sport1-0.05007540.0678412-0.73810.4611140.230557
Sport20.1164470.1006151.1570.2482060.124103
Month-0.6330940.284108-2.2280.02672540.0133627

\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) & 24.59 & 4.44794 & 5.528 & 7.95758e-08 & 3.97879e-08 \tabularnewline
Separate & 0.435581 & 0.0573042 & 7.601 & 5.5544e-13 & 2.7772e-13 \tabularnewline
Software & 0.0056091 & 0.0948941 & 0.05911 & 0.952911 & 0.476456 \tabularnewline
Happiness & 0.0201522 & 0.104012 & 0.1937 & 0.846526 & 0.423263 \tabularnewline
Depression & -0.0444458 & 0.076261 & -0.5828 & 0.560533 & 0.280267 \tabularnewline
Sport1 & -0.0500754 & 0.0678412 & -0.7381 & 0.461114 & 0.230557 \tabularnewline
Sport2 & 0.116447 & 0.100615 & 1.157 & 0.248206 & 0.124103 \tabularnewline
Month & -0.633094 & 0.284108 & -2.228 & 0.0267254 & 0.0133627 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225827&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]24.59[/C][C]4.44794[/C][C]5.528[/C][C]7.95758e-08[/C][C]3.97879e-08[/C][/ROW]
[ROW][C]Separate[/C][C]0.435581[/C][C]0.0573042[/C][C]7.601[/C][C]5.5544e-13[/C][C]2.7772e-13[/C][/ROW]
[ROW][C]Software[/C][C]0.0056091[/C][C]0.0948941[/C][C]0.05911[/C][C]0.952911[/C][C]0.476456[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0201522[/C][C]0.104012[/C][C]0.1937[/C][C]0.846526[/C][C]0.423263[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0444458[/C][C]0.076261[/C][C]-0.5828[/C][C]0.560533[/C][C]0.280267[/C][/ROW]
[ROW][C]Sport1[/C][C]-0.0500754[/C][C]0.0678412[/C][C]-0.7381[/C][C]0.461114[/C][C]0.230557[/C][/ROW]
[ROW][C]Sport2[/C][C]0.116447[/C][C]0.100615[/C][C]1.157[/C][C]0.248206[/C][C]0.124103[/C][/ROW]
[ROW][C]Month[/C][C]-0.633094[/C][C]0.284108[/C][C]-2.228[/C][C]0.0267254[/C][C]0.0133627[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225827&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225827&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)24.594.447945.5287.95758e-083.97879e-08
Separate0.4355810.05730427.6015.5544e-132.7772e-13
Software0.00560910.09489410.059110.9529110.476456
Happiness0.02015220.1040120.19370.8465260.423263
Depression-0.04444580.076261-0.58280.5605330.280267
Sport1-0.05007540.0678412-0.73810.4611140.230557
Sport20.1164470.1006151.1570.2482060.124103
Month-0.6330940.284108-2.2280.02672540.0133627






Multiple Linear Regression - Regression Statistics
Multiple R0.490507
R-squared0.240597
Adjusted R-squared0.219832
F-TEST (value)11.5867
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value8.74079e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.35332
Sum Squared Residuals2878.66

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.490507 \tabularnewline
R-squared & 0.240597 \tabularnewline
Adjusted R-squared & 0.219832 \tabularnewline
F-TEST (value) & 11.5867 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 256 \tabularnewline
p-value & 8.74079e-13 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.35332 \tabularnewline
Sum Squared Residuals & 2878.66 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225827&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.490507[/C][/ROW]
[ROW][C]R-squared[/C][C]0.240597[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.219832[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]11.5867[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]256[/C][/ROW]
[ROW][C]p-value[/C][C]8.74079e-13[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.35332[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2878.66[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225827&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225827&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 R0.490507
R-squared0.240597
Adjusted R-squared0.219832
F-TEST (value)11.5867
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value8.74079e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.35332
Sum Squared Residuals2878.66






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
14136.33274.66735
23934.54884.45116
33035.4069-5.40688
43134.4278-3.42775
53436.0215-2.02149
63532.97662.02337
73933.42145.57864
83436.1447-2.14472
93635.59720.402821
103736.88650.113499
113834.09943.90065
123634.93521.06476
133835.27542.72462
143936.34482.65517
153336.8262-3.82622
163234.2813-2.28126
173634.03121.96879
183837.24670.753252
193936.91312.08687
203233.9805-1.98051
213234.7379-2.7379
223133.7805-2.78047
233936.40462.59537
243737.0654-0.0654364
253934.50054.49948
264134.1526.84798
273635.22860.771378
283336.3711-3.37111
293334.3479-1.34793
303434.7349-0.734932
313134.0848-3.08479
322733.6096-6.60961
333733.80133.19873
343436.9712-2.97116
353432.91641.08356
363234.8408-2.84079
372932.8919-3.89191
383634.55451.44554
392933.9002-4.90024
403534.57550.42447
413734.32372.67634
423434.4019-0.401863
433834.02053.97955
443533.9481.05204
453832.39355.60652
463735.10151.89855
473837.60730.392657
483335.1779-2.17791
493636.367-0.367048
503834.15563.84439
513236.919-4.919
523232.9784-0.978411
533233.9091-1.90909
543437.3886-3.38864
553233.6491-1.64908
563735.49631.50374
573935.04843.95159
582935.2072-6.20723
593735.78391.21612
603534.83510.164899
613031.4723-1.47231
623834.88223.11782
633435.4878-1.48778
643134.865-3.86504
653433.32570.67434
663535.861-0.860985
673634.63481.36516
683030.9088-0.908765
693936.74442.25565
703535.5585-0.5585
713835.45782.54218
723135.6673-4.66729
733436.5831-2.5831
743837.25690.743067
753431.47622.52384
763932.47426.52578
773735.71521.28477
783432.99871.00134
792833.1711-5.17109
803731.08775.91228
813335.2213-2.22129
823536.0299-1.02992
833733.84143.15864
843234.4177-2.41771
853333.1397-0.139719
863836.50621.49383
873334.3205-1.3205
882932.999-3.99895
893333.3658-0.365763
903135.4563-4.45633
913633.01582.98422
923537.4105-2.41046
933231.62140.378628
942932.5672-3.5672
953935.29663.7034
963734.662.33995
973533.05651.94352
983734.52322.47682
993235.4047-3.40474
1003835.3512.64896
1013734.68142.31858
1023636.0476-0.0476345
1033231.83560.164386
1043336.4166-3.41664
1054032.97117.02892
1063835.07252.92747
1074136.35714.64293
1083634.23961.76037
1094336.91756.08249
1103034.615-4.61502
1113133.6849-2.68486
1123237.9506-5.95063
1133231.68850.311549
1143734.62162.37841
1153734.01382.98623
1163336.5538-3.55381
1173437.2001-3.20015
1183334.8838-1.88381
1193835.52052.47945
1203335.1511-2.1511
1213131.3034-0.303404
1223836.95891.04114
1233736.50370.496318
1243633.2332.767
1253134.0075-3.00752
1263934.13864.86142
1274436.62477.37534
1283336-3.00005
1293533.93771.06232
1303233.7978-1.79784
1312832.9047-4.90473
1324035.7794.22097
1332732.4268-5.42678
1343736.29840.701616
1353232.5737-0.573712
1362828.2304-0.230441
1373434.962-0.962029
1383034.4426-4.44262
1393534.38010.61986
1403134.6027-3.60265
1413234.1102-2.11021
1423035.8587-5.85872
1433035.2025-5.20254
1443129.60881.39117
1454033.58846.41163
1463231.5490.450953
1473635.07160.928353
1483233.1832-1.18323
1493533.28611.71389
1503836.99041.00963
1514235.47196.52805
1523436.003-2.00304
1533536.5071-1.50711
1543834.63573.36428
1553333.3018-0.301832
1563633.01582.98422
1573235.6211-3.62114
1583336-3.00005
1593433.85380.146199
1603235.9139-3.91385
1613435.4371-1.43707
1622729.8442-2.84425
1633130.07280.927246
1643833.22844.77163
1653435.473-1.47303
1662431.0764-7.07639
1673033.4942-3.49421
1682629.6205-3.62049
1693435.4318-1.43178
1702734.31-7.30996
1713731.69495.30515
1723635.11710.882882
1734134.14266.85744
1742929.1824-0.182369
1753631.15244.84756
1763234.0128-2.01277
1773733.11743.88264
1783031.5048-1.50482
1793132.4823-1.48234
1803834.57763.42241
1813634.30611.69388
1823532.00832.99169
1833134.8228-3.82281
1843833.0534.94702
1852231.671-9.67097
1863234.1097-2.10966
1873633.4592.54103
1883932.63596.36412
1892830.2906-2.29059
1903234.1101-2.11009
1913232.3961-0.396145
1923836.32221.67778
1933233.0882-1.08815
1943534.98440.0156223
1953232.8189-0.818949
1963735.57221.42776
1973432.25061.74936
1983335.2404-2.24037
1993332.57130.428747
2002632.5839-6.58393
2013031.855-1.85498
2022431.7211-7.72112
2033432.16831.83172
2043432.64321.3568
2053333.6958-0.695784
2063434.6276-0.627626
2073535.7011-0.701141
2083534.03590.964103
2093633.31442.68562
2103433.46140.538649
2113432.94631.05369
2124138.65782.34225
2133236.0286-4.02857
2143032.9831-2.98312
2153533.70761.29245
2162829.8155-1.81551
2173334.5855-1.58554
2183934.13964.8604
2193633.23712.7629
2203636.3101-0.310058
2213533.30661.69338
2223833.85764.14244
2233332.59610.403931
2243133.0356-2.03557
2253431.98342.01655
2263234.6692-2.66922
2273132.6533-1.65334
2283332.99910.000852617
2293432.77541.2246
2303434.0676-0.0676252
2313431.92772.07228
2323335.473-2.47301
2333233.6594-1.65938
2344133.33627.66378
2353433.06130.938669
2363632.28653.71354
2373732.22994.77006
2383630.47715.52286
2392932.3107-3.31072
2403731.93925.06076
2412733.1719-6.17187
2423533.5551.44503
2432830.541-2.54105
2443532.91742.08259
2453732.93064.06936
2462933.6845-4.68452
2473234.1192-2.11919
2483632.04863.95142
2491927.5185-8.51853
2502126.7582-5.75819
2513133.5405-2.54054
2523332.67740.322631
2533633.81082.18922
2543332.93390.0660713
2553733.2613.73896
2563433.28920.710833
2573534.30940.690633
2583132.544-1.544
2593733.55233.44769
2603532.45522.54482
2612731.7241-4.72406
2623435.3835-1.38351
2634033.94626.05382
2642932.7656-3.76563

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 41 & 36.3327 & 4.66735 \tabularnewline
2 & 39 & 34.5488 & 4.45116 \tabularnewline
3 & 30 & 35.4069 & -5.40688 \tabularnewline
4 & 31 & 34.4278 & -3.42775 \tabularnewline
5 & 34 & 36.0215 & -2.02149 \tabularnewline
6 & 35 & 32.9766 & 2.02337 \tabularnewline
7 & 39 & 33.4214 & 5.57864 \tabularnewline
8 & 34 & 36.1447 & -2.14472 \tabularnewline
9 & 36 & 35.5972 & 0.402821 \tabularnewline
10 & 37 & 36.8865 & 0.113499 \tabularnewline
11 & 38 & 34.0994 & 3.90065 \tabularnewline
12 & 36 & 34.9352 & 1.06476 \tabularnewline
13 & 38 & 35.2754 & 2.72462 \tabularnewline
14 & 39 & 36.3448 & 2.65517 \tabularnewline
15 & 33 & 36.8262 & -3.82622 \tabularnewline
16 & 32 & 34.2813 & -2.28126 \tabularnewline
17 & 36 & 34.0312 & 1.96879 \tabularnewline
18 & 38 & 37.2467 & 0.753252 \tabularnewline
19 & 39 & 36.9131 & 2.08687 \tabularnewline
20 & 32 & 33.9805 & -1.98051 \tabularnewline
21 & 32 & 34.7379 & -2.7379 \tabularnewline
22 & 31 & 33.7805 & -2.78047 \tabularnewline
23 & 39 & 36.4046 & 2.59537 \tabularnewline
24 & 37 & 37.0654 & -0.0654364 \tabularnewline
25 & 39 & 34.5005 & 4.49948 \tabularnewline
26 & 41 & 34.152 & 6.84798 \tabularnewline
27 & 36 & 35.2286 & 0.771378 \tabularnewline
28 & 33 & 36.3711 & -3.37111 \tabularnewline
29 & 33 & 34.3479 & -1.34793 \tabularnewline
30 & 34 & 34.7349 & -0.734932 \tabularnewline
31 & 31 & 34.0848 & -3.08479 \tabularnewline
32 & 27 & 33.6096 & -6.60961 \tabularnewline
33 & 37 & 33.8013 & 3.19873 \tabularnewline
34 & 34 & 36.9712 & -2.97116 \tabularnewline
35 & 34 & 32.9164 & 1.08356 \tabularnewline
36 & 32 & 34.8408 & -2.84079 \tabularnewline
37 & 29 & 32.8919 & -3.89191 \tabularnewline
38 & 36 & 34.5545 & 1.44554 \tabularnewline
39 & 29 & 33.9002 & -4.90024 \tabularnewline
40 & 35 & 34.5755 & 0.42447 \tabularnewline
41 & 37 & 34.3237 & 2.67634 \tabularnewline
42 & 34 & 34.4019 & -0.401863 \tabularnewline
43 & 38 & 34.0205 & 3.97955 \tabularnewline
44 & 35 & 33.948 & 1.05204 \tabularnewline
45 & 38 & 32.3935 & 5.60652 \tabularnewline
46 & 37 & 35.1015 & 1.89855 \tabularnewline
47 & 38 & 37.6073 & 0.392657 \tabularnewline
48 & 33 & 35.1779 & -2.17791 \tabularnewline
49 & 36 & 36.367 & -0.367048 \tabularnewline
50 & 38 & 34.1556 & 3.84439 \tabularnewline
51 & 32 & 36.919 & -4.919 \tabularnewline
52 & 32 & 32.9784 & -0.978411 \tabularnewline
53 & 32 & 33.9091 & -1.90909 \tabularnewline
54 & 34 & 37.3886 & -3.38864 \tabularnewline
55 & 32 & 33.6491 & -1.64908 \tabularnewline
56 & 37 & 35.4963 & 1.50374 \tabularnewline
57 & 39 & 35.0484 & 3.95159 \tabularnewline
58 & 29 & 35.2072 & -6.20723 \tabularnewline
59 & 37 & 35.7839 & 1.21612 \tabularnewline
60 & 35 & 34.8351 & 0.164899 \tabularnewline
61 & 30 & 31.4723 & -1.47231 \tabularnewline
62 & 38 & 34.8822 & 3.11782 \tabularnewline
63 & 34 & 35.4878 & -1.48778 \tabularnewline
64 & 31 & 34.865 & -3.86504 \tabularnewline
65 & 34 & 33.3257 & 0.67434 \tabularnewline
66 & 35 & 35.861 & -0.860985 \tabularnewline
67 & 36 & 34.6348 & 1.36516 \tabularnewline
68 & 30 & 30.9088 & -0.908765 \tabularnewline
69 & 39 & 36.7444 & 2.25565 \tabularnewline
70 & 35 & 35.5585 & -0.5585 \tabularnewline
71 & 38 & 35.4578 & 2.54218 \tabularnewline
72 & 31 & 35.6673 & -4.66729 \tabularnewline
73 & 34 & 36.5831 & -2.5831 \tabularnewline
74 & 38 & 37.2569 & 0.743067 \tabularnewline
75 & 34 & 31.4762 & 2.52384 \tabularnewline
76 & 39 & 32.4742 & 6.52578 \tabularnewline
77 & 37 & 35.7152 & 1.28477 \tabularnewline
78 & 34 & 32.9987 & 1.00134 \tabularnewline
79 & 28 & 33.1711 & -5.17109 \tabularnewline
80 & 37 & 31.0877 & 5.91228 \tabularnewline
81 & 33 & 35.2213 & -2.22129 \tabularnewline
82 & 35 & 36.0299 & -1.02992 \tabularnewline
83 & 37 & 33.8414 & 3.15864 \tabularnewline
84 & 32 & 34.4177 & -2.41771 \tabularnewline
85 & 33 & 33.1397 & -0.139719 \tabularnewline
86 & 38 & 36.5062 & 1.49383 \tabularnewline
87 & 33 & 34.3205 & -1.3205 \tabularnewline
88 & 29 & 32.999 & -3.99895 \tabularnewline
89 & 33 & 33.3658 & -0.365763 \tabularnewline
90 & 31 & 35.4563 & -4.45633 \tabularnewline
91 & 36 & 33.0158 & 2.98422 \tabularnewline
92 & 35 & 37.4105 & -2.41046 \tabularnewline
93 & 32 & 31.6214 & 0.378628 \tabularnewline
94 & 29 & 32.5672 & -3.5672 \tabularnewline
95 & 39 & 35.2966 & 3.7034 \tabularnewline
96 & 37 & 34.66 & 2.33995 \tabularnewline
97 & 35 & 33.0565 & 1.94352 \tabularnewline
98 & 37 & 34.5232 & 2.47682 \tabularnewline
99 & 32 & 35.4047 & -3.40474 \tabularnewline
100 & 38 & 35.351 & 2.64896 \tabularnewline
101 & 37 & 34.6814 & 2.31858 \tabularnewline
102 & 36 & 36.0476 & -0.0476345 \tabularnewline
103 & 32 & 31.8356 & 0.164386 \tabularnewline
104 & 33 & 36.4166 & -3.41664 \tabularnewline
105 & 40 & 32.9711 & 7.02892 \tabularnewline
106 & 38 & 35.0725 & 2.92747 \tabularnewline
107 & 41 & 36.3571 & 4.64293 \tabularnewline
108 & 36 & 34.2396 & 1.76037 \tabularnewline
109 & 43 & 36.9175 & 6.08249 \tabularnewline
110 & 30 & 34.615 & -4.61502 \tabularnewline
111 & 31 & 33.6849 & -2.68486 \tabularnewline
112 & 32 & 37.9506 & -5.95063 \tabularnewline
113 & 32 & 31.6885 & 0.311549 \tabularnewline
114 & 37 & 34.6216 & 2.37841 \tabularnewline
115 & 37 & 34.0138 & 2.98623 \tabularnewline
116 & 33 & 36.5538 & -3.55381 \tabularnewline
117 & 34 & 37.2001 & -3.20015 \tabularnewline
118 & 33 & 34.8838 & -1.88381 \tabularnewline
119 & 38 & 35.5205 & 2.47945 \tabularnewline
120 & 33 & 35.1511 & -2.1511 \tabularnewline
121 & 31 & 31.3034 & -0.303404 \tabularnewline
122 & 38 & 36.9589 & 1.04114 \tabularnewline
123 & 37 & 36.5037 & 0.496318 \tabularnewline
124 & 36 & 33.233 & 2.767 \tabularnewline
125 & 31 & 34.0075 & -3.00752 \tabularnewline
126 & 39 & 34.1386 & 4.86142 \tabularnewline
127 & 44 & 36.6247 & 7.37534 \tabularnewline
128 & 33 & 36 & -3.00005 \tabularnewline
129 & 35 & 33.9377 & 1.06232 \tabularnewline
130 & 32 & 33.7978 & -1.79784 \tabularnewline
131 & 28 & 32.9047 & -4.90473 \tabularnewline
132 & 40 & 35.779 & 4.22097 \tabularnewline
133 & 27 & 32.4268 & -5.42678 \tabularnewline
134 & 37 & 36.2984 & 0.701616 \tabularnewline
135 & 32 & 32.5737 & -0.573712 \tabularnewline
136 & 28 & 28.2304 & -0.230441 \tabularnewline
137 & 34 & 34.962 & -0.962029 \tabularnewline
138 & 30 & 34.4426 & -4.44262 \tabularnewline
139 & 35 & 34.3801 & 0.61986 \tabularnewline
140 & 31 & 34.6027 & -3.60265 \tabularnewline
141 & 32 & 34.1102 & -2.11021 \tabularnewline
142 & 30 & 35.8587 & -5.85872 \tabularnewline
143 & 30 & 35.2025 & -5.20254 \tabularnewline
144 & 31 & 29.6088 & 1.39117 \tabularnewline
145 & 40 & 33.5884 & 6.41163 \tabularnewline
146 & 32 & 31.549 & 0.450953 \tabularnewline
147 & 36 & 35.0716 & 0.928353 \tabularnewline
148 & 32 & 33.1832 & -1.18323 \tabularnewline
149 & 35 & 33.2861 & 1.71389 \tabularnewline
150 & 38 & 36.9904 & 1.00963 \tabularnewline
151 & 42 & 35.4719 & 6.52805 \tabularnewline
152 & 34 & 36.003 & -2.00304 \tabularnewline
153 & 35 & 36.5071 & -1.50711 \tabularnewline
154 & 38 & 34.6357 & 3.36428 \tabularnewline
155 & 33 & 33.3018 & -0.301832 \tabularnewline
156 & 36 & 33.0158 & 2.98422 \tabularnewline
157 & 32 & 35.6211 & -3.62114 \tabularnewline
158 & 33 & 36 & -3.00005 \tabularnewline
159 & 34 & 33.8538 & 0.146199 \tabularnewline
160 & 32 & 35.9139 & -3.91385 \tabularnewline
161 & 34 & 35.4371 & -1.43707 \tabularnewline
162 & 27 & 29.8442 & -2.84425 \tabularnewline
163 & 31 & 30.0728 & 0.927246 \tabularnewline
164 & 38 & 33.2284 & 4.77163 \tabularnewline
165 & 34 & 35.473 & -1.47303 \tabularnewline
166 & 24 & 31.0764 & -7.07639 \tabularnewline
167 & 30 & 33.4942 & -3.49421 \tabularnewline
168 & 26 & 29.6205 & -3.62049 \tabularnewline
169 & 34 & 35.4318 & -1.43178 \tabularnewline
170 & 27 & 34.31 & -7.30996 \tabularnewline
171 & 37 & 31.6949 & 5.30515 \tabularnewline
172 & 36 & 35.1171 & 0.882882 \tabularnewline
173 & 41 & 34.1426 & 6.85744 \tabularnewline
174 & 29 & 29.1824 & -0.182369 \tabularnewline
175 & 36 & 31.1524 & 4.84756 \tabularnewline
176 & 32 & 34.0128 & -2.01277 \tabularnewline
177 & 37 & 33.1174 & 3.88264 \tabularnewline
178 & 30 & 31.5048 & -1.50482 \tabularnewline
179 & 31 & 32.4823 & -1.48234 \tabularnewline
180 & 38 & 34.5776 & 3.42241 \tabularnewline
181 & 36 & 34.3061 & 1.69388 \tabularnewline
182 & 35 & 32.0083 & 2.99169 \tabularnewline
183 & 31 & 34.8228 & -3.82281 \tabularnewline
184 & 38 & 33.053 & 4.94702 \tabularnewline
185 & 22 & 31.671 & -9.67097 \tabularnewline
186 & 32 & 34.1097 & -2.10966 \tabularnewline
187 & 36 & 33.459 & 2.54103 \tabularnewline
188 & 39 & 32.6359 & 6.36412 \tabularnewline
189 & 28 & 30.2906 & -2.29059 \tabularnewline
190 & 32 & 34.1101 & -2.11009 \tabularnewline
191 & 32 & 32.3961 & -0.396145 \tabularnewline
192 & 38 & 36.3222 & 1.67778 \tabularnewline
193 & 32 & 33.0882 & -1.08815 \tabularnewline
194 & 35 & 34.9844 & 0.0156223 \tabularnewline
195 & 32 & 32.8189 & -0.818949 \tabularnewline
196 & 37 & 35.5722 & 1.42776 \tabularnewline
197 & 34 & 32.2506 & 1.74936 \tabularnewline
198 & 33 & 35.2404 & -2.24037 \tabularnewline
199 & 33 & 32.5713 & 0.428747 \tabularnewline
200 & 26 & 32.5839 & -6.58393 \tabularnewline
201 & 30 & 31.855 & -1.85498 \tabularnewline
202 & 24 & 31.7211 & -7.72112 \tabularnewline
203 & 34 & 32.1683 & 1.83172 \tabularnewline
204 & 34 & 32.6432 & 1.3568 \tabularnewline
205 & 33 & 33.6958 & -0.695784 \tabularnewline
206 & 34 & 34.6276 & -0.627626 \tabularnewline
207 & 35 & 35.7011 & -0.701141 \tabularnewline
208 & 35 & 34.0359 & 0.964103 \tabularnewline
209 & 36 & 33.3144 & 2.68562 \tabularnewline
210 & 34 & 33.4614 & 0.538649 \tabularnewline
211 & 34 & 32.9463 & 1.05369 \tabularnewline
212 & 41 & 38.6578 & 2.34225 \tabularnewline
213 & 32 & 36.0286 & -4.02857 \tabularnewline
214 & 30 & 32.9831 & -2.98312 \tabularnewline
215 & 35 & 33.7076 & 1.29245 \tabularnewline
216 & 28 & 29.8155 & -1.81551 \tabularnewline
217 & 33 & 34.5855 & -1.58554 \tabularnewline
218 & 39 & 34.1396 & 4.8604 \tabularnewline
219 & 36 & 33.2371 & 2.7629 \tabularnewline
220 & 36 & 36.3101 & -0.310058 \tabularnewline
221 & 35 & 33.3066 & 1.69338 \tabularnewline
222 & 38 & 33.8576 & 4.14244 \tabularnewline
223 & 33 & 32.5961 & 0.403931 \tabularnewline
224 & 31 & 33.0356 & -2.03557 \tabularnewline
225 & 34 & 31.9834 & 2.01655 \tabularnewline
226 & 32 & 34.6692 & -2.66922 \tabularnewline
227 & 31 & 32.6533 & -1.65334 \tabularnewline
228 & 33 & 32.9991 & 0.000852617 \tabularnewline
229 & 34 & 32.7754 & 1.2246 \tabularnewline
230 & 34 & 34.0676 & -0.0676252 \tabularnewline
231 & 34 & 31.9277 & 2.07228 \tabularnewline
232 & 33 & 35.473 & -2.47301 \tabularnewline
233 & 32 & 33.6594 & -1.65938 \tabularnewline
234 & 41 & 33.3362 & 7.66378 \tabularnewline
235 & 34 & 33.0613 & 0.938669 \tabularnewline
236 & 36 & 32.2865 & 3.71354 \tabularnewline
237 & 37 & 32.2299 & 4.77006 \tabularnewline
238 & 36 & 30.4771 & 5.52286 \tabularnewline
239 & 29 & 32.3107 & -3.31072 \tabularnewline
240 & 37 & 31.9392 & 5.06076 \tabularnewline
241 & 27 & 33.1719 & -6.17187 \tabularnewline
242 & 35 & 33.555 & 1.44503 \tabularnewline
243 & 28 & 30.541 & -2.54105 \tabularnewline
244 & 35 & 32.9174 & 2.08259 \tabularnewline
245 & 37 & 32.9306 & 4.06936 \tabularnewline
246 & 29 & 33.6845 & -4.68452 \tabularnewline
247 & 32 & 34.1192 & -2.11919 \tabularnewline
248 & 36 & 32.0486 & 3.95142 \tabularnewline
249 & 19 & 27.5185 & -8.51853 \tabularnewline
250 & 21 & 26.7582 & -5.75819 \tabularnewline
251 & 31 & 33.5405 & -2.54054 \tabularnewline
252 & 33 & 32.6774 & 0.322631 \tabularnewline
253 & 36 & 33.8108 & 2.18922 \tabularnewline
254 & 33 & 32.9339 & 0.0660713 \tabularnewline
255 & 37 & 33.261 & 3.73896 \tabularnewline
256 & 34 & 33.2892 & 0.710833 \tabularnewline
257 & 35 & 34.3094 & 0.690633 \tabularnewline
258 & 31 & 32.544 & -1.544 \tabularnewline
259 & 37 & 33.5523 & 3.44769 \tabularnewline
260 & 35 & 32.4552 & 2.54482 \tabularnewline
261 & 27 & 31.7241 & -4.72406 \tabularnewline
262 & 34 & 35.3835 & -1.38351 \tabularnewline
263 & 40 & 33.9462 & 6.05382 \tabularnewline
264 & 29 & 32.7656 & -3.76563 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225827&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]36.3327[/C][C]4.66735[/C][/ROW]
[ROW][C]2[/C][C]39[/C][C]34.5488[/C][C]4.45116[/C][/ROW]
[ROW][C]3[/C][C]30[/C][C]35.4069[/C][C]-5.40688[/C][/ROW]
[ROW][C]4[/C][C]31[/C][C]34.4278[/C][C]-3.42775[/C][/ROW]
[ROW][C]5[/C][C]34[/C][C]36.0215[/C][C]-2.02149[/C][/ROW]
[ROW][C]6[/C][C]35[/C][C]32.9766[/C][C]2.02337[/C][/ROW]
[ROW][C]7[/C][C]39[/C][C]33.4214[/C][C]5.57864[/C][/ROW]
[ROW][C]8[/C][C]34[/C][C]36.1447[/C][C]-2.14472[/C][/ROW]
[ROW][C]9[/C][C]36[/C][C]35.5972[/C][C]0.402821[/C][/ROW]
[ROW][C]10[/C][C]37[/C][C]36.8865[/C][C]0.113499[/C][/ROW]
[ROW][C]11[/C][C]38[/C][C]34.0994[/C][C]3.90065[/C][/ROW]
[ROW][C]12[/C][C]36[/C][C]34.9352[/C][C]1.06476[/C][/ROW]
[ROW][C]13[/C][C]38[/C][C]35.2754[/C][C]2.72462[/C][/ROW]
[ROW][C]14[/C][C]39[/C][C]36.3448[/C][C]2.65517[/C][/ROW]
[ROW][C]15[/C][C]33[/C][C]36.8262[/C][C]-3.82622[/C][/ROW]
[ROW][C]16[/C][C]32[/C][C]34.2813[/C][C]-2.28126[/C][/ROW]
[ROW][C]17[/C][C]36[/C][C]34.0312[/C][C]1.96879[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]37.2467[/C][C]0.753252[/C][/ROW]
[ROW][C]19[/C][C]39[/C][C]36.9131[/C][C]2.08687[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]33.9805[/C][C]-1.98051[/C][/ROW]
[ROW][C]21[/C][C]32[/C][C]34.7379[/C][C]-2.7379[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]33.7805[/C][C]-2.78047[/C][/ROW]
[ROW][C]23[/C][C]39[/C][C]36.4046[/C][C]2.59537[/C][/ROW]
[ROW][C]24[/C][C]37[/C][C]37.0654[/C][C]-0.0654364[/C][/ROW]
[ROW][C]25[/C][C]39[/C][C]34.5005[/C][C]4.49948[/C][/ROW]
[ROW][C]26[/C][C]41[/C][C]34.152[/C][C]6.84798[/C][/ROW]
[ROW][C]27[/C][C]36[/C][C]35.2286[/C][C]0.771378[/C][/ROW]
[ROW][C]28[/C][C]33[/C][C]36.3711[/C][C]-3.37111[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]34.3479[/C][C]-1.34793[/C][/ROW]
[ROW][C]30[/C][C]34[/C][C]34.7349[/C][C]-0.734932[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]34.0848[/C][C]-3.08479[/C][/ROW]
[ROW][C]32[/C][C]27[/C][C]33.6096[/C][C]-6.60961[/C][/ROW]
[ROW][C]33[/C][C]37[/C][C]33.8013[/C][C]3.19873[/C][/ROW]
[ROW][C]34[/C][C]34[/C][C]36.9712[/C][C]-2.97116[/C][/ROW]
[ROW][C]35[/C][C]34[/C][C]32.9164[/C][C]1.08356[/C][/ROW]
[ROW][C]36[/C][C]32[/C][C]34.8408[/C][C]-2.84079[/C][/ROW]
[ROW][C]37[/C][C]29[/C][C]32.8919[/C][C]-3.89191[/C][/ROW]
[ROW][C]38[/C][C]36[/C][C]34.5545[/C][C]1.44554[/C][/ROW]
[ROW][C]39[/C][C]29[/C][C]33.9002[/C][C]-4.90024[/C][/ROW]
[ROW][C]40[/C][C]35[/C][C]34.5755[/C][C]0.42447[/C][/ROW]
[ROW][C]41[/C][C]37[/C][C]34.3237[/C][C]2.67634[/C][/ROW]
[ROW][C]42[/C][C]34[/C][C]34.4019[/C][C]-0.401863[/C][/ROW]
[ROW][C]43[/C][C]38[/C][C]34.0205[/C][C]3.97955[/C][/ROW]
[ROW][C]44[/C][C]35[/C][C]33.948[/C][C]1.05204[/C][/ROW]
[ROW][C]45[/C][C]38[/C][C]32.3935[/C][C]5.60652[/C][/ROW]
[ROW][C]46[/C][C]37[/C][C]35.1015[/C][C]1.89855[/C][/ROW]
[ROW][C]47[/C][C]38[/C][C]37.6073[/C][C]0.392657[/C][/ROW]
[ROW][C]48[/C][C]33[/C][C]35.1779[/C][C]-2.17791[/C][/ROW]
[ROW][C]49[/C][C]36[/C][C]36.367[/C][C]-0.367048[/C][/ROW]
[ROW][C]50[/C][C]38[/C][C]34.1556[/C][C]3.84439[/C][/ROW]
[ROW][C]51[/C][C]32[/C][C]36.919[/C][C]-4.919[/C][/ROW]
[ROW][C]52[/C][C]32[/C][C]32.9784[/C][C]-0.978411[/C][/ROW]
[ROW][C]53[/C][C]32[/C][C]33.9091[/C][C]-1.90909[/C][/ROW]
[ROW][C]54[/C][C]34[/C][C]37.3886[/C][C]-3.38864[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]33.6491[/C][C]-1.64908[/C][/ROW]
[ROW][C]56[/C][C]37[/C][C]35.4963[/C][C]1.50374[/C][/ROW]
[ROW][C]57[/C][C]39[/C][C]35.0484[/C][C]3.95159[/C][/ROW]
[ROW][C]58[/C][C]29[/C][C]35.2072[/C][C]-6.20723[/C][/ROW]
[ROW][C]59[/C][C]37[/C][C]35.7839[/C][C]1.21612[/C][/ROW]
[ROW][C]60[/C][C]35[/C][C]34.8351[/C][C]0.164899[/C][/ROW]
[ROW][C]61[/C][C]30[/C][C]31.4723[/C][C]-1.47231[/C][/ROW]
[ROW][C]62[/C][C]38[/C][C]34.8822[/C][C]3.11782[/C][/ROW]
[ROW][C]63[/C][C]34[/C][C]35.4878[/C][C]-1.48778[/C][/ROW]
[ROW][C]64[/C][C]31[/C][C]34.865[/C][C]-3.86504[/C][/ROW]
[ROW][C]65[/C][C]34[/C][C]33.3257[/C][C]0.67434[/C][/ROW]
[ROW][C]66[/C][C]35[/C][C]35.861[/C][C]-0.860985[/C][/ROW]
[ROW][C]67[/C][C]36[/C][C]34.6348[/C][C]1.36516[/C][/ROW]
[ROW][C]68[/C][C]30[/C][C]30.9088[/C][C]-0.908765[/C][/ROW]
[ROW][C]69[/C][C]39[/C][C]36.7444[/C][C]2.25565[/C][/ROW]
[ROW][C]70[/C][C]35[/C][C]35.5585[/C][C]-0.5585[/C][/ROW]
[ROW][C]71[/C][C]38[/C][C]35.4578[/C][C]2.54218[/C][/ROW]
[ROW][C]72[/C][C]31[/C][C]35.6673[/C][C]-4.66729[/C][/ROW]
[ROW][C]73[/C][C]34[/C][C]36.5831[/C][C]-2.5831[/C][/ROW]
[ROW][C]74[/C][C]38[/C][C]37.2569[/C][C]0.743067[/C][/ROW]
[ROW][C]75[/C][C]34[/C][C]31.4762[/C][C]2.52384[/C][/ROW]
[ROW][C]76[/C][C]39[/C][C]32.4742[/C][C]6.52578[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.7152[/C][C]1.28477[/C][/ROW]
[ROW][C]78[/C][C]34[/C][C]32.9987[/C][C]1.00134[/C][/ROW]
[ROW][C]79[/C][C]28[/C][C]33.1711[/C][C]-5.17109[/C][/ROW]
[ROW][C]80[/C][C]37[/C][C]31.0877[/C][C]5.91228[/C][/ROW]
[ROW][C]81[/C][C]33[/C][C]35.2213[/C][C]-2.22129[/C][/ROW]
[ROW][C]82[/C][C]35[/C][C]36.0299[/C][C]-1.02992[/C][/ROW]
[ROW][C]83[/C][C]37[/C][C]33.8414[/C][C]3.15864[/C][/ROW]
[ROW][C]84[/C][C]32[/C][C]34.4177[/C][C]-2.41771[/C][/ROW]
[ROW][C]85[/C][C]33[/C][C]33.1397[/C][C]-0.139719[/C][/ROW]
[ROW][C]86[/C][C]38[/C][C]36.5062[/C][C]1.49383[/C][/ROW]
[ROW][C]87[/C][C]33[/C][C]34.3205[/C][C]-1.3205[/C][/ROW]
[ROW][C]88[/C][C]29[/C][C]32.999[/C][C]-3.99895[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]33.3658[/C][C]-0.365763[/C][/ROW]
[ROW][C]90[/C][C]31[/C][C]35.4563[/C][C]-4.45633[/C][/ROW]
[ROW][C]91[/C][C]36[/C][C]33.0158[/C][C]2.98422[/C][/ROW]
[ROW][C]92[/C][C]35[/C][C]37.4105[/C][C]-2.41046[/C][/ROW]
[ROW][C]93[/C][C]32[/C][C]31.6214[/C][C]0.378628[/C][/ROW]
[ROW][C]94[/C][C]29[/C][C]32.5672[/C][C]-3.5672[/C][/ROW]
[ROW][C]95[/C][C]39[/C][C]35.2966[/C][C]3.7034[/C][/ROW]
[ROW][C]96[/C][C]37[/C][C]34.66[/C][C]2.33995[/C][/ROW]
[ROW][C]97[/C][C]35[/C][C]33.0565[/C][C]1.94352[/C][/ROW]
[ROW][C]98[/C][C]37[/C][C]34.5232[/C][C]2.47682[/C][/ROW]
[ROW][C]99[/C][C]32[/C][C]35.4047[/C][C]-3.40474[/C][/ROW]
[ROW][C]100[/C][C]38[/C][C]35.351[/C][C]2.64896[/C][/ROW]
[ROW][C]101[/C][C]37[/C][C]34.6814[/C][C]2.31858[/C][/ROW]
[ROW][C]102[/C][C]36[/C][C]36.0476[/C][C]-0.0476345[/C][/ROW]
[ROW][C]103[/C][C]32[/C][C]31.8356[/C][C]0.164386[/C][/ROW]
[ROW][C]104[/C][C]33[/C][C]36.4166[/C][C]-3.41664[/C][/ROW]
[ROW][C]105[/C][C]40[/C][C]32.9711[/C][C]7.02892[/C][/ROW]
[ROW][C]106[/C][C]38[/C][C]35.0725[/C][C]2.92747[/C][/ROW]
[ROW][C]107[/C][C]41[/C][C]36.3571[/C][C]4.64293[/C][/ROW]
[ROW][C]108[/C][C]36[/C][C]34.2396[/C][C]1.76037[/C][/ROW]
[ROW][C]109[/C][C]43[/C][C]36.9175[/C][C]6.08249[/C][/ROW]
[ROW][C]110[/C][C]30[/C][C]34.615[/C][C]-4.61502[/C][/ROW]
[ROW][C]111[/C][C]31[/C][C]33.6849[/C][C]-2.68486[/C][/ROW]
[ROW][C]112[/C][C]32[/C][C]37.9506[/C][C]-5.95063[/C][/ROW]
[ROW][C]113[/C][C]32[/C][C]31.6885[/C][C]0.311549[/C][/ROW]
[ROW][C]114[/C][C]37[/C][C]34.6216[/C][C]2.37841[/C][/ROW]
[ROW][C]115[/C][C]37[/C][C]34.0138[/C][C]2.98623[/C][/ROW]
[ROW][C]116[/C][C]33[/C][C]36.5538[/C][C]-3.55381[/C][/ROW]
[ROW][C]117[/C][C]34[/C][C]37.2001[/C][C]-3.20015[/C][/ROW]
[ROW][C]118[/C][C]33[/C][C]34.8838[/C][C]-1.88381[/C][/ROW]
[ROW][C]119[/C][C]38[/C][C]35.5205[/C][C]2.47945[/C][/ROW]
[ROW][C]120[/C][C]33[/C][C]35.1511[/C][C]-2.1511[/C][/ROW]
[ROW][C]121[/C][C]31[/C][C]31.3034[/C][C]-0.303404[/C][/ROW]
[ROW][C]122[/C][C]38[/C][C]36.9589[/C][C]1.04114[/C][/ROW]
[ROW][C]123[/C][C]37[/C][C]36.5037[/C][C]0.496318[/C][/ROW]
[ROW][C]124[/C][C]36[/C][C]33.233[/C][C]2.767[/C][/ROW]
[ROW][C]125[/C][C]31[/C][C]34.0075[/C][C]-3.00752[/C][/ROW]
[ROW][C]126[/C][C]39[/C][C]34.1386[/C][C]4.86142[/C][/ROW]
[ROW][C]127[/C][C]44[/C][C]36.6247[/C][C]7.37534[/C][/ROW]
[ROW][C]128[/C][C]33[/C][C]36[/C][C]-3.00005[/C][/ROW]
[ROW][C]129[/C][C]35[/C][C]33.9377[/C][C]1.06232[/C][/ROW]
[ROW][C]130[/C][C]32[/C][C]33.7978[/C][C]-1.79784[/C][/ROW]
[ROW][C]131[/C][C]28[/C][C]32.9047[/C][C]-4.90473[/C][/ROW]
[ROW][C]132[/C][C]40[/C][C]35.779[/C][C]4.22097[/C][/ROW]
[ROW][C]133[/C][C]27[/C][C]32.4268[/C][C]-5.42678[/C][/ROW]
[ROW][C]134[/C][C]37[/C][C]36.2984[/C][C]0.701616[/C][/ROW]
[ROW][C]135[/C][C]32[/C][C]32.5737[/C][C]-0.573712[/C][/ROW]
[ROW][C]136[/C][C]28[/C][C]28.2304[/C][C]-0.230441[/C][/ROW]
[ROW][C]137[/C][C]34[/C][C]34.962[/C][C]-0.962029[/C][/ROW]
[ROW][C]138[/C][C]30[/C][C]34.4426[/C][C]-4.44262[/C][/ROW]
[ROW][C]139[/C][C]35[/C][C]34.3801[/C][C]0.61986[/C][/ROW]
[ROW][C]140[/C][C]31[/C][C]34.6027[/C][C]-3.60265[/C][/ROW]
[ROW][C]141[/C][C]32[/C][C]34.1102[/C][C]-2.11021[/C][/ROW]
[ROW][C]142[/C][C]30[/C][C]35.8587[/C][C]-5.85872[/C][/ROW]
[ROW][C]143[/C][C]30[/C][C]35.2025[/C][C]-5.20254[/C][/ROW]
[ROW][C]144[/C][C]31[/C][C]29.6088[/C][C]1.39117[/C][/ROW]
[ROW][C]145[/C][C]40[/C][C]33.5884[/C][C]6.41163[/C][/ROW]
[ROW][C]146[/C][C]32[/C][C]31.549[/C][C]0.450953[/C][/ROW]
[ROW][C]147[/C][C]36[/C][C]35.0716[/C][C]0.928353[/C][/ROW]
[ROW][C]148[/C][C]32[/C][C]33.1832[/C][C]-1.18323[/C][/ROW]
[ROW][C]149[/C][C]35[/C][C]33.2861[/C][C]1.71389[/C][/ROW]
[ROW][C]150[/C][C]38[/C][C]36.9904[/C][C]1.00963[/C][/ROW]
[ROW][C]151[/C][C]42[/C][C]35.4719[/C][C]6.52805[/C][/ROW]
[ROW][C]152[/C][C]34[/C][C]36.003[/C][C]-2.00304[/C][/ROW]
[ROW][C]153[/C][C]35[/C][C]36.5071[/C][C]-1.50711[/C][/ROW]
[ROW][C]154[/C][C]38[/C][C]34.6357[/C][C]3.36428[/C][/ROW]
[ROW][C]155[/C][C]33[/C][C]33.3018[/C][C]-0.301832[/C][/ROW]
[ROW][C]156[/C][C]36[/C][C]33.0158[/C][C]2.98422[/C][/ROW]
[ROW][C]157[/C][C]32[/C][C]35.6211[/C][C]-3.62114[/C][/ROW]
[ROW][C]158[/C][C]33[/C][C]36[/C][C]-3.00005[/C][/ROW]
[ROW][C]159[/C][C]34[/C][C]33.8538[/C][C]0.146199[/C][/ROW]
[ROW][C]160[/C][C]32[/C][C]35.9139[/C][C]-3.91385[/C][/ROW]
[ROW][C]161[/C][C]34[/C][C]35.4371[/C][C]-1.43707[/C][/ROW]
[ROW][C]162[/C][C]27[/C][C]29.8442[/C][C]-2.84425[/C][/ROW]
[ROW][C]163[/C][C]31[/C][C]30.0728[/C][C]0.927246[/C][/ROW]
[ROW][C]164[/C][C]38[/C][C]33.2284[/C][C]4.77163[/C][/ROW]
[ROW][C]165[/C][C]34[/C][C]35.473[/C][C]-1.47303[/C][/ROW]
[ROW][C]166[/C][C]24[/C][C]31.0764[/C][C]-7.07639[/C][/ROW]
[ROW][C]167[/C][C]30[/C][C]33.4942[/C][C]-3.49421[/C][/ROW]
[ROW][C]168[/C][C]26[/C][C]29.6205[/C][C]-3.62049[/C][/ROW]
[ROW][C]169[/C][C]34[/C][C]35.4318[/C][C]-1.43178[/C][/ROW]
[ROW][C]170[/C][C]27[/C][C]34.31[/C][C]-7.30996[/C][/ROW]
[ROW][C]171[/C][C]37[/C][C]31.6949[/C][C]5.30515[/C][/ROW]
[ROW][C]172[/C][C]36[/C][C]35.1171[/C][C]0.882882[/C][/ROW]
[ROW][C]173[/C][C]41[/C][C]34.1426[/C][C]6.85744[/C][/ROW]
[ROW][C]174[/C][C]29[/C][C]29.1824[/C][C]-0.182369[/C][/ROW]
[ROW][C]175[/C][C]36[/C][C]31.1524[/C][C]4.84756[/C][/ROW]
[ROW][C]176[/C][C]32[/C][C]34.0128[/C][C]-2.01277[/C][/ROW]
[ROW][C]177[/C][C]37[/C][C]33.1174[/C][C]3.88264[/C][/ROW]
[ROW][C]178[/C][C]30[/C][C]31.5048[/C][C]-1.50482[/C][/ROW]
[ROW][C]179[/C][C]31[/C][C]32.4823[/C][C]-1.48234[/C][/ROW]
[ROW][C]180[/C][C]38[/C][C]34.5776[/C][C]3.42241[/C][/ROW]
[ROW][C]181[/C][C]36[/C][C]34.3061[/C][C]1.69388[/C][/ROW]
[ROW][C]182[/C][C]35[/C][C]32.0083[/C][C]2.99169[/C][/ROW]
[ROW][C]183[/C][C]31[/C][C]34.8228[/C][C]-3.82281[/C][/ROW]
[ROW][C]184[/C][C]38[/C][C]33.053[/C][C]4.94702[/C][/ROW]
[ROW][C]185[/C][C]22[/C][C]31.671[/C][C]-9.67097[/C][/ROW]
[ROW][C]186[/C][C]32[/C][C]34.1097[/C][C]-2.10966[/C][/ROW]
[ROW][C]187[/C][C]36[/C][C]33.459[/C][C]2.54103[/C][/ROW]
[ROW][C]188[/C][C]39[/C][C]32.6359[/C][C]6.36412[/C][/ROW]
[ROW][C]189[/C][C]28[/C][C]30.2906[/C][C]-2.29059[/C][/ROW]
[ROW][C]190[/C][C]32[/C][C]34.1101[/C][C]-2.11009[/C][/ROW]
[ROW][C]191[/C][C]32[/C][C]32.3961[/C][C]-0.396145[/C][/ROW]
[ROW][C]192[/C][C]38[/C][C]36.3222[/C][C]1.67778[/C][/ROW]
[ROW][C]193[/C][C]32[/C][C]33.0882[/C][C]-1.08815[/C][/ROW]
[ROW][C]194[/C][C]35[/C][C]34.9844[/C][C]0.0156223[/C][/ROW]
[ROW][C]195[/C][C]32[/C][C]32.8189[/C][C]-0.818949[/C][/ROW]
[ROW][C]196[/C][C]37[/C][C]35.5722[/C][C]1.42776[/C][/ROW]
[ROW][C]197[/C][C]34[/C][C]32.2506[/C][C]1.74936[/C][/ROW]
[ROW][C]198[/C][C]33[/C][C]35.2404[/C][C]-2.24037[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]32.5713[/C][C]0.428747[/C][/ROW]
[ROW][C]200[/C][C]26[/C][C]32.5839[/C][C]-6.58393[/C][/ROW]
[ROW][C]201[/C][C]30[/C][C]31.855[/C][C]-1.85498[/C][/ROW]
[ROW][C]202[/C][C]24[/C][C]31.7211[/C][C]-7.72112[/C][/ROW]
[ROW][C]203[/C][C]34[/C][C]32.1683[/C][C]1.83172[/C][/ROW]
[ROW][C]204[/C][C]34[/C][C]32.6432[/C][C]1.3568[/C][/ROW]
[ROW][C]205[/C][C]33[/C][C]33.6958[/C][C]-0.695784[/C][/ROW]
[ROW][C]206[/C][C]34[/C][C]34.6276[/C][C]-0.627626[/C][/ROW]
[ROW][C]207[/C][C]35[/C][C]35.7011[/C][C]-0.701141[/C][/ROW]
[ROW][C]208[/C][C]35[/C][C]34.0359[/C][C]0.964103[/C][/ROW]
[ROW][C]209[/C][C]36[/C][C]33.3144[/C][C]2.68562[/C][/ROW]
[ROW][C]210[/C][C]34[/C][C]33.4614[/C][C]0.538649[/C][/ROW]
[ROW][C]211[/C][C]34[/C][C]32.9463[/C][C]1.05369[/C][/ROW]
[ROW][C]212[/C][C]41[/C][C]38.6578[/C][C]2.34225[/C][/ROW]
[ROW][C]213[/C][C]32[/C][C]36.0286[/C][C]-4.02857[/C][/ROW]
[ROW][C]214[/C][C]30[/C][C]32.9831[/C][C]-2.98312[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]33.7076[/C][C]1.29245[/C][/ROW]
[ROW][C]216[/C][C]28[/C][C]29.8155[/C][C]-1.81551[/C][/ROW]
[ROW][C]217[/C][C]33[/C][C]34.5855[/C][C]-1.58554[/C][/ROW]
[ROW][C]218[/C][C]39[/C][C]34.1396[/C][C]4.8604[/C][/ROW]
[ROW][C]219[/C][C]36[/C][C]33.2371[/C][C]2.7629[/C][/ROW]
[ROW][C]220[/C][C]36[/C][C]36.3101[/C][C]-0.310058[/C][/ROW]
[ROW][C]221[/C][C]35[/C][C]33.3066[/C][C]1.69338[/C][/ROW]
[ROW][C]222[/C][C]38[/C][C]33.8576[/C][C]4.14244[/C][/ROW]
[ROW][C]223[/C][C]33[/C][C]32.5961[/C][C]0.403931[/C][/ROW]
[ROW][C]224[/C][C]31[/C][C]33.0356[/C][C]-2.03557[/C][/ROW]
[ROW][C]225[/C][C]34[/C][C]31.9834[/C][C]2.01655[/C][/ROW]
[ROW][C]226[/C][C]32[/C][C]34.6692[/C][C]-2.66922[/C][/ROW]
[ROW][C]227[/C][C]31[/C][C]32.6533[/C][C]-1.65334[/C][/ROW]
[ROW][C]228[/C][C]33[/C][C]32.9991[/C][C]0.000852617[/C][/ROW]
[ROW][C]229[/C][C]34[/C][C]32.7754[/C][C]1.2246[/C][/ROW]
[ROW][C]230[/C][C]34[/C][C]34.0676[/C][C]-0.0676252[/C][/ROW]
[ROW][C]231[/C][C]34[/C][C]31.9277[/C][C]2.07228[/C][/ROW]
[ROW][C]232[/C][C]33[/C][C]35.473[/C][C]-2.47301[/C][/ROW]
[ROW][C]233[/C][C]32[/C][C]33.6594[/C][C]-1.65938[/C][/ROW]
[ROW][C]234[/C][C]41[/C][C]33.3362[/C][C]7.66378[/C][/ROW]
[ROW][C]235[/C][C]34[/C][C]33.0613[/C][C]0.938669[/C][/ROW]
[ROW][C]236[/C][C]36[/C][C]32.2865[/C][C]3.71354[/C][/ROW]
[ROW][C]237[/C][C]37[/C][C]32.2299[/C][C]4.77006[/C][/ROW]
[ROW][C]238[/C][C]36[/C][C]30.4771[/C][C]5.52286[/C][/ROW]
[ROW][C]239[/C][C]29[/C][C]32.3107[/C][C]-3.31072[/C][/ROW]
[ROW][C]240[/C][C]37[/C][C]31.9392[/C][C]5.06076[/C][/ROW]
[ROW][C]241[/C][C]27[/C][C]33.1719[/C][C]-6.17187[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]33.555[/C][C]1.44503[/C][/ROW]
[ROW][C]243[/C][C]28[/C][C]30.541[/C][C]-2.54105[/C][/ROW]
[ROW][C]244[/C][C]35[/C][C]32.9174[/C][C]2.08259[/C][/ROW]
[ROW][C]245[/C][C]37[/C][C]32.9306[/C][C]4.06936[/C][/ROW]
[ROW][C]246[/C][C]29[/C][C]33.6845[/C][C]-4.68452[/C][/ROW]
[ROW][C]247[/C][C]32[/C][C]34.1192[/C][C]-2.11919[/C][/ROW]
[ROW][C]248[/C][C]36[/C][C]32.0486[/C][C]3.95142[/C][/ROW]
[ROW][C]249[/C][C]19[/C][C]27.5185[/C][C]-8.51853[/C][/ROW]
[ROW][C]250[/C][C]21[/C][C]26.7582[/C][C]-5.75819[/C][/ROW]
[ROW][C]251[/C][C]31[/C][C]33.5405[/C][C]-2.54054[/C][/ROW]
[ROW][C]252[/C][C]33[/C][C]32.6774[/C][C]0.322631[/C][/ROW]
[ROW][C]253[/C][C]36[/C][C]33.8108[/C][C]2.18922[/C][/ROW]
[ROW][C]254[/C][C]33[/C][C]32.9339[/C][C]0.0660713[/C][/ROW]
[ROW][C]255[/C][C]37[/C][C]33.261[/C][C]3.73896[/C][/ROW]
[ROW][C]256[/C][C]34[/C][C]33.2892[/C][C]0.710833[/C][/ROW]
[ROW][C]257[/C][C]35[/C][C]34.3094[/C][C]0.690633[/C][/ROW]
[ROW][C]258[/C][C]31[/C][C]32.544[/C][C]-1.544[/C][/ROW]
[ROW][C]259[/C][C]37[/C][C]33.5523[/C][C]3.44769[/C][/ROW]
[ROW][C]260[/C][C]35[/C][C]32.4552[/C][C]2.54482[/C][/ROW]
[ROW][C]261[/C][C]27[/C][C]31.7241[/C][C]-4.72406[/C][/ROW]
[ROW][C]262[/C][C]34[/C][C]35.3835[/C][C]-1.38351[/C][/ROW]
[ROW][C]263[/C][C]40[/C][C]33.9462[/C][C]6.05382[/C][/ROW]
[ROW][C]264[/C][C]29[/C][C]32.7656[/C][C]-3.76563[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225827&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225827&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
14136.33274.66735
23934.54884.45116
33035.4069-5.40688
43134.4278-3.42775
53436.0215-2.02149
63532.97662.02337
73933.42145.57864
83436.1447-2.14472
93635.59720.402821
103736.88650.113499
113834.09943.90065
123634.93521.06476
133835.27542.72462
143936.34482.65517
153336.8262-3.82622
163234.2813-2.28126
173634.03121.96879
183837.24670.753252
193936.91312.08687
203233.9805-1.98051
213234.7379-2.7379
223133.7805-2.78047
233936.40462.59537
243737.0654-0.0654364
253934.50054.49948
264134.1526.84798
273635.22860.771378
283336.3711-3.37111
293334.3479-1.34793
303434.7349-0.734932
313134.0848-3.08479
322733.6096-6.60961
333733.80133.19873
343436.9712-2.97116
353432.91641.08356
363234.8408-2.84079
372932.8919-3.89191
383634.55451.44554
392933.9002-4.90024
403534.57550.42447
413734.32372.67634
423434.4019-0.401863
433834.02053.97955
443533.9481.05204
453832.39355.60652
463735.10151.89855
473837.60730.392657
483335.1779-2.17791
493636.367-0.367048
503834.15563.84439
513236.919-4.919
523232.9784-0.978411
533233.9091-1.90909
543437.3886-3.38864
553233.6491-1.64908
563735.49631.50374
573935.04843.95159
582935.2072-6.20723
593735.78391.21612
603534.83510.164899
613031.4723-1.47231
623834.88223.11782
633435.4878-1.48778
643134.865-3.86504
653433.32570.67434
663535.861-0.860985
673634.63481.36516
683030.9088-0.908765
693936.74442.25565
703535.5585-0.5585
713835.45782.54218
723135.6673-4.66729
733436.5831-2.5831
743837.25690.743067
753431.47622.52384
763932.47426.52578
773735.71521.28477
783432.99871.00134
792833.1711-5.17109
803731.08775.91228
813335.2213-2.22129
823536.0299-1.02992
833733.84143.15864
843234.4177-2.41771
853333.1397-0.139719
863836.50621.49383
873334.3205-1.3205
882932.999-3.99895
893333.3658-0.365763
903135.4563-4.45633
913633.01582.98422
923537.4105-2.41046
933231.62140.378628
942932.5672-3.5672
953935.29663.7034
963734.662.33995
973533.05651.94352
983734.52322.47682
993235.4047-3.40474
1003835.3512.64896
1013734.68142.31858
1023636.0476-0.0476345
1033231.83560.164386
1043336.4166-3.41664
1054032.97117.02892
1063835.07252.92747
1074136.35714.64293
1083634.23961.76037
1094336.91756.08249
1103034.615-4.61502
1113133.6849-2.68486
1123237.9506-5.95063
1133231.68850.311549
1143734.62162.37841
1153734.01382.98623
1163336.5538-3.55381
1173437.2001-3.20015
1183334.8838-1.88381
1193835.52052.47945
1203335.1511-2.1511
1213131.3034-0.303404
1223836.95891.04114
1233736.50370.496318
1243633.2332.767
1253134.0075-3.00752
1263934.13864.86142
1274436.62477.37534
1283336-3.00005
1293533.93771.06232
1303233.7978-1.79784
1312832.9047-4.90473
1324035.7794.22097
1332732.4268-5.42678
1343736.29840.701616
1353232.5737-0.573712
1362828.2304-0.230441
1373434.962-0.962029
1383034.4426-4.44262
1393534.38010.61986
1403134.6027-3.60265
1413234.1102-2.11021
1423035.8587-5.85872
1433035.2025-5.20254
1443129.60881.39117
1454033.58846.41163
1463231.5490.450953
1473635.07160.928353
1483233.1832-1.18323
1493533.28611.71389
1503836.99041.00963
1514235.47196.52805
1523436.003-2.00304
1533536.5071-1.50711
1543834.63573.36428
1553333.3018-0.301832
1563633.01582.98422
1573235.6211-3.62114
1583336-3.00005
1593433.85380.146199
1603235.9139-3.91385
1613435.4371-1.43707
1622729.8442-2.84425
1633130.07280.927246
1643833.22844.77163
1653435.473-1.47303
1662431.0764-7.07639
1673033.4942-3.49421
1682629.6205-3.62049
1693435.4318-1.43178
1702734.31-7.30996
1713731.69495.30515
1723635.11710.882882
1734134.14266.85744
1742929.1824-0.182369
1753631.15244.84756
1763234.0128-2.01277
1773733.11743.88264
1783031.5048-1.50482
1793132.4823-1.48234
1803834.57763.42241
1813634.30611.69388
1823532.00832.99169
1833134.8228-3.82281
1843833.0534.94702
1852231.671-9.67097
1863234.1097-2.10966
1873633.4592.54103
1883932.63596.36412
1892830.2906-2.29059
1903234.1101-2.11009
1913232.3961-0.396145
1923836.32221.67778
1933233.0882-1.08815
1943534.98440.0156223
1953232.8189-0.818949
1963735.57221.42776
1973432.25061.74936
1983335.2404-2.24037
1993332.57130.428747
2002632.5839-6.58393
2013031.855-1.85498
2022431.7211-7.72112
2033432.16831.83172
2043432.64321.3568
2053333.6958-0.695784
2063434.6276-0.627626
2073535.7011-0.701141
2083534.03590.964103
2093633.31442.68562
2103433.46140.538649
2113432.94631.05369
2124138.65782.34225
2133236.0286-4.02857
2143032.9831-2.98312
2153533.70761.29245
2162829.8155-1.81551
2173334.5855-1.58554
2183934.13964.8604
2193633.23712.7629
2203636.3101-0.310058
2213533.30661.69338
2223833.85764.14244
2233332.59610.403931
2243133.0356-2.03557
2253431.98342.01655
2263234.6692-2.66922
2273132.6533-1.65334
2283332.99910.000852617
2293432.77541.2246
2303434.0676-0.0676252
2313431.92772.07228
2323335.473-2.47301
2333233.6594-1.65938
2344133.33627.66378
2353433.06130.938669
2363632.28653.71354
2373732.22994.77006
2383630.47715.52286
2392932.3107-3.31072
2403731.93925.06076
2412733.1719-6.17187
2423533.5551.44503
2432830.541-2.54105
2443532.91742.08259
2453732.93064.06936
2462933.6845-4.68452
2473234.1192-2.11919
2483632.04863.95142
2491927.5185-8.51853
2502126.7582-5.75819
2513133.5405-2.54054
2523332.67740.322631
2533633.81082.18922
2543332.93390.0660713
2553733.2613.73896
2563433.28920.710833
2573534.30940.690633
2583132.544-1.544
2593733.55233.44769
2603532.45522.54482
2612731.7241-4.72406
2623435.3835-1.38351
2634033.94626.05382
2642932.7656-3.76563






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.04710090.09420180.952899
120.7577240.4845530.242276
130.8487620.3024750.151238
140.7717740.4564510.228226
150.7421410.5157180.257859
160.7328790.5342420.267121
170.6848950.6302110.315105
180.6075520.7848960.392448
190.523320.953360.47668
200.5554550.8890890.444545
210.6092130.7815730.390787
220.5632490.8735020.436751
230.5363430.9273150.463657
240.4726850.9453690.527315
250.5407770.9184470.459223
260.7586480.4827040.241352
270.7124190.5751620.287581
280.6905120.6189750.309488
290.6654960.6690080.334504
300.6135370.7729260.386463
310.6204460.7591070.379554
320.8055610.3888790.194439
330.7846460.4307080.215354
340.7627430.4745150.237257
350.7171440.5657110.282856
360.7039320.5921360.296068
370.705630.5887390.29437
380.6613790.6772430.338621
390.7209860.5580280.279014
400.6753850.6492290.324615
410.6528190.6943610.347181
420.6051050.789790.394895
430.5776040.8447910.422396
440.5298840.9402310.470116
450.5827020.8345960.417298
460.5460190.9079620.453981
470.497420.9948390.50258
480.4689350.937870.531065
490.4204510.8409020.579549
500.4168450.833690.583155
510.4799330.9598650.520067
520.4429230.8858460.557077
530.4108490.8216990.589151
540.380840.761680.61916
550.3463590.6927170.653641
560.3412620.6825240.658738
570.3560970.7121930.643903
580.4780680.9561360.521932
590.4400510.8801020.559949
600.3980090.7960180.601991
610.3617750.7235510.638225
620.3492760.6985530.650724
630.3184760.6369510.681524
640.3327140.6654290.667286
650.2944150.5888310.705585
660.2589170.5178330.741083
670.2327270.4654540.767273
680.2175890.4351770.782411
690.2041010.4082010.795899
700.1767260.3534510.823274
710.1687810.3375620.831219
720.1980090.3960190.801991
730.1848070.3696140.815193
740.1604020.3208040.839598
750.1424860.2849720.857514
760.2069520.4139030.793048
770.1808590.3617170.819141
780.1558730.3117460.844127
790.2205990.4411980.779401
800.2509560.5019130.749044
810.2382240.4764490.761776
820.2118610.4237220.788139
830.2004870.4009730.799513
840.1924810.3849620.807519
850.1682130.3364250.831787
860.1528770.3057540.847123
870.1363190.2726380.863681
880.151850.30370.84815
890.130210.2604210.86979
900.1430930.2861850.856907
910.1346720.2693440.865328
920.12080.2415990.8792
930.1038970.2077930.896103
940.1135760.2271530.886424
950.1205020.2410040.879498
960.1128120.2256250.887188
970.099840.199680.90016
980.09105780.1821160.908942
990.09120510.182410.908795
1000.08419020.168380.91581
1010.07846570.1569310.921534
1020.06559070.1311810.934409
1030.05496740.1099350.945033
1040.05308050.1061610.94692
1050.09676460.1935290.903235
1060.09282620.1856520.907174
1070.1124630.2249270.887537
1080.09994130.1998830.900059
1090.15040.3007990.8496
1100.1721140.3442290.827886
1110.1675860.3351720.832414
1120.2059750.4119490.794025
1130.190850.3816990.80915
1140.1776920.3553840.822308
1150.1720450.3440910.827955
1160.1737480.3474960.826252
1170.1693540.3387070.830646
1180.1537190.3074380.846281
1190.145360.290720.85464
1200.1337110.2674230.866289
1210.1186880.2373770.881312
1220.1046120.2092240.895388
1230.08995170.1799030.910048
1240.08447330.1689470.915527
1250.08205870.1641170.917941
1260.09839510.196790.901605
1270.1780310.3560630.821969
1280.1744250.348850.825575
1290.1549980.3099960.845002
1300.1404920.2809840.859508
1310.1641810.3283630.835819
1320.1795920.3591850.820408
1330.2228890.4457770.777111
1340.198460.396920.80154
1350.1760450.3520910.823955
1360.1554370.3108740.844563
1370.1364770.2729550.863523
1380.1522940.3045880.847706
1390.1324980.2649960.867502
1400.1352240.2704480.864776
1410.1254290.2508570.874571
1420.1650220.3300440.834978
1430.1991610.3983230.800839
1440.1809580.3619160.819042
1450.2543530.5087070.745647
1460.2292850.4585690.770715
1470.2053650.4107290.794635
1480.1832430.3664850.816757
1490.1668960.3337920.833104
1500.1471280.2942570.852872
1510.2232510.4465020.776749
1520.204730.4094610.79527
1530.1856770.3713540.814323
1540.203010.4060210.79699
1550.1814060.3628120.818594
1560.1989560.3979120.801044
1570.1898240.3796470.810176
1580.1752520.3505050.824748
1590.1671620.3343250.832838
1600.1570260.3140510.842974
1610.1361870.2723730.863813
1620.1271290.2542580.872871
1630.1169940.2339880.883006
1640.1516610.3033230.848339
1650.1370360.2740730.862964
1660.2176960.4353930.782304
1670.213870.427740.78613
1680.2035390.4070790.796461
1690.1824490.3648980.817551
1700.2771640.5543270.722836
1710.3239010.6478020.676099
1720.2933360.5866720.706664
1730.4049990.8099990.595001
1740.3704870.7409740.629513
1750.4467860.8935730.553214
1760.4180830.8361670.581917
1770.4229340.8458680.577066
1780.3891880.7783760.610812
1790.3575630.7151260.642437
1800.3560150.7120290.643985
1810.3247790.6495580.675221
1820.3188950.6377890.681105
1830.3358890.6717780.664111
1840.4067880.8135760.593212
1850.6151260.7697480.384874
1860.59350.8130010.4065
1870.5806670.8386650.419333
1880.7285160.5429680.271484
1890.7041220.5917550.295878
1900.7128780.5742430.287122
1910.6790720.6418560.320928
1920.6484770.7030460.351523
1930.618010.7639810.38199
1940.5946890.8106230.405311
1950.5547810.8904380.445219
1960.5162250.9675510.483775
1970.4962770.9925540.503723
1980.4689020.9378050.531098
1990.4271040.8542080.572896
2000.4933890.9867770.506611
2010.4631170.9262330.536883
2020.6039240.7921520.396076
2030.5995410.8009180.400459
2040.5591130.8817750.440887
2050.5157790.9684420.484221
2060.4756160.9512330.524384
2070.4418650.883730.558135
2080.4019880.8039750.598012
2090.3782780.7565570.621722
2100.3436410.6872830.656359
2110.3037810.6075620.696219
2120.2702610.5405220.729739
2130.3259860.6519730.674014
2140.313070.626140.68693
2150.2740190.5480380.725981
2160.2379970.4759940.762003
2170.2120510.4241010.787949
2180.2379610.4759230.762039
2190.2110650.422130.788935
2200.1929840.3859670.807016
2210.1677690.3355380.832231
2220.1837140.3674280.816286
2230.1516480.3032950.848352
2240.1282240.2564480.871776
2250.2045860.4091710.795414
2260.1818840.3637680.818116
2270.1573250.3146510.842675
2280.1695120.3390230.830488
2290.1379240.2758490.862076
2300.1093080.2186160.890692
2310.1039220.2078450.896078
2320.2006690.4013380.799331
2330.1772560.3545110.822744
2340.2488490.4976990.751151
2350.2077150.415430.792285
2360.2343740.4687480.765626
2370.2114820.4229640.788518
2380.3048620.6097230.695138
2390.2519910.5039820.748009
2400.4358820.8717640.564118
2410.4988520.9977050.501148
2420.4234230.8468460.576577
2430.3533080.7066160.646692
2440.3057870.6115750.694213
2450.3060450.612090.693955
2460.5117630.9764750.488237
2470.5523690.8952610.447631
2480.521120.957760.47888
2490.7026870.5946260.297313
2500.7027190.5945630.297281
2510.6791860.6416280.320814
2520.6978370.6043260.302163
2530.5311660.9376690.468834

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.0471009 & 0.0942018 & 0.952899 \tabularnewline
12 & 0.757724 & 0.484553 & 0.242276 \tabularnewline
13 & 0.848762 & 0.302475 & 0.151238 \tabularnewline
14 & 0.771774 & 0.456451 & 0.228226 \tabularnewline
15 & 0.742141 & 0.515718 & 0.257859 \tabularnewline
16 & 0.732879 & 0.534242 & 0.267121 \tabularnewline
17 & 0.684895 & 0.630211 & 0.315105 \tabularnewline
18 & 0.607552 & 0.784896 & 0.392448 \tabularnewline
19 & 0.52332 & 0.95336 & 0.47668 \tabularnewline
20 & 0.555455 & 0.889089 & 0.444545 \tabularnewline
21 & 0.609213 & 0.781573 & 0.390787 \tabularnewline
22 & 0.563249 & 0.873502 & 0.436751 \tabularnewline
23 & 0.536343 & 0.927315 & 0.463657 \tabularnewline
24 & 0.472685 & 0.945369 & 0.527315 \tabularnewline
25 & 0.540777 & 0.918447 & 0.459223 \tabularnewline
26 & 0.758648 & 0.482704 & 0.241352 \tabularnewline
27 & 0.712419 & 0.575162 & 0.287581 \tabularnewline
28 & 0.690512 & 0.618975 & 0.309488 \tabularnewline
29 & 0.665496 & 0.669008 & 0.334504 \tabularnewline
30 & 0.613537 & 0.772926 & 0.386463 \tabularnewline
31 & 0.620446 & 0.759107 & 0.379554 \tabularnewline
32 & 0.805561 & 0.388879 & 0.194439 \tabularnewline
33 & 0.784646 & 0.430708 & 0.215354 \tabularnewline
34 & 0.762743 & 0.474515 & 0.237257 \tabularnewline
35 & 0.717144 & 0.565711 & 0.282856 \tabularnewline
36 & 0.703932 & 0.592136 & 0.296068 \tabularnewline
37 & 0.70563 & 0.588739 & 0.29437 \tabularnewline
38 & 0.661379 & 0.677243 & 0.338621 \tabularnewline
39 & 0.720986 & 0.558028 & 0.279014 \tabularnewline
40 & 0.675385 & 0.649229 & 0.324615 \tabularnewline
41 & 0.652819 & 0.694361 & 0.347181 \tabularnewline
42 & 0.605105 & 0.78979 & 0.394895 \tabularnewline
43 & 0.577604 & 0.844791 & 0.422396 \tabularnewline
44 & 0.529884 & 0.940231 & 0.470116 \tabularnewline
45 & 0.582702 & 0.834596 & 0.417298 \tabularnewline
46 & 0.546019 & 0.907962 & 0.453981 \tabularnewline
47 & 0.49742 & 0.994839 & 0.50258 \tabularnewline
48 & 0.468935 & 0.93787 & 0.531065 \tabularnewline
49 & 0.420451 & 0.840902 & 0.579549 \tabularnewline
50 & 0.416845 & 0.83369 & 0.583155 \tabularnewline
51 & 0.479933 & 0.959865 & 0.520067 \tabularnewline
52 & 0.442923 & 0.885846 & 0.557077 \tabularnewline
53 & 0.410849 & 0.821699 & 0.589151 \tabularnewline
54 & 0.38084 & 0.76168 & 0.61916 \tabularnewline
55 & 0.346359 & 0.692717 & 0.653641 \tabularnewline
56 & 0.341262 & 0.682524 & 0.658738 \tabularnewline
57 & 0.356097 & 0.712193 & 0.643903 \tabularnewline
58 & 0.478068 & 0.956136 & 0.521932 \tabularnewline
59 & 0.440051 & 0.880102 & 0.559949 \tabularnewline
60 & 0.398009 & 0.796018 & 0.601991 \tabularnewline
61 & 0.361775 & 0.723551 & 0.638225 \tabularnewline
62 & 0.349276 & 0.698553 & 0.650724 \tabularnewline
63 & 0.318476 & 0.636951 & 0.681524 \tabularnewline
64 & 0.332714 & 0.665429 & 0.667286 \tabularnewline
65 & 0.294415 & 0.588831 & 0.705585 \tabularnewline
66 & 0.258917 & 0.517833 & 0.741083 \tabularnewline
67 & 0.232727 & 0.465454 & 0.767273 \tabularnewline
68 & 0.217589 & 0.435177 & 0.782411 \tabularnewline
69 & 0.204101 & 0.408201 & 0.795899 \tabularnewline
70 & 0.176726 & 0.353451 & 0.823274 \tabularnewline
71 & 0.168781 & 0.337562 & 0.831219 \tabularnewline
72 & 0.198009 & 0.396019 & 0.801991 \tabularnewline
73 & 0.184807 & 0.369614 & 0.815193 \tabularnewline
74 & 0.160402 & 0.320804 & 0.839598 \tabularnewline
75 & 0.142486 & 0.284972 & 0.857514 \tabularnewline
76 & 0.206952 & 0.413903 & 0.793048 \tabularnewline
77 & 0.180859 & 0.361717 & 0.819141 \tabularnewline
78 & 0.155873 & 0.311746 & 0.844127 \tabularnewline
79 & 0.220599 & 0.441198 & 0.779401 \tabularnewline
80 & 0.250956 & 0.501913 & 0.749044 \tabularnewline
81 & 0.238224 & 0.476449 & 0.761776 \tabularnewline
82 & 0.211861 & 0.423722 & 0.788139 \tabularnewline
83 & 0.200487 & 0.400973 & 0.799513 \tabularnewline
84 & 0.192481 & 0.384962 & 0.807519 \tabularnewline
85 & 0.168213 & 0.336425 & 0.831787 \tabularnewline
86 & 0.152877 & 0.305754 & 0.847123 \tabularnewline
87 & 0.136319 & 0.272638 & 0.863681 \tabularnewline
88 & 0.15185 & 0.3037 & 0.84815 \tabularnewline
89 & 0.13021 & 0.260421 & 0.86979 \tabularnewline
90 & 0.143093 & 0.286185 & 0.856907 \tabularnewline
91 & 0.134672 & 0.269344 & 0.865328 \tabularnewline
92 & 0.1208 & 0.241599 & 0.8792 \tabularnewline
93 & 0.103897 & 0.207793 & 0.896103 \tabularnewline
94 & 0.113576 & 0.227153 & 0.886424 \tabularnewline
95 & 0.120502 & 0.241004 & 0.879498 \tabularnewline
96 & 0.112812 & 0.225625 & 0.887188 \tabularnewline
97 & 0.09984 & 0.19968 & 0.90016 \tabularnewline
98 & 0.0910578 & 0.182116 & 0.908942 \tabularnewline
99 & 0.0912051 & 0.18241 & 0.908795 \tabularnewline
100 & 0.0841902 & 0.16838 & 0.91581 \tabularnewline
101 & 0.0784657 & 0.156931 & 0.921534 \tabularnewline
102 & 0.0655907 & 0.131181 & 0.934409 \tabularnewline
103 & 0.0549674 & 0.109935 & 0.945033 \tabularnewline
104 & 0.0530805 & 0.106161 & 0.94692 \tabularnewline
105 & 0.0967646 & 0.193529 & 0.903235 \tabularnewline
106 & 0.0928262 & 0.185652 & 0.907174 \tabularnewline
107 & 0.112463 & 0.224927 & 0.887537 \tabularnewline
108 & 0.0999413 & 0.199883 & 0.900059 \tabularnewline
109 & 0.1504 & 0.300799 & 0.8496 \tabularnewline
110 & 0.172114 & 0.344229 & 0.827886 \tabularnewline
111 & 0.167586 & 0.335172 & 0.832414 \tabularnewline
112 & 0.205975 & 0.411949 & 0.794025 \tabularnewline
113 & 0.19085 & 0.381699 & 0.80915 \tabularnewline
114 & 0.177692 & 0.355384 & 0.822308 \tabularnewline
115 & 0.172045 & 0.344091 & 0.827955 \tabularnewline
116 & 0.173748 & 0.347496 & 0.826252 \tabularnewline
117 & 0.169354 & 0.338707 & 0.830646 \tabularnewline
118 & 0.153719 & 0.307438 & 0.846281 \tabularnewline
119 & 0.14536 & 0.29072 & 0.85464 \tabularnewline
120 & 0.133711 & 0.267423 & 0.866289 \tabularnewline
121 & 0.118688 & 0.237377 & 0.881312 \tabularnewline
122 & 0.104612 & 0.209224 & 0.895388 \tabularnewline
123 & 0.0899517 & 0.179903 & 0.910048 \tabularnewline
124 & 0.0844733 & 0.168947 & 0.915527 \tabularnewline
125 & 0.0820587 & 0.164117 & 0.917941 \tabularnewline
126 & 0.0983951 & 0.19679 & 0.901605 \tabularnewline
127 & 0.178031 & 0.356063 & 0.821969 \tabularnewline
128 & 0.174425 & 0.34885 & 0.825575 \tabularnewline
129 & 0.154998 & 0.309996 & 0.845002 \tabularnewline
130 & 0.140492 & 0.280984 & 0.859508 \tabularnewline
131 & 0.164181 & 0.328363 & 0.835819 \tabularnewline
132 & 0.179592 & 0.359185 & 0.820408 \tabularnewline
133 & 0.222889 & 0.445777 & 0.777111 \tabularnewline
134 & 0.19846 & 0.39692 & 0.80154 \tabularnewline
135 & 0.176045 & 0.352091 & 0.823955 \tabularnewline
136 & 0.155437 & 0.310874 & 0.844563 \tabularnewline
137 & 0.136477 & 0.272955 & 0.863523 \tabularnewline
138 & 0.152294 & 0.304588 & 0.847706 \tabularnewline
139 & 0.132498 & 0.264996 & 0.867502 \tabularnewline
140 & 0.135224 & 0.270448 & 0.864776 \tabularnewline
141 & 0.125429 & 0.250857 & 0.874571 \tabularnewline
142 & 0.165022 & 0.330044 & 0.834978 \tabularnewline
143 & 0.199161 & 0.398323 & 0.800839 \tabularnewline
144 & 0.180958 & 0.361916 & 0.819042 \tabularnewline
145 & 0.254353 & 0.508707 & 0.745647 \tabularnewline
146 & 0.229285 & 0.458569 & 0.770715 \tabularnewline
147 & 0.205365 & 0.410729 & 0.794635 \tabularnewline
148 & 0.183243 & 0.366485 & 0.816757 \tabularnewline
149 & 0.166896 & 0.333792 & 0.833104 \tabularnewline
150 & 0.147128 & 0.294257 & 0.852872 \tabularnewline
151 & 0.223251 & 0.446502 & 0.776749 \tabularnewline
152 & 0.20473 & 0.409461 & 0.79527 \tabularnewline
153 & 0.185677 & 0.371354 & 0.814323 \tabularnewline
154 & 0.20301 & 0.406021 & 0.79699 \tabularnewline
155 & 0.181406 & 0.362812 & 0.818594 \tabularnewline
156 & 0.198956 & 0.397912 & 0.801044 \tabularnewline
157 & 0.189824 & 0.379647 & 0.810176 \tabularnewline
158 & 0.175252 & 0.350505 & 0.824748 \tabularnewline
159 & 0.167162 & 0.334325 & 0.832838 \tabularnewline
160 & 0.157026 & 0.314051 & 0.842974 \tabularnewline
161 & 0.136187 & 0.272373 & 0.863813 \tabularnewline
162 & 0.127129 & 0.254258 & 0.872871 \tabularnewline
163 & 0.116994 & 0.233988 & 0.883006 \tabularnewline
164 & 0.151661 & 0.303323 & 0.848339 \tabularnewline
165 & 0.137036 & 0.274073 & 0.862964 \tabularnewline
166 & 0.217696 & 0.435393 & 0.782304 \tabularnewline
167 & 0.21387 & 0.42774 & 0.78613 \tabularnewline
168 & 0.203539 & 0.407079 & 0.796461 \tabularnewline
169 & 0.182449 & 0.364898 & 0.817551 \tabularnewline
170 & 0.277164 & 0.554327 & 0.722836 \tabularnewline
171 & 0.323901 & 0.647802 & 0.676099 \tabularnewline
172 & 0.293336 & 0.586672 & 0.706664 \tabularnewline
173 & 0.404999 & 0.809999 & 0.595001 \tabularnewline
174 & 0.370487 & 0.740974 & 0.629513 \tabularnewline
175 & 0.446786 & 0.893573 & 0.553214 \tabularnewline
176 & 0.418083 & 0.836167 & 0.581917 \tabularnewline
177 & 0.422934 & 0.845868 & 0.577066 \tabularnewline
178 & 0.389188 & 0.778376 & 0.610812 \tabularnewline
179 & 0.357563 & 0.715126 & 0.642437 \tabularnewline
180 & 0.356015 & 0.712029 & 0.643985 \tabularnewline
181 & 0.324779 & 0.649558 & 0.675221 \tabularnewline
182 & 0.318895 & 0.637789 & 0.681105 \tabularnewline
183 & 0.335889 & 0.671778 & 0.664111 \tabularnewline
184 & 0.406788 & 0.813576 & 0.593212 \tabularnewline
185 & 0.615126 & 0.769748 & 0.384874 \tabularnewline
186 & 0.5935 & 0.813001 & 0.4065 \tabularnewline
187 & 0.580667 & 0.838665 & 0.419333 \tabularnewline
188 & 0.728516 & 0.542968 & 0.271484 \tabularnewline
189 & 0.704122 & 0.591755 & 0.295878 \tabularnewline
190 & 0.712878 & 0.574243 & 0.287122 \tabularnewline
191 & 0.679072 & 0.641856 & 0.320928 \tabularnewline
192 & 0.648477 & 0.703046 & 0.351523 \tabularnewline
193 & 0.61801 & 0.763981 & 0.38199 \tabularnewline
194 & 0.594689 & 0.810623 & 0.405311 \tabularnewline
195 & 0.554781 & 0.890438 & 0.445219 \tabularnewline
196 & 0.516225 & 0.967551 & 0.483775 \tabularnewline
197 & 0.496277 & 0.992554 & 0.503723 \tabularnewline
198 & 0.468902 & 0.937805 & 0.531098 \tabularnewline
199 & 0.427104 & 0.854208 & 0.572896 \tabularnewline
200 & 0.493389 & 0.986777 & 0.506611 \tabularnewline
201 & 0.463117 & 0.926233 & 0.536883 \tabularnewline
202 & 0.603924 & 0.792152 & 0.396076 \tabularnewline
203 & 0.599541 & 0.800918 & 0.400459 \tabularnewline
204 & 0.559113 & 0.881775 & 0.440887 \tabularnewline
205 & 0.515779 & 0.968442 & 0.484221 \tabularnewline
206 & 0.475616 & 0.951233 & 0.524384 \tabularnewline
207 & 0.441865 & 0.88373 & 0.558135 \tabularnewline
208 & 0.401988 & 0.803975 & 0.598012 \tabularnewline
209 & 0.378278 & 0.756557 & 0.621722 \tabularnewline
210 & 0.343641 & 0.687283 & 0.656359 \tabularnewline
211 & 0.303781 & 0.607562 & 0.696219 \tabularnewline
212 & 0.270261 & 0.540522 & 0.729739 \tabularnewline
213 & 0.325986 & 0.651973 & 0.674014 \tabularnewline
214 & 0.31307 & 0.62614 & 0.68693 \tabularnewline
215 & 0.274019 & 0.548038 & 0.725981 \tabularnewline
216 & 0.237997 & 0.475994 & 0.762003 \tabularnewline
217 & 0.212051 & 0.424101 & 0.787949 \tabularnewline
218 & 0.237961 & 0.475923 & 0.762039 \tabularnewline
219 & 0.211065 & 0.42213 & 0.788935 \tabularnewline
220 & 0.192984 & 0.385967 & 0.807016 \tabularnewline
221 & 0.167769 & 0.335538 & 0.832231 \tabularnewline
222 & 0.183714 & 0.367428 & 0.816286 \tabularnewline
223 & 0.151648 & 0.303295 & 0.848352 \tabularnewline
224 & 0.128224 & 0.256448 & 0.871776 \tabularnewline
225 & 0.204586 & 0.409171 & 0.795414 \tabularnewline
226 & 0.181884 & 0.363768 & 0.818116 \tabularnewline
227 & 0.157325 & 0.314651 & 0.842675 \tabularnewline
228 & 0.169512 & 0.339023 & 0.830488 \tabularnewline
229 & 0.137924 & 0.275849 & 0.862076 \tabularnewline
230 & 0.109308 & 0.218616 & 0.890692 \tabularnewline
231 & 0.103922 & 0.207845 & 0.896078 \tabularnewline
232 & 0.200669 & 0.401338 & 0.799331 \tabularnewline
233 & 0.177256 & 0.354511 & 0.822744 \tabularnewline
234 & 0.248849 & 0.497699 & 0.751151 \tabularnewline
235 & 0.207715 & 0.41543 & 0.792285 \tabularnewline
236 & 0.234374 & 0.468748 & 0.765626 \tabularnewline
237 & 0.211482 & 0.422964 & 0.788518 \tabularnewline
238 & 0.304862 & 0.609723 & 0.695138 \tabularnewline
239 & 0.251991 & 0.503982 & 0.748009 \tabularnewline
240 & 0.435882 & 0.871764 & 0.564118 \tabularnewline
241 & 0.498852 & 0.997705 & 0.501148 \tabularnewline
242 & 0.423423 & 0.846846 & 0.576577 \tabularnewline
243 & 0.353308 & 0.706616 & 0.646692 \tabularnewline
244 & 0.305787 & 0.611575 & 0.694213 \tabularnewline
245 & 0.306045 & 0.61209 & 0.693955 \tabularnewline
246 & 0.511763 & 0.976475 & 0.488237 \tabularnewline
247 & 0.552369 & 0.895261 & 0.447631 \tabularnewline
248 & 0.52112 & 0.95776 & 0.47888 \tabularnewline
249 & 0.702687 & 0.594626 & 0.297313 \tabularnewline
250 & 0.702719 & 0.594563 & 0.297281 \tabularnewline
251 & 0.679186 & 0.641628 & 0.320814 \tabularnewline
252 & 0.697837 & 0.604326 & 0.302163 \tabularnewline
253 & 0.531166 & 0.937669 & 0.468834 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225827&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]11[/C][C]0.0471009[/C][C]0.0942018[/C][C]0.952899[/C][/ROW]
[ROW][C]12[/C][C]0.757724[/C][C]0.484553[/C][C]0.242276[/C][/ROW]
[ROW][C]13[/C][C]0.848762[/C][C]0.302475[/C][C]0.151238[/C][/ROW]
[ROW][C]14[/C][C]0.771774[/C][C]0.456451[/C][C]0.228226[/C][/ROW]
[ROW][C]15[/C][C]0.742141[/C][C]0.515718[/C][C]0.257859[/C][/ROW]
[ROW][C]16[/C][C]0.732879[/C][C]0.534242[/C][C]0.267121[/C][/ROW]
[ROW][C]17[/C][C]0.684895[/C][C]0.630211[/C][C]0.315105[/C][/ROW]
[ROW][C]18[/C][C]0.607552[/C][C]0.784896[/C][C]0.392448[/C][/ROW]
[ROW][C]19[/C][C]0.52332[/C][C]0.95336[/C][C]0.47668[/C][/ROW]
[ROW][C]20[/C][C]0.555455[/C][C]0.889089[/C][C]0.444545[/C][/ROW]
[ROW][C]21[/C][C]0.609213[/C][C]0.781573[/C][C]0.390787[/C][/ROW]
[ROW][C]22[/C][C]0.563249[/C][C]0.873502[/C][C]0.436751[/C][/ROW]
[ROW][C]23[/C][C]0.536343[/C][C]0.927315[/C][C]0.463657[/C][/ROW]
[ROW][C]24[/C][C]0.472685[/C][C]0.945369[/C][C]0.527315[/C][/ROW]
[ROW][C]25[/C][C]0.540777[/C][C]0.918447[/C][C]0.459223[/C][/ROW]
[ROW][C]26[/C][C]0.758648[/C][C]0.482704[/C][C]0.241352[/C][/ROW]
[ROW][C]27[/C][C]0.712419[/C][C]0.575162[/C][C]0.287581[/C][/ROW]
[ROW][C]28[/C][C]0.690512[/C][C]0.618975[/C][C]0.309488[/C][/ROW]
[ROW][C]29[/C][C]0.665496[/C][C]0.669008[/C][C]0.334504[/C][/ROW]
[ROW][C]30[/C][C]0.613537[/C][C]0.772926[/C][C]0.386463[/C][/ROW]
[ROW][C]31[/C][C]0.620446[/C][C]0.759107[/C][C]0.379554[/C][/ROW]
[ROW][C]32[/C][C]0.805561[/C][C]0.388879[/C][C]0.194439[/C][/ROW]
[ROW][C]33[/C][C]0.784646[/C][C]0.430708[/C][C]0.215354[/C][/ROW]
[ROW][C]34[/C][C]0.762743[/C][C]0.474515[/C][C]0.237257[/C][/ROW]
[ROW][C]35[/C][C]0.717144[/C][C]0.565711[/C][C]0.282856[/C][/ROW]
[ROW][C]36[/C][C]0.703932[/C][C]0.592136[/C][C]0.296068[/C][/ROW]
[ROW][C]37[/C][C]0.70563[/C][C]0.588739[/C][C]0.29437[/C][/ROW]
[ROW][C]38[/C][C]0.661379[/C][C]0.677243[/C][C]0.338621[/C][/ROW]
[ROW][C]39[/C][C]0.720986[/C][C]0.558028[/C][C]0.279014[/C][/ROW]
[ROW][C]40[/C][C]0.675385[/C][C]0.649229[/C][C]0.324615[/C][/ROW]
[ROW][C]41[/C][C]0.652819[/C][C]0.694361[/C][C]0.347181[/C][/ROW]
[ROW][C]42[/C][C]0.605105[/C][C]0.78979[/C][C]0.394895[/C][/ROW]
[ROW][C]43[/C][C]0.577604[/C][C]0.844791[/C][C]0.422396[/C][/ROW]
[ROW][C]44[/C][C]0.529884[/C][C]0.940231[/C][C]0.470116[/C][/ROW]
[ROW][C]45[/C][C]0.582702[/C][C]0.834596[/C][C]0.417298[/C][/ROW]
[ROW][C]46[/C][C]0.546019[/C][C]0.907962[/C][C]0.453981[/C][/ROW]
[ROW][C]47[/C][C]0.49742[/C][C]0.994839[/C][C]0.50258[/C][/ROW]
[ROW][C]48[/C][C]0.468935[/C][C]0.93787[/C][C]0.531065[/C][/ROW]
[ROW][C]49[/C][C]0.420451[/C][C]0.840902[/C][C]0.579549[/C][/ROW]
[ROW][C]50[/C][C]0.416845[/C][C]0.83369[/C][C]0.583155[/C][/ROW]
[ROW][C]51[/C][C]0.479933[/C][C]0.959865[/C][C]0.520067[/C][/ROW]
[ROW][C]52[/C][C]0.442923[/C][C]0.885846[/C][C]0.557077[/C][/ROW]
[ROW][C]53[/C][C]0.410849[/C][C]0.821699[/C][C]0.589151[/C][/ROW]
[ROW][C]54[/C][C]0.38084[/C][C]0.76168[/C][C]0.61916[/C][/ROW]
[ROW][C]55[/C][C]0.346359[/C][C]0.692717[/C][C]0.653641[/C][/ROW]
[ROW][C]56[/C][C]0.341262[/C][C]0.682524[/C][C]0.658738[/C][/ROW]
[ROW][C]57[/C][C]0.356097[/C][C]0.712193[/C][C]0.643903[/C][/ROW]
[ROW][C]58[/C][C]0.478068[/C][C]0.956136[/C][C]0.521932[/C][/ROW]
[ROW][C]59[/C][C]0.440051[/C][C]0.880102[/C][C]0.559949[/C][/ROW]
[ROW][C]60[/C][C]0.398009[/C][C]0.796018[/C][C]0.601991[/C][/ROW]
[ROW][C]61[/C][C]0.361775[/C][C]0.723551[/C][C]0.638225[/C][/ROW]
[ROW][C]62[/C][C]0.349276[/C][C]0.698553[/C][C]0.650724[/C][/ROW]
[ROW][C]63[/C][C]0.318476[/C][C]0.636951[/C][C]0.681524[/C][/ROW]
[ROW][C]64[/C][C]0.332714[/C][C]0.665429[/C][C]0.667286[/C][/ROW]
[ROW][C]65[/C][C]0.294415[/C][C]0.588831[/C][C]0.705585[/C][/ROW]
[ROW][C]66[/C][C]0.258917[/C][C]0.517833[/C][C]0.741083[/C][/ROW]
[ROW][C]67[/C][C]0.232727[/C][C]0.465454[/C][C]0.767273[/C][/ROW]
[ROW][C]68[/C][C]0.217589[/C][C]0.435177[/C][C]0.782411[/C][/ROW]
[ROW][C]69[/C][C]0.204101[/C][C]0.408201[/C][C]0.795899[/C][/ROW]
[ROW][C]70[/C][C]0.176726[/C][C]0.353451[/C][C]0.823274[/C][/ROW]
[ROW][C]71[/C][C]0.168781[/C][C]0.337562[/C][C]0.831219[/C][/ROW]
[ROW][C]72[/C][C]0.198009[/C][C]0.396019[/C][C]0.801991[/C][/ROW]
[ROW][C]73[/C][C]0.184807[/C][C]0.369614[/C][C]0.815193[/C][/ROW]
[ROW][C]74[/C][C]0.160402[/C][C]0.320804[/C][C]0.839598[/C][/ROW]
[ROW][C]75[/C][C]0.142486[/C][C]0.284972[/C][C]0.857514[/C][/ROW]
[ROW][C]76[/C][C]0.206952[/C][C]0.413903[/C][C]0.793048[/C][/ROW]
[ROW][C]77[/C][C]0.180859[/C][C]0.361717[/C][C]0.819141[/C][/ROW]
[ROW][C]78[/C][C]0.155873[/C][C]0.311746[/C][C]0.844127[/C][/ROW]
[ROW][C]79[/C][C]0.220599[/C][C]0.441198[/C][C]0.779401[/C][/ROW]
[ROW][C]80[/C][C]0.250956[/C][C]0.501913[/C][C]0.749044[/C][/ROW]
[ROW][C]81[/C][C]0.238224[/C][C]0.476449[/C][C]0.761776[/C][/ROW]
[ROW][C]82[/C][C]0.211861[/C][C]0.423722[/C][C]0.788139[/C][/ROW]
[ROW][C]83[/C][C]0.200487[/C][C]0.400973[/C][C]0.799513[/C][/ROW]
[ROW][C]84[/C][C]0.192481[/C][C]0.384962[/C][C]0.807519[/C][/ROW]
[ROW][C]85[/C][C]0.168213[/C][C]0.336425[/C][C]0.831787[/C][/ROW]
[ROW][C]86[/C][C]0.152877[/C][C]0.305754[/C][C]0.847123[/C][/ROW]
[ROW][C]87[/C][C]0.136319[/C][C]0.272638[/C][C]0.863681[/C][/ROW]
[ROW][C]88[/C][C]0.15185[/C][C]0.3037[/C][C]0.84815[/C][/ROW]
[ROW][C]89[/C][C]0.13021[/C][C]0.260421[/C][C]0.86979[/C][/ROW]
[ROW][C]90[/C][C]0.143093[/C][C]0.286185[/C][C]0.856907[/C][/ROW]
[ROW][C]91[/C][C]0.134672[/C][C]0.269344[/C][C]0.865328[/C][/ROW]
[ROW][C]92[/C][C]0.1208[/C][C]0.241599[/C][C]0.8792[/C][/ROW]
[ROW][C]93[/C][C]0.103897[/C][C]0.207793[/C][C]0.896103[/C][/ROW]
[ROW][C]94[/C][C]0.113576[/C][C]0.227153[/C][C]0.886424[/C][/ROW]
[ROW][C]95[/C][C]0.120502[/C][C]0.241004[/C][C]0.879498[/C][/ROW]
[ROW][C]96[/C][C]0.112812[/C][C]0.225625[/C][C]0.887188[/C][/ROW]
[ROW][C]97[/C][C]0.09984[/C][C]0.19968[/C][C]0.90016[/C][/ROW]
[ROW][C]98[/C][C]0.0910578[/C][C]0.182116[/C][C]0.908942[/C][/ROW]
[ROW][C]99[/C][C]0.0912051[/C][C]0.18241[/C][C]0.908795[/C][/ROW]
[ROW][C]100[/C][C]0.0841902[/C][C]0.16838[/C][C]0.91581[/C][/ROW]
[ROW][C]101[/C][C]0.0784657[/C][C]0.156931[/C][C]0.921534[/C][/ROW]
[ROW][C]102[/C][C]0.0655907[/C][C]0.131181[/C][C]0.934409[/C][/ROW]
[ROW][C]103[/C][C]0.0549674[/C][C]0.109935[/C][C]0.945033[/C][/ROW]
[ROW][C]104[/C][C]0.0530805[/C][C]0.106161[/C][C]0.94692[/C][/ROW]
[ROW][C]105[/C][C]0.0967646[/C][C]0.193529[/C][C]0.903235[/C][/ROW]
[ROW][C]106[/C][C]0.0928262[/C][C]0.185652[/C][C]0.907174[/C][/ROW]
[ROW][C]107[/C][C]0.112463[/C][C]0.224927[/C][C]0.887537[/C][/ROW]
[ROW][C]108[/C][C]0.0999413[/C][C]0.199883[/C][C]0.900059[/C][/ROW]
[ROW][C]109[/C][C]0.1504[/C][C]0.300799[/C][C]0.8496[/C][/ROW]
[ROW][C]110[/C][C]0.172114[/C][C]0.344229[/C][C]0.827886[/C][/ROW]
[ROW][C]111[/C][C]0.167586[/C][C]0.335172[/C][C]0.832414[/C][/ROW]
[ROW][C]112[/C][C]0.205975[/C][C]0.411949[/C][C]0.794025[/C][/ROW]
[ROW][C]113[/C][C]0.19085[/C][C]0.381699[/C][C]0.80915[/C][/ROW]
[ROW][C]114[/C][C]0.177692[/C][C]0.355384[/C][C]0.822308[/C][/ROW]
[ROW][C]115[/C][C]0.172045[/C][C]0.344091[/C][C]0.827955[/C][/ROW]
[ROW][C]116[/C][C]0.173748[/C][C]0.347496[/C][C]0.826252[/C][/ROW]
[ROW][C]117[/C][C]0.169354[/C][C]0.338707[/C][C]0.830646[/C][/ROW]
[ROW][C]118[/C][C]0.153719[/C][C]0.307438[/C][C]0.846281[/C][/ROW]
[ROW][C]119[/C][C]0.14536[/C][C]0.29072[/C][C]0.85464[/C][/ROW]
[ROW][C]120[/C][C]0.133711[/C][C]0.267423[/C][C]0.866289[/C][/ROW]
[ROW][C]121[/C][C]0.118688[/C][C]0.237377[/C][C]0.881312[/C][/ROW]
[ROW][C]122[/C][C]0.104612[/C][C]0.209224[/C][C]0.895388[/C][/ROW]
[ROW][C]123[/C][C]0.0899517[/C][C]0.179903[/C][C]0.910048[/C][/ROW]
[ROW][C]124[/C][C]0.0844733[/C][C]0.168947[/C][C]0.915527[/C][/ROW]
[ROW][C]125[/C][C]0.0820587[/C][C]0.164117[/C][C]0.917941[/C][/ROW]
[ROW][C]126[/C][C]0.0983951[/C][C]0.19679[/C][C]0.901605[/C][/ROW]
[ROW][C]127[/C][C]0.178031[/C][C]0.356063[/C][C]0.821969[/C][/ROW]
[ROW][C]128[/C][C]0.174425[/C][C]0.34885[/C][C]0.825575[/C][/ROW]
[ROW][C]129[/C][C]0.154998[/C][C]0.309996[/C][C]0.845002[/C][/ROW]
[ROW][C]130[/C][C]0.140492[/C][C]0.280984[/C][C]0.859508[/C][/ROW]
[ROW][C]131[/C][C]0.164181[/C][C]0.328363[/C][C]0.835819[/C][/ROW]
[ROW][C]132[/C][C]0.179592[/C][C]0.359185[/C][C]0.820408[/C][/ROW]
[ROW][C]133[/C][C]0.222889[/C][C]0.445777[/C][C]0.777111[/C][/ROW]
[ROW][C]134[/C][C]0.19846[/C][C]0.39692[/C][C]0.80154[/C][/ROW]
[ROW][C]135[/C][C]0.176045[/C][C]0.352091[/C][C]0.823955[/C][/ROW]
[ROW][C]136[/C][C]0.155437[/C][C]0.310874[/C][C]0.844563[/C][/ROW]
[ROW][C]137[/C][C]0.136477[/C][C]0.272955[/C][C]0.863523[/C][/ROW]
[ROW][C]138[/C][C]0.152294[/C][C]0.304588[/C][C]0.847706[/C][/ROW]
[ROW][C]139[/C][C]0.132498[/C][C]0.264996[/C][C]0.867502[/C][/ROW]
[ROW][C]140[/C][C]0.135224[/C][C]0.270448[/C][C]0.864776[/C][/ROW]
[ROW][C]141[/C][C]0.125429[/C][C]0.250857[/C][C]0.874571[/C][/ROW]
[ROW][C]142[/C][C]0.165022[/C][C]0.330044[/C][C]0.834978[/C][/ROW]
[ROW][C]143[/C][C]0.199161[/C][C]0.398323[/C][C]0.800839[/C][/ROW]
[ROW][C]144[/C][C]0.180958[/C][C]0.361916[/C][C]0.819042[/C][/ROW]
[ROW][C]145[/C][C]0.254353[/C][C]0.508707[/C][C]0.745647[/C][/ROW]
[ROW][C]146[/C][C]0.229285[/C][C]0.458569[/C][C]0.770715[/C][/ROW]
[ROW][C]147[/C][C]0.205365[/C][C]0.410729[/C][C]0.794635[/C][/ROW]
[ROW][C]148[/C][C]0.183243[/C][C]0.366485[/C][C]0.816757[/C][/ROW]
[ROW][C]149[/C][C]0.166896[/C][C]0.333792[/C][C]0.833104[/C][/ROW]
[ROW][C]150[/C][C]0.147128[/C][C]0.294257[/C][C]0.852872[/C][/ROW]
[ROW][C]151[/C][C]0.223251[/C][C]0.446502[/C][C]0.776749[/C][/ROW]
[ROW][C]152[/C][C]0.20473[/C][C]0.409461[/C][C]0.79527[/C][/ROW]
[ROW][C]153[/C][C]0.185677[/C][C]0.371354[/C][C]0.814323[/C][/ROW]
[ROW][C]154[/C][C]0.20301[/C][C]0.406021[/C][C]0.79699[/C][/ROW]
[ROW][C]155[/C][C]0.181406[/C][C]0.362812[/C][C]0.818594[/C][/ROW]
[ROW][C]156[/C][C]0.198956[/C][C]0.397912[/C][C]0.801044[/C][/ROW]
[ROW][C]157[/C][C]0.189824[/C][C]0.379647[/C][C]0.810176[/C][/ROW]
[ROW][C]158[/C][C]0.175252[/C][C]0.350505[/C][C]0.824748[/C][/ROW]
[ROW][C]159[/C][C]0.167162[/C][C]0.334325[/C][C]0.832838[/C][/ROW]
[ROW][C]160[/C][C]0.157026[/C][C]0.314051[/C][C]0.842974[/C][/ROW]
[ROW][C]161[/C][C]0.136187[/C][C]0.272373[/C][C]0.863813[/C][/ROW]
[ROW][C]162[/C][C]0.127129[/C][C]0.254258[/C][C]0.872871[/C][/ROW]
[ROW][C]163[/C][C]0.116994[/C][C]0.233988[/C][C]0.883006[/C][/ROW]
[ROW][C]164[/C][C]0.151661[/C][C]0.303323[/C][C]0.848339[/C][/ROW]
[ROW][C]165[/C][C]0.137036[/C][C]0.274073[/C][C]0.862964[/C][/ROW]
[ROW][C]166[/C][C]0.217696[/C][C]0.435393[/C][C]0.782304[/C][/ROW]
[ROW][C]167[/C][C]0.21387[/C][C]0.42774[/C][C]0.78613[/C][/ROW]
[ROW][C]168[/C][C]0.203539[/C][C]0.407079[/C][C]0.796461[/C][/ROW]
[ROW][C]169[/C][C]0.182449[/C][C]0.364898[/C][C]0.817551[/C][/ROW]
[ROW][C]170[/C][C]0.277164[/C][C]0.554327[/C][C]0.722836[/C][/ROW]
[ROW][C]171[/C][C]0.323901[/C][C]0.647802[/C][C]0.676099[/C][/ROW]
[ROW][C]172[/C][C]0.293336[/C][C]0.586672[/C][C]0.706664[/C][/ROW]
[ROW][C]173[/C][C]0.404999[/C][C]0.809999[/C][C]0.595001[/C][/ROW]
[ROW][C]174[/C][C]0.370487[/C][C]0.740974[/C][C]0.629513[/C][/ROW]
[ROW][C]175[/C][C]0.446786[/C][C]0.893573[/C][C]0.553214[/C][/ROW]
[ROW][C]176[/C][C]0.418083[/C][C]0.836167[/C][C]0.581917[/C][/ROW]
[ROW][C]177[/C][C]0.422934[/C][C]0.845868[/C][C]0.577066[/C][/ROW]
[ROW][C]178[/C][C]0.389188[/C][C]0.778376[/C][C]0.610812[/C][/ROW]
[ROW][C]179[/C][C]0.357563[/C][C]0.715126[/C][C]0.642437[/C][/ROW]
[ROW][C]180[/C][C]0.356015[/C][C]0.712029[/C][C]0.643985[/C][/ROW]
[ROW][C]181[/C][C]0.324779[/C][C]0.649558[/C][C]0.675221[/C][/ROW]
[ROW][C]182[/C][C]0.318895[/C][C]0.637789[/C][C]0.681105[/C][/ROW]
[ROW][C]183[/C][C]0.335889[/C][C]0.671778[/C][C]0.664111[/C][/ROW]
[ROW][C]184[/C][C]0.406788[/C][C]0.813576[/C][C]0.593212[/C][/ROW]
[ROW][C]185[/C][C]0.615126[/C][C]0.769748[/C][C]0.384874[/C][/ROW]
[ROW][C]186[/C][C]0.5935[/C][C]0.813001[/C][C]0.4065[/C][/ROW]
[ROW][C]187[/C][C]0.580667[/C][C]0.838665[/C][C]0.419333[/C][/ROW]
[ROW][C]188[/C][C]0.728516[/C][C]0.542968[/C][C]0.271484[/C][/ROW]
[ROW][C]189[/C][C]0.704122[/C][C]0.591755[/C][C]0.295878[/C][/ROW]
[ROW][C]190[/C][C]0.712878[/C][C]0.574243[/C][C]0.287122[/C][/ROW]
[ROW][C]191[/C][C]0.679072[/C][C]0.641856[/C][C]0.320928[/C][/ROW]
[ROW][C]192[/C][C]0.648477[/C][C]0.703046[/C][C]0.351523[/C][/ROW]
[ROW][C]193[/C][C]0.61801[/C][C]0.763981[/C][C]0.38199[/C][/ROW]
[ROW][C]194[/C][C]0.594689[/C][C]0.810623[/C][C]0.405311[/C][/ROW]
[ROW][C]195[/C][C]0.554781[/C][C]0.890438[/C][C]0.445219[/C][/ROW]
[ROW][C]196[/C][C]0.516225[/C][C]0.967551[/C][C]0.483775[/C][/ROW]
[ROW][C]197[/C][C]0.496277[/C][C]0.992554[/C][C]0.503723[/C][/ROW]
[ROW][C]198[/C][C]0.468902[/C][C]0.937805[/C][C]0.531098[/C][/ROW]
[ROW][C]199[/C][C]0.427104[/C][C]0.854208[/C][C]0.572896[/C][/ROW]
[ROW][C]200[/C][C]0.493389[/C][C]0.986777[/C][C]0.506611[/C][/ROW]
[ROW][C]201[/C][C]0.463117[/C][C]0.926233[/C][C]0.536883[/C][/ROW]
[ROW][C]202[/C][C]0.603924[/C][C]0.792152[/C][C]0.396076[/C][/ROW]
[ROW][C]203[/C][C]0.599541[/C][C]0.800918[/C][C]0.400459[/C][/ROW]
[ROW][C]204[/C][C]0.559113[/C][C]0.881775[/C][C]0.440887[/C][/ROW]
[ROW][C]205[/C][C]0.515779[/C][C]0.968442[/C][C]0.484221[/C][/ROW]
[ROW][C]206[/C][C]0.475616[/C][C]0.951233[/C][C]0.524384[/C][/ROW]
[ROW][C]207[/C][C]0.441865[/C][C]0.88373[/C][C]0.558135[/C][/ROW]
[ROW][C]208[/C][C]0.401988[/C][C]0.803975[/C][C]0.598012[/C][/ROW]
[ROW][C]209[/C][C]0.378278[/C][C]0.756557[/C][C]0.621722[/C][/ROW]
[ROW][C]210[/C][C]0.343641[/C][C]0.687283[/C][C]0.656359[/C][/ROW]
[ROW][C]211[/C][C]0.303781[/C][C]0.607562[/C][C]0.696219[/C][/ROW]
[ROW][C]212[/C][C]0.270261[/C][C]0.540522[/C][C]0.729739[/C][/ROW]
[ROW][C]213[/C][C]0.325986[/C][C]0.651973[/C][C]0.674014[/C][/ROW]
[ROW][C]214[/C][C]0.31307[/C][C]0.62614[/C][C]0.68693[/C][/ROW]
[ROW][C]215[/C][C]0.274019[/C][C]0.548038[/C][C]0.725981[/C][/ROW]
[ROW][C]216[/C][C]0.237997[/C][C]0.475994[/C][C]0.762003[/C][/ROW]
[ROW][C]217[/C][C]0.212051[/C][C]0.424101[/C][C]0.787949[/C][/ROW]
[ROW][C]218[/C][C]0.237961[/C][C]0.475923[/C][C]0.762039[/C][/ROW]
[ROW][C]219[/C][C]0.211065[/C][C]0.42213[/C][C]0.788935[/C][/ROW]
[ROW][C]220[/C][C]0.192984[/C][C]0.385967[/C][C]0.807016[/C][/ROW]
[ROW][C]221[/C][C]0.167769[/C][C]0.335538[/C][C]0.832231[/C][/ROW]
[ROW][C]222[/C][C]0.183714[/C][C]0.367428[/C][C]0.816286[/C][/ROW]
[ROW][C]223[/C][C]0.151648[/C][C]0.303295[/C][C]0.848352[/C][/ROW]
[ROW][C]224[/C][C]0.128224[/C][C]0.256448[/C][C]0.871776[/C][/ROW]
[ROW][C]225[/C][C]0.204586[/C][C]0.409171[/C][C]0.795414[/C][/ROW]
[ROW][C]226[/C][C]0.181884[/C][C]0.363768[/C][C]0.818116[/C][/ROW]
[ROW][C]227[/C][C]0.157325[/C][C]0.314651[/C][C]0.842675[/C][/ROW]
[ROW][C]228[/C][C]0.169512[/C][C]0.339023[/C][C]0.830488[/C][/ROW]
[ROW][C]229[/C][C]0.137924[/C][C]0.275849[/C][C]0.862076[/C][/ROW]
[ROW][C]230[/C][C]0.109308[/C][C]0.218616[/C][C]0.890692[/C][/ROW]
[ROW][C]231[/C][C]0.103922[/C][C]0.207845[/C][C]0.896078[/C][/ROW]
[ROW][C]232[/C][C]0.200669[/C][C]0.401338[/C][C]0.799331[/C][/ROW]
[ROW][C]233[/C][C]0.177256[/C][C]0.354511[/C][C]0.822744[/C][/ROW]
[ROW][C]234[/C][C]0.248849[/C][C]0.497699[/C][C]0.751151[/C][/ROW]
[ROW][C]235[/C][C]0.207715[/C][C]0.41543[/C][C]0.792285[/C][/ROW]
[ROW][C]236[/C][C]0.234374[/C][C]0.468748[/C][C]0.765626[/C][/ROW]
[ROW][C]237[/C][C]0.211482[/C][C]0.422964[/C][C]0.788518[/C][/ROW]
[ROW][C]238[/C][C]0.304862[/C][C]0.609723[/C][C]0.695138[/C][/ROW]
[ROW][C]239[/C][C]0.251991[/C][C]0.503982[/C][C]0.748009[/C][/ROW]
[ROW][C]240[/C][C]0.435882[/C][C]0.871764[/C][C]0.564118[/C][/ROW]
[ROW][C]241[/C][C]0.498852[/C][C]0.997705[/C][C]0.501148[/C][/ROW]
[ROW][C]242[/C][C]0.423423[/C][C]0.846846[/C][C]0.576577[/C][/ROW]
[ROW][C]243[/C][C]0.353308[/C][C]0.706616[/C][C]0.646692[/C][/ROW]
[ROW][C]244[/C][C]0.305787[/C][C]0.611575[/C][C]0.694213[/C][/ROW]
[ROW][C]245[/C][C]0.306045[/C][C]0.61209[/C][C]0.693955[/C][/ROW]
[ROW][C]246[/C][C]0.511763[/C][C]0.976475[/C][C]0.488237[/C][/ROW]
[ROW][C]247[/C][C]0.552369[/C][C]0.895261[/C][C]0.447631[/C][/ROW]
[ROW][C]248[/C][C]0.52112[/C][C]0.95776[/C][C]0.47888[/C][/ROW]
[ROW][C]249[/C][C]0.702687[/C][C]0.594626[/C][C]0.297313[/C][/ROW]
[ROW][C]250[/C][C]0.702719[/C][C]0.594563[/C][C]0.297281[/C][/ROW]
[ROW][C]251[/C][C]0.679186[/C][C]0.641628[/C][C]0.320814[/C][/ROW]
[ROW][C]252[/C][C]0.697837[/C][C]0.604326[/C][C]0.302163[/C][/ROW]
[ROW][C]253[/C][C]0.531166[/C][C]0.937669[/C][C]0.468834[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225827&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225827&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
110.04710090.09420180.952899
120.7577240.4845530.242276
130.8487620.3024750.151238
140.7717740.4564510.228226
150.7421410.5157180.257859
160.7328790.5342420.267121
170.6848950.6302110.315105
180.6075520.7848960.392448
190.523320.953360.47668
200.5554550.8890890.444545
210.6092130.7815730.390787
220.5632490.8735020.436751
230.5363430.9273150.463657
240.4726850.9453690.527315
250.5407770.9184470.459223
260.7586480.4827040.241352
270.7124190.5751620.287581
280.6905120.6189750.309488
290.6654960.6690080.334504
300.6135370.7729260.386463
310.6204460.7591070.379554
320.8055610.3888790.194439
330.7846460.4307080.215354
340.7627430.4745150.237257
350.7171440.5657110.282856
360.7039320.5921360.296068
370.705630.5887390.29437
380.6613790.6772430.338621
390.7209860.5580280.279014
400.6753850.6492290.324615
410.6528190.6943610.347181
420.6051050.789790.394895
430.5776040.8447910.422396
440.5298840.9402310.470116
450.5827020.8345960.417298
460.5460190.9079620.453981
470.497420.9948390.50258
480.4689350.937870.531065
490.4204510.8409020.579549
500.4168450.833690.583155
510.4799330.9598650.520067
520.4429230.8858460.557077
530.4108490.8216990.589151
540.380840.761680.61916
550.3463590.6927170.653641
560.3412620.6825240.658738
570.3560970.7121930.643903
580.4780680.9561360.521932
590.4400510.8801020.559949
600.3980090.7960180.601991
610.3617750.7235510.638225
620.3492760.6985530.650724
630.3184760.6369510.681524
640.3327140.6654290.667286
650.2944150.5888310.705585
660.2589170.5178330.741083
670.2327270.4654540.767273
680.2175890.4351770.782411
690.2041010.4082010.795899
700.1767260.3534510.823274
710.1687810.3375620.831219
720.1980090.3960190.801991
730.1848070.3696140.815193
740.1604020.3208040.839598
750.1424860.2849720.857514
760.2069520.4139030.793048
770.1808590.3617170.819141
780.1558730.3117460.844127
790.2205990.4411980.779401
800.2509560.5019130.749044
810.2382240.4764490.761776
820.2118610.4237220.788139
830.2004870.4009730.799513
840.1924810.3849620.807519
850.1682130.3364250.831787
860.1528770.3057540.847123
870.1363190.2726380.863681
880.151850.30370.84815
890.130210.2604210.86979
900.1430930.2861850.856907
910.1346720.2693440.865328
920.12080.2415990.8792
930.1038970.2077930.896103
940.1135760.2271530.886424
950.1205020.2410040.879498
960.1128120.2256250.887188
970.099840.199680.90016
980.09105780.1821160.908942
990.09120510.182410.908795
1000.08419020.168380.91581
1010.07846570.1569310.921534
1020.06559070.1311810.934409
1030.05496740.1099350.945033
1040.05308050.1061610.94692
1050.09676460.1935290.903235
1060.09282620.1856520.907174
1070.1124630.2249270.887537
1080.09994130.1998830.900059
1090.15040.3007990.8496
1100.1721140.3442290.827886
1110.1675860.3351720.832414
1120.2059750.4119490.794025
1130.190850.3816990.80915
1140.1776920.3553840.822308
1150.1720450.3440910.827955
1160.1737480.3474960.826252
1170.1693540.3387070.830646
1180.1537190.3074380.846281
1190.145360.290720.85464
1200.1337110.2674230.866289
1210.1186880.2373770.881312
1220.1046120.2092240.895388
1230.08995170.1799030.910048
1240.08447330.1689470.915527
1250.08205870.1641170.917941
1260.09839510.196790.901605
1270.1780310.3560630.821969
1280.1744250.348850.825575
1290.1549980.3099960.845002
1300.1404920.2809840.859508
1310.1641810.3283630.835819
1320.1795920.3591850.820408
1330.2228890.4457770.777111
1340.198460.396920.80154
1350.1760450.3520910.823955
1360.1554370.3108740.844563
1370.1364770.2729550.863523
1380.1522940.3045880.847706
1390.1324980.2649960.867502
1400.1352240.2704480.864776
1410.1254290.2508570.874571
1420.1650220.3300440.834978
1430.1991610.3983230.800839
1440.1809580.3619160.819042
1450.2543530.5087070.745647
1460.2292850.4585690.770715
1470.2053650.4107290.794635
1480.1832430.3664850.816757
1490.1668960.3337920.833104
1500.1471280.2942570.852872
1510.2232510.4465020.776749
1520.204730.4094610.79527
1530.1856770.3713540.814323
1540.203010.4060210.79699
1550.1814060.3628120.818594
1560.1989560.3979120.801044
1570.1898240.3796470.810176
1580.1752520.3505050.824748
1590.1671620.3343250.832838
1600.1570260.3140510.842974
1610.1361870.2723730.863813
1620.1271290.2542580.872871
1630.1169940.2339880.883006
1640.1516610.3033230.848339
1650.1370360.2740730.862964
1660.2176960.4353930.782304
1670.213870.427740.78613
1680.2035390.4070790.796461
1690.1824490.3648980.817551
1700.2771640.5543270.722836
1710.3239010.6478020.676099
1720.2933360.5866720.706664
1730.4049990.8099990.595001
1740.3704870.7409740.629513
1750.4467860.8935730.553214
1760.4180830.8361670.581917
1770.4229340.8458680.577066
1780.3891880.7783760.610812
1790.3575630.7151260.642437
1800.3560150.7120290.643985
1810.3247790.6495580.675221
1820.3188950.6377890.681105
1830.3358890.6717780.664111
1840.4067880.8135760.593212
1850.6151260.7697480.384874
1860.59350.8130010.4065
1870.5806670.8386650.419333
1880.7285160.5429680.271484
1890.7041220.5917550.295878
1900.7128780.5742430.287122
1910.6790720.6418560.320928
1920.6484770.7030460.351523
1930.618010.7639810.38199
1940.5946890.8106230.405311
1950.5547810.8904380.445219
1960.5162250.9675510.483775
1970.4962770.9925540.503723
1980.4689020.9378050.531098
1990.4271040.8542080.572896
2000.4933890.9867770.506611
2010.4631170.9262330.536883
2020.6039240.7921520.396076
2030.5995410.8009180.400459
2040.5591130.8817750.440887
2050.5157790.9684420.484221
2060.4756160.9512330.524384
2070.4418650.883730.558135
2080.4019880.8039750.598012
2090.3782780.7565570.621722
2100.3436410.6872830.656359
2110.3037810.6075620.696219
2120.2702610.5405220.729739
2130.3259860.6519730.674014
2140.313070.626140.68693
2150.2740190.5480380.725981
2160.2379970.4759940.762003
2170.2120510.4241010.787949
2180.2379610.4759230.762039
2190.2110650.422130.788935
2200.1929840.3859670.807016
2210.1677690.3355380.832231
2220.1837140.3674280.816286
2230.1516480.3032950.848352
2240.1282240.2564480.871776
2250.2045860.4091710.795414
2260.1818840.3637680.818116
2270.1573250.3146510.842675
2280.1695120.3390230.830488
2290.1379240.2758490.862076
2300.1093080.2186160.890692
2310.1039220.2078450.896078
2320.2006690.4013380.799331
2330.1772560.3545110.822744
2340.2488490.4976990.751151
2350.2077150.415430.792285
2360.2343740.4687480.765626
2370.2114820.4229640.788518
2380.3048620.6097230.695138
2390.2519910.5039820.748009
2400.4358820.8717640.564118
2410.4988520.9977050.501148
2420.4234230.8468460.576577
2430.3533080.7066160.646692
2440.3057870.6115750.694213
2450.3060450.612090.693955
2460.5117630.9764750.488237
2470.5523690.8952610.447631
2480.521120.957760.47888
2490.7026870.5946260.297313
2500.7027190.5945630.297281
2510.6791860.6416280.320814
2520.6978370.6043260.302163
2530.5311660.9376690.468834






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 level10.00411523OK

\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 & 0.00411523 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225827&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]0.00411523[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225827&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225827&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 level10.00411523OK


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 = No Linear Trend ;
Parameters (R input):
par1 = 8 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}