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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 computationWed, 20 Nov 2013 08:51:48 -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/20/t1384955640kktc0gbiow68wk9.htm/, Retrieved Wed, 01 May 2024 15:55:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226612, Retrieved Wed, 01 May 2024 15:55:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact102

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [WS7: 1] [2013-11-20 13:51:48] [0af71617a8b1f082fed242286206dd2f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41 38 13 12 14 12 53 32
39 32 16 11 18 11 83 51
30 35 19 15 11 14 66 42
31 33 15 6 12 12 67 41
34 37 14 13 16 21 76 46
35 29 13 10 18 12 78 47
39 31 19 12 14 22 53 37
34 36 15 14 14 11 80 49
36 35 14 12 15 10 74 45
37 38 15 9 15 13 76 47
38 31 16 10 17 10 79 49
36 34 16 12 19 8 54 33
38 35 16 12 10 15 67 42
39 38 16 11 16 14 54 33
33 37 17 15 18 10 87 53
32 33 15 12 14 14 58 36
36 32 15 10 14 14 75 45
38 38 20 12 17 11 88 54
39 38 18 11 14 10 64 41
32 32 16 12 16 13 57 36
32 33 16 11 18 9.5 66 41
31 31 16 12 11 14 68 44
39 38 19 13 14 12 54 33
37 39 16 11 12 14 56 37
39 32 17 12 17 11 86 52
41 32 17 13 9 9 80 47
36 35 16 10 16 11 76 43
33 37 15 14 14 15 69 44
33 33 16 12 15 14 78 45
34 33 14 10 11 13 67 44
31 31 15 12 16 9 80 49
27 32 12 8 13 15 54 33
37 31 14 10 17 10 71 43
34 37 16 12 15 11 84 54
34 30 14 12 14 13 74 42
32 33 10 7 16 8 71 44
29 31 10 9 9 20 63 37
36 33 14 12 15 12 71 43
29 31 16 10 17 10 76 46
35 33 16 10 13 10 69 42
37 32 16 10 15 9 74 45
34 33 14 12 16 14 75 44
38 32 20 15 16 8 54 33
35 33 14 10 12 14 52 31
38 28 14 10 15 11 69 42
37 35 11 12 11 13 68 40
38 39 14 13 15 9 65 43
33 34 15 11 15 11 75 46
36 38 16 11 17 15 74 42
38 32 14 12 13 11 75 45
32 38 16 14 16 10 72 44
32 30 14 10 14 14 67 40
32 33 12 12 11 18 63 37
34 38 16 13 12 14 62 46
32 32 9 5 12 11 63 36
37 35 14 6 15 14.5 76 47
39 34 16 12 16 13 74 45
29 34 16 12 15 9 67 42
37 36 15 11 12 10 73 43
35 34 16 10 12 15 70 43
30 28 12 7 8 20 53 32
38 34 16 12 13 12 77 45
34 35 16 14 11 12 80 48
31 35 14 11 14 14 52 31
34 31 16 12 15 13 54 33
35 37 17 13 10 11 80 49
36 35 18 14 11 17 66 42
30 27 18 11 12 12 73 41
39 40 12 12 15 13 63 38
35 37 16 12 15 14 69 42
38 36 10 8 14 13 67 44
31 38 14 11 16 15 54 33
34 39 18 14 15 13 81 48
38 41 18 14 15 10 69 40
34 27 16 12 13 11 84 50
39 30 17 9 12 19 80 49
37 37 16 13 17 13 70 43
34 31 16 11 13 17 69 44
28 31 13 12 15 13 77 47
37 27 16 12 13 9 54 33
33 36 16 12 15 11 79 46
35 37 16 12 15 9 71 45
37 33 15 12 16 12 73 43
32 34 15 11 15 12 72 44
33 31 16 10 14 13 77 47
38 39 14 9 15 13 75 45
33 34 16 12 14 12 69 42
29 32 16 12 13 15 54 33
33 33 15 12 7 22 70 43
31 36 12 9 17 13 73 46
36 32 17 15 13 15 54 33
35 41 16 12 15 13 77 46
32 28 15 12 14 15 82 48
29 30 13 12 13 12.5 80 47
39 36 16 10 16 11 80 47
37 35 16 13 12 16 69 43
35 31 16 9 14 11 78 46
37 34 16 12 17 11 81 48
32 36 14 10 15 10 76 46
38 36 16 14 17 10 76 45
37 35 16 11 12 16 73 45
36 37 20 15 16 12 85 52
32 28 15 11 11 11 66 42
33 39 16 11 15 16 79 47
40 32 13 12 9 19 68 41
38 35 17 12 16 11 76 47
41 39 16 12 15 16 71 43
36 35 16 11 10 15 54 33
43 42 12 7 10 24 46 30
30 34 16 12 15 14 85 52
31 33 16 14 11 15 74 44
32 41 17 11 13 11 88 55
32 33 13 11 14 15 38 11
37 34 12 10 18 12 76 47
37 32 18 13 16 10 86 53
33 40 14 13 14 14 54 33
34 40 14 8 14 13 67 44
33 35 13 11 14 9 69 42
38 36 16 12 14 15 90 55
33 37 13 11 12 15 54 33
31 27 16 13 14 14 76 46
38 39 13 12 15 11 89 54
37 38 16 14 15 8 76 47
36 31 15 13 15 11 73 45
31 33 16 15 13 11 79 47
39 32 15 10 17 8 90 55
44 39 17 11 17 10 74 44
33 36 15 9 19 11 81 53
35 33 12 11 15 13 72 44
32 33 16 10 13 11 71 42
28 32 10 11 9 20 66 40
40 37 16 8 15 10 77 46
27 30 12 11 15 15 65 40
37 38 14 12 15 12 74 46
32 29 15 12 16 14 85 53
28 22 13 9 11 23 54 33
34 35 15 11 14 14 63 42
30 35 11 10 11 16 54 35
35 34 12 8 15 11 64 40
31 35 11 9 13 12 69 41
32 34 16 8 15 10 54 33
30 37 15 9 16 14 84 51
30 35 17 15 14 12 86 53
31 23 16 11 15 12 77 46
40 31 10 8 16 11 89 55
32 27 18 13 16 12 76 47
36 36 13 12 11 13 60 38
32 31 16 12 12 11 75 46
35 32 13 9 9 19 73 46
38 39 10 7 16 12 85 53
42 37 15 13 13 17 79 47
34 38 16 9 16 9 71 41
35 39 16 6 12 12 72 44
38 34 14 8 9 19 69 43
33 31 10 8 13 18 78 51
36 32 17 15 13 15 54 33
32 37 13 6 14 14 69 43
33 36 15 9 19 11 81 53
34 32 16 11 13 9 84 51
32 38 12 8 12 18 84 50
34 36 13 8 13 16 69 46
27 26 13 10 10 24 66 43
31 26 12 8 14 14 81 47
38 33 17 14 16 20 82 50
34 39 15 10 10 18 72 43
24 30 10 8 11 23 54 33
30 33 14 11 14 12 78 48
26 25 11 12 12 14 74 44
34 38 13 12 9 16 82 50
27 37 16 12 9 18 73 41
37 31 12 5 11 20 55 34
36 37 16 12 16 12 72 44
41 35 12 10 9 12 78 47
29 25 9 7 13 17 59 35
36 28 12 12 16 13 72 44
32 35 15 11 13 9 78 44
37 33 12 8 9 16 68 43
30 30 12 9 12 18 69 41
31 31 14 10 16 10 67 41
38 37 12 9 11 14 74 42
36 36 16 12 14 11 54 33
35 30 11 6 13 9 67 41
31 36 19 15 15 11 70 44
38 32 15 12 14 10 80 48
22 28 8 12 16 11 89 55
32 36 16 12 13 19 76 44
36 34 17 11 14 14 74 43
39 31 12 7 15 12 87 52
28 28 11 7 13 14 54 30
32 36 11 5 11 21 61 39
32 36 14 12 11 13 38 11
38 40 16 12 14 10 75 44
32 33 12 3 15 15 69 42
35 37 16 11 11 16 62 41
32 32 13 10 15 14 72 44
37 38 15 12 12 12 70 44
34 31 16 9 14 19 79 48
33 37 16 12 14 15 87 53
33 33 14 9 8 19 62 37
26 32 16 12 13 13 77 44
30 30 16 12 9 17 69 44
24 30 14 10 15 12 69 40
34 31 11 9 17 11 75 42
34 32 12 12 13 14 54 35
33 34 15 8 15 11 72 43
34 36 15 11 15 13 74 45
35 37 16 11 14 12 85 55
35 36 16 12 16 15 52 31
36 33 11 10 13 14 70 44
34 33 15 10 16 12 84 50
34 33 12 12 9 17 64 40
41 44 12 12 16 11 84 53
32 39 15 11 11 18 87 54
30 32 15 8 10 13 79 49
35 35 16 12 11 17 67 40
28 25 14 10 15 13 65 41
33 35 17 11 17 11 85 52
39 34 14 10 14 12 83 52
36 35 13 8 8 22 61 36
36 39 15 12 15 14 82 52
35 33 13 12 11 12 76 46
38 36 14 10 16 12 58 31
33 32 15 12 10 17 72 44
31 32 12 9 15 9 72 44
34 36 13 9 9 21 38 11
32 36 8 6 16 10 78 46
31 32 14 10 19 11 54 33
33 34 14 9 12 12 63 34
34 33 11 9 8 23 66 42
34 35 12 9 11 13 70 43
34 30 13 6 14 12 71 43
33 38 10 10 9 16 67 44
32 34 16 6 15 9 58 36
41 33 18 14 13 17 72 46
34 32 13 10 16 9 72 44
36 31 11 10 11 14 70 43
37 30 4 6 12 17 76 50
36 27 13 12 13 13 50 33
29 31 16 12 10 11 72 43
37 30 10 7 11 12 72 44
27 32 12 8 12 10 88 53
35 35 12 11 8 19 53 34
28 28 10 3 12 16 58 35
35 33 13 6 12 16 66 40
37 31 15 10 15 14 82 53
29 35 12 8 11 20 69 42
32 35 14 9 13 15 68 43
36 32 10 9 14 23 44 29
19 21 12 8 10 20 56 36
21 20 12 9 12 16 53 30
31 34 11 7 15 14 70 42
33 32 10 7 13 17 78 47
36 34 12 6 13 11 71 44
33 32 16 9 13 13 72 45
37 33 12 10 12 17 68 44
34 33 14 11 12 15 67 43
35 37 16 12 9 21 75 43
31 32 14 8 9 18 62 40
37 34 13 11 15 15 67 41
35 30 4 3 10 8 83 52
27 30 15 11 14 12 64 38
34 38 11 12 15 12 68 41
40 36 11 7 7 22 62 39
29 32 14 9 14 12 72 43

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time19 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 & 19 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226612&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]19 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=226612&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226612&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 time19 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Depression[t] = + 29.9486 -0.040303Connected[t] + 0.00601675Separate[t] -0.0846506Learning[t] -0.0234887Software[t] -0.706983Happiness[t] -0.146226Sport1[t] + 0.142997Sport2[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Depression[t] =  +  29.9486 -0.040303Connected[t] +  0.00601675Separate[t] -0.0846506Learning[t] -0.0234887Software[t] -0.706983Happiness[t] -0.146226Sport1[t] +  0.142997Sport2[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226612&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Depression[t] =  +  29.9486 -0.040303Connected[t] +  0.00601675Separate[t] -0.0846506Learning[t] -0.0234887Software[t] -0.706983Happiness[t] -0.146226Sport1[t] +  0.142997Sport2[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226612&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226612&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
Depression[t] = + 29.9486 -0.040303Connected[t] + 0.00601675Separate[t] -0.0846506Learning[t] -0.0234887Software[t] -0.706983Happiness[t] -0.146226Sport1[t] + 0.142997Sport2[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)29.94862.1263614.089.5778e-344.7889e-34
Connected-0.0403030.0511228-0.78840.4312180.215609
Separate0.006016750.05240660.11480.9086870.454343
Learning-0.08465060.0914823-0.92530.355670.177835
Software-0.02348870.0942012-0.24930.8032930.401647
Happiness-0.7069830.0731529-9.6644.88043e-192.44021e-19
Sport1-0.1462260.0547451-2.6710.008046610.0040233
Sport20.1429970.08229151.7380.08346790.041734

\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) & 29.9486 & 2.12636 & 14.08 & 9.5778e-34 & 4.7889e-34 \tabularnewline
Connected & -0.040303 & 0.0511228 & -0.7884 & 0.431218 & 0.215609 \tabularnewline
Separate & 0.00601675 & 0.0524066 & 0.1148 & 0.908687 & 0.454343 \tabularnewline
Learning & -0.0846506 & 0.0914823 & -0.9253 & 0.35567 & 0.177835 \tabularnewline
Software & -0.0234887 & 0.0942012 & -0.2493 & 0.803293 & 0.401647 \tabularnewline
Happiness & -0.706983 & 0.0731529 & -9.664 & 4.88043e-19 & 2.44021e-19 \tabularnewline
Sport1 & -0.146226 & 0.0547451 & -2.671 & 0.00804661 & 0.0040233 \tabularnewline
Sport2 & 0.142997 & 0.0822915 & 1.738 & 0.0834679 & 0.041734 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226612&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]29.9486[/C][C]2.12636[/C][C]14.08[/C][C]9.5778e-34[/C][C]4.7889e-34[/C][/ROW]
[ROW][C]Connected[/C][C]-0.040303[/C][C]0.0511228[/C][C]-0.7884[/C][C]0.431218[/C][C]0.215609[/C][/ROW]
[ROW][C]Separate[/C][C]0.00601675[/C][C]0.0524066[/C][C]0.1148[/C][C]0.908687[/C][C]0.454343[/C][/ROW]
[ROW][C]Learning[/C][C]-0.0846506[/C][C]0.0914823[/C][C]-0.9253[/C][C]0.35567[/C][C]0.177835[/C][/ROW]
[ROW][C]Software[/C][C]-0.0234887[/C][C]0.0942012[/C][C]-0.2493[/C][C]0.803293[/C][C]0.401647[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.706983[/C][C]0.0731529[/C][C]-9.664[/C][C]4.88043e-19[/C][C]2.44021e-19[/C][/ROW]
[ROW][C]Sport1[/C][C]-0.146226[/C][C]0.0547451[/C][C]-2.671[/C][C]0.00804661[/C][C]0.0040233[/C][/ROW]
[ROW][C]Sport2[/C][C]0.142997[/C][C]0.0822915[/C][C]1.738[/C][C]0.0834679[/C][C]0.041734[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226612&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226612&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)29.94862.1263614.089.5778e-344.7889e-34
Connected-0.0403030.0511228-0.78840.4312180.215609
Separate0.006016750.05240660.11480.9086870.454343
Learning-0.08465060.0914823-0.92530.355670.177835
Software-0.02348870.0942012-0.24930.8032930.401647
Happiness-0.7069830.0731529-9.6644.88043e-192.44021e-19
Sport1-0.1462260.0547451-2.6710.008046610.0040233
Sport20.1429970.08229151.7380.08346790.041734






Multiple Linear Regression - Regression Statistics
Multiple R0.618653
R-squared0.382731
Adjusted R-squared0.365853
F-TEST (value)22.6757
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.76293
Sum Squared Residuals1954.24

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.618653 \tabularnewline
R-squared & 0.382731 \tabularnewline
Adjusted R-squared & 0.365853 \tabularnewline
F-TEST (value) & 22.6757 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 256 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.76293 \tabularnewline
Sum Squared Residuals & 1954.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226612&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.618653[/C][/ROW]
[ROW][C]R-squared[/C][C]0.382731[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.365853[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]22.6757[/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]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.76293[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1954.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226612&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226612&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 R0.618653
R-squared0.382731
Adjusted R-squared0.365853
F-TEST (value)22.6757
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.76293
Sum Squared Residuals1954.24






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11214.0707-2.07068
2119.386971.61303
31415.5676-1.56758
41215.069-3.06904
52111.46349.53655
6129.966712.03329
72214.31627.68375
81112.6073-1.60735
91012.2507-2.25074
101312.20780.792159
111010.4506-0.450633
12810.456-2.45603
131516.1303-1.13033
141412.50361.49637
15109.181350.818645
161414.0749-0.0748812
171412.75581.24423
18119.506131.49387
191013.43-3.43001
201312.71650.283528
219.510.731-1.23097
221415.8212-1.82117
231213.6167-1.61666
241415.6977-1.69772
25119.690131.30987
26915.4043-6.40427
271110.8430.157017
281513.54721.45284
291411.60542.39459
301316.0748-3.0748
31911.3312-2.33118
321515.4812-0.48118
331010.9721-0.972058
341111.9988-0.998793
351312.57920.42075
36812.4447-4.44466
372017.62432.37574
381212.3914-0.391384
391010.823-0.823044
401013.8728-3.87278
41912.0701-3.07006
421411.32312.6769
43812.0753-4.07527
441415.6619-1.66193
451112.4771-1.47713
461315.4547-2.45469
47913.2007-4.20074
481112.3012-1.30124
491510.284.71999
501113.4198-2.41982
511011.6562-1.65619
521413.44440.555582
531815.86172.13835
541416.1753-2.17526
551115.424-4.42403
5614.512.34492.15509
571311.24751.75247
58912.9521-3.95213
591014.1365-4.13647
601514.58260.417444
612018.89781.10216
621212.9701-0.970102
631214.4946-2.49463
641414.3977-0.397724
651313.3465-0.346518
661115.2552-4.25518
671715.43391.5661
681213.8245-1.82449
691312.93670.0632873
701412.43591.56409
711314.1963-1.19627
721512.99542.00465
731311.37521.62476
741011.8368-1.83679
751112.7806-1.7806
761913.73185.26816
771310.91462.08538
781714.16362.83644
791312.48110.51894
80914.6155-5.61551
811111.6202-0.620229
82912.5724-3.57245
831211.2670.733004
841212.4942-0.494223
851312.77960.220445
861312.11840.881563
871213.2054-1.20545
881514.9680.0319831
892218.22973.77026
901311.57331.42671
911514.53080.46922
921311.86221.13784
931512.25142.74865
9412.513.41-0.910031
951110.71520.284823
961614.58371.41627
971112.4332-1.43321
981110.02660.97344
991012.3155-2.31549
1001010.2534-0.25345
1011614.33181.6682
1021210.36991.63009
1031115.8774-4.87742
1041611.80484.19523
1051916.70342.29661
1061111.2027-0.202738
1071612.05673.94333
1081516.8484-1.84839
1092417.78186.21825
1101411.70972.29027
1111514.90890.091125
1121113.0144-2.01437
1131513.61731.38275
1141210.29331.70671
1151010.5126-0.512578
1161414.2938-0.293768
1171314.0429-1.04295
118913.4889-4.4889
1191511.80423.19581
1201515.8213-0.821313
1211412.76891.23114
1221111.3724-0.372438
123812.0057-4.00575
1241112.2648-1.26475
1251113.1693-2.16928
12689.7505-1.7505
1271010.165-0.164952
128119.655941.34406
1291312.62120.378751
1301113.7012-2.70124
1312017.61392.38608
1321011.7305-1.73053
1331513.37721.62279
1341212.3715-0.37148
1351411.11972.88029
1362316.68656.31346
1371414.1567-0.156653
1381617.116-1.11596
1391113.2955-2.29555
1401214.3498-2.34977
1411013.5391-3.53913
1421411.17912.82085
1431212.2644-0.26439
1441211.93860.0614428
1451111.0276-0.0276187
1461211.28830.711718
1471316.2155-3.21551
1481114.3363-3.3363
1491916.95922.04077
1501211.47880.521245
1511712.88164.11835
152911.4103-2.41026
1531214.5571-2.55714
1541916.94512.0549
1551814.46723.53282
1561514.53080.46922
1571413.80170.19832
158119.655941.34406
159912.9772-3.97717
1601814.06693.93307
1611614.80411.19594
1622417.10976.89033
1631412.63081.36925
1642010.69549.30464
1651815.85912.14089
1662317.17335.82668
1671213.0551-1.05508
1681414.8255-0.825503
1691616.2211-0.221125
1701816.27231.72767
1712016.55333.44666
1721211.53590.464062
1731216.2085-4.20849
1741715.19081.80924
1751311.82041.17961
176913.0369-4.03685
1771617.2949-1.29491
1781814.98233.01767
1791012.2198-2.21977
1801414.8209-0.820873
1811114.003-3.00298
182914.5214-5.5214
1831112.4065-1.40645
1841012.3261-2.32605
1851111.8104-0.810368
1861913.22725.77282
1871412.43521.56476
1881211.49260.507448
1891415.096-1.09596
1902116.70724.29278
1911315.6481-2.64811
1921012.4487-2.44867
1931513.08271.91725
1941616.1679-0.167911
1951412.6751.32502
1961214.7067-2.70669
1971912.61336.38671
1981512.16442.83559
1991917.98971.01031
2001313.2987-0.298707
2011717.1232-0.1232
2021212.7674-0.767407
2031110.64250.357492
2041415.3911-1.3911
2051112.3814-1.38139
2061312.27620.723804
2071212.6857-0.685733
2081512.63582.36423
2091414.3955-0.395503
2101210.82741.17262
2111717.4778-0.47778
2121111.2474-0.247411
2131814.58883.41117
2141315.8596-2.85959
2151715.25831.74174
2161313.304-0.30401
2171110.11970.880287
2181212.5627-0.562721
2192217.99224.00782
2201412.02131.97867
2211215.0421-3.04214
2221211.85380.146211
2231715.95331.04669
224912.8234-3.82342
2252117.13663.86341
2261011.9179-1.91791
2271110.86180.138211
2281214.5926-2.59256
2292318.33344.66658
2301315.698-2.69795
2311213.3865-1.38651
2321617.8978-1.89776
233913.4302-4.4302
2341713.5013.49898
235911.8874-2.88739
2361415.6544-1.65444
2371715.71131.28873
2381315.4947-2.49467
2391115.8809-4.88086
2401215.6138-3.61378
2411014.0764-4.07644
2421918.93050.0695193
2431616.1116-0.11163
2441615.08040.919643
2451412.12291.87713
2462015.92624.07382
2471514.48770.512261
2482315.44757.55245
2492017.99492.00509
2501616.0515-0.0515255
2511412.97351.02646
2521713.92473.0753
2531114.2646-3.2646
2541313.9612-0.961177
2551715.271.73002
2561515.2013-0.201332
2572115.94355.05655
2581817.80980.190224
2591512.76412.23585
260816.5387-8.53873
2611213.6905-1.69048
2621212.9087-0.908708
2632219.01952.98047
2641213.2987-1.29871

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 14.0707 & -2.07068 \tabularnewline
2 & 11 & 9.38697 & 1.61303 \tabularnewline
3 & 14 & 15.5676 & -1.56758 \tabularnewline
4 & 12 & 15.069 & -3.06904 \tabularnewline
5 & 21 & 11.4634 & 9.53655 \tabularnewline
6 & 12 & 9.96671 & 2.03329 \tabularnewline
7 & 22 & 14.3162 & 7.68375 \tabularnewline
8 & 11 & 12.6073 & -1.60735 \tabularnewline
9 & 10 & 12.2507 & -2.25074 \tabularnewline
10 & 13 & 12.2078 & 0.792159 \tabularnewline
11 & 10 & 10.4506 & -0.450633 \tabularnewline
12 & 8 & 10.456 & -2.45603 \tabularnewline
13 & 15 & 16.1303 & -1.13033 \tabularnewline
14 & 14 & 12.5036 & 1.49637 \tabularnewline
15 & 10 & 9.18135 & 0.818645 \tabularnewline
16 & 14 & 14.0749 & -0.0748812 \tabularnewline
17 & 14 & 12.7558 & 1.24423 \tabularnewline
18 & 11 & 9.50613 & 1.49387 \tabularnewline
19 & 10 & 13.43 & -3.43001 \tabularnewline
20 & 13 & 12.7165 & 0.283528 \tabularnewline
21 & 9.5 & 10.731 & -1.23097 \tabularnewline
22 & 14 & 15.8212 & -1.82117 \tabularnewline
23 & 12 & 13.6167 & -1.61666 \tabularnewline
24 & 14 & 15.6977 & -1.69772 \tabularnewline
25 & 11 & 9.69013 & 1.30987 \tabularnewline
26 & 9 & 15.4043 & -6.40427 \tabularnewline
27 & 11 & 10.843 & 0.157017 \tabularnewline
28 & 15 & 13.5472 & 1.45284 \tabularnewline
29 & 14 & 11.6054 & 2.39459 \tabularnewline
30 & 13 & 16.0748 & -3.0748 \tabularnewline
31 & 9 & 11.3312 & -2.33118 \tabularnewline
32 & 15 & 15.4812 & -0.48118 \tabularnewline
33 & 10 & 10.9721 & -0.972058 \tabularnewline
34 & 11 & 11.9988 & -0.998793 \tabularnewline
35 & 13 & 12.5792 & 0.42075 \tabularnewline
36 & 8 & 12.4447 & -4.44466 \tabularnewline
37 & 20 & 17.6243 & 2.37574 \tabularnewline
38 & 12 & 12.3914 & -0.391384 \tabularnewline
39 & 10 & 10.823 & -0.823044 \tabularnewline
40 & 10 & 13.8728 & -3.87278 \tabularnewline
41 & 9 & 12.0701 & -3.07006 \tabularnewline
42 & 14 & 11.3231 & 2.6769 \tabularnewline
43 & 8 & 12.0753 & -4.07527 \tabularnewline
44 & 14 & 15.6619 & -1.66193 \tabularnewline
45 & 11 & 12.4771 & -1.47713 \tabularnewline
46 & 13 & 15.4547 & -2.45469 \tabularnewline
47 & 9 & 13.2007 & -4.20074 \tabularnewline
48 & 11 & 12.3012 & -1.30124 \tabularnewline
49 & 15 & 10.28 & 4.71999 \tabularnewline
50 & 11 & 13.4198 & -2.41982 \tabularnewline
51 & 10 & 11.6562 & -1.65619 \tabularnewline
52 & 14 & 13.4444 & 0.555582 \tabularnewline
53 & 18 & 15.8617 & 2.13835 \tabularnewline
54 & 14 & 16.1753 & -2.17526 \tabularnewline
55 & 11 & 15.424 & -4.42403 \tabularnewline
56 & 14.5 & 12.3449 & 2.15509 \tabularnewline
57 & 13 & 11.2475 & 1.75247 \tabularnewline
58 & 9 & 12.9521 & -3.95213 \tabularnewline
59 & 10 & 14.1365 & -4.13647 \tabularnewline
60 & 15 & 14.5826 & 0.417444 \tabularnewline
61 & 20 & 18.8978 & 1.10216 \tabularnewline
62 & 12 & 12.9701 & -0.970102 \tabularnewline
63 & 12 & 14.4946 & -2.49463 \tabularnewline
64 & 14 & 14.3977 & -0.397724 \tabularnewline
65 & 13 & 13.3465 & -0.346518 \tabularnewline
66 & 11 & 15.2552 & -4.25518 \tabularnewline
67 & 17 & 15.4339 & 1.5661 \tabularnewline
68 & 12 & 13.8245 & -1.82449 \tabularnewline
69 & 13 & 12.9367 & 0.0632873 \tabularnewline
70 & 14 & 12.4359 & 1.56409 \tabularnewline
71 & 13 & 14.1963 & -1.19627 \tabularnewline
72 & 15 & 12.9954 & 2.00465 \tabularnewline
73 & 13 & 11.3752 & 1.62476 \tabularnewline
74 & 10 & 11.8368 & -1.83679 \tabularnewline
75 & 11 & 12.7806 & -1.7806 \tabularnewline
76 & 19 & 13.7318 & 5.26816 \tabularnewline
77 & 13 & 10.9146 & 2.08538 \tabularnewline
78 & 17 & 14.1636 & 2.83644 \tabularnewline
79 & 13 & 12.4811 & 0.51894 \tabularnewline
80 & 9 & 14.6155 & -5.61551 \tabularnewline
81 & 11 & 11.6202 & -0.620229 \tabularnewline
82 & 9 & 12.5724 & -3.57245 \tabularnewline
83 & 12 & 11.267 & 0.733004 \tabularnewline
84 & 12 & 12.4942 & -0.494223 \tabularnewline
85 & 13 & 12.7796 & 0.220445 \tabularnewline
86 & 13 & 12.1184 & 0.881563 \tabularnewline
87 & 12 & 13.2054 & -1.20545 \tabularnewline
88 & 15 & 14.968 & 0.0319831 \tabularnewline
89 & 22 & 18.2297 & 3.77026 \tabularnewline
90 & 13 & 11.5733 & 1.42671 \tabularnewline
91 & 15 & 14.5308 & 0.46922 \tabularnewline
92 & 13 & 11.8622 & 1.13784 \tabularnewline
93 & 15 & 12.2514 & 2.74865 \tabularnewline
94 & 12.5 & 13.41 & -0.910031 \tabularnewline
95 & 11 & 10.7152 & 0.284823 \tabularnewline
96 & 16 & 14.5837 & 1.41627 \tabularnewline
97 & 11 & 12.4332 & -1.43321 \tabularnewline
98 & 11 & 10.0266 & 0.97344 \tabularnewline
99 & 10 & 12.3155 & -2.31549 \tabularnewline
100 & 10 & 10.2534 & -0.25345 \tabularnewline
101 & 16 & 14.3318 & 1.6682 \tabularnewline
102 & 12 & 10.3699 & 1.63009 \tabularnewline
103 & 11 & 15.8774 & -4.87742 \tabularnewline
104 & 16 & 11.8048 & 4.19523 \tabularnewline
105 & 19 & 16.7034 & 2.29661 \tabularnewline
106 & 11 & 11.2027 & -0.202738 \tabularnewline
107 & 16 & 12.0567 & 3.94333 \tabularnewline
108 & 15 & 16.8484 & -1.84839 \tabularnewline
109 & 24 & 17.7818 & 6.21825 \tabularnewline
110 & 14 & 11.7097 & 2.29027 \tabularnewline
111 & 15 & 14.9089 & 0.091125 \tabularnewline
112 & 11 & 13.0144 & -2.01437 \tabularnewline
113 & 15 & 13.6173 & 1.38275 \tabularnewline
114 & 12 & 10.2933 & 1.70671 \tabularnewline
115 & 10 & 10.5126 & -0.512578 \tabularnewline
116 & 14 & 14.2938 & -0.293768 \tabularnewline
117 & 13 & 14.0429 & -1.04295 \tabularnewline
118 & 9 & 13.4889 & -4.4889 \tabularnewline
119 & 15 & 11.8042 & 3.19581 \tabularnewline
120 & 15 & 15.8213 & -0.821313 \tabularnewline
121 & 14 & 12.7689 & 1.23114 \tabularnewline
122 & 11 & 11.3724 & -0.372438 \tabularnewline
123 & 8 & 12.0057 & -4.00575 \tabularnewline
124 & 11 & 12.2648 & -1.26475 \tabularnewline
125 & 11 & 13.1693 & -2.16928 \tabularnewline
126 & 8 & 9.7505 & -1.7505 \tabularnewline
127 & 10 & 10.165 & -0.164952 \tabularnewline
128 & 11 & 9.65594 & 1.34406 \tabularnewline
129 & 13 & 12.6212 & 0.378751 \tabularnewline
130 & 11 & 13.7012 & -2.70124 \tabularnewline
131 & 20 & 17.6139 & 2.38608 \tabularnewline
132 & 10 & 11.7305 & -1.73053 \tabularnewline
133 & 15 & 13.3772 & 1.62279 \tabularnewline
134 & 12 & 12.3715 & -0.37148 \tabularnewline
135 & 14 & 11.1197 & 2.88029 \tabularnewline
136 & 23 & 16.6865 & 6.31346 \tabularnewline
137 & 14 & 14.1567 & -0.156653 \tabularnewline
138 & 16 & 17.116 & -1.11596 \tabularnewline
139 & 11 & 13.2955 & -2.29555 \tabularnewline
140 & 12 & 14.3498 & -2.34977 \tabularnewline
141 & 10 & 13.5391 & -3.53913 \tabularnewline
142 & 14 & 11.1791 & 2.82085 \tabularnewline
143 & 12 & 12.2644 & -0.26439 \tabularnewline
144 & 12 & 11.9386 & 0.0614428 \tabularnewline
145 & 11 & 11.0276 & -0.0276187 \tabularnewline
146 & 12 & 11.2883 & 0.711718 \tabularnewline
147 & 13 & 16.2155 & -3.21551 \tabularnewline
148 & 11 & 14.3363 & -3.3363 \tabularnewline
149 & 19 & 16.9592 & 2.04077 \tabularnewline
150 & 12 & 11.4788 & 0.521245 \tabularnewline
151 & 17 & 12.8816 & 4.11835 \tabularnewline
152 & 9 & 11.4103 & -2.41026 \tabularnewline
153 & 12 & 14.5571 & -2.55714 \tabularnewline
154 & 19 & 16.9451 & 2.0549 \tabularnewline
155 & 18 & 14.4672 & 3.53282 \tabularnewline
156 & 15 & 14.5308 & 0.46922 \tabularnewline
157 & 14 & 13.8017 & 0.19832 \tabularnewline
158 & 11 & 9.65594 & 1.34406 \tabularnewline
159 & 9 & 12.9772 & -3.97717 \tabularnewline
160 & 18 & 14.0669 & 3.93307 \tabularnewline
161 & 16 & 14.8041 & 1.19594 \tabularnewline
162 & 24 & 17.1097 & 6.89033 \tabularnewline
163 & 14 & 12.6308 & 1.36925 \tabularnewline
164 & 20 & 10.6954 & 9.30464 \tabularnewline
165 & 18 & 15.8591 & 2.14089 \tabularnewline
166 & 23 & 17.1733 & 5.82668 \tabularnewline
167 & 12 & 13.0551 & -1.05508 \tabularnewline
168 & 14 & 14.8255 & -0.825503 \tabularnewline
169 & 16 & 16.2211 & -0.221125 \tabularnewline
170 & 18 & 16.2723 & 1.72767 \tabularnewline
171 & 20 & 16.5533 & 3.44666 \tabularnewline
172 & 12 & 11.5359 & 0.464062 \tabularnewline
173 & 12 & 16.2085 & -4.20849 \tabularnewline
174 & 17 & 15.1908 & 1.80924 \tabularnewline
175 & 13 & 11.8204 & 1.17961 \tabularnewline
176 & 9 & 13.0369 & -4.03685 \tabularnewline
177 & 16 & 17.2949 & -1.29491 \tabularnewline
178 & 18 & 14.9823 & 3.01767 \tabularnewline
179 & 10 & 12.2198 & -2.21977 \tabularnewline
180 & 14 & 14.8209 & -0.820873 \tabularnewline
181 & 11 & 14.003 & -3.00298 \tabularnewline
182 & 9 & 14.5214 & -5.5214 \tabularnewline
183 & 11 & 12.4065 & -1.40645 \tabularnewline
184 & 10 & 12.3261 & -2.32605 \tabularnewline
185 & 11 & 11.8104 & -0.810368 \tabularnewline
186 & 19 & 13.2272 & 5.77282 \tabularnewline
187 & 14 & 12.4352 & 1.56476 \tabularnewline
188 & 12 & 11.4926 & 0.507448 \tabularnewline
189 & 14 & 15.096 & -1.09596 \tabularnewline
190 & 21 & 16.7072 & 4.29278 \tabularnewline
191 & 13 & 15.6481 & -2.64811 \tabularnewline
192 & 10 & 12.4487 & -2.44867 \tabularnewline
193 & 15 & 13.0827 & 1.91725 \tabularnewline
194 & 16 & 16.1679 & -0.167911 \tabularnewline
195 & 14 & 12.675 & 1.32502 \tabularnewline
196 & 12 & 14.7067 & -2.70669 \tabularnewline
197 & 19 & 12.6133 & 6.38671 \tabularnewline
198 & 15 & 12.1644 & 2.83559 \tabularnewline
199 & 19 & 17.9897 & 1.01031 \tabularnewline
200 & 13 & 13.2987 & -0.298707 \tabularnewline
201 & 17 & 17.1232 & -0.1232 \tabularnewline
202 & 12 & 12.7674 & -0.767407 \tabularnewline
203 & 11 & 10.6425 & 0.357492 \tabularnewline
204 & 14 & 15.3911 & -1.3911 \tabularnewline
205 & 11 & 12.3814 & -1.38139 \tabularnewline
206 & 13 & 12.2762 & 0.723804 \tabularnewline
207 & 12 & 12.6857 & -0.685733 \tabularnewline
208 & 15 & 12.6358 & 2.36423 \tabularnewline
209 & 14 & 14.3955 & -0.395503 \tabularnewline
210 & 12 & 10.8274 & 1.17262 \tabularnewline
211 & 17 & 17.4778 & -0.47778 \tabularnewline
212 & 11 & 11.2474 & -0.247411 \tabularnewline
213 & 18 & 14.5888 & 3.41117 \tabularnewline
214 & 13 & 15.8596 & -2.85959 \tabularnewline
215 & 17 & 15.2583 & 1.74174 \tabularnewline
216 & 13 & 13.304 & -0.30401 \tabularnewline
217 & 11 & 10.1197 & 0.880287 \tabularnewline
218 & 12 & 12.5627 & -0.562721 \tabularnewline
219 & 22 & 17.9922 & 4.00782 \tabularnewline
220 & 14 & 12.0213 & 1.97867 \tabularnewline
221 & 12 & 15.0421 & -3.04214 \tabularnewline
222 & 12 & 11.8538 & 0.146211 \tabularnewline
223 & 17 & 15.9533 & 1.04669 \tabularnewline
224 & 9 & 12.8234 & -3.82342 \tabularnewline
225 & 21 & 17.1366 & 3.86341 \tabularnewline
226 & 10 & 11.9179 & -1.91791 \tabularnewline
227 & 11 & 10.8618 & 0.138211 \tabularnewline
228 & 12 & 14.5926 & -2.59256 \tabularnewline
229 & 23 & 18.3334 & 4.66658 \tabularnewline
230 & 13 & 15.698 & -2.69795 \tabularnewline
231 & 12 & 13.3865 & -1.38651 \tabularnewline
232 & 16 & 17.8978 & -1.89776 \tabularnewline
233 & 9 & 13.4302 & -4.4302 \tabularnewline
234 & 17 & 13.501 & 3.49898 \tabularnewline
235 & 9 & 11.8874 & -2.88739 \tabularnewline
236 & 14 & 15.6544 & -1.65444 \tabularnewline
237 & 17 & 15.7113 & 1.28873 \tabularnewline
238 & 13 & 15.4947 & -2.49467 \tabularnewline
239 & 11 & 15.8809 & -4.88086 \tabularnewline
240 & 12 & 15.6138 & -3.61378 \tabularnewline
241 & 10 & 14.0764 & -4.07644 \tabularnewline
242 & 19 & 18.9305 & 0.0695193 \tabularnewline
243 & 16 & 16.1116 & -0.11163 \tabularnewline
244 & 16 & 15.0804 & 0.919643 \tabularnewline
245 & 14 & 12.1229 & 1.87713 \tabularnewline
246 & 20 & 15.9262 & 4.07382 \tabularnewline
247 & 15 & 14.4877 & 0.512261 \tabularnewline
248 & 23 & 15.4475 & 7.55245 \tabularnewline
249 & 20 & 17.9949 & 2.00509 \tabularnewline
250 & 16 & 16.0515 & -0.0515255 \tabularnewline
251 & 14 & 12.9735 & 1.02646 \tabularnewline
252 & 17 & 13.9247 & 3.0753 \tabularnewline
253 & 11 & 14.2646 & -3.2646 \tabularnewline
254 & 13 & 13.9612 & -0.961177 \tabularnewline
255 & 17 & 15.27 & 1.73002 \tabularnewline
256 & 15 & 15.2013 & -0.201332 \tabularnewline
257 & 21 & 15.9435 & 5.05655 \tabularnewline
258 & 18 & 17.8098 & 0.190224 \tabularnewline
259 & 15 & 12.7641 & 2.23585 \tabularnewline
260 & 8 & 16.5387 & -8.53873 \tabularnewline
261 & 12 & 13.6905 & -1.69048 \tabularnewline
262 & 12 & 12.9087 & -0.908708 \tabularnewline
263 & 22 & 19.0195 & 2.98047 \tabularnewline
264 & 12 & 13.2987 & -1.29871 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226612&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]12[/C][C]14.0707[/C][C]-2.07068[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]9.38697[/C][C]1.61303[/C][/ROW]
[ROW][C]3[/C][C]14[/C][C]15.5676[/C][C]-1.56758[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]15.069[/C][C]-3.06904[/C][/ROW]
[ROW][C]5[/C][C]21[/C][C]11.4634[/C][C]9.53655[/C][/ROW]
[ROW][C]6[/C][C]12[/C][C]9.96671[/C][C]2.03329[/C][/ROW]
[ROW][C]7[/C][C]22[/C][C]14.3162[/C][C]7.68375[/C][/ROW]
[ROW][C]8[/C][C]11[/C][C]12.6073[/C][C]-1.60735[/C][/ROW]
[ROW][C]9[/C][C]10[/C][C]12.2507[/C][C]-2.25074[/C][/ROW]
[ROW][C]10[/C][C]13[/C][C]12.2078[/C][C]0.792159[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]10.4506[/C][C]-0.450633[/C][/ROW]
[ROW][C]12[/C][C]8[/C][C]10.456[/C][C]-2.45603[/C][/ROW]
[ROW][C]13[/C][C]15[/C][C]16.1303[/C][C]-1.13033[/C][/ROW]
[ROW][C]14[/C][C]14[/C][C]12.5036[/C][C]1.49637[/C][/ROW]
[ROW][C]15[/C][C]10[/C][C]9.18135[/C][C]0.818645[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]14.0749[/C][C]-0.0748812[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]12.7558[/C][C]1.24423[/C][/ROW]
[ROW][C]18[/C][C]11[/C][C]9.50613[/C][C]1.49387[/C][/ROW]
[ROW][C]19[/C][C]10[/C][C]13.43[/C][C]-3.43001[/C][/ROW]
[ROW][C]20[/C][C]13[/C][C]12.7165[/C][C]0.283528[/C][/ROW]
[ROW][C]21[/C][C]9.5[/C][C]10.731[/C][C]-1.23097[/C][/ROW]
[ROW][C]22[/C][C]14[/C][C]15.8212[/C][C]-1.82117[/C][/ROW]
[ROW][C]23[/C][C]12[/C][C]13.6167[/C][C]-1.61666[/C][/ROW]
[ROW][C]24[/C][C]14[/C][C]15.6977[/C][C]-1.69772[/C][/ROW]
[ROW][C]25[/C][C]11[/C][C]9.69013[/C][C]1.30987[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.4043[/C][C]-6.40427[/C][/ROW]
[ROW][C]27[/C][C]11[/C][C]10.843[/C][C]0.157017[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]13.5472[/C][C]1.45284[/C][/ROW]
[ROW][C]29[/C][C]14[/C][C]11.6054[/C][C]2.39459[/C][/ROW]
[ROW][C]30[/C][C]13[/C][C]16.0748[/C][C]-3.0748[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]11.3312[/C][C]-2.33118[/C][/ROW]
[ROW][C]32[/C][C]15[/C][C]15.4812[/C][C]-0.48118[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.9721[/C][C]-0.972058[/C][/ROW]
[ROW][C]34[/C][C]11[/C][C]11.9988[/C][C]-0.998793[/C][/ROW]
[ROW][C]35[/C][C]13[/C][C]12.5792[/C][C]0.42075[/C][/ROW]
[ROW][C]36[/C][C]8[/C][C]12.4447[/C][C]-4.44466[/C][/ROW]
[ROW][C]37[/C][C]20[/C][C]17.6243[/C][C]2.37574[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]12.3914[/C][C]-0.391384[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]10.823[/C][C]-0.823044[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]13.8728[/C][C]-3.87278[/C][/ROW]
[ROW][C]41[/C][C]9[/C][C]12.0701[/C][C]-3.07006[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]11.3231[/C][C]2.6769[/C][/ROW]
[ROW][C]43[/C][C]8[/C][C]12.0753[/C][C]-4.07527[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]15.6619[/C][C]-1.66193[/C][/ROW]
[ROW][C]45[/C][C]11[/C][C]12.4771[/C][C]-1.47713[/C][/ROW]
[ROW][C]46[/C][C]13[/C][C]15.4547[/C][C]-2.45469[/C][/ROW]
[ROW][C]47[/C][C]9[/C][C]13.2007[/C][C]-4.20074[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]12.3012[/C][C]-1.30124[/C][/ROW]
[ROW][C]49[/C][C]15[/C][C]10.28[/C][C]4.71999[/C][/ROW]
[ROW][C]50[/C][C]11[/C][C]13.4198[/C][C]-2.41982[/C][/ROW]
[ROW][C]51[/C][C]10[/C][C]11.6562[/C][C]-1.65619[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.4444[/C][C]0.555582[/C][/ROW]
[ROW][C]53[/C][C]18[/C][C]15.8617[/C][C]2.13835[/C][/ROW]
[ROW][C]54[/C][C]14[/C][C]16.1753[/C][C]-2.17526[/C][/ROW]
[ROW][C]55[/C][C]11[/C][C]15.424[/C][C]-4.42403[/C][/ROW]
[ROW][C]56[/C][C]14.5[/C][C]12.3449[/C][C]2.15509[/C][/ROW]
[ROW][C]57[/C][C]13[/C][C]11.2475[/C][C]1.75247[/C][/ROW]
[ROW][C]58[/C][C]9[/C][C]12.9521[/C][C]-3.95213[/C][/ROW]
[ROW][C]59[/C][C]10[/C][C]14.1365[/C][C]-4.13647[/C][/ROW]
[ROW][C]60[/C][C]15[/C][C]14.5826[/C][C]0.417444[/C][/ROW]
[ROW][C]61[/C][C]20[/C][C]18.8978[/C][C]1.10216[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]12.9701[/C][C]-0.970102[/C][/ROW]
[ROW][C]63[/C][C]12[/C][C]14.4946[/C][C]-2.49463[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.3977[/C][C]-0.397724[/C][/ROW]
[ROW][C]65[/C][C]13[/C][C]13.3465[/C][C]-0.346518[/C][/ROW]
[ROW][C]66[/C][C]11[/C][C]15.2552[/C][C]-4.25518[/C][/ROW]
[ROW][C]67[/C][C]17[/C][C]15.4339[/C][C]1.5661[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]13.8245[/C][C]-1.82449[/C][/ROW]
[ROW][C]69[/C][C]13[/C][C]12.9367[/C][C]0.0632873[/C][/ROW]
[ROW][C]70[/C][C]14[/C][C]12.4359[/C][C]1.56409[/C][/ROW]
[ROW][C]71[/C][C]13[/C][C]14.1963[/C][C]-1.19627[/C][/ROW]
[ROW][C]72[/C][C]15[/C][C]12.9954[/C][C]2.00465[/C][/ROW]
[ROW][C]73[/C][C]13[/C][C]11.3752[/C][C]1.62476[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]11.8368[/C][C]-1.83679[/C][/ROW]
[ROW][C]75[/C][C]11[/C][C]12.7806[/C][C]-1.7806[/C][/ROW]
[ROW][C]76[/C][C]19[/C][C]13.7318[/C][C]5.26816[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]10.9146[/C][C]2.08538[/C][/ROW]
[ROW][C]78[/C][C]17[/C][C]14.1636[/C][C]2.83644[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]12.4811[/C][C]0.51894[/C][/ROW]
[ROW][C]80[/C][C]9[/C][C]14.6155[/C][C]-5.61551[/C][/ROW]
[ROW][C]81[/C][C]11[/C][C]11.6202[/C][C]-0.620229[/C][/ROW]
[ROW][C]82[/C][C]9[/C][C]12.5724[/C][C]-3.57245[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]11.267[/C][C]0.733004[/C][/ROW]
[ROW][C]84[/C][C]12[/C][C]12.4942[/C][C]-0.494223[/C][/ROW]
[ROW][C]85[/C][C]13[/C][C]12.7796[/C][C]0.220445[/C][/ROW]
[ROW][C]86[/C][C]13[/C][C]12.1184[/C][C]0.881563[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]13.2054[/C][C]-1.20545[/C][/ROW]
[ROW][C]88[/C][C]15[/C][C]14.968[/C][C]0.0319831[/C][/ROW]
[ROW][C]89[/C][C]22[/C][C]18.2297[/C][C]3.77026[/C][/ROW]
[ROW][C]90[/C][C]13[/C][C]11.5733[/C][C]1.42671[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]14.5308[/C][C]0.46922[/C][/ROW]
[ROW][C]92[/C][C]13[/C][C]11.8622[/C][C]1.13784[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]12.2514[/C][C]2.74865[/C][/ROW]
[ROW][C]94[/C][C]12.5[/C][C]13.41[/C][C]-0.910031[/C][/ROW]
[ROW][C]95[/C][C]11[/C][C]10.7152[/C][C]0.284823[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]14.5837[/C][C]1.41627[/C][/ROW]
[ROW][C]97[/C][C]11[/C][C]12.4332[/C][C]-1.43321[/C][/ROW]
[ROW][C]98[/C][C]11[/C][C]10.0266[/C][C]0.97344[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]12.3155[/C][C]-2.31549[/C][/ROW]
[ROW][C]100[/C][C]10[/C][C]10.2534[/C][C]-0.25345[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.3318[/C][C]1.6682[/C][/ROW]
[ROW][C]102[/C][C]12[/C][C]10.3699[/C][C]1.63009[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]15.8774[/C][C]-4.87742[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]11.8048[/C][C]4.19523[/C][/ROW]
[ROW][C]105[/C][C]19[/C][C]16.7034[/C][C]2.29661[/C][/ROW]
[ROW][C]106[/C][C]11[/C][C]11.2027[/C][C]-0.202738[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]12.0567[/C][C]3.94333[/C][/ROW]
[ROW][C]108[/C][C]15[/C][C]16.8484[/C][C]-1.84839[/C][/ROW]
[ROW][C]109[/C][C]24[/C][C]17.7818[/C][C]6.21825[/C][/ROW]
[ROW][C]110[/C][C]14[/C][C]11.7097[/C][C]2.29027[/C][/ROW]
[ROW][C]111[/C][C]15[/C][C]14.9089[/C][C]0.091125[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]13.0144[/C][C]-2.01437[/C][/ROW]
[ROW][C]113[/C][C]15[/C][C]13.6173[/C][C]1.38275[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]10.2933[/C][C]1.70671[/C][/ROW]
[ROW][C]115[/C][C]10[/C][C]10.5126[/C][C]-0.512578[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]14.2938[/C][C]-0.293768[/C][/ROW]
[ROW][C]117[/C][C]13[/C][C]14.0429[/C][C]-1.04295[/C][/ROW]
[ROW][C]118[/C][C]9[/C][C]13.4889[/C][C]-4.4889[/C][/ROW]
[ROW][C]119[/C][C]15[/C][C]11.8042[/C][C]3.19581[/C][/ROW]
[ROW][C]120[/C][C]15[/C][C]15.8213[/C][C]-0.821313[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]12.7689[/C][C]1.23114[/C][/ROW]
[ROW][C]122[/C][C]11[/C][C]11.3724[/C][C]-0.372438[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]12.0057[/C][C]-4.00575[/C][/ROW]
[ROW][C]124[/C][C]11[/C][C]12.2648[/C][C]-1.26475[/C][/ROW]
[ROW][C]125[/C][C]11[/C][C]13.1693[/C][C]-2.16928[/C][/ROW]
[ROW][C]126[/C][C]8[/C][C]9.7505[/C][C]-1.7505[/C][/ROW]
[ROW][C]127[/C][C]10[/C][C]10.165[/C][C]-0.164952[/C][/ROW]
[ROW][C]128[/C][C]11[/C][C]9.65594[/C][C]1.34406[/C][/ROW]
[ROW][C]129[/C][C]13[/C][C]12.6212[/C][C]0.378751[/C][/ROW]
[ROW][C]130[/C][C]11[/C][C]13.7012[/C][C]-2.70124[/C][/ROW]
[ROW][C]131[/C][C]20[/C][C]17.6139[/C][C]2.38608[/C][/ROW]
[ROW][C]132[/C][C]10[/C][C]11.7305[/C][C]-1.73053[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]13.3772[/C][C]1.62279[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]12.3715[/C][C]-0.37148[/C][/ROW]
[ROW][C]135[/C][C]14[/C][C]11.1197[/C][C]2.88029[/C][/ROW]
[ROW][C]136[/C][C]23[/C][C]16.6865[/C][C]6.31346[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]14.1567[/C][C]-0.156653[/C][/ROW]
[ROW][C]138[/C][C]16[/C][C]17.116[/C][C]-1.11596[/C][/ROW]
[ROW][C]139[/C][C]11[/C][C]13.2955[/C][C]-2.29555[/C][/ROW]
[ROW][C]140[/C][C]12[/C][C]14.3498[/C][C]-2.34977[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]13.5391[/C][C]-3.53913[/C][/ROW]
[ROW][C]142[/C][C]14[/C][C]11.1791[/C][C]2.82085[/C][/ROW]
[ROW][C]143[/C][C]12[/C][C]12.2644[/C][C]-0.26439[/C][/ROW]
[ROW][C]144[/C][C]12[/C][C]11.9386[/C][C]0.0614428[/C][/ROW]
[ROW][C]145[/C][C]11[/C][C]11.0276[/C][C]-0.0276187[/C][/ROW]
[ROW][C]146[/C][C]12[/C][C]11.2883[/C][C]0.711718[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]16.2155[/C][C]-3.21551[/C][/ROW]
[ROW][C]148[/C][C]11[/C][C]14.3363[/C][C]-3.3363[/C][/ROW]
[ROW][C]149[/C][C]19[/C][C]16.9592[/C][C]2.04077[/C][/ROW]
[ROW][C]150[/C][C]12[/C][C]11.4788[/C][C]0.521245[/C][/ROW]
[ROW][C]151[/C][C]17[/C][C]12.8816[/C][C]4.11835[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.4103[/C][C]-2.41026[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.5571[/C][C]-2.55714[/C][/ROW]
[ROW][C]154[/C][C]19[/C][C]16.9451[/C][C]2.0549[/C][/ROW]
[ROW][C]155[/C][C]18[/C][C]14.4672[/C][C]3.53282[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]14.5308[/C][C]0.46922[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.8017[/C][C]0.19832[/C][/ROW]
[ROW][C]158[/C][C]11[/C][C]9.65594[/C][C]1.34406[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]12.9772[/C][C]-3.97717[/C][/ROW]
[ROW][C]160[/C][C]18[/C][C]14.0669[/C][C]3.93307[/C][/ROW]
[ROW][C]161[/C][C]16[/C][C]14.8041[/C][C]1.19594[/C][/ROW]
[ROW][C]162[/C][C]24[/C][C]17.1097[/C][C]6.89033[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]12.6308[/C][C]1.36925[/C][/ROW]
[ROW][C]164[/C][C]20[/C][C]10.6954[/C][C]9.30464[/C][/ROW]
[ROW][C]165[/C][C]18[/C][C]15.8591[/C][C]2.14089[/C][/ROW]
[ROW][C]166[/C][C]23[/C][C]17.1733[/C][C]5.82668[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]13.0551[/C][C]-1.05508[/C][/ROW]
[ROW][C]168[/C][C]14[/C][C]14.8255[/C][C]-0.825503[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]16.2211[/C][C]-0.221125[/C][/ROW]
[ROW][C]170[/C][C]18[/C][C]16.2723[/C][C]1.72767[/C][/ROW]
[ROW][C]171[/C][C]20[/C][C]16.5533[/C][C]3.44666[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.5359[/C][C]0.464062[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]16.2085[/C][C]-4.20849[/C][/ROW]
[ROW][C]174[/C][C]17[/C][C]15.1908[/C][C]1.80924[/C][/ROW]
[ROW][C]175[/C][C]13[/C][C]11.8204[/C][C]1.17961[/C][/ROW]
[ROW][C]176[/C][C]9[/C][C]13.0369[/C][C]-4.03685[/C][/ROW]
[ROW][C]177[/C][C]16[/C][C]17.2949[/C][C]-1.29491[/C][/ROW]
[ROW][C]178[/C][C]18[/C][C]14.9823[/C][C]3.01767[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]12.2198[/C][C]-2.21977[/C][/ROW]
[ROW][C]180[/C][C]14[/C][C]14.8209[/C][C]-0.820873[/C][/ROW]
[ROW][C]181[/C][C]11[/C][C]14.003[/C][C]-3.00298[/C][/ROW]
[ROW][C]182[/C][C]9[/C][C]14.5214[/C][C]-5.5214[/C][/ROW]
[ROW][C]183[/C][C]11[/C][C]12.4065[/C][C]-1.40645[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]12.3261[/C][C]-2.32605[/C][/ROW]
[ROW][C]185[/C][C]11[/C][C]11.8104[/C][C]-0.810368[/C][/ROW]
[ROW][C]186[/C][C]19[/C][C]13.2272[/C][C]5.77282[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]12.4352[/C][C]1.56476[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]11.4926[/C][C]0.507448[/C][/ROW]
[ROW][C]189[/C][C]14[/C][C]15.096[/C][C]-1.09596[/C][/ROW]
[ROW][C]190[/C][C]21[/C][C]16.7072[/C][C]4.29278[/C][/ROW]
[ROW][C]191[/C][C]13[/C][C]15.6481[/C][C]-2.64811[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]12.4487[/C][C]-2.44867[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]13.0827[/C][C]1.91725[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]16.1679[/C][C]-0.167911[/C][/ROW]
[ROW][C]195[/C][C]14[/C][C]12.675[/C][C]1.32502[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.7067[/C][C]-2.70669[/C][/ROW]
[ROW][C]197[/C][C]19[/C][C]12.6133[/C][C]6.38671[/C][/ROW]
[ROW][C]198[/C][C]15[/C][C]12.1644[/C][C]2.83559[/C][/ROW]
[ROW][C]199[/C][C]19[/C][C]17.9897[/C][C]1.01031[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.2987[/C][C]-0.298707[/C][/ROW]
[ROW][C]201[/C][C]17[/C][C]17.1232[/C][C]-0.1232[/C][/ROW]
[ROW][C]202[/C][C]12[/C][C]12.7674[/C][C]-0.767407[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]10.6425[/C][C]0.357492[/C][/ROW]
[ROW][C]204[/C][C]14[/C][C]15.3911[/C][C]-1.3911[/C][/ROW]
[ROW][C]205[/C][C]11[/C][C]12.3814[/C][C]-1.38139[/C][/ROW]
[ROW][C]206[/C][C]13[/C][C]12.2762[/C][C]0.723804[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]12.6857[/C][C]-0.685733[/C][/ROW]
[ROW][C]208[/C][C]15[/C][C]12.6358[/C][C]2.36423[/C][/ROW]
[ROW][C]209[/C][C]14[/C][C]14.3955[/C][C]-0.395503[/C][/ROW]
[ROW][C]210[/C][C]12[/C][C]10.8274[/C][C]1.17262[/C][/ROW]
[ROW][C]211[/C][C]17[/C][C]17.4778[/C][C]-0.47778[/C][/ROW]
[ROW][C]212[/C][C]11[/C][C]11.2474[/C][C]-0.247411[/C][/ROW]
[ROW][C]213[/C][C]18[/C][C]14.5888[/C][C]3.41117[/C][/ROW]
[ROW][C]214[/C][C]13[/C][C]15.8596[/C][C]-2.85959[/C][/ROW]
[ROW][C]215[/C][C]17[/C][C]15.2583[/C][C]1.74174[/C][/ROW]
[ROW][C]216[/C][C]13[/C][C]13.304[/C][C]-0.30401[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]10.1197[/C][C]0.880287[/C][/ROW]
[ROW][C]218[/C][C]12[/C][C]12.5627[/C][C]-0.562721[/C][/ROW]
[ROW][C]219[/C][C]22[/C][C]17.9922[/C][C]4.00782[/C][/ROW]
[ROW][C]220[/C][C]14[/C][C]12.0213[/C][C]1.97867[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]15.0421[/C][C]-3.04214[/C][/ROW]
[ROW][C]222[/C][C]12[/C][C]11.8538[/C][C]0.146211[/C][/ROW]
[ROW][C]223[/C][C]17[/C][C]15.9533[/C][C]1.04669[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]12.8234[/C][C]-3.82342[/C][/ROW]
[ROW][C]225[/C][C]21[/C][C]17.1366[/C][C]3.86341[/C][/ROW]
[ROW][C]226[/C][C]10[/C][C]11.9179[/C][C]-1.91791[/C][/ROW]
[ROW][C]227[/C][C]11[/C][C]10.8618[/C][C]0.138211[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]14.5926[/C][C]-2.59256[/C][/ROW]
[ROW][C]229[/C][C]23[/C][C]18.3334[/C][C]4.66658[/C][/ROW]
[ROW][C]230[/C][C]13[/C][C]15.698[/C][C]-2.69795[/C][/ROW]
[ROW][C]231[/C][C]12[/C][C]13.3865[/C][C]-1.38651[/C][/ROW]
[ROW][C]232[/C][C]16[/C][C]17.8978[/C][C]-1.89776[/C][/ROW]
[ROW][C]233[/C][C]9[/C][C]13.4302[/C][C]-4.4302[/C][/ROW]
[ROW][C]234[/C][C]17[/C][C]13.501[/C][C]3.49898[/C][/ROW]
[ROW][C]235[/C][C]9[/C][C]11.8874[/C][C]-2.88739[/C][/ROW]
[ROW][C]236[/C][C]14[/C][C]15.6544[/C][C]-1.65444[/C][/ROW]
[ROW][C]237[/C][C]17[/C][C]15.7113[/C][C]1.28873[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]15.4947[/C][C]-2.49467[/C][/ROW]
[ROW][C]239[/C][C]11[/C][C]15.8809[/C][C]-4.88086[/C][/ROW]
[ROW][C]240[/C][C]12[/C][C]15.6138[/C][C]-3.61378[/C][/ROW]
[ROW][C]241[/C][C]10[/C][C]14.0764[/C][C]-4.07644[/C][/ROW]
[ROW][C]242[/C][C]19[/C][C]18.9305[/C][C]0.0695193[/C][/ROW]
[ROW][C]243[/C][C]16[/C][C]16.1116[/C][C]-0.11163[/C][/ROW]
[ROW][C]244[/C][C]16[/C][C]15.0804[/C][C]0.919643[/C][/ROW]
[ROW][C]245[/C][C]14[/C][C]12.1229[/C][C]1.87713[/C][/ROW]
[ROW][C]246[/C][C]20[/C][C]15.9262[/C][C]4.07382[/C][/ROW]
[ROW][C]247[/C][C]15[/C][C]14.4877[/C][C]0.512261[/C][/ROW]
[ROW][C]248[/C][C]23[/C][C]15.4475[/C][C]7.55245[/C][/ROW]
[ROW][C]249[/C][C]20[/C][C]17.9949[/C][C]2.00509[/C][/ROW]
[ROW][C]250[/C][C]16[/C][C]16.0515[/C][C]-0.0515255[/C][/ROW]
[ROW][C]251[/C][C]14[/C][C]12.9735[/C][C]1.02646[/C][/ROW]
[ROW][C]252[/C][C]17[/C][C]13.9247[/C][C]3.0753[/C][/ROW]
[ROW][C]253[/C][C]11[/C][C]14.2646[/C][C]-3.2646[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.9612[/C][C]-0.961177[/C][/ROW]
[ROW][C]255[/C][C]17[/C][C]15.27[/C][C]1.73002[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]15.2013[/C][C]-0.201332[/C][/ROW]
[ROW][C]257[/C][C]21[/C][C]15.9435[/C][C]5.05655[/C][/ROW]
[ROW][C]258[/C][C]18[/C][C]17.8098[/C][C]0.190224[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.7641[/C][C]2.23585[/C][/ROW]
[ROW][C]260[/C][C]8[/C][C]16.5387[/C][C]-8.53873[/C][/ROW]
[ROW][C]261[/C][C]12[/C][C]13.6905[/C][C]-1.69048[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]12.9087[/C][C]-0.908708[/C][/ROW]
[ROW][C]263[/C][C]22[/C][C]19.0195[/C][C]2.98047[/C][/ROW]
[ROW][C]264[/C][C]12[/C][C]13.2987[/C][C]-1.29871[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226612&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226612&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
11214.0707-2.07068
2119.386971.61303
31415.5676-1.56758
41215.069-3.06904
52111.46349.53655
6129.966712.03329
72214.31627.68375
81112.6073-1.60735
91012.2507-2.25074
101312.20780.792159
111010.4506-0.450633
12810.456-2.45603
131516.1303-1.13033
141412.50361.49637
15109.181350.818645
161414.0749-0.0748812
171412.75581.24423
18119.506131.49387
191013.43-3.43001
201312.71650.283528
219.510.731-1.23097
221415.8212-1.82117
231213.6167-1.61666
241415.6977-1.69772
25119.690131.30987
26915.4043-6.40427
271110.8430.157017
281513.54721.45284
291411.60542.39459
301316.0748-3.0748
31911.3312-2.33118
321515.4812-0.48118
331010.9721-0.972058
341111.9988-0.998793
351312.57920.42075
36812.4447-4.44466
372017.62432.37574
381212.3914-0.391384
391010.823-0.823044
401013.8728-3.87278
41912.0701-3.07006
421411.32312.6769
43812.0753-4.07527
441415.6619-1.66193
451112.4771-1.47713
461315.4547-2.45469
47913.2007-4.20074
481112.3012-1.30124
491510.284.71999
501113.4198-2.41982
511011.6562-1.65619
521413.44440.555582
531815.86172.13835
541416.1753-2.17526
551115.424-4.42403
5614.512.34492.15509
571311.24751.75247
58912.9521-3.95213
591014.1365-4.13647
601514.58260.417444
612018.89781.10216
621212.9701-0.970102
631214.4946-2.49463
641414.3977-0.397724
651313.3465-0.346518
661115.2552-4.25518
671715.43391.5661
681213.8245-1.82449
691312.93670.0632873
701412.43591.56409
711314.1963-1.19627
721512.99542.00465
731311.37521.62476
741011.8368-1.83679
751112.7806-1.7806
761913.73185.26816
771310.91462.08538
781714.16362.83644
791312.48110.51894
80914.6155-5.61551
811111.6202-0.620229
82912.5724-3.57245
831211.2670.733004
841212.4942-0.494223
851312.77960.220445
861312.11840.881563
871213.2054-1.20545
881514.9680.0319831
892218.22973.77026
901311.57331.42671
911514.53080.46922
921311.86221.13784
931512.25142.74865
9412.513.41-0.910031
951110.71520.284823
961614.58371.41627
971112.4332-1.43321
981110.02660.97344
991012.3155-2.31549
1001010.2534-0.25345
1011614.33181.6682
1021210.36991.63009
1031115.8774-4.87742
1041611.80484.19523
1051916.70342.29661
1061111.2027-0.202738
1071612.05673.94333
1081516.8484-1.84839
1092417.78186.21825
1101411.70972.29027
1111514.90890.091125
1121113.0144-2.01437
1131513.61731.38275
1141210.29331.70671
1151010.5126-0.512578
1161414.2938-0.293768
1171314.0429-1.04295
118913.4889-4.4889
1191511.80423.19581
1201515.8213-0.821313
1211412.76891.23114
1221111.3724-0.372438
123812.0057-4.00575
1241112.2648-1.26475
1251113.1693-2.16928
12689.7505-1.7505
1271010.165-0.164952
128119.655941.34406
1291312.62120.378751
1301113.7012-2.70124
1312017.61392.38608
1321011.7305-1.73053
1331513.37721.62279
1341212.3715-0.37148
1351411.11972.88029
1362316.68656.31346
1371414.1567-0.156653
1381617.116-1.11596
1391113.2955-2.29555
1401214.3498-2.34977
1411013.5391-3.53913
1421411.17912.82085
1431212.2644-0.26439
1441211.93860.0614428
1451111.0276-0.0276187
1461211.28830.711718
1471316.2155-3.21551
1481114.3363-3.3363
1491916.95922.04077
1501211.47880.521245
1511712.88164.11835
152911.4103-2.41026
1531214.5571-2.55714
1541916.94512.0549
1551814.46723.53282
1561514.53080.46922
1571413.80170.19832
158119.655941.34406
159912.9772-3.97717
1601814.06693.93307
1611614.80411.19594
1622417.10976.89033
1631412.63081.36925
1642010.69549.30464
1651815.85912.14089
1662317.17335.82668
1671213.0551-1.05508
1681414.8255-0.825503
1691616.2211-0.221125
1701816.27231.72767
1712016.55333.44666
1721211.53590.464062
1731216.2085-4.20849
1741715.19081.80924
1751311.82041.17961
176913.0369-4.03685
1771617.2949-1.29491
1781814.98233.01767
1791012.2198-2.21977
1801414.8209-0.820873
1811114.003-3.00298
182914.5214-5.5214
1831112.4065-1.40645
1841012.3261-2.32605
1851111.8104-0.810368
1861913.22725.77282
1871412.43521.56476
1881211.49260.507448
1891415.096-1.09596
1902116.70724.29278
1911315.6481-2.64811
1921012.4487-2.44867
1931513.08271.91725
1941616.1679-0.167911
1951412.6751.32502
1961214.7067-2.70669
1971912.61336.38671
1981512.16442.83559
1991917.98971.01031
2001313.2987-0.298707
2011717.1232-0.1232
2021212.7674-0.767407
2031110.64250.357492
2041415.3911-1.3911
2051112.3814-1.38139
2061312.27620.723804
2071212.6857-0.685733
2081512.63582.36423
2091414.3955-0.395503
2101210.82741.17262
2111717.4778-0.47778
2121111.2474-0.247411
2131814.58883.41117
2141315.8596-2.85959
2151715.25831.74174
2161313.304-0.30401
2171110.11970.880287
2181212.5627-0.562721
2192217.99224.00782
2201412.02131.97867
2211215.0421-3.04214
2221211.85380.146211
2231715.95331.04669
224912.8234-3.82342
2252117.13663.86341
2261011.9179-1.91791
2271110.86180.138211
2281214.5926-2.59256
2292318.33344.66658
2301315.698-2.69795
2311213.3865-1.38651
2321617.8978-1.89776
233913.4302-4.4302
2341713.5013.49898
235911.8874-2.88739
2361415.6544-1.65444
2371715.71131.28873
2381315.4947-2.49467
2391115.8809-4.88086
2401215.6138-3.61378
2411014.0764-4.07644
2421918.93050.0695193
2431616.1116-0.11163
2441615.08040.919643
2451412.12291.87713
2462015.92624.07382
2471514.48770.512261
2482315.44757.55245
2492017.99492.00509
2501616.0515-0.0515255
2511412.97351.02646
2521713.92473.0753
2531114.2646-3.2646
2541313.9612-0.961177
2551715.271.73002
2561515.2013-0.201332
2572115.94355.05655
2581817.80980.190224
2591512.76412.23585
260816.5387-8.53873
2611213.6905-1.69048
2621212.9087-0.908708
2632219.01952.98047
2641213.2987-1.29871






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.4463280.8926560.553672
120.9522340.09553290.0477664
130.9458210.1083590.0541793
140.9597720.08045530.0402276
150.9360390.1279220.0639608
160.9012590.1974830.0987414
170.9501850.09962930.0498146
180.9322190.1355620.0677812
190.9571080.08578360.0428918
200.9376050.1247910.0623955
210.9265420.1469170.0734584
220.9218150.1563690.0781847
230.8944370.2111270.105563
240.875070.249860.12493
250.8366460.3267080.163354
260.8377230.3245530.162277
270.8488010.3023980.151199
280.8089630.3820730.191037
290.8402570.3194850.159743
300.8307680.3384640.169232
310.8365680.3268630.163432
320.8052950.3894110.194705
330.7742720.4514570.225728
340.7497870.5004250.250213
350.716310.5673790.28369
360.7506890.4986210.249311
370.8321420.3357170.167858
380.7970180.4059640.202982
390.7632040.4735920.236796
400.7628260.4743480.237174
410.7510930.4978150.248907
420.7375340.5249330.262466
430.7902790.4194420.209721
440.7550510.4898970.244949
450.7187060.5625880.281294
460.6928640.6142730.307136
470.7487030.5025940.251297
480.714860.5702810.28514
490.7683180.4633640.231682
500.7426770.5146470.257323
510.7306890.5386220.269311
520.6963510.6072980.303649
530.6985560.6028890.301444
540.6661090.6677820.333891
550.6781580.6436850.321842
560.6939830.6120350.306017
570.6716190.6567620.328381
580.7083310.5833380.291669
590.723330.5533410.27667
600.7001470.5997060.299853
610.7122490.5755010.287751
620.6757690.6484610.324231
630.652090.695820.34791
640.6120840.7758330.387916
650.571170.8576590.42883
660.5813680.8372630.418632
670.5841120.8317760.415888
680.5542640.8914730.445736
690.5135640.9728710.486436
700.4895370.9790740.510463
710.4507580.9015160.549242
720.4269950.8539910.573005
730.4002770.8005550.599723
740.3793880.7587770.620612
750.3495250.6990510.650475
760.5113810.9772390.488619
770.4901660.9803320.509834
780.5064320.9871370.493568
790.468180.936360.53182
800.5661950.8676090.433805
810.5293440.9413120.470656
820.5534280.8931430.446572
830.5170410.9659170.482959
840.4790580.9581160.520942
850.4411860.8823720.558814
860.4076290.8152570.592371
870.3757110.7514220.624289
880.3426720.6853440.657328
890.4330310.8660620.566969
900.4035110.8070220.596489
910.3749560.7499120.625044
920.3446890.6893790.655311
930.3444010.6888030.655599
940.313190.626380.68681
950.2804810.5609620.719519
960.2645880.5291750.735412
970.2419150.483830.758085
980.2154560.4309120.784544
990.2074790.4149580.792521
1000.1823280.3646560.817672
1010.171850.34370.82815
1020.1537130.3074270.846287
1030.1940610.3881230.805939
1040.2249140.4498270.775086
1050.2337290.4674590.766271
1060.2067240.4134480.793276
1070.2318870.4637740.768113
1080.2154440.4308880.784556
1090.3440330.6880660.655967
1100.3353860.6707730.664614
1110.3046270.6092540.695373
1120.2935580.5871150.706442
1130.2693810.5387620.730619
1140.250510.5010210.74949
1150.2235720.4471440.776428
1160.197590.3951810.80241
1170.1767880.3535770.823212
1180.2154230.4308450.784577
1190.2213570.4427140.778643
1200.197430.3948610.80257
1210.1823230.3646460.817677
1220.1614520.3229040.838548
1230.1906430.3812870.809357
1240.171640.3432810.82836
1250.1619490.3238990.838051
1260.1507610.3015220.849239
1270.1325750.2651490.867425
1280.1182260.2364520.881774
1290.1018590.2037180.898141
1300.100890.201780.89911
1310.1025620.2051230.897438
1320.0945480.1890960.905452
1330.08634470.1726890.913655
1340.07337990.146760.92662
1350.07485010.14970.92515
1360.1492240.2984470.850776
1370.1300290.2600580.869971
1380.1152080.2304160.884792
1390.1103980.2207960.889602
1400.1051490.2102980.894851
1410.1177750.2355510.882225
1420.1185330.2370650.881467
1430.1019430.2038870.898057
1440.08679030.1735810.91321
1450.07390060.1478010.926099
1460.06261180.1252240.937388
1470.06863010.137260.93137
1480.07478570.1495710.925214
1490.07027420.1405480.929726
1500.05970820.1194160.940292
1510.07280110.1456020.927199
1520.06989170.1397830.930108
1530.06854250.1370850.931457
1540.06373040.1274610.93627
1550.0709190.1418380.929081
1560.06046150.1209230.939538
1570.05050120.1010020.949499
1580.04306940.08613880.956931
1590.05236390.1047280.947636
1600.06526640.1305330.934734
1610.05582610.1116520.944174
1620.1230240.2460480.876976
1630.1124770.2249540.887523
1640.3959740.7919480.604026
1650.3788860.7577720.621114
1660.487090.974180.51291
1670.4550030.9100060.544997
1680.4232520.8465040.576748
1690.3870160.7740310.612984
1700.3651130.7302250.634887
1710.3749110.7498210.625089
1720.3401640.6803280.659836
1730.3835020.7670040.616498
1740.370750.74150.62925
1750.3485080.6970150.651492
1760.3850930.7701860.614907
1770.3591540.7183070.640846
1780.3716940.7433880.628306
1790.3568330.7136660.643167
1800.3245210.6490420.675479
1810.3519330.7038660.648067
1820.4570750.914150.542925
1830.4421090.8842180.557891
1840.4306230.8612460.569377
1850.4140620.8281230.585938
1860.5412290.9175410.458771
1870.5092430.9815140.490757
1880.4765170.9530330.523483
1890.440280.8805610.55972
1900.4790350.958070.520965
1910.5084530.9830950.491547
1920.5254130.9491740.474587
1930.5161610.9676770.483839
1940.4853520.9707040.514648
1950.4575470.9150950.542453
1960.4928150.9856310.507185
1970.6973940.6052120.302606
1980.7055090.5889820.294491
1990.6688720.6622560.331128
2000.6293520.7412960.370648
2010.5890260.8219470.410974
2020.5482290.9035430.451771
2030.5235460.9529070.476454
2040.519320.9613590.48068
2050.4820680.9641360.517932
2060.4394460.8788920.560554
2070.3982530.7965050.601747
2080.3648430.7296860.635157
2090.3237660.6475320.676234
2100.3164330.6328650.683567
2110.2909110.5818220.709089
2120.2565790.5131590.743421
2130.2837070.5674150.716293
2140.2659420.5318840.734058
2150.2329720.4659440.767028
2160.2002630.4005260.799737
2170.1901390.3802790.809861
2180.1604920.3209840.839508
2190.1634970.3269930.836503
2200.1551550.3103110.844845
2210.154120.308240.84588
2220.1275380.2550760.872462
2230.1049220.2098430.895078
2240.1058390.2116790.894161
2250.09576820.1915360.904232
2260.07798030.1559610.92202
2270.06071950.1214390.93928
2280.05700010.1140.943
2290.07715870.1543170.922841
2300.07343510.146870.926565
2310.05652090.1130420.943479
2320.05802220.1160440.941978
2330.1207750.241550.879225
2340.1285170.2570350.871483
2350.1221870.2443740.877813
2360.09518630.1903730.904814
2370.1238310.2476620.876169
2380.1684370.3368750.831563
2390.2707810.5415620.729219
2400.269150.5382990.73085
2410.2231840.4463690.776816
2420.2711650.5423310.728835
2430.2114670.4229340.788533
2440.1585680.3171350.841432
2450.235040.4700790.76496
2460.2565840.5131680.743416
2470.1896870.3793740.810313
2480.234550.46910.76545
2490.3441550.6883110.655845
2500.2475750.4951490.752425
2510.2786780.5573550.721322
2520.9092770.1814450.0907227
2530.8430760.3138470.156924

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.446328 & 0.892656 & 0.553672 \tabularnewline
12 & 0.952234 & 0.0955329 & 0.0477664 \tabularnewline
13 & 0.945821 & 0.108359 & 0.0541793 \tabularnewline
14 & 0.959772 & 0.0804553 & 0.0402276 \tabularnewline
15 & 0.936039 & 0.127922 & 0.0639608 \tabularnewline
16 & 0.901259 & 0.197483 & 0.0987414 \tabularnewline
17 & 0.950185 & 0.0996293 & 0.0498146 \tabularnewline
18 & 0.932219 & 0.135562 & 0.0677812 \tabularnewline
19 & 0.957108 & 0.0857836 & 0.0428918 \tabularnewline
20 & 0.937605 & 0.124791 & 0.0623955 \tabularnewline
21 & 0.926542 & 0.146917 & 0.0734584 \tabularnewline
22 & 0.921815 & 0.156369 & 0.0781847 \tabularnewline
23 & 0.894437 & 0.211127 & 0.105563 \tabularnewline
24 & 0.87507 & 0.24986 & 0.12493 \tabularnewline
25 & 0.836646 & 0.326708 & 0.163354 \tabularnewline
26 & 0.837723 & 0.324553 & 0.162277 \tabularnewline
27 & 0.848801 & 0.302398 & 0.151199 \tabularnewline
28 & 0.808963 & 0.382073 & 0.191037 \tabularnewline
29 & 0.840257 & 0.319485 & 0.159743 \tabularnewline
30 & 0.830768 & 0.338464 & 0.169232 \tabularnewline
31 & 0.836568 & 0.326863 & 0.163432 \tabularnewline
32 & 0.805295 & 0.389411 & 0.194705 \tabularnewline
33 & 0.774272 & 0.451457 & 0.225728 \tabularnewline
34 & 0.749787 & 0.500425 & 0.250213 \tabularnewline
35 & 0.71631 & 0.567379 & 0.28369 \tabularnewline
36 & 0.750689 & 0.498621 & 0.249311 \tabularnewline
37 & 0.832142 & 0.335717 & 0.167858 \tabularnewline
38 & 0.797018 & 0.405964 & 0.202982 \tabularnewline
39 & 0.763204 & 0.473592 & 0.236796 \tabularnewline
40 & 0.762826 & 0.474348 & 0.237174 \tabularnewline
41 & 0.751093 & 0.497815 & 0.248907 \tabularnewline
42 & 0.737534 & 0.524933 & 0.262466 \tabularnewline
43 & 0.790279 & 0.419442 & 0.209721 \tabularnewline
44 & 0.755051 & 0.489897 & 0.244949 \tabularnewline
45 & 0.718706 & 0.562588 & 0.281294 \tabularnewline
46 & 0.692864 & 0.614273 & 0.307136 \tabularnewline
47 & 0.748703 & 0.502594 & 0.251297 \tabularnewline
48 & 0.71486 & 0.570281 & 0.28514 \tabularnewline
49 & 0.768318 & 0.463364 & 0.231682 \tabularnewline
50 & 0.742677 & 0.514647 & 0.257323 \tabularnewline
51 & 0.730689 & 0.538622 & 0.269311 \tabularnewline
52 & 0.696351 & 0.607298 & 0.303649 \tabularnewline
53 & 0.698556 & 0.602889 & 0.301444 \tabularnewline
54 & 0.666109 & 0.667782 & 0.333891 \tabularnewline
55 & 0.678158 & 0.643685 & 0.321842 \tabularnewline
56 & 0.693983 & 0.612035 & 0.306017 \tabularnewline
57 & 0.671619 & 0.656762 & 0.328381 \tabularnewline
58 & 0.708331 & 0.583338 & 0.291669 \tabularnewline
59 & 0.72333 & 0.553341 & 0.27667 \tabularnewline
60 & 0.700147 & 0.599706 & 0.299853 \tabularnewline
61 & 0.712249 & 0.575501 & 0.287751 \tabularnewline
62 & 0.675769 & 0.648461 & 0.324231 \tabularnewline
63 & 0.65209 & 0.69582 & 0.34791 \tabularnewline
64 & 0.612084 & 0.775833 & 0.387916 \tabularnewline
65 & 0.57117 & 0.857659 & 0.42883 \tabularnewline
66 & 0.581368 & 0.837263 & 0.418632 \tabularnewline
67 & 0.584112 & 0.831776 & 0.415888 \tabularnewline
68 & 0.554264 & 0.891473 & 0.445736 \tabularnewline
69 & 0.513564 & 0.972871 & 0.486436 \tabularnewline
70 & 0.489537 & 0.979074 & 0.510463 \tabularnewline
71 & 0.450758 & 0.901516 & 0.549242 \tabularnewline
72 & 0.426995 & 0.853991 & 0.573005 \tabularnewline
73 & 0.400277 & 0.800555 & 0.599723 \tabularnewline
74 & 0.379388 & 0.758777 & 0.620612 \tabularnewline
75 & 0.349525 & 0.699051 & 0.650475 \tabularnewline
76 & 0.511381 & 0.977239 & 0.488619 \tabularnewline
77 & 0.490166 & 0.980332 & 0.509834 \tabularnewline
78 & 0.506432 & 0.987137 & 0.493568 \tabularnewline
79 & 0.46818 & 0.93636 & 0.53182 \tabularnewline
80 & 0.566195 & 0.867609 & 0.433805 \tabularnewline
81 & 0.529344 & 0.941312 & 0.470656 \tabularnewline
82 & 0.553428 & 0.893143 & 0.446572 \tabularnewline
83 & 0.517041 & 0.965917 & 0.482959 \tabularnewline
84 & 0.479058 & 0.958116 & 0.520942 \tabularnewline
85 & 0.441186 & 0.882372 & 0.558814 \tabularnewline
86 & 0.407629 & 0.815257 & 0.592371 \tabularnewline
87 & 0.375711 & 0.751422 & 0.624289 \tabularnewline
88 & 0.342672 & 0.685344 & 0.657328 \tabularnewline
89 & 0.433031 & 0.866062 & 0.566969 \tabularnewline
90 & 0.403511 & 0.807022 & 0.596489 \tabularnewline
91 & 0.374956 & 0.749912 & 0.625044 \tabularnewline
92 & 0.344689 & 0.689379 & 0.655311 \tabularnewline
93 & 0.344401 & 0.688803 & 0.655599 \tabularnewline
94 & 0.31319 & 0.62638 & 0.68681 \tabularnewline
95 & 0.280481 & 0.560962 & 0.719519 \tabularnewline
96 & 0.264588 & 0.529175 & 0.735412 \tabularnewline
97 & 0.241915 & 0.48383 & 0.758085 \tabularnewline
98 & 0.215456 & 0.430912 & 0.784544 \tabularnewline
99 & 0.207479 & 0.414958 & 0.792521 \tabularnewline
100 & 0.182328 & 0.364656 & 0.817672 \tabularnewline
101 & 0.17185 & 0.3437 & 0.82815 \tabularnewline
102 & 0.153713 & 0.307427 & 0.846287 \tabularnewline
103 & 0.194061 & 0.388123 & 0.805939 \tabularnewline
104 & 0.224914 & 0.449827 & 0.775086 \tabularnewline
105 & 0.233729 & 0.467459 & 0.766271 \tabularnewline
106 & 0.206724 & 0.413448 & 0.793276 \tabularnewline
107 & 0.231887 & 0.463774 & 0.768113 \tabularnewline
108 & 0.215444 & 0.430888 & 0.784556 \tabularnewline
109 & 0.344033 & 0.688066 & 0.655967 \tabularnewline
110 & 0.335386 & 0.670773 & 0.664614 \tabularnewline
111 & 0.304627 & 0.609254 & 0.695373 \tabularnewline
112 & 0.293558 & 0.587115 & 0.706442 \tabularnewline
113 & 0.269381 & 0.538762 & 0.730619 \tabularnewline
114 & 0.25051 & 0.501021 & 0.74949 \tabularnewline
115 & 0.223572 & 0.447144 & 0.776428 \tabularnewline
116 & 0.19759 & 0.395181 & 0.80241 \tabularnewline
117 & 0.176788 & 0.353577 & 0.823212 \tabularnewline
118 & 0.215423 & 0.430845 & 0.784577 \tabularnewline
119 & 0.221357 & 0.442714 & 0.778643 \tabularnewline
120 & 0.19743 & 0.394861 & 0.80257 \tabularnewline
121 & 0.182323 & 0.364646 & 0.817677 \tabularnewline
122 & 0.161452 & 0.322904 & 0.838548 \tabularnewline
123 & 0.190643 & 0.381287 & 0.809357 \tabularnewline
124 & 0.17164 & 0.343281 & 0.82836 \tabularnewline
125 & 0.161949 & 0.323899 & 0.838051 \tabularnewline
126 & 0.150761 & 0.301522 & 0.849239 \tabularnewline
127 & 0.132575 & 0.265149 & 0.867425 \tabularnewline
128 & 0.118226 & 0.236452 & 0.881774 \tabularnewline
129 & 0.101859 & 0.203718 & 0.898141 \tabularnewline
130 & 0.10089 & 0.20178 & 0.89911 \tabularnewline
131 & 0.102562 & 0.205123 & 0.897438 \tabularnewline
132 & 0.094548 & 0.189096 & 0.905452 \tabularnewline
133 & 0.0863447 & 0.172689 & 0.913655 \tabularnewline
134 & 0.0733799 & 0.14676 & 0.92662 \tabularnewline
135 & 0.0748501 & 0.1497 & 0.92515 \tabularnewline
136 & 0.149224 & 0.298447 & 0.850776 \tabularnewline
137 & 0.130029 & 0.260058 & 0.869971 \tabularnewline
138 & 0.115208 & 0.230416 & 0.884792 \tabularnewline
139 & 0.110398 & 0.220796 & 0.889602 \tabularnewline
140 & 0.105149 & 0.210298 & 0.894851 \tabularnewline
141 & 0.117775 & 0.235551 & 0.882225 \tabularnewline
142 & 0.118533 & 0.237065 & 0.881467 \tabularnewline
143 & 0.101943 & 0.203887 & 0.898057 \tabularnewline
144 & 0.0867903 & 0.173581 & 0.91321 \tabularnewline
145 & 0.0739006 & 0.147801 & 0.926099 \tabularnewline
146 & 0.0626118 & 0.125224 & 0.937388 \tabularnewline
147 & 0.0686301 & 0.13726 & 0.93137 \tabularnewline
148 & 0.0747857 & 0.149571 & 0.925214 \tabularnewline
149 & 0.0702742 & 0.140548 & 0.929726 \tabularnewline
150 & 0.0597082 & 0.119416 & 0.940292 \tabularnewline
151 & 0.0728011 & 0.145602 & 0.927199 \tabularnewline
152 & 0.0698917 & 0.139783 & 0.930108 \tabularnewline
153 & 0.0685425 & 0.137085 & 0.931457 \tabularnewline
154 & 0.0637304 & 0.127461 & 0.93627 \tabularnewline
155 & 0.070919 & 0.141838 & 0.929081 \tabularnewline
156 & 0.0604615 & 0.120923 & 0.939538 \tabularnewline
157 & 0.0505012 & 0.101002 & 0.949499 \tabularnewline
158 & 0.0430694 & 0.0861388 & 0.956931 \tabularnewline
159 & 0.0523639 & 0.104728 & 0.947636 \tabularnewline
160 & 0.0652664 & 0.130533 & 0.934734 \tabularnewline
161 & 0.0558261 & 0.111652 & 0.944174 \tabularnewline
162 & 0.123024 & 0.246048 & 0.876976 \tabularnewline
163 & 0.112477 & 0.224954 & 0.887523 \tabularnewline
164 & 0.395974 & 0.791948 & 0.604026 \tabularnewline
165 & 0.378886 & 0.757772 & 0.621114 \tabularnewline
166 & 0.48709 & 0.97418 & 0.51291 \tabularnewline
167 & 0.455003 & 0.910006 & 0.544997 \tabularnewline
168 & 0.423252 & 0.846504 & 0.576748 \tabularnewline
169 & 0.387016 & 0.774031 & 0.612984 \tabularnewline
170 & 0.365113 & 0.730225 & 0.634887 \tabularnewline
171 & 0.374911 & 0.749821 & 0.625089 \tabularnewline
172 & 0.340164 & 0.680328 & 0.659836 \tabularnewline
173 & 0.383502 & 0.767004 & 0.616498 \tabularnewline
174 & 0.37075 & 0.7415 & 0.62925 \tabularnewline
175 & 0.348508 & 0.697015 & 0.651492 \tabularnewline
176 & 0.385093 & 0.770186 & 0.614907 \tabularnewline
177 & 0.359154 & 0.718307 & 0.640846 \tabularnewline
178 & 0.371694 & 0.743388 & 0.628306 \tabularnewline
179 & 0.356833 & 0.713666 & 0.643167 \tabularnewline
180 & 0.324521 & 0.649042 & 0.675479 \tabularnewline
181 & 0.351933 & 0.703866 & 0.648067 \tabularnewline
182 & 0.457075 & 0.91415 & 0.542925 \tabularnewline
183 & 0.442109 & 0.884218 & 0.557891 \tabularnewline
184 & 0.430623 & 0.861246 & 0.569377 \tabularnewline
185 & 0.414062 & 0.828123 & 0.585938 \tabularnewline
186 & 0.541229 & 0.917541 & 0.458771 \tabularnewline
187 & 0.509243 & 0.981514 & 0.490757 \tabularnewline
188 & 0.476517 & 0.953033 & 0.523483 \tabularnewline
189 & 0.44028 & 0.880561 & 0.55972 \tabularnewline
190 & 0.479035 & 0.95807 & 0.520965 \tabularnewline
191 & 0.508453 & 0.983095 & 0.491547 \tabularnewline
192 & 0.525413 & 0.949174 & 0.474587 \tabularnewline
193 & 0.516161 & 0.967677 & 0.483839 \tabularnewline
194 & 0.485352 & 0.970704 & 0.514648 \tabularnewline
195 & 0.457547 & 0.915095 & 0.542453 \tabularnewline
196 & 0.492815 & 0.985631 & 0.507185 \tabularnewline
197 & 0.697394 & 0.605212 & 0.302606 \tabularnewline
198 & 0.705509 & 0.588982 & 0.294491 \tabularnewline
199 & 0.668872 & 0.662256 & 0.331128 \tabularnewline
200 & 0.629352 & 0.741296 & 0.370648 \tabularnewline
201 & 0.589026 & 0.821947 & 0.410974 \tabularnewline
202 & 0.548229 & 0.903543 & 0.451771 \tabularnewline
203 & 0.523546 & 0.952907 & 0.476454 \tabularnewline
204 & 0.51932 & 0.961359 & 0.48068 \tabularnewline
205 & 0.482068 & 0.964136 & 0.517932 \tabularnewline
206 & 0.439446 & 0.878892 & 0.560554 \tabularnewline
207 & 0.398253 & 0.796505 & 0.601747 \tabularnewline
208 & 0.364843 & 0.729686 & 0.635157 \tabularnewline
209 & 0.323766 & 0.647532 & 0.676234 \tabularnewline
210 & 0.316433 & 0.632865 & 0.683567 \tabularnewline
211 & 0.290911 & 0.581822 & 0.709089 \tabularnewline
212 & 0.256579 & 0.513159 & 0.743421 \tabularnewline
213 & 0.283707 & 0.567415 & 0.716293 \tabularnewline
214 & 0.265942 & 0.531884 & 0.734058 \tabularnewline
215 & 0.232972 & 0.465944 & 0.767028 \tabularnewline
216 & 0.200263 & 0.400526 & 0.799737 \tabularnewline
217 & 0.190139 & 0.380279 & 0.809861 \tabularnewline
218 & 0.160492 & 0.320984 & 0.839508 \tabularnewline
219 & 0.163497 & 0.326993 & 0.836503 \tabularnewline
220 & 0.155155 & 0.310311 & 0.844845 \tabularnewline
221 & 0.15412 & 0.30824 & 0.84588 \tabularnewline
222 & 0.127538 & 0.255076 & 0.872462 \tabularnewline
223 & 0.104922 & 0.209843 & 0.895078 \tabularnewline
224 & 0.105839 & 0.211679 & 0.894161 \tabularnewline
225 & 0.0957682 & 0.191536 & 0.904232 \tabularnewline
226 & 0.0779803 & 0.155961 & 0.92202 \tabularnewline
227 & 0.0607195 & 0.121439 & 0.93928 \tabularnewline
228 & 0.0570001 & 0.114 & 0.943 \tabularnewline
229 & 0.0771587 & 0.154317 & 0.922841 \tabularnewline
230 & 0.0734351 & 0.14687 & 0.926565 \tabularnewline
231 & 0.0565209 & 0.113042 & 0.943479 \tabularnewline
232 & 0.0580222 & 0.116044 & 0.941978 \tabularnewline
233 & 0.120775 & 0.24155 & 0.879225 \tabularnewline
234 & 0.128517 & 0.257035 & 0.871483 \tabularnewline
235 & 0.122187 & 0.244374 & 0.877813 \tabularnewline
236 & 0.0951863 & 0.190373 & 0.904814 \tabularnewline
237 & 0.123831 & 0.247662 & 0.876169 \tabularnewline
238 & 0.168437 & 0.336875 & 0.831563 \tabularnewline
239 & 0.270781 & 0.541562 & 0.729219 \tabularnewline
240 & 0.26915 & 0.538299 & 0.73085 \tabularnewline
241 & 0.223184 & 0.446369 & 0.776816 \tabularnewline
242 & 0.271165 & 0.542331 & 0.728835 \tabularnewline
243 & 0.211467 & 0.422934 & 0.788533 \tabularnewline
244 & 0.158568 & 0.317135 & 0.841432 \tabularnewline
245 & 0.23504 & 0.470079 & 0.76496 \tabularnewline
246 & 0.256584 & 0.513168 & 0.743416 \tabularnewline
247 & 0.189687 & 0.379374 & 0.810313 \tabularnewline
248 & 0.23455 & 0.4691 & 0.76545 \tabularnewline
249 & 0.344155 & 0.688311 & 0.655845 \tabularnewline
250 & 0.247575 & 0.495149 & 0.752425 \tabularnewline
251 & 0.278678 & 0.557355 & 0.721322 \tabularnewline
252 & 0.909277 & 0.181445 & 0.0907227 \tabularnewline
253 & 0.843076 & 0.313847 & 0.156924 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226612&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]0.446328[/C][C]0.892656[/C][C]0.553672[/C][/ROW]
[ROW][C]12[/C][C]0.952234[/C][C]0.0955329[/C][C]0.0477664[/C][/ROW]
[ROW][C]13[/C][C]0.945821[/C][C]0.108359[/C][C]0.0541793[/C][/ROW]
[ROW][C]14[/C][C]0.959772[/C][C]0.0804553[/C][C]0.0402276[/C][/ROW]
[ROW][C]15[/C][C]0.936039[/C][C]0.127922[/C][C]0.0639608[/C][/ROW]
[ROW][C]16[/C][C]0.901259[/C][C]0.197483[/C][C]0.0987414[/C][/ROW]
[ROW][C]17[/C][C]0.950185[/C][C]0.0996293[/C][C]0.0498146[/C][/ROW]
[ROW][C]18[/C][C]0.932219[/C][C]0.135562[/C][C]0.0677812[/C][/ROW]
[ROW][C]19[/C][C]0.957108[/C][C]0.0857836[/C][C]0.0428918[/C][/ROW]
[ROW][C]20[/C][C]0.937605[/C][C]0.124791[/C][C]0.0623955[/C][/ROW]
[ROW][C]21[/C][C]0.926542[/C][C]0.146917[/C][C]0.0734584[/C][/ROW]
[ROW][C]22[/C][C]0.921815[/C][C]0.156369[/C][C]0.0781847[/C][/ROW]
[ROW][C]23[/C][C]0.894437[/C][C]0.211127[/C][C]0.105563[/C][/ROW]
[ROW][C]24[/C][C]0.87507[/C][C]0.24986[/C][C]0.12493[/C][/ROW]
[ROW][C]25[/C][C]0.836646[/C][C]0.326708[/C][C]0.163354[/C][/ROW]
[ROW][C]26[/C][C]0.837723[/C][C]0.324553[/C][C]0.162277[/C][/ROW]
[ROW][C]27[/C][C]0.848801[/C][C]0.302398[/C][C]0.151199[/C][/ROW]
[ROW][C]28[/C][C]0.808963[/C][C]0.382073[/C][C]0.191037[/C][/ROW]
[ROW][C]29[/C][C]0.840257[/C][C]0.319485[/C][C]0.159743[/C][/ROW]
[ROW][C]30[/C][C]0.830768[/C][C]0.338464[/C][C]0.169232[/C][/ROW]
[ROW][C]31[/C][C]0.836568[/C][C]0.326863[/C][C]0.163432[/C][/ROW]
[ROW][C]32[/C][C]0.805295[/C][C]0.389411[/C][C]0.194705[/C][/ROW]
[ROW][C]33[/C][C]0.774272[/C][C]0.451457[/C][C]0.225728[/C][/ROW]
[ROW][C]34[/C][C]0.749787[/C][C]0.500425[/C][C]0.250213[/C][/ROW]
[ROW][C]35[/C][C]0.71631[/C][C]0.567379[/C][C]0.28369[/C][/ROW]
[ROW][C]36[/C][C]0.750689[/C][C]0.498621[/C][C]0.249311[/C][/ROW]
[ROW][C]37[/C][C]0.832142[/C][C]0.335717[/C][C]0.167858[/C][/ROW]
[ROW][C]38[/C][C]0.797018[/C][C]0.405964[/C][C]0.202982[/C][/ROW]
[ROW][C]39[/C][C]0.763204[/C][C]0.473592[/C][C]0.236796[/C][/ROW]
[ROW][C]40[/C][C]0.762826[/C][C]0.474348[/C][C]0.237174[/C][/ROW]
[ROW][C]41[/C][C]0.751093[/C][C]0.497815[/C][C]0.248907[/C][/ROW]
[ROW][C]42[/C][C]0.737534[/C][C]0.524933[/C][C]0.262466[/C][/ROW]
[ROW][C]43[/C][C]0.790279[/C][C]0.419442[/C][C]0.209721[/C][/ROW]
[ROW][C]44[/C][C]0.755051[/C][C]0.489897[/C][C]0.244949[/C][/ROW]
[ROW][C]45[/C][C]0.718706[/C][C]0.562588[/C][C]0.281294[/C][/ROW]
[ROW][C]46[/C][C]0.692864[/C][C]0.614273[/C][C]0.307136[/C][/ROW]
[ROW][C]47[/C][C]0.748703[/C][C]0.502594[/C][C]0.251297[/C][/ROW]
[ROW][C]48[/C][C]0.71486[/C][C]0.570281[/C][C]0.28514[/C][/ROW]
[ROW][C]49[/C][C]0.768318[/C][C]0.463364[/C][C]0.231682[/C][/ROW]
[ROW][C]50[/C][C]0.742677[/C][C]0.514647[/C][C]0.257323[/C][/ROW]
[ROW][C]51[/C][C]0.730689[/C][C]0.538622[/C][C]0.269311[/C][/ROW]
[ROW][C]52[/C][C]0.696351[/C][C]0.607298[/C][C]0.303649[/C][/ROW]
[ROW][C]53[/C][C]0.698556[/C][C]0.602889[/C][C]0.301444[/C][/ROW]
[ROW][C]54[/C][C]0.666109[/C][C]0.667782[/C][C]0.333891[/C][/ROW]
[ROW][C]55[/C][C]0.678158[/C][C]0.643685[/C][C]0.321842[/C][/ROW]
[ROW][C]56[/C][C]0.693983[/C][C]0.612035[/C][C]0.306017[/C][/ROW]
[ROW][C]57[/C][C]0.671619[/C][C]0.656762[/C][C]0.328381[/C][/ROW]
[ROW][C]58[/C][C]0.708331[/C][C]0.583338[/C][C]0.291669[/C][/ROW]
[ROW][C]59[/C][C]0.72333[/C][C]0.553341[/C][C]0.27667[/C][/ROW]
[ROW][C]60[/C][C]0.700147[/C][C]0.599706[/C][C]0.299853[/C][/ROW]
[ROW][C]61[/C][C]0.712249[/C][C]0.575501[/C][C]0.287751[/C][/ROW]
[ROW][C]62[/C][C]0.675769[/C][C]0.648461[/C][C]0.324231[/C][/ROW]
[ROW][C]63[/C][C]0.65209[/C][C]0.69582[/C][C]0.34791[/C][/ROW]
[ROW][C]64[/C][C]0.612084[/C][C]0.775833[/C][C]0.387916[/C][/ROW]
[ROW][C]65[/C][C]0.57117[/C][C]0.857659[/C][C]0.42883[/C][/ROW]
[ROW][C]66[/C][C]0.581368[/C][C]0.837263[/C][C]0.418632[/C][/ROW]
[ROW][C]67[/C][C]0.584112[/C][C]0.831776[/C][C]0.415888[/C][/ROW]
[ROW][C]68[/C][C]0.554264[/C][C]0.891473[/C][C]0.445736[/C][/ROW]
[ROW][C]69[/C][C]0.513564[/C][C]0.972871[/C][C]0.486436[/C][/ROW]
[ROW][C]70[/C][C]0.489537[/C][C]0.979074[/C][C]0.510463[/C][/ROW]
[ROW][C]71[/C][C]0.450758[/C][C]0.901516[/C][C]0.549242[/C][/ROW]
[ROW][C]72[/C][C]0.426995[/C][C]0.853991[/C][C]0.573005[/C][/ROW]
[ROW][C]73[/C][C]0.400277[/C][C]0.800555[/C][C]0.599723[/C][/ROW]
[ROW][C]74[/C][C]0.379388[/C][C]0.758777[/C][C]0.620612[/C][/ROW]
[ROW][C]75[/C][C]0.349525[/C][C]0.699051[/C][C]0.650475[/C][/ROW]
[ROW][C]76[/C][C]0.511381[/C][C]0.977239[/C][C]0.488619[/C][/ROW]
[ROW][C]77[/C][C]0.490166[/C][C]0.980332[/C][C]0.509834[/C][/ROW]
[ROW][C]78[/C][C]0.506432[/C][C]0.987137[/C][C]0.493568[/C][/ROW]
[ROW][C]79[/C][C]0.46818[/C][C]0.93636[/C][C]0.53182[/C][/ROW]
[ROW][C]80[/C][C]0.566195[/C][C]0.867609[/C][C]0.433805[/C][/ROW]
[ROW][C]81[/C][C]0.529344[/C][C]0.941312[/C][C]0.470656[/C][/ROW]
[ROW][C]82[/C][C]0.553428[/C][C]0.893143[/C][C]0.446572[/C][/ROW]
[ROW][C]83[/C][C]0.517041[/C][C]0.965917[/C][C]0.482959[/C][/ROW]
[ROW][C]84[/C][C]0.479058[/C][C]0.958116[/C][C]0.520942[/C][/ROW]
[ROW][C]85[/C][C]0.441186[/C][C]0.882372[/C][C]0.558814[/C][/ROW]
[ROW][C]86[/C][C]0.407629[/C][C]0.815257[/C][C]0.592371[/C][/ROW]
[ROW][C]87[/C][C]0.375711[/C][C]0.751422[/C][C]0.624289[/C][/ROW]
[ROW][C]88[/C][C]0.342672[/C][C]0.685344[/C][C]0.657328[/C][/ROW]
[ROW][C]89[/C][C]0.433031[/C][C]0.866062[/C][C]0.566969[/C][/ROW]
[ROW][C]90[/C][C]0.403511[/C][C]0.807022[/C][C]0.596489[/C][/ROW]
[ROW][C]91[/C][C]0.374956[/C][C]0.749912[/C][C]0.625044[/C][/ROW]
[ROW][C]92[/C][C]0.344689[/C][C]0.689379[/C][C]0.655311[/C][/ROW]
[ROW][C]93[/C][C]0.344401[/C][C]0.688803[/C][C]0.655599[/C][/ROW]
[ROW][C]94[/C][C]0.31319[/C][C]0.62638[/C][C]0.68681[/C][/ROW]
[ROW][C]95[/C][C]0.280481[/C][C]0.560962[/C][C]0.719519[/C][/ROW]
[ROW][C]96[/C][C]0.264588[/C][C]0.529175[/C][C]0.735412[/C][/ROW]
[ROW][C]97[/C][C]0.241915[/C][C]0.48383[/C][C]0.758085[/C][/ROW]
[ROW][C]98[/C][C]0.215456[/C][C]0.430912[/C][C]0.784544[/C][/ROW]
[ROW][C]99[/C][C]0.207479[/C][C]0.414958[/C][C]0.792521[/C][/ROW]
[ROW][C]100[/C][C]0.182328[/C][C]0.364656[/C][C]0.817672[/C][/ROW]
[ROW][C]101[/C][C]0.17185[/C][C]0.3437[/C][C]0.82815[/C][/ROW]
[ROW][C]102[/C][C]0.153713[/C][C]0.307427[/C][C]0.846287[/C][/ROW]
[ROW][C]103[/C][C]0.194061[/C][C]0.388123[/C][C]0.805939[/C][/ROW]
[ROW][C]104[/C][C]0.224914[/C][C]0.449827[/C][C]0.775086[/C][/ROW]
[ROW][C]105[/C][C]0.233729[/C][C]0.467459[/C][C]0.766271[/C][/ROW]
[ROW][C]106[/C][C]0.206724[/C][C]0.413448[/C][C]0.793276[/C][/ROW]
[ROW][C]107[/C][C]0.231887[/C][C]0.463774[/C][C]0.768113[/C][/ROW]
[ROW][C]108[/C][C]0.215444[/C][C]0.430888[/C][C]0.784556[/C][/ROW]
[ROW][C]109[/C][C]0.344033[/C][C]0.688066[/C][C]0.655967[/C][/ROW]
[ROW][C]110[/C][C]0.335386[/C][C]0.670773[/C][C]0.664614[/C][/ROW]
[ROW][C]111[/C][C]0.304627[/C][C]0.609254[/C][C]0.695373[/C][/ROW]
[ROW][C]112[/C][C]0.293558[/C][C]0.587115[/C][C]0.706442[/C][/ROW]
[ROW][C]113[/C][C]0.269381[/C][C]0.538762[/C][C]0.730619[/C][/ROW]
[ROW][C]114[/C][C]0.25051[/C][C]0.501021[/C][C]0.74949[/C][/ROW]
[ROW][C]115[/C][C]0.223572[/C][C]0.447144[/C][C]0.776428[/C][/ROW]
[ROW][C]116[/C][C]0.19759[/C][C]0.395181[/C][C]0.80241[/C][/ROW]
[ROW][C]117[/C][C]0.176788[/C][C]0.353577[/C][C]0.823212[/C][/ROW]
[ROW][C]118[/C][C]0.215423[/C][C]0.430845[/C][C]0.784577[/C][/ROW]
[ROW][C]119[/C][C]0.221357[/C][C]0.442714[/C][C]0.778643[/C][/ROW]
[ROW][C]120[/C][C]0.19743[/C][C]0.394861[/C][C]0.80257[/C][/ROW]
[ROW][C]121[/C][C]0.182323[/C][C]0.364646[/C][C]0.817677[/C][/ROW]
[ROW][C]122[/C][C]0.161452[/C][C]0.322904[/C][C]0.838548[/C][/ROW]
[ROW][C]123[/C][C]0.190643[/C][C]0.381287[/C][C]0.809357[/C][/ROW]
[ROW][C]124[/C][C]0.17164[/C][C]0.343281[/C][C]0.82836[/C][/ROW]
[ROW][C]125[/C][C]0.161949[/C][C]0.323899[/C][C]0.838051[/C][/ROW]
[ROW][C]126[/C][C]0.150761[/C][C]0.301522[/C][C]0.849239[/C][/ROW]
[ROW][C]127[/C][C]0.132575[/C][C]0.265149[/C][C]0.867425[/C][/ROW]
[ROW][C]128[/C][C]0.118226[/C][C]0.236452[/C][C]0.881774[/C][/ROW]
[ROW][C]129[/C][C]0.101859[/C][C]0.203718[/C][C]0.898141[/C][/ROW]
[ROW][C]130[/C][C]0.10089[/C][C]0.20178[/C][C]0.89911[/C][/ROW]
[ROW][C]131[/C][C]0.102562[/C][C]0.205123[/C][C]0.897438[/C][/ROW]
[ROW][C]132[/C][C]0.094548[/C][C]0.189096[/C][C]0.905452[/C][/ROW]
[ROW][C]133[/C][C]0.0863447[/C][C]0.172689[/C][C]0.913655[/C][/ROW]
[ROW][C]134[/C][C]0.0733799[/C][C]0.14676[/C][C]0.92662[/C][/ROW]
[ROW][C]135[/C][C]0.0748501[/C][C]0.1497[/C][C]0.92515[/C][/ROW]
[ROW][C]136[/C][C]0.149224[/C][C]0.298447[/C][C]0.850776[/C][/ROW]
[ROW][C]137[/C][C]0.130029[/C][C]0.260058[/C][C]0.869971[/C][/ROW]
[ROW][C]138[/C][C]0.115208[/C][C]0.230416[/C][C]0.884792[/C][/ROW]
[ROW][C]139[/C][C]0.110398[/C][C]0.220796[/C][C]0.889602[/C][/ROW]
[ROW][C]140[/C][C]0.105149[/C][C]0.210298[/C][C]0.894851[/C][/ROW]
[ROW][C]141[/C][C]0.117775[/C][C]0.235551[/C][C]0.882225[/C][/ROW]
[ROW][C]142[/C][C]0.118533[/C][C]0.237065[/C][C]0.881467[/C][/ROW]
[ROW][C]143[/C][C]0.101943[/C][C]0.203887[/C][C]0.898057[/C][/ROW]
[ROW][C]144[/C][C]0.0867903[/C][C]0.173581[/C][C]0.91321[/C][/ROW]
[ROW][C]145[/C][C]0.0739006[/C][C]0.147801[/C][C]0.926099[/C][/ROW]
[ROW][C]146[/C][C]0.0626118[/C][C]0.125224[/C][C]0.937388[/C][/ROW]
[ROW][C]147[/C][C]0.0686301[/C][C]0.13726[/C][C]0.93137[/C][/ROW]
[ROW][C]148[/C][C]0.0747857[/C][C]0.149571[/C][C]0.925214[/C][/ROW]
[ROW][C]149[/C][C]0.0702742[/C][C]0.140548[/C][C]0.929726[/C][/ROW]
[ROW][C]150[/C][C]0.0597082[/C][C]0.119416[/C][C]0.940292[/C][/ROW]
[ROW][C]151[/C][C]0.0728011[/C][C]0.145602[/C][C]0.927199[/C][/ROW]
[ROW][C]152[/C][C]0.0698917[/C][C]0.139783[/C][C]0.930108[/C][/ROW]
[ROW][C]153[/C][C]0.0685425[/C][C]0.137085[/C][C]0.931457[/C][/ROW]
[ROW][C]154[/C][C]0.0637304[/C][C]0.127461[/C][C]0.93627[/C][/ROW]
[ROW][C]155[/C][C]0.070919[/C][C]0.141838[/C][C]0.929081[/C][/ROW]
[ROW][C]156[/C][C]0.0604615[/C][C]0.120923[/C][C]0.939538[/C][/ROW]
[ROW][C]157[/C][C]0.0505012[/C][C]0.101002[/C][C]0.949499[/C][/ROW]
[ROW][C]158[/C][C]0.0430694[/C][C]0.0861388[/C][C]0.956931[/C][/ROW]
[ROW][C]159[/C][C]0.0523639[/C][C]0.104728[/C][C]0.947636[/C][/ROW]
[ROW][C]160[/C][C]0.0652664[/C][C]0.130533[/C][C]0.934734[/C][/ROW]
[ROW][C]161[/C][C]0.0558261[/C][C]0.111652[/C][C]0.944174[/C][/ROW]
[ROW][C]162[/C][C]0.123024[/C][C]0.246048[/C][C]0.876976[/C][/ROW]
[ROW][C]163[/C][C]0.112477[/C][C]0.224954[/C][C]0.887523[/C][/ROW]
[ROW][C]164[/C][C]0.395974[/C][C]0.791948[/C][C]0.604026[/C][/ROW]
[ROW][C]165[/C][C]0.378886[/C][C]0.757772[/C][C]0.621114[/C][/ROW]
[ROW][C]166[/C][C]0.48709[/C][C]0.97418[/C][C]0.51291[/C][/ROW]
[ROW][C]167[/C][C]0.455003[/C][C]0.910006[/C][C]0.544997[/C][/ROW]
[ROW][C]168[/C][C]0.423252[/C][C]0.846504[/C][C]0.576748[/C][/ROW]
[ROW][C]169[/C][C]0.387016[/C][C]0.774031[/C][C]0.612984[/C][/ROW]
[ROW][C]170[/C][C]0.365113[/C][C]0.730225[/C][C]0.634887[/C][/ROW]
[ROW][C]171[/C][C]0.374911[/C][C]0.749821[/C][C]0.625089[/C][/ROW]
[ROW][C]172[/C][C]0.340164[/C][C]0.680328[/C][C]0.659836[/C][/ROW]
[ROW][C]173[/C][C]0.383502[/C][C]0.767004[/C][C]0.616498[/C][/ROW]
[ROW][C]174[/C][C]0.37075[/C][C]0.7415[/C][C]0.62925[/C][/ROW]
[ROW][C]175[/C][C]0.348508[/C][C]0.697015[/C][C]0.651492[/C][/ROW]
[ROW][C]176[/C][C]0.385093[/C][C]0.770186[/C][C]0.614907[/C][/ROW]
[ROW][C]177[/C][C]0.359154[/C][C]0.718307[/C][C]0.640846[/C][/ROW]
[ROW][C]178[/C][C]0.371694[/C][C]0.743388[/C][C]0.628306[/C][/ROW]
[ROW][C]179[/C][C]0.356833[/C][C]0.713666[/C][C]0.643167[/C][/ROW]
[ROW][C]180[/C][C]0.324521[/C][C]0.649042[/C][C]0.675479[/C][/ROW]
[ROW][C]181[/C][C]0.351933[/C][C]0.703866[/C][C]0.648067[/C][/ROW]
[ROW][C]182[/C][C]0.457075[/C][C]0.91415[/C][C]0.542925[/C][/ROW]
[ROW][C]183[/C][C]0.442109[/C][C]0.884218[/C][C]0.557891[/C][/ROW]
[ROW][C]184[/C][C]0.430623[/C][C]0.861246[/C][C]0.569377[/C][/ROW]
[ROW][C]185[/C][C]0.414062[/C][C]0.828123[/C][C]0.585938[/C][/ROW]
[ROW][C]186[/C][C]0.541229[/C][C]0.917541[/C][C]0.458771[/C][/ROW]
[ROW][C]187[/C][C]0.509243[/C][C]0.981514[/C][C]0.490757[/C][/ROW]
[ROW][C]188[/C][C]0.476517[/C][C]0.953033[/C][C]0.523483[/C][/ROW]
[ROW][C]189[/C][C]0.44028[/C][C]0.880561[/C][C]0.55972[/C][/ROW]
[ROW][C]190[/C][C]0.479035[/C][C]0.95807[/C][C]0.520965[/C][/ROW]
[ROW][C]191[/C][C]0.508453[/C][C]0.983095[/C][C]0.491547[/C][/ROW]
[ROW][C]192[/C][C]0.525413[/C][C]0.949174[/C][C]0.474587[/C][/ROW]
[ROW][C]193[/C][C]0.516161[/C][C]0.967677[/C][C]0.483839[/C][/ROW]
[ROW][C]194[/C][C]0.485352[/C][C]0.970704[/C][C]0.514648[/C][/ROW]
[ROW][C]195[/C][C]0.457547[/C][C]0.915095[/C][C]0.542453[/C][/ROW]
[ROW][C]196[/C][C]0.492815[/C][C]0.985631[/C][C]0.507185[/C][/ROW]
[ROW][C]197[/C][C]0.697394[/C][C]0.605212[/C][C]0.302606[/C][/ROW]
[ROW][C]198[/C][C]0.705509[/C][C]0.588982[/C][C]0.294491[/C][/ROW]
[ROW][C]199[/C][C]0.668872[/C][C]0.662256[/C][C]0.331128[/C][/ROW]
[ROW][C]200[/C][C]0.629352[/C][C]0.741296[/C][C]0.370648[/C][/ROW]
[ROW][C]201[/C][C]0.589026[/C][C]0.821947[/C][C]0.410974[/C][/ROW]
[ROW][C]202[/C][C]0.548229[/C][C]0.903543[/C][C]0.451771[/C][/ROW]
[ROW][C]203[/C][C]0.523546[/C][C]0.952907[/C][C]0.476454[/C][/ROW]
[ROW][C]204[/C][C]0.51932[/C][C]0.961359[/C][C]0.48068[/C][/ROW]
[ROW][C]205[/C][C]0.482068[/C][C]0.964136[/C][C]0.517932[/C][/ROW]
[ROW][C]206[/C][C]0.439446[/C][C]0.878892[/C][C]0.560554[/C][/ROW]
[ROW][C]207[/C][C]0.398253[/C][C]0.796505[/C][C]0.601747[/C][/ROW]
[ROW][C]208[/C][C]0.364843[/C][C]0.729686[/C][C]0.635157[/C][/ROW]
[ROW][C]209[/C][C]0.323766[/C][C]0.647532[/C][C]0.676234[/C][/ROW]
[ROW][C]210[/C][C]0.316433[/C][C]0.632865[/C][C]0.683567[/C][/ROW]
[ROW][C]211[/C][C]0.290911[/C][C]0.581822[/C][C]0.709089[/C][/ROW]
[ROW][C]212[/C][C]0.256579[/C][C]0.513159[/C][C]0.743421[/C][/ROW]
[ROW][C]213[/C][C]0.283707[/C][C]0.567415[/C][C]0.716293[/C][/ROW]
[ROW][C]214[/C][C]0.265942[/C][C]0.531884[/C][C]0.734058[/C][/ROW]
[ROW][C]215[/C][C]0.232972[/C][C]0.465944[/C][C]0.767028[/C][/ROW]
[ROW][C]216[/C][C]0.200263[/C][C]0.400526[/C][C]0.799737[/C][/ROW]
[ROW][C]217[/C][C]0.190139[/C][C]0.380279[/C][C]0.809861[/C][/ROW]
[ROW][C]218[/C][C]0.160492[/C][C]0.320984[/C][C]0.839508[/C][/ROW]
[ROW][C]219[/C][C]0.163497[/C][C]0.326993[/C][C]0.836503[/C][/ROW]
[ROW][C]220[/C][C]0.155155[/C][C]0.310311[/C][C]0.844845[/C][/ROW]
[ROW][C]221[/C][C]0.15412[/C][C]0.30824[/C][C]0.84588[/C][/ROW]
[ROW][C]222[/C][C]0.127538[/C][C]0.255076[/C][C]0.872462[/C][/ROW]
[ROW][C]223[/C][C]0.104922[/C][C]0.209843[/C][C]0.895078[/C][/ROW]
[ROW][C]224[/C][C]0.105839[/C][C]0.211679[/C][C]0.894161[/C][/ROW]
[ROW][C]225[/C][C]0.0957682[/C][C]0.191536[/C][C]0.904232[/C][/ROW]
[ROW][C]226[/C][C]0.0779803[/C][C]0.155961[/C][C]0.92202[/C][/ROW]
[ROW][C]227[/C][C]0.0607195[/C][C]0.121439[/C][C]0.93928[/C][/ROW]
[ROW][C]228[/C][C]0.0570001[/C][C]0.114[/C][C]0.943[/C][/ROW]
[ROW][C]229[/C][C]0.0771587[/C][C]0.154317[/C][C]0.922841[/C][/ROW]
[ROW][C]230[/C][C]0.0734351[/C][C]0.14687[/C][C]0.926565[/C][/ROW]
[ROW][C]231[/C][C]0.0565209[/C][C]0.113042[/C][C]0.943479[/C][/ROW]
[ROW][C]232[/C][C]0.0580222[/C][C]0.116044[/C][C]0.941978[/C][/ROW]
[ROW][C]233[/C][C]0.120775[/C][C]0.24155[/C][C]0.879225[/C][/ROW]
[ROW][C]234[/C][C]0.128517[/C][C]0.257035[/C][C]0.871483[/C][/ROW]
[ROW][C]235[/C][C]0.122187[/C][C]0.244374[/C][C]0.877813[/C][/ROW]
[ROW][C]236[/C][C]0.0951863[/C][C]0.190373[/C][C]0.904814[/C][/ROW]
[ROW][C]237[/C][C]0.123831[/C][C]0.247662[/C][C]0.876169[/C][/ROW]
[ROW][C]238[/C][C]0.168437[/C][C]0.336875[/C][C]0.831563[/C][/ROW]
[ROW][C]239[/C][C]0.270781[/C][C]0.541562[/C][C]0.729219[/C][/ROW]
[ROW][C]240[/C][C]0.26915[/C][C]0.538299[/C][C]0.73085[/C][/ROW]
[ROW][C]241[/C][C]0.223184[/C][C]0.446369[/C][C]0.776816[/C][/ROW]
[ROW][C]242[/C][C]0.271165[/C][C]0.542331[/C][C]0.728835[/C][/ROW]
[ROW][C]243[/C][C]0.211467[/C][C]0.422934[/C][C]0.788533[/C][/ROW]
[ROW][C]244[/C][C]0.158568[/C][C]0.317135[/C][C]0.841432[/C][/ROW]
[ROW][C]245[/C][C]0.23504[/C][C]0.470079[/C][C]0.76496[/C][/ROW]
[ROW][C]246[/C][C]0.256584[/C][C]0.513168[/C][C]0.743416[/C][/ROW]
[ROW][C]247[/C][C]0.189687[/C][C]0.379374[/C][C]0.810313[/C][/ROW]
[ROW][C]248[/C][C]0.23455[/C][C]0.4691[/C][C]0.76545[/C][/ROW]
[ROW][C]249[/C][C]0.344155[/C][C]0.688311[/C][C]0.655845[/C][/ROW]
[ROW][C]250[/C][C]0.247575[/C][C]0.495149[/C][C]0.752425[/C][/ROW]
[ROW][C]251[/C][C]0.278678[/C][C]0.557355[/C][C]0.721322[/C][/ROW]
[ROW][C]252[/C][C]0.909277[/C][C]0.181445[/C][C]0.0907227[/C][/ROW]
[ROW][C]253[/C][C]0.843076[/C][C]0.313847[/C][C]0.156924[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226612&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226612&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
110.4463280.8926560.553672
120.9522340.09553290.0477664
130.9458210.1083590.0541793
140.9597720.08045530.0402276
150.9360390.1279220.0639608
160.9012590.1974830.0987414
170.9501850.09962930.0498146
180.9322190.1355620.0677812
190.9571080.08578360.0428918
200.9376050.1247910.0623955
210.9265420.1469170.0734584
220.9218150.1563690.0781847
230.8944370.2111270.105563
240.875070.249860.12493
250.8366460.3267080.163354
260.8377230.3245530.162277
270.8488010.3023980.151199
280.8089630.3820730.191037
290.8402570.3194850.159743
300.8307680.3384640.169232
310.8365680.3268630.163432
320.8052950.3894110.194705
330.7742720.4514570.225728
340.7497870.5004250.250213
350.716310.5673790.28369
360.7506890.4986210.249311
370.8321420.3357170.167858
380.7970180.4059640.202982
390.7632040.4735920.236796
400.7628260.4743480.237174
410.7510930.4978150.248907
420.7375340.5249330.262466
430.7902790.4194420.209721
440.7550510.4898970.244949
450.7187060.5625880.281294
460.6928640.6142730.307136
470.7487030.5025940.251297
480.714860.5702810.28514
490.7683180.4633640.231682
500.7426770.5146470.257323
510.7306890.5386220.269311
520.6963510.6072980.303649
530.6985560.6028890.301444
540.6661090.6677820.333891
550.6781580.6436850.321842
560.6939830.6120350.306017
570.6716190.6567620.328381
580.7083310.5833380.291669
590.723330.5533410.27667
600.7001470.5997060.299853
610.7122490.5755010.287751
620.6757690.6484610.324231
630.652090.695820.34791
640.6120840.7758330.387916
650.571170.8576590.42883
660.5813680.8372630.418632
670.5841120.8317760.415888
680.5542640.8914730.445736
690.5135640.9728710.486436
700.4895370.9790740.510463
710.4507580.9015160.549242
720.4269950.8539910.573005
730.4002770.8005550.599723
740.3793880.7587770.620612
750.3495250.6990510.650475
760.5113810.9772390.488619
770.4901660.9803320.509834
780.5064320.9871370.493568
790.468180.936360.53182
800.5661950.8676090.433805
810.5293440.9413120.470656
820.5534280.8931430.446572
830.5170410.9659170.482959
840.4790580.9581160.520942
850.4411860.8823720.558814
860.4076290.8152570.592371
870.3757110.7514220.624289
880.3426720.6853440.657328
890.4330310.8660620.566969
900.4035110.8070220.596489
910.3749560.7499120.625044
920.3446890.6893790.655311
930.3444010.6888030.655599
940.313190.626380.68681
950.2804810.5609620.719519
960.2645880.5291750.735412
970.2419150.483830.758085
980.2154560.4309120.784544
990.2074790.4149580.792521
1000.1823280.3646560.817672
1010.171850.34370.82815
1020.1537130.3074270.846287
1030.1940610.3881230.805939
1040.2249140.4498270.775086
1050.2337290.4674590.766271
1060.2067240.4134480.793276
1070.2318870.4637740.768113
1080.2154440.4308880.784556
1090.3440330.6880660.655967
1100.3353860.6707730.664614
1110.3046270.6092540.695373
1120.2935580.5871150.706442
1130.2693810.5387620.730619
1140.250510.5010210.74949
1150.2235720.4471440.776428
1160.197590.3951810.80241
1170.1767880.3535770.823212
1180.2154230.4308450.784577
1190.2213570.4427140.778643
1200.197430.3948610.80257
1210.1823230.3646460.817677
1220.1614520.3229040.838548
1230.1906430.3812870.809357
1240.171640.3432810.82836
1250.1619490.3238990.838051
1260.1507610.3015220.849239
1270.1325750.2651490.867425
1280.1182260.2364520.881774
1290.1018590.2037180.898141
1300.100890.201780.89911
1310.1025620.2051230.897438
1320.0945480.1890960.905452
1330.08634470.1726890.913655
1340.07337990.146760.92662
1350.07485010.14970.92515
1360.1492240.2984470.850776
1370.1300290.2600580.869971
1380.1152080.2304160.884792
1390.1103980.2207960.889602
1400.1051490.2102980.894851
1410.1177750.2355510.882225
1420.1185330.2370650.881467
1430.1019430.2038870.898057
1440.08679030.1735810.91321
1450.07390060.1478010.926099
1460.06261180.1252240.937388
1470.06863010.137260.93137
1480.07478570.1495710.925214
1490.07027420.1405480.929726
1500.05970820.1194160.940292
1510.07280110.1456020.927199
1520.06989170.1397830.930108
1530.06854250.1370850.931457
1540.06373040.1274610.93627
1550.0709190.1418380.929081
1560.06046150.1209230.939538
1570.05050120.1010020.949499
1580.04306940.08613880.956931
1590.05236390.1047280.947636
1600.06526640.1305330.934734
1610.05582610.1116520.944174
1620.1230240.2460480.876976
1630.1124770.2249540.887523
1640.3959740.7919480.604026
1650.3788860.7577720.621114
1660.487090.974180.51291
1670.4550030.9100060.544997
1680.4232520.8465040.576748
1690.3870160.7740310.612984
1700.3651130.7302250.634887
1710.3749110.7498210.625089
1720.3401640.6803280.659836
1730.3835020.7670040.616498
1740.370750.74150.62925
1750.3485080.6970150.651492
1760.3850930.7701860.614907
1770.3591540.7183070.640846
1780.3716940.7433880.628306
1790.3568330.7136660.643167
1800.3245210.6490420.675479
1810.3519330.7038660.648067
1820.4570750.914150.542925
1830.4421090.8842180.557891
1840.4306230.8612460.569377
1850.4140620.8281230.585938
1860.5412290.9175410.458771
1870.5092430.9815140.490757
1880.4765170.9530330.523483
1890.440280.8805610.55972
1900.4790350.958070.520965
1910.5084530.9830950.491547
1920.5254130.9491740.474587
1930.5161610.9676770.483839
1940.4853520.9707040.514648
1950.4575470.9150950.542453
1960.4928150.9856310.507185
1970.6973940.6052120.302606
1980.7055090.5889820.294491
1990.6688720.6622560.331128
2000.6293520.7412960.370648
2010.5890260.8219470.410974
2020.5482290.9035430.451771
2030.5235460.9529070.476454
2040.519320.9613590.48068
2050.4820680.9641360.517932
2060.4394460.8788920.560554
2070.3982530.7965050.601747
2080.3648430.7296860.635157
2090.3237660.6475320.676234
2100.3164330.6328650.683567
2110.2909110.5818220.709089
2120.2565790.5131590.743421
2130.2837070.5674150.716293
2140.2659420.5318840.734058
2150.2329720.4659440.767028
2160.2002630.4005260.799737
2170.1901390.3802790.809861
2180.1604920.3209840.839508
2190.1634970.3269930.836503
2200.1551550.3103110.844845
2210.154120.308240.84588
2220.1275380.2550760.872462
2230.1049220.2098430.895078
2240.1058390.2116790.894161
2250.09576820.1915360.904232
2260.07798030.1559610.92202
2270.06071950.1214390.93928
2280.05700010.1140.943
2290.07715870.1543170.922841
2300.07343510.146870.926565
2310.05652090.1130420.943479
2320.05802220.1160440.941978
2330.1207750.241550.879225
2340.1285170.2570350.871483
2350.1221870.2443740.877813
2360.09518630.1903730.904814
2370.1238310.2476620.876169
2380.1684370.3368750.831563
2390.2707810.5415620.729219
2400.269150.5382990.73085
2410.2231840.4463690.776816
2420.2711650.5423310.728835
2430.2114670.4229340.788533
2440.1585680.3171350.841432
2450.235040.4700790.76496
2460.2565840.5131680.743416
2470.1896870.3793740.810313
2480.234550.46910.76545
2490.3441550.6883110.655845
2500.2475750.4951490.752425
2510.2786780.5573550.721322
2520.9092770.1814450.0907227
2530.8430760.3138470.156924






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 level50.0205761OK

\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 & 5 & 0.0205761 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226612&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]5[/C][C]0.0205761[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226612&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226612&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 level50.0205761OK


Figures (Output of Computation)

Figure 1
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Figure 2
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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 = 6 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 6 ; 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')
}