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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationThu, 14 Nov 2013 15:39:51 -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/14/t1384461620x0xgexa2191uode.htm/, Retrieved Mon, 29 Apr 2024 16:13:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=225425, Retrieved Mon, 29 Apr 2024 16:13:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- R P   [Multiple Regression] [] [2013-11-14 20:00:48] [4d39cf209776852399955073f9d0ee7a]
- R  D      [Multiple Regression] [] [2013-11-14 20:39:51] [a5501fab9c787febb2a952032c60b28f] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 14 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225425&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]14 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225425&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225425&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 time14 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Depression[t] = + 29.5953 -0.0329363Connected[t] + 0.00703234Separate[t] -0.0890917Learning[t] -0.0264338Software[t] -0.711344Happiness[t] -0.0559275Sport1[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Depression[t] =  +  29.5953 -0.0329363Connected[t] +  0.00703234Separate[t] -0.0890917Learning[t] -0.0264338Software[t] -0.711344Happiness[t] -0.0559275Sport1[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225425&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Depression[t] =  +  29.5953 -0.0329363Connected[t] +  0.00703234Separate[t] -0.0890917Learning[t] -0.0264338Software[t] -0.711344Happiness[t] -0.0559275Sport1[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225425&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225425&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] = + 29.5953 -0.0329363Connected[t] + 0.00703234Separate[t] -0.0890917Learning[t] -0.0264338Software[t] -0.711344Happiness[t] -0.0559275Sport1[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)29.59532.1249213.933.12232e-331.56116e-33
Connected-0.03293630.0511466-0.6440.5201760.260088
Separate0.007032340.05260890.13370.8937660.446883
Learning-0.08909170.0918052-0.97040.3327380.166369
Software-0.02643380.0945553-0.27960.7800410.39002
Happiness-0.7113440.0733965-9.6923.92391e-191.96196e-19
Sport1-0.05592750.0172933-3.2340.001380220.000690108

\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) & 29.5953 & 2.12492 & 13.93 & 3.12232e-33 & 1.56116e-33 \tabularnewline
Connected & -0.0329363 & 0.0511466 & -0.644 & 0.520176 & 0.260088 \tabularnewline
Separate & 0.00703234 & 0.0526089 & 0.1337 & 0.893766 & 0.446883 \tabularnewline
Learning & -0.0890917 & 0.0918052 & -0.9704 & 0.332738 & 0.166369 \tabularnewline
Software & -0.0264338 & 0.0945553 & -0.2796 & 0.780041 & 0.39002 \tabularnewline
Happiness & -0.711344 & 0.0733965 & -9.692 & 3.92391e-19 & 1.96196e-19 \tabularnewline
Sport1 & -0.0559275 & 0.0172933 & -3.234 & 0.00138022 & 0.000690108 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225425&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]29.5953[/C][C]2.12492[/C][C]13.93[/C][C]3.12232e-33[/C][C]1.56116e-33[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0329363[/C][C]0.0511466[/C][C]-0.644[/C][C]0.520176[/C][C]0.260088[/C][/ROW]
[ROW][C]Separate[/C][C]0.00703234[/C][C]0.0526089[/C][C]0.1337[/C][C]0.893766[/C][C]0.446883[/C][/ROW]
[ROW][C]Learning[/C][C]-0.0890917[/C][C]0.0918052[/C][C]-0.9704[/C][C]0.332738[/C][C]0.166369[/C][/ROW]
[ROW][C]Software[/C][C]-0.0264338[/C][C]0.0945553[/C][C]-0.2796[/C][C]0.780041[/C][C]0.39002[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.711344[/C][C]0.0733965[/C][C]-9.692[/C][C]3.92391e-19[/C][C]1.96196e-19[/C][/ROW]
[ROW][C]Sport1[/C][C]-0.0559275[/C][C]0.0172933[/C][C]-3.234[/C][C]0.00138022[/C][C]0.000690108[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225425&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225425&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)29.59532.1249213.933.12232e-331.56116e-33
Connected-0.03293630.0511466-0.6440.5201760.260088
Separate0.007032340.05260890.13370.8937660.446883
Learning-0.08909170.0918052-0.97040.3327380.166369
Software-0.02643380.0945553-0.27960.7800410.39002
Happiness-0.7113440.0733965-9.6923.92391e-191.96196e-19
Sport1-0.05592750.0172933-3.2340.001380220.000690108






Multiple Linear Regression - Regression Statistics
Multiple R0.61274
R-squared0.37545
Adjusted R-squared0.360869
F-TEST (value)25.7494
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.77376
Sum Squared Residuals1977.3

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.61274 \tabularnewline
R-squared & 0.37545 \tabularnewline
Adjusted R-squared & 0.360869 \tabularnewline
F-TEST (value) & 25.7494 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 257 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.77376 \tabularnewline
Sum Squared Residuals & 1977.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225425&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.61274[/C][/ROW]
[ROW][C]R-squared[/C][C]0.37545[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.360869[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]25.7494[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]257[/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]2.77376[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1977.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225425&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225425&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 R0.61274
R-squared0.37545
Adjusted R-squared0.360869
F-TEST (value)25.7494
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.77376
Sum Squared Residuals1977.3






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11214.1138-2.11377
2119.373411.62659
31415.2481-1.24809
41215.0281-3.02809
52111.51279.48726
61210.05741.9426
72213.59598.40414
81112.5892-1.58916
91012.2824-2.28244
101312.1490.851045
111010.3608-0.360797
12810.3704-2.3704
131515.9866-0.986595
141412.46021.53982
15109.187650.812351
161413.91720.082788
171412.88051.11946
18119.497441.50256
191013.1454-3.14541
201312.45430.545672
219.510.5618-1.06176
221415.4217-1.42175
231213.5627-1.56273
241415.2666-1.26661
25119.801441.19856
26915.7355-6.73545
271111.3339-0.333925
281513.24431.75566
291411.96532.03471
301315.624-2.62398
31911.283-2.28299
321515.3829-0.382925
331011.0193-1.01934
341111.6249-0.624919
351313.0245-0.0244947
36812.3451-4.34509
372017.80382.1962
381212.4362-0.436158
391010.825-0.825006
401013.8783-3.87832
41912.1031-3.10309
421411.5672.43302
43811.9888-3.98882
441415.7186-1.71861
451112.4998-1.49985
461315.6977-2.69772
47912.7216-3.72161
481112.2556-1.25563
491510.72914.2709
501113.5622-2.56223
511011.6047-1.60474
521413.53470.465273
531816.03891.96112
541414.97-0.969953
551115.7728-4.77282
5614.512.29632.20375
571311.28711.71293
58912.7193-3.71927
591014.3838-4.38384
601514.54080.459231
612018.89511.10493
621213.2863-1.28626
631214.6271-2.62707
641414.4153-0.415303
651313.2605-0.260549
661115.2569-4.25689
671715.1661.834
681214.2838-2.28382
691313.0122-0.0121782
701412.43091.56911
711313.7885-0.788538
721512.90192.09814
731311.57571.42428
741012.1292-2.12916
751112.9773-1.97728
761913.7595.24104
771310.862.14003
781713.87083.12924
791312.43910.56089
80914.5563-5.5563
811111.9305-0.93046
82912.319-3.31904
831211.49090.509069
841212.4563-0.45635
851312.77140.228635
861312.26810.731929
871213.187-1.18701
881514.8550.145049
892218.19263.80745
901311.34491.65512
911514.4560.543997
921312.01160.988396
931512.53982.46021
9412.513.654-1.15405
951111.0184-0.018439
961614.45861.54144
971112.676-1.676
981110.25010.749892
991012.3622-2.36223
1001010.458-0.458006
1011614.28771.71229
1021210.35611.64389
1031115.5951-4.5951
1041611.9784.02201
1051916.82232.17768
1061111.1261-0.126093
1071612.13553.86451
1081516.806-1.80596
1092417.53426.46585
1101411.67962.32036
1111515.0474-0.047381
1121112.8552-1.85524
1131515.2404-0.240378
1141210.22761.77236
1151010.4631-0.463133
1161414.2199-0.21987
1171313.592-0.592045
118913.4878-4.48776
1191511.86193.13808
1201515.7634-0.76342
1211412.78571.21427
1221111.4949-0.494876
123811.9277-3.92769
1241112.1947-1.19471
1251113.3186-2.31862
12689.80878-1.80878
1271010.3835-0.38355
128119.141621.85838
1291312.61780.382216
1301113.8653-2.86527
1312017.62312.37688
1321011.9245-1.92453
1331513.25171.74833
1341212.2706-0.270601
1351410.95643.04365
1362316.58686.41317
1371413.61220.387799
1381616.7641-0.764125
1391113.1515-2.15154
1401214.496-2.49602
1411013.4533-3.45325
1421411.21372.78629
1431212.1737-0.173696
1441212.0432-0.0432014
1451111.0344-0.0344116
1461211.15190.848073
1471316.0069-3.00692
1481114.286-3.28598
1491916.78672.21334
1501211.40670.593313
1511713.12643.87359
152911.727-2.72697
1531214.5698-2.56981
1541916.8632.13703
1551814.01423.9858
1561514.4560.543997
1571413.66690.333075
158119.141621.85838
159913.0389-4.03888
1601814.2943.70604
1611614.25251.7475
1622416.66177.33833
1631412.98761.0124
1642010.72369.2764
1651816.00881.99121
1662317.06855.93146
1671212.9801-0.980061
1681414.9428-0.942786
1691616.2791-0.279144
1701816.73871.26126
1712016.49263.50741
1721211.51880.481168
1731216.3932-4.39316
1741715.28191.7181
1751311.81191.18809
176913.5505-4.55051
1771617.123-1.12299
1781815.1162.88395
1791012.152-2.15201
1801415.3335-1.33349
1811113.9412-2.94118
182914.5203-5.52027
1831112.1531-1.1531
1841012.4822-2.48216
1851111.6786-0.678616
1861913.55395.44613
1871412.74591.25409
1881211.73880.261203
1891415.4374-1.43738
1902116.4464.55404
1911317.28-4.27998
1921012.729-2.72896
1931513.09581.90415
1941615.69420.305804
1951412.64691.3531
1961214.5393-2.53925
1971912.6536.34699
1981512.20142.79858
1991918.0970.902978
2001313.6674-0.667428
2011716.81440.185587
2021212.975-0.975019
2031111.1881-0.188145
2041415.0466-1.04664
2051112.5027-1.50271
2061312.29270.707313
2071212.2738-0.273833
2081512.66332.33671
2091414.2349-0.234915
2101211.02740.972595
2111717.3398-0.339769
2121111.0886-0.0886144
2131814.4983.50203
2141315.7527-2.75269
2151715.37411.62594
2161313.0318-0.0318217
2171110.10250.897482
2181212.4375-0.437463
2192218.18373.81627
2201411.77412.22594
2211215.1239-3.12392
2221212.46-0.459963
2231715.93961.06037
224912.7954-3.79536
2252118.80522.19481
2261012.1793-2.17932
2271110.75210.247934
2281215.2028-3.20275
2292318.10774.89235
2301315.6749-2.67488
2311213.44-1.43997
2321617.4711-1.47114
233913.2824-4.28241
2341713.2293.771
235911.8697-2.86969
2361415.6435-1.64354
2371715.2861.71396
2381315.0802-2.08022
2391115.9753-4.97526
2401215.6601-3.66011
2411014.1927-4.19274
2421918.67390.326123
2431616.1198-0.119846
2441615.13050.869543
2451411.73772.26227
2462015.92194.07807
2471514.25170.748261
2482315.08627.91382
2492017.59122.40876
2501616.237-0.236992
2511413.06320.936757
2521714.04772.95233
2531114.2027-3.20266
2541313.7958-0.795812
2551714.93612.06391
2561514.88620.113795
2572116.36344.63661
2581817.4710.529048
2591512.74952.25051
260816.4624-8.46241
2611213.7517-1.75167
2621212.9722-0.972249
2632218.91913.08095
2641213.3944-1.3944

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 14.1138 & -2.11377 \tabularnewline
2 & 11 & 9.37341 & 1.62659 \tabularnewline
3 & 14 & 15.2481 & -1.24809 \tabularnewline
4 & 12 & 15.0281 & -3.02809 \tabularnewline
5 & 21 & 11.5127 & 9.48726 \tabularnewline
6 & 12 & 10.0574 & 1.9426 \tabularnewline
7 & 22 & 13.5959 & 8.40414 \tabularnewline
8 & 11 & 12.5892 & -1.58916 \tabularnewline
9 & 10 & 12.2824 & -2.28244 \tabularnewline
10 & 13 & 12.149 & 0.851045 \tabularnewline
11 & 10 & 10.3608 & -0.360797 \tabularnewline
12 & 8 & 10.3704 & -2.3704 \tabularnewline
13 & 15 & 15.9866 & -0.986595 \tabularnewline
14 & 14 & 12.4602 & 1.53982 \tabularnewline
15 & 10 & 9.18765 & 0.812351 \tabularnewline
16 & 14 & 13.9172 & 0.082788 \tabularnewline
17 & 14 & 12.8805 & 1.11946 \tabularnewline
18 & 11 & 9.49744 & 1.50256 \tabularnewline
19 & 10 & 13.1454 & -3.14541 \tabularnewline
20 & 13 & 12.4543 & 0.545672 \tabularnewline
21 & 9.5 & 10.5618 & -1.06176 \tabularnewline
22 & 14 & 15.4217 & -1.42175 \tabularnewline
23 & 12 & 13.5627 & -1.56273 \tabularnewline
24 & 14 & 15.2666 & -1.26661 \tabularnewline
25 & 11 & 9.80144 & 1.19856 \tabularnewline
26 & 9 & 15.7355 & -6.73545 \tabularnewline
27 & 11 & 11.3339 & -0.333925 \tabularnewline
28 & 15 & 13.2443 & 1.75566 \tabularnewline
29 & 14 & 11.9653 & 2.03471 \tabularnewline
30 & 13 & 15.624 & -2.62398 \tabularnewline
31 & 9 & 11.283 & -2.28299 \tabularnewline
32 & 15 & 15.3829 & -0.382925 \tabularnewline
33 & 10 & 11.0193 & -1.01934 \tabularnewline
34 & 11 & 11.6249 & -0.624919 \tabularnewline
35 & 13 & 13.0245 & -0.0244947 \tabularnewline
36 & 8 & 12.3451 & -4.34509 \tabularnewline
37 & 20 & 17.8038 & 2.1962 \tabularnewline
38 & 12 & 12.4362 & -0.436158 \tabularnewline
39 & 10 & 10.825 & -0.825006 \tabularnewline
40 & 10 & 13.8783 & -3.87832 \tabularnewline
41 & 9 & 12.1031 & -3.10309 \tabularnewline
42 & 14 & 11.567 & 2.43302 \tabularnewline
43 & 8 & 11.9888 & -3.98882 \tabularnewline
44 & 14 & 15.7186 & -1.71861 \tabularnewline
45 & 11 & 12.4998 & -1.49985 \tabularnewline
46 & 13 & 15.6977 & -2.69772 \tabularnewline
47 & 9 & 12.7216 & -3.72161 \tabularnewline
48 & 11 & 12.2556 & -1.25563 \tabularnewline
49 & 15 & 10.7291 & 4.2709 \tabularnewline
50 & 11 & 13.5622 & -2.56223 \tabularnewline
51 & 10 & 11.6047 & -1.60474 \tabularnewline
52 & 14 & 13.5347 & 0.465273 \tabularnewline
53 & 18 & 16.0389 & 1.96112 \tabularnewline
54 & 14 & 14.97 & -0.969953 \tabularnewline
55 & 11 & 15.7728 & -4.77282 \tabularnewline
56 & 14.5 & 12.2963 & 2.20375 \tabularnewline
57 & 13 & 11.2871 & 1.71293 \tabularnewline
58 & 9 & 12.7193 & -3.71927 \tabularnewline
59 & 10 & 14.3838 & -4.38384 \tabularnewline
60 & 15 & 14.5408 & 0.459231 \tabularnewline
61 & 20 & 18.8951 & 1.10493 \tabularnewline
62 & 12 & 13.2863 & -1.28626 \tabularnewline
63 & 12 & 14.6271 & -2.62707 \tabularnewline
64 & 14 & 14.4153 & -0.415303 \tabularnewline
65 & 13 & 13.2605 & -0.260549 \tabularnewline
66 & 11 & 15.2569 & -4.25689 \tabularnewline
67 & 17 & 15.166 & 1.834 \tabularnewline
68 & 12 & 14.2838 & -2.28382 \tabularnewline
69 & 13 & 13.0122 & -0.0121782 \tabularnewline
70 & 14 & 12.4309 & 1.56911 \tabularnewline
71 & 13 & 13.7885 & -0.788538 \tabularnewline
72 & 15 & 12.9019 & 2.09814 \tabularnewline
73 & 13 & 11.5757 & 1.42428 \tabularnewline
74 & 10 & 12.1292 & -2.12916 \tabularnewline
75 & 11 & 12.9773 & -1.97728 \tabularnewline
76 & 19 & 13.759 & 5.24104 \tabularnewline
77 & 13 & 10.86 & 2.14003 \tabularnewline
78 & 17 & 13.8708 & 3.12924 \tabularnewline
79 & 13 & 12.4391 & 0.56089 \tabularnewline
80 & 9 & 14.5563 & -5.5563 \tabularnewline
81 & 11 & 11.9305 & -0.93046 \tabularnewline
82 & 9 & 12.319 & -3.31904 \tabularnewline
83 & 12 & 11.4909 & 0.509069 \tabularnewline
84 & 12 & 12.4563 & -0.45635 \tabularnewline
85 & 13 & 12.7714 & 0.228635 \tabularnewline
86 & 13 & 12.2681 & 0.731929 \tabularnewline
87 & 12 & 13.187 & -1.18701 \tabularnewline
88 & 15 & 14.855 & 0.145049 \tabularnewline
89 & 22 & 18.1926 & 3.80745 \tabularnewline
90 & 13 & 11.3449 & 1.65512 \tabularnewline
91 & 15 & 14.456 & 0.543997 \tabularnewline
92 & 13 & 12.0116 & 0.988396 \tabularnewline
93 & 15 & 12.5398 & 2.46021 \tabularnewline
94 & 12.5 & 13.654 & -1.15405 \tabularnewline
95 & 11 & 11.0184 & -0.018439 \tabularnewline
96 & 16 & 14.4586 & 1.54144 \tabularnewline
97 & 11 & 12.676 & -1.676 \tabularnewline
98 & 11 & 10.2501 & 0.749892 \tabularnewline
99 & 10 & 12.3622 & -2.36223 \tabularnewline
100 & 10 & 10.458 & -0.458006 \tabularnewline
101 & 16 & 14.2877 & 1.71229 \tabularnewline
102 & 12 & 10.3561 & 1.64389 \tabularnewline
103 & 11 & 15.5951 & -4.5951 \tabularnewline
104 & 16 & 11.978 & 4.02201 \tabularnewline
105 & 19 & 16.8223 & 2.17768 \tabularnewline
106 & 11 & 11.1261 & -0.126093 \tabularnewline
107 & 16 & 12.1355 & 3.86451 \tabularnewline
108 & 15 & 16.806 & -1.80596 \tabularnewline
109 & 24 & 17.5342 & 6.46585 \tabularnewline
110 & 14 & 11.6796 & 2.32036 \tabularnewline
111 & 15 & 15.0474 & -0.047381 \tabularnewline
112 & 11 & 12.8552 & -1.85524 \tabularnewline
113 & 15 & 15.2404 & -0.240378 \tabularnewline
114 & 12 & 10.2276 & 1.77236 \tabularnewline
115 & 10 & 10.4631 & -0.463133 \tabularnewline
116 & 14 & 14.2199 & -0.21987 \tabularnewline
117 & 13 & 13.592 & -0.592045 \tabularnewline
118 & 9 & 13.4878 & -4.48776 \tabularnewline
119 & 15 & 11.8619 & 3.13808 \tabularnewline
120 & 15 & 15.7634 & -0.76342 \tabularnewline
121 & 14 & 12.7857 & 1.21427 \tabularnewline
122 & 11 & 11.4949 & -0.494876 \tabularnewline
123 & 8 & 11.9277 & -3.92769 \tabularnewline
124 & 11 & 12.1947 & -1.19471 \tabularnewline
125 & 11 & 13.3186 & -2.31862 \tabularnewline
126 & 8 & 9.80878 & -1.80878 \tabularnewline
127 & 10 & 10.3835 & -0.38355 \tabularnewline
128 & 11 & 9.14162 & 1.85838 \tabularnewline
129 & 13 & 12.6178 & 0.382216 \tabularnewline
130 & 11 & 13.8653 & -2.86527 \tabularnewline
131 & 20 & 17.6231 & 2.37688 \tabularnewline
132 & 10 & 11.9245 & -1.92453 \tabularnewline
133 & 15 & 13.2517 & 1.74833 \tabularnewline
134 & 12 & 12.2706 & -0.270601 \tabularnewline
135 & 14 & 10.9564 & 3.04365 \tabularnewline
136 & 23 & 16.5868 & 6.41317 \tabularnewline
137 & 14 & 13.6122 & 0.387799 \tabularnewline
138 & 16 & 16.7641 & -0.764125 \tabularnewline
139 & 11 & 13.1515 & -2.15154 \tabularnewline
140 & 12 & 14.496 & -2.49602 \tabularnewline
141 & 10 & 13.4533 & -3.45325 \tabularnewline
142 & 14 & 11.2137 & 2.78629 \tabularnewline
143 & 12 & 12.1737 & -0.173696 \tabularnewline
144 & 12 & 12.0432 & -0.0432014 \tabularnewline
145 & 11 & 11.0344 & -0.0344116 \tabularnewline
146 & 12 & 11.1519 & 0.848073 \tabularnewline
147 & 13 & 16.0069 & -3.00692 \tabularnewline
148 & 11 & 14.286 & -3.28598 \tabularnewline
149 & 19 & 16.7867 & 2.21334 \tabularnewline
150 & 12 & 11.4067 & 0.593313 \tabularnewline
151 & 17 & 13.1264 & 3.87359 \tabularnewline
152 & 9 & 11.727 & -2.72697 \tabularnewline
153 & 12 & 14.5698 & -2.56981 \tabularnewline
154 & 19 & 16.863 & 2.13703 \tabularnewline
155 & 18 & 14.0142 & 3.9858 \tabularnewline
156 & 15 & 14.456 & 0.543997 \tabularnewline
157 & 14 & 13.6669 & 0.333075 \tabularnewline
158 & 11 & 9.14162 & 1.85838 \tabularnewline
159 & 9 & 13.0389 & -4.03888 \tabularnewline
160 & 18 & 14.294 & 3.70604 \tabularnewline
161 & 16 & 14.2525 & 1.7475 \tabularnewline
162 & 24 & 16.6617 & 7.33833 \tabularnewline
163 & 14 & 12.9876 & 1.0124 \tabularnewline
164 & 20 & 10.7236 & 9.2764 \tabularnewline
165 & 18 & 16.0088 & 1.99121 \tabularnewline
166 & 23 & 17.0685 & 5.93146 \tabularnewline
167 & 12 & 12.9801 & -0.980061 \tabularnewline
168 & 14 & 14.9428 & -0.942786 \tabularnewline
169 & 16 & 16.2791 & -0.279144 \tabularnewline
170 & 18 & 16.7387 & 1.26126 \tabularnewline
171 & 20 & 16.4926 & 3.50741 \tabularnewline
172 & 12 & 11.5188 & 0.481168 \tabularnewline
173 & 12 & 16.3932 & -4.39316 \tabularnewline
174 & 17 & 15.2819 & 1.7181 \tabularnewline
175 & 13 & 11.8119 & 1.18809 \tabularnewline
176 & 9 & 13.5505 & -4.55051 \tabularnewline
177 & 16 & 17.123 & -1.12299 \tabularnewline
178 & 18 & 15.116 & 2.88395 \tabularnewline
179 & 10 & 12.152 & -2.15201 \tabularnewline
180 & 14 & 15.3335 & -1.33349 \tabularnewline
181 & 11 & 13.9412 & -2.94118 \tabularnewline
182 & 9 & 14.5203 & -5.52027 \tabularnewline
183 & 11 & 12.1531 & -1.1531 \tabularnewline
184 & 10 & 12.4822 & -2.48216 \tabularnewline
185 & 11 & 11.6786 & -0.678616 \tabularnewline
186 & 19 & 13.5539 & 5.44613 \tabularnewline
187 & 14 & 12.7459 & 1.25409 \tabularnewline
188 & 12 & 11.7388 & 0.261203 \tabularnewline
189 & 14 & 15.4374 & -1.43738 \tabularnewline
190 & 21 & 16.446 & 4.55404 \tabularnewline
191 & 13 & 17.28 & -4.27998 \tabularnewline
192 & 10 & 12.729 & -2.72896 \tabularnewline
193 & 15 & 13.0958 & 1.90415 \tabularnewline
194 & 16 & 15.6942 & 0.305804 \tabularnewline
195 & 14 & 12.6469 & 1.3531 \tabularnewline
196 & 12 & 14.5393 & -2.53925 \tabularnewline
197 & 19 & 12.653 & 6.34699 \tabularnewline
198 & 15 & 12.2014 & 2.79858 \tabularnewline
199 & 19 & 18.097 & 0.902978 \tabularnewline
200 & 13 & 13.6674 & -0.667428 \tabularnewline
201 & 17 & 16.8144 & 0.185587 \tabularnewline
202 & 12 & 12.975 & -0.975019 \tabularnewline
203 & 11 & 11.1881 & -0.188145 \tabularnewline
204 & 14 & 15.0466 & -1.04664 \tabularnewline
205 & 11 & 12.5027 & -1.50271 \tabularnewline
206 & 13 & 12.2927 & 0.707313 \tabularnewline
207 & 12 & 12.2738 & -0.273833 \tabularnewline
208 & 15 & 12.6633 & 2.33671 \tabularnewline
209 & 14 & 14.2349 & -0.234915 \tabularnewline
210 & 12 & 11.0274 & 0.972595 \tabularnewline
211 & 17 & 17.3398 & -0.339769 \tabularnewline
212 & 11 & 11.0886 & -0.0886144 \tabularnewline
213 & 18 & 14.498 & 3.50203 \tabularnewline
214 & 13 & 15.7527 & -2.75269 \tabularnewline
215 & 17 & 15.3741 & 1.62594 \tabularnewline
216 & 13 & 13.0318 & -0.0318217 \tabularnewline
217 & 11 & 10.1025 & 0.897482 \tabularnewline
218 & 12 & 12.4375 & -0.437463 \tabularnewline
219 & 22 & 18.1837 & 3.81627 \tabularnewline
220 & 14 & 11.7741 & 2.22594 \tabularnewline
221 & 12 & 15.1239 & -3.12392 \tabularnewline
222 & 12 & 12.46 & -0.459963 \tabularnewline
223 & 17 & 15.9396 & 1.06037 \tabularnewline
224 & 9 & 12.7954 & -3.79536 \tabularnewline
225 & 21 & 18.8052 & 2.19481 \tabularnewline
226 & 10 & 12.1793 & -2.17932 \tabularnewline
227 & 11 & 10.7521 & 0.247934 \tabularnewline
228 & 12 & 15.2028 & -3.20275 \tabularnewline
229 & 23 & 18.1077 & 4.89235 \tabularnewline
230 & 13 & 15.6749 & -2.67488 \tabularnewline
231 & 12 & 13.44 & -1.43997 \tabularnewline
232 & 16 & 17.4711 & -1.47114 \tabularnewline
233 & 9 & 13.2824 & -4.28241 \tabularnewline
234 & 17 & 13.229 & 3.771 \tabularnewline
235 & 9 & 11.8697 & -2.86969 \tabularnewline
236 & 14 & 15.6435 & -1.64354 \tabularnewline
237 & 17 & 15.286 & 1.71396 \tabularnewline
238 & 13 & 15.0802 & -2.08022 \tabularnewline
239 & 11 & 15.9753 & -4.97526 \tabularnewline
240 & 12 & 15.6601 & -3.66011 \tabularnewline
241 & 10 & 14.1927 & -4.19274 \tabularnewline
242 & 19 & 18.6739 & 0.326123 \tabularnewline
243 & 16 & 16.1198 & -0.119846 \tabularnewline
244 & 16 & 15.1305 & 0.869543 \tabularnewline
245 & 14 & 11.7377 & 2.26227 \tabularnewline
246 & 20 & 15.9219 & 4.07807 \tabularnewline
247 & 15 & 14.2517 & 0.748261 \tabularnewline
248 & 23 & 15.0862 & 7.91382 \tabularnewline
249 & 20 & 17.5912 & 2.40876 \tabularnewline
250 & 16 & 16.237 & -0.236992 \tabularnewline
251 & 14 & 13.0632 & 0.936757 \tabularnewline
252 & 17 & 14.0477 & 2.95233 \tabularnewline
253 & 11 & 14.2027 & -3.20266 \tabularnewline
254 & 13 & 13.7958 & -0.795812 \tabularnewline
255 & 17 & 14.9361 & 2.06391 \tabularnewline
256 & 15 & 14.8862 & 0.113795 \tabularnewline
257 & 21 & 16.3634 & 4.63661 \tabularnewline
258 & 18 & 17.471 & 0.529048 \tabularnewline
259 & 15 & 12.7495 & 2.25051 \tabularnewline
260 & 8 & 16.4624 & -8.46241 \tabularnewline
261 & 12 & 13.7517 & -1.75167 \tabularnewline
262 & 12 & 12.9722 & -0.972249 \tabularnewline
263 & 22 & 18.9191 & 3.08095 \tabularnewline
264 & 12 & 13.3944 & -1.3944 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225425&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]14.1138[/C][C]-2.11377[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]9.37341[/C][C]1.62659[/C][/ROW]
[ROW][C]3[/C][C]14[/C][C]15.2481[/C][C]-1.24809[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]15.0281[/C][C]-3.02809[/C][/ROW]
[ROW][C]5[/C][C]21[/C][C]11.5127[/C][C]9.48726[/C][/ROW]
[ROW][C]6[/C][C]12[/C][C]10.0574[/C][C]1.9426[/C][/ROW]
[ROW][C]7[/C][C]22[/C][C]13.5959[/C][C]8.40414[/C][/ROW]
[ROW][C]8[/C][C]11[/C][C]12.5892[/C][C]-1.58916[/C][/ROW]
[ROW][C]9[/C][C]10[/C][C]12.2824[/C][C]-2.28244[/C][/ROW]
[ROW][C]10[/C][C]13[/C][C]12.149[/C][C]0.851045[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]10.3608[/C][C]-0.360797[/C][/ROW]
[ROW][C]12[/C][C]8[/C][C]10.3704[/C][C]-2.3704[/C][/ROW]
[ROW][C]13[/C][C]15[/C][C]15.9866[/C][C]-0.986595[/C][/ROW]
[ROW][C]14[/C][C]14[/C][C]12.4602[/C][C]1.53982[/C][/ROW]
[ROW][C]15[/C][C]10[/C][C]9.18765[/C][C]0.812351[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.9172[/C][C]0.082788[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]12.8805[/C][C]1.11946[/C][/ROW]
[ROW][C]18[/C][C]11[/C][C]9.49744[/C][C]1.50256[/C][/ROW]
[ROW][C]19[/C][C]10[/C][C]13.1454[/C][C]-3.14541[/C][/ROW]
[ROW][C]20[/C][C]13[/C][C]12.4543[/C][C]0.545672[/C][/ROW]
[ROW][C]21[/C][C]9.5[/C][C]10.5618[/C][C]-1.06176[/C][/ROW]
[ROW][C]22[/C][C]14[/C][C]15.4217[/C][C]-1.42175[/C][/ROW]
[ROW][C]23[/C][C]12[/C][C]13.5627[/C][C]-1.56273[/C][/ROW]
[ROW][C]24[/C][C]14[/C][C]15.2666[/C][C]-1.26661[/C][/ROW]
[ROW][C]25[/C][C]11[/C][C]9.80144[/C][C]1.19856[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.7355[/C][C]-6.73545[/C][/ROW]
[ROW][C]27[/C][C]11[/C][C]11.3339[/C][C]-0.333925[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]13.2443[/C][C]1.75566[/C][/ROW]
[ROW][C]29[/C][C]14[/C][C]11.9653[/C][C]2.03471[/C][/ROW]
[ROW][C]30[/C][C]13[/C][C]15.624[/C][C]-2.62398[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]11.283[/C][C]-2.28299[/C][/ROW]
[ROW][C]32[/C][C]15[/C][C]15.3829[/C][C]-0.382925[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]11.0193[/C][C]-1.01934[/C][/ROW]
[ROW][C]34[/C][C]11[/C][C]11.6249[/C][C]-0.624919[/C][/ROW]
[ROW][C]35[/C][C]13[/C][C]13.0245[/C][C]-0.0244947[/C][/ROW]
[ROW][C]36[/C][C]8[/C][C]12.3451[/C][C]-4.34509[/C][/ROW]
[ROW][C]37[/C][C]20[/C][C]17.8038[/C][C]2.1962[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]12.4362[/C][C]-0.436158[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]10.825[/C][C]-0.825006[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]13.8783[/C][C]-3.87832[/C][/ROW]
[ROW][C]41[/C][C]9[/C][C]12.1031[/C][C]-3.10309[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]11.567[/C][C]2.43302[/C][/ROW]
[ROW][C]43[/C][C]8[/C][C]11.9888[/C][C]-3.98882[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]15.7186[/C][C]-1.71861[/C][/ROW]
[ROW][C]45[/C][C]11[/C][C]12.4998[/C][C]-1.49985[/C][/ROW]
[ROW][C]46[/C][C]13[/C][C]15.6977[/C][C]-2.69772[/C][/ROW]
[ROW][C]47[/C][C]9[/C][C]12.7216[/C][C]-3.72161[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]12.2556[/C][C]-1.25563[/C][/ROW]
[ROW][C]49[/C][C]15[/C][C]10.7291[/C][C]4.2709[/C][/ROW]
[ROW][C]50[/C][C]11[/C][C]13.5622[/C][C]-2.56223[/C][/ROW]
[ROW][C]51[/C][C]10[/C][C]11.6047[/C][C]-1.60474[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.5347[/C][C]0.465273[/C][/ROW]
[ROW][C]53[/C][C]18[/C][C]16.0389[/C][C]1.96112[/C][/ROW]
[ROW][C]54[/C][C]14[/C][C]14.97[/C][C]-0.969953[/C][/ROW]
[ROW][C]55[/C][C]11[/C][C]15.7728[/C][C]-4.77282[/C][/ROW]
[ROW][C]56[/C][C]14.5[/C][C]12.2963[/C][C]2.20375[/C][/ROW]
[ROW][C]57[/C][C]13[/C][C]11.2871[/C][C]1.71293[/C][/ROW]
[ROW][C]58[/C][C]9[/C][C]12.7193[/C][C]-3.71927[/C][/ROW]
[ROW][C]59[/C][C]10[/C][C]14.3838[/C][C]-4.38384[/C][/ROW]
[ROW][C]60[/C][C]15[/C][C]14.5408[/C][C]0.459231[/C][/ROW]
[ROW][C]61[/C][C]20[/C][C]18.8951[/C][C]1.10493[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]13.2863[/C][C]-1.28626[/C][/ROW]
[ROW][C]63[/C][C]12[/C][C]14.6271[/C][C]-2.62707[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.4153[/C][C]-0.415303[/C][/ROW]
[ROW][C]65[/C][C]13[/C][C]13.2605[/C][C]-0.260549[/C][/ROW]
[ROW][C]66[/C][C]11[/C][C]15.2569[/C][C]-4.25689[/C][/ROW]
[ROW][C]67[/C][C]17[/C][C]15.166[/C][C]1.834[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.2838[/C][C]-2.28382[/C][/ROW]
[ROW][C]69[/C][C]13[/C][C]13.0122[/C][C]-0.0121782[/C][/ROW]
[ROW][C]70[/C][C]14[/C][C]12.4309[/C][C]1.56911[/C][/ROW]
[ROW][C]71[/C][C]13[/C][C]13.7885[/C][C]-0.788538[/C][/ROW]
[ROW][C]72[/C][C]15[/C][C]12.9019[/C][C]2.09814[/C][/ROW]
[ROW][C]73[/C][C]13[/C][C]11.5757[/C][C]1.42428[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]12.1292[/C][C]-2.12916[/C][/ROW]
[ROW][C]75[/C][C]11[/C][C]12.9773[/C][C]-1.97728[/C][/ROW]
[ROW][C]76[/C][C]19[/C][C]13.759[/C][C]5.24104[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]10.86[/C][C]2.14003[/C][/ROW]
[ROW][C]78[/C][C]17[/C][C]13.8708[/C][C]3.12924[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]12.4391[/C][C]0.56089[/C][/ROW]
[ROW][C]80[/C][C]9[/C][C]14.5563[/C][C]-5.5563[/C][/ROW]
[ROW][C]81[/C][C]11[/C][C]11.9305[/C][C]-0.93046[/C][/ROW]
[ROW][C]82[/C][C]9[/C][C]12.319[/C][C]-3.31904[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]11.4909[/C][C]0.509069[/C][/ROW]
[ROW][C]84[/C][C]12[/C][C]12.4563[/C][C]-0.45635[/C][/ROW]
[ROW][C]85[/C][C]13[/C][C]12.7714[/C][C]0.228635[/C][/ROW]
[ROW][C]86[/C][C]13[/C][C]12.2681[/C][C]0.731929[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]13.187[/C][C]-1.18701[/C][/ROW]
[ROW][C]88[/C][C]15[/C][C]14.855[/C][C]0.145049[/C][/ROW]
[ROW][C]89[/C][C]22[/C][C]18.1926[/C][C]3.80745[/C][/ROW]
[ROW][C]90[/C][C]13[/C][C]11.3449[/C][C]1.65512[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]14.456[/C][C]0.543997[/C][/ROW]
[ROW][C]92[/C][C]13[/C][C]12.0116[/C][C]0.988396[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]12.5398[/C][C]2.46021[/C][/ROW]
[ROW][C]94[/C][C]12.5[/C][C]13.654[/C][C]-1.15405[/C][/ROW]
[ROW][C]95[/C][C]11[/C][C]11.0184[/C][C]-0.018439[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]14.4586[/C][C]1.54144[/C][/ROW]
[ROW][C]97[/C][C]11[/C][C]12.676[/C][C]-1.676[/C][/ROW]
[ROW][C]98[/C][C]11[/C][C]10.2501[/C][C]0.749892[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]12.3622[/C][C]-2.36223[/C][/ROW]
[ROW][C]100[/C][C]10[/C][C]10.458[/C][C]-0.458006[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.2877[/C][C]1.71229[/C][/ROW]
[ROW][C]102[/C][C]12[/C][C]10.3561[/C][C]1.64389[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]15.5951[/C][C]-4.5951[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]11.978[/C][C]4.02201[/C][/ROW]
[ROW][C]105[/C][C]19[/C][C]16.8223[/C][C]2.17768[/C][/ROW]
[ROW][C]106[/C][C]11[/C][C]11.1261[/C][C]-0.126093[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]12.1355[/C][C]3.86451[/C][/ROW]
[ROW][C]108[/C][C]15[/C][C]16.806[/C][C]-1.80596[/C][/ROW]
[ROW][C]109[/C][C]24[/C][C]17.5342[/C][C]6.46585[/C][/ROW]
[ROW][C]110[/C][C]14[/C][C]11.6796[/C][C]2.32036[/C][/ROW]
[ROW][C]111[/C][C]15[/C][C]15.0474[/C][C]-0.047381[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]12.8552[/C][C]-1.85524[/C][/ROW]
[ROW][C]113[/C][C]15[/C][C]15.2404[/C][C]-0.240378[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]10.2276[/C][C]1.77236[/C][/ROW]
[ROW][C]115[/C][C]10[/C][C]10.4631[/C][C]-0.463133[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]14.2199[/C][C]-0.21987[/C][/ROW]
[ROW][C]117[/C][C]13[/C][C]13.592[/C][C]-0.592045[/C][/ROW]
[ROW][C]118[/C][C]9[/C][C]13.4878[/C][C]-4.48776[/C][/ROW]
[ROW][C]119[/C][C]15[/C][C]11.8619[/C][C]3.13808[/C][/ROW]
[ROW][C]120[/C][C]15[/C][C]15.7634[/C][C]-0.76342[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]12.7857[/C][C]1.21427[/C][/ROW]
[ROW][C]122[/C][C]11[/C][C]11.4949[/C][C]-0.494876[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]11.9277[/C][C]-3.92769[/C][/ROW]
[ROW][C]124[/C][C]11[/C][C]12.1947[/C][C]-1.19471[/C][/ROW]
[ROW][C]125[/C][C]11[/C][C]13.3186[/C][C]-2.31862[/C][/ROW]
[ROW][C]126[/C][C]8[/C][C]9.80878[/C][C]-1.80878[/C][/ROW]
[ROW][C]127[/C][C]10[/C][C]10.3835[/C][C]-0.38355[/C][/ROW]
[ROW][C]128[/C][C]11[/C][C]9.14162[/C][C]1.85838[/C][/ROW]
[ROW][C]129[/C][C]13[/C][C]12.6178[/C][C]0.382216[/C][/ROW]
[ROW][C]130[/C][C]11[/C][C]13.8653[/C][C]-2.86527[/C][/ROW]
[ROW][C]131[/C][C]20[/C][C]17.6231[/C][C]2.37688[/C][/ROW]
[ROW][C]132[/C][C]10[/C][C]11.9245[/C][C]-1.92453[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]13.2517[/C][C]1.74833[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]12.2706[/C][C]-0.270601[/C][/ROW]
[ROW][C]135[/C][C]14[/C][C]10.9564[/C][C]3.04365[/C][/ROW]
[ROW][C]136[/C][C]23[/C][C]16.5868[/C][C]6.41317[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.6122[/C][C]0.387799[/C][/ROW]
[ROW][C]138[/C][C]16[/C][C]16.7641[/C][C]-0.764125[/C][/ROW]
[ROW][C]139[/C][C]11[/C][C]13.1515[/C][C]-2.15154[/C][/ROW]
[ROW][C]140[/C][C]12[/C][C]14.496[/C][C]-2.49602[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]13.4533[/C][C]-3.45325[/C][/ROW]
[ROW][C]142[/C][C]14[/C][C]11.2137[/C][C]2.78629[/C][/ROW]
[ROW][C]143[/C][C]12[/C][C]12.1737[/C][C]-0.173696[/C][/ROW]
[ROW][C]144[/C][C]12[/C][C]12.0432[/C][C]-0.0432014[/C][/ROW]
[ROW][C]145[/C][C]11[/C][C]11.0344[/C][C]-0.0344116[/C][/ROW]
[ROW][C]146[/C][C]12[/C][C]11.1519[/C][C]0.848073[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]16.0069[/C][C]-3.00692[/C][/ROW]
[ROW][C]148[/C][C]11[/C][C]14.286[/C][C]-3.28598[/C][/ROW]
[ROW][C]149[/C][C]19[/C][C]16.7867[/C][C]2.21334[/C][/ROW]
[ROW][C]150[/C][C]12[/C][C]11.4067[/C][C]0.593313[/C][/ROW]
[ROW][C]151[/C][C]17[/C][C]13.1264[/C][C]3.87359[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.727[/C][C]-2.72697[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.5698[/C][C]-2.56981[/C][/ROW]
[ROW][C]154[/C][C]19[/C][C]16.863[/C][C]2.13703[/C][/ROW]
[ROW][C]155[/C][C]18[/C][C]14.0142[/C][C]3.9858[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]14.456[/C][C]0.543997[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.6669[/C][C]0.333075[/C][/ROW]
[ROW][C]158[/C][C]11[/C][C]9.14162[/C][C]1.85838[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]13.0389[/C][C]-4.03888[/C][/ROW]
[ROW][C]160[/C][C]18[/C][C]14.294[/C][C]3.70604[/C][/ROW]
[ROW][C]161[/C][C]16[/C][C]14.2525[/C][C]1.7475[/C][/ROW]
[ROW][C]162[/C][C]24[/C][C]16.6617[/C][C]7.33833[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]12.9876[/C][C]1.0124[/C][/ROW]
[ROW][C]164[/C][C]20[/C][C]10.7236[/C][C]9.2764[/C][/ROW]
[ROW][C]165[/C][C]18[/C][C]16.0088[/C][C]1.99121[/C][/ROW]
[ROW][C]166[/C][C]23[/C][C]17.0685[/C][C]5.93146[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]12.9801[/C][C]-0.980061[/C][/ROW]
[ROW][C]168[/C][C]14[/C][C]14.9428[/C][C]-0.942786[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]16.2791[/C][C]-0.279144[/C][/ROW]
[ROW][C]170[/C][C]18[/C][C]16.7387[/C][C]1.26126[/C][/ROW]
[ROW][C]171[/C][C]20[/C][C]16.4926[/C][C]3.50741[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.5188[/C][C]0.481168[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]16.3932[/C][C]-4.39316[/C][/ROW]
[ROW][C]174[/C][C]17[/C][C]15.2819[/C][C]1.7181[/C][/ROW]
[ROW][C]175[/C][C]13[/C][C]11.8119[/C][C]1.18809[/C][/ROW]
[ROW][C]176[/C][C]9[/C][C]13.5505[/C][C]-4.55051[/C][/ROW]
[ROW][C]177[/C][C]16[/C][C]17.123[/C][C]-1.12299[/C][/ROW]
[ROW][C]178[/C][C]18[/C][C]15.116[/C][C]2.88395[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]12.152[/C][C]-2.15201[/C][/ROW]
[ROW][C]180[/C][C]14[/C][C]15.3335[/C][C]-1.33349[/C][/ROW]
[ROW][C]181[/C][C]11[/C][C]13.9412[/C][C]-2.94118[/C][/ROW]
[ROW][C]182[/C][C]9[/C][C]14.5203[/C][C]-5.52027[/C][/ROW]
[ROW][C]183[/C][C]11[/C][C]12.1531[/C][C]-1.1531[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]12.4822[/C][C]-2.48216[/C][/ROW]
[ROW][C]185[/C][C]11[/C][C]11.6786[/C][C]-0.678616[/C][/ROW]
[ROW][C]186[/C][C]19[/C][C]13.5539[/C][C]5.44613[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]12.7459[/C][C]1.25409[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]11.7388[/C][C]0.261203[/C][/ROW]
[ROW][C]189[/C][C]14[/C][C]15.4374[/C][C]-1.43738[/C][/ROW]
[ROW][C]190[/C][C]21[/C][C]16.446[/C][C]4.55404[/C][/ROW]
[ROW][C]191[/C][C]13[/C][C]17.28[/C][C]-4.27998[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]12.729[/C][C]-2.72896[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]13.0958[/C][C]1.90415[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]15.6942[/C][C]0.305804[/C][/ROW]
[ROW][C]195[/C][C]14[/C][C]12.6469[/C][C]1.3531[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.5393[/C][C]-2.53925[/C][/ROW]
[ROW][C]197[/C][C]19[/C][C]12.653[/C][C]6.34699[/C][/ROW]
[ROW][C]198[/C][C]15[/C][C]12.2014[/C][C]2.79858[/C][/ROW]
[ROW][C]199[/C][C]19[/C][C]18.097[/C][C]0.902978[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.6674[/C][C]-0.667428[/C][/ROW]
[ROW][C]201[/C][C]17[/C][C]16.8144[/C][C]0.185587[/C][/ROW]
[ROW][C]202[/C][C]12[/C][C]12.975[/C][C]-0.975019[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]11.1881[/C][C]-0.188145[/C][/ROW]
[ROW][C]204[/C][C]14[/C][C]15.0466[/C][C]-1.04664[/C][/ROW]
[ROW][C]205[/C][C]11[/C][C]12.5027[/C][C]-1.50271[/C][/ROW]
[ROW][C]206[/C][C]13[/C][C]12.2927[/C][C]0.707313[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]12.2738[/C][C]-0.273833[/C][/ROW]
[ROW][C]208[/C][C]15[/C][C]12.6633[/C][C]2.33671[/C][/ROW]
[ROW][C]209[/C][C]14[/C][C]14.2349[/C][C]-0.234915[/C][/ROW]
[ROW][C]210[/C][C]12[/C][C]11.0274[/C][C]0.972595[/C][/ROW]
[ROW][C]211[/C][C]17[/C][C]17.3398[/C][C]-0.339769[/C][/ROW]
[ROW][C]212[/C][C]11[/C][C]11.0886[/C][C]-0.0886144[/C][/ROW]
[ROW][C]213[/C][C]18[/C][C]14.498[/C][C]3.50203[/C][/ROW]
[ROW][C]214[/C][C]13[/C][C]15.7527[/C][C]-2.75269[/C][/ROW]
[ROW][C]215[/C][C]17[/C][C]15.3741[/C][C]1.62594[/C][/ROW]
[ROW][C]216[/C][C]13[/C][C]13.0318[/C][C]-0.0318217[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]10.1025[/C][C]0.897482[/C][/ROW]
[ROW][C]218[/C][C]12[/C][C]12.4375[/C][C]-0.437463[/C][/ROW]
[ROW][C]219[/C][C]22[/C][C]18.1837[/C][C]3.81627[/C][/ROW]
[ROW][C]220[/C][C]14[/C][C]11.7741[/C][C]2.22594[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]15.1239[/C][C]-3.12392[/C][/ROW]
[ROW][C]222[/C][C]12[/C][C]12.46[/C][C]-0.459963[/C][/ROW]
[ROW][C]223[/C][C]17[/C][C]15.9396[/C][C]1.06037[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]12.7954[/C][C]-3.79536[/C][/ROW]
[ROW][C]225[/C][C]21[/C][C]18.8052[/C][C]2.19481[/C][/ROW]
[ROW][C]226[/C][C]10[/C][C]12.1793[/C][C]-2.17932[/C][/ROW]
[ROW][C]227[/C][C]11[/C][C]10.7521[/C][C]0.247934[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]15.2028[/C][C]-3.20275[/C][/ROW]
[ROW][C]229[/C][C]23[/C][C]18.1077[/C][C]4.89235[/C][/ROW]
[ROW][C]230[/C][C]13[/C][C]15.6749[/C][C]-2.67488[/C][/ROW]
[ROW][C]231[/C][C]12[/C][C]13.44[/C][C]-1.43997[/C][/ROW]
[ROW][C]232[/C][C]16[/C][C]17.4711[/C][C]-1.47114[/C][/ROW]
[ROW][C]233[/C][C]9[/C][C]13.2824[/C][C]-4.28241[/C][/ROW]
[ROW][C]234[/C][C]17[/C][C]13.229[/C][C]3.771[/C][/ROW]
[ROW][C]235[/C][C]9[/C][C]11.8697[/C][C]-2.86969[/C][/ROW]
[ROW][C]236[/C][C]14[/C][C]15.6435[/C][C]-1.64354[/C][/ROW]
[ROW][C]237[/C][C]17[/C][C]15.286[/C][C]1.71396[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]15.0802[/C][C]-2.08022[/C][/ROW]
[ROW][C]239[/C][C]11[/C][C]15.9753[/C][C]-4.97526[/C][/ROW]
[ROW][C]240[/C][C]12[/C][C]15.6601[/C][C]-3.66011[/C][/ROW]
[ROW][C]241[/C][C]10[/C][C]14.1927[/C][C]-4.19274[/C][/ROW]
[ROW][C]242[/C][C]19[/C][C]18.6739[/C][C]0.326123[/C][/ROW]
[ROW][C]243[/C][C]16[/C][C]16.1198[/C][C]-0.119846[/C][/ROW]
[ROW][C]244[/C][C]16[/C][C]15.1305[/C][C]0.869543[/C][/ROW]
[ROW][C]245[/C][C]14[/C][C]11.7377[/C][C]2.26227[/C][/ROW]
[ROW][C]246[/C][C]20[/C][C]15.9219[/C][C]4.07807[/C][/ROW]
[ROW][C]247[/C][C]15[/C][C]14.2517[/C][C]0.748261[/C][/ROW]
[ROW][C]248[/C][C]23[/C][C]15.0862[/C][C]7.91382[/C][/ROW]
[ROW][C]249[/C][C]20[/C][C]17.5912[/C][C]2.40876[/C][/ROW]
[ROW][C]250[/C][C]16[/C][C]16.237[/C][C]-0.236992[/C][/ROW]
[ROW][C]251[/C][C]14[/C][C]13.0632[/C][C]0.936757[/C][/ROW]
[ROW][C]252[/C][C]17[/C][C]14.0477[/C][C]2.95233[/C][/ROW]
[ROW][C]253[/C][C]11[/C][C]14.2027[/C][C]-3.20266[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.7958[/C][C]-0.795812[/C][/ROW]
[ROW][C]255[/C][C]17[/C][C]14.9361[/C][C]2.06391[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]14.8862[/C][C]0.113795[/C][/ROW]
[ROW][C]257[/C][C]21[/C][C]16.3634[/C][C]4.63661[/C][/ROW]
[ROW][C]258[/C][C]18[/C][C]17.471[/C][C]0.529048[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.7495[/C][C]2.25051[/C][/ROW]
[ROW][C]260[/C][C]8[/C][C]16.4624[/C][C]-8.46241[/C][/ROW]
[ROW][C]261[/C][C]12[/C][C]13.7517[/C][C]-1.75167[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]12.9722[/C][C]-0.972249[/C][/ROW]
[ROW][C]263[/C][C]22[/C][C]18.9191[/C][C]3.08095[/C][/ROW]
[ROW][C]264[/C][C]12[/C][C]13.3944[/C][C]-1.3944[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225425&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225425&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
11214.1138-2.11377
2119.373411.62659
31415.2481-1.24809
41215.0281-3.02809
52111.51279.48726
61210.05741.9426
72213.59598.40414
81112.5892-1.58916
91012.2824-2.28244
101312.1490.851045
111010.3608-0.360797
12810.3704-2.3704
131515.9866-0.986595
141412.46021.53982
15109.187650.812351
161413.91720.082788
171412.88051.11946
18119.497441.50256
191013.1454-3.14541
201312.45430.545672
219.510.5618-1.06176
221415.4217-1.42175
231213.5627-1.56273
241415.2666-1.26661
25119.801441.19856
26915.7355-6.73545
271111.3339-0.333925
281513.24431.75566
291411.96532.03471
301315.624-2.62398
31911.283-2.28299
321515.3829-0.382925
331011.0193-1.01934
341111.6249-0.624919
351313.0245-0.0244947
36812.3451-4.34509
372017.80382.1962
381212.4362-0.436158
391010.825-0.825006
401013.8783-3.87832
41912.1031-3.10309
421411.5672.43302
43811.9888-3.98882
441415.7186-1.71861
451112.4998-1.49985
461315.6977-2.69772
47912.7216-3.72161
481112.2556-1.25563
491510.72914.2709
501113.5622-2.56223
511011.6047-1.60474
521413.53470.465273
531816.03891.96112
541414.97-0.969953
551115.7728-4.77282
5614.512.29632.20375
571311.28711.71293
58912.7193-3.71927
591014.3838-4.38384
601514.54080.459231
612018.89511.10493
621213.2863-1.28626
631214.6271-2.62707
641414.4153-0.415303
651313.2605-0.260549
661115.2569-4.25689
671715.1661.834
681214.2838-2.28382
691313.0122-0.0121782
701412.43091.56911
711313.7885-0.788538
721512.90192.09814
731311.57571.42428
741012.1292-2.12916
751112.9773-1.97728
761913.7595.24104
771310.862.14003
781713.87083.12924
791312.43910.56089
80914.5563-5.5563
811111.9305-0.93046
82912.319-3.31904
831211.49090.509069
841212.4563-0.45635
851312.77140.228635
861312.26810.731929
871213.187-1.18701
881514.8550.145049
892218.19263.80745
901311.34491.65512
911514.4560.543997
921312.01160.988396
931512.53982.46021
9412.513.654-1.15405
951111.0184-0.018439
961614.45861.54144
971112.676-1.676
981110.25010.749892
991012.3622-2.36223
1001010.458-0.458006
1011614.28771.71229
1021210.35611.64389
1031115.5951-4.5951
1041611.9784.02201
1051916.82232.17768
1061111.1261-0.126093
1071612.13553.86451
1081516.806-1.80596
1092417.53426.46585
1101411.67962.32036
1111515.0474-0.047381
1121112.8552-1.85524
1131515.2404-0.240378
1141210.22761.77236
1151010.4631-0.463133
1161414.2199-0.21987
1171313.592-0.592045
118913.4878-4.48776
1191511.86193.13808
1201515.7634-0.76342
1211412.78571.21427
1221111.4949-0.494876
123811.9277-3.92769
1241112.1947-1.19471
1251113.3186-2.31862
12689.80878-1.80878
1271010.3835-0.38355
128119.141621.85838
1291312.61780.382216
1301113.8653-2.86527
1312017.62312.37688
1321011.9245-1.92453
1331513.25171.74833
1341212.2706-0.270601
1351410.95643.04365
1362316.58686.41317
1371413.61220.387799
1381616.7641-0.764125
1391113.1515-2.15154
1401214.496-2.49602
1411013.4533-3.45325
1421411.21372.78629
1431212.1737-0.173696
1441212.0432-0.0432014
1451111.0344-0.0344116
1461211.15190.848073
1471316.0069-3.00692
1481114.286-3.28598
1491916.78672.21334
1501211.40670.593313
1511713.12643.87359
152911.727-2.72697
1531214.5698-2.56981
1541916.8632.13703
1551814.01423.9858
1561514.4560.543997
1571413.66690.333075
158119.141621.85838
159913.0389-4.03888
1601814.2943.70604
1611614.25251.7475
1622416.66177.33833
1631412.98761.0124
1642010.72369.2764
1651816.00881.99121
1662317.06855.93146
1671212.9801-0.980061
1681414.9428-0.942786
1691616.2791-0.279144
1701816.73871.26126
1712016.49263.50741
1721211.51880.481168
1731216.3932-4.39316
1741715.28191.7181
1751311.81191.18809
176913.5505-4.55051
1771617.123-1.12299
1781815.1162.88395
1791012.152-2.15201
1801415.3335-1.33349
1811113.9412-2.94118
182914.5203-5.52027
1831112.1531-1.1531
1841012.4822-2.48216
1851111.6786-0.678616
1861913.55395.44613
1871412.74591.25409
1881211.73880.261203
1891415.4374-1.43738
1902116.4464.55404
1911317.28-4.27998
1921012.729-2.72896
1931513.09581.90415
1941615.69420.305804
1951412.64691.3531
1961214.5393-2.53925
1971912.6536.34699
1981512.20142.79858
1991918.0970.902978
2001313.6674-0.667428
2011716.81440.185587
2021212.975-0.975019
2031111.1881-0.188145
2041415.0466-1.04664
2051112.5027-1.50271
2061312.29270.707313
2071212.2738-0.273833
2081512.66332.33671
2091414.2349-0.234915
2101211.02740.972595
2111717.3398-0.339769
2121111.0886-0.0886144
2131814.4983.50203
2141315.7527-2.75269
2151715.37411.62594
2161313.0318-0.0318217
2171110.10250.897482
2181212.4375-0.437463
2192218.18373.81627
2201411.77412.22594
2211215.1239-3.12392
2221212.46-0.459963
2231715.93961.06037
224912.7954-3.79536
2252118.80522.19481
2261012.1793-2.17932
2271110.75210.247934
2281215.2028-3.20275
2292318.10774.89235
2301315.6749-2.67488
2311213.44-1.43997
2321617.4711-1.47114
233913.2824-4.28241
2341713.2293.771
235911.8697-2.86969
2361415.6435-1.64354
2371715.2861.71396
2381315.0802-2.08022
2391115.9753-4.97526
2401215.6601-3.66011
2411014.1927-4.19274
2421918.67390.326123
2431616.1198-0.119846
2441615.13050.869543
2451411.73772.26227
2462015.92194.07807
2471514.25170.748261
2482315.08627.91382
2492017.59122.40876
2501616.237-0.236992
2511413.06320.936757
2521714.04772.95233
2531114.2027-3.20266
2541313.7958-0.795812
2551714.93612.06391
2561514.88620.113795
2572116.36344.63661
2581817.4710.529048
2591512.74952.25051
260816.4624-8.46241
2611213.7517-1.75167
2621212.9722-0.972249
2632218.91913.08095
2641213.3944-1.3944






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.8377510.3244970.162249
110.7452160.5095690.254784
120.9994180.001164320.000582162
130.9987470.002506450.00125323
140.9974080.005184310.00259215
150.9955550.008890090.00444505
160.9918910.01621880.00810941
170.9863430.02731420.0136571
180.9785180.0429630.0214815
190.9795440.04091230.0204562
200.9684560.06308810.031544
210.9569070.08618650.0430933
220.9414060.1171870.0585935
230.9270460.1459080.0729541
240.9012130.1975740.0987868
250.8744510.2510970.125549
260.9450050.1099910.0549953
270.9255690.1488620.0744309
280.9098140.1803720.0901858
290.8916880.2166240.108312
300.8660740.2678530.133926
310.8672160.2655670.132784
320.8353060.3293880.164694
330.8077920.3844170.192208
340.7677940.4644130.232206
350.7231210.5537570.276879
360.7379620.5240760.262038
370.8056240.3887520.194376
380.7678610.4642780.232139
390.7338370.5323270.266163
400.737490.525020.26251
410.726470.5470610.27353
420.7054070.5891850.294593
430.7725220.4549560.227478
440.7367760.5264490.263224
450.6984630.6030740.301537
460.6765180.6469650.323482
470.7063980.5872030.293602
480.6700140.6599710.329986
490.7148850.570230.285115
500.687670.6246610.31233
510.6745180.6509630.325482
520.6375250.7249490.362475
530.6399090.7201820.360091
540.5977520.8044960.402248
550.6150350.769930.384965
560.6324760.7350480.367524
570.6086340.7827320.391366
580.6441420.7117160.355858
590.6647320.6705360.335268
600.6396180.7207640.360382
610.6525050.694990.347495
620.6150050.7699890.384995
630.5915570.8168850.408443
640.5499010.9001980.450099
650.5078230.9843530.492177
660.5178920.9642160.482108
670.5228320.9543370.477168
680.4988610.9977230.501139
690.4579560.9159130.542044
700.4335590.8671180.566441
710.3941820.7883640.605818
720.3716340.7432680.628366
730.3441880.6883760.655812
740.3284780.6569560.671522
750.3020640.6041270.697936
760.4598740.9197470.540126
770.4397010.8794020.560299
780.464410.928820.53559
790.427280.8545590.57272
800.5220430.9559150.477957
810.4876040.9752070.512396
820.5031950.9936090.496805
830.46580.9316010.5342
840.4280890.8561770.571911
850.3913340.7826680.608666
860.3579310.7158630.642069
870.327250.65450.67275
880.2953840.5907680.704616
890.3820390.7640770.617961
900.356840.713680.64316
910.3287280.6574570.671272
920.2987990.5975970.701201
930.2939150.587830.706085
940.2663450.5326910.733655
950.2361970.4723940.763803
960.2230190.4460380.776981
970.20470.4093990.7953
980.1800540.3601070.819946
990.1732520.3465030.826748
1000.1514410.3028820.848559
1010.1426830.2853660.857317
1020.1269140.2538270.873086
1030.1548830.3097660.845117
1040.1777460.3554930.822254
1050.1845020.3690050.815498
1060.1611170.3222340.838883
1070.1813940.3627880.818606
1080.1658920.3317840.834108
1090.2897850.579570.710215
1100.2821370.5642740.717863
1110.2538910.5077830.746109
1120.2419860.4839720.758014
1130.2148810.4297630.785119
1140.1983930.3967860.801607
1150.1749830.3499670.825017
1160.152760.305520.84724
1170.1340010.2680010.865999
1180.165750.3315010.83425
1190.1693660.3387330.830634
1200.1486250.2972510.851375
1210.1360130.2720260.863987
1220.1189790.2379580.881021
1230.140890.2817790.85911
1240.1252070.2504150.874793
1250.1188610.2377220.881139
1260.1106880.2213760.889312
1270.09633360.1926670.903666
1280.08766190.1753240.912338
1290.07463880.1492780.925361
1300.07492850.1498570.925071
1310.07633430.1526690.923666
1320.07089090.1417820.929109
1330.06493180.1298640.935068
1340.0544980.1089960.945502
1350.05646290.1129260.943537
1360.1197960.2395920.880204
1370.1031310.2062610.896869
1380.08884830.1776970.911152
1390.08338720.1667740.916613
1400.08000820.1600160.919992
1410.08768890.1753780.912311
1420.08796240.1759250.912038
1430.07462240.1492450.925378
1440.06284390.1256880.937156
1450.05260720.1052140.947393
1460.04416110.08832230.955839
1470.04594060.09188110.954059
1480.04993720.09987430.950063
1490.04741520.09483050.952585
1500.03983980.07967960.96016
1510.04637450.0927490.953626
1520.0460250.09205010.953975
1530.04441290.08882580.955587
1540.04135340.08270680.958647
1550.05094160.1018830.949058
1560.04281110.08562220.957189
1570.0353390.0706780.964661
1580.03153030.06306050.96847
1590.03967830.07935660.960322
1600.04731510.09463030.952685
1610.04212520.08425030.957875
1620.1116720.2233450.888328
1630.09796190.1959240.902038
1640.3478560.6957130.652144
1650.329090.6581790.67091
1660.4464230.8928460.553577
1670.4140070.8280150.585993
1680.3831670.7663350.616833
1690.3483230.6966460.651677
1700.3206190.6412380.679381
1710.3330290.6660570.666971
1720.3002240.6004470.699776
1730.3538030.7076060.646197
1740.3379270.6758540.662073
1750.3134260.6268530.686574
1760.3735460.7470920.626454
1770.345570.6911410.65443
1780.3515030.7030060.648497
1790.3349690.6699390.665031
1800.3105290.6210590.689471
1810.3280360.6560720.671964
1820.4305980.8611960.569402
1830.4059640.8119280.594036
1840.4044040.8088080.595596
1850.3847280.7694550.615272
1860.4844350.968870.515565
1870.4484270.8968540.551573
1880.4097180.8194360.590282
1890.3787320.7574640.621268
1900.4440560.8881110.555944
1910.5453930.9092150.454607
1920.5695630.8608750.430437
1930.5626440.8747120.437356
1940.5285730.9428550.471427
1950.5007820.9984370.499218
1960.5295230.9409530.470477
1970.7202580.5594840.279742
1980.7257880.5484230.274212
1990.690150.61970.30985
2000.6524420.6951160.347558
2010.6123790.7752410.387621
2020.5730160.8539670.426984
2030.5362240.9275510.463776
2040.520220.959560.47978
2050.4848130.9696270.515187
2060.4422870.8845750.557713
2070.39890.79780.6011
2080.3654720.7309440.634528
2090.3243660.6487320.675634
2100.3039170.6078330.696083
2110.2770640.5541280.722936
2120.2417950.4835910.758205
2130.27560.5512010.7244
2140.2553110.5106210.744689
2150.222550.44510.77745
2160.1912890.3825770.808711
2170.1796440.3592890.820356
2180.1507190.3014390.849281
2190.1508860.3017730.849114
2200.1508730.3017460.849127
2210.1570480.3140960.842952
2220.1351240.2702480.864876
2230.1113040.2226090.888696
2240.1128930.2257870.887107
2250.0965840.1931680.903416
2260.07894960.1578990.92105
2270.06165640.1233130.938344
2280.07161080.1432220.928389
2290.09816560.1963310.901834
2300.09438280.1887660.905617
2310.07409030.1481810.92591
2320.06946470.1389290.930535
2330.1328750.2657510.867125
2340.1453650.2907290.854635
2350.141770.2835410.85823
2360.113670.2273410.88633
2370.1594290.3188580.840571
2380.2107190.4214370.789281
2390.3322670.6645340.667733
2400.3307050.661410.669295
2410.2816120.5632230.718388
2420.3394970.6789940.660503
2430.2737670.5475340.726233
2440.2131430.4262850.786857
2450.2873210.5746410.712679
2460.3108250.6216510.689175
2470.2374140.4748280.762586
2480.2985260.5970510.701474
2490.2992350.598470.700765
2500.2831290.5662580.716871
2510.3271980.6543960.672802
2520.9469190.1061620.0530812
2530.9062640.1874720.0937362
2540.9475990.1048020.0524011

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.837751 & 0.324497 & 0.162249 \tabularnewline
11 & 0.745216 & 0.509569 & 0.254784 \tabularnewline
12 & 0.999418 & 0.00116432 & 0.000582162 \tabularnewline
13 & 0.998747 & 0.00250645 & 0.00125323 \tabularnewline
14 & 0.997408 & 0.00518431 & 0.00259215 \tabularnewline
15 & 0.995555 & 0.00889009 & 0.00444505 \tabularnewline
16 & 0.991891 & 0.0162188 & 0.00810941 \tabularnewline
17 & 0.986343 & 0.0273142 & 0.0136571 \tabularnewline
18 & 0.978518 & 0.042963 & 0.0214815 \tabularnewline
19 & 0.979544 & 0.0409123 & 0.0204562 \tabularnewline
20 & 0.968456 & 0.0630881 & 0.031544 \tabularnewline
21 & 0.956907 & 0.0861865 & 0.0430933 \tabularnewline
22 & 0.941406 & 0.117187 & 0.0585935 \tabularnewline
23 & 0.927046 & 0.145908 & 0.0729541 \tabularnewline
24 & 0.901213 & 0.197574 & 0.0987868 \tabularnewline
25 & 0.874451 & 0.251097 & 0.125549 \tabularnewline
26 & 0.945005 & 0.109991 & 0.0549953 \tabularnewline
27 & 0.925569 & 0.148862 & 0.0744309 \tabularnewline
28 & 0.909814 & 0.180372 & 0.0901858 \tabularnewline
29 & 0.891688 & 0.216624 & 0.108312 \tabularnewline
30 & 0.866074 & 0.267853 & 0.133926 \tabularnewline
31 & 0.867216 & 0.265567 & 0.132784 \tabularnewline
32 & 0.835306 & 0.329388 & 0.164694 \tabularnewline
33 & 0.807792 & 0.384417 & 0.192208 \tabularnewline
34 & 0.767794 & 0.464413 & 0.232206 \tabularnewline
35 & 0.723121 & 0.553757 & 0.276879 \tabularnewline
36 & 0.737962 & 0.524076 & 0.262038 \tabularnewline
37 & 0.805624 & 0.388752 & 0.194376 \tabularnewline
38 & 0.767861 & 0.464278 & 0.232139 \tabularnewline
39 & 0.733837 & 0.532327 & 0.266163 \tabularnewline
40 & 0.73749 & 0.52502 & 0.26251 \tabularnewline
41 & 0.72647 & 0.547061 & 0.27353 \tabularnewline
42 & 0.705407 & 0.589185 & 0.294593 \tabularnewline
43 & 0.772522 & 0.454956 & 0.227478 \tabularnewline
44 & 0.736776 & 0.526449 & 0.263224 \tabularnewline
45 & 0.698463 & 0.603074 & 0.301537 \tabularnewline
46 & 0.676518 & 0.646965 & 0.323482 \tabularnewline
47 & 0.706398 & 0.587203 & 0.293602 \tabularnewline
48 & 0.670014 & 0.659971 & 0.329986 \tabularnewline
49 & 0.714885 & 0.57023 & 0.285115 \tabularnewline
50 & 0.68767 & 0.624661 & 0.31233 \tabularnewline
51 & 0.674518 & 0.650963 & 0.325482 \tabularnewline
52 & 0.637525 & 0.724949 & 0.362475 \tabularnewline
53 & 0.639909 & 0.720182 & 0.360091 \tabularnewline
54 & 0.597752 & 0.804496 & 0.402248 \tabularnewline
55 & 0.615035 & 0.76993 & 0.384965 \tabularnewline
56 & 0.632476 & 0.735048 & 0.367524 \tabularnewline
57 & 0.608634 & 0.782732 & 0.391366 \tabularnewline
58 & 0.644142 & 0.711716 & 0.355858 \tabularnewline
59 & 0.664732 & 0.670536 & 0.335268 \tabularnewline
60 & 0.639618 & 0.720764 & 0.360382 \tabularnewline
61 & 0.652505 & 0.69499 & 0.347495 \tabularnewline
62 & 0.615005 & 0.769989 & 0.384995 \tabularnewline
63 & 0.591557 & 0.816885 & 0.408443 \tabularnewline
64 & 0.549901 & 0.900198 & 0.450099 \tabularnewline
65 & 0.507823 & 0.984353 & 0.492177 \tabularnewline
66 & 0.517892 & 0.964216 & 0.482108 \tabularnewline
67 & 0.522832 & 0.954337 & 0.477168 \tabularnewline
68 & 0.498861 & 0.997723 & 0.501139 \tabularnewline
69 & 0.457956 & 0.915913 & 0.542044 \tabularnewline
70 & 0.433559 & 0.867118 & 0.566441 \tabularnewline
71 & 0.394182 & 0.788364 & 0.605818 \tabularnewline
72 & 0.371634 & 0.743268 & 0.628366 \tabularnewline
73 & 0.344188 & 0.688376 & 0.655812 \tabularnewline
74 & 0.328478 & 0.656956 & 0.671522 \tabularnewline
75 & 0.302064 & 0.604127 & 0.697936 \tabularnewline
76 & 0.459874 & 0.919747 & 0.540126 \tabularnewline
77 & 0.439701 & 0.879402 & 0.560299 \tabularnewline
78 & 0.46441 & 0.92882 & 0.53559 \tabularnewline
79 & 0.42728 & 0.854559 & 0.57272 \tabularnewline
80 & 0.522043 & 0.955915 & 0.477957 \tabularnewline
81 & 0.487604 & 0.975207 & 0.512396 \tabularnewline
82 & 0.503195 & 0.993609 & 0.496805 \tabularnewline
83 & 0.4658 & 0.931601 & 0.5342 \tabularnewline
84 & 0.428089 & 0.856177 & 0.571911 \tabularnewline
85 & 0.391334 & 0.782668 & 0.608666 \tabularnewline
86 & 0.357931 & 0.715863 & 0.642069 \tabularnewline
87 & 0.32725 & 0.6545 & 0.67275 \tabularnewline
88 & 0.295384 & 0.590768 & 0.704616 \tabularnewline
89 & 0.382039 & 0.764077 & 0.617961 \tabularnewline
90 & 0.35684 & 0.71368 & 0.64316 \tabularnewline
91 & 0.328728 & 0.657457 & 0.671272 \tabularnewline
92 & 0.298799 & 0.597597 & 0.701201 \tabularnewline
93 & 0.293915 & 0.58783 & 0.706085 \tabularnewline
94 & 0.266345 & 0.532691 & 0.733655 \tabularnewline
95 & 0.236197 & 0.472394 & 0.763803 \tabularnewline
96 & 0.223019 & 0.446038 & 0.776981 \tabularnewline
97 & 0.2047 & 0.409399 & 0.7953 \tabularnewline
98 & 0.180054 & 0.360107 & 0.819946 \tabularnewline
99 & 0.173252 & 0.346503 & 0.826748 \tabularnewline
100 & 0.151441 & 0.302882 & 0.848559 \tabularnewline
101 & 0.142683 & 0.285366 & 0.857317 \tabularnewline
102 & 0.126914 & 0.253827 & 0.873086 \tabularnewline
103 & 0.154883 & 0.309766 & 0.845117 \tabularnewline
104 & 0.177746 & 0.355493 & 0.822254 \tabularnewline
105 & 0.184502 & 0.369005 & 0.815498 \tabularnewline
106 & 0.161117 & 0.322234 & 0.838883 \tabularnewline
107 & 0.181394 & 0.362788 & 0.818606 \tabularnewline
108 & 0.165892 & 0.331784 & 0.834108 \tabularnewline
109 & 0.289785 & 0.57957 & 0.710215 \tabularnewline
110 & 0.282137 & 0.564274 & 0.717863 \tabularnewline
111 & 0.253891 & 0.507783 & 0.746109 \tabularnewline
112 & 0.241986 & 0.483972 & 0.758014 \tabularnewline
113 & 0.214881 & 0.429763 & 0.785119 \tabularnewline
114 & 0.198393 & 0.396786 & 0.801607 \tabularnewline
115 & 0.174983 & 0.349967 & 0.825017 \tabularnewline
116 & 0.15276 & 0.30552 & 0.84724 \tabularnewline
117 & 0.134001 & 0.268001 & 0.865999 \tabularnewline
118 & 0.16575 & 0.331501 & 0.83425 \tabularnewline
119 & 0.169366 & 0.338733 & 0.830634 \tabularnewline
120 & 0.148625 & 0.297251 & 0.851375 \tabularnewline
121 & 0.136013 & 0.272026 & 0.863987 \tabularnewline
122 & 0.118979 & 0.237958 & 0.881021 \tabularnewline
123 & 0.14089 & 0.281779 & 0.85911 \tabularnewline
124 & 0.125207 & 0.250415 & 0.874793 \tabularnewline
125 & 0.118861 & 0.237722 & 0.881139 \tabularnewline
126 & 0.110688 & 0.221376 & 0.889312 \tabularnewline
127 & 0.0963336 & 0.192667 & 0.903666 \tabularnewline
128 & 0.0876619 & 0.175324 & 0.912338 \tabularnewline
129 & 0.0746388 & 0.149278 & 0.925361 \tabularnewline
130 & 0.0749285 & 0.149857 & 0.925071 \tabularnewline
131 & 0.0763343 & 0.152669 & 0.923666 \tabularnewline
132 & 0.0708909 & 0.141782 & 0.929109 \tabularnewline
133 & 0.0649318 & 0.129864 & 0.935068 \tabularnewline
134 & 0.054498 & 0.108996 & 0.945502 \tabularnewline
135 & 0.0564629 & 0.112926 & 0.943537 \tabularnewline
136 & 0.119796 & 0.239592 & 0.880204 \tabularnewline
137 & 0.103131 & 0.206261 & 0.896869 \tabularnewline
138 & 0.0888483 & 0.177697 & 0.911152 \tabularnewline
139 & 0.0833872 & 0.166774 & 0.916613 \tabularnewline
140 & 0.0800082 & 0.160016 & 0.919992 \tabularnewline
141 & 0.0876889 & 0.175378 & 0.912311 \tabularnewline
142 & 0.0879624 & 0.175925 & 0.912038 \tabularnewline
143 & 0.0746224 & 0.149245 & 0.925378 \tabularnewline
144 & 0.0628439 & 0.125688 & 0.937156 \tabularnewline
145 & 0.0526072 & 0.105214 & 0.947393 \tabularnewline
146 & 0.0441611 & 0.0883223 & 0.955839 \tabularnewline
147 & 0.0459406 & 0.0918811 & 0.954059 \tabularnewline
148 & 0.0499372 & 0.0998743 & 0.950063 \tabularnewline
149 & 0.0474152 & 0.0948305 & 0.952585 \tabularnewline
150 & 0.0398398 & 0.0796796 & 0.96016 \tabularnewline
151 & 0.0463745 & 0.092749 & 0.953626 \tabularnewline
152 & 0.046025 & 0.0920501 & 0.953975 \tabularnewline
153 & 0.0444129 & 0.0888258 & 0.955587 \tabularnewline
154 & 0.0413534 & 0.0827068 & 0.958647 \tabularnewline
155 & 0.0509416 & 0.101883 & 0.949058 \tabularnewline
156 & 0.0428111 & 0.0856222 & 0.957189 \tabularnewline
157 & 0.035339 & 0.070678 & 0.964661 \tabularnewline
158 & 0.0315303 & 0.0630605 & 0.96847 \tabularnewline
159 & 0.0396783 & 0.0793566 & 0.960322 \tabularnewline
160 & 0.0473151 & 0.0946303 & 0.952685 \tabularnewline
161 & 0.0421252 & 0.0842503 & 0.957875 \tabularnewline
162 & 0.111672 & 0.223345 & 0.888328 \tabularnewline
163 & 0.0979619 & 0.195924 & 0.902038 \tabularnewline
164 & 0.347856 & 0.695713 & 0.652144 \tabularnewline
165 & 0.32909 & 0.658179 & 0.67091 \tabularnewline
166 & 0.446423 & 0.892846 & 0.553577 \tabularnewline
167 & 0.414007 & 0.828015 & 0.585993 \tabularnewline
168 & 0.383167 & 0.766335 & 0.616833 \tabularnewline
169 & 0.348323 & 0.696646 & 0.651677 \tabularnewline
170 & 0.320619 & 0.641238 & 0.679381 \tabularnewline
171 & 0.333029 & 0.666057 & 0.666971 \tabularnewline
172 & 0.300224 & 0.600447 & 0.699776 \tabularnewline
173 & 0.353803 & 0.707606 & 0.646197 \tabularnewline
174 & 0.337927 & 0.675854 & 0.662073 \tabularnewline
175 & 0.313426 & 0.626853 & 0.686574 \tabularnewline
176 & 0.373546 & 0.747092 & 0.626454 \tabularnewline
177 & 0.34557 & 0.691141 & 0.65443 \tabularnewline
178 & 0.351503 & 0.703006 & 0.648497 \tabularnewline
179 & 0.334969 & 0.669939 & 0.665031 \tabularnewline
180 & 0.310529 & 0.621059 & 0.689471 \tabularnewline
181 & 0.328036 & 0.656072 & 0.671964 \tabularnewline
182 & 0.430598 & 0.861196 & 0.569402 \tabularnewline
183 & 0.405964 & 0.811928 & 0.594036 \tabularnewline
184 & 0.404404 & 0.808808 & 0.595596 \tabularnewline
185 & 0.384728 & 0.769455 & 0.615272 \tabularnewline
186 & 0.484435 & 0.96887 & 0.515565 \tabularnewline
187 & 0.448427 & 0.896854 & 0.551573 \tabularnewline
188 & 0.409718 & 0.819436 & 0.590282 \tabularnewline
189 & 0.378732 & 0.757464 & 0.621268 \tabularnewline
190 & 0.444056 & 0.888111 & 0.555944 \tabularnewline
191 & 0.545393 & 0.909215 & 0.454607 \tabularnewline
192 & 0.569563 & 0.860875 & 0.430437 \tabularnewline
193 & 0.562644 & 0.874712 & 0.437356 \tabularnewline
194 & 0.528573 & 0.942855 & 0.471427 \tabularnewline
195 & 0.500782 & 0.998437 & 0.499218 \tabularnewline
196 & 0.529523 & 0.940953 & 0.470477 \tabularnewline
197 & 0.720258 & 0.559484 & 0.279742 \tabularnewline
198 & 0.725788 & 0.548423 & 0.274212 \tabularnewline
199 & 0.69015 & 0.6197 & 0.30985 \tabularnewline
200 & 0.652442 & 0.695116 & 0.347558 \tabularnewline
201 & 0.612379 & 0.775241 & 0.387621 \tabularnewline
202 & 0.573016 & 0.853967 & 0.426984 \tabularnewline
203 & 0.536224 & 0.927551 & 0.463776 \tabularnewline
204 & 0.52022 & 0.95956 & 0.47978 \tabularnewline
205 & 0.484813 & 0.969627 & 0.515187 \tabularnewline
206 & 0.442287 & 0.884575 & 0.557713 \tabularnewline
207 & 0.3989 & 0.7978 & 0.6011 \tabularnewline
208 & 0.365472 & 0.730944 & 0.634528 \tabularnewline
209 & 0.324366 & 0.648732 & 0.675634 \tabularnewline
210 & 0.303917 & 0.607833 & 0.696083 \tabularnewline
211 & 0.277064 & 0.554128 & 0.722936 \tabularnewline
212 & 0.241795 & 0.483591 & 0.758205 \tabularnewline
213 & 0.2756 & 0.551201 & 0.7244 \tabularnewline
214 & 0.255311 & 0.510621 & 0.744689 \tabularnewline
215 & 0.22255 & 0.4451 & 0.77745 \tabularnewline
216 & 0.191289 & 0.382577 & 0.808711 \tabularnewline
217 & 0.179644 & 0.359289 & 0.820356 \tabularnewline
218 & 0.150719 & 0.301439 & 0.849281 \tabularnewline
219 & 0.150886 & 0.301773 & 0.849114 \tabularnewline
220 & 0.150873 & 0.301746 & 0.849127 \tabularnewline
221 & 0.157048 & 0.314096 & 0.842952 \tabularnewline
222 & 0.135124 & 0.270248 & 0.864876 \tabularnewline
223 & 0.111304 & 0.222609 & 0.888696 \tabularnewline
224 & 0.112893 & 0.225787 & 0.887107 \tabularnewline
225 & 0.096584 & 0.193168 & 0.903416 \tabularnewline
226 & 0.0789496 & 0.157899 & 0.92105 \tabularnewline
227 & 0.0616564 & 0.123313 & 0.938344 \tabularnewline
228 & 0.0716108 & 0.143222 & 0.928389 \tabularnewline
229 & 0.0981656 & 0.196331 & 0.901834 \tabularnewline
230 & 0.0943828 & 0.188766 & 0.905617 \tabularnewline
231 & 0.0740903 & 0.148181 & 0.92591 \tabularnewline
232 & 0.0694647 & 0.138929 & 0.930535 \tabularnewline
233 & 0.132875 & 0.265751 & 0.867125 \tabularnewline
234 & 0.145365 & 0.290729 & 0.854635 \tabularnewline
235 & 0.14177 & 0.283541 & 0.85823 \tabularnewline
236 & 0.11367 & 0.227341 & 0.88633 \tabularnewline
237 & 0.159429 & 0.318858 & 0.840571 \tabularnewline
238 & 0.210719 & 0.421437 & 0.789281 \tabularnewline
239 & 0.332267 & 0.664534 & 0.667733 \tabularnewline
240 & 0.330705 & 0.66141 & 0.669295 \tabularnewline
241 & 0.281612 & 0.563223 & 0.718388 \tabularnewline
242 & 0.339497 & 0.678994 & 0.660503 \tabularnewline
243 & 0.273767 & 0.547534 & 0.726233 \tabularnewline
244 & 0.213143 & 0.426285 & 0.786857 \tabularnewline
245 & 0.287321 & 0.574641 & 0.712679 \tabularnewline
246 & 0.310825 & 0.621651 & 0.689175 \tabularnewline
247 & 0.237414 & 0.474828 & 0.762586 \tabularnewline
248 & 0.298526 & 0.597051 & 0.701474 \tabularnewline
249 & 0.299235 & 0.59847 & 0.700765 \tabularnewline
250 & 0.283129 & 0.566258 & 0.716871 \tabularnewline
251 & 0.327198 & 0.654396 & 0.672802 \tabularnewline
252 & 0.946919 & 0.106162 & 0.0530812 \tabularnewline
253 & 0.906264 & 0.187472 & 0.0937362 \tabularnewline
254 & 0.947599 & 0.104802 & 0.0524011 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225425&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]10[/C][C]0.837751[/C][C]0.324497[/C][C]0.162249[/C][/ROW]
[ROW][C]11[/C][C]0.745216[/C][C]0.509569[/C][C]0.254784[/C][/ROW]
[ROW][C]12[/C][C]0.999418[/C][C]0.00116432[/C][C]0.000582162[/C][/ROW]
[ROW][C]13[/C][C]0.998747[/C][C]0.00250645[/C][C]0.00125323[/C][/ROW]
[ROW][C]14[/C][C]0.997408[/C][C]0.00518431[/C][C]0.00259215[/C][/ROW]
[ROW][C]15[/C][C]0.995555[/C][C]0.00889009[/C][C]0.00444505[/C][/ROW]
[ROW][C]16[/C][C]0.991891[/C][C]0.0162188[/C][C]0.00810941[/C][/ROW]
[ROW][C]17[/C][C]0.986343[/C][C]0.0273142[/C][C]0.0136571[/C][/ROW]
[ROW][C]18[/C][C]0.978518[/C][C]0.042963[/C][C]0.0214815[/C][/ROW]
[ROW][C]19[/C][C]0.979544[/C][C]0.0409123[/C][C]0.0204562[/C][/ROW]
[ROW][C]20[/C][C]0.968456[/C][C]0.0630881[/C][C]0.031544[/C][/ROW]
[ROW][C]21[/C][C]0.956907[/C][C]0.0861865[/C][C]0.0430933[/C][/ROW]
[ROW][C]22[/C][C]0.941406[/C][C]0.117187[/C][C]0.0585935[/C][/ROW]
[ROW][C]23[/C][C]0.927046[/C][C]0.145908[/C][C]0.0729541[/C][/ROW]
[ROW][C]24[/C][C]0.901213[/C][C]0.197574[/C][C]0.0987868[/C][/ROW]
[ROW][C]25[/C][C]0.874451[/C][C]0.251097[/C][C]0.125549[/C][/ROW]
[ROW][C]26[/C][C]0.945005[/C][C]0.109991[/C][C]0.0549953[/C][/ROW]
[ROW][C]27[/C][C]0.925569[/C][C]0.148862[/C][C]0.0744309[/C][/ROW]
[ROW][C]28[/C][C]0.909814[/C][C]0.180372[/C][C]0.0901858[/C][/ROW]
[ROW][C]29[/C][C]0.891688[/C][C]0.216624[/C][C]0.108312[/C][/ROW]
[ROW][C]30[/C][C]0.866074[/C][C]0.267853[/C][C]0.133926[/C][/ROW]
[ROW][C]31[/C][C]0.867216[/C][C]0.265567[/C][C]0.132784[/C][/ROW]
[ROW][C]32[/C][C]0.835306[/C][C]0.329388[/C][C]0.164694[/C][/ROW]
[ROW][C]33[/C][C]0.807792[/C][C]0.384417[/C][C]0.192208[/C][/ROW]
[ROW][C]34[/C][C]0.767794[/C][C]0.464413[/C][C]0.232206[/C][/ROW]
[ROW][C]35[/C][C]0.723121[/C][C]0.553757[/C][C]0.276879[/C][/ROW]
[ROW][C]36[/C][C]0.737962[/C][C]0.524076[/C][C]0.262038[/C][/ROW]
[ROW][C]37[/C][C]0.805624[/C][C]0.388752[/C][C]0.194376[/C][/ROW]
[ROW][C]38[/C][C]0.767861[/C][C]0.464278[/C][C]0.232139[/C][/ROW]
[ROW][C]39[/C][C]0.733837[/C][C]0.532327[/C][C]0.266163[/C][/ROW]
[ROW][C]40[/C][C]0.73749[/C][C]0.52502[/C][C]0.26251[/C][/ROW]
[ROW][C]41[/C][C]0.72647[/C][C]0.547061[/C][C]0.27353[/C][/ROW]
[ROW][C]42[/C][C]0.705407[/C][C]0.589185[/C][C]0.294593[/C][/ROW]
[ROW][C]43[/C][C]0.772522[/C][C]0.454956[/C][C]0.227478[/C][/ROW]
[ROW][C]44[/C][C]0.736776[/C][C]0.526449[/C][C]0.263224[/C][/ROW]
[ROW][C]45[/C][C]0.698463[/C][C]0.603074[/C][C]0.301537[/C][/ROW]
[ROW][C]46[/C][C]0.676518[/C][C]0.646965[/C][C]0.323482[/C][/ROW]
[ROW][C]47[/C][C]0.706398[/C][C]0.587203[/C][C]0.293602[/C][/ROW]
[ROW][C]48[/C][C]0.670014[/C][C]0.659971[/C][C]0.329986[/C][/ROW]
[ROW][C]49[/C][C]0.714885[/C][C]0.57023[/C][C]0.285115[/C][/ROW]
[ROW][C]50[/C][C]0.68767[/C][C]0.624661[/C][C]0.31233[/C][/ROW]
[ROW][C]51[/C][C]0.674518[/C][C]0.650963[/C][C]0.325482[/C][/ROW]
[ROW][C]52[/C][C]0.637525[/C][C]0.724949[/C][C]0.362475[/C][/ROW]
[ROW][C]53[/C][C]0.639909[/C][C]0.720182[/C][C]0.360091[/C][/ROW]
[ROW][C]54[/C][C]0.597752[/C][C]0.804496[/C][C]0.402248[/C][/ROW]
[ROW][C]55[/C][C]0.615035[/C][C]0.76993[/C][C]0.384965[/C][/ROW]
[ROW][C]56[/C][C]0.632476[/C][C]0.735048[/C][C]0.367524[/C][/ROW]
[ROW][C]57[/C][C]0.608634[/C][C]0.782732[/C][C]0.391366[/C][/ROW]
[ROW][C]58[/C][C]0.644142[/C][C]0.711716[/C][C]0.355858[/C][/ROW]
[ROW][C]59[/C][C]0.664732[/C][C]0.670536[/C][C]0.335268[/C][/ROW]
[ROW][C]60[/C][C]0.639618[/C][C]0.720764[/C][C]0.360382[/C][/ROW]
[ROW][C]61[/C][C]0.652505[/C][C]0.69499[/C][C]0.347495[/C][/ROW]
[ROW][C]62[/C][C]0.615005[/C][C]0.769989[/C][C]0.384995[/C][/ROW]
[ROW][C]63[/C][C]0.591557[/C][C]0.816885[/C][C]0.408443[/C][/ROW]
[ROW][C]64[/C][C]0.549901[/C][C]0.900198[/C][C]0.450099[/C][/ROW]
[ROW][C]65[/C][C]0.507823[/C][C]0.984353[/C][C]0.492177[/C][/ROW]
[ROW][C]66[/C][C]0.517892[/C][C]0.964216[/C][C]0.482108[/C][/ROW]
[ROW][C]67[/C][C]0.522832[/C][C]0.954337[/C][C]0.477168[/C][/ROW]
[ROW][C]68[/C][C]0.498861[/C][C]0.997723[/C][C]0.501139[/C][/ROW]
[ROW][C]69[/C][C]0.457956[/C][C]0.915913[/C][C]0.542044[/C][/ROW]
[ROW][C]70[/C][C]0.433559[/C][C]0.867118[/C][C]0.566441[/C][/ROW]
[ROW][C]71[/C][C]0.394182[/C][C]0.788364[/C][C]0.605818[/C][/ROW]
[ROW][C]72[/C][C]0.371634[/C][C]0.743268[/C][C]0.628366[/C][/ROW]
[ROW][C]73[/C][C]0.344188[/C][C]0.688376[/C][C]0.655812[/C][/ROW]
[ROW][C]74[/C][C]0.328478[/C][C]0.656956[/C][C]0.671522[/C][/ROW]
[ROW][C]75[/C][C]0.302064[/C][C]0.604127[/C][C]0.697936[/C][/ROW]
[ROW][C]76[/C][C]0.459874[/C][C]0.919747[/C][C]0.540126[/C][/ROW]
[ROW][C]77[/C][C]0.439701[/C][C]0.879402[/C][C]0.560299[/C][/ROW]
[ROW][C]78[/C][C]0.46441[/C][C]0.92882[/C][C]0.53559[/C][/ROW]
[ROW][C]79[/C][C]0.42728[/C][C]0.854559[/C][C]0.57272[/C][/ROW]
[ROW][C]80[/C][C]0.522043[/C][C]0.955915[/C][C]0.477957[/C][/ROW]
[ROW][C]81[/C][C]0.487604[/C][C]0.975207[/C][C]0.512396[/C][/ROW]
[ROW][C]82[/C][C]0.503195[/C][C]0.993609[/C][C]0.496805[/C][/ROW]
[ROW][C]83[/C][C]0.4658[/C][C]0.931601[/C][C]0.5342[/C][/ROW]
[ROW][C]84[/C][C]0.428089[/C][C]0.856177[/C][C]0.571911[/C][/ROW]
[ROW][C]85[/C][C]0.391334[/C][C]0.782668[/C][C]0.608666[/C][/ROW]
[ROW][C]86[/C][C]0.357931[/C][C]0.715863[/C][C]0.642069[/C][/ROW]
[ROW][C]87[/C][C]0.32725[/C][C]0.6545[/C][C]0.67275[/C][/ROW]
[ROW][C]88[/C][C]0.295384[/C][C]0.590768[/C][C]0.704616[/C][/ROW]
[ROW][C]89[/C][C]0.382039[/C][C]0.764077[/C][C]0.617961[/C][/ROW]
[ROW][C]90[/C][C]0.35684[/C][C]0.71368[/C][C]0.64316[/C][/ROW]
[ROW][C]91[/C][C]0.328728[/C][C]0.657457[/C][C]0.671272[/C][/ROW]
[ROW][C]92[/C][C]0.298799[/C][C]0.597597[/C][C]0.701201[/C][/ROW]
[ROW][C]93[/C][C]0.293915[/C][C]0.58783[/C][C]0.706085[/C][/ROW]
[ROW][C]94[/C][C]0.266345[/C][C]0.532691[/C][C]0.733655[/C][/ROW]
[ROW][C]95[/C][C]0.236197[/C][C]0.472394[/C][C]0.763803[/C][/ROW]
[ROW][C]96[/C][C]0.223019[/C][C]0.446038[/C][C]0.776981[/C][/ROW]
[ROW][C]97[/C][C]0.2047[/C][C]0.409399[/C][C]0.7953[/C][/ROW]
[ROW][C]98[/C][C]0.180054[/C][C]0.360107[/C][C]0.819946[/C][/ROW]
[ROW][C]99[/C][C]0.173252[/C][C]0.346503[/C][C]0.826748[/C][/ROW]
[ROW][C]100[/C][C]0.151441[/C][C]0.302882[/C][C]0.848559[/C][/ROW]
[ROW][C]101[/C][C]0.142683[/C][C]0.285366[/C][C]0.857317[/C][/ROW]
[ROW][C]102[/C][C]0.126914[/C][C]0.253827[/C][C]0.873086[/C][/ROW]
[ROW][C]103[/C][C]0.154883[/C][C]0.309766[/C][C]0.845117[/C][/ROW]
[ROW][C]104[/C][C]0.177746[/C][C]0.355493[/C][C]0.822254[/C][/ROW]
[ROW][C]105[/C][C]0.184502[/C][C]0.369005[/C][C]0.815498[/C][/ROW]
[ROW][C]106[/C][C]0.161117[/C][C]0.322234[/C][C]0.838883[/C][/ROW]
[ROW][C]107[/C][C]0.181394[/C][C]0.362788[/C][C]0.818606[/C][/ROW]
[ROW][C]108[/C][C]0.165892[/C][C]0.331784[/C][C]0.834108[/C][/ROW]
[ROW][C]109[/C][C]0.289785[/C][C]0.57957[/C][C]0.710215[/C][/ROW]
[ROW][C]110[/C][C]0.282137[/C][C]0.564274[/C][C]0.717863[/C][/ROW]
[ROW][C]111[/C][C]0.253891[/C][C]0.507783[/C][C]0.746109[/C][/ROW]
[ROW][C]112[/C][C]0.241986[/C][C]0.483972[/C][C]0.758014[/C][/ROW]
[ROW][C]113[/C][C]0.214881[/C][C]0.429763[/C][C]0.785119[/C][/ROW]
[ROW][C]114[/C][C]0.198393[/C][C]0.396786[/C][C]0.801607[/C][/ROW]
[ROW][C]115[/C][C]0.174983[/C][C]0.349967[/C][C]0.825017[/C][/ROW]
[ROW][C]116[/C][C]0.15276[/C][C]0.30552[/C][C]0.84724[/C][/ROW]
[ROW][C]117[/C][C]0.134001[/C][C]0.268001[/C][C]0.865999[/C][/ROW]
[ROW][C]118[/C][C]0.16575[/C][C]0.331501[/C][C]0.83425[/C][/ROW]
[ROW][C]119[/C][C]0.169366[/C][C]0.338733[/C][C]0.830634[/C][/ROW]
[ROW][C]120[/C][C]0.148625[/C][C]0.297251[/C][C]0.851375[/C][/ROW]
[ROW][C]121[/C][C]0.136013[/C][C]0.272026[/C][C]0.863987[/C][/ROW]
[ROW][C]122[/C][C]0.118979[/C][C]0.237958[/C][C]0.881021[/C][/ROW]
[ROW][C]123[/C][C]0.14089[/C][C]0.281779[/C][C]0.85911[/C][/ROW]
[ROW][C]124[/C][C]0.125207[/C][C]0.250415[/C][C]0.874793[/C][/ROW]
[ROW][C]125[/C][C]0.118861[/C][C]0.237722[/C][C]0.881139[/C][/ROW]
[ROW][C]126[/C][C]0.110688[/C][C]0.221376[/C][C]0.889312[/C][/ROW]
[ROW][C]127[/C][C]0.0963336[/C][C]0.192667[/C][C]0.903666[/C][/ROW]
[ROW][C]128[/C][C]0.0876619[/C][C]0.175324[/C][C]0.912338[/C][/ROW]
[ROW][C]129[/C][C]0.0746388[/C][C]0.149278[/C][C]0.925361[/C][/ROW]
[ROW][C]130[/C][C]0.0749285[/C][C]0.149857[/C][C]0.925071[/C][/ROW]
[ROW][C]131[/C][C]0.0763343[/C][C]0.152669[/C][C]0.923666[/C][/ROW]
[ROW][C]132[/C][C]0.0708909[/C][C]0.141782[/C][C]0.929109[/C][/ROW]
[ROW][C]133[/C][C]0.0649318[/C][C]0.129864[/C][C]0.935068[/C][/ROW]
[ROW][C]134[/C][C]0.054498[/C][C]0.108996[/C][C]0.945502[/C][/ROW]
[ROW][C]135[/C][C]0.0564629[/C][C]0.112926[/C][C]0.943537[/C][/ROW]
[ROW][C]136[/C][C]0.119796[/C][C]0.239592[/C][C]0.880204[/C][/ROW]
[ROW][C]137[/C][C]0.103131[/C][C]0.206261[/C][C]0.896869[/C][/ROW]
[ROW][C]138[/C][C]0.0888483[/C][C]0.177697[/C][C]0.911152[/C][/ROW]
[ROW][C]139[/C][C]0.0833872[/C][C]0.166774[/C][C]0.916613[/C][/ROW]
[ROW][C]140[/C][C]0.0800082[/C][C]0.160016[/C][C]0.919992[/C][/ROW]
[ROW][C]141[/C][C]0.0876889[/C][C]0.175378[/C][C]0.912311[/C][/ROW]
[ROW][C]142[/C][C]0.0879624[/C][C]0.175925[/C][C]0.912038[/C][/ROW]
[ROW][C]143[/C][C]0.0746224[/C][C]0.149245[/C][C]0.925378[/C][/ROW]
[ROW][C]144[/C][C]0.0628439[/C][C]0.125688[/C][C]0.937156[/C][/ROW]
[ROW][C]145[/C][C]0.0526072[/C][C]0.105214[/C][C]0.947393[/C][/ROW]
[ROW][C]146[/C][C]0.0441611[/C][C]0.0883223[/C][C]0.955839[/C][/ROW]
[ROW][C]147[/C][C]0.0459406[/C][C]0.0918811[/C][C]0.954059[/C][/ROW]
[ROW][C]148[/C][C]0.0499372[/C][C]0.0998743[/C][C]0.950063[/C][/ROW]
[ROW][C]149[/C][C]0.0474152[/C][C]0.0948305[/C][C]0.952585[/C][/ROW]
[ROW][C]150[/C][C]0.0398398[/C][C]0.0796796[/C][C]0.96016[/C][/ROW]
[ROW][C]151[/C][C]0.0463745[/C][C]0.092749[/C][C]0.953626[/C][/ROW]
[ROW][C]152[/C][C]0.046025[/C][C]0.0920501[/C][C]0.953975[/C][/ROW]
[ROW][C]153[/C][C]0.0444129[/C][C]0.0888258[/C][C]0.955587[/C][/ROW]
[ROW][C]154[/C][C]0.0413534[/C][C]0.0827068[/C][C]0.958647[/C][/ROW]
[ROW][C]155[/C][C]0.0509416[/C][C]0.101883[/C][C]0.949058[/C][/ROW]
[ROW][C]156[/C][C]0.0428111[/C][C]0.0856222[/C][C]0.957189[/C][/ROW]
[ROW][C]157[/C][C]0.035339[/C][C]0.070678[/C][C]0.964661[/C][/ROW]
[ROW][C]158[/C][C]0.0315303[/C][C]0.0630605[/C][C]0.96847[/C][/ROW]
[ROW][C]159[/C][C]0.0396783[/C][C]0.0793566[/C][C]0.960322[/C][/ROW]
[ROW][C]160[/C][C]0.0473151[/C][C]0.0946303[/C][C]0.952685[/C][/ROW]
[ROW][C]161[/C][C]0.0421252[/C][C]0.0842503[/C][C]0.957875[/C][/ROW]
[ROW][C]162[/C][C]0.111672[/C][C]0.223345[/C][C]0.888328[/C][/ROW]
[ROW][C]163[/C][C]0.0979619[/C][C]0.195924[/C][C]0.902038[/C][/ROW]
[ROW][C]164[/C][C]0.347856[/C][C]0.695713[/C][C]0.652144[/C][/ROW]
[ROW][C]165[/C][C]0.32909[/C][C]0.658179[/C][C]0.67091[/C][/ROW]
[ROW][C]166[/C][C]0.446423[/C][C]0.892846[/C][C]0.553577[/C][/ROW]
[ROW][C]167[/C][C]0.414007[/C][C]0.828015[/C][C]0.585993[/C][/ROW]
[ROW][C]168[/C][C]0.383167[/C][C]0.766335[/C][C]0.616833[/C][/ROW]
[ROW][C]169[/C][C]0.348323[/C][C]0.696646[/C][C]0.651677[/C][/ROW]
[ROW][C]170[/C][C]0.320619[/C][C]0.641238[/C][C]0.679381[/C][/ROW]
[ROW][C]171[/C][C]0.333029[/C][C]0.666057[/C][C]0.666971[/C][/ROW]
[ROW][C]172[/C][C]0.300224[/C][C]0.600447[/C][C]0.699776[/C][/ROW]
[ROW][C]173[/C][C]0.353803[/C][C]0.707606[/C][C]0.646197[/C][/ROW]
[ROW][C]174[/C][C]0.337927[/C][C]0.675854[/C][C]0.662073[/C][/ROW]
[ROW][C]175[/C][C]0.313426[/C][C]0.626853[/C][C]0.686574[/C][/ROW]
[ROW][C]176[/C][C]0.373546[/C][C]0.747092[/C][C]0.626454[/C][/ROW]
[ROW][C]177[/C][C]0.34557[/C][C]0.691141[/C][C]0.65443[/C][/ROW]
[ROW][C]178[/C][C]0.351503[/C][C]0.703006[/C][C]0.648497[/C][/ROW]
[ROW][C]179[/C][C]0.334969[/C][C]0.669939[/C][C]0.665031[/C][/ROW]
[ROW][C]180[/C][C]0.310529[/C][C]0.621059[/C][C]0.689471[/C][/ROW]
[ROW][C]181[/C][C]0.328036[/C][C]0.656072[/C][C]0.671964[/C][/ROW]
[ROW][C]182[/C][C]0.430598[/C][C]0.861196[/C][C]0.569402[/C][/ROW]
[ROW][C]183[/C][C]0.405964[/C][C]0.811928[/C][C]0.594036[/C][/ROW]
[ROW][C]184[/C][C]0.404404[/C][C]0.808808[/C][C]0.595596[/C][/ROW]
[ROW][C]185[/C][C]0.384728[/C][C]0.769455[/C][C]0.615272[/C][/ROW]
[ROW][C]186[/C][C]0.484435[/C][C]0.96887[/C][C]0.515565[/C][/ROW]
[ROW][C]187[/C][C]0.448427[/C][C]0.896854[/C][C]0.551573[/C][/ROW]
[ROW][C]188[/C][C]0.409718[/C][C]0.819436[/C][C]0.590282[/C][/ROW]
[ROW][C]189[/C][C]0.378732[/C][C]0.757464[/C][C]0.621268[/C][/ROW]
[ROW][C]190[/C][C]0.444056[/C][C]0.888111[/C][C]0.555944[/C][/ROW]
[ROW][C]191[/C][C]0.545393[/C][C]0.909215[/C][C]0.454607[/C][/ROW]
[ROW][C]192[/C][C]0.569563[/C][C]0.860875[/C][C]0.430437[/C][/ROW]
[ROW][C]193[/C][C]0.562644[/C][C]0.874712[/C][C]0.437356[/C][/ROW]
[ROW][C]194[/C][C]0.528573[/C][C]0.942855[/C][C]0.471427[/C][/ROW]
[ROW][C]195[/C][C]0.500782[/C][C]0.998437[/C][C]0.499218[/C][/ROW]
[ROW][C]196[/C][C]0.529523[/C][C]0.940953[/C][C]0.470477[/C][/ROW]
[ROW][C]197[/C][C]0.720258[/C][C]0.559484[/C][C]0.279742[/C][/ROW]
[ROW][C]198[/C][C]0.725788[/C][C]0.548423[/C][C]0.274212[/C][/ROW]
[ROW][C]199[/C][C]0.69015[/C][C]0.6197[/C][C]0.30985[/C][/ROW]
[ROW][C]200[/C][C]0.652442[/C][C]0.695116[/C][C]0.347558[/C][/ROW]
[ROW][C]201[/C][C]0.612379[/C][C]0.775241[/C][C]0.387621[/C][/ROW]
[ROW][C]202[/C][C]0.573016[/C][C]0.853967[/C][C]0.426984[/C][/ROW]
[ROW][C]203[/C][C]0.536224[/C][C]0.927551[/C][C]0.463776[/C][/ROW]
[ROW][C]204[/C][C]0.52022[/C][C]0.95956[/C][C]0.47978[/C][/ROW]
[ROW][C]205[/C][C]0.484813[/C][C]0.969627[/C][C]0.515187[/C][/ROW]
[ROW][C]206[/C][C]0.442287[/C][C]0.884575[/C][C]0.557713[/C][/ROW]
[ROW][C]207[/C][C]0.3989[/C][C]0.7978[/C][C]0.6011[/C][/ROW]
[ROW][C]208[/C][C]0.365472[/C][C]0.730944[/C][C]0.634528[/C][/ROW]
[ROW][C]209[/C][C]0.324366[/C][C]0.648732[/C][C]0.675634[/C][/ROW]
[ROW][C]210[/C][C]0.303917[/C][C]0.607833[/C][C]0.696083[/C][/ROW]
[ROW][C]211[/C][C]0.277064[/C][C]0.554128[/C][C]0.722936[/C][/ROW]
[ROW][C]212[/C][C]0.241795[/C][C]0.483591[/C][C]0.758205[/C][/ROW]
[ROW][C]213[/C][C]0.2756[/C][C]0.551201[/C][C]0.7244[/C][/ROW]
[ROW][C]214[/C][C]0.255311[/C][C]0.510621[/C][C]0.744689[/C][/ROW]
[ROW][C]215[/C][C]0.22255[/C][C]0.4451[/C][C]0.77745[/C][/ROW]
[ROW][C]216[/C][C]0.191289[/C][C]0.382577[/C][C]0.808711[/C][/ROW]
[ROW][C]217[/C][C]0.179644[/C][C]0.359289[/C][C]0.820356[/C][/ROW]
[ROW][C]218[/C][C]0.150719[/C][C]0.301439[/C][C]0.849281[/C][/ROW]
[ROW][C]219[/C][C]0.150886[/C][C]0.301773[/C][C]0.849114[/C][/ROW]
[ROW][C]220[/C][C]0.150873[/C][C]0.301746[/C][C]0.849127[/C][/ROW]
[ROW][C]221[/C][C]0.157048[/C][C]0.314096[/C][C]0.842952[/C][/ROW]
[ROW][C]222[/C][C]0.135124[/C][C]0.270248[/C][C]0.864876[/C][/ROW]
[ROW][C]223[/C][C]0.111304[/C][C]0.222609[/C][C]0.888696[/C][/ROW]
[ROW][C]224[/C][C]0.112893[/C][C]0.225787[/C][C]0.887107[/C][/ROW]
[ROW][C]225[/C][C]0.096584[/C][C]0.193168[/C][C]0.903416[/C][/ROW]
[ROW][C]226[/C][C]0.0789496[/C][C]0.157899[/C][C]0.92105[/C][/ROW]
[ROW][C]227[/C][C]0.0616564[/C][C]0.123313[/C][C]0.938344[/C][/ROW]
[ROW][C]228[/C][C]0.0716108[/C][C]0.143222[/C][C]0.928389[/C][/ROW]
[ROW][C]229[/C][C]0.0981656[/C][C]0.196331[/C][C]0.901834[/C][/ROW]
[ROW][C]230[/C][C]0.0943828[/C][C]0.188766[/C][C]0.905617[/C][/ROW]
[ROW][C]231[/C][C]0.0740903[/C][C]0.148181[/C][C]0.92591[/C][/ROW]
[ROW][C]232[/C][C]0.0694647[/C][C]0.138929[/C][C]0.930535[/C][/ROW]
[ROW][C]233[/C][C]0.132875[/C][C]0.265751[/C][C]0.867125[/C][/ROW]
[ROW][C]234[/C][C]0.145365[/C][C]0.290729[/C][C]0.854635[/C][/ROW]
[ROW][C]235[/C][C]0.14177[/C][C]0.283541[/C][C]0.85823[/C][/ROW]
[ROW][C]236[/C][C]0.11367[/C][C]0.227341[/C][C]0.88633[/C][/ROW]
[ROW][C]237[/C][C]0.159429[/C][C]0.318858[/C][C]0.840571[/C][/ROW]
[ROW][C]238[/C][C]0.210719[/C][C]0.421437[/C][C]0.789281[/C][/ROW]
[ROW][C]239[/C][C]0.332267[/C][C]0.664534[/C][C]0.667733[/C][/ROW]
[ROW][C]240[/C][C]0.330705[/C][C]0.66141[/C][C]0.669295[/C][/ROW]
[ROW][C]241[/C][C]0.281612[/C][C]0.563223[/C][C]0.718388[/C][/ROW]
[ROW][C]242[/C][C]0.339497[/C][C]0.678994[/C][C]0.660503[/C][/ROW]
[ROW][C]243[/C][C]0.273767[/C][C]0.547534[/C][C]0.726233[/C][/ROW]
[ROW][C]244[/C][C]0.213143[/C][C]0.426285[/C][C]0.786857[/C][/ROW]
[ROW][C]245[/C][C]0.287321[/C][C]0.574641[/C][C]0.712679[/C][/ROW]
[ROW][C]246[/C][C]0.310825[/C][C]0.621651[/C][C]0.689175[/C][/ROW]
[ROW][C]247[/C][C]0.237414[/C][C]0.474828[/C][C]0.762586[/C][/ROW]
[ROW][C]248[/C][C]0.298526[/C][C]0.597051[/C][C]0.701474[/C][/ROW]
[ROW][C]249[/C][C]0.299235[/C][C]0.59847[/C][C]0.700765[/C][/ROW]
[ROW][C]250[/C][C]0.283129[/C][C]0.566258[/C][C]0.716871[/C][/ROW]
[ROW][C]251[/C][C]0.327198[/C][C]0.654396[/C][C]0.672802[/C][/ROW]
[ROW][C]252[/C][C]0.946919[/C][C]0.106162[/C][C]0.0530812[/C][/ROW]
[ROW][C]253[/C][C]0.906264[/C][C]0.187472[/C][C]0.0937362[/C][/ROW]
[ROW][C]254[/C][C]0.947599[/C][C]0.104802[/C][C]0.0524011[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225425&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225425&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.8377510.3244970.162249
110.7452160.5095690.254784
120.9994180.001164320.000582162
130.9987470.002506450.00125323
140.9974080.005184310.00259215
150.9955550.008890090.00444505
160.9918910.01621880.00810941
170.9863430.02731420.0136571
180.9785180.0429630.0214815
190.9795440.04091230.0204562
200.9684560.06308810.031544
210.9569070.08618650.0430933
220.9414060.1171870.0585935
230.9270460.1459080.0729541
240.9012130.1975740.0987868
250.8744510.2510970.125549
260.9450050.1099910.0549953
270.9255690.1488620.0744309
280.9098140.1803720.0901858
290.8916880.2166240.108312
300.8660740.2678530.133926
310.8672160.2655670.132784
320.8353060.3293880.164694
330.8077920.3844170.192208
340.7677940.4644130.232206
350.7231210.5537570.276879
360.7379620.5240760.262038
370.8056240.3887520.194376
380.7678610.4642780.232139
390.7338370.5323270.266163
400.737490.525020.26251
410.726470.5470610.27353
420.7054070.5891850.294593
430.7725220.4549560.227478
440.7367760.5264490.263224
450.6984630.6030740.301537
460.6765180.6469650.323482
470.7063980.5872030.293602
480.6700140.6599710.329986
490.7148850.570230.285115
500.687670.6246610.31233
510.6745180.6509630.325482
520.6375250.7249490.362475
530.6399090.7201820.360091
540.5977520.8044960.402248
550.6150350.769930.384965
560.6324760.7350480.367524
570.6086340.7827320.391366
580.6441420.7117160.355858
590.6647320.6705360.335268
600.6396180.7207640.360382
610.6525050.694990.347495
620.6150050.7699890.384995
630.5915570.8168850.408443
640.5499010.9001980.450099
650.5078230.9843530.492177
660.5178920.9642160.482108
670.5228320.9543370.477168
680.4988610.9977230.501139
690.4579560.9159130.542044
700.4335590.8671180.566441
710.3941820.7883640.605818
720.3716340.7432680.628366
730.3441880.6883760.655812
740.3284780.6569560.671522
750.3020640.6041270.697936
760.4598740.9197470.540126
770.4397010.8794020.560299
780.464410.928820.53559
790.427280.8545590.57272
800.5220430.9559150.477957
810.4876040.9752070.512396
820.5031950.9936090.496805
830.46580.9316010.5342
840.4280890.8561770.571911
850.3913340.7826680.608666
860.3579310.7158630.642069
870.327250.65450.67275
880.2953840.5907680.704616
890.3820390.7640770.617961
900.356840.713680.64316
910.3287280.6574570.671272
920.2987990.5975970.701201
930.2939150.587830.706085
940.2663450.5326910.733655
950.2361970.4723940.763803
960.2230190.4460380.776981
970.20470.4093990.7953
980.1800540.3601070.819946
990.1732520.3465030.826748
1000.1514410.3028820.848559
1010.1426830.2853660.857317
1020.1269140.2538270.873086
1030.1548830.3097660.845117
1040.1777460.3554930.822254
1050.1845020.3690050.815498
1060.1611170.3222340.838883
1070.1813940.3627880.818606
1080.1658920.3317840.834108
1090.2897850.579570.710215
1100.2821370.5642740.717863
1110.2538910.5077830.746109
1120.2419860.4839720.758014
1130.2148810.4297630.785119
1140.1983930.3967860.801607
1150.1749830.3499670.825017
1160.152760.305520.84724
1170.1340010.2680010.865999
1180.165750.3315010.83425
1190.1693660.3387330.830634
1200.1486250.2972510.851375
1210.1360130.2720260.863987
1220.1189790.2379580.881021
1230.140890.2817790.85911
1240.1252070.2504150.874793
1250.1188610.2377220.881139
1260.1106880.2213760.889312
1270.09633360.1926670.903666
1280.08766190.1753240.912338
1290.07463880.1492780.925361
1300.07492850.1498570.925071
1310.07633430.1526690.923666
1320.07089090.1417820.929109
1330.06493180.1298640.935068
1340.0544980.1089960.945502
1350.05646290.1129260.943537
1360.1197960.2395920.880204
1370.1031310.2062610.896869
1380.08884830.1776970.911152
1390.08338720.1667740.916613
1400.08000820.1600160.919992
1410.08768890.1753780.912311
1420.08796240.1759250.912038
1430.07462240.1492450.925378
1440.06284390.1256880.937156
1450.05260720.1052140.947393
1460.04416110.08832230.955839
1470.04594060.09188110.954059
1480.04993720.09987430.950063
1490.04741520.09483050.952585
1500.03983980.07967960.96016
1510.04637450.0927490.953626
1520.0460250.09205010.953975
1530.04441290.08882580.955587
1540.04135340.08270680.958647
1550.05094160.1018830.949058
1560.04281110.08562220.957189
1570.0353390.0706780.964661
1580.03153030.06306050.96847
1590.03967830.07935660.960322
1600.04731510.09463030.952685
1610.04212520.08425030.957875
1620.1116720.2233450.888328
1630.09796190.1959240.902038
1640.3478560.6957130.652144
1650.329090.6581790.67091
1660.4464230.8928460.553577
1670.4140070.8280150.585993
1680.3831670.7663350.616833
1690.3483230.6966460.651677
1700.3206190.6412380.679381
1710.3330290.6660570.666971
1720.3002240.6004470.699776
1730.3538030.7076060.646197
1740.3379270.6758540.662073
1750.3134260.6268530.686574
1760.3735460.7470920.626454
1770.345570.6911410.65443
1780.3515030.7030060.648497
1790.3349690.6699390.665031
1800.3105290.6210590.689471
1810.3280360.6560720.671964
1820.4305980.8611960.569402
1830.4059640.8119280.594036
1840.4044040.8088080.595596
1850.3847280.7694550.615272
1860.4844350.968870.515565
1870.4484270.8968540.551573
1880.4097180.8194360.590282
1890.3787320.7574640.621268
1900.4440560.8881110.555944
1910.5453930.9092150.454607
1920.5695630.8608750.430437
1930.5626440.8747120.437356
1940.5285730.9428550.471427
1950.5007820.9984370.499218
1960.5295230.9409530.470477
1970.7202580.5594840.279742
1980.7257880.5484230.274212
1990.690150.61970.30985
2000.6524420.6951160.347558
2010.6123790.7752410.387621
2020.5730160.8539670.426984
2030.5362240.9275510.463776
2040.520220.959560.47978
2050.4848130.9696270.515187
2060.4422870.8845750.557713
2070.39890.79780.6011
2080.3654720.7309440.634528
2090.3243660.6487320.675634
2100.3039170.6078330.696083
2110.2770640.5541280.722936
2120.2417950.4835910.758205
2130.27560.5512010.7244
2140.2553110.5106210.744689
2150.222550.44510.77745
2160.1912890.3825770.808711
2170.1796440.3592890.820356
2180.1507190.3014390.849281
2190.1508860.3017730.849114
2200.1508730.3017460.849127
2210.1570480.3140960.842952
2220.1351240.2702480.864876
2230.1113040.2226090.888696
2240.1128930.2257870.887107
2250.0965840.1931680.903416
2260.07894960.1578990.92105
2270.06165640.1233130.938344
2280.07161080.1432220.928389
2290.09816560.1963310.901834
2300.09438280.1887660.905617
2310.07409030.1481810.92591
2320.06946470.1389290.930535
2330.1328750.2657510.867125
2340.1453650.2907290.854635
2350.141770.2835410.85823
2360.113670.2273410.88633
2370.1594290.3188580.840571
2380.2107190.4214370.789281
2390.3322670.6645340.667733
2400.3307050.661410.669295
2410.2816120.5632230.718388
2420.3394970.6789940.660503
2430.2737670.5475340.726233
2440.2131430.4262850.786857
2450.2873210.5746410.712679
2460.3108250.6216510.689175
2470.2374140.4748280.762586
2480.2985260.5970510.701474
2490.2992350.598470.700765
2500.2831290.5662580.716871
2510.3271980.6543960.672802
2520.9469190.1061620.0530812
2530.9062640.1874720.0937362
2540.9475990.1048020.0524011






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level40.0163265NOK
5% type I error level80.0326531OK
10% type I error level250.102041NOK

\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 & 4 & 0.0163265 & NOK \tabularnewline
5% type I error level & 8 & 0.0326531 & OK \tabularnewline
10% type I error level & 25 & 0.102041 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225425&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]4[/C][C]0.0163265[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]8[/C][C]0.0326531[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]25[/C][C]0.102041[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225425&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225425&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 level40.0163265NOK
5% type I error level80.0326531OK
10% type I error level250.102041NOK


Figures (Output of Computation)

Figure 1
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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')
}