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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 09 Nov 2014 20:30:20 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/09/t1415565031udf5gx9gd4wt9yc.htm/, Retrieved Fri, 17 May 2024 06:18:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=253225, Retrieved Fri, 17 May 2024 06:18:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact74

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-11-09 20:30:20] [e63466588bf3c49b37383cc70d2c7b07] [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 time8 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 & 8 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253225&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]8 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=253225&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253225&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 time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Depression[t] = + 28.442 -0.0255287Connected[t] + 0.00568142Separate[t] -0.069574Learning[t] -0.00863213Software[t] -0.693151Happiness[t] -0.058051Sport1[t] + 0.00289983t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Depression[t] =  +  28.442 -0.0255287Connected[t] +  0.00568142Separate[t] -0.069574Learning[t] -0.00863213Software[t] -0.693151Happiness[t] -0.058051Sport1[t] +  0.00289983t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253225&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Depression[t] =  +  28.442 -0.0255287Connected[t] +  0.00568142Separate[t] -0.069574Learning[t] -0.00863213Software[t] -0.693151Happiness[t] -0.058051Sport1[t] +  0.00289983t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253225&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253225&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] = + 28.442 -0.0255287Connected[t] + 0.00568142Separate[t] -0.069574Learning[t] -0.00863213Software[t] -0.693151Happiness[t] -0.058051Sport1[t] + 0.00289983t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)28.4422.3529212.096.48065e-273.24033e-27
Connected-0.02552870.0515295-0.49540.620730.310365
Separate0.005681420.0525920.1080.9140580.457029
Learning-0.0695740.0933401-0.74540.4567250.228362
Software-0.008632130.0957857-0.090120.9282630.464131
Happiness-0.6931510.0750746-9.2331.03729e-175.18647e-18
Sport1-0.0580510.0173837-3.3390.0009646020.000482301
t0.002899830.002547021.1390.2559690.127984

\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) & 28.442 & 2.35292 & 12.09 & 6.48065e-27 & 3.24033e-27 \tabularnewline
Connected & -0.0255287 & 0.0515295 & -0.4954 & 0.62073 & 0.310365 \tabularnewline
Separate & 0.00568142 & 0.052592 & 0.108 & 0.914058 & 0.457029 \tabularnewline
Learning & -0.069574 & 0.0933401 & -0.7454 & 0.456725 & 0.228362 \tabularnewline
Software & -0.00863213 & 0.0957857 & -0.09012 & 0.928263 & 0.464131 \tabularnewline
Happiness & -0.693151 & 0.0750746 & -9.233 & 1.03729e-17 & 5.18647e-18 \tabularnewline
Sport1 & -0.058051 & 0.0173837 & -3.339 & 0.000964602 & 0.000482301 \tabularnewline
t & 0.00289983 & 0.00254702 & 1.139 & 0.255969 & 0.127984 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253225&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]28.442[/C][C]2.35292[/C][C]12.09[/C][C]6.48065e-27[/C][C]3.24033e-27[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0255287[/C][C]0.0515295[/C][C]-0.4954[/C][C]0.62073[/C][C]0.310365[/C][/ROW]
[ROW][C]Separate[/C][C]0.00568142[/C][C]0.052592[/C][C]0.108[/C][C]0.914058[/C][C]0.457029[/C][/ROW]
[ROW][C]Learning[/C][C]-0.069574[/C][C]0.0933401[/C][C]-0.7454[/C][C]0.456725[/C][C]0.228362[/C][/ROW]
[ROW][C]Software[/C][C]-0.00863213[/C][C]0.0957857[/C][C]-0.09012[/C][C]0.928263[/C][C]0.464131[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.693151[/C][C]0.0750746[/C][C]-9.233[/C][C]1.03729e-17[/C][C]5.18647e-18[/C][/ROW]
[ROW][C]Sport1[/C][C]-0.058051[/C][C]0.0173837[/C][C]-3.339[/C][C]0.000964602[/C][C]0.000482301[/C][/ROW]
[ROW][C]t[/C][C]0.00289983[/C][C]0.00254702[/C][C]1.139[/C][C]0.255969[/C][C]0.127984[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253225&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253225&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)28.4422.3529212.096.48065e-273.24033e-27
Connected-0.02552870.0515295-0.49540.620730.310365
Separate0.005681420.0525920.1080.9140580.457029
Learning-0.0695740.0933401-0.74540.4567250.228362
Software-0.008632130.0957857-0.090120.9282630.464131
Happiness-0.6931510.0750746-9.2331.03729e-175.18647e-18
Sport1-0.0580510.0173837-3.3390.0009646020.000482301
t0.002899830.002547021.1390.2559690.127984






Multiple Linear Regression - Regression Statistics
Multiple R0.615302
R-squared0.378597
Adjusted R-squared0.361605
F-TEST (value)22.2815
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.77217
Sum Squared Residuals1967.33

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.615302 \tabularnewline
R-squared & 0.378597 \tabularnewline
Adjusted R-squared & 0.361605 \tabularnewline
F-TEST (value) & 22.2815 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 256 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.77217 \tabularnewline
Sum Squared Residuals & 1967.33 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253225&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.615302[/C][/ROW]
[ROW][C]R-squared[/C][C]0.378597[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.361605[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]22.2815[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]256[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.77217[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1967.33[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253225&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253225&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 R0.615302
R-squared0.378597
Adjusted R-squared0.361605
F-TEST (value)22.2815
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.77217
Sum Squared Residuals1967.33






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11213.8252-1.82525
2119.130891.86911
31414.9763-0.976266
41214.5471-2.54706
52111.21029.78982
6129.735172.26483
72213.43658.56351
81112.2891-1.28909
91011.9772-1.97725
101311.81191.18812
111010.1108-0.110825
12810.2295-2.22954
131515.6708-0.670753
141412.26961.73044
15109.013860.986137
161413.64070.359308
171412.56621.43381
18119.352871.64713
191012.9507-2.9507
201312.24880.751214
219.510.3572-0.857239
221415.1016-1.10162
231213.456-1.45597
241415.0118-1.0118
25119.638381.36162
26915.4751-6.4751
271111.0983-0.098309
281513.01691.98314
291411.72912.27088
301315.2741-2.27406
31911.0349-2.03493
321514.97770.0223432
331010.8037-0.803706
341111.3925-0.392506
351312.76840.231555
36811.9488-3.94875
372017.31612.68392
381212.2241-0.224134
391010.5959-0.595931
401013.636-3.63598
41911.9056-2.90559
421411.36142.63856
43812.0323-4.03227
441415.4667-1.46675
451112.2983-1.29833
461315.3886-2.38864
47912.5729-3.57294
481112.0423-1.04225
491510.59354.40653
501113.3563-2.35629
511011.4847-1.48474
521413.29240.707579
531815.74592.2541
541414.8041-0.804126
551115.322-4.32202
5614.512.02372.4763
571311.20191.79813
58912.5596-3.55957
591014.179-4.17895
601514.33480.665241
612018.49491.50512
621213.1472-1.1472
631214.4528-2.45278
641414.2433-0.243288
651313.1898-0.189843
661115.0795-4.07952
671715.08691.91311
681214.1239-2.1239
691312.88080.119231
701412.34211.65786
711313.524-0.523994
721512.78112.21887
731311.53471.4653
741012.1435-2.14346
751112.8409-1.84089
761913.61495.38514
771310.85842.14161
781713.75173.24829
791312.25720.742839
80914.5203-5.52033
811111.8389-0.8389
82912.2608-3.26083
831211.45030.549729
841212.3463-0.346329
851312.64860.35139
861312.140.859951
871213.1186-1.1186
881514.77620.223835
892217.98234.01771
901311.18231.81775
911514.51070.489306
921311.96431.03575
931512.44232.55765
9412.513.4816-0.981597
951110.99240.00761143
961614.42591.57407
971112.5829-1.58293
981110.27230.727683
991012.2472-2.24719
1001010.5369-0.536941
1011614.22551.77451
1021210.48321.51676
1031115.4882-4.48825
1041611.93134.06873
1051916.71332.28674
1061111.1895-0.1895
1071612.19153.80848
1081516.7606-1.76059
1092417.40186.59821
1101411.63992.36009
1111515.0055-0.00550164
1121112.7856-1.78563
1131515.2308-0.230776
1141210.21141.78862
1151010.5654-0.565366
1161414.2381-0.238062
1171313.5039-0.503931
118913.4315-4.43153
1191511.8763.12396
1201515.7058-0.705757
1211412.81351.18651
1221111.4754-0.475406
123812.0268-4.02683
1241112.2678-1.26785
1251113.3609-2.36091
12689.85547-1.85547
1271010.5515-0.551533
128119.181961.81804
1291312.60330.396724
1301113.8575-2.85745
1312017.42852.57155
1321011.9644-1.9644
1331513.20841.79158
1341212.3312-0.331243
1351411.00942.99063
1362316.5056.49501
1371413.67030.329746
1381616.6641-0.664108
1391113.1283-2.12826
1401214.3959-2.39594
1411013.5129-3.51286
1421411.21012.78988
1431212.2809-0.280917
1441212.1235-0.123523
1451110.99570.00430668
1461211.3350.664993
1471316.038-3.038
1481114.342-3.34197
1491916.70412.29587
1501211.34750.652463
1511713.26513.73495
152911.8278-2.82778
1531214.5513-2.55128
1541916.82472.17533
1551813.92144.07859
1561514.69920.300818
1571413.62470.375327
158119.268951.73105
159913.1215-4.12151
1601814.20693.7931
1611614.25541.74458
1622416.61657.38345
1631412.96081.0392
1642010.98089.01924
1651816.0331.96705
1662316.95696.04309
1671213.0468-1.04681
1681414.925-0.924968
1691616.2734-0.273392
1701816.7631.23695
1712016.47393.52609
1721211.74510.254913
1731216.4083-4.40829
1741715.22571.7743
1751311.98091.01905
176913.6568-4.65679
1771617.1084-1.10841
1781815.12682.87316
1791012.3056-2.30561
1801415.3711-1.37107
1811114.1967-3.19672
182914.5292-5.52921
1831112.4736-1.47358
1841012.6919-2.69189
1851111.6588-0.658778
1861913.72945.27063
1871412.98081.0192
1881211.82470.175349
1891415.4629-1.46288
1902116.40634.59367
1911317.4753-4.47525
1921012.9812-2.98122
1931513.10871.89134
1941615.88930.110693
1951412.80461.19537
1961214.7531-2.75311
1971912.84046.15961
1981512.41262.5874
1991918.1680.831998
2001313.8424-0.842358
2011716.96880.0312088
2021213.1224-1.12237
2031111.3584-0.358413
2041415.2632-1.2632
2051112.6976-1.69758
2061312.54430.455688
2071212.5124-0.512379
2081513.03031.96965
2091414.3903-0.390343
2101211.27380.726162
2111717.4813-0.48127
2121111.3549-0.35489
2131814.65073.34935
2141315.8483-2.84829
2151715.641.36005
2161313.2647-0.264652
2171110.4320.567954
2181212.689-0.689001
2192218.2973.70297
2201412.07791.92214
2211215.3323-3.33225
2221212.8025-0.802466
2231716.16960.830365
224912.9925-3.99246
2252119.00461.99544
2261012.2582-2.25819
2271111.1257-0.125693
2281215.4271-3.42713
2292318.2064.79401
2301315.839-2.83902
2311213.6323-1.63233
2321617.5784-1.57836
233913.5647-4.5647
2341713.69753.30245
235912.1764-3.17641
2361415.8436-1.84358
2371715.29541.70464
2381315.445-2.44496
2391116.2429-5.24289
2401215.8033-3.80333
2411014.3031-4.30314
2421918.89730.102657
2431616.1845-0.184521
2441615.33810.661899
2451412.09661.90336
2462016.07973.92026
2471514.530.469974
2482315.39217.60786
2492017.7122.288
2501616.4374-0.437384
2511413.28510.714944
2521714.2172.783
2531114.4305-3.43052
2541314.1364-1.1364
2551715.23791.76211
2561515.2276-0.227642
2572116.6954.305
2581817.69990.300051
2591513.15561.84444
260816.419-8.41895
2611214.1221-2.12208
2621213.336-1.33603
2632219.11112.88893
2641213.7135-1.71351

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 13.8252 & -1.82525 \tabularnewline
2 & 11 & 9.13089 & 1.86911 \tabularnewline
3 & 14 & 14.9763 & -0.976266 \tabularnewline
4 & 12 & 14.5471 & -2.54706 \tabularnewline
5 & 21 & 11.2102 & 9.78982 \tabularnewline
6 & 12 & 9.73517 & 2.26483 \tabularnewline
7 & 22 & 13.4365 & 8.56351 \tabularnewline
8 & 11 & 12.2891 & -1.28909 \tabularnewline
9 & 10 & 11.9772 & -1.97725 \tabularnewline
10 & 13 & 11.8119 & 1.18812 \tabularnewline
11 & 10 & 10.1108 & -0.110825 \tabularnewline
12 & 8 & 10.2295 & -2.22954 \tabularnewline
13 & 15 & 15.6708 & -0.670753 \tabularnewline
14 & 14 & 12.2696 & 1.73044 \tabularnewline
15 & 10 & 9.01386 & 0.986137 \tabularnewline
16 & 14 & 13.6407 & 0.359308 \tabularnewline
17 & 14 & 12.5662 & 1.43381 \tabularnewline
18 & 11 & 9.35287 & 1.64713 \tabularnewline
19 & 10 & 12.9507 & -2.9507 \tabularnewline
20 & 13 & 12.2488 & 0.751214 \tabularnewline
21 & 9.5 & 10.3572 & -0.857239 \tabularnewline
22 & 14 & 15.1016 & -1.10162 \tabularnewline
23 & 12 & 13.456 & -1.45597 \tabularnewline
24 & 14 & 15.0118 & -1.0118 \tabularnewline
25 & 11 & 9.63838 & 1.36162 \tabularnewline
26 & 9 & 15.4751 & -6.4751 \tabularnewline
27 & 11 & 11.0983 & -0.098309 \tabularnewline
28 & 15 & 13.0169 & 1.98314 \tabularnewline
29 & 14 & 11.7291 & 2.27088 \tabularnewline
30 & 13 & 15.2741 & -2.27406 \tabularnewline
31 & 9 & 11.0349 & -2.03493 \tabularnewline
32 & 15 & 14.9777 & 0.0223432 \tabularnewline
33 & 10 & 10.8037 & -0.803706 \tabularnewline
34 & 11 & 11.3925 & -0.392506 \tabularnewline
35 & 13 & 12.7684 & 0.231555 \tabularnewline
36 & 8 & 11.9488 & -3.94875 \tabularnewline
37 & 20 & 17.3161 & 2.68392 \tabularnewline
38 & 12 & 12.2241 & -0.224134 \tabularnewline
39 & 10 & 10.5959 & -0.595931 \tabularnewline
40 & 10 & 13.636 & -3.63598 \tabularnewline
41 & 9 & 11.9056 & -2.90559 \tabularnewline
42 & 14 & 11.3614 & 2.63856 \tabularnewline
43 & 8 & 12.0323 & -4.03227 \tabularnewline
44 & 14 & 15.4667 & -1.46675 \tabularnewline
45 & 11 & 12.2983 & -1.29833 \tabularnewline
46 & 13 & 15.3886 & -2.38864 \tabularnewline
47 & 9 & 12.5729 & -3.57294 \tabularnewline
48 & 11 & 12.0423 & -1.04225 \tabularnewline
49 & 15 & 10.5935 & 4.40653 \tabularnewline
50 & 11 & 13.3563 & -2.35629 \tabularnewline
51 & 10 & 11.4847 & -1.48474 \tabularnewline
52 & 14 & 13.2924 & 0.707579 \tabularnewline
53 & 18 & 15.7459 & 2.2541 \tabularnewline
54 & 14 & 14.8041 & -0.804126 \tabularnewline
55 & 11 & 15.322 & -4.32202 \tabularnewline
56 & 14.5 & 12.0237 & 2.4763 \tabularnewline
57 & 13 & 11.2019 & 1.79813 \tabularnewline
58 & 9 & 12.5596 & -3.55957 \tabularnewline
59 & 10 & 14.179 & -4.17895 \tabularnewline
60 & 15 & 14.3348 & 0.665241 \tabularnewline
61 & 20 & 18.4949 & 1.50512 \tabularnewline
62 & 12 & 13.1472 & -1.1472 \tabularnewline
63 & 12 & 14.4528 & -2.45278 \tabularnewline
64 & 14 & 14.2433 & -0.243288 \tabularnewline
65 & 13 & 13.1898 & -0.189843 \tabularnewline
66 & 11 & 15.0795 & -4.07952 \tabularnewline
67 & 17 & 15.0869 & 1.91311 \tabularnewline
68 & 12 & 14.1239 & -2.1239 \tabularnewline
69 & 13 & 12.8808 & 0.119231 \tabularnewline
70 & 14 & 12.3421 & 1.65786 \tabularnewline
71 & 13 & 13.524 & -0.523994 \tabularnewline
72 & 15 & 12.7811 & 2.21887 \tabularnewline
73 & 13 & 11.5347 & 1.4653 \tabularnewline
74 & 10 & 12.1435 & -2.14346 \tabularnewline
75 & 11 & 12.8409 & -1.84089 \tabularnewline
76 & 19 & 13.6149 & 5.38514 \tabularnewline
77 & 13 & 10.8584 & 2.14161 \tabularnewline
78 & 17 & 13.7517 & 3.24829 \tabularnewline
79 & 13 & 12.2572 & 0.742839 \tabularnewline
80 & 9 & 14.5203 & -5.52033 \tabularnewline
81 & 11 & 11.8389 & -0.8389 \tabularnewline
82 & 9 & 12.2608 & -3.26083 \tabularnewline
83 & 12 & 11.4503 & 0.549729 \tabularnewline
84 & 12 & 12.3463 & -0.346329 \tabularnewline
85 & 13 & 12.6486 & 0.35139 \tabularnewline
86 & 13 & 12.14 & 0.859951 \tabularnewline
87 & 12 & 13.1186 & -1.1186 \tabularnewline
88 & 15 & 14.7762 & 0.223835 \tabularnewline
89 & 22 & 17.9823 & 4.01771 \tabularnewline
90 & 13 & 11.1823 & 1.81775 \tabularnewline
91 & 15 & 14.5107 & 0.489306 \tabularnewline
92 & 13 & 11.9643 & 1.03575 \tabularnewline
93 & 15 & 12.4423 & 2.55765 \tabularnewline
94 & 12.5 & 13.4816 & -0.981597 \tabularnewline
95 & 11 & 10.9924 & 0.00761143 \tabularnewline
96 & 16 & 14.4259 & 1.57407 \tabularnewline
97 & 11 & 12.5829 & -1.58293 \tabularnewline
98 & 11 & 10.2723 & 0.727683 \tabularnewline
99 & 10 & 12.2472 & -2.24719 \tabularnewline
100 & 10 & 10.5369 & -0.536941 \tabularnewline
101 & 16 & 14.2255 & 1.77451 \tabularnewline
102 & 12 & 10.4832 & 1.51676 \tabularnewline
103 & 11 & 15.4882 & -4.48825 \tabularnewline
104 & 16 & 11.9313 & 4.06873 \tabularnewline
105 & 19 & 16.7133 & 2.28674 \tabularnewline
106 & 11 & 11.1895 & -0.1895 \tabularnewline
107 & 16 & 12.1915 & 3.80848 \tabularnewline
108 & 15 & 16.7606 & -1.76059 \tabularnewline
109 & 24 & 17.4018 & 6.59821 \tabularnewline
110 & 14 & 11.6399 & 2.36009 \tabularnewline
111 & 15 & 15.0055 & -0.00550164 \tabularnewline
112 & 11 & 12.7856 & -1.78563 \tabularnewline
113 & 15 & 15.2308 & -0.230776 \tabularnewline
114 & 12 & 10.2114 & 1.78862 \tabularnewline
115 & 10 & 10.5654 & -0.565366 \tabularnewline
116 & 14 & 14.2381 & -0.238062 \tabularnewline
117 & 13 & 13.5039 & -0.503931 \tabularnewline
118 & 9 & 13.4315 & -4.43153 \tabularnewline
119 & 15 & 11.876 & 3.12396 \tabularnewline
120 & 15 & 15.7058 & -0.705757 \tabularnewline
121 & 14 & 12.8135 & 1.18651 \tabularnewline
122 & 11 & 11.4754 & -0.475406 \tabularnewline
123 & 8 & 12.0268 & -4.02683 \tabularnewline
124 & 11 & 12.2678 & -1.26785 \tabularnewline
125 & 11 & 13.3609 & -2.36091 \tabularnewline
126 & 8 & 9.85547 & -1.85547 \tabularnewline
127 & 10 & 10.5515 & -0.551533 \tabularnewline
128 & 11 & 9.18196 & 1.81804 \tabularnewline
129 & 13 & 12.6033 & 0.396724 \tabularnewline
130 & 11 & 13.8575 & -2.85745 \tabularnewline
131 & 20 & 17.4285 & 2.57155 \tabularnewline
132 & 10 & 11.9644 & -1.9644 \tabularnewline
133 & 15 & 13.2084 & 1.79158 \tabularnewline
134 & 12 & 12.3312 & -0.331243 \tabularnewline
135 & 14 & 11.0094 & 2.99063 \tabularnewline
136 & 23 & 16.505 & 6.49501 \tabularnewline
137 & 14 & 13.6703 & 0.329746 \tabularnewline
138 & 16 & 16.6641 & -0.664108 \tabularnewline
139 & 11 & 13.1283 & -2.12826 \tabularnewline
140 & 12 & 14.3959 & -2.39594 \tabularnewline
141 & 10 & 13.5129 & -3.51286 \tabularnewline
142 & 14 & 11.2101 & 2.78988 \tabularnewline
143 & 12 & 12.2809 & -0.280917 \tabularnewline
144 & 12 & 12.1235 & -0.123523 \tabularnewline
145 & 11 & 10.9957 & 0.00430668 \tabularnewline
146 & 12 & 11.335 & 0.664993 \tabularnewline
147 & 13 & 16.038 & -3.038 \tabularnewline
148 & 11 & 14.342 & -3.34197 \tabularnewline
149 & 19 & 16.7041 & 2.29587 \tabularnewline
150 & 12 & 11.3475 & 0.652463 \tabularnewline
151 & 17 & 13.2651 & 3.73495 \tabularnewline
152 & 9 & 11.8278 & -2.82778 \tabularnewline
153 & 12 & 14.5513 & -2.55128 \tabularnewline
154 & 19 & 16.8247 & 2.17533 \tabularnewline
155 & 18 & 13.9214 & 4.07859 \tabularnewline
156 & 15 & 14.6992 & 0.300818 \tabularnewline
157 & 14 & 13.6247 & 0.375327 \tabularnewline
158 & 11 & 9.26895 & 1.73105 \tabularnewline
159 & 9 & 13.1215 & -4.12151 \tabularnewline
160 & 18 & 14.2069 & 3.7931 \tabularnewline
161 & 16 & 14.2554 & 1.74458 \tabularnewline
162 & 24 & 16.6165 & 7.38345 \tabularnewline
163 & 14 & 12.9608 & 1.0392 \tabularnewline
164 & 20 & 10.9808 & 9.01924 \tabularnewline
165 & 18 & 16.033 & 1.96705 \tabularnewline
166 & 23 & 16.9569 & 6.04309 \tabularnewline
167 & 12 & 13.0468 & -1.04681 \tabularnewline
168 & 14 & 14.925 & -0.924968 \tabularnewline
169 & 16 & 16.2734 & -0.273392 \tabularnewline
170 & 18 & 16.763 & 1.23695 \tabularnewline
171 & 20 & 16.4739 & 3.52609 \tabularnewline
172 & 12 & 11.7451 & 0.254913 \tabularnewline
173 & 12 & 16.4083 & -4.40829 \tabularnewline
174 & 17 & 15.2257 & 1.7743 \tabularnewline
175 & 13 & 11.9809 & 1.01905 \tabularnewline
176 & 9 & 13.6568 & -4.65679 \tabularnewline
177 & 16 & 17.1084 & -1.10841 \tabularnewline
178 & 18 & 15.1268 & 2.87316 \tabularnewline
179 & 10 & 12.3056 & -2.30561 \tabularnewline
180 & 14 & 15.3711 & -1.37107 \tabularnewline
181 & 11 & 14.1967 & -3.19672 \tabularnewline
182 & 9 & 14.5292 & -5.52921 \tabularnewline
183 & 11 & 12.4736 & -1.47358 \tabularnewline
184 & 10 & 12.6919 & -2.69189 \tabularnewline
185 & 11 & 11.6588 & -0.658778 \tabularnewline
186 & 19 & 13.7294 & 5.27063 \tabularnewline
187 & 14 & 12.9808 & 1.0192 \tabularnewline
188 & 12 & 11.8247 & 0.175349 \tabularnewline
189 & 14 & 15.4629 & -1.46288 \tabularnewline
190 & 21 & 16.4063 & 4.59367 \tabularnewline
191 & 13 & 17.4753 & -4.47525 \tabularnewline
192 & 10 & 12.9812 & -2.98122 \tabularnewline
193 & 15 & 13.1087 & 1.89134 \tabularnewline
194 & 16 & 15.8893 & 0.110693 \tabularnewline
195 & 14 & 12.8046 & 1.19537 \tabularnewline
196 & 12 & 14.7531 & -2.75311 \tabularnewline
197 & 19 & 12.8404 & 6.15961 \tabularnewline
198 & 15 & 12.4126 & 2.5874 \tabularnewline
199 & 19 & 18.168 & 0.831998 \tabularnewline
200 & 13 & 13.8424 & -0.842358 \tabularnewline
201 & 17 & 16.9688 & 0.0312088 \tabularnewline
202 & 12 & 13.1224 & -1.12237 \tabularnewline
203 & 11 & 11.3584 & -0.358413 \tabularnewline
204 & 14 & 15.2632 & -1.2632 \tabularnewline
205 & 11 & 12.6976 & -1.69758 \tabularnewline
206 & 13 & 12.5443 & 0.455688 \tabularnewline
207 & 12 & 12.5124 & -0.512379 \tabularnewline
208 & 15 & 13.0303 & 1.96965 \tabularnewline
209 & 14 & 14.3903 & -0.390343 \tabularnewline
210 & 12 & 11.2738 & 0.726162 \tabularnewline
211 & 17 & 17.4813 & -0.48127 \tabularnewline
212 & 11 & 11.3549 & -0.35489 \tabularnewline
213 & 18 & 14.6507 & 3.34935 \tabularnewline
214 & 13 & 15.8483 & -2.84829 \tabularnewline
215 & 17 & 15.64 & 1.36005 \tabularnewline
216 & 13 & 13.2647 & -0.264652 \tabularnewline
217 & 11 & 10.432 & 0.567954 \tabularnewline
218 & 12 & 12.689 & -0.689001 \tabularnewline
219 & 22 & 18.297 & 3.70297 \tabularnewline
220 & 14 & 12.0779 & 1.92214 \tabularnewline
221 & 12 & 15.3323 & -3.33225 \tabularnewline
222 & 12 & 12.8025 & -0.802466 \tabularnewline
223 & 17 & 16.1696 & 0.830365 \tabularnewline
224 & 9 & 12.9925 & -3.99246 \tabularnewline
225 & 21 & 19.0046 & 1.99544 \tabularnewline
226 & 10 & 12.2582 & -2.25819 \tabularnewline
227 & 11 & 11.1257 & -0.125693 \tabularnewline
228 & 12 & 15.4271 & -3.42713 \tabularnewline
229 & 23 & 18.206 & 4.79401 \tabularnewline
230 & 13 & 15.839 & -2.83902 \tabularnewline
231 & 12 & 13.6323 & -1.63233 \tabularnewline
232 & 16 & 17.5784 & -1.57836 \tabularnewline
233 & 9 & 13.5647 & -4.5647 \tabularnewline
234 & 17 & 13.6975 & 3.30245 \tabularnewline
235 & 9 & 12.1764 & -3.17641 \tabularnewline
236 & 14 & 15.8436 & -1.84358 \tabularnewline
237 & 17 & 15.2954 & 1.70464 \tabularnewline
238 & 13 & 15.445 & -2.44496 \tabularnewline
239 & 11 & 16.2429 & -5.24289 \tabularnewline
240 & 12 & 15.8033 & -3.80333 \tabularnewline
241 & 10 & 14.3031 & -4.30314 \tabularnewline
242 & 19 & 18.8973 & 0.102657 \tabularnewline
243 & 16 & 16.1845 & -0.184521 \tabularnewline
244 & 16 & 15.3381 & 0.661899 \tabularnewline
245 & 14 & 12.0966 & 1.90336 \tabularnewline
246 & 20 & 16.0797 & 3.92026 \tabularnewline
247 & 15 & 14.53 & 0.469974 \tabularnewline
248 & 23 & 15.3921 & 7.60786 \tabularnewline
249 & 20 & 17.712 & 2.288 \tabularnewline
250 & 16 & 16.4374 & -0.437384 \tabularnewline
251 & 14 & 13.2851 & 0.714944 \tabularnewline
252 & 17 & 14.217 & 2.783 \tabularnewline
253 & 11 & 14.4305 & -3.43052 \tabularnewline
254 & 13 & 14.1364 & -1.1364 \tabularnewline
255 & 17 & 15.2379 & 1.76211 \tabularnewline
256 & 15 & 15.2276 & -0.227642 \tabularnewline
257 & 21 & 16.695 & 4.305 \tabularnewline
258 & 18 & 17.6999 & 0.300051 \tabularnewline
259 & 15 & 13.1556 & 1.84444 \tabularnewline
260 & 8 & 16.419 & -8.41895 \tabularnewline
261 & 12 & 14.1221 & -2.12208 \tabularnewline
262 & 12 & 13.336 & -1.33603 \tabularnewline
263 & 22 & 19.1111 & 2.88893 \tabularnewline
264 & 12 & 13.7135 & -1.71351 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253225&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]13.8252[/C][C]-1.82525[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]9.13089[/C][C]1.86911[/C][/ROW]
[ROW][C]3[/C][C]14[/C][C]14.9763[/C][C]-0.976266[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.5471[/C][C]-2.54706[/C][/ROW]
[ROW][C]5[/C][C]21[/C][C]11.2102[/C][C]9.78982[/C][/ROW]
[ROW][C]6[/C][C]12[/C][C]9.73517[/C][C]2.26483[/C][/ROW]
[ROW][C]7[/C][C]22[/C][C]13.4365[/C][C]8.56351[/C][/ROW]
[ROW][C]8[/C][C]11[/C][C]12.2891[/C][C]-1.28909[/C][/ROW]
[ROW][C]9[/C][C]10[/C][C]11.9772[/C][C]-1.97725[/C][/ROW]
[ROW][C]10[/C][C]13[/C][C]11.8119[/C][C]1.18812[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]10.1108[/C][C]-0.110825[/C][/ROW]
[ROW][C]12[/C][C]8[/C][C]10.2295[/C][C]-2.22954[/C][/ROW]
[ROW][C]13[/C][C]15[/C][C]15.6708[/C][C]-0.670753[/C][/ROW]
[ROW][C]14[/C][C]14[/C][C]12.2696[/C][C]1.73044[/C][/ROW]
[ROW][C]15[/C][C]10[/C][C]9.01386[/C][C]0.986137[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.6407[/C][C]0.359308[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]12.5662[/C][C]1.43381[/C][/ROW]
[ROW][C]18[/C][C]11[/C][C]9.35287[/C][C]1.64713[/C][/ROW]
[ROW][C]19[/C][C]10[/C][C]12.9507[/C][C]-2.9507[/C][/ROW]
[ROW][C]20[/C][C]13[/C][C]12.2488[/C][C]0.751214[/C][/ROW]
[ROW][C]21[/C][C]9.5[/C][C]10.3572[/C][C]-0.857239[/C][/ROW]
[ROW][C]22[/C][C]14[/C][C]15.1016[/C][C]-1.10162[/C][/ROW]
[ROW][C]23[/C][C]12[/C][C]13.456[/C][C]-1.45597[/C][/ROW]
[ROW][C]24[/C][C]14[/C][C]15.0118[/C][C]-1.0118[/C][/ROW]
[ROW][C]25[/C][C]11[/C][C]9.63838[/C][C]1.36162[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.4751[/C][C]-6.4751[/C][/ROW]
[ROW][C]27[/C][C]11[/C][C]11.0983[/C][C]-0.098309[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]13.0169[/C][C]1.98314[/C][/ROW]
[ROW][C]29[/C][C]14[/C][C]11.7291[/C][C]2.27088[/C][/ROW]
[ROW][C]30[/C][C]13[/C][C]15.2741[/C][C]-2.27406[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]11.0349[/C][C]-2.03493[/C][/ROW]
[ROW][C]32[/C][C]15[/C][C]14.9777[/C][C]0.0223432[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.8037[/C][C]-0.803706[/C][/ROW]
[ROW][C]34[/C][C]11[/C][C]11.3925[/C][C]-0.392506[/C][/ROW]
[ROW][C]35[/C][C]13[/C][C]12.7684[/C][C]0.231555[/C][/ROW]
[ROW][C]36[/C][C]8[/C][C]11.9488[/C][C]-3.94875[/C][/ROW]
[ROW][C]37[/C][C]20[/C][C]17.3161[/C][C]2.68392[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]12.2241[/C][C]-0.224134[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]10.5959[/C][C]-0.595931[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]13.636[/C][C]-3.63598[/C][/ROW]
[ROW][C]41[/C][C]9[/C][C]11.9056[/C][C]-2.90559[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]11.3614[/C][C]2.63856[/C][/ROW]
[ROW][C]43[/C][C]8[/C][C]12.0323[/C][C]-4.03227[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]15.4667[/C][C]-1.46675[/C][/ROW]
[ROW][C]45[/C][C]11[/C][C]12.2983[/C][C]-1.29833[/C][/ROW]
[ROW][C]46[/C][C]13[/C][C]15.3886[/C][C]-2.38864[/C][/ROW]
[ROW][C]47[/C][C]9[/C][C]12.5729[/C][C]-3.57294[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]12.0423[/C][C]-1.04225[/C][/ROW]
[ROW][C]49[/C][C]15[/C][C]10.5935[/C][C]4.40653[/C][/ROW]
[ROW][C]50[/C][C]11[/C][C]13.3563[/C][C]-2.35629[/C][/ROW]
[ROW][C]51[/C][C]10[/C][C]11.4847[/C][C]-1.48474[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.2924[/C][C]0.707579[/C][/ROW]
[ROW][C]53[/C][C]18[/C][C]15.7459[/C][C]2.2541[/C][/ROW]
[ROW][C]54[/C][C]14[/C][C]14.8041[/C][C]-0.804126[/C][/ROW]
[ROW][C]55[/C][C]11[/C][C]15.322[/C][C]-4.32202[/C][/ROW]
[ROW][C]56[/C][C]14.5[/C][C]12.0237[/C][C]2.4763[/C][/ROW]
[ROW][C]57[/C][C]13[/C][C]11.2019[/C][C]1.79813[/C][/ROW]
[ROW][C]58[/C][C]9[/C][C]12.5596[/C][C]-3.55957[/C][/ROW]
[ROW][C]59[/C][C]10[/C][C]14.179[/C][C]-4.17895[/C][/ROW]
[ROW][C]60[/C][C]15[/C][C]14.3348[/C][C]0.665241[/C][/ROW]
[ROW][C]61[/C][C]20[/C][C]18.4949[/C][C]1.50512[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]13.1472[/C][C]-1.1472[/C][/ROW]
[ROW][C]63[/C][C]12[/C][C]14.4528[/C][C]-2.45278[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.2433[/C][C]-0.243288[/C][/ROW]
[ROW][C]65[/C][C]13[/C][C]13.1898[/C][C]-0.189843[/C][/ROW]
[ROW][C]66[/C][C]11[/C][C]15.0795[/C][C]-4.07952[/C][/ROW]
[ROW][C]67[/C][C]17[/C][C]15.0869[/C][C]1.91311[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.1239[/C][C]-2.1239[/C][/ROW]
[ROW][C]69[/C][C]13[/C][C]12.8808[/C][C]0.119231[/C][/ROW]
[ROW][C]70[/C][C]14[/C][C]12.3421[/C][C]1.65786[/C][/ROW]
[ROW][C]71[/C][C]13[/C][C]13.524[/C][C]-0.523994[/C][/ROW]
[ROW][C]72[/C][C]15[/C][C]12.7811[/C][C]2.21887[/C][/ROW]
[ROW][C]73[/C][C]13[/C][C]11.5347[/C][C]1.4653[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]12.1435[/C][C]-2.14346[/C][/ROW]
[ROW][C]75[/C][C]11[/C][C]12.8409[/C][C]-1.84089[/C][/ROW]
[ROW][C]76[/C][C]19[/C][C]13.6149[/C][C]5.38514[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]10.8584[/C][C]2.14161[/C][/ROW]
[ROW][C]78[/C][C]17[/C][C]13.7517[/C][C]3.24829[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]12.2572[/C][C]0.742839[/C][/ROW]
[ROW][C]80[/C][C]9[/C][C]14.5203[/C][C]-5.52033[/C][/ROW]
[ROW][C]81[/C][C]11[/C][C]11.8389[/C][C]-0.8389[/C][/ROW]
[ROW][C]82[/C][C]9[/C][C]12.2608[/C][C]-3.26083[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]11.4503[/C][C]0.549729[/C][/ROW]
[ROW][C]84[/C][C]12[/C][C]12.3463[/C][C]-0.346329[/C][/ROW]
[ROW][C]85[/C][C]13[/C][C]12.6486[/C][C]0.35139[/C][/ROW]
[ROW][C]86[/C][C]13[/C][C]12.14[/C][C]0.859951[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]13.1186[/C][C]-1.1186[/C][/ROW]
[ROW][C]88[/C][C]15[/C][C]14.7762[/C][C]0.223835[/C][/ROW]
[ROW][C]89[/C][C]22[/C][C]17.9823[/C][C]4.01771[/C][/ROW]
[ROW][C]90[/C][C]13[/C][C]11.1823[/C][C]1.81775[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]14.5107[/C][C]0.489306[/C][/ROW]
[ROW][C]92[/C][C]13[/C][C]11.9643[/C][C]1.03575[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]12.4423[/C][C]2.55765[/C][/ROW]
[ROW][C]94[/C][C]12.5[/C][C]13.4816[/C][C]-0.981597[/C][/ROW]
[ROW][C]95[/C][C]11[/C][C]10.9924[/C][C]0.00761143[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]14.4259[/C][C]1.57407[/C][/ROW]
[ROW][C]97[/C][C]11[/C][C]12.5829[/C][C]-1.58293[/C][/ROW]
[ROW][C]98[/C][C]11[/C][C]10.2723[/C][C]0.727683[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]12.2472[/C][C]-2.24719[/C][/ROW]
[ROW][C]100[/C][C]10[/C][C]10.5369[/C][C]-0.536941[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.2255[/C][C]1.77451[/C][/ROW]
[ROW][C]102[/C][C]12[/C][C]10.4832[/C][C]1.51676[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]15.4882[/C][C]-4.48825[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]11.9313[/C][C]4.06873[/C][/ROW]
[ROW][C]105[/C][C]19[/C][C]16.7133[/C][C]2.28674[/C][/ROW]
[ROW][C]106[/C][C]11[/C][C]11.1895[/C][C]-0.1895[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]12.1915[/C][C]3.80848[/C][/ROW]
[ROW][C]108[/C][C]15[/C][C]16.7606[/C][C]-1.76059[/C][/ROW]
[ROW][C]109[/C][C]24[/C][C]17.4018[/C][C]6.59821[/C][/ROW]
[ROW][C]110[/C][C]14[/C][C]11.6399[/C][C]2.36009[/C][/ROW]
[ROW][C]111[/C][C]15[/C][C]15.0055[/C][C]-0.00550164[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]12.7856[/C][C]-1.78563[/C][/ROW]
[ROW][C]113[/C][C]15[/C][C]15.2308[/C][C]-0.230776[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]10.2114[/C][C]1.78862[/C][/ROW]
[ROW][C]115[/C][C]10[/C][C]10.5654[/C][C]-0.565366[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]14.2381[/C][C]-0.238062[/C][/ROW]
[ROW][C]117[/C][C]13[/C][C]13.5039[/C][C]-0.503931[/C][/ROW]
[ROW][C]118[/C][C]9[/C][C]13.4315[/C][C]-4.43153[/C][/ROW]
[ROW][C]119[/C][C]15[/C][C]11.876[/C][C]3.12396[/C][/ROW]
[ROW][C]120[/C][C]15[/C][C]15.7058[/C][C]-0.705757[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]12.8135[/C][C]1.18651[/C][/ROW]
[ROW][C]122[/C][C]11[/C][C]11.4754[/C][C]-0.475406[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]12.0268[/C][C]-4.02683[/C][/ROW]
[ROW][C]124[/C][C]11[/C][C]12.2678[/C][C]-1.26785[/C][/ROW]
[ROW][C]125[/C][C]11[/C][C]13.3609[/C][C]-2.36091[/C][/ROW]
[ROW][C]126[/C][C]8[/C][C]9.85547[/C][C]-1.85547[/C][/ROW]
[ROW][C]127[/C][C]10[/C][C]10.5515[/C][C]-0.551533[/C][/ROW]
[ROW][C]128[/C][C]11[/C][C]9.18196[/C][C]1.81804[/C][/ROW]
[ROW][C]129[/C][C]13[/C][C]12.6033[/C][C]0.396724[/C][/ROW]
[ROW][C]130[/C][C]11[/C][C]13.8575[/C][C]-2.85745[/C][/ROW]
[ROW][C]131[/C][C]20[/C][C]17.4285[/C][C]2.57155[/C][/ROW]
[ROW][C]132[/C][C]10[/C][C]11.9644[/C][C]-1.9644[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]13.2084[/C][C]1.79158[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]12.3312[/C][C]-0.331243[/C][/ROW]
[ROW][C]135[/C][C]14[/C][C]11.0094[/C][C]2.99063[/C][/ROW]
[ROW][C]136[/C][C]23[/C][C]16.505[/C][C]6.49501[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.6703[/C][C]0.329746[/C][/ROW]
[ROW][C]138[/C][C]16[/C][C]16.6641[/C][C]-0.664108[/C][/ROW]
[ROW][C]139[/C][C]11[/C][C]13.1283[/C][C]-2.12826[/C][/ROW]
[ROW][C]140[/C][C]12[/C][C]14.3959[/C][C]-2.39594[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]13.5129[/C][C]-3.51286[/C][/ROW]
[ROW][C]142[/C][C]14[/C][C]11.2101[/C][C]2.78988[/C][/ROW]
[ROW][C]143[/C][C]12[/C][C]12.2809[/C][C]-0.280917[/C][/ROW]
[ROW][C]144[/C][C]12[/C][C]12.1235[/C][C]-0.123523[/C][/ROW]
[ROW][C]145[/C][C]11[/C][C]10.9957[/C][C]0.00430668[/C][/ROW]
[ROW][C]146[/C][C]12[/C][C]11.335[/C][C]0.664993[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]16.038[/C][C]-3.038[/C][/ROW]
[ROW][C]148[/C][C]11[/C][C]14.342[/C][C]-3.34197[/C][/ROW]
[ROW][C]149[/C][C]19[/C][C]16.7041[/C][C]2.29587[/C][/ROW]
[ROW][C]150[/C][C]12[/C][C]11.3475[/C][C]0.652463[/C][/ROW]
[ROW][C]151[/C][C]17[/C][C]13.2651[/C][C]3.73495[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.8278[/C][C]-2.82778[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.5513[/C][C]-2.55128[/C][/ROW]
[ROW][C]154[/C][C]19[/C][C]16.8247[/C][C]2.17533[/C][/ROW]
[ROW][C]155[/C][C]18[/C][C]13.9214[/C][C]4.07859[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]14.6992[/C][C]0.300818[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.6247[/C][C]0.375327[/C][/ROW]
[ROW][C]158[/C][C]11[/C][C]9.26895[/C][C]1.73105[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]13.1215[/C][C]-4.12151[/C][/ROW]
[ROW][C]160[/C][C]18[/C][C]14.2069[/C][C]3.7931[/C][/ROW]
[ROW][C]161[/C][C]16[/C][C]14.2554[/C][C]1.74458[/C][/ROW]
[ROW][C]162[/C][C]24[/C][C]16.6165[/C][C]7.38345[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]12.9608[/C][C]1.0392[/C][/ROW]
[ROW][C]164[/C][C]20[/C][C]10.9808[/C][C]9.01924[/C][/ROW]
[ROW][C]165[/C][C]18[/C][C]16.033[/C][C]1.96705[/C][/ROW]
[ROW][C]166[/C][C]23[/C][C]16.9569[/C][C]6.04309[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]13.0468[/C][C]-1.04681[/C][/ROW]
[ROW][C]168[/C][C]14[/C][C]14.925[/C][C]-0.924968[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]16.2734[/C][C]-0.273392[/C][/ROW]
[ROW][C]170[/C][C]18[/C][C]16.763[/C][C]1.23695[/C][/ROW]
[ROW][C]171[/C][C]20[/C][C]16.4739[/C][C]3.52609[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.7451[/C][C]0.254913[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]16.4083[/C][C]-4.40829[/C][/ROW]
[ROW][C]174[/C][C]17[/C][C]15.2257[/C][C]1.7743[/C][/ROW]
[ROW][C]175[/C][C]13[/C][C]11.9809[/C][C]1.01905[/C][/ROW]
[ROW][C]176[/C][C]9[/C][C]13.6568[/C][C]-4.65679[/C][/ROW]
[ROW][C]177[/C][C]16[/C][C]17.1084[/C][C]-1.10841[/C][/ROW]
[ROW][C]178[/C][C]18[/C][C]15.1268[/C][C]2.87316[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]12.3056[/C][C]-2.30561[/C][/ROW]
[ROW][C]180[/C][C]14[/C][C]15.3711[/C][C]-1.37107[/C][/ROW]
[ROW][C]181[/C][C]11[/C][C]14.1967[/C][C]-3.19672[/C][/ROW]
[ROW][C]182[/C][C]9[/C][C]14.5292[/C][C]-5.52921[/C][/ROW]
[ROW][C]183[/C][C]11[/C][C]12.4736[/C][C]-1.47358[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]12.6919[/C][C]-2.69189[/C][/ROW]
[ROW][C]185[/C][C]11[/C][C]11.6588[/C][C]-0.658778[/C][/ROW]
[ROW][C]186[/C][C]19[/C][C]13.7294[/C][C]5.27063[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]12.9808[/C][C]1.0192[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]11.8247[/C][C]0.175349[/C][/ROW]
[ROW][C]189[/C][C]14[/C][C]15.4629[/C][C]-1.46288[/C][/ROW]
[ROW][C]190[/C][C]21[/C][C]16.4063[/C][C]4.59367[/C][/ROW]
[ROW][C]191[/C][C]13[/C][C]17.4753[/C][C]-4.47525[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]12.9812[/C][C]-2.98122[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]13.1087[/C][C]1.89134[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]15.8893[/C][C]0.110693[/C][/ROW]
[ROW][C]195[/C][C]14[/C][C]12.8046[/C][C]1.19537[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.7531[/C][C]-2.75311[/C][/ROW]
[ROW][C]197[/C][C]19[/C][C]12.8404[/C][C]6.15961[/C][/ROW]
[ROW][C]198[/C][C]15[/C][C]12.4126[/C][C]2.5874[/C][/ROW]
[ROW][C]199[/C][C]19[/C][C]18.168[/C][C]0.831998[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.8424[/C][C]-0.842358[/C][/ROW]
[ROW][C]201[/C][C]17[/C][C]16.9688[/C][C]0.0312088[/C][/ROW]
[ROW][C]202[/C][C]12[/C][C]13.1224[/C][C]-1.12237[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]11.3584[/C][C]-0.358413[/C][/ROW]
[ROW][C]204[/C][C]14[/C][C]15.2632[/C][C]-1.2632[/C][/ROW]
[ROW][C]205[/C][C]11[/C][C]12.6976[/C][C]-1.69758[/C][/ROW]
[ROW][C]206[/C][C]13[/C][C]12.5443[/C][C]0.455688[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]12.5124[/C][C]-0.512379[/C][/ROW]
[ROW][C]208[/C][C]15[/C][C]13.0303[/C][C]1.96965[/C][/ROW]
[ROW][C]209[/C][C]14[/C][C]14.3903[/C][C]-0.390343[/C][/ROW]
[ROW][C]210[/C][C]12[/C][C]11.2738[/C][C]0.726162[/C][/ROW]
[ROW][C]211[/C][C]17[/C][C]17.4813[/C][C]-0.48127[/C][/ROW]
[ROW][C]212[/C][C]11[/C][C]11.3549[/C][C]-0.35489[/C][/ROW]
[ROW][C]213[/C][C]18[/C][C]14.6507[/C][C]3.34935[/C][/ROW]
[ROW][C]214[/C][C]13[/C][C]15.8483[/C][C]-2.84829[/C][/ROW]
[ROW][C]215[/C][C]17[/C][C]15.64[/C][C]1.36005[/C][/ROW]
[ROW][C]216[/C][C]13[/C][C]13.2647[/C][C]-0.264652[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]10.432[/C][C]0.567954[/C][/ROW]
[ROW][C]218[/C][C]12[/C][C]12.689[/C][C]-0.689001[/C][/ROW]
[ROW][C]219[/C][C]22[/C][C]18.297[/C][C]3.70297[/C][/ROW]
[ROW][C]220[/C][C]14[/C][C]12.0779[/C][C]1.92214[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]15.3323[/C][C]-3.33225[/C][/ROW]
[ROW][C]222[/C][C]12[/C][C]12.8025[/C][C]-0.802466[/C][/ROW]
[ROW][C]223[/C][C]17[/C][C]16.1696[/C][C]0.830365[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]12.9925[/C][C]-3.99246[/C][/ROW]
[ROW][C]225[/C][C]21[/C][C]19.0046[/C][C]1.99544[/C][/ROW]
[ROW][C]226[/C][C]10[/C][C]12.2582[/C][C]-2.25819[/C][/ROW]
[ROW][C]227[/C][C]11[/C][C]11.1257[/C][C]-0.125693[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]15.4271[/C][C]-3.42713[/C][/ROW]
[ROW][C]229[/C][C]23[/C][C]18.206[/C][C]4.79401[/C][/ROW]
[ROW][C]230[/C][C]13[/C][C]15.839[/C][C]-2.83902[/C][/ROW]
[ROW][C]231[/C][C]12[/C][C]13.6323[/C][C]-1.63233[/C][/ROW]
[ROW][C]232[/C][C]16[/C][C]17.5784[/C][C]-1.57836[/C][/ROW]
[ROW][C]233[/C][C]9[/C][C]13.5647[/C][C]-4.5647[/C][/ROW]
[ROW][C]234[/C][C]17[/C][C]13.6975[/C][C]3.30245[/C][/ROW]
[ROW][C]235[/C][C]9[/C][C]12.1764[/C][C]-3.17641[/C][/ROW]
[ROW][C]236[/C][C]14[/C][C]15.8436[/C][C]-1.84358[/C][/ROW]
[ROW][C]237[/C][C]17[/C][C]15.2954[/C][C]1.70464[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]15.445[/C][C]-2.44496[/C][/ROW]
[ROW][C]239[/C][C]11[/C][C]16.2429[/C][C]-5.24289[/C][/ROW]
[ROW][C]240[/C][C]12[/C][C]15.8033[/C][C]-3.80333[/C][/ROW]
[ROW][C]241[/C][C]10[/C][C]14.3031[/C][C]-4.30314[/C][/ROW]
[ROW][C]242[/C][C]19[/C][C]18.8973[/C][C]0.102657[/C][/ROW]
[ROW][C]243[/C][C]16[/C][C]16.1845[/C][C]-0.184521[/C][/ROW]
[ROW][C]244[/C][C]16[/C][C]15.3381[/C][C]0.661899[/C][/ROW]
[ROW][C]245[/C][C]14[/C][C]12.0966[/C][C]1.90336[/C][/ROW]
[ROW][C]246[/C][C]20[/C][C]16.0797[/C][C]3.92026[/C][/ROW]
[ROW][C]247[/C][C]15[/C][C]14.53[/C][C]0.469974[/C][/ROW]
[ROW][C]248[/C][C]23[/C][C]15.3921[/C][C]7.60786[/C][/ROW]
[ROW][C]249[/C][C]20[/C][C]17.712[/C][C]2.288[/C][/ROW]
[ROW][C]250[/C][C]16[/C][C]16.4374[/C][C]-0.437384[/C][/ROW]
[ROW][C]251[/C][C]14[/C][C]13.2851[/C][C]0.714944[/C][/ROW]
[ROW][C]252[/C][C]17[/C][C]14.217[/C][C]2.783[/C][/ROW]
[ROW][C]253[/C][C]11[/C][C]14.4305[/C][C]-3.43052[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]14.1364[/C][C]-1.1364[/C][/ROW]
[ROW][C]255[/C][C]17[/C][C]15.2379[/C][C]1.76211[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]15.2276[/C][C]-0.227642[/C][/ROW]
[ROW][C]257[/C][C]21[/C][C]16.695[/C][C]4.305[/C][/ROW]
[ROW][C]258[/C][C]18[/C][C]17.6999[/C][C]0.300051[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]13.1556[/C][C]1.84444[/C][/ROW]
[ROW][C]260[/C][C]8[/C][C]16.419[/C][C]-8.41895[/C][/ROW]
[ROW][C]261[/C][C]12[/C][C]14.1221[/C][C]-2.12208[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]13.336[/C][C]-1.33603[/C][/ROW]
[ROW][C]263[/C][C]22[/C][C]19.1111[/C][C]2.88893[/C][/ROW]
[ROW][C]264[/C][C]12[/C][C]13.7135[/C][C]-1.71351[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253225&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253225&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
11213.8252-1.82525
2119.130891.86911
31414.9763-0.976266
41214.5471-2.54706
52111.21029.78982
6129.735172.26483
72213.43658.56351
81112.2891-1.28909
91011.9772-1.97725
101311.81191.18812
111010.1108-0.110825
12810.2295-2.22954
131515.6708-0.670753
141412.26961.73044
15109.013860.986137
161413.64070.359308
171412.56621.43381
18119.352871.64713
191012.9507-2.9507
201312.24880.751214
219.510.3572-0.857239
221415.1016-1.10162
231213.456-1.45597
241415.0118-1.0118
25119.638381.36162
26915.4751-6.4751
271111.0983-0.098309
281513.01691.98314
291411.72912.27088
301315.2741-2.27406
31911.0349-2.03493
321514.97770.0223432
331010.8037-0.803706
341111.3925-0.392506
351312.76840.231555
36811.9488-3.94875
372017.31612.68392
381212.2241-0.224134
391010.5959-0.595931
401013.636-3.63598
41911.9056-2.90559
421411.36142.63856
43812.0323-4.03227
441415.4667-1.46675
451112.2983-1.29833
461315.3886-2.38864
47912.5729-3.57294
481112.0423-1.04225
491510.59354.40653
501113.3563-2.35629
511011.4847-1.48474
521413.29240.707579
531815.74592.2541
541414.8041-0.804126
551115.322-4.32202
5614.512.02372.4763
571311.20191.79813
58912.5596-3.55957
591014.179-4.17895
601514.33480.665241
612018.49491.50512
621213.1472-1.1472
631214.4528-2.45278
641414.2433-0.243288
651313.1898-0.189843
661115.0795-4.07952
671715.08691.91311
681214.1239-2.1239
691312.88080.119231
701412.34211.65786
711313.524-0.523994
721512.78112.21887
731311.53471.4653
741012.1435-2.14346
751112.8409-1.84089
761913.61495.38514
771310.85842.14161
781713.75173.24829
791312.25720.742839
80914.5203-5.52033
811111.8389-0.8389
82912.2608-3.26083
831211.45030.549729
841212.3463-0.346329
851312.64860.35139
861312.140.859951
871213.1186-1.1186
881514.77620.223835
892217.98234.01771
901311.18231.81775
911514.51070.489306
921311.96431.03575
931512.44232.55765
9412.513.4816-0.981597
951110.99240.00761143
961614.42591.57407
971112.5829-1.58293
981110.27230.727683
991012.2472-2.24719
1001010.5369-0.536941
1011614.22551.77451
1021210.48321.51676
1031115.4882-4.48825
1041611.93134.06873
1051916.71332.28674
1061111.1895-0.1895
1071612.19153.80848
1081516.7606-1.76059
1092417.40186.59821
1101411.63992.36009
1111515.0055-0.00550164
1121112.7856-1.78563
1131515.2308-0.230776
1141210.21141.78862
1151010.5654-0.565366
1161414.2381-0.238062
1171313.5039-0.503931
118913.4315-4.43153
1191511.8763.12396
1201515.7058-0.705757
1211412.81351.18651
1221111.4754-0.475406
123812.0268-4.02683
1241112.2678-1.26785
1251113.3609-2.36091
12689.85547-1.85547
1271010.5515-0.551533
128119.181961.81804
1291312.60330.396724
1301113.8575-2.85745
1312017.42852.57155
1321011.9644-1.9644
1331513.20841.79158
1341212.3312-0.331243
1351411.00942.99063
1362316.5056.49501
1371413.67030.329746
1381616.6641-0.664108
1391113.1283-2.12826
1401214.3959-2.39594
1411013.5129-3.51286
1421411.21012.78988
1431212.2809-0.280917
1441212.1235-0.123523
1451110.99570.00430668
1461211.3350.664993
1471316.038-3.038
1481114.342-3.34197
1491916.70412.29587
1501211.34750.652463
1511713.26513.73495
152911.8278-2.82778
1531214.5513-2.55128
1541916.82472.17533
1551813.92144.07859
1561514.69920.300818
1571413.62470.375327
158119.268951.73105
159913.1215-4.12151
1601814.20693.7931
1611614.25541.74458
1622416.61657.38345
1631412.96081.0392
1642010.98089.01924
1651816.0331.96705
1662316.95696.04309
1671213.0468-1.04681
1681414.925-0.924968
1691616.2734-0.273392
1701816.7631.23695
1712016.47393.52609
1721211.74510.254913
1731216.4083-4.40829
1741715.22571.7743
1751311.98091.01905
176913.6568-4.65679
1771617.1084-1.10841
1781815.12682.87316
1791012.3056-2.30561
1801415.3711-1.37107
1811114.1967-3.19672
182914.5292-5.52921
1831112.4736-1.47358
1841012.6919-2.69189
1851111.6588-0.658778
1861913.72945.27063
1871412.98081.0192
1881211.82470.175349
1891415.4629-1.46288
1902116.40634.59367
1911317.4753-4.47525
1921012.9812-2.98122
1931513.10871.89134
1941615.88930.110693
1951412.80461.19537
1961214.7531-2.75311
1971912.84046.15961
1981512.41262.5874
1991918.1680.831998
2001313.8424-0.842358
2011716.96880.0312088
2021213.1224-1.12237
2031111.3584-0.358413
2041415.2632-1.2632
2051112.6976-1.69758
2061312.54430.455688
2071212.5124-0.512379
2081513.03031.96965
2091414.3903-0.390343
2101211.27380.726162
2111717.4813-0.48127
2121111.3549-0.35489
2131814.65073.34935
2141315.8483-2.84829
2151715.641.36005
2161313.2647-0.264652
2171110.4320.567954
2181212.689-0.689001
2192218.2973.70297
2201412.07791.92214
2211215.3323-3.33225
2221212.8025-0.802466
2231716.16960.830365
224912.9925-3.99246
2252119.00461.99544
2261012.2582-2.25819
2271111.1257-0.125693
2281215.4271-3.42713
2292318.2064.79401
2301315.839-2.83902
2311213.6323-1.63233
2321617.5784-1.57836
233913.5647-4.5647
2341713.69753.30245
235912.1764-3.17641
2361415.8436-1.84358
2371715.29541.70464
2381315.445-2.44496
2391116.2429-5.24289
2401215.8033-3.80333
2411014.3031-4.30314
2421918.89730.102657
2431616.1845-0.184521
2441615.33810.661899
2451412.09661.90336
2462016.07973.92026
2471514.530.469974
2482315.39217.60786
2492017.7122.288
2501616.4374-0.437384
2511413.28510.714944
2521714.2172.783
2531114.4305-3.43052
2541314.1364-1.1364
2551715.23791.76211
2561515.2276-0.227642
2572116.6954.305
2581817.69990.300051
2591513.15561.84444
260816.419-8.41895
2611214.1221-2.12208
2621213.336-1.33603
2632219.11112.88893
2641213.7135-1.71351






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.8083330.3833350.191667
120.9996910.0006173730.000308687
130.9992130.001573770.000786884
140.9984050.003190440.00159522
150.9967950.006409750.00320488
160.9947320.01053620.00526809
170.9915680.01686480.00843239
180.9858550.02829030.0141452
190.9838540.03229210.0161461
200.974760.05047910.0252396
210.9622940.07541220.0377061
220.9445680.1108640.0554318
230.9238870.1522270.0761134
240.903120.1937610.0968804
250.8713450.2573090.128655
260.9137450.1725110.0862555
270.8903080.2193840.109692
280.8971260.2057480.102874
290.8927220.2145560.107278
300.864240.271520.13576
310.8452280.3095440.154772
320.8202640.3594730.179736
330.779440.441120.22056
340.7357920.5284170.264208
350.6970060.6059870.302994
360.6844590.6310830.315541
370.7864430.4271130.213557
380.7458040.5083920.254196
390.7015570.5968870.298443
400.6780430.6439140.321957
410.6415790.7168410.358421
420.6539520.6920960.346048
430.6658160.6683680.334184
440.6262750.747450.373725
450.5810170.8379660.418983
460.5387790.9224420.461221
470.5178460.9643070.482154
480.4732150.946430.526785
490.6280170.7439670.371983
500.5893380.8213240.410662
510.5494480.9011040.450552
520.5298860.9402280.470114
530.5624440.8751110.437556
540.5224530.9550930.477547
550.5216710.9566570.478329
560.5878710.8242570.412129
570.585640.828720.41436
580.5951790.8096430.404821
590.5950550.8098910.404945
600.5906130.8187740.409387
610.6200930.7598150.379907
620.5825130.8349740.417487
630.5525820.8948360.447418
640.51320.9736010.4868
650.4736920.9473830.526308
660.4726240.9452480.527376
670.5013180.9973650.498682
680.4732750.9465510.526725
690.4384430.8768860.561557
700.4267430.8534850.573257
710.3896190.7792370.610381
720.3735640.7471270.626436
730.3518230.7036460.648177
740.3304740.6609480.669526
750.3028040.6056070.697196
760.477590.955180.52241
770.4589230.9178450.541077
780.482720.965440.51728
790.4447150.8894290.555285
800.5410270.9179470.458973
810.5060790.9878420.493921
820.518550.96290.48145
830.4823650.9647310.517635
840.4443920.8887850.555608
850.4083070.8166150.591693
860.3752650.750530.624735
870.3441820.6883630.655818
880.3127710.6255410.687229
890.4002670.8005340.599733
900.3733170.7466330.626683
910.3443730.6887460.655627
920.3129070.6258140.687093
930.3048130.6096260.695187
940.2778680.5557350.722132
950.2470680.4941370.752932
960.2310540.4621070.768946
970.2145790.4291580.785421
980.1885410.3770810.811459
990.1839170.3678340.816083
1000.1616110.3232230.838389
1010.1507840.3015690.849216
1020.1334340.2668680.866566
1030.1676980.3353960.832302
1040.1873770.3747540.812623
1050.1901810.3803610.809819
1060.166850.33370.83315
1070.18090.36180.8191
1080.1682040.3364070.831796
1090.2745770.5491540.725423
1100.2612760.5225530.738724
1110.2330860.4661720.766914
1120.2257470.4514940.774253
1130.1998130.3996270.800187
1140.1810540.3621090.818946
1150.1604110.3208220.839589
1160.1403540.2807070.859646
1170.1243410.2486810.875659
1180.1625220.3250450.837478
1190.1617710.3235410.838229
1200.1426490.2852990.857351
1210.127370.2547390.87263
1220.112240.224480.88776
1230.1392490.2784980.860751
1240.1254070.2508140.874593
1250.1214940.2429890.878506
1260.1157570.2315140.884243
1270.1018220.2036450.898178
1280.0911850.182370.908815
1290.07744490.154890.922555
1300.08052520.161050.919475
1310.07984840.1596970.920152
1320.07608410.1521680.923916
1330.06827630.1365530.931724
1340.05770460.1154090.942295
1350.05774540.1154910.942255
1360.1107580.2215150.889242
1370.09465370.1893070.905346
1380.08213830.1642770.917862
1390.0798110.1596220.920189
1400.07925630.1585130.920744
1410.09254760.1850950.907452
1420.08988140.1797630.910119
1430.07659180.1531840.923408
1440.06484760.1296950.935152
1450.05441740.1088350.945583
1460.04533720.09067440.954663
1470.05036480.100730.949635
1480.05831030.1166210.94169
1490.05363860.1072770.946361
1500.04465320.08930630.955347
1510.04870680.09741370.951293
1520.05107850.1021570.948921
1530.05231270.1046250.947687
1540.04713190.09426380.952868
1550.05355480.107110.946445
1560.04514090.09028190.954859
1570.03726050.07452110.962739
1580.03214070.06428150.967859
1590.04392130.08784270.956079
1600.04888050.0977610.951119
1610.04216380.08432760.957836
1620.1015690.2031390.898431
1630.08783880.1756780.912161
1640.3018430.6036860.698157
1650.2807070.5614150.719293
1660.3890640.7781280.610936
1670.360520.7210410.63948
1680.3341920.6683830.665808
1690.3017260.6034530.698274
1700.2753910.5507830.724609
1710.288490.576980.71151
1720.2581410.5162810.741859
1730.3073530.6147070.692647
1740.2977450.5954910.702255
1750.2784310.5568620.721569
1760.336280.672560.66372
1770.3082490.6164980.691751
1780.3194750.638950.680525
1790.3058640.6117270.694136
1800.2809310.5618620.719069
1810.2989930.5979870.701007
1820.4012270.8024540.598773
1830.3791080.7582160.620892
1840.3830180.7660360.616982
1850.361920.7238410.63808
1860.4530130.9060260.546987
1870.4155760.8311520.584424
1880.3777930.7555870.622207
1890.34880.6976010.6512
1900.4150990.8301980.584901
1910.5152570.9694860.484743
1920.5426120.9147760.457388
1930.5345420.9309150.465458
1940.498980.997960.50102
1950.4711430.9422860.528857
1960.500520.9989610.49948
1970.6956810.6086380.304319
1980.7037160.5925680.296284
1990.6668270.6663470.333173
2000.6288570.7422850.371143
2010.5870030.8259940.412997
2020.5490720.9018570.450928
2030.5175810.9648390.482419
2040.4936250.987250.506375
2050.4573820.9147630.542618
2060.4157590.8315190.584241
2070.3733450.7466890.626655
2080.3383010.6766020.661699
2090.2982150.596430.701785
2100.2838570.5677150.716143
2110.2528280.5056560.747172
2120.2182250.4364490.781775
2130.2596940.5193890.740306
2140.2364320.4728640.763568
2150.2051950.4103890.794805
2160.1797080.3594150.820292
2170.1772920.3545830.822708
2180.1520370.3040750.847963
2190.1679740.3359480.832026
2200.1889140.3778270.811086
2210.1770160.3540320.822984
2220.1480710.2961420.851929
2230.1303220.2606440.869678
2240.121380.2427590.87862
2250.09978140.1995630.900219
2260.08358680.1671740.916413
2270.06529890.1305980.934701
2280.06623880.1324780.933761
2290.1122560.2245110.887744
2300.09659130.1931830.903409
2310.07658440.1531690.923416
2320.06238150.1247630.937618
2330.1079150.215830.892085
2340.1188940.2377880.881106
2350.1136620.2273240.886338
2360.08984490.179690.910155
2370.1321540.2643070.867846
2380.1710520.3421040.828948
2390.3087220.6174430.691278
2400.35620.71240.6438
2410.3403990.6807990.659601
2420.779330.4413390.22067
2430.7120710.5758590.287929
2440.6760460.6479080.323954
2450.6024830.7950340.397517
2460.5240210.9519580.475979
2470.5561890.8876220.443811
2480.5169880.9660240.483012
2490.4460120.8920240.553988
2500.3376640.6753270.662336
2510.2706860.5413710.729314
2520.9476440.1047120.0523561
2530.8676860.2646290.132314

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.808333 & 0.383335 & 0.191667 \tabularnewline
12 & 0.999691 & 0.000617373 & 0.000308687 \tabularnewline
13 & 0.999213 & 0.00157377 & 0.000786884 \tabularnewline
14 & 0.998405 & 0.00319044 & 0.00159522 \tabularnewline
15 & 0.996795 & 0.00640975 & 0.00320488 \tabularnewline
16 & 0.994732 & 0.0105362 & 0.00526809 \tabularnewline
17 & 0.991568 & 0.0168648 & 0.00843239 \tabularnewline
18 & 0.985855 & 0.0282903 & 0.0141452 \tabularnewline
19 & 0.983854 & 0.0322921 & 0.0161461 \tabularnewline
20 & 0.97476 & 0.0504791 & 0.0252396 \tabularnewline
21 & 0.962294 & 0.0754122 & 0.0377061 \tabularnewline
22 & 0.944568 & 0.110864 & 0.0554318 \tabularnewline
23 & 0.923887 & 0.152227 & 0.0761134 \tabularnewline
24 & 0.90312 & 0.193761 & 0.0968804 \tabularnewline
25 & 0.871345 & 0.257309 & 0.128655 \tabularnewline
26 & 0.913745 & 0.172511 & 0.0862555 \tabularnewline
27 & 0.890308 & 0.219384 & 0.109692 \tabularnewline
28 & 0.897126 & 0.205748 & 0.102874 \tabularnewline
29 & 0.892722 & 0.214556 & 0.107278 \tabularnewline
30 & 0.86424 & 0.27152 & 0.13576 \tabularnewline
31 & 0.845228 & 0.309544 & 0.154772 \tabularnewline
32 & 0.820264 & 0.359473 & 0.179736 \tabularnewline
33 & 0.77944 & 0.44112 & 0.22056 \tabularnewline
34 & 0.735792 & 0.528417 & 0.264208 \tabularnewline
35 & 0.697006 & 0.605987 & 0.302994 \tabularnewline
36 & 0.684459 & 0.631083 & 0.315541 \tabularnewline
37 & 0.786443 & 0.427113 & 0.213557 \tabularnewline
38 & 0.745804 & 0.508392 & 0.254196 \tabularnewline
39 & 0.701557 & 0.596887 & 0.298443 \tabularnewline
40 & 0.678043 & 0.643914 & 0.321957 \tabularnewline
41 & 0.641579 & 0.716841 & 0.358421 \tabularnewline
42 & 0.653952 & 0.692096 & 0.346048 \tabularnewline
43 & 0.665816 & 0.668368 & 0.334184 \tabularnewline
44 & 0.626275 & 0.74745 & 0.373725 \tabularnewline
45 & 0.581017 & 0.837966 & 0.418983 \tabularnewline
46 & 0.538779 & 0.922442 & 0.461221 \tabularnewline
47 & 0.517846 & 0.964307 & 0.482154 \tabularnewline
48 & 0.473215 & 0.94643 & 0.526785 \tabularnewline
49 & 0.628017 & 0.743967 & 0.371983 \tabularnewline
50 & 0.589338 & 0.821324 & 0.410662 \tabularnewline
51 & 0.549448 & 0.901104 & 0.450552 \tabularnewline
52 & 0.529886 & 0.940228 & 0.470114 \tabularnewline
53 & 0.562444 & 0.875111 & 0.437556 \tabularnewline
54 & 0.522453 & 0.955093 & 0.477547 \tabularnewline
55 & 0.521671 & 0.956657 & 0.478329 \tabularnewline
56 & 0.587871 & 0.824257 & 0.412129 \tabularnewline
57 & 0.58564 & 0.82872 & 0.41436 \tabularnewline
58 & 0.595179 & 0.809643 & 0.404821 \tabularnewline
59 & 0.595055 & 0.809891 & 0.404945 \tabularnewline
60 & 0.590613 & 0.818774 & 0.409387 \tabularnewline
61 & 0.620093 & 0.759815 & 0.379907 \tabularnewline
62 & 0.582513 & 0.834974 & 0.417487 \tabularnewline
63 & 0.552582 & 0.894836 & 0.447418 \tabularnewline
64 & 0.5132 & 0.973601 & 0.4868 \tabularnewline
65 & 0.473692 & 0.947383 & 0.526308 \tabularnewline
66 & 0.472624 & 0.945248 & 0.527376 \tabularnewline
67 & 0.501318 & 0.997365 & 0.498682 \tabularnewline
68 & 0.473275 & 0.946551 & 0.526725 \tabularnewline
69 & 0.438443 & 0.876886 & 0.561557 \tabularnewline
70 & 0.426743 & 0.853485 & 0.573257 \tabularnewline
71 & 0.389619 & 0.779237 & 0.610381 \tabularnewline
72 & 0.373564 & 0.747127 & 0.626436 \tabularnewline
73 & 0.351823 & 0.703646 & 0.648177 \tabularnewline
74 & 0.330474 & 0.660948 & 0.669526 \tabularnewline
75 & 0.302804 & 0.605607 & 0.697196 \tabularnewline
76 & 0.47759 & 0.95518 & 0.52241 \tabularnewline
77 & 0.458923 & 0.917845 & 0.541077 \tabularnewline
78 & 0.48272 & 0.96544 & 0.51728 \tabularnewline
79 & 0.444715 & 0.889429 & 0.555285 \tabularnewline
80 & 0.541027 & 0.917947 & 0.458973 \tabularnewline
81 & 0.506079 & 0.987842 & 0.493921 \tabularnewline
82 & 0.51855 & 0.9629 & 0.48145 \tabularnewline
83 & 0.482365 & 0.964731 & 0.517635 \tabularnewline
84 & 0.444392 & 0.888785 & 0.555608 \tabularnewline
85 & 0.408307 & 0.816615 & 0.591693 \tabularnewline
86 & 0.375265 & 0.75053 & 0.624735 \tabularnewline
87 & 0.344182 & 0.688363 & 0.655818 \tabularnewline
88 & 0.312771 & 0.625541 & 0.687229 \tabularnewline
89 & 0.400267 & 0.800534 & 0.599733 \tabularnewline
90 & 0.373317 & 0.746633 & 0.626683 \tabularnewline
91 & 0.344373 & 0.688746 & 0.655627 \tabularnewline
92 & 0.312907 & 0.625814 & 0.687093 \tabularnewline
93 & 0.304813 & 0.609626 & 0.695187 \tabularnewline
94 & 0.277868 & 0.555735 & 0.722132 \tabularnewline
95 & 0.247068 & 0.494137 & 0.752932 \tabularnewline
96 & 0.231054 & 0.462107 & 0.768946 \tabularnewline
97 & 0.214579 & 0.429158 & 0.785421 \tabularnewline
98 & 0.188541 & 0.377081 & 0.811459 \tabularnewline
99 & 0.183917 & 0.367834 & 0.816083 \tabularnewline
100 & 0.161611 & 0.323223 & 0.838389 \tabularnewline
101 & 0.150784 & 0.301569 & 0.849216 \tabularnewline
102 & 0.133434 & 0.266868 & 0.866566 \tabularnewline
103 & 0.167698 & 0.335396 & 0.832302 \tabularnewline
104 & 0.187377 & 0.374754 & 0.812623 \tabularnewline
105 & 0.190181 & 0.380361 & 0.809819 \tabularnewline
106 & 0.16685 & 0.3337 & 0.83315 \tabularnewline
107 & 0.1809 & 0.3618 & 0.8191 \tabularnewline
108 & 0.168204 & 0.336407 & 0.831796 \tabularnewline
109 & 0.274577 & 0.549154 & 0.725423 \tabularnewline
110 & 0.261276 & 0.522553 & 0.738724 \tabularnewline
111 & 0.233086 & 0.466172 & 0.766914 \tabularnewline
112 & 0.225747 & 0.451494 & 0.774253 \tabularnewline
113 & 0.199813 & 0.399627 & 0.800187 \tabularnewline
114 & 0.181054 & 0.362109 & 0.818946 \tabularnewline
115 & 0.160411 & 0.320822 & 0.839589 \tabularnewline
116 & 0.140354 & 0.280707 & 0.859646 \tabularnewline
117 & 0.124341 & 0.248681 & 0.875659 \tabularnewline
118 & 0.162522 & 0.325045 & 0.837478 \tabularnewline
119 & 0.161771 & 0.323541 & 0.838229 \tabularnewline
120 & 0.142649 & 0.285299 & 0.857351 \tabularnewline
121 & 0.12737 & 0.254739 & 0.87263 \tabularnewline
122 & 0.11224 & 0.22448 & 0.88776 \tabularnewline
123 & 0.139249 & 0.278498 & 0.860751 \tabularnewline
124 & 0.125407 & 0.250814 & 0.874593 \tabularnewline
125 & 0.121494 & 0.242989 & 0.878506 \tabularnewline
126 & 0.115757 & 0.231514 & 0.884243 \tabularnewline
127 & 0.101822 & 0.203645 & 0.898178 \tabularnewline
128 & 0.091185 & 0.18237 & 0.908815 \tabularnewline
129 & 0.0774449 & 0.15489 & 0.922555 \tabularnewline
130 & 0.0805252 & 0.16105 & 0.919475 \tabularnewline
131 & 0.0798484 & 0.159697 & 0.920152 \tabularnewline
132 & 0.0760841 & 0.152168 & 0.923916 \tabularnewline
133 & 0.0682763 & 0.136553 & 0.931724 \tabularnewline
134 & 0.0577046 & 0.115409 & 0.942295 \tabularnewline
135 & 0.0577454 & 0.115491 & 0.942255 \tabularnewline
136 & 0.110758 & 0.221515 & 0.889242 \tabularnewline
137 & 0.0946537 & 0.189307 & 0.905346 \tabularnewline
138 & 0.0821383 & 0.164277 & 0.917862 \tabularnewline
139 & 0.079811 & 0.159622 & 0.920189 \tabularnewline
140 & 0.0792563 & 0.158513 & 0.920744 \tabularnewline
141 & 0.0925476 & 0.185095 & 0.907452 \tabularnewline
142 & 0.0898814 & 0.179763 & 0.910119 \tabularnewline
143 & 0.0765918 & 0.153184 & 0.923408 \tabularnewline
144 & 0.0648476 & 0.129695 & 0.935152 \tabularnewline
145 & 0.0544174 & 0.108835 & 0.945583 \tabularnewline
146 & 0.0453372 & 0.0906744 & 0.954663 \tabularnewline
147 & 0.0503648 & 0.10073 & 0.949635 \tabularnewline
148 & 0.0583103 & 0.116621 & 0.94169 \tabularnewline
149 & 0.0536386 & 0.107277 & 0.946361 \tabularnewline
150 & 0.0446532 & 0.0893063 & 0.955347 \tabularnewline
151 & 0.0487068 & 0.0974137 & 0.951293 \tabularnewline
152 & 0.0510785 & 0.102157 & 0.948921 \tabularnewline
153 & 0.0523127 & 0.104625 & 0.947687 \tabularnewline
154 & 0.0471319 & 0.0942638 & 0.952868 \tabularnewline
155 & 0.0535548 & 0.10711 & 0.946445 \tabularnewline
156 & 0.0451409 & 0.0902819 & 0.954859 \tabularnewline
157 & 0.0372605 & 0.0745211 & 0.962739 \tabularnewline
158 & 0.0321407 & 0.0642815 & 0.967859 \tabularnewline
159 & 0.0439213 & 0.0878427 & 0.956079 \tabularnewline
160 & 0.0488805 & 0.097761 & 0.951119 \tabularnewline
161 & 0.0421638 & 0.0843276 & 0.957836 \tabularnewline
162 & 0.101569 & 0.203139 & 0.898431 \tabularnewline
163 & 0.0878388 & 0.175678 & 0.912161 \tabularnewline
164 & 0.301843 & 0.603686 & 0.698157 \tabularnewline
165 & 0.280707 & 0.561415 & 0.719293 \tabularnewline
166 & 0.389064 & 0.778128 & 0.610936 \tabularnewline
167 & 0.36052 & 0.721041 & 0.63948 \tabularnewline
168 & 0.334192 & 0.668383 & 0.665808 \tabularnewline
169 & 0.301726 & 0.603453 & 0.698274 \tabularnewline
170 & 0.275391 & 0.550783 & 0.724609 \tabularnewline
171 & 0.28849 & 0.57698 & 0.71151 \tabularnewline
172 & 0.258141 & 0.516281 & 0.741859 \tabularnewline
173 & 0.307353 & 0.614707 & 0.692647 \tabularnewline
174 & 0.297745 & 0.595491 & 0.702255 \tabularnewline
175 & 0.278431 & 0.556862 & 0.721569 \tabularnewline
176 & 0.33628 & 0.67256 & 0.66372 \tabularnewline
177 & 0.308249 & 0.616498 & 0.691751 \tabularnewline
178 & 0.319475 & 0.63895 & 0.680525 \tabularnewline
179 & 0.305864 & 0.611727 & 0.694136 \tabularnewline
180 & 0.280931 & 0.561862 & 0.719069 \tabularnewline
181 & 0.298993 & 0.597987 & 0.701007 \tabularnewline
182 & 0.401227 & 0.802454 & 0.598773 \tabularnewline
183 & 0.379108 & 0.758216 & 0.620892 \tabularnewline
184 & 0.383018 & 0.766036 & 0.616982 \tabularnewline
185 & 0.36192 & 0.723841 & 0.63808 \tabularnewline
186 & 0.453013 & 0.906026 & 0.546987 \tabularnewline
187 & 0.415576 & 0.831152 & 0.584424 \tabularnewline
188 & 0.377793 & 0.755587 & 0.622207 \tabularnewline
189 & 0.3488 & 0.697601 & 0.6512 \tabularnewline
190 & 0.415099 & 0.830198 & 0.584901 \tabularnewline
191 & 0.515257 & 0.969486 & 0.484743 \tabularnewline
192 & 0.542612 & 0.914776 & 0.457388 \tabularnewline
193 & 0.534542 & 0.930915 & 0.465458 \tabularnewline
194 & 0.49898 & 0.99796 & 0.50102 \tabularnewline
195 & 0.471143 & 0.942286 & 0.528857 \tabularnewline
196 & 0.50052 & 0.998961 & 0.49948 \tabularnewline
197 & 0.695681 & 0.608638 & 0.304319 \tabularnewline
198 & 0.703716 & 0.592568 & 0.296284 \tabularnewline
199 & 0.666827 & 0.666347 & 0.333173 \tabularnewline
200 & 0.628857 & 0.742285 & 0.371143 \tabularnewline
201 & 0.587003 & 0.825994 & 0.412997 \tabularnewline
202 & 0.549072 & 0.901857 & 0.450928 \tabularnewline
203 & 0.517581 & 0.964839 & 0.482419 \tabularnewline
204 & 0.493625 & 0.98725 & 0.506375 \tabularnewline
205 & 0.457382 & 0.914763 & 0.542618 \tabularnewline
206 & 0.415759 & 0.831519 & 0.584241 \tabularnewline
207 & 0.373345 & 0.746689 & 0.626655 \tabularnewline
208 & 0.338301 & 0.676602 & 0.661699 \tabularnewline
209 & 0.298215 & 0.59643 & 0.701785 \tabularnewline
210 & 0.283857 & 0.567715 & 0.716143 \tabularnewline
211 & 0.252828 & 0.505656 & 0.747172 \tabularnewline
212 & 0.218225 & 0.436449 & 0.781775 \tabularnewline
213 & 0.259694 & 0.519389 & 0.740306 \tabularnewline
214 & 0.236432 & 0.472864 & 0.763568 \tabularnewline
215 & 0.205195 & 0.410389 & 0.794805 \tabularnewline
216 & 0.179708 & 0.359415 & 0.820292 \tabularnewline
217 & 0.177292 & 0.354583 & 0.822708 \tabularnewline
218 & 0.152037 & 0.304075 & 0.847963 \tabularnewline
219 & 0.167974 & 0.335948 & 0.832026 \tabularnewline
220 & 0.188914 & 0.377827 & 0.811086 \tabularnewline
221 & 0.177016 & 0.354032 & 0.822984 \tabularnewline
222 & 0.148071 & 0.296142 & 0.851929 \tabularnewline
223 & 0.130322 & 0.260644 & 0.869678 \tabularnewline
224 & 0.12138 & 0.242759 & 0.87862 \tabularnewline
225 & 0.0997814 & 0.199563 & 0.900219 \tabularnewline
226 & 0.0835868 & 0.167174 & 0.916413 \tabularnewline
227 & 0.0652989 & 0.130598 & 0.934701 \tabularnewline
228 & 0.0662388 & 0.132478 & 0.933761 \tabularnewline
229 & 0.112256 & 0.224511 & 0.887744 \tabularnewline
230 & 0.0965913 & 0.193183 & 0.903409 \tabularnewline
231 & 0.0765844 & 0.153169 & 0.923416 \tabularnewline
232 & 0.0623815 & 0.124763 & 0.937618 \tabularnewline
233 & 0.107915 & 0.21583 & 0.892085 \tabularnewline
234 & 0.118894 & 0.237788 & 0.881106 \tabularnewline
235 & 0.113662 & 0.227324 & 0.886338 \tabularnewline
236 & 0.0898449 & 0.17969 & 0.910155 \tabularnewline
237 & 0.132154 & 0.264307 & 0.867846 \tabularnewline
238 & 0.171052 & 0.342104 & 0.828948 \tabularnewline
239 & 0.308722 & 0.617443 & 0.691278 \tabularnewline
240 & 0.3562 & 0.7124 & 0.6438 \tabularnewline
241 & 0.340399 & 0.680799 & 0.659601 \tabularnewline
242 & 0.77933 & 0.441339 & 0.22067 \tabularnewline
243 & 0.712071 & 0.575859 & 0.287929 \tabularnewline
244 & 0.676046 & 0.647908 & 0.323954 \tabularnewline
245 & 0.602483 & 0.795034 & 0.397517 \tabularnewline
246 & 0.524021 & 0.951958 & 0.475979 \tabularnewline
247 & 0.556189 & 0.887622 & 0.443811 \tabularnewline
248 & 0.516988 & 0.966024 & 0.483012 \tabularnewline
249 & 0.446012 & 0.892024 & 0.553988 \tabularnewline
250 & 0.337664 & 0.675327 & 0.662336 \tabularnewline
251 & 0.270686 & 0.541371 & 0.729314 \tabularnewline
252 & 0.947644 & 0.104712 & 0.0523561 \tabularnewline
253 & 0.867686 & 0.264629 & 0.132314 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253225&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]11[/C][C]0.808333[/C][C]0.383335[/C][C]0.191667[/C][/ROW]
[ROW][C]12[/C][C]0.999691[/C][C]0.000617373[/C][C]0.000308687[/C][/ROW]
[ROW][C]13[/C][C]0.999213[/C][C]0.00157377[/C][C]0.000786884[/C][/ROW]
[ROW][C]14[/C][C]0.998405[/C][C]0.00319044[/C][C]0.00159522[/C][/ROW]
[ROW][C]15[/C][C]0.996795[/C][C]0.00640975[/C][C]0.00320488[/C][/ROW]
[ROW][C]16[/C][C]0.994732[/C][C]0.0105362[/C][C]0.00526809[/C][/ROW]
[ROW][C]17[/C][C]0.991568[/C][C]0.0168648[/C][C]0.00843239[/C][/ROW]
[ROW][C]18[/C][C]0.985855[/C][C]0.0282903[/C][C]0.0141452[/C][/ROW]
[ROW][C]19[/C][C]0.983854[/C][C]0.0322921[/C][C]0.0161461[/C][/ROW]
[ROW][C]20[/C][C]0.97476[/C][C]0.0504791[/C][C]0.0252396[/C][/ROW]
[ROW][C]21[/C][C]0.962294[/C][C]0.0754122[/C][C]0.0377061[/C][/ROW]
[ROW][C]22[/C][C]0.944568[/C][C]0.110864[/C][C]0.0554318[/C][/ROW]
[ROW][C]23[/C][C]0.923887[/C][C]0.152227[/C][C]0.0761134[/C][/ROW]
[ROW][C]24[/C][C]0.90312[/C][C]0.193761[/C][C]0.0968804[/C][/ROW]
[ROW][C]25[/C][C]0.871345[/C][C]0.257309[/C][C]0.128655[/C][/ROW]
[ROW][C]26[/C][C]0.913745[/C][C]0.172511[/C][C]0.0862555[/C][/ROW]
[ROW][C]27[/C][C]0.890308[/C][C]0.219384[/C][C]0.109692[/C][/ROW]
[ROW][C]28[/C][C]0.897126[/C][C]0.205748[/C][C]0.102874[/C][/ROW]
[ROW][C]29[/C][C]0.892722[/C][C]0.214556[/C][C]0.107278[/C][/ROW]
[ROW][C]30[/C][C]0.86424[/C][C]0.27152[/C][C]0.13576[/C][/ROW]
[ROW][C]31[/C][C]0.845228[/C][C]0.309544[/C][C]0.154772[/C][/ROW]
[ROW][C]32[/C][C]0.820264[/C][C]0.359473[/C][C]0.179736[/C][/ROW]
[ROW][C]33[/C][C]0.77944[/C][C]0.44112[/C][C]0.22056[/C][/ROW]
[ROW][C]34[/C][C]0.735792[/C][C]0.528417[/C][C]0.264208[/C][/ROW]
[ROW][C]35[/C][C]0.697006[/C][C]0.605987[/C][C]0.302994[/C][/ROW]
[ROW][C]36[/C][C]0.684459[/C][C]0.631083[/C][C]0.315541[/C][/ROW]
[ROW][C]37[/C][C]0.786443[/C][C]0.427113[/C][C]0.213557[/C][/ROW]
[ROW][C]38[/C][C]0.745804[/C][C]0.508392[/C][C]0.254196[/C][/ROW]
[ROW][C]39[/C][C]0.701557[/C][C]0.596887[/C][C]0.298443[/C][/ROW]
[ROW][C]40[/C][C]0.678043[/C][C]0.643914[/C][C]0.321957[/C][/ROW]
[ROW][C]41[/C][C]0.641579[/C][C]0.716841[/C][C]0.358421[/C][/ROW]
[ROW][C]42[/C][C]0.653952[/C][C]0.692096[/C][C]0.346048[/C][/ROW]
[ROW][C]43[/C][C]0.665816[/C][C]0.668368[/C][C]0.334184[/C][/ROW]
[ROW][C]44[/C][C]0.626275[/C][C]0.74745[/C][C]0.373725[/C][/ROW]
[ROW][C]45[/C][C]0.581017[/C][C]0.837966[/C][C]0.418983[/C][/ROW]
[ROW][C]46[/C][C]0.538779[/C][C]0.922442[/C][C]0.461221[/C][/ROW]
[ROW][C]47[/C][C]0.517846[/C][C]0.964307[/C][C]0.482154[/C][/ROW]
[ROW][C]48[/C][C]0.473215[/C][C]0.94643[/C][C]0.526785[/C][/ROW]
[ROW][C]49[/C][C]0.628017[/C][C]0.743967[/C][C]0.371983[/C][/ROW]
[ROW][C]50[/C][C]0.589338[/C][C]0.821324[/C][C]0.410662[/C][/ROW]
[ROW][C]51[/C][C]0.549448[/C][C]0.901104[/C][C]0.450552[/C][/ROW]
[ROW][C]52[/C][C]0.529886[/C][C]0.940228[/C][C]0.470114[/C][/ROW]
[ROW][C]53[/C][C]0.562444[/C][C]0.875111[/C][C]0.437556[/C][/ROW]
[ROW][C]54[/C][C]0.522453[/C][C]0.955093[/C][C]0.477547[/C][/ROW]
[ROW][C]55[/C][C]0.521671[/C][C]0.956657[/C][C]0.478329[/C][/ROW]
[ROW][C]56[/C][C]0.587871[/C][C]0.824257[/C][C]0.412129[/C][/ROW]
[ROW][C]57[/C][C]0.58564[/C][C]0.82872[/C][C]0.41436[/C][/ROW]
[ROW][C]58[/C][C]0.595179[/C][C]0.809643[/C][C]0.404821[/C][/ROW]
[ROW][C]59[/C][C]0.595055[/C][C]0.809891[/C][C]0.404945[/C][/ROW]
[ROW][C]60[/C][C]0.590613[/C][C]0.818774[/C][C]0.409387[/C][/ROW]
[ROW][C]61[/C][C]0.620093[/C][C]0.759815[/C][C]0.379907[/C][/ROW]
[ROW][C]62[/C][C]0.582513[/C][C]0.834974[/C][C]0.417487[/C][/ROW]
[ROW][C]63[/C][C]0.552582[/C][C]0.894836[/C][C]0.447418[/C][/ROW]
[ROW][C]64[/C][C]0.5132[/C][C]0.973601[/C][C]0.4868[/C][/ROW]
[ROW][C]65[/C][C]0.473692[/C][C]0.947383[/C][C]0.526308[/C][/ROW]
[ROW][C]66[/C][C]0.472624[/C][C]0.945248[/C][C]0.527376[/C][/ROW]
[ROW][C]67[/C][C]0.501318[/C][C]0.997365[/C][C]0.498682[/C][/ROW]
[ROW][C]68[/C][C]0.473275[/C][C]0.946551[/C][C]0.526725[/C][/ROW]
[ROW][C]69[/C][C]0.438443[/C][C]0.876886[/C][C]0.561557[/C][/ROW]
[ROW][C]70[/C][C]0.426743[/C][C]0.853485[/C][C]0.573257[/C][/ROW]
[ROW][C]71[/C][C]0.389619[/C][C]0.779237[/C][C]0.610381[/C][/ROW]
[ROW][C]72[/C][C]0.373564[/C][C]0.747127[/C][C]0.626436[/C][/ROW]
[ROW][C]73[/C][C]0.351823[/C][C]0.703646[/C][C]0.648177[/C][/ROW]
[ROW][C]74[/C][C]0.330474[/C][C]0.660948[/C][C]0.669526[/C][/ROW]
[ROW][C]75[/C][C]0.302804[/C][C]0.605607[/C][C]0.697196[/C][/ROW]
[ROW][C]76[/C][C]0.47759[/C][C]0.95518[/C][C]0.52241[/C][/ROW]
[ROW][C]77[/C][C]0.458923[/C][C]0.917845[/C][C]0.541077[/C][/ROW]
[ROW][C]78[/C][C]0.48272[/C][C]0.96544[/C][C]0.51728[/C][/ROW]
[ROW][C]79[/C][C]0.444715[/C][C]0.889429[/C][C]0.555285[/C][/ROW]
[ROW][C]80[/C][C]0.541027[/C][C]0.917947[/C][C]0.458973[/C][/ROW]
[ROW][C]81[/C][C]0.506079[/C][C]0.987842[/C][C]0.493921[/C][/ROW]
[ROW][C]82[/C][C]0.51855[/C][C]0.9629[/C][C]0.48145[/C][/ROW]
[ROW][C]83[/C][C]0.482365[/C][C]0.964731[/C][C]0.517635[/C][/ROW]
[ROW][C]84[/C][C]0.444392[/C][C]0.888785[/C][C]0.555608[/C][/ROW]
[ROW][C]85[/C][C]0.408307[/C][C]0.816615[/C][C]0.591693[/C][/ROW]
[ROW][C]86[/C][C]0.375265[/C][C]0.75053[/C][C]0.624735[/C][/ROW]
[ROW][C]87[/C][C]0.344182[/C][C]0.688363[/C][C]0.655818[/C][/ROW]
[ROW][C]88[/C][C]0.312771[/C][C]0.625541[/C][C]0.687229[/C][/ROW]
[ROW][C]89[/C][C]0.400267[/C][C]0.800534[/C][C]0.599733[/C][/ROW]
[ROW][C]90[/C][C]0.373317[/C][C]0.746633[/C][C]0.626683[/C][/ROW]
[ROW][C]91[/C][C]0.344373[/C][C]0.688746[/C][C]0.655627[/C][/ROW]
[ROW][C]92[/C][C]0.312907[/C][C]0.625814[/C][C]0.687093[/C][/ROW]
[ROW][C]93[/C][C]0.304813[/C][C]0.609626[/C][C]0.695187[/C][/ROW]
[ROW][C]94[/C][C]0.277868[/C][C]0.555735[/C][C]0.722132[/C][/ROW]
[ROW][C]95[/C][C]0.247068[/C][C]0.494137[/C][C]0.752932[/C][/ROW]
[ROW][C]96[/C][C]0.231054[/C][C]0.462107[/C][C]0.768946[/C][/ROW]
[ROW][C]97[/C][C]0.214579[/C][C]0.429158[/C][C]0.785421[/C][/ROW]
[ROW][C]98[/C][C]0.188541[/C][C]0.377081[/C][C]0.811459[/C][/ROW]
[ROW][C]99[/C][C]0.183917[/C][C]0.367834[/C][C]0.816083[/C][/ROW]
[ROW][C]100[/C][C]0.161611[/C][C]0.323223[/C][C]0.838389[/C][/ROW]
[ROW][C]101[/C][C]0.150784[/C][C]0.301569[/C][C]0.849216[/C][/ROW]
[ROW][C]102[/C][C]0.133434[/C][C]0.266868[/C][C]0.866566[/C][/ROW]
[ROW][C]103[/C][C]0.167698[/C][C]0.335396[/C][C]0.832302[/C][/ROW]
[ROW][C]104[/C][C]0.187377[/C][C]0.374754[/C][C]0.812623[/C][/ROW]
[ROW][C]105[/C][C]0.190181[/C][C]0.380361[/C][C]0.809819[/C][/ROW]
[ROW][C]106[/C][C]0.16685[/C][C]0.3337[/C][C]0.83315[/C][/ROW]
[ROW][C]107[/C][C]0.1809[/C][C]0.3618[/C][C]0.8191[/C][/ROW]
[ROW][C]108[/C][C]0.168204[/C][C]0.336407[/C][C]0.831796[/C][/ROW]
[ROW][C]109[/C][C]0.274577[/C][C]0.549154[/C][C]0.725423[/C][/ROW]
[ROW][C]110[/C][C]0.261276[/C][C]0.522553[/C][C]0.738724[/C][/ROW]
[ROW][C]111[/C][C]0.233086[/C][C]0.466172[/C][C]0.766914[/C][/ROW]
[ROW][C]112[/C][C]0.225747[/C][C]0.451494[/C][C]0.774253[/C][/ROW]
[ROW][C]113[/C][C]0.199813[/C][C]0.399627[/C][C]0.800187[/C][/ROW]
[ROW][C]114[/C][C]0.181054[/C][C]0.362109[/C][C]0.818946[/C][/ROW]
[ROW][C]115[/C][C]0.160411[/C][C]0.320822[/C][C]0.839589[/C][/ROW]
[ROW][C]116[/C][C]0.140354[/C][C]0.280707[/C][C]0.859646[/C][/ROW]
[ROW][C]117[/C][C]0.124341[/C][C]0.248681[/C][C]0.875659[/C][/ROW]
[ROW][C]118[/C][C]0.162522[/C][C]0.325045[/C][C]0.837478[/C][/ROW]
[ROW][C]119[/C][C]0.161771[/C][C]0.323541[/C][C]0.838229[/C][/ROW]
[ROW][C]120[/C][C]0.142649[/C][C]0.285299[/C][C]0.857351[/C][/ROW]
[ROW][C]121[/C][C]0.12737[/C][C]0.254739[/C][C]0.87263[/C][/ROW]
[ROW][C]122[/C][C]0.11224[/C][C]0.22448[/C][C]0.88776[/C][/ROW]
[ROW][C]123[/C][C]0.139249[/C][C]0.278498[/C][C]0.860751[/C][/ROW]
[ROW][C]124[/C][C]0.125407[/C][C]0.250814[/C][C]0.874593[/C][/ROW]
[ROW][C]125[/C][C]0.121494[/C][C]0.242989[/C][C]0.878506[/C][/ROW]
[ROW][C]126[/C][C]0.115757[/C][C]0.231514[/C][C]0.884243[/C][/ROW]
[ROW][C]127[/C][C]0.101822[/C][C]0.203645[/C][C]0.898178[/C][/ROW]
[ROW][C]128[/C][C]0.091185[/C][C]0.18237[/C][C]0.908815[/C][/ROW]
[ROW][C]129[/C][C]0.0774449[/C][C]0.15489[/C][C]0.922555[/C][/ROW]
[ROW][C]130[/C][C]0.0805252[/C][C]0.16105[/C][C]0.919475[/C][/ROW]
[ROW][C]131[/C][C]0.0798484[/C][C]0.159697[/C][C]0.920152[/C][/ROW]
[ROW][C]132[/C][C]0.0760841[/C][C]0.152168[/C][C]0.923916[/C][/ROW]
[ROW][C]133[/C][C]0.0682763[/C][C]0.136553[/C][C]0.931724[/C][/ROW]
[ROW][C]134[/C][C]0.0577046[/C][C]0.115409[/C][C]0.942295[/C][/ROW]
[ROW][C]135[/C][C]0.0577454[/C][C]0.115491[/C][C]0.942255[/C][/ROW]
[ROW][C]136[/C][C]0.110758[/C][C]0.221515[/C][C]0.889242[/C][/ROW]
[ROW][C]137[/C][C]0.0946537[/C][C]0.189307[/C][C]0.905346[/C][/ROW]
[ROW][C]138[/C][C]0.0821383[/C][C]0.164277[/C][C]0.917862[/C][/ROW]
[ROW][C]139[/C][C]0.079811[/C][C]0.159622[/C][C]0.920189[/C][/ROW]
[ROW][C]140[/C][C]0.0792563[/C][C]0.158513[/C][C]0.920744[/C][/ROW]
[ROW][C]141[/C][C]0.0925476[/C][C]0.185095[/C][C]0.907452[/C][/ROW]
[ROW][C]142[/C][C]0.0898814[/C][C]0.179763[/C][C]0.910119[/C][/ROW]
[ROW][C]143[/C][C]0.0765918[/C][C]0.153184[/C][C]0.923408[/C][/ROW]
[ROW][C]144[/C][C]0.0648476[/C][C]0.129695[/C][C]0.935152[/C][/ROW]
[ROW][C]145[/C][C]0.0544174[/C][C]0.108835[/C][C]0.945583[/C][/ROW]
[ROW][C]146[/C][C]0.0453372[/C][C]0.0906744[/C][C]0.954663[/C][/ROW]
[ROW][C]147[/C][C]0.0503648[/C][C]0.10073[/C][C]0.949635[/C][/ROW]
[ROW][C]148[/C][C]0.0583103[/C][C]0.116621[/C][C]0.94169[/C][/ROW]
[ROW][C]149[/C][C]0.0536386[/C][C]0.107277[/C][C]0.946361[/C][/ROW]
[ROW][C]150[/C][C]0.0446532[/C][C]0.0893063[/C][C]0.955347[/C][/ROW]
[ROW][C]151[/C][C]0.0487068[/C][C]0.0974137[/C][C]0.951293[/C][/ROW]
[ROW][C]152[/C][C]0.0510785[/C][C]0.102157[/C][C]0.948921[/C][/ROW]
[ROW][C]153[/C][C]0.0523127[/C][C]0.104625[/C][C]0.947687[/C][/ROW]
[ROW][C]154[/C][C]0.0471319[/C][C]0.0942638[/C][C]0.952868[/C][/ROW]
[ROW][C]155[/C][C]0.0535548[/C][C]0.10711[/C][C]0.946445[/C][/ROW]
[ROW][C]156[/C][C]0.0451409[/C][C]0.0902819[/C][C]0.954859[/C][/ROW]
[ROW][C]157[/C][C]0.0372605[/C][C]0.0745211[/C][C]0.962739[/C][/ROW]
[ROW][C]158[/C][C]0.0321407[/C][C]0.0642815[/C][C]0.967859[/C][/ROW]
[ROW][C]159[/C][C]0.0439213[/C][C]0.0878427[/C][C]0.956079[/C][/ROW]
[ROW][C]160[/C][C]0.0488805[/C][C]0.097761[/C][C]0.951119[/C][/ROW]
[ROW][C]161[/C][C]0.0421638[/C][C]0.0843276[/C][C]0.957836[/C][/ROW]
[ROW][C]162[/C][C]0.101569[/C][C]0.203139[/C][C]0.898431[/C][/ROW]
[ROW][C]163[/C][C]0.0878388[/C][C]0.175678[/C][C]0.912161[/C][/ROW]
[ROW][C]164[/C][C]0.301843[/C][C]0.603686[/C][C]0.698157[/C][/ROW]
[ROW][C]165[/C][C]0.280707[/C][C]0.561415[/C][C]0.719293[/C][/ROW]
[ROW][C]166[/C][C]0.389064[/C][C]0.778128[/C][C]0.610936[/C][/ROW]
[ROW][C]167[/C][C]0.36052[/C][C]0.721041[/C][C]0.63948[/C][/ROW]
[ROW][C]168[/C][C]0.334192[/C][C]0.668383[/C][C]0.665808[/C][/ROW]
[ROW][C]169[/C][C]0.301726[/C][C]0.603453[/C][C]0.698274[/C][/ROW]
[ROW][C]170[/C][C]0.275391[/C][C]0.550783[/C][C]0.724609[/C][/ROW]
[ROW][C]171[/C][C]0.28849[/C][C]0.57698[/C][C]0.71151[/C][/ROW]
[ROW][C]172[/C][C]0.258141[/C][C]0.516281[/C][C]0.741859[/C][/ROW]
[ROW][C]173[/C][C]0.307353[/C][C]0.614707[/C][C]0.692647[/C][/ROW]
[ROW][C]174[/C][C]0.297745[/C][C]0.595491[/C][C]0.702255[/C][/ROW]
[ROW][C]175[/C][C]0.278431[/C][C]0.556862[/C][C]0.721569[/C][/ROW]
[ROW][C]176[/C][C]0.33628[/C][C]0.67256[/C][C]0.66372[/C][/ROW]
[ROW][C]177[/C][C]0.308249[/C][C]0.616498[/C][C]0.691751[/C][/ROW]
[ROW][C]178[/C][C]0.319475[/C][C]0.63895[/C][C]0.680525[/C][/ROW]
[ROW][C]179[/C][C]0.305864[/C][C]0.611727[/C][C]0.694136[/C][/ROW]
[ROW][C]180[/C][C]0.280931[/C][C]0.561862[/C][C]0.719069[/C][/ROW]
[ROW][C]181[/C][C]0.298993[/C][C]0.597987[/C][C]0.701007[/C][/ROW]
[ROW][C]182[/C][C]0.401227[/C][C]0.802454[/C][C]0.598773[/C][/ROW]
[ROW][C]183[/C][C]0.379108[/C][C]0.758216[/C][C]0.620892[/C][/ROW]
[ROW][C]184[/C][C]0.383018[/C][C]0.766036[/C][C]0.616982[/C][/ROW]
[ROW][C]185[/C][C]0.36192[/C][C]0.723841[/C][C]0.63808[/C][/ROW]
[ROW][C]186[/C][C]0.453013[/C][C]0.906026[/C][C]0.546987[/C][/ROW]
[ROW][C]187[/C][C]0.415576[/C][C]0.831152[/C][C]0.584424[/C][/ROW]
[ROW][C]188[/C][C]0.377793[/C][C]0.755587[/C][C]0.622207[/C][/ROW]
[ROW][C]189[/C][C]0.3488[/C][C]0.697601[/C][C]0.6512[/C][/ROW]
[ROW][C]190[/C][C]0.415099[/C][C]0.830198[/C][C]0.584901[/C][/ROW]
[ROW][C]191[/C][C]0.515257[/C][C]0.969486[/C][C]0.484743[/C][/ROW]
[ROW][C]192[/C][C]0.542612[/C][C]0.914776[/C][C]0.457388[/C][/ROW]
[ROW][C]193[/C][C]0.534542[/C][C]0.930915[/C][C]0.465458[/C][/ROW]
[ROW][C]194[/C][C]0.49898[/C][C]0.99796[/C][C]0.50102[/C][/ROW]
[ROW][C]195[/C][C]0.471143[/C][C]0.942286[/C][C]0.528857[/C][/ROW]
[ROW][C]196[/C][C]0.50052[/C][C]0.998961[/C][C]0.49948[/C][/ROW]
[ROW][C]197[/C][C]0.695681[/C][C]0.608638[/C][C]0.304319[/C][/ROW]
[ROW][C]198[/C][C]0.703716[/C][C]0.592568[/C][C]0.296284[/C][/ROW]
[ROW][C]199[/C][C]0.666827[/C][C]0.666347[/C][C]0.333173[/C][/ROW]
[ROW][C]200[/C][C]0.628857[/C][C]0.742285[/C][C]0.371143[/C][/ROW]
[ROW][C]201[/C][C]0.587003[/C][C]0.825994[/C][C]0.412997[/C][/ROW]
[ROW][C]202[/C][C]0.549072[/C][C]0.901857[/C][C]0.450928[/C][/ROW]
[ROW][C]203[/C][C]0.517581[/C][C]0.964839[/C][C]0.482419[/C][/ROW]
[ROW][C]204[/C][C]0.493625[/C][C]0.98725[/C][C]0.506375[/C][/ROW]
[ROW][C]205[/C][C]0.457382[/C][C]0.914763[/C][C]0.542618[/C][/ROW]
[ROW][C]206[/C][C]0.415759[/C][C]0.831519[/C][C]0.584241[/C][/ROW]
[ROW][C]207[/C][C]0.373345[/C][C]0.746689[/C][C]0.626655[/C][/ROW]
[ROW][C]208[/C][C]0.338301[/C][C]0.676602[/C][C]0.661699[/C][/ROW]
[ROW][C]209[/C][C]0.298215[/C][C]0.59643[/C][C]0.701785[/C][/ROW]
[ROW][C]210[/C][C]0.283857[/C][C]0.567715[/C][C]0.716143[/C][/ROW]
[ROW][C]211[/C][C]0.252828[/C][C]0.505656[/C][C]0.747172[/C][/ROW]
[ROW][C]212[/C][C]0.218225[/C][C]0.436449[/C][C]0.781775[/C][/ROW]
[ROW][C]213[/C][C]0.259694[/C][C]0.519389[/C][C]0.740306[/C][/ROW]
[ROW][C]214[/C][C]0.236432[/C][C]0.472864[/C][C]0.763568[/C][/ROW]
[ROW][C]215[/C][C]0.205195[/C][C]0.410389[/C][C]0.794805[/C][/ROW]
[ROW][C]216[/C][C]0.179708[/C][C]0.359415[/C][C]0.820292[/C][/ROW]
[ROW][C]217[/C][C]0.177292[/C][C]0.354583[/C][C]0.822708[/C][/ROW]
[ROW][C]218[/C][C]0.152037[/C][C]0.304075[/C][C]0.847963[/C][/ROW]
[ROW][C]219[/C][C]0.167974[/C][C]0.335948[/C][C]0.832026[/C][/ROW]
[ROW][C]220[/C][C]0.188914[/C][C]0.377827[/C][C]0.811086[/C][/ROW]
[ROW][C]221[/C][C]0.177016[/C][C]0.354032[/C][C]0.822984[/C][/ROW]
[ROW][C]222[/C][C]0.148071[/C][C]0.296142[/C][C]0.851929[/C][/ROW]
[ROW][C]223[/C][C]0.130322[/C][C]0.260644[/C][C]0.869678[/C][/ROW]
[ROW][C]224[/C][C]0.12138[/C][C]0.242759[/C][C]0.87862[/C][/ROW]
[ROW][C]225[/C][C]0.0997814[/C][C]0.199563[/C][C]0.900219[/C][/ROW]
[ROW][C]226[/C][C]0.0835868[/C][C]0.167174[/C][C]0.916413[/C][/ROW]
[ROW][C]227[/C][C]0.0652989[/C][C]0.130598[/C][C]0.934701[/C][/ROW]
[ROW][C]228[/C][C]0.0662388[/C][C]0.132478[/C][C]0.933761[/C][/ROW]
[ROW][C]229[/C][C]0.112256[/C][C]0.224511[/C][C]0.887744[/C][/ROW]
[ROW][C]230[/C][C]0.0965913[/C][C]0.193183[/C][C]0.903409[/C][/ROW]
[ROW][C]231[/C][C]0.0765844[/C][C]0.153169[/C][C]0.923416[/C][/ROW]
[ROW][C]232[/C][C]0.0623815[/C][C]0.124763[/C][C]0.937618[/C][/ROW]
[ROW][C]233[/C][C]0.107915[/C][C]0.21583[/C][C]0.892085[/C][/ROW]
[ROW][C]234[/C][C]0.118894[/C][C]0.237788[/C][C]0.881106[/C][/ROW]
[ROW][C]235[/C][C]0.113662[/C][C]0.227324[/C][C]0.886338[/C][/ROW]
[ROW][C]236[/C][C]0.0898449[/C][C]0.17969[/C][C]0.910155[/C][/ROW]
[ROW][C]237[/C][C]0.132154[/C][C]0.264307[/C][C]0.867846[/C][/ROW]
[ROW][C]238[/C][C]0.171052[/C][C]0.342104[/C][C]0.828948[/C][/ROW]
[ROW][C]239[/C][C]0.308722[/C][C]0.617443[/C][C]0.691278[/C][/ROW]
[ROW][C]240[/C][C]0.3562[/C][C]0.7124[/C][C]0.6438[/C][/ROW]
[ROW][C]241[/C][C]0.340399[/C][C]0.680799[/C][C]0.659601[/C][/ROW]
[ROW][C]242[/C][C]0.77933[/C][C]0.441339[/C][C]0.22067[/C][/ROW]
[ROW][C]243[/C][C]0.712071[/C][C]0.575859[/C][C]0.287929[/C][/ROW]
[ROW][C]244[/C][C]0.676046[/C][C]0.647908[/C][C]0.323954[/C][/ROW]
[ROW][C]245[/C][C]0.602483[/C][C]0.795034[/C][C]0.397517[/C][/ROW]
[ROW][C]246[/C][C]0.524021[/C][C]0.951958[/C][C]0.475979[/C][/ROW]
[ROW][C]247[/C][C]0.556189[/C][C]0.887622[/C][C]0.443811[/C][/ROW]
[ROW][C]248[/C][C]0.516988[/C][C]0.966024[/C][C]0.483012[/C][/ROW]
[ROW][C]249[/C][C]0.446012[/C][C]0.892024[/C][C]0.553988[/C][/ROW]
[ROW][C]250[/C][C]0.337664[/C][C]0.675327[/C][C]0.662336[/C][/ROW]
[ROW][C]251[/C][C]0.270686[/C][C]0.541371[/C][C]0.729314[/C][/ROW]
[ROW][C]252[/C][C]0.947644[/C][C]0.104712[/C][C]0.0523561[/C][/ROW]
[ROW][C]253[/C][C]0.867686[/C][C]0.264629[/C][C]0.132314[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253225&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253225&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.8083330.3833350.191667
120.9996910.0006173730.000308687
130.9992130.001573770.000786884
140.9984050.003190440.00159522
150.9967950.006409750.00320488
160.9947320.01053620.00526809
170.9915680.01686480.00843239
180.9858550.02829030.0141452
190.9838540.03229210.0161461
200.974760.05047910.0252396
210.9622940.07541220.0377061
220.9445680.1108640.0554318
230.9238870.1522270.0761134
240.903120.1937610.0968804
250.8713450.2573090.128655
260.9137450.1725110.0862555
270.8903080.2193840.109692
280.8971260.2057480.102874
290.8927220.2145560.107278
300.864240.271520.13576
310.8452280.3095440.154772
320.8202640.3594730.179736
330.779440.441120.22056
340.7357920.5284170.264208
350.6970060.6059870.302994
360.6844590.6310830.315541
370.7864430.4271130.213557
380.7458040.5083920.254196
390.7015570.5968870.298443
400.6780430.6439140.321957
410.6415790.7168410.358421
420.6539520.6920960.346048
430.6658160.6683680.334184
440.6262750.747450.373725
450.5810170.8379660.418983
460.5387790.9224420.461221
470.5178460.9643070.482154
480.4732150.946430.526785
490.6280170.7439670.371983
500.5893380.8213240.410662
510.5494480.9011040.450552
520.5298860.9402280.470114
530.5624440.8751110.437556
540.5224530.9550930.477547
550.5216710.9566570.478329
560.5878710.8242570.412129
570.585640.828720.41436
580.5951790.8096430.404821
590.5950550.8098910.404945
600.5906130.8187740.409387
610.6200930.7598150.379907
620.5825130.8349740.417487
630.5525820.8948360.447418
640.51320.9736010.4868
650.4736920.9473830.526308
660.4726240.9452480.527376
670.5013180.9973650.498682
680.4732750.9465510.526725
690.4384430.8768860.561557
700.4267430.8534850.573257
710.3896190.7792370.610381
720.3735640.7471270.626436
730.3518230.7036460.648177
740.3304740.6609480.669526
750.3028040.6056070.697196
760.477590.955180.52241
770.4589230.9178450.541077
780.482720.965440.51728
790.4447150.8894290.555285
800.5410270.9179470.458973
810.5060790.9878420.493921
820.518550.96290.48145
830.4823650.9647310.517635
840.4443920.8887850.555608
850.4083070.8166150.591693
860.3752650.750530.624735
870.3441820.6883630.655818
880.3127710.6255410.687229
890.4002670.8005340.599733
900.3733170.7466330.626683
910.3443730.6887460.655627
920.3129070.6258140.687093
930.3048130.6096260.695187
940.2778680.5557350.722132
950.2470680.4941370.752932
960.2310540.4621070.768946
970.2145790.4291580.785421
980.1885410.3770810.811459
990.1839170.3678340.816083
1000.1616110.3232230.838389
1010.1507840.3015690.849216
1020.1334340.2668680.866566
1030.1676980.3353960.832302
1040.1873770.3747540.812623
1050.1901810.3803610.809819
1060.166850.33370.83315
1070.18090.36180.8191
1080.1682040.3364070.831796
1090.2745770.5491540.725423
1100.2612760.5225530.738724
1110.2330860.4661720.766914
1120.2257470.4514940.774253
1130.1998130.3996270.800187
1140.1810540.3621090.818946
1150.1604110.3208220.839589
1160.1403540.2807070.859646
1170.1243410.2486810.875659
1180.1625220.3250450.837478
1190.1617710.3235410.838229
1200.1426490.2852990.857351
1210.127370.2547390.87263
1220.112240.224480.88776
1230.1392490.2784980.860751
1240.1254070.2508140.874593
1250.1214940.2429890.878506
1260.1157570.2315140.884243
1270.1018220.2036450.898178
1280.0911850.182370.908815
1290.07744490.154890.922555
1300.08052520.161050.919475
1310.07984840.1596970.920152
1320.07608410.1521680.923916
1330.06827630.1365530.931724
1340.05770460.1154090.942295
1350.05774540.1154910.942255
1360.1107580.2215150.889242
1370.09465370.1893070.905346
1380.08213830.1642770.917862
1390.0798110.1596220.920189
1400.07925630.1585130.920744
1410.09254760.1850950.907452
1420.08988140.1797630.910119
1430.07659180.1531840.923408
1440.06484760.1296950.935152
1450.05441740.1088350.945583
1460.04533720.09067440.954663
1470.05036480.100730.949635
1480.05831030.1166210.94169
1490.05363860.1072770.946361
1500.04465320.08930630.955347
1510.04870680.09741370.951293
1520.05107850.1021570.948921
1530.05231270.1046250.947687
1540.04713190.09426380.952868
1550.05355480.107110.946445
1560.04514090.09028190.954859
1570.03726050.07452110.962739
1580.03214070.06428150.967859
1590.04392130.08784270.956079
1600.04888050.0977610.951119
1610.04216380.08432760.957836
1620.1015690.2031390.898431
1630.08783880.1756780.912161
1640.3018430.6036860.698157
1650.2807070.5614150.719293
1660.3890640.7781280.610936
1670.360520.7210410.63948
1680.3341920.6683830.665808
1690.3017260.6034530.698274
1700.2753910.5507830.724609
1710.288490.576980.71151
1720.2581410.5162810.741859
1730.3073530.6147070.692647
1740.2977450.5954910.702255
1750.2784310.5568620.721569
1760.336280.672560.66372
1770.3082490.6164980.691751
1780.3194750.638950.680525
1790.3058640.6117270.694136
1800.2809310.5618620.719069
1810.2989930.5979870.701007
1820.4012270.8024540.598773
1830.3791080.7582160.620892
1840.3830180.7660360.616982
1850.361920.7238410.63808
1860.4530130.9060260.546987
1870.4155760.8311520.584424
1880.3777930.7555870.622207
1890.34880.6976010.6512
1900.4150990.8301980.584901
1910.5152570.9694860.484743
1920.5426120.9147760.457388
1930.5345420.9309150.465458
1940.498980.997960.50102
1950.4711430.9422860.528857
1960.500520.9989610.49948
1970.6956810.6086380.304319
1980.7037160.5925680.296284
1990.6668270.6663470.333173
2000.6288570.7422850.371143
2010.5870030.8259940.412997
2020.5490720.9018570.450928
2030.5175810.9648390.482419
2040.4936250.987250.506375
2050.4573820.9147630.542618
2060.4157590.8315190.584241
2070.3733450.7466890.626655
2080.3383010.6766020.661699
2090.2982150.596430.701785
2100.2838570.5677150.716143
2110.2528280.5056560.747172
2120.2182250.4364490.781775
2130.2596940.5193890.740306
2140.2364320.4728640.763568
2150.2051950.4103890.794805
2160.1797080.3594150.820292
2170.1772920.3545830.822708
2180.1520370.3040750.847963
2190.1679740.3359480.832026
2200.1889140.3778270.811086
2210.1770160.3540320.822984
2220.1480710.2961420.851929
2230.1303220.2606440.869678
2240.121380.2427590.87862
2250.09978140.1995630.900219
2260.08358680.1671740.916413
2270.06529890.1305980.934701
2280.06623880.1324780.933761
2290.1122560.2245110.887744
2300.09659130.1931830.903409
2310.07658440.1531690.923416
2320.06238150.1247630.937618
2330.1079150.215830.892085
2340.1188940.2377880.881106
2350.1136620.2273240.886338
2360.08984490.179690.910155
2370.1321540.2643070.867846
2380.1710520.3421040.828948
2390.3087220.6174430.691278
2400.35620.71240.6438
2410.3403990.6807990.659601
2420.779330.4413390.22067
2430.7120710.5758590.287929
2440.6760460.6479080.323954
2450.6024830.7950340.397517
2460.5240210.9519580.475979
2470.5561890.8876220.443811
2480.5169880.9660240.483012
2490.4460120.8920240.553988
2500.3376640.6753270.662336
2510.2706860.5413710.729314
2520.9476440.1047120.0523561
2530.8676860.2646290.132314






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level40.0164609NOK
5% type I error level80.0329218OK
10% type I error level200.0823045OK

\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 & 0.0164609 & NOK \tabularnewline
5% type I error level & 8 & 0.0329218 & OK \tabularnewline
10% type I error level & 20 & 0.0823045 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253225&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]0.0164609[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]8[/C][C]0.0329218[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]20[/C][C]0.0823045[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253225&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253225&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 level40.0164609NOK
5% type I error level80.0329218OK
10% type I error level200.0823045OK


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

Parameters (Session):
par1 = 6 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 6 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
R code (references can be found in the software module):
par3 <- 'Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- '7'
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')
}