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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationThu, 13 Nov 2014 17:55:04 +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/13/t1415901324t45ujnygd01kyi3.htm/, Retrieved Wed, 15 May 2024 18:10:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=254530, Retrieved Wed, 15 May 2024 18:10:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact58

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2013-11-04 07:18:26] [0307e7a6407eb638caabc417e3a6b260]
- RMPD    [Multiple Regression] [] [2014-11-13 17:55:04] [f11ff77f11120bba23ccca75f7c5b5e0] [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 time9 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 9 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254530&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254530&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254530&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 time9 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Sport1[t] = + 62.2724 + 0.147679Connected[t] + 0.0776011Separate[t] + 0.0956438Learning[t] + 0.124046Software[t] + 0.543746Happiness[t] -0.699219Depression[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Sport1[t] =  +  62.2724 +  0.147679Connected[t] +  0.0776011Separate[t] +  0.0956438Learning[t] +  0.124046Software[t] +  0.543746Happiness[t] -0.699219Depression[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254530&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Sport1[t] =  +  62.2724 +  0.147679Connected[t] +  0.0776011Separate[t] +  0.0956438Learning[t] +  0.124046Software[t] +  0.543746Happiness[t] -0.699219Depression[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254530&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254530&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
Sport1[t] = + 62.2724 + 0.147679Connected[t] + 0.0776011Separate[t] + 0.0956438Learning[t] + 0.124046Software[t] + 0.543746Happiness[t] -0.699219Depression[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)62.27249.163566.7967.48167e-113.74084e-11
Connected0.1476790.1807580.8170.4146840.207342
Separate0.07760110.1859610.41730.6768080.338404
Learning0.09564380.3251490.29420.7688780.384439
Software0.1240460.3342950.37110.7108940.355447
Happiness0.5437460.3013561.8040.07235030.0361751
Depression-0.6992190.216205-3.2340.001380220.000690108

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 62.2724 & 9.16356 & 6.796 & 7.48167e-11 & 3.74084e-11 \tabularnewline
Connected & 0.147679 & 0.180758 & 0.817 & 0.414684 & 0.207342 \tabularnewline
Separate & 0.0776011 & 0.185961 & 0.4173 & 0.676808 & 0.338404 \tabularnewline
Learning & 0.0956438 & 0.325149 & 0.2942 & 0.768878 & 0.384439 \tabularnewline
Software & 0.124046 & 0.334295 & 0.3711 & 0.710894 & 0.355447 \tabularnewline
Happiness & 0.543746 & 0.301356 & 1.804 & 0.0723503 & 0.0361751 \tabularnewline
Depression & -0.699219 & 0.216205 & -3.234 & 0.00138022 & 0.000690108 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254530&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]62.2724[/C][C]9.16356[/C][C]6.796[/C][C]7.48167e-11[/C][C]3.74084e-11[/C][/ROW]
[ROW][C]Connected[/C][C]0.147679[/C][C]0.180758[/C][C]0.817[/C][C]0.414684[/C][C]0.207342[/C][/ROW]
[ROW][C]Separate[/C][C]0.0776011[/C][C]0.185961[/C][C]0.4173[/C][C]0.676808[/C][C]0.338404[/C][/ROW]
[ROW][C]Learning[/C][C]0.0956438[/C][C]0.325149[/C][C]0.2942[/C][C]0.768878[/C][C]0.384439[/C][/ROW]
[ROW][C]Software[/C][C]0.124046[/C][C]0.334295[/C][C]0.3711[/C][C]0.710894[/C][C]0.355447[/C][/ROW]
[ROW][C]Happiness[/C][C]0.543746[/C][C]0.301356[/C][C]1.804[/C][C]0.0723503[/C][C]0.0361751[/C][/ROW]
[ROW][C]Depression[/C][C]-0.699219[/C][C]0.216205[/C][C]-3.234[/C][C]0.00138022[/C][C]0.000690108[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254530&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254530&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)62.27249.163566.7967.48167e-113.74084e-11
Connected0.1476790.1807580.8170.4146840.207342
Separate0.07760110.1859610.41730.6768080.338404
Learning0.09564380.3251490.29420.7688780.384439
Software0.1240460.3342950.37110.7108940.355447
Happiness0.5437460.3013561.8040.07235030.0361751
Depression-0.6992190.216205-3.2340.001380220.000690108






Multiple Linear Regression - Regression Statistics
Multiple R0.360873
R-squared0.130229
Adjusted R-squared0.109923
F-TEST (value)6.41335
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value2.59717e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation9.80761
Sum Squared Residuals24720.6

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.360873 \tabularnewline
R-squared & 0.130229 \tabularnewline
Adjusted R-squared & 0.109923 \tabularnewline
F-TEST (value) & 6.41335 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 257 \tabularnewline
p-value & 2.59717e-06 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 9.80761 \tabularnewline
Sum Squared Residuals & 24720.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254530&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.360873[/C][/ROW]
[ROW][C]R-squared[/C][C]0.130229[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.109923[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]6.41335[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]257[/C][/ROW]
[ROW][C]p-value[/C][C]2.59717e-06[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]9.80761[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]24720.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254530&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254530&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 R0.360873
R-squared0.130229
Adjusted R-squared0.109923
F-TEST (value)6.41335
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value2.59717e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation9.80761
Sum Squared Residuals24720.6






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
15373.2299-20.2299
28375.5067.494
36669.2889-3.28892
46769.7246-2.7246
57667.13278.86727
67873.57234.42772
75365.973-12.973
88073.17956.82049
97474.2965-0.2965
107672.30283.69717
117975.31213.68786
125477.9836-23.9836
136768.5683-1.56832
145472.7865-18.7865
158776.29910.701
165870.3056-12.3056
177570.57064.42937
188875.786812.2132
196474.6871-10.6871
205772.1104-15.1104
216675.5987-9.59867
226868.4671-0.467128
235473.6324-19.6324
245670.3937-14.3937
258675.181910.8181
268072.64987.35019
277674.08421.91578
286970.3126-1.31256
297871.09276.90733
306769.3252-2.32521
318074.58635.41369
325467.4635-13.4635
337174.9732-3.97318
348473.648410.3516
357470.97173.02827
367174.49-3.48996
376361.9431.05703
387172.7429-1.74286
397673.9832.01697
406972.8493-3.84932
417474.8538-0.853791
427571.59283.40719
435477.2472-23.2472
445269.3174-17.3174
456973.1013-4.10134
466869.8846-1.88461
476575.7255-10.7255
487573.04821.95176
497472.18791.81206
507572.57232.42766
517274.9217-2.92171
526769.7291-2.72907
536365.5906-2.59056
546270.1212-8.12117
556369.796-6.79598
567670.55345.44658
577473.29930.700685
586774.0756-7.07565
597372.86210.137859
607068.88711.11292
615361.2573-8.25729
627772.21964.78038
638070.86719.1329
645270.0934-18.0934
655471.7844-17.7844
668071.29718.70295
676667.8577-1.85765
687370.01852.98153
696372.8386-9.8386
706971.6984-2.69844
716771.1493-4.1493
725470.7145-16.7145
738172.84468.15544
746975.6881-6.68813
758471.784912.2151
768066.342113.6579
777073.9046-3.90455
786967.7761.22404
797770.61146.38864
805473.6264-19.6264
817973.42315.57687
827175.1945-4.19453
837373.5299-0.529929
847272.2013-0.201342
857770.84496.15515
867572.43252.56753
876972.025-3.02497
885468.6376-14.6376
897061.05338.94669
907372.06210.937884
915470.1392-16.1392
927772.70814.29194
938269.218412.7816
948069.943610.0564
958074.60495.39514
966968.9330.0670371
977872.41465.5854
988174.94616.05386
997673.53532.46471
1007676.1963-0.19633
1017368.68494.31513
1028574.54310.457
1036670.26-4.25997
1047970.03588.9642
1056865.00332.99667
1067674.72331.27668
1077171.3413-0.341277
1085468.1489-14.1489
1094662.5542-16.5542
1108570.727214.2728
1117468.17125.8288
1128872.547615.4524
1133869.2911-31.2911
1147674.161.84
1158675.261710.7383
1165471.0249-17.0249
1176771.2516-4.25156
1186973.7892-4.78924
1199070.820919.1791
1205468.6616-14.6616
1217669.9126.08799
1228974.107414.8926
1237676.5148-0.514799
1247373.5066-0.506566
1257972.17966.82039
1269076.840213.1598
1277477.0387-3.03872
1288175.13035.86966
1297271.58060.419371
1307171.7071-0.707066
1316662.1213.87902
1327774.73752.26248
1336568.768-3.76795
1347473.27850.721455
1358571.082713.9173
1365460.3736-6.37364
1376370.6321-7.63212
1385466.5051-12.5051
1396472.6845-8.68453
1406970.4131-1.41311
1415473.3233-19.3233
1428471.03612.964
1438672.127313.8727
1447771.29575.70431
1458973.542615.4574
1467672.73693.2631
1476070.0058-10.0058
1487571.25623.74379
1497363.89289.10721
1508573.044811.9552
1517969.57549.42455
1527175.2961-4.29606
1537270.87661.12344
1546964.46264.53737
1557865.983112.0169
1565470.1392-16.1392
1576969.6804-0.680447
1588175.13035.86966
1598473.447310.5527
1608466.026117.9739
1616968.20410.795888
1626659.41746.58255
1638168.831612.1684
1648268.523213.4768
1657265.84666.15338
1665459.9928-5.99276
1677871.1896.81101
1687467.32876.67135
1698266.680515.3195
1707364.45778.54235
1715563.907-8.907
1727273.7883-1.7883
1737869.93468.0654
1745965.4063-6.40626
1757272.0081-0.00809423
1767873.28914.71089
1776866.14371.85628
1786965.2343.76599
1796773.5434-6.54335
1807469.21184.78822
1815473.3224-19.3224
1826772.3413-5.34134
1837073.7868-3.78684
1848073.9116.08905
1858970.956418.0436
1867666.59429.40579
1877471.04122.95884
1888772.219214.7808
1895467.7803-13.7803
1906162.7617-1.76174
1913869.5107-31.5107
1927574.62740.372594
1936968.74680.253211
1946268.001-6.00097
1957270.33241.66763
1967071.743-1.74295
1977966.673212.3268
1988770.160116.8399
1996263.2269-1.22693
2007769.5937.40696
2016965.05673.9433
2026970.4898-1.48981
2037573.41991.58006
2045469.6927-15.6927
2057272.6761-0.676103
2067471.95272.04732
2078572.429112.5709
2085271.4654-19.4654
2097069.72190.278092
2108472.838811.1612
2116465.4976-1.49765
2128475.38658.61345
2138766.219120.7809
2147967.960711.0393
2156767.2706-0.270594
2166569.9933-4.99331
2178574.404610.5954
2188372.471710.5283
2196161.5078-0.507829
2208271.905710.0943
2217670.32465.67545
2225873.5667-15.5667
2237266.1035.89696
2247273.4611-1.46109
2253862.6571-24.6571
2267873.0094.99101
2275474.553-20.553
2286370.374-7.37405
2296660.29085.70919
2307069.16510.834923
2317170.8310.168965
2326765.99781.00219
2335873.7744-15.7744
2347269.52832.47166
2357274.6676-2.66757
2367068.47921.52079
2377665.829710.1703
2385070.3949-20.3949
2397269.72572.27432
2407269.47992.52005
2418870.415917.5841
2425363.7343-10.7343
2435865.2463-7.24632
2446667.3272-1.32715
2458271.184510.8155
2466963.40815.5919
2476868.7501-0.750061
2484463.6754-19.6754
2495660.3011-4.30115
2505364.5273-11.5273
2517069.77650.223532
2527866.635811.3642
2537171.4966-0.496627
2547270.25471.74534
2556867.32380.67617
2566768.5946-1.59456
2577563.541411.4586
2586263.9729-1.97289
2596770.6508-3.6508
2608370.367712.6323
2616470.6088-6.60879
2626872.5486-4.54858
2636261.31710.682932
2647270.71561.28438

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 53 & 73.2299 & -20.2299 \tabularnewline
2 & 83 & 75.506 & 7.494 \tabularnewline
3 & 66 & 69.2889 & -3.28892 \tabularnewline
4 & 67 & 69.7246 & -2.7246 \tabularnewline
5 & 76 & 67.1327 & 8.86727 \tabularnewline
6 & 78 & 73.5723 & 4.42772 \tabularnewline
7 & 53 & 65.973 & -12.973 \tabularnewline
8 & 80 & 73.1795 & 6.82049 \tabularnewline
9 & 74 & 74.2965 & -0.2965 \tabularnewline
10 & 76 & 72.3028 & 3.69717 \tabularnewline
11 & 79 & 75.3121 & 3.68786 \tabularnewline
12 & 54 & 77.9836 & -23.9836 \tabularnewline
13 & 67 & 68.5683 & -1.56832 \tabularnewline
14 & 54 & 72.7865 & -18.7865 \tabularnewline
15 & 87 & 76.299 & 10.701 \tabularnewline
16 & 58 & 70.3056 & -12.3056 \tabularnewline
17 & 75 & 70.5706 & 4.42937 \tabularnewline
18 & 88 & 75.7868 & 12.2132 \tabularnewline
19 & 64 & 74.6871 & -10.6871 \tabularnewline
20 & 57 & 72.1104 & -15.1104 \tabularnewline
21 & 66 & 75.5987 & -9.59867 \tabularnewline
22 & 68 & 68.4671 & -0.467128 \tabularnewline
23 & 54 & 73.6324 & -19.6324 \tabularnewline
24 & 56 & 70.3937 & -14.3937 \tabularnewline
25 & 86 & 75.1819 & 10.8181 \tabularnewline
26 & 80 & 72.6498 & 7.35019 \tabularnewline
27 & 76 & 74.0842 & 1.91578 \tabularnewline
28 & 69 & 70.3126 & -1.31256 \tabularnewline
29 & 78 & 71.0927 & 6.90733 \tabularnewline
30 & 67 & 69.3252 & -2.32521 \tabularnewline
31 & 80 & 74.5863 & 5.41369 \tabularnewline
32 & 54 & 67.4635 & -13.4635 \tabularnewline
33 & 71 & 74.9732 & -3.97318 \tabularnewline
34 & 84 & 73.6484 & 10.3516 \tabularnewline
35 & 74 & 70.9717 & 3.02827 \tabularnewline
36 & 71 & 74.49 & -3.48996 \tabularnewline
37 & 63 & 61.943 & 1.05703 \tabularnewline
38 & 71 & 72.7429 & -1.74286 \tabularnewline
39 & 76 & 73.983 & 2.01697 \tabularnewline
40 & 69 & 72.8493 & -3.84932 \tabularnewline
41 & 74 & 74.8538 & -0.853791 \tabularnewline
42 & 75 & 71.5928 & 3.40719 \tabularnewline
43 & 54 & 77.2472 & -23.2472 \tabularnewline
44 & 52 & 69.3174 & -17.3174 \tabularnewline
45 & 69 & 73.1013 & -4.10134 \tabularnewline
46 & 68 & 69.8846 & -1.88461 \tabularnewline
47 & 65 & 75.7255 & -10.7255 \tabularnewline
48 & 75 & 73.0482 & 1.95176 \tabularnewline
49 & 74 & 72.1879 & 1.81206 \tabularnewline
50 & 75 & 72.5723 & 2.42766 \tabularnewline
51 & 72 & 74.9217 & -2.92171 \tabularnewline
52 & 67 & 69.7291 & -2.72907 \tabularnewline
53 & 63 & 65.5906 & -2.59056 \tabularnewline
54 & 62 & 70.1212 & -8.12117 \tabularnewline
55 & 63 & 69.796 & -6.79598 \tabularnewline
56 & 76 & 70.5534 & 5.44658 \tabularnewline
57 & 74 & 73.2993 & 0.700685 \tabularnewline
58 & 67 & 74.0756 & -7.07565 \tabularnewline
59 & 73 & 72.8621 & 0.137859 \tabularnewline
60 & 70 & 68.8871 & 1.11292 \tabularnewline
61 & 53 & 61.2573 & -8.25729 \tabularnewline
62 & 77 & 72.2196 & 4.78038 \tabularnewline
63 & 80 & 70.8671 & 9.1329 \tabularnewline
64 & 52 & 70.0934 & -18.0934 \tabularnewline
65 & 54 & 71.7844 & -17.7844 \tabularnewline
66 & 80 & 71.2971 & 8.70295 \tabularnewline
67 & 66 & 67.8577 & -1.85765 \tabularnewline
68 & 73 & 70.0185 & 2.98153 \tabularnewline
69 & 63 & 72.8386 & -9.8386 \tabularnewline
70 & 69 & 71.6984 & -2.69844 \tabularnewline
71 & 67 & 71.1493 & -4.1493 \tabularnewline
72 & 54 & 70.7145 & -16.7145 \tabularnewline
73 & 81 & 72.8446 & 8.15544 \tabularnewline
74 & 69 & 75.6881 & -6.68813 \tabularnewline
75 & 84 & 71.7849 & 12.2151 \tabularnewline
76 & 80 & 66.3421 & 13.6579 \tabularnewline
77 & 70 & 73.9046 & -3.90455 \tabularnewline
78 & 69 & 67.776 & 1.22404 \tabularnewline
79 & 77 & 70.6114 & 6.38864 \tabularnewline
80 & 54 & 73.6264 & -19.6264 \tabularnewline
81 & 79 & 73.4231 & 5.57687 \tabularnewline
82 & 71 & 75.1945 & -4.19453 \tabularnewline
83 & 73 & 73.5299 & -0.529929 \tabularnewline
84 & 72 & 72.2013 & -0.201342 \tabularnewline
85 & 77 & 70.8449 & 6.15515 \tabularnewline
86 & 75 & 72.4325 & 2.56753 \tabularnewline
87 & 69 & 72.025 & -3.02497 \tabularnewline
88 & 54 & 68.6376 & -14.6376 \tabularnewline
89 & 70 & 61.0533 & 8.94669 \tabularnewline
90 & 73 & 72.0621 & 0.937884 \tabularnewline
91 & 54 & 70.1392 & -16.1392 \tabularnewline
92 & 77 & 72.7081 & 4.29194 \tabularnewline
93 & 82 & 69.2184 & 12.7816 \tabularnewline
94 & 80 & 69.9436 & 10.0564 \tabularnewline
95 & 80 & 74.6049 & 5.39514 \tabularnewline
96 & 69 & 68.933 & 0.0670371 \tabularnewline
97 & 78 & 72.4146 & 5.5854 \tabularnewline
98 & 81 & 74.9461 & 6.05386 \tabularnewline
99 & 76 & 73.5353 & 2.46471 \tabularnewline
100 & 76 & 76.1963 & -0.19633 \tabularnewline
101 & 73 & 68.6849 & 4.31513 \tabularnewline
102 & 85 & 74.543 & 10.457 \tabularnewline
103 & 66 & 70.26 & -4.25997 \tabularnewline
104 & 79 & 70.0358 & 8.9642 \tabularnewline
105 & 68 & 65.0033 & 2.99667 \tabularnewline
106 & 76 & 74.7233 & 1.27668 \tabularnewline
107 & 71 & 71.3413 & -0.341277 \tabularnewline
108 & 54 & 68.1489 & -14.1489 \tabularnewline
109 & 46 & 62.5542 & -16.5542 \tabularnewline
110 & 85 & 70.7272 & 14.2728 \tabularnewline
111 & 74 & 68.1712 & 5.8288 \tabularnewline
112 & 88 & 72.5476 & 15.4524 \tabularnewline
113 & 38 & 69.2911 & -31.2911 \tabularnewline
114 & 76 & 74.16 & 1.84 \tabularnewline
115 & 86 & 75.2617 & 10.7383 \tabularnewline
116 & 54 & 71.0249 & -17.0249 \tabularnewline
117 & 67 & 71.2516 & -4.25156 \tabularnewline
118 & 69 & 73.7892 & -4.78924 \tabularnewline
119 & 90 & 70.8209 & 19.1791 \tabularnewline
120 & 54 & 68.6616 & -14.6616 \tabularnewline
121 & 76 & 69.912 & 6.08799 \tabularnewline
122 & 89 & 74.1074 & 14.8926 \tabularnewline
123 & 76 & 76.5148 & -0.514799 \tabularnewline
124 & 73 & 73.5066 & -0.506566 \tabularnewline
125 & 79 & 72.1796 & 6.82039 \tabularnewline
126 & 90 & 76.8402 & 13.1598 \tabularnewline
127 & 74 & 77.0387 & -3.03872 \tabularnewline
128 & 81 & 75.1303 & 5.86966 \tabularnewline
129 & 72 & 71.5806 & 0.419371 \tabularnewline
130 & 71 & 71.7071 & -0.707066 \tabularnewline
131 & 66 & 62.121 & 3.87902 \tabularnewline
132 & 77 & 74.7375 & 2.26248 \tabularnewline
133 & 65 & 68.768 & -3.76795 \tabularnewline
134 & 74 & 73.2785 & 0.721455 \tabularnewline
135 & 85 & 71.0827 & 13.9173 \tabularnewline
136 & 54 & 60.3736 & -6.37364 \tabularnewline
137 & 63 & 70.6321 & -7.63212 \tabularnewline
138 & 54 & 66.5051 & -12.5051 \tabularnewline
139 & 64 & 72.6845 & -8.68453 \tabularnewline
140 & 69 & 70.4131 & -1.41311 \tabularnewline
141 & 54 & 73.3233 & -19.3233 \tabularnewline
142 & 84 & 71.036 & 12.964 \tabularnewline
143 & 86 & 72.1273 & 13.8727 \tabularnewline
144 & 77 & 71.2957 & 5.70431 \tabularnewline
145 & 89 & 73.5426 & 15.4574 \tabularnewline
146 & 76 & 72.7369 & 3.2631 \tabularnewline
147 & 60 & 70.0058 & -10.0058 \tabularnewline
148 & 75 & 71.2562 & 3.74379 \tabularnewline
149 & 73 & 63.8928 & 9.10721 \tabularnewline
150 & 85 & 73.0448 & 11.9552 \tabularnewline
151 & 79 & 69.5754 & 9.42455 \tabularnewline
152 & 71 & 75.2961 & -4.29606 \tabularnewline
153 & 72 & 70.8766 & 1.12344 \tabularnewline
154 & 69 & 64.4626 & 4.53737 \tabularnewline
155 & 78 & 65.9831 & 12.0169 \tabularnewline
156 & 54 & 70.1392 & -16.1392 \tabularnewline
157 & 69 & 69.6804 & -0.680447 \tabularnewline
158 & 81 & 75.1303 & 5.86966 \tabularnewline
159 & 84 & 73.4473 & 10.5527 \tabularnewline
160 & 84 & 66.0261 & 17.9739 \tabularnewline
161 & 69 & 68.2041 & 0.795888 \tabularnewline
162 & 66 & 59.4174 & 6.58255 \tabularnewline
163 & 81 & 68.8316 & 12.1684 \tabularnewline
164 & 82 & 68.5232 & 13.4768 \tabularnewline
165 & 72 & 65.8466 & 6.15338 \tabularnewline
166 & 54 & 59.9928 & -5.99276 \tabularnewline
167 & 78 & 71.189 & 6.81101 \tabularnewline
168 & 74 & 67.3287 & 6.67135 \tabularnewline
169 & 82 & 66.6805 & 15.3195 \tabularnewline
170 & 73 & 64.4577 & 8.54235 \tabularnewline
171 & 55 & 63.907 & -8.907 \tabularnewline
172 & 72 & 73.7883 & -1.7883 \tabularnewline
173 & 78 & 69.9346 & 8.0654 \tabularnewline
174 & 59 & 65.4063 & -6.40626 \tabularnewline
175 & 72 & 72.0081 & -0.00809423 \tabularnewline
176 & 78 & 73.2891 & 4.71089 \tabularnewline
177 & 68 & 66.1437 & 1.85628 \tabularnewline
178 & 69 & 65.234 & 3.76599 \tabularnewline
179 & 67 & 73.5434 & -6.54335 \tabularnewline
180 & 74 & 69.2118 & 4.78822 \tabularnewline
181 & 54 & 73.3224 & -19.3224 \tabularnewline
182 & 67 & 72.3413 & -5.34134 \tabularnewline
183 & 70 & 73.7868 & -3.78684 \tabularnewline
184 & 80 & 73.911 & 6.08905 \tabularnewline
185 & 89 & 70.9564 & 18.0436 \tabularnewline
186 & 76 & 66.5942 & 9.40579 \tabularnewline
187 & 74 & 71.0412 & 2.95884 \tabularnewline
188 & 87 & 72.2192 & 14.7808 \tabularnewline
189 & 54 & 67.7803 & -13.7803 \tabularnewline
190 & 61 & 62.7617 & -1.76174 \tabularnewline
191 & 38 & 69.5107 & -31.5107 \tabularnewline
192 & 75 & 74.6274 & 0.372594 \tabularnewline
193 & 69 & 68.7468 & 0.253211 \tabularnewline
194 & 62 & 68.001 & -6.00097 \tabularnewline
195 & 72 & 70.3324 & 1.66763 \tabularnewline
196 & 70 & 71.743 & -1.74295 \tabularnewline
197 & 79 & 66.6732 & 12.3268 \tabularnewline
198 & 87 & 70.1601 & 16.8399 \tabularnewline
199 & 62 & 63.2269 & -1.22693 \tabularnewline
200 & 77 & 69.593 & 7.40696 \tabularnewline
201 & 69 & 65.0567 & 3.9433 \tabularnewline
202 & 69 & 70.4898 & -1.48981 \tabularnewline
203 & 75 & 73.4199 & 1.58006 \tabularnewline
204 & 54 & 69.6927 & -15.6927 \tabularnewline
205 & 72 & 72.6761 & -0.676103 \tabularnewline
206 & 74 & 71.9527 & 2.04732 \tabularnewline
207 & 85 & 72.4291 & 12.5709 \tabularnewline
208 & 52 & 71.4654 & -19.4654 \tabularnewline
209 & 70 & 69.7219 & 0.278092 \tabularnewline
210 & 84 & 72.8388 & 11.1612 \tabularnewline
211 & 64 & 65.4976 & -1.49765 \tabularnewline
212 & 84 & 75.3865 & 8.61345 \tabularnewline
213 & 87 & 66.2191 & 20.7809 \tabularnewline
214 & 79 & 67.9607 & 11.0393 \tabularnewline
215 & 67 & 67.2706 & -0.270594 \tabularnewline
216 & 65 & 69.9933 & -4.99331 \tabularnewline
217 & 85 & 74.4046 & 10.5954 \tabularnewline
218 & 83 & 72.4717 & 10.5283 \tabularnewline
219 & 61 & 61.5078 & -0.507829 \tabularnewline
220 & 82 & 71.9057 & 10.0943 \tabularnewline
221 & 76 & 70.3246 & 5.67545 \tabularnewline
222 & 58 & 73.5667 & -15.5667 \tabularnewline
223 & 72 & 66.103 & 5.89696 \tabularnewline
224 & 72 & 73.4611 & -1.46109 \tabularnewline
225 & 38 & 62.6571 & -24.6571 \tabularnewline
226 & 78 & 73.009 & 4.99101 \tabularnewline
227 & 54 & 74.553 & -20.553 \tabularnewline
228 & 63 & 70.374 & -7.37405 \tabularnewline
229 & 66 & 60.2908 & 5.70919 \tabularnewline
230 & 70 & 69.1651 & 0.834923 \tabularnewline
231 & 71 & 70.831 & 0.168965 \tabularnewline
232 & 67 & 65.9978 & 1.00219 \tabularnewline
233 & 58 & 73.7744 & -15.7744 \tabularnewline
234 & 72 & 69.5283 & 2.47166 \tabularnewline
235 & 72 & 74.6676 & -2.66757 \tabularnewline
236 & 70 & 68.4792 & 1.52079 \tabularnewline
237 & 76 & 65.8297 & 10.1703 \tabularnewline
238 & 50 & 70.3949 & -20.3949 \tabularnewline
239 & 72 & 69.7257 & 2.27432 \tabularnewline
240 & 72 & 69.4799 & 2.52005 \tabularnewline
241 & 88 & 70.4159 & 17.5841 \tabularnewline
242 & 53 & 63.7343 & -10.7343 \tabularnewline
243 & 58 & 65.2463 & -7.24632 \tabularnewline
244 & 66 & 67.3272 & -1.32715 \tabularnewline
245 & 82 & 71.1845 & 10.8155 \tabularnewline
246 & 69 & 63.4081 & 5.5919 \tabularnewline
247 & 68 & 68.7501 & -0.750061 \tabularnewline
248 & 44 & 63.6754 & -19.6754 \tabularnewline
249 & 56 & 60.3011 & -4.30115 \tabularnewline
250 & 53 & 64.5273 & -11.5273 \tabularnewline
251 & 70 & 69.7765 & 0.223532 \tabularnewline
252 & 78 & 66.6358 & 11.3642 \tabularnewline
253 & 71 & 71.4966 & -0.496627 \tabularnewline
254 & 72 & 70.2547 & 1.74534 \tabularnewline
255 & 68 & 67.3238 & 0.67617 \tabularnewline
256 & 67 & 68.5946 & -1.59456 \tabularnewline
257 & 75 & 63.5414 & 11.4586 \tabularnewline
258 & 62 & 63.9729 & -1.97289 \tabularnewline
259 & 67 & 70.6508 & -3.6508 \tabularnewline
260 & 83 & 70.3677 & 12.6323 \tabularnewline
261 & 64 & 70.6088 & -6.60879 \tabularnewline
262 & 68 & 72.5486 & -4.54858 \tabularnewline
263 & 62 & 61.3171 & 0.682932 \tabularnewline
264 & 72 & 70.7156 & 1.28438 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254530&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]53[/C][C]73.2299[/C][C]-20.2299[/C][/ROW]
[ROW][C]2[/C][C]83[/C][C]75.506[/C][C]7.494[/C][/ROW]
[ROW][C]3[/C][C]66[/C][C]69.2889[/C][C]-3.28892[/C][/ROW]
[ROW][C]4[/C][C]67[/C][C]69.7246[/C][C]-2.7246[/C][/ROW]
[ROW][C]5[/C][C]76[/C][C]67.1327[/C][C]8.86727[/C][/ROW]
[ROW][C]6[/C][C]78[/C][C]73.5723[/C][C]4.42772[/C][/ROW]
[ROW][C]7[/C][C]53[/C][C]65.973[/C][C]-12.973[/C][/ROW]
[ROW][C]8[/C][C]80[/C][C]73.1795[/C][C]6.82049[/C][/ROW]
[ROW][C]9[/C][C]74[/C][C]74.2965[/C][C]-0.2965[/C][/ROW]
[ROW][C]10[/C][C]76[/C][C]72.3028[/C][C]3.69717[/C][/ROW]
[ROW][C]11[/C][C]79[/C][C]75.3121[/C][C]3.68786[/C][/ROW]
[ROW][C]12[/C][C]54[/C][C]77.9836[/C][C]-23.9836[/C][/ROW]
[ROW][C]13[/C][C]67[/C][C]68.5683[/C][C]-1.56832[/C][/ROW]
[ROW][C]14[/C][C]54[/C][C]72.7865[/C][C]-18.7865[/C][/ROW]
[ROW][C]15[/C][C]87[/C][C]76.299[/C][C]10.701[/C][/ROW]
[ROW][C]16[/C][C]58[/C][C]70.3056[/C][C]-12.3056[/C][/ROW]
[ROW][C]17[/C][C]75[/C][C]70.5706[/C][C]4.42937[/C][/ROW]
[ROW][C]18[/C][C]88[/C][C]75.7868[/C][C]12.2132[/C][/ROW]
[ROW][C]19[/C][C]64[/C][C]74.6871[/C][C]-10.6871[/C][/ROW]
[ROW][C]20[/C][C]57[/C][C]72.1104[/C][C]-15.1104[/C][/ROW]
[ROW][C]21[/C][C]66[/C][C]75.5987[/C][C]-9.59867[/C][/ROW]
[ROW][C]22[/C][C]68[/C][C]68.4671[/C][C]-0.467128[/C][/ROW]
[ROW][C]23[/C][C]54[/C][C]73.6324[/C][C]-19.6324[/C][/ROW]
[ROW][C]24[/C][C]56[/C][C]70.3937[/C][C]-14.3937[/C][/ROW]
[ROW][C]25[/C][C]86[/C][C]75.1819[/C][C]10.8181[/C][/ROW]
[ROW][C]26[/C][C]80[/C][C]72.6498[/C][C]7.35019[/C][/ROW]
[ROW][C]27[/C][C]76[/C][C]74.0842[/C][C]1.91578[/C][/ROW]
[ROW][C]28[/C][C]69[/C][C]70.3126[/C][C]-1.31256[/C][/ROW]
[ROW][C]29[/C][C]78[/C][C]71.0927[/C][C]6.90733[/C][/ROW]
[ROW][C]30[/C][C]67[/C][C]69.3252[/C][C]-2.32521[/C][/ROW]
[ROW][C]31[/C][C]80[/C][C]74.5863[/C][C]5.41369[/C][/ROW]
[ROW][C]32[/C][C]54[/C][C]67.4635[/C][C]-13.4635[/C][/ROW]
[ROW][C]33[/C][C]71[/C][C]74.9732[/C][C]-3.97318[/C][/ROW]
[ROW][C]34[/C][C]84[/C][C]73.6484[/C][C]10.3516[/C][/ROW]
[ROW][C]35[/C][C]74[/C][C]70.9717[/C][C]3.02827[/C][/ROW]
[ROW][C]36[/C][C]71[/C][C]74.49[/C][C]-3.48996[/C][/ROW]
[ROW][C]37[/C][C]63[/C][C]61.943[/C][C]1.05703[/C][/ROW]
[ROW][C]38[/C][C]71[/C][C]72.7429[/C][C]-1.74286[/C][/ROW]
[ROW][C]39[/C][C]76[/C][C]73.983[/C][C]2.01697[/C][/ROW]
[ROW][C]40[/C][C]69[/C][C]72.8493[/C][C]-3.84932[/C][/ROW]
[ROW][C]41[/C][C]74[/C][C]74.8538[/C][C]-0.853791[/C][/ROW]
[ROW][C]42[/C][C]75[/C][C]71.5928[/C][C]3.40719[/C][/ROW]
[ROW][C]43[/C][C]54[/C][C]77.2472[/C][C]-23.2472[/C][/ROW]
[ROW][C]44[/C][C]52[/C][C]69.3174[/C][C]-17.3174[/C][/ROW]
[ROW][C]45[/C][C]69[/C][C]73.1013[/C][C]-4.10134[/C][/ROW]
[ROW][C]46[/C][C]68[/C][C]69.8846[/C][C]-1.88461[/C][/ROW]
[ROW][C]47[/C][C]65[/C][C]75.7255[/C][C]-10.7255[/C][/ROW]
[ROW][C]48[/C][C]75[/C][C]73.0482[/C][C]1.95176[/C][/ROW]
[ROW][C]49[/C][C]74[/C][C]72.1879[/C][C]1.81206[/C][/ROW]
[ROW][C]50[/C][C]75[/C][C]72.5723[/C][C]2.42766[/C][/ROW]
[ROW][C]51[/C][C]72[/C][C]74.9217[/C][C]-2.92171[/C][/ROW]
[ROW][C]52[/C][C]67[/C][C]69.7291[/C][C]-2.72907[/C][/ROW]
[ROW][C]53[/C][C]63[/C][C]65.5906[/C][C]-2.59056[/C][/ROW]
[ROW][C]54[/C][C]62[/C][C]70.1212[/C][C]-8.12117[/C][/ROW]
[ROW][C]55[/C][C]63[/C][C]69.796[/C][C]-6.79598[/C][/ROW]
[ROW][C]56[/C][C]76[/C][C]70.5534[/C][C]5.44658[/C][/ROW]
[ROW][C]57[/C][C]74[/C][C]73.2993[/C][C]0.700685[/C][/ROW]
[ROW][C]58[/C][C]67[/C][C]74.0756[/C][C]-7.07565[/C][/ROW]
[ROW][C]59[/C][C]73[/C][C]72.8621[/C][C]0.137859[/C][/ROW]
[ROW][C]60[/C][C]70[/C][C]68.8871[/C][C]1.11292[/C][/ROW]
[ROW][C]61[/C][C]53[/C][C]61.2573[/C][C]-8.25729[/C][/ROW]
[ROW][C]62[/C][C]77[/C][C]72.2196[/C][C]4.78038[/C][/ROW]
[ROW][C]63[/C][C]80[/C][C]70.8671[/C][C]9.1329[/C][/ROW]
[ROW][C]64[/C][C]52[/C][C]70.0934[/C][C]-18.0934[/C][/ROW]
[ROW][C]65[/C][C]54[/C][C]71.7844[/C][C]-17.7844[/C][/ROW]
[ROW][C]66[/C][C]80[/C][C]71.2971[/C][C]8.70295[/C][/ROW]
[ROW][C]67[/C][C]66[/C][C]67.8577[/C][C]-1.85765[/C][/ROW]
[ROW][C]68[/C][C]73[/C][C]70.0185[/C][C]2.98153[/C][/ROW]
[ROW][C]69[/C][C]63[/C][C]72.8386[/C][C]-9.8386[/C][/ROW]
[ROW][C]70[/C][C]69[/C][C]71.6984[/C][C]-2.69844[/C][/ROW]
[ROW][C]71[/C][C]67[/C][C]71.1493[/C][C]-4.1493[/C][/ROW]
[ROW][C]72[/C][C]54[/C][C]70.7145[/C][C]-16.7145[/C][/ROW]
[ROW][C]73[/C][C]81[/C][C]72.8446[/C][C]8.15544[/C][/ROW]
[ROW][C]74[/C][C]69[/C][C]75.6881[/C][C]-6.68813[/C][/ROW]
[ROW][C]75[/C][C]84[/C][C]71.7849[/C][C]12.2151[/C][/ROW]
[ROW][C]76[/C][C]80[/C][C]66.3421[/C][C]13.6579[/C][/ROW]
[ROW][C]77[/C][C]70[/C][C]73.9046[/C][C]-3.90455[/C][/ROW]
[ROW][C]78[/C][C]69[/C][C]67.776[/C][C]1.22404[/C][/ROW]
[ROW][C]79[/C][C]77[/C][C]70.6114[/C][C]6.38864[/C][/ROW]
[ROW][C]80[/C][C]54[/C][C]73.6264[/C][C]-19.6264[/C][/ROW]
[ROW][C]81[/C][C]79[/C][C]73.4231[/C][C]5.57687[/C][/ROW]
[ROW][C]82[/C][C]71[/C][C]75.1945[/C][C]-4.19453[/C][/ROW]
[ROW][C]83[/C][C]73[/C][C]73.5299[/C][C]-0.529929[/C][/ROW]
[ROW][C]84[/C][C]72[/C][C]72.2013[/C][C]-0.201342[/C][/ROW]
[ROW][C]85[/C][C]77[/C][C]70.8449[/C][C]6.15515[/C][/ROW]
[ROW][C]86[/C][C]75[/C][C]72.4325[/C][C]2.56753[/C][/ROW]
[ROW][C]87[/C][C]69[/C][C]72.025[/C][C]-3.02497[/C][/ROW]
[ROW][C]88[/C][C]54[/C][C]68.6376[/C][C]-14.6376[/C][/ROW]
[ROW][C]89[/C][C]70[/C][C]61.0533[/C][C]8.94669[/C][/ROW]
[ROW][C]90[/C][C]73[/C][C]72.0621[/C][C]0.937884[/C][/ROW]
[ROW][C]91[/C][C]54[/C][C]70.1392[/C][C]-16.1392[/C][/ROW]
[ROW][C]92[/C][C]77[/C][C]72.7081[/C][C]4.29194[/C][/ROW]
[ROW][C]93[/C][C]82[/C][C]69.2184[/C][C]12.7816[/C][/ROW]
[ROW][C]94[/C][C]80[/C][C]69.9436[/C][C]10.0564[/C][/ROW]
[ROW][C]95[/C][C]80[/C][C]74.6049[/C][C]5.39514[/C][/ROW]
[ROW][C]96[/C][C]69[/C][C]68.933[/C][C]0.0670371[/C][/ROW]
[ROW][C]97[/C][C]78[/C][C]72.4146[/C][C]5.5854[/C][/ROW]
[ROW][C]98[/C][C]81[/C][C]74.9461[/C][C]6.05386[/C][/ROW]
[ROW][C]99[/C][C]76[/C][C]73.5353[/C][C]2.46471[/C][/ROW]
[ROW][C]100[/C][C]76[/C][C]76.1963[/C][C]-0.19633[/C][/ROW]
[ROW][C]101[/C][C]73[/C][C]68.6849[/C][C]4.31513[/C][/ROW]
[ROW][C]102[/C][C]85[/C][C]74.543[/C][C]10.457[/C][/ROW]
[ROW][C]103[/C][C]66[/C][C]70.26[/C][C]-4.25997[/C][/ROW]
[ROW][C]104[/C][C]79[/C][C]70.0358[/C][C]8.9642[/C][/ROW]
[ROW][C]105[/C][C]68[/C][C]65.0033[/C][C]2.99667[/C][/ROW]
[ROW][C]106[/C][C]76[/C][C]74.7233[/C][C]1.27668[/C][/ROW]
[ROW][C]107[/C][C]71[/C][C]71.3413[/C][C]-0.341277[/C][/ROW]
[ROW][C]108[/C][C]54[/C][C]68.1489[/C][C]-14.1489[/C][/ROW]
[ROW][C]109[/C][C]46[/C][C]62.5542[/C][C]-16.5542[/C][/ROW]
[ROW][C]110[/C][C]85[/C][C]70.7272[/C][C]14.2728[/C][/ROW]
[ROW][C]111[/C][C]74[/C][C]68.1712[/C][C]5.8288[/C][/ROW]
[ROW][C]112[/C][C]88[/C][C]72.5476[/C][C]15.4524[/C][/ROW]
[ROW][C]113[/C][C]38[/C][C]69.2911[/C][C]-31.2911[/C][/ROW]
[ROW][C]114[/C][C]76[/C][C]74.16[/C][C]1.84[/C][/ROW]
[ROW][C]115[/C][C]86[/C][C]75.2617[/C][C]10.7383[/C][/ROW]
[ROW][C]116[/C][C]54[/C][C]71.0249[/C][C]-17.0249[/C][/ROW]
[ROW][C]117[/C][C]67[/C][C]71.2516[/C][C]-4.25156[/C][/ROW]
[ROW][C]118[/C][C]69[/C][C]73.7892[/C][C]-4.78924[/C][/ROW]
[ROW][C]119[/C][C]90[/C][C]70.8209[/C][C]19.1791[/C][/ROW]
[ROW][C]120[/C][C]54[/C][C]68.6616[/C][C]-14.6616[/C][/ROW]
[ROW][C]121[/C][C]76[/C][C]69.912[/C][C]6.08799[/C][/ROW]
[ROW][C]122[/C][C]89[/C][C]74.1074[/C][C]14.8926[/C][/ROW]
[ROW][C]123[/C][C]76[/C][C]76.5148[/C][C]-0.514799[/C][/ROW]
[ROW][C]124[/C][C]73[/C][C]73.5066[/C][C]-0.506566[/C][/ROW]
[ROW][C]125[/C][C]79[/C][C]72.1796[/C][C]6.82039[/C][/ROW]
[ROW][C]126[/C][C]90[/C][C]76.8402[/C][C]13.1598[/C][/ROW]
[ROW][C]127[/C][C]74[/C][C]77.0387[/C][C]-3.03872[/C][/ROW]
[ROW][C]128[/C][C]81[/C][C]75.1303[/C][C]5.86966[/C][/ROW]
[ROW][C]129[/C][C]72[/C][C]71.5806[/C][C]0.419371[/C][/ROW]
[ROW][C]130[/C][C]71[/C][C]71.7071[/C][C]-0.707066[/C][/ROW]
[ROW][C]131[/C][C]66[/C][C]62.121[/C][C]3.87902[/C][/ROW]
[ROW][C]132[/C][C]77[/C][C]74.7375[/C][C]2.26248[/C][/ROW]
[ROW][C]133[/C][C]65[/C][C]68.768[/C][C]-3.76795[/C][/ROW]
[ROW][C]134[/C][C]74[/C][C]73.2785[/C][C]0.721455[/C][/ROW]
[ROW][C]135[/C][C]85[/C][C]71.0827[/C][C]13.9173[/C][/ROW]
[ROW][C]136[/C][C]54[/C][C]60.3736[/C][C]-6.37364[/C][/ROW]
[ROW][C]137[/C][C]63[/C][C]70.6321[/C][C]-7.63212[/C][/ROW]
[ROW][C]138[/C][C]54[/C][C]66.5051[/C][C]-12.5051[/C][/ROW]
[ROW][C]139[/C][C]64[/C][C]72.6845[/C][C]-8.68453[/C][/ROW]
[ROW][C]140[/C][C]69[/C][C]70.4131[/C][C]-1.41311[/C][/ROW]
[ROW][C]141[/C][C]54[/C][C]73.3233[/C][C]-19.3233[/C][/ROW]
[ROW][C]142[/C][C]84[/C][C]71.036[/C][C]12.964[/C][/ROW]
[ROW][C]143[/C][C]86[/C][C]72.1273[/C][C]13.8727[/C][/ROW]
[ROW][C]144[/C][C]77[/C][C]71.2957[/C][C]5.70431[/C][/ROW]
[ROW][C]145[/C][C]89[/C][C]73.5426[/C][C]15.4574[/C][/ROW]
[ROW][C]146[/C][C]76[/C][C]72.7369[/C][C]3.2631[/C][/ROW]
[ROW][C]147[/C][C]60[/C][C]70.0058[/C][C]-10.0058[/C][/ROW]
[ROW][C]148[/C][C]75[/C][C]71.2562[/C][C]3.74379[/C][/ROW]
[ROW][C]149[/C][C]73[/C][C]63.8928[/C][C]9.10721[/C][/ROW]
[ROW][C]150[/C][C]85[/C][C]73.0448[/C][C]11.9552[/C][/ROW]
[ROW][C]151[/C][C]79[/C][C]69.5754[/C][C]9.42455[/C][/ROW]
[ROW][C]152[/C][C]71[/C][C]75.2961[/C][C]-4.29606[/C][/ROW]
[ROW][C]153[/C][C]72[/C][C]70.8766[/C][C]1.12344[/C][/ROW]
[ROW][C]154[/C][C]69[/C][C]64.4626[/C][C]4.53737[/C][/ROW]
[ROW][C]155[/C][C]78[/C][C]65.9831[/C][C]12.0169[/C][/ROW]
[ROW][C]156[/C][C]54[/C][C]70.1392[/C][C]-16.1392[/C][/ROW]
[ROW][C]157[/C][C]69[/C][C]69.6804[/C][C]-0.680447[/C][/ROW]
[ROW][C]158[/C][C]81[/C][C]75.1303[/C][C]5.86966[/C][/ROW]
[ROW][C]159[/C][C]84[/C][C]73.4473[/C][C]10.5527[/C][/ROW]
[ROW][C]160[/C][C]84[/C][C]66.0261[/C][C]17.9739[/C][/ROW]
[ROW][C]161[/C][C]69[/C][C]68.2041[/C][C]0.795888[/C][/ROW]
[ROW][C]162[/C][C]66[/C][C]59.4174[/C][C]6.58255[/C][/ROW]
[ROW][C]163[/C][C]81[/C][C]68.8316[/C][C]12.1684[/C][/ROW]
[ROW][C]164[/C][C]82[/C][C]68.5232[/C][C]13.4768[/C][/ROW]
[ROW][C]165[/C][C]72[/C][C]65.8466[/C][C]6.15338[/C][/ROW]
[ROW][C]166[/C][C]54[/C][C]59.9928[/C][C]-5.99276[/C][/ROW]
[ROW][C]167[/C][C]78[/C][C]71.189[/C][C]6.81101[/C][/ROW]
[ROW][C]168[/C][C]74[/C][C]67.3287[/C][C]6.67135[/C][/ROW]
[ROW][C]169[/C][C]82[/C][C]66.6805[/C][C]15.3195[/C][/ROW]
[ROW][C]170[/C][C]73[/C][C]64.4577[/C][C]8.54235[/C][/ROW]
[ROW][C]171[/C][C]55[/C][C]63.907[/C][C]-8.907[/C][/ROW]
[ROW][C]172[/C][C]72[/C][C]73.7883[/C][C]-1.7883[/C][/ROW]
[ROW][C]173[/C][C]78[/C][C]69.9346[/C][C]8.0654[/C][/ROW]
[ROW][C]174[/C][C]59[/C][C]65.4063[/C][C]-6.40626[/C][/ROW]
[ROW][C]175[/C][C]72[/C][C]72.0081[/C][C]-0.00809423[/C][/ROW]
[ROW][C]176[/C][C]78[/C][C]73.2891[/C][C]4.71089[/C][/ROW]
[ROW][C]177[/C][C]68[/C][C]66.1437[/C][C]1.85628[/C][/ROW]
[ROW][C]178[/C][C]69[/C][C]65.234[/C][C]3.76599[/C][/ROW]
[ROW][C]179[/C][C]67[/C][C]73.5434[/C][C]-6.54335[/C][/ROW]
[ROW][C]180[/C][C]74[/C][C]69.2118[/C][C]4.78822[/C][/ROW]
[ROW][C]181[/C][C]54[/C][C]73.3224[/C][C]-19.3224[/C][/ROW]
[ROW][C]182[/C][C]67[/C][C]72.3413[/C][C]-5.34134[/C][/ROW]
[ROW][C]183[/C][C]70[/C][C]73.7868[/C][C]-3.78684[/C][/ROW]
[ROW][C]184[/C][C]80[/C][C]73.911[/C][C]6.08905[/C][/ROW]
[ROW][C]185[/C][C]89[/C][C]70.9564[/C][C]18.0436[/C][/ROW]
[ROW][C]186[/C][C]76[/C][C]66.5942[/C][C]9.40579[/C][/ROW]
[ROW][C]187[/C][C]74[/C][C]71.0412[/C][C]2.95884[/C][/ROW]
[ROW][C]188[/C][C]87[/C][C]72.2192[/C][C]14.7808[/C][/ROW]
[ROW][C]189[/C][C]54[/C][C]67.7803[/C][C]-13.7803[/C][/ROW]
[ROW][C]190[/C][C]61[/C][C]62.7617[/C][C]-1.76174[/C][/ROW]
[ROW][C]191[/C][C]38[/C][C]69.5107[/C][C]-31.5107[/C][/ROW]
[ROW][C]192[/C][C]75[/C][C]74.6274[/C][C]0.372594[/C][/ROW]
[ROW][C]193[/C][C]69[/C][C]68.7468[/C][C]0.253211[/C][/ROW]
[ROW][C]194[/C][C]62[/C][C]68.001[/C][C]-6.00097[/C][/ROW]
[ROW][C]195[/C][C]72[/C][C]70.3324[/C][C]1.66763[/C][/ROW]
[ROW][C]196[/C][C]70[/C][C]71.743[/C][C]-1.74295[/C][/ROW]
[ROW][C]197[/C][C]79[/C][C]66.6732[/C][C]12.3268[/C][/ROW]
[ROW][C]198[/C][C]87[/C][C]70.1601[/C][C]16.8399[/C][/ROW]
[ROW][C]199[/C][C]62[/C][C]63.2269[/C][C]-1.22693[/C][/ROW]
[ROW][C]200[/C][C]77[/C][C]69.593[/C][C]7.40696[/C][/ROW]
[ROW][C]201[/C][C]69[/C][C]65.0567[/C][C]3.9433[/C][/ROW]
[ROW][C]202[/C][C]69[/C][C]70.4898[/C][C]-1.48981[/C][/ROW]
[ROW][C]203[/C][C]75[/C][C]73.4199[/C][C]1.58006[/C][/ROW]
[ROW][C]204[/C][C]54[/C][C]69.6927[/C][C]-15.6927[/C][/ROW]
[ROW][C]205[/C][C]72[/C][C]72.6761[/C][C]-0.676103[/C][/ROW]
[ROW][C]206[/C][C]74[/C][C]71.9527[/C][C]2.04732[/C][/ROW]
[ROW][C]207[/C][C]85[/C][C]72.4291[/C][C]12.5709[/C][/ROW]
[ROW][C]208[/C][C]52[/C][C]71.4654[/C][C]-19.4654[/C][/ROW]
[ROW][C]209[/C][C]70[/C][C]69.7219[/C][C]0.278092[/C][/ROW]
[ROW][C]210[/C][C]84[/C][C]72.8388[/C][C]11.1612[/C][/ROW]
[ROW][C]211[/C][C]64[/C][C]65.4976[/C][C]-1.49765[/C][/ROW]
[ROW][C]212[/C][C]84[/C][C]75.3865[/C][C]8.61345[/C][/ROW]
[ROW][C]213[/C][C]87[/C][C]66.2191[/C][C]20.7809[/C][/ROW]
[ROW][C]214[/C][C]79[/C][C]67.9607[/C][C]11.0393[/C][/ROW]
[ROW][C]215[/C][C]67[/C][C]67.2706[/C][C]-0.270594[/C][/ROW]
[ROW][C]216[/C][C]65[/C][C]69.9933[/C][C]-4.99331[/C][/ROW]
[ROW][C]217[/C][C]85[/C][C]74.4046[/C][C]10.5954[/C][/ROW]
[ROW][C]218[/C][C]83[/C][C]72.4717[/C][C]10.5283[/C][/ROW]
[ROW][C]219[/C][C]61[/C][C]61.5078[/C][C]-0.507829[/C][/ROW]
[ROW][C]220[/C][C]82[/C][C]71.9057[/C][C]10.0943[/C][/ROW]
[ROW][C]221[/C][C]76[/C][C]70.3246[/C][C]5.67545[/C][/ROW]
[ROW][C]222[/C][C]58[/C][C]73.5667[/C][C]-15.5667[/C][/ROW]
[ROW][C]223[/C][C]72[/C][C]66.103[/C][C]5.89696[/C][/ROW]
[ROW][C]224[/C][C]72[/C][C]73.4611[/C][C]-1.46109[/C][/ROW]
[ROW][C]225[/C][C]38[/C][C]62.6571[/C][C]-24.6571[/C][/ROW]
[ROW][C]226[/C][C]78[/C][C]73.009[/C][C]4.99101[/C][/ROW]
[ROW][C]227[/C][C]54[/C][C]74.553[/C][C]-20.553[/C][/ROW]
[ROW][C]228[/C][C]63[/C][C]70.374[/C][C]-7.37405[/C][/ROW]
[ROW][C]229[/C][C]66[/C][C]60.2908[/C][C]5.70919[/C][/ROW]
[ROW][C]230[/C][C]70[/C][C]69.1651[/C][C]0.834923[/C][/ROW]
[ROW][C]231[/C][C]71[/C][C]70.831[/C][C]0.168965[/C][/ROW]
[ROW][C]232[/C][C]67[/C][C]65.9978[/C][C]1.00219[/C][/ROW]
[ROW][C]233[/C][C]58[/C][C]73.7744[/C][C]-15.7744[/C][/ROW]
[ROW][C]234[/C][C]72[/C][C]69.5283[/C][C]2.47166[/C][/ROW]
[ROW][C]235[/C][C]72[/C][C]74.6676[/C][C]-2.66757[/C][/ROW]
[ROW][C]236[/C][C]70[/C][C]68.4792[/C][C]1.52079[/C][/ROW]
[ROW][C]237[/C][C]76[/C][C]65.8297[/C][C]10.1703[/C][/ROW]
[ROW][C]238[/C][C]50[/C][C]70.3949[/C][C]-20.3949[/C][/ROW]
[ROW][C]239[/C][C]72[/C][C]69.7257[/C][C]2.27432[/C][/ROW]
[ROW][C]240[/C][C]72[/C][C]69.4799[/C][C]2.52005[/C][/ROW]
[ROW][C]241[/C][C]88[/C][C]70.4159[/C][C]17.5841[/C][/ROW]
[ROW][C]242[/C][C]53[/C][C]63.7343[/C][C]-10.7343[/C][/ROW]
[ROW][C]243[/C][C]58[/C][C]65.2463[/C][C]-7.24632[/C][/ROW]
[ROW][C]244[/C][C]66[/C][C]67.3272[/C][C]-1.32715[/C][/ROW]
[ROW][C]245[/C][C]82[/C][C]71.1845[/C][C]10.8155[/C][/ROW]
[ROW][C]246[/C][C]69[/C][C]63.4081[/C][C]5.5919[/C][/ROW]
[ROW][C]247[/C][C]68[/C][C]68.7501[/C][C]-0.750061[/C][/ROW]
[ROW][C]248[/C][C]44[/C][C]63.6754[/C][C]-19.6754[/C][/ROW]
[ROW][C]249[/C][C]56[/C][C]60.3011[/C][C]-4.30115[/C][/ROW]
[ROW][C]250[/C][C]53[/C][C]64.5273[/C][C]-11.5273[/C][/ROW]
[ROW][C]251[/C][C]70[/C][C]69.7765[/C][C]0.223532[/C][/ROW]
[ROW][C]252[/C][C]78[/C][C]66.6358[/C][C]11.3642[/C][/ROW]
[ROW][C]253[/C][C]71[/C][C]71.4966[/C][C]-0.496627[/C][/ROW]
[ROW][C]254[/C][C]72[/C][C]70.2547[/C][C]1.74534[/C][/ROW]
[ROW][C]255[/C][C]68[/C][C]67.3238[/C][C]0.67617[/C][/ROW]
[ROW][C]256[/C][C]67[/C][C]68.5946[/C][C]-1.59456[/C][/ROW]
[ROW][C]257[/C][C]75[/C][C]63.5414[/C][C]11.4586[/C][/ROW]
[ROW][C]258[/C][C]62[/C][C]63.9729[/C][C]-1.97289[/C][/ROW]
[ROW][C]259[/C][C]67[/C][C]70.6508[/C][C]-3.6508[/C][/ROW]
[ROW][C]260[/C][C]83[/C][C]70.3677[/C][C]12.6323[/C][/ROW]
[ROW][C]261[/C][C]64[/C][C]70.6088[/C][C]-6.60879[/C][/ROW]
[ROW][C]262[/C][C]68[/C][C]72.5486[/C][C]-4.54858[/C][/ROW]
[ROW][C]263[/C][C]62[/C][C]61.3171[/C][C]0.682932[/C][/ROW]
[ROW][C]264[/C][C]72[/C][C]70.7156[/C][C]1.28438[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254530&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254530&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
15373.2299-20.2299
28375.5067.494
36669.2889-3.28892
46769.7246-2.7246
57667.13278.86727
67873.57234.42772
75365.973-12.973
88073.17956.82049
97474.2965-0.2965
107672.30283.69717
117975.31213.68786
125477.9836-23.9836
136768.5683-1.56832
145472.7865-18.7865
158776.29910.701
165870.3056-12.3056
177570.57064.42937
188875.786812.2132
196474.6871-10.6871
205772.1104-15.1104
216675.5987-9.59867
226868.4671-0.467128
235473.6324-19.6324
245670.3937-14.3937
258675.181910.8181
268072.64987.35019
277674.08421.91578
286970.3126-1.31256
297871.09276.90733
306769.3252-2.32521
318074.58635.41369
325467.4635-13.4635
337174.9732-3.97318
348473.648410.3516
357470.97173.02827
367174.49-3.48996
376361.9431.05703
387172.7429-1.74286
397673.9832.01697
406972.8493-3.84932
417474.8538-0.853791
427571.59283.40719
435477.2472-23.2472
445269.3174-17.3174
456973.1013-4.10134
466869.8846-1.88461
476575.7255-10.7255
487573.04821.95176
497472.18791.81206
507572.57232.42766
517274.9217-2.92171
526769.7291-2.72907
536365.5906-2.59056
546270.1212-8.12117
556369.796-6.79598
567670.55345.44658
577473.29930.700685
586774.0756-7.07565
597372.86210.137859
607068.88711.11292
615361.2573-8.25729
627772.21964.78038
638070.86719.1329
645270.0934-18.0934
655471.7844-17.7844
668071.29718.70295
676667.8577-1.85765
687370.01852.98153
696372.8386-9.8386
706971.6984-2.69844
716771.1493-4.1493
725470.7145-16.7145
738172.84468.15544
746975.6881-6.68813
758471.784912.2151
768066.342113.6579
777073.9046-3.90455
786967.7761.22404
797770.61146.38864
805473.6264-19.6264
817973.42315.57687
827175.1945-4.19453
837373.5299-0.529929
847272.2013-0.201342
857770.84496.15515
867572.43252.56753
876972.025-3.02497
885468.6376-14.6376
897061.05338.94669
907372.06210.937884
915470.1392-16.1392
927772.70814.29194
938269.218412.7816
948069.943610.0564
958074.60495.39514
966968.9330.0670371
977872.41465.5854
988174.94616.05386
997673.53532.46471
1007676.1963-0.19633
1017368.68494.31513
1028574.54310.457
1036670.26-4.25997
1047970.03588.9642
1056865.00332.99667
1067674.72331.27668
1077171.3413-0.341277
1085468.1489-14.1489
1094662.5542-16.5542
1108570.727214.2728
1117468.17125.8288
1128872.547615.4524
1133869.2911-31.2911
1147674.161.84
1158675.261710.7383
1165471.0249-17.0249
1176771.2516-4.25156
1186973.7892-4.78924
1199070.820919.1791
1205468.6616-14.6616
1217669.9126.08799
1228974.107414.8926
1237676.5148-0.514799
1247373.5066-0.506566
1257972.17966.82039
1269076.840213.1598
1277477.0387-3.03872
1288175.13035.86966
1297271.58060.419371
1307171.7071-0.707066
1316662.1213.87902
1327774.73752.26248
1336568.768-3.76795
1347473.27850.721455
1358571.082713.9173
1365460.3736-6.37364
1376370.6321-7.63212
1385466.5051-12.5051
1396472.6845-8.68453
1406970.4131-1.41311
1415473.3233-19.3233
1428471.03612.964
1438672.127313.8727
1447771.29575.70431
1458973.542615.4574
1467672.73693.2631
1476070.0058-10.0058
1487571.25623.74379
1497363.89289.10721
1508573.044811.9552
1517969.57549.42455
1527175.2961-4.29606
1537270.87661.12344
1546964.46264.53737
1557865.983112.0169
1565470.1392-16.1392
1576969.6804-0.680447
1588175.13035.86966
1598473.447310.5527
1608466.026117.9739
1616968.20410.795888
1626659.41746.58255
1638168.831612.1684
1648268.523213.4768
1657265.84666.15338
1665459.9928-5.99276
1677871.1896.81101
1687467.32876.67135
1698266.680515.3195
1707364.45778.54235
1715563.907-8.907
1727273.7883-1.7883
1737869.93468.0654
1745965.4063-6.40626
1757272.0081-0.00809423
1767873.28914.71089
1776866.14371.85628
1786965.2343.76599
1796773.5434-6.54335
1807469.21184.78822
1815473.3224-19.3224
1826772.3413-5.34134
1837073.7868-3.78684
1848073.9116.08905
1858970.956418.0436
1867666.59429.40579
1877471.04122.95884
1888772.219214.7808
1895467.7803-13.7803
1906162.7617-1.76174
1913869.5107-31.5107
1927574.62740.372594
1936968.74680.253211
1946268.001-6.00097
1957270.33241.66763
1967071.743-1.74295
1977966.673212.3268
1988770.160116.8399
1996263.2269-1.22693
2007769.5937.40696
2016965.05673.9433
2026970.4898-1.48981
2037573.41991.58006
2045469.6927-15.6927
2057272.6761-0.676103
2067471.95272.04732
2078572.429112.5709
2085271.4654-19.4654
2097069.72190.278092
2108472.838811.1612
2116465.4976-1.49765
2128475.38658.61345
2138766.219120.7809
2147967.960711.0393
2156767.2706-0.270594
2166569.9933-4.99331
2178574.404610.5954
2188372.471710.5283
2196161.5078-0.507829
2208271.905710.0943
2217670.32465.67545
2225873.5667-15.5667
2237266.1035.89696
2247273.4611-1.46109
2253862.6571-24.6571
2267873.0094.99101
2275474.553-20.553
2286370.374-7.37405
2296660.29085.70919
2307069.16510.834923
2317170.8310.168965
2326765.99781.00219
2335873.7744-15.7744
2347269.52832.47166
2357274.6676-2.66757
2367068.47921.52079
2377665.829710.1703
2385070.3949-20.3949
2397269.72572.27432
2407269.47992.52005
2418870.415917.5841
2425363.7343-10.7343
2435865.2463-7.24632
2446667.3272-1.32715
2458271.184510.8155
2466963.40815.5919
2476868.7501-0.750061
2484463.6754-19.6754
2495660.3011-4.30115
2505364.5273-11.5273
2517069.77650.223532
2527866.635811.3642
2537171.4966-0.496627
2547270.25471.74534
2556867.32380.67617
2566768.5946-1.59456
2577563.541411.4586
2586263.9729-1.97289
2596770.6508-3.6508
2608370.367712.6323
2616470.6088-6.60879
2626872.5486-4.54858
2636261.31710.682932
2647270.71561.28438






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.1078830.2157660.892117
110.03894620.07789230.961054
120.9444740.1110530.0555264
130.9139720.1720550.0860277
140.8948130.2103740.105187
150.9091060.1817870.0908936
160.9429840.1140320.0570161
170.9250930.1498140.074907
180.9531660.09366790.0468339
190.9369870.1260270.0630135
200.960320.07936050.0396802
210.9568720.08625570.0431278
220.9390630.1218730.0609365
230.9517170.0965660.048283
240.9448390.1103220.0551611
250.9565330.08693470.0434673
260.9567180.08656480.0432824
270.9451010.1097980.054899
280.9268060.1463890.0731944
290.9166650.166670.0833348
300.8913540.2172910.108646
310.8641110.2717780.135889
320.8630920.2738150.136908
330.8337630.3324740.166237
340.8568850.286230.143115
350.8247390.3505220.175261
360.7876590.4246830.212341
370.7572530.4854950.242747
380.7138390.5723230.286161
390.6676520.6646960.332348
400.6204990.7590020.379501
410.5698160.8603680.430184
420.5257170.9485670.474283
430.7451580.5096830.254842
440.788890.422220.21111
450.7553260.4893480.244674
460.7157120.5685760.284288
470.698720.6025610.30128
480.6620350.675930.337965
490.6296430.7407150.370357
500.5949320.8101360.405068
510.5501170.8997660.449883
520.5059170.9881670.494083
530.4606660.9213320.539334
540.4270430.8540860.572957
550.3899130.7798260.610087
560.3878740.7757470.612126
570.3488830.6977660.651117
580.3211980.6423960.678802
590.292350.5846990.70765
600.2625590.5251180.737441
610.2430280.4860560.756972
620.2304860.4609720.769514
630.2472540.4945070.752746
640.312960.6259190.68704
650.3931360.7862710.606864
660.409440.818880.59056
670.3700950.740190.629905
680.3376150.675230.662385
690.320350.6406990.67965
700.2855220.5710440.714478
710.2533420.5066830.746658
720.2873870.5747740.712613
730.2956750.591350.704325
740.2712740.5425480.728726
750.2843950.568790.715605
760.3255590.6511180.674441
770.2937320.5874640.706268
780.2608280.5216550.739172
790.2480760.4961520.751924
800.3732810.7465620.626719
810.3582210.7164430.641779
820.3265460.6530920.673454
830.2932070.5864140.706793
840.2617910.5235820.738209
850.2454530.4909060.754547
860.2276540.4553080.772346
870.2014120.4028250.798588
880.2348740.4697490.765126
890.2333760.4667530.766624
900.2099410.4198810.790059
910.2616260.5232520.738374
920.2447080.4894150.755292
930.2689190.5378390.731081
940.2749540.5499070.725046
950.2604360.5208720.739564
960.2316830.4633660.768317
970.2140810.4281630.785919
980.2009740.4019480.799026
990.1801870.3603740.819813
1000.158540.317080.84146
1010.142610.285220.85739
1020.1464190.2928380.853581
1030.129750.2595010.87025
1040.1285250.2570510.871475
1050.1130230.2260460.886977
1060.09705150.1941030.902949
1070.08242980.164860.91757
1080.0974160.1948320.902584
1090.118280.236560.88172
1100.1383930.2767860.861607
1110.1252250.2504510.874775
1120.1605230.3210450.839477
1130.4277560.8555110.572244
1140.3994730.7989450.600527
1150.4002840.8005680.599716
1160.4655150.931030.534485
1170.4358740.8717470.564126
1180.4082440.8164880.591756
1190.5130230.9739540.486977
1200.5500930.8998150.449907
1210.5252880.9494240.474712
1220.5886910.8226180.411309
1230.5556180.8887630.444382
1240.5204690.9590620.479531
1250.4993580.9987170.500642
1260.5283930.9432150.471607
1270.4977260.9954530.502274
1280.4731840.9463690.526816
1290.4397280.8794570.560272
1300.404790.8095790.59521
1310.3831880.7663770.616812
1320.3524340.7048690.647566
1330.3246730.6493460.675327
1340.2955550.591110.704445
1350.3227360.6454720.677264
1360.3025650.605130.697435
1370.2907480.5814950.709252
1380.3075410.6150820.692459
1390.2984820.5969630.701518
1400.2719350.5438690.728065
1410.3629440.7258880.637056
1420.3874120.7748230.612588
1430.4110620.8221240.588938
1440.3917180.7834350.608282
1450.4569360.9138720.543064
1460.4295510.8591020.570449
1470.4351840.8703680.564816
1480.4056930.8113850.594307
1490.409940.819880.59006
1500.4302490.8604990.569751
1510.4271720.8543440.572828
1520.4005290.8010590.599471
1530.3695970.7391940.630403
1540.3461630.6923260.653837
1550.366280.7325590.63372
1560.424930.8498610.57507
1570.390950.7819010.60905
1580.3665280.7330570.633472
1590.3714240.7428490.628576
1600.4470670.8941340.552933
1610.4112950.822590.588705
1620.3963250.792650.603675
1630.4254430.8508870.574557
1640.4766370.9532740.523363
1650.4516410.9032810.548359
1660.4278830.8557670.572117
1670.4070520.8141040.592948
1680.3914610.7829210.608539
1690.4299060.8598120.570094
1700.4140410.8280830.585959
1710.4015780.8031550.598422
1720.3668530.7337070.633147
1730.3528490.7056990.647151
1740.3280480.6560960.671952
1750.2967240.5934480.703276
1760.2699550.539910.730045
1770.240440.480880.75956
1780.2174660.4349320.782534
1790.2001470.4002940.799853
1800.1786650.3573290.821335
1810.2605020.5210040.739498
1820.240410.4808190.75959
1830.2166580.4333150.783342
1840.1994560.3989120.800544
1850.2965920.5931840.703408
1860.2992250.5984490.700775
1870.268050.5361010.73195
1880.3079950.6159910.692005
1890.3296490.6592970.670351
1900.2977230.5954470.702277
1910.7022180.5955640.297782
1920.6730860.6538280.326914
1930.6349710.7300580.365029
1940.6269770.7460470.373023
1950.591930.816140.40807
1960.5676190.8647610.432381
1970.6472940.7054120.352706
1980.7162640.5674710.283736
1990.6825930.6348140.317407
2000.6644180.6711630.335582
2010.6319540.7360920.368046
2020.5912990.8174020.408701
2030.5610310.8779370.438969
2040.6148630.7702750.385137
2050.5724020.8551960.427598
2060.5302660.9394690.469734
2070.5417920.9164150.458208
2080.6353490.7293020.364651
2090.5915830.8168330.408417
2100.629460.7410810.37054
2110.5919710.8160580.408029
2120.5588310.8823370.441169
2130.6894790.6210420.310521
2140.6856380.6287230.314362
2150.6415080.7169850.358492
2160.599550.80090.40045
2170.6602530.6794940.339747
2180.6816850.636630.318315
2190.6354440.7291120.364556
2200.6805120.6389760.319488
2210.6418780.7162450.358122
2220.6670620.6658770.332938
2230.6504430.6991150.349557
2240.5998480.8003050.400152
2250.8633250.2733510.136675
2260.8380980.3238030.161902
2270.8700010.2599970.129999
2280.8655560.2688880.134444
2290.8420350.315930.157965
2300.8063890.3872210.193611
2310.7635520.4728960.236448
2320.7360330.5279350.263967
2330.8642130.2715740.135787
2340.8719840.2560310.128016
2350.8360050.327990.163995
2360.7950760.4098470.204924
2370.8578740.2842520.142126
2380.8966990.2066020.103301
2390.8662310.2675370.133769
2400.8218380.3563240.178162
2410.8665760.2668480.133424
2420.9108610.1782780.089139
2430.8921650.2156690.107835
2440.8626590.2746810.137341
2450.9493980.1012040.0506021
2460.9213770.1572470.0786234
2470.8807510.2384990.119249
2480.9339240.1321520.0660758
2490.8890970.2218060.110903
2500.8726460.2547080.127354
2510.7999960.4000080.200004
2520.8869070.2261860.113093
2530.8133940.3732130.186606
2540.7135070.5729870.286493

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.107883 & 0.215766 & 0.892117 \tabularnewline
11 & 0.0389462 & 0.0778923 & 0.961054 \tabularnewline
12 & 0.944474 & 0.111053 & 0.0555264 \tabularnewline
13 & 0.913972 & 0.172055 & 0.0860277 \tabularnewline
14 & 0.894813 & 0.210374 & 0.105187 \tabularnewline
15 & 0.909106 & 0.181787 & 0.0908936 \tabularnewline
16 & 0.942984 & 0.114032 & 0.0570161 \tabularnewline
17 & 0.925093 & 0.149814 & 0.074907 \tabularnewline
18 & 0.953166 & 0.0936679 & 0.0468339 \tabularnewline
19 & 0.936987 & 0.126027 & 0.0630135 \tabularnewline
20 & 0.96032 & 0.0793605 & 0.0396802 \tabularnewline
21 & 0.956872 & 0.0862557 & 0.0431278 \tabularnewline
22 & 0.939063 & 0.121873 & 0.0609365 \tabularnewline
23 & 0.951717 & 0.096566 & 0.048283 \tabularnewline
24 & 0.944839 & 0.110322 & 0.0551611 \tabularnewline
25 & 0.956533 & 0.0869347 & 0.0434673 \tabularnewline
26 & 0.956718 & 0.0865648 & 0.0432824 \tabularnewline
27 & 0.945101 & 0.109798 & 0.054899 \tabularnewline
28 & 0.926806 & 0.146389 & 0.0731944 \tabularnewline
29 & 0.916665 & 0.16667 & 0.0833348 \tabularnewline
30 & 0.891354 & 0.217291 & 0.108646 \tabularnewline
31 & 0.864111 & 0.271778 & 0.135889 \tabularnewline
32 & 0.863092 & 0.273815 & 0.136908 \tabularnewline
33 & 0.833763 & 0.332474 & 0.166237 \tabularnewline
34 & 0.856885 & 0.28623 & 0.143115 \tabularnewline
35 & 0.824739 & 0.350522 & 0.175261 \tabularnewline
36 & 0.787659 & 0.424683 & 0.212341 \tabularnewline
37 & 0.757253 & 0.485495 & 0.242747 \tabularnewline
38 & 0.713839 & 0.572323 & 0.286161 \tabularnewline
39 & 0.667652 & 0.664696 & 0.332348 \tabularnewline
40 & 0.620499 & 0.759002 & 0.379501 \tabularnewline
41 & 0.569816 & 0.860368 & 0.430184 \tabularnewline
42 & 0.525717 & 0.948567 & 0.474283 \tabularnewline
43 & 0.745158 & 0.509683 & 0.254842 \tabularnewline
44 & 0.78889 & 0.42222 & 0.21111 \tabularnewline
45 & 0.755326 & 0.489348 & 0.244674 \tabularnewline
46 & 0.715712 & 0.568576 & 0.284288 \tabularnewline
47 & 0.69872 & 0.602561 & 0.30128 \tabularnewline
48 & 0.662035 & 0.67593 & 0.337965 \tabularnewline
49 & 0.629643 & 0.740715 & 0.370357 \tabularnewline
50 & 0.594932 & 0.810136 & 0.405068 \tabularnewline
51 & 0.550117 & 0.899766 & 0.449883 \tabularnewline
52 & 0.505917 & 0.988167 & 0.494083 \tabularnewline
53 & 0.460666 & 0.921332 & 0.539334 \tabularnewline
54 & 0.427043 & 0.854086 & 0.572957 \tabularnewline
55 & 0.389913 & 0.779826 & 0.610087 \tabularnewline
56 & 0.387874 & 0.775747 & 0.612126 \tabularnewline
57 & 0.348883 & 0.697766 & 0.651117 \tabularnewline
58 & 0.321198 & 0.642396 & 0.678802 \tabularnewline
59 & 0.29235 & 0.584699 & 0.70765 \tabularnewline
60 & 0.262559 & 0.525118 & 0.737441 \tabularnewline
61 & 0.243028 & 0.486056 & 0.756972 \tabularnewline
62 & 0.230486 & 0.460972 & 0.769514 \tabularnewline
63 & 0.247254 & 0.494507 & 0.752746 \tabularnewline
64 & 0.31296 & 0.625919 & 0.68704 \tabularnewline
65 & 0.393136 & 0.786271 & 0.606864 \tabularnewline
66 & 0.40944 & 0.81888 & 0.59056 \tabularnewline
67 & 0.370095 & 0.74019 & 0.629905 \tabularnewline
68 & 0.337615 & 0.67523 & 0.662385 \tabularnewline
69 & 0.32035 & 0.640699 & 0.67965 \tabularnewline
70 & 0.285522 & 0.571044 & 0.714478 \tabularnewline
71 & 0.253342 & 0.506683 & 0.746658 \tabularnewline
72 & 0.287387 & 0.574774 & 0.712613 \tabularnewline
73 & 0.295675 & 0.59135 & 0.704325 \tabularnewline
74 & 0.271274 & 0.542548 & 0.728726 \tabularnewline
75 & 0.284395 & 0.56879 & 0.715605 \tabularnewline
76 & 0.325559 & 0.651118 & 0.674441 \tabularnewline
77 & 0.293732 & 0.587464 & 0.706268 \tabularnewline
78 & 0.260828 & 0.521655 & 0.739172 \tabularnewline
79 & 0.248076 & 0.496152 & 0.751924 \tabularnewline
80 & 0.373281 & 0.746562 & 0.626719 \tabularnewline
81 & 0.358221 & 0.716443 & 0.641779 \tabularnewline
82 & 0.326546 & 0.653092 & 0.673454 \tabularnewline
83 & 0.293207 & 0.586414 & 0.706793 \tabularnewline
84 & 0.261791 & 0.523582 & 0.738209 \tabularnewline
85 & 0.245453 & 0.490906 & 0.754547 \tabularnewline
86 & 0.227654 & 0.455308 & 0.772346 \tabularnewline
87 & 0.201412 & 0.402825 & 0.798588 \tabularnewline
88 & 0.234874 & 0.469749 & 0.765126 \tabularnewline
89 & 0.233376 & 0.466753 & 0.766624 \tabularnewline
90 & 0.209941 & 0.419881 & 0.790059 \tabularnewline
91 & 0.261626 & 0.523252 & 0.738374 \tabularnewline
92 & 0.244708 & 0.489415 & 0.755292 \tabularnewline
93 & 0.268919 & 0.537839 & 0.731081 \tabularnewline
94 & 0.274954 & 0.549907 & 0.725046 \tabularnewline
95 & 0.260436 & 0.520872 & 0.739564 \tabularnewline
96 & 0.231683 & 0.463366 & 0.768317 \tabularnewline
97 & 0.214081 & 0.428163 & 0.785919 \tabularnewline
98 & 0.200974 & 0.401948 & 0.799026 \tabularnewline
99 & 0.180187 & 0.360374 & 0.819813 \tabularnewline
100 & 0.15854 & 0.31708 & 0.84146 \tabularnewline
101 & 0.14261 & 0.28522 & 0.85739 \tabularnewline
102 & 0.146419 & 0.292838 & 0.853581 \tabularnewline
103 & 0.12975 & 0.259501 & 0.87025 \tabularnewline
104 & 0.128525 & 0.257051 & 0.871475 \tabularnewline
105 & 0.113023 & 0.226046 & 0.886977 \tabularnewline
106 & 0.0970515 & 0.194103 & 0.902949 \tabularnewline
107 & 0.0824298 & 0.16486 & 0.91757 \tabularnewline
108 & 0.097416 & 0.194832 & 0.902584 \tabularnewline
109 & 0.11828 & 0.23656 & 0.88172 \tabularnewline
110 & 0.138393 & 0.276786 & 0.861607 \tabularnewline
111 & 0.125225 & 0.250451 & 0.874775 \tabularnewline
112 & 0.160523 & 0.321045 & 0.839477 \tabularnewline
113 & 0.427756 & 0.855511 & 0.572244 \tabularnewline
114 & 0.399473 & 0.798945 & 0.600527 \tabularnewline
115 & 0.400284 & 0.800568 & 0.599716 \tabularnewline
116 & 0.465515 & 0.93103 & 0.534485 \tabularnewline
117 & 0.435874 & 0.871747 & 0.564126 \tabularnewline
118 & 0.408244 & 0.816488 & 0.591756 \tabularnewline
119 & 0.513023 & 0.973954 & 0.486977 \tabularnewline
120 & 0.550093 & 0.899815 & 0.449907 \tabularnewline
121 & 0.525288 & 0.949424 & 0.474712 \tabularnewline
122 & 0.588691 & 0.822618 & 0.411309 \tabularnewline
123 & 0.555618 & 0.888763 & 0.444382 \tabularnewline
124 & 0.520469 & 0.959062 & 0.479531 \tabularnewline
125 & 0.499358 & 0.998717 & 0.500642 \tabularnewline
126 & 0.528393 & 0.943215 & 0.471607 \tabularnewline
127 & 0.497726 & 0.995453 & 0.502274 \tabularnewline
128 & 0.473184 & 0.946369 & 0.526816 \tabularnewline
129 & 0.439728 & 0.879457 & 0.560272 \tabularnewline
130 & 0.40479 & 0.809579 & 0.59521 \tabularnewline
131 & 0.383188 & 0.766377 & 0.616812 \tabularnewline
132 & 0.352434 & 0.704869 & 0.647566 \tabularnewline
133 & 0.324673 & 0.649346 & 0.675327 \tabularnewline
134 & 0.295555 & 0.59111 & 0.704445 \tabularnewline
135 & 0.322736 & 0.645472 & 0.677264 \tabularnewline
136 & 0.302565 & 0.60513 & 0.697435 \tabularnewline
137 & 0.290748 & 0.581495 & 0.709252 \tabularnewline
138 & 0.307541 & 0.615082 & 0.692459 \tabularnewline
139 & 0.298482 & 0.596963 & 0.701518 \tabularnewline
140 & 0.271935 & 0.543869 & 0.728065 \tabularnewline
141 & 0.362944 & 0.725888 & 0.637056 \tabularnewline
142 & 0.387412 & 0.774823 & 0.612588 \tabularnewline
143 & 0.411062 & 0.822124 & 0.588938 \tabularnewline
144 & 0.391718 & 0.783435 & 0.608282 \tabularnewline
145 & 0.456936 & 0.913872 & 0.543064 \tabularnewline
146 & 0.429551 & 0.859102 & 0.570449 \tabularnewline
147 & 0.435184 & 0.870368 & 0.564816 \tabularnewline
148 & 0.405693 & 0.811385 & 0.594307 \tabularnewline
149 & 0.40994 & 0.81988 & 0.59006 \tabularnewline
150 & 0.430249 & 0.860499 & 0.569751 \tabularnewline
151 & 0.427172 & 0.854344 & 0.572828 \tabularnewline
152 & 0.400529 & 0.801059 & 0.599471 \tabularnewline
153 & 0.369597 & 0.739194 & 0.630403 \tabularnewline
154 & 0.346163 & 0.692326 & 0.653837 \tabularnewline
155 & 0.36628 & 0.732559 & 0.63372 \tabularnewline
156 & 0.42493 & 0.849861 & 0.57507 \tabularnewline
157 & 0.39095 & 0.781901 & 0.60905 \tabularnewline
158 & 0.366528 & 0.733057 & 0.633472 \tabularnewline
159 & 0.371424 & 0.742849 & 0.628576 \tabularnewline
160 & 0.447067 & 0.894134 & 0.552933 \tabularnewline
161 & 0.411295 & 0.82259 & 0.588705 \tabularnewline
162 & 0.396325 & 0.79265 & 0.603675 \tabularnewline
163 & 0.425443 & 0.850887 & 0.574557 \tabularnewline
164 & 0.476637 & 0.953274 & 0.523363 \tabularnewline
165 & 0.451641 & 0.903281 & 0.548359 \tabularnewline
166 & 0.427883 & 0.855767 & 0.572117 \tabularnewline
167 & 0.407052 & 0.814104 & 0.592948 \tabularnewline
168 & 0.391461 & 0.782921 & 0.608539 \tabularnewline
169 & 0.429906 & 0.859812 & 0.570094 \tabularnewline
170 & 0.414041 & 0.828083 & 0.585959 \tabularnewline
171 & 0.401578 & 0.803155 & 0.598422 \tabularnewline
172 & 0.366853 & 0.733707 & 0.633147 \tabularnewline
173 & 0.352849 & 0.705699 & 0.647151 \tabularnewline
174 & 0.328048 & 0.656096 & 0.671952 \tabularnewline
175 & 0.296724 & 0.593448 & 0.703276 \tabularnewline
176 & 0.269955 & 0.53991 & 0.730045 \tabularnewline
177 & 0.24044 & 0.48088 & 0.75956 \tabularnewline
178 & 0.217466 & 0.434932 & 0.782534 \tabularnewline
179 & 0.200147 & 0.400294 & 0.799853 \tabularnewline
180 & 0.178665 & 0.357329 & 0.821335 \tabularnewline
181 & 0.260502 & 0.521004 & 0.739498 \tabularnewline
182 & 0.24041 & 0.480819 & 0.75959 \tabularnewline
183 & 0.216658 & 0.433315 & 0.783342 \tabularnewline
184 & 0.199456 & 0.398912 & 0.800544 \tabularnewline
185 & 0.296592 & 0.593184 & 0.703408 \tabularnewline
186 & 0.299225 & 0.598449 & 0.700775 \tabularnewline
187 & 0.26805 & 0.536101 & 0.73195 \tabularnewline
188 & 0.307995 & 0.615991 & 0.692005 \tabularnewline
189 & 0.329649 & 0.659297 & 0.670351 \tabularnewline
190 & 0.297723 & 0.595447 & 0.702277 \tabularnewline
191 & 0.702218 & 0.595564 & 0.297782 \tabularnewline
192 & 0.673086 & 0.653828 & 0.326914 \tabularnewline
193 & 0.634971 & 0.730058 & 0.365029 \tabularnewline
194 & 0.626977 & 0.746047 & 0.373023 \tabularnewline
195 & 0.59193 & 0.81614 & 0.40807 \tabularnewline
196 & 0.567619 & 0.864761 & 0.432381 \tabularnewline
197 & 0.647294 & 0.705412 & 0.352706 \tabularnewline
198 & 0.716264 & 0.567471 & 0.283736 \tabularnewline
199 & 0.682593 & 0.634814 & 0.317407 \tabularnewline
200 & 0.664418 & 0.671163 & 0.335582 \tabularnewline
201 & 0.631954 & 0.736092 & 0.368046 \tabularnewline
202 & 0.591299 & 0.817402 & 0.408701 \tabularnewline
203 & 0.561031 & 0.877937 & 0.438969 \tabularnewline
204 & 0.614863 & 0.770275 & 0.385137 \tabularnewline
205 & 0.572402 & 0.855196 & 0.427598 \tabularnewline
206 & 0.530266 & 0.939469 & 0.469734 \tabularnewline
207 & 0.541792 & 0.916415 & 0.458208 \tabularnewline
208 & 0.635349 & 0.729302 & 0.364651 \tabularnewline
209 & 0.591583 & 0.816833 & 0.408417 \tabularnewline
210 & 0.62946 & 0.741081 & 0.37054 \tabularnewline
211 & 0.591971 & 0.816058 & 0.408029 \tabularnewline
212 & 0.558831 & 0.882337 & 0.441169 \tabularnewline
213 & 0.689479 & 0.621042 & 0.310521 \tabularnewline
214 & 0.685638 & 0.628723 & 0.314362 \tabularnewline
215 & 0.641508 & 0.716985 & 0.358492 \tabularnewline
216 & 0.59955 & 0.8009 & 0.40045 \tabularnewline
217 & 0.660253 & 0.679494 & 0.339747 \tabularnewline
218 & 0.681685 & 0.63663 & 0.318315 \tabularnewline
219 & 0.635444 & 0.729112 & 0.364556 \tabularnewline
220 & 0.680512 & 0.638976 & 0.319488 \tabularnewline
221 & 0.641878 & 0.716245 & 0.358122 \tabularnewline
222 & 0.667062 & 0.665877 & 0.332938 \tabularnewline
223 & 0.650443 & 0.699115 & 0.349557 \tabularnewline
224 & 0.599848 & 0.800305 & 0.400152 \tabularnewline
225 & 0.863325 & 0.273351 & 0.136675 \tabularnewline
226 & 0.838098 & 0.323803 & 0.161902 \tabularnewline
227 & 0.870001 & 0.259997 & 0.129999 \tabularnewline
228 & 0.865556 & 0.268888 & 0.134444 \tabularnewline
229 & 0.842035 & 0.31593 & 0.157965 \tabularnewline
230 & 0.806389 & 0.387221 & 0.193611 \tabularnewline
231 & 0.763552 & 0.472896 & 0.236448 \tabularnewline
232 & 0.736033 & 0.527935 & 0.263967 \tabularnewline
233 & 0.864213 & 0.271574 & 0.135787 \tabularnewline
234 & 0.871984 & 0.256031 & 0.128016 \tabularnewline
235 & 0.836005 & 0.32799 & 0.163995 \tabularnewline
236 & 0.795076 & 0.409847 & 0.204924 \tabularnewline
237 & 0.857874 & 0.284252 & 0.142126 \tabularnewline
238 & 0.896699 & 0.206602 & 0.103301 \tabularnewline
239 & 0.866231 & 0.267537 & 0.133769 \tabularnewline
240 & 0.821838 & 0.356324 & 0.178162 \tabularnewline
241 & 0.866576 & 0.266848 & 0.133424 \tabularnewline
242 & 0.910861 & 0.178278 & 0.089139 \tabularnewline
243 & 0.892165 & 0.215669 & 0.107835 \tabularnewline
244 & 0.862659 & 0.274681 & 0.137341 \tabularnewline
245 & 0.949398 & 0.101204 & 0.0506021 \tabularnewline
246 & 0.921377 & 0.157247 & 0.0786234 \tabularnewline
247 & 0.880751 & 0.238499 & 0.119249 \tabularnewline
248 & 0.933924 & 0.132152 & 0.0660758 \tabularnewline
249 & 0.889097 & 0.221806 & 0.110903 \tabularnewline
250 & 0.872646 & 0.254708 & 0.127354 \tabularnewline
251 & 0.799996 & 0.400008 & 0.200004 \tabularnewline
252 & 0.886907 & 0.226186 & 0.113093 \tabularnewline
253 & 0.813394 & 0.373213 & 0.186606 \tabularnewline
254 & 0.713507 & 0.572987 & 0.286493 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254530&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]10[/C][C]0.107883[/C][C]0.215766[/C][C]0.892117[/C][/ROW]
[ROW][C]11[/C][C]0.0389462[/C][C]0.0778923[/C][C]0.961054[/C][/ROW]
[ROW][C]12[/C][C]0.944474[/C][C]0.111053[/C][C]0.0555264[/C][/ROW]
[ROW][C]13[/C][C]0.913972[/C][C]0.172055[/C][C]0.0860277[/C][/ROW]
[ROW][C]14[/C][C]0.894813[/C][C]0.210374[/C][C]0.105187[/C][/ROW]
[ROW][C]15[/C][C]0.909106[/C][C]0.181787[/C][C]0.0908936[/C][/ROW]
[ROW][C]16[/C][C]0.942984[/C][C]0.114032[/C][C]0.0570161[/C][/ROW]
[ROW][C]17[/C][C]0.925093[/C][C]0.149814[/C][C]0.074907[/C][/ROW]
[ROW][C]18[/C][C]0.953166[/C][C]0.0936679[/C][C]0.0468339[/C][/ROW]
[ROW][C]19[/C][C]0.936987[/C][C]0.126027[/C][C]0.0630135[/C][/ROW]
[ROW][C]20[/C][C]0.96032[/C][C]0.0793605[/C][C]0.0396802[/C][/ROW]
[ROW][C]21[/C][C]0.956872[/C][C]0.0862557[/C][C]0.0431278[/C][/ROW]
[ROW][C]22[/C][C]0.939063[/C][C]0.121873[/C][C]0.0609365[/C][/ROW]
[ROW][C]23[/C][C]0.951717[/C][C]0.096566[/C][C]0.048283[/C][/ROW]
[ROW][C]24[/C][C]0.944839[/C][C]0.110322[/C][C]0.0551611[/C][/ROW]
[ROW][C]25[/C][C]0.956533[/C][C]0.0869347[/C][C]0.0434673[/C][/ROW]
[ROW][C]26[/C][C]0.956718[/C][C]0.0865648[/C][C]0.0432824[/C][/ROW]
[ROW][C]27[/C][C]0.945101[/C][C]0.109798[/C][C]0.054899[/C][/ROW]
[ROW][C]28[/C][C]0.926806[/C][C]0.146389[/C][C]0.0731944[/C][/ROW]
[ROW][C]29[/C][C]0.916665[/C][C]0.16667[/C][C]0.0833348[/C][/ROW]
[ROW][C]30[/C][C]0.891354[/C][C]0.217291[/C][C]0.108646[/C][/ROW]
[ROW][C]31[/C][C]0.864111[/C][C]0.271778[/C][C]0.135889[/C][/ROW]
[ROW][C]32[/C][C]0.863092[/C][C]0.273815[/C][C]0.136908[/C][/ROW]
[ROW][C]33[/C][C]0.833763[/C][C]0.332474[/C][C]0.166237[/C][/ROW]
[ROW][C]34[/C][C]0.856885[/C][C]0.28623[/C][C]0.143115[/C][/ROW]
[ROW][C]35[/C][C]0.824739[/C][C]0.350522[/C][C]0.175261[/C][/ROW]
[ROW][C]36[/C][C]0.787659[/C][C]0.424683[/C][C]0.212341[/C][/ROW]
[ROW][C]37[/C][C]0.757253[/C][C]0.485495[/C][C]0.242747[/C][/ROW]
[ROW][C]38[/C][C]0.713839[/C][C]0.572323[/C][C]0.286161[/C][/ROW]
[ROW][C]39[/C][C]0.667652[/C][C]0.664696[/C][C]0.332348[/C][/ROW]
[ROW][C]40[/C][C]0.620499[/C][C]0.759002[/C][C]0.379501[/C][/ROW]
[ROW][C]41[/C][C]0.569816[/C][C]0.860368[/C][C]0.430184[/C][/ROW]
[ROW][C]42[/C][C]0.525717[/C][C]0.948567[/C][C]0.474283[/C][/ROW]
[ROW][C]43[/C][C]0.745158[/C][C]0.509683[/C][C]0.254842[/C][/ROW]
[ROW][C]44[/C][C]0.78889[/C][C]0.42222[/C][C]0.21111[/C][/ROW]
[ROW][C]45[/C][C]0.755326[/C][C]0.489348[/C][C]0.244674[/C][/ROW]
[ROW][C]46[/C][C]0.715712[/C][C]0.568576[/C][C]0.284288[/C][/ROW]
[ROW][C]47[/C][C]0.69872[/C][C]0.602561[/C][C]0.30128[/C][/ROW]
[ROW][C]48[/C][C]0.662035[/C][C]0.67593[/C][C]0.337965[/C][/ROW]
[ROW][C]49[/C][C]0.629643[/C][C]0.740715[/C][C]0.370357[/C][/ROW]
[ROW][C]50[/C][C]0.594932[/C][C]0.810136[/C][C]0.405068[/C][/ROW]
[ROW][C]51[/C][C]0.550117[/C][C]0.899766[/C][C]0.449883[/C][/ROW]
[ROW][C]52[/C][C]0.505917[/C][C]0.988167[/C][C]0.494083[/C][/ROW]
[ROW][C]53[/C][C]0.460666[/C][C]0.921332[/C][C]0.539334[/C][/ROW]
[ROW][C]54[/C][C]0.427043[/C][C]0.854086[/C][C]0.572957[/C][/ROW]
[ROW][C]55[/C][C]0.389913[/C][C]0.779826[/C][C]0.610087[/C][/ROW]
[ROW][C]56[/C][C]0.387874[/C][C]0.775747[/C][C]0.612126[/C][/ROW]
[ROW][C]57[/C][C]0.348883[/C][C]0.697766[/C][C]0.651117[/C][/ROW]
[ROW][C]58[/C][C]0.321198[/C][C]0.642396[/C][C]0.678802[/C][/ROW]
[ROW][C]59[/C][C]0.29235[/C][C]0.584699[/C][C]0.70765[/C][/ROW]
[ROW][C]60[/C][C]0.262559[/C][C]0.525118[/C][C]0.737441[/C][/ROW]
[ROW][C]61[/C][C]0.243028[/C][C]0.486056[/C][C]0.756972[/C][/ROW]
[ROW][C]62[/C][C]0.230486[/C][C]0.460972[/C][C]0.769514[/C][/ROW]
[ROW][C]63[/C][C]0.247254[/C][C]0.494507[/C][C]0.752746[/C][/ROW]
[ROW][C]64[/C][C]0.31296[/C][C]0.625919[/C][C]0.68704[/C][/ROW]
[ROW][C]65[/C][C]0.393136[/C][C]0.786271[/C][C]0.606864[/C][/ROW]
[ROW][C]66[/C][C]0.40944[/C][C]0.81888[/C][C]0.59056[/C][/ROW]
[ROW][C]67[/C][C]0.370095[/C][C]0.74019[/C][C]0.629905[/C][/ROW]
[ROW][C]68[/C][C]0.337615[/C][C]0.67523[/C][C]0.662385[/C][/ROW]
[ROW][C]69[/C][C]0.32035[/C][C]0.640699[/C][C]0.67965[/C][/ROW]
[ROW][C]70[/C][C]0.285522[/C][C]0.571044[/C][C]0.714478[/C][/ROW]
[ROW][C]71[/C][C]0.253342[/C][C]0.506683[/C][C]0.746658[/C][/ROW]
[ROW][C]72[/C][C]0.287387[/C][C]0.574774[/C][C]0.712613[/C][/ROW]
[ROW][C]73[/C][C]0.295675[/C][C]0.59135[/C][C]0.704325[/C][/ROW]
[ROW][C]74[/C][C]0.271274[/C][C]0.542548[/C][C]0.728726[/C][/ROW]
[ROW][C]75[/C][C]0.284395[/C][C]0.56879[/C][C]0.715605[/C][/ROW]
[ROW][C]76[/C][C]0.325559[/C][C]0.651118[/C][C]0.674441[/C][/ROW]
[ROW][C]77[/C][C]0.293732[/C][C]0.587464[/C][C]0.706268[/C][/ROW]
[ROW][C]78[/C][C]0.260828[/C][C]0.521655[/C][C]0.739172[/C][/ROW]
[ROW][C]79[/C][C]0.248076[/C][C]0.496152[/C][C]0.751924[/C][/ROW]
[ROW][C]80[/C][C]0.373281[/C][C]0.746562[/C][C]0.626719[/C][/ROW]
[ROW][C]81[/C][C]0.358221[/C][C]0.716443[/C][C]0.641779[/C][/ROW]
[ROW][C]82[/C][C]0.326546[/C][C]0.653092[/C][C]0.673454[/C][/ROW]
[ROW][C]83[/C][C]0.293207[/C][C]0.586414[/C][C]0.706793[/C][/ROW]
[ROW][C]84[/C][C]0.261791[/C][C]0.523582[/C][C]0.738209[/C][/ROW]
[ROW][C]85[/C][C]0.245453[/C][C]0.490906[/C][C]0.754547[/C][/ROW]
[ROW][C]86[/C][C]0.227654[/C][C]0.455308[/C][C]0.772346[/C][/ROW]
[ROW][C]87[/C][C]0.201412[/C][C]0.402825[/C][C]0.798588[/C][/ROW]
[ROW][C]88[/C][C]0.234874[/C][C]0.469749[/C][C]0.765126[/C][/ROW]
[ROW][C]89[/C][C]0.233376[/C][C]0.466753[/C][C]0.766624[/C][/ROW]
[ROW][C]90[/C][C]0.209941[/C][C]0.419881[/C][C]0.790059[/C][/ROW]
[ROW][C]91[/C][C]0.261626[/C][C]0.523252[/C][C]0.738374[/C][/ROW]
[ROW][C]92[/C][C]0.244708[/C][C]0.489415[/C][C]0.755292[/C][/ROW]
[ROW][C]93[/C][C]0.268919[/C][C]0.537839[/C][C]0.731081[/C][/ROW]
[ROW][C]94[/C][C]0.274954[/C][C]0.549907[/C][C]0.725046[/C][/ROW]
[ROW][C]95[/C][C]0.260436[/C][C]0.520872[/C][C]0.739564[/C][/ROW]
[ROW][C]96[/C][C]0.231683[/C][C]0.463366[/C][C]0.768317[/C][/ROW]
[ROW][C]97[/C][C]0.214081[/C][C]0.428163[/C][C]0.785919[/C][/ROW]
[ROW][C]98[/C][C]0.200974[/C][C]0.401948[/C][C]0.799026[/C][/ROW]
[ROW][C]99[/C][C]0.180187[/C][C]0.360374[/C][C]0.819813[/C][/ROW]
[ROW][C]100[/C][C]0.15854[/C][C]0.31708[/C][C]0.84146[/C][/ROW]
[ROW][C]101[/C][C]0.14261[/C][C]0.28522[/C][C]0.85739[/C][/ROW]
[ROW][C]102[/C][C]0.146419[/C][C]0.292838[/C][C]0.853581[/C][/ROW]
[ROW][C]103[/C][C]0.12975[/C][C]0.259501[/C][C]0.87025[/C][/ROW]
[ROW][C]104[/C][C]0.128525[/C][C]0.257051[/C][C]0.871475[/C][/ROW]
[ROW][C]105[/C][C]0.113023[/C][C]0.226046[/C][C]0.886977[/C][/ROW]
[ROW][C]106[/C][C]0.0970515[/C][C]0.194103[/C][C]0.902949[/C][/ROW]
[ROW][C]107[/C][C]0.0824298[/C][C]0.16486[/C][C]0.91757[/C][/ROW]
[ROW][C]108[/C][C]0.097416[/C][C]0.194832[/C][C]0.902584[/C][/ROW]
[ROW][C]109[/C][C]0.11828[/C][C]0.23656[/C][C]0.88172[/C][/ROW]
[ROW][C]110[/C][C]0.138393[/C][C]0.276786[/C][C]0.861607[/C][/ROW]
[ROW][C]111[/C][C]0.125225[/C][C]0.250451[/C][C]0.874775[/C][/ROW]
[ROW][C]112[/C][C]0.160523[/C][C]0.321045[/C][C]0.839477[/C][/ROW]
[ROW][C]113[/C][C]0.427756[/C][C]0.855511[/C][C]0.572244[/C][/ROW]
[ROW][C]114[/C][C]0.399473[/C][C]0.798945[/C][C]0.600527[/C][/ROW]
[ROW][C]115[/C][C]0.400284[/C][C]0.800568[/C][C]0.599716[/C][/ROW]
[ROW][C]116[/C][C]0.465515[/C][C]0.93103[/C][C]0.534485[/C][/ROW]
[ROW][C]117[/C][C]0.435874[/C][C]0.871747[/C][C]0.564126[/C][/ROW]
[ROW][C]118[/C][C]0.408244[/C][C]0.816488[/C][C]0.591756[/C][/ROW]
[ROW][C]119[/C][C]0.513023[/C][C]0.973954[/C][C]0.486977[/C][/ROW]
[ROW][C]120[/C][C]0.550093[/C][C]0.899815[/C][C]0.449907[/C][/ROW]
[ROW][C]121[/C][C]0.525288[/C][C]0.949424[/C][C]0.474712[/C][/ROW]
[ROW][C]122[/C][C]0.588691[/C][C]0.822618[/C][C]0.411309[/C][/ROW]
[ROW][C]123[/C][C]0.555618[/C][C]0.888763[/C][C]0.444382[/C][/ROW]
[ROW][C]124[/C][C]0.520469[/C][C]0.959062[/C][C]0.479531[/C][/ROW]
[ROW][C]125[/C][C]0.499358[/C][C]0.998717[/C][C]0.500642[/C][/ROW]
[ROW][C]126[/C][C]0.528393[/C][C]0.943215[/C][C]0.471607[/C][/ROW]
[ROW][C]127[/C][C]0.497726[/C][C]0.995453[/C][C]0.502274[/C][/ROW]
[ROW][C]128[/C][C]0.473184[/C][C]0.946369[/C][C]0.526816[/C][/ROW]
[ROW][C]129[/C][C]0.439728[/C][C]0.879457[/C][C]0.560272[/C][/ROW]
[ROW][C]130[/C][C]0.40479[/C][C]0.809579[/C][C]0.59521[/C][/ROW]
[ROW][C]131[/C][C]0.383188[/C][C]0.766377[/C][C]0.616812[/C][/ROW]
[ROW][C]132[/C][C]0.352434[/C][C]0.704869[/C][C]0.647566[/C][/ROW]
[ROW][C]133[/C][C]0.324673[/C][C]0.649346[/C][C]0.675327[/C][/ROW]
[ROW][C]134[/C][C]0.295555[/C][C]0.59111[/C][C]0.704445[/C][/ROW]
[ROW][C]135[/C][C]0.322736[/C][C]0.645472[/C][C]0.677264[/C][/ROW]
[ROW][C]136[/C][C]0.302565[/C][C]0.60513[/C][C]0.697435[/C][/ROW]
[ROW][C]137[/C][C]0.290748[/C][C]0.581495[/C][C]0.709252[/C][/ROW]
[ROW][C]138[/C][C]0.307541[/C][C]0.615082[/C][C]0.692459[/C][/ROW]
[ROW][C]139[/C][C]0.298482[/C][C]0.596963[/C][C]0.701518[/C][/ROW]
[ROW][C]140[/C][C]0.271935[/C][C]0.543869[/C][C]0.728065[/C][/ROW]
[ROW][C]141[/C][C]0.362944[/C][C]0.725888[/C][C]0.637056[/C][/ROW]
[ROW][C]142[/C][C]0.387412[/C][C]0.774823[/C][C]0.612588[/C][/ROW]
[ROW][C]143[/C][C]0.411062[/C][C]0.822124[/C][C]0.588938[/C][/ROW]
[ROW][C]144[/C][C]0.391718[/C][C]0.783435[/C][C]0.608282[/C][/ROW]
[ROW][C]145[/C][C]0.456936[/C][C]0.913872[/C][C]0.543064[/C][/ROW]
[ROW][C]146[/C][C]0.429551[/C][C]0.859102[/C][C]0.570449[/C][/ROW]
[ROW][C]147[/C][C]0.435184[/C][C]0.870368[/C][C]0.564816[/C][/ROW]
[ROW][C]148[/C][C]0.405693[/C][C]0.811385[/C][C]0.594307[/C][/ROW]
[ROW][C]149[/C][C]0.40994[/C][C]0.81988[/C][C]0.59006[/C][/ROW]
[ROW][C]150[/C][C]0.430249[/C][C]0.860499[/C][C]0.569751[/C][/ROW]
[ROW][C]151[/C][C]0.427172[/C][C]0.854344[/C][C]0.572828[/C][/ROW]
[ROW][C]152[/C][C]0.400529[/C][C]0.801059[/C][C]0.599471[/C][/ROW]
[ROW][C]153[/C][C]0.369597[/C][C]0.739194[/C][C]0.630403[/C][/ROW]
[ROW][C]154[/C][C]0.346163[/C][C]0.692326[/C][C]0.653837[/C][/ROW]
[ROW][C]155[/C][C]0.36628[/C][C]0.732559[/C][C]0.63372[/C][/ROW]
[ROW][C]156[/C][C]0.42493[/C][C]0.849861[/C][C]0.57507[/C][/ROW]
[ROW][C]157[/C][C]0.39095[/C][C]0.781901[/C][C]0.60905[/C][/ROW]
[ROW][C]158[/C][C]0.366528[/C][C]0.733057[/C][C]0.633472[/C][/ROW]
[ROW][C]159[/C][C]0.371424[/C][C]0.742849[/C][C]0.628576[/C][/ROW]
[ROW][C]160[/C][C]0.447067[/C][C]0.894134[/C][C]0.552933[/C][/ROW]
[ROW][C]161[/C][C]0.411295[/C][C]0.82259[/C][C]0.588705[/C][/ROW]
[ROW][C]162[/C][C]0.396325[/C][C]0.79265[/C][C]0.603675[/C][/ROW]
[ROW][C]163[/C][C]0.425443[/C][C]0.850887[/C][C]0.574557[/C][/ROW]
[ROW][C]164[/C][C]0.476637[/C][C]0.953274[/C][C]0.523363[/C][/ROW]
[ROW][C]165[/C][C]0.451641[/C][C]0.903281[/C][C]0.548359[/C][/ROW]
[ROW][C]166[/C][C]0.427883[/C][C]0.855767[/C][C]0.572117[/C][/ROW]
[ROW][C]167[/C][C]0.407052[/C][C]0.814104[/C][C]0.592948[/C][/ROW]
[ROW][C]168[/C][C]0.391461[/C][C]0.782921[/C][C]0.608539[/C][/ROW]
[ROW][C]169[/C][C]0.429906[/C][C]0.859812[/C][C]0.570094[/C][/ROW]
[ROW][C]170[/C][C]0.414041[/C][C]0.828083[/C][C]0.585959[/C][/ROW]
[ROW][C]171[/C][C]0.401578[/C][C]0.803155[/C][C]0.598422[/C][/ROW]
[ROW][C]172[/C][C]0.366853[/C][C]0.733707[/C][C]0.633147[/C][/ROW]
[ROW][C]173[/C][C]0.352849[/C][C]0.705699[/C][C]0.647151[/C][/ROW]
[ROW][C]174[/C][C]0.328048[/C][C]0.656096[/C][C]0.671952[/C][/ROW]
[ROW][C]175[/C][C]0.296724[/C][C]0.593448[/C][C]0.703276[/C][/ROW]
[ROW][C]176[/C][C]0.269955[/C][C]0.53991[/C][C]0.730045[/C][/ROW]
[ROW][C]177[/C][C]0.24044[/C][C]0.48088[/C][C]0.75956[/C][/ROW]
[ROW][C]178[/C][C]0.217466[/C][C]0.434932[/C][C]0.782534[/C][/ROW]
[ROW][C]179[/C][C]0.200147[/C][C]0.400294[/C][C]0.799853[/C][/ROW]
[ROW][C]180[/C][C]0.178665[/C][C]0.357329[/C][C]0.821335[/C][/ROW]
[ROW][C]181[/C][C]0.260502[/C][C]0.521004[/C][C]0.739498[/C][/ROW]
[ROW][C]182[/C][C]0.24041[/C][C]0.480819[/C][C]0.75959[/C][/ROW]
[ROW][C]183[/C][C]0.216658[/C][C]0.433315[/C][C]0.783342[/C][/ROW]
[ROW][C]184[/C][C]0.199456[/C][C]0.398912[/C][C]0.800544[/C][/ROW]
[ROW][C]185[/C][C]0.296592[/C][C]0.593184[/C][C]0.703408[/C][/ROW]
[ROW][C]186[/C][C]0.299225[/C][C]0.598449[/C][C]0.700775[/C][/ROW]
[ROW][C]187[/C][C]0.26805[/C][C]0.536101[/C][C]0.73195[/C][/ROW]
[ROW][C]188[/C][C]0.307995[/C][C]0.615991[/C][C]0.692005[/C][/ROW]
[ROW][C]189[/C][C]0.329649[/C][C]0.659297[/C][C]0.670351[/C][/ROW]
[ROW][C]190[/C][C]0.297723[/C][C]0.595447[/C][C]0.702277[/C][/ROW]
[ROW][C]191[/C][C]0.702218[/C][C]0.595564[/C][C]0.297782[/C][/ROW]
[ROW][C]192[/C][C]0.673086[/C][C]0.653828[/C][C]0.326914[/C][/ROW]
[ROW][C]193[/C][C]0.634971[/C][C]0.730058[/C][C]0.365029[/C][/ROW]
[ROW][C]194[/C][C]0.626977[/C][C]0.746047[/C][C]0.373023[/C][/ROW]
[ROW][C]195[/C][C]0.59193[/C][C]0.81614[/C][C]0.40807[/C][/ROW]
[ROW][C]196[/C][C]0.567619[/C][C]0.864761[/C][C]0.432381[/C][/ROW]
[ROW][C]197[/C][C]0.647294[/C][C]0.705412[/C][C]0.352706[/C][/ROW]
[ROW][C]198[/C][C]0.716264[/C][C]0.567471[/C][C]0.283736[/C][/ROW]
[ROW][C]199[/C][C]0.682593[/C][C]0.634814[/C][C]0.317407[/C][/ROW]
[ROW][C]200[/C][C]0.664418[/C][C]0.671163[/C][C]0.335582[/C][/ROW]
[ROW][C]201[/C][C]0.631954[/C][C]0.736092[/C][C]0.368046[/C][/ROW]
[ROW][C]202[/C][C]0.591299[/C][C]0.817402[/C][C]0.408701[/C][/ROW]
[ROW][C]203[/C][C]0.561031[/C][C]0.877937[/C][C]0.438969[/C][/ROW]
[ROW][C]204[/C][C]0.614863[/C][C]0.770275[/C][C]0.385137[/C][/ROW]
[ROW][C]205[/C][C]0.572402[/C][C]0.855196[/C][C]0.427598[/C][/ROW]
[ROW][C]206[/C][C]0.530266[/C][C]0.939469[/C][C]0.469734[/C][/ROW]
[ROW][C]207[/C][C]0.541792[/C][C]0.916415[/C][C]0.458208[/C][/ROW]
[ROW][C]208[/C][C]0.635349[/C][C]0.729302[/C][C]0.364651[/C][/ROW]
[ROW][C]209[/C][C]0.591583[/C][C]0.816833[/C][C]0.408417[/C][/ROW]
[ROW][C]210[/C][C]0.62946[/C][C]0.741081[/C][C]0.37054[/C][/ROW]
[ROW][C]211[/C][C]0.591971[/C][C]0.816058[/C][C]0.408029[/C][/ROW]
[ROW][C]212[/C][C]0.558831[/C][C]0.882337[/C][C]0.441169[/C][/ROW]
[ROW][C]213[/C][C]0.689479[/C][C]0.621042[/C][C]0.310521[/C][/ROW]
[ROW][C]214[/C][C]0.685638[/C][C]0.628723[/C][C]0.314362[/C][/ROW]
[ROW][C]215[/C][C]0.641508[/C][C]0.716985[/C][C]0.358492[/C][/ROW]
[ROW][C]216[/C][C]0.59955[/C][C]0.8009[/C][C]0.40045[/C][/ROW]
[ROW][C]217[/C][C]0.660253[/C][C]0.679494[/C][C]0.339747[/C][/ROW]
[ROW][C]218[/C][C]0.681685[/C][C]0.63663[/C][C]0.318315[/C][/ROW]
[ROW][C]219[/C][C]0.635444[/C][C]0.729112[/C][C]0.364556[/C][/ROW]
[ROW][C]220[/C][C]0.680512[/C][C]0.638976[/C][C]0.319488[/C][/ROW]
[ROW][C]221[/C][C]0.641878[/C][C]0.716245[/C][C]0.358122[/C][/ROW]
[ROW][C]222[/C][C]0.667062[/C][C]0.665877[/C][C]0.332938[/C][/ROW]
[ROW][C]223[/C][C]0.650443[/C][C]0.699115[/C][C]0.349557[/C][/ROW]
[ROW][C]224[/C][C]0.599848[/C][C]0.800305[/C][C]0.400152[/C][/ROW]
[ROW][C]225[/C][C]0.863325[/C][C]0.273351[/C][C]0.136675[/C][/ROW]
[ROW][C]226[/C][C]0.838098[/C][C]0.323803[/C][C]0.161902[/C][/ROW]
[ROW][C]227[/C][C]0.870001[/C][C]0.259997[/C][C]0.129999[/C][/ROW]
[ROW][C]228[/C][C]0.865556[/C][C]0.268888[/C][C]0.134444[/C][/ROW]
[ROW][C]229[/C][C]0.842035[/C][C]0.31593[/C][C]0.157965[/C][/ROW]
[ROW][C]230[/C][C]0.806389[/C][C]0.387221[/C][C]0.193611[/C][/ROW]
[ROW][C]231[/C][C]0.763552[/C][C]0.472896[/C][C]0.236448[/C][/ROW]
[ROW][C]232[/C][C]0.736033[/C][C]0.527935[/C][C]0.263967[/C][/ROW]
[ROW][C]233[/C][C]0.864213[/C][C]0.271574[/C][C]0.135787[/C][/ROW]
[ROW][C]234[/C][C]0.871984[/C][C]0.256031[/C][C]0.128016[/C][/ROW]
[ROW][C]235[/C][C]0.836005[/C][C]0.32799[/C][C]0.163995[/C][/ROW]
[ROW][C]236[/C][C]0.795076[/C][C]0.409847[/C][C]0.204924[/C][/ROW]
[ROW][C]237[/C][C]0.857874[/C][C]0.284252[/C][C]0.142126[/C][/ROW]
[ROW][C]238[/C][C]0.896699[/C][C]0.206602[/C][C]0.103301[/C][/ROW]
[ROW][C]239[/C][C]0.866231[/C][C]0.267537[/C][C]0.133769[/C][/ROW]
[ROW][C]240[/C][C]0.821838[/C][C]0.356324[/C][C]0.178162[/C][/ROW]
[ROW][C]241[/C][C]0.866576[/C][C]0.266848[/C][C]0.133424[/C][/ROW]
[ROW][C]242[/C][C]0.910861[/C][C]0.178278[/C][C]0.089139[/C][/ROW]
[ROW][C]243[/C][C]0.892165[/C][C]0.215669[/C][C]0.107835[/C][/ROW]
[ROW][C]244[/C][C]0.862659[/C][C]0.274681[/C][C]0.137341[/C][/ROW]
[ROW][C]245[/C][C]0.949398[/C][C]0.101204[/C][C]0.0506021[/C][/ROW]
[ROW][C]246[/C][C]0.921377[/C][C]0.157247[/C][C]0.0786234[/C][/ROW]
[ROW][C]247[/C][C]0.880751[/C][C]0.238499[/C][C]0.119249[/C][/ROW]
[ROW][C]248[/C][C]0.933924[/C][C]0.132152[/C][C]0.0660758[/C][/ROW]
[ROW][C]249[/C][C]0.889097[/C][C]0.221806[/C][C]0.110903[/C][/ROW]
[ROW][C]250[/C][C]0.872646[/C][C]0.254708[/C][C]0.127354[/C][/ROW]
[ROW][C]251[/C][C]0.799996[/C][C]0.400008[/C][C]0.200004[/C][/ROW]
[ROW][C]252[/C][C]0.886907[/C][C]0.226186[/C][C]0.113093[/C][/ROW]
[ROW][C]253[/C][C]0.813394[/C][C]0.373213[/C][C]0.186606[/C][/ROW]
[ROW][C]254[/C][C]0.713507[/C][C]0.572987[/C][C]0.286493[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254530&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254530&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.1078830.2157660.892117
110.03894620.07789230.961054
120.9444740.1110530.0555264
130.9139720.1720550.0860277
140.8948130.2103740.105187
150.9091060.1817870.0908936
160.9429840.1140320.0570161
170.9250930.1498140.074907
180.9531660.09366790.0468339
190.9369870.1260270.0630135
200.960320.07936050.0396802
210.9568720.08625570.0431278
220.9390630.1218730.0609365
230.9517170.0965660.048283
240.9448390.1103220.0551611
250.9565330.08693470.0434673
260.9567180.08656480.0432824
270.9451010.1097980.054899
280.9268060.1463890.0731944
290.9166650.166670.0833348
300.8913540.2172910.108646
310.8641110.2717780.135889
320.8630920.2738150.136908
330.8337630.3324740.166237
340.8568850.286230.143115
350.8247390.3505220.175261
360.7876590.4246830.212341
370.7572530.4854950.242747
380.7138390.5723230.286161
390.6676520.6646960.332348
400.6204990.7590020.379501
410.5698160.8603680.430184
420.5257170.9485670.474283
430.7451580.5096830.254842
440.788890.422220.21111
450.7553260.4893480.244674
460.7157120.5685760.284288
470.698720.6025610.30128
480.6620350.675930.337965
490.6296430.7407150.370357
500.5949320.8101360.405068
510.5501170.8997660.449883
520.5059170.9881670.494083
530.4606660.9213320.539334
540.4270430.8540860.572957
550.3899130.7798260.610087
560.3878740.7757470.612126
570.3488830.6977660.651117
580.3211980.6423960.678802
590.292350.5846990.70765
600.2625590.5251180.737441
610.2430280.4860560.756972
620.2304860.4609720.769514
630.2472540.4945070.752746
640.312960.6259190.68704
650.3931360.7862710.606864
660.409440.818880.59056
670.3700950.740190.629905
680.3376150.675230.662385
690.320350.6406990.67965
700.2855220.5710440.714478
710.2533420.5066830.746658
720.2873870.5747740.712613
730.2956750.591350.704325
740.2712740.5425480.728726
750.2843950.568790.715605
760.3255590.6511180.674441
770.2937320.5874640.706268
780.2608280.5216550.739172
790.2480760.4961520.751924
800.3732810.7465620.626719
810.3582210.7164430.641779
820.3265460.6530920.673454
830.2932070.5864140.706793
840.2617910.5235820.738209
850.2454530.4909060.754547
860.2276540.4553080.772346
870.2014120.4028250.798588
880.2348740.4697490.765126
890.2333760.4667530.766624
900.2099410.4198810.790059
910.2616260.5232520.738374
920.2447080.4894150.755292
930.2689190.5378390.731081
940.2749540.5499070.725046
950.2604360.5208720.739564
960.2316830.4633660.768317
970.2140810.4281630.785919
980.2009740.4019480.799026
990.1801870.3603740.819813
1000.158540.317080.84146
1010.142610.285220.85739
1020.1464190.2928380.853581
1030.129750.2595010.87025
1040.1285250.2570510.871475
1050.1130230.2260460.886977
1060.09705150.1941030.902949
1070.08242980.164860.91757
1080.0974160.1948320.902584
1090.118280.236560.88172
1100.1383930.2767860.861607
1110.1252250.2504510.874775
1120.1605230.3210450.839477
1130.4277560.8555110.572244
1140.3994730.7989450.600527
1150.4002840.8005680.599716
1160.4655150.931030.534485
1170.4358740.8717470.564126
1180.4082440.8164880.591756
1190.5130230.9739540.486977
1200.5500930.8998150.449907
1210.5252880.9494240.474712
1220.5886910.8226180.411309
1230.5556180.8887630.444382
1240.5204690.9590620.479531
1250.4993580.9987170.500642
1260.5283930.9432150.471607
1270.4977260.9954530.502274
1280.4731840.9463690.526816
1290.4397280.8794570.560272
1300.404790.8095790.59521
1310.3831880.7663770.616812
1320.3524340.7048690.647566
1330.3246730.6493460.675327
1340.2955550.591110.704445
1350.3227360.6454720.677264
1360.3025650.605130.697435
1370.2907480.5814950.709252
1380.3075410.6150820.692459
1390.2984820.5969630.701518
1400.2719350.5438690.728065
1410.3629440.7258880.637056
1420.3874120.7748230.612588
1430.4110620.8221240.588938
1440.3917180.7834350.608282
1450.4569360.9138720.543064
1460.4295510.8591020.570449
1470.4351840.8703680.564816
1480.4056930.8113850.594307
1490.409940.819880.59006
1500.4302490.8604990.569751
1510.4271720.8543440.572828
1520.4005290.8010590.599471
1530.3695970.7391940.630403
1540.3461630.6923260.653837
1550.366280.7325590.63372
1560.424930.8498610.57507
1570.390950.7819010.60905
1580.3665280.7330570.633472
1590.3714240.7428490.628576
1600.4470670.8941340.552933
1610.4112950.822590.588705
1620.3963250.792650.603675
1630.4254430.8508870.574557
1640.4766370.9532740.523363
1650.4516410.9032810.548359
1660.4278830.8557670.572117
1670.4070520.8141040.592948
1680.3914610.7829210.608539
1690.4299060.8598120.570094
1700.4140410.8280830.585959
1710.4015780.8031550.598422
1720.3668530.7337070.633147
1730.3528490.7056990.647151
1740.3280480.6560960.671952
1750.2967240.5934480.703276
1760.2699550.539910.730045
1770.240440.480880.75956
1780.2174660.4349320.782534
1790.2001470.4002940.799853
1800.1786650.3573290.821335
1810.2605020.5210040.739498
1820.240410.4808190.75959
1830.2166580.4333150.783342
1840.1994560.3989120.800544
1850.2965920.5931840.703408
1860.2992250.5984490.700775
1870.268050.5361010.73195
1880.3079950.6159910.692005
1890.3296490.6592970.670351
1900.2977230.5954470.702277
1910.7022180.5955640.297782
1920.6730860.6538280.326914
1930.6349710.7300580.365029
1940.6269770.7460470.373023
1950.591930.816140.40807
1960.5676190.8647610.432381
1970.6472940.7054120.352706
1980.7162640.5674710.283736
1990.6825930.6348140.317407
2000.6644180.6711630.335582
2010.6319540.7360920.368046
2020.5912990.8174020.408701
2030.5610310.8779370.438969
2040.6148630.7702750.385137
2050.5724020.8551960.427598
2060.5302660.9394690.469734
2070.5417920.9164150.458208
2080.6353490.7293020.364651
2090.5915830.8168330.408417
2100.629460.7410810.37054
2110.5919710.8160580.408029
2120.5588310.8823370.441169
2130.6894790.6210420.310521
2140.6856380.6287230.314362
2150.6415080.7169850.358492
2160.599550.80090.40045
2170.6602530.6794940.339747
2180.6816850.636630.318315
2190.6354440.7291120.364556
2200.6805120.6389760.319488
2210.6418780.7162450.358122
2220.6670620.6658770.332938
2230.6504430.6991150.349557
2240.5998480.8003050.400152
2250.8633250.2733510.136675
2260.8380980.3238030.161902
2270.8700010.2599970.129999
2280.8655560.2688880.134444
2290.8420350.315930.157965
2300.8063890.3872210.193611
2310.7635520.4728960.236448
2320.7360330.5279350.263967
2330.8642130.2715740.135787
2340.8719840.2560310.128016
2350.8360050.327990.163995
2360.7950760.4098470.204924
2370.8578740.2842520.142126
2380.8966990.2066020.103301
2390.8662310.2675370.133769
2400.8218380.3563240.178162
2410.8665760.2668480.133424
2420.9108610.1782780.089139
2430.8921650.2156690.107835
2440.8626590.2746810.137341
2450.9493980.1012040.0506021
2460.9213770.1572470.0786234
2470.8807510.2384990.119249
2480.9339240.1321520.0660758
2490.8890970.2218060.110903
2500.8726460.2547080.127354
2510.7999960.4000080.200004
2520.8869070.2261860.113093
2530.8133940.3732130.186606
2540.7135070.5729870.286493






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level70.0285714OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 0 & 0 & OK \tabularnewline
10% type I error level & 7 & 0.0285714 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254530&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]7[/C][C]0.0285714[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254530&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254530&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level70.0285714OK


Figures (Output of Computation)

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

Parameters (Session):
par1 = 7 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 7 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}