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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 09 Nov 2014 20:26:54 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/09/t1415564869rpez0rljv405g9h.htm/, Retrieved Tue, 28 May 2024 22:49:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=253224, Retrieved Tue, 28 May 2024 22:49:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact88

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-11-09 20:26:54] [e63466588bf3c49b37383cc70d2c7b07] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'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 & 8 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253224&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253224&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253224&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Sport1[t] = + 55.4476 + 0.188407Connected[t] + 0.0687173Separate[t] + 0.207058Learning[t] + 0.226774Software[t] + 0.622413Happiness[t] -0.719066Depression[t] + 0.0171498t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Sport1[t] =  +  55.4476 +  0.188407Connected[t] +  0.0687173Separate[t] +  0.207058Learning[t] +  0.226774Software[t] +  0.622413Happiness[t] -0.719066Depression[t] +  0.0171498t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253224&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Sport1[t] =  +  55.4476 +  0.188407Connected[t] +  0.0687173Separate[t] +  0.207058Learning[t] +  0.226774Software[t] +  0.622413Happiness[t] -0.719066Depression[t] +  0.0171498t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253224&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253224&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] = + 55.4476 + 0.188407Connected[t] + 0.0687173Separate[t] + 0.207058Learning[t] + 0.226774Software[t] + 0.622413Happiness[t] -0.719066Depression[t] + 0.0171498t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)55.44769.783055.6683.89025e-081.94512e-08
Connected0.1884070.1810621.0410.2990590.14953
Separate0.06871730.1850510.37130.710690.355345
Learning0.2070580.3286110.63010.5291910.264595
Software0.2267740.3368240.67330.5013820.250691
Happiness0.6224130.302572.0570.04069090.0203455
Depression-0.7190660.215328-3.3390.0009646020.000482301
t0.01714980.008922731.9220.05571110.0278556

\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) & 55.4476 & 9.78305 & 5.668 & 3.89025e-08 & 1.94512e-08 \tabularnewline
Connected & 0.188407 & 0.181062 & 1.041 & 0.299059 & 0.14953 \tabularnewline
Separate & 0.0687173 & 0.185051 & 0.3713 & 0.71069 & 0.355345 \tabularnewline
Learning & 0.207058 & 0.328611 & 0.6301 & 0.529191 & 0.264595 \tabularnewline
Software & 0.226774 & 0.336824 & 0.6733 & 0.501382 & 0.250691 \tabularnewline
Happiness & 0.622413 & 0.30257 & 2.057 & 0.0406909 & 0.0203455 \tabularnewline
Depression & -0.719066 & 0.215328 & -3.339 & 0.000964602 & 0.000482301 \tabularnewline
t & 0.0171498 & 0.00892273 & 1.922 & 0.0557111 & 0.0278556 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253224&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]55.4476[/C][C]9.78305[/C][C]5.668[/C][C]3.89025e-08[/C][C]1.94512e-08[/C][/ROW]
[ROW][C]Connected[/C][C]0.188407[/C][C]0.181062[/C][C]1.041[/C][C]0.299059[/C][C]0.14953[/C][/ROW]
[ROW][C]Separate[/C][C]0.0687173[/C][C]0.185051[/C][C]0.3713[/C][C]0.71069[/C][C]0.355345[/C][/ROW]
[ROW][C]Learning[/C][C]0.207058[/C][C]0.328611[/C][C]0.6301[/C][C]0.529191[/C][C]0.264595[/C][/ROW]
[ROW][C]Software[/C][C]0.226774[/C][C]0.336824[/C][C]0.6733[/C][C]0.501382[/C][C]0.250691[/C][/ROW]
[ROW][C]Happiness[/C][C]0.622413[/C][C]0.30257[/C][C]2.057[/C][C]0.0406909[/C][C]0.0203455[/C][/ROW]
[ROW][C]Depression[/C][C]-0.719066[/C][C]0.215328[/C][C]-3.339[/C][C]0.000964602[/C][C]0.000482301[/C][/ROW]
[ROW][C]t[/C][C]0.0171498[/C][C]0.00892273[/C][C]1.922[/C][C]0.0557111[/C][C]0.0278556[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253224&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253224&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)55.44769.783055.6683.89025e-081.94512e-08
Connected0.1884070.1810621.0410.2990590.14953
Separate0.06871730.1850510.37130.710690.355345
Learning0.2070580.3286110.63010.5291910.264595
Software0.2267740.3368240.67330.5013820.250691
Happiness0.6224130.302572.0570.04069090.0203455
Depression-0.7190660.215328-3.3390.0009646020.000482301
t0.01714980.008922731.9220.05571110.0278556






Multiple Linear Regression - Regression Statistics
Multiple R0.377627
R-squared0.142602
Adjusted R-squared0.119157
F-TEST (value)6.08253
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value1.39614e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation9.7566
Sum Squared Residuals24369

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.377627 \tabularnewline
R-squared & 0.142602 \tabularnewline
Adjusted R-squared & 0.119157 \tabularnewline
F-TEST (value) & 6.08253 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 256 \tabularnewline
p-value & 1.39614e-06 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 9.7566 \tabularnewline
Sum Squared Residuals & 24369 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253224&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.377627[/C][/ROW]
[ROW][C]R-squared[/C][C]0.142602[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.119157[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]6.08253[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]256[/C][/ROW]
[ROW][C]p-value[/C][C]1.39614e-06[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]9.7566[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]24369[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253224&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253224&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 R0.377627
R-squared0.142602
Adjusted R-squared0.119157
F-TEST (value)6.08253
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value1.39614e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation9.7566
Sum Squared Residuals24369






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
15371.2987-18.2987
28374.12998.87011
36667.6717-1.67172
46766.93120.0688129
57665.186810.8132
67871.67176.3283
75364.5955-11.5955
88071.54928.45076
97472.55541.44464
107670.33665.66339
117973.8975.103
125476.88-22.88
136766.70750.292508
145471.346-17.346
158775.399211.6008
165868.4927-10.4927
177568.74126.25876
188875.060812.9392
196473.4773-9.47727
205770.6636-13.6636
216674.2842-8.28421
226866.60961.3904
235472.7683-18.7683
245668.7197-12.7197
258674.335811.6642
268071.41538.58468
277672.7283.27203
286968.89630.103718
297869.73368.26645
306767.3009-0.30086
318073.26436.73571
325464.8866-10.8866
337173.6718-2.67177
348472.439811.5602
357469.50124.49876
367172.2258-1.22579
376359.00813.99185
387171.4771-0.477137
397672.68153.31847
406971.4769-2.47691
417473.7660.233957
427570.35324.6468
435477.2923-23.2923
445267.6327-15.6327
456971.8959-2.89593
466868.1103-0.110285
476574.8046-9.80458
487571.85153.14852
497471.28432.71566
507571.46533.53473
517274.2183-2.21825
526768.2434-1.24336
536363.7626-0.762592
546269.0538-7.05383
556367.1755-4.17546
567668.95347.04663
577472.75441.24562
586773.1413-6.14132
597371.7831.21698
607067.67092.32913
615358.7402-5.74015
627771.50365.49645
638070.04459.95548
645268.8311-16.8311
655471.121-17.121
668070.49879.50126
676667.3087-1.30871
687369.18313.81689
696371.9218-8.92184
706971.0884-2.08838
716769.5492-2.54924
725469.7002-15.7002
738172.67568.32442
746975.741-6.74099
758471.210912.7891
768065.52814.472
777073.7759-3.7759
786966.99612.00393
797769.60957.39053
805473.3-19.3
817972.98876.01131
827174.8895-3.88951
837373.2668-0.266756
847271.56140.438597
857770.19966.80039
867571.69013.30994
876971.6127-2.61268
885467.9592-13.9592
897059.823610.1764
907371.06441.93563
915470.2168-16.2168
927772.45964.54039
938268.750613.2494
948069.101110.8989
958074.52815.4719
966968.69510.304947
977871.99366.00642
988175.14135.85874
997672.96043.03961
1007676.674-0.674012
1017368.32734.67275
1028575.39479.60532
1036669.7044-3.70436
1047969.76729.23281
1056864.33613.66392
1067675.12020.879775
1077171.5527-0.552661
1085467.7331-13.7331
1094661.3432-15.3432
1108570.626214.3738
1117468.00795.99215
1128872.41115.589
1133868.7963-30.7963
1147674.03721.96278
1158676.03299.96709
1165470.8969-16.8969
1176770.6876-3.68761
1186973.5223-4.52229
1199071.083718.9163
1205468.1348-14.1348
1217670.12665.87342
1228974.218814.7812
1237677.2108-1.21079
1247373.9675-0.967484
1257972.59586.40419
1269077.357412.6426
1277478.0004-4.00039
1288175.3975.60299
1297271.48940.510593
1307171.7361-0.736102
1316660.95415.04591
1327775.06291.93713
1336568.4065-3.40647
1347473.65550.344488
1358571.503513.4965
1365459.6079-5.60791
1376370.8553-7.85533
1385465.7585-11.7585
1396472.4874-8.48743
1406969.8755-0.875498
1415473.5038-19.5038
1428471.116212.8838
1438672.963913.0361
1447771.85325.14685
1458973.534515.4655
1467673.84082.1592
1476070.1368-10.1368
1487571.73853.2615
1497363.46839.53168
1508572.847312.1527
1517970.4148.58595
1527175.9124-4.91239
1537270.85951.1405
1546964.2374.76299
1557865.486512.5135
1565471.3316-17.3316
1576969.411-0.410961
1588175.91155.0885
1598474.20649.79355
1608465.656518.3435
1616968.18070.819342
1626659.02566.97443
1638168.816112.1839
1648269.959412.0406
1657266.01775.9823
1665459.0706-5.07057
1677871.70986.29016
1687467.34636.65374
1698266.872715.1273
1707364.68548.31464
1715563.5653-8.56532
1727275.0866-3.08661
1737870.26977.73031
1745964.9316-5.93161
1757272.9723-0.972305
1767874.12033.87972
1776866.11741.88259
1786965.26543.73456
1796774.4228-7.42279
1807469.54194.45813
1815474.6465-20.6465
1826772.4827-5.48271
1837075.6627-5.66266
1848075.31194.68812
1858971.11617.884
1867667.60378.39634
1877472.4351.56497
1888772.929414.0706
1895467.7779-13.7779
1906162.3666-1.36659
1913870.3449-32.3449
1927576.2059-1.20588
1936968.76950.230548
1946269.0604-7.06039
1957271.24860.751425
1967073.0586-3.05862
1977967.767611.2324
1988771.565315.4347
1996263.6024-1.60236
2007770.75286.24715
2016966.02032.97973
2026971.3691-2.36913
2037574.4550.544996
2045470.7814-16.7814
2057273.8637-1.86368
2067473.44890.551139
2078574.026810.9732
2085273.2897-21.2897
2097070.6521-0.652074
2108474.4269.57399
2116466.3233-2.32332
2128477.08656.91351
2138767.313319.6867
2147968.765210.2348
2156768.7908-1.79081
2166571.3002-6.3002
2178576.47758.52254
2188374.12218.87792
2196162.057-1.05698
2208273.77968.22037
2217671.73044.26956
2225875.3845-17.3845
2237267.51564.48442
2247274.719-2.71901
2253863.42-25.42
2267873.61144.38862
2275476.4629-22.4629
2286371.6915-8.69154
2296660.80785.19218
2307070.2274-0.227366
2317172.014-1.01397
2326766.690.309956
2335875.3471-17.3471
2347272.2222-0.222154
2357276.5291-4.52912
2367069.73290.267142
2377665.978410.0216
2385072.3238-22.3238
2397271.48910.510915
2407270.47191.5281
2418871.443916.5561
2425364.8935-11.8935
2435865.5293-7.52931
2446668.5104-2.51039
2458273.39358.6065
2466964.29954.70051
2476870.3629-2.36291
2484464.9692-20.9692
2495660.8824-4.88242
2505365.5555-12.5555
2517071.0636-1.06355
2527867.71110.289
2537172.9325-1.93254
2547272.3175-0.31746
2556869.0568-1.05682
2566770.5878-3.58777
2577565.52749.47255
2586265.2834-3.28337
2596772.9333-5.93334
2608370.542512.4575
2616472.7576-8.7576
2626874.6643-6.66429
2636262.3706-0.370612
2647272.6627-0.662695

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 53 & 71.2987 & -18.2987 \tabularnewline
2 & 83 & 74.1299 & 8.87011 \tabularnewline
3 & 66 & 67.6717 & -1.67172 \tabularnewline
4 & 67 & 66.9312 & 0.0688129 \tabularnewline
5 & 76 & 65.1868 & 10.8132 \tabularnewline
6 & 78 & 71.6717 & 6.3283 \tabularnewline
7 & 53 & 64.5955 & -11.5955 \tabularnewline
8 & 80 & 71.5492 & 8.45076 \tabularnewline
9 & 74 & 72.5554 & 1.44464 \tabularnewline
10 & 76 & 70.3366 & 5.66339 \tabularnewline
11 & 79 & 73.897 & 5.103 \tabularnewline
12 & 54 & 76.88 & -22.88 \tabularnewline
13 & 67 & 66.7075 & 0.292508 \tabularnewline
14 & 54 & 71.346 & -17.346 \tabularnewline
15 & 87 & 75.3992 & 11.6008 \tabularnewline
16 & 58 & 68.4927 & -10.4927 \tabularnewline
17 & 75 & 68.7412 & 6.25876 \tabularnewline
18 & 88 & 75.0608 & 12.9392 \tabularnewline
19 & 64 & 73.4773 & -9.47727 \tabularnewline
20 & 57 & 70.6636 & -13.6636 \tabularnewline
21 & 66 & 74.2842 & -8.28421 \tabularnewline
22 & 68 & 66.6096 & 1.3904 \tabularnewline
23 & 54 & 72.7683 & -18.7683 \tabularnewline
24 & 56 & 68.7197 & -12.7197 \tabularnewline
25 & 86 & 74.3358 & 11.6642 \tabularnewline
26 & 80 & 71.4153 & 8.58468 \tabularnewline
27 & 76 & 72.728 & 3.27203 \tabularnewline
28 & 69 & 68.8963 & 0.103718 \tabularnewline
29 & 78 & 69.7336 & 8.26645 \tabularnewline
30 & 67 & 67.3009 & -0.30086 \tabularnewline
31 & 80 & 73.2643 & 6.73571 \tabularnewline
32 & 54 & 64.8866 & -10.8866 \tabularnewline
33 & 71 & 73.6718 & -2.67177 \tabularnewline
34 & 84 & 72.4398 & 11.5602 \tabularnewline
35 & 74 & 69.5012 & 4.49876 \tabularnewline
36 & 71 & 72.2258 & -1.22579 \tabularnewline
37 & 63 & 59.0081 & 3.99185 \tabularnewline
38 & 71 & 71.4771 & -0.477137 \tabularnewline
39 & 76 & 72.6815 & 3.31847 \tabularnewline
40 & 69 & 71.4769 & -2.47691 \tabularnewline
41 & 74 & 73.766 & 0.233957 \tabularnewline
42 & 75 & 70.3532 & 4.6468 \tabularnewline
43 & 54 & 77.2923 & -23.2923 \tabularnewline
44 & 52 & 67.6327 & -15.6327 \tabularnewline
45 & 69 & 71.8959 & -2.89593 \tabularnewline
46 & 68 & 68.1103 & -0.110285 \tabularnewline
47 & 65 & 74.8046 & -9.80458 \tabularnewline
48 & 75 & 71.8515 & 3.14852 \tabularnewline
49 & 74 & 71.2843 & 2.71566 \tabularnewline
50 & 75 & 71.4653 & 3.53473 \tabularnewline
51 & 72 & 74.2183 & -2.21825 \tabularnewline
52 & 67 & 68.2434 & -1.24336 \tabularnewline
53 & 63 & 63.7626 & -0.762592 \tabularnewline
54 & 62 & 69.0538 & -7.05383 \tabularnewline
55 & 63 & 67.1755 & -4.17546 \tabularnewline
56 & 76 & 68.9534 & 7.04663 \tabularnewline
57 & 74 & 72.7544 & 1.24562 \tabularnewline
58 & 67 & 73.1413 & -6.14132 \tabularnewline
59 & 73 & 71.783 & 1.21698 \tabularnewline
60 & 70 & 67.6709 & 2.32913 \tabularnewline
61 & 53 & 58.7402 & -5.74015 \tabularnewline
62 & 77 & 71.5036 & 5.49645 \tabularnewline
63 & 80 & 70.0445 & 9.95548 \tabularnewline
64 & 52 & 68.8311 & -16.8311 \tabularnewline
65 & 54 & 71.121 & -17.121 \tabularnewline
66 & 80 & 70.4987 & 9.50126 \tabularnewline
67 & 66 & 67.3087 & -1.30871 \tabularnewline
68 & 73 & 69.1831 & 3.81689 \tabularnewline
69 & 63 & 71.9218 & -8.92184 \tabularnewline
70 & 69 & 71.0884 & -2.08838 \tabularnewline
71 & 67 & 69.5492 & -2.54924 \tabularnewline
72 & 54 & 69.7002 & -15.7002 \tabularnewline
73 & 81 & 72.6756 & 8.32442 \tabularnewline
74 & 69 & 75.741 & -6.74099 \tabularnewline
75 & 84 & 71.2109 & 12.7891 \tabularnewline
76 & 80 & 65.528 & 14.472 \tabularnewline
77 & 70 & 73.7759 & -3.7759 \tabularnewline
78 & 69 & 66.9961 & 2.00393 \tabularnewline
79 & 77 & 69.6095 & 7.39053 \tabularnewline
80 & 54 & 73.3 & -19.3 \tabularnewline
81 & 79 & 72.9887 & 6.01131 \tabularnewline
82 & 71 & 74.8895 & -3.88951 \tabularnewline
83 & 73 & 73.2668 & -0.266756 \tabularnewline
84 & 72 & 71.5614 & 0.438597 \tabularnewline
85 & 77 & 70.1996 & 6.80039 \tabularnewline
86 & 75 & 71.6901 & 3.30994 \tabularnewline
87 & 69 & 71.6127 & -2.61268 \tabularnewline
88 & 54 & 67.9592 & -13.9592 \tabularnewline
89 & 70 & 59.8236 & 10.1764 \tabularnewline
90 & 73 & 71.0644 & 1.93563 \tabularnewline
91 & 54 & 70.2168 & -16.2168 \tabularnewline
92 & 77 & 72.4596 & 4.54039 \tabularnewline
93 & 82 & 68.7506 & 13.2494 \tabularnewline
94 & 80 & 69.1011 & 10.8989 \tabularnewline
95 & 80 & 74.5281 & 5.4719 \tabularnewline
96 & 69 & 68.6951 & 0.304947 \tabularnewline
97 & 78 & 71.9936 & 6.00642 \tabularnewline
98 & 81 & 75.1413 & 5.85874 \tabularnewline
99 & 76 & 72.9604 & 3.03961 \tabularnewline
100 & 76 & 76.674 & -0.674012 \tabularnewline
101 & 73 & 68.3273 & 4.67275 \tabularnewline
102 & 85 & 75.3947 & 9.60532 \tabularnewline
103 & 66 & 69.7044 & -3.70436 \tabularnewline
104 & 79 & 69.7672 & 9.23281 \tabularnewline
105 & 68 & 64.3361 & 3.66392 \tabularnewline
106 & 76 & 75.1202 & 0.879775 \tabularnewline
107 & 71 & 71.5527 & -0.552661 \tabularnewline
108 & 54 & 67.7331 & -13.7331 \tabularnewline
109 & 46 & 61.3432 & -15.3432 \tabularnewline
110 & 85 & 70.6262 & 14.3738 \tabularnewline
111 & 74 & 68.0079 & 5.99215 \tabularnewline
112 & 88 & 72.411 & 15.589 \tabularnewline
113 & 38 & 68.7963 & -30.7963 \tabularnewline
114 & 76 & 74.0372 & 1.96278 \tabularnewline
115 & 86 & 76.0329 & 9.96709 \tabularnewline
116 & 54 & 70.8969 & -16.8969 \tabularnewline
117 & 67 & 70.6876 & -3.68761 \tabularnewline
118 & 69 & 73.5223 & -4.52229 \tabularnewline
119 & 90 & 71.0837 & 18.9163 \tabularnewline
120 & 54 & 68.1348 & -14.1348 \tabularnewline
121 & 76 & 70.1266 & 5.87342 \tabularnewline
122 & 89 & 74.2188 & 14.7812 \tabularnewline
123 & 76 & 77.2108 & -1.21079 \tabularnewline
124 & 73 & 73.9675 & -0.967484 \tabularnewline
125 & 79 & 72.5958 & 6.40419 \tabularnewline
126 & 90 & 77.3574 & 12.6426 \tabularnewline
127 & 74 & 78.0004 & -4.00039 \tabularnewline
128 & 81 & 75.397 & 5.60299 \tabularnewline
129 & 72 & 71.4894 & 0.510593 \tabularnewline
130 & 71 & 71.7361 & -0.736102 \tabularnewline
131 & 66 & 60.9541 & 5.04591 \tabularnewline
132 & 77 & 75.0629 & 1.93713 \tabularnewline
133 & 65 & 68.4065 & -3.40647 \tabularnewline
134 & 74 & 73.6555 & 0.344488 \tabularnewline
135 & 85 & 71.5035 & 13.4965 \tabularnewline
136 & 54 & 59.6079 & -5.60791 \tabularnewline
137 & 63 & 70.8553 & -7.85533 \tabularnewline
138 & 54 & 65.7585 & -11.7585 \tabularnewline
139 & 64 & 72.4874 & -8.48743 \tabularnewline
140 & 69 & 69.8755 & -0.875498 \tabularnewline
141 & 54 & 73.5038 & -19.5038 \tabularnewline
142 & 84 & 71.1162 & 12.8838 \tabularnewline
143 & 86 & 72.9639 & 13.0361 \tabularnewline
144 & 77 & 71.8532 & 5.14685 \tabularnewline
145 & 89 & 73.5345 & 15.4655 \tabularnewline
146 & 76 & 73.8408 & 2.1592 \tabularnewline
147 & 60 & 70.1368 & -10.1368 \tabularnewline
148 & 75 & 71.7385 & 3.2615 \tabularnewline
149 & 73 & 63.4683 & 9.53168 \tabularnewline
150 & 85 & 72.8473 & 12.1527 \tabularnewline
151 & 79 & 70.414 & 8.58595 \tabularnewline
152 & 71 & 75.9124 & -4.91239 \tabularnewline
153 & 72 & 70.8595 & 1.1405 \tabularnewline
154 & 69 & 64.237 & 4.76299 \tabularnewline
155 & 78 & 65.4865 & 12.5135 \tabularnewline
156 & 54 & 71.3316 & -17.3316 \tabularnewline
157 & 69 & 69.411 & -0.410961 \tabularnewline
158 & 81 & 75.9115 & 5.0885 \tabularnewline
159 & 84 & 74.2064 & 9.79355 \tabularnewline
160 & 84 & 65.6565 & 18.3435 \tabularnewline
161 & 69 & 68.1807 & 0.819342 \tabularnewline
162 & 66 & 59.0256 & 6.97443 \tabularnewline
163 & 81 & 68.8161 & 12.1839 \tabularnewline
164 & 82 & 69.9594 & 12.0406 \tabularnewline
165 & 72 & 66.0177 & 5.9823 \tabularnewline
166 & 54 & 59.0706 & -5.07057 \tabularnewline
167 & 78 & 71.7098 & 6.29016 \tabularnewline
168 & 74 & 67.3463 & 6.65374 \tabularnewline
169 & 82 & 66.8727 & 15.1273 \tabularnewline
170 & 73 & 64.6854 & 8.31464 \tabularnewline
171 & 55 & 63.5653 & -8.56532 \tabularnewline
172 & 72 & 75.0866 & -3.08661 \tabularnewline
173 & 78 & 70.2697 & 7.73031 \tabularnewline
174 & 59 & 64.9316 & -5.93161 \tabularnewline
175 & 72 & 72.9723 & -0.972305 \tabularnewline
176 & 78 & 74.1203 & 3.87972 \tabularnewline
177 & 68 & 66.1174 & 1.88259 \tabularnewline
178 & 69 & 65.2654 & 3.73456 \tabularnewline
179 & 67 & 74.4228 & -7.42279 \tabularnewline
180 & 74 & 69.5419 & 4.45813 \tabularnewline
181 & 54 & 74.6465 & -20.6465 \tabularnewline
182 & 67 & 72.4827 & -5.48271 \tabularnewline
183 & 70 & 75.6627 & -5.66266 \tabularnewline
184 & 80 & 75.3119 & 4.68812 \tabularnewline
185 & 89 & 71.116 & 17.884 \tabularnewline
186 & 76 & 67.6037 & 8.39634 \tabularnewline
187 & 74 & 72.435 & 1.56497 \tabularnewline
188 & 87 & 72.9294 & 14.0706 \tabularnewline
189 & 54 & 67.7779 & -13.7779 \tabularnewline
190 & 61 & 62.3666 & -1.36659 \tabularnewline
191 & 38 & 70.3449 & -32.3449 \tabularnewline
192 & 75 & 76.2059 & -1.20588 \tabularnewline
193 & 69 & 68.7695 & 0.230548 \tabularnewline
194 & 62 & 69.0604 & -7.06039 \tabularnewline
195 & 72 & 71.2486 & 0.751425 \tabularnewline
196 & 70 & 73.0586 & -3.05862 \tabularnewline
197 & 79 & 67.7676 & 11.2324 \tabularnewline
198 & 87 & 71.5653 & 15.4347 \tabularnewline
199 & 62 & 63.6024 & -1.60236 \tabularnewline
200 & 77 & 70.7528 & 6.24715 \tabularnewline
201 & 69 & 66.0203 & 2.97973 \tabularnewline
202 & 69 & 71.3691 & -2.36913 \tabularnewline
203 & 75 & 74.455 & 0.544996 \tabularnewline
204 & 54 & 70.7814 & -16.7814 \tabularnewline
205 & 72 & 73.8637 & -1.86368 \tabularnewline
206 & 74 & 73.4489 & 0.551139 \tabularnewline
207 & 85 & 74.0268 & 10.9732 \tabularnewline
208 & 52 & 73.2897 & -21.2897 \tabularnewline
209 & 70 & 70.6521 & -0.652074 \tabularnewline
210 & 84 & 74.426 & 9.57399 \tabularnewline
211 & 64 & 66.3233 & -2.32332 \tabularnewline
212 & 84 & 77.0865 & 6.91351 \tabularnewline
213 & 87 & 67.3133 & 19.6867 \tabularnewline
214 & 79 & 68.7652 & 10.2348 \tabularnewline
215 & 67 & 68.7908 & -1.79081 \tabularnewline
216 & 65 & 71.3002 & -6.3002 \tabularnewline
217 & 85 & 76.4775 & 8.52254 \tabularnewline
218 & 83 & 74.1221 & 8.87792 \tabularnewline
219 & 61 & 62.057 & -1.05698 \tabularnewline
220 & 82 & 73.7796 & 8.22037 \tabularnewline
221 & 76 & 71.7304 & 4.26956 \tabularnewline
222 & 58 & 75.3845 & -17.3845 \tabularnewline
223 & 72 & 67.5156 & 4.48442 \tabularnewline
224 & 72 & 74.719 & -2.71901 \tabularnewline
225 & 38 & 63.42 & -25.42 \tabularnewline
226 & 78 & 73.6114 & 4.38862 \tabularnewline
227 & 54 & 76.4629 & -22.4629 \tabularnewline
228 & 63 & 71.6915 & -8.69154 \tabularnewline
229 & 66 & 60.8078 & 5.19218 \tabularnewline
230 & 70 & 70.2274 & -0.227366 \tabularnewline
231 & 71 & 72.014 & -1.01397 \tabularnewline
232 & 67 & 66.69 & 0.309956 \tabularnewline
233 & 58 & 75.3471 & -17.3471 \tabularnewline
234 & 72 & 72.2222 & -0.222154 \tabularnewline
235 & 72 & 76.5291 & -4.52912 \tabularnewline
236 & 70 & 69.7329 & 0.267142 \tabularnewline
237 & 76 & 65.9784 & 10.0216 \tabularnewline
238 & 50 & 72.3238 & -22.3238 \tabularnewline
239 & 72 & 71.4891 & 0.510915 \tabularnewline
240 & 72 & 70.4719 & 1.5281 \tabularnewline
241 & 88 & 71.4439 & 16.5561 \tabularnewline
242 & 53 & 64.8935 & -11.8935 \tabularnewline
243 & 58 & 65.5293 & -7.52931 \tabularnewline
244 & 66 & 68.5104 & -2.51039 \tabularnewline
245 & 82 & 73.3935 & 8.6065 \tabularnewline
246 & 69 & 64.2995 & 4.70051 \tabularnewline
247 & 68 & 70.3629 & -2.36291 \tabularnewline
248 & 44 & 64.9692 & -20.9692 \tabularnewline
249 & 56 & 60.8824 & -4.88242 \tabularnewline
250 & 53 & 65.5555 & -12.5555 \tabularnewline
251 & 70 & 71.0636 & -1.06355 \tabularnewline
252 & 78 & 67.711 & 10.289 \tabularnewline
253 & 71 & 72.9325 & -1.93254 \tabularnewline
254 & 72 & 72.3175 & -0.31746 \tabularnewline
255 & 68 & 69.0568 & -1.05682 \tabularnewline
256 & 67 & 70.5878 & -3.58777 \tabularnewline
257 & 75 & 65.5274 & 9.47255 \tabularnewline
258 & 62 & 65.2834 & -3.28337 \tabularnewline
259 & 67 & 72.9333 & -5.93334 \tabularnewline
260 & 83 & 70.5425 & 12.4575 \tabularnewline
261 & 64 & 72.7576 & -8.7576 \tabularnewline
262 & 68 & 74.6643 & -6.66429 \tabularnewline
263 & 62 & 62.3706 & -0.370612 \tabularnewline
264 & 72 & 72.6627 & -0.662695 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253224&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]71.2987[/C][C]-18.2987[/C][/ROW]
[ROW][C]2[/C][C]83[/C][C]74.1299[/C][C]8.87011[/C][/ROW]
[ROW][C]3[/C][C]66[/C][C]67.6717[/C][C]-1.67172[/C][/ROW]
[ROW][C]4[/C][C]67[/C][C]66.9312[/C][C]0.0688129[/C][/ROW]
[ROW][C]5[/C][C]76[/C][C]65.1868[/C][C]10.8132[/C][/ROW]
[ROW][C]6[/C][C]78[/C][C]71.6717[/C][C]6.3283[/C][/ROW]
[ROW][C]7[/C][C]53[/C][C]64.5955[/C][C]-11.5955[/C][/ROW]
[ROW][C]8[/C][C]80[/C][C]71.5492[/C][C]8.45076[/C][/ROW]
[ROW][C]9[/C][C]74[/C][C]72.5554[/C][C]1.44464[/C][/ROW]
[ROW][C]10[/C][C]76[/C][C]70.3366[/C][C]5.66339[/C][/ROW]
[ROW][C]11[/C][C]79[/C][C]73.897[/C][C]5.103[/C][/ROW]
[ROW][C]12[/C][C]54[/C][C]76.88[/C][C]-22.88[/C][/ROW]
[ROW][C]13[/C][C]67[/C][C]66.7075[/C][C]0.292508[/C][/ROW]
[ROW][C]14[/C][C]54[/C][C]71.346[/C][C]-17.346[/C][/ROW]
[ROW][C]15[/C][C]87[/C][C]75.3992[/C][C]11.6008[/C][/ROW]
[ROW][C]16[/C][C]58[/C][C]68.4927[/C][C]-10.4927[/C][/ROW]
[ROW][C]17[/C][C]75[/C][C]68.7412[/C][C]6.25876[/C][/ROW]
[ROW][C]18[/C][C]88[/C][C]75.0608[/C][C]12.9392[/C][/ROW]
[ROW][C]19[/C][C]64[/C][C]73.4773[/C][C]-9.47727[/C][/ROW]
[ROW][C]20[/C][C]57[/C][C]70.6636[/C][C]-13.6636[/C][/ROW]
[ROW][C]21[/C][C]66[/C][C]74.2842[/C][C]-8.28421[/C][/ROW]
[ROW][C]22[/C][C]68[/C][C]66.6096[/C][C]1.3904[/C][/ROW]
[ROW][C]23[/C][C]54[/C][C]72.7683[/C][C]-18.7683[/C][/ROW]
[ROW][C]24[/C][C]56[/C][C]68.7197[/C][C]-12.7197[/C][/ROW]
[ROW][C]25[/C][C]86[/C][C]74.3358[/C][C]11.6642[/C][/ROW]
[ROW][C]26[/C][C]80[/C][C]71.4153[/C][C]8.58468[/C][/ROW]
[ROW][C]27[/C][C]76[/C][C]72.728[/C][C]3.27203[/C][/ROW]
[ROW][C]28[/C][C]69[/C][C]68.8963[/C][C]0.103718[/C][/ROW]
[ROW][C]29[/C][C]78[/C][C]69.7336[/C][C]8.26645[/C][/ROW]
[ROW][C]30[/C][C]67[/C][C]67.3009[/C][C]-0.30086[/C][/ROW]
[ROW][C]31[/C][C]80[/C][C]73.2643[/C][C]6.73571[/C][/ROW]
[ROW][C]32[/C][C]54[/C][C]64.8866[/C][C]-10.8866[/C][/ROW]
[ROW][C]33[/C][C]71[/C][C]73.6718[/C][C]-2.67177[/C][/ROW]
[ROW][C]34[/C][C]84[/C][C]72.4398[/C][C]11.5602[/C][/ROW]
[ROW][C]35[/C][C]74[/C][C]69.5012[/C][C]4.49876[/C][/ROW]
[ROW][C]36[/C][C]71[/C][C]72.2258[/C][C]-1.22579[/C][/ROW]
[ROW][C]37[/C][C]63[/C][C]59.0081[/C][C]3.99185[/C][/ROW]
[ROW][C]38[/C][C]71[/C][C]71.4771[/C][C]-0.477137[/C][/ROW]
[ROW][C]39[/C][C]76[/C][C]72.6815[/C][C]3.31847[/C][/ROW]
[ROW][C]40[/C][C]69[/C][C]71.4769[/C][C]-2.47691[/C][/ROW]
[ROW][C]41[/C][C]74[/C][C]73.766[/C][C]0.233957[/C][/ROW]
[ROW][C]42[/C][C]75[/C][C]70.3532[/C][C]4.6468[/C][/ROW]
[ROW][C]43[/C][C]54[/C][C]77.2923[/C][C]-23.2923[/C][/ROW]
[ROW][C]44[/C][C]52[/C][C]67.6327[/C][C]-15.6327[/C][/ROW]
[ROW][C]45[/C][C]69[/C][C]71.8959[/C][C]-2.89593[/C][/ROW]
[ROW][C]46[/C][C]68[/C][C]68.1103[/C][C]-0.110285[/C][/ROW]
[ROW][C]47[/C][C]65[/C][C]74.8046[/C][C]-9.80458[/C][/ROW]
[ROW][C]48[/C][C]75[/C][C]71.8515[/C][C]3.14852[/C][/ROW]
[ROW][C]49[/C][C]74[/C][C]71.2843[/C][C]2.71566[/C][/ROW]
[ROW][C]50[/C][C]75[/C][C]71.4653[/C][C]3.53473[/C][/ROW]
[ROW][C]51[/C][C]72[/C][C]74.2183[/C][C]-2.21825[/C][/ROW]
[ROW][C]52[/C][C]67[/C][C]68.2434[/C][C]-1.24336[/C][/ROW]
[ROW][C]53[/C][C]63[/C][C]63.7626[/C][C]-0.762592[/C][/ROW]
[ROW][C]54[/C][C]62[/C][C]69.0538[/C][C]-7.05383[/C][/ROW]
[ROW][C]55[/C][C]63[/C][C]67.1755[/C][C]-4.17546[/C][/ROW]
[ROW][C]56[/C][C]76[/C][C]68.9534[/C][C]7.04663[/C][/ROW]
[ROW][C]57[/C][C]74[/C][C]72.7544[/C][C]1.24562[/C][/ROW]
[ROW][C]58[/C][C]67[/C][C]73.1413[/C][C]-6.14132[/C][/ROW]
[ROW][C]59[/C][C]73[/C][C]71.783[/C][C]1.21698[/C][/ROW]
[ROW][C]60[/C][C]70[/C][C]67.6709[/C][C]2.32913[/C][/ROW]
[ROW][C]61[/C][C]53[/C][C]58.7402[/C][C]-5.74015[/C][/ROW]
[ROW][C]62[/C][C]77[/C][C]71.5036[/C][C]5.49645[/C][/ROW]
[ROW][C]63[/C][C]80[/C][C]70.0445[/C][C]9.95548[/C][/ROW]
[ROW][C]64[/C][C]52[/C][C]68.8311[/C][C]-16.8311[/C][/ROW]
[ROW][C]65[/C][C]54[/C][C]71.121[/C][C]-17.121[/C][/ROW]
[ROW][C]66[/C][C]80[/C][C]70.4987[/C][C]9.50126[/C][/ROW]
[ROW][C]67[/C][C]66[/C][C]67.3087[/C][C]-1.30871[/C][/ROW]
[ROW][C]68[/C][C]73[/C][C]69.1831[/C][C]3.81689[/C][/ROW]
[ROW][C]69[/C][C]63[/C][C]71.9218[/C][C]-8.92184[/C][/ROW]
[ROW][C]70[/C][C]69[/C][C]71.0884[/C][C]-2.08838[/C][/ROW]
[ROW][C]71[/C][C]67[/C][C]69.5492[/C][C]-2.54924[/C][/ROW]
[ROW][C]72[/C][C]54[/C][C]69.7002[/C][C]-15.7002[/C][/ROW]
[ROW][C]73[/C][C]81[/C][C]72.6756[/C][C]8.32442[/C][/ROW]
[ROW][C]74[/C][C]69[/C][C]75.741[/C][C]-6.74099[/C][/ROW]
[ROW][C]75[/C][C]84[/C][C]71.2109[/C][C]12.7891[/C][/ROW]
[ROW][C]76[/C][C]80[/C][C]65.528[/C][C]14.472[/C][/ROW]
[ROW][C]77[/C][C]70[/C][C]73.7759[/C][C]-3.7759[/C][/ROW]
[ROW][C]78[/C][C]69[/C][C]66.9961[/C][C]2.00393[/C][/ROW]
[ROW][C]79[/C][C]77[/C][C]69.6095[/C][C]7.39053[/C][/ROW]
[ROW][C]80[/C][C]54[/C][C]73.3[/C][C]-19.3[/C][/ROW]
[ROW][C]81[/C][C]79[/C][C]72.9887[/C][C]6.01131[/C][/ROW]
[ROW][C]82[/C][C]71[/C][C]74.8895[/C][C]-3.88951[/C][/ROW]
[ROW][C]83[/C][C]73[/C][C]73.2668[/C][C]-0.266756[/C][/ROW]
[ROW][C]84[/C][C]72[/C][C]71.5614[/C][C]0.438597[/C][/ROW]
[ROW][C]85[/C][C]77[/C][C]70.1996[/C][C]6.80039[/C][/ROW]
[ROW][C]86[/C][C]75[/C][C]71.6901[/C][C]3.30994[/C][/ROW]
[ROW][C]87[/C][C]69[/C][C]71.6127[/C][C]-2.61268[/C][/ROW]
[ROW][C]88[/C][C]54[/C][C]67.9592[/C][C]-13.9592[/C][/ROW]
[ROW][C]89[/C][C]70[/C][C]59.8236[/C][C]10.1764[/C][/ROW]
[ROW][C]90[/C][C]73[/C][C]71.0644[/C][C]1.93563[/C][/ROW]
[ROW][C]91[/C][C]54[/C][C]70.2168[/C][C]-16.2168[/C][/ROW]
[ROW][C]92[/C][C]77[/C][C]72.4596[/C][C]4.54039[/C][/ROW]
[ROW][C]93[/C][C]82[/C][C]68.7506[/C][C]13.2494[/C][/ROW]
[ROW][C]94[/C][C]80[/C][C]69.1011[/C][C]10.8989[/C][/ROW]
[ROW][C]95[/C][C]80[/C][C]74.5281[/C][C]5.4719[/C][/ROW]
[ROW][C]96[/C][C]69[/C][C]68.6951[/C][C]0.304947[/C][/ROW]
[ROW][C]97[/C][C]78[/C][C]71.9936[/C][C]6.00642[/C][/ROW]
[ROW][C]98[/C][C]81[/C][C]75.1413[/C][C]5.85874[/C][/ROW]
[ROW][C]99[/C][C]76[/C][C]72.9604[/C][C]3.03961[/C][/ROW]
[ROW][C]100[/C][C]76[/C][C]76.674[/C][C]-0.674012[/C][/ROW]
[ROW][C]101[/C][C]73[/C][C]68.3273[/C][C]4.67275[/C][/ROW]
[ROW][C]102[/C][C]85[/C][C]75.3947[/C][C]9.60532[/C][/ROW]
[ROW][C]103[/C][C]66[/C][C]69.7044[/C][C]-3.70436[/C][/ROW]
[ROW][C]104[/C][C]79[/C][C]69.7672[/C][C]9.23281[/C][/ROW]
[ROW][C]105[/C][C]68[/C][C]64.3361[/C][C]3.66392[/C][/ROW]
[ROW][C]106[/C][C]76[/C][C]75.1202[/C][C]0.879775[/C][/ROW]
[ROW][C]107[/C][C]71[/C][C]71.5527[/C][C]-0.552661[/C][/ROW]
[ROW][C]108[/C][C]54[/C][C]67.7331[/C][C]-13.7331[/C][/ROW]
[ROW][C]109[/C][C]46[/C][C]61.3432[/C][C]-15.3432[/C][/ROW]
[ROW][C]110[/C][C]85[/C][C]70.6262[/C][C]14.3738[/C][/ROW]
[ROW][C]111[/C][C]74[/C][C]68.0079[/C][C]5.99215[/C][/ROW]
[ROW][C]112[/C][C]88[/C][C]72.411[/C][C]15.589[/C][/ROW]
[ROW][C]113[/C][C]38[/C][C]68.7963[/C][C]-30.7963[/C][/ROW]
[ROW][C]114[/C][C]76[/C][C]74.0372[/C][C]1.96278[/C][/ROW]
[ROW][C]115[/C][C]86[/C][C]76.0329[/C][C]9.96709[/C][/ROW]
[ROW][C]116[/C][C]54[/C][C]70.8969[/C][C]-16.8969[/C][/ROW]
[ROW][C]117[/C][C]67[/C][C]70.6876[/C][C]-3.68761[/C][/ROW]
[ROW][C]118[/C][C]69[/C][C]73.5223[/C][C]-4.52229[/C][/ROW]
[ROW][C]119[/C][C]90[/C][C]71.0837[/C][C]18.9163[/C][/ROW]
[ROW][C]120[/C][C]54[/C][C]68.1348[/C][C]-14.1348[/C][/ROW]
[ROW][C]121[/C][C]76[/C][C]70.1266[/C][C]5.87342[/C][/ROW]
[ROW][C]122[/C][C]89[/C][C]74.2188[/C][C]14.7812[/C][/ROW]
[ROW][C]123[/C][C]76[/C][C]77.2108[/C][C]-1.21079[/C][/ROW]
[ROW][C]124[/C][C]73[/C][C]73.9675[/C][C]-0.967484[/C][/ROW]
[ROW][C]125[/C][C]79[/C][C]72.5958[/C][C]6.40419[/C][/ROW]
[ROW][C]126[/C][C]90[/C][C]77.3574[/C][C]12.6426[/C][/ROW]
[ROW][C]127[/C][C]74[/C][C]78.0004[/C][C]-4.00039[/C][/ROW]
[ROW][C]128[/C][C]81[/C][C]75.397[/C][C]5.60299[/C][/ROW]
[ROW][C]129[/C][C]72[/C][C]71.4894[/C][C]0.510593[/C][/ROW]
[ROW][C]130[/C][C]71[/C][C]71.7361[/C][C]-0.736102[/C][/ROW]
[ROW][C]131[/C][C]66[/C][C]60.9541[/C][C]5.04591[/C][/ROW]
[ROW][C]132[/C][C]77[/C][C]75.0629[/C][C]1.93713[/C][/ROW]
[ROW][C]133[/C][C]65[/C][C]68.4065[/C][C]-3.40647[/C][/ROW]
[ROW][C]134[/C][C]74[/C][C]73.6555[/C][C]0.344488[/C][/ROW]
[ROW][C]135[/C][C]85[/C][C]71.5035[/C][C]13.4965[/C][/ROW]
[ROW][C]136[/C][C]54[/C][C]59.6079[/C][C]-5.60791[/C][/ROW]
[ROW][C]137[/C][C]63[/C][C]70.8553[/C][C]-7.85533[/C][/ROW]
[ROW][C]138[/C][C]54[/C][C]65.7585[/C][C]-11.7585[/C][/ROW]
[ROW][C]139[/C][C]64[/C][C]72.4874[/C][C]-8.48743[/C][/ROW]
[ROW][C]140[/C][C]69[/C][C]69.8755[/C][C]-0.875498[/C][/ROW]
[ROW][C]141[/C][C]54[/C][C]73.5038[/C][C]-19.5038[/C][/ROW]
[ROW][C]142[/C][C]84[/C][C]71.1162[/C][C]12.8838[/C][/ROW]
[ROW][C]143[/C][C]86[/C][C]72.9639[/C][C]13.0361[/C][/ROW]
[ROW][C]144[/C][C]77[/C][C]71.8532[/C][C]5.14685[/C][/ROW]
[ROW][C]145[/C][C]89[/C][C]73.5345[/C][C]15.4655[/C][/ROW]
[ROW][C]146[/C][C]76[/C][C]73.8408[/C][C]2.1592[/C][/ROW]
[ROW][C]147[/C][C]60[/C][C]70.1368[/C][C]-10.1368[/C][/ROW]
[ROW][C]148[/C][C]75[/C][C]71.7385[/C][C]3.2615[/C][/ROW]
[ROW][C]149[/C][C]73[/C][C]63.4683[/C][C]9.53168[/C][/ROW]
[ROW][C]150[/C][C]85[/C][C]72.8473[/C][C]12.1527[/C][/ROW]
[ROW][C]151[/C][C]79[/C][C]70.414[/C][C]8.58595[/C][/ROW]
[ROW][C]152[/C][C]71[/C][C]75.9124[/C][C]-4.91239[/C][/ROW]
[ROW][C]153[/C][C]72[/C][C]70.8595[/C][C]1.1405[/C][/ROW]
[ROW][C]154[/C][C]69[/C][C]64.237[/C][C]4.76299[/C][/ROW]
[ROW][C]155[/C][C]78[/C][C]65.4865[/C][C]12.5135[/C][/ROW]
[ROW][C]156[/C][C]54[/C][C]71.3316[/C][C]-17.3316[/C][/ROW]
[ROW][C]157[/C][C]69[/C][C]69.411[/C][C]-0.410961[/C][/ROW]
[ROW][C]158[/C][C]81[/C][C]75.9115[/C][C]5.0885[/C][/ROW]
[ROW][C]159[/C][C]84[/C][C]74.2064[/C][C]9.79355[/C][/ROW]
[ROW][C]160[/C][C]84[/C][C]65.6565[/C][C]18.3435[/C][/ROW]
[ROW][C]161[/C][C]69[/C][C]68.1807[/C][C]0.819342[/C][/ROW]
[ROW][C]162[/C][C]66[/C][C]59.0256[/C][C]6.97443[/C][/ROW]
[ROW][C]163[/C][C]81[/C][C]68.8161[/C][C]12.1839[/C][/ROW]
[ROW][C]164[/C][C]82[/C][C]69.9594[/C][C]12.0406[/C][/ROW]
[ROW][C]165[/C][C]72[/C][C]66.0177[/C][C]5.9823[/C][/ROW]
[ROW][C]166[/C][C]54[/C][C]59.0706[/C][C]-5.07057[/C][/ROW]
[ROW][C]167[/C][C]78[/C][C]71.7098[/C][C]6.29016[/C][/ROW]
[ROW][C]168[/C][C]74[/C][C]67.3463[/C][C]6.65374[/C][/ROW]
[ROW][C]169[/C][C]82[/C][C]66.8727[/C][C]15.1273[/C][/ROW]
[ROW][C]170[/C][C]73[/C][C]64.6854[/C][C]8.31464[/C][/ROW]
[ROW][C]171[/C][C]55[/C][C]63.5653[/C][C]-8.56532[/C][/ROW]
[ROW][C]172[/C][C]72[/C][C]75.0866[/C][C]-3.08661[/C][/ROW]
[ROW][C]173[/C][C]78[/C][C]70.2697[/C][C]7.73031[/C][/ROW]
[ROW][C]174[/C][C]59[/C][C]64.9316[/C][C]-5.93161[/C][/ROW]
[ROW][C]175[/C][C]72[/C][C]72.9723[/C][C]-0.972305[/C][/ROW]
[ROW][C]176[/C][C]78[/C][C]74.1203[/C][C]3.87972[/C][/ROW]
[ROW][C]177[/C][C]68[/C][C]66.1174[/C][C]1.88259[/C][/ROW]
[ROW][C]178[/C][C]69[/C][C]65.2654[/C][C]3.73456[/C][/ROW]
[ROW][C]179[/C][C]67[/C][C]74.4228[/C][C]-7.42279[/C][/ROW]
[ROW][C]180[/C][C]74[/C][C]69.5419[/C][C]4.45813[/C][/ROW]
[ROW][C]181[/C][C]54[/C][C]74.6465[/C][C]-20.6465[/C][/ROW]
[ROW][C]182[/C][C]67[/C][C]72.4827[/C][C]-5.48271[/C][/ROW]
[ROW][C]183[/C][C]70[/C][C]75.6627[/C][C]-5.66266[/C][/ROW]
[ROW][C]184[/C][C]80[/C][C]75.3119[/C][C]4.68812[/C][/ROW]
[ROW][C]185[/C][C]89[/C][C]71.116[/C][C]17.884[/C][/ROW]
[ROW][C]186[/C][C]76[/C][C]67.6037[/C][C]8.39634[/C][/ROW]
[ROW][C]187[/C][C]74[/C][C]72.435[/C][C]1.56497[/C][/ROW]
[ROW][C]188[/C][C]87[/C][C]72.9294[/C][C]14.0706[/C][/ROW]
[ROW][C]189[/C][C]54[/C][C]67.7779[/C][C]-13.7779[/C][/ROW]
[ROW][C]190[/C][C]61[/C][C]62.3666[/C][C]-1.36659[/C][/ROW]
[ROW][C]191[/C][C]38[/C][C]70.3449[/C][C]-32.3449[/C][/ROW]
[ROW][C]192[/C][C]75[/C][C]76.2059[/C][C]-1.20588[/C][/ROW]
[ROW][C]193[/C][C]69[/C][C]68.7695[/C][C]0.230548[/C][/ROW]
[ROW][C]194[/C][C]62[/C][C]69.0604[/C][C]-7.06039[/C][/ROW]
[ROW][C]195[/C][C]72[/C][C]71.2486[/C][C]0.751425[/C][/ROW]
[ROW][C]196[/C][C]70[/C][C]73.0586[/C][C]-3.05862[/C][/ROW]
[ROW][C]197[/C][C]79[/C][C]67.7676[/C][C]11.2324[/C][/ROW]
[ROW][C]198[/C][C]87[/C][C]71.5653[/C][C]15.4347[/C][/ROW]
[ROW][C]199[/C][C]62[/C][C]63.6024[/C][C]-1.60236[/C][/ROW]
[ROW][C]200[/C][C]77[/C][C]70.7528[/C][C]6.24715[/C][/ROW]
[ROW][C]201[/C][C]69[/C][C]66.0203[/C][C]2.97973[/C][/ROW]
[ROW][C]202[/C][C]69[/C][C]71.3691[/C][C]-2.36913[/C][/ROW]
[ROW][C]203[/C][C]75[/C][C]74.455[/C][C]0.544996[/C][/ROW]
[ROW][C]204[/C][C]54[/C][C]70.7814[/C][C]-16.7814[/C][/ROW]
[ROW][C]205[/C][C]72[/C][C]73.8637[/C][C]-1.86368[/C][/ROW]
[ROW][C]206[/C][C]74[/C][C]73.4489[/C][C]0.551139[/C][/ROW]
[ROW][C]207[/C][C]85[/C][C]74.0268[/C][C]10.9732[/C][/ROW]
[ROW][C]208[/C][C]52[/C][C]73.2897[/C][C]-21.2897[/C][/ROW]
[ROW][C]209[/C][C]70[/C][C]70.6521[/C][C]-0.652074[/C][/ROW]
[ROW][C]210[/C][C]84[/C][C]74.426[/C][C]9.57399[/C][/ROW]
[ROW][C]211[/C][C]64[/C][C]66.3233[/C][C]-2.32332[/C][/ROW]
[ROW][C]212[/C][C]84[/C][C]77.0865[/C][C]6.91351[/C][/ROW]
[ROW][C]213[/C][C]87[/C][C]67.3133[/C][C]19.6867[/C][/ROW]
[ROW][C]214[/C][C]79[/C][C]68.7652[/C][C]10.2348[/C][/ROW]
[ROW][C]215[/C][C]67[/C][C]68.7908[/C][C]-1.79081[/C][/ROW]
[ROW][C]216[/C][C]65[/C][C]71.3002[/C][C]-6.3002[/C][/ROW]
[ROW][C]217[/C][C]85[/C][C]76.4775[/C][C]8.52254[/C][/ROW]
[ROW][C]218[/C][C]83[/C][C]74.1221[/C][C]8.87792[/C][/ROW]
[ROW][C]219[/C][C]61[/C][C]62.057[/C][C]-1.05698[/C][/ROW]
[ROW][C]220[/C][C]82[/C][C]73.7796[/C][C]8.22037[/C][/ROW]
[ROW][C]221[/C][C]76[/C][C]71.7304[/C][C]4.26956[/C][/ROW]
[ROW][C]222[/C][C]58[/C][C]75.3845[/C][C]-17.3845[/C][/ROW]
[ROW][C]223[/C][C]72[/C][C]67.5156[/C][C]4.48442[/C][/ROW]
[ROW][C]224[/C][C]72[/C][C]74.719[/C][C]-2.71901[/C][/ROW]
[ROW][C]225[/C][C]38[/C][C]63.42[/C][C]-25.42[/C][/ROW]
[ROW][C]226[/C][C]78[/C][C]73.6114[/C][C]4.38862[/C][/ROW]
[ROW][C]227[/C][C]54[/C][C]76.4629[/C][C]-22.4629[/C][/ROW]
[ROW][C]228[/C][C]63[/C][C]71.6915[/C][C]-8.69154[/C][/ROW]
[ROW][C]229[/C][C]66[/C][C]60.8078[/C][C]5.19218[/C][/ROW]
[ROW][C]230[/C][C]70[/C][C]70.2274[/C][C]-0.227366[/C][/ROW]
[ROW][C]231[/C][C]71[/C][C]72.014[/C][C]-1.01397[/C][/ROW]
[ROW][C]232[/C][C]67[/C][C]66.69[/C][C]0.309956[/C][/ROW]
[ROW][C]233[/C][C]58[/C][C]75.3471[/C][C]-17.3471[/C][/ROW]
[ROW][C]234[/C][C]72[/C][C]72.2222[/C][C]-0.222154[/C][/ROW]
[ROW][C]235[/C][C]72[/C][C]76.5291[/C][C]-4.52912[/C][/ROW]
[ROW][C]236[/C][C]70[/C][C]69.7329[/C][C]0.267142[/C][/ROW]
[ROW][C]237[/C][C]76[/C][C]65.9784[/C][C]10.0216[/C][/ROW]
[ROW][C]238[/C][C]50[/C][C]72.3238[/C][C]-22.3238[/C][/ROW]
[ROW][C]239[/C][C]72[/C][C]71.4891[/C][C]0.510915[/C][/ROW]
[ROW][C]240[/C][C]72[/C][C]70.4719[/C][C]1.5281[/C][/ROW]
[ROW][C]241[/C][C]88[/C][C]71.4439[/C][C]16.5561[/C][/ROW]
[ROW][C]242[/C][C]53[/C][C]64.8935[/C][C]-11.8935[/C][/ROW]
[ROW][C]243[/C][C]58[/C][C]65.5293[/C][C]-7.52931[/C][/ROW]
[ROW][C]244[/C][C]66[/C][C]68.5104[/C][C]-2.51039[/C][/ROW]
[ROW][C]245[/C][C]82[/C][C]73.3935[/C][C]8.6065[/C][/ROW]
[ROW][C]246[/C][C]69[/C][C]64.2995[/C][C]4.70051[/C][/ROW]
[ROW][C]247[/C][C]68[/C][C]70.3629[/C][C]-2.36291[/C][/ROW]
[ROW][C]248[/C][C]44[/C][C]64.9692[/C][C]-20.9692[/C][/ROW]
[ROW][C]249[/C][C]56[/C][C]60.8824[/C][C]-4.88242[/C][/ROW]
[ROW][C]250[/C][C]53[/C][C]65.5555[/C][C]-12.5555[/C][/ROW]
[ROW][C]251[/C][C]70[/C][C]71.0636[/C][C]-1.06355[/C][/ROW]
[ROW][C]252[/C][C]78[/C][C]67.711[/C][C]10.289[/C][/ROW]
[ROW][C]253[/C][C]71[/C][C]72.9325[/C][C]-1.93254[/C][/ROW]
[ROW][C]254[/C][C]72[/C][C]72.3175[/C][C]-0.31746[/C][/ROW]
[ROW][C]255[/C][C]68[/C][C]69.0568[/C][C]-1.05682[/C][/ROW]
[ROW][C]256[/C][C]67[/C][C]70.5878[/C][C]-3.58777[/C][/ROW]
[ROW][C]257[/C][C]75[/C][C]65.5274[/C][C]9.47255[/C][/ROW]
[ROW][C]258[/C][C]62[/C][C]65.2834[/C][C]-3.28337[/C][/ROW]
[ROW][C]259[/C][C]67[/C][C]72.9333[/C][C]-5.93334[/C][/ROW]
[ROW][C]260[/C][C]83[/C][C]70.5425[/C][C]12.4575[/C][/ROW]
[ROW][C]261[/C][C]64[/C][C]72.7576[/C][C]-8.7576[/C][/ROW]
[ROW][C]262[/C][C]68[/C][C]74.6643[/C][C]-6.66429[/C][/ROW]
[ROW][C]263[/C][C]62[/C][C]62.3706[/C][C]-0.370612[/C][/ROW]
[ROW][C]264[/C][C]72[/C][C]72.6627[/C][C]-0.662695[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253224&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253224&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
15371.2987-18.2987
28374.12998.87011
36667.6717-1.67172
46766.93120.0688129
57665.186810.8132
67871.67176.3283
75364.5955-11.5955
88071.54928.45076
97472.55541.44464
107670.33665.66339
117973.8975.103
125476.88-22.88
136766.70750.292508
145471.346-17.346
158775.399211.6008
165868.4927-10.4927
177568.74126.25876
188875.060812.9392
196473.4773-9.47727
205770.6636-13.6636
216674.2842-8.28421
226866.60961.3904
235472.7683-18.7683
245668.7197-12.7197
258674.335811.6642
268071.41538.58468
277672.7283.27203
286968.89630.103718
297869.73368.26645
306767.3009-0.30086
318073.26436.73571
325464.8866-10.8866
337173.6718-2.67177
348472.439811.5602
357469.50124.49876
367172.2258-1.22579
376359.00813.99185
387171.4771-0.477137
397672.68153.31847
406971.4769-2.47691
417473.7660.233957
427570.35324.6468
435477.2923-23.2923
445267.6327-15.6327
456971.8959-2.89593
466868.1103-0.110285
476574.8046-9.80458
487571.85153.14852
497471.28432.71566
507571.46533.53473
517274.2183-2.21825
526768.2434-1.24336
536363.7626-0.762592
546269.0538-7.05383
556367.1755-4.17546
567668.95347.04663
577472.75441.24562
586773.1413-6.14132
597371.7831.21698
607067.67092.32913
615358.7402-5.74015
627771.50365.49645
638070.04459.95548
645268.8311-16.8311
655471.121-17.121
668070.49879.50126
676667.3087-1.30871
687369.18313.81689
696371.9218-8.92184
706971.0884-2.08838
716769.5492-2.54924
725469.7002-15.7002
738172.67568.32442
746975.741-6.74099
758471.210912.7891
768065.52814.472
777073.7759-3.7759
786966.99612.00393
797769.60957.39053
805473.3-19.3
817972.98876.01131
827174.8895-3.88951
837373.2668-0.266756
847271.56140.438597
857770.19966.80039
867571.69013.30994
876971.6127-2.61268
885467.9592-13.9592
897059.823610.1764
907371.06441.93563
915470.2168-16.2168
927772.45964.54039
938268.750613.2494
948069.101110.8989
958074.52815.4719
966968.69510.304947
977871.99366.00642
988175.14135.85874
997672.96043.03961
1007676.674-0.674012
1017368.32734.67275
1028575.39479.60532
1036669.7044-3.70436
1047969.76729.23281
1056864.33613.66392
1067675.12020.879775
1077171.5527-0.552661
1085467.7331-13.7331
1094661.3432-15.3432
1108570.626214.3738
1117468.00795.99215
1128872.41115.589
1133868.7963-30.7963
1147674.03721.96278
1158676.03299.96709
1165470.8969-16.8969
1176770.6876-3.68761
1186973.5223-4.52229
1199071.083718.9163
1205468.1348-14.1348
1217670.12665.87342
1228974.218814.7812
1237677.2108-1.21079
1247373.9675-0.967484
1257972.59586.40419
1269077.357412.6426
1277478.0004-4.00039
1288175.3975.60299
1297271.48940.510593
1307171.7361-0.736102
1316660.95415.04591
1327775.06291.93713
1336568.4065-3.40647
1347473.65550.344488
1358571.503513.4965
1365459.6079-5.60791
1376370.8553-7.85533
1385465.7585-11.7585
1396472.4874-8.48743
1406969.8755-0.875498
1415473.5038-19.5038
1428471.116212.8838
1438672.963913.0361
1447771.85325.14685
1458973.534515.4655
1467673.84082.1592
1476070.1368-10.1368
1487571.73853.2615
1497363.46839.53168
1508572.847312.1527
1517970.4148.58595
1527175.9124-4.91239
1537270.85951.1405
1546964.2374.76299
1557865.486512.5135
1565471.3316-17.3316
1576969.411-0.410961
1588175.91155.0885
1598474.20649.79355
1608465.656518.3435
1616968.18070.819342
1626659.02566.97443
1638168.816112.1839
1648269.959412.0406
1657266.01775.9823
1665459.0706-5.07057
1677871.70986.29016
1687467.34636.65374
1698266.872715.1273
1707364.68548.31464
1715563.5653-8.56532
1727275.0866-3.08661
1737870.26977.73031
1745964.9316-5.93161
1757272.9723-0.972305
1767874.12033.87972
1776866.11741.88259
1786965.26543.73456
1796774.4228-7.42279
1807469.54194.45813
1815474.6465-20.6465
1826772.4827-5.48271
1837075.6627-5.66266
1848075.31194.68812
1858971.11617.884
1867667.60378.39634
1877472.4351.56497
1888772.929414.0706
1895467.7779-13.7779
1906162.3666-1.36659
1913870.3449-32.3449
1927576.2059-1.20588
1936968.76950.230548
1946269.0604-7.06039
1957271.24860.751425
1967073.0586-3.05862
1977967.767611.2324
1988771.565315.4347
1996263.6024-1.60236
2007770.75286.24715
2016966.02032.97973
2026971.3691-2.36913
2037574.4550.544996
2045470.7814-16.7814
2057273.8637-1.86368
2067473.44890.551139
2078574.026810.9732
2085273.2897-21.2897
2097070.6521-0.652074
2108474.4269.57399
2116466.3233-2.32332
2128477.08656.91351
2138767.313319.6867
2147968.765210.2348
2156768.7908-1.79081
2166571.3002-6.3002
2178576.47758.52254
2188374.12218.87792
2196162.057-1.05698
2208273.77968.22037
2217671.73044.26956
2225875.3845-17.3845
2237267.51564.48442
2247274.719-2.71901
2253863.42-25.42
2267873.61144.38862
2275476.4629-22.4629
2286371.6915-8.69154
2296660.80785.19218
2307070.2274-0.227366
2317172.014-1.01397
2326766.690.309956
2335875.3471-17.3471
2347272.2222-0.222154
2357276.5291-4.52912
2367069.73290.267142
2377665.978410.0216
2385072.3238-22.3238
2397271.48910.510915
2407270.47191.5281
2418871.443916.5561
2425364.8935-11.8935
2435865.5293-7.52931
2446668.5104-2.51039
2458273.39358.6065
2466964.29954.70051
2476870.3629-2.36291
2484464.9692-20.9692
2495660.8824-4.88242
2505365.5555-12.5555
2517071.0636-1.06355
2527867.71110.289
2537172.9325-1.93254
2547272.3175-0.31746
2556869.0568-1.05682
2566770.5878-3.58777
2577565.52749.47255
2586265.2834-3.28337
2596772.9333-5.93334
2608370.542512.4575
2616472.7576-8.7576
2626874.6643-6.66429
2636262.3706-0.370612
2647272.6627-0.662695






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.07980990.159620.92019
120.9719150.05617010.028085
130.9498470.1003050.0501526
140.9361020.1277950.0638977
150.9406310.1187370.0593686
160.9607970.07840640.0392032
170.9516070.09678610.048393
180.9704470.05910540.0295527
190.9586750.08265080.0413254
200.9700910.05981750.0299087
210.9623360.07532890.0376644
220.9507420.09851570.0492578
230.9526630.09467480.0473374
240.9375230.1249530.0624767
250.9646830.07063440.0353172
260.9672330.0655330.0327665
270.9593830.08123440.0406172
280.9449790.1100420.0550212
290.9361740.1276520.0638258
300.9148270.1703470.0851733
310.8911470.2177060.108853
320.8900570.2198860.109943
330.8635460.2729080.136454
340.882440.2351190.11756
350.8533660.2932670.146634
360.8190430.3619140.180957
370.7885830.4228350.211417
380.7491120.5017760.250888
390.7047590.5904830.295241
400.6600560.6798880.339944
410.6101910.7796180.389809
420.5631610.8736780.436839
430.7781130.4437750.221887
440.8077510.3844980.192249
450.773570.452860.22643
460.7361220.5277570.263878
470.7112250.577550.288775
480.6813340.6373320.318666
490.6585690.6828630.341431
500.6267790.7464420.373221
510.5817580.8364840.418242
520.5362950.9274110.463705
530.4898120.9796240.510188
540.4524490.9048990.547551
550.4123420.8246840.587658
560.4167040.8334070.583296
570.3768170.7536330.623183
580.3470430.6940870.652957
590.3171160.6342330.682884
600.2852420.5704840.714758
610.2644460.5288920.735554
620.249340.4986790.75066
630.261410.522820.73859
640.3344940.6689890.665506
650.4137450.8274890.586255
660.4319680.8639360.568032
670.3919260.7838520.608074
680.3584630.7169260.641537
690.3405440.6810880.659456
700.3048540.6097070.695146
710.2719320.5438630.728068
720.305410.610820.69459
730.3162520.6325050.683748
740.2911840.5823670.708816
750.302910.605820.69709
760.3370410.6740820.662959
770.3053870.6107730.694613
780.2709920.5419840.729008
790.2534190.5068390.746581
800.3915970.7831930.608403
810.3728420.7456850.627158
820.3417060.6834120.658294
830.3073180.6146360.692682
840.2746070.5492140.725393
850.2539040.5078070.746096
860.2316160.4632310.768384
870.2064380.4128760.793562
880.2486570.4973150.751343
890.2423540.4847090.757646
900.2164170.4328350.783583
910.2780410.5560830.721959
920.2576490.5152990.742351
930.2736070.5472130.726393
940.2724910.5449820.727509
950.2507750.5015490.749225
960.2220160.4440320.777984
970.1997140.3994270.800286
980.1806760.3613510.819324
990.1581950.316390.841805
1000.1374210.2748420.862579
1010.1196510.2393020.880349
1020.1153730.2307450.884627
1030.1046930.2093860.895307
1040.09773380.1954680.902266
1050.08306670.1661330.916933
1060.06980760.1396150.930192
1070.05871110.1174220.941289
1080.07818360.1563670.921816
1090.104750.20950.89525
1100.1135680.2271360.886432
1110.09914050.1982810.90086
1120.1182280.2364570.881772
1130.4078620.8157240.592138
1140.3750310.7500620.624969
1150.3618280.7236570.638172
1160.4484070.8968150.551593
1170.4252530.8505050.574747
1180.4051870.8103730.594813
1190.4821780.9643550.517822
1200.5438280.9123430.456172
1210.5118860.9762280.488114
1220.5514490.8971030.448551
1230.5200330.9599340.479967
1240.4879630.9759260.512037
1250.4583480.9166950.541652
1260.462670.9253410.53733
1270.4404580.8809160.559542
1280.408140.816280.59186
1290.3752290.7504570.624771
1300.3459190.6918380.654081
1310.3189130.6378260.681087
1320.2874960.5749920.712504
1330.2701830.5403650.729817
1340.2433820.4867650.756618
1350.2496270.4992540.750373
1360.2449810.4899610.755019
1370.2480840.4961690.751916
1380.2863390.5726780.713661
1390.2961830.5923650.703817
1400.2753130.5506260.724687
1410.4175060.8350120.582494
1420.4212850.842570.578715
1430.423530.847060.57647
1440.3947680.7895370.605232
1450.4273190.8546370.572681
1460.398260.7965190.60174
1470.4304090.8608170.569591
1480.3953790.7907570.604621
1490.3811770.7623550.618823
1500.3807490.7614980.619251
1510.3612530.7225060.638747
1520.3481190.6962390.651881
1530.3187630.6375270.681237
1540.2891120.5782240.710888
1550.2885910.5771820.711409
1560.385440.7708810.61456
1570.3576030.7152060.642397
1580.3262410.6524820.673759
1590.3120680.6241360.687932
1600.357710.715420.64229
1610.3254640.6509280.674536
1620.3025570.6051130.697443
1630.3105380.6210760.689462
1640.3392410.6784810.660759
1650.3097060.6194120.690294
1660.2962970.5925940.703703
1670.2705670.5411340.729433
1680.2505280.5010550.749472
1690.2671290.5342590.732871
1700.2474530.4949060.752547
1710.2483830.4967670.751617
1720.2260830.4521660.773917
1730.2066440.4132870.793356
1740.1943460.3886930.805654
1750.1729160.3458330.827084
1760.1506990.3013980.849301
1770.1294920.2589850.870508
1780.1127650.225530.887235
1790.1079230.2158460.892077
1800.09192280.1838460.908077
1810.1704250.3408510.829575
1820.1616890.3233790.838311
1830.1493530.2987070.850647
1840.1311470.2622940.868853
1850.1956990.3913980.804301
1860.192620.3852390.80738
1870.1679640.3359280.832036
1880.1942210.3884410.805779
1890.2175230.4350470.782477
1900.1926190.3852380.807381
1910.6224270.7551460.377573
1920.5937430.8125150.406257
1930.5549170.8901660.445083
1940.5621430.8757130.437857
1950.5223630.9552730.477637
1960.5071610.9856780.492839
1970.5620810.8758390.437919
1980.6193870.7612260.380613
1990.585990.8280190.41401
2000.5594240.8811530.440576
2010.5212240.9575510.478776
2020.4810470.9620940.518953
2030.4493910.8987820.550609
2040.5246170.9507670.475383
2050.4835650.9671290.516435
2060.4399380.8798750.560062
2070.439230.878460.56077
2080.5634450.873110.436555
2090.5186720.9626560.481328
2100.5426820.9146360.457318
2110.507710.9845790.49229
2120.4672290.9344570.532771
2130.5910620.8178760.408938
2140.5853090.8293810.414691
2150.5394410.9211170.460559
2160.502090.9958190.49791
2170.5760780.8478450.423922
2180.613970.772060.38603
2190.5676530.8646940.432347
2200.6465580.7068830.353442
2210.6187190.7625620.381281
2220.6307540.7384920.369246
2230.6490870.7018260.350913
2240.6037820.7924360.396218
2250.8237620.3524770.176238
2260.8029490.3941030.197051
2270.8292950.3414090.170705
2280.817760.364480.18224
2290.7952580.4094830.204742
2300.7503430.4993140.249657
2310.7044510.5910990.295549
2320.6622880.6754230.337712
2330.820350.35930.17965
2340.8231040.3537930.176896
2350.7812990.4374020.218701
2360.7304270.5391460.269573
2370.8060710.3878580.193929
2380.853780.292440.14622
2390.8173760.3652470.182624
2400.7646490.4707010.235351
2410.8171370.3657250.182863
2420.9018140.1963710.0981856
2430.8824030.2351940.117597
2440.8703270.2593460.129673
2450.9202280.1595450.0797723
2460.8769470.2461060.123053
2470.8354490.3291010.164551
2480.9043760.1912480.0956239
2490.8423430.3153140.157657
2500.8514910.2970180.148509
2510.7968110.4063790.203189
2520.7870640.4258710.212936
2530.6646860.6706280.335314

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.0798099 & 0.15962 & 0.92019 \tabularnewline
12 & 0.971915 & 0.0561701 & 0.028085 \tabularnewline
13 & 0.949847 & 0.100305 & 0.0501526 \tabularnewline
14 & 0.936102 & 0.127795 & 0.0638977 \tabularnewline
15 & 0.940631 & 0.118737 & 0.0593686 \tabularnewline
16 & 0.960797 & 0.0784064 & 0.0392032 \tabularnewline
17 & 0.951607 & 0.0967861 & 0.048393 \tabularnewline
18 & 0.970447 & 0.0591054 & 0.0295527 \tabularnewline
19 & 0.958675 & 0.0826508 & 0.0413254 \tabularnewline
20 & 0.970091 & 0.0598175 & 0.0299087 \tabularnewline
21 & 0.962336 & 0.0753289 & 0.0376644 \tabularnewline
22 & 0.950742 & 0.0985157 & 0.0492578 \tabularnewline
23 & 0.952663 & 0.0946748 & 0.0473374 \tabularnewline
24 & 0.937523 & 0.124953 & 0.0624767 \tabularnewline
25 & 0.964683 & 0.0706344 & 0.0353172 \tabularnewline
26 & 0.967233 & 0.065533 & 0.0327665 \tabularnewline
27 & 0.959383 & 0.0812344 & 0.0406172 \tabularnewline
28 & 0.944979 & 0.110042 & 0.0550212 \tabularnewline
29 & 0.936174 & 0.127652 & 0.0638258 \tabularnewline
30 & 0.914827 & 0.170347 & 0.0851733 \tabularnewline
31 & 0.891147 & 0.217706 & 0.108853 \tabularnewline
32 & 0.890057 & 0.219886 & 0.109943 \tabularnewline
33 & 0.863546 & 0.272908 & 0.136454 \tabularnewline
34 & 0.88244 & 0.235119 & 0.11756 \tabularnewline
35 & 0.853366 & 0.293267 & 0.146634 \tabularnewline
36 & 0.819043 & 0.361914 & 0.180957 \tabularnewline
37 & 0.788583 & 0.422835 & 0.211417 \tabularnewline
38 & 0.749112 & 0.501776 & 0.250888 \tabularnewline
39 & 0.704759 & 0.590483 & 0.295241 \tabularnewline
40 & 0.660056 & 0.679888 & 0.339944 \tabularnewline
41 & 0.610191 & 0.779618 & 0.389809 \tabularnewline
42 & 0.563161 & 0.873678 & 0.436839 \tabularnewline
43 & 0.778113 & 0.443775 & 0.221887 \tabularnewline
44 & 0.807751 & 0.384498 & 0.192249 \tabularnewline
45 & 0.77357 & 0.45286 & 0.22643 \tabularnewline
46 & 0.736122 & 0.527757 & 0.263878 \tabularnewline
47 & 0.711225 & 0.57755 & 0.288775 \tabularnewline
48 & 0.681334 & 0.637332 & 0.318666 \tabularnewline
49 & 0.658569 & 0.682863 & 0.341431 \tabularnewline
50 & 0.626779 & 0.746442 & 0.373221 \tabularnewline
51 & 0.581758 & 0.836484 & 0.418242 \tabularnewline
52 & 0.536295 & 0.927411 & 0.463705 \tabularnewline
53 & 0.489812 & 0.979624 & 0.510188 \tabularnewline
54 & 0.452449 & 0.904899 & 0.547551 \tabularnewline
55 & 0.412342 & 0.824684 & 0.587658 \tabularnewline
56 & 0.416704 & 0.833407 & 0.583296 \tabularnewline
57 & 0.376817 & 0.753633 & 0.623183 \tabularnewline
58 & 0.347043 & 0.694087 & 0.652957 \tabularnewline
59 & 0.317116 & 0.634233 & 0.682884 \tabularnewline
60 & 0.285242 & 0.570484 & 0.714758 \tabularnewline
61 & 0.264446 & 0.528892 & 0.735554 \tabularnewline
62 & 0.24934 & 0.498679 & 0.75066 \tabularnewline
63 & 0.26141 & 0.52282 & 0.73859 \tabularnewline
64 & 0.334494 & 0.668989 & 0.665506 \tabularnewline
65 & 0.413745 & 0.827489 & 0.586255 \tabularnewline
66 & 0.431968 & 0.863936 & 0.568032 \tabularnewline
67 & 0.391926 & 0.783852 & 0.608074 \tabularnewline
68 & 0.358463 & 0.716926 & 0.641537 \tabularnewline
69 & 0.340544 & 0.681088 & 0.659456 \tabularnewline
70 & 0.304854 & 0.609707 & 0.695146 \tabularnewline
71 & 0.271932 & 0.543863 & 0.728068 \tabularnewline
72 & 0.30541 & 0.61082 & 0.69459 \tabularnewline
73 & 0.316252 & 0.632505 & 0.683748 \tabularnewline
74 & 0.291184 & 0.582367 & 0.708816 \tabularnewline
75 & 0.30291 & 0.60582 & 0.69709 \tabularnewline
76 & 0.337041 & 0.674082 & 0.662959 \tabularnewline
77 & 0.305387 & 0.610773 & 0.694613 \tabularnewline
78 & 0.270992 & 0.541984 & 0.729008 \tabularnewline
79 & 0.253419 & 0.506839 & 0.746581 \tabularnewline
80 & 0.391597 & 0.783193 & 0.608403 \tabularnewline
81 & 0.372842 & 0.745685 & 0.627158 \tabularnewline
82 & 0.341706 & 0.683412 & 0.658294 \tabularnewline
83 & 0.307318 & 0.614636 & 0.692682 \tabularnewline
84 & 0.274607 & 0.549214 & 0.725393 \tabularnewline
85 & 0.253904 & 0.507807 & 0.746096 \tabularnewline
86 & 0.231616 & 0.463231 & 0.768384 \tabularnewline
87 & 0.206438 & 0.412876 & 0.793562 \tabularnewline
88 & 0.248657 & 0.497315 & 0.751343 \tabularnewline
89 & 0.242354 & 0.484709 & 0.757646 \tabularnewline
90 & 0.216417 & 0.432835 & 0.783583 \tabularnewline
91 & 0.278041 & 0.556083 & 0.721959 \tabularnewline
92 & 0.257649 & 0.515299 & 0.742351 \tabularnewline
93 & 0.273607 & 0.547213 & 0.726393 \tabularnewline
94 & 0.272491 & 0.544982 & 0.727509 \tabularnewline
95 & 0.250775 & 0.501549 & 0.749225 \tabularnewline
96 & 0.222016 & 0.444032 & 0.777984 \tabularnewline
97 & 0.199714 & 0.399427 & 0.800286 \tabularnewline
98 & 0.180676 & 0.361351 & 0.819324 \tabularnewline
99 & 0.158195 & 0.31639 & 0.841805 \tabularnewline
100 & 0.137421 & 0.274842 & 0.862579 \tabularnewline
101 & 0.119651 & 0.239302 & 0.880349 \tabularnewline
102 & 0.115373 & 0.230745 & 0.884627 \tabularnewline
103 & 0.104693 & 0.209386 & 0.895307 \tabularnewline
104 & 0.0977338 & 0.195468 & 0.902266 \tabularnewline
105 & 0.0830667 & 0.166133 & 0.916933 \tabularnewline
106 & 0.0698076 & 0.139615 & 0.930192 \tabularnewline
107 & 0.0587111 & 0.117422 & 0.941289 \tabularnewline
108 & 0.0781836 & 0.156367 & 0.921816 \tabularnewline
109 & 0.10475 & 0.2095 & 0.89525 \tabularnewline
110 & 0.113568 & 0.227136 & 0.886432 \tabularnewline
111 & 0.0991405 & 0.198281 & 0.90086 \tabularnewline
112 & 0.118228 & 0.236457 & 0.881772 \tabularnewline
113 & 0.407862 & 0.815724 & 0.592138 \tabularnewline
114 & 0.375031 & 0.750062 & 0.624969 \tabularnewline
115 & 0.361828 & 0.723657 & 0.638172 \tabularnewline
116 & 0.448407 & 0.896815 & 0.551593 \tabularnewline
117 & 0.425253 & 0.850505 & 0.574747 \tabularnewline
118 & 0.405187 & 0.810373 & 0.594813 \tabularnewline
119 & 0.482178 & 0.964355 & 0.517822 \tabularnewline
120 & 0.543828 & 0.912343 & 0.456172 \tabularnewline
121 & 0.511886 & 0.976228 & 0.488114 \tabularnewline
122 & 0.551449 & 0.897103 & 0.448551 \tabularnewline
123 & 0.520033 & 0.959934 & 0.479967 \tabularnewline
124 & 0.487963 & 0.975926 & 0.512037 \tabularnewline
125 & 0.458348 & 0.916695 & 0.541652 \tabularnewline
126 & 0.46267 & 0.925341 & 0.53733 \tabularnewline
127 & 0.440458 & 0.880916 & 0.559542 \tabularnewline
128 & 0.40814 & 0.81628 & 0.59186 \tabularnewline
129 & 0.375229 & 0.750457 & 0.624771 \tabularnewline
130 & 0.345919 & 0.691838 & 0.654081 \tabularnewline
131 & 0.318913 & 0.637826 & 0.681087 \tabularnewline
132 & 0.287496 & 0.574992 & 0.712504 \tabularnewline
133 & 0.270183 & 0.540365 & 0.729817 \tabularnewline
134 & 0.243382 & 0.486765 & 0.756618 \tabularnewline
135 & 0.249627 & 0.499254 & 0.750373 \tabularnewline
136 & 0.244981 & 0.489961 & 0.755019 \tabularnewline
137 & 0.248084 & 0.496169 & 0.751916 \tabularnewline
138 & 0.286339 & 0.572678 & 0.713661 \tabularnewline
139 & 0.296183 & 0.592365 & 0.703817 \tabularnewline
140 & 0.275313 & 0.550626 & 0.724687 \tabularnewline
141 & 0.417506 & 0.835012 & 0.582494 \tabularnewline
142 & 0.421285 & 0.84257 & 0.578715 \tabularnewline
143 & 0.42353 & 0.84706 & 0.57647 \tabularnewline
144 & 0.394768 & 0.789537 & 0.605232 \tabularnewline
145 & 0.427319 & 0.854637 & 0.572681 \tabularnewline
146 & 0.39826 & 0.796519 & 0.60174 \tabularnewline
147 & 0.430409 & 0.860817 & 0.569591 \tabularnewline
148 & 0.395379 & 0.790757 & 0.604621 \tabularnewline
149 & 0.381177 & 0.762355 & 0.618823 \tabularnewline
150 & 0.380749 & 0.761498 & 0.619251 \tabularnewline
151 & 0.361253 & 0.722506 & 0.638747 \tabularnewline
152 & 0.348119 & 0.696239 & 0.651881 \tabularnewline
153 & 0.318763 & 0.637527 & 0.681237 \tabularnewline
154 & 0.289112 & 0.578224 & 0.710888 \tabularnewline
155 & 0.288591 & 0.577182 & 0.711409 \tabularnewline
156 & 0.38544 & 0.770881 & 0.61456 \tabularnewline
157 & 0.357603 & 0.715206 & 0.642397 \tabularnewline
158 & 0.326241 & 0.652482 & 0.673759 \tabularnewline
159 & 0.312068 & 0.624136 & 0.687932 \tabularnewline
160 & 0.35771 & 0.71542 & 0.64229 \tabularnewline
161 & 0.325464 & 0.650928 & 0.674536 \tabularnewline
162 & 0.302557 & 0.605113 & 0.697443 \tabularnewline
163 & 0.310538 & 0.621076 & 0.689462 \tabularnewline
164 & 0.339241 & 0.678481 & 0.660759 \tabularnewline
165 & 0.309706 & 0.619412 & 0.690294 \tabularnewline
166 & 0.296297 & 0.592594 & 0.703703 \tabularnewline
167 & 0.270567 & 0.541134 & 0.729433 \tabularnewline
168 & 0.250528 & 0.501055 & 0.749472 \tabularnewline
169 & 0.267129 & 0.534259 & 0.732871 \tabularnewline
170 & 0.247453 & 0.494906 & 0.752547 \tabularnewline
171 & 0.248383 & 0.496767 & 0.751617 \tabularnewline
172 & 0.226083 & 0.452166 & 0.773917 \tabularnewline
173 & 0.206644 & 0.413287 & 0.793356 \tabularnewline
174 & 0.194346 & 0.388693 & 0.805654 \tabularnewline
175 & 0.172916 & 0.345833 & 0.827084 \tabularnewline
176 & 0.150699 & 0.301398 & 0.849301 \tabularnewline
177 & 0.129492 & 0.258985 & 0.870508 \tabularnewline
178 & 0.112765 & 0.22553 & 0.887235 \tabularnewline
179 & 0.107923 & 0.215846 & 0.892077 \tabularnewline
180 & 0.0919228 & 0.183846 & 0.908077 \tabularnewline
181 & 0.170425 & 0.340851 & 0.829575 \tabularnewline
182 & 0.161689 & 0.323379 & 0.838311 \tabularnewline
183 & 0.149353 & 0.298707 & 0.850647 \tabularnewline
184 & 0.131147 & 0.262294 & 0.868853 \tabularnewline
185 & 0.195699 & 0.391398 & 0.804301 \tabularnewline
186 & 0.19262 & 0.385239 & 0.80738 \tabularnewline
187 & 0.167964 & 0.335928 & 0.832036 \tabularnewline
188 & 0.194221 & 0.388441 & 0.805779 \tabularnewline
189 & 0.217523 & 0.435047 & 0.782477 \tabularnewline
190 & 0.192619 & 0.385238 & 0.807381 \tabularnewline
191 & 0.622427 & 0.755146 & 0.377573 \tabularnewline
192 & 0.593743 & 0.812515 & 0.406257 \tabularnewline
193 & 0.554917 & 0.890166 & 0.445083 \tabularnewline
194 & 0.562143 & 0.875713 & 0.437857 \tabularnewline
195 & 0.522363 & 0.955273 & 0.477637 \tabularnewline
196 & 0.507161 & 0.985678 & 0.492839 \tabularnewline
197 & 0.562081 & 0.875839 & 0.437919 \tabularnewline
198 & 0.619387 & 0.761226 & 0.380613 \tabularnewline
199 & 0.58599 & 0.828019 & 0.41401 \tabularnewline
200 & 0.559424 & 0.881153 & 0.440576 \tabularnewline
201 & 0.521224 & 0.957551 & 0.478776 \tabularnewline
202 & 0.481047 & 0.962094 & 0.518953 \tabularnewline
203 & 0.449391 & 0.898782 & 0.550609 \tabularnewline
204 & 0.524617 & 0.950767 & 0.475383 \tabularnewline
205 & 0.483565 & 0.967129 & 0.516435 \tabularnewline
206 & 0.439938 & 0.879875 & 0.560062 \tabularnewline
207 & 0.43923 & 0.87846 & 0.56077 \tabularnewline
208 & 0.563445 & 0.87311 & 0.436555 \tabularnewline
209 & 0.518672 & 0.962656 & 0.481328 \tabularnewline
210 & 0.542682 & 0.914636 & 0.457318 \tabularnewline
211 & 0.50771 & 0.984579 & 0.49229 \tabularnewline
212 & 0.467229 & 0.934457 & 0.532771 \tabularnewline
213 & 0.591062 & 0.817876 & 0.408938 \tabularnewline
214 & 0.585309 & 0.829381 & 0.414691 \tabularnewline
215 & 0.539441 & 0.921117 & 0.460559 \tabularnewline
216 & 0.50209 & 0.995819 & 0.49791 \tabularnewline
217 & 0.576078 & 0.847845 & 0.423922 \tabularnewline
218 & 0.61397 & 0.77206 & 0.38603 \tabularnewline
219 & 0.567653 & 0.864694 & 0.432347 \tabularnewline
220 & 0.646558 & 0.706883 & 0.353442 \tabularnewline
221 & 0.618719 & 0.762562 & 0.381281 \tabularnewline
222 & 0.630754 & 0.738492 & 0.369246 \tabularnewline
223 & 0.649087 & 0.701826 & 0.350913 \tabularnewline
224 & 0.603782 & 0.792436 & 0.396218 \tabularnewline
225 & 0.823762 & 0.352477 & 0.176238 \tabularnewline
226 & 0.802949 & 0.394103 & 0.197051 \tabularnewline
227 & 0.829295 & 0.341409 & 0.170705 \tabularnewline
228 & 0.81776 & 0.36448 & 0.18224 \tabularnewline
229 & 0.795258 & 0.409483 & 0.204742 \tabularnewline
230 & 0.750343 & 0.499314 & 0.249657 \tabularnewline
231 & 0.704451 & 0.591099 & 0.295549 \tabularnewline
232 & 0.662288 & 0.675423 & 0.337712 \tabularnewline
233 & 0.82035 & 0.3593 & 0.17965 \tabularnewline
234 & 0.823104 & 0.353793 & 0.176896 \tabularnewline
235 & 0.781299 & 0.437402 & 0.218701 \tabularnewline
236 & 0.730427 & 0.539146 & 0.269573 \tabularnewline
237 & 0.806071 & 0.387858 & 0.193929 \tabularnewline
238 & 0.85378 & 0.29244 & 0.14622 \tabularnewline
239 & 0.817376 & 0.365247 & 0.182624 \tabularnewline
240 & 0.764649 & 0.470701 & 0.235351 \tabularnewline
241 & 0.817137 & 0.365725 & 0.182863 \tabularnewline
242 & 0.901814 & 0.196371 & 0.0981856 \tabularnewline
243 & 0.882403 & 0.235194 & 0.117597 \tabularnewline
244 & 0.870327 & 0.259346 & 0.129673 \tabularnewline
245 & 0.920228 & 0.159545 & 0.0797723 \tabularnewline
246 & 0.876947 & 0.246106 & 0.123053 \tabularnewline
247 & 0.835449 & 0.329101 & 0.164551 \tabularnewline
248 & 0.904376 & 0.191248 & 0.0956239 \tabularnewline
249 & 0.842343 & 0.315314 & 0.157657 \tabularnewline
250 & 0.851491 & 0.297018 & 0.148509 \tabularnewline
251 & 0.796811 & 0.406379 & 0.203189 \tabularnewline
252 & 0.787064 & 0.425871 & 0.212936 \tabularnewline
253 & 0.664686 & 0.670628 & 0.335314 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253224&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]11[/C][C]0.0798099[/C][C]0.15962[/C][C]0.92019[/C][/ROW]
[ROW][C]12[/C][C]0.971915[/C][C]0.0561701[/C][C]0.028085[/C][/ROW]
[ROW][C]13[/C][C]0.949847[/C][C]0.100305[/C][C]0.0501526[/C][/ROW]
[ROW][C]14[/C][C]0.936102[/C][C]0.127795[/C][C]0.0638977[/C][/ROW]
[ROW][C]15[/C][C]0.940631[/C][C]0.118737[/C][C]0.0593686[/C][/ROW]
[ROW][C]16[/C][C]0.960797[/C][C]0.0784064[/C][C]0.0392032[/C][/ROW]
[ROW][C]17[/C][C]0.951607[/C][C]0.0967861[/C][C]0.048393[/C][/ROW]
[ROW][C]18[/C][C]0.970447[/C][C]0.0591054[/C][C]0.0295527[/C][/ROW]
[ROW][C]19[/C][C]0.958675[/C][C]0.0826508[/C][C]0.0413254[/C][/ROW]
[ROW][C]20[/C][C]0.970091[/C][C]0.0598175[/C][C]0.0299087[/C][/ROW]
[ROW][C]21[/C][C]0.962336[/C][C]0.0753289[/C][C]0.0376644[/C][/ROW]
[ROW][C]22[/C][C]0.950742[/C][C]0.0985157[/C][C]0.0492578[/C][/ROW]
[ROW][C]23[/C][C]0.952663[/C][C]0.0946748[/C][C]0.0473374[/C][/ROW]
[ROW][C]24[/C][C]0.937523[/C][C]0.124953[/C][C]0.0624767[/C][/ROW]
[ROW][C]25[/C][C]0.964683[/C][C]0.0706344[/C][C]0.0353172[/C][/ROW]
[ROW][C]26[/C][C]0.967233[/C][C]0.065533[/C][C]0.0327665[/C][/ROW]
[ROW][C]27[/C][C]0.959383[/C][C]0.0812344[/C][C]0.0406172[/C][/ROW]
[ROW][C]28[/C][C]0.944979[/C][C]0.110042[/C][C]0.0550212[/C][/ROW]
[ROW][C]29[/C][C]0.936174[/C][C]0.127652[/C][C]0.0638258[/C][/ROW]
[ROW][C]30[/C][C]0.914827[/C][C]0.170347[/C][C]0.0851733[/C][/ROW]
[ROW][C]31[/C][C]0.891147[/C][C]0.217706[/C][C]0.108853[/C][/ROW]
[ROW][C]32[/C][C]0.890057[/C][C]0.219886[/C][C]0.109943[/C][/ROW]
[ROW][C]33[/C][C]0.863546[/C][C]0.272908[/C][C]0.136454[/C][/ROW]
[ROW][C]34[/C][C]0.88244[/C][C]0.235119[/C][C]0.11756[/C][/ROW]
[ROW][C]35[/C][C]0.853366[/C][C]0.293267[/C][C]0.146634[/C][/ROW]
[ROW][C]36[/C][C]0.819043[/C][C]0.361914[/C][C]0.180957[/C][/ROW]
[ROW][C]37[/C][C]0.788583[/C][C]0.422835[/C][C]0.211417[/C][/ROW]
[ROW][C]38[/C][C]0.749112[/C][C]0.501776[/C][C]0.250888[/C][/ROW]
[ROW][C]39[/C][C]0.704759[/C][C]0.590483[/C][C]0.295241[/C][/ROW]
[ROW][C]40[/C][C]0.660056[/C][C]0.679888[/C][C]0.339944[/C][/ROW]
[ROW][C]41[/C][C]0.610191[/C][C]0.779618[/C][C]0.389809[/C][/ROW]
[ROW][C]42[/C][C]0.563161[/C][C]0.873678[/C][C]0.436839[/C][/ROW]
[ROW][C]43[/C][C]0.778113[/C][C]0.443775[/C][C]0.221887[/C][/ROW]
[ROW][C]44[/C][C]0.807751[/C][C]0.384498[/C][C]0.192249[/C][/ROW]
[ROW][C]45[/C][C]0.77357[/C][C]0.45286[/C][C]0.22643[/C][/ROW]
[ROW][C]46[/C][C]0.736122[/C][C]0.527757[/C][C]0.263878[/C][/ROW]
[ROW][C]47[/C][C]0.711225[/C][C]0.57755[/C][C]0.288775[/C][/ROW]
[ROW][C]48[/C][C]0.681334[/C][C]0.637332[/C][C]0.318666[/C][/ROW]
[ROW][C]49[/C][C]0.658569[/C][C]0.682863[/C][C]0.341431[/C][/ROW]
[ROW][C]50[/C][C]0.626779[/C][C]0.746442[/C][C]0.373221[/C][/ROW]
[ROW][C]51[/C][C]0.581758[/C][C]0.836484[/C][C]0.418242[/C][/ROW]
[ROW][C]52[/C][C]0.536295[/C][C]0.927411[/C][C]0.463705[/C][/ROW]
[ROW][C]53[/C][C]0.489812[/C][C]0.979624[/C][C]0.510188[/C][/ROW]
[ROW][C]54[/C][C]0.452449[/C][C]0.904899[/C][C]0.547551[/C][/ROW]
[ROW][C]55[/C][C]0.412342[/C][C]0.824684[/C][C]0.587658[/C][/ROW]
[ROW][C]56[/C][C]0.416704[/C][C]0.833407[/C][C]0.583296[/C][/ROW]
[ROW][C]57[/C][C]0.376817[/C][C]0.753633[/C][C]0.623183[/C][/ROW]
[ROW][C]58[/C][C]0.347043[/C][C]0.694087[/C][C]0.652957[/C][/ROW]
[ROW][C]59[/C][C]0.317116[/C][C]0.634233[/C][C]0.682884[/C][/ROW]
[ROW][C]60[/C][C]0.285242[/C][C]0.570484[/C][C]0.714758[/C][/ROW]
[ROW][C]61[/C][C]0.264446[/C][C]0.528892[/C][C]0.735554[/C][/ROW]
[ROW][C]62[/C][C]0.24934[/C][C]0.498679[/C][C]0.75066[/C][/ROW]
[ROW][C]63[/C][C]0.26141[/C][C]0.52282[/C][C]0.73859[/C][/ROW]
[ROW][C]64[/C][C]0.334494[/C][C]0.668989[/C][C]0.665506[/C][/ROW]
[ROW][C]65[/C][C]0.413745[/C][C]0.827489[/C][C]0.586255[/C][/ROW]
[ROW][C]66[/C][C]0.431968[/C][C]0.863936[/C][C]0.568032[/C][/ROW]
[ROW][C]67[/C][C]0.391926[/C][C]0.783852[/C][C]0.608074[/C][/ROW]
[ROW][C]68[/C][C]0.358463[/C][C]0.716926[/C][C]0.641537[/C][/ROW]
[ROW][C]69[/C][C]0.340544[/C][C]0.681088[/C][C]0.659456[/C][/ROW]
[ROW][C]70[/C][C]0.304854[/C][C]0.609707[/C][C]0.695146[/C][/ROW]
[ROW][C]71[/C][C]0.271932[/C][C]0.543863[/C][C]0.728068[/C][/ROW]
[ROW][C]72[/C][C]0.30541[/C][C]0.61082[/C][C]0.69459[/C][/ROW]
[ROW][C]73[/C][C]0.316252[/C][C]0.632505[/C][C]0.683748[/C][/ROW]
[ROW][C]74[/C][C]0.291184[/C][C]0.582367[/C][C]0.708816[/C][/ROW]
[ROW][C]75[/C][C]0.30291[/C][C]0.60582[/C][C]0.69709[/C][/ROW]
[ROW][C]76[/C][C]0.337041[/C][C]0.674082[/C][C]0.662959[/C][/ROW]
[ROW][C]77[/C][C]0.305387[/C][C]0.610773[/C][C]0.694613[/C][/ROW]
[ROW][C]78[/C][C]0.270992[/C][C]0.541984[/C][C]0.729008[/C][/ROW]
[ROW][C]79[/C][C]0.253419[/C][C]0.506839[/C][C]0.746581[/C][/ROW]
[ROW][C]80[/C][C]0.391597[/C][C]0.783193[/C][C]0.608403[/C][/ROW]
[ROW][C]81[/C][C]0.372842[/C][C]0.745685[/C][C]0.627158[/C][/ROW]
[ROW][C]82[/C][C]0.341706[/C][C]0.683412[/C][C]0.658294[/C][/ROW]
[ROW][C]83[/C][C]0.307318[/C][C]0.614636[/C][C]0.692682[/C][/ROW]
[ROW][C]84[/C][C]0.274607[/C][C]0.549214[/C][C]0.725393[/C][/ROW]
[ROW][C]85[/C][C]0.253904[/C][C]0.507807[/C][C]0.746096[/C][/ROW]
[ROW][C]86[/C][C]0.231616[/C][C]0.463231[/C][C]0.768384[/C][/ROW]
[ROW][C]87[/C][C]0.206438[/C][C]0.412876[/C][C]0.793562[/C][/ROW]
[ROW][C]88[/C][C]0.248657[/C][C]0.497315[/C][C]0.751343[/C][/ROW]
[ROW][C]89[/C][C]0.242354[/C][C]0.484709[/C][C]0.757646[/C][/ROW]
[ROW][C]90[/C][C]0.216417[/C][C]0.432835[/C][C]0.783583[/C][/ROW]
[ROW][C]91[/C][C]0.278041[/C][C]0.556083[/C][C]0.721959[/C][/ROW]
[ROW][C]92[/C][C]0.257649[/C][C]0.515299[/C][C]0.742351[/C][/ROW]
[ROW][C]93[/C][C]0.273607[/C][C]0.547213[/C][C]0.726393[/C][/ROW]
[ROW][C]94[/C][C]0.272491[/C][C]0.544982[/C][C]0.727509[/C][/ROW]
[ROW][C]95[/C][C]0.250775[/C][C]0.501549[/C][C]0.749225[/C][/ROW]
[ROW][C]96[/C][C]0.222016[/C][C]0.444032[/C][C]0.777984[/C][/ROW]
[ROW][C]97[/C][C]0.199714[/C][C]0.399427[/C][C]0.800286[/C][/ROW]
[ROW][C]98[/C][C]0.180676[/C][C]0.361351[/C][C]0.819324[/C][/ROW]
[ROW][C]99[/C][C]0.158195[/C][C]0.31639[/C][C]0.841805[/C][/ROW]
[ROW][C]100[/C][C]0.137421[/C][C]0.274842[/C][C]0.862579[/C][/ROW]
[ROW][C]101[/C][C]0.119651[/C][C]0.239302[/C][C]0.880349[/C][/ROW]
[ROW][C]102[/C][C]0.115373[/C][C]0.230745[/C][C]0.884627[/C][/ROW]
[ROW][C]103[/C][C]0.104693[/C][C]0.209386[/C][C]0.895307[/C][/ROW]
[ROW][C]104[/C][C]0.0977338[/C][C]0.195468[/C][C]0.902266[/C][/ROW]
[ROW][C]105[/C][C]0.0830667[/C][C]0.166133[/C][C]0.916933[/C][/ROW]
[ROW][C]106[/C][C]0.0698076[/C][C]0.139615[/C][C]0.930192[/C][/ROW]
[ROW][C]107[/C][C]0.0587111[/C][C]0.117422[/C][C]0.941289[/C][/ROW]
[ROW][C]108[/C][C]0.0781836[/C][C]0.156367[/C][C]0.921816[/C][/ROW]
[ROW][C]109[/C][C]0.10475[/C][C]0.2095[/C][C]0.89525[/C][/ROW]
[ROW][C]110[/C][C]0.113568[/C][C]0.227136[/C][C]0.886432[/C][/ROW]
[ROW][C]111[/C][C]0.0991405[/C][C]0.198281[/C][C]0.90086[/C][/ROW]
[ROW][C]112[/C][C]0.118228[/C][C]0.236457[/C][C]0.881772[/C][/ROW]
[ROW][C]113[/C][C]0.407862[/C][C]0.815724[/C][C]0.592138[/C][/ROW]
[ROW][C]114[/C][C]0.375031[/C][C]0.750062[/C][C]0.624969[/C][/ROW]
[ROW][C]115[/C][C]0.361828[/C][C]0.723657[/C][C]0.638172[/C][/ROW]
[ROW][C]116[/C][C]0.448407[/C][C]0.896815[/C][C]0.551593[/C][/ROW]
[ROW][C]117[/C][C]0.425253[/C][C]0.850505[/C][C]0.574747[/C][/ROW]
[ROW][C]118[/C][C]0.405187[/C][C]0.810373[/C][C]0.594813[/C][/ROW]
[ROW][C]119[/C][C]0.482178[/C][C]0.964355[/C][C]0.517822[/C][/ROW]
[ROW][C]120[/C][C]0.543828[/C][C]0.912343[/C][C]0.456172[/C][/ROW]
[ROW][C]121[/C][C]0.511886[/C][C]0.976228[/C][C]0.488114[/C][/ROW]
[ROW][C]122[/C][C]0.551449[/C][C]0.897103[/C][C]0.448551[/C][/ROW]
[ROW][C]123[/C][C]0.520033[/C][C]0.959934[/C][C]0.479967[/C][/ROW]
[ROW][C]124[/C][C]0.487963[/C][C]0.975926[/C][C]0.512037[/C][/ROW]
[ROW][C]125[/C][C]0.458348[/C][C]0.916695[/C][C]0.541652[/C][/ROW]
[ROW][C]126[/C][C]0.46267[/C][C]0.925341[/C][C]0.53733[/C][/ROW]
[ROW][C]127[/C][C]0.440458[/C][C]0.880916[/C][C]0.559542[/C][/ROW]
[ROW][C]128[/C][C]0.40814[/C][C]0.81628[/C][C]0.59186[/C][/ROW]
[ROW][C]129[/C][C]0.375229[/C][C]0.750457[/C][C]0.624771[/C][/ROW]
[ROW][C]130[/C][C]0.345919[/C][C]0.691838[/C][C]0.654081[/C][/ROW]
[ROW][C]131[/C][C]0.318913[/C][C]0.637826[/C][C]0.681087[/C][/ROW]
[ROW][C]132[/C][C]0.287496[/C][C]0.574992[/C][C]0.712504[/C][/ROW]
[ROW][C]133[/C][C]0.270183[/C][C]0.540365[/C][C]0.729817[/C][/ROW]
[ROW][C]134[/C][C]0.243382[/C][C]0.486765[/C][C]0.756618[/C][/ROW]
[ROW][C]135[/C][C]0.249627[/C][C]0.499254[/C][C]0.750373[/C][/ROW]
[ROW][C]136[/C][C]0.244981[/C][C]0.489961[/C][C]0.755019[/C][/ROW]
[ROW][C]137[/C][C]0.248084[/C][C]0.496169[/C][C]0.751916[/C][/ROW]
[ROW][C]138[/C][C]0.286339[/C][C]0.572678[/C][C]0.713661[/C][/ROW]
[ROW][C]139[/C][C]0.296183[/C][C]0.592365[/C][C]0.703817[/C][/ROW]
[ROW][C]140[/C][C]0.275313[/C][C]0.550626[/C][C]0.724687[/C][/ROW]
[ROW][C]141[/C][C]0.417506[/C][C]0.835012[/C][C]0.582494[/C][/ROW]
[ROW][C]142[/C][C]0.421285[/C][C]0.84257[/C][C]0.578715[/C][/ROW]
[ROW][C]143[/C][C]0.42353[/C][C]0.84706[/C][C]0.57647[/C][/ROW]
[ROW][C]144[/C][C]0.394768[/C][C]0.789537[/C][C]0.605232[/C][/ROW]
[ROW][C]145[/C][C]0.427319[/C][C]0.854637[/C][C]0.572681[/C][/ROW]
[ROW][C]146[/C][C]0.39826[/C][C]0.796519[/C][C]0.60174[/C][/ROW]
[ROW][C]147[/C][C]0.430409[/C][C]0.860817[/C][C]0.569591[/C][/ROW]
[ROW][C]148[/C][C]0.395379[/C][C]0.790757[/C][C]0.604621[/C][/ROW]
[ROW][C]149[/C][C]0.381177[/C][C]0.762355[/C][C]0.618823[/C][/ROW]
[ROW][C]150[/C][C]0.380749[/C][C]0.761498[/C][C]0.619251[/C][/ROW]
[ROW][C]151[/C][C]0.361253[/C][C]0.722506[/C][C]0.638747[/C][/ROW]
[ROW][C]152[/C][C]0.348119[/C][C]0.696239[/C][C]0.651881[/C][/ROW]
[ROW][C]153[/C][C]0.318763[/C][C]0.637527[/C][C]0.681237[/C][/ROW]
[ROW][C]154[/C][C]0.289112[/C][C]0.578224[/C][C]0.710888[/C][/ROW]
[ROW][C]155[/C][C]0.288591[/C][C]0.577182[/C][C]0.711409[/C][/ROW]
[ROW][C]156[/C][C]0.38544[/C][C]0.770881[/C][C]0.61456[/C][/ROW]
[ROW][C]157[/C][C]0.357603[/C][C]0.715206[/C][C]0.642397[/C][/ROW]
[ROW][C]158[/C][C]0.326241[/C][C]0.652482[/C][C]0.673759[/C][/ROW]
[ROW][C]159[/C][C]0.312068[/C][C]0.624136[/C][C]0.687932[/C][/ROW]
[ROW][C]160[/C][C]0.35771[/C][C]0.71542[/C][C]0.64229[/C][/ROW]
[ROW][C]161[/C][C]0.325464[/C][C]0.650928[/C][C]0.674536[/C][/ROW]
[ROW][C]162[/C][C]0.302557[/C][C]0.605113[/C][C]0.697443[/C][/ROW]
[ROW][C]163[/C][C]0.310538[/C][C]0.621076[/C][C]0.689462[/C][/ROW]
[ROW][C]164[/C][C]0.339241[/C][C]0.678481[/C][C]0.660759[/C][/ROW]
[ROW][C]165[/C][C]0.309706[/C][C]0.619412[/C][C]0.690294[/C][/ROW]
[ROW][C]166[/C][C]0.296297[/C][C]0.592594[/C][C]0.703703[/C][/ROW]
[ROW][C]167[/C][C]0.270567[/C][C]0.541134[/C][C]0.729433[/C][/ROW]
[ROW][C]168[/C][C]0.250528[/C][C]0.501055[/C][C]0.749472[/C][/ROW]
[ROW][C]169[/C][C]0.267129[/C][C]0.534259[/C][C]0.732871[/C][/ROW]
[ROW][C]170[/C][C]0.247453[/C][C]0.494906[/C][C]0.752547[/C][/ROW]
[ROW][C]171[/C][C]0.248383[/C][C]0.496767[/C][C]0.751617[/C][/ROW]
[ROW][C]172[/C][C]0.226083[/C][C]0.452166[/C][C]0.773917[/C][/ROW]
[ROW][C]173[/C][C]0.206644[/C][C]0.413287[/C][C]0.793356[/C][/ROW]
[ROW][C]174[/C][C]0.194346[/C][C]0.388693[/C][C]0.805654[/C][/ROW]
[ROW][C]175[/C][C]0.172916[/C][C]0.345833[/C][C]0.827084[/C][/ROW]
[ROW][C]176[/C][C]0.150699[/C][C]0.301398[/C][C]0.849301[/C][/ROW]
[ROW][C]177[/C][C]0.129492[/C][C]0.258985[/C][C]0.870508[/C][/ROW]
[ROW][C]178[/C][C]0.112765[/C][C]0.22553[/C][C]0.887235[/C][/ROW]
[ROW][C]179[/C][C]0.107923[/C][C]0.215846[/C][C]0.892077[/C][/ROW]
[ROW][C]180[/C][C]0.0919228[/C][C]0.183846[/C][C]0.908077[/C][/ROW]
[ROW][C]181[/C][C]0.170425[/C][C]0.340851[/C][C]0.829575[/C][/ROW]
[ROW][C]182[/C][C]0.161689[/C][C]0.323379[/C][C]0.838311[/C][/ROW]
[ROW][C]183[/C][C]0.149353[/C][C]0.298707[/C][C]0.850647[/C][/ROW]
[ROW][C]184[/C][C]0.131147[/C][C]0.262294[/C][C]0.868853[/C][/ROW]
[ROW][C]185[/C][C]0.195699[/C][C]0.391398[/C][C]0.804301[/C][/ROW]
[ROW][C]186[/C][C]0.19262[/C][C]0.385239[/C][C]0.80738[/C][/ROW]
[ROW][C]187[/C][C]0.167964[/C][C]0.335928[/C][C]0.832036[/C][/ROW]
[ROW][C]188[/C][C]0.194221[/C][C]0.388441[/C][C]0.805779[/C][/ROW]
[ROW][C]189[/C][C]0.217523[/C][C]0.435047[/C][C]0.782477[/C][/ROW]
[ROW][C]190[/C][C]0.192619[/C][C]0.385238[/C][C]0.807381[/C][/ROW]
[ROW][C]191[/C][C]0.622427[/C][C]0.755146[/C][C]0.377573[/C][/ROW]
[ROW][C]192[/C][C]0.593743[/C][C]0.812515[/C][C]0.406257[/C][/ROW]
[ROW][C]193[/C][C]0.554917[/C][C]0.890166[/C][C]0.445083[/C][/ROW]
[ROW][C]194[/C][C]0.562143[/C][C]0.875713[/C][C]0.437857[/C][/ROW]
[ROW][C]195[/C][C]0.522363[/C][C]0.955273[/C][C]0.477637[/C][/ROW]
[ROW][C]196[/C][C]0.507161[/C][C]0.985678[/C][C]0.492839[/C][/ROW]
[ROW][C]197[/C][C]0.562081[/C][C]0.875839[/C][C]0.437919[/C][/ROW]
[ROW][C]198[/C][C]0.619387[/C][C]0.761226[/C][C]0.380613[/C][/ROW]
[ROW][C]199[/C][C]0.58599[/C][C]0.828019[/C][C]0.41401[/C][/ROW]
[ROW][C]200[/C][C]0.559424[/C][C]0.881153[/C][C]0.440576[/C][/ROW]
[ROW][C]201[/C][C]0.521224[/C][C]0.957551[/C][C]0.478776[/C][/ROW]
[ROW][C]202[/C][C]0.481047[/C][C]0.962094[/C][C]0.518953[/C][/ROW]
[ROW][C]203[/C][C]0.449391[/C][C]0.898782[/C][C]0.550609[/C][/ROW]
[ROW][C]204[/C][C]0.524617[/C][C]0.950767[/C][C]0.475383[/C][/ROW]
[ROW][C]205[/C][C]0.483565[/C][C]0.967129[/C][C]0.516435[/C][/ROW]
[ROW][C]206[/C][C]0.439938[/C][C]0.879875[/C][C]0.560062[/C][/ROW]
[ROW][C]207[/C][C]0.43923[/C][C]0.87846[/C][C]0.56077[/C][/ROW]
[ROW][C]208[/C][C]0.563445[/C][C]0.87311[/C][C]0.436555[/C][/ROW]
[ROW][C]209[/C][C]0.518672[/C][C]0.962656[/C][C]0.481328[/C][/ROW]
[ROW][C]210[/C][C]0.542682[/C][C]0.914636[/C][C]0.457318[/C][/ROW]
[ROW][C]211[/C][C]0.50771[/C][C]0.984579[/C][C]0.49229[/C][/ROW]
[ROW][C]212[/C][C]0.467229[/C][C]0.934457[/C][C]0.532771[/C][/ROW]
[ROW][C]213[/C][C]0.591062[/C][C]0.817876[/C][C]0.408938[/C][/ROW]
[ROW][C]214[/C][C]0.585309[/C][C]0.829381[/C][C]0.414691[/C][/ROW]
[ROW][C]215[/C][C]0.539441[/C][C]0.921117[/C][C]0.460559[/C][/ROW]
[ROW][C]216[/C][C]0.50209[/C][C]0.995819[/C][C]0.49791[/C][/ROW]
[ROW][C]217[/C][C]0.576078[/C][C]0.847845[/C][C]0.423922[/C][/ROW]
[ROW][C]218[/C][C]0.61397[/C][C]0.77206[/C][C]0.38603[/C][/ROW]
[ROW][C]219[/C][C]0.567653[/C][C]0.864694[/C][C]0.432347[/C][/ROW]
[ROW][C]220[/C][C]0.646558[/C][C]0.706883[/C][C]0.353442[/C][/ROW]
[ROW][C]221[/C][C]0.618719[/C][C]0.762562[/C][C]0.381281[/C][/ROW]
[ROW][C]222[/C][C]0.630754[/C][C]0.738492[/C][C]0.369246[/C][/ROW]
[ROW][C]223[/C][C]0.649087[/C][C]0.701826[/C][C]0.350913[/C][/ROW]
[ROW][C]224[/C][C]0.603782[/C][C]0.792436[/C][C]0.396218[/C][/ROW]
[ROW][C]225[/C][C]0.823762[/C][C]0.352477[/C][C]0.176238[/C][/ROW]
[ROW][C]226[/C][C]0.802949[/C][C]0.394103[/C][C]0.197051[/C][/ROW]
[ROW][C]227[/C][C]0.829295[/C][C]0.341409[/C][C]0.170705[/C][/ROW]
[ROW][C]228[/C][C]0.81776[/C][C]0.36448[/C][C]0.18224[/C][/ROW]
[ROW][C]229[/C][C]0.795258[/C][C]0.409483[/C][C]0.204742[/C][/ROW]
[ROW][C]230[/C][C]0.750343[/C][C]0.499314[/C][C]0.249657[/C][/ROW]
[ROW][C]231[/C][C]0.704451[/C][C]0.591099[/C][C]0.295549[/C][/ROW]
[ROW][C]232[/C][C]0.662288[/C][C]0.675423[/C][C]0.337712[/C][/ROW]
[ROW][C]233[/C][C]0.82035[/C][C]0.3593[/C][C]0.17965[/C][/ROW]
[ROW][C]234[/C][C]0.823104[/C][C]0.353793[/C][C]0.176896[/C][/ROW]
[ROW][C]235[/C][C]0.781299[/C][C]0.437402[/C][C]0.218701[/C][/ROW]
[ROW][C]236[/C][C]0.730427[/C][C]0.539146[/C][C]0.269573[/C][/ROW]
[ROW][C]237[/C][C]0.806071[/C][C]0.387858[/C][C]0.193929[/C][/ROW]
[ROW][C]238[/C][C]0.85378[/C][C]0.29244[/C][C]0.14622[/C][/ROW]
[ROW][C]239[/C][C]0.817376[/C][C]0.365247[/C][C]0.182624[/C][/ROW]
[ROW][C]240[/C][C]0.764649[/C][C]0.470701[/C][C]0.235351[/C][/ROW]
[ROW][C]241[/C][C]0.817137[/C][C]0.365725[/C][C]0.182863[/C][/ROW]
[ROW][C]242[/C][C]0.901814[/C][C]0.196371[/C][C]0.0981856[/C][/ROW]
[ROW][C]243[/C][C]0.882403[/C][C]0.235194[/C][C]0.117597[/C][/ROW]
[ROW][C]244[/C][C]0.870327[/C][C]0.259346[/C][C]0.129673[/C][/ROW]
[ROW][C]245[/C][C]0.920228[/C][C]0.159545[/C][C]0.0797723[/C][/ROW]
[ROW][C]246[/C][C]0.876947[/C][C]0.246106[/C][C]0.123053[/C][/ROW]
[ROW][C]247[/C][C]0.835449[/C][C]0.329101[/C][C]0.164551[/C][/ROW]
[ROW][C]248[/C][C]0.904376[/C][C]0.191248[/C][C]0.0956239[/C][/ROW]
[ROW][C]249[/C][C]0.842343[/C][C]0.315314[/C][C]0.157657[/C][/ROW]
[ROW][C]250[/C][C]0.851491[/C][C]0.297018[/C][C]0.148509[/C][/ROW]
[ROW][C]251[/C][C]0.796811[/C][C]0.406379[/C][C]0.203189[/C][/ROW]
[ROW][C]252[/C][C]0.787064[/C][C]0.425871[/C][C]0.212936[/C][/ROW]
[ROW][C]253[/C][C]0.664686[/C][C]0.670628[/C][C]0.335314[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253224&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253224&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.07980990.159620.92019
120.9719150.05617010.028085
130.9498470.1003050.0501526
140.9361020.1277950.0638977
150.9406310.1187370.0593686
160.9607970.07840640.0392032
170.9516070.09678610.048393
180.9704470.05910540.0295527
190.9586750.08265080.0413254
200.9700910.05981750.0299087
210.9623360.07532890.0376644
220.9507420.09851570.0492578
230.9526630.09467480.0473374
240.9375230.1249530.0624767
250.9646830.07063440.0353172
260.9672330.0655330.0327665
270.9593830.08123440.0406172
280.9449790.1100420.0550212
290.9361740.1276520.0638258
300.9148270.1703470.0851733
310.8911470.2177060.108853
320.8900570.2198860.109943
330.8635460.2729080.136454
340.882440.2351190.11756
350.8533660.2932670.146634
360.8190430.3619140.180957
370.7885830.4228350.211417
380.7491120.5017760.250888
390.7047590.5904830.295241
400.6600560.6798880.339944
410.6101910.7796180.389809
420.5631610.8736780.436839
430.7781130.4437750.221887
440.8077510.3844980.192249
450.773570.452860.22643
460.7361220.5277570.263878
470.7112250.577550.288775
480.6813340.6373320.318666
490.6585690.6828630.341431
500.6267790.7464420.373221
510.5817580.8364840.418242
520.5362950.9274110.463705
530.4898120.9796240.510188
540.4524490.9048990.547551
550.4123420.8246840.587658
560.4167040.8334070.583296
570.3768170.7536330.623183
580.3470430.6940870.652957
590.3171160.6342330.682884
600.2852420.5704840.714758
610.2644460.5288920.735554
620.249340.4986790.75066
630.261410.522820.73859
640.3344940.6689890.665506
650.4137450.8274890.586255
660.4319680.8639360.568032
670.3919260.7838520.608074
680.3584630.7169260.641537
690.3405440.6810880.659456
700.3048540.6097070.695146
710.2719320.5438630.728068
720.305410.610820.69459
730.3162520.6325050.683748
740.2911840.5823670.708816
750.302910.605820.69709
760.3370410.6740820.662959
770.3053870.6107730.694613
780.2709920.5419840.729008
790.2534190.5068390.746581
800.3915970.7831930.608403
810.3728420.7456850.627158
820.3417060.6834120.658294
830.3073180.6146360.692682
840.2746070.5492140.725393
850.2539040.5078070.746096
860.2316160.4632310.768384
870.2064380.4128760.793562
880.2486570.4973150.751343
890.2423540.4847090.757646
900.2164170.4328350.783583
910.2780410.5560830.721959
920.2576490.5152990.742351
930.2736070.5472130.726393
940.2724910.5449820.727509
950.2507750.5015490.749225
960.2220160.4440320.777984
970.1997140.3994270.800286
980.1806760.3613510.819324
990.1581950.316390.841805
1000.1374210.2748420.862579
1010.1196510.2393020.880349
1020.1153730.2307450.884627
1030.1046930.2093860.895307
1040.09773380.1954680.902266
1050.08306670.1661330.916933
1060.06980760.1396150.930192
1070.05871110.1174220.941289
1080.07818360.1563670.921816
1090.104750.20950.89525
1100.1135680.2271360.886432
1110.09914050.1982810.90086
1120.1182280.2364570.881772
1130.4078620.8157240.592138
1140.3750310.7500620.624969
1150.3618280.7236570.638172
1160.4484070.8968150.551593
1170.4252530.8505050.574747
1180.4051870.8103730.594813
1190.4821780.9643550.517822
1200.5438280.9123430.456172
1210.5118860.9762280.488114
1220.5514490.8971030.448551
1230.5200330.9599340.479967
1240.4879630.9759260.512037
1250.4583480.9166950.541652
1260.462670.9253410.53733
1270.4404580.8809160.559542
1280.408140.816280.59186
1290.3752290.7504570.624771
1300.3459190.6918380.654081
1310.3189130.6378260.681087
1320.2874960.5749920.712504
1330.2701830.5403650.729817
1340.2433820.4867650.756618
1350.2496270.4992540.750373
1360.2449810.4899610.755019
1370.2480840.4961690.751916
1380.2863390.5726780.713661
1390.2961830.5923650.703817
1400.2753130.5506260.724687
1410.4175060.8350120.582494
1420.4212850.842570.578715
1430.423530.847060.57647
1440.3947680.7895370.605232
1450.4273190.8546370.572681
1460.398260.7965190.60174
1470.4304090.8608170.569591
1480.3953790.7907570.604621
1490.3811770.7623550.618823
1500.3807490.7614980.619251
1510.3612530.7225060.638747
1520.3481190.6962390.651881
1530.3187630.6375270.681237
1540.2891120.5782240.710888
1550.2885910.5771820.711409
1560.385440.7708810.61456
1570.3576030.7152060.642397
1580.3262410.6524820.673759
1590.3120680.6241360.687932
1600.357710.715420.64229
1610.3254640.6509280.674536
1620.3025570.6051130.697443
1630.3105380.6210760.689462
1640.3392410.6784810.660759
1650.3097060.6194120.690294
1660.2962970.5925940.703703
1670.2705670.5411340.729433
1680.2505280.5010550.749472
1690.2671290.5342590.732871
1700.2474530.4949060.752547
1710.2483830.4967670.751617
1720.2260830.4521660.773917
1730.2066440.4132870.793356
1740.1943460.3886930.805654
1750.1729160.3458330.827084
1760.1506990.3013980.849301
1770.1294920.2589850.870508
1780.1127650.225530.887235
1790.1079230.2158460.892077
1800.09192280.1838460.908077
1810.1704250.3408510.829575
1820.1616890.3233790.838311
1830.1493530.2987070.850647
1840.1311470.2622940.868853
1850.1956990.3913980.804301
1860.192620.3852390.80738
1870.1679640.3359280.832036
1880.1942210.3884410.805779
1890.2175230.4350470.782477
1900.1926190.3852380.807381
1910.6224270.7551460.377573
1920.5937430.8125150.406257
1930.5549170.8901660.445083
1940.5621430.8757130.437857
1950.5223630.9552730.477637
1960.5071610.9856780.492839
1970.5620810.8758390.437919
1980.6193870.7612260.380613
1990.585990.8280190.41401
2000.5594240.8811530.440576
2010.5212240.9575510.478776
2020.4810470.9620940.518953
2030.4493910.8987820.550609
2040.5246170.9507670.475383
2050.4835650.9671290.516435
2060.4399380.8798750.560062
2070.439230.878460.56077
2080.5634450.873110.436555
2090.5186720.9626560.481328
2100.5426820.9146360.457318
2110.507710.9845790.49229
2120.4672290.9344570.532771
2130.5910620.8178760.408938
2140.5853090.8293810.414691
2150.5394410.9211170.460559
2160.502090.9958190.49791
2170.5760780.8478450.423922
2180.613970.772060.38603
2190.5676530.8646940.432347
2200.6465580.7068830.353442
2210.6187190.7625620.381281
2220.6307540.7384920.369246
2230.6490870.7018260.350913
2240.6037820.7924360.396218
2250.8237620.3524770.176238
2260.8029490.3941030.197051
2270.8292950.3414090.170705
2280.817760.364480.18224
2290.7952580.4094830.204742
2300.7503430.4993140.249657
2310.7044510.5910990.295549
2320.6622880.6754230.337712
2330.820350.35930.17965
2340.8231040.3537930.176896
2350.7812990.4374020.218701
2360.7304270.5391460.269573
2370.8060710.3878580.193929
2380.853780.292440.14622
2390.8173760.3652470.182624
2400.7646490.4707010.235351
2410.8171370.3657250.182863
2420.9018140.1963710.0981856
2430.8824030.2351940.117597
2440.8703270.2593460.129673
2450.9202280.1595450.0797723
2460.8769470.2461060.123053
2470.8354490.3291010.164551
2480.9043760.1912480.0956239
2490.8423430.3153140.157657
2500.8514910.2970180.148509
2510.7968110.4063790.203189
2520.7870640.4258710.212936
2530.6646860.6706280.335314






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 level120.0493827OK

\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 & 12 & 0.0493827 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253224&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]12[/C][C]0.0493827[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253224&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253224&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 level120.0493827OK


Figures (Output of Computation)

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

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