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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 20 Nov 2013 16:22:21 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/20/t1384982583iyauury81cq4ey4.htm/, Retrieved Wed, 01 May 2024 20:11:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226732, Retrieved Wed, 01 May 2024 20:11:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact59

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [lkjhlkju] [2013-11-20 21:22:21] [9c1e2bb2413149fa15098d3e18bf4ebf] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 13 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226732&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]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226732&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226732&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 time13 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 5.0896 + 0.0385942Connected[t] + 0.00782622Separate[t] + 0.198368Learning[t] -0.0016268Software[t] + 0.0605411Sport1[t] -0.557171Q1[t] -0.154235Q2[t] -0.2176Q3[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  5.0896 +  0.0385942Connected[t] +  0.00782622Separate[t] +  0.198368Learning[t] -0.0016268Software[t] +  0.0605411Sport1[t] -0.557171Q1[t] -0.154235Q2[t] -0.2176Q3[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226732&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  5.0896 +  0.0385942Connected[t] +  0.00782622Separate[t] +  0.198368Learning[t] -0.0016268Software[t] +  0.0605411Sport1[t] -0.557171Q1[t] -0.154235Q2[t] -0.2176Q3[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226732&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226732&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
Happiness[t] = + 5.0896 + 0.0385942Connected[t] + 0.00782622Separate[t] + 0.198368Learning[t] -0.0016268Software[t] + 0.0605411Sport1[t] -0.557171Q1[t] -0.154235Q2[t] -0.2176Q3[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)5.08961.79342.8380.004905580.00245279
Connected0.03859420.04358250.88550.3766980.188349
Separate0.007826220.04493160.17420.8618620.430931
Learning0.1983680.07705782.5740.01061010.00530504
Software-0.00162680.0807099-0.020160.9839350.491967
Sport10.06054110.01431364.233.2661e-051.63305e-05
Q1-0.5571710.4118-1.3530.1772490.0886247
Q2-0.1542350.413441-0.37310.7094210.35471
Q3-0.21760.413982-0.52560.5996040.299802

\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) & 5.0896 & 1.7934 & 2.838 & 0.00490558 & 0.00245279 \tabularnewline
Connected & 0.0385942 & 0.0435825 & 0.8855 & 0.376698 & 0.188349 \tabularnewline
Separate & 0.00782622 & 0.0449316 & 0.1742 & 0.861862 & 0.430931 \tabularnewline
Learning & 0.198368 & 0.0770578 & 2.574 & 0.0106101 & 0.00530504 \tabularnewline
Software & -0.0016268 & 0.0807099 & -0.02016 & 0.983935 & 0.491967 \tabularnewline
Sport1 & 0.0605411 & 0.0143136 & 4.23 & 3.2661e-05 & 1.63305e-05 \tabularnewline
Q1 & -0.557171 & 0.4118 & -1.353 & 0.177249 & 0.0886247 \tabularnewline
Q2 & -0.154235 & 0.413441 & -0.3731 & 0.709421 & 0.35471 \tabularnewline
Q3 & -0.2176 & 0.413982 & -0.5256 & 0.599604 & 0.299802 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226732&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]5.0896[/C][C]1.7934[/C][C]2.838[/C][C]0.00490558[/C][C]0.00245279[/C][/ROW]
[ROW][C]Connected[/C][C]0.0385942[/C][C]0.0435825[/C][C]0.8855[/C][C]0.376698[/C][C]0.188349[/C][/ROW]
[ROW][C]Separate[/C][C]0.00782622[/C][C]0.0449316[/C][C]0.1742[/C][C]0.861862[/C][C]0.430931[/C][/ROW]
[ROW][C]Learning[/C][C]0.198368[/C][C]0.0770578[/C][C]2.574[/C][C]0.0106101[/C][C]0.00530504[/C][/ROW]
[ROW][C]Software[/C][C]-0.0016268[/C][C]0.0807099[/C][C]-0.02016[/C][C]0.983935[/C][C]0.491967[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0605411[/C][C]0.0143136[/C][C]4.23[/C][C]3.2661e-05[/C][C]1.63305e-05[/C][/ROW]
[ROW][C]Q1[/C][C]-0.557171[/C][C]0.4118[/C][C]-1.353[/C][C]0.177249[/C][C]0.0886247[/C][/ROW]
[ROW][C]Q2[/C][C]-0.154235[/C][C]0.413441[/C][C]-0.3731[/C][C]0.709421[/C][C]0.35471[/C][/ROW]
[ROW][C]Q3[/C][C]-0.2176[/C][C]0.413982[/C][C]-0.5256[/C][C]0.599604[/C][C]0.299802[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226732&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226732&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)5.08961.79342.8380.004905580.00245279
Connected0.03859420.04358250.88550.3766980.188349
Separate0.007826220.04493160.17420.8618620.430931
Learning0.1983680.07705782.5740.01061010.00530504
Software-0.00162680.0807099-0.020160.9839350.491967
Sport10.06054110.01431364.233.2661e-051.63305e-05
Q1-0.5571710.4118-1.3530.1772490.0886247
Q2-0.1542350.413441-0.37310.7094210.35471
Q3-0.21760.413982-0.52560.5996040.299802






Multiple Linear Regression - Regression Statistics
Multiple R0.369877
R-squared0.136809
Adjusted R-squared0.109728
F-TEST (value)5.05192
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value7.69066e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.35758
Sum Squared Residuals1417.33

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.369877 \tabularnewline
R-squared & 0.136809 \tabularnewline
Adjusted R-squared & 0.109728 \tabularnewline
F-TEST (value) & 5.05192 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 255 \tabularnewline
p-value & 7.69066e-06 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.35758 \tabularnewline
Sum Squared Residuals & 1417.33 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226732&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.369877[/C][/ROW]
[ROW][C]R-squared[/C][C]0.136809[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.109728[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]5.05192[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]255[/C][/ROW]
[ROW][C]p-value[/C][C]7.69066e-06[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.35758[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1417.33[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226732&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226732&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 R0.369877
R-squared0.136809
Adjusted R-squared0.109728
F-TEST (value)5.05192
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value7.69066e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.35758
Sum Squared Residuals1417.33






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11412.18011.81987
21814.87193.12811
31114.044-3.04405
41213.5663-1.5663
51613.49132.50867
61813.79784.20215
71413.57790.422062
81414.4796-0.479582
91513.43341.56659
101514.22280.777248
111714.52162.47844
121913.16875.83133
131013.4835-3.48355
141613.16322.83685
151815.05012.94989
161413.05030.949736
171413.67210.327904
181715.97481.0252
191414.1019-0.101933
201613.18032.81974
211813.17744.82258
221113.6456-2.64556
231413.69160.308364
241213.3691-1.36911
251714.84732.15269
26914.9626-5.96256
271614.29411.70595
281413.78290.217139
291513.94091.05912
301113.323-2.32297
311614.11031.88968
321312.01870.981296
331713.26233.73767
341514.7770.22304
351413.65670.343337
361612.85363.14641
37911.6774-2.6774
381513.63911.36093
391713.99263.00741
401314.0336-1.03362
411513.84851.15148
421613.8042.19595
431613.80122.1988
441212.6077-0.607685
451513.15641.84364
461112.9166-1.91659
471513.3351.66502
481514.12750.87249
491713.85533.14475
501313.9506-0.950599
511613.91452.08551
521413.37650.62346
531112.2007-1.20069
541213.4513-1.45125
551211.94870.0512795
561514.160.839981
571613.93812.0619
581513.53131.46869
591213.9589-1.95886
601214.102-2.10199
61811.4871-3.4871
621314.4841-1.48407
631114.4525-3.45252
641412.46731.53267
651512.51082.48917
661014.7701-4.77013
671114.0789-3.07887
681214.431-2.43097
691512.52562.47436
701513.90741.09256
711412.64721.35276
721612.61193.38811
731514.60150.398465
741514.4480.551992
751314.6353-1.63533
761215.0305-3.03047
771713.64063.3594
781313.8235-0.823512
791513.41621.58382
801313.1525-0.152481
811514.02490.975103
821514.02850.971481
831613.93382.06625
841513.90731.09271
851413.86790.132063
861514.01030.989738
871413.74340.256595
881312.88290.117141
89713.2582-6.25818
901713.19883.80119
911313.1289-0.128906
921514.57730.422695
931413.90690.093052
941313.6919-0.691936
951614.65981.34017
961214.1216-2.12158
971414.0073-0.00729357
981714.68762.31236
991513.75081.24923
1001714.59022.40984
1011213.8098-1.80983
1021615.70330.296718
1031113.2795-2.27949
1041514.60720.392826
105913.0027-4.00269
1061614.62971.37028
1071514.21240.787629
1081013.1781-3.17812
1091011.6746-1.6746
1101514.65960.340355
1111113.9578-2.95784
1121315.3275-2.32747
1131410.88723.11284
1141813.59474.40529
1151615.30640.693562
1161412.70151.29852
1171412.97811.02193
1181413.22110.778882
1191415.2234-1.22339
1201212.4829-0.482889
1211413.6940.305977
1221514.65460.345411
1231514.34960.65038
1241514.09550.904522
1251313.9193-0.91935
1261715.09891.90107
1271714.70982.29023
1281914.50974.49034
1291512.8632.13703
1301313.8847-0.884686
131912.1646-3.16457
1321514.74550.254521
1331512.1072.89305
1341513.89841.10158
1351614.4361.56403
1361112.1758-1.17578
1371412.89031.10973
1381111.8021-0.802109
1391512.73092.26908
1401312.90470.0953188
1411512.46362.53637
1421614.42911.57091
1431414.8581-0.858135
1441514.28370.716317
1451613.67762.32237
1461614.53231.46771
1471112.7349-1.73486
1481214.2622-2.26218
149913.1173-4.11731
1501613.82552.17455
1511314.5196-1.51965
1521614.15691.84313
1531213.7115-1.71154
154913.6095-4.60951
1551313.0811-0.081093
1561313.3465-0.346506
1571412.80341.19663
1581914.35544.64457
1591314.6761-1.67609
1601214.0749-2.07487
1611312.86950.130518
1621012.7391-2.73912
1631413.54310.456866
1641615.12830.871702
1651013.4681-3.46807
1661111.3363-0.336298
1671413.76960.230444
1681212.9313-0.931273
169913.6657-4.66566
170913.8408-4.84085
1711112.2446-1.24464
1721614.28191.71811
173913.4751-4.47506
1741311.59611.4039
1751613.20042.79962
1761314.2784-1.27837
177912.7029-3.70288
1781212.8711-0.87109
1791613.12822.87183
1801113.6916-2.69157
1811412.62721.37285
1821312.74950.25051
1831514.33260.667366
1841414.6059-0.605907
1851612.55623.44378
1861314.2076-1.20762
1871414.3619-0.361888
1881514.47350.526508
1891311.27211.72792
1901112.319-1.31905
1911111.447-0.446952
1921414.5642-0.56418
1931512.57862.42142
1941113.4853-2.48528
1951513.27891.72107
1961214.0089-2.00886
1971414.0292-0.0292405
1981414.92-0.919989
199812.9199-4.91993
2001314.1595-1.15952
201913.2567-4.25675
2021513.03461.96537
2031713.13483.86519
2041312.28240.717644
2051513.39361.6064
2061513.9671.03302
2071414.8144-0.814356
2081613.02462.97535
2091312.58370.416257
2101614.55051.44946
211912.678-3.67799
2121614.46271.53734
2131114.2974-3.29737
2141014.0889-4.08889
2151113.7073-2.70734
2161513.0621.93805
2171714.58032.41969
2181414.4924-0.492428
219812.7941-4.79409
2201514.70460.295416
2211113.3019-2.30188
2221612.9563.04404
2231013.711-3.71101
2241513.26121.73881
225910.9911-1.99108
2261612.75153.24849
2271912.3496.65104
2281213.2059-1.2059
229812.266-4.26602
2301113.1251-2.12514
2311413.28640.713568
232912.6843-3.68427
2331512.7092.29095
2341314.6828-1.6828
2351613.35612.64388
2361113.1253-2.12526
2371211.580.419966
2381312.12240.877617
2391013.7472-3.74717
2401113.0836-2.08362
2411213.5199-1.51993
242812.1313-4.13128
2431211.6620.338045
2441213.2634-1.2634
2451514.12670.873349
2461112.8733-1.87325
2471313.2602-0.260239
2481411.36232.63772
2491011.1878-1.18777
2501211.47680.523178
2511512.7432.25695
2521313.3081-0.308146
2531312.8570.143014
2541313.9776-0.977621
2551213.0392-1.03919
2561213.4756-1.47558
257913.8677-4.86775
258912.8999-3.89991
2591513.18321.81678
2601012.4887-2.48868
2611412.64151.35848
2621512.82432.17571
263712.6217-5.62172
2641413.58070.419257

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 12.1801 & 1.81987 \tabularnewline
2 & 18 & 14.8719 & 3.12811 \tabularnewline
3 & 11 & 14.044 & -3.04405 \tabularnewline
4 & 12 & 13.5663 & -1.5663 \tabularnewline
5 & 16 & 13.4913 & 2.50867 \tabularnewline
6 & 18 & 13.7978 & 4.20215 \tabularnewline
7 & 14 & 13.5779 & 0.422062 \tabularnewline
8 & 14 & 14.4796 & -0.479582 \tabularnewline
9 & 15 & 13.4334 & 1.56659 \tabularnewline
10 & 15 & 14.2228 & 0.777248 \tabularnewline
11 & 17 & 14.5216 & 2.47844 \tabularnewline
12 & 19 & 13.1687 & 5.83133 \tabularnewline
13 & 10 & 13.4835 & -3.48355 \tabularnewline
14 & 16 & 13.1632 & 2.83685 \tabularnewline
15 & 18 & 15.0501 & 2.94989 \tabularnewline
16 & 14 & 13.0503 & 0.949736 \tabularnewline
17 & 14 & 13.6721 & 0.327904 \tabularnewline
18 & 17 & 15.9748 & 1.0252 \tabularnewline
19 & 14 & 14.1019 & -0.101933 \tabularnewline
20 & 16 & 13.1803 & 2.81974 \tabularnewline
21 & 18 & 13.1774 & 4.82258 \tabularnewline
22 & 11 & 13.6456 & -2.64556 \tabularnewline
23 & 14 & 13.6916 & 0.308364 \tabularnewline
24 & 12 & 13.3691 & -1.36911 \tabularnewline
25 & 17 & 14.8473 & 2.15269 \tabularnewline
26 & 9 & 14.9626 & -5.96256 \tabularnewline
27 & 16 & 14.2941 & 1.70595 \tabularnewline
28 & 14 & 13.7829 & 0.217139 \tabularnewline
29 & 15 & 13.9409 & 1.05912 \tabularnewline
30 & 11 & 13.323 & -2.32297 \tabularnewline
31 & 16 & 14.1103 & 1.88968 \tabularnewline
32 & 13 & 12.0187 & 0.981296 \tabularnewline
33 & 17 & 13.2623 & 3.73767 \tabularnewline
34 & 15 & 14.777 & 0.22304 \tabularnewline
35 & 14 & 13.6567 & 0.343337 \tabularnewline
36 & 16 & 12.8536 & 3.14641 \tabularnewline
37 & 9 & 11.6774 & -2.6774 \tabularnewline
38 & 15 & 13.6391 & 1.36093 \tabularnewline
39 & 17 & 13.9926 & 3.00741 \tabularnewline
40 & 13 & 14.0336 & -1.03362 \tabularnewline
41 & 15 & 13.8485 & 1.15148 \tabularnewline
42 & 16 & 13.804 & 2.19595 \tabularnewline
43 & 16 & 13.8012 & 2.1988 \tabularnewline
44 & 12 & 12.6077 & -0.607685 \tabularnewline
45 & 15 & 13.1564 & 1.84364 \tabularnewline
46 & 11 & 12.9166 & -1.91659 \tabularnewline
47 & 15 & 13.335 & 1.66502 \tabularnewline
48 & 15 & 14.1275 & 0.87249 \tabularnewline
49 & 17 & 13.8553 & 3.14475 \tabularnewline
50 & 13 & 13.9506 & -0.950599 \tabularnewline
51 & 16 & 13.9145 & 2.08551 \tabularnewline
52 & 14 & 13.3765 & 0.62346 \tabularnewline
53 & 11 & 12.2007 & -1.20069 \tabularnewline
54 & 12 & 13.4513 & -1.45125 \tabularnewline
55 & 12 & 11.9487 & 0.0512795 \tabularnewline
56 & 15 & 14.16 & 0.839981 \tabularnewline
57 & 16 & 13.9381 & 2.0619 \tabularnewline
58 & 15 & 13.5313 & 1.46869 \tabularnewline
59 & 12 & 13.9589 & -1.95886 \tabularnewline
60 & 12 & 14.102 & -2.10199 \tabularnewline
61 & 8 & 11.4871 & -3.4871 \tabularnewline
62 & 13 & 14.4841 & -1.48407 \tabularnewline
63 & 11 & 14.4525 & -3.45252 \tabularnewline
64 & 14 & 12.4673 & 1.53267 \tabularnewline
65 & 15 & 12.5108 & 2.48917 \tabularnewline
66 & 10 & 14.7701 & -4.77013 \tabularnewline
67 & 11 & 14.0789 & -3.07887 \tabularnewline
68 & 12 & 14.431 & -2.43097 \tabularnewline
69 & 15 & 12.5256 & 2.47436 \tabularnewline
70 & 15 & 13.9074 & 1.09256 \tabularnewline
71 & 14 & 12.6472 & 1.35276 \tabularnewline
72 & 16 & 12.6119 & 3.38811 \tabularnewline
73 & 15 & 14.6015 & 0.398465 \tabularnewline
74 & 15 & 14.448 & 0.551992 \tabularnewline
75 & 13 & 14.6353 & -1.63533 \tabularnewline
76 & 12 & 15.0305 & -3.03047 \tabularnewline
77 & 17 & 13.6406 & 3.3594 \tabularnewline
78 & 13 & 13.8235 & -0.823512 \tabularnewline
79 & 15 & 13.4162 & 1.58382 \tabularnewline
80 & 13 & 13.1525 & -0.152481 \tabularnewline
81 & 15 & 14.0249 & 0.975103 \tabularnewline
82 & 15 & 14.0285 & 0.971481 \tabularnewline
83 & 16 & 13.9338 & 2.06625 \tabularnewline
84 & 15 & 13.9073 & 1.09271 \tabularnewline
85 & 14 & 13.8679 & 0.132063 \tabularnewline
86 & 15 & 14.0103 & 0.989738 \tabularnewline
87 & 14 & 13.7434 & 0.256595 \tabularnewline
88 & 13 & 12.8829 & 0.117141 \tabularnewline
89 & 7 & 13.2582 & -6.25818 \tabularnewline
90 & 17 & 13.1988 & 3.80119 \tabularnewline
91 & 13 & 13.1289 & -0.128906 \tabularnewline
92 & 15 & 14.5773 & 0.422695 \tabularnewline
93 & 14 & 13.9069 & 0.093052 \tabularnewline
94 & 13 & 13.6919 & -0.691936 \tabularnewline
95 & 16 & 14.6598 & 1.34017 \tabularnewline
96 & 12 & 14.1216 & -2.12158 \tabularnewline
97 & 14 & 14.0073 & -0.00729357 \tabularnewline
98 & 17 & 14.6876 & 2.31236 \tabularnewline
99 & 15 & 13.7508 & 1.24923 \tabularnewline
100 & 17 & 14.5902 & 2.40984 \tabularnewline
101 & 12 & 13.8098 & -1.80983 \tabularnewline
102 & 16 & 15.7033 & 0.296718 \tabularnewline
103 & 11 & 13.2795 & -2.27949 \tabularnewline
104 & 15 & 14.6072 & 0.392826 \tabularnewline
105 & 9 & 13.0027 & -4.00269 \tabularnewline
106 & 16 & 14.6297 & 1.37028 \tabularnewline
107 & 15 & 14.2124 & 0.787629 \tabularnewline
108 & 10 & 13.1781 & -3.17812 \tabularnewline
109 & 10 & 11.6746 & -1.6746 \tabularnewline
110 & 15 & 14.6596 & 0.340355 \tabularnewline
111 & 11 & 13.9578 & -2.95784 \tabularnewline
112 & 13 & 15.3275 & -2.32747 \tabularnewline
113 & 14 & 10.8872 & 3.11284 \tabularnewline
114 & 18 & 13.5947 & 4.40529 \tabularnewline
115 & 16 & 15.3064 & 0.693562 \tabularnewline
116 & 14 & 12.7015 & 1.29852 \tabularnewline
117 & 14 & 12.9781 & 1.02193 \tabularnewline
118 & 14 & 13.2211 & 0.778882 \tabularnewline
119 & 14 & 15.2234 & -1.22339 \tabularnewline
120 & 12 & 12.4829 & -0.482889 \tabularnewline
121 & 14 & 13.694 & 0.305977 \tabularnewline
122 & 15 & 14.6546 & 0.345411 \tabularnewline
123 & 15 & 14.3496 & 0.65038 \tabularnewline
124 & 15 & 14.0955 & 0.904522 \tabularnewline
125 & 13 & 13.9193 & -0.91935 \tabularnewline
126 & 17 & 15.0989 & 1.90107 \tabularnewline
127 & 17 & 14.7098 & 2.29023 \tabularnewline
128 & 19 & 14.5097 & 4.49034 \tabularnewline
129 & 15 & 12.863 & 2.13703 \tabularnewline
130 & 13 & 13.8847 & -0.884686 \tabularnewline
131 & 9 & 12.1646 & -3.16457 \tabularnewline
132 & 15 & 14.7455 & 0.254521 \tabularnewline
133 & 15 & 12.107 & 2.89305 \tabularnewline
134 & 15 & 13.8984 & 1.10158 \tabularnewline
135 & 16 & 14.436 & 1.56403 \tabularnewline
136 & 11 & 12.1758 & -1.17578 \tabularnewline
137 & 14 & 12.8903 & 1.10973 \tabularnewline
138 & 11 & 11.8021 & -0.802109 \tabularnewline
139 & 15 & 12.7309 & 2.26908 \tabularnewline
140 & 13 & 12.9047 & 0.0953188 \tabularnewline
141 & 15 & 12.4636 & 2.53637 \tabularnewline
142 & 16 & 14.4291 & 1.57091 \tabularnewline
143 & 14 & 14.8581 & -0.858135 \tabularnewline
144 & 15 & 14.2837 & 0.716317 \tabularnewline
145 & 16 & 13.6776 & 2.32237 \tabularnewline
146 & 16 & 14.5323 & 1.46771 \tabularnewline
147 & 11 & 12.7349 & -1.73486 \tabularnewline
148 & 12 & 14.2622 & -2.26218 \tabularnewline
149 & 9 & 13.1173 & -4.11731 \tabularnewline
150 & 16 & 13.8255 & 2.17455 \tabularnewline
151 & 13 & 14.5196 & -1.51965 \tabularnewline
152 & 16 & 14.1569 & 1.84313 \tabularnewline
153 & 12 & 13.7115 & -1.71154 \tabularnewline
154 & 9 & 13.6095 & -4.60951 \tabularnewline
155 & 13 & 13.0811 & -0.081093 \tabularnewline
156 & 13 & 13.3465 & -0.346506 \tabularnewline
157 & 14 & 12.8034 & 1.19663 \tabularnewline
158 & 19 & 14.3554 & 4.64457 \tabularnewline
159 & 13 & 14.6761 & -1.67609 \tabularnewline
160 & 12 & 14.0749 & -2.07487 \tabularnewline
161 & 13 & 12.8695 & 0.130518 \tabularnewline
162 & 10 & 12.7391 & -2.73912 \tabularnewline
163 & 14 & 13.5431 & 0.456866 \tabularnewline
164 & 16 & 15.1283 & 0.871702 \tabularnewline
165 & 10 & 13.4681 & -3.46807 \tabularnewline
166 & 11 & 11.3363 & -0.336298 \tabularnewline
167 & 14 & 13.7696 & 0.230444 \tabularnewline
168 & 12 & 12.9313 & -0.931273 \tabularnewline
169 & 9 & 13.6657 & -4.66566 \tabularnewline
170 & 9 & 13.8408 & -4.84085 \tabularnewline
171 & 11 & 12.2446 & -1.24464 \tabularnewline
172 & 16 & 14.2819 & 1.71811 \tabularnewline
173 & 9 & 13.4751 & -4.47506 \tabularnewline
174 & 13 & 11.5961 & 1.4039 \tabularnewline
175 & 16 & 13.2004 & 2.79962 \tabularnewline
176 & 13 & 14.2784 & -1.27837 \tabularnewline
177 & 9 & 12.7029 & -3.70288 \tabularnewline
178 & 12 & 12.8711 & -0.87109 \tabularnewline
179 & 16 & 13.1282 & 2.87183 \tabularnewline
180 & 11 & 13.6916 & -2.69157 \tabularnewline
181 & 14 & 12.6272 & 1.37285 \tabularnewline
182 & 13 & 12.7495 & 0.25051 \tabularnewline
183 & 15 & 14.3326 & 0.667366 \tabularnewline
184 & 14 & 14.6059 & -0.605907 \tabularnewline
185 & 16 & 12.5562 & 3.44378 \tabularnewline
186 & 13 & 14.2076 & -1.20762 \tabularnewline
187 & 14 & 14.3619 & -0.361888 \tabularnewline
188 & 15 & 14.4735 & 0.526508 \tabularnewline
189 & 13 & 11.2721 & 1.72792 \tabularnewline
190 & 11 & 12.319 & -1.31905 \tabularnewline
191 & 11 & 11.447 & -0.446952 \tabularnewline
192 & 14 & 14.5642 & -0.56418 \tabularnewline
193 & 15 & 12.5786 & 2.42142 \tabularnewline
194 & 11 & 13.4853 & -2.48528 \tabularnewline
195 & 15 & 13.2789 & 1.72107 \tabularnewline
196 & 12 & 14.0089 & -2.00886 \tabularnewline
197 & 14 & 14.0292 & -0.0292405 \tabularnewline
198 & 14 & 14.92 & -0.919989 \tabularnewline
199 & 8 & 12.9199 & -4.91993 \tabularnewline
200 & 13 & 14.1595 & -1.15952 \tabularnewline
201 & 9 & 13.2567 & -4.25675 \tabularnewline
202 & 15 & 13.0346 & 1.96537 \tabularnewline
203 & 17 & 13.1348 & 3.86519 \tabularnewline
204 & 13 & 12.2824 & 0.717644 \tabularnewline
205 & 15 & 13.3936 & 1.6064 \tabularnewline
206 & 15 & 13.967 & 1.03302 \tabularnewline
207 & 14 & 14.8144 & -0.814356 \tabularnewline
208 & 16 & 13.0246 & 2.97535 \tabularnewline
209 & 13 & 12.5837 & 0.416257 \tabularnewline
210 & 16 & 14.5505 & 1.44946 \tabularnewline
211 & 9 & 12.678 & -3.67799 \tabularnewline
212 & 16 & 14.4627 & 1.53734 \tabularnewline
213 & 11 & 14.2974 & -3.29737 \tabularnewline
214 & 10 & 14.0889 & -4.08889 \tabularnewline
215 & 11 & 13.7073 & -2.70734 \tabularnewline
216 & 15 & 13.062 & 1.93805 \tabularnewline
217 & 17 & 14.5803 & 2.41969 \tabularnewline
218 & 14 & 14.4924 & -0.492428 \tabularnewline
219 & 8 & 12.7941 & -4.79409 \tabularnewline
220 & 15 & 14.7046 & 0.295416 \tabularnewline
221 & 11 & 13.3019 & -2.30188 \tabularnewline
222 & 16 & 12.956 & 3.04404 \tabularnewline
223 & 10 & 13.711 & -3.71101 \tabularnewline
224 & 15 & 13.2612 & 1.73881 \tabularnewline
225 & 9 & 10.9911 & -1.99108 \tabularnewline
226 & 16 & 12.7515 & 3.24849 \tabularnewline
227 & 19 & 12.349 & 6.65104 \tabularnewline
228 & 12 & 13.2059 & -1.2059 \tabularnewline
229 & 8 & 12.266 & -4.26602 \tabularnewline
230 & 11 & 13.1251 & -2.12514 \tabularnewline
231 & 14 & 13.2864 & 0.713568 \tabularnewline
232 & 9 & 12.6843 & -3.68427 \tabularnewline
233 & 15 & 12.709 & 2.29095 \tabularnewline
234 & 13 & 14.6828 & -1.6828 \tabularnewline
235 & 16 & 13.3561 & 2.64388 \tabularnewline
236 & 11 & 13.1253 & -2.12526 \tabularnewline
237 & 12 & 11.58 & 0.419966 \tabularnewline
238 & 13 & 12.1224 & 0.877617 \tabularnewline
239 & 10 & 13.7472 & -3.74717 \tabularnewline
240 & 11 & 13.0836 & -2.08362 \tabularnewline
241 & 12 & 13.5199 & -1.51993 \tabularnewline
242 & 8 & 12.1313 & -4.13128 \tabularnewline
243 & 12 & 11.662 & 0.338045 \tabularnewline
244 & 12 & 13.2634 & -1.2634 \tabularnewline
245 & 15 & 14.1267 & 0.873349 \tabularnewline
246 & 11 & 12.8733 & -1.87325 \tabularnewline
247 & 13 & 13.2602 & -0.260239 \tabularnewline
248 & 14 & 11.3623 & 2.63772 \tabularnewline
249 & 10 & 11.1878 & -1.18777 \tabularnewline
250 & 12 & 11.4768 & 0.523178 \tabularnewline
251 & 15 & 12.743 & 2.25695 \tabularnewline
252 & 13 & 13.3081 & -0.308146 \tabularnewline
253 & 13 & 12.857 & 0.143014 \tabularnewline
254 & 13 & 13.9776 & -0.977621 \tabularnewline
255 & 12 & 13.0392 & -1.03919 \tabularnewline
256 & 12 & 13.4756 & -1.47558 \tabularnewline
257 & 9 & 13.8677 & -4.86775 \tabularnewline
258 & 9 & 12.8999 & -3.89991 \tabularnewline
259 & 15 & 13.1832 & 1.81678 \tabularnewline
260 & 10 & 12.4887 & -2.48868 \tabularnewline
261 & 14 & 12.6415 & 1.35848 \tabularnewline
262 & 15 & 12.8243 & 2.17571 \tabularnewline
263 & 7 & 12.6217 & -5.62172 \tabularnewline
264 & 14 & 13.5807 & 0.419257 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226732&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]14[/C][C]12.1801[/C][C]1.81987[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]14.8719[/C][C]3.12811[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]14.044[/C][C]-3.04405[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]13.5663[/C][C]-1.5663[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]13.4913[/C][C]2.50867[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]13.7978[/C][C]4.20215[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]13.5779[/C][C]0.422062[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]14.4796[/C][C]-0.479582[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]13.4334[/C][C]1.56659[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.2228[/C][C]0.777248[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]14.5216[/C][C]2.47844[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]13.1687[/C][C]5.83133[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.4835[/C][C]-3.48355[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.1632[/C][C]2.83685[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.0501[/C][C]2.94989[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.0503[/C][C]0.949736[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.6721[/C][C]0.327904[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.9748[/C][C]1.0252[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]14.1019[/C][C]-0.101933[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.1803[/C][C]2.81974[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]13.1774[/C][C]4.82258[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.6456[/C][C]-2.64556[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]13.6916[/C][C]0.308364[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.3691[/C][C]-1.36911[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]14.8473[/C][C]2.15269[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]14.9626[/C][C]-5.96256[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.2941[/C][C]1.70595[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.7829[/C][C]0.217139[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]13.9409[/C][C]1.05912[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]13.323[/C][C]-2.32297[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]14.1103[/C][C]1.88968[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.0187[/C][C]0.981296[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]13.2623[/C][C]3.73767[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]14.777[/C][C]0.22304[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]13.6567[/C][C]0.343337[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]12.8536[/C][C]3.14641[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]11.6774[/C][C]-2.6774[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]13.6391[/C][C]1.36093[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]13.9926[/C][C]3.00741[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]14.0336[/C][C]-1.03362[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]13.8485[/C][C]1.15148[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.804[/C][C]2.19595[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]13.8012[/C][C]2.1988[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]12.6077[/C][C]-0.607685[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]13.1564[/C][C]1.84364[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]12.9166[/C][C]-1.91659[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]13.335[/C][C]1.66502[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.1275[/C][C]0.87249[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.8553[/C][C]3.14475[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]13.9506[/C][C]-0.950599[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]13.9145[/C][C]2.08551[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.3765[/C][C]0.62346[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]12.2007[/C][C]-1.20069[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.4513[/C][C]-1.45125[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]11.9487[/C][C]0.0512795[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]14.16[/C][C]0.839981[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]13.9381[/C][C]2.0619[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]13.5313[/C][C]1.46869[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]13.9589[/C][C]-1.95886[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]14.102[/C][C]-2.10199[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]11.4871[/C][C]-3.4871[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.4841[/C][C]-1.48407[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.4525[/C][C]-3.45252[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]12.4673[/C][C]1.53267[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]12.5108[/C][C]2.48917[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]14.7701[/C][C]-4.77013[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]14.0789[/C][C]-3.07887[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.431[/C][C]-2.43097[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]12.5256[/C][C]2.47436[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.9074[/C][C]1.09256[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]12.6472[/C][C]1.35276[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.6119[/C][C]3.38811[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.6015[/C][C]0.398465[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]14.448[/C][C]0.551992[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.6353[/C][C]-1.63533[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]15.0305[/C][C]-3.03047[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]13.6406[/C][C]3.3594[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]13.8235[/C][C]-0.823512[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.4162[/C][C]1.58382[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]13.1525[/C][C]-0.152481[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.0249[/C][C]0.975103[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]14.0285[/C][C]0.971481[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]13.9338[/C][C]2.06625[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]13.9073[/C][C]1.09271[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]13.8679[/C][C]0.132063[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]14.0103[/C][C]0.989738[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]13.7434[/C][C]0.256595[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.8829[/C][C]0.117141[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]13.2582[/C][C]-6.25818[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.1988[/C][C]3.80119[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]13.1289[/C][C]-0.128906[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.5773[/C][C]0.422695[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.9069[/C][C]0.093052[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.6919[/C][C]-0.691936[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.6598[/C][C]1.34017[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]14.1216[/C][C]-2.12158[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.0073[/C][C]-0.00729357[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.6876[/C][C]2.31236[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]13.7508[/C][C]1.24923[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]14.5902[/C][C]2.40984[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]13.8098[/C][C]-1.80983[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]15.7033[/C][C]0.296718[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]13.2795[/C][C]-2.27949[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]14.6072[/C][C]0.392826[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]13.0027[/C][C]-4.00269[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.6297[/C][C]1.37028[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]14.2124[/C][C]0.787629[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]13.1781[/C][C]-3.17812[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]11.6746[/C][C]-1.6746[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]14.6596[/C][C]0.340355[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.9578[/C][C]-2.95784[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.3275[/C][C]-2.32747[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]10.8872[/C][C]3.11284[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]13.5947[/C][C]4.40529[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.3064[/C][C]0.693562[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]12.7015[/C][C]1.29852[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]12.9781[/C][C]1.02193[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]13.2211[/C][C]0.778882[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]15.2234[/C][C]-1.22339[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.4829[/C][C]-0.482889[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.694[/C][C]0.305977[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.6546[/C][C]0.345411[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]14.3496[/C][C]0.65038[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.0955[/C][C]0.904522[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]13.9193[/C][C]-0.91935[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]15.0989[/C][C]1.90107[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]14.7098[/C][C]2.29023[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.5097[/C][C]4.49034[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]12.863[/C][C]2.13703[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]13.8847[/C][C]-0.884686[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]12.1646[/C][C]-3.16457[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]14.7455[/C][C]0.254521[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.107[/C][C]2.89305[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]13.8984[/C][C]1.10158[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]14.436[/C][C]1.56403[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]12.1758[/C][C]-1.17578[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]12.8903[/C][C]1.10973[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]11.8021[/C][C]-0.802109[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]12.7309[/C][C]2.26908[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]12.9047[/C][C]0.0953188[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]12.4636[/C][C]2.53637[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]14.4291[/C][C]1.57091[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.8581[/C][C]-0.858135[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.2837[/C][C]0.716317[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]13.6776[/C][C]2.32237[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.5323[/C][C]1.46771[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]12.7349[/C][C]-1.73486[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.2622[/C][C]-2.26218[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]13.1173[/C][C]-4.11731[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]13.8255[/C][C]2.17455[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]14.5196[/C][C]-1.51965[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]14.1569[/C][C]1.84313[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]13.7115[/C][C]-1.71154[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]13.6095[/C][C]-4.60951[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]13.0811[/C][C]-0.081093[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]13.3465[/C][C]-0.346506[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]12.8034[/C][C]1.19663[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.3554[/C][C]4.64457[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]14.6761[/C][C]-1.67609[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]14.0749[/C][C]-2.07487[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.8695[/C][C]0.130518[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]12.7391[/C][C]-2.73912[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.5431[/C][C]0.456866[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]15.1283[/C][C]0.871702[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]13.4681[/C][C]-3.46807[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]11.3363[/C][C]-0.336298[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]13.7696[/C][C]0.230444[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]12.9313[/C][C]-0.931273[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]13.6657[/C][C]-4.66566[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]13.8408[/C][C]-4.84085[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]12.2446[/C][C]-1.24464[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.2819[/C][C]1.71811[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]13.4751[/C][C]-4.47506[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.5961[/C][C]1.4039[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.2004[/C][C]2.79962[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]14.2784[/C][C]-1.27837[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.7029[/C][C]-3.70288[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.8711[/C][C]-0.87109[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]13.1282[/C][C]2.87183[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.6916[/C][C]-2.69157[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]12.6272[/C][C]1.37285[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]12.7495[/C][C]0.25051[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]14.3326[/C][C]0.667366[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]14.6059[/C][C]-0.605907[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]12.5562[/C][C]3.44378[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]14.2076[/C][C]-1.20762[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]14.3619[/C][C]-0.361888[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.4735[/C][C]0.526508[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]11.2721[/C][C]1.72792[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]12.319[/C][C]-1.31905[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]11.447[/C][C]-0.446952[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]14.5642[/C][C]-0.56418[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.5786[/C][C]2.42142[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]13.4853[/C][C]-2.48528[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]13.2789[/C][C]1.72107[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.0089[/C][C]-2.00886[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]14.0292[/C][C]-0.0292405[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]14.92[/C][C]-0.919989[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]12.9199[/C][C]-4.91993[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]14.1595[/C][C]-1.15952[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]13.2567[/C][C]-4.25675[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.0346[/C][C]1.96537[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]13.1348[/C][C]3.86519[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.2824[/C][C]0.717644[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]13.3936[/C][C]1.6064[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.967[/C][C]1.03302[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.8144[/C][C]-0.814356[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]13.0246[/C][C]2.97535[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]12.5837[/C][C]0.416257[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.5505[/C][C]1.44946[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]12.678[/C][C]-3.67799[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.4627[/C][C]1.53734[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]14.2974[/C][C]-3.29737[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]14.0889[/C][C]-4.08889[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]13.7073[/C][C]-2.70734[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.062[/C][C]1.93805[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.5803[/C][C]2.41969[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.4924[/C][C]-0.492428[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]12.7941[/C][C]-4.79409[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]14.7046[/C][C]0.295416[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]13.3019[/C][C]-2.30188[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]12.956[/C][C]3.04404[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]13.711[/C][C]-3.71101[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]13.2612[/C][C]1.73881[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]10.9911[/C][C]-1.99108[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]12.7515[/C][C]3.24849[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]12.349[/C][C]6.65104[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.2059[/C][C]-1.2059[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]12.266[/C][C]-4.26602[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.1251[/C][C]-2.12514[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.2864[/C][C]0.713568[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]12.6843[/C][C]-3.68427[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]12.709[/C][C]2.29095[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]14.6828[/C][C]-1.6828[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]13.3561[/C][C]2.64388[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.1253[/C][C]-2.12526[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.58[/C][C]0.419966[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]12.1224[/C][C]0.877617[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]13.7472[/C][C]-3.74717[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.0836[/C][C]-2.08362[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]13.5199[/C][C]-1.51993[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]12.1313[/C][C]-4.13128[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.662[/C][C]0.338045[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]13.2634[/C][C]-1.2634[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]14.1267[/C][C]0.873349[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]12.8733[/C][C]-1.87325[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]13.2602[/C][C]-0.260239[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]11.3623[/C][C]2.63772[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]11.1878[/C][C]-1.18777[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.4768[/C][C]0.523178[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.743[/C][C]2.25695[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]13.3081[/C][C]-0.308146[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]12.857[/C][C]0.143014[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.9776[/C][C]-0.977621[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.0392[/C][C]-1.03919[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]13.4756[/C][C]-1.47558[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]13.8677[/C][C]-4.86775[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]12.8999[/C][C]-3.89991[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]13.1832[/C][C]1.81678[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]12.4887[/C][C]-2.48868[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]12.6415[/C][C]1.35848[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]12.8243[/C][C]2.17571[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]12.6217[/C][C]-5.62172[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.5807[/C][C]0.419257[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226732&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226732&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
11412.18011.81987
21814.87193.12811
31114.044-3.04405
41213.5663-1.5663
51613.49132.50867
61813.79784.20215
71413.57790.422062
81414.4796-0.479582
91513.43341.56659
101514.22280.777248
111714.52162.47844
121913.16875.83133
131013.4835-3.48355
141613.16322.83685
151815.05012.94989
161413.05030.949736
171413.67210.327904
181715.97481.0252
191414.1019-0.101933
201613.18032.81974
211813.17744.82258
221113.6456-2.64556
231413.69160.308364
241213.3691-1.36911
251714.84732.15269
26914.9626-5.96256
271614.29411.70595
281413.78290.217139
291513.94091.05912
301113.323-2.32297
311614.11031.88968
321312.01870.981296
331713.26233.73767
341514.7770.22304
351413.65670.343337
361612.85363.14641
37911.6774-2.6774
381513.63911.36093
391713.99263.00741
401314.0336-1.03362
411513.84851.15148
421613.8042.19595
431613.80122.1988
441212.6077-0.607685
451513.15641.84364
461112.9166-1.91659
471513.3351.66502
481514.12750.87249
491713.85533.14475
501313.9506-0.950599
511613.91452.08551
521413.37650.62346
531112.2007-1.20069
541213.4513-1.45125
551211.94870.0512795
561514.160.839981
571613.93812.0619
581513.53131.46869
591213.9589-1.95886
601214.102-2.10199
61811.4871-3.4871
621314.4841-1.48407
631114.4525-3.45252
641412.46731.53267
651512.51082.48917
661014.7701-4.77013
671114.0789-3.07887
681214.431-2.43097
691512.52562.47436
701513.90741.09256
711412.64721.35276
721612.61193.38811
731514.60150.398465
741514.4480.551992
751314.6353-1.63533
761215.0305-3.03047
771713.64063.3594
781313.8235-0.823512
791513.41621.58382
801313.1525-0.152481
811514.02490.975103
821514.02850.971481
831613.93382.06625
841513.90731.09271
851413.86790.132063
861514.01030.989738
871413.74340.256595
881312.88290.117141
89713.2582-6.25818
901713.19883.80119
911313.1289-0.128906
921514.57730.422695
931413.90690.093052
941313.6919-0.691936
951614.65981.34017
961214.1216-2.12158
971414.0073-0.00729357
981714.68762.31236
991513.75081.24923
1001714.59022.40984
1011213.8098-1.80983
1021615.70330.296718
1031113.2795-2.27949
1041514.60720.392826
105913.0027-4.00269
1061614.62971.37028
1071514.21240.787629
1081013.1781-3.17812
1091011.6746-1.6746
1101514.65960.340355
1111113.9578-2.95784
1121315.3275-2.32747
1131410.88723.11284
1141813.59474.40529
1151615.30640.693562
1161412.70151.29852
1171412.97811.02193
1181413.22110.778882
1191415.2234-1.22339
1201212.4829-0.482889
1211413.6940.305977
1221514.65460.345411
1231514.34960.65038
1241514.09550.904522
1251313.9193-0.91935
1261715.09891.90107
1271714.70982.29023
1281914.50974.49034
1291512.8632.13703
1301313.8847-0.884686
131912.1646-3.16457
1321514.74550.254521
1331512.1072.89305
1341513.89841.10158
1351614.4361.56403
1361112.1758-1.17578
1371412.89031.10973
1381111.8021-0.802109
1391512.73092.26908
1401312.90470.0953188
1411512.46362.53637
1421614.42911.57091
1431414.8581-0.858135
1441514.28370.716317
1451613.67762.32237
1461614.53231.46771
1471112.7349-1.73486
1481214.2622-2.26218
149913.1173-4.11731
1501613.82552.17455
1511314.5196-1.51965
1521614.15691.84313
1531213.7115-1.71154
154913.6095-4.60951
1551313.0811-0.081093
1561313.3465-0.346506
1571412.80341.19663
1581914.35544.64457
1591314.6761-1.67609
1601214.0749-2.07487
1611312.86950.130518
1621012.7391-2.73912
1631413.54310.456866
1641615.12830.871702
1651013.4681-3.46807
1661111.3363-0.336298
1671413.76960.230444
1681212.9313-0.931273
169913.6657-4.66566
170913.8408-4.84085
1711112.2446-1.24464
1721614.28191.71811
173913.4751-4.47506
1741311.59611.4039
1751613.20042.79962
1761314.2784-1.27837
177912.7029-3.70288
1781212.8711-0.87109
1791613.12822.87183
1801113.6916-2.69157
1811412.62721.37285
1821312.74950.25051
1831514.33260.667366
1841414.6059-0.605907
1851612.55623.44378
1861314.2076-1.20762
1871414.3619-0.361888
1881514.47350.526508
1891311.27211.72792
1901112.319-1.31905
1911111.447-0.446952
1921414.5642-0.56418
1931512.57862.42142
1941113.4853-2.48528
1951513.27891.72107
1961214.0089-2.00886
1971414.0292-0.0292405
1981414.92-0.919989
199812.9199-4.91993
2001314.1595-1.15952
201913.2567-4.25675
2021513.03461.96537
2031713.13483.86519
2041312.28240.717644
2051513.39361.6064
2061513.9671.03302
2071414.8144-0.814356
2081613.02462.97535
2091312.58370.416257
2101614.55051.44946
211912.678-3.67799
2121614.46271.53734
2131114.2974-3.29737
2141014.0889-4.08889
2151113.7073-2.70734
2161513.0621.93805
2171714.58032.41969
2181414.4924-0.492428
219812.7941-4.79409
2201514.70460.295416
2211113.3019-2.30188
2221612.9563.04404
2231013.711-3.71101
2241513.26121.73881
225910.9911-1.99108
2261612.75153.24849
2271912.3496.65104
2281213.2059-1.2059
229812.266-4.26602
2301113.1251-2.12514
2311413.28640.713568
232912.6843-3.68427
2331512.7092.29095
2341314.6828-1.6828
2351613.35612.64388
2361113.1253-2.12526
2371211.580.419966
2381312.12240.877617
2391013.7472-3.74717
2401113.0836-2.08362
2411213.5199-1.51993
242812.1313-4.13128
2431211.6620.338045
2441213.2634-1.2634
2451514.12670.873349
2461112.8733-1.87325
2471313.2602-0.260239
2481411.36232.63772
2491011.1878-1.18777
2501211.47680.523178
2511512.7432.25695
2521313.3081-0.308146
2531312.8570.143014
2541313.9776-0.977621
2551213.0392-1.03919
2561213.4756-1.47558
257913.8677-4.86775
258912.8999-3.89991
2591513.18321.81678
2601012.4887-2.48868
2611412.64151.35848
2621512.82432.17571
263712.6217-5.62172
2641413.58070.419257






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.7889770.4220470.211023
130.872780.2544410.12722
140.797730.404540.20227
150.8054470.3891050.194553
160.7366690.5266620.263331
170.6724470.6551060.327553
180.6396010.7207990.360399
190.55080.89840.4492
200.5116690.9766620.488331
210.8008120.3983760.199188
220.8934120.2131760.106588
230.8542740.2914520.145726
240.8453730.3092540.154627
250.8028950.394210.197105
260.9790590.04188210.0209411
270.9699710.06005870.0300294
280.9582510.08349880.0417494
290.9426770.1146470.0573234
300.952010.09597940.0479897
310.9364440.1271110.0635556
320.9179760.1640480.0820239
330.9105480.1789040.0894522
340.8853830.2292330.114617
350.8661560.2676890.133844
360.8415430.3169130.158457
370.8964950.207010.103505
380.8754960.2490070.124504
390.8743530.2512930.125647
400.8674860.2650270.132514
410.8390140.3219720.160986
420.824610.3507790.17539
430.8121690.3756610.187831
440.7899130.4201730.210087
450.7577320.4845360.242268
460.7591350.481730.240865
470.7250950.5498090.274905
480.6840890.6318220.315911
490.6821090.6357820.317891
500.6492420.7015170.350758
510.6197450.760510.380255
520.5750970.8498050.424903
530.5597970.8804070.440203
540.5207870.9584250.479213
550.4897560.9795130.510244
560.4500080.9000160.549992
570.4176550.8353110.582345
580.3997520.7995040.600248
590.4226730.8453460.577327
600.4425760.8851510.557424
610.5163840.9672330.483616
620.4950990.9901980.504901
630.591480.817040.40852
640.5635520.8728970.436448
650.5546850.890630.445315
660.673680.652640.32632
670.7111930.5776140.288807
680.7214770.5570460.278523
690.7046160.5907680.295384
700.6788350.642330.321165
710.645390.7092210.35461
720.6691650.661670.330835
730.6347370.7305260.365263
740.5980480.8039050.401952
750.5756170.8487650.424383
760.6087890.7824220.391211
770.6231010.7537970.376899
780.5863290.8273420.413671
790.5620840.8758320.437916
800.5224510.9550990.477549
810.4882610.9765220.511739
820.4556760.9113530.544324
830.4408050.8816110.559195
840.4075480.8150960.592452
850.3718740.7437480.628126
860.3386760.6773510.661324
870.3044360.6088720.695564
880.2714550.5429090.728545
890.5329670.9340650.467033
900.5793140.8413720.420686
910.541930.9161410.45807
920.5080850.9838310.491915
930.4701950.9403890.529805
940.4342350.868470.565765
950.4039770.8079540.596023
960.4007020.8014040.599298
970.3656770.7313540.634323
980.3678310.7356620.632169
990.3386740.6773470.661326
1000.3383160.6766310.661684
1010.3350340.6700680.664966
1020.3038480.6076950.696152
1030.2988060.5976120.701194
1040.2697410.5394810.730259
1050.3444740.6889480.655526
1060.3231360.6462730.676864
1070.29550.5910010.7045
1080.3260980.6521970.673902
1090.3316880.6633770.668312
1100.2997190.5994390.700281
1110.3210240.6420470.678976
1120.3354520.6709030.664548
1130.3594380.7188760.640562
1140.4349240.8698470.565076
1150.4034820.8069640.596518
1160.380870.761740.61913
1170.3549130.7098260.645087
1180.3258150.651630.674185
1190.3051160.6102330.694884
1200.2786180.5572350.721382
1210.2500090.5000180.749991
1220.2251210.4502410.774879
1230.2025020.4050030.797498
1240.1825280.3650560.817472
1250.1626240.3252490.837376
1260.1541110.3082220.845889
1270.1552190.3104390.844781
1280.2127920.4255840.787208
1290.2082940.4165890.791706
1300.1865950.373190.813405
1310.2159840.4319680.784016
1320.1932920.3865850.806708
1330.206220.412440.79378
1340.1907670.3815340.809233
1350.1777590.3555180.822241
1360.1621610.3243210.837839
1370.1491710.2983420.850829
1380.1327960.2655910.867204
1390.1293440.2586890.870656
1400.1123070.2246150.887693
1410.1182220.2364440.881778
1420.1088980.2177960.891102
1430.09427010.188540.90573
1440.08216670.1643330.917833
1450.0819350.163870.918065
1460.07739740.1547950.922603
1470.07149890.1429980.928501
1480.06975730.1395150.930243
1490.100910.201820.89909
1500.1026410.2052820.897359
1510.09257320.1851460.907427
1520.08795990.175920.91204
1530.0850330.1700660.914967
1540.1293870.2587750.870613
1550.1116650.223330.888335
1560.09525070.1905010.904749
1570.08736170.1747230.912638
1580.1502650.3005290.849735
1590.1389010.2778030.861099
1600.1364750.2729490.863525
1610.1212750.2425490.878725
1620.1302790.2605580.869721
1630.1120830.2241670.887917
1640.09912410.1982480.900876
1650.111890.2237790.88811
1660.09572910.1914580.904271
1670.08114030.1622810.91886
1680.07311590.1462320.926884
1690.1065590.2131190.893441
1700.1583540.3167080.841646
1710.1423860.2847720.857614
1720.1384340.2768680.861566
1730.1829890.3659780.817011
1740.1638460.3276920.836154
1750.171640.343280.82836
1760.153390.3067790.84661
1770.1786660.3573330.821334
1780.1574760.3149530.842524
1790.1701970.3403950.829803
1800.1713550.3427110.828645
1810.1630030.3260050.836997
1820.1409180.2818350.859082
1830.1261940.2523880.873806
1840.1074730.2149460.892527
1850.1256280.2512550.874372
1860.108650.2173010.89135
1870.09193990.183880.90806
1880.07737620.1547520.922624
1890.07026760.1405350.929732
1900.06150290.1230060.938497
1910.05066430.1013290.949336
1920.04137650.08275310.958623
1930.04191060.08382110.958089
1940.0395360.0790720.960464
1950.03743140.07486280.962569
1960.03313540.06627080.966865
1970.02673630.05347260.973264
1980.02126070.04252140.978739
1990.03849540.07699080.961505
2000.03193760.06387520.968062
2010.04400380.08800770.955996
2020.0405740.0811480.959426
2030.06430290.1286060.935697
2040.05277930.1055590.947221
2050.04901080.09802160.950989
2060.04251270.08502530.957487
2070.03403640.06807270.965964
2080.03898340.07796670.961017
2090.03250340.06500690.967497
2100.03001110.06002220.969989
2110.03546460.07092920.964535
2120.03796160.07592330.962038
2130.03624410.07248830.963756
2140.05038330.1007670.949617
2150.04732130.09464260.952679
2160.04258960.08517920.95741
2170.05239240.1047850.947608
2180.0414130.0828260.958587
2190.07529060.1505810.924709
2200.06843740.1368750.931563
2210.05673380.1134680.943266
2220.07623280.1524660.923767
2230.09758560.1951710.902414
2240.09781940.1956390.902181
2250.08644310.1728860.913557
2260.157520.3150390.84248
2270.3941490.7882980.605851
2280.3425970.6851950.657403
2290.425830.8516610.57417
2300.3759750.751950.624025
2310.3284320.6568650.671568
2320.3412730.6825450.658727
2330.3890.7780010.611
2340.3322580.6645160.667742
2350.3735020.7470040.626498
2360.345090.6901810.65491
2370.2856470.5712940.714353
2380.2499130.4998250.750087
2390.3409510.6819020.659049
2400.294040.5880790.70596
2410.2438120.4876240.756188
2420.282950.56590.71705
2430.2472970.4945950.752703
2440.1921080.3842160.807892
2450.219540.439080.78046
2460.1853020.3706050.814698
2470.1289340.2578670.871066
2480.1956860.3913720.804314
2490.1707710.3415420.829229
2500.1236830.2473670.876317
2510.07614560.1522910.923854
2520.03925520.07851040.960745

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.788977 & 0.422047 & 0.211023 \tabularnewline
13 & 0.87278 & 0.254441 & 0.12722 \tabularnewline
14 & 0.79773 & 0.40454 & 0.20227 \tabularnewline
15 & 0.805447 & 0.389105 & 0.194553 \tabularnewline
16 & 0.736669 & 0.526662 & 0.263331 \tabularnewline
17 & 0.672447 & 0.655106 & 0.327553 \tabularnewline
18 & 0.639601 & 0.720799 & 0.360399 \tabularnewline
19 & 0.5508 & 0.8984 & 0.4492 \tabularnewline
20 & 0.511669 & 0.976662 & 0.488331 \tabularnewline
21 & 0.800812 & 0.398376 & 0.199188 \tabularnewline
22 & 0.893412 & 0.213176 & 0.106588 \tabularnewline
23 & 0.854274 & 0.291452 & 0.145726 \tabularnewline
24 & 0.845373 & 0.309254 & 0.154627 \tabularnewline
25 & 0.802895 & 0.39421 & 0.197105 \tabularnewline
26 & 0.979059 & 0.0418821 & 0.0209411 \tabularnewline
27 & 0.969971 & 0.0600587 & 0.0300294 \tabularnewline
28 & 0.958251 & 0.0834988 & 0.0417494 \tabularnewline
29 & 0.942677 & 0.114647 & 0.0573234 \tabularnewline
30 & 0.95201 & 0.0959794 & 0.0479897 \tabularnewline
31 & 0.936444 & 0.127111 & 0.0635556 \tabularnewline
32 & 0.917976 & 0.164048 & 0.0820239 \tabularnewline
33 & 0.910548 & 0.178904 & 0.0894522 \tabularnewline
34 & 0.885383 & 0.229233 & 0.114617 \tabularnewline
35 & 0.866156 & 0.267689 & 0.133844 \tabularnewline
36 & 0.841543 & 0.316913 & 0.158457 \tabularnewline
37 & 0.896495 & 0.20701 & 0.103505 \tabularnewline
38 & 0.875496 & 0.249007 & 0.124504 \tabularnewline
39 & 0.874353 & 0.251293 & 0.125647 \tabularnewline
40 & 0.867486 & 0.265027 & 0.132514 \tabularnewline
41 & 0.839014 & 0.321972 & 0.160986 \tabularnewline
42 & 0.82461 & 0.350779 & 0.17539 \tabularnewline
43 & 0.812169 & 0.375661 & 0.187831 \tabularnewline
44 & 0.789913 & 0.420173 & 0.210087 \tabularnewline
45 & 0.757732 & 0.484536 & 0.242268 \tabularnewline
46 & 0.759135 & 0.48173 & 0.240865 \tabularnewline
47 & 0.725095 & 0.549809 & 0.274905 \tabularnewline
48 & 0.684089 & 0.631822 & 0.315911 \tabularnewline
49 & 0.682109 & 0.635782 & 0.317891 \tabularnewline
50 & 0.649242 & 0.701517 & 0.350758 \tabularnewline
51 & 0.619745 & 0.76051 & 0.380255 \tabularnewline
52 & 0.575097 & 0.849805 & 0.424903 \tabularnewline
53 & 0.559797 & 0.880407 & 0.440203 \tabularnewline
54 & 0.520787 & 0.958425 & 0.479213 \tabularnewline
55 & 0.489756 & 0.979513 & 0.510244 \tabularnewline
56 & 0.450008 & 0.900016 & 0.549992 \tabularnewline
57 & 0.417655 & 0.835311 & 0.582345 \tabularnewline
58 & 0.399752 & 0.799504 & 0.600248 \tabularnewline
59 & 0.422673 & 0.845346 & 0.577327 \tabularnewline
60 & 0.442576 & 0.885151 & 0.557424 \tabularnewline
61 & 0.516384 & 0.967233 & 0.483616 \tabularnewline
62 & 0.495099 & 0.990198 & 0.504901 \tabularnewline
63 & 0.59148 & 0.81704 & 0.40852 \tabularnewline
64 & 0.563552 & 0.872897 & 0.436448 \tabularnewline
65 & 0.554685 & 0.89063 & 0.445315 \tabularnewline
66 & 0.67368 & 0.65264 & 0.32632 \tabularnewline
67 & 0.711193 & 0.577614 & 0.288807 \tabularnewline
68 & 0.721477 & 0.557046 & 0.278523 \tabularnewline
69 & 0.704616 & 0.590768 & 0.295384 \tabularnewline
70 & 0.678835 & 0.64233 & 0.321165 \tabularnewline
71 & 0.64539 & 0.709221 & 0.35461 \tabularnewline
72 & 0.669165 & 0.66167 & 0.330835 \tabularnewline
73 & 0.634737 & 0.730526 & 0.365263 \tabularnewline
74 & 0.598048 & 0.803905 & 0.401952 \tabularnewline
75 & 0.575617 & 0.848765 & 0.424383 \tabularnewline
76 & 0.608789 & 0.782422 & 0.391211 \tabularnewline
77 & 0.623101 & 0.753797 & 0.376899 \tabularnewline
78 & 0.586329 & 0.827342 & 0.413671 \tabularnewline
79 & 0.562084 & 0.875832 & 0.437916 \tabularnewline
80 & 0.522451 & 0.955099 & 0.477549 \tabularnewline
81 & 0.488261 & 0.976522 & 0.511739 \tabularnewline
82 & 0.455676 & 0.911353 & 0.544324 \tabularnewline
83 & 0.440805 & 0.881611 & 0.559195 \tabularnewline
84 & 0.407548 & 0.815096 & 0.592452 \tabularnewline
85 & 0.371874 & 0.743748 & 0.628126 \tabularnewline
86 & 0.338676 & 0.677351 & 0.661324 \tabularnewline
87 & 0.304436 & 0.608872 & 0.695564 \tabularnewline
88 & 0.271455 & 0.542909 & 0.728545 \tabularnewline
89 & 0.532967 & 0.934065 & 0.467033 \tabularnewline
90 & 0.579314 & 0.841372 & 0.420686 \tabularnewline
91 & 0.54193 & 0.916141 & 0.45807 \tabularnewline
92 & 0.508085 & 0.983831 & 0.491915 \tabularnewline
93 & 0.470195 & 0.940389 & 0.529805 \tabularnewline
94 & 0.434235 & 0.86847 & 0.565765 \tabularnewline
95 & 0.403977 & 0.807954 & 0.596023 \tabularnewline
96 & 0.400702 & 0.801404 & 0.599298 \tabularnewline
97 & 0.365677 & 0.731354 & 0.634323 \tabularnewline
98 & 0.367831 & 0.735662 & 0.632169 \tabularnewline
99 & 0.338674 & 0.677347 & 0.661326 \tabularnewline
100 & 0.338316 & 0.676631 & 0.661684 \tabularnewline
101 & 0.335034 & 0.670068 & 0.664966 \tabularnewline
102 & 0.303848 & 0.607695 & 0.696152 \tabularnewline
103 & 0.298806 & 0.597612 & 0.701194 \tabularnewline
104 & 0.269741 & 0.539481 & 0.730259 \tabularnewline
105 & 0.344474 & 0.688948 & 0.655526 \tabularnewline
106 & 0.323136 & 0.646273 & 0.676864 \tabularnewline
107 & 0.2955 & 0.591001 & 0.7045 \tabularnewline
108 & 0.326098 & 0.652197 & 0.673902 \tabularnewline
109 & 0.331688 & 0.663377 & 0.668312 \tabularnewline
110 & 0.299719 & 0.599439 & 0.700281 \tabularnewline
111 & 0.321024 & 0.642047 & 0.678976 \tabularnewline
112 & 0.335452 & 0.670903 & 0.664548 \tabularnewline
113 & 0.359438 & 0.718876 & 0.640562 \tabularnewline
114 & 0.434924 & 0.869847 & 0.565076 \tabularnewline
115 & 0.403482 & 0.806964 & 0.596518 \tabularnewline
116 & 0.38087 & 0.76174 & 0.61913 \tabularnewline
117 & 0.354913 & 0.709826 & 0.645087 \tabularnewline
118 & 0.325815 & 0.65163 & 0.674185 \tabularnewline
119 & 0.305116 & 0.610233 & 0.694884 \tabularnewline
120 & 0.278618 & 0.557235 & 0.721382 \tabularnewline
121 & 0.250009 & 0.500018 & 0.749991 \tabularnewline
122 & 0.225121 & 0.450241 & 0.774879 \tabularnewline
123 & 0.202502 & 0.405003 & 0.797498 \tabularnewline
124 & 0.182528 & 0.365056 & 0.817472 \tabularnewline
125 & 0.162624 & 0.325249 & 0.837376 \tabularnewline
126 & 0.154111 & 0.308222 & 0.845889 \tabularnewline
127 & 0.155219 & 0.310439 & 0.844781 \tabularnewline
128 & 0.212792 & 0.425584 & 0.787208 \tabularnewline
129 & 0.208294 & 0.416589 & 0.791706 \tabularnewline
130 & 0.186595 & 0.37319 & 0.813405 \tabularnewline
131 & 0.215984 & 0.431968 & 0.784016 \tabularnewline
132 & 0.193292 & 0.386585 & 0.806708 \tabularnewline
133 & 0.20622 & 0.41244 & 0.79378 \tabularnewline
134 & 0.190767 & 0.381534 & 0.809233 \tabularnewline
135 & 0.177759 & 0.355518 & 0.822241 \tabularnewline
136 & 0.162161 & 0.324321 & 0.837839 \tabularnewline
137 & 0.149171 & 0.298342 & 0.850829 \tabularnewline
138 & 0.132796 & 0.265591 & 0.867204 \tabularnewline
139 & 0.129344 & 0.258689 & 0.870656 \tabularnewline
140 & 0.112307 & 0.224615 & 0.887693 \tabularnewline
141 & 0.118222 & 0.236444 & 0.881778 \tabularnewline
142 & 0.108898 & 0.217796 & 0.891102 \tabularnewline
143 & 0.0942701 & 0.18854 & 0.90573 \tabularnewline
144 & 0.0821667 & 0.164333 & 0.917833 \tabularnewline
145 & 0.081935 & 0.16387 & 0.918065 \tabularnewline
146 & 0.0773974 & 0.154795 & 0.922603 \tabularnewline
147 & 0.0714989 & 0.142998 & 0.928501 \tabularnewline
148 & 0.0697573 & 0.139515 & 0.930243 \tabularnewline
149 & 0.10091 & 0.20182 & 0.89909 \tabularnewline
150 & 0.102641 & 0.205282 & 0.897359 \tabularnewline
151 & 0.0925732 & 0.185146 & 0.907427 \tabularnewline
152 & 0.0879599 & 0.17592 & 0.91204 \tabularnewline
153 & 0.085033 & 0.170066 & 0.914967 \tabularnewline
154 & 0.129387 & 0.258775 & 0.870613 \tabularnewline
155 & 0.111665 & 0.22333 & 0.888335 \tabularnewline
156 & 0.0952507 & 0.190501 & 0.904749 \tabularnewline
157 & 0.0873617 & 0.174723 & 0.912638 \tabularnewline
158 & 0.150265 & 0.300529 & 0.849735 \tabularnewline
159 & 0.138901 & 0.277803 & 0.861099 \tabularnewline
160 & 0.136475 & 0.272949 & 0.863525 \tabularnewline
161 & 0.121275 & 0.242549 & 0.878725 \tabularnewline
162 & 0.130279 & 0.260558 & 0.869721 \tabularnewline
163 & 0.112083 & 0.224167 & 0.887917 \tabularnewline
164 & 0.0991241 & 0.198248 & 0.900876 \tabularnewline
165 & 0.11189 & 0.223779 & 0.88811 \tabularnewline
166 & 0.0957291 & 0.191458 & 0.904271 \tabularnewline
167 & 0.0811403 & 0.162281 & 0.91886 \tabularnewline
168 & 0.0731159 & 0.146232 & 0.926884 \tabularnewline
169 & 0.106559 & 0.213119 & 0.893441 \tabularnewline
170 & 0.158354 & 0.316708 & 0.841646 \tabularnewline
171 & 0.142386 & 0.284772 & 0.857614 \tabularnewline
172 & 0.138434 & 0.276868 & 0.861566 \tabularnewline
173 & 0.182989 & 0.365978 & 0.817011 \tabularnewline
174 & 0.163846 & 0.327692 & 0.836154 \tabularnewline
175 & 0.17164 & 0.34328 & 0.82836 \tabularnewline
176 & 0.15339 & 0.306779 & 0.84661 \tabularnewline
177 & 0.178666 & 0.357333 & 0.821334 \tabularnewline
178 & 0.157476 & 0.314953 & 0.842524 \tabularnewline
179 & 0.170197 & 0.340395 & 0.829803 \tabularnewline
180 & 0.171355 & 0.342711 & 0.828645 \tabularnewline
181 & 0.163003 & 0.326005 & 0.836997 \tabularnewline
182 & 0.140918 & 0.281835 & 0.859082 \tabularnewline
183 & 0.126194 & 0.252388 & 0.873806 \tabularnewline
184 & 0.107473 & 0.214946 & 0.892527 \tabularnewline
185 & 0.125628 & 0.251255 & 0.874372 \tabularnewline
186 & 0.10865 & 0.217301 & 0.89135 \tabularnewline
187 & 0.0919399 & 0.18388 & 0.90806 \tabularnewline
188 & 0.0773762 & 0.154752 & 0.922624 \tabularnewline
189 & 0.0702676 & 0.140535 & 0.929732 \tabularnewline
190 & 0.0615029 & 0.123006 & 0.938497 \tabularnewline
191 & 0.0506643 & 0.101329 & 0.949336 \tabularnewline
192 & 0.0413765 & 0.0827531 & 0.958623 \tabularnewline
193 & 0.0419106 & 0.0838211 & 0.958089 \tabularnewline
194 & 0.039536 & 0.079072 & 0.960464 \tabularnewline
195 & 0.0374314 & 0.0748628 & 0.962569 \tabularnewline
196 & 0.0331354 & 0.0662708 & 0.966865 \tabularnewline
197 & 0.0267363 & 0.0534726 & 0.973264 \tabularnewline
198 & 0.0212607 & 0.0425214 & 0.978739 \tabularnewline
199 & 0.0384954 & 0.0769908 & 0.961505 \tabularnewline
200 & 0.0319376 & 0.0638752 & 0.968062 \tabularnewline
201 & 0.0440038 & 0.0880077 & 0.955996 \tabularnewline
202 & 0.040574 & 0.081148 & 0.959426 \tabularnewline
203 & 0.0643029 & 0.128606 & 0.935697 \tabularnewline
204 & 0.0527793 & 0.105559 & 0.947221 \tabularnewline
205 & 0.0490108 & 0.0980216 & 0.950989 \tabularnewline
206 & 0.0425127 & 0.0850253 & 0.957487 \tabularnewline
207 & 0.0340364 & 0.0680727 & 0.965964 \tabularnewline
208 & 0.0389834 & 0.0779667 & 0.961017 \tabularnewline
209 & 0.0325034 & 0.0650069 & 0.967497 \tabularnewline
210 & 0.0300111 & 0.0600222 & 0.969989 \tabularnewline
211 & 0.0354646 & 0.0709292 & 0.964535 \tabularnewline
212 & 0.0379616 & 0.0759233 & 0.962038 \tabularnewline
213 & 0.0362441 & 0.0724883 & 0.963756 \tabularnewline
214 & 0.0503833 & 0.100767 & 0.949617 \tabularnewline
215 & 0.0473213 & 0.0946426 & 0.952679 \tabularnewline
216 & 0.0425896 & 0.0851792 & 0.95741 \tabularnewline
217 & 0.0523924 & 0.104785 & 0.947608 \tabularnewline
218 & 0.041413 & 0.082826 & 0.958587 \tabularnewline
219 & 0.0752906 & 0.150581 & 0.924709 \tabularnewline
220 & 0.0684374 & 0.136875 & 0.931563 \tabularnewline
221 & 0.0567338 & 0.113468 & 0.943266 \tabularnewline
222 & 0.0762328 & 0.152466 & 0.923767 \tabularnewline
223 & 0.0975856 & 0.195171 & 0.902414 \tabularnewline
224 & 0.0978194 & 0.195639 & 0.902181 \tabularnewline
225 & 0.0864431 & 0.172886 & 0.913557 \tabularnewline
226 & 0.15752 & 0.315039 & 0.84248 \tabularnewline
227 & 0.394149 & 0.788298 & 0.605851 \tabularnewline
228 & 0.342597 & 0.685195 & 0.657403 \tabularnewline
229 & 0.42583 & 0.851661 & 0.57417 \tabularnewline
230 & 0.375975 & 0.75195 & 0.624025 \tabularnewline
231 & 0.328432 & 0.656865 & 0.671568 \tabularnewline
232 & 0.341273 & 0.682545 & 0.658727 \tabularnewline
233 & 0.389 & 0.778001 & 0.611 \tabularnewline
234 & 0.332258 & 0.664516 & 0.667742 \tabularnewline
235 & 0.373502 & 0.747004 & 0.626498 \tabularnewline
236 & 0.34509 & 0.690181 & 0.65491 \tabularnewline
237 & 0.285647 & 0.571294 & 0.714353 \tabularnewline
238 & 0.249913 & 0.499825 & 0.750087 \tabularnewline
239 & 0.340951 & 0.681902 & 0.659049 \tabularnewline
240 & 0.29404 & 0.588079 & 0.70596 \tabularnewline
241 & 0.243812 & 0.487624 & 0.756188 \tabularnewline
242 & 0.28295 & 0.5659 & 0.71705 \tabularnewline
243 & 0.247297 & 0.494595 & 0.752703 \tabularnewline
244 & 0.192108 & 0.384216 & 0.807892 \tabularnewline
245 & 0.21954 & 0.43908 & 0.78046 \tabularnewline
246 & 0.185302 & 0.370605 & 0.814698 \tabularnewline
247 & 0.128934 & 0.257867 & 0.871066 \tabularnewline
248 & 0.195686 & 0.391372 & 0.804314 \tabularnewline
249 & 0.170771 & 0.341542 & 0.829229 \tabularnewline
250 & 0.123683 & 0.247367 & 0.876317 \tabularnewline
251 & 0.0761456 & 0.152291 & 0.923854 \tabularnewline
252 & 0.0392552 & 0.0785104 & 0.960745 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226732&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]12[/C][C]0.788977[/C][C]0.422047[/C][C]0.211023[/C][/ROW]
[ROW][C]13[/C][C]0.87278[/C][C]0.254441[/C][C]0.12722[/C][/ROW]
[ROW][C]14[/C][C]0.79773[/C][C]0.40454[/C][C]0.20227[/C][/ROW]
[ROW][C]15[/C][C]0.805447[/C][C]0.389105[/C][C]0.194553[/C][/ROW]
[ROW][C]16[/C][C]0.736669[/C][C]0.526662[/C][C]0.263331[/C][/ROW]
[ROW][C]17[/C][C]0.672447[/C][C]0.655106[/C][C]0.327553[/C][/ROW]
[ROW][C]18[/C][C]0.639601[/C][C]0.720799[/C][C]0.360399[/C][/ROW]
[ROW][C]19[/C][C]0.5508[/C][C]0.8984[/C][C]0.4492[/C][/ROW]
[ROW][C]20[/C][C]0.511669[/C][C]0.976662[/C][C]0.488331[/C][/ROW]
[ROW][C]21[/C][C]0.800812[/C][C]0.398376[/C][C]0.199188[/C][/ROW]
[ROW][C]22[/C][C]0.893412[/C][C]0.213176[/C][C]0.106588[/C][/ROW]
[ROW][C]23[/C][C]0.854274[/C][C]0.291452[/C][C]0.145726[/C][/ROW]
[ROW][C]24[/C][C]0.845373[/C][C]0.309254[/C][C]0.154627[/C][/ROW]
[ROW][C]25[/C][C]0.802895[/C][C]0.39421[/C][C]0.197105[/C][/ROW]
[ROW][C]26[/C][C]0.979059[/C][C]0.0418821[/C][C]0.0209411[/C][/ROW]
[ROW][C]27[/C][C]0.969971[/C][C]0.0600587[/C][C]0.0300294[/C][/ROW]
[ROW][C]28[/C][C]0.958251[/C][C]0.0834988[/C][C]0.0417494[/C][/ROW]
[ROW][C]29[/C][C]0.942677[/C][C]0.114647[/C][C]0.0573234[/C][/ROW]
[ROW][C]30[/C][C]0.95201[/C][C]0.0959794[/C][C]0.0479897[/C][/ROW]
[ROW][C]31[/C][C]0.936444[/C][C]0.127111[/C][C]0.0635556[/C][/ROW]
[ROW][C]32[/C][C]0.917976[/C][C]0.164048[/C][C]0.0820239[/C][/ROW]
[ROW][C]33[/C][C]0.910548[/C][C]0.178904[/C][C]0.0894522[/C][/ROW]
[ROW][C]34[/C][C]0.885383[/C][C]0.229233[/C][C]0.114617[/C][/ROW]
[ROW][C]35[/C][C]0.866156[/C][C]0.267689[/C][C]0.133844[/C][/ROW]
[ROW][C]36[/C][C]0.841543[/C][C]0.316913[/C][C]0.158457[/C][/ROW]
[ROW][C]37[/C][C]0.896495[/C][C]0.20701[/C][C]0.103505[/C][/ROW]
[ROW][C]38[/C][C]0.875496[/C][C]0.249007[/C][C]0.124504[/C][/ROW]
[ROW][C]39[/C][C]0.874353[/C][C]0.251293[/C][C]0.125647[/C][/ROW]
[ROW][C]40[/C][C]0.867486[/C][C]0.265027[/C][C]0.132514[/C][/ROW]
[ROW][C]41[/C][C]0.839014[/C][C]0.321972[/C][C]0.160986[/C][/ROW]
[ROW][C]42[/C][C]0.82461[/C][C]0.350779[/C][C]0.17539[/C][/ROW]
[ROW][C]43[/C][C]0.812169[/C][C]0.375661[/C][C]0.187831[/C][/ROW]
[ROW][C]44[/C][C]0.789913[/C][C]0.420173[/C][C]0.210087[/C][/ROW]
[ROW][C]45[/C][C]0.757732[/C][C]0.484536[/C][C]0.242268[/C][/ROW]
[ROW][C]46[/C][C]0.759135[/C][C]0.48173[/C][C]0.240865[/C][/ROW]
[ROW][C]47[/C][C]0.725095[/C][C]0.549809[/C][C]0.274905[/C][/ROW]
[ROW][C]48[/C][C]0.684089[/C][C]0.631822[/C][C]0.315911[/C][/ROW]
[ROW][C]49[/C][C]0.682109[/C][C]0.635782[/C][C]0.317891[/C][/ROW]
[ROW][C]50[/C][C]0.649242[/C][C]0.701517[/C][C]0.350758[/C][/ROW]
[ROW][C]51[/C][C]0.619745[/C][C]0.76051[/C][C]0.380255[/C][/ROW]
[ROW][C]52[/C][C]0.575097[/C][C]0.849805[/C][C]0.424903[/C][/ROW]
[ROW][C]53[/C][C]0.559797[/C][C]0.880407[/C][C]0.440203[/C][/ROW]
[ROW][C]54[/C][C]0.520787[/C][C]0.958425[/C][C]0.479213[/C][/ROW]
[ROW][C]55[/C][C]0.489756[/C][C]0.979513[/C][C]0.510244[/C][/ROW]
[ROW][C]56[/C][C]0.450008[/C][C]0.900016[/C][C]0.549992[/C][/ROW]
[ROW][C]57[/C][C]0.417655[/C][C]0.835311[/C][C]0.582345[/C][/ROW]
[ROW][C]58[/C][C]0.399752[/C][C]0.799504[/C][C]0.600248[/C][/ROW]
[ROW][C]59[/C][C]0.422673[/C][C]0.845346[/C][C]0.577327[/C][/ROW]
[ROW][C]60[/C][C]0.442576[/C][C]0.885151[/C][C]0.557424[/C][/ROW]
[ROW][C]61[/C][C]0.516384[/C][C]0.967233[/C][C]0.483616[/C][/ROW]
[ROW][C]62[/C][C]0.495099[/C][C]0.990198[/C][C]0.504901[/C][/ROW]
[ROW][C]63[/C][C]0.59148[/C][C]0.81704[/C][C]0.40852[/C][/ROW]
[ROW][C]64[/C][C]0.563552[/C][C]0.872897[/C][C]0.436448[/C][/ROW]
[ROW][C]65[/C][C]0.554685[/C][C]0.89063[/C][C]0.445315[/C][/ROW]
[ROW][C]66[/C][C]0.67368[/C][C]0.65264[/C][C]0.32632[/C][/ROW]
[ROW][C]67[/C][C]0.711193[/C][C]0.577614[/C][C]0.288807[/C][/ROW]
[ROW][C]68[/C][C]0.721477[/C][C]0.557046[/C][C]0.278523[/C][/ROW]
[ROW][C]69[/C][C]0.704616[/C][C]0.590768[/C][C]0.295384[/C][/ROW]
[ROW][C]70[/C][C]0.678835[/C][C]0.64233[/C][C]0.321165[/C][/ROW]
[ROW][C]71[/C][C]0.64539[/C][C]0.709221[/C][C]0.35461[/C][/ROW]
[ROW][C]72[/C][C]0.669165[/C][C]0.66167[/C][C]0.330835[/C][/ROW]
[ROW][C]73[/C][C]0.634737[/C][C]0.730526[/C][C]0.365263[/C][/ROW]
[ROW][C]74[/C][C]0.598048[/C][C]0.803905[/C][C]0.401952[/C][/ROW]
[ROW][C]75[/C][C]0.575617[/C][C]0.848765[/C][C]0.424383[/C][/ROW]
[ROW][C]76[/C][C]0.608789[/C][C]0.782422[/C][C]0.391211[/C][/ROW]
[ROW][C]77[/C][C]0.623101[/C][C]0.753797[/C][C]0.376899[/C][/ROW]
[ROW][C]78[/C][C]0.586329[/C][C]0.827342[/C][C]0.413671[/C][/ROW]
[ROW][C]79[/C][C]0.562084[/C][C]0.875832[/C][C]0.437916[/C][/ROW]
[ROW][C]80[/C][C]0.522451[/C][C]0.955099[/C][C]0.477549[/C][/ROW]
[ROW][C]81[/C][C]0.488261[/C][C]0.976522[/C][C]0.511739[/C][/ROW]
[ROW][C]82[/C][C]0.455676[/C][C]0.911353[/C][C]0.544324[/C][/ROW]
[ROW][C]83[/C][C]0.440805[/C][C]0.881611[/C][C]0.559195[/C][/ROW]
[ROW][C]84[/C][C]0.407548[/C][C]0.815096[/C][C]0.592452[/C][/ROW]
[ROW][C]85[/C][C]0.371874[/C][C]0.743748[/C][C]0.628126[/C][/ROW]
[ROW][C]86[/C][C]0.338676[/C][C]0.677351[/C][C]0.661324[/C][/ROW]
[ROW][C]87[/C][C]0.304436[/C][C]0.608872[/C][C]0.695564[/C][/ROW]
[ROW][C]88[/C][C]0.271455[/C][C]0.542909[/C][C]0.728545[/C][/ROW]
[ROW][C]89[/C][C]0.532967[/C][C]0.934065[/C][C]0.467033[/C][/ROW]
[ROW][C]90[/C][C]0.579314[/C][C]0.841372[/C][C]0.420686[/C][/ROW]
[ROW][C]91[/C][C]0.54193[/C][C]0.916141[/C][C]0.45807[/C][/ROW]
[ROW][C]92[/C][C]0.508085[/C][C]0.983831[/C][C]0.491915[/C][/ROW]
[ROW][C]93[/C][C]0.470195[/C][C]0.940389[/C][C]0.529805[/C][/ROW]
[ROW][C]94[/C][C]0.434235[/C][C]0.86847[/C][C]0.565765[/C][/ROW]
[ROW][C]95[/C][C]0.403977[/C][C]0.807954[/C][C]0.596023[/C][/ROW]
[ROW][C]96[/C][C]0.400702[/C][C]0.801404[/C][C]0.599298[/C][/ROW]
[ROW][C]97[/C][C]0.365677[/C][C]0.731354[/C][C]0.634323[/C][/ROW]
[ROW][C]98[/C][C]0.367831[/C][C]0.735662[/C][C]0.632169[/C][/ROW]
[ROW][C]99[/C][C]0.338674[/C][C]0.677347[/C][C]0.661326[/C][/ROW]
[ROW][C]100[/C][C]0.338316[/C][C]0.676631[/C][C]0.661684[/C][/ROW]
[ROW][C]101[/C][C]0.335034[/C][C]0.670068[/C][C]0.664966[/C][/ROW]
[ROW][C]102[/C][C]0.303848[/C][C]0.607695[/C][C]0.696152[/C][/ROW]
[ROW][C]103[/C][C]0.298806[/C][C]0.597612[/C][C]0.701194[/C][/ROW]
[ROW][C]104[/C][C]0.269741[/C][C]0.539481[/C][C]0.730259[/C][/ROW]
[ROW][C]105[/C][C]0.344474[/C][C]0.688948[/C][C]0.655526[/C][/ROW]
[ROW][C]106[/C][C]0.323136[/C][C]0.646273[/C][C]0.676864[/C][/ROW]
[ROW][C]107[/C][C]0.2955[/C][C]0.591001[/C][C]0.7045[/C][/ROW]
[ROW][C]108[/C][C]0.326098[/C][C]0.652197[/C][C]0.673902[/C][/ROW]
[ROW][C]109[/C][C]0.331688[/C][C]0.663377[/C][C]0.668312[/C][/ROW]
[ROW][C]110[/C][C]0.299719[/C][C]0.599439[/C][C]0.700281[/C][/ROW]
[ROW][C]111[/C][C]0.321024[/C][C]0.642047[/C][C]0.678976[/C][/ROW]
[ROW][C]112[/C][C]0.335452[/C][C]0.670903[/C][C]0.664548[/C][/ROW]
[ROW][C]113[/C][C]0.359438[/C][C]0.718876[/C][C]0.640562[/C][/ROW]
[ROW][C]114[/C][C]0.434924[/C][C]0.869847[/C][C]0.565076[/C][/ROW]
[ROW][C]115[/C][C]0.403482[/C][C]0.806964[/C][C]0.596518[/C][/ROW]
[ROW][C]116[/C][C]0.38087[/C][C]0.76174[/C][C]0.61913[/C][/ROW]
[ROW][C]117[/C][C]0.354913[/C][C]0.709826[/C][C]0.645087[/C][/ROW]
[ROW][C]118[/C][C]0.325815[/C][C]0.65163[/C][C]0.674185[/C][/ROW]
[ROW][C]119[/C][C]0.305116[/C][C]0.610233[/C][C]0.694884[/C][/ROW]
[ROW][C]120[/C][C]0.278618[/C][C]0.557235[/C][C]0.721382[/C][/ROW]
[ROW][C]121[/C][C]0.250009[/C][C]0.500018[/C][C]0.749991[/C][/ROW]
[ROW][C]122[/C][C]0.225121[/C][C]0.450241[/C][C]0.774879[/C][/ROW]
[ROW][C]123[/C][C]0.202502[/C][C]0.405003[/C][C]0.797498[/C][/ROW]
[ROW][C]124[/C][C]0.182528[/C][C]0.365056[/C][C]0.817472[/C][/ROW]
[ROW][C]125[/C][C]0.162624[/C][C]0.325249[/C][C]0.837376[/C][/ROW]
[ROW][C]126[/C][C]0.154111[/C][C]0.308222[/C][C]0.845889[/C][/ROW]
[ROW][C]127[/C][C]0.155219[/C][C]0.310439[/C][C]0.844781[/C][/ROW]
[ROW][C]128[/C][C]0.212792[/C][C]0.425584[/C][C]0.787208[/C][/ROW]
[ROW][C]129[/C][C]0.208294[/C][C]0.416589[/C][C]0.791706[/C][/ROW]
[ROW][C]130[/C][C]0.186595[/C][C]0.37319[/C][C]0.813405[/C][/ROW]
[ROW][C]131[/C][C]0.215984[/C][C]0.431968[/C][C]0.784016[/C][/ROW]
[ROW][C]132[/C][C]0.193292[/C][C]0.386585[/C][C]0.806708[/C][/ROW]
[ROW][C]133[/C][C]0.20622[/C][C]0.41244[/C][C]0.79378[/C][/ROW]
[ROW][C]134[/C][C]0.190767[/C][C]0.381534[/C][C]0.809233[/C][/ROW]
[ROW][C]135[/C][C]0.177759[/C][C]0.355518[/C][C]0.822241[/C][/ROW]
[ROW][C]136[/C][C]0.162161[/C][C]0.324321[/C][C]0.837839[/C][/ROW]
[ROW][C]137[/C][C]0.149171[/C][C]0.298342[/C][C]0.850829[/C][/ROW]
[ROW][C]138[/C][C]0.132796[/C][C]0.265591[/C][C]0.867204[/C][/ROW]
[ROW][C]139[/C][C]0.129344[/C][C]0.258689[/C][C]0.870656[/C][/ROW]
[ROW][C]140[/C][C]0.112307[/C][C]0.224615[/C][C]0.887693[/C][/ROW]
[ROW][C]141[/C][C]0.118222[/C][C]0.236444[/C][C]0.881778[/C][/ROW]
[ROW][C]142[/C][C]0.108898[/C][C]0.217796[/C][C]0.891102[/C][/ROW]
[ROW][C]143[/C][C]0.0942701[/C][C]0.18854[/C][C]0.90573[/C][/ROW]
[ROW][C]144[/C][C]0.0821667[/C][C]0.164333[/C][C]0.917833[/C][/ROW]
[ROW][C]145[/C][C]0.081935[/C][C]0.16387[/C][C]0.918065[/C][/ROW]
[ROW][C]146[/C][C]0.0773974[/C][C]0.154795[/C][C]0.922603[/C][/ROW]
[ROW][C]147[/C][C]0.0714989[/C][C]0.142998[/C][C]0.928501[/C][/ROW]
[ROW][C]148[/C][C]0.0697573[/C][C]0.139515[/C][C]0.930243[/C][/ROW]
[ROW][C]149[/C][C]0.10091[/C][C]0.20182[/C][C]0.89909[/C][/ROW]
[ROW][C]150[/C][C]0.102641[/C][C]0.205282[/C][C]0.897359[/C][/ROW]
[ROW][C]151[/C][C]0.0925732[/C][C]0.185146[/C][C]0.907427[/C][/ROW]
[ROW][C]152[/C][C]0.0879599[/C][C]0.17592[/C][C]0.91204[/C][/ROW]
[ROW][C]153[/C][C]0.085033[/C][C]0.170066[/C][C]0.914967[/C][/ROW]
[ROW][C]154[/C][C]0.129387[/C][C]0.258775[/C][C]0.870613[/C][/ROW]
[ROW][C]155[/C][C]0.111665[/C][C]0.22333[/C][C]0.888335[/C][/ROW]
[ROW][C]156[/C][C]0.0952507[/C][C]0.190501[/C][C]0.904749[/C][/ROW]
[ROW][C]157[/C][C]0.0873617[/C][C]0.174723[/C][C]0.912638[/C][/ROW]
[ROW][C]158[/C][C]0.150265[/C][C]0.300529[/C][C]0.849735[/C][/ROW]
[ROW][C]159[/C][C]0.138901[/C][C]0.277803[/C][C]0.861099[/C][/ROW]
[ROW][C]160[/C][C]0.136475[/C][C]0.272949[/C][C]0.863525[/C][/ROW]
[ROW][C]161[/C][C]0.121275[/C][C]0.242549[/C][C]0.878725[/C][/ROW]
[ROW][C]162[/C][C]0.130279[/C][C]0.260558[/C][C]0.869721[/C][/ROW]
[ROW][C]163[/C][C]0.112083[/C][C]0.224167[/C][C]0.887917[/C][/ROW]
[ROW][C]164[/C][C]0.0991241[/C][C]0.198248[/C][C]0.900876[/C][/ROW]
[ROW][C]165[/C][C]0.11189[/C][C]0.223779[/C][C]0.88811[/C][/ROW]
[ROW][C]166[/C][C]0.0957291[/C][C]0.191458[/C][C]0.904271[/C][/ROW]
[ROW][C]167[/C][C]0.0811403[/C][C]0.162281[/C][C]0.91886[/C][/ROW]
[ROW][C]168[/C][C]0.0731159[/C][C]0.146232[/C][C]0.926884[/C][/ROW]
[ROW][C]169[/C][C]0.106559[/C][C]0.213119[/C][C]0.893441[/C][/ROW]
[ROW][C]170[/C][C]0.158354[/C][C]0.316708[/C][C]0.841646[/C][/ROW]
[ROW][C]171[/C][C]0.142386[/C][C]0.284772[/C][C]0.857614[/C][/ROW]
[ROW][C]172[/C][C]0.138434[/C][C]0.276868[/C][C]0.861566[/C][/ROW]
[ROW][C]173[/C][C]0.182989[/C][C]0.365978[/C][C]0.817011[/C][/ROW]
[ROW][C]174[/C][C]0.163846[/C][C]0.327692[/C][C]0.836154[/C][/ROW]
[ROW][C]175[/C][C]0.17164[/C][C]0.34328[/C][C]0.82836[/C][/ROW]
[ROW][C]176[/C][C]0.15339[/C][C]0.306779[/C][C]0.84661[/C][/ROW]
[ROW][C]177[/C][C]0.178666[/C][C]0.357333[/C][C]0.821334[/C][/ROW]
[ROW][C]178[/C][C]0.157476[/C][C]0.314953[/C][C]0.842524[/C][/ROW]
[ROW][C]179[/C][C]0.170197[/C][C]0.340395[/C][C]0.829803[/C][/ROW]
[ROW][C]180[/C][C]0.171355[/C][C]0.342711[/C][C]0.828645[/C][/ROW]
[ROW][C]181[/C][C]0.163003[/C][C]0.326005[/C][C]0.836997[/C][/ROW]
[ROW][C]182[/C][C]0.140918[/C][C]0.281835[/C][C]0.859082[/C][/ROW]
[ROW][C]183[/C][C]0.126194[/C][C]0.252388[/C][C]0.873806[/C][/ROW]
[ROW][C]184[/C][C]0.107473[/C][C]0.214946[/C][C]0.892527[/C][/ROW]
[ROW][C]185[/C][C]0.125628[/C][C]0.251255[/C][C]0.874372[/C][/ROW]
[ROW][C]186[/C][C]0.10865[/C][C]0.217301[/C][C]0.89135[/C][/ROW]
[ROW][C]187[/C][C]0.0919399[/C][C]0.18388[/C][C]0.90806[/C][/ROW]
[ROW][C]188[/C][C]0.0773762[/C][C]0.154752[/C][C]0.922624[/C][/ROW]
[ROW][C]189[/C][C]0.0702676[/C][C]0.140535[/C][C]0.929732[/C][/ROW]
[ROW][C]190[/C][C]0.0615029[/C][C]0.123006[/C][C]0.938497[/C][/ROW]
[ROW][C]191[/C][C]0.0506643[/C][C]0.101329[/C][C]0.949336[/C][/ROW]
[ROW][C]192[/C][C]0.0413765[/C][C]0.0827531[/C][C]0.958623[/C][/ROW]
[ROW][C]193[/C][C]0.0419106[/C][C]0.0838211[/C][C]0.958089[/C][/ROW]
[ROW][C]194[/C][C]0.039536[/C][C]0.079072[/C][C]0.960464[/C][/ROW]
[ROW][C]195[/C][C]0.0374314[/C][C]0.0748628[/C][C]0.962569[/C][/ROW]
[ROW][C]196[/C][C]0.0331354[/C][C]0.0662708[/C][C]0.966865[/C][/ROW]
[ROW][C]197[/C][C]0.0267363[/C][C]0.0534726[/C][C]0.973264[/C][/ROW]
[ROW][C]198[/C][C]0.0212607[/C][C]0.0425214[/C][C]0.978739[/C][/ROW]
[ROW][C]199[/C][C]0.0384954[/C][C]0.0769908[/C][C]0.961505[/C][/ROW]
[ROW][C]200[/C][C]0.0319376[/C][C]0.0638752[/C][C]0.968062[/C][/ROW]
[ROW][C]201[/C][C]0.0440038[/C][C]0.0880077[/C][C]0.955996[/C][/ROW]
[ROW][C]202[/C][C]0.040574[/C][C]0.081148[/C][C]0.959426[/C][/ROW]
[ROW][C]203[/C][C]0.0643029[/C][C]0.128606[/C][C]0.935697[/C][/ROW]
[ROW][C]204[/C][C]0.0527793[/C][C]0.105559[/C][C]0.947221[/C][/ROW]
[ROW][C]205[/C][C]0.0490108[/C][C]0.0980216[/C][C]0.950989[/C][/ROW]
[ROW][C]206[/C][C]0.0425127[/C][C]0.0850253[/C][C]0.957487[/C][/ROW]
[ROW][C]207[/C][C]0.0340364[/C][C]0.0680727[/C][C]0.965964[/C][/ROW]
[ROW][C]208[/C][C]0.0389834[/C][C]0.0779667[/C][C]0.961017[/C][/ROW]
[ROW][C]209[/C][C]0.0325034[/C][C]0.0650069[/C][C]0.967497[/C][/ROW]
[ROW][C]210[/C][C]0.0300111[/C][C]0.0600222[/C][C]0.969989[/C][/ROW]
[ROW][C]211[/C][C]0.0354646[/C][C]0.0709292[/C][C]0.964535[/C][/ROW]
[ROW][C]212[/C][C]0.0379616[/C][C]0.0759233[/C][C]0.962038[/C][/ROW]
[ROW][C]213[/C][C]0.0362441[/C][C]0.0724883[/C][C]0.963756[/C][/ROW]
[ROW][C]214[/C][C]0.0503833[/C][C]0.100767[/C][C]0.949617[/C][/ROW]
[ROW][C]215[/C][C]0.0473213[/C][C]0.0946426[/C][C]0.952679[/C][/ROW]
[ROW][C]216[/C][C]0.0425896[/C][C]0.0851792[/C][C]0.95741[/C][/ROW]
[ROW][C]217[/C][C]0.0523924[/C][C]0.104785[/C][C]0.947608[/C][/ROW]
[ROW][C]218[/C][C]0.041413[/C][C]0.082826[/C][C]0.958587[/C][/ROW]
[ROW][C]219[/C][C]0.0752906[/C][C]0.150581[/C][C]0.924709[/C][/ROW]
[ROW][C]220[/C][C]0.0684374[/C][C]0.136875[/C][C]0.931563[/C][/ROW]
[ROW][C]221[/C][C]0.0567338[/C][C]0.113468[/C][C]0.943266[/C][/ROW]
[ROW][C]222[/C][C]0.0762328[/C][C]0.152466[/C][C]0.923767[/C][/ROW]
[ROW][C]223[/C][C]0.0975856[/C][C]0.195171[/C][C]0.902414[/C][/ROW]
[ROW][C]224[/C][C]0.0978194[/C][C]0.195639[/C][C]0.902181[/C][/ROW]
[ROW][C]225[/C][C]0.0864431[/C][C]0.172886[/C][C]0.913557[/C][/ROW]
[ROW][C]226[/C][C]0.15752[/C][C]0.315039[/C][C]0.84248[/C][/ROW]
[ROW][C]227[/C][C]0.394149[/C][C]0.788298[/C][C]0.605851[/C][/ROW]
[ROW][C]228[/C][C]0.342597[/C][C]0.685195[/C][C]0.657403[/C][/ROW]
[ROW][C]229[/C][C]0.42583[/C][C]0.851661[/C][C]0.57417[/C][/ROW]
[ROW][C]230[/C][C]0.375975[/C][C]0.75195[/C][C]0.624025[/C][/ROW]
[ROW][C]231[/C][C]0.328432[/C][C]0.656865[/C][C]0.671568[/C][/ROW]
[ROW][C]232[/C][C]0.341273[/C][C]0.682545[/C][C]0.658727[/C][/ROW]
[ROW][C]233[/C][C]0.389[/C][C]0.778001[/C][C]0.611[/C][/ROW]
[ROW][C]234[/C][C]0.332258[/C][C]0.664516[/C][C]0.667742[/C][/ROW]
[ROW][C]235[/C][C]0.373502[/C][C]0.747004[/C][C]0.626498[/C][/ROW]
[ROW][C]236[/C][C]0.34509[/C][C]0.690181[/C][C]0.65491[/C][/ROW]
[ROW][C]237[/C][C]0.285647[/C][C]0.571294[/C][C]0.714353[/C][/ROW]
[ROW][C]238[/C][C]0.249913[/C][C]0.499825[/C][C]0.750087[/C][/ROW]
[ROW][C]239[/C][C]0.340951[/C][C]0.681902[/C][C]0.659049[/C][/ROW]
[ROW][C]240[/C][C]0.29404[/C][C]0.588079[/C][C]0.70596[/C][/ROW]
[ROW][C]241[/C][C]0.243812[/C][C]0.487624[/C][C]0.756188[/C][/ROW]
[ROW][C]242[/C][C]0.28295[/C][C]0.5659[/C][C]0.71705[/C][/ROW]
[ROW][C]243[/C][C]0.247297[/C][C]0.494595[/C][C]0.752703[/C][/ROW]
[ROW][C]244[/C][C]0.192108[/C][C]0.384216[/C][C]0.807892[/C][/ROW]
[ROW][C]245[/C][C]0.21954[/C][C]0.43908[/C][C]0.78046[/C][/ROW]
[ROW][C]246[/C][C]0.185302[/C][C]0.370605[/C][C]0.814698[/C][/ROW]
[ROW][C]247[/C][C]0.128934[/C][C]0.257867[/C][C]0.871066[/C][/ROW]
[ROW][C]248[/C][C]0.195686[/C][C]0.391372[/C][C]0.804314[/C][/ROW]
[ROW][C]249[/C][C]0.170771[/C][C]0.341542[/C][C]0.829229[/C][/ROW]
[ROW][C]250[/C][C]0.123683[/C][C]0.247367[/C][C]0.876317[/C][/ROW]
[ROW][C]251[/C][C]0.0761456[/C][C]0.152291[/C][C]0.923854[/C][/ROW]
[ROW][C]252[/C][C]0.0392552[/C][C]0.0785104[/C][C]0.960745[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226732&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226732&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
120.7889770.4220470.211023
130.872780.2544410.12722
140.797730.404540.20227
150.8054470.3891050.194553
160.7366690.5266620.263331
170.6724470.6551060.327553
180.6396010.7207990.360399
190.55080.89840.4492
200.5116690.9766620.488331
210.8008120.3983760.199188
220.8934120.2131760.106588
230.8542740.2914520.145726
240.8453730.3092540.154627
250.8028950.394210.197105
260.9790590.04188210.0209411
270.9699710.06005870.0300294
280.9582510.08349880.0417494
290.9426770.1146470.0573234
300.952010.09597940.0479897
310.9364440.1271110.0635556
320.9179760.1640480.0820239
330.9105480.1789040.0894522
340.8853830.2292330.114617
350.8661560.2676890.133844
360.8415430.3169130.158457
370.8964950.207010.103505
380.8754960.2490070.124504
390.8743530.2512930.125647
400.8674860.2650270.132514
410.8390140.3219720.160986
420.824610.3507790.17539
430.8121690.3756610.187831
440.7899130.4201730.210087
450.7577320.4845360.242268
460.7591350.481730.240865
470.7250950.5498090.274905
480.6840890.6318220.315911
490.6821090.6357820.317891
500.6492420.7015170.350758
510.6197450.760510.380255
520.5750970.8498050.424903
530.5597970.8804070.440203
540.5207870.9584250.479213
550.4897560.9795130.510244
560.4500080.9000160.549992
570.4176550.8353110.582345
580.3997520.7995040.600248
590.4226730.8453460.577327
600.4425760.8851510.557424
610.5163840.9672330.483616
620.4950990.9901980.504901
630.591480.817040.40852
640.5635520.8728970.436448
650.5546850.890630.445315
660.673680.652640.32632
670.7111930.5776140.288807
680.7214770.5570460.278523
690.7046160.5907680.295384
700.6788350.642330.321165
710.645390.7092210.35461
720.6691650.661670.330835
730.6347370.7305260.365263
740.5980480.8039050.401952
750.5756170.8487650.424383
760.6087890.7824220.391211
770.6231010.7537970.376899
780.5863290.8273420.413671
790.5620840.8758320.437916
800.5224510.9550990.477549
810.4882610.9765220.511739
820.4556760.9113530.544324
830.4408050.8816110.559195
840.4075480.8150960.592452
850.3718740.7437480.628126
860.3386760.6773510.661324
870.3044360.6088720.695564
880.2714550.5429090.728545
890.5329670.9340650.467033
900.5793140.8413720.420686
910.541930.9161410.45807
920.5080850.9838310.491915
930.4701950.9403890.529805
940.4342350.868470.565765
950.4039770.8079540.596023
960.4007020.8014040.599298
970.3656770.7313540.634323
980.3678310.7356620.632169
990.3386740.6773470.661326
1000.3383160.6766310.661684
1010.3350340.6700680.664966
1020.3038480.6076950.696152
1030.2988060.5976120.701194
1040.2697410.5394810.730259
1050.3444740.6889480.655526
1060.3231360.6462730.676864
1070.29550.5910010.7045
1080.3260980.6521970.673902
1090.3316880.6633770.668312
1100.2997190.5994390.700281
1110.3210240.6420470.678976
1120.3354520.6709030.664548
1130.3594380.7188760.640562
1140.4349240.8698470.565076
1150.4034820.8069640.596518
1160.380870.761740.61913
1170.3549130.7098260.645087
1180.3258150.651630.674185
1190.3051160.6102330.694884
1200.2786180.5572350.721382
1210.2500090.5000180.749991
1220.2251210.4502410.774879
1230.2025020.4050030.797498
1240.1825280.3650560.817472
1250.1626240.3252490.837376
1260.1541110.3082220.845889
1270.1552190.3104390.844781
1280.2127920.4255840.787208
1290.2082940.4165890.791706
1300.1865950.373190.813405
1310.2159840.4319680.784016
1320.1932920.3865850.806708
1330.206220.412440.79378
1340.1907670.3815340.809233
1350.1777590.3555180.822241
1360.1621610.3243210.837839
1370.1491710.2983420.850829
1380.1327960.2655910.867204
1390.1293440.2586890.870656
1400.1123070.2246150.887693
1410.1182220.2364440.881778
1420.1088980.2177960.891102
1430.09427010.188540.90573
1440.08216670.1643330.917833
1450.0819350.163870.918065
1460.07739740.1547950.922603
1470.07149890.1429980.928501
1480.06975730.1395150.930243
1490.100910.201820.89909
1500.1026410.2052820.897359
1510.09257320.1851460.907427
1520.08795990.175920.91204
1530.0850330.1700660.914967
1540.1293870.2587750.870613
1550.1116650.223330.888335
1560.09525070.1905010.904749
1570.08736170.1747230.912638
1580.1502650.3005290.849735
1590.1389010.2778030.861099
1600.1364750.2729490.863525
1610.1212750.2425490.878725
1620.1302790.2605580.869721
1630.1120830.2241670.887917
1640.09912410.1982480.900876
1650.111890.2237790.88811
1660.09572910.1914580.904271
1670.08114030.1622810.91886
1680.07311590.1462320.926884
1690.1065590.2131190.893441
1700.1583540.3167080.841646
1710.1423860.2847720.857614
1720.1384340.2768680.861566
1730.1829890.3659780.817011
1740.1638460.3276920.836154
1750.171640.343280.82836
1760.153390.3067790.84661
1770.1786660.3573330.821334
1780.1574760.3149530.842524
1790.1701970.3403950.829803
1800.1713550.3427110.828645
1810.1630030.3260050.836997
1820.1409180.2818350.859082
1830.1261940.2523880.873806
1840.1074730.2149460.892527
1850.1256280.2512550.874372
1860.108650.2173010.89135
1870.09193990.183880.90806
1880.07737620.1547520.922624
1890.07026760.1405350.929732
1900.06150290.1230060.938497
1910.05066430.1013290.949336
1920.04137650.08275310.958623
1930.04191060.08382110.958089
1940.0395360.0790720.960464
1950.03743140.07486280.962569
1960.03313540.06627080.966865
1970.02673630.05347260.973264
1980.02126070.04252140.978739
1990.03849540.07699080.961505
2000.03193760.06387520.968062
2010.04400380.08800770.955996
2020.0405740.0811480.959426
2030.06430290.1286060.935697
2040.05277930.1055590.947221
2050.04901080.09802160.950989
2060.04251270.08502530.957487
2070.03403640.06807270.965964
2080.03898340.07796670.961017
2090.03250340.06500690.967497
2100.03001110.06002220.969989
2110.03546460.07092920.964535
2120.03796160.07592330.962038
2130.03624410.07248830.963756
2140.05038330.1007670.949617
2150.04732130.09464260.952679
2160.04258960.08517920.95741
2170.05239240.1047850.947608
2180.0414130.0828260.958587
2190.07529060.1505810.924709
2200.06843740.1368750.931563
2210.05673380.1134680.943266
2220.07623280.1524660.923767
2230.09758560.1951710.902414
2240.09781940.1956390.902181
2250.08644310.1728860.913557
2260.157520.3150390.84248
2270.3941490.7882980.605851
2280.3425970.6851950.657403
2290.425830.8516610.57417
2300.3759750.751950.624025
2310.3284320.6568650.671568
2320.3412730.6825450.658727
2330.3890.7780010.611
2340.3322580.6645160.667742
2350.3735020.7470040.626498
2360.345090.6901810.65491
2370.2856470.5712940.714353
2380.2499130.4998250.750087
2390.3409510.6819020.659049
2400.294040.5880790.70596
2410.2438120.4876240.756188
2420.282950.56590.71705
2430.2472970.4945950.752703
2440.1921080.3842160.807892
2450.219540.439080.78046
2460.1853020.3706050.814698
2470.1289340.2578670.871066
2480.1956860.3913720.804314
2490.1707710.3415420.829229
2500.1236830.2473670.876317
2510.07614560.1522910.923854
2520.03925520.07851040.960745






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level20.00829876OK
10% type I error level280.116183NOK

\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 & 2 & 0.00829876 & OK \tabularnewline
10% type I error level & 28 & 0.116183 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226732&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]2[/C][C]0.00829876[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]28[/C][C]0.116183[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226732&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226732&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 level20.00829876OK
10% type I error level280.116183NOK


Figures (Output of Computation)

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

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