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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 17 Nov 2013 09:41:28 -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/17/t13846993082q6pabvpm3376zb.htm/, Retrieved Sun, 28 Apr 2024 20:04:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=225764, Retrieved Sun, 28 Apr 2024 20:04:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [ws 7 ] [2013-11-17 14:41:28] [3ab494e3ec4169588a52211572c2f14a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41 38 13 12 14 12 9 32
39 32 16 11 18 11 9 51
30 35 19 15 11 14 9 42
31 33 15 6 12 12 9 41
34 37 14 13 16 21 9 46
35 29 13 10 18 12 9 47
39 31 19 12 14 22 9 37
34 36 15 14 14 11 9 49
36 35 14 12 15 10 9 45
37 38 15 9 15 13 9 47
38 31 16 10 17 10 9 49
36 34 16 12 19 8 9 33
38 35 16 12 10 15 9 42
39 38 16 11 16 14 9 33
33 37 17 15 18 10 9 53
32 33 15 12 14 14 9 36
36 32 15 10 14 14 9 45
38 38 20 12 17 11 9 54
39 38 18 11 14 10 9 41
32 32 16 12 16 13 9 36
32 33 16 11 18 9.5 9 41
31 31 16 12 11 14 9 44
39 38 19 13 14 12 9 33
37 39 16 11 12 14 9 37
39 32 17 12 17 11 9 52
41 32 17 13 9 9 9 47
36 35 16 10 16 11 9 43
33 37 15 14 14 15 9 44
33 33 16 12 15 14 9 45
34 33 14 10 11 13 9 44
31 31 15 12 16 9 9 49
27 32 12 8 13 15 9 33
37 31 14 10 17 10 9 43
34 37 16 12 15 11 9 54
34 30 14 12 14 13 9 42
32 33 10 7 16 8 9 44
29 31 10 9 9 20 9 37
36 33 14 12 15 12 9 43
29 31 16 10 17 10 9 46
35 33 16 10 13 10 9 42
37 32 16 10 15 9 9 45
34 33 14 12 16 14 9 44
38 32 20 15 16 8 9 33
35 33 14 10 12 14 9 31
38 28 14 10 15 11 9 42
37 35 11 12 11 13 9 40
38 39 14 13 15 9 9 43
33 34 15 11 15 11 9 46
36 38 16 11 17 15 9 42
38 32 14 12 13 11 9 45
32 38 16 14 16 10 9 44
32 30 14 10 14 14 9 40
32 33 12 12 11 18 9 37
34 38 16 13 12 14 9 46
32 32 9 5 12 11 9 36
37 35 14 6 15 14.5 9 47
39 34 16 12 16 13 9 45
29 34 16 12 15 9 9 42
37 36 15 11 12 10 9 43
35 34 16 10 12 15 9 43
30 28 12 7 8 20 9 32
38 34 16 12 13 12 9 45
34 35 16 14 11 12 9 48
31 35 14 11 14 14 9 31
34 31 16 12 15 13 9 33
35 37 17 13 10 11 10 49
36 35 18 14 11 17 10 42
30 27 18 11 12 12 10 41
39 40 12 12 15 13 10 38
35 37 16 12 15 14 10 42
38 36 10 8 14 13 10 44
31 38 14 11 16 15 10 33
34 39 18 14 15 13 10 48
38 41 18 14 15 10 10 40
34 27 16 12 13 11 10 50
39 30 17 9 12 19 10 49
37 37 16 13 17 13 10 43
34 31 16 11 13 17 10 44
28 31 13 12 15 13 10 47
37 27 16 12 13 9 10 33
33 36 16 12 15 11 10 46
35 37 16 12 15 9 10 45
37 33 15 12 16 12 10 43
32 34 15 11 15 12 10 44
33 31 16 10 14 13 10 47
38 39 14 9 15 13 10 45
33 34 16 12 14 12 10 42
29 32 16 12 13 15 10 33
33 33 15 12 7 22 10 43
31 36 12 9 17 13 10 46
36 32 17 15 13 15 10 33
35 41 16 12 15 13 10 46
32 28 15 12 14 15 10 48
29 30 13 12 13 12.5 10 47
39 36 16 10 16 11 10 47
37 35 16 13 12 16 10 43
35 31 16 9 14 11 10 46
37 34 16 12 17 11 10 48
32 36 14 10 15 10 10 46
38 36 16 14 17 10 10 45
37 35 16 11 12 16 10 45
36 37 20 15 16 12 10 52
32 28 15 11 11 11 10 42
33 39 16 11 15 16 10 47
40 32 13 12 9 19 10 41
38 35 17 12 16 11 10 47
41 39 16 12 15 16 10 43
36 35 16 11 10 15 10 33
43 42 12 7 10 24 10 30
30 34 16 12 15 14 10 52
31 33 16 14 11 15 10 44
32 41 17 11 13 11 10 55
32 33 13 11 14 15 10 11
37 34 12 10 18 12 10 47
37 32 18 13 16 10 10 53
33 40 14 13 14 14 10 33
34 40 14 8 14 13 10 44
33 35 13 11 14 9 10 42
38 36 16 12 14 15 10 55
33 37 13 11 12 15 10 33
31 27 16 13 14 14 10 46
38 39 13 12 15 11 10 54
37 38 16 14 15 8 10 47
36 31 15 13 15 11 10 45
31 33 16 15 13 11 10 47
39 32 15 10 17 8 10 55
44 39 17 11 17 10 10 44
33 36 15 9 19 11 10 53
35 33 12 11 15 13 10 44
32 33 16 10 13 11 10 42
28 32 10 11 9 20 10 40
40 37 16 8 15 10 10 46
27 30 12 11 15 15 10 40
37 38 14 12 15 12 10 46
32 29 15 12 16 14 10 53
28 22 13 9 11 23 10 33
34 35 15 11 14 14 10 42
30 35 11 10 11 16 10 35
35 34 12 8 15 11 10 40
31 35 11 9 13 12 10 41
32 34 16 8 15 10 10 33
30 37 15 9 16 14 10 51
30 35 17 15 14 12 10 53
31 23 16 11 15 12 10 46
40 31 10 8 16 11 10 55
32 27 18 13 16 12 10 47
36 36 13 12 11 13 10 38
32 31 16 12 12 11 10 46
35 32 13 9 9 19 10 46
38 39 10 7 16 12 10 53
42 37 15 13 13 17 10 47
34 38 16 9 16 9 10 41
35 39 16 6 12 12 10 44
38 34 14 8 9 19 9 43
33 31 10 8 13 18 10 51
36 32 17 15 13 15 10 33
32 37 13 6 14 14 10 43
33 36 15 9 19 11 10 53
34 32 16 11 13 9 10 51
32 38 12 8 12 18 10 50
34 36 13 8 13 16 10 46
27 26 13 10 10 24 11 43
31 26 12 8 14 14 11 47
38 33 17 14 16 20 11 50
34 39 15 10 10 18 11 43
24 30 10 8 11 23 11 33
30 33 14 11 14 12 11 48
26 25 11 12 12 14 11 44
34 38 13 12 9 16 11 50
27 37 16 12 9 18 11 41
37 31 12 5 11 20 11 34
36 37 16 12 16 12 11 44
41 35 12 10 9 12 11 47
29 25 9 7 13 17 11 35
36 28 12 12 16 13 11 44
32 35 15 11 13 9 11 44
37 33 12 8 9 16 11 43
30 30 12 9 12 18 11 41
31 31 14 10 16 10 11 41
38 37 12 9 11 14 11 42
36 36 16 12 14 11 11 33
35 30 11 6 13 9 11 41
31 36 19 15 15 11 11 44
38 32 15 12 14 10 11 48
22 28 8 12 16 11 11 55
32 36 16 12 13 19 11 44
36 34 17 11 14 14 11 43
39 31 12 7 15 12 11 52
28 28 11 7 13 14 11 30
32 36 11 5 11 21 11 39
32 36 14 12 11 13 11 11
38 40 16 12 14 10 11 44
32 33 12 3 15 15 11 42
35 37 16 11 11 16 11 41
32 32 13 10 15 14 11 44
37 38 15 12 12 12 11 44
34 31 16 9 14 19 11 48
33 37 16 12 14 15 11 53
33 33 14 9 8 19 11 37
26 32 16 12 13 13 11 44
30 30 16 12 9 17 11 44
24 30 14 10 15 12 11 40
34 31 11 9 17 11 11 42
34 32 12 12 13 14 11 35
33 34 15 8 15 11 11 43
34 36 15 11 15 13 11 45
35 37 16 11 14 12 11 55
35 36 16 12 16 15 11 31
36 33 11 10 13 14 11 44
34 33 15 10 16 12 11 50
34 33 12 12 9 17 11 40
41 44 12 12 16 11 11 53
32 39 15 11 11 18 11 54
30 32 15 8 10 13 11 49
35 35 16 12 11 17 11 40
28 25 14 10 15 13 11 41
33 35 17 11 17 11 11 52
39 34 14 10 14 12 11 52
36 35 13 8 8 22 11 36
36 39 15 12 15 14 11 52
35 33 13 12 11 12 11 46
38 36 14 10 16 12 11 31
33 32 15 12 10 17 11 44
31 32 12 9 15 9 11 44
34 36 13 9 9 21 11 11
32 36 8 6 16 10 11 46
31 32 14 10 19 11 11 33
33 34 14 9 12 12 11 34
34 33 11 9 8 23 11 42
34 35 12 9 11 13 11 43
34 30 13 6 14 12 11 43
33 38 10 10 9 16 11 44
32 34 16 6 15 9 11 36
41 33 18 14 13 17 11 46
34 32 13 10 16 9 11 44
36 31 11 10 11 14 11 43
37 30 4 6 12 17 11 50
36 27 13 12 13 13 11 33
29 31 16 12 10 11 11 43
37 30 10 7 11 12 11 44
27 32 12 8 12 10 11 53
35 35 12 11 8 19 11 34
28 28 10 3 12 16 11 35
35 33 13 6 12 16 11 40
37 31 15 10 15 14 11 53
29 35 12 8 11 20 11 42
32 35 14 9 13 15 11 43
36 32 10 9 14 23 11 29
19 21 12 8 10 20 11 36
21 20 12 9 12 16 11 30
31 34 11 7 15 14 11 42
33 32 10 7 13 17 11 47
36 34 12 6 13 11 11 44
33 32 16 9 13 13 11 45
37 33 12 10 12 17 11 44
34 33 14 11 12 15 11 43
35 37 16 12 9 21 11 43
31 32 14 8 9 18 11 40
37 34 13 11 15 15 11 41
35 30 4 3 10 8 11 52
27 30 15 11 14 12 11 38
34 38 11 12 15 12 11 41
40 36 11 7 7 22 11 39
29 32 14 9 14 12 11 43

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time21 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 21 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225764&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]21 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225764&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225764&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 time21 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 18.3483 + 0.00325718Connected[t] + 0.0117633Separate[t] + 0.0939744Learning[t] -0.0189188Software[t] -0.367088Depression[t] -0.307801Month[t] + 0.0380326Sport2[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  18.3483 +  0.00325718Connected[t] +  0.0117633Separate[t] +  0.0939744Learning[t] -0.0189188Software[t] -0.367088Depression[t] -0.307801Month[t] +  0.0380326Sport2[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225764&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  18.3483 +  0.00325718Connected[t] +  0.0117633Separate[t] +  0.0939744Learning[t] -0.0189188Software[t] -0.367088Depression[t] -0.307801Month[t] +  0.0380326Sport2[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225764&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225764&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] = + 18.3483 + 0.00325718Connected[t] + 0.0117633Separate[t] + 0.0939744Learning[t] -0.0189188Software[t] -0.367088Depression[t] -0.307801Month[t] + 0.0380326Sport2[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)18.34832.622736.9962.29674e-111.14837e-11
Connected0.003257180.03745460.086960.9307690.465384
Separate0.01176330.03809540.30880.7577360.378868
Learning0.09397440.06710321.40.1625910.0812954
Software-0.01891880.0687787-0.27510.7834860.391743
Depression-0.3670880.0387157-9.4821.79526e-188.97631e-19
Month-0.3078010.171249-1.7970.07345310.0367266
Sport20.03803260.01899162.0030.04627540.0231377

\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) & 18.3483 & 2.62273 & 6.996 & 2.29674e-11 & 1.14837e-11 \tabularnewline
Connected & 0.00325718 & 0.0374546 & 0.08696 & 0.930769 & 0.465384 \tabularnewline
Separate & 0.0117633 & 0.0380954 & 0.3088 & 0.757736 & 0.378868 \tabularnewline
Learning & 0.0939744 & 0.0671032 & 1.4 & 0.162591 & 0.0812954 \tabularnewline
Software & -0.0189188 & 0.0687787 & -0.2751 & 0.783486 & 0.391743 \tabularnewline
Depression & -0.367088 & 0.0387157 & -9.482 & 1.79526e-18 & 8.97631e-19 \tabularnewline
Month & -0.307801 & 0.171249 & -1.797 & 0.0734531 & 0.0367266 \tabularnewline
Sport2 & 0.0380326 & 0.0189916 & 2.003 & 0.0462754 & 0.0231377 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225764&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]18.3483[/C][C]2.62273[/C][C]6.996[/C][C]2.29674e-11[/C][C]1.14837e-11[/C][/ROW]
[ROW][C]Connected[/C][C]0.00325718[/C][C]0.0374546[/C][C]0.08696[/C][C]0.930769[/C][C]0.465384[/C][/ROW]
[ROW][C]Separate[/C][C]0.0117633[/C][C]0.0380954[/C][C]0.3088[/C][C]0.757736[/C][C]0.378868[/C][/ROW]
[ROW][C]Learning[/C][C]0.0939744[/C][C]0.0671032[/C][C]1.4[/C][C]0.162591[/C][C]0.0812954[/C][/ROW]
[ROW][C]Software[/C][C]-0.0189188[/C][C]0.0687787[/C][C]-0.2751[/C][C]0.783486[/C][C]0.391743[/C][/ROW]
[ROW][C]Depression[/C][C]-0.367088[/C][C]0.0387157[/C][C]-9.482[/C][C]1.79526e-18[/C][C]8.97631e-19[/C][/ROW]
[ROW][C]Month[/C][C]-0.307801[/C][C]0.171249[/C][C]-1.797[/C][C]0.0734531[/C][C]0.0367266[/C][/ROW]
[ROW][C]Sport2[/C][C]0.0380326[/C][C]0.0189916[/C][C]2.003[/C][C]0.0462754[/C][C]0.0231377[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225764&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225764&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)18.34832.622736.9962.29674e-111.14837e-11
Connected0.003257180.03745460.086960.9307690.465384
Separate0.01176330.03809540.30880.7577360.378868
Learning0.09397440.06710321.40.1625910.0812954
Software-0.01891880.0687787-0.27510.7834860.391743
Depression-0.3670880.0387157-9.4821.79526e-188.97631e-19
Month-0.3078010.171249-1.7970.07345310.0367266
Sport20.03803260.01899162.0030.04627540.0231377






Multiple Linear Regression - Regression Statistics
Multiple R0.609366
R-squared0.371326
Adjusted R-squared0.354136
F-TEST (value)21.6009
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.00805
Sum Squared Residuals1032.26

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.609366 \tabularnewline
R-squared & 0.371326 \tabularnewline
Adjusted R-squared & 0.354136 \tabularnewline
F-TEST (value) & 21.6009 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 256 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.00805 \tabularnewline
Sum Squared Residuals & 1032.26 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225764&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.609366[/C][/ROW]
[ROW][C]R-squared[/C][C]0.371326[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.354136[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]21.6009[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]256[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.00805[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1032.26[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225764&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225764&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 R0.609366
R-squared0.371326
Adjusted R-squared0.354136
F-TEST (value)21.6009
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.00805
Sum Squared Residuals1032.26






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11413.96530.0347363
21815.27872.72128
31114.0474-3.04738
41214.5176-2.51763
51611.23444.76558
61814.44823.55182
71410.95953.04047
81415.0827-1.08269
91515.2363-0.236263
101514.40030.59966
111715.57361.42636
121915.69023.30977
131013.4812-3.48119
141613.56342.43655
151815.77942.22056
161413.4830.516965
171413.86440.135569
181715.81711.18288
191415.524-1.52401
201613.93232.06767
211815.4382.56201
221113.8545-2.85449
231414.5417-0.541709
241213.7208-1.72083
251715.39181.60819
26915.9234-6.92342
271615.01890.981105
281413.43270.56732
291513.92261.07744
301114.1048-3.10476
311615.78610.213883
321312.76760.232448
331715.15421.84576
341515.4164-0.416428
351413.95560.0444311
361615.61450.385452
37910.8721-1.87212
381514.40250.597506
391715.43021.56977
401315.3212-2.32117
411515.7971-0.797105
421613.69982.30016
431615.99240.00763705
441213.2465-1.24651
451514.71710.282914
461113.6662-2.66617
471515.5619-0.561935
481514.99860.00143481
491713.52893.47112
501314.8404-1.8404
511615.37060.629398
521413.54370.456261
531111.7708-0.77079
541214.0037-2.00375
551214.1411-2.14112
561513.77721.2228
571614.3211.67905
581515.6426-0.642639
591215.2881-3.28811
601213.5355-1.53552
61810.8757-2.87571
621314.6848-1.68479
631114.7598-3.75978
641413.23810.761914
651513.8131.18701
661014.9968-4.99678
671112.5828-1.5828
681214.3233-2.32332
691513.44161.55839
701513.55421.44577
711413.50720.49278
721612.67463.32545
731514.31990.680107
741515.1535-0.153453
751314.8389-1.83886
761212.0664-0.0664309
771713.94693.05305
781312.47410.52589
791513.73621.26382
801314.9363-1.93626
811514.78930.210653
821515.5038-0.503769
831614.19191.80808
841514.24440.755646
851414.0722-0.0722236
861513.93751.06248
871414.2466-0.246601
881312.76650.233512
89710.508-3.50801
901713.72953.27049
911312.82650.173494
921514.12050.8795
931413.20570.79428
941313.9112-0.911215
951614.88481.11524
961212.8222-0.822153
971414.7938-0.793801
981714.85492.14509
991515.0031-0.00306684
1001715.09691.90315
1011212.9361-0.936056
1021614.99111.00887
1031114.4648-3.4648
1041513.04611.95385
105911.3563-2.3563
1061614.92591.07412
1071512.90122.09885
1081012.8435-2.8435
109109.230520.769476
1101513.8831.11702
1111113.1653-2.16529
1121315.3001-2.30009
1131411.68832.3117
1141814.11173.88827
1151615.55770.442331
1161413.03380.966157
1171413.91710.0828586
1181415.0966-1.09663
1191413.67960.320428
1201212.5753-0.575328
1211413.55680.443221
1221514.86330.13674
1231515.9274-0.927362
1241514.58940.410624
1251314.7288-1.72882
1261716.14930.850742
1271715.26441.73562
1281915.01843.98164
1291513.59341.40665
1301314.6365-1.63651
131910.6491-1.64909
1321515.2667-0.266674
1331512.64572.3543
1341514.27090.729135
1351613.77472.22527
136119.483721.51628
1371413.45240.547611
1381112.082-1.08198
1391514.24390.756083
1401313.8007-0.800702
1411514.71090.289097
1421613.8432.15698
1431414.7042-0.704169
1441514.28170.71826
1451614.60751.39255
1461614.52021.47981
1471113.4788-2.47876
1481214.7273-2.72727
149911.5869-2.58693
1501614.27081.72919
1511312.5530.446967
1521615.41690.583099
1531214.5015-2.50151
154911.9268-2.92683
1551311.86291.1371
1561312.82650.173494
1571413.41410.58592
1581915.01843.98164
1591315.6888-2.68881
1601212.0919-0.0919049
1611312.75090.249086
162109.214040.785963
1631412.99391.00606
1641611.3674.63299
1651011.7802-1.78024
166118.9942.006
1671413.97640.0235686
1681212.6821-0.682147
169912.5431-3.54309
170911.714-2.71398
1711110.43210.567894
1721614.05991.94007
173913.8287-4.82872
1741311.1551.84499
1751613.21112.78893
1761315.0496-2.04958
177912.2095-3.20952
1781211.32230.677728
1791614.4431.55697
1801112.9371-1.93706
1811413.99690.00310594
1821314.6051-1.60514
1831514.62410.375867
1841414.8-0.799958
1851613.94212.05789
1861311.46551.53448
1871413.36530.634679
1881514.02210.977924
1891312.28610.71391
1901110.20370.796264
1911112.225-1.22502
1921414.8359-0.835908
1931512.61692.38311
1941112.4931-1.49314
1951513.00981.99018
1961213.981-1.98097
1971411.62212.3779
1981413.29120.708817
199811.0361-3.03606
2001313.6015-0.601451
201912.1226-3.1226
2021513.63631.36374
2031713.86073.13926
2041312.54220.457771
2051514.32560.674377
2061513.63751.36246
2071414.4939-0.493947
2081612.44923.55078
2091312.84670.153337
2101614.17841.82158
211911.6429-2.64289
2121614.4921.50796
2131112.1732-1.17316
2141013.7863-3.78634
2151112.0456-1.04557
2161513.26141.73859
2171714.81092.18913
2181414.1886-0.188558
21989.85501-1.85501
2201513.55961.44044
2211113.8038-2.80376
2221613.41012.58986
2231012.0619-2.06192
2241514.76690.233051
22599.25761-0.257612
2261614.20711.7929
2271913.78345.21656
2281213.5033-1.50335
22989.47921-1.47921
2301113.3056-2.30562
2311413.76460.235373
232912.0676-3.06756
2331514.92210.0778736
2341312.41990.580106
2351614.85181.14822
2361112.7851-1.7851
2371211.35940.640585
2381312.87490.125075
2391014.2956-4.2956
2401113.5116-2.51159
2411214.748-2.74804
242810.7262-2.72622
2431211.72380.276223
2441212.2207-0.220723
2451513.54461.45542
2461110.70060.299395
2471312.75290.247118
248148.885565.11444
2491010.2752-0.275152
2501211.49110.508857
2511512.82282.17717
2521311.80071.19926
2531314.1293-1.12934
2541313.719-0.71904
2551211.84260.157371
2561212.698-0.698032
257910.7148-1.71484
258911.5179-2.51789
2591512.54952.45047
2601014.7895-4.78952
2611413.6450.354981
2621513.48121.51879
26379.82487-2.82487
2641413.80910.190914

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 13.9653 & 0.0347363 \tabularnewline
2 & 18 & 15.2787 & 2.72128 \tabularnewline
3 & 11 & 14.0474 & -3.04738 \tabularnewline
4 & 12 & 14.5176 & -2.51763 \tabularnewline
5 & 16 & 11.2344 & 4.76558 \tabularnewline
6 & 18 & 14.4482 & 3.55182 \tabularnewline
7 & 14 & 10.9595 & 3.04047 \tabularnewline
8 & 14 & 15.0827 & -1.08269 \tabularnewline
9 & 15 & 15.2363 & -0.236263 \tabularnewline
10 & 15 & 14.4003 & 0.59966 \tabularnewline
11 & 17 & 15.5736 & 1.42636 \tabularnewline
12 & 19 & 15.6902 & 3.30977 \tabularnewline
13 & 10 & 13.4812 & -3.48119 \tabularnewline
14 & 16 & 13.5634 & 2.43655 \tabularnewline
15 & 18 & 15.7794 & 2.22056 \tabularnewline
16 & 14 & 13.483 & 0.516965 \tabularnewline
17 & 14 & 13.8644 & 0.135569 \tabularnewline
18 & 17 & 15.8171 & 1.18288 \tabularnewline
19 & 14 & 15.524 & -1.52401 \tabularnewline
20 & 16 & 13.9323 & 2.06767 \tabularnewline
21 & 18 & 15.438 & 2.56201 \tabularnewline
22 & 11 & 13.8545 & -2.85449 \tabularnewline
23 & 14 & 14.5417 & -0.541709 \tabularnewline
24 & 12 & 13.7208 & -1.72083 \tabularnewline
25 & 17 & 15.3918 & 1.60819 \tabularnewline
26 & 9 & 15.9234 & -6.92342 \tabularnewline
27 & 16 & 15.0189 & 0.981105 \tabularnewline
28 & 14 & 13.4327 & 0.56732 \tabularnewline
29 & 15 & 13.9226 & 1.07744 \tabularnewline
30 & 11 & 14.1048 & -3.10476 \tabularnewline
31 & 16 & 15.7861 & 0.213883 \tabularnewline
32 & 13 & 12.7676 & 0.232448 \tabularnewline
33 & 17 & 15.1542 & 1.84576 \tabularnewline
34 & 15 & 15.4164 & -0.416428 \tabularnewline
35 & 14 & 13.9556 & 0.0444311 \tabularnewline
36 & 16 & 15.6145 & 0.385452 \tabularnewline
37 & 9 & 10.8721 & -1.87212 \tabularnewline
38 & 15 & 14.4025 & 0.597506 \tabularnewline
39 & 17 & 15.4302 & 1.56977 \tabularnewline
40 & 13 & 15.3212 & -2.32117 \tabularnewline
41 & 15 & 15.7971 & -0.797105 \tabularnewline
42 & 16 & 13.6998 & 2.30016 \tabularnewline
43 & 16 & 15.9924 & 0.00763705 \tabularnewline
44 & 12 & 13.2465 & -1.24651 \tabularnewline
45 & 15 & 14.7171 & 0.282914 \tabularnewline
46 & 11 & 13.6662 & -2.66617 \tabularnewline
47 & 15 & 15.5619 & -0.561935 \tabularnewline
48 & 15 & 14.9986 & 0.00143481 \tabularnewline
49 & 17 & 13.5289 & 3.47112 \tabularnewline
50 & 13 & 14.8404 & -1.8404 \tabularnewline
51 & 16 & 15.3706 & 0.629398 \tabularnewline
52 & 14 & 13.5437 & 0.456261 \tabularnewline
53 & 11 & 11.7708 & -0.77079 \tabularnewline
54 & 12 & 14.0037 & -2.00375 \tabularnewline
55 & 12 & 14.1411 & -2.14112 \tabularnewline
56 & 15 & 13.7772 & 1.2228 \tabularnewline
57 & 16 & 14.321 & 1.67905 \tabularnewline
58 & 15 & 15.6426 & -0.642639 \tabularnewline
59 & 12 & 15.2881 & -3.28811 \tabularnewline
60 & 12 & 13.5355 & -1.53552 \tabularnewline
61 & 8 & 10.8757 & -2.87571 \tabularnewline
62 & 13 & 14.6848 & -1.68479 \tabularnewline
63 & 11 & 14.7598 & -3.75978 \tabularnewline
64 & 14 & 13.2381 & 0.761914 \tabularnewline
65 & 15 & 13.813 & 1.18701 \tabularnewline
66 & 10 & 14.9968 & -4.99678 \tabularnewline
67 & 11 & 12.5828 & -1.5828 \tabularnewline
68 & 12 & 14.3233 & -2.32332 \tabularnewline
69 & 15 & 13.4416 & 1.55839 \tabularnewline
70 & 15 & 13.5542 & 1.44577 \tabularnewline
71 & 14 & 13.5072 & 0.49278 \tabularnewline
72 & 16 & 12.6746 & 3.32545 \tabularnewline
73 & 15 & 14.3199 & 0.680107 \tabularnewline
74 & 15 & 15.1535 & -0.153453 \tabularnewline
75 & 13 & 14.8389 & -1.83886 \tabularnewline
76 & 12 & 12.0664 & -0.0664309 \tabularnewline
77 & 17 & 13.9469 & 3.05305 \tabularnewline
78 & 13 & 12.4741 & 0.52589 \tabularnewline
79 & 15 & 13.7362 & 1.26382 \tabularnewline
80 & 13 & 14.9363 & -1.93626 \tabularnewline
81 & 15 & 14.7893 & 0.210653 \tabularnewline
82 & 15 & 15.5038 & -0.503769 \tabularnewline
83 & 16 & 14.1919 & 1.80808 \tabularnewline
84 & 15 & 14.2444 & 0.755646 \tabularnewline
85 & 14 & 14.0722 & -0.0722236 \tabularnewline
86 & 15 & 13.9375 & 1.06248 \tabularnewline
87 & 14 & 14.2466 & -0.246601 \tabularnewline
88 & 13 & 12.7665 & 0.233512 \tabularnewline
89 & 7 & 10.508 & -3.50801 \tabularnewline
90 & 17 & 13.7295 & 3.27049 \tabularnewline
91 & 13 & 12.8265 & 0.173494 \tabularnewline
92 & 15 & 14.1205 & 0.8795 \tabularnewline
93 & 14 & 13.2057 & 0.79428 \tabularnewline
94 & 13 & 13.9112 & -0.911215 \tabularnewline
95 & 16 & 14.8848 & 1.11524 \tabularnewline
96 & 12 & 12.8222 & -0.822153 \tabularnewline
97 & 14 & 14.7938 & -0.793801 \tabularnewline
98 & 17 & 14.8549 & 2.14509 \tabularnewline
99 & 15 & 15.0031 & -0.00306684 \tabularnewline
100 & 17 & 15.0969 & 1.90315 \tabularnewline
101 & 12 & 12.9361 & -0.936056 \tabularnewline
102 & 16 & 14.9911 & 1.00887 \tabularnewline
103 & 11 & 14.4648 & -3.4648 \tabularnewline
104 & 15 & 13.0461 & 1.95385 \tabularnewline
105 & 9 & 11.3563 & -2.3563 \tabularnewline
106 & 16 & 14.9259 & 1.07412 \tabularnewline
107 & 15 & 12.9012 & 2.09885 \tabularnewline
108 & 10 & 12.8435 & -2.8435 \tabularnewline
109 & 10 & 9.23052 & 0.769476 \tabularnewline
110 & 15 & 13.883 & 1.11702 \tabularnewline
111 & 11 & 13.1653 & -2.16529 \tabularnewline
112 & 13 & 15.3001 & -2.30009 \tabularnewline
113 & 14 & 11.6883 & 2.3117 \tabularnewline
114 & 18 & 14.1117 & 3.88827 \tabularnewline
115 & 16 & 15.5577 & 0.442331 \tabularnewline
116 & 14 & 13.0338 & 0.966157 \tabularnewline
117 & 14 & 13.9171 & 0.0828586 \tabularnewline
118 & 14 & 15.0966 & -1.09663 \tabularnewline
119 & 14 & 13.6796 & 0.320428 \tabularnewline
120 & 12 & 12.5753 & -0.575328 \tabularnewline
121 & 14 & 13.5568 & 0.443221 \tabularnewline
122 & 15 & 14.8633 & 0.13674 \tabularnewline
123 & 15 & 15.9274 & -0.927362 \tabularnewline
124 & 15 & 14.5894 & 0.410624 \tabularnewline
125 & 13 & 14.7288 & -1.72882 \tabularnewline
126 & 17 & 16.1493 & 0.850742 \tabularnewline
127 & 17 & 15.2644 & 1.73562 \tabularnewline
128 & 19 & 15.0184 & 3.98164 \tabularnewline
129 & 15 & 13.5934 & 1.40665 \tabularnewline
130 & 13 & 14.6365 & -1.63651 \tabularnewline
131 & 9 & 10.6491 & -1.64909 \tabularnewline
132 & 15 & 15.2667 & -0.266674 \tabularnewline
133 & 15 & 12.6457 & 2.3543 \tabularnewline
134 & 15 & 14.2709 & 0.729135 \tabularnewline
135 & 16 & 13.7747 & 2.22527 \tabularnewline
136 & 11 & 9.48372 & 1.51628 \tabularnewline
137 & 14 & 13.4524 & 0.547611 \tabularnewline
138 & 11 & 12.082 & -1.08198 \tabularnewline
139 & 15 & 14.2439 & 0.756083 \tabularnewline
140 & 13 & 13.8007 & -0.800702 \tabularnewline
141 & 15 & 14.7109 & 0.289097 \tabularnewline
142 & 16 & 13.843 & 2.15698 \tabularnewline
143 & 14 & 14.7042 & -0.704169 \tabularnewline
144 & 15 & 14.2817 & 0.71826 \tabularnewline
145 & 16 & 14.6075 & 1.39255 \tabularnewline
146 & 16 & 14.5202 & 1.47981 \tabularnewline
147 & 11 & 13.4788 & -2.47876 \tabularnewline
148 & 12 & 14.7273 & -2.72727 \tabularnewline
149 & 9 & 11.5869 & -2.58693 \tabularnewline
150 & 16 & 14.2708 & 1.72919 \tabularnewline
151 & 13 & 12.553 & 0.446967 \tabularnewline
152 & 16 & 15.4169 & 0.583099 \tabularnewline
153 & 12 & 14.5015 & -2.50151 \tabularnewline
154 & 9 & 11.9268 & -2.92683 \tabularnewline
155 & 13 & 11.8629 & 1.1371 \tabularnewline
156 & 13 & 12.8265 & 0.173494 \tabularnewline
157 & 14 & 13.4141 & 0.58592 \tabularnewline
158 & 19 & 15.0184 & 3.98164 \tabularnewline
159 & 13 & 15.6888 & -2.68881 \tabularnewline
160 & 12 & 12.0919 & -0.0919049 \tabularnewline
161 & 13 & 12.7509 & 0.249086 \tabularnewline
162 & 10 & 9.21404 & 0.785963 \tabularnewline
163 & 14 & 12.9939 & 1.00606 \tabularnewline
164 & 16 & 11.367 & 4.63299 \tabularnewline
165 & 10 & 11.7802 & -1.78024 \tabularnewline
166 & 11 & 8.994 & 2.006 \tabularnewline
167 & 14 & 13.9764 & 0.0235686 \tabularnewline
168 & 12 & 12.6821 & -0.682147 \tabularnewline
169 & 9 & 12.5431 & -3.54309 \tabularnewline
170 & 9 & 11.714 & -2.71398 \tabularnewline
171 & 11 & 10.4321 & 0.567894 \tabularnewline
172 & 16 & 14.0599 & 1.94007 \tabularnewline
173 & 9 & 13.8287 & -4.82872 \tabularnewline
174 & 13 & 11.155 & 1.84499 \tabularnewline
175 & 16 & 13.2111 & 2.78893 \tabularnewline
176 & 13 & 15.0496 & -2.04958 \tabularnewline
177 & 9 & 12.2095 & -3.20952 \tabularnewline
178 & 12 & 11.3223 & 0.677728 \tabularnewline
179 & 16 & 14.443 & 1.55697 \tabularnewline
180 & 11 & 12.9371 & -1.93706 \tabularnewline
181 & 14 & 13.9969 & 0.00310594 \tabularnewline
182 & 13 & 14.6051 & -1.60514 \tabularnewline
183 & 15 & 14.6241 & 0.375867 \tabularnewline
184 & 14 & 14.8 & -0.799958 \tabularnewline
185 & 16 & 13.9421 & 2.05789 \tabularnewline
186 & 13 & 11.4655 & 1.53448 \tabularnewline
187 & 14 & 13.3653 & 0.634679 \tabularnewline
188 & 15 & 14.0221 & 0.977924 \tabularnewline
189 & 13 & 12.2861 & 0.71391 \tabularnewline
190 & 11 & 10.2037 & 0.796264 \tabularnewline
191 & 11 & 12.225 & -1.22502 \tabularnewline
192 & 14 & 14.8359 & -0.835908 \tabularnewline
193 & 15 & 12.6169 & 2.38311 \tabularnewline
194 & 11 & 12.4931 & -1.49314 \tabularnewline
195 & 15 & 13.0098 & 1.99018 \tabularnewline
196 & 12 & 13.981 & -1.98097 \tabularnewline
197 & 14 & 11.6221 & 2.3779 \tabularnewline
198 & 14 & 13.2912 & 0.708817 \tabularnewline
199 & 8 & 11.0361 & -3.03606 \tabularnewline
200 & 13 & 13.6015 & -0.601451 \tabularnewline
201 & 9 & 12.1226 & -3.1226 \tabularnewline
202 & 15 & 13.6363 & 1.36374 \tabularnewline
203 & 17 & 13.8607 & 3.13926 \tabularnewline
204 & 13 & 12.5422 & 0.457771 \tabularnewline
205 & 15 & 14.3256 & 0.674377 \tabularnewline
206 & 15 & 13.6375 & 1.36246 \tabularnewline
207 & 14 & 14.4939 & -0.493947 \tabularnewline
208 & 16 & 12.4492 & 3.55078 \tabularnewline
209 & 13 & 12.8467 & 0.153337 \tabularnewline
210 & 16 & 14.1784 & 1.82158 \tabularnewline
211 & 9 & 11.6429 & -2.64289 \tabularnewline
212 & 16 & 14.492 & 1.50796 \tabularnewline
213 & 11 & 12.1732 & -1.17316 \tabularnewline
214 & 10 & 13.7863 & -3.78634 \tabularnewline
215 & 11 & 12.0456 & -1.04557 \tabularnewline
216 & 15 & 13.2614 & 1.73859 \tabularnewline
217 & 17 & 14.8109 & 2.18913 \tabularnewline
218 & 14 & 14.1886 & -0.188558 \tabularnewline
219 & 8 & 9.85501 & -1.85501 \tabularnewline
220 & 15 & 13.5596 & 1.44044 \tabularnewline
221 & 11 & 13.8038 & -2.80376 \tabularnewline
222 & 16 & 13.4101 & 2.58986 \tabularnewline
223 & 10 & 12.0619 & -2.06192 \tabularnewline
224 & 15 & 14.7669 & 0.233051 \tabularnewline
225 & 9 & 9.25761 & -0.257612 \tabularnewline
226 & 16 & 14.2071 & 1.7929 \tabularnewline
227 & 19 & 13.7834 & 5.21656 \tabularnewline
228 & 12 & 13.5033 & -1.50335 \tabularnewline
229 & 8 & 9.47921 & -1.47921 \tabularnewline
230 & 11 & 13.3056 & -2.30562 \tabularnewline
231 & 14 & 13.7646 & 0.235373 \tabularnewline
232 & 9 & 12.0676 & -3.06756 \tabularnewline
233 & 15 & 14.9221 & 0.0778736 \tabularnewline
234 & 13 & 12.4199 & 0.580106 \tabularnewline
235 & 16 & 14.8518 & 1.14822 \tabularnewline
236 & 11 & 12.7851 & -1.7851 \tabularnewline
237 & 12 & 11.3594 & 0.640585 \tabularnewline
238 & 13 & 12.8749 & 0.125075 \tabularnewline
239 & 10 & 14.2956 & -4.2956 \tabularnewline
240 & 11 & 13.5116 & -2.51159 \tabularnewline
241 & 12 & 14.748 & -2.74804 \tabularnewline
242 & 8 & 10.7262 & -2.72622 \tabularnewline
243 & 12 & 11.7238 & 0.276223 \tabularnewline
244 & 12 & 12.2207 & -0.220723 \tabularnewline
245 & 15 & 13.5446 & 1.45542 \tabularnewline
246 & 11 & 10.7006 & 0.299395 \tabularnewline
247 & 13 & 12.7529 & 0.247118 \tabularnewline
248 & 14 & 8.88556 & 5.11444 \tabularnewline
249 & 10 & 10.2752 & -0.275152 \tabularnewline
250 & 12 & 11.4911 & 0.508857 \tabularnewline
251 & 15 & 12.8228 & 2.17717 \tabularnewline
252 & 13 & 11.8007 & 1.19926 \tabularnewline
253 & 13 & 14.1293 & -1.12934 \tabularnewline
254 & 13 & 13.719 & -0.71904 \tabularnewline
255 & 12 & 11.8426 & 0.157371 \tabularnewline
256 & 12 & 12.698 & -0.698032 \tabularnewline
257 & 9 & 10.7148 & -1.71484 \tabularnewline
258 & 9 & 11.5179 & -2.51789 \tabularnewline
259 & 15 & 12.5495 & 2.45047 \tabularnewline
260 & 10 & 14.7895 & -4.78952 \tabularnewline
261 & 14 & 13.645 & 0.354981 \tabularnewline
262 & 15 & 13.4812 & 1.51879 \tabularnewline
263 & 7 & 9.82487 & -2.82487 \tabularnewline
264 & 14 & 13.8091 & 0.190914 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225764&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]13.9653[/C][C]0.0347363[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]15.2787[/C][C]2.72128[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]14.0474[/C][C]-3.04738[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.5176[/C][C]-2.51763[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]11.2344[/C][C]4.76558[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.4482[/C][C]3.55182[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.9595[/C][C]3.04047[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]15.0827[/C][C]-1.08269[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]15.2363[/C][C]-0.236263[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.4003[/C][C]0.59966[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.5736[/C][C]1.42636[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.6902[/C][C]3.30977[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.4812[/C][C]-3.48119[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.5634[/C][C]2.43655[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.7794[/C][C]2.22056[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.483[/C][C]0.516965[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.8644[/C][C]0.135569[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.8171[/C][C]1.18288[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.524[/C][C]-1.52401[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.9323[/C][C]2.06767[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.438[/C][C]2.56201[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.8545[/C][C]-2.85449[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.5417[/C][C]-0.541709[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.7208[/C][C]-1.72083[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.3918[/C][C]1.60819[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.9234[/C][C]-6.92342[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]15.0189[/C][C]0.981105[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.4327[/C][C]0.56732[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]13.9226[/C][C]1.07744[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]14.1048[/C][C]-3.10476[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.7861[/C][C]0.213883[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.7676[/C][C]0.232448[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]15.1542[/C][C]1.84576[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.4164[/C][C]-0.416428[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]13.9556[/C][C]0.0444311[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.6145[/C][C]0.385452[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.8721[/C][C]-1.87212[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.4025[/C][C]0.597506[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.4302[/C][C]1.56977[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.3212[/C][C]-2.32117[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.7971[/C][C]-0.797105[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.6998[/C][C]2.30016[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]15.9924[/C][C]0.00763705[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.2465[/C][C]-1.24651[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.7171[/C][C]0.282914[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.6662[/C][C]-2.66617[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.5619[/C][C]-0.561935[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.9986[/C][C]0.00143481[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.5289[/C][C]3.47112[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.8404[/C][C]-1.8404[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.3706[/C][C]0.629398[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.5437[/C][C]0.456261[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.7708[/C][C]-0.77079[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]14.0037[/C][C]-2.00375[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]14.1411[/C][C]-2.14112[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.7772[/C][C]1.2228[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.321[/C][C]1.67905[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.6426[/C][C]-0.642639[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.2881[/C][C]-3.28811[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.5355[/C][C]-1.53552[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.8757[/C][C]-2.87571[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.6848[/C][C]-1.68479[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.7598[/C][C]-3.75978[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.2381[/C][C]0.761914[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.813[/C][C]1.18701[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]14.9968[/C][C]-4.99678[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.5828[/C][C]-1.5828[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.3233[/C][C]-2.32332[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.4416[/C][C]1.55839[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.5542[/C][C]1.44577[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.5072[/C][C]0.49278[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.6746[/C][C]3.32545[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.3199[/C][C]0.680107[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.1535[/C][C]-0.153453[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.8389[/C][C]-1.83886[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]12.0664[/C][C]-0.0664309[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]13.9469[/C][C]3.05305[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.4741[/C][C]0.52589[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.7362[/C][C]1.26382[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]14.9363[/C][C]-1.93626[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.7893[/C][C]0.210653[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.5038[/C][C]-0.503769[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.1919[/C][C]1.80808[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.2444[/C][C]0.755646[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.0722[/C][C]-0.0722236[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.9375[/C][C]1.06248[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.2466[/C][C]-0.246601[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.7665[/C][C]0.233512[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.508[/C][C]-3.50801[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.7295[/C][C]3.27049[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]12.8265[/C][C]0.173494[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.1205[/C][C]0.8795[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.2057[/C][C]0.79428[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.9112[/C][C]-0.911215[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.8848[/C][C]1.11524[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.8222[/C][C]-0.822153[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.7938[/C][C]-0.793801[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.8549[/C][C]2.14509[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]15.0031[/C][C]-0.00306684[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.0969[/C][C]1.90315[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]12.9361[/C][C]-0.936056[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]14.9911[/C][C]1.00887[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.4648[/C][C]-3.4648[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]13.0461[/C][C]1.95385[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.3563[/C][C]-2.3563[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.9259[/C][C]1.07412[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.9012[/C][C]2.09885[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.8435[/C][C]-2.8435[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.23052[/C][C]0.769476[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.883[/C][C]1.11702[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.1653[/C][C]-2.16529[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.3001[/C][C]-2.30009[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]11.6883[/C][C]2.3117[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.1117[/C][C]3.88827[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.5577[/C][C]0.442331[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.0338[/C][C]0.966157[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.9171[/C][C]0.0828586[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.0966[/C][C]-1.09663[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.6796[/C][C]0.320428[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.5753[/C][C]-0.575328[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.5568[/C][C]0.443221[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.8633[/C][C]0.13674[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]15.9274[/C][C]-0.927362[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.5894[/C][C]0.410624[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.7288[/C][C]-1.72882[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.1493[/C][C]0.850742[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.2644[/C][C]1.73562[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]15.0184[/C][C]3.98164[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.5934[/C][C]1.40665[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.6365[/C][C]-1.63651[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.6491[/C][C]-1.64909[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.2667[/C][C]-0.266674[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.6457[/C][C]2.3543[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.2709[/C][C]0.729135[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.7747[/C][C]2.22527[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.48372[/C][C]1.51628[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.4524[/C][C]0.547611[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]12.082[/C][C]-1.08198[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.2439[/C][C]0.756083[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.8007[/C][C]-0.800702[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.7109[/C][C]0.289097[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.843[/C][C]2.15698[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.7042[/C][C]-0.704169[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.2817[/C][C]0.71826[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.6075[/C][C]1.39255[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.5202[/C][C]1.47981[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.4788[/C][C]-2.47876[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.7273[/C][C]-2.72727[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.5869[/C][C]-2.58693[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]14.2708[/C][C]1.72919[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.553[/C][C]0.446967[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.4169[/C][C]0.583099[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.5015[/C][C]-2.50151[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.9268[/C][C]-2.92683[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.8629[/C][C]1.1371[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.8265[/C][C]0.173494[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.4141[/C][C]0.58592[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]15.0184[/C][C]3.98164[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.6888[/C][C]-2.68881[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.0919[/C][C]-0.0919049[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.7509[/C][C]0.249086[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.21404[/C][C]0.785963[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]12.9939[/C][C]1.00606[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.367[/C][C]4.63299[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.7802[/C][C]-1.78024[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]8.994[/C][C]2.006[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]13.9764[/C][C]0.0235686[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]12.6821[/C][C]-0.682147[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.5431[/C][C]-3.54309[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.714[/C][C]-2.71398[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.4321[/C][C]0.567894[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.0599[/C][C]1.94007[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]13.8287[/C][C]-4.82872[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.155[/C][C]1.84499[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.2111[/C][C]2.78893[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.0496[/C][C]-2.04958[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.2095[/C][C]-3.20952[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.3223[/C][C]0.677728[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.443[/C][C]1.55697[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]12.9371[/C][C]-1.93706[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]13.9969[/C][C]0.00310594[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.6051[/C][C]-1.60514[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]14.6241[/C][C]0.375867[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]14.8[/C][C]-0.799958[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]13.9421[/C][C]2.05789[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.4655[/C][C]1.53448[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.3653[/C][C]0.634679[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.0221[/C][C]0.977924[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.2861[/C][C]0.71391[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.2037[/C][C]0.796264[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]12.225[/C][C]-1.22502[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]14.8359[/C][C]-0.835908[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.6169[/C][C]2.38311[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.4931[/C][C]-1.49314[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]13.0098[/C][C]1.99018[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]13.981[/C][C]-1.98097[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.6221[/C][C]2.3779[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.2912[/C][C]0.708817[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.0361[/C][C]-3.03606[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.6015[/C][C]-0.601451[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]12.1226[/C][C]-3.1226[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.6363[/C][C]1.36374[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]13.8607[/C][C]3.13926[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.5422[/C][C]0.457771[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.3256[/C][C]0.674377[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.6375[/C][C]1.36246[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.4939[/C][C]-0.493947[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.4492[/C][C]3.55078[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]12.8467[/C][C]0.153337[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.1784[/C][C]1.82158[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.6429[/C][C]-2.64289[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.492[/C][C]1.50796[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.1732[/C][C]-1.17316[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.7863[/C][C]-3.78634[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]12.0456[/C][C]-1.04557[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.2614[/C][C]1.73859[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.8109[/C][C]2.18913[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.1886[/C][C]-0.188558[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.85501[/C][C]-1.85501[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.5596[/C][C]1.44044[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]13.8038[/C][C]-2.80376[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]13.4101[/C][C]2.58986[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]12.0619[/C][C]-2.06192[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]14.7669[/C][C]0.233051[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.25761[/C][C]-0.257612[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.2071[/C][C]1.7929[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]13.7834[/C][C]5.21656[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.5033[/C][C]-1.50335[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.47921[/C][C]-1.47921[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.3056[/C][C]-2.30562[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.7646[/C][C]0.235373[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]12.0676[/C][C]-3.06756[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]14.9221[/C][C]0.0778736[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.4199[/C][C]0.580106[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]14.8518[/C][C]1.14822[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.7851[/C][C]-1.7851[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.3594[/C][C]0.640585[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]12.8749[/C][C]0.125075[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.2956[/C][C]-4.2956[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.5116[/C][C]-2.51159[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.748[/C][C]-2.74804[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.7262[/C][C]-2.72622[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.7238[/C][C]0.276223[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.2207[/C][C]-0.220723[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.5446[/C][C]1.45542[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.7006[/C][C]0.299395[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.7529[/C][C]0.247118[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]8.88556[/C][C]5.11444[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]10.2752[/C][C]-0.275152[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.4911[/C][C]0.508857[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.8228[/C][C]2.17717[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.8007[/C][C]1.19926[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.1293[/C][C]-1.12934[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.719[/C][C]-0.71904[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]11.8426[/C][C]0.157371[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.698[/C][C]-0.698032[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.7148[/C][C]-1.71484[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.5179[/C][C]-2.51789[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.5495[/C][C]2.45047[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.7895[/C][C]-4.78952[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.645[/C][C]0.354981[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.4812[/C][C]1.51879[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.82487[/C][C]-2.82487[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.8091[/C][C]0.190914[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225764&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225764&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
11413.96530.0347363
21815.27872.72128
31114.0474-3.04738
41214.5176-2.51763
51611.23444.76558
61814.44823.55182
71410.95953.04047
81415.0827-1.08269
91515.2363-0.236263
101514.40030.59966
111715.57361.42636
121915.69023.30977
131013.4812-3.48119
141613.56342.43655
151815.77942.22056
161413.4830.516965
171413.86440.135569
181715.81711.18288
191415.524-1.52401
201613.93232.06767
211815.4382.56201
221113.8545-2.85449
231414.5417-0.541709
241213.7208-1.72083
251715.39181.60819
26915.9234-6.92342
271615.01890.981105
281413.43270.56732
291513.92261.07744
301114.1048-3.10476
311615.78610.213883
321312.76760.232448
331715.15421.84576
341515.4164-0.416428
351413.95560.0444311
361615.61450.385452
37910.8721-1.87212
381514.40250.597506
391715.43021.56977
401315.3212-2.32117
411515.7971-0.797105
421613.69982.30016
431615.99240.00763705
441213.2465-1.24651
451514.71710.282914
461113.6662-2.66617
471515.5619-0.561935
481514.99860.00143481
491713.52893.47112
501314.8404-1.8404
511615.37060.629398
521413.54370.456261
531111.7708-0.77079
541214.0037-2.00375
551214.1411-2.14112
561513.77721.2228
571614.3211.67905
581515.6426-0.642639
591215.2881-3.28811
601213.5355-1.53552
61810.8757-2.87571
621314.6848-1.68479
631114.7598-3.75978
641413.23810.761914
651513.8131.18701
661014.9968-4.99678
671112.5828-1.5828
681214.3233-2.32332
691513.44161.55839
701513.55421.44577
711413.50720.49278
721612.67463.32545
731514.31990.680107
741515.1535-0.153453
751314.8389-1.83886
761212.0664-0.0664309
771713.94693.05305
781312.47410.52589
791513.73621.26382
801314.9363-1.93626
811514.78930.210653
821515.5038-0.503769
831614.19191.80808
841514.24440.755646
851414.0722-0.0722236
861513.93751.06248
871414.2466-0.246601
881312.76650.233512
89710.508-3.50801
901713.72953.27049
911312.82650.173494
921514.12050.8795
931413.20570.79428
941313.9112-0.911215
951614.88481.11524
961212.8222-0.822153
971414.7938-0.793801
981714.85492.14509
991515.0031-0.00306684
1001715.09691.90315
1011212.9361-0.936056
1021614.99111.00887
1031114.4648-3.4648
1041513.04611.95385
105911.3563-2.3563
1061614.92591.07412
1071512.90122.09885
1081012.8435-2.8435
109109.230520.769476
1101513.8831.11702
1111113.1653-2.16529
1121315.3001-2.30009
1131411.68832.3117
1141814.11173.88827
1151615.55770.442331
1161413.03380.966157
1171413.91710.0828586
1181415.0966-1.09663
1191413.67960.320428
1201212.5753-0.575328
1211413.55680.443221
1221514.86330.13674
1231515.9274-0.927362
1241514.58940.410624
1251314.7288-1.72882
1261716.14930.850742
1271715.26441.73562
1281915.01843.98164
1291513.59341.40665
1301314.6365-1.63651
131910.6491-1.64909
1321515.2667-0.266674
1331512.64572.3543
1341514.27090.729135
1351613.77472.22527
136119.483721.51628
1371413.45240.547611
1381112.082-1.08198
1391514.24390.756083
1401313.8007-0.800702
1411514.71090.289097
1421613.8432.15698
1431414.7042-0.704169
1441514.28170.71826
1451614.60751.39255
1461614.52021.47981
1471113.4788-2.47876
1481214.7273-2.72727
149911.5869-2.58693
1501614.27081.72919
1511312.5530.446967
1521615.41690.583099
1531214.5015-2.50151
154911.9268-2.92683
1551311.86291.1371
1561312.82650.173494
1571413.41410.58592
1581915.01843.98164
1591315.6888-2.68881
1601212.0919-0.0919049
1611312.75090.249086
162109.214040.785963
1631412.99391.00606
1641611.3674.63299
1651011.7802-1.78024
166118.9942.006
1671413.97640.0235686
1681212.6821-0.682147
169912.5431-3.54309
170911.714-2.71398
1711110.43210.567894
1721614.05991.94007
173913.8287-4.82872
1741311.1551.84499
1751613.21112.78893
1761315.0496-2.04958
177912.2095-3.20952
1781211.32230.677728
1791614.4431.55697
1801112.9371-1.93706
1811413.99690.00310594
1821314.6051-1.60514
1831514.62410.375867
1841414.8-0.799958
1851613.94212.05789
1861311.46551.53448
1871413.36530.634679
1881514.02210.977924
1891312.28610.71391
1901110.20370.796264
1911112.225-1.22502
1921414.8359-0.835908
1931512.61692.38311
1941112.4931-1.49314
1951513.00981.99018
1961213.981-1.98097
1971411.62212.3779
1981413.29120.708817
199811.0361-3.03606
2001313.6015-0.601451
201912.1226-3.1226
2021513.63631.36374
2031713.86073.13926
2041312.54220.457771
2051514.32560.674377
2061513.63751.36246
2071414.4939-0.493947
2081612.44923.55078
2091312.84670.153337
2101614.17841.82158
211911.6429-2.64289
2121614.4921.50796
2131112.1732-1.17316
2141013.7863-3.78634
2151112.0456-1.04557
2161513.26141.73859
2171714.81092.18913
2181414.1886-0.188558
21989.85501-1.85501
2201513.55961.44044
2211113.8038-2.80376
2221613.41012.58986
2231012.0619-2.06192
2241514.76690.233051
22599.25761-0.257612
2261614.20711.7929
2271913.78345.21656
2281213.5033-1.50335
22989.47921-1.47921
2301113.3056-2.30562
2311413.76460.235373
232912.0676-3.06756
2331514.92210.0778736
2341312.41990.580106
2351614.85181.14822
2361112.7851-1.7851
2371211.35940.640585
2381312.87490.125075
2391014.2956-4.2956
2401113.5116-2.51159
2411214.748-2.74804
242810.7262-2.72622
2431211.72380.276223
2441212.2207-0.220723
2451513.54461.45542
2461110.70060.299395
2471312.75290.247118
248148.885565.11444
2491010.2752-0.275152
2501211.49110.508857
2511512.82282.17717
2521311.80071.19926
2531314.1293-1.12934
2541313.719-0.71904
2551211.84260.157371
2561212.698-0.698032
257910.7148-1.71484
258911.5179-2.51789
2591512.54952.45047
2601014.7895-4.78952
2611413.6450.354981
2621513.48121.51879
26379.82487-2.82487
2641413.80910.190914






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.08015120.1603020.919849
120.9023390.1953220.097661
130.982410.03518080.0175904
140.9822130.03557350.0177867
150.9878580.02428490.0121424
160.9782720.04345550.0217278
170.9686270.06274640.0313732
180.9566630.08667480.0433374
190.9418810.1162370.0581185
200.9346470.1307060.065353
210.9434140.1131730.0565864
220.9689410.06211860.0310593
230.955250.08949980.0447499
240.9453130.1093740.0546872
250.9262570.1474860.0737431
260.9989450.002110110.00105506
270.9983890.003221670.00161084
280.9974560.005088790.00254439
290.996140.007719480.00385974
300.998170.0036610.0018305
310.9971620.005676610.0028383
320.9957580.008484910.00424246
330.9947530.01049480.00524741
340.9923810.0152370.00761851
350.9894530.02109420.0105471
360.9851310.02973740.0148687
370.9887850.02243080.0112154
380.9844630.0310730.0155365
390.982390.03521930.0176096
400.9826710.03465720.0173286
410.9773130.04537490.0226874
420.9757120.04857640.0242882
430.9679540.06409160.0320458
440.9617720.07645670.0382284
450.9506840.09863180.0493159
460.9591570.08168680.0408434
470.9477140.1045720.0522859
480.9337720.1324560.0662278
490.9516730.09665410.0483271
500.9483180.1033640.0516822
510.9365930.1268140.0634068
520.9215480.1569040.0784522
530.9078140.1843720.0921858
540.9099740.1800520.0900262
550.9032730.1934530.0967267
560.8870030.2259930.112997
570.875790.248420.12421
580.8524770.2950450.147523
590.8797950.240410.120205
600.8757870.2484250.124213
610.8960390.2079230.103961
620.8915660.2168680.108434
630.9329520.1340960.067048
640.922610.1547810.0773903
650.9122880.1754230.0877117
660.9234170.1531650.0765826
670.9212730.1574540.0787272
680.9140010.1719980.085999
690.9427710.1144580.0572291
700.9472240.1055510.0527756
710.9392530.1214940.0607468
720.9602250.07955060.0397753
730.9522480.09550330.0477516
740.9415150.1169690.0584846
750.9347320.1305350.0652677
760.9211750.1576490.0788247
770.9367460.1265080.0632542
780.9244810.1510390.0755193
790.9175250.164950.0824748
800.9118480.1763030.0881517
810.8954670.2090670.104533
820.877810.2443790.12219
830.8736150.2527710.126385
840.8552520.2894960.144748
850.8323810.3352380.167619
860.8103980.3792040.189602
870.7838830.4322330.216117
880.7550790.4898420.244921
890.822630.3547410.17737
900.8506130.2987750.149387
910.8283260.3433490.171674
920.8056880.3886250.194312
930.7846330.4307340.215367
940.7615380.4769240.238462
950.7370370.5259260.262963
960.7133930.5732140.286607
970.6867590.6264810.313241
980.6867470.6265060.313253
990.6535350.6929290.346465
1000.6446240.7107510.355376
1010.6217370.7565260.378263
1020.592580.814840.40742
1030.6528360.6943280.347164
1040.6409440.7181120.359056
1050.6581140.6837730.341886
1060.6307310.7385380.369269
1070.6219370.7561250.378063
1080.6619940.6760120.338006
1090.6326060.7347880.367394
1100.6057020.7885960.394298
1110.6110290.7779420.388971
1120.6412890.7174230.358711
1130.6511180.6977630.348882
1140.726310.5473790.27369
1150.6974230.6051540.302577
1160.6722110.6555770.327789
1170.6418030.7163930.358197
1180.6203080.7593840.379692
1190.5857630.8284750.414237
1200.5555570.8888860.444443
1210.5255260.9489490.474474
1220.4915970.9831940.508403
1230.4656760.9313520.534324
1240.4316840.8633670.568316
1250.4228610.8457220.577139
1260.3919750.7839510.608025
1270.3762890.7525770.623711
1280.4682250.9364510.531775
1290.4474310.8948610.552569
1300.4367580.8735170.563242
1310.4254430.8508870.574557
1320.3945970.7891940.605403
1330.4083680.8167350.591632
1340.3785820.7571640.621418
1350.3852510.7705030.614749
1360.3712040.7424070.628796
1370.340340.6806810.65966
1380.318580.6371610.68142
1390.2911960.5823920.708804
1400.2668710.5337420.733129
1410.2387560.4775120.761244
1420.2438930.4877860.756107
1430.2186360.4372720.781364
1440.1972620.3945240.802738
1450.1835440.3670880.816456
1460.1746850.349370.825315
1470.1840340.3680690.815966
1480.2033160.4066310.796684
1490.2256890.4513780.774311
1500.2217080.4434160.778292
1510.1979170.3958330.802083
1520.1771920.3543840.822808
1530.1898330.3796670.810167
1540.2290990.4581970.770901
1550.2056270.4112540.794373
1560.1842340.3684680.815766
1570.1612930.3225860.838707
1580.2321540.4643080.767846
1590.2593670.5187340.740633
1600.2320710.4641420.767929
1610.2050220.4100440.794978
1620.1813230.3626460.818677
1630.1605680.3211360.839432
1640.2626180.5252360.737382
1650.2582370.5164740.741763
1660.255480.510960.74452
1670.2273890.4547790.772611
1680.2061180.4122360.793882
1690.2618340.5236690.738166
1700.2839530.5679050.716047
1710.2566280.5132560.743372
1720.2532730.5065470.746727
1730.4109010.8218020.589099
1740.3993720.7987440.600628
1750.4242790.8485580.575721
1760.4302180.8604360.569782
1770.482820.965640.51718
1780.4496980.8993960.550302
1790.4299130.8598250.570087
1800.4252630.8505250.574737
1810.3881650.776330.611835
1820.3779040.7558070.622096
1830.3419410.6838820.658059
1840.3135810.6271630.686419
1850.329950.6599010.67005
1860.3229740.6459470.677026
1870.2899470.5798940.710053
1880.2625080.5250170.737492
1890.2332750.4665490.766725
1900.2130470.4260940.786953
1910.2173010.4346010.782699
1920.1982360.3964710.801764
1930.2168790.4337580.783121
1940.2039590.4079190.796041
1950.2050370.4100750.794963
1960.212880.4257610.78712
1970.2565870.5131740.743413
1980.2371720.4743440.762828
1990.2669710.5339430.733029
2000.235320.470640.76468
2010.2661790.5323580.733821
2020.2456870.4913730.754313
2030.2854440.5708870.714556
2040.2501490.5002980.749851
2050.2193490.4386970.780651
2060.2006220.4012450.799378
2070.1720590.3441180.827941
2080.2018470.4036940.798153
2090.1724320.3448650.827568
2100.1752240.3504480.824776
2110.1952410.3904820.804759
2120.1863050.372610.813695
2130.1608280.3216560.839172
2140.2033610.4067230.796639
2150.1794780.3589550.820522
2160.1695930.3391860.830407
2170.1910010.3820030.808999
2180.1619820.3239640.838018
2190.1518190.3036380.848181
2200.1610120.3220250.838988
2210.1739480.3478960.826052
2220.1699690.3399390.830031
2230.1598240.3196490.840176
2240.132180.264360.86782
2250.1408330.2816660.859167
2260.1647230.3294460.835277
2270.362090.724180.63791
2280.3382650.6765290.661735
2290.3113640.6227290.688636
2300.2950350.5900690.704965
2310.2535490.5070970.746451
2320.2836190.5672380.716381
2330.2434820.4869630.756518
2340.2029870.4059730.797013
2350.2021140.4042280.797886
2360.1808660.3617310.819134
2370.1520050.3040090.847995
2380.1176780.2353570.882322
2390.23120.46240.7688
2400.2245160.4490310.775484
2410.1923530.3847070.807647
2420.3838330.7676670.616167
2430.3387530.6775060.661247
2440.2762030.5524050.723797
2450.4158120.8316230.584188
2460.3323560.6647130.667644
2470.2580970.5161950.741903
2480.3926420.7852850.607358
2490.2950710.5901410.704929
2500.2063990.4127980.793601
2510.3179810.6359610.682019
2520.8692370.2615270.130763
2530.7449360.5101290.255064

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.0801512 & 0.160302 & 0.919849 \tabularnewline
12 & 0.902339 & 0.195322 & 0.097661 \tabularnewline
13 & 0.98241 & 0.0351808 & 0.0175904 \tabularnewline
14 & 0.982213 & 0.0355735 & 0.0177867 \tabularnewline
15 & 0.987858 & 0.0242849 & 0.0121424 \tabularnewline
16 & 0.978272 & 0.0434555 & 0.0217278 \tabularnewline
17 & 0.968627 & 0.0627464 & 0.0313732 \tabularnewline
18 & 0.956663 & 0.0866748 & 0.0433374 \tabularnewline
19 & 0.941881 & 0.116237 & 0.0581185 \tabularnewline
20 & 0.934647 & 0.130706 & 0.065353 \tabularnewline
21 & 0.943414 & 0.113173 & 0.0565864 \tabularnewline
22 & 0.968941 & 0.0621186 & 0.0310593 \tabularnewline
23 & 0.95525 & 0.0894998 & 0.0447499 \tabularnewline
24 & 0.945313 & 0.109374 & 0.0546872 \tabularnewline
25 & 0.926257 & 0.147486 & 0.0737431 \tabularnewline
26 & 0.998945 & 0.00211011 & 0.00105506 \tabularnewline
27 & 0.998389 & 0.00322167 & 0.00161084 \tabularnewline
28 & 0.997456 & 0.00508879 & 0.00254439 \tabularnewline
29 & 0.99614 & 0.00771948 & 0.00385974 \tabularnewline
30 & 0.99817 & 0.003661 & 0.0018305 \tabularnewline
31 & 0.997162 & 0.00567661 & 0.0028383 \tabularnewline
32 & 0.995758 & 0.00848491 & 0.00424246 \tabularnewline
33 & 0.994753 & 0.0104948 & 0.00524741 \tabularnewline
34 & 0.992381 & 0.015237 & 0.00761851 \tabularnewline
35 & 0.989453 & 0.0210942 & 0.0105471 \tabularnewline
36 & 0.985131 & 0.0297374 & 0.0148687 \tabularnewline
37 & 0.988785 & 0.0224308 & 0.0112154 \tabularnewline
38 & 0.984463 & 0.031073 & 0.0155365 \tabularnewline
39 & 0.98239 & 0.0352193 & 0.0176096 \tabularnewline
40 & 0.982671 & 0.0346572 & 0.0173286 \tabularnewline
41 & 0.977313 & 0.0453749 & 0.0226874 \tabularnewline
42 & 0.975712 & 0.0485764 & 0.0242882 \tabularnewline
43 & 0.967954 & 0.0640916 & 0.0320458 \tabularnewline
44 & 0.961772 & 0.0764567 & 0.0382284 \tabularnewline
45 & 0.950684 & 0.0986318 & 0.0493159 \tabularnewline
46 & 0.959157 & 0.0816868 & 0.0408434 \tabularnewline
47 & 0.947714 & 0.104572 & 0.0522859 \tabularnewline
48 & 0.933772 & 0.132456 & 0.0662278 \tabularnewline
49 & 0.951673 & 0.0966541 & 0.0483271 \tabularnewline
50 & 0.948318 & 0.103364 & 0.0516822 \tabularnewline
51 & 0.936593 & 0.126814 & 0.0634068 \tabularnewline
52 & 0.921548 & 0.156904 & 0.0784522 \tabularnewline
53 & 0.907814 & 0.184372 & 0.0921858 \tabularnewline
54 & 0.909974 & 0.180052 & 0.0900262 \tabularnewline
55 & 0.903273 & 0.193453 & 0.0967267 \tabularnewline
56 & 0.887003 & 0.225993 & 0.112997 \tabularnewline
57 & 0.87579 & 0.24842 & 0.12421 \tabularnewline
58 & 0.852477 & 0.295045 & 0.147523 \tabularnewline
59 & 0.879795 & 0.24041 & 0.120205 \tabularnewline
60 & 0.875787 & 0.248425 & 0.124213 \tabularnewline
61 & 0.896039 & 0.207923 & 0.103961 \tabularnewline
62 & 0.891566 & 0.216868 & 0.108434 \tabularnewline
63 & 0.932952 & 0.134096 & 0.067048 \tabularnewline
64 & 0.92261 & 0.154781 & 0.0773903 \tabularnewline
65 & 0.912288 & 0.175423 & 0.0877117 \tabularnewline
66 & 0.923417 & 0.153165 & 0.0765826 \tabularnewline
67 & 0.921273 & 0.157454 & 0.0787272 \tabularnewline
68 & 0.914001 & 0.171998 & 0.085999 \tabularnewline
69 & 0.942771 & 0.114458 & 0.0572291 \tabularnewline
70 & 0.947224 & 0.105551 & 0.0527756 \tabularnewline
71 & 0.939253 & 0.121494 & 0.0607468 \tabularnewline
72 & 0.960225 & 0.0795506 & 0.0397753 \tabularnewline
73 & 0.952248 & 0.0955033 & 0.0477516 \tabularnewline
74 & 0.941515 & 0.116969 & 0.0584846 \tabularnewline
75 & 0.934732 & 0.130535 & 0.0652677 \tabularnewline
76 & 0.921175 & 0.157649 & 0.0788247 \tabularnewline
77 & 0.936746 & 0.126508 & 0.0632542 \tabularnewline
78 & 0.924481 & 0.151039 & 0.0755193 \tabularnewline
79 & 0.917525 & 0.16495 & 0.0824748 \tabularnewline
80 & 0.911848 & 0.176303 & 0.0881517 \tabularnewline
81 & 0.895467 & 0.209067 & 0.104533 \tabularnewline
82 & 0.87781 & 0.244379 & 0.12219 \tabularnewline
83 & 0.873615 & 0.252771 & 0.126385 \tabularnewline
84 & 0.855252 & 0.289496 & 0.144748 \tabularnewline
85 & 0.832381 & 0.335238 & 0.167619 \tabularnewline
86 & 0.810398 & 0.379204 & 0.189602 \tabularnewline
87 & 0.783883 & 0.432233 & 0.216117 \tabularnewline
88 & 0.755079 & 0.489842 & 0.244921 \tabularnewline
89 & 0.82263 & 0.354741 & 0.17737 \tabularnewline
90 & 0.850613 & 0.298775 & 0.149387 \tabularnewline
91 & 0.828326 & 0.343349 & 0.171674 \tabularnewline
92 & 0.805688 & 0.388625 & 0.194312 \tabularnewline
93 & 0.784633 & 0.430734 & 0.215367 \tabularnewline
94 & 0.761538 & 0.476924 & 0.238462 \tabularnewline
95 & 0.737037 & 0.525926 & 0.262963 \tabularnewline
96 & 0.713393 & 0.573214 & 0.286607 \tabularnewline
97 & 0.686759 & 0.626481 & 0.313241 \tabularnewline
98 & 0.686747 & 0.626506 & 0.313253 \tabularnewline
99 & 0.653535 & 0.692929 & 0.346465 \tabularnewline
100 & 0.644624 & 0.710751 & 0.355376 \tabularnewline
101 & 0.621737 & 0.756526 & 0.378263 \tabularnewline
102 & 0.59258 & 0.81484 & 0.40742 \tabularnewline
103 & 0.652836 & 0.694328 & 0.347164 \tabularnewline
104 & 0.640944 & 0.718112 & 0.359056 \tabularnewline
105 & 0.658114 & 0.683773 & 0.341886 \tabularnewline
106 & 0.630731 & 0.738538 & 0.369269 \tabularnewline
107 & 0.621937 & 0.756125 & 0.378063 \tabularnewline
108 & 0.661994 & 0.676012 & 0.338006 \tabularnewline
109 & 0.632606 & 0.734788 & 0.367394 \tabularnewline
110 & 0.605702 & 0.788596 & 0.394298 \tabularnewline
111 & 0.611029 & 0.777942 & 0.388971 \tabularnewline
112 & 0.641289 & 0.717423 & 0.358711 \tabularnewline
113 & 0.651118 & 0.697763 & 0.348882 \tabularnewline
114 & 0.72631 & 0.547379 & 0.27369 \tabularnewline
115 & 0.697423 & 0.605154 & 0.302577 \tabularnewline
116 & 0.672211 & 0.655577 & 0.327789 \tabularnewline
117 & 0.641803 & 0.716393 & 0.358197 \tabularnewline
118 & 0.620308 & 0.759384 & 0.379692 \tabularnewline
119 & 0.585763 & 0.828475 & 0.414237 \tabularnewline
120 & 0.555557 & 0.888886 & 0.444443 \tabularnewline
121 & 0.525526 & 0.948949 & 0.474474 \tabularnewline
122 & 0.491597 & 0.983194 & 0.508403 \tabularnewline
123 & 0.465676 & 0.931352 & 0.534324 \tabularnewline
124 & 0.431684 & 0.863367 & 0.568316 \tabularnewline
125 & 0.422861 & 0.845722 & 0.577139 \tabularnewline
126 & 0.391975 & 0.783951 & 0.608025 \tabularnewline
127 & 0.376289 & 0.752577 & 0.623711 \tabularnewline
128 & 0.468225 & 0.936451 & 0.531775 \tabularnewline
129 & 0.447431 & 0.894861 & 0.552569 \tabularnewline
130 & 0.436758 & 0.873517 & 0.563242 \tabularnewline
131 & 0.425443 & 0.850887 & 0.574557 \tabularnewline
132 & 0.394597 & 0.789194 & 0.605403 \tabularnewline
133 & 0.408368 & 0.816735 & 0.591632 \tabularnewline
134 & 0.378582 & 0.757164 & 0.621418 \tabularnewline
135 & 0.385251 & 0.770503 & 0.614749 \tabularnewline
136 & 0.371204 & 0.742407 & 0.628796 \tabularnewline
137 & 0.34034 & 0.680681 & 0.65966 \tabularnewline
138 & 0.31858 & 0.637161 & 0.68142 \tabularnewline
139 & 0.291196 & 0.582392 & 0.708804 \tabularnewline
140 & 0.266871 & 0.533742 & 0.733129 \tabularnewline
141 & 0.238756 & 0.477512 & 0.761244 \tabularnewline
142 & 0.243893 & 0.487786 & 0.756107 \tabularnewline
143 & 0.218636 & 0.437272 & 0.781364 \tabularnewline
144 & 0.197262 & 0.394524 & 0.802738 \tabularnewline
145 & 0.183544 & 0.367088 & 0.816456 \tabularnewline
146 & 0.174685 & 0.34937 & 0.825315 \tabularnewline
147 & 0.184034 & 0.368069 & 0.815966 \tabularnewline
148 & 0.203316 & 0.406631 & 0.796684 \tabularnewline
149 & 0.225689 & 0.451378 & 0.774311 \tabularnewline
150 & 0.221708 & 0.443416 & 0.778292 \tabularnewline
151 & 0.197917 & 0.395833 & 0.802083 \tabularnewline
152 & 0.177192 & 0.354384 & 0.822808 \tabularnewline
153 & 0.189833 & 0.379667 & 0.810167 \tabularnewline
154 & 0.229099 & 0.458197 & 0.770901 \tabularnewline
155 & 0.205627 & 0.411254 & 0.794373 \tabularnewline
156 & 0.184234 & 0.368468 & 0.815766 \tabularnewline
157 & 0.161293 & 0.322586 & 0.838707 \tabularnewline
158 & 0.232154 & 0.464308 & 0.767846 \tabularnewline
159 & 0.259367 & 0.518734 & 0.740633 \tabularnewline
160 & 0.232071 & 0.464142 & 0.767929 \tabularnewline
161 & 0.205022 & 0.410044 & 0.794978 \tabularnewline
162 & 0.181323 & 0.362646 & 0.818677 \tabularnewline
163 & 0.160568 & 0.321136 & 0.839432 \tabularnewline
164 & 0.262618 & 0.525236 & 0.737382 \tabularnewline
165 & 0.258237 & 0.516474 & 0.741763 \tabularnewline
166 & 0.25548 & 0.51096 & 0.74452 \tabularnewline
167 & 0.227389 & 0.454779 & 0.772611 \tabularnewline
168 & 0.206118 & 0.412236 & 0.793882 \tabularnewline
169 & 0.261834 & 0.523669 & 0.738166 \tabularnewline
170 & 0.283953 & 0.567905 & 0.716047 \tabularnewline
171 & 0.256628 & 0.513256 & 0.743372 \tabularnewline
172 & 0.253273 & 0.506547 & 0.746727 \tabularnewline
173 & 0.410901 & 0.821802 & 0.589099 \tabularnewline
174 & 0.399372 & 0.798744 & 0.600628 \tabularnewline
175 & 0.424279 & 0.848558 & 0.575721 \tabularnewline
176 & 0.430218 & 0.860436 & 0.569782 \tabularnewline
177 & 0.48282 & 0.96564 & 0.51718 \tabularnewline
178 & 0.449698 & 0.899396 & 0.550302 \tabularnewline
179 & 0.429913 & 0.859825 & 0.570087 \tabularnewline
180 & 0.425263 & 0.850525 & 0.574737 \tabularnewline
181 & 0.388165 & 0.77633 & 0.611835 \tabularnewline
182 & 0.377904 & 0.755807 & 0.622096 \tabularnewline
183 & 0.341941 & 0.683882 & 0.658059 \tabularnewline
184 & 0.313581 & 0.627163 & 0.686419 \tabularnewline
185 & 0.32995 & 0.659901 & 0.67005 \tabularnewline
186 & 0.322974 & 0.645947 & 0.677026 \tabularnewline
187 & 0.289947 & 0.579894 & 0.710053 \tabularnewline
188 & 0.262508 & 0.525017 & 0.737492 \tabularnewline
189 & 0.233275 & 0.466549 & 0.766725 \tabularnewline
190 & 0.213047 & 0.426094 & 0.786953 \tabularnewline
191 & 0.217301 & 0.434601 & 0.782699 \tabularnewline
192 & 0.198236 & 0.396471 & 0.801764 \tabularnewline
193 & 0.216879 & 0.433758 & 0.783121 \tabularnewline
194 & 0.203959 & 0.407919 & 0.796041 \tabularnewline
195 & 0.205037 & 0.410075 & 0.794963 \tabularnewline
196 & 0.21288 & 0.425761 & 0.78712 \tabularnewline
197 & 0.256587 & 0.513174 & 0.743413 \tabularnewline
198 & 0.237172 & 0.474344 & 0.762828 \tabularnewline
199 & 0.266971 & 0.533943 & 0.733029 \tabularnewline
200 & 0.23532 & 0.47064 & 0.76468 \tabularnewline
201 & 0.266179 & 0.532358 & 0.733821 \tabularnewline
202 & 0.245687 & 0.491373 & 0.754313 \tabularnewline
203 & 0.285444 & 0.570887 & 0.714556 \tabularnewline
204 & 0.250149 & 0.500298 & 0.749851 \tabularnewline
205 & 0.219349 & 0.438697 & 0.780651 \tabularnewline
206 & 0.200622 & 0.401245 & 0.799378 \tabularnewline
207 & 0.172059 & 0.344118 & 0.827941 \tabularnewline
208 & 0.201847 & 0.403694 & 0.798153 \tabularnewline
209 & 0.172432 & 0.344865 & 0.827568 \tabularnewline
210 & 0.175224 & 0.350448 & 0.824776 \tabularnewline
211 & 0.195241 & 0.390482 & 0.804759 \tabularnewline
212 & 0.186305 & 0.37261 & 0.813695 \tabularnewline
213 & 0.160828 & 0.321656 & 0.839172 \tabularnewline
214 & 0.203361 & 0.406723 & 0.796639 \tabularnewline
215 & 0.179478 & 0.358955 & 0.820522 \tabularnewline
216 & 0.169593 & 0.339186 & 0.830407 \tabularnewline
217 & 0.191001 & 0.382003 & 0.808999 \tabularnewline
218 & 0.161982 & 0.323964 & 0.838018 \tabularnewline
219 & 0.151819 & 0.303638 & 0.848181 \tabularnewline
220 & 0.161012 & 0.322025 & 0.838988 \tabularnewline
221 & 0.173948 & 0.347896 & 0.826052 \tabularnewline
222 & 0.169969 & 0.339939 & 0.830031 \tabularnewline
223 & 0.159824 & 0.319649 & 0.840176 \tabularnewline
224 & 0.13218 & 0.26436 & 0.86782 \tabularnewline
225 & 0.140833 & 0.281666 & 0.859167 \tabularnewline
226 & 0.164723 & 0.329446 & 0.835277 \tabularnewline
227 & 0.36209 & 0.72418 & 0.63791 \tabularnewline
228 & 0.338265 & 0.676529 & 0.661735 \tabularnewline
229 & 0.311364 & 0.622729 & 0.688636 \tabularnewline
230 & 0.295035 & 0.590069 & 0.704965 \tabularnewline
231 & 0.253549 & 0.507097 & 0.746451 \tabularnewline
232 & 0.283619 & 0.567238 & 0.716381 \tabularnewline
233 & 0.243482 & 0.486963 & 0.756518 \tabularnewline
234 & 0.202987 & 0.405973 & 0.797013 \tabularnewline
235 & 0.202114 & 0.404228 & 0.797886 \tabularnewline
236 & 0.180866 & 0.361731 & 0.819134 \tabularnewline
237 & 0.152005 & 0.304009 & 0.847995 \tabularnewline
238 & 0.117678 & 0.235357 & 0.882322 \tabularnewline
239 & 0.2312 & 0.4624 & 0.7688 \tabularnewline
240 & 0.224516 & 0.449031 & 0.775484 \tabularnewline
241 & 0.192353 & 0.384707 & 0.807647 \tabularnewline
242 & 0.383833 & 0.767667 & 0.616167 \tabularnewline
243 & 0.338753 & 0.677506 & 0.661247 \tabularnewline
244 & 0.276203 & 0.552405 & 0.723797 \tabularnewline
245 & 0.415812 & 0.831623 & 0.584188 \tabularnewline
246 & 0.332356 & 0.664713 & 0.667644 \tabularnewline
247 & 0.258097 & 0.516195 & 0.741903 \tabularnewline
248 & 0.392642 & 0.785285 & 0.607358 \tabularnewline
249 & 0.295071 & 0.590141 & 0.704929 \tabularnewline
250 & 0.206399 & 0.412798 & 0.793601 \tabularnewline
251 & 0.317981 & 0.635961 & 0.682019 \tabularnewline
252 & 0.869237 & 0.261527 & 0.130763 \tabularnewline
253 & 0.744936 & 0.510129 & 0.255064 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225764&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]11[/C][C]0.0801512[/C][C]0.160302[/C][C]0.919849[/C][/ROW]
[ROW][C]12[/C][C]0.902339[/C][C]0.195322[/C][C]0.097661[/C][/ROW]
[ROW][C]13[/C][C]0.98241[/C][C]0.0351808[/C][C]0.0175904[/C][/ROW]
[ROW][C]14[/C][C]0.982213[/C][C]0.0355735[/C][C]0.0177867[/C][/ROW]
[ROW][C]15[/C][C]0.987858[/C][C]0.0242849[/C][C]0.0121424[/C][/ROW]
[ROW][C]16[/C][C]0.978272[/C][C]0.0434555[/C][C]0.0217278[/C][/ROW]
[ROW][C]17[/C][C]0.968627[/C][C]0.0627464[/C][C]0.0313732[/C][/ROW]
[ROW][C]18[/C][C]0.956663[/C][C]0.0866748[/C][C]0.0433374[/C][/ROW]
[ROW][C]19[/C][C]0.941881[/C][C]0.116237[/C][C]0.0581185[/C][/ROW]
[ROW][C]20[/C][C]0.934647[/C][C]0.130706[/C][C]0.065353[/C][/ROW]
[ROW][C]21[/C][C]0.943414[/C][C]0.113173[/C][C]0.0565864[/C][/ROW]
[ROW][C]22[/C][C]0.968941[/C][C]0.0621186[/C][C]0.0310593[/C][/ROW]
[ROW][C]23[/C][C]0.95525[/C][C]0.0894998[/C][C]0.0447499[/C][/ROW]
[ROW][C]24[/C][C]0.945313[/C][C]0.109374[/C][C]0.0546872[/C][/ROW]
[ROW][C]25[/C][C]0.926257[/C][C]0.147486[/C][C]0.0737431[/C][/ROW]
[ROW][C]26[/C][C]0.998945[/C][C]0.00211011[/C][C]0.00105506[/C][/ROW]
[ROW][C]27[/C][C]0.998389[/C][C]0.00322167[/C][C]0.00161084[/C][/ROW]
[ROW][C]28[/C][C]0.997456[/C][C]0.00508879[/C][C]0.00254439[/C][/ROW]
[ROW][C]29[/C][C]0.99614[/C][C]0.00771948[/C][C]0.00385974[/C][/ROW]
[ROW][C]30[/C][C]0.99817[/C][C]0.003661[/C][C]0.0018305[/C][/ROW]
[ROW][C]31[/C][C]0.997162[/C][C]0.00567661[/C][C]0.0028383[/C][/ROW]
[ROW][C]32[/C][C]0.995758[/C][C]0.00848491[/C][C]0.00424246[/C][/ROW]
[ROW][C]33[/C][C]0.994753[/C][C]0.0104948[/C][C]0.00524741[/C][/ROW]
[ROW][C]34[/C][C]0.992381[/C][C]0.015237[/C][C]0.00761851[/C][/ROW]
[ROW][C]35[/C][C]0.989453[/C][C]0.0210942[/C][C]0.0105471[/C][/ROW]
[ROW][C]36[/C][C]0.985131[/C][C]0.0297374[/C][C]0.0148687[/C][/ROW]
[ROW][C]37[/C][C]0.988785[/C][C]0.0224308[/C][C]0.0112154[/C][/ROW]
[ROW][C]38[/C][C]0.984463[/C][C]0.031073[/C][C]0.0155365[/C][/ROW]
[ROW][C]39[/C][C]0.98239[/C][C]0.0352193[/C][C]0.0176096[/C][/ROW]
[ROW][C]40[/C][C]0.982671[/C][C]0.0346572[/C][C]0.0173286[/C][/ROW]
[ROW][C]41[/C][C]0.977313[/C][C]0.0453749[/C][C]0.0226874[/C][/ROW]
[ROW][C]42[/C][C]0.975712[/C][C]0.0485764[/C][C]0.0242882[/C][/ROW]
[ROW][C]43[/C][C]0.967954[/C][C]0.0640916[/C][C]0.0320458[/C][/ROW]
[ROW][C]44[/C][C]0.961772[/C][C]0.0764567[/C][C]0.0382284[/C][/ROW]
[ROW][C]45[/C][C]0.950684[/C][C]0.0986318[/C][C]0.0493159[/C][/ROW]
[ROW][C]46[/C][C]0.959157[/C][C]0.0816868[/C][C]0.0408434[/C][/ROW]
[ROW][C]47[/C][C]0.947714[/C][C]0.104572[/C][C]0.0522859[/C][/ROW]
[ROW][C]48[/C][C]0.933772[/C][C]0.132456[/C][C]0.0662278[/C][/ROW]
[ROW][C]49[/C][C]0.951673[/C][C]0.0966541[/C][C]0.0483271[/C][/ROW]
[ROW][C]50[/C][C]0.948318[/C][C]0.103364[/C][C]0.0516822[/C][/ROW]
[ROW][C]51[/C][C]0.936593[/C][C]0.126814[/C][C]0.0634068[/C][/ROW]
[ROW][C]52[/C][C]0.921548[/C][C]0.156904[/C][C]0.0784522[/C][/ROW]
[ROW][C]53[/C][C]0.907814[/C][C]0.184372[/C][C]0.0921858[/C][/ROW]
[ROW][C]54[/C][C]0.909974[/C][C]0.180052[/C][C]0.0900262[/C][/ROW]
[ROW][C]55[/C][C]0.903273[/C][C]0.193453[/C][C]0.0967267[/C][/ROW]
[ROW][C]56[/C][C]0.887003[/C][C]0.225993[/C][C]0.112997[/C][/ROW]
[ROW][C]57[/C][C]0.87579[/C][C]0.24842[/C][C]0.12421[/C][/ROW]
[ROW][C]58[/C][C]0.852477[/C][C]0.295045[/C][C]0.147523[/C][/ROW]
[ROW][C]59[/C][C]0.879795[/C][C]0.24041[/C][C]0.120205[/C][/ROW]
[ROW][C]60[/C][C]0.875787[/C][C]0.248425[/C][C]0.124213[/C][/ROW]
[ROW][C]61[/C][C]0.896039[/C][C]0.207923[/C][C]0.103961[/C][/ROW]
[ROW][C]62[/C][C]0.891566[/C][C]0.216868[/C][C]0.108434[/C][/ROW]
[ROW][C]63[/C][C]0.932952[/C][C]0.134096[/C][C]0.067048[/C][/ROW]
[ROW][C]64[/C][C]0.92261[/C][C]0.154781[/C][C]0.0773903[/C][/ROW]
[ROW][C]65[/C][C]0.912288[/C][C]0.175423[/C][C]0.0877117[/C][/ROW]
[ROW][C]66[/C][C]0.923417[/C][C]0.153165[/C][C]0.0765826[/C][/ROW]
[ROW][C]67[/C][C]0.921273[/C][C]0.157454[/C][C]0.0787272[/C][/ROW]
[ROW][C]68[/C][C]0.914001[/C][C]0.171998[/C][C]0.085999[/C][/ROW]
[ROW][C]69[/C][C]0.942771[/C][C]0.114458[/C][C]0.0572291[/C][/ROW]
[ROW][C]70[/C][C]0.947224[/C][C]0.105551[/C][C]0.0527756[/C][/ROW]
[ROW][C]71[/C][C]0.939253[/C][C]0.121494[/C][C]0.0607468[/C][/ROW]
[ROW][C]72[/C][C]0.960225[/C][C]0.0795506[/C][C]0.0397753[/C][/ROW]
[ROW][C]73[/C][C]0.952248[/C][C]0.0955033[/C][C]0.0477516[/C][/ROW]
[ROW][C]74[/C][C]0.941515[/C][C]0.116969[/C][C]0.0584846[/C][/ROW]
[ROW][C]75[/C][C]0.934732[/C][C]0.130535[/C][C]0.0652677[/C][/ROW]
[ROW][C]76[/C][C]0.921175[/C][C]0.157649[/C][C]0.0788247[/C][/ROW]
[ROW][C]77[/C][C]0.936746[/C][C]0.126508[/C][C]0.0632542[/C][/ROW]
[ROW][C]78[/C][C]0.924481[/C][C]0.151039[/C][C]0.0755193[/C][/ROW]
[ROW][C]79[/C][C]0.917525[/C][C]0.16495[/C][C]0.0824748[/C][/ROW]
[ROW][C]80[/C][C]0.911848[/C][C]0.176303[/C][C]0.0881517[/C][/ROW]
[ROW][C]81[/C][C]0.895467[/C][C]0.209067[/C][C]0.104533[/C][/ROW]
[ROW][C]82[/C][C]0.87781[/C][C]0.244379[/C][C]0.12219[/C][/ROW]
[ROW][C]83[/C][C]0.873615[/C][C]0.252771[/C][C]0.126385[/C][/ROW]
[ROW][C]84[/C][C]0.855252[/C][C]0.289496[/C][C]0.144748[/C][/ROW]
[ROW][C]85[/C][C]0.832381[/C][C]0.335238[/C][C]0.167619[/C][/ROW]
[ROW][C]86[/C][C]0.810398[/C][C]0.379204[/C][C]0.189602[/C][/ROW]
[ROW][C]87[/C][C]0.783883[/C][C]0.432233[/C][C]0.216117[/C][/ROW]
[ROW][C]88[/C][C]0.755079[/C][C]0.489842[/C][C]0.244921[/C][/ROW]
[ROW][C]89[/C][C]0.82263[/C][C]0.354741[/C][C]0.17737[/C][/ROW]
[ROW][C]90[/C][C]0.850613[/C][C]0.298775[/C][C]0.149387[/C][/ROW]
[ROW][C]91[/C][C]0.828326[/C][C]0.343349[/C][C]0.171674[/C][/ROW]
[ROW][C]92[/C][C]0.805688[/C][C]0.388625[/C][C]0.194312[/C][/ROW]
[ROW][C]93[/C][C]0.784633[/C][C]0.430734[/C][C]0.215367[/C][/ROW]
[ROW][C]94[/C][C]0.761538[/C][C]0.476924[/C][C]0.238462[/C][/ROW]
[ROW][C]95[/C][C]0.737037[/C][C]0.525926[/C][C]0.262963[/C][/ROW]
[ROW][C]96[/C][C]0.713393[/C][C]0.573214[/C][C]0.286607[/C][/ROW]
[ROW][C]97[/C][C]0.686759[/C][C]0.626481[/C][C]0.313241[/C][/ROW]
[ROW][C]98[/C][C]0.686747[/C][C]0.626506[/C][C]0.313253[/C][/ROW]
[ROW][C]99[/C][C]0.653535[/C][C]0.692929[/C][C]0.346465[/C][/ROW]
[ROW][C]100[/C][C]0.644624[/C][C]0.710751[/C][C]0.355376[/C][/ROW]
[ROW][C]101[/C][C]0.621737[/C][C]0.756526[/C][C]0.378263[/C][/ROW]
[ROW][C]102[/C][C]0.59258[/C][C]0.81484[/C][C]0.40742[/C][/ROW]
[ROW][C]103[/C][C]0.652836[/C][C]0.694328[/C][C]0.347164[/C][/ROW]
[ROW][C]104[/C][C]0.640944[/C][C]0.718112[/C][C]0.359056[/C][/ROW]
[ROW][C]105[/C][C]0.658114[/C][C]0.683773[/C][C]0.341886[/C][/ROW]
[ROW][C]106[/C][C]0.630731[/C][C]0.738538[/C][C]0.369269[/C][/ROW]
[ROW][C]107[/C][C]0.621937[/C][C]0.756125[/C][C]0.378063[/C][/ROW]
[ROW][C]108[/C][C]0.661994[/C][C]0.676012[/C][C]0.338006[/C][/ROW]
[ROW][C]109[/C][C]0.632606[/C][C]0.734788[/C][C]0.367394[/C][/ROW]
[ROW][C]110[/C][C]0.605702[/C][C]0.788596[/C][C]0.394298[/C][/ROW]
[ROW][C]111[/C][C]0.611029[/C][C]0.777942[/C][C]0.388971[/C][/ROW]
[ROW][C]112[/C][C]0.641289[/C][C]0.717423[/C][C]0.358711[/C][/ROW]
[ROW][C]113[/C][C]0.651118[/C][C]0.697763[/C][C]0.348882[/C][/ROW]
[ROW][C]114[/C][C]0.72631[/C][C]0.547379[/C][C]0.27369[/C][/ROW]
[ROW][C]115[/C][C]0.697423[/C][C]0.605154[/C][C]0.302577[/C][/ROW]
[ROW][C]116[/C][C]0.672211[/C][C]0.655577[/C][C]0.327789[/C][/ROW]
[ROW][C]117[/C][C]0.641803[/C][C]0.716393[/C][C]0.358197[/C][/ROW]
[ROW][C]118[/C][C]0.620308[/C][C]0.759384[/C][C]0.379692[/C][/ROW]
[ROW][C]119[/C][C]0.585763[/C][C]0.828475[/C][C]0.414237[/C][/ROW]
[ROW][C]120[/C][C]0.555557[/C][C]0.888886[/C][C]0.444443[/C][/ROW]
[ROW][C]121[/C][C]0.525526[/C][C]0.948949[/C][C]0.474474[/C][/ROW]
[ROW][C]122[/C][C]0.491597[/C][C]0.983194[/C][C]0.508403[/C][/ROW]
[ROW][C]123[/C][C]0.465676[/C][C]0.931352[/C][C]0.534324[/C][/ROW]
[ROW][C]124[/C][C]0.431684[/C][C]0.863367[/C][C]0.568316[/C][/ROW]
[ROW][C]125[/C][C]0.422861[/C][C]0.845722[/C][C]0.577139[/C][/ROW]
[ROW][C]126[/C][C]0.391975[/C][C]0.783951[/C][C]0.608025[/C][/ROW]
[ROW][C]127[/C][C]0.376289[/C][C]0.752577[/C][C]0.623711[/C][/ROW]
[ROW][C]128[/C][C]0.468225[/C][C]0.936451[/C][C]0.531775[/C][/ROW]
[ROW][C]129[/C][C]0.447431[/C][C]0.894861[/C][C]0.552569[/C][/ROW]
[ROW][C]130[/C][C]0.436758[/C][C]0.873517[/C][C]0.563242[/C][/ROW]
[ROW][C]131[/C][C]0.425443[/C][C]0.850887[/C][C]0.574557[/C][/ROW]
[ROW][C]132[/C][C]0.394597[/C][C]0.789194[/C][C]0.605403[/C][/ROW]
[ROW][C]133[/C][C]0.408368[/C][C]0.816735[/C][C]0.591632[/C][/ROW]
[ROW][C]134[/C][C]0.378582[/C][C]0.757164[/C][C]0.621418[/C][/ROW]
[ROW][C]135[/C][C]0.385251[/C][C]0.770503[/C][C]0.614749[/C][/ROW]
[ROW][C]136[/C][C]0.371204[/C][C]0.742407[/C][C]0.628796[/C][/ROW]
[ROW][C]137[/C][C]0.34034[/C][C]0.680681[/C][C]0.65966[/C][/ROW]
[ROW][C]138[/C][C]0.31858[/C][C]0.637161[/C][C]0.68142[/C][/ROW]
[ROW][C]139[/C][C]0.291196[/C][C]0.582392[/C][C]0.708804[/C][/ROW]
[ROW][C]140[/C][C]0.266871[/C][C]0.533742[/C][C]0.733129[/C][/ROW]
[ROW][C]141[/C][C]0.238756[/C][C]0.477512[/C][C]0.761244[/C][/ROW]
[ROW][C]142[/C][C]0.243893[/C][C]0.487786[/C][C]0.756107[/C][/ROW]
[ROW][C]143[/C][C]0.218636[/C][C]0.437272[/C][C]0.781364[/C][/ROW]
[ROW][C]144[/C][C]0.197262[/C][C]0.394524[/C][C]0.802738[/C][/ROW]
[ROW][C]145[/C][C]0.183544[/C][C]0.367088[/C][C]0.816456[/C][/ROW]
[ROW][C]146[/C][C]0.174685[/C][C]0.34937[/C][C]0.825315[/C][/ROW]
[ROW][C]147[/C][C]0.184034[/C][C]0.368069[/C][C]0.815966[/C][/ROW]
[ROW][C]148[/C][C]0.203316[/C][C]0.406631[/C][C]0.796684[/C][/ROW]
[ROW][C]149[/C][C]0.225689[/C][C]0.451378[/C][C]0.774311[/C][/ROW]
[ROW][C]150[/C][C]0.221708[/C][C]0.443416[/C][C]0.778292[/C][/ROW]
[ROW][C]151[/C][C]0.197917[/C][C]0.395833[/C][C]0.802083[/C][/ROW]
[ROW][C]152[/C][C]0.177192[/C][C]0.354384[/C][C]0.822808[/C][/ROW]
[ROW][C]153[/C][C]0.189833[/C][C]0.379667[/C][C]0.810167[/C][/ROW]
[ROW][C]154[/C][C]0.229099[/C][C]0.458197[/C][C]0.770901[/C][/ROW]
[ROW][C]155[/C][C]0.205627[/C][C]0.411254[/C][C]0.794373[/C][/ROW]
[ROW][C]156[/C][C]0.184234[/C][C]0.368468[/C][C]0.815766[/C][/ROW]
[ROW][C]157[/C][C]0.161293[/C][C]0.322586[/C][C]0.838707[/C][/ROW]
[ROW][C]158[/C][C]0.232154[/C][C]0.464308[/C][C]0.767846[/C][/ROW]
[ROW][C]159[/C][C]0.259367[/C][C]0.518734[/C][C]0.740633[/C][/ROW]
[ROW][C]160[/C][C]0.232071[/C][C]0.464142[/C][C]0.767929[/C][/ROW]
[ROW][C]161[/C][C]0.205022[/C][C]0.410044[/C][C]0.794978[/C][/ROW]
[ROW][C]162[/C][C]0.181323[/C][C]0.362646[/C][C]0.818677[/C][/ROW]
[ROW][C]163[/C][C]0.160568[/C][C]0.321136[/C][C]0.839432[/C][/ROW]
[ROW][C]164[/C][C]0.262618[/C][C]0.525236[/C][C]0.737382[/C][/ROW]
[ROW][C]165[/C][C]0.258237[/C][C]0.516474[/C][C]0.741763[/C][/ROW]
[ROW][C]166[/C][C]0.25548[/C][C]0.51096[/C][C]0.74452[/C][/ROW]
[ROW][C]167[/C][C]0.227389[/C][C]0.454779[/C][C]0.772611[/C][/ROW]
[ROW][C]168[/C][C]0.206118[/C][C]0.412236[/C][C]0.793882[/C][/ROW]
[ROW][C]169[/C][C]0.261834[/C][C]0.523669[/C][C]0.738166[/C][/ROW]
[ROW][C]170[/C][C]0.283953[/C][C]0.567905[/C][C]0.716047[/C][/ROW]
[ROW][C]171[/C][C]0.256628[/C][C]0.513256[/C][C]0.743372[/C][/ROW]
[ROW][C]172[/C][C]0.253273[/C][C]0.506547[/C][C]0.746727[/C][/ROW]
[ROW][C]173[/C][C]0.410901[/C][C]0.821802[/C][C]0.589099[/C][/ROW]
[ROW][C]174[/C][C]0.399372[/C][C]0.798744[/C][C]0.600628[/C][/ROW]
[ROW][C]175[/C][C]0.424279[/C][C]0.848558[/C][C]0.575721[/C][/ROW]
[ROW][C]176[/C][C]0.430218[/C][C]0.860436[/C][C]0.569782[/C][/ROW]
[ROW][C]177[/C][C]0.48282[/C][C]0.96564[/C][C]0.51718[/C][/ROW]
[ROW][C]178[/C][C]0.449698[/C][C]0.899396[/C][C]0.550302[/C][/ROW]
[ROW][C]179[/C][C]0.429913[/C][C]0.859825[/C][C]0.570087[/C][/ROW]
[ROW][C]180[/C][C]0.425263[/C][C]0.850525[/C][C]0.574737[/C][/ROW]
[ROW][C]181[/C][C]0.388165[/C][C]0.77633[/C][C]0.611835[/C][/ROW]
[ROW][C]182[/C][C]0.377904[/C][C]0.755807[/C][C]0.622096[/C][/ROW]
[ROW][C]183[/C][C]0.341941[/C][C]0.683882[/C][C]0.658059[/C][/ROW]
[ROW][C]184[/C][C]0.313581[/C][C]0.627163[/C][C]0.686419[/C][/ROW]
[ROW][C]185[/C][C]0.32995[/C][C]0.659901[/C][C]0.67005[/C][/ROW]
[ROW][C]186[/C][C]0.322974[/C][C]0.645947[/C][C]0.677026[/C][/ROW]
[ROW][C]187[/C][C]0.289947[/C][C]0.579894[/C][C]0.710053[/C][/ROW]
[ROW][C]188[/C][C]0.262508[/C][C]0.525017[/C][C]0.737492[/C][/ROW]
[ROW][C]189[/C][C]0.233275[/C][C]0.466549[/C][C]0.766725[/C][/ROW]
[ROW][C]190[/C][C]0.213047[/C][C]0.426094[/C][C]0.786953[/C][/ROW]
[ROW][C]191[/C][C]0.217301[/C][C]0.434601[/C][C]0.782699[/C][/ROW]
[ROW][C]192[/C][C]0.198236[/C][C]0.396471[/C][C]0.801764[/C][/ROW]
[ROW][C]193[/C][C]0.216879[/C][C]0.433758[/C][C]0.783121[/C][/ROW]
[ROW][C]194[/C][C]0.203959[/C][C]0.407919[/C][C]0.796041[/C][/ROW]
[ROW][C]195[/C][C]0.205037[/C][C]0.410075[/C][C]0.794963[/C][/ROW]
[ROW][C]196[/C][C]0.21288[/C][C]0.425761[/C][C]0.78712[/C][/ROW]
[ROW][C]197[/C][C]0.256587[/C][C]0.513174[/C][C]0.743413[/C][/ROW]
[ROW][C]198[/C][C]0.237172[/C][C]0.474344[/C][C]0.762828[/C][/ROW]
[ROW][C]199[/C][C]0.266971[/C][C]0.533943[/C][C]0.733029[/C][/ROW]
[ROW][C]200[/C][C]0.23532[/C][C]0.47064[/C][C]0.76468[/C][/ROW]
[ROW][C]201[/C][C]0.266179[/C][C]0.532358[/C][C]0.733821[/C][/ROW]
[ROW][C]202[/C][C]0.245687[/C][C]0.491373[/C][C]0.754313[/C][/ROW]
[ROW][C]203[/C][C]0.285444[/C][C]0.570887[/C][C]0.714556[/C][/ROW]
[ROW][C]204[/C][C]0.250149[/C][C]0.500298[/C][C]0.749851[/C][/ROW]
[ROW][C]205[/C][C]0.219349[/C][C]0.438697[/C][C]0.780651[/C][/ROW]
[ROW][C]206[/C][C]0.200622[/C][C]0.401245[/C][C]0.799378[/C][/ROW]
[ROW][C]207[/C][C]0.172059[/C][C]0.344118[/C][C]0.827941[/C][/ROW]
[ROW][C]208[/C][C]0.201847[/C][C]0.403694[/C][C]0.798153[/C][/ROW]
[ROW][C]209[/C][C]0.172432[/C][C]0.344865[/C][C]0.827568[/C][/ROW]
[ROW][C]210[/C][C]0.175224[/C][C]0.350448[/C][C]0.824776[/C][/ROW]
[ROW][C]211[/C][C]0.195241[/C][C]0.390482[/C][C]0.804759[/C][/ROW]
[ROW][C]212[/C][C]0.186305[/C][C]0.37261[/C][C]0.813695[/C][/ROW]
[ROW][C]213[/C][C]0.160828[/C][C]0.321656[/C][C]0.839172[/C][/ROW]
[ROW][C]214[/C][C]0.203361[/C][C]0.406723[/C][C]0.796639[/C][/ROW]
[ROW][C]215[/C][C]0.179478[/C][C]0.358955[/C][C]0.820522[/C][/ROW]
[ROW][C]216[/C][C]0.169593[/C][C]0.339186[/C][C]0.830407[/C][/ROW]
[ROW][C]217[/C][C]0.191001[/C][C]0.382003[/C][C]0.808999[/C][/ROW]
[ROW][C]218[/C][C]0.161982[/C][C]0.323964[/C][C]0.838018[/C][/ROW]
[ROW][C]219[/C][C]0.151819[/C][C]0.303638[/C][C]0.848181[/C][/ROW]
[ROW][C]220[/C][C]0.161012[/C][C]0.322025[/C][C]0.838988[/C][/ROW]
[ROW][C]221[/C][C]0.173948[/C][C]0.347896[/C][C]0.826052[/C][/ROW]
[ROW][C]222[/C][C]0.169969[/C][C]0.339939[/C][C]0.830031[/C][/ROW]
[ROW][C]223[/C][C]0.159824[/C][C]0.319649[/C][C]0.840176[/C][/ROW]
[ROW][C]224[/C][C]0.13218[/C][C]0.26436[/C][C]0.86782[/C][/ROW]
[ROW][C]225[/C][C]0.140833[/C][C]0.281666[/C][C]0.859167[/C][/ROW]
[ROW][C]226[/C][C]0.164723[/C][C]0.329446[/C][C]0.835277[/C][/ROW]
[ROW][C]227[/C][C]0.36209[/C][C]0.72418[/C][C]0.63791[/C][/ROW]
[ROW][C]228[/C][C]0.338265[/C][C]0.676529[/C][C]0.661735[/C][/ROW]
[ROW][C]229[/C][C]0.311364[/C][C]0.622729[/C][C]0.688636[/C][/ROW]
[ROW][C]230[/C][C]0.295035[/C][C]0.590069[/C][C]0.704965[/C][/ROW]
[ROW][C]231[/C][C]0.253549[/C][C]0.507097[/C][C]0.746451[/C][/ROW]
[ROW][C]232[/C][C]0.283619[/C][C]0.567238[/C][C]0.716381[/C][/ROW]
[ROW][C]233[/C][C]0.243482[/C][C]0.486963[/C][C]0.756518[/C][/ROW]
[ROW][C]234[/C][C]0.202987[/C][C]0.405973[/C][C]0.797013[/C][/ROW]
[ROW][C]235[/C][C]0.202114[/C][C]0.404228[/C][C]0.797886[/C][/ROW]
[ROW][C]236[/C][C]0.180866[/C][C]0.361731[/C][C]0.819134[/C][/ROW]
[ROW][C]237[/C][C]0.152005[/C][C]0.304009[/C][C]0.847995[/C][/ROW]
[ROW][C]238[/C][C]0.117678[/C][C]0.235357[/C][C]0.882322[/C][/ROW]
[ROW][C]239[/C][C]0.2312[/C][C]0.4624[/C][C]0.7688[/C][/ROW]
[ROW][C]240[/C][C]0.224516[/C][C]0.449031[/C][C]0.775484[/C][/ROW]
[ROW][C]241[/C][C]0.192353[/C][C]0.384707[/C][C]0.807647[/C][/ROW]
[ROW][C]242[/C][C]0.383833[/C][C]0.767667[/C][C]0.616167[/C][/ROW]
[ROW][C]243[/C][C]0.338753[/C][C]0.677506[/C][C]0.661247[/C][/ROW]
[ROW][C]244[/C][C]0.276203[/C][C]0.552405[/C][C]0.723797[/C][/ROW]
[ROW][C]245[/C][C]0.415812[/C][C]0.831623[/C][C]0.584188[/C][/ROW]
[ROW][C]246[/C][C]0.332356[/C][C]0.664713[/C][C]0.667644[/C][/ROW]
[ROW][C]247[/C][C]0.258097[/C][C]0.516195[/C][C]0.741903[/C][/ROW]
[ROW][C]248[/C][C]0.392642[/C][C]0.785285[/C][C]0.607358[/C][/ROW]
[ROW][C]249[/C][C]0.295071[/C][C]0.590141[/C][C]0.704929[/C][/ROW]
[ROW][C]250[/C][C]0.206399[/C][C]0.412798[/C][C]0.793601[/C][/ROW]
[ROW][C]251[/C][C]0.317981[/C][C]0.635961[/C][C]0.682019[/C][/ROW]
[ROW][C]252[/C][C]0.869237[/C][C]0.261527[/C][C]0.130763[/C][/ROW]
[ROW][C]253[/C][C]0.744936[/C][C]0.510129[/C][C]0.255064[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225764&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225764&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.08015120.1603020.919849
120.9023390.1953220.097661
130.982410.03518080.0175904
140.9822130.03557350.0177867
150.9878580.02428490.0121424
160.9782720.04345550.0217278
170.9686270.06274640.0313732
180.9566630.08667480.0433374
190.9418810.1162370.0581185
200.9346470.1307060.065353
210.9434140.1131730.0565864
220.9689410.06211860.0310593
230.955250.08949980.0447499
240.9453130.1093740.0546872
250.9262570.1474860.0737431
260.9989450.002110110.00105506
270.9983890.003221670.00161084
280.9974560.005088790.00254439
290.996140.007719480.00385974
300.998170.0036610.0018305
310.9971620.005676610.0028383
320.9957580.008484910.00424246
330.9947530.01049480.00524741
340.9923810.0152370.00761851
350.9894530.02109420.0105471
360.9851310.02973740.0148687
370.9887850.02243080.0112154
380.9844630.0310730.0155365
390.982390.03521930.0176096
400.9826710.03465720.0173286
410.9773130.04537490.0226874
420.9757120.04857640.0242882
430.9679540.06409160.0320458
440.9617720.07645670.0382284
450.9506840.09863180.0493159
460.9591570.08168680.0408434
470.9477140.1045720.0522859
480.9337720.1324560.0662278
490.9516730.09665410.0483271
500.9483180.1033640.0516822
510.9365930.1268140.0634068
520.9215480.1569040.0784522
530.9078140.1843720.0921858
540.9099740.1800520.0900262
550.9032730.1934530.0967267
560.8870030.2259930.112997
570.875790.248420.12421
580.8524770.2950450.147523
590.8797950.240410.120205
600.8757870.2484250.124213
610.8960390.2079230.103961
620.8915660.2168680.108434
630.9329520.1340960.067048
640.922610.1547810.0773903
650.9122880.1754230.0877117
660.9234170.1531650.0765826
670.9212730.1574540.0787272
680.9140010.1719980.085999
690.9427710.1144580.0572291
700.9472240.1055510.0527756
710.9392530.1214940.0607468
720.9602250.07955060.0397753
730.9522480.09550330.0477516
740.9415150.1169690.0584846
750.9347320.1305350.0652677
760.9211750.1576490.0788247
770.9367460.1265080.0632542
780.9244810.1510390.0755193
790.9175250.164950.0824748
800.9118480.1763030.0881517
810.8954670.2090670.104533
820.877810.2443790.12219
830.8736150.2527710.126385
840.8552520.2894960.144748
850.8323810.3352380.167619
860.8103980.3792040.189602
870.7838830.4322330.216117
880.7550790.4898420.244921
890.822630.3547410.17737
900.8506130.2987750.149387
910.8283260.3433490.171674
920.8056880.3886250.194312
930.7846330.4307340.215367
940.7615380.4769240.238462
950.7370370.5259260.262963
960.7133930.5732140.286607
970.6867590.6264810.313241
980.6867470.6265060.313253
990.6535350.6929290.346465
1000.6446240.7107510.355376
1010.6217370.7565260.378263
1020.592580.814840.40742
1030.6528360.6943280.347164
1040.6409440.7181120.359056
1050.6581140.6837730.341886
1060.6307310.7385380.369269
1070.6219370.7561250.378063
1080.6619940.6760120.338006
1090.6326060.7347880.367394
1100.6057020.7885960.394298
1110.6110290.7779420.388971
1120.6412890.7174230.358711
1130.6511180.6977630.348882
1140.726310.5473790.27369
1150.6974230.6051540.302577
1160.6722110.6555770.327789
1170.6418030.7163930.358197
1180.6203080.7593840.379692
1190.5857630.8284750.414237
1200.5555570.8888860.444443
1210.5255260.9489490.474474
1220.4915970.9831940.508403
1230.4656760.9313520.534324
1240.4316840.8633670.568316
1250.4228610.8457220.577139
1260.3919750.7839510.608025
1270.3762890.7525770.623711
1280.4682250.9364510.531775
1290.4474310.8948610.552569
1300.4367580.8735170.563242
1310.4254430.8508870.574557
1320.3945970.7891940.605403
1330.4083680.8167350.591632
1340.3785820.7571640.621418
1350.3852510.7705030.614749
1360.3712040.7424070.628796
1370.340340.6806810.65966
1380.318580.6371610.68142
1390.2911960.5823920.708804
1400.2668710.5337420.733129
1410.2387560.4775120.761244
1420.2438930.4877860.756107
1430.2186360.4372720.781364
1440.1972620.3945240.802738
1450.1835440.3670880.816456
1460.1746850.349370.825315
1470.1840340.3680690.815966
1480.2033160.4066310.796684
1490.2256890.4513780.774311
1500.2217080.4434160.778292
1510.1979170.3958330.802083
1520.1771920.3543840.822808
1530.1898330.3796670.810167
1540.2290990.4581970.770901
1550.2056270.4112540.794373
1560.1842340.3684680.815766
1570.1612930.3225860.838707
1580.2321540.4643080.767846
1590.2593670.5187340.740633
1600.2320710.4641420.767929
1610.2050220.4100440.794978
1620.1813230.3626460.818677
1630.1605680.3211360.839432
1640.2626180.5252360.737382
1650.2582370.5164740.741763
1660.255480.510960.74452
1670.2273890.4547790.772611
1680.2061180.4122360.793882
1690.2618340.5236690.738166
1700.2839530.5679050.716047
1710.2566280.5132560.743372
1720.2532730.5065470.746727
1730.4109010.8218020.589099
1740.3993720.7987440.600628
1750.4242790.8485580.575721
1760.4302180.8604360.569782
1770.482820.965640.51718
1780.4496980.8993960.550302
1790.4299130.8598250.570087
1800.4252630.8505250.574737
1810.3881650.776330.611835
1820.3779040.7558070.622096
1830.3419410.6838820.658059
1840.3135810.6271630.686419
1850.329950.6599010.67005
1860.3229740.6459470.677026
1870.2899470.5798940.710053
1880.2625080.5250170.737492
1890.2332750.4665490.766725
1900.2130470.4260940.786953
1910.2173010.4346010.782699
1920.1982360.3964710.801764
1930.2168790.4337580.783121
1940.2039590.4079190.796041
1950.2050370.4100750.794963
1960.212880.4257610.78712
1970.2565870.5131740.743413
1980.2371720.4743440.762828
1990.2669710.5339430.733029
2000.235320.470640.76468
2010.2661790.5323580.733821
2020.2456870.4913730.754313
2030.2854440.5708870.714556
2040.2501490.5002980.749851
2050.2193490.4386970.780651
2060.2006220.4012450.799378
2070.1720590.3441180.827941
2080.2018470.4036940.798153
2090.1724320.3448650.827568
2100.1752240.3504480.824776
2110.1952410.3904820.804759
2120.1863050.372610.813695
2130.1608280.3216560.839172
2140.2033610.4067230.796639
2150.1794780.3589550.820522
2160.1695930.3391860.830407
2170.1910010.3820030.808999
2180.1619820.3239640.838018
2190.1518190.3036380.848181
2200.1610120.3220250.838988
2210.1739480.3478960.826052
2220.1699690.3399390.830031
2230.1598240.3196490.840176
2240.132180.264360.86782
2250.1408330.2816660.859167
2260.1647230.3294460.835277
2270.362090.724180.63791
2280.3382650.6765290.661735
2290.3113640.6227290.688636
2300.2950350.5900690.704965
2310.2535490.5070970.746451
2320.2836190.5672380.716381
2330.2434820.4869630.756518
2340.2029870.4059730.797013
2350.2021140.4042280.797886
2360.1808660.3617310.819134
2370.1520050.3040090.847995
2380.1176780.2353570.882322
2390.23120.46240.7688
2400.2245160.4490310.775484
2410.1923530.3847070.807647
2420.3838330.7676670.616167
2430.3387530.6775060.661247
2440.2762030.5524050.723797
2450.4158120.8316230.584188
2460.3323560.6647130.667644
2470.2580970.5161950.741903
2480.3926420.7852850.607358
2490.2950710.5901410.704929
2500.2063990.4127980.793601
2510.3179810.6359610.682019
2520.8692370.2615270.130763
2530.7449360.5101290.255064






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level70.0288066NOK
5% type I error level210.0864198NOK
10% type I error level320.131687NOK

\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 & 7 & 0.0288066 & NOK \tabularnewline
5% type I error level & 21 & 0.0864198 & NOK \tabularnewline
10% type I error level & 32 & 0.131687 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225764&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]7[/C][C]0.0288066[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]21[/C][C]0.0864198[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]32[/C][C]0.131687[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225764&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225764&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 level70.0288066NOK
5% type I error level210.0864198NOK
10% type I error level320.131687NOK


Figures (Output of Computation)

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

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