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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 computationSat, 02 Nov 2013 15:41:02 -0400
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/02/t13834213282mntbszxp9oi7y9.htm/, Retrieved Tue, 07 May 2024 04:47:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221806, Retrieved Tue, 07 May 2024 04:47:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact84

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [WORKSHOP 7 ] [2013-11-02 19:41:02] [4c6743e926d608f4adf2160fecf92c6f] [Current]
- R PD    [Multiple Regression] [ws7 1] [2013-11-02 20:57:07] [69bf0eb8b9b38defaaf4848d8c317571]
-   PD    [Multiple Regression] [w7] [2013-11-02 21:02:57] [69bf0eb8b9b38defaaf4848d8c317571]
-   PD    [Multiple Regression] [W7] [2013-11-02 21:13:17] [69bf0eb8b9b38defaaf4848d8c317571]
-   PD    [Multiple Regression] [7] [2013-11-02 21:22:54] [69bf0eb8b9b38defaaf4848d8c317571]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41 38 13 12 14 12 53 32
39 32 16 11 18 11 83 51
30 35 19 15 11 14 66 42
31 33 15   6 12 12 67 41
34 37 14 13 16 21 76 46
35 29 13 10 18 12 78 47
39 31 19 12 14 22 53 37
34 36 15 14 14 11 80 49
36 35 14 12 15 10 74 45
37 38 15   9 15 13 76 47
38 31 16 10 17 10 79 49
36 34 16 12 19   8 54 33
38 35 16 12 10 15 67 42
39 38 16 11 16 14 54 33
33 37 17 15 18 10 87 53
32 33 15 12 14 14 58 36
36 32 15 10 14 14 75 45
38 38 20 12 17 11 88 54
39 38 18 11 14 10 64 41
32 32 16 12 16 13 57 36
32 33 16 11 18 9.5 66 41
31 31 16 12 11 14 68 44
39 38 19 13 14 12 54 33
37 39 16 11 12 14 56 37
39 32 17 12 17 11 86 52
41 32 17 13   9   9 80 47
36 35 16 10 16 11 76 43
33 37 15 14 14 15 69 44
33 33 16 12 15 14 78 45
34 33 14 10 11 13 67 44
31 31 15 12 16   9 80 49
27 32 12   8 13 15 54 33
37 31 14 10 17 10 71 43
34 37 16 12 15 11 84 54
34 30 14 12 14 13 74 42
32 33 10   7 16   8 71 44
29 31 10   9   9 20 63 37
36 33 14 12 15 12 71 43
29 31 16 10 17 10 76 46
35 33 16 10 13 10 69 42
37 32 16 10 15   9 74 45
34 33 14 12 16 14 75 44
38 32 20 15 16   8 54 33
35 33 14 10 12 14 52 31
38 28 14 10 15 11 69 42
37 35 11 12 11 13 68 40
38 39 14 13 15   9 65 43
33 34 15 11 15 11 75 46
36 38 16 11 17 15 74 42
38 32 14 12 13 11 75 45
32 38 16 14 16 10 72 44
32 30 14 10 14 14 67 40
32 33 12 12 11 18 63 37
34 38 16 13 12 14 62 46
32 32   9   5 12 11 63 36
37 35 14   6 15 14 76 47
39 34 16 12 16 13 74 45
29 34 16 12 15   9 67 42
37 36 15 11 12 10 73 43
35 34 16 10 12 15 70 43
30 28 12   7   8 20 53 32
38 34 16 12 13 12 77 45
34 35 16 14 11 12 80 48
31 35 14 11 14 14 52 31
34 31 16 12 15 13 54 33
35 37 17 13 10 11 80 49
36 35 18 14 11 17 66 42
30 27 18 11 12 12 73 41
39 40 12 12 15 13 63 38
35 37 16 12 15 14 69 42
38 36 10   8 14 13 67 44
31 38 14 11 16 15 54 33
34 39 18 14 15 13 81 48
38 41 18 14 15 10 69 40
34 27 16 12 13 11 84 50
39 30 17   9 12 19 80 49
37 37 16 13 17 13 70 43
34 31 16 11 13 17 69 44
28 31 13 12 15 13 77 47
37 27 16 12 13   9 54 33
33 36 16 12 15 11 79 46
35 37 16 12 15   9 71 45
37 33 15 12 16 12 73 43
32 34 15 11 15 12 72 44
33 31 16 10 14 13 77 47
38 39 14   9 15 13 75 45
33 34 16 12 14 12 69 42
29 32 16 12 13 15 54 33
33 33 15 12   7 22 70 43
31 36 12   9 17 13 73 46
36 32 17 15 13 15 54 33
35 41 16 12 15 13 77 46
32 28 15 12 14 15 82 48
29 30 13 12 13 12 80 47
39 36 16 10 16 11 80 47
37 35 16 13 12 16 69 43
35 31 16   9 14 11 78 46
37 34 16 12 17 11 81 48
32 36 14 10 15 10 76 46
38 36 16 14 17 10 76 45
37 35 16 11 12 16 73 45
36 37 20 15 16 12 85 52
32 28 15 11 11 11 66 42
33 39 16 11 15 16 79 47
40 32 13 12   9 19 68 41
38 35 17 12 16 11 76 47
41 39 16 12 15 16 71 43
36 35 16 11 10 15 54 33
43 42 12   7 10 24 46 30
30 34 16 12 15 14 85 52
31 33 16 14 11 15 74 44
32 41 17 11 13 11 88 55
32 33 13 11 14 15 38 11
37 34 12 10 18 12 76 47
37 32 18 13 16 10 86 53
33 40 14 13 14 14 54 33
34 40 14   8 14 13 67 44
33 35 13 11 14   9 69 42
38 36 16 12 14 15 90 55
33 37 13 11 12 15 54 33
31 27 16 13 14 14 76 46
38 39 13 12 15 11 89 54
37 38 16 14 15   8 76 47
36 31 15 13 15 11 73 45
31 33 16 15 13 11 79 47
39 32 15 10 17   8 90 55
44 39 17 11 17 10 74 44
33 36 15   9 19 11 81 53
35 33 12 11 15 13 72 44
32 33 16 10 13 11 71 42
28 32 10 11   9 20 66 40
40 37 16   8 15 10 77 46
27 30 12 11 15 15 65 40
37 38 14 12 15 12 74 46
32 29 15 12 16 14 85 53
28 22 13   9 11 23 54 33
34 35 15 11 14 14 63 42
30 35 11 10 11 16 54 35
35 34 12   8 15 11 64 40
31 35 11   9 13 12 69 41
32 34 16   8 15 10 54 33
30 37 15   9 16 14 84 51
30 35 17 15 14 12 86 53
31 23 16 11 15 12 77 46
40 31 10   8 16 11 89 55
32 27 18 13 16 12 76 47
36 36 13 12 11 13 60 38
32 31 16 12 12 11 75 46
35 32 13   9   9 19 73 46
38 39 10   7 16 12 85 53
42 37 15 13 13 17 79 47
34 38 16   9 16   9 71 41
35 39 16   6 12 12 72 44
38 34 14   8   9 19 69 43
33 31 10   8 13 18 78 51
36 32 17 15 13 15 54 33
32 37 13   6 14 14 69 43
33 36 15   9 19 11 81 53
34 32 16 11 13   9 84 51
32 38 12   8 12 18 84 50
34 36 13   8 13 16 69 46
27 26 13 10 10 24 66 43
31 26 12   8 14 14 81 47
38 33 17 14 16 20 82 50
34 39 15 10 10 18 72 43
24 30 10   8 11 23 54 33
30 33 14 11 14 12 78 48
26 25 11 12 12 14 74 44
34 38 13 12   9 16 82 50
27 37 16 12   9 18 73 41
37 31 12   5 11 20 55 34
36 37 16 12 16 12 72 44
41 35 12 10   9 12 78 47
29 25   9   7 13 17 59 35
36 28 12 12 16 13 72 44
32 35 15 11 13   9 78 44
37 33 12   8   9 16 68 43
30 30 12   9 12 18 69 41
31 31 14 10 16 10 67 41
38 37 12   9 11 14 74 42
36 36 16 12 14 11 54 33
35 30 11   6 13   9 67 41
31 36 19 15 15 11 70 44
38 32 15 12 14 10 80 48
22 28   8 12 16 11 89 55
32 36 16 12 13 19 76 44
36 34 17 11 14 14 74 43
39 31 12   7 15 12 87 52
28 28 11   7 13 14 54 30
32 36 11   5 11 21 61 39
32 36 14 12 11 13 38 11
38 40 16 12 14 10 75 44
32 33 12   3 15 15 69 42
35 37 16 11 11 16 62 41
32 32 13 10 15 14 72 44
37 38 15 12 12 12 70 44
34 31 16   9 14 19 79 48
33 37 16 12 14 15 87 53
33 33 14   9   8 19 62 37
26 32 16 12 13 13 77 44
30 30 16 12   9 17 69 44
24 30 14 10 15 12 69 40
34 31 11   9 17 11 75 42
34 32 12 12 13 14 54 35
33 34 15   8 15 11 72 43
34 36 15 11 15 13 74 45
35 37 16 11 14 12 85 55
35 36 16 12 16 15 52 31
36 33 11 10 13 14 70 44
34 33 15 10 16 12 84 50
34 33 12 12   9 17 64 40
41 44 12 12 16 11 84 53
32 39 15 11 11 18 87 54
30 32 15   8 10 13 79 49
35 35 16 12 11 17 67 40
28 25 14 10 15 13 65 41
33 35 17 11 17 11 85 52
39 34 14 10 14 12 83 52
36 35 13   8   8 22 61 36
36 39 15 12 15 14 82 52
35 33 13 12 11 12 76 46
38 36 14 10 16 12 58 31
33 32 15 12 10 17 72 44
31 32 12   9 15   9 72 44
34 36 13   9   9 21 38 11
32 36   8   6 16 10 78 46
31 32 14 10 19 11 54 33
33 34 14   9 12 12 63 34
34 33 11   9   8 23 66 42
34 35 12   9 11 13 70 43
34 30 13   6 14 12 71 43
33 38 10 10   9 16 67 44
32 34 16   6 15   9 58 36
41 33 18 14 13 17 72 46
34 32 13 10 16   9 72 44
36 31 11 10 11 14 70 43
37 30   4   6 12 17 76 50
36 27 13 12 13 13 50 33
29 31 16 12 10 11 72 43
37 30 10   7 11 12 72 44
27 32 12   8 12 10 88 53
35 35 12 11   8 19 53 34
28 28 10   3 12 16 58 35
35 33 13   6 12 16 66 40
37 31 15 10 15 14 82 53
29 35 12   8 11 20 69 42
32 35 14   9 13 15 68 43
36 32 10   9 14 23 44 29
19 21 12   8 10 20 56 36
21 20 12   9 12 16 53 30
31 34 11   7 15 14 70 42
33 32 10   7 13 17 78 47
36 34 12   6 13 11 71 44
33 32 16   9 13 13 72 45
37 33 12 10 12 17 68 44
34 33 14 11 12 15 67 43
35 37 16 12   9 21 75 43
31 32 14   8   9 18 62 40
37 34 13 11 15 15 67 41
35 30   4   3 10   8 83 52
27 30 15 11 14 12 64 38
34 38 11 12 15 12 68 41
40 36 11   7   7 22 62 39
29 32 14   9 14 12 72 43

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time22 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 22 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221806&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]22 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221806&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221806&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 time22 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 5.33063 + 0.0334462Connected[t] + 0.0429147Separate[t] + 0.55744Software[t] + 0.0707992Happiness[t] -0.0288762Depression[t] + 0.0235591Sport1[t] -0.0252568Sport2[t] -0.00493647t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  5.33063 +  0.0334462Connected[t] +  0.0429147Separate[t] +  0.55744Software[t] +  0.0707992Happiness[t] -0.0288762Depression[t] +  0.0235591Sport1[t] -0.0252568Sport2[t] -0.00493647t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221806&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  5.33063 +  0.0334462Connected[t] +  0.0429147Separate[t] +  0.55744Software[t] +  0.0707992Happiness[t] -0.0288762Depression[t] +  0.0235591Sport1[t] -0.0252568Sport2[t] -0.00493647t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221806&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221806&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
Learning[t] = + 5.33063 + 0.0334462Connected[t] + 0.0429147Separate[t] + 0.55744Software[t] + 0.0707992Happiness[t] -0.0288762Depression[t] + 0.0235591Sport1[t] -0.0252568Sport2[t] -0.00493647t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)5.330631.962312.7170.007049030.00352452
Connected0.03344620.034590.96690.3344930.167247
Separate0.04291470.03513251.2220.2230220.111511
Software0.557440.053862510.353.47336e-211.73668e-21
Happiness0.07079920.05790811.2230.2226040.111302
Depression-0.02887620.0421026-0.68590.4934290.246714
Sport10.02355910.03739170.63010.5292190.264609
Sport2-0.02525680.055664-0.45370.6504050.325202
t-0.004936470.00168407-2.9310.00368210.00184105

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 5.33063 & 1.96231 & 2.717 & 0.00704903 & 0.00352452 \tabularnewline
Connected & 0.0334462 & 0.03459 & 0.9669 & 0.334493 & 0.167247 \tabularnewline
Separate & 0.0429147 & 0.0351325 & 1.222 & 0.223022 & 0.111511 \tabularnewline
Software & 0.55744 & 0.0538625 & 10.35 & 3.47336e-21 & 1.73668e-21 \tabularnewline
Happiness & 0.0707992 & 0.0579081 & 1.223 & 0.222604 & 0.111302 \tabularnewline
Depression & -0.0288762 & 0.0421026 & -0.6859 & 0.493429 & 0.246714 \tabularnewline
Sport1 & 0.0235591 & 0.0373917 & 0.6301 & 0.529219 & 0.264609 \tabularnewline
Sport2 & -0.0252568 & 0.055664 & -0.4537 & 0.650405 & 0.325202 \tabularnewline
t & -0.00493647 & 0.00168407 & -2.931 & 0.0036821 & 0.00184105 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221806&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]5.33063[/C][C]1.96231[/C][C]2.717[/C][C]0.00704903[/C][C]0.00352452[/C][/ROW]
[ROW][C]Connected[/C][C]0.0334462[/C][C]0.03459[/C][C]0.9669[/C][C]0.334493[/C][C]0.167247[/C][/ROW]
[ROW][C]Separate[/C][C]0.0429147[/C][C]0.0351325[/C][C]1.222[/C][C]0.223022[/C][C]0.111511[/C][/ROW]
[ROW][C]Software[/C][C]0.55744[/C][C]0.0538625[/C][C]10.35[/C][C]3.47336e-21[/C][C]1.73668e-21[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0707992[/C][C]0.0579081[/C][C]1.223[/C][C]0.222604[/C][C]0.111302[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0288762[/C][C]0.0421026[/C][C]-0.6859[/C][C]0.493429[/C][C]0.246714[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0235591[/C][C]0.0373917[/C][C]0.6301[/C][C]0.529219[/C][C]0.264609[/C][/ROW]
[ROW][C]Sport2[/C][C]-0.0252568[/C][C]0.055664[/C][C]-0.4537[/C][C]0.650405[/C][C]0.325202[/C][/ROW]
[ROW][C]t[/C][C]-0.00493647[/C][C]0.00168407[/C][C]-2.931[/C][C]0.0036821[/C][C]0.00184105[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221806&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221806&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)5.330631.962312.7170.007049030.00352452
Connected0.03344620.034590.96690.3344930.167247
Separate0.04291470.03513251.2220.2230220.111511
Software0.557440.053862510.353.47336e-211.73668e-21
Happiness0.07079920.05790811.2230.2226040.111302
Depression-0.02887620.0421026-0.68590.4934290.246714
Sport10.02355910.03739170.63010.5292190.264609
Sport2-0.02525680.055664-0.45370.6504050.325202
t-0.004936470.00168407-2.9310.00368210.00184105






Multiple Linear Regression - Regression Statistics
Multiple R0.667542
R-squared0.445612
Adjusted R-squared0.42822
F-TEST (value)25.6209
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.85711
Sum Squared Residuals879.461

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.667542 \tabularnewline
R-squared & 0.445612 \tabularnewline
Adjusted R-squared & 0.42822 \tabularnewline
F-TEST (value) & 25.6209 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 255 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.85711 \tabularnewline
Sum Squared Residuals & 879.461 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221806&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.667542[/C][/ROW]
[ROW][C]R-squared[/C][C]0.445612[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.42822[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]25.6209[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]255[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]1.85711[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]879.461[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221806&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221806&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 R0.667542
R-squared0.445612
Adjusted R-squared0.42822
F-TEST (value)25.6209
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.85711
Sum Squared Residuals879.461






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11316.1021-3.10212
21615.75430.245669
31917.05151.94853
41512.15462.84545
51416.4328-2.43275
61314.869-1.86897
71915.29023.70984
81517.0981-2.0981
91416.0616-2.06161
101514.45650.543482
111614.99051.00954
121616.1767-0.176735
131615.52120.478765
141615.49580.504237
151718.0064-1.00641
161515.4715-0.471502
171514.61570.384252
182016.42813.57194
191815.47852.52148
201615.55580.444243
211615.36470.635292
221615.14370.856254
231916.48242.51763
241615.08530.914685
251716.17290.827146
261716.26850.731461
271614.99741.00257
281516.7605-1.76047
291615.75540.244557
301414.1809-0.180859
311515.7541-0.75412
321212.8345-0.834469
331414.8115-0.811476
341615.93650.0634619
351415.5701-1.57014
361013.0046-3.00464
371013.0746-3.07463
381415.7547-1.75471
391614.55631.44369
401614.49081.5092
411614.72231.27766
421415.7501-1.75009
432017.46472.53531
441414.1621-0.162069
451414.4646-0.464604
461115.5275-4.52751
471416.5374-2.53737
481515.1378-0.13782
491615.50840.491558
501415.6504-1.65045
511617.0131-1.01306
521414.1612-0.161169
531215.0535-3.05349
541615.82290.177108
55911.3968-2.39681
561412.39951.6005
571615.86630.133747
581615.48240.517583
591515.1483-0.148263
601614.21811.78189
611211.56590.434128
621615.69530.304719
631616.5677-0.567663
641414.7144-0.714423
651615.29190.708113
661716.04750.952491
671816.29211.70786
681814.47623.52376
691215.9114-3.91135
701615.65530.344662
711013.3385-3.33851
721414.913-0.913002
731816.96781.03216
741817.18850.811511
751615.26440.735575
761713.51243.48765
771616.4139-0.413892
781614.48871.51127
791315.2104-2.21036
801615.12040.879573
811615.71240.287578
821615.71180.288171
831515.6839-0.683929
841514.87760.122379
851614.16231.8377
861414.1847-0.184662
871615.36270.637265
881614.85471.14532
891514.52390.476107
901213.8713-1.87127
911716.74630.253684
921615.83470.165284
931515.1103-0.11028
941315.0848-2.0848
951614.79821.20179
961615.77010.229914
971613.71912.28092
981615.81470.185339
991414.4334-0.433438
1001617.0258-1.0258
1011614.67421.32575
1022017.45612.54393
1031514.18120.818822
1041615.00050.999451
1051314.8677-1.86774
1061715.68821.31181
1071615.72330.276696
1081614.3491.65102
1091212.2762-0.276221
1101615.28630.713718
1111616.0176-0.0175886
1121715.02621.9738
1131314.5666-1.56659
1141214.5702-2.57018
1151816.15191.84806
1161415.8507-1.85068
1171413.14930.850694
1181314.7818-1.78181
1191615.53760.462398
1201314.4168-1.41683
1211615.39120.608826
1221315.8395-2.83954
1231616.8303-0.83028
1241515.8273-0.827262
1251616.805-0.805047
1261514.66450.335515
1271715.52771.47225
1281513.96161.0384
1291214.684-2.68403
1301613.96442.03558
1311013.7299-3.72986
1321613.48972.5103
1331214.1463-2.14633
1341415.5237-1.52373
1351515.0607-0.0607315
1361312.11020.889791
1371514.43570.564275
1381113.4342-2.43418
1391212.9756-0.975563
1401113.3593-2.35926
1411612.83543.16457
1421513.65721.34277
1431716.82390.176131
1441614.14321.85679
1451013.2654-3.26536
1461815.47532.5247
1471314.9004-1.90044
1481614.8271.17297
1491312.80250.197505
1501012.8871-2.88706
1511515.9281-0.928128
1521613.87532.12475
1531611.85234.14768
1541412.38811.61193
1551012.4092-2.40921
1561716.42540.574554
1571311.68481.31517
1581513.81351.18649
1591614.53941.46061
1601212.7473-0.7473
1611312.59960.400381
1621312.6080.392021
1631212.4463-0.446265
1641716.23660.763374
1651513.69981.3002
1661011.6142-1.61421
1671414.3276-0.327615
1681114.2105-3.21046
1691314.7978-1.79776
1701614.47331.52669
1711210.47981.52015
1721615.3340.66602
1731213.8656-1.86555
174911.3521-2.35207
1751214.9041-2.90406
1761514.55280.447235
1771212.2612-0.261245
1781212.6796-0.679599
1791413.77560.224448
1801213.3749-1.37494
1811614.98771.01232
1821111.4383-0.43833
1831916.65282.34719
1841515.1307-0.130661
185814.5669-6.56688
1861614.76791.23213
1871714.44682.55323
1881212.3912-0.391178
1891111.4684-0.468438
1901110.41960.580407
1911414.7131-0.71308
1921615.41770.582282
193129.730322.26968
1941614.00521.99483
1951313.6287-0.628651
1961514.96160.0384496
1971612.9343.06598
1981615.00310.996859
1991412.42911.57094
2001614.52321.47676
2011613.97912.02091
2021413.32880.671202
2031113.4051-2.40511
2041214.4276-2.42764
2051512.69562.30443
2061514.42110.578922
2071614.45721.54284
2081614.85041.14957
2091113.5475-2.54752
2101513.92411.07587
2111214.1755-2.17549
2121215.6884-3.68843
2131514.09980.900246
2141512.06662.93341
2151614.48731.51271
2161413.03050.96947
2171714.57212.42788
2181413.87910.120887
2191311.87411.12588
2201515.0878-0.0878435
2211314.5767-1.57671
2221413.99480.00523547
2231514.19810.801869
2241213.039-1.03899
2251312.56720.432797
226811.6947-3.69466
2271413.66080.339176
2281412.91351.08653
2291112.1669-1.16686
2301212.8179-0.817888
2311311.19091.80911
2321013.1366-3.13659
2331611.31374.68626
2341815.73112.26892
2351313.7133-0.713265
2361113.2121-2.21207
237410.9166-6.91663
2381314.0973-1.09728
2391614.1411.85904
2401011.5901-1.59015
2411212.1722-0.172203
2421213.3481-1.34813
243108.811511.18849
2441310.98982.01022
2451513.51441.48558
2461211.81380.186203
2471412.70381.2962
2481012.3319-2.33187
2491210.63821.36181
2501211.55260.447358
2511111.7357-0.735666
2521011.5458-1.54575
2531211.25370.746341
2541612.67543.32457
2551213.1493-1.14935
2561413.6610.339039
2571614.22141.77861
2581411.49452.50554
2591314.0523-1.05232
26049.29656-5.29656
2611513.55721.44276
2621114.7765-3.77645
2631111.1532-0.153167
2641412.64251.35753

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 16.1021 & -3.10212 \tabularnewline
2 & 16 & 15.7543 & 0.245669 \tabularnewline
3 & 19 & 17.0515 & 1.94853 \tabularnewline
4 & 15 & 12.1546 & 2.84545 \tabularnewline
5 & 14 & 16.4328 & -2.43275 \tabularnewline
6 & 13 & 14.869 & -1.86897 \tabularnewline
7 & 19 & 15.2902 & 3.70984 \tabularnewline
8 & 15 & 17.0981 & -2.0981 \tabularnewline
9 & 14 & 16.0616 & -2.06161 \tabularnewline
10 & 15 & 14.4565 & 0.543482 \tabularnewline
11 & 16 & 14.9905 & 1.00954 \tabularnewline
12 & 16 & 16.1767 & -0.176735 \tabularnewline
13 & 16 & 15.5212 & 0.478765 \tabularnewline
14 & 16 & 15.4958 & 0.504237 \tabularnewline
15 & 17 & 18.0064 & -1.00641 \tabularnewline
16 & 15 & 15.4715 & -0.471502 \tabularnewline
17 & 15 & 14.6157 & 0.384252 \tabularnewline
18 & 20 & 16.4281 & 3.57194 \tabularnewline
19 & 18 & 15.4785 & 2.52148 \tabularnewline
20 & 16 & 15.5558 & 0.444243 \tabularnewline
21 & 16 & 15.3647 & 0.635292 \tabularnewline
22 & 16 & 15.1437 & 0.856254 \tabularnewline
23 & 19 & 16.4824 & 2.51763 \tabularnewline
24 & 16 & 15.0853 & 0.914685 \tabularnewline
25 & 17 & 16.1729 & 0.827146 \tabularnewline
26 & 17 & 16.2685 & 0.731461 \tabularnewline
27 & 16 & 14.9974 & 1.00257 \tabularnewline
28 & 15 & 16.7605 & -1.76047 \tabularnewline
29 & 16 & 15.7554 & 0.244557 \tabularnewline
30 & 14 & 14.1809 & -0.180859 \tabularnewline
31 & 15 & 15.7541 & -0.75412 \tabularnewline
32 & 12 & 12.8345 & -0.834469 \tabularnewline
33 & 14 & 14.8115 & -0.811476 \tabularnewline
34 & 16 & 15.9365 & 0.0634619 \tabularnewline
35 & 14 & 15.5701 & -1.57014 \tabularnewline
36 & 10 & 13.0046 & -3.00464 \tabularnewline
37 & 10 & 13.0746 & -3.07463 \tabularnewline
38 & 14 & 15.7547 & -1.75471 \tabularnewline
39 & 16 & 14.5563 & 1.44369 \tabularnewline
40 & 16 & 14.4908 & 1.5092 \tabularnewline
41 & 16 & 14.7223 & 1.27766 \tabularnewline
42 & 14 & 15.7501 & -1.75009 \tabularnewline
43 & 20 & 17.4647 & 2.53531 \tabularnewline
44 & 14 & 14.1621 & -0.162069 \tabularnewline
45 & 14 & 14.4646 & -0.464604 \tabularnewline
46 & 11 & 15.5275 & -4.52751 \tabularnewline
47 & 14 & 16.5374 & -2.53737 \tabularnewline
48 & 15 & 15.1378 & -0.13782 \tabularnewline
49 & 16 & 15.5084 & 0.491558 \tabularnewline
50 & 14 & 15.6504 & -1.65045 \tabularnewline
51 & 16 & 17.0131 & -1.01306 \tabularnewline
52 & 14 & 14.1612 & -0.161169 \tabularnewline
53 & 12 & 15.0535 & -3.05349 \tabularnewline
54 & 16 & 15.8229 & 0.177108 \tabularnewline
55 & 9 & 11.3968 & -2.39681 \tabularnewline
56 & 14 & 12.3995 & 1.6005 \tabularnewline
57 & 16 & 15.8663 & 0.133747 \tabularnewline
58 & 16 & 15.4824 & 0.517583 \tabularnewline
59 & 15 & 15.1483 & -0.148263 \tabularnewline
60 & 16 & 14.2181 & 1.78189 \tabularnewline
61 & 12 & 11.5659 & 0.434128 \tabularnewline
62 & 16 & 15.6953 & 0.304719 \tabularnewline
63 & 16 & 16.5677 & -0.567663 \tabularnewline
64 & 14 & 14.7144 & -0.714423 \tabularnewline
65 & 16 & 15.2919 & 0.708113 \tabularnewline
66 & 17 & 16.0475 & 0.952491 \tabularnewline
67 & 18 & 16.2921 & 1.70786 \tabularnewline
68 & 18 & 14.4762 & 3.52376 \tabularnewline
69 & 12 & 15.9114 & -3.91135 \tabularnewline
70 & 16 & 15.6553 & 0.344662 \tabularnewline
71 & 10 & 13.3385 & -3.33851 \tabularnewline
72 & 14 & 14.913 & -0.913002 \tabularnewline
73 & 18 & 16.9678 & 1.03216 \tabularnewline
74 & 18 & 17.1885 & 0.811511 \tabularnewline
75 & 16 & 15.2644 & 0.735575 \tabularnewline
76 & 17 & 13.5124 & 3.48765 \tabularnewline
77 & 16 & 16.4139 & -0.413892 \tabularnewline
78 & 16 & 14.4887 & 1.51127 \tabularnewline
79 & 13 & 15.2104 & -2.21036 \tabularnewline
80 & 16 & 15.1204 & 0.879573 \tabularnewline
81 & 16 & 15.7124 & 0.287578 \tabularnewline
82 & 16 & 15.7118 & 0.288171 \tabularnewline
83 & 15 & 15.6839 & -0.683929 \tabularnewline
84 & 15 & 14.8776 & 0.122379 \tabularnewline
85 & 16 & 14.1623 & 1.8377 \tabularnewline
86 & 14 & 14.1847 & -0.184662 \tabularnewline
87 & 16 & 15.3627 & 0.637265 \tabularnewline
88 & 16 & 14.8547 & 1.14532 \tabularnewline
89 & 15 & 14.5239 & 0.476107 \tabularnewline
90 & 12 & 13.8713 & -1.87127 \tabularnewline
91 & 17 & 16.7463 & 0.253684 \tabularnewline
92 & 16 & 15.8347 & 0.165284 \tabularnewline
93 & 15 & 15.1103 & -0.11028 \tabularnewline
94 & 13 & 15.0848 & -2.0848 \tabularnewline
95 & 16 & 14.7982 & 1.20179 \tabularnewline
96 & 16 & 15.7701 & 0.229914 \tabularnewline
97 & 16 & 13.7191 & 2.28092 \tabularnewline
98 & 16 & 15.8147 & 0.185339 \tabularnewline
99 & 14 & 14.4334 & -0.433438 \tabularnewline
100 & 16 & 17.0258 & -1.0258 \tabularnewline
101 & 16 & 14.6742 & 1.32575 \tabularnewline
102 & 20 & 17.4561 & 2.54393 \tabularnewline
103 & 15 & 14.1812 & 0.818822 \tabularnewline
104 & 16 & 15.0005 & 0.999451 \tabularnewline
105 & 13 & 14.8677 & -1.86774 \tabularnewline
106 & 17 & 15.6882 & 1.31181 \tabularnewline
107 & 16 & 15.7233 & 0.276696 \tabularnewline
108 & 16 & 14.349 & 1.65102 \tabularnewline
109 & 12 & 12.2762 & -0.276221 \tabularnewline
110 & 16 & 15.2863 & 0.713718 \tabularnewline
111 & 16 & 16.0176 & -0.0175886 \tabularnewline
112 & 17 & 15.0262 & 1.9738 \tabularnewline
113 & 13 & 14.5666 & -1.56659 \tabularnewline
114 & 12 & 14.5702 & -2.57018 \tabularnewline
115 & 18 & 16.1519 & 1.84806 \tabularnewline
116 & 14 & 15.8507 & -1.85068 \tabularnewline
117 & 14 & 13.1493 & 0.850694 \tabularnewline
118 & 13 & 14.7818 & -1.78181 \tabularnewline
119 & 16 & 15.5376 & 0.462398 \tabularnewline
120 & 13 & 14.4168 & -1.41683 \tabularnewline
121 & 16 & 15.3912 & 0.608826 \tabularnewline
122 & 13 & 15.8395 & -2.83954 \tabularnewline
123 & 16 & 16.8303 & -0.83028 \tabularnewline
124 & 15 & 15.8273 & -0.827262 \tabularnewline
125 & 16 & 16.805 & -0.805047 \tabularnewline
126 & 15 & 14.6645 & 0.335515 \tabularnewline
127 & 17 & 15.5277 & 1.47225 \tabularnewline
128 & 15 & 13.9616 & 1.0384 \tabularnewline
129 & 12 & 14.684 & -2.68403 \tabularnewline
130 & 16 & 13.9644 & 2.03558 \tabularnewline
131 & 10 & 13.7299 & -3.72986 \tabularnewline
132 & 16 & 13.4897 & 2.5103 \tabularnewline
133 & 12 & 14.1463 & -2.14633 \tabularnewline
134 & 14 & 15.5237 & -1.52373 \tabularnewline
135 & 15 & 15.0607 & -0.0607315 \tabularnewline
136 & 13 & 12.1102 & 0.889791 \tabularnewline
137 & 15 & 14.4357 & 0.564275 \tabularnewline
138 & 11 & 13.4342 & -2.43418 \tabularnewline
139 & 12 & 12.9756 & -0.975563 \tabularnewline
140 & 11 & 13.3593 & -2.35926 \tabularnewline
141 & 16 & 12.8354 & 3.16457 \tabularnewline
142 & 15 & 13.6572 & 1.34277 \tabularnewline
143 & 17 & 16.8239 & 0.176131 \tabularnewline
144 & 16 & 14.1432 & 1.85679 \tabularnewline
145 & 10 & 13.2654 & -3.26536 \tabularnewline
146 & 18 & 15.4753 & 2.5247 \tabularnewline
147 & 13 & 14.9004 & -1.90044 \tabularnewline
148 & 16 & 14.827 & 1.17297 \tabularnewline
149 & 13 & 12.8025 & 0.197505 \tabularnewline
150 & 10 & 12.8871 & -2.88706 \tabularnewline
151 & 15 & 15.9281 & -0.928128 \tabularnewline
152 & 16 & 13.8753 & 2.12475 \tabularnewline
153 & 16 & 11.8523 & 4.14768 \tabularnewline
154 & 14 & 12.3881 & 1.61193 \tabularnewline
155 & 10 & 12.4092 & -2.40921 \tabularnewline
156 & 17 & 16.4254 & 0.574554 \tabularnewline
157 & 13 & 11.6848 & 1.31517 \tabularnewline
158 & 15 & 13.8135 & 1.18649 \tabularnewline
159 & 16 & 14.5394 & 1.46061 \tabularnewline
160 & 12 & 12.7473 & -0.7473 \tabularnewline
161 & 13 & 12.5996 & 0.400381 \tabularnewline
162 & 13 & 12.608 & 0.392021 \tabularnewline
163 & 12 & 12.4463 & -0.446265 \tabularnewline
164 & 17 & 16.2366 & 0.763374 \tabularnewline
165 & 15 & 13.6998 & 1.3002 \tabularnewline
166 & 10 & 11.6142 & -1.61421 \tabularnewline
167 & 14 & 14.3276 & -0.327615 \tabularnewline
168 & 11 & 14.2105 & -3.21046 \tabularnewline
169 & 13 & 14.7978 & -1.79776 \tabularnewline
170 & 16 & 14.4733 & 1.52669 \tabularnewline
171 & 12 & 10.4798 & 1.52015 \tabularnewline
172 & 16 & 15.334 & 0.66602 \tabularnewline
173 & 12 & 13.8656 & -1.86555 \tabularnewline
174 & 9 & 11.3521 & -2.35207 \tabularnewline
175 & 12 & 14.9041 & -2.90406 \tabularnewline
176 & 15 & 14.5528 & 0.447235 \tabularnewline
177 & 12 & 12.2612 & -0.261245 \tabularnewline
178 & 12 & 12.6796 & -0.679599 \tabularnewline
179 & 14 & 13.7756 & 0.224448 \tabularnewline
180 & 12 & 13.3749 & -1.37494 \tabularnewline
181 & 16 & 14.9877 & 1.01232 \tabularnewline
182 & 11 & 11.4383 & -0.43833 \tabularnewline
183 & 19 & 16.6528 & 2.34719 \tabularnewline
184 & 15 & 15.1307 & -0.130661 \tabularnewline
185 & 8 & 14.5669 & -6.56688 \tabularnewline
186 & 16 & 14.7679 & 1.23213 \tabularnewline
187 & 17 & 14.4468 & 2.55323 \tabularnewline
188 & 12 & 12.3912 & -0.391178 \tabularnewline
189 & 11 & 11.4684 & -0.468438 \tabularnewline
190 & 11 & 10.4196 & 0.580407 \tabularnewline
191 & 14 & 14.7131 & -0.71308 \tabularnewline
192 & 16 & 15.4177 & 0.582282 \tabularnewline
193 & 12 & 9.73032 & 2.26968 \tabularnewline
194 & 16 & 14.0052 & 1.99483 \tabularnewline
195 & 13 & 13.6287 & -0.628651 \tabularnewline
196 & 15 & 14.9616 & 0.0384496 \tabularnewline
197 & 16 & 12.934 & 3.06598 \tabularnewline
198 & 16 & 15.0031 & 0.996859 \tabularnewline
199 & 14 & 12.4291 & 1.57094 \tabularnewline
200 & 16 & 14.5232 & 1.47676 \tabularnewline
201 & 16 & 13.9791 & 2.02091 \tabularnewline
202 & 14 & 13.3288 & 0.671202 \tabularnewline
203 & 11 & 13.4051 & -2.40511 \tabularnewline
204 & 12 & 14.4276 & -2.42764 \tabularnewline
205 & 15 & 12.6956 & 2.30443 \tabularnewline
206 & 15 & 14.4211 & 0.578922 \tabularnewline
207 & 16 & 14.4572 & 1.54284 \tabularnewline
208 & 16 & 14.8504 & 1.14957 \tabularnewline
209 & 11 & 13.5475 & -2.54752 \tabularnewline
210 & 15 & 13.9241 & 1.07587 \tabularnewline
211 & 12 & 14.1755 & -2.17549 \tabularnewline
212 & 12 & 15.6884 & -3.68843 \tabularnewline
213 & 15 & 14.0998 & 0.900246 \tabularnewline
214 & 15 & 12.0666 & 2.93341 \tabularnewline
215 & 16 & 14.4873 & 1.51271 \tabularnewline
216 & 14 & 13.0305 & 0.96947 \tabularnewline
217 & 17 & 14.5721 & 2.42788 \tabularnewline
218 & 14 & 13.8791 & 0.120887 \tabularnewline
219 & 13 & 11.8741 & 1.12588 \tabularnewline
220 & 15 & 15.0878 & -0.0878435 \tabularnewline
221 & 13 & 14.5767 & -1.57671 \tabularnewline
222 & 14 & 13.9948 & 0.00523547 \tabularnewline
223 & 15 & 14.1981 & 0.801869 \tabularnewline
224 & 12 & 13.039 & -1.03899 \tabularnewline
225 & 13 & 12.5672 & 0.432797 \tabularnewline
226 & 8 & 11.6947 & -3.69466 \tabularnewline
227 & 14 & 13.6608 & 0.339176 \tabularnewline
228 & 14 & 12.9135 & 1.08653 \tabularnewline
229 & 11 & 12.1669 & -1.16686 \tabularnewline
230 & 12 & 12.8179 & -0.817888 \tabularnewline
231 & 13 & 11.1909 & 1.80911 \tabularnewline
232 & 10 & 13.1366 & -3.13659 \tabularnewline
233 & 16 & 11.3137 & 4.68626 \tabularnewline
234 & 18 & 15.7311 & 2.26892 \tabularnewline
235 & 13 & 13.7133 & -0.713265 \tabularnewline
236 & 11 & 13.2121 & -2.21207 \tabularnewline
237 & 4 & 10.9166 & -6.91663 \tabularnewline
238 & 13 & 14.0973 & -1.09728 \tabularnewline
239 & 16 & 14.141 & 1.85904 \tabularnewline
240 & 10 & 11.5901 & -1.59015 \tabularnewline
241 & 12 & 12.1722 & -0.172203 \tabularnewline
242 & 12 & 13.3481 & -1.34813 \tabularnewline
243 & 10 & 8.81151 & 1.18849 \tabularnewline
244 & 13 & 10.9898 & 2.01022 \tabularnewline
245 & 15 & 13.5144 & 1.48558 \tabularnewline
246 & 12 & 11.8138 & 0.186203 \tabularnewline
247 & 14 & 12.7038 & 1.2962 \tabularnewline
248 & 10 & 12.3319 & -2.33187 \tabularnewline
249 & 12 & 10.6382 & 1.36181 \tabularnewline
250 & 12 & 11.5526 & 0.447358 \tabularnewline
251 & 11 & 11.7357 & -0.735666 \tabularnewline
252 & 10 & 11.5458 & -1.54575 \tabularnewline
253 & 12 & 11.2537 & 0.746341 \tabularnewline
254 & 16 & 12.6754 & 3.32457 \tabularnewline
255 & 12 & 13.1493 & -1.14935 \tabularnewline
256 & 14 & 13.661 & 0.339039 \tabularnewline
257 & 16 & 14.2214 & 1.77861 \tabularnewline
258 & 14 & 11.4945 & 2.50554 \tabularnewline
259 & 13 & 14.0523 & -1.05232 \tabularnewline
260 & 4 & 9.29656 & -5.29656 \tabularnewline
261 & 15 & 13.5572 & 1.44276 \tabularnewline
262 & 11 & 14.7765 & -3.77645 \tabularnewline
263 & 11 & 11.1532 & -0.153167 \tabularnewline
264 & 14 & 12.6425 & 1.35753 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221806&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]13[/C][C]16.1021[/C][C]-3.10212[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.7543[/C][C]0.245669[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]17.0515[/C][C]1.94853[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]12.1546[/C][C]2.84545[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.4328[/C][C]-2.43275[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.869[/C][C]-1.86897[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.2902[/C][C]3.70984[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]17.0981[/C][C]-2.0981[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]16.0616[/C][C]-2.06161[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.4565[/C][C]0.543482[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.9905[/C][C]1.00954[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.1767[/C][C]-0.176735[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.5212[/C][C]0.478765[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.4958[/C][C]0.504237[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]18.0064[/C][C]-1.00641[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.4715[/C][C]-0.471502[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.6157[/C][C]0.384252[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.4281[/C][C]3.57194[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.4785[/C][C]2.52148[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.5558[/C][C]0.444243[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.3647[/C][C]0.635292[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]15.1437[/C][C]0.856254[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.4824[/C][C]2.51763[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]15.0853[/C][C]0.914685[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]16.1729[/C][C]0.827146[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.2685[/C][C]0.731461[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.9974[/C][C]1.00257[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.7605[/C][C]-1.76047[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.7554[/C][C]0.244557[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.1809[/C][C]-0.180859[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.7541[/C][C]-0.75412[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.8345[/C][C]-0.834469[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.8115[/C][C]-0.811476[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.9365[/C][C]0.0634619[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.5701[/C][C]-1.57014[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]13.0046[/C][C]-3.00464[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]13.0746[/C][C]-3.07463[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.7547[/C][C]-1.75471[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.5563[/C][C]1.44369[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.4908[/C][C]1.5092[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.7223[/C][C]1.27766[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.7501[/C][C]-1.75009[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.4647[/C][C]2.53531[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.1621[/C][C]-0.162069[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.4646[/C][C]-0.464604[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.5275[/C][C]-4.52751[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.5374[/C][C]-2.53737[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.1378[/C][C]-0.13782[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.5084[/C][C]0.491558[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.6504[/C][C]-1.65045[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]17.0131[/C][C]-1.01306[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.1612[/C][C]-0.161169[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]15.0535[/C][C]-3.05349[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.8229[/C][C]0.177108[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]11.3968[/C][C]-2.39681[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.3995[/C][C]1.6005[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.8663[/C][C]0.133747[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.4824[/C][C]0.517583[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]15.1483[/C][C]-0.148263[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.2181[/C][C]1.78189[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.5659[/C][C]0.434128[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.6953[/C][C]0.304719[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.5677[/C][C]-0.567663[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.7144[/C][C]-0.714423[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.2919[/C][C]0.708113[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]16.0475[/C][C]0.952491[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.2921[/C][C]1.70786[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.4762[/C][C]3.52376[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.9114[/C][C]-3.91135[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.6553[/C][C]0.344662[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.3385[/C][C]-3.33851[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.913[/C][C]-0.913002[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.9678[/C][C]1.03216[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.1885[/C][C]0.811511[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.2644[/C][C]0.735575[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.5124[/C][C]3.48765[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.4139[/C][C]-0.413892[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.4887[/C][C]1.51127[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]15.2104[/C][C]-2.21036[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.1204[/C][C]0.879573[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.7124[/C][C]0.287578[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.7118[/C][C]0.288171[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.6839[/C][C]-0.683929[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.8776[/C][C]0.122379[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]14.1623[/C][C]1.8377[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.1847[/C][C]-0.184662[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.3627[/C][C]0.637265[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.8547[/C][C]1.14532[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.5239[/C][C]0.476107[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.8713[/C][C]-1.87127[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.7463[/C][C]0.253684[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.8347[/C][C]0.165284[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.1103[/C][C]-0.11028[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]15.0848[/C][C]-2.0848[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.7982[/C][C]1.20179[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.7701[/C][C]0.229914[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.7191[/C][C]2.28092[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.8147[/C][C]0.185339[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.4334[/C][C]-0.433438[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.0258[/C][C]-1.0258[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.6742[/C][C]1.32575[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.4561[/C][C]2.54393[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.1812[/C][C]0.818822[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]15.0005[/C][C]0.999451[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.8677[/C][C]-1.86774[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.6882[/C][C]1.31181[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.7233[/C][C]0.276696[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.349[/C][C]1.65102[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.2762[/C][C]-0.276221[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.2863[/C][C]0.713718[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]16.0176[/C][C]-0.0175886[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]15.0262[/C][C]1.9738[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.5666[/C][C]-1.56659[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.5702[/C][C]-2.57018[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.1519[/C][C]1.84806[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.8507[/C][C]-1.85068[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.1493[/C][C]0.850694[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.7818[/C][C]-1.78181[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.5376[/C][C]0.462398[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.4168[/C][C]-1.41683[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.3912[/C][C]0.608826[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.8395[/C][C]-2.83954[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]16.8303[/C][C]-0.83028[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.8273[/C][C]-0.827262[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.805[/C][C]-0.805047[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.6645[/C][C]0.335515[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.5277[/C][C]1.47225[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]13.9616[/C][C]1.0384[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.684[/C][C]-2.68403[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.9644[/C][C]2.03558[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.7299[/C][C]-3.72986[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4897[/C][C]2.5103[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.1463[/C][C]-2.14633[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.5237[/C][C]-1.52373[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.0607[/C][C]-0.0607315[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]12.1102[/C][C]0.889791[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.4357[/C][C]0.564275[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.4342[/C][C]-2.43418[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]12.9756[/C][C]-0.975563[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.3593[/C][C]-2.35926[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8354[/C][C]3.16457[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.6572[/C][C]1.34277[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]16.8239[/C][C]0.176131[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.1432[/C][C]1.85679[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.2654[/C][C]-3.26536[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.4753[/C][C]2.5247[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]14.9004[/C][C]-1.90044[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.827[/C][C]1.17297[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.8025[/C][C]0.197505[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.8871[/C][C]-2.88706[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]15.9281[/C][C]-0.928128[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.8753[/C][C]2.12475[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.8523[/C][C]4.14768[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.3881[/C][C]1.61193[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.4092[/C][C]-2.40921[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.4254[/C][C]0.574554[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.6848[/C][C]1.31517[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]13.8135[/C][C]1.18649[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.5394[/C][C]1.46061[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.7473[/C][C]-0.7473[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.5996[/C][C]0.400381[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.608[/C][C]0.392021[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.4463[/C][C]-0.446265[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.2366[/C][C]0.763374[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.6998[/C][C]1.3002[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.6142[/C][C]-1.61421[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.3276[/C][C]-0.327615[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.2105[/C][C]-3.21046[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.7978[/C][C]-1.79776[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.4733[/C][C]1.52669[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.4798[/C][C]1.52015[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.334[/C][C]0.66602[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.8656[/C][C]-1.86555[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.3521[/C][C]-2.35207[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]14.9041[/C][C]-2.90406[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.5528[/C][C]0.447235[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.2612[/C][C]-0.261245[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.6796[/C][C]-0.679599[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.7756[/C][C]0.224448[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.3749[/C][C]-1.37494[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]14.9877[/C][C]1.01232[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.4383[/C][C]-0.43833[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]16.6528[/C][C]2.34719[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.1307[/C][C]-0.130661[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.5669[/C][C]-6.56688[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.7679[/C][C]1.23213[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.4468[/C][C]2.55323[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.3912[/C][C]-0.391178[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.4684[/C][C]-0.468438[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.4196[/C][C]0.580407[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14.7131[/C][C]-0.71308[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.4177[/C][C]0.582282[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.73032[/C][C]2.26968[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.0052[/C][C]1.99483[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.6287[/C][C]-0.628651[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]14.9616[/C][C]0.0384496[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]12.934[/C][C]3.06598[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.0031[/C][C]0.996859[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4291[/C][C]1.57094[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.5232[/C][C]1.47676[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]13.9791[/C][C]2.02091[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.3288[/C][C]0.671202[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.4051[/C][C]-2.40511[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.4276[/C][C]-2.42764[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.6956[/C][C]2.30443[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.4211[/C][C]0.578922[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.4572[/C][C]1.54284[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]14.8504[/C][C]1.14957[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.5475[/C][C]-2.54752[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]13.9241[/C][C]1.07587[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.1755[/C][C]-2.17549[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]15.6884[/C][C]-3.68843[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.0998[/C][C]0.900246[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.0666[/C][C]2.93341[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.4873[/C][C]1.51271[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.0305[/C][C]0.96947[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.5721[/C][C]2.42788[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.8791[/C][C]0.120887[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.8741[/C][C]1.12588[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.0878[/C][C]-0.0878435[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]14.5767[/C][C]-1.57671[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]13.9948[/C][C]0.00523547[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.1981[/C][C]0.801869[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.039[/C][C]-1.03899[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.5672[/C][C]0.432797[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.6947[/C][C]-3.69466[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]13.6608[/C][C]0.339176[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]12.9135[/C][C]1.08653[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.1669[/C][C]-1.16686[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]12.8179[/C][C]-0.817888[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.1909[/C][C]1.80911[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.1366[/C][C]-3.13659[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.3137[/C][C]4.68626[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]15.7311[/C][C]2.26892[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]13.7133[/C][C]-0.713265[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.2121[/C][C]-2.21207[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]10.9166[/C][C]-6.91663[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.0973[/C][C]-1.09728[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.141[/C][C]1.85904[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.5901[/C][C]-1.59015[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.1722[/C][C]-0.172203[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.3481[/C][C]-1.34813[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.81151[/C][C]1.18849[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]10.9898[/C][C]2.01022[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.5144[/C][C]1.48558[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]11.8138[/C][C]0.186203[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]12.7038[/C][C]1.2962[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.3319[/C][C]-2.33187[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.6382[/C][C]1.36181[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.5526[/C][C]0.447358[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.7357[/C][C]-0.735666[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.5458[/C][C]-1.54575[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.2537[/C][C]0.746341[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]12.6754[/C][C]3.32457[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.1493[/C][C]-1.14935[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.661[/C][C]0.339039[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.2214[/C][C]1.77861[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.4945[/C][C]2.50554[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.0523[/C][C]-1.05232[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.29656[/C][C]-5.29656[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.5572[/C][C]1.44276[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]14.7765[/C][C]-3.77645[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.1532[/C][C]-0.153167[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]12.6425[/C][C]1.35753[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221806&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221806&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
11316.1021-3.10212
21615.75430.245669
31917.05151.94853
41512.15462.84545
51416.4328-2.43275
61314.869-1.86897
71915.29023.70984
81517.0981-2.0981
91416.0616-2.06161
101514.45650.543482
111614.99051.00954
121616.1767-0.176735
131615.52120.478765
141615.49580.504237
151718.0064-1.00641
161515.4715-0.471502
171514.61570.384252
182016.42813.57194
191815.47852.52148
201615.55580.444243
211615.36470.635292
221615.14370.856254
231916.48242.51763
241615.08530.914685
251716.17290.827146
261716.26850.731461
271614.99741.00257
281516.7605-1.76047
291615.75540.244557
301414.1809-0.180859
311515.7541-0.75412
321212.8345-0.834469
331414.8115-0.811476
341615.93650.0634619
351415.5701-1.57014
361013.0046-3.00464
371013.0746-3.07463
381415.7547-1.75471
391614.55631.44369
401614.49081.5092
411614.72231.27766
421415.7501-1.75009
432017.46472.53531
441414.1621-0.162069
451414.4646-0.464604
461115.5275-4.52751
471416.5374-2.53737
481515.1378-0.13782
491615.50840.491558
501415.6504-1.65045
511617.0131-1.01306
521414.1612-0.161169
531215.0535-3.05349
541615.82290.177108
55911.3968-2.39681
561412.39951.6005
571615.86630.133747
581615.48240.517583
591515.1483-0.148263
601614.21811.78189
611211.56590.434128
621615.69530.304719
631616.5677-0.567663
641414.7144-0.714423
651615.29190.708113
661716.04750.952491
671816.29211.70786
681814.47623.52376
691215.9114-3.91135
701615.65530.344662
711013.3385-3.33851
721414.913-0.913002
731816.96781.03216
741817.18850.811511
751615.26440.735575
761713.51243.48765
771616.4139-0.413892
781614.48871.51127
791315.2104-2.21036
801615.12040.879573
811615.71240.287578
821615.71180.288171
831515.6839-0.683929
841514.87760.122379
851614.16231.8377
861414.1847-0.184662
871615.36270.637265
881614.85471.14532
891514.52390.476107
901213.8713-1.87127
911716.74630.253684
921615.83470.165284
931515.1103-0.11028
941315.0848-2.0848
951614.79821.20179
961615.77010.229914
971613.71912.28092
981615.81470.185339
991414.4334-0.433438
1001617.0258-1.0258
1011614.67421.32575
1022017.45612.54393
1031514.18120.818822
1041615.00050.999451
1051314.8677-1.86774
1061715.68821.31181
1071615.72330.276696
1081614.3491.65102
1091212.2762-0.276221
1101615.28630.713718
1111616.0176-0.0175886
1121715.02621.9738
1131314.5666-1.56659
1141214.5702-2.57018
1151816.15191.84806
1161415.8507-1.85068
1171413.14930.850694
1181314.7818-1.78181
1191615.53760.462398
1201314.4168-1.41683
1211615.39120.608826
1221315.8395-2.83954
1231616.8303-0.83028
1241515.8273-0.827262
1251616.805-0.805047
1261514.66450.335515
1271715.52771.47225
1281513.96161.0384
1291214.684-2.68403
1301613.96442.03558
1311013.7299-3.72986
1321613.48972.5103
1331214.1463-2.14633
1341415.5237-1.52373
1351515.0607-0.0607315
1361312.11020.889791
1371514.43570.564275
1381113.4342-2.43418
1391212.9756-0.975563
1401113.3593-2.35926
1411612.83543.16457
1421513.65721.34277
1431716.82390.176131
1441614.14321.85679
1451013.2654-3.26536
1461815.47532.5247
1471314.9004-1.90044
1481614.8271.17297
1491312.80250.197505
1501012.8871-2.88706
1511515.9281-0.928128
1521613.87532.12475
1531611.85234.14768
1541412.38811.61193
1551012.4092-2.40921
1561716.42540.574554
1571311.68481.31517
1581513.81351.18649
1591614.53941.46061
1601212.7473-0.7473
1611312.59960.400381
1621312.6080.392021
1631212.4463-0.446265
1641716.23660.763374
1651513.69981.3002
1661011.6142-1.61421
1671414.3276-0.327615
1681114.2105-3.21046
1691314.7978-1.79776
1701614.47331.52669
1711210.47981.52015
1721615.3340.66602
1731213.8656-1.86555
174911.3521-2.35207
1751214.9041-2.90406
1761514.55280.447235
1771212.2612-0.261245
1781212.6796-0.679599
1791413.77560.224448
1801213.3749-1.37494
1811614.98771.01232
1821111.4383-0.43833
1831916.65282.34719
1841515.1307-0.130661
185814.5669-6.56688
1861614.76791.23213
1871714.44682.55323
1881212.3912-0.391178
1891111.4684-0.468438
1901110.41960.580407
1911414.7131-0.71308
1921615.41770.582282
193129.730322.26968
1941614.00521.99483
1951313.6287-0.628651
1961514.96160.0384496
1971612.9343.06598
1981615.00310.996859
1991412.42911.57094
2001614.52321.47676
2011613.97912.02091
2021413.32880.671202
2031113.4051-2.40511
2041214.4276-2.42764
2051512.69562.30443
2061514.42110.578922
2071614.45721.54284
2081614.85041.14957
2091113.5475-2.54752
2101513.92411.07587
2111214.1755-2.17549
2121215.6884-3.68843
2131514.09980.900246
2141512.06662.93341
2151614.48731.51271
2161413.03050.96947
2171714.57212.42788
2181413.87910.120887
2191311.87411.12588
2201515.0878-0.0878435
2211314.5767-1.57671
2221413.99480.00523547
2231514.19810.801869
2241213.039-1.03899
2251312.56720.432797
226811.6947-3.69466
2271413.66080.339176
2281412.91351.08653
2291112.1669-1.16686
2301212.8179-0.817888
2311311.19091.80911
2321013.1366-3.13659
2331611.31374.68626
2341815.73112.26892
2351313.7133-0.713265
2361113.2121-2.21207
237410.9166-6.91663
2381314.0973-1.09728
2391614.1411.85904
2401011.5901-1.59015
2411212.1722-0.172203
2421213.3481-1.34813
243108.811511.18849
2441310.98982.01022
2451513.51441.48558
2461211.81380.186203
2471412.70381.2962
2481012.3319-2.33187
2491210.63821.36181
2501211.55260.447358
2511111.7357-0.735666
2521011.5458-1.54575
2531211.25370.746341
2541612.67543.32457
2551213.1493-1.14935
2561413.6610.339039
2571614.22141.77861
2581411.49452.50554
2591314.0523-1.05232
26049.29656-5.29656
2611513.55721.44276
2621114.7765-3.77645
2631111.1532-0.153167
2641412.64251.35753






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.09490480.189810.905095
130.1688170.3376330.831183
140.1788590.3577170.821141
150.1021040.2042090.897896
160.07842480.156850.921575
170.08701970.1740390.91298
180.2132160.4264310.786784
190.1758050.3516090.824195
200.1394010.2788020.860599
210.1076130.2152250.892387
220.1313960.2627910.868604
230.2298420.4596840.770158
240.3453920.6907850.654608
250.2821520.5643030.717848
260.2373180.4746360.762682
270.2278920.4557830.772108
280.3384790.6769580.661521
290.289320.578640.71068
300.3978770.7957530.602123
310.3568830.7137670.643117
320.3294090.6588190.670591
330.3141140.6282270.685886
340.2782560.5565110.721744
350.2368130.4736260.763187
360.3668860.7337720.633114
370.3956010.7912020.604399
380.3715540.7431090.628446
390.4161870.8323730.583813
400.3965310.7930620.603469
410.3577880.7155760.642212
420.3194770.6389540.680523
430.3384060.6768120.661594
440.29140.58280.7086
450.264490.5289810.73551
460.44160.8831990.5584
470.5322440.9355110.467756
480.4891780.9783570.510822
490.5136180.9727640.486382
500.4865910.9731810.513409
510.4415230.8830470.558477
520.4003910.8007830.599609
530.3998350.799670.600165
540.3580530.7161070.641947
550.3460460.6920910.653954
560.34220.68440.6578
570.3032820.6065640.696718
580.2846210.5692420.715379
590.2548080.5096160.745192
600.2755580.5511160.724442
610.2524390.5048770.747561
620.2277810.4555630.772219
630.19920.3984010.8008
640.1715790.3431590.828421
650.1513940.3027890.848606
660.1426780.2853570.857322
670.138760.277520.86124
680.2686540.5373070.731346
690.3635890.7271780.636411
700.3332270.6664530.666773
710.4418150.883630.558185
720.4071760.8143530.592824
730.4078570.8157140.592143
740.3960110.7920220.603989
750.3589490.7178980.641051
760.425330.850660.57467
770.3875750.7751490.612425
780.3616940.7233880.638306
790.376360.7527190.62364
800.3427320.6854640.657268
810.3141410.6282820.685859
820.2804820.5609640.719518
830.2529030.5058070.747097
840.223070.446140.77693
850.216980.4339590.78302
860.1895380.3790750.810462
870.1672230.3344460.832777
880.1548930.3097860.845107
890.1334220.2668440.866578
900.132030.264060.86797
910.1129390.2258790.887061
920.09869980.19740.9013
930.083930.167860.91607
940.08740920.1748180.912591
950.07908240.1581650.920918
960.06618050.1323610.93382
970.07092040.1418410.92908
980.0589110.1178220.941089
990.04888130.09776250.951119
1000.04294860.08589710.957051
1010.0375980.07519590.962402
1020.04348940.08697890.956511
1030.03665590.07331180.963344
1040.03286480.06572970.967135
1050.039170.07833990.96083
1060.03408070.06816130.965919
1070.02767630.05535250.972324
1080.02680680.05361360.973193
1090.02178010.04356020.97822
1100.01774820.03549640.982252
1110.0140720.0281440.985928
1120.01422010.02844020.98578
1130.01291090.02582180.987089
1140.01888680.03777360.981113
1150.01775670.03551330.982243
1160.01726040.03452070.98274
1170.01418660.02837330.985813
1180.01426970.02853950.98573
1190.01150230.02300450.988498
1200.01029710.02059430.989703
1210.00827190.01654380.991728
1220.01252880.02505750.987471
1230.01045440.02090880.989546
1240.008979380.01795880.991021
1250.00729950.0145990.9927
1260.005776920.01155380.994223
1270.005261780.01052360.994738
1280.004253520.008507050.995746
1290.006010380.01202080.99399
1300.00660990.01321980.99339
1310.01375190.02750380.986248
1320.01644110.03288210.983559
1330.0176240.0352480.982376
1340.01671540.03343080.983285
1350.01336090.02672170.986639
1360.0112360.0224720.988764
1370.008927710.01785540.991072
1380.01116280.02232560.988837
1390.009566730.01913350.990433
1400.01132090.02264180.988679
1410.01797880.03595760.982021
1420.01656910.03313830.983431
1430.01332270.02664550.986677
1440.01371740.02743480.986283
1450.02459890.04919770.975401
1460.02985820.05971650.970142
1470.03133960.06267930.96866
1480.02773380.05546750.972266
1490.02257090.04514170.977429
1500.0315140.06302790.968486
1510.02661630.05323250.973384
1520.02896980.05793950.97103
1530.05860870.1172170.941391
1540.05647490.112950.943525
1550.06468120.1293620.935319
1560.05499750.1099950.945003
1570.049080.09815990.95092
1580.04274520.08549040.957255
1590.0413880.08277610.958612
1600.03551790.07103580.964482
1610.02899960.05799920.971
1620.02367150.0473430.976328
1630.01933820.03867630.980662
1640.01635160.03270320.983648
1650.01447030.02894060.98553
1660.01496970.02993940.98503
1670.01190120.02380250.988099
1680.01753340.03506680.982467
1690.01765340.03530680.982347
1700.01675440.03350880.983246
1710.01547450.0309490.984525
1720.0124870.0249740.987513
1730.01210010.02420030.9879
1740.0137870.02757390.986213
1750.01794950.03589890.982051
1760.01439220.02878440.985608
1770.01136350.02272710.988636
1780.009555120.01911020.990445
1790.007397490.0147950.992603
1800.006515630.01303130.993484
1810.005315790.01063160.994684
1820.004090510.008181010.995909
1830.004428260.008856530.995572
1840.003354790.006709570.996645
1850.09165540.1833110.908345
1860.08194690.1638940.918053
1870.09043940.1808790.909561
1880.0759160.1518320.924084
1890.06776120.1355220.932239
1900.05660240.1132050.943398
1910.05237690.1047540.947623
1920.04326740.08653480.956733
1930.04438890.08877770.955611
1940.04487130.08974250.955129
1950.03880210.07760410.961198
1960.03122330.06244650.968777
1970.03942450.07884890.960576
1980.03219150.0643830.967809
1990.02897140.05794280.971029
2000.02486380.04972760.975136
2010.02325260.04650510.976747
2020.0196560.03931190.980344
2030.02581280.05162560.974187
2040.03006460.06012930.969935
2050.03148760.06297530.968512
2060.02468180.04936350.975318
2070.02362770.04725540.976372
2080.01931570.03863130.980684
2090.02153820.04307640.978462
2100.01716540.03433090.982835
2110.01972650.03945310.980273
2120.03199640.06399280.968004
2130.02490920.04981840.975091
2140.03221260.06442520.967787
2150.02733370.05466740.972666
2160.02114610.04229220.978854
2170.02322980.04645950.97677
2180.01958760.03917520.980412
2190.01819840.03639690.981802
2200.01391610.02783220.986084
2210.0115890.02317810.988411
2220.008321920.01664380.991678
2230.006382750.01276550.993617
2240.004810840.009621680.995189
2250.004095180.008190350.995905
2260.009468770.01893750.990531
2270.00741950.0148390.992581
2280.005490250.01098050.99451
2290.003926990.007853970.996073
2300.002891240.005782470.997109
2310.002606960.005213920.997393
2320.006138840.01227770.993861
2330.02477190.04954390.975228
2340.03775560.07551120.962244
2350.02723680.05447360.972763
2360.022830.04566010.97717
2370.197390.394780.80261
2380.1556850.3113690.844315
2390.1296240.2592480.870376
2400.1005560.2011130.899444
2410.0884190.1768380.911581
2420.1379540.2759070.862046
2430.1129730.2259470.887027
2440.1183070.2366150.881693
2450.09683090.1936620.903169
2460.08218340.1643670.917817
2470.05306260.1061250.946937
2480.04521030.09042070.95479
2490.04045830.08091670.959542
2500.1155090.2310180.884491
2510.09471370.1894270.905286
2520.4314540.8629090.568546

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.0949048 & 0.18981 & 0.905095 \tabularnewline
13 & 0.168817 & 0.337633 & 0.831183 \tabularnewline
14 & 0.178859 & 0.357717 & 0.821141 \tabularnewline
15 & 0.102104 & 0.204209 & 0.897896 \tabularnewline
16 & 0.0784248 & 0.15685 & 0.921575 \tabularnewline
17 & 0.0870197 & 0.174039 & 0.91298 \tabularnewline
18 & 0.213216 & 0.426431 & 0.786784 \tabularnewline
19 & 0.175805 & 0.351609 & 0.824195 \tabularnewline
20 & 0.139401 & 0.278802 & 0.860599 \tabularnewline
21 & 0.107613 & 0.215225 & 0.892387 \tabularnewline
22 & 0.131396 & 0.262791 & 0.868604 \tabularnewline
23 & 0.229842 & 0.459684 & 0.770158 \tabularnewline
24 & 0.345392 & 0.690785 & 0.654608 \tabularnewline
25 & 0.282152 & 0.564303 & 0.717848 \tabularnewline
26 & 0.237318 & 0.474636 & 0.762682 \tabularnewline
27 & 0.227892 & 0.455783 & 0.772108 \tabularnewline
28 & 0.338479 & 0.676958 & 0.661521 \tabularnewline
29 & 0.28932 & 0.57864 & 0.71068 \tabularnewline
30 & 0.397877 & 0.795753 & 0.602123 \tabularnewline
31 & 0.356883 & 0.713767 & 0.643117 \tabularnewline
32 & 0.329409 & 0.658819 & 0.670591 \tabularnewline
33 & 0.314114 & 0.628227 & 0.685886 \tabularnewline
34 & 0.278256 & 0.556511 & 0.721744 \tabularnewline
35 & 0.236813 & 0.473626 & 0.763187 \tabularnewline
36 & 0.366886 & 0.733772 & 0.633114 \tabularnewline
37 & 0.395601 & 0.791202 & 0.604399 \tabularnewline
38 & 0.371554 & 0.743109 & 0.628446 \tabularnewline
39 & 0.416187 & 0.832373 & 0.583813 \tabularnewline
40 & 0.396531 & 0.793062 & 0.603469 \tabularnewline
41 & 0.357788 & 0.715576 & 0.642212 \tabularnewline
42 & 0.319477 & 0.638954 & 0.680523 \tabularnewline
43 & 0.338406 & 0.676812 & 0.661594 \tabularnewline
44 & 0.2914 & 0.5828 & 0.7086 \tabularnewline
45 & 0.26449 & 0.528981 & 0.73551 \tabularnewline
46 & 0.4416 & 0.883199 & 0.5584 \tabularnewline
47 & 0.532244 & 0.935511 & 0.467756 \tabularnewline
48 & 0.489178 & 0.978357 & 0.510822 \tabularnewline
49 & 0.513618 & 0.972764 & 0.486382 \tabularnewline
50 & 0.486591 & 0.973181 & 0.513409 \tabularnewline
51 & 0.441523 & 0.883047 & 0.558477 \tabularnewline
52 & 0.400391 & 0.800783 & 0.599609 \tabularnewline
53 & 0.399835 & 0.79967 & 0.600165 \tabularnewline
54 & 0.358053 & 0.716107 & 0.641947 \tabularnewline
55 & 0.346046 & 0.692091 & 0.653954 \tabularnewline
56 & 0.3422 & 0.6844 & 0.6578 \tabularnewline
57 & 0.303282 & 0.606564 & 0.696718 \tabularnewline
58 & 0.284621 & 0.569242 & 0.715379 \tabularnewline
59 & 0.254808 & 0.509616 & 0.745192 \tabularnewline
60 & 0.275558 & 0.551116 & 0.724442 \tabularnewline
61 & 0.252439 & 0.504877 & 0.747561 \tabularnewline
62 & 0.227781 & 0.455563 & 0.772219 \tabularnewline
63 & 0.1992 & 0.398401 & 0.8008 \tabularnewline
64 & 0.171579 & 0.343159 & 0.828421 \tabularnewline
65 & 0.151394 & 0.302789 & 0.848606 \tabularnewline
66 & 0.142678 & 0.285357 & 0.857322 \tabularnewline
67 & 0.13876 & 0.27752 & 0.86124 \tabularnewline
68 & 0.268654 & 0.537307 & 0.731346 \tabularnewline
69 & 0.363589 & 0.727178 & 0.636411 \tabularnewline
70 & 0.333227 & 0.666453 & 0.666773 \tabularnewline
71 & 0.441815 & 0.88363 & 0.558185 \tabularnewline
72 & 0.407176 & 0.814353 & 0.592824 \tabularnewline
73 & 0.407857 & 0.815714 & 0.592143 \tabularnewline
74 & 0.396011 & 0.792022 & 0.603989 \tabularnewline
75 & 0.358949 & 0.717898 & 0.641051 \tabularnewline
76 & 0.42533 & 0.85066 & 0.57467 \tabularnewline
77 & 0.387575 & 0.775149 & 0.612425 \tabularnewline
78 & 0.361694 & 0.723388 & 0.638306 \tabularnewline
79 & 0.37636 & 0.752719 & 0.62364 \tabularnewline
80 & 0.342732 & 0.685464 & 0.657268 \tabularnewline
81 & 0.314141 & 0.628282 & 0.685859 \tabularnewline
82 & 0.280482 & 0.560964 & 0.719518 \tabularnewline
83 & 0.252903 & 0.505807 & 0.747097 \tabularnewline
84 & 0.22307 & 0.44614 & 0.77693 \tabularnewline
85 & 0.21698 & 0.433959 & 0.78302 \tabularnewline
86 & 0.189538 & 0.379075 & 0.810462 \tabularnewline
87 & 0.167223 & 0.334446 & 0.832777 \tabularnewline
88 & 0.154893 & 0.309786 & 0.845107 \tabularnewline
89 & 0.133422 & 0.266844 & 0.866578 \tabularnewline
90 & 0.13203 & 0.26406 & 0.86797 \tabularnewline
91 & 0.112939 & 0.225879 & 0.887061 \tabularnewline
92 & 0.0986998 & 0.1974 & 0.9013 \tabularnewline
93 & 0.08393 & 0.16786 & 0.91607 \tabularnewline
94 & 0.0874092 & 0.174818 & 0.912591 \tabularnewline
95 & 0.0790824 & 0.158165 & 0.920918 \tabularnewline
96 & 0.0661805 & 0.132361 & 0.93382 \tabularnewline
97 & 0.0709204 & 0.141841 & 0.92908 \tabularnewline
98 & 0.058911 & 0.117822 & 0.941089 \tabularnewline
99 & 0.0488813 & 0.0977625 & 0.951119 \tabularnewline
100 & 0.0429486 & 0.0858971 & 0.957051 \tabularnewline
101 & 0.037598 & 0.0751959 & 0.962402 \tabularnewline
102 & 0.0434894 & 0.0869789 & 0.956511 \tabularnewline
103 & 0.0366559 & 0.0733118 & 0.963344 \tabularnewline
104 & 0.0328648 & 0.0657297 & 0.967135 \tabularnewline
105 & 0.03917 & 0.0783399 & 0.96083 \tabularnewline
106 & 0.0340807 & 0.0681613 & 0.965919 \tabularnewline
107 & 0.0276763 & 0.0553525 & 0.972324 \tabularnewline
108 & 0.0268068 & 0.0536136 & 0.973193 \tabularnewline
109 & 0.0217801 & 0.0435602 & 0.97822 \tabularnewline
110 & 0.0177482 & 0.0354964 & 0.982252 \tabularnewline
111 & 0.014072 & 0.028144 & 0.985928 \tabularnewline
112 & 0.0142201 & 0.0284402 & 0.98578 \tabularnewline
113 & 0.0129109 & 0.0258218 & 0.987089 \tabularnewline
114 & 0.0188868 & 0.0377736 & 0.981113 \tabularnewline
115 & 0.0177567 & 0.0355133 & 0.982243 \tabularnewline
116 & 0.0172604 & 0.0345207 & 0.98274 \tabularnewline
117 & 0.0141866 & 0.0283733 & 0.985813 \tabularnewline
118 & 0.0142697 & 0.0285395 & 0.98573 \tabularnewline
119 & 0.0115023 & 0.0230045 & 0.988498 \tabularnewline
120 & 0.0102971 & 0.0205943 & 0.989703 \tabularnewline
121 & 0.0082719 & 0.0165438 & 0.991728 \tabularnewline
122 & 0.0125288 & 0.0250575 & 0.987471 \tabularnewline
123 & 0.0104544 & 0.0209088 & 0.989546 \tabularnewline
124 & 0.00897938 & 0.0179588 & 0.991021 \tabularnewline
125 & 0.0072995 & 0.014599 & 0.9927 \tabularnewline
126 & 0.00577692 & 0.0115538 & 0.994223 \tabularnewline
127 & 0.00526178 & 0.0105236 & 0.994738 \tabularnewline
128 & 0.00425352 & 0.00850705 & 0.995746 \tabularnewline
129 & 0.00601038 & 0.0120208 & 0.99399 \tabularnewline
130 & 0.0066099 & 0.0132198 & 0.99339 \tabularnewline
131 & 0.0137519 & 0.0275038 & 0.986248 \tabularnewline
132 & 0.0164411 & 0.0328821 & 0.983559 \tabularnewline
133 & 0.017624 & 0.035248 & 0.982376 \tabularnewline
134 & 0.0167154 & 0.0334308 & 0.983285 \tabularnewline
135 & 0.0133609 & 0.0267217 & 0.986639 \tabularnewline
136 & 0.011236 & 0.022472 & 0.988764 \tabularnewline
137 & 0.00892771 & 0.0178554 & 0.991072 \tabularnewline
138 & 0.0111628 & 0.0223256 & 0.988837 \tabularnewline
139 & 0.00956673 & 0.0191335 & 0.990433 \tabularnewline
140 & 0.0113209 & 0.0226418 & 0.988679 \tabularnewline
141 & 0.0179788 & 0.0359576 & 0.982021 \tabularnewline
142 & 0.0165691 & 0.0331383 & 0.983431 \tabularnewline
143 & 0.0133227 & 0.0266455 & 0.986677 \tabularnewline
144 & 0.0137174 & 0.0274348 & 0.986283 \tabularnewline
145 & 0.0245989 & 0.0491977 & 0.975401 \tabularnewline
146 & 0.0298582 & 0.0597165 & 0.970142 \tabularnewline
147 & 0.0313396 & 0.0626793 & 0.96866 \tabularnewline
148 & 0.0277338 & 0.0554675 & 0.972266 \tabularnewline
149 & 0.0225709 & 0.0451417 & 0.977429 \tabularnewline
150 & 0.031514 & 0.0630279 & 0.968486 \tabularnewline
151 & 0.0266163 & 0.0532325 & 0.973384 \tabularnewline
152 & 0.0289698 & 0.0579395 & 0.97103 \tabularnewline
153 & 0.0586087 & 0.117217 & 0.941391 \tabularnewline
154 & 0.0564749 & 0.11295 & 0.943525 \tabularnewline
155 & 0.0646812 & 0.129362 & 0.935319 \tabularnewline
156 & 0.0549975 & 0.109995 & 0.945003 \tabularnewline
157 & 0.04908 & 0.0981599 & 0.95092 \tabularnewline
158 & 0.0427452 & 0.0854904 & 0.957255 \tabularnewline
159 & 0.041388 & 0.0827761 & 0.958612 \tabularnewline
160 & 0.0355179 & 0.0710358 & 0.964482 \tabularnewline
161 & 0.0289996 & 0.0579992 & 0.971 \tabularnewline
162 & 0.0236715 & 0.047343 & 0.976328 \tabularnewline
163 & 0.0193382 & 0.0386763 & 0.980662 \tabularnewline
164 & 0.0163516 & 0.0327032 & 0.983648 \tabularnewline
165 & 0.0144703 & 0.0289406 & 0.98553 \tabularnewline
166 & 0.0149697 & 0.0299394 & 0.98503 \tabularnewline
167 & 0.0119012 & 0.0238025 & 0.988099 \tabularnewline
168 & 0.0175334 & 0.0350668 & 0.982467 \tabularnewline
169 & 0.0176534 & 0.0353068 & 0.982347 \tabularnewline
170 & 0.0167544 & 0.0335088 & 0.983246 \tabularnewline
171 & 0.0154745 & 0.030949 & 0.984525 \tabularnewline
172 & 0.012487 & 0.024974 & 0.987513 \tabularnewline
173 & 0.0121001 & 0.0242003 & 0.9879 \tabularnewline
174 & 0.013787 & 0.0275739 & 0.986213 \tabularnewline
175 & 0.0179495 & 0.0358989 & 0.982051 \tabularnewline
176 & 0.0143922 & 0.0287844 & 0.985608 \tabularnewline
177 & 0.0113635 & 0.0227271 & 0.988636 \tabularnewline
178 & 0.00955512 & 0.0191102 & 0.990445 \tabularnewline
179 & 0.00739749 & 0.014795 & 0.992603 \tabularnewline
180 & 0.00651563 & 0.0130313 & 0.993484 \tabularnewline
181 & 0.00531579 & 0.0106316 & 0.994684 \tabularnewline
182 & 0.00409051 & 0.00818101 & 0.995909 \tabularnewline
183 & 0.00442826 & 0.00885653 & 0.995572 \tabularnewline
184 & 0.00335479 & 0.00670957 & 0.996645 \tabularnewline
185 & 0.0916554 & 0.183311 & 0.908345 \tabularnewline
186 & 0.0819469 & 0.163894 & 0.918053 \tabularnewline
187 & 0.0904394 & 0.180879 & 0.909561 \tabularnewline
188 & 0.075916 & 0.151832 & 0.924084 \tabularnewline
189 & 0.0677612 & 0.135522 & 0.932239 \tabularnewline
190 & 0.0566024 & 0.113205 & 0.943398 \tabularnewline
191 & 0.0523769 & 0.104754 & 0.947623 \tabularnewline
192 & 0.0432674 & 0.0865348 & 0.956733 \tabularnewline
193 & 0.0443889 & 0.0887777 & 0.955611 \tabularnewline
194 & 0.0448713 & 0.0897425 & 0.955129 \tabularnewline
195 & 0.0388021 & 0.0776041 & 0.961198 \tabularnewline
196 & 0.0312233 & 0.0624465 & 0.968777 \tabularnewline
197 & 0.0394245 & 0.0788489 & 0.960576 \tabularnewline
198 & 0.0321915 & 0.064383 & 0.967809 \tabularnewline
199 & 0.0289714 & 0.0579428 & 0.971029 \tabularnewline
200 & 0.0248638 & 0.0497276 & 0.975136 \tabularnewline
201 & 0.0232526 & 0.0465051 & 0.976747 \tabularnewline
202 & 0.019656 & 0.0393119 & 0.980344 \tabularnewline
203 & 0.0258128 & 0.0516256 & 0.974187 \tabularnewline
204 & 0.0300646 & 0.0601293 & 0.969935 \tabularnewline
205 & 0.0314876 & 0.0629753 & 0.968512 \tabularnewline
206 & 0.0246818 & 0.0493635 & 0.975318 \tabularnewline
207 & 0.0236277 & 0.0472554 & 0.976372 \tabularnewline
208 & 0.0193157 & 0.0386313 & 0.980684 \tabularnewline
209 & 0.0215382 & 0.0430764 & 0.978462 \tabularnewline
210 & 0.0171654 & 0.0343309 & 0.982835 \tabularnewline
211 & 0.0197265 & 0.0394531 & 0.980273 \tabularnewline
212 & 0.0319964 & 0.0639928 & 0.968004 \tabularnewline
213 & 0.0249092 & 0.0498184 & 0.975091 \tabularnewline
214 & 0.0322126 & 0.0644252 & 0.967787 \tabularnewline
215 & 0.0273337 & 0.0546674 & 0.972666 \tabularnewline
216 & 0.0211461 & 0.0422922 & 0.978854 \tabularnewline
217 & 0.0232298 & 0.0464595 & 0.97677 \tabularnewline
218 & 0.0195876 & 0.0391752 & 0.980412 \tabularnewline
219 & 0.0181984 & 0.0363969 & 0.981802 \tabularnewline
220 & 0.0139161 & 0.0278322 & 0.986084 \tabularnewline
221 & 0.011589 & 0.0231781 & 0.988411 \tabularnewline
222 & 0.00832192 & 0.0166438 & 0.991678 \tabularnewline
223 & 0.00638275 & 0.0127655 & 0.993617 \tabularnewline
224 & 0.00481084 & 0.00962168 & 0.995189 \tabularnewline
225 & 0.00409518 & 0.00819035 & 0.995905 \tabularnewline
226 & 0.00946877 & 0.0189375 & 0.990531 \tabularnewline
227 & 0.0074195 & 0.014839 & 0.992581 \tabularnewline
228 & 0.00549025 & 0.0109805 & 0.99451 \tabularnewline
229 & 0.00392699 & 0.00785397 & 0.996073 \tabularnewline
230 & 0.00289124 & 0.00578247 & 0.997109 \tabularnewline
231 & 0.00260696 & 0.00521392 & 0.997393 \tabularnewline
232 & 0.00613884 & 0.0122777 & 0.993861 \tabularnewline
233 & 0.0247719 & 0.0495439 & 0.975228 \tabularnewline
234 & 0.0377556 & 0.0755112 & 0.962244 \tabularnewline
235 & 0.0272368 & 0.0544736 & 0.972763 \tabularnewline
236 & 0.02283 & 0.0456601 & 0.97717 \tabularnewline
237 & 0.19739 & 0.39478 & 0.80261 \tabularnewline
238 & 0.155685 & 0.311369 & 0.844315 \tabularnewline
239 & 0.129624 & 0.259248 & 0.870376 \tabularnewline
240 & 0.100556 & 0.201113 & 0.899444 \tabularnewline
241 & 0.088419 & 0.176838 & 0.911581 \tabularnewline
242 & 0.137954 & 0.275907 & 0.862046 \tabularnewline
243 & 0.112973 & 0.225947 & 0.887027 \tabularnewline
244 & 0.118307 & 0.236615 & 0.881693 \tabularnewline
245 & 0.0968309 & 0.193662 & 0.903169 \tabularnewline
246 & 0.0821834 & 0.164367 & 0.917817 \tabularnewline
247 & 0.0530626 & 0.106125 & 0.946937 \tabularnewline
248 & 0.0452103 & 0.0904207 & 0.95479 \tabularnewline
249 & 0.0404583 & 0.0809167 & 0.959542 \tabularnewline
250 & 0.115509 & 0.231018 & 0.884491 \tabularnewline
251 & 0.0947137 & 0.189427 & 0.905286 \tabularnewline
252 & 0.431454 & 0.862909 & 0.568546 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221806&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]12[/C][C]0.0949048[/C][C]0.18981[/C][C]0.905095[/C][/ROW]
[ROW][C]13[/C][C]0.168817[/C][C]0.337633[/C][C]0.831183[/C][/ROW]
[ROW][C]14[/C][C]0.178859[/C][C]0.357717[/C][C]0.821141[/C][/ROW]
[ROW][C]15[/C][C]0.102104[/C][C]0.204209[/C][C]0.897896[/C][/ROW]
[ROW][C]16[/C][C]0.0784248[/C][C]0.15685[/C][C]0.921575[/C][/ROW]
[ROW][C]17[/C][C]0.0870197[/C][C]0.174039[/C][C]0.91298[/C][/ROW]
[ROW][C]18[/C][C]0.213216[/C][C]0.426431[/C][C]0.786784[/C][/ROW]
[ROW][C]19[/C][C]0.175805[/C][C]0.351609[/C][C]0.824195[/C][/ROW]
[ROW][C]20[/C][C]0.139401[/C][C]0.278802[/C][C]0.860599[/C][/ROW]
[ROW][C]21[/C][C]0.107613[/C][C]0.215225[/C][C]0.892387[/C][/ROW]
[ROW][C]22[/C][C]0.131396[/C][C]0.262791[/C][C]0.868604[/C][/ROW]
[ROW][C]23[/C][C]0.229842[/C][C]0.459684[/C][C]0.770158[/C][/ROW]
[ROW][C]24[/C][C]0.345392[/C][C]0.690785[/C][C]0.654608[/C][/ROW]
[ROW][C]25[/C][C]0.282152[/C][C]0.564303[/C][C]0.717848[/C][/ROW]
[ROW][C]26[/C][C]0.237318[/C][C]0.474636[/C][C]0.762682[/C][/ROW]
[ROW][C]27[/C][C]0.227892[/C][C]0.455783[/C][C]0.772108[/C][/ROW]
[ROW][C]28[/C][C]0.338479[/C][C]0.676958[/C][C]0.661521[/C][/ROW]
[ROW][C]29[/C][C]0.28932[/C][C]0.57864[/C][C]0.71068[/C][/ROW]
[ROW][C]30[/C][C]0.397877[/C][C]0.795753[/C][C]0.602123[/C][/ROW]
[ROW][C]31[/C][C]0.356883[/C][C]0.713767[/C][C]0.643117[/C][/ROW]
[ROW][C]32[/C][C]0.329409[/C][C]0.658819[/C][C]0.670591[/C][/ROW]
[ROW][C]33[/C][C]0.314114[/C][C]0.628227[/C][C]0.685886[/C][/ROW]
[ROW][C]34[/C][C]0.278256[/C][C]0.556511[/C][C]0.721744[/C][/ROW]
[ROW][C]35[/C][C]0.236813[/C][C]0.473626[/C][C]0.763187[/C][/ROW]
[ROW][C]36[/C][C]0.366886[/C][C]0.733772[/C][C]0.633114[/C][/ROW]
[ROW][C]37[/C][C]0.395601[/C][C]0.791202[/C][C]0.604399[/C][/ROW]
[ROW][C]38[/C][C]0.371554[/C][C]0.743109[/C][C]0.628446[/C][/ROW]
[ROW][C]39[/C][C]0.416187[/C][C]0.832373[/C][C]0.583813[/C][/ROW]
[ROW][C]40[/C][C]0.396531[/C][C]0.793062[/C][C]0.603469[/C][/ROW]
[ROW][C]41[/C][C]0.357788[/C][C]0.715576[/C][C]0.642212[/C][/ROW]
[ROW][C]42[/C][C]0.319477[/C][C]0.638954[/C][C]0.680523[/C][/ROW]
[ROW][C]43[/C][C]0.338406[/C][C]0.676812[/C][C]0.661594[/C][/ROW]
[ROW][C]44[/C][C]0.2914[/C][C]0.5828[/C][C]0.7086[/C][/ROW]
[ROW][C]45[/C][C]0.26449[/C][C]0.528981[/C][C]0.73551[/C][/ROW]
[ROW][C]46[/C][C]0.4416[/C][C]0.883199[/C][C]0.5584[/C][/ROW]
[ROW][C]47[/C][C]0.532244[/C][C]0.935511[/C][C]0.467756[/C][/ROW]
[ROW][C]48[/C][C]0.489178[/C][C]0.978357[/C][C]0.510822[/C][/ROW]
[ROW][C]49[/C][C]0.513618[/C][C]0.972764[/C][C]0.486382[/C][/ROW]
[ROW][C]50[/C][C]0.486591[/C][C]0.973181[/C][C]0.513409[/C][/ROW]
[ROW][C]51[/C][C]0.441523[/C][C]0.883047[/C][C]0.558477[/C][/ROW]
[ROW][C]52[/C][C]0.400391[/C][C]0.800783[/C][C]0.599609[/C][/ROW]
[ROW][C]53[/C][C]0.399835[/C][C]0.79967[/C][C]0.600165[/C][/ROW]
[ROW][C]54[/C][C]0.358053[/C][C]0.716107[/C][C]0.641947[/C][/ROW]
[ROW][C]55[/C][C]0.346046[/C][C]0.692091[/C][C]0.653954[/C][/ROW]
[ROW][C]56[/C][C]0.3422[/C][C]0.6844[/C][C]0.6578[/C][/ROW]
[ROW][C]57[/C][C]0.303282[/C][C]0.606564[/C][C]0.696718[/C][/ROW]
[ROW][C]58[/C][C]0.284621[/C][C]0.569242[/C][C]0.715379[/C][/ROW]
[ROW][C]59[/C][C]0.254808[/C][C]0.509616[/C][C]0.745192[/C][/ROW]
[ROW][C]60[/C][C]0.275558[/C][C]0.551116[/C][C]0.724442[/C][/ROW]
[ROW][C]61[/C][C]0.252439[/C][C]0.504877[/C][C]0.747561[/C][/ROW]
[ROW][C]62[/C][C]0.227781[/C][C]0.455563[/C][C]0.772219[/C][/ROW]
[ROW][C]63[/C][C]0.1992[/C][C]0.398401[/C][C]0.8008[/C][/ROW]
[ROW][C]64[/C][C]0.171579[/C][C]0.343159[/C][C]0.828421[/C][/ROW]
[ROW][C]65[/C][C]0.151394[/C][C]0.302789[/C][C]0.848606[/C][/ROW]
[ROW][C]66[/C][C]0.142678[/C][C]0.285357[/C][C]0.857322[/C][/ROW]
[ROW][C]67[/C][C]0.13876[/C][C]0.27752[/C][C]0.86124[/C][/ROW]
[ROW][C]68[/C][C]0.268654[/C][C]0.537307[/C][C]0.731346[/C][/ROW]
[ROW][C]69[/C][C]0.363589[/C][C]0.727178[/C][C]0.636411[/C][/ROW]
[ROW][C]70[/C][C]0.333227[/C][C]0.666453[/C][C]0.666773[/C][/ROW]
[ROW][C]71[/C][C]0.441815[/C][C]0.88363[/C][C]0.558185[/C][/ROW]
[ROW][C]72[/C][C]0.407176[/C][C]0.814353[/C][C]0.592824[/C][/ROW]
[ROW][C]73[/C][C]0.407857[/C][C]0.815714[/C][C]0.592143[/C][/ROW]
[ROW][C]74[/C][C]0.396011[/C][C]0.792022[/C][C]0.603989[/C][/ROW]
[ROW][C]75[/C][C]0.358949[/C][C]0.717898[/C][C]0.641051[/C][/ROW]
[ROW][C]76[/C][C]0.42533[/C][C]0.85066[/C][C]0.57467[/C][/ROW]
[ROW][C]77[/C][C]0.387575[/C][C]0.775149[/C][C]0.612425[/C][/ROW]
[ROW][C]78[/C][C]0.361694[/C][C]0.723388[/C][C]0.638306[/C][/ROW]
[ROW][C]79[/C][C]0.37636[/C][C]0.752719[/C][C]0.62364[/C][/ROW]
[ROW][C]80[/C][C]0.342732[/C][C]0.685464[/C][C]0.657268[/C][/ROW]
[ROW][C]81[/C][C]0.314141[/C][C]0.628282[/C][C]0.685859[/C][/ROW]
[ROW][C]82[/C][C]0.280482[/C][C]0.560964[/C][C]0.719518[/C][/ROW]
[ROW][C]83[/C][C]0.252903[/C][C]0.505807[/C][C]0.747097[/C][/ROW]
[ROW][C]84[/C][C]0.22307[/C][C]0.44614[/C][C]0.77693[/C][/ROW]
[ROW][C]85[/C][C]0.21698[/C][C]0.433959[/C][C]0.78302[/C][/ROW]
[ROW][C]86[/C][C]0.189538[/C][C]0.379075[/C][C]0.810462[/C][/ROW]
[ROW][C]87[/C][C]0.167223[/C][C]0.334446[/C][C]0.832777[/C][/ROW]
[ROW][C]88[/C][C]0.154893[/C][C]0.309786[/C][C]0.845107[/C][/ROW]
[ROW][C]89[/C][C]0.133422[/C][C]0.266844[/C][C]0.866578[/C][/ROW]
[ROW][C]90[/C][C]0.13203[/C][C]0.26406[/C][C]0.86797[/C][/ROW]
[ROW][C]91[/C][C]0.112939[/C][C]0.225879[/C][C]0.887061[/C][/ROW]
[ROW][C]92[/C][C]0.0986998[/C][C]0.1974[/C][C]0.9013[/C][/ROW]
[ROW][C]93[/C][C]0.08393[/C][C]0.16786[/C][C]0.91607[/C][/ROW]
[ROW][C]94[/C][C]0.0874092[/C][C]0.174818[/C][C]0.912591[/C][/ROW]
[ROW][C]95[/C][C]0.0790824[/C][C]0.158165[/C][C]0.920918[/C][/ROW]
[ROW][C]96[/C][C]0.0661805[/C][C]0.132361[/C][C]0.93382[/C][/ROW]
[ROW][C]97[/C][C]0.0709204[/C][C]0.141841[/C][C]0.92908[/C][/ROW]
[ROW][C]98[/C][C]0.058911[/C][C]0.117822[/C][C]0.941089[/C][/ROW]
[ROW][C]99[/C][C]0.0488813[/C][C]0.0977625[/C][C]0.951119[/C][/ROW]
[ROW][C]100[/C][C]0.0429486[/C][C]0.0858971[/C][C]0.957051[/C][/ROW]
[ROW][C]101[/C][C]0.037598[/C][C]0.0751959[/C][C]0.962402[/C][/ROW]
[ROW][C]102[/C][C]0.0434894[/C][C]0.0869789[/C][C]0.956511[/C][/ROW]
[ROW][C]103[/C][C]0.0366559[/C][C]0.0733118[/C][C]0.963344[/C][/ROW]
[ROW][C]104[/C][C]0.0328648[/C][C]0.0657297[/C][C]0.967135[/C][/ROW]
[ROW][C]105[/C][C]0.03917[/C][C]0.0783399[/C][C]0.96083[/C][/ROW]
[ROW][C]106[/C][C]0.0340807[/C][C]0.0681613[/C][C]0.965919[/C][/ROW]
[ROW][C]107[/C][C]0.0276763[/C][C]0.0553525[/C][C]0.972324[/C][/ROW]
[ROW][C]108[/C][C]0.0268068[/C][C]0.0536136[/C][C]0.973193[/C][/ROW]
[ROW][C]109[/C][C]0.0217801[/C][C]0.0435602[/C][C]0.97822[/C][/ROW]
[ROW][C]110[/C][C]0.0177482[/C][C]0.0354964[/C][C]0.982252[/C][/ROW]
[ROW][C]111[/C][C]0.014072[/C][C]0.028144[/C][C]0.985928[/C][/ROW]
[ROW][C]112[/C][C]0.0142201[/C][C]0.0284402[/C][C]0.98578[/C][/ROW]
[ROW][C]113[/C][C]0.0129109[/C][C]0.0258218[/C][C]0.987089[/C][/ROW]
[ROW][C]114[/C][C]0.0188868[/C][C]0.0377736[/C][C]0.981113[/C][/ROW]
[ROW][C]115[/C][C]0.0177567[/C][C]0.0355133[/C][C]0.982243[/C][/ROW]
[ROW][C]116[/C][C]0.0172604[/C][C]0.0345207[/C][C]0.98274[/C][/ROW]
[ROW][C]117[/C][C]0.0141866[/C][C]0.0283733[/C][C]0.985813[/C][/ROW]
[ROW][C]118[/C][C]0.0142697[/C][C]0.0285395[/C][C]0.98573[/C][/ROW]
[ROW][C]119[/C][C]0.0115023[/C][C]0.0230045[/C][C]0.988498[/C][/ROW]
[ROW][C]120[/C][C]0.0102971[/C][C]0.0205943[/C][C]0.989703[/C][/ROW]
[ROW][C]121[/C][C]0.0082719[/C][C]0.0165438[/C][C]0.991728[/C][/ROW]
[ROW][C]122[/C][C]0.0125288[/C][C]0.0250575[/C][C]0.987471[/C][/ROW]
[ROW][C]123[/C][C]0.0104544[/C][C]0.0209088[/C][C]0.989546[/C][/ROW]
[ROW][C]124[/C][C]0.00897938[/C][C]0.0179588[/C][C]0.991021[/C][/ROW]
[ROW][C]125[/C][C]0.0072995[/C][C]0.014599[/C][C]0.9927[/C][/ROW]
[ROW][C]126[/C][C]0.00577692[/C][C]0.0115538[/C][C]0.994223[/C][/ROW]
[ROW][C]127[/C][C]0.00526178[/C][C]0.0105236[/C][C]0.994738[/C][/ROW]
[ROW][C]128[/C][C]0.00425352[/C][C]0.00850705[/C][C]0.995746[/C][/ROW]
[ROW][C]129[/C][C]0.00601038[/C][C]0.0120208[/C][C]0.99399[/C][/ROW]
[ROW][C]130[/C][C]0.0066099[/C][C]0.0132198[/C][C]0.99339[/C][/ROW]
[ROW][C]131[/C][C]0.0137519[/C][C]0.0275038[/C][C]0.986248[/C][/ROW]
[ROW][C]132[/C][C]0.0164411[/C][C]0.0328821[/C][C]0.983559[/C][/ROW]
[ROW][C]133[/C][C]0.017624[/C][C]0.035248[/C][C]0.982376[/C][/ROW]
[ROW][C]134[/C][C]0.0167154[/C][C]0.0334308[/C][C]0.983285[/C][/ROW]
[ROW][C]135[/C][C]0.0133609[/C][C]0.0267217[/C][C]0.986639[/C][/ROW]
[ROW][C]136[/C][C]0.011236[/C][C]0.022472[/C][C]0.988764[/C][/ROW]
[ROW][C]137[/C][C]0.00892771[/C][C]0.0178554[/C][C]0.991072[/C][/ROW]
[ROW][C]138[/C][C]0.0111628[/C][C]0.0223256[/C][C]0.988837[/C][/ROW]
[ROW][C]139[/C][C]0.00956673[/C][C]0.0191335[/C][C]0.990433[/C][/ROW]
[ROW][C]140[/C][C]0.0113209[/C][C]0.0226418[/C][C]0.988679[/C][/ROW]
[ROW][C]141[/C][C]0.0179788[/C][C]0.0359576[/C][C]0.982021[/C][/ROW]
[ROW][C]142[/C][C]0.0165691[/C][C]0.0331383[/C][C]0.983431[/C][/ROW]
[ROW][C]143[/C][C]0.0133227[/C][C]0.0266455[/C][C]0.986677[/C][/ROW]
[ROW][C]144[/C][C]0.0137174[/C][C]0.0274348[/C][C]0.986283[/C][/ROW]
[ROW][C]145[/C][C]0.0245989[/C][C]0.0491977[/C][C]0.975401[/C][/ROW]
[ROW][C]146[/C][C]0.0298582[/C][C]0.0597165[/C][C]0.970142[/C][/ROW]
[ROW][C]147[/C][C]0.0313396[/C][C]0.0626793[/C][C]0.96866[/C][/ROW]
[ROW][C]148[/C][C]0.0277338[/C][C]0.0554675[/C][C]0.972266[/C][/ROW]
[ROW][C]149[/C][C]0.0225709[/C][C]0.0451417[/C][C]0.977429[/C][/ROW]
[ROW][C]150[/C][C]0.031514[/C][C]0.0630279[/C][C]0.968486[/C][/ROW]
[ROW][C]151[/C][C]0.0266163[/C][C]0.0532325[/C][C]0.973384[/C][/ROW]
[ROW][C]152[/C][C]0.0289698[/C][C]0.0579395[/C][C]0.97103[/C][/ROW]
[ROW][C]153[/C][C]0.0586087[/C][C]0.117217[/C][C]0.941391[/C][/ROW]
[ROW][C]154[/C][C]0.0564749[/C][C]0.11295[/C][C]0.943525[/C][/ROW]
[ROW][C]155[/C][C]0.0646812[/C][C]0.129362[/C][C]0.935319[/C][/ROW]
[ROW][C]156[/C][C]0.0549975[/C][C]0.109995[/C][C]0.945003[/C][/ROW]
[ROW][C]157[/C][C]0.04908[/C][C]0.0981599[/C][C]0.95092[/C][/ROW]
[ROW][C]158[/C][C]0.0427452[/C][C]0.0854904[/C][C]0.957255[/C][/ROW]
[ROW][C]159[/C][C]0.041388[/C][C]0.0827761[/C][C]0.958612[/C][/ROW]
[ROW][C]160[/C][C]0.0355179[/C][C]0.0710358[/C][C]0.964482[/C][/ROW]
[ROW][C]161[/C][C]0.0289996[/C][C]0.0579992[/C][C]0.971[/C][/ROW]
[ROW][C]162[/C][C]0.0236715[/C][C]0.047343[/C][C]0.976328[/C][/ROW]
[ROW][C]163[/C][C]0.0193382[/C][C]0.0386763[/C][C]0.980662[/C][/ROW]
[ROW][C]164[/C][C]0.0163516[/C][C]0.0327032[/C][C]0.983648[/C][/ROW]
[ROW][C]165[/C][C]0.0144703[/C][C]0.0289406[/C][C]0.98553[/C][/ROW]
[ROW][C]166[/C][C]0.0149697[/C][C]0.0299394[/C][C]0.98503[/C][/ROW]
[ROW][C]167[/C][C]0.0119012[/C][C]0.0238025[/C][C]0.988099[/C][/ROW]
[ROW][C]168[/C][C]0.0175334[/C][C]0.0350668[/C][C]0.982467[/C][/ROW]
[ROW][C]169[/C][C]0.0176534[/C][C]0.0353068[/C][C]0.982347[/C][/ROW]
[ROW][C]170[/C][C]0.0167544[/C][C]0.0335088[/C][C]0.983246[/C][/ROW]
[ROW][C]171[/C][C]0.0154745[/C][C]0.030949[/C][C]0.984525[/C][/ROW]
[ROW][C]172[/C][C]0.012487[/C][C]0.024974[/C][C]0.987513[/C][/ROW]
[ROW][C]173[/C][C]0.0121001[/C][C]0.0242003[/C][C]0.9879[/C][/ROW]
[ROW][C]174[/C][C]0.013787[/C][C]0.0275739[/C][C]0.986213[/C][/ROW]
[ROW][C]175[/C][C]0.0179495[/C][C]0.0358989[/C][C]0.982051[/C][/ROW]
[ROW][C]176[/C][C]0.0143922[/C][C]0.0287844[/C][C]0.985608[/C][/ROW]
[ROW][C]177[/C][C]0.0113635[/C][C]0.0227271[/C][C]0.988636[/C][/ROW]
[ROW][C]178[/C][C]0.00955512[/C][C]0.0191102[/C][C]0.990445[/C][/ROW]
[ROW][C]179[/C][C]0.00739749[/C][C]0.014795[/C][C]0.992603[/C][/ROW]
[ROW][C]180[/C][C]0.00651563[/C][C]0.0130313[/C][C]0.993484[/C][/ROW]
[ROW][C]181[/C][C]0.00531579[/C][C]0.0106316[/C][C]0.994684[/C][/ROW]
[ROW][C]182[/C][C]0.00409051[/C][C]0.00818101[/C][C]0.995909[/C][/ROW]
[ROW][C]183[/C][C]0.00442826[/C][C]0.00885653[/C][C]0.995572[/C][/ROW]
[ROW][C]184[/C][C]0.00335479[/C][C]0.00670957[/C][C]0.996645[/C][/ROW]
[ROW][C]185[/C][C]0.0916554[/C][C]0.183311[/C][C]0.908345[/C][/ROW]
[ROW][C]186[/C][C]0.0819469[/C][C]0.163894[/C][C]0.918053[/C][/ROW]
[ROW][C]187[/C][C]0.0904394[/C][C]0.180879[/C][C]0.909561[/C][/ROW]
[ROW][C]188[/C][C]0.075916[/C][C]0.151832[/C][C]0.924084[/C][/ROW]
[ROW][C]189[/C][C]0.0677612[/C][C]0.135522[/C][C]0.932239[/C][/ROW]
[ROW][C]190[/C][C]0.0566024[/C][C]0.113205[/C][C]0.943398[/C][/ROW]
[ROW][C]191[/C][C]0.0523769[/C][C]0.104754[/C][C]0.947623[/C][/ROW]
[ROW][C]192[/C][C]0.0432674[/C][C]0.0865348[/C][C]0.956733[/C][/ROW]
[ROW][C]193[/C][C]0.0443889[/C][C]0.0887777[/C][C]0.955611[/C][/ROW]
[ROW][C]194[/C][C]0.0448713[/C][C]0.0897425[/C][C]0.955129[/C][/ROW]
[ROW][C]195[/C][C]0.0388021[/C][C]0.0776041[/C][C]0.961198[/C][/ROW]
[ROW][C]196[/C][C]0.0312233[/C][C]0.0624465[/C][C]0.968777[/C][/ROW]
[ROW][C]197[/C][C]0.0394245[/C][C]0.0788489[/C][C]0.960576[/C][/ROW]
[ROW][C]198[/C][C]0.0321915[/C][C]0.064383[/C][C]0.967809[/C][/ROW]
[ROW][C]199[/C][C]0.0289714[/C][C]0.0579428[/C][C]0.971029[/C][/ROW]
[ROW][C]200[/C][C]0.0248638[/C][C]0.0497276[/C][C]0.975136[/C][/ROW]
[ROW][C]201[/C][C]0.0232526[/C][C]0.0465051[/C][C]0.976747[/C][/ROW]
[ROW][C]202[/C][C]0.019656[/C][C]0.0393119[/C][C]0.980344[/C][/ROW]
[ROW][C]203[/C][C]0.0258128[/C][C]0.0516256[/C][C]0.974187[/C][/ROW]
[ROW][C]204[/C][C]0.0300646[/C][C]0.0601293[/C][C]0.969935[/C][/ROW]
[ROW][C]205[/C][C]0.0314876[/C][C]0.0629753[/C][C]0.968512[/C][/ROW]
[ROW][C]206[/C][C]0.0246818[/C][C]0.0493635[/C][C]0.975318[/C][/ROW]
[ROW][C]207[/C][C]0.0236277[/C][C]0.0472554[/C][C]0.976372[/C][/ROW]
[ROW][C]208[/C][C]0.0193157[/C][C]0.0386313[/C][C]0.980684[/C][/ROW]
[ROW][C]209[/C][C]0.0215382[/C][C]0.0430764[/C][C]0.978462[/C][/ROW]
[ROW][C]210[/C][C]0.0171654[/C][C]0.0343309[/C][C]0.982835[/C][/ROW]
[ROW][C]211[/C][C]0.0197265[/C][C]0.0394531[/C][C]0.980273[/C][/ROW]
[ROW][C]212[/C][C]0.0319964[/C][C]0.0639928[/C][C]0.968004[/C][/ROW]
[ROW][C]213[/C][C]0.0249092[/C][C]0.0498184[/C][C]0.975091[/C][/ROW]
[ROW][C]214[/C][C]0.0322126[/C][C]0.0644252[/C][C]0.967787[/C][/ROW]
[ROW][C]215[/C][C]0.0273337[/C][C]0.0546674[/C][C]0.972666[/C][/ROW]
[ROW][C]216[/C][C]0.0211461[/C][C]0.0422922[/C][C]0.978854[/C][/ROW]
[ROW][C]217[/C][C]0.0232298[/C][C]0.0464595[/C][C]0.97677[/C][/ROW]
[ROW][C]218[/C][C]0.0195876[/C][C]0.0391752[/C][C]0.980412[/C][/ROW]
[ROW][C]219[/C][C]0.0181984[/C][C]0.0363969[/C][C]0.981802[/C][/ROW]
[ROW][C]220[/C][C]0.0139161[/C][C]0.0278322[/C][C]0.986084[/C][/ROW]
[ROW][C]221[/C][C]0.011589[/C][C]0.0231781[/C][C]0.988411[/C][/ROW]
[ROW][C]222[/C][C]0.00832192[/C][C]0.0166438[/C][C]0.991678[/C][/ROW]
[ROW][C]223[/C][C]0.00638275[/C][C]0.0127655[/C][C]0.993617[/C][/ROW]
[ROW][C]224[/C][C]0.00481084[/C][C]0.00962168[/C][C]0.995189[/C][/ROW]
[ROW][C]225[/C][C]0.00409518[/C][C]0.00819035[/C][C]0.995905[/C][/ROW]
[ROW][C]226[/C][C]0.00946877[/C][C]0.0189375[/C][C]0.990531[/C][/ROW]
[ROW][C]227[/C][C]0.0074195[/C][C]0.014839[/C][C]0.992581[/C][/ROW]
[ROW][C]228[/C][C]0.00549025[/C][C]0.0109805[/C][C]0.99451[/C][/ROW]
[ROW][C]229[/C][C]0.00392699[/C][C]0.00785397[/C][C]0.996073[/C][/ROW]
[ROW][C]230[/C][C]0.00289124[/C][C]0.00578247[/C][C]0.997109[/C][/ROW]
[ROW][C]231[/C][C]0.00260696[/C][C]0.00521392[/C][C]0.997393[/C][/ROW]
[ROW][C]232[/C][C]0.00613884[/C][C]0.0122777[/C][C]0.993861[/C][/ROW]
[ROW][C]233[/C][C]0.0247719[/C][C]0.0495439[/C][C]0.975228[/C][/ROW]
[ROW][C]234[/C][C]0.0377556[/C][C]0.0755112[/C][C]0.962244[/C][/ROW]
[ROW][C]235[/C][C]0.0272368[/C][C]0.0544736[/C][C]0.972763[/C][/ROW]
[ROW][C]236[/C][C]0.02283[/C][C]0.0456601[/C][C]0.97717[/C][/ROW]
[ROW][C]237[/C][C]0.19739[/C][C]0.39478[/C][C]0.80261[/C][/ROW]
[ROW][C]238[/C][C]0.155685[/C][C]0.311369[/C][C]0.844315[/C][/ROW]
[ROW][C]239[/C][C]0.129624[/C][C]0.259248[/C][C]0.870376[/C][/ROW]
[ROW][C]240[/C][C]0.100556[/C][C]0.201113[/C][C]0.899444[/C][/ROW]
[ROW][C]241[/C][C]0.088419[/C][C]0.176838[/C][C]0.911581[/C][/ROW]
[ROW][C]242[/C][C]0.137954[/C][C]0.275907[/C][C]0.862046[/C][/ROW]
[ROW][C]243[/C][C]0.112973[/C][C]0.225947[/C][C]0.887027[/C][/ROW]
[ROW][C]244[/C][C]0.118307[/C][C]0.236615[/C][C]0.881693[/C][/ROW]
[ROW][C]245[/C][C]0.0968309[/C][C]0.193662[/C][C]0.903169[/C][/ROW]
[ROW][C]246[/C][C]0.0821834[/C][C]0.164367[/C][C]0.917817[/C][/ROW]
[ROW][C]247[/C][C]0.0530626[/C][C]0.106125[/C][C]0.946937[/C][/ROW]
[ROW][C]248[/C][C]0.0452103[/C][C]0.0904207[/C][C]0.95479[/C][/ROW]
[ROW][C]249[/C][C]0.0404583[/C][C]0.0809167[/C][C]0.959542[/C][/ROW]
[ROW][C]250[/C][C]0.115509[/C][C]0.231018[/C][C]0.884491[/C][/ROW]
[ROW][C]251[/C][C]0.0947137[/C][C]0.189427[/C][C]0.905286[/C][/ROW]
[ROW][C]252[/C][C]0.431454[/C][C]0.862909[/C][C]0.568546[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221806&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221806&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.09490480.189810.905095
130.1688170.3376330.831183
140.1788590.3577170.821141
150.1021040.2042090.897896
160.07842480.156850.921575
170.08701970.1740390.91298
180.2132160.4264310.786784
190.1758050.3516090.824195
200.1394010.2788020.860599
210.1076130.2152250.892387
220.1313960.2627910.868604
230.2298420.4596840.770158
240.3453920.6907850.654608
250.2821520.5643030.717848
260.2373180.4746360.762682
270.2278920.4557830.772108
280.3384790.6769580.661521
290.289320.578640.71068
300.3978770.7957530.602123
310.3568830.7137670.643117
320.3294090.6588190.670591
330.3141140.6282270.685886
340.2782560.5565110.721744
350.2368130.4736260.763187
360.3668860.7337720.633114
370.3956010.7912020.604399
380.3715540.7431090.628446
390.4161870.8323730.583813
400.3965310.7930620.603469
410.3577880.7155760.642212
420.3194770.6389540.680523
430.3384060.6768120.661594
440.29140.58280.7086
450.264490.5289810.73551
460.44160.8831990.5584
470.5322440.9355110.467756
480.4891780.9783570.510822
490.5136180.9727640.486382
500.4865910.9731810.513409
510.4415230.8830470.558477
520.4003910.8007830.599609
530.3998350.799670.600165
540.3580530.7161070.641947
550.3460460.6920910.653954
560.34220.68440.6578
570.3032820.6065640.696718
580.2846210.5692420.715379
590.2548080.5096160.745192
600.2755580.5511160.724442
610.2524390.5048770.747561
620.2277810.4555630.772219
630.19920.3984010.8008
640.1715790.3431590.828421
650.1513940.3027890.848606
660.1426780.2853570.857322
670.138760.277520.86124
680.2686540.5373070.731346
690.3635890.7271780.636411
700.3332270.6664530.666773
710.4418150.883630.558185
720.4071760.8143530.592824
730.4078570.8157140.592143
740.3960110.7920220.603989
750.3589490.7178980.641051
760.425330.850660.57467
770.3875750.7751490.612425
780.3616940.7233880.638306
790.376360.7527190.62364
800.3427320.6854640.657268
810.3141410.6282820.685859
820.2804820.5609640.719518
830.2529030.5058070.747097
840.223070.446140.77693
850.216980.4339590.78302
860.1895380.3790750.810462
870.1672230.3344460.832777
880.1548930.3097860.845107
890.1334220.2668440.866578
900.132030.264060.86797
910.1129390.2258790.887061
920.09869980.19740.9013
930.083930.167860.91607
940.08740920.1748180.912591
950.07908240.1581650.920918
960.06618050.1323610.93382
970.07092040.1418410.92908
980.0589110.1178220.941089
990.04888130.09776250.951119
1000.04294860.08589710.957051
1010.0375980.07519590.962402
1020.04348940.08697890.956511
1030.03665590.07331180.963344
1040.03286480.06572970.967135
1050.039170.07833990.96083
1060.03408070.06816130.965919
1070.02767630.05535250.972324
1080.02680680.05361360.973193
1090.02178010.04356020.97822
1100.01774820.03549640.982252
1110.0140720.0281440.985928
1120.01422010.02844020.98578
1130.01291090.02582180.987089
1140.01888680.03777360.981113
1150.01775670.03551330.982243
1160.01726040.03452070.98274
1170.01418660.02837330.985813
1180.01426970.02853950.98573
1190.01150230.02300450.988498
1200.01029710.02059430.989703
1210.00827190.01654380.991728
1220.01252880.02505750.987471
1230.01045440.02090880.989546
1240.008979380.01795880.991021
1250.00729950.0145990.9927
1260.005776920.01155380.994223
1270.005261780.01052360.994738
1280.004253520.008507050.995746
1290.006010380.01202080.99399
1300.00660990.01321980.99339
1310.01375190.02750380.986248
1320.01644110.03288210.983559
1330.0176240.0352480.982376
1340.01671540.03343080.983285
1350.01336090.02672170.986639
1360.0112360.0224720.988764
1370.008927710.01785540.991072
1380.01116280.02232560.988837
1390.009566730.01913350.990433
1400.01132090.02264180.988679
1410.01797880.03595760.982021
1420.01656910.03313830.983431
1430.01332270.02664550.986677
1440.01371740.02743480.986283
1450.02459890.04919770.975401
1460.02985820.05971650.970142
1470.03133960.06267930.96866
1480.02773380.05546750.972266
1490.02257090.04514170.977429
1500.0315140.06302790.968486
1510.02661630.05323250.973384
1520.02896980.05793950.97103
1530.05860870.1172170.941391
1540.05647490.112950.943525
1550.06468120.1293620.935319
1560.05499750.1099950.945003
1570.049080.09815990.95092
1580.04274520.08549040.957255
1590.0413880.08277610.958612
1600.03551790.07103580.964482
1610.02899960.05799920.971
1620.02367150.0473430.976328
1630.01933820.03867630.980662
1640.01635160.03270320.983648
1650.01447030.02894060.98553
1660.01496970.02993940.98503
1670.01190120.02380250.988099
1680.01753340.03506680.982467
1690.01765340.03530680.982347
1700.01675440.03350880.983246
1710.01547450.0309490.984525
1720.0124870.0249740.987513
1730.01210010.02420030.9879
1740.0137870.02757390.986213
1750.01794950.03589890.982051
1760.01439220.02878440.985608
1770.01136350.02272710.988636
1780.009555120.01911020.990445
1790.007397490.0147950.992603
1800.006515630.01303130.993484
1810.005315790.01063160.994684
1820.004090510.008181010.995909
1830.004428260.008856530.995572
1840.003354790.006709570.996645
1850.09165540.1833110.908345
1860.08194690.1638940.918053
1870.09043940.1808790.909561
1880.0759160.1518320.924084
1890.06776120.1355220.932239
1900.05660240.1132050.943398
1910.05237690.1047540.947623
1920.04326740.08653480.956733
1930.04438890.08877770.955611
1940.04487130.08974250.955129
1950.03880210.07760410.961198
1960.03122330.06244650.968777
1970.03942450.07884890.960576
1980.03219150.0643830.967809
1990.02897140.05794280.971029
2000.02486380.04972760.975136
2010.02325260.04650510.976747
2020.0196560.03931190.980344
2030.02581280.05162560.974187
2040.03006460.06012930.969935
2050.03148760.06297530.968512
2060.02468180.04936350.975318
2070.02362770.04725540.976372
2080.01931570.03863130.980684
2090.02153820.04307640.978462
2100.01716540.03433090.982835
2110.01972650.03945310.980273
2120.03199640.06399280.968004
2130.02490920.04981840.975091
2140.03221260.06442520.967787
2150.02733370.05466740.972666
2160.02114610.04229220.978854
2170.02322980.04645950.97677
2180.01958760.03917520.980412
2190.01819840.03639690.981802
2200.01391610.02783220.986084
2210.0115890.02317810.988411
2220.008321920.01664380.991678
2230.006382750.01276550.993617
2240.004810840.009621680.995189
2250.004095180.008190350.995905
2260.009468770.01893750.990531
2270.00741950.0148390.992581
2280.005490250.01098050.99451
2290.003926990.007853970.996073
2300.002891240.005782470.997109
2310.002606960.005213920.997393
2320.006138840.01227770.993861
2330.02477190.04954390.975228
2340.03775560.07551120.962244
2350.02723680.05447360.972763
2360.022830.04566010.97717
2370.197390.394780.80261
2380.1556850.3113690.844315
2390.1296240.2592480.870376
2400.1005560.2011130.899444
2410.0884190.1768380.911581
2420.1379540.2759070.862046
2430.1129730.2259470.887027
2440.1183070.2366150.881693
2450.09683090.1936620.903169
2460.08218340.1643670.917817
2470.05306260.1061250.946937
2480.04521030.09042070.95479
2490.04045830.08091670.959542
2500.1155090.2310180.884491
2510.09471370.1894270.905286
2520.4314540.8629090.568546






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level90.0373444NOK
5% type I error level900.373444NOK
10% type I error level1290.53527NOK

\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 & 9 & 0.0373444 & NOK \tabularnewline
5% type I error level & 90 & 0.373444 & NOK \tabularnewline
10% type I error level & 129 & 0.53527 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221806&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]9[/C][C]0.0373444[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]90[/C][C]0.373444[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]129[/C][C]0.53527[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221806&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221806&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 level90.0373444NOK
5% type I error level900.373444NOK
10% type I error level1290.53527NOK


Figures (Output of Computation)

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

Parameters (Session):
par1 = 3 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 3 ; par2 = Do not include Seasonal Dummies ; par3 = 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')
}