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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 03 Nov 2013 09:44:12 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/03/t1383490071nq2ls6k7eb7ee12.htm/, Retrieved Mon, 29 Apr 2024 14:55:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221924, Retrieved Mon, 29 Apr 2024 14:55:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2013-11-03 14:44:12] [0e9124696d12fe9c83a0561864c9b933] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41 38 13 12 14 12 53 32 9
39 32 16 11 18 11 83 51 9
30 35 19 15 11 14 66 42 9
31 33 15 6 12 12 67 41 9
34 37 14 13 16 21 76 46 9
35 29 13 10 18 12 78 47 9
39 31 19 12 14 22 53 37 9
34 36 15 14 14 11 80 49 9
36 35 14 12 15 10 74 45 9
37 38 15 9 15 13 76 47 9
38 31 16 10 17 10 79 49 9
36 34 16 12 19 8 54 33 9
38 35 16 12 10 15 67 42 9
39 38 16 11 16 14 54 33 9
33 37 17 15 18 10 87 53 9
32 33 15 12 14 14 58 36 9
36 32 15 10 14 14 75 45 9
38 38 20 12 17 11 88 54 9
39 38 18 11 14 10 64 41 9
32 32 16 12 16 13 57 36 9
32 33 16 11 18 9.5 66 41 9
31 31 16 12 11 14 68 44 9
39 38 19 13 14 12 54 33 9
37 39 16 11 12 14 56 37 9
39 32 17 12 17 11 86 52 9
41 32 17 13 9 9 80 47 9
36 35 16 10 16 11 76 43 9
33 37 15 14 14 15 69 44 9
33 33 16 12 15 14 78 45 9
34 33 14 10 11 13 67 44 9
31 31 15 12 16 9 80 49 9
27 32 12 8 13 15 54 33 9
37 31 14 10 17 10 71 43 9
34 37 16 12 15 11 84 54 9
34 30 14 12 14 13 74 42 9
32 33 10 7 16 8 71 44 9
29 31 10 9 9 20 63 37 9
36 33 14 12 15 12 71 43 9
29 31 16 10 17 10 76 46 9
35 33 16 10 13 10 69 42 9
37 32 16 10 15 9 74 45 9
34 33 14 12 16 14 75 44 9
38 32 20 15 16 8 54 33 9
35 33 14 10 12 14 52 31 9
38 28 14 10 15 11 69 42 9
37 35 11 12 11 13 68 40 9
38 39 14 13 15 9 65 43 9
33 34 15 11 15 11 75 46 9
36 38 16 11 17 15 74 42 9
38 32 14 12 13 11 75 45 9
32 38 16 14 16 10 72 44 9
32 30 14 10 14 14 67 40 9
32 33 12 12 11 18 63 37 9
34 38 16 13 12 14 62 46 9
32 32 9 5 12 11 63 36 9
37 35 14 6 15 14.5 76 47 9
39 34 16 12 16 13 74 45 9
29 34 16 12 15 9 67 42 9
37 36 15 11 12 10 73 43 9
35 34 16 10 12 15 70 43 9
30 28 12 7 8 20 53 32 9
38 34 16 12 13 12 77 45 9
34 35 16 14 11 12 80 48 9
31 35 14 11 14 14 52 31 9
34 31 16 12 15 13 54 33 9
35 37 17 13 10 11 80 49 10
36 35 18 14 11 17 66 42 10
30 27 18 11 12 12 73 41 10
39 40 12 12 15 13 63 38 10
35 37 16 12 15 14 69 42 10
38 36 10 8 14 13 67 44 10
31 38 14 11 16 15 54 33 10
34 39 18 14 15 13 81 48 10
38 41 18 14 15 10 69 40 10
34 27 16 12 13 11 84 50 10
39 30 17 9 12 19 80 49 10
37 37 16 13 17 13 70 43 10
34 31 16 11 13 17 69 44 10
28 31 13 12 15 13 77 47 10
37 27 16 12 13 9 54 33 10
33 36 16 12 15 11 79 46 10
35 37 16 12 15 9 71 45 10
37 33 15 12 16 12 73 43 10
32 34 15 11 15 12 72 44 10
33 31 16 10 14 13 77 47 10
38 39 14 9 15 13 75 45 10
33 34 16 12 14 12 69 42 10
29 32 16 12 13 15 54 33 10
33 33 15 12 7 22 70 43 10
31 36 12 9 17 13 73 46 10
36 32 17 15 13 15 54 33 10
35 41 16 12 15 13 77 46 10
32 28 15 12 14 15 82 48 10
29 30 13 12 13 12.5 80 47 10
39 36 16 10 16 11 80 47 10
37 35 16 13 12 16 69 43 10
35 31 16 9 14 11 78 46 10
37 34 16 12 17 11 81 48 10
32 36 14 10 15 10 76 46 10
38 36 16 14 17 10 76 45 10
37 35 16 11 12 16 73 45 10
36 37 20 15 16 12 85 52 10
32 28 15 11 11 11 66 42 10
33 39 16 11 15 16 79 47 10
40 32 13 12 9 19 68 41 10
38 35 17 12 16 11 76 47 10
41 39 16 12 15 16 71 43 10
36 35 16 11 10 15 54 33 10
43 42 12 7 10 24 46 30 10
30 34 16 12 15 14 85 52 10
31 33 16 14 11 15 74 44 10
32 41 17 11 13 11 88 55 10
32 33 13 11 14 15 38 11 10
37 34 12 10 18 12 76 47 10
37 32 18 13 16 10 86 53 10
33 40 14 13 14 14 54 33 10
34 40 14 8 14 13 67 44 10
33 35 13 11 14 9 69 42 10
38 36 16 12 14 15 90 55 10
33 37 13 11 12 15 54 33 10
31 27 16 13 14 14 76 46 10
38 39 13 12 15 11 89 54 10
37 38 16 14 15 8 76 47 10
36 31 15 13 15 11 73 45 10
31 33 16 15 13 11 79 47 10
39 32 15 10 17 8 90 55 10
44 39 17 11 17 10 74 44 10
33 36 15 9 19 11 81 53 10
35 33 12 11 15 13 72 44 10
32 33 16 10 13 11 71 42 10
28 32 10 11 9 20 66 40 10
40 37 16 8 15 10 77 46 10
27 30 12 11 15 15 65 40 10
37 38 14 12 15 12 74 46 10
32 29 15 12 16 14 85 53 10
28 22 13 9 11 23 54 33 10
34 35 15 11 14 14 63 42 10
30 35 11 10 11 16 54 35 10
35 34 12 8 15 11 64 40 10
31 35 11 9 13 12 69 41 10
32 34 16 8 15 10 54 33 10
30 37 15 9 16 14 84 51 10
30 35 17 15 14 12 86 53 10
31 23 16 11 15 12 77 46 10
40 31 10 8 16 11 89 55 10
32 27 18 13 16 12 76 47 10
36 36 13 12 11 13 60 38 10
32 31 16 12 12 11 75 46 10
35 32 13 9 9 19 73 46 10
38 39 10 7 16 12 85 53 10
42 37 15 13 13 17 79 47 10
34 38 16 9 16 9 71 41 10
35 39 16 6 12 12 72 44 10
38 34 14 8 9 19 69 43 9
33 31 10 8 13 18 78 51 10
36 32 17 15 13 15 54 33 10
32 37 13 6 14 14 69 43 10
33 36 15 9 19 11 81 53 10
34 32 16 11 13 9 84 51 10
32 38 12 8 12 18 84 50 10
34 36 13 8 13 16 69 46 10
27 26 13 10 10 24 66 43 11
31 26 12 8 14 14 81 47 11
38 33 17 14 16 20 82 50 11
34 39 15 10 10 18 72 43 11
24 30 10 8 11 23 54 33 11
30 33 14 11 14 12 78 48 11
26 25 11 12 12 14 74 44 11
34 38 13 12 9 16 82 50 11
27 37 16 12 9 18 73 41 11
37 31 12 5 11 20 55 34 11
36 37 16 12 16 12 72 44 11
41 35 12 10 9 12 78 47 11
29 25 9 7 13 17 59 35 11
36 28 12 12 16 13 72 44 11
32 35 15 11 13 9 78 44 11
37 33 12 8 9 16 68 43 11
30 30 12 9 12 18 69 41 11
31 31 14 10 16 10 67 41 11
38 37 12 9 11 14 74 42 11
36 36 16 12 14 11 54 33 11
35 30 11 6 13 9 67 41 11
31 36 19 15 15 11 70 44 11
38 32 15 12 14 10 80 48 11
22 28 8 12 16 11 89 55 11
32 36 16 12 13 19 76 44 11
36 34 17 11 14 14 74 43 11
39 31 12 7 15 12 87 52 11
28 28 11 7 13 14 54 30 11
32 36 11 5 11 21 61 39 11
32 36 14 12 11 13 38 11 11
38 40 16 12 14 10 75 44 11
32 33 12 3 15 15 69 42 11
35 37 16 11 11 16 62 41 11
32 32 13 10 15 14 72 44 11
37 38 15 12 12 12 70 44 11
34 31 16 9 14 19 79 48 11
33 37 16 12 14 15 87 53 11
33 33 14 9 8 19 62 37 11
26 32 16 12 13 13 77 44 11
30 30 16 12 9 17 69 44 11
24 30 14 10 15 12 69 40 11
34 31 11 9 17 11 75 42 11
34 32 12 12 13 14 54 35 11
33 34 15 8 15 11 72 43 11
34 36 15 11 15 13 74 45 11
35 37 16 11 14 12 85 55 11
35 36 16 12 16 15 52 31 11
36 33 11 10 13 14 70 44 11
34 33 15 10 16 12 84 50 11
34 33 12 12 9 17 64 40 11
41 44 12 12 16 11 84 53 11
32 39 15 11 11 18 87 54 11
30 32 15 8 10 13 79 49 11
35 35 16 12 11 17 67 40 11
28 25 14 10 15 13 65 41 11
33 35 17 11 17 11 85 52 11
39 34 14 10 14 12 83 52 11
36 35 13 8 8 22 61 36 11
36 39 15 12 15 14 82 52 11
35 33 13 12 11 12 76 46 11
38 36 14 10 16 12 58 31 11
33 32 15 12 10 17 72 44 11
31 32 12 9 15 9 72 44 11
34 36 13 9 9 21 38 11 11
32 36 8 6 16 10 78 46 11
31 32 14 10 19 11 54 33 11
33 34 14 9 12 12 63 34 11
34 33 11 9 8 23 66 42 11
34 35 12 9 11 13 70 43 11
34 30 13 6 14 12 71 43 11
33 38 10 10 9 16 67 44 11
32 34 16 6 15 9 58 36 11
41 33 18 14 13 17 72 46 11
34 32 13 10 16 9 72 44 11
36 31 11 10 11 14 70 43 11
37 30 4 6 12 17 76 50 11
36 27 13 12 13 13 50 33 11
29 31 16 12 10 11 72 43 11
37 30 10 7 11 12 72 44 11
27 32 12 8 12 10 88 53 11
35 35 12 11 8 19 53 34 11
28 28 10 3 12 16 58 35 11
35 33 13 6 12 16 66 40 11
37 31 15 10 15 14 82 53 11
29 35 12 8 11 20 69 42 11
32 35 14 9 13 15 68 43 11
36 32 10 9 14 23 44 29 11
19 21 12 8 10 20 56 36 11
21 20 12 9 12 16 53 30 11
31 34 11 7 15 14 70 42 11
33 32 10 7 13 17 78 47 11
36 34 12 6 13 11 71 44 11
33 32 16 9 13 13 72 45 11
37 33 12 10 12 17 68 44 11
34 33 14 11 12 15 67 43 11
35 37 16 12 9 21 75 43 11
31 32 14 8 9 18 62 40 11
37 34 13 11 15 15 67 41 11
35 30 4 3 10 8 83 52 11
27 30 15 11 14 12 64 38 11
34 38 11 12 15 12 68 41 11
40 36 11 7 7 22 62 39 11
29 32 14 9 14 12 72 43 11

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 seconds
R Server'George Udny Yule' @ yule.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 & 15 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221924&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]15 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221924&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221924&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 time15 seconds
R Server'George Udny Yule' @ yule.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 4.00445 + 0.033972Connected[t] + 0.0426649Separate[t] + 0.553914Software[t] + 0.0693844Happiness[t] -0.0309725Depression[t] + 0.0210589Sport1[t] -0.0218368Sport2[t] + 0.161768Month[t] -0.00651732t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  4.00445 +  0.033972Connected[t] +  0.0426649Separate[t] +  0.553914Software[t] +  0.0693844Happiness[t] -0.0309725Depression[t] +  0.0210589Sport1[t] -0.0218368Sport2[t] +  0.161768Month[t] -0.00651732t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221924&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  4.00445 +  0.033972Connected[t] +  0.0426649Separate[t] +  0.553914Software[t] +  0.0693844Happiness[t] -0.0309725Depression[t] +  0.0210589Sport1[t] -0.0218368Sport2[t] +  0.161768Month[t] -0.00651732t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221924&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221924&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] = + 4.00445 + 0.033972Connected[t] + 0.0426649Separate[t] + 0.553914Software[t] + 0.0693844Happiness[t] -0.0309725Depression[t] + 0.0210589Sport1[t] -0.0218368Sport2[t] + 0.161768Month[t] -0.00651732t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.004453.893741.0280.3047250.152362
Connected0.0339720.03467460.97970.3281470.164074
Separate0.04266490.03519591.2120.2265580.113279
Software0.5539140.054660710.131.72999e-208.64997e-21
Happiness0.06938440.05810211.1940.2335220.116761
Depression-0.03097250.0424556-0.72950.4663530.233176
Sport10.02105890.03797880.55450.579730.289865
Sport2-0.02183680.0564192-0.3870.6990470.349524
Month0.1617680.4087380.39580.6926040.346302
t-0.006517320.00433239-1.5040.133740.0668701

\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) & 4.00445 & 3.89374 & 1.028 & 0.304725 & 0.152362 \tabularnewline
Connected & 0.033972 & 0.0346746 & 0.9797 & 0.328147 & 0.164074 \tabularnewline
Separate & 0.0426649 & 0.0351959 & 1.212 & 0.226558 & 0.113279 \tabularnewline
Software & 0.553914 & 0.0546607 & 10.13 & 1.72999e-20 & 8.64997e-21 \tabularnewline
Happiness & 0.0693844 & 0.0581021 & 1.194 & 0.233522 & 0.116761 \tabularnewline
Depression & -0.0309725 & 0.0424556 & -0.7295 & 0.466353 & 0.233176 \tabularnewline
Sport1 & 0.0210589 & 0.0379788 & 0.5545 & 0.57973 & 0.289865 \tabularnewline
Sport2 & -0.0218368 & 0.0564192 & -0.387 & 0.699047 & 0.349524 \tabularnewline
Month & 0.161768 & 0.408738 & 0.3958 & 0.692604 & 0.346302 \tabularnewline
t & -0.00651732 & 0.00433239 & -1.504 & 0.13374 & 0.0668701 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221924&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]4.00445[/C][C]3.89374[/C][C]1.028[/C][C]0.304725[/C][C]0.152362[/C][/ROW]
[ROW][C]Connected[/C][C]0.033972[/C][C]0.0346746[/C][C]0.9797[/C][C]0.328147[/C][C]0.164074[/C][/ROW]
[ROW][C]Separate[/C][C]0.0426649[/C][C]0.0351959[/C][C]1.212[/C][C]0.226558[/C][C]0.113279[/C][/ROW]
[ROW][C]Software[/C][C]0.553914[/C][C]0.0546607[/C][C]10.13[/C][C]1.72999e-20[/C][C]8.64997e-21[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0693844[/C][C]0.0581021[/C][C]1.194[/C][C]0.233522[/C][C]0.116761[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0309725[/C][C]0.0424556[/C][C]-0.7295[/C][C]0.466353[/C][C]0.233176[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0210589[/C][C]0.0379788[/C][C]0.5545[/C][C]0.57973[/C][C]0.289865[/C][/ROW]
[ROW][C]Sport2[/C][C]-0.0218368[/C][C]0.0564192[/C][C]-0.387[/C][C]0.699047[/C][C]0.349524[/C][/ROW]
[ROW][C]Month[/C][C]0.161768[/C][C]0.408738[/C][C]0.3958[/C][C]0.692604[/C][C]0.346302[/C][/ROW]
[ROW][C]t[/C][C]-0.00651732[/C][C]0.00433239[/C][C]-1.504[/C][C]0.13374[/C][C]0.0668701[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221924&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221924&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)4.004453.893741.0280.3047250.152362
Connected0.0339720.03467460.97970.3281470.164074
Separate0.04266490.03519591.2120.2265580.113279
Software0.5539140.054660710.131.72999e-208.64997e-21
Happiness0.06938440.05810211.1940.2335220.116761
Depression-0.03097250.0424556-0.72950.4663530.233176
Sport10.02105890.03797880.55450.579730.289865
Sport2-0.02183680.0564192-0.3870.6990470.349524
Month0.1617680.4087380.39580.6926040.346302
t-0.006517320.00433239-1.5040.133740.0668701






Multiple Linear Regression - Regression Statistics
Multiple R0.667804
R-squared0.445963
Adjusted R-squared0.426331
F-TEST (value)22.717
F-TEST (DF numerator)9
F-TEST (DF denominator)254
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.86018
Sum Squared Residuals878.905

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.667804 \tabularnewline
R-squared & 0.445963 \tabularnewline
Adjusted R-squared & 0.426331 \tabularnewline
F-TEST (value) & 22.717 \tabularnewline
F-TEST (DF numerator) & 9 \tabularnewline
F-TEST (DF denominator) & 254 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.86018 \tabularnewline
Sum Squared Residuals & 878.905 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221924&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.667804[/C][/ROW]
[ROW][C]R-squared[/C][C]0.445963[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.426331[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]22.717[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]9[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]254[/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]1.86018[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]878.905[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221924&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221924&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 R0.667804
R-squared0.445963
Adjusted R-squared0.426331
F-TEST (value)22.717
F-TEST (DF numerator)9
F-TEST (DF denominator)254
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.86018
Sum Squared Residuals878.905






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11316.132-3.132
21615.7730.226987
31917.06431.93568
41512.19542.80456
51416.418-2.41803
61314.8802-1.88023
71915.30743.69261
81517.0994-2.09941
91416.0717-2.07169
101514.47090.529072
111615.00480.995168
121616.1898-0.189823
131615.52990.470117
141615.50150.498538
151717.985-0.984972
161515.4712-0.471169
171514.61150.388483
182016.41513.58493
191815.48992.51011
201615.55110.448882
211615.36090.63913
221615.14050.859494
231916.47382.52619
241615.08820.911758
251716.1490.851015
261716.2540.745974
271614.97081.02924
281516.7314-1.7314
291615.71440.285552
301414.1777-0.177698
311515.7272-0.727157
321212.8196-0.819627
331414.79-0.790028
341615.90920.090767
351415.5242-1.52418
361012.9949-2.99493
371013.036-3.03602
381415.7159-1.71591
391614.51891.48107
401614.4641.53603
411614.69231.30774
421415.6917-1.69174
432017.4242.57601
441414.1268-0.126833
451414.4278-0.427776
461115.4769-4.4769
471416.5017-2.50167
481515.0873-0.0872734
491615.43450.565501
501415.5958-1.59575
511616.947-0.947006
521414.1029-0.102906
531214.9814-2.98144
541615.78580.214207
55911.3564-2.35637
561412.33491.66507
571615.79460.205419
581615.42090.579053
591515.083-0.0830125
601614.15131.84873
611211.5070.493039
621615.6140.385981
631616.481-0.481005
641414.6386-0.638612
651615.21610.783934
661716.12840.871641
671816.3661.63402
681814.54613.45393
691215.986-3.98596
701615.72360.27641
711013.4365-3.43646
721414.9825-0.982476
731817.01590.984117
741817.24550.754512
751615.32570.674279
761713.57583.42425
771616.4688-0.46879
781614.55221.44778
791315.2614-2.2614
801615.19650.803547
811615.75740.24255
821615.77690.223148
831515.7299-0.729877
841514.930.0700298
851614.21491.78506
861414.2366-0.236631
871615.40940.590583
881614.91.09997
891514.55750.442476
901213.9196-1.91958
911716.780.219977
921615.8630.137035
931515.1302-0.13018
941315.0948-2.09484
951614.83081.16918
961615.79870.201267
971613.75562.24439
981615.83440.165573
991414.4661-0.466133
1001617.0397-1.03971
1011614.69891.30112
1022017.46072.53935
1031514.22090.779093
1041615.00490.995068
1051314.8816-1.88163
1061715.70611.29392
1071615.72990.270053
1081614.37341.62659
1091212.306-0.305983
1101615.28360.716383
1111616.0108-0.0107717
1121715.03511.96492
1131314.5406-1.54061
1141214.5773-2.57728
1151816.14991.85008
1161415.849-1.84902
1171413.17140.828563
1181314.789-1.78905
1191615.52150.478505
1201314.4174-1.41739
1211615.37330.626735
1221315.824-2.82399
1231616.8207-0.820673
1241515.8152-0.815194
1251616.7759-0.775886
1261514.65630.343682
1271715.51351.48645
1281513.95621.04381
1291214.665-2.66497
1301613.94842.05159
1311013.6993-3.69935
1321613.47872.52127
1331214.1171-2.11712
1341415.497-1.49698
1351515.0229-0.0228515
1361312.07830.921716
1371514.4180.582025
1381113.4149-2.41488
1391212.9615-0.961539
1401113.3294-2.32943
1411612.81983.18017
1421513.61151.38852
1431716.76470.235264
1441614.09731.90273
1451013.2326-3.23261
1461815.42322.57682
1471314.8643-1.86431
1481614.78111.2189
1491312.75940.240626
1501012.8479-2.84795
1511515.8571-0.857125
1521613.82432.17568
1531611.81784.18221
1541412.17961.82037
1551012.3604-2.36037
1561716.35640.643603
1571311.641.36004
1581513.76071.23933
1591614.47781.52222
1601212.6713-0.671269
1611312.55020.449842
1621312.69520.304814
1631212.5325-0.532527
1641716.29440.705563
1651513.78031.21973
1661011.696-1.69605
1671414.4098-0.409814
1681114.2824-3.2824
1691314.8697-1.86966
1701614.52771.47227
1711210.57821.42184
1721615.40540.594604
1731213.9507-1.95073
174911.4328-2.43276
1751214.9709-2.97089
1761514.61530.384688
1771212.3485-0.348485
1781212.741-0.741024
1791413.84830.151743
1801213.4364-1.43638
1811615.05740.942577
1821111.5291-0.52909
1831916.70242.29761
1841515.1861-0.186108
185814.6098-6.60985
1861614.79491.20512
1871714.4892.51103
1881212.4493-0.449279
1891111.5258-0.525825
1901110.4840.516008
1911414.7297-0.729729
1921615.45730.542659
193129.794952.20505
1941614.05821.94176
1951313.6671-0.667127
1961515.006-0.00596155
1971612.96133.03872
1981615.02170.978304
1991412.46551.5345
2001614.5361.46397
2011614.01021.98982
2021413.35050.649485
2031113.4249-2.42489
2041214.4629-2.46295
2051512.72822.27182
2061514.43920.560792
2071614.48421.5158
2081614.86391.13608
2091113.5736-2.57355
2101513.9331.06701
2111214.1909-2.19094
2121215.7004-3.70037
2131514.09850.901528
2141512.08982.9102
2151614.48611.51388
2161413.04480.955209
2171714.57042.42962
2181413.88990.110123
2191311.87631.12366
2201515.0825-0.0824598
2211314.5751-1.57506
2221413.9860.0139668
2231514.18660.813397
2241213.0451-1.0451
2251312.52780.472207
226811.696-3.69605
2271413.65620.343801
2281412.90011.09993
2291112.1551-1.15511
2301212.8142-0.814199
2311311.19281.8072
2321013.1324-3.1324
2331611.32394.67613
2341815.70172.29834
2351313.6986-0.698625
2361113.1953-2.19532
237410.9144-6.91442
2381314.0864-1.08639
2391614.11141.88856
2401011.581-1.58104
2411212.1458-0.14579
2421213.3223-1.32233
243108.801961.19804
2441310.96762.0324
2451513.48251.51749
2461211.77010.229882
2471412.67021.32983
2481012.2934-2.29345
2491210.60141.39859
2501211.50460.495414
2511111.6933-0.693327
2521011.497-1.49703
2531211.22780.772228
2541612.6333.36697
2551213.1033-1.10331
2561413.61150.38849
2571614.1381.86198
2581411.45132.5487
2591313.9884-0.988366
26049.27855-5.27855
2611513.49081.50918
2621114.7054-3.70545
2631111.1004-0.100382
2641412.5761.424

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 16.132 & -3.132 \tabularnewline
2 & 16 & 15.773 & 0.226987 \tabularnewline
3 & 19 & 17.0643 & 1.93568 \tabularnewline
4 & 15 & 12.1954 & 2.80456 \tabularnewline
5 & 14 & 16.418 & -2.41803 \tabularnewline
6 & 13 & 14.8802 & -1.88023 \tabularnewline
7 & 19 & 15.3074 & 3.69261 \tabularnewline
8 & 15 & 17.0994 & -2.09941 \tabularnewline
9 & 14 & 16.0717 & -2.07169 \tabularnewline
10 & 15 & 14.4709 & 0.529072 \tabularnewline
11 & 16 & 15.0048 & 0.995168 \tabularnewline
12 & 16 & 16.1898 & -0.189823 \tabularnewline
13 & 16 & 15.5299 & 0.470117 \tabularnewline
14 & 16 & 15.5015 & 0.498538 \tabularnewline
15 & 17 & 17.985 & -0.984972 \tabularnewline
16 & 15 & 15.4712 & -0.471169 \tabularnewline
17 & 15 & 14.6115 & 0.388483 \tabularnewline
18 & 20 & 16.4151 & 3.58493 \tabularnewline
19 & 18 & 15.4899 & 2.51011 \tabularnewline
20 & 16 & 15.5511 & 0.448882 \tabularnewline
21 & 16 & 15.3609 & 0.63913 \tabularnewline
22 & 16 & 15.1405 & 0.859494 \tabularnewline
23 & 19 & 16.4738 & 2.52619 \tabularnewline
24 & 16 & 15.0882 & 0.911758 \tabularnewline
25 & 17 & 16.149 & 0.851015 \tabularnewline
26 & 17 & 16.254 & 0.745974 \tabularnewline
27 & 16 & 14.9708 & 1.02924 \tabularnewline
28 & 15 & 16.7314 & -1.7314 \tabularnewline
29 & 16 & 15.7144 & 0.285552 \tabularnewline
30 & 14 & 14.1777 & -0.177698 \tabularnewline
31 & 15 & 15.7272 & -0.727157 \tabularnewline
32 & 12 & 12.8196 & -0.819627 \tabularnewline
33 & 14 & 14.79 & -0.790028 \tabularnewline
34 & 16 & 15.9092 & 0.090767 \tabularnewline
35 & 14 & 15.5242 & -1.52418 \tabularnewline
36 & 10 & 12.9949 & -2.99493 \tabularnewline
37 & 10 & 13.036 & -3.03602 \tabularnewline
38 & 14 & 15.7159 & -1.71591 \tabularnewline
39 & 16 & 14.5189 & 1.48107 \tabularnewline
40 & 16 & 14.464 & 1.53603 \tabularnewline
41 & 16 & 14.6923 & 1.30774 \tabularnewline
42 & 14 & 15.6917 & -1.69174 \tabularnewline
43 & 20 & 17.424 & 2.57601 \tabularnewline
44 & 14 & 14.1268 & -0.126833 \tabularnewline
45 & 14 & 14.4278 & -0.427776 \tabularnewline
46 & 11 & 15.4769 & -4.4769 \tabularnewline
47 & 14 & 16.5017 & -2.50167 \tabularnewline
48 & 15 & 15.0873 & -0.0872734 \tabularnewline
49 & 16 & 15.4345 & 0.565501 \tabularnewline
50 & 14 & 15.5958 & -1.59575 \tabularnewline
51 & 16 & 16.947 & -0.947006 \tabularnewline
52 & 14 & 14.1029 & -0.102906 \tabularnewline
53 & 12 & 14.9814 & -2.98144 \tabularnewline
54 & 16 & 15.7858 & 0.214207 \tabularnewline
55 & 9 & 11.3564 & -2.35637 \tabularnewline
56 & 14 & 12.3349 & 1.66507 \tabularnewline
57 & 16 & 15.7946 & 0.205419 \tabularnewline
58 & 16 & 15.4209 & 0.579053 \tabularnewline
59 & 15 & 15.083 & -0.0830125 \tabularnewline
60 & 16 & 14.1513 & 1.84873 \tabularnewline
61 & 12 & 11.507 & 0.493039 \tabularnewline
62 & 16 & 15.614 & 0.385981 \tabularnewline
63 & 16 & 16.481 & -0.481005 \tabularnewline
64 & 14 & 14.6386 & -0.638612 \tabularnewline
65 & 16 & 15.2161 & 0.783934 \tabularnewline
66 & 17 & 16.1284 & 0.871641 \tabularnewline
67 & 18 & 16.366 & 1.63402 \tabularnewline
68 & 18 & 14.5461 & 3.45393 \tabularnewline
69 & 12 & 15.986 & -3.98596 \tabularnewline
70 & 16 & 15.7236 & 0.27641 \tabularnewline
71 & 10 & 13.4365 & -3.43646 \tabularnewline
72 & 14 & 14.9825 & -0.982476 \tabularnewline
73 & 18 & 17.0159 & 0.984117 \tabularnewline
74 & 18 & 17.2455 & 0.754512 \tabularnewline
75 & 16 & 15.3257 & 0.674279 \tabularnewline
76 & 17 & 13.5758 & 3.42425 \tabularnewline
77 & 16 & 16.4688 & -0.46879 \tabularnewline
78 & 16 & 14.5522 & 1.44778 \tabularnewline
79 & 13 & 15.2614 & -2.2614 \tabularnewline
80 & 16 & 15.1965 & 0.803547 \tabularnewline
81 & 16 & 15.7574 & 0.24255 \tabularnewline
82 & 16 & 15.7769 & 0.223148 \tabularnewline
83 & 15 & 15.7299 & -0.729877 \tabularnewline
84 & 15 & 14.93 & 0.0700298 \tabularnewline
85 & 16 & 14.2149 & 1.78506 \tabularnewline
86 & 14 & 14.2366 & -0.236631 \tabularnewline
87 & 16 & 15.4094 & 0.590583 \tabularnewline
88 & 16 & 14.9 & 1.09997 \tabularnewline
89 & 15 & 14.5575 & 0.442476 \tabularnewline
90 & 12 & 13.9196 & -1.91958 \tabularnewline
91 & 17 & 16.78 & 0.219977 \tabularnewline
92 & 16 & 15.863 & 0.137035 \tabularnewline
93 & 15 & 15.1302 & -0.13018 \tabularnewline
94 & 13 & 15.0948 & -2.09484 \tabularnewline
95 & 16 & 14.8308 & 1.16918 \tabularnewline
96 & 16 & 15.7987 & 0.201267 \tabularnewline
97 & 16 & 13.7556 & 2.24439 \tabularnewline
98 & 16 & 15.8344 & 0.165573 \tabularnewline
99 & 14 & 14.4661 & -0.466133 \tabularnewline
100 & 16 & 17.0397 & -1.03971 \tabularnewline
101 & 16 & 14.6989 & 1.30112 \tabularnewline
102 & 20 & 17.4607 & 2.53935 \tabularnewline
103 & 15 & 14.2209 & 0.779093 \tabularnewline
104 & 16 & 15.0049 & 0.995068 \tabularnewline
105 & 13 & 14.8816 & -1.88163 \tabularnewline
106 & 17 & 15.7061 & 1.29392 \tabularnewline
107 & 16 & 15.7299 & 0.270053 \tabularnewline
108 & 16 & 14.3734 & 1.62659 \tabularnewline
109 & 12 & 12.306 & -0.305983 \tabularnewline
110 & 16 & 15.2836 & 0.716383 \tabularnewline
111 & 16 & 16.0108 & -0.0107717 \tabularnewline
112 & 17 & 15.0351 & 1.96492 \tabularnewline
113 & 13 & 14.5406 & -1.54061 \tabularnewline
114 & 12 & 14.5773 & -2.57728 \tabularnewline
115 & 18 & 16.1499 & 1.85008 \tabularnewline
116 & 14 & 15.849 & -1.84902 \tabularnewline
117 & 14 & 13.1714 & 0.828563 \tabularnewline
118 & 13 & 14.789 & -1.78905 \tabularnewline
119 & 16 & 15.5215 & 0.478505 \tabularnewline
120 & 13 & 14.4174 & -1.41739 \tabularnewline
121 & 16 & 15.3733 & 0.626735 \tabularnewline
122 & 13 & 15.824 & -2.82399 \tabularnewline
123 & 16 & 16.8207 & -0.820673 \tabularnewline
124 & 15 & 15.8152 & -0.815194 \tabularnewline
125 & 16 & 16.7759 & -0.775886 \tabularnewline
126 & 15 & 14.6563 & 0.343682 \tabularnewline
127 & 17 & 15.5135 & 1.48645 \tabularnewline
128 & 15 & 13.9562 & 1.04381 \tabularnewline
129 & 12 & 14.665 & -2.66497 \tabularnewline
130 & 16 & 13.9484 & 2.05159 \tabularnewline
131 & 10 & 13.6993 & -3.69935 \tabularnewline
132 & 16 & 13.4787 & 2.52127 \tabularnewline
133 & 12 & 14.1171 & -2.11712 \tabularnewline
134 & 14 & 15.497 & -1.49698 \tabularnewline
135 & 15 & 15.0229 & -0.0228515 \tabularnewline
136 & 13 & 12.0783 & 0.921716 \tabularnewline
137 & 15 & 14.418 & 0.582025 \tabularnewline
138 & 11 & 13.4149 & -2.41488 \tabularnewline
139 & 12 & 12.9615 & -0.961539 \tabularnewline
140 & 11 & 13.3294 & -2.32943 \tabularnewline
141 & 16 & 12.8198 & 3.18017 \tabularnewline
142 & 15 & 13.6115 & 1.38852 \tabularnewline
143 & 17 & 16.7647 & 0.235264 \tabularnewline
144 & 16 & 14.0973 & 1.90273 \tabularnewline
145 & 10 & 13.2326 & -3.23261 \tabularnewline
146 & 18 & 15.4232 & 2.57682 \tabularnewline
147 & 13 & 14.8643 & -1.86431 \tabularnewline
148 & 16 & 14.7811 & 1.2189 \tabularnewline
149 & 13 & 12.7594 & 0.240626 \tabularnewline
150 & 10 & 12.8479 & -2.84795 \tabularnewline
151 & 15 & 15.8571 & -0.857125 \tabularnewline
152 & 16 & 13.8243 & 2.17568 \tabularnewline
153 & 16 & 11.8178 & 4.18221 \tabularnewline
154 & 14 & 12.1796 & 1.82037 \tabularnewline
155 & 10 & 12.3604 & -2.36037 \tabularnewline
156 & 17 & 16.3564 & 0.643603 \tabularnewline
157 & 13 & 11.64 & 1.36004 \tabularnewline
158 & 15 & 13.7607 & 1.23933 \tabularnewline
159 & 16 & 14.4778 & 1.52222 \tabularnewline
160 & 12 & 12.6713 & -0.671269 \tabularnewline
161 & 13 & 12.5502 & 0.449842 \tabularnewline
162 & 13 & 12.6952 & 0.304814 \tabularnewline
163 & 12 & 12.5325 & -0.532527 \tabularnewline
164 & 17 & 16.2944 & 0.705563 \tabularnewline
165 & 15 & 13.7803 & 1.21973 \tabularnewline
166 & 10 & 11.696 & -1.69605 \tabularnewline
167 & 14 & 14.4098 & -0.409814 \tabularnewline
168 & 11 & 14.2824 & -3.2824 \tabularnewline
169 & 13 & 14.8697 & -1.86966 \tabularnewline
170 & 16 & 14.5277 & 1.47227 \tabularnewline
171 & 12 & 10.5782 & 1.42184 \tabularnewline
172 & 16 & 15.4054 & 0.594604 \tabularnewline
173 & 12 & 13.9507 & -1.95073 \tabularnewline
174 & 9 & 11.4328 & -2.43276 \tabularnewline
175 & 12 & 14.9709 & -2.97089 \tabularnewline
176 & 15 & 14.6153 & 0.384688 \tabularnewline
177 & 12 & 12.3485 & -0.348485 \tabularnewline
178 & 12 & 12.741 & -0.741024 \tabularnewline
179 & 14 & 13.8483 & 0.151743 \tabularnewline
180 & 12 & 13.4364 & -1.43638 \tabularnewline
181 & 16 & 15.0574 & 0.942577 \tabularnewline
182 & 11 & 11.5291 & -0.52909 \tabularnewline
183 & 19 & 16.7024 & 2.29761 \tabularnewline
184 & 15 & 15.1861 & -0.186108 \tabularnewline
185 & 8 & 14.6098 & -6.60985 \tabularnewline
186 & 16 & 14.7949 & 1.20512 \tabularnewline
187 & 17 & 14.489 & 2.51103 \tabularnewline
188 & 12 & 12.4493 & -0.449279 \tabularnewline
189 & 11 & 11.5258 & -0.525825 \tabularnewline
190 & 11 & 10.484 & 0.516008 \tabularnewline
191 & 14 & 14.7297 & -0.729729 \tabularnewline
192 & 16 & 15.4573 & 0.542659 \tabularnewline
193 & 12 & 9.79495 & 2.20505 \tabularnewline
194 & 16 & 14.0582 & 1.94176 \tabularnewline
195 & 13 & 13.6671 & -0.667127 \tabularnewline
196 & 15 & 15.006 & -0.00596155 \tabularnewline
197 & 16 & 12.9613 & 3.03872 \tabularnewline
198 & 16 & 15.0217 & 0.978304 \tabularnewline
199 & 14 & 12.4655 & 1.5345 \tabularnewline
200 & 16 & 14.536 & 1.46397 \tabularnewline
201 & 16 & 14.0102 & 1.98982 \tabularnewline
202 & 14 & 13.3505 & 0.649485 \tabularnewline
203 & 11 & 13.4249 & -2.42489 \tabularnewline
204 & 12 & 14.4629 & -2.46295 \tabularnewline
205 & 15 & 12.7282 & 2.27182 \tabularnewline
206 & 15 & 14.4392 & 0.560792 \tabularnewline
207 & 16 & 14.4842 & 1.5158 \tabularnewline
208 & 16 & 14.8639 & 1.13608 \tabularnewline
209 & 11 & 13.5736 & -2.57355 \tabularnewline
210 & 15 & 13.933 & 1.06701 \tabularnewline
211 & 12 & 14.1909 & -2.19094 \tabularnewline
212 & 12 & 15.7004 & -3.70037 \tabularnewline
213 & 15 & 14.0985 & 0.901528 \tabularnewline
214 & 15 & 12.0898 & 2.9102 \tabularnewline
215 & 16 & 14.4861 & 1.51388 \tabularnewline
216 & 14 & 13.0448 & 0.955209 \tabularnewline
217 & 17 & 14.5704 & 2.42962 \tabularnewline
218 & 14 & 13.8899 & 0.110123 \tabularnewline
219 & 13 & 11.8763 & 1.12366 \tabularnewline
220 & 15 & 15.0825 & -0.0824598 \tabularnewline
221 & 13 & 14.5751 & -1.57506 \tabularnewline
222 & 14 & 13.986 & 0.0139668 \tabularnewline
223 & 15 & 14.1866 & 0.813397 \tabularnewline
224 & 12 & 13.0451 & -1.0451 \tabularnewline
225 & 13 & 12.5278 & 0.472207 \tabularnewline
226 & 8 & 11.696 & -3.69605 \tabularnewline
227 & 14 & 13.6562 & 0.343801 \tabularnewline
228 & 14 & 12.9001 & 1.09993 \tabularnewline
229 & 11 & 12.1551 & -1.15511 \tabularnewline
230 & 12 & 12.8142 & -0.814199 \tabularnewline
231 & 13 & 11.1928 & 1.8072 \tabularnewline
232 & 10 & 13.1324 & -3.1324 \tabularnewline
233 & 16 & 11.3239 & 4.67613 \tabularnewline
234 & 18 & 15.7017 & 2.29834 \tabularnewline
235 & 13 & 13.6986 & -0.698625 \tabularnewline
236 & 11 & 13.1953 & -2.19532 \tabularnewline
237 & 4 & 10.9144 & -6.91442 \tabularnewline
238 & 13 & 14.0864 & -1.08639 \tabularnewline
239 & 16 & 14.1114 & 1.88856 \tabularnewline
240 & 10 & 11.581 & -1.58104 \tabularnewline
241 & 12 & 12.1458 & -0.14579 \tabularnewline
242 & 12 & 13.3223 & -1.32233 \tabularnewline
243 & 10 & 8.80196 & 1.19804 \tabularnewline
244 & 13 & 10.9676 & 2.0324 \tabularnewline
245 & 15 & 13.4825 & 1.51749 \tabularnewline
246 & 12 & 11.7701 & 0.229882 \tabularnewline
247 & 14 & 12.6702 & 1.32983 \tabularnewline
248 & 10 & 12.2934 & -2.29345 \tabularnewline
249 & 12 & 10.6014 & 1.39859 \tabularnewline
250 & 12 & 11.5046 & 0.495414 \tabularnewline
251 & 11 & 11.6933 & -0.693327 \tabularnewline
252 & 10 & 11.497 & -1.49703 \tabularnewline
253 & 12 & 11.2278 & 0.772228 \tabularnewline
254 & 16 & 12.633 & 3.36697 \tabularnewline
255 & 12 & 13.1033 & -1.10331 \tabularnewline
256 & 14 & 13.6115 & 0.38849 \tabularnewline
257 & 16 & 14.138 & 1.86198 \tabularnewline
258 & 14 & 11.4513 & 2.5487 \tabularnewline
259 & 13 & 13.9884 & -0.988366 \tabularnewline
260 & 4 & 9.27855 & -5.27855 \tabularnewline
261 & 15 & 13.4908 & 1.50918 \tabularnewline
262 & 11 & 14.7054 & -3.70545 \tabularnewline
263 & 11 & 11.1004 & -0.100382 \tabularnewline
264 & 14 & 12.576 & 1.424 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221924&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]16.132[/C][C]-3.132[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.773[/C][C]0.226987[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]17.0643[/C][C]1.93568[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]12.1954[/C][C]2.80456[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.418[/C][C]-2.41803[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.8802[/C][C]-1.88023[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.3074[/C][C]3.69261[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]17.0994[/C][C]-2.09941[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]16.0717[/C][C]-2.07169[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.4709[/C][C]0.529072[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]15.0048[/C][C]0.995168[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.1898[/C][C]-0.189823[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.5299[/C][C]0.470117[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.5015[/C][C]0.498538[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]17.985[/C][C]-0.984972[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.4712[/C][C]-0.471169[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.6115[/C][C]0.388483[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.4151[/C][C]3.58493[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.4899[/C][C]2.51011[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.5511[/C][C]0.448882[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.3609[/C][C]0.63913[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]15.1405[/C][C]0.859494[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.4738[/C][C]2.52619[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]15.0882[/C][C]0.911758[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]16.149[/C][C]0.851015[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.254[/C][C]0.745974[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.9708[/C][C]1.02924[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.7314[/C][C]-1.7314[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.7144[/C][C]0.285552[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.1777[/C][C]-0.177698[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.7272[/C][C]-0.727157[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.8196[/C][C]-0.819627[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.79[/C][C]-0.790028[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.9092[/C][C]0.090767[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.5242[/C][C]-1.52418[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.9949[/C][C]-2.99493[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]13.036[/C][C]-3.03602[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.7159[/C][C]-1.71591[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.5189[/C][C]1.48107[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.464[/C][C]1.53603[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.6923[/C][C]1.30774[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.6917[/C][C]-1.69174[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.424[/C][C]2.57601[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.1268[/C][C]-0.126833[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.4278[/C][C]-0.427776[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.4769[/C][C]-4.4769[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.5017[/C][C]-2.50167[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.0873[/C][C]-0.0872734[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.4345[/C][C]0.565501[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.5958[/C][C]-1.59575[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]16.947[/C][C]-0.947006[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.1029[/C][C]-0.102906[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]14.9814[/C][C]-2.98144[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.7858[/C][C]0.214207[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]11.3564[/C][C]-2.35637[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.3349[/C][C]1.66507[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.7946[/C][C]0.205419[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.4209[/C][C]0.579053[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]15.083[/C][C]-0.0830125[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.1513[/C][C]1.84873[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.507[/C][C]0.493039[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.614[/C][C]0.385981[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.481[/C][C]-0.481005[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.6386[/C][C]-0.638612[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.2161[/C][C]0.783934[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]16.1284[/C][C]0.871641[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.366[/C][C]1.63402[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.5461[/C][C]3.45393[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.986[/C][C]-3.98596[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.7236[/C][C]0.27641[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.4365[/C][C]-3.43646[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.9825[/C][C]-0.982476[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]17.0159[/C][C]0.984117[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.2455[/C][C]0.754512[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.3257[/C][C]0.674279[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.5758[/C][C]3.42425[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.4688[/C][C]-0.46879[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.5522[/C][C]1.44778[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]15.2614[/C][C]-2.2614[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.1965[/C][C]0.803547[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.7574[/C][C]0.24255[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.7769[/C][C]0.223148[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.7299[/C][C]-0.729877[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.93[/C][C]0.0700298[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]14.2149[/C][C]1.78506[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.2366[/C][C]-0.236631[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.4094[/C][C]0.590583[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.9[/C][C]1.09997[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.5575[/C][C]0.442476[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.9196[/C][C]-1.91958[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.78[/C][C]0.219977[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.863[/C][C]0.137035[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.1302[/C][C]-0.13018[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]15.0948[/C][C]-2.09484[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.8308[/C][C]1.16918[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.7987[/C][C]0.201267[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.7556[/C][C]2.24439[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.8344[/C][C]0.165573[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.4661[/C][C]-0.466133[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.0397[/C][C]-1.03971[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.6989[/C][C]1.30112[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.4607[/C][C]2.53935[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.2209[/C][C]0.779093[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]15.0049[/C][C]0.995068[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.8816[/C][C]-1.88163[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.7061[/C][C]1.29392[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.7299[/C][C]0.270053[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.3734[/C][C]1.62659[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.306[/C][C]-0.305983[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.2836[/C][C]0.716383[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]16.0108[/C][C]-0.0107717[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]15.0351[/C][C]1.96492[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.5406[/C][C]-1.54061[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.5773[/C][C]-2.57728[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.1499[/C][C]1.85008[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.849[/C][C]-1.84902[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.1714[/C][C]0.828563[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.789[/C][C]-1.78905[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.5215[/C][C]0.478505[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.4174[/C][C]-1.41739[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.3733[/C][C]0.626735[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.824[/C][C]-2.82399[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]16.8207[/C][C]-0.820673[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.8152[/C][C]-0.815194[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.7759[/C][C]-0.775886[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.6563[/C][C]0.343682[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.5135[/C][C]1.48645[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]13.9562[/C][C]1.04381[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.665[/C][C]-2.66497[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.9484[/C][C]2.05159[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.6993[/C][C]-3.69935[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4787[/C][C]2.52127[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.1171[/C][C]-2.11712[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.497[/C][C]-1.49698[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.0229[/C][C]-0.0228515[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]12.0783[/C][C]0.921716[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.418[/C][C]0.582025[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.4149[/C][C]-2.41488[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]12.9615[/C][C]-0.961539[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.3294[/C][C]-2.32943[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8198[/C][C]3.18017[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.6115[/C][C]1.38852[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]16.7647[/C][C]0.235264[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.0973[/C][C]1.90273[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.2326[/C][C]-3.23261[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.4232[/C][C]2.57682[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]14.8643[/C][C]-1.86431[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.7811[/C][C]1.2189[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.7594[/C][C]0.240626[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.8479[/C][C]-2.84795[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]15.8571[/C][C]-0.857125[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.8243[/C][C]2.17568[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.8178[/C][C]4.18221[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.1796[/C][C]1.82037[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.3604[/C][C]-2.36037[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.3564[/C][C]0.643603[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.64[/C][C]1.36004[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]13.7607[/C][C]1.23933[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.4778[/C][C]1.52222[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.6713[/C][C]-0.671269[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.5502[/C][C]0.449842[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.6952[/C][C]0.304814[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.5325[/C][C]-0.532527[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.2944[/C][C]0.705563[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.7803[/C][C]1.21973[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.696[/C][C]-1.69605[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.4098[/C][C]-0.409814[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.2824[/C][C]-3.2824[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.8697[/C][C]-1.86966[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.5277[/C][C]1.47227[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.5782[/C][C]1.42184[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.4054[/C][C]0.594604[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.9507[/C][C]-1.95073[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.4328[/C][C]-2.43276[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]14.9709[/C][C]-2.97089[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.6153[/C][C]0.384688[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.3485[/C][C]-0.348485[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.741[/C][C]-0.741024[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.8483[/C][C]0.151743[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.4364[/C][C]-1.43638[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]15.0574[/C][C]0.942577[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.5291[/C][C]-0.52909[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]16.7024[/C][C]2.29761[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.1861[/C][C]-0.186108[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.6098[/C][C]-6.60985[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.7949[/C][C]1.20512[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.489[/C][C]2.51103[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.4493[/C][C]-0.449279[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.5258[/C][C]-0.525825[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.484[/C][C]0.516008[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14.7297[/C][C]-0.729729[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.4573[/C][C]0.542659[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.79495[/C][C]2.20505[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.0582[/C][C]1.94176[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.6671[/C][C]-0.667127[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]15.006[/C][C]-0.00596155[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]12.9613[/C][C]3.03872[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.0217[/C][C]0.978304[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4655[/C][C]1.5345[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.536[/C][C]1.46397[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]14.0102[/C][C]1.98982[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.3505[/C][C]0.649485[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.4249[/C][C]-2.42489[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.4629[/C][C]-2.46295[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.7282[/C][C]2.27182[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.4392[/C][C]0.560792[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.4842[/C][C]1.5158[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]14.8639[/C][C]1.13608[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.5736[/C][C]-2.57355[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]13.933[/C][C]1.06701[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.1909[/C][C]-2.19094[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]15.7004[/C][C]-3.70037[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.0985[/C][C]0.901528[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.0898[/C][C]2.9102[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.4861[/C][C]1.51388[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.0448[/C][C]0.955209[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.5704[/C][C]2.42962[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.8899[/C][C]0.110123[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.8763[/C][C]1.12366[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.0825[/C][C]-0.0824598[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]14.5751[/C][C]-1.57506[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]13.986[/C][C]0.0139668[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.1866[/C][C]0.813397[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.0451[/C][C]-1.0451[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.5278[/C][C]0.472207[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.696[/C][C]-3.69605[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]13.6562[/C][C]0.343801[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]12.9001[/C][C]1.09993[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.1551[/C][C]-1.15511[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]12.8142[/C][C]-0.814199[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.1928[/C][C]1.8072[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.1324[/C][C]-3.1324[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.3239[/C][C]4.67613[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]15.7017[/C][C]2.29834[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]13.6986[/C][C]-0.698625[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.1953[/C][C]-2.19532[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]10.9144[/C][C]-6.91442[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.0864[/C][C]-1.08639[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.1114[/C][C]1.88856[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.581[/C][C]-1.58104[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.1458[/C][C]-0.14579[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.3223[/C][C]-1.32233[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.80196[/C][C]1.19804[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]10.9676[/C][C]2.0324[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.4825[/C][C]1.51749[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]11.7701[/C][C]0.229882[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]12.6702[/C][C]1.32983[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.2934[/C][C]-2.29345[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.6014[/C][C]1.39859[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.5046[/C][C]0.495414[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.6933[/C][C]-0.693327[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.497[/C][C]-1.49703[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.2278[/C][C]0.772228[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]12.633[/C][C]3.36697[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.1033[/C][C]-1.10331[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.6115[/C][C]0.38849[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.138[/C][C]1.86198[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.4513[/C][C]2.5487[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]13.9884[/C][C]-0.988366[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.27855[/C][C]-5.27855[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.4908[/C][C]1.50918[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]14.7054[/C][C]-3.70545[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.1004[/C][C]-0.100382[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]12.576[/C][C]1.424[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221924&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221924&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
11316.132-3.132
21615.7730.226987
31917.06431.93568
41512.19542.80456
51416.418-2.41803
61314.8802-1.88023
71915.30743.69261
81517.0994-2.09941
91416.0717-2.07169
101514.47090.529072
111615.00480.995168
121616.1898-0.189823
131615.52990.470117
141615.50150.498538
151717.985-0.984972
161515.4712-0.471169
171514.61150.388483
182016.41513.58493
191815.48992.51011
201615.55110.448882
211615.36090.63913
221615.14050.859494
231916.47382.52619
241615.08820.911758
251716.1490.851015
261716.2540.745974
271614.97081.02924
281516.7314-1.7314
291615.71440.285552
301414.1777-0.177698
311515.7272-0.727157
321212.8196-0.819627
331414.79-0.790028
341615.90920.090767
351415.5242-1.52418
361012.9949-2.99493
371013.036-3.03602
381415.7159-1.71591
391614.51891.48107
401614.4641.53603
411614.69231.30774
421415.6917-1.69174
432017.4242.57601
441414.1268-0.126833
451414.4278-0.427776
461115.4769-4.4769
471416.5017-2.50167
481515.0873-0.0872734
491615.43450.565501
501415.5958-1.59575
511616.947-0.947006
521414.1029-0.102906
531214.9814-2.98144
541615.78580.214207
55911.3564-2.35637
561412.33491.66507
571615.79460.205419
581615.42090.579053
591515.083-0.0830125
601614.15131.84873
611211.5070.493039
621615.6140.385981
631616.481-0.481005
641414.6386-0.638612
651615.21610.783934
661716.12840.871641
671816.3661.63402
681814.54613.45393
691215.986-3.98596
701615.72360.27641
711013.4365-3.43646
721414.9825-0.982476
731817.01590.984117
741817.24550.754512
751615.32570.674279
761713.57583.42425
771616.4688-0.46879
781614.55221.44778
791315.2614-2.2614
801615.19650.803547
811615.75740.24255
821615.77690.223148
831515.7299-0.729877
841514.930.0700298
851614.21491.78506
861414.2366-0.236631
871615.40940.590583
881614.91.09997
891514.55750.442476
901213.9196-1.91958
911716.780.219977
921615.8630.137035
931515.1302-0.13018
941315.0948-2.09484
951614.83081.16918
961615.79870.201267
971613.75562.24439
981615.83440.165573
991414.4661-0.466133
1001617.0397-1.03971
1011614.69891.30112
1022017.46072.53935
1031514.22090.779093
1041615.00490.995068
1051314.8816-1.88163
1061715.70611.29392
1071615.72990.270053
1081614.37341.62659
1091212.306-0.305983
1101615.28360.716383
1111616.0108-0.0107717
1121715.03511.96492
1131314.5406-1.54061
1141214.5773-2.57728
1151816.14991.85008
1161415.849-1.84902
1171413.17140.828563
1181314.789-1.78905
1191615.52150.478505
1201314.4174-1.41739
1211615.37330.626735
1221315.824-2.82399
1231616.8207-0.820673
1241515.8152-0.815194
1251616.7759-0.775886
1261514.65630.343682
1271715.51351.48645
1281513.95621.04381
1291214.665-2.66497
1301613.94842.05159
1311013.6993-3.69935
1321613.47872.52127
1331214.1171-2.11712
1341415.497-1.49698
1351515.0229-0.0228515
1361312.07830.921716
1371514.4180.582025
1381113.4149-2.41488
1391212.9615-0.961539
1401113.3294-2.32943
1411612.81983.18017
1421513.61151.38852
1431716.76470.235264
1441614.09731.90273
1451013.2326-3.23261
1461815.42322.57682
1471314.8643-1.86431
1481614.78111.2189
1491312.75940.240626
1501012.8479-2.84795
1511515.8571-0.857125
1521613.82432.17568
1531611.81784.18221
1541412.17961.82037
1551012.3604-2.36037
1561716.35640.643603
1571311.641.36004
1581513.76071.23933
1591614.47781.52222
1601212.6713-0.671269
1611312.55020.449842
1621312.69520.304814
1631212.5325-0.532527
1641716.29440.705563
1651513.78031.21973
1661011.696-1.69605
1671414.4098-0.409814
1681114.2824-3.2824
1691314.8697-1.86966
1701614.52771.47227
1711210.57821.42184
1721615.40540.594604
1731213.9507-1.95073
174911.4328-2.43276
1751214.9709-2.97089
1761514.61530.384688
1771212.3485-0.348485
1781212.741-0.741024
1791413.84830.151743
1801213.4364-1.43638
1811615.05740.942577
1821111.5291-0.52909
1831916.70242.29761
1841515.1861-0.186108
185814.6098-6.60985
1861614.79491.20512
1871714.4892.51103
1881212.4493-0.449279
1891111.5258-0.525825
1901110.4840.516008
1911414.7297-0.729729
1921615.45730.542659
193129.794952.20505
1941614.05821.94176
1951313.6671-0.667127
1961515.006-0.00596155
1971612.96133.03872
1981615.02170.978304
1991412.46551.5345
2001614.5361.46397
2011614.01021.98982
2021413.35050.649485
2031113.4249-2.42489
2041214.4629-2.46295
2051512.72822.27182
2061514.43920.560792
2071614.48421.5158
2081614.86391.13608
2091113.5736-2.57355
2101513.9331.06701
2111214.1909-2.19094
2121215.7004-3.70037
2131514.09850.901528
2141512.08982.9102
2151614.48611.51388
2161413.04480.955209
2171714.57042.42962
2181413.88990.110123
2191311.87631.12366
2201515.0825-0.0824598
2211314.5751-1.57506
2221413.9860.0139668
2231514.18660.813397
2241213.0451-1.0451
2251312.52780.472207
226811.696-3.69605
2271413.65620.343801
2281412.90011.09993
2291112.1551-1.15511
2301212.8142-0.814199
2311311.19281.8072
2321013.1324-3.1324
2331611.32394.67613
2341815.70172.29834
2351313.6986-0.698625
2361113.1953-2.19532
237410.9144-6.91442
2381314.0864-1.08639
2391614.11141.88856
2401011.581-1.58104
2411212.1458-0.14579
2421213.3223-1.32233
243108.801961.19804
2441310.96762.0324
2451513.48251.51749
2461211.77010.229882
2471412.67021.32983
2481012.2934-2.29345
2491210.60141.39859
2501211.50460.495414
2511111.6933-0.693327
2521011.497-1.49703
2531211.22780.772228
2541612.6333.36697
2551213.1033-1.10331
2561413.61150.38849
2571614.1381.86198
2581411.45132.5487
2591313.9884-0.988366
26049.27855-5.27855
2611513.49081.50918
2621114.7054-3.70545
2631111.1004-0.100382
2641412.5761.424






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.3098080.6196150.690192
140.2982460.5964920.701754
150.1808810.3617610.819119
160.137960.2759190.86204
170.143730.2874590.85627
180.2956730.5913450.704327
190.2459530.4919060.754047
200.1975320.3950630.802468
210.1546390.3092770.845361
220.181180.362360.81882
230.2923710.5847410.707629
240.4135630.8271260.586437
250.3438720.6877430.656128
260.2927450.5854910.707255
270.2802750.560550.719725
280.3963790.7927590.603621
290.3427050.6854110.657295
300.4535910.9071820.546409
310.409820.8196410.59018
320.37970.7594010.6203
330.3621990.7243980.637801
340.3230610.6461230.676939
350.2774190.5548390.722581
360.4125990.8251990.587401
370.4404870.8809730.559513
380.4147510.8295020.585249
390.4589970.9179930.541003
400.4380770.8761550.561923
410.3976070.7952130.602393
420.3570110.7140220.642989
430.3758030.7516070.624197
440.3262190.6524380.673781
450.2972290.5944570.702771
460.4777680.9555350.522232
470.5669830.8660340.433017
480.5236940.9526110.476306
490.5470910.9058190.452909
500.5197960.9604080.480204
510.4743620.9487240.525638
520.4323250.8646510.567675
530.4325850.8651710.567415
540.3893690.7787370.610631
550.3778090.7556170.622191
560.3735940.7471880.626406
570.3328520.6657050.667148
580.3129810.6259620.687019
590.2817260.5634520.718274
600.3015550.603110.698445
610.2767870.5535740.723213
620.2505080.5010160.749492
630.2206830.4413660.779317
640.1917080.3834170.808292
650.1693680.3387360.830632
660.1437840.2875680.856216
670.1245280.2490560.875472
680.1507140.3014280.849286
690.3438890.6877770.656111
700.3056430.6112870.694357
710.4568780.9137550.543122
720.4199290.8398570.580071
730.410250.8205010.58975
740.3894760.7789520.610524
750.3530670.7061340.646933
760.4024790.8049570.597521
770.367580.7351610.63242
780.3389470.6778940.661053
790.3663870.7327740.633613
800.3344410.6688810.665559
810.302660.6053210.69734
820.2687120.5374240.731288
830.2434650.486930.756535
840.2133950.426790.786605
850.2044740.4089470.795526
860.1775890.3551780.822411
870.1551740.3103480.844826
880.1411340.2822690.858866
890.1209890.2419770.879011
900.1202550.240510.879745
910.1024790.2049580.897521
920.08914610.1782920.910854
930.07551080.1510220.924489
940.07953270.1590650.920467
950.07183280.1436660.928167
960.05977190.1195440.940228
970.06365130.1273030.936349
980.05257290.1051460.947427
990.04334850.08669710.956651
1000.03753920.07507850.962461
1010.03299040.06598080.96701
1020.03983940.07967880.960161
1030.03354910.06709820.966451
1040.03052020.06104030.96948
1050.03570510.07141030.964295
1060.0312650.06253010.968735
1070.02530970.05061940.97469
1080.0246050.04920990.975395
1090.01984060.03968130.980159
1100.01624010.03248010.98376
1110.01281130.02562260.987189
1120.01322590.02645180.986774
1130.01212230.02424460.987878
1140.01698040.03396080.98302
1150.01619280.03238550.983807
1160.01548670.03097350.984513
1170.01279340.02558680.987207
1180.01269350.0253870.987307
1190.01012740.02025480.989873
1200.008949420.01789880.991051
1210.007135530.01427110.992864
1220.01030090.02060180.989699
1230.008418230.01683650.991582
1240.007014960.01402990.992985
1250.005612310.01122460.994388
1260.004373090.008746180.995627
1270.004114880.008229760.995885
1280.003371340.006742670.996629
1290.004595190.009190380.995405
1300.005208330.01041670.994792
1310.01065720.02131430.989343
1320.01316380.02632760.986836
1330.01405990.02811970.98594
1340.01302660.02605330.986973
1350.01026830.02053660.989732
1360.008693010.0173860.991307
1370.006919310.01383860.993081
1380.008731240.01746250.991269
1390.007445630.01489130.992554
1400.009115020.018230.990885
1410.01492450.0298490.985076
1420.0142880.02857610.985712
1430.01178750.0235750.988212
1440.01174250.02348490.988258
1450.02085450.0417090.979145
1460.02489670.04979330.975103
1470.02642360.05284720.973576
1480.02308860.04617710.976911
1490.01857540.03715080.981425
1500.02658260.05316530.973417
1510.02268520.04537040.977315
1520.02527520.05055040.974725
1530.05101440.1020290.948986
1540.04999730.09999470.950003
1550.05905630.1181130.940944
1560.05005290.1001060.949947
1570.04423790.08847570.955762
1580.03797770.07595540.962022
1590.03675450.07350910.963245
1600.03105940.06211880.968941
1610.0251750.05035010.974825
1620.02033150.04066310.979668
1630.01688680.03377370.983113
1640.01408510.02817010.985915
1650.01203780.02407550.987962
1660.0127190.02543810.987281
1670.01015660.02031330.989843
1680.01572540.03145080.984275
1690.01608870.03217740.983911
1700.01500080.03000170.984999
1710.01358950.0271790.98641
1720.01083940.02167880.989161
1730.01084420.02168830.989156
1740.01259650.02519290.987404
1750.01663110.03326220.983369
1760.01324810.02649610.986752
1770.01045290.02090580.989547
1780.00876860.01753720.991231
1790.006752180.01350440.993248
1800.005952280.01190460.994048
1810.004820210.009640430.99518
1820.003708350.007416690.996292
1830.003986920.007973850.996013
1840.003009610.006019220.99699
1850.08534150.1706830.914659
1860.07602150.1520430.923978
1870.08374140.1674830.916259
1880.07004030.1400810.92996
1890.06228760.1245750.937712
1900.05174480.103490.948255
1910.04773150.0954630.952269
1920.03922580.07845150.960774
1930.04002440.08004870.959976
1940.04030470.08060940.959695
1950.03470060.06940120.965299
1960.02776620.05553230.972234
1970.03510520.07021040.964895
1980.02850140.05700280.971499
1990.02553140.05106290.974469
2000.02181960.04363920.97818
2010.02032690.04065390.979673
2020.017090.03417990.98291
2030.02246440.04492880.977536
2040.02615490.05230980.973845
2050.0273220.0546440.972678
2060.0212570.0425140.978743
2070.02026530.04053060.979735
2080.01646880.03293770.983531
2090.01832730.03665460.981673
2100.0145010.0290020.985499
2110.01661830.03323660.983382
2120.02709010.05418020.97291
2130.02091310.04182620.979087
2140.02711390.05422790.972886
2150.02287250.04574510.977127
2160.0175320.0350640.982468
2170.0192560.03851190.980744
2180.01609810.03219610.983902
2190.01487380.02974760.985126
2200.01124520.02249050.988755
2210.009261830.01852370.990738
2220.006565630.01313130.993434
2230.004982040.009964070.995018
2240.003705870.007411730.996294
2250.003129110.006258210.996871
2260.007308020.0146160.992692
2270.005656590.01131320.994343
2280.004130040.008260070.99587
2290.002900960.005801910.997099
2300.002100070.004200130.9979
2310.001874350.00374870.998126
2320.004452680.008905370.995547
2330.01865140.03730270.981349
2340.02870560.05741120.971294
2350.02024080.04048160.979759
2360.01663850.0332770.983361
2370.1588120.3176230.841188
2380.1220540.2441070.877946
2390.09960490.199210.900395
2400.07508580.1501720.924914
2410.06464260.1292850.935357
2420.1024910.2049810.897509
2430.08149170.1629830.918508
2440.08426830.1685370.915732
2450.06658710.1331740.933413
2460.05443570.1088710.945564
2470.03299080.06598150.967009
2480.02663920.05327830.973361
2490.02249140.04498270.977509
2500.06644730.1328950.933553
2510.04869720.09739450.951303

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.309808 & 0.619615 & 0.690192 \tabularnewline
14 & 0.298246 & 0.596492 & 0.701754 \tabularnewline
15 & 0.180881 & 0.361761 & 0.819119 \tabularnewline
16 & 0.13796 & 0.275919 & 0.86204 \tabularnewline
17 & 0.14373 & 0.287459 & 0.85627 \tabularnewline
18 & 0.295673 & 0.591345 & 0.704327 \tabularnewline
19 & 0.245953 & 0.491906 & 0.754047 \tabularnewline
20 & 0.197532 & 0.395063 & 0.802468 \tabularnewline
21 & 0.154639 & 0.309277 & 0.845361 \tabularnewline
22 & 0.18118 & 0.36236 & 0.81882 \tabularnewline
23 & 0.292371 & 0.584741 & 0.707629 \tabularnewline
24 & 0.413563 & 0.827126 & 0.586437 \tabularnewline
25 & 0.343872 & 0.687743 & 0.656128 \tabularnewline
26 & 0.292745 & 0.585491 & 0.707255 \tabularnewline
27 & 0.280275 & 0.56055 & 0.719725 \tabularnewline
28 & 0.396379 & 0.792759 & 0.603621 \tabularnewline
29 & 0.342705 & 0.685411 & 0.657295 \tabularnewline
30 & 0.453591 & 0.907182 & 0.546409 \tabularnewline
31 & 0.40982 & 0.819641 & 0.59018 \tabularnewline
32 & 0.3797 & 0.759401 & 0.6203 \tabularnewline
33 & 0.362199 & 0.724398 & 0.637801 \tabularnewline
34 & 0.323061 & 0.646123 & 0.676939 \tabularnewline
35 & 0.277419 & 0.554839 & 0.722581 \tabularnewline
36 & 0.412599 & 0.825199 & 0.587401 \tabularnewline
37 & 0.440487 & 0.880973 & 0.559513 \tabularnewline
38 & 0.414751 & 0.829502 & 0.585249 \tabularnewline
39 & 0.458997 & 0.917993 & 0.541003 \tabularnewline
40 & 0.438077 & 0.876155 & 0.561923 \tabularnewline
41 & 0.397607 & 0.795213 & 0.602393 \tabularnewline
42 & 0.357011 & 0.714022 & 0.642989 \tabularnewline
43 & 0.375803 & 0.751607 & 0.624197 \tabularnewline
44 & 0.326219 & 0.652438 & 0.673781 \tabularnewline
45 & 0.297229 & 0.594457 & 0.702771 \tabularnewline
46 & 0.477768 & 0.955535 & 0.522232 \tabularnewline
47 & 0.566983 & 0.866034 & 0.433017 \tabularnewline
48 & 0.523694 & 0.952611 & 0.476306 \tabularnewline
49 & 0.547091 & 0.905819 & 0.452909 \tabularnewline
50 & 0.519796 & 0.960408 & 0.480204 \tabularnewline
51 & 0.474362 & 0.948724 & 0.525638 \tabularnewline
52 & 0.432325 & 0.864651 & 0.567675 \tabularnewline
53 & 0.432585 & 0.865171 & 0.567415 \tabularnewline
54 & 0.389369 & 0.778737 & 0.610631 \tabularnewline
55 & 0.377809 & 0.755617 & 0.622191 \tabularnewline
56 & 0.373594 & 0.747188 & 0.626406 \tabularnewline
57 & 0.332852 & 0.665705 & 0.667148 \tabularnewline
58 & 0.312981 & 0.625962 & 0.687019 \tabularnewline
59 & 0.281726 & 0.563452 & 0.718274 \tabularnewline
60 & 0.301555 & 0.60311 & 0.698445 \tabularnewline
61 & 0.276787 & 0.553574 & 0.723213 \tabularnewline
62 & 0.250508 & 0.501016 & 0.749492 \tabularnewline
63 & 0.220683 & 0.441366 & 0.779317 \tabularnewline
64 & 0.191708 & 0.383417 & 0.808292 \tabularnewline
65 & 0.169368 & 0.338736 & 0.830632 \tabularnewline
66 & 0.143784 & 0.287568 & 0.856216 \tabularnewline
67 & 0.124528 & 0.249056 & 0.875472 \tabularnewline
68 & 0.150714 & 0.301428 & 0.849286 \tabularnewline
69 & 0.343889 & 0.687777 & 0.656111 \tabularnewline
70 & 0.305643 & 0.611287 & 0.694357 \tabularnewline
71 & 0.456878 & 0.913755 & 0.543122 \tabularnewline
72 & 0.419929 & 0.839857 & 0.580071 \tabularnewline
73 & 0.41025 & 0.820501 & 0.58975 \tabularnewline
74 & 0.389476 & 0.778952 & 0.610524 \tabularnewline
75 & 0.353067 & 0.706134 & 0.646933 \tabularnewline
76 & 0.402479 & 0.804957 & 0.597521 \tabularnewline
77 & 0.36758 & 0.735161 & 0.63242 \tabularnewline
78 & 0.338947 & 0.677894 & 0.661053 \tabularnewline
79 & 0.366387 & 0.732774 & 0.633613 \tabularnewline
80 & 0.334441 & 0.668881 & 0.665559 \tabularnewline
81 & 0.30266 & 0.605321 & 0.69734 \tabularnewline
82 & 0.268712 & 0.537424 & 0.731288 \tabularnewline
83 & 0.243465 & 0.48693 & 0.756535 \tabularnewline
84 & 0.213395 & 0.42679 & 0.786605 \tabularnewline
85 & 0.204474 & 0.408947 & 0.795526 \tabularnewline
86 & 0.177589 & 0.355178 & 0.822411 \tabularnewline
87 & 0.155174 & 0.310348 & 0.844826 \tabularnewline
88 & 0.141134 & 0.282269 & 0.858866 \tabularnewline
89 & 0.120989 & 0.241977 & 0.879011 \tabularnewline
90 & 0.120255 & 0.24051 & 0.879745 \tabularnewline
91 & 0.102479 & 0.204958 & 0.897521 \tabularnewline
92 & 0.0891461 & 0.178292 & 0.910854 \tabularnewline
93 & 0.0755108 & 0.151022 & 0.924489 \tabularnewline
94 & 0.0795327 & 0.159065 & 0.920467 \tabularnewline
95 & 0.0718328 & 0.143666 & 0.928167 \tabularnewline
96 & 0.0597719 & 0.119544 & 0.940228 \tabularnewline
97 & 0.0636513 & 0.127303 & 0.936349 \tabularnewline
98 & 0.0525729 & 0.105146 & 0.947427 \tabularnewline
99 & 0.0433485 & 0.0866971 & 0.956651 \tabularnewline
100 & 0.0375392 & 0.0750785 & 0.962461 \tabularnewline
101 & 0.0329904 & 0.0659808 & 0.96701 \tabularnewline
102 & 0.0398394 & 0.0796788 & 0.960161 \tabularnewline
103 & 0.0335491 & 0.0670982 & 0.966451 \tabularnewline
104 & 0.0305202 & 0.0610403 & 0.96948 \tabularnewline
105 & 0.0357051 & 0.0714103 & 0.964295 \tabularnewline
106 & 0.031265 & 0.0625301 & 0.968735 \tabularnewline
107 & 0.0253097 & 0.0506194 & 0.97469 \tabularnewline
108 & 0.024605 & 0.0492099 & 0.975395 \tabularnewline
109 & 0.0198406 & 0.0396813 & 0.980159 \tabularnewline
110 & 0.0162401 & 0.0324801 & 0.98376 \tabularnewline
111 & 0.0128113 & 0.0256226 & 0.987189 \tabularnewline
112 & 0.0132259 & 0.0264518 & 0.986774 \tabularnewline
113 & 0.0121223 & 0.0242446 & 0.987878 \tabularnewline
114 & 0.0169804 & 0.0339608 & 0.98302 \tabularnewline
115 & 0.0161928 & 0.0323855 & 0.983807 \tabularnewline
116 & 0.0154867 & 0.0309735 & 0.984513 \tabularnewline
117 & 0.0127934 & 0.0255868 & 0.987207 \tabularnewline
118 & 0.0126935 & 0.025387 & 0.987307 \tabularnewline
119 & 0.0101274 & 0.0202548 & 0.989873 \tabularnewline
120 & 0.00894942 & 0.0178988 & 0.991051 \tabularnewline
121 & 0.00713553 & 0.0142711 & 0.992864 \tabularnewline
122 & 0.0103009 & 0.0206018 & 0.989699 \tabularnewline
123 & 0.00841823 & 0.0168365 & 0.991582 \tabularnewline
124 & 0.00701496 & 0.0140299 & 0.992985 \tabularnewline
125 & 0.00561231 & 0.0112246 & 0.994388 \tabularnewline
126 & 0.00437309 & 0.00874618 & 0.995627 \tabularnewline
127 & 0.00411488 & 0.00822976 & 0.995885 \tabularnewline
128 & 0.00337134 & 0.00674267 & 0.996629 \tabularnewline
129 & 0.00459519 & 0.00919038 & 0.995405 \tabularnewline
130 & 0.00520833 & 0.0104167 & 0.994792 \tabularnewline
131 & 0.0106572 & 0.0213143 & 0.989343 \tabularnewline
132 & 0.0131638 & 0.0263276 & 0.986836 \tabularnewline
133 & 0.0140599 & 0.0281197 & 0.98594 \tabularnewline
134 & 0.0130266 & 0.0260533 & 0.986973 \tabularnewline
135 & 0.0102683 & 0.0205366 & 0.989732 \tabularnewline
136 & 0.00869301 & 0.017386 & 0.991307 \tabularnewline
137 & 0.00691931 & 0.0138386 & 0.993081 \tabularnewline
138 & 0.00873124 & 0.0174625 & 0.991269 \tabularnewline
139 & 0.00744563 & 0.0148913 & 0.992554 \tabularnewline
140 & 0.00911502 & 0.01823 & 0.990885 \tabularnewline
141 & 0.0149245 & 0.029849 & 0.985076 \tabularnewline
142 & 0.014288 & 0.0285761 & 0.985712 \tabularnewline
143 & 0.0117875 & 0.023575 & 0.988212 \tabularnewline
144 & 0.0117425 & 0.0234849 & 0.988258 \tabularnewline
145 & 0.0208545 & 0.041709 & 0.979145 \tabularnewline
146 & 0.0248967 & 0.0497933 & 0.975103 \tabularnewline
147 & 0.0264236 & 0.0528472 & 0.973576 \tabularnewline
148 & 0.0230886 & 0.0461771 & 0.976911 \tabularnewline
149 & 0.0185754 & 0.0371508 & 0.981425 \tabularnewline
150 & 0.0265826 & 0.0531653 & 0.973417 \tabularnewline
151 & 0.0226852 & 0.0453704 & 0.977315 \tabularnewline
152 & 0.0252752 & 0.0505504 & 0.974725 \tabularnewline
153 & 0.0510144 & 0.102029 & 0.948986 \tabularnewline
154 & 0.0499973 & 0.0999947 & 0.950003 \tabularnewline
155 & 0.0590563 & 0.118113 & 0.940944 \tabularnewline
156 & 0.0500529 & 0.100106 & 0.949947 \tabularnewline
157 & 0.0442379 & 0.0884757 & 0.955762 \tabularnewline
158 & 0.0379777 & 0.0759554 & 0.962022 \tabularnewline
159 & 0.0367545 & 0.0735091 & 0.963245 \tabularnewline
160 & 0.0310594 & 0.0621188 & 0.968941 \tabularnewline
161 & 0.025175 & 0.0503501 & 0.974825 \tabularnewline
162 & 0.0203315 & 0.0406631 & 0.979668 \tabularnewline
163 & 0.0168868 & 0.0337737 & 0.983113 \tabularnewline
164 & 0.0140851 & 0.0281701 & 0.985915 \tabularnewline
165 & 0.0120378 & 0.0240755 & 0.987962 \tabularnewline
166 & 0.012719 & 0.0254381 & 0.987281 \tabularnewline
167 & 0.0101566 & 0.0203133 & 0.989843 \tabularnewline
168 & 0.0157254 & 0.0314508 & 0.984275 \tabularnewline
169 & 0.0160887 & 0.0321774 & 0.983911 \tabularnewline
170 & 0.0150008 & 0.0300017 & 0.984999 \tabularnewline
171 & 0.0135895 & 0.027179 & 0.98641 \tabularnewline
172 & 0.0108394 & 0.0216788 & 0.989161 \tabularnewline
173 & 0.0108442 & 0.0216883 & 0.989156 \tabularnewline
174 & 0.0125965 & 0.0251929 & 0.987404 \tabularnewline
175 & 0.0166311 & 0.0332622 & 0.983369 \tabularnewline
176 & 0.0132481 & 0.0264961 & 0.986752 \tabularnewline
177 & 0.0104529 & 0.0209058 & 0.989547 \tabularnewline
178 & 0.0087686 & 0.0175372 & 0.991231 \tabularnewline
179 & 0.00675218 & 0.0135044 & 0.993248 \tabularnewline
180 & 0.00595228 & 0.0119046 & 0.994048 \tabularnewline
181 & 0.00482021 & 0.00964043 & 0.99518 \tabularnewline
182 & 0.00370835 & 0.00741669 & 0.996292 \tabularnewline
183 & 0.00398692 & 0.00797385 & 0.996013 \tabularnewline
184 & 0.00300961 & 0.00601922 & 0.99699 \tabularnewline
185 & 0.0853415 & 0.170683 & 0.914659 \tabularnewline
186 & 0.0760215 & 0.152043 & 0.923978 \tabularnewline
187 & 0.0837414 & 0.167483 & 0.916259 \tabularnewline
188 & 0.0700403 & 0.140081 & 0.92996 \tabularnewline
189 & 0.0622876 & 0.124575 & 0.937712 \tabularnewline
190 & 0.0517448 & 0.10349 & 0.948255 \tabularnewline
191 & 0.0477315 & 0.095463 & 0.952269 \tabularnewline
192 & 0.0392258 & 0.0784515 & 0.960774 \tabularnewline
193 & 0.0400244 & 0.0800487 & 0.959976 \tabularnewline
194 & 0.0403047 & 0.0806094 & 0.959695 \tabularnewline
195 & 0.0347006 & 0.0694012 & 0.965299 \tabularnewline
196 & 0.0277662 & 0.0555323 & 0.972234 \tabularnewline
197 & 0.0351052 & 0.0702104 & 0.964895 \tabularnewline
198 & 0.0285014 & 0.0570028 & 0.971499 \tabularnewline
199 & 0.0255314 & 0.0510629 & 0.974469 \tabularnewline
200 & 0.0218196 & 0.0436392 & 0.97818 \tabularnewline
201 & 0.0203269 & 0.0406539 & 0.979673 \tabularnewline
202 & 0.01709 & 0.0341799 & 0.98291 \tabularnewline
203 & 0.0224644 & 0.0449288 & 0.977536 \tabularnewline
204 & 0.0261549 & 0.0523098 & 0.973845 \tabularnewline
205 & 0.027322 & 0.054644 & 0.972678 \tabularnewline
206 & 0.021257 & 0.042514 & 0.978743 \tabularnewline
207 & 0.0202653 & 0.0405306 & 0.979735 \tabularnewline
208 & 0.0164688 & 0.0329377 & 0.983531 \tabularnewline
209 & 0.0183273 & 0.0366546 & 0.981673 \tabularnewline
210 & 0.014501 & 0.029002 & 0.985499 \tabularnewline
211 & 0.0166183 & 0.0332366 & 0.983382 \tabularnewline
212 & 0.0270901 & 0.0541802 & 0.97291 \tabularnewline
213 & 0.0209131 & 0.0418262 & 0.979087 \tabularnewline
214 & 0.0271139 & 0.0542279 & 0.972886 \tabularnewline
215 & 0.0228725 & 0.0457451 & 0.977127 \tabularnewline
216 & 0.017532 & 0.035064 & 0.982468 \tabularnewline
217 & 0.019256 & 0.0385119 & 0.980744 \tabularnewline
218 & 0.0160981 & 0.0321961 & 0.983902 \tabularnewline
219 & 0.0148738 & 0.0297476 & 0.985126 \tabularnewline
220 & 0.0112452 & 0.0224905 & 0.988755 \tabularnewline
221 & 0.00926183 & 0.0185237 & 0.990738 \tabularnewline
222 & 0.00656563 & 0.0131313 & 0.993434 \tabularnewline
223 & 0.00498204 & 0.00996407 & 0.995018 \tabularnewline
224 & 0.00370587 & 0.00741173 & 0.996294 \tabularnewline
225 & 0.00312911 & 0.00625821 & 0.996871 \tabularnewline
226 & 0.00730802 & 0.014616 & 0.992692 \tabularnewline
227 & 0.00565659 & 0.0113132 & 0.994343 \tabularnewline
228 & 0.00413004 & 0.00826007 & 0.99587 \tabularnewline
229 & 0.00290096 & 0.00580191 & 0.997099 \tabularnewline
230 & 0.00210007 & 0.00420013 & 0.9979 \tabularnewline
231 & 0.00187435 & 0.0037487 & 0.998126 \tabularnewline
232 & 0.00445268 & 0.00890537 & 0.995547 \tabularnewline
233 & 0.0186514 & 0.0373027 & 0.981349 \tabularnewline
234 & 0.0287056 & 0.0574112 & 0.971294 \tabularnewline
235 & 0.0202408 & 0.0404816 & 0.979759 \tabularnewline
236 & 0.0166385 & 0.033277 & 0.983361 \tabularnewline
237 & 0.158812 & 0.317623 & 0.841188 \tabularnewline
238 & 0.122054 & 0.244107 & 0.877946 \tabularnewline
239 & 0.0996049 & 0.19921 & 0.900395 \tabularnewline
240 & 0.0750858 & 0.150172 & 0.924914 \tabularnewline
241 & 0.0646426 & 0.129285 & 0.935357 \tabularnewline
242 & 0.102491 & 0.204981 & 0.897509 \tabularnewline
243 & 0.0814917 & 0.162983 & 0.918508 \tabularnewline
244 & 0.0842683 & 0.168537 & 0.915732 \tabularnewline
245 & 0.0665871 & 0.133174 & 0.933413 \tabularnewline
246 & 0.0544357 & 0.108871 & 0.945564 \tabularnewline
247 & 0.0329908 & 0.0659815 & 0.967009 \tabularnewline
248 & 0.0266392 & 0.0532783 & 0.973361 \tabularnewline
249 & 0.0224914 & 0.0449827 & 0.977509 \tabularnewline
250 & 0.0664473 & 0.132895 & 0.933553 \tabularnewline
251 & 0.0486972 & 0.0973945 & 0.951303 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221924&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]13[/C][C]0.309808[/C][C]0.619615[/C][C]0.690192[/C][/ROW]
[ROW][C]14[/C][C]0.298246[/C][C]0.596492[/C][C]0.701754[/C][/ROW]
[ROW][C]15[/C][C]0.180881[/C][C]0.361761[/C][C]0.819119[/C][/ROW]
[ROW][C]16[/C][C]0.13796[/C][C]0.275919[/C][C]0.86204[/C][/ROW]
[ROW][C]17[/C][C]0.14373[/C][C]0.287459[/C][C]0.85627[/C][/ROW]
[ROW][C]18[/C][C]0.295673[/C][C]0.591345[/C][C]0.704327[/C][/ROW]
[ROW][C]19[/C][C]0.245953[/C][C]0.491906[/C][C]0.754047[/C][/ROW]
[ROW][C]20[/C][C]0.197532[/C][C]0.395063[/C][C]0.802468[/C][/ROW]
[ROW][C]21[/C][C]0.154639[/C][C]0.309277[/C][C]0.845361[/C][/ROW]
[ROW][C]22[/C][C]0.18118[/C][C]0.36236[/C][C]0.81882[/C][/ROW]
[ROW][C]23[/C][C]0.292371[/C][C]0.584741[/C][C]0.707629[/C][/ROW]
[ROW][C]24[/C][C]0.413563[/C][C]0.827126[/C][C]0.586437[/C][/ROW]
[ROW][C]25[/C][C]0.343872[/C][C]0.687743[/C][C]0.656128[/C][/ROW]
[ROW][C]26[/C][C]0.292745[/C][C]0.585491[/C][C]0.707255[/C][/ROW]
[ROW][C]27[/C][C]0.280275[/C][C]0.56055[/C][C]0.719725[/C][/ROW]
[ROW][C]28[/C][C]0.396379[/C][C]0.792759[/C][C]0.603621[/C][/ROW]
[ROW][C]29[/C][C]0.342705[/C][C]0.685411[/C][C]0.657295[/C][/ROW]
[ROW][C]30[/C][C]0.453591[/C][C]0.907182[/C][C]0.546409[/C][/ROW]
[ROW][C]31[/C][C]0.40982[/C][C]0.819641[/C][C]0.59018[/C][/ROW]
[ROW][C]32[/C][C]0.3797[/C][C]0.759401[/C][C]0.6203[/C][/ROW]
[ROW][C]33[/C][C]0.362199[/C][C]0.724398[/C][C]0.637801[/C][/ROW]
[ROW][C]34[/C][C]0.323061[/C][C]0.646123[/C][C]0.676939[/C][/ROW]
[ROW][C]35[/C][C]0.277419[/C][C]0.554839[/C][C]0.722581[/C][/ROW]
[ROW][C]36[/C][C]0.412599[/C][C]0.825199[/C][C]0.587401[/C][/ROW]
[ROW][C]37[/C][C]0.440487[/C][C]0.880973[/C][C]0.559513[/C][/ROW]
[ROW][C]38[/C][C]0.414751[/C][C]0.829502[/C][C]0.585249[/C][/ROW]
[ROW][C]39[/C][C]0.458997[/C][C]0.917993[/C][C]0.541003[/C][/ROW]
[ROW][C]40[/C][C]0.438077[/C][C]0.876155[/C][C]0.561923[/C][/ROW]
[ROW][C]41[/C][C]0.397607[/C][C]0.795213[/C][C]0.602393[/C][/ROW]
[ROW][C]42[/C][C]0.357011[/C][C]0.714022[/C][C]0.642989[/C][/ROW]
[ROW][C]43[/C][C]0.375803[/C][C]0.751607[/C][C]0.624197[/C][/ROW]
[ROW][C]44[/C][C]0.326219[/C][C]0.652438[/C][C]0.673781[/C][/ROW]
[ROW][C]45[/C][C]0.297229[/C][C]0.594457[/C][C]0.702771[/C][/ROW]
[ROW][C]46[/C][C]0.477768[/C][C]0.955535[/C][C]0.522232[/C][/ROW]
[ROW][C]47[/C][C]0.566983[/C][C]0.866034[/C][C]0.433017[/C][/ROW]
[ROW][C]48[/C][C]0.523694[/C][C]0.952611[/C][C]0.476306[/C][/ROW]
[ROW][C]49[/C][C]0.547091[/C][C]0.905819[/C][C]0.452909[/C][/ROW]
[ROW][C]50[/C][C]0.519796[/C][C]0.960408[/C][C]0.480204[/C][/ROW]
[ROW][C]51[/C][C]0.474362[/C][C]0.948724[/C][C]0.525638[/C][/ROW]
[ROW][C]52[/C][C]0.432325[/C][C]0.864651[/C][C]0.567675[/C][/ROW]
[ROW][C]53[/C][C]0.432585[/C][C]0.865171[/C][C]0.567415[/C][/ROW]
[ROW][C]54[/C][C]0.389369[/C][C]0.778737[/C][C]0.610631[/C][/ROW]
[ROW][C]55[/C][C]0.377809[/C][C]0.755617[/C][C]0.622191[/C][/ROW]
[ROW][C]56[/C][C]0.373594[/C][C]0.747188[/C][C]0.626406[/C][/ROW]
[ROW][C]57[/C][C]0.332852[/C][C]0.665705[/C][C]0.667148[/C][/ROW]
[ROW][C]58[/C][C]0.312981[/C][C]0.625962[/C][C]0.687019[/C][/ROW]
[ROW][C]59[/C][C]0.281726[/C][C]0.563452[/C][C]0.718274[/C][/ROW]
[ROW][C]60[/C][C]0.301555[/C][C]0.60311[/C][C]0.698445[/C][/ROW]
[ROW][C]61[/C][C]0.276787[/C][C]0.553574[/C][C]0.723213[/C][/ROW]
[ROW][C]62[/C][C]0.250508[/C][C]0.501016[/C][C]0.749492[/C][/ROW]
[ROW][C]63[/C][C]0.220683[/C][C]0.441366[/C][C]0.779317[/C][/ROW]
[ROW][C]64[/C][C]0.191708[/C][C]0.383417[/C][C]0.808292[/C][/ROW]
[ROW][C]65[/C][C]0.169368[/C][C]0.338736[/C][C]0.830632[/C][/ROW]
[ROW][C]66[/C][C]0.143784[/C][C]0.287568[/C][C]0.856216[/C][/ROW]
[ROW][C]67[/C][C]0.124528[/C][C]0.249056[/C][C]0.875472[/C][/ROW]
[ROW][C]68[/C][C]0.150714[/C][C]0.301428[/C][C]0.849286[/C][/ROW]
[ROW][C]69[/C][C]0.343889[/C][C]0.687777[/C][C]0.656111[/C][/ROW]
[ROW][C]70[/C][C]0.305643[/C][C]0.611287[/C][C]0.694357[/C][/ROW]
[ROW][C]71[/C][C]0.456878[/C][C]0.913755[/C][C]0.543122[/C][/ROW]
[ROW][C]72[/C][C]0.419929[/C][C]0.839857[/C][C]0.580071[/C][/ROW]
[ROW][C]73[/C][C]0.41025[/C][C]0.820501[/C][C]0.58975[/C][/ROW]
[ROW][C]74[/C][C]0.389476[/C][C]0.778952[/C][C]0.610524[/C][/ROW]
[ROW][C]75[/C][C]0.353067[/C][C]0.706134[/C][C]0.646933[/C][/ROW]
[ROW][C]76[/C][C]0.402479[/C][C]0.804957[/C][C]0.597521[/C][/ROW]
[ROW][C]77[/C][C]0.36758[/C][C]0.735161[/C][C]0.63242[/C][/ROW]
[ROW][C]78[/C][C]0.338947[/C][C]0.677894[/C][C]0.661053[/C][/ROW]
[ROW][C]79[/C][C]0.366387[/C][C]0.732774[/C][C]0.633613[/C][/ROW]
[ROW][C]80[/C][C]0.334441[/C][C]0.668881[/C][C]0.665559[/C][/ROW]
[ROW][C]81[/C][C]0.30266[/C][C]0.605321[/C][C]0.69734[/C][/ROW]
[ROW][C]82[/C][C]0.268712[/C][C]0.537424[/C][C]0.731288[/C][/ROW]
[ROW][C]83[/C][C]0.243465[/C][C]0.48693[/C][C]0.756535[/C][/ROW]
[ROW][C]84[/C][C]0.213395[/C][C]0.42679[/C][C]0.786605[/C][/ROW]
[ROW][C]85[/C][C]0.204474[/C][C]0.408947[/C][C]0.795526[/C][/ROW]
[ROW][C]86[/C][C]0.177589[/C][C]0.355178[/C][C]0.822411[/C][/ROW]
[ROW][C]87[/C][C]0.155174[/C][C]0.310348[/C][C]0.844826[/C][/ROW]
[ROW][C]88[/C][C]0.141134[/C][C]0.282269[/C][C]0.858866[/C][/ROW]
[ROW][C]89[/C][C]0.120989[/C][C]0.241977[/C][C]0.879011[/C][/ROW]
[ROW][C]90[/C][C]0.120255[/C][C]0.24051[/C][C]0.879745[/C][/ROW]
[ROW][C]91[/C][C]0.102479[/C][C]0.204958[/C][C]0.897521[/C][/ROW]
[ROW][C]92[/C][C]0.0891461[/C][C]0.178292[/C][C]0.910854[/C][/ROW]
[ROW][C]93[/C][C]0.0755108[/C][C]0.151022[/C][C]0.924489[/C][/ROW]
[ROW][C]94[/C][C]0.0795327[/C][C]0.159065[/C][C]0.920467[/C][/ROW]
[ROW][C]95[/C][C]0.0718328[/C][C]0.143666[/C][C]0.928167[/C][/ROW]
[ROW][C]96[/C][C]0.0597719[/C][C]0.119544[/C][C]0.940228[/C][/ROW]
[ROW][C]97[/C][C]0.0636513[/C][C]0.127303[/C][C]0.936349[/C][/ROW]
[ROW][C]98[/C][C]0.0525729[/C][C]0.105146[/C][C]0.947427[/C][/ROW]
[ROW][C]99[/C][C]0.0433485[/C][C]0.0866971[/C][C]0.956651[/C][/ROW]
[ROW][C]100[/C][C]0.0375392[/C][C]0.0750785[/C][C]0.962461[/C][/ROW]
[ROW][C]101[/C][C]0.0329904[/C][C]0.0659808[/C][C]0.96701[/C][/ROW]
[ROW][C]102[/C][C]0.0398394[/C][C]0.0796788[/C][C]0.960161[/C][/ROW]
[ROW][C]103[/C][C]0.0335491[/C][C]0.0670982[/C][C]0.966451[/C][/ROW]
[ROW][C]104[/C][C]0.0305202[/C][C]0.0610403[/C][C]0.96948[/C][/ROW]
[ROW][C]105[/C][C]0.0357051[/C][C]0.0714103[/C][C]0.964295[/C][/ROW]
[ROW][C]106[/C][C]0.031265[/C][C]0.0625301[/C][C]0.968735[/C][/ROW]
[ROW][C]107[/C][C]0.0253097[/C][C]0.0506194[/C][C]0.97469[/C][/ROW]
[ROW][C]108[/C][C]0.024605[/C][C]0.0492099[/C][C]0.975395[/C][/ROW]
[ROW][C]109[/C][C]0.0198406[/C][C]0.0396813[/C][C]0.980159[/C][/ROW]
[ROW][C]110[/C][C]0.0162401[/C][C]0.0324801[/C][C]0.98376[/C][/ROW]
[ROW][C]111[/C][C]0.0128113[/C][C]0.0256226[/C][C]0.987189[/C][/ROW]
[ROW][C]112[/C][C]0.0132259[/C][C]0.0264518[/C][C]0.986774[/C][/ROW]
[ROW][C]113[/C][C]0.0121223[/C][C]0.0242446[/C][C]0.987878[/C][/ROW]
[ROW][C]114[/C][C]0.0169804[/C][C]0.0339608[/C][C]0.98302[/C][/ROW]
[ROW][C]115[/C][C]0.0161928[/C][C]0.0323855[/C][C]0.983807[/C][/ROW]
[ROW][C]116[/C][C]0.0154867[/C][C]0.0309735[/C][C]0.984513[/C][/ROW]
[ROW][C]117[/C][C]0.0127934[/C][C]0.0255868[/C][C]0.987207[/C][/ROW]
[ROW][C]118[/C][C]0.0126935[/C][C]0.025387[/C][C]0.987307[/C][/ROW]
[ROW][C]119[/C][C]0.0101274[/C][C]0.0202548[/C][C]0.989873[/C][/ROW]
[ROW][C]120[/C][C]0.00894942[/C][C]0.0178988[/C][C]0.991051[/C][/ROW]
[ROW][C]121[/C][C]0.00713553[/C][C]0.0142711[/C][C]0.992864[/C][/ROW]
[ROW][C]122[/C][C]0.0103009[/C][C]0.0206018[/C][C]0.989699[/C][/ROW]
[ROW][C]123[/C][C]0.00841823[/C][C]0.0168365[/C][C]0.991582[/C][/ROW]
[ROW][C]124[/C][C]0.00701496[/C][C]0.0140299[/C][C]0.992985[/C][/ROW]
[ROW][C]125[/C][C]0.00561231[/C][C]0.0112246[/C][C]0.994388[/C][/ROW]
[ROW][C]126[/C][C]0.00437309[/C][C]0.00874618[/C][C]0.995627[/C][/ROW]
[ROW][C]127[/C][C]0.00411488[/C][C]0.00822976[/C][C]0.995885[/C][/ROW]
[ROW][C]128[/C][C]0.00337134[/C][C]0.00674267[/C][C]0.996629[/C][/ROW]
[ROW][C]129[/C][C]0.00459519[/C][C]0.00919038[/C][C]0.995405[/C][/ROW]
[ROW][C]130[/C][C]0.00520833[/C][C]0.0104167[/C][C]0.994792[/C][/ROW]
[ROW][C]131[/C][C]0.0106572[/C][C]0.0213143[/C][C]0.989343[/C][/ROW]
[ROW][C]132[/C][C]0.0131638[/C][C]0.0263276[/C][C]0.986836[/C][/ROW]
[ROW][C]133[/C][C]0.0140599[/C][C]0.0281197[/C][C]0.98594[/C][/ROW]
[ROW][C]134[/C][C]0.0130266[/C][C]0.0260533[/C][C]0.986973[/C][/ROW]
[ROW][C]135[/C][C]0.0102683[/C][C]0.0205366[/C][C]0.989732[/C][/ROW]
[ROW][C]136[/C][C]0.00869301[/C][C]0.017386[/C][C]0.991307[/C][/ROW]
[ROW][C]137[/C][C]0.00691931[/C][C]0.0138386[/C][C]0.993081[/C][/ROW]
[ROW][C]138[/C][C]0.00873124[/C][C]0.0174625[/C][C]0.991269[/C][/ROW]
[ROW][C]139[/C][C]0.00744563[/C][C]0.0148913[/C][C]0.992554[/C][/ROW]
[ROW][C]140[/C][C]0.00911502[/C][C]0.01823[/C][C]0.990885[/C][/ROW]
[ROW][C]141[/C][C]0.0149245[/C][C]0.029849[/C][C]0.985076[/C][/ROW]
[ROW][C]142[/C][C]0.014288[/C][C]0.0285761[/C][C]0.985712[/C][/ROW]
[ROW][C]143[/C][C]0.0117875[/C][C]0.023575[/C][C]0.988212[/C][/ROW]
[ROW][C]144[/C][C]0.0117425[/C][C]0.0234849[/C][C]0.988258[/C][/ROW]
[ROW][C]145[/C][C]0.0208545[/C][C]0.041709[/C][C]0.979145[/C][/ROW]
[ROW][C]146[/C][C]0.0248967[/C][C]0.0497933[/C][C]0.975103[/C][/ROW]
[ROW][C]147[/C][C]0.0264236[/C][C]0.0528472[/C][C]0.973576[/C][/ROW]
[ROW][C]148[/C][C]0.0230886[/C][C]0.0461771[/C][C]0.976911[/C][/ROW]
[ROW][C]149[/C][C]0.0185754[/C][C]0.0371508[/C][C]0.981425[/C][/ROW]
[ROW][C]150[/C][C]0.0265826[/C][C]0.0531653[/C][C]0.973417[/C][/ROW]
[ROW][C]151[/C][C]0.0226852[/C][C]0.0453704[/C][C]0.977315[/C][/ROW]
[ROW][C]152[/C][C]0.0252752[/C][C]0.0505504[/C][C]0.974725[/C][/ROW]
[ROW][C]153[/C][C]0.0510144[/C][C]0.102029[/C][C]0.948986[/C][/ROW]
[ROW][C]154[/C][C]0.0499973[/C][C]0.0999947[/C][C]0.950003[/C][/ROW]
[ROW][C]155[/C][C]0.0590563[/C][C]0.118113[/C][C]0.940944[/C][/ROW]
[ROW][C]156[/C][C]0.0500529[/C][C]0.100106[/C][C]0.949947[/C][/ROW]
[ROW][C]157[/C][C]0.0442379[/C][C]0.0884757[/C][C]0.955762[/C][/ROW]
[ROW][C]158[/C][C]0.0379777[/C][C]0.0759554[/C][C]0.962022[/C][/ROW]
[ROW][C]159[/C][C]0.0367545[/C][C]0.0735091[/C][C]0.963245[/C][/ROW]
[ROW][C]160[/C][C]0.0310594[/C][C]0.0621188[/C][C]0.968941[/C][/ROW]
[ROW][C]161[/C][C]0.025175[/C][C]0.0503501[/C][C]0.974825[/C][/ROW]
[ROW][C]162[/C][C]0.0203315[/C][C]0.0406631[/C][C]0.979668[/C][/ROW]
[ROW][C]163[/C][C]0.0168868[/C][C]0.0337737[/C][C]0.983113[/C][/ROW]
[ROW][C]164[/C][C]0.0140851[/C][C]0.0281701[/C][C]0.985915[/C][/ROW]
[ROW][C]165[/C][C]0.0120378[/C][C]0.0240755[/C][C]0.987962[/C][/ROW]
[ROW][C]166[/C][C]0.012719[/C][C]0.0254381[/C][C]0.987281[/C][/ROW]
[ROW][C]167[/C][C]0.0101566[/C][C]0.0203133[/C][C]0.989843[/C][/ROW]
[ROW][C]168[/C][C]0.0157254[/C][C]0.0314508[/C][C]0.984275[/C][/ROW]
[ROW][C]169[/C][C]0.0160887[/C][C]0.0321774[/C][C]0.983911[/C][/ROW]
[ROW][C]170[/C][C]0.0150008[/C][C]0.0300017[/C][C]0.984999[/C][/ROW]
[ROW][C]171[/C][C]0.0135895[/C][C]0.027179[/C][C]0.98641[/C][/ROW]
[ROW][C]172[/C][C]0.0108394[/C][C]0.0216788[/C][C]0.989161[/C][/ROW]
[ROW][C]173[/C][C]0.0108442[/C][C]0.0216883[/C][C]0.989156[/C][/ROW]
[ROW][C]174[/C][C]0.0125965[/C][C]0.0251929[/C][C]0.987404[/C][/ROW]
[ROW][C]175[/C][C]0.0166311[/C][C]0.0332622[/C][C]0.983369[/C][/ROW]
[ROW][C]176[/C][C]0.0132481[/C][C]0.0264961[/C][C]0.986752[/C][/ROW]
[ROW][C]177[/C][C]0.0104529[/C][C]0.0209058[/C][C]0.989547[/C][/ROW]
[ROW][C]178[/C][C]0.0087686[/C][C]0.0175372[/C][C]0.991231[/C][/ROW]
[ROW][C]179[/C][C]0.00675218[/C][C]0.0135044[/C][C]0.993248[/C][/ROW]
[ROW][C]180[/C][C]0.00595228[/C][C]0.0119046[/C][C]0.994048[/C][/ROW]
[ROW][C]181[/C][C]0.00482021[/C][C]0.00964043[/C][C]0.99518[/C][/ROW]
[ROW][C]182[/C][C]0.00370835[/C][C]0.00741669[/C][C]0.996292[/C][/ROW]
[ROW][C]183[/C][C]0.00398692[/C][C]0.00797385[/C][C]0.996013[/C][/ROW]
[ROW][C]184[/C][C]0.00300961[/C][C]0.00601922[/C][C]0.99699[/C][/ROW]
[ROW][C]185[/C][C]0.0853415[/C][C]0.170683[/C][C]0.914659[/C][/ROW]
[ROW][C]186[/C][C]0.0760215[/C][C]0.152043[/C][C]0.923978[/C][/ROW]
[ROW][C]187[/C][C]0.0837414[/C][C]0.167483[/C][C]0.916259[/C][/ROW]
[ROW][C]188[/C][C]0.0700403[/C][C]0.140081[/C][C]0.92996[/C][/ROW]
[ROW][C]189[/C][C]0.0622876[/C][C]0.124575[/C][C]0.937712[/C][/ROW]
[ROW][C]190[/C][C]0.0517448[/C][C]0.10349[/C][C]0.948255[/C][/ROW]
[ROW][C]191[/C][C]0.0477315[/C][C]0.095463[/C][C]0.952269[/C][/ROW]
[ROW][C]192[/C][C]0.0392258[/C][C]0.0784515[/C][C]0.960774[/C][/ROW]
[ROW][C]193[/C][C]0.0400244[/C][C]0.0800487[/C][C]0.959976[/C][/ROW]
[ROW][C]194[/C][C]0.0403047[/C][C]0.0806094[/C][C]0.959695[/C][/ROW]
[ROW][C]195[/C][C]0.0347006[/C][C]0.0694012[/C][C]0.965299[/C][/ROW]
[ROW][C]196[/C][C]0.0277662[/C][C]0.0555323[/C][C]0.972234[/C][/ROW]
[ROW][C]197[/C][C]0.0351052[/C][C]0.0702104[/C][C]0.964895[/C][/ROW]
[ROW][C]198[/C][C]0.0285014[/C][C]0.0570028[/C][C]0.971499[/C][/ROW]
[ROW][C]199[/C][C]0.0255314[/C][C]0.0510629[/C][C]0.974469[/C][/ROW]
[ROW][C]200[/C][C]0.0218196[/C][C]0.0436392[/C][C]0.97818[/C][/ROW]
[ROW][C]201[/C][C]0.0203269[/C][C]0.0406539[/C][C]0.979673[/C][/ROW]
[ROW][C]202[/C][C]0.01709[/C][C]0.0341799[/C][C]0.98291[/C][/ROW]
[ROW][C]203[/C][C]0.0224644[/C][C]0.0449288[/C][C]0.977536[/C][/ROW]
[ROW][C]204[/C][C]0.0261549[/C][C]0.0523098[/C][C]0.973845[/C][/ROW]
[ROW][C]205[/C][C]0.027322[/C][C]0.054644[/C][C]0.972678[/C][/ROW]
[ROW][C]206[/C][C]0.021257[/C][C]0.042514[/C][C]0.978743[/C][/ROW]
[ROW][C]207[/C][C]0.0202653[/C][C]0.0405306[/C][C]0.979735[/C][/ROW]
[ROW][C]208[/C][C]0.0164688[/C][C]0.0329377[/C][C]0.983531[/C][/ROW]
[ROW][C]209[/C][C]0.0183273[/C][C]0.0366546[/C][C]0.981673[/C][/ROW]
[ROW][C]210[/C][C]0.014501[/C][C]0.029002[/C][C]0.985499[/C][/ROW]
[ROW][C]211[/C][C]0.0166183[/C][C]0.0332366[/C][C]0.983382[/C][/ROW]
[ROW][C]212[/C][C]0.0270901[/C][C]0.0541802[/C][C]0.97291[/C][/ROW]
[ROW][C]213[/C][C]0.0209131[/C][C]0.0418262[/C][C]0.979087[/C][/ROW]
[ROW][C]214[/C][C]0.0271139[/C][C]0.0542279[/C][C]0.972886[/C][/ROW]
[ROW][C]215[/C][C]0.0228725[/C][C]0.0457451[/C][C]0.977127[/C][/ROW]
[ROW][C]216[/C][C]0.017532[/C][C]0.035064[/C][C]0.982468[/C][/ROW]
[ROW][C]217[/C][C]0.019256[/C][C]0.0385119[/C][C]0.980744[/C][/ROW]
[ROW][C]218[/C][C]0.0160981[/C][C]0.0321961[/C][C]0.983902[/C][/ROW]
[ROW][C]219[/C][C]0.0148738[/C][C]0.0297476[/C][C]0.985126[/C][/ROW]
[ROW][C]220[/C][C]0.0112452[/C][C]0.0224905[/C][C]0.988755[/C][/ROW]
[ROW][C]221[/C][C]0.00926183[/C][C]0.0185237[/C][C]0.990738[/C][/ROW]
[ROW][C]222[/C][C]0.00656563[/C][C]0.0131313[/C][C]0.993434[/C][/ROW]
[ROW][C]223[/C][C]0.00498204[/C][C]0.00996407[/C][C]0.995018[/C][/ROW]
[ROW][C]224[/C][C]0.00370587[/C][C]0.00741173[/C][C]0.996294[/C][/ROW]
[ROW][C]225[/C][C]0.00312911[/C][C]0.00625821[/C][C]0.996871[/C][/ROW]
[ROW][C]226[/C][C]0.00730802[/C][C]0.014616[/C][C]0.992692[/C][/ROW]
[ROW][C]227[/C][C]0.00565659[/C][C]0.0113132[/C][C]0.994343[/C][/ROW]
[ROW][C]228[/C][C]0.00413004[/C][C]0.00826007[/C][C]0.99587[/C][/ROW]
[ROW][C]229[/C][C]0.00290096[/C][C]0.00580191[/C][C]0.997099[/C][/ROW]
[ROW][C]230[/C][C]0.00210007[/C][C]0.00420013[/C][C]0.9979[/C][/ROW]
[ROW][C]231[/C][C]0.00187435[/C][C]0.0037487[/C][C]0.998126[/C][/ROW]
[ROW][C]232[/C][C]0.00445268[/C][C]0.00890537[/C][C]0.995547[/C][/ROW]
[ROW][C]233[/C][C]0.0186514[/C][C]0.0373027[/C][C]0.981349[/C][/ROW]
[ROW][C]234[/C][C]0.0287056[/C][C]0.0574112[/C][C]0.971294[/C][/ROW]
[ROW][C]235[/C][C]0.0202408[/C][C]0.0404816[/C][C]0.979759[/C][/ROW]
[ROW][C]236[/C][C]0.0166385[/C][C]0.033277[/C][C]0.983361[/C][/ROW]
[ROW][C]237[/C][C]0.158812[/C][C]0.317623[/C][C]0.841188[/C][/ROW]
[ROW][C]238[/C][C]0.122054[/C][C]0.244107[/C][C]0.877946[/C][/ROW]
[ROW][C]239[/C][C]0.0996049[/C][C]0.19921[/C][C]0.900395[/C][/ROW]
[ROW][C]240[/C][C]0.0750858[/C][C]0.150172[/C][C]0.924914[/C][/ROW]
[ROW][C]241[/C][C]0.0646426[/C][C]0.129285[/C][C]0.935357[/C][/ROW]
[ROW][C]242[/C][C]0.102491[/C][C]0.204981[/C][C]0.897509[/C][/ROW]
[ROW][C]243[/C][C]0.0814917[/C][C]0.162983[/C][C]0.918508[/C][/ROW]
[ROW][C]244[/C][C]0.0842683[/C][C]0.168537[/C][C]0.915732[/C][/ROW]
[ROW][C]245[/C][C]0.0665871[/C][C]0.133174[/C][C]0.933413[/C][/ROW]
[ROW][C]246[/C][C]0.0544357[/C][C]0.108871[/C][C]0.945564[/C][/ROW]
[ROW][C]247[/C][C]0.0329908[/C][C]0.0659815[/C][C]0.967009[/C][/ROW]
[ROW][C]248[/C][C]0.0266392[/C][C]0.0532783[/C][C]0.973361[/C][/ROW]
[ROW][C]249[/C][C]0.0224914[/C][C]0.0449827[/C][C]0.977509[/C][/ROW]
[ROW][C]250[/C][C]0.0664473[/C][C]0.132895[/C][C]0.933553[/C][/ROW]
[ROW][C]251[/C][C]0.0486972[/C][C]0.0973945[/C][C]0.951303[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221924&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221924&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
130.3098080.6196150.690192
140.2982460.5964920.701754
150.1808810.3617610.819119
160.137960.2759190.86204
170.143730.2874590.85627
180.2956730.5913450.704327
190.2459530.4919060.754047
200.1975320.3950630.802468
210.1546390.3092770.845361
220.181180.362360.81882
230.2923710.5847410.707629
240.4135630.8271260.586437
250.3438720.6877430.656128
260.2927450.5854910.707255
270.2802750.560550.719725
280.3963790.7927590.603621
290.3427050.6854110.657295
300.4535910.9071820.546409
310.409820.8196410.59018
320.37970.7594010.6203
330.3621990.7243980.637801
340.3230610.6461230.676939
350.2774190.5548390.722581
360.4125990.8251990.587401
370.4404870.8809730.559513
380.4147510.8295020.585249
390.4589970.9179930.541003
400.4380770.8761550.561923
410.3976070.7952130.602393
420.3570110.7140220.642989
430.3758030.7516070.624197
440.3262190.6524380.673781
450.2972290.5944570.702771
460.4777680.9555350.522232
470.5669830.8660340.433017
480.5236940.9526110.476306
490.5470910.9058190.452909
500.5197960.9604080.480204
510.4743620.9487240.525638
520.4323250.8646510.567675
530.4325850.8651710.567415
540.3893690.7787370.610631
550.3778090.7556170.622191
560.3735940.7471880.626406
570.3328520.6657050.667148
580.3129810.6259620.687019
590.2817260.5634520.718274
600.3015550.603110.698445
610.2767870.5535740.723213
620.2505080.5010160.749492
630.2206830.4413660.779317
640.1917080.3834170.808292
650.1693680.3387360.830632
660.1437840.2875680.856216
670.1245280.2490560.875472
680.1507140.3014280.849286
690.3438890.6877770.656111
700.3056430.6112870.694357
710.4568780.9137550.543122
720.4199290.8398570.580071
730.410250.8205010.58975
740.3894760.7789520.610524
750.3530670.7061340.646933
760.4024790.8049570.597521
770.367580.7351610.63242
780.3389470.6778940.661053
790.3663870.7327740.633613
800.3344410.6688810.665559
810.302660.6053210.69734
820.2687120.5374240.731288
830.2434650.486930.756535
840.2133950.426790.786605
850.2044740.4089470.795526
860.1775890.3551780.822411
870.1551740.3103480.844826
880.1411340.2822690.858866
890.1209890.2419770.879011
900.1202550.240510.879745
910.1024790.2049580.897521
920.08914610.1782920.910854
930.07551080.1510220.924489
940.07953270.1590650.920467
950.07183280.1436660.928167
960.05977190.1195440.940228
970.06365130.1273030.936349
980.05257290.1051460.947427
990.04334850.08669710.956651
1000.03753920.07507850.962461
1010.03299040.06598080.96701
1020.03983940.07967880.960161
1030.03354910.06709820.966451
1040.03052020.06104030.96948
1050.03570510.07141030.964295
1060.0312650.06253010.968735
1070.02530970.05061940.97469
1080.0246050.04920990.975395
1090.01984060.03968130.980159
1100.01624010.03248010.98376
1110.01281130.02562260.987189
1120.01322590.02645180.986774
1130.01212230.02424460.987878
1140.01698040.03396080.98302
1150.01619280.03238550.983807
1160.01548670.03097350.984513
1170.01279340.02558680.987207
1180.01269350.0253870.987307
1190.01012740.02025480.989873
1200.008949420.01789880.991051
1210.007135530.01427110.992864
1220.01030090.02060180.989699
1230.008418230.01683650.991582
1240.007014960.01402990.992985
1250.005612310.01122460.994388
1260.004373090.008746180.995627
1270.004114880.008229760.995885
1280.003371340.006742670.996629
1290.004595190.009190380.995405
1300.005208330.01041670.994792
1310.01065720.02131430.989343
1320.01316380.02632760.986836
1330.01405990.02811970.98594
1340.01302660.02605330.986973
1350.01026830.02053660.989732
1360.008693010.0173860.991307
1370.006919310.01383860.993081
1380.008731240.01746250.991269
1390.007445630.01489130.992554
1400.009115020.018230.990885
1410.01492450.0298490.985076
1420.0142880.02857610.985712
1430.01178750.0235750.988212
1440.01174250.02348490.988258
1450.02085450.0417090.979145
1460.02489670.04979330.975103
1470.02642360.05284720.973576
1480.02308860.04617710.976911
1490.01857540.03715080.981425
1500.02658260.05316530.973417
1510.02268520.04537040.977315
1520.02527520.05055040.974725
1530.05101440.1020290.948986
1540.04999730.09999470.950003
1550.05905630.1181130.940944
1560.05005290.1001060.949947
1570.04423790.08847570.955762
1580.03797770.07595540.962022
1590.03675450.07350910.963245
1600.03105940.06211880.968941
1610.0251750.05035010.974825
1620.02033150.04066310.979668
1630.01688680.03377370.983113
1640.01408510.02817010.985915
1650.01203780.02407550.987962
1660.0127190.02543810.987281
1670.01015660.02031330.989843
1680.01572540.03145080.984275
1690.01608870.03217740.983911
1700.01500080.03000170.984999
1710.01358950.0271790.98641
1720.01083940.02167880.989161
1730.01084420.02168830.989156
1740.01259650.02519290.987404
1750.01663110.03326220.983369
1760.01324810.02649610.986752
1770.01045290.02090580.989547
1780.00876860.01753720.991231
1790.006752180.01350440.993248
1800.005952280.01190460.994048
1810.004820210.009640430.99518
1820.003708350.007416690.996292
1830.003986920.007973850.996013
1840.003009610.006019220.99699
1850.08534150.1706830.914659
1860.07602150.1520430.923978
1870.08374140.1674830.916259
1880.07004030.1400810.92996
1890.06228760.1245750.937712
1900.05174480.103490.948255
1910.04773150.0954630.952269
1920.03922580.07845150.960774
1930.04002440.08004870.959976
1940.04030470.08060940.959695
1950.03470060.06940120.965299
1960.02776620.05553230.972234
1970.03510520.07021040.964895
1980.02850140.05700280.971499
1990.02553140.05106290.974469
2000.02181960.04363920.97818
2010.02032690.04065390.979673
2020.017090.03417990.98291
2030.02246440.04492880.977536
2040.02615490.05230980.973845
2050.0273220.0546440.972678
2060.0212570.0425140.978743
2070.02026530.04053060.979735
2080.01646880.03293770.983531
2090.01832730.03665460.981673
2100.0145010.0290020.985499
2110.01661830.03323660.983382
2120.02709010.05418020.97291
2130.02091310.04182620.979087
2140.02711390.05422790.972886
2150.02287250.04574510.977127
2160.0175320.0350640.982468
2170.0192560.03851190.980744
2180.01609810.03219610.983902
2190.01487380.02974760.985126
2200.01124520.02249050.988755
2210.009261830.01852370.990738
2220.006565630.01313130.993434
2230.004982040.009964070.995018
2240.003705870.007411730.996294
2250.003129110.006258210.996871
2260.007308020.0146160.992692
2270.005656590.01131320.994343
2280.004130040.008260070.99587
2290.002900960.005801910.997099
2300.002100070.004200130.9979
2310.001874350.00374870.998126
2320.004452680.008905370.995547
2330.01865140.03730270.981349
2340.02870560.05741120.971294
2350.02024080.04048160.979759
2360.01663850.0332770.983361
2370.1588120.3176230.841188
2380.1220540.2441070.877946
2390.09960490.199210.900395
2400.07508580.1501720.924914
2410.06464260.1292850.935357
2420.1024910.2049810.897509
2430.08149170.1629830.918508
2440.08426830.1685370.915732
2450.06658710.1331740.933413
2460.05443570.1088710.945564
2470.03299080.06598150.967009
2480.02663920.05327830.973361
2490.02249140.04498270.977509
2500.06644730.1328950.933553
2510.04869720.09739450.951303






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level160.0669456NOK
5% type I error level980.410042NOK
10% type I error level1330.556485NOK

\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 & 16 & 0.0669456 & NOK \tabularnewline
5% type I error level & 98 & 0.410042 & NOK \tabularnewline
10% type I error level & 133 & 0.556485 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221924&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]16[/C][C]0.0669456[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]98[/C][C]0.410042[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]133[/C][C]0.556485[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221924&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221924&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 level160.0669456NOK
5% type I error level980.410042NOK
10% type I error level1330.556485NOK


Figures (Output of Computation)

Figure 1
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Figure 2
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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')
}