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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 computationThu, 31 Oct 2013 10:32:56 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Oct/31/t1383230048gl0bdo0rwj84n71.htm/, Retrieved Mon, 29 Apr 2024 00:07:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221533, Retrieved Mon, 29 Apr 2024 00:07:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact66

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [multiple regressi...] [2013-10-31 14:32:56] [3019cd50fc986427c986281495e68f5c] [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 time21 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 21 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221533&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]21 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221533&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221533&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time21 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Month[t] = + 11.5272 -0.0272Connected[t] + 0.00587323Separate[t] -0.0608208Learning[t] -0.0405238Software[t] -0.0409822Happiness[t] + 0.0304204Depression[t] + 0.0316725Sport1[t] -0.0338941Sport2[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Month[t] =  +  11.5272 -0.0272Connected[t] +  0.00587323Separate[t] -0.0608208Learning[t] -0.0405238Software[t] -0.0409822Happiness[t] +  0.0304204Depression[t] +  0.0316725Sport1[t] -0.0338941Sport2[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221533&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Month[t] =  +  11.5272 -0.0272Connected[t] +  0.00587323Separate[t] -0.0608208Learning[t] -0.0405238Software[t] -0.0409822Happiness[t] +  0.0304204Depression[t] +  0.0316725Sport1[t] -0.0338941Sport2[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221533&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221533&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
Month[t] = + 11.5272 -0.0272Connected[t] + 0.00587323Separate[t] -0.0608208Learning[t] -0.0405238Software[t] -0.0409822Happiness[t] + 0.0304204Depression[t] + 0.0316725Sport1[t] -0.0338941Sport2[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)11.52720.74129915.558.37724e-394.18862e-39
Connected-0.02720.0133941-2.0310.04331790.021659
Separate0.005873230.01371410.42830.6688230.334411
Learning-0.06082080.0239791-2.5360.01179690.00589846
Software-0.04052380.0246536-1.6440.1014650.0507325
Happiness-0.04098220.0223638-1.8330.0680390.0340195
Depression0.03042040.0163551.860.06403640.0320182
Sport10.03167250.0145242.1810.03011960.0150598
Sport2-0.03389410.0216607-1.5650.1188760.0594379

\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) & 11.5272 & 0.741299 & 15.55 & 8.37724e-39 & 4.18862e-39 \tabularnewline
Connected & -0.0272 & 0.0133941 & -2.031 & 0.0433179 & 0.021659 \tabularnewline
Separate & 0.00587323 & 0.0137141 & 0.4283 & 0.668823 & 0.334411 \tabularnewline
Learning & -0.0608208 & 0.0239791 & -2.536 & 0.0117969 & 0.00589846 \tabularnewline
Software & -0.0405238 & 0.0246536 & -1.644 & 0.101465 & 0.0507325 \tabularnewline
Happiness & -0.0409822 & 0.0223638 & -1.833 & 0.068039 & 0.0340195 \tabularnewline
Depression & 0.0304204 & 0.016355 & 1.86 & 0.0640364 & 0.0320182 \tabularnewline
Sport1 & 0.0316725 & 0.014524 & 2.181 & 0.0301196 & 0.0150598 \tabularnewline
Sport2 & -0.0338941 & 0.0216607 & -1.565 & 0.118876 & 0.0594379 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221533&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]11.5272[/C][C]0.741299[/C][C]15.55[/C][C]8.37724e-39[/C][C]4.18862e-39[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0272[/C][C]0.0133941[/C][C]-2.031[/C][C]0.0433179[/C][C]0.021659[/C][/ROW]
[ROW][C]Separate[/C][C]0.00587323[/C][C]0.0137141[/C][C]0.4283[/C][C]0.668823[/C][C]0.334411[/C][/ROW]
[ROW][C]Learning[/C][C]-0.0608208[/C][C]0.0239791[/C][C]-2.536[/C][C]0.0117969[/C][C]0.00589846[/C][/ROW]
[ROW][C]Software[/C][C]-0.0405238[/C][C]0.0246536[/C][C]-1.644[/C][C]0.101465[/C][C]0.0507325[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.0409822[/C][C]0.0223638[/C][C]-1.833[/C][C]0.068039[/C][C]0.0340195[/C][/ROW]
[ROW][C]Depression[/C][C]0.0304204[/C][C]0.016355[/C][C]1.86[/C][C]0.0640364[/C][C]0.0320182[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0316725[/C][C]0.014524[/C][C]2.181[/C][C]0.0301196[/C][C]0.0150598[/C][/ROW]
[ROW][C]Sport2[/C][C]-0.0338941[/C][C]0.0216607[/C][C]-1.565[/C][C]0.118876[/C][C]0.0594379[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221533&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221533&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)11.52720.74129915.558.37724e-394.18862e-39
Connected-0.02720.0133941-2.0310.04331790.021659
Separate0.005873230.01371410.42830.6688230.334411
Learning-0.06082080.0239791-2.5360.01179690.00589846
Software-0.04052380.0246536-1.6440.1014650.0507325
Happiness-0.04098220.0223638-1.8330.0680390.0340195
Depression0.03042040.0163551.860.06403640.0320182
Sport10.03167250.0145242.1810.03011960.0150598
Sport2-0.03389410.0216607-1.5650.1188760.0594379






Multiple Linear Regression - Regression Statistics
Multiple R0.431614
R-squared0.186291
Adjusted R-squared0.160763
F-TEST (value)7.29746
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value9.97714e-09
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.723004
Sum Squared Residuals133.297

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.431614 \tabularnewline
R-squared & 0.186291 \tabularnewline
Adjusted R-squared & 0.160763 \tabularnewline
F-TEST (value) & 7.29746 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 255 \tabularnewline
p-value & 9.97714e-09 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.723004 \tabularnewline
Sum Squared Residuals & 133.297 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221533&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.431614[/C][/ROW]
[ROW][C]R-squared[/C][C]0.186291[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.160763[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]7.29746[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]255[/C][/ROW]
[ROW][C]p-value[/C][C]9.97714e-09[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.723004[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]133.297[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221533&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221533&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 R0.431614
R-squared0.186291
Adjusted R-squared0.160763
F-TEST (value)7.29746
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value9.97714e-09
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.723004
Sum Squared Residuals133.297






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
199.74358-0.743583
299.73264-0.732641
399.79526-0.795256
4910.328-1.32805
5910.2725-1.27253
6910.0544-1.05444
799.52668-0.526679
899.96808-0.968084
999.92382-0.923818
10910.0618-1.06181
1199.74615-0.746152
1299.34481-0.344813
1399.98476-0.984764
1499.6327-0.632699
1599.73077-0.730773
1699.921-0.921002
17910.1208-1.12076
1899.60894-0.608936
1999.51691-0.516912
2099.71025-0.710251
2199.68379-0.683794
22910.0442-1.04415
2399.39031-0.390313
2499.78467-0.78467
2599.7334-0.733402
2699.88493-0.884931
27910.0038-1.0038
2899.94391-0.943912
29910.1204-1.1204
30910.1149-1.1149
3199.95856-0.95856
32910.4421-1.44208
3399.84498-0.844979
3499.91042-0.910421
35910.1828-1.18278
36910.3038-1.30383
37910.9284-1.92843
3899.94568-0.945683
3999.99762-0.997617
4099.92396-0.923962
4199.80798-0.807984
42910.1127-1.11274
4399.03676-0.0367589
44910.0427-1.04267
4599.88309-0.883093
46910.3137-1.31371
4799.6047-0.604703
48910.0074-1.00745
49910.0321-1.03214
5099.99586-0.995855
5199.77712-0.777115
52910.1947-1.19473
53910.4726-1.47256
5499.66434-0.664337
55910.7128-1.71279
56910.2722-1.27221
5799.76498-0.764982
5899.83626-0.836258
59910.0413-1.04126
60910.1207-1.1207
61910.7367-1.73675
6299.97973-0.979726
63910.0887-1.08865
64910.0407-1.04073
6599.69762-0.697625
661010.0296-0.0295678
67109.824660.175339
681010.125-0.124964
69109.973350.0266514
70109.906120.0938757
711010.2251-0.2251
721010.0024-0.00236136
73109.888670.111334
74109.591430.408565
751010.0692-0.0692293
761010.2031-0.203149
77109.696590.303406
781010.044-0.0440461
791010.2972-0.297236
80109.552810.447185
811010.0445-0.0445381
82109.715680.284315
83109.880020.119975
841010.0378-0.0378376
851010.1008-0.100803
861010.1374-0.137416
87109.923050.0769539
88109.98230.0176968
891010.5669-0.566852
901010.2526-0.252634
91109.609510.390489
921010.017-0.0170001
931010.2755-0.275466
941010.4259-0.425935
95109.919180.0808183
96109.949350.0506526
971010.0917-0.091653
98109.837580.162416
991010.149-0.14899
100109.653980.346018
1011010.0893-0.0892965
102109.580060.419935
1031010.0139-0.0138602
1041010.2209-0.220889
1051010.3234-0.323438
106109.671950.32805
107109.844960.155038
108109.972990.0270068
1091010.3512-0.35117
1101010.1923-0.192323
1111010.1953-0.195307
1121010.1428-0.142777
1131010.3275-0.327492
1141010.0269-0.0268847
115109.663130.336875
116109.93020.0697957
1171010.1141-0.114109
1181010.0606-0.0606444
1191010.1146-0.114552
1201010.1668-0.166838
1211010.0428-0.0427813
1221010.1542-0.154192
123109.646260.353736
124109.797730.202272
1251010.0078-0.00781739
126109.869840.130162
127109.53970.460298
128109.889090.110913
1291010.1632-0.163247
1301010.0993-0.0993271
1311010.8738-0.873794
132109.928340.071659
1331010.3379-0.337938
134109.941180.0588158
1351010.0945-0.0945013
1361010.5801-0.580132
137109.873870.12613
1381010.4025-0.402471
1391010.112-0.112048
1401010.4839-0.483871
141109.840480.159522
1421010.3536-0.353574
143109.993720.00627626
1441010.0302-0.0301854
1451010.3225-0.322487
146109.717240.28276
1471010.0395-0.0395463
1481010.0386-0.0386287
1491010.5699-0.569901
1501010.4359-0.435916
1511010.0565-0.0565009
152109.964920.0350763
1531010.2503-0.250348
154910.4547-1.45474
1551010.636-0.635956
156109.609510.390489
1571010.4204-0.420418
158109.889090.110913
1591010.0444-0.0443843
1601010.8475-0.847538
1611010.2792-0.279237
1621110.70280.297167
1631110.60730.392721
164119.941291.05871
1651110.47470.525345
1661110.95890.0410954
1671110.24260.757374
1681110.59810.401929
1691110.5690.431017
1701110.65190.348117
1711110.51760.482376
172119.804331.19567
1731110.35610.643857
1741110.7210.27903
1751110.02520.974825
1761110.22440.775551
1771110.47480.525223
1781110.64440.355611
179119.990261.00974
1801110.51170.48833
181119.652731.34727
1821110.31270.68733
183119.577641.42236
184119.920311.07969
1851110.7540.245986
1861110.36980.630163
1871110.00650.993542
1881110.37830.621691
1891110.5640.436005
1901110.79480.205204
1911110.30590.694127
192119.883691.11631
1931110.60260.397351
194119.98361.0164
1951110.24910.750903
196119.944411.05559
1971110.32610.6739
1981110.22920.770804
1991110.5670.433015
2001110.35870.641306
2011110.27040.729622
2021110.37380.626151
2031110.34060.65943
204119.991381.00862
2051110.13570.864317
2061110.05510.944945
207119.992931.00707
208119.724091.27591
2091110.28640.713568
2101110.15380.846189
2111110.39970.600305
212119.997331.00267
2131110.54980.450199
2141110.48960.510369
2151110.1540.845989
2161110.10550.894481
217119.923071.07693
2181110.0670.932991
2191110.6920.308041
2201110.02430.975708
2211110.25430.745687
222119.943961.05604
2231110.31540.68462
2241110.22550.77446
2251110.75920.240808
2261110.69840.301628
227119.763021.23698
2281110.32930.670658
2291110.80110.198851
2301110.41770.582281
2311110.32740.672591
2321110.5880.412029
233119.916111.08389
234119.649411.35059
2351110.00160.998387
2361110.39050.609456
2371110.94840.0516334
238119.757471.24253
2391110.20890.791142
2401110.50850.491527
2411110.72990.270057
2421110.38160.618444
2431110.8460.154046
2441110.46480.535205
245119.997261.00274
2461110.80940.190592
2471110.2660.733991
2481110.29960.700368
2491110.83180.168212
2501110.63570.364308
2511110.53570.4643
2521110.78750.212491
2531110.3340.666009
2541110.09760.902391
2551110.26730.732691
2561110.12810.871875
2571110.52110.478899
2581110.4830.517049
2591110.05810.94194
2601111.0864-0.0864378
2611110.14130.858688
2621110.18470.815317
2631110.72220.27783
2641110.32440.675564

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 9 & 9.74358 & -0.743583 \tabularnewline
2 & 9 & 9.73264 & -0.732641 \tabularnewline
3 & 9 & 9.79526 & -0.795256 \tabularnewline
4 & 9 & 10.328 & -1.32805 \tabularnewline
5 & 9 & 10.2725 & -1.27253 \tabularnewline
6 & 9 & 10.0544 & -1.05444 \tabularnewline
7 & 9 & 9.52668 & -0.526679 \tabularnewline
8 & 9 & 9.96808 & -0.968084 \tabularnewline
9 & 9 & 9.92382 & -0.923818 \tabularnewline
10 & 9 & 10.0618 & -1.06181 \tabularnewline
11 & 9 & 9.74615 & -0.746152 \tabularnewline
12 & 9 & 9.34481 & -0.344813 \tabularnewline
13 & 9 & 9.98476 & -0.984764 \tabularnewline
14 & 9 & 9.6327 & -0.632699 \tabularnewline
15 & 9 & 9.73077 & -0.730773 \tabularnewline
16 & 9 & 9.921 & -0.921002 \tabularnewline
17 & 9 & 10.1208 & -1.12076 \tabularnewline
18 & 9 & 9.60894 & -0.608936 \tabularnewline
19 & 9 & 9.51691 & -0.516912 \tabularnewline
20 & 9 & 9.71025 & -0.710251 \tabularnewline
21 & 9 & 9.68379 & -0.683794 \tabularnewline
22 & 9 & 10.0442 & -1.04415 \tabularnewline
23 & 9 & 9.39031 & -0.390313 \tabularnewline
24 & 9 & 9.78467 & -0.78467 \tabularnewline
25 & 9 & 9.7334 & -0.733402 \tabularnewline
26 & 9 & 9.88493 & -0.884931 \tabularnewline
27 & 9 & 10.0038 & -1.0038 \tabularnewline
28 & 9 & 9.94391 & -0.943912 \tabularnewline
29 & 9 & 10.1204 & -1.1204 \tabularnewline
30 & 9 & 10.1149 & -1.1149 \tabularnewline
31 & 9 & 9.95856 & -0.95856 \tabularnewline
32 & 9 & 10.4421 & -1.44208 \tabularnewline
33 & 9 & 9.84498 & -0.844979 \tabularnewline
34 & 9 & 9.91042 & -0.910421 \tabularnewline
35 & 9 & 10.1828 & -1.18278 \tabularnewline
36 & 9 & 10.3038 & -1.30383 \tabularnewline
37 & 9 & 10.9284 & -1.92843 \tabularnewline
38 & 9 & 9.94568 & -0.945683 \tabularnewline
39 & 9 & 9.99762 & -0.997617 \tabularnewline
40 & 9 & 9.92396 & -0.923962 \tabularnewline
41 & 9 & 9.80798 & -0.807984 \tabularnewline
42 & 9 & 10.1127 & -1.11274 \tabularnewline
43 & 9 & 9.03676 & -0.0367589 \tabularnewline
44 & 9 & 10.0427 & -1.04267 \tabularnewline
45 & 9 & 9.88309 & -0.883093 \tabularnewline
46 & 9 & 10.3137 & -1.31371 \tabularnewline
47 & 9 & 9.6047 & -0.604703 \tabularnewline
48 & 9 & 10.0074 & -1.00745 \tabularnewline
49 & 9 & 10.0321 & -1.03214 \tabularnewline
50 & 9 & 9.99586 & -0.995855 \tabularnewline
51 & 9 & 9.77712 & -0.777115 \tabularnewline
52 & 9 & 10.1947 & -1.19473 \tabularnewline
53 & 9 & 10.4726 & -1.47256 \tabularnewline
54 & 9 & 9.66434 & -0.664337 \tabularnewline
55 & 9 & 10.7128 & -1.71279 \tabularnewline
56 & 9 & 10.2722 & -1.27221 \tabularnewline
57 & 9 & 9.76498 & -0.764982 \tabularnewline
58 & 9 & 9.83626 & -0.836258 \tabularnewline
59 & 9 & 10.0413 & -1.04126 \tabularnewline
60 & 9 & 10.1207 & -1.1207 \tabularnewline
61 & 9 & 10.7367 & -1.73675 \tabularnewline
62 & 9 & 9.97973 & -0.979726 \tabularnewline
63 & 9 & 10.0887 & -1.08865 \tabularnewline
64 & 9 & 10.0407 & -1.04073 \tabularnewline
65 & 9 & 9.69762 & -0.697625 \tabularnewline
66 & 10 & 10.0296 & -0.0295678 \tabularnewline
67 & 10 & 9.82466 & 0.175339 \tabularnewline
68 & 10 & 10.125 & -0.124964 \tabularnewline
69 & 10 & 9.97335 & 0.0266514 \tabularnewline
70 & 10 & 9.90612 & 0.0938757 \tabularnewline
71 & 10 & 10.2251 & -0.2251 \tabularnewline
72 & 10 & 10.0024 & -0.00236136 \tabularnewline
73 & 10 & 9.88867 & 0.111334 \tabularnewline
74 & 10 & 9.59143 & 0.408565 \tabularnewline
75 & 10 & 10.0692 & -0.0692293 \tabularnewline
76 & 10 & 10.2031 & -0.203149 \tabularnewline
77 & 10 & 9.69659 & 0.303406 \tabularnewline
78 & 10 & 10.044 & -0.0440461 \tabularnewline
79 & 10 & 10.2972 & -0.297236 \tabularnewline
80 & 10 & 9.55281 & 0.447185 \tabularnewline
81 & 10 & 10.0445 & -0.0445381 \tabularnewline
82 & 10 & 9.71568 & 0.284315 \tabularnewline
83 & 10 & 9.88002 & 0.119975 \tabularnewline
84 & 10 & 10.0378 & -0.0378376 \tabularnewline
85 & 10 & 10.1008 & -0.100803 \tabularnewline
86 & 10 & 10.1374 & -0.137416 \tabularnewline
87 & 10 & 9.92305 & 0.0769539 \tabularnewline
88 & 10 & 9.9823 & 0.0176968 \tabularnewline
89 & 10 & 10.5669 & -0.566852 \tabularnewline
90 & 10 & 10.2526 & -0.252634 \tabularnewline
91 & 10 & 9.60951 & 0.390489 \tabularnewline
92 & 10 & 10.017 & -0.0170001 \tabularnewline
93 & 10 & 10.2755 & -0.275466 \tabularnewline
94 & 10 & 10.4259 & -0.425935 \tabularnewline
95 & 10 & 9.91918 & 0.0808183 \tabularnewline
96 & 10 & 9.94935 & 0.0506526 \tabularnewline
97 & 10 & 10.0917 & -0.091653 \tabularnewline
98 & 10 & 9.83758 & 0.162416 \tabularnewline
99 & 10 & 10.149 & -0.14899 \tabularnewline
100 & 10 & 9.65398 & 0.346018 \tabularnewline
101 & 10 & 10.0893 & -0.0892965 \tabularnewline
102 & 10 & 9.58006 & 0.419935 \tabularnewline
103 & 10 & 10.0139 & -0.0138602 \tabularnewline
104 & 10 & 10.2209 & -0.220889 \tabularnewline
105 & 10 & 10.3234 & -0.323438 \tabularnewline
106 & 10 & 9.67195 & 0.32805 \tabularnewline
107 & 10 & 9.84496 & 0.155038 \tabularnewline
108 & 10 & 9.97299 & 0.0270068 \tabularnewline
109 & 10 & 10.3512 & -0.35117 \tabularnewline
110 & 10 & 10.1923 & -0.192323 \tabularnewline
111 & 10 & 10.1953 & -0.195307 \tabularnewline
112 & 10 & 10.1428 & -0.142777 \tabularnewline
113 & 10 & 10.3275 & -0.327492 \tabularnewline
114 & 10 & 10.0269 & -0.0268847 \tabularnewline
115 & 10 & 9.66313 & 0.336875 \tabularnewline
116 & 10 & 9.9302 & 0.0697957 \tabularnewline
117 & 10 & 10.1141 & -0.114109 \tabularnewline
118 & 10 & 10.0606 & -0.0606444 \tabularnewline
119 & 10 & 10.1146 & -0.114552 \tabularnewline
120 & 10 & 10.1668 & -0.166838 \tabularnewline
121 & 10 & 10.0428 & -0.0427813 \tabularnewline
122 & 10 & 10.1542 & -0.154192 \tabularnewline
123 & 10 & 9.64626 & 0.353736 \tabularnewline
124 & 10 & 9.79773 & 0.202272 \tabularnewline
125 & 10 & 10.0078 & -0.00781739 \tabularnewline
126 & 10 & 9.86984 & 0.130162 \tabularnewline
127 & 10 & 9.5397 & 0.460298 \tabularnewline
128 & 10 & 9.88909 & 0.110913 \tabularnewline
129 & 10 & 10.1632 & -0.163247 \tabularnewline
130 & 10 & 10.0993 & -0.0993271 \tabularnewline
131 & 10 & 10.8738 & -0.873794 \tabularnewline
132 & 10 & 9.92834 & 0.071659 \tabularnewline
133 & 10 & 10.3379 & -0.337938 \tabularnewline
134 & 10 & 9.94118 & 0.0588158 \tabularnewline
135 & 10 & 10.0945 & -0.0945013 \tabularnewline
136 & 10 & 10.5801 & -0.580132 \tabularnewline
137 & 10 & 9.87387 & 0.12613 \tabularnewline
138 & 10 & 10.4025 & -0.402471 \tabularnewline
139 & 10 & 10.112 & -0.112048 \tabularnewline
140 & 10 & 10.4839 & -0.483871 \tabularnewline
141 & 10 & 9.84048 & 0.159522 \tabularnewline
142 & 10 & 10.3536 & -0.353574 \tabularnewline
143 & 10 & 9.99372 & 0.00627626 \tabularnewline
144 & 10 & 10.0302 & -0.0301854 \tabularnewline
145 & 10 & 10.3225 & -0.322487 \tabularnewline
146 & 10 & 9.71724 & 0.28276 \tabularnewline
147 & 10 & 10.0395 & -0.0395463 \tabularnewline
148 & 10 & 10.0386 & -0.0386287 \tabularnewline
149 & 10 & 10.5699 & -0.569901 \tabularnewline
150 & 10 & 10.4359 & -0.435916 \tabularnewline
151 & 10 & 10.0565 & -0.0565009 \tabularnewline
152 & 10 & 9.96492 & 0.0350763 \tabularnewline
153 & 10 & 10.2503 & -0.250348 \tabularnewline
154 & 9 & 10.4547 & -1.45474 \tabularnewline
155 & 10 & 10.636 & -0.635956 \tabularnewline
156 & 10 & 9.60951 & 0.390489 \tabularnewline
157 & 10 & 10.4204 & -0.420418 \tabularnewline
158 & 10 & 9.88909 & 0.110913 \tabularnewline
159 & 10 & 10.0444 & -0.0443843 \tabularnewline
160 & 10 & 10.8475 & -0.847538 \tabularnewline
161 & 10 & 10.2792 & -0.279237 \tabularnewline
162 & 11 & 10.7028 & 0.297167 \tabularnewline
163 & 11 & 10.6073 & 0.392721 \tabularnewline
164 & 11 & 9.94129 & 1.05871 \tabularnewline
165 & 11 & 10.4747 & 0.525345 \tabularnewline
166 & 11 & 10.9589 & 0.0410954 \tabularnewline
167 & 11 & 10.2426 & 0.757374 \tabularnewline
168 & 11 & 10.5981 & 0.401929 \tabularnewline
169 & 11 & 10.569 & 0.431017 \tabularnewline
170 & 11 & 10.6519 & 0.348117 \tabularnewline
171 & 11 & 10.5176 & 0.482376 \tabularnewline
172 & 11 & 9.80433 & 1.19567 \tabularnewline
173 & 11 & 10.3561 & 0.643857 \tabularnewline
174 & 11 & 10.721 & 0.27903 \tabularnewline
175 & 11 & 10.0252 & 0.974825 \tabularnewline
176 & 11 & 10.2244 & 0.775551 \tabularnewline
177 & 11 & 10.4748 & 0.525223 \tabularnewline
178 & 11 & 10.6444 & 0.355611 \tabularnewline
179 & 11 & 9.99026 & 1.00974 \tabularnewline
180 & 11 & 10.5117 & 0.48833 \tabularnewline
181 & 11 & 9.65273 & 1.34727 \tabularnewline
182 & 11 & 10.3127 & 0.68733 \tabularnewline
183 & 11 & 9.57764 & 1.42236 \tabularnewline
184 & 11 & 9.92031 & 1.07969 \tabularnewline
185 & 11 & 10.754 & 0.245986 \tabularnewline
186 & 11 & 10.3698 & 0.630163 \tabularnewline
187 & 11 & 10.0065 & 0.993542 \tabularnewline
188 & 11 & 10.3783 & 0.621691 \tabularnewline
189 & 11 & 10.564 & 0.436005 \tabularnewline
190 & 11 & 10.7948 & 0.205204 \tabularnewline
191 & 11 & 10.3059 & 0.694127 \tabularnewline
192 & 11 & 9.88369 & 1.11631 \tabularnewline
193 & 11 & 10.6026 & 0.397351 \tabularnewline
194 & 11 & 9.9836 & 1.0164 \tabularnewline
195 & 11 & 10.2491 & 0.750903 \tabularnewline
196 & 11 & 9.94441 & 1.05559 \tabularnewline
197 & 11 & 10.3261 & 0.6739 \tabularnewline
198 & 11 & 10.2292 & 0.770804 \tabularnewline
199 & 11 & 10.567 & 0.433015 \tabularnewline
200 & 11 & 10.3587 & 0.641306 \tabularnewline
201 & 11 & 10.2704 & 0.729622 \tabularnewline
202 & 11 & 10.3738 & 0.626151 \tabularnewline
203 & 11 & 10.3406 & 0.65943 \tabularnewline
204 & 11 & 9.99138 & 1.00862 \tabularnewline
205 & 11 & 10.1357 & 0.864317 \tabularnewline
206 & 11 & 10.0551 & 0.944945 \tabularnewline
207 & 11 & 9.99293 & 1.00707 \tabularnewline
208 & 11 & 9.72409 & 1.27591 \tabularnewline
209 & 11 & 10.2864 & 0.713568 \tabularnewline
210 & 11 & 10.1538 & 0.846189 \tabularnewline
211 & 11 & 10.3997 & 0.600305 \tabularnewline
212 & 11 & 9.99733 & 1.00267 \tabularnewline
213 & 11 & 10.5498 & 0.450199 \tabularnewline
214 & 11 & 10.4896 & 0.510369 \tabularnewline
215 & 11 & 10.154 & 0.845989 \tabularnewline
216 & 11 & 10.1055 & 0.894481 \tabularnewline
217 & 11 & 9.92307 & 1.07693 \tabularnewline
218 & 11 & 10.067 & 0.932991 \tabularnewline
219 & 11 & 10.692 & 0.308041 \tabularnewline
220 & 11 & 10.0243 & 0.975708 \tabularnewline
221 & 11 & 10.2543 & 0.745687 \tabularnewline
222 & 11 & 9.94396 & 1.05604 \tabularnewline
223 & 11 & 10.3154 & 0.68462 \tabularnewline
224 & 11 & 10.2255 & 0.77446 \tabularnewline
225 & 11 & 10.7592 & 0.240808 \tabularnewline
226 & 11 & 10.6984 & 0.301628 \tabularnewline
227 & 11 & 9.76302 & 1.23698 \tabularnewline
228 & 11 & 10.3293 & 0.670658 \tabularnewline
229 & 11 & 10.8011 & 0.198851 \tabularnewline
230 & 11 & 10.4177 & 0.582281 \tabularnewline
231 & 11 & 10.3274 & 0.672591 \tabularnewline
232 & 11 & 10.588 & 0.412029 \tabularnewline
233 & 11 & 9.91611 & 1.08389 \tabularnewline
234 & 11 & 9.64941 & 1.35059 \tabularnewline
235 & 11 & 10.0016 & 0.998387 \tabularnewline
236 & 11 & 10.3905 & 0.609456 \tabularnewline
237 & 11 & 10.9484 & 0.0516334 \tabularnewline
238 & 11 & 9.75747 & 1.24253 \tabularnewline
239 & 11 & 10.2089 & 0.791142 \tabularnewline
240 & 11 & 10.5085 & 0.491527 \tabularnewline
241 & 11 & 10.7299 & 0.270057 \tabularnewline
242 & 11 & 10.3816 & 0.618444 \tabularnewline
243 & 11 & 10.846 & 0.154046 \tabularnewline
244 & 11 & 10.4648 & 0.535205 \tabularnewline
245 & 11 & 9.99726 & 1.00274 \tabularnewline
246 & 11 & 10.8094 & 0.190592 \tabularnewline
247 & 11 & 10.266 & 0.733991 \tabularnewline
248 & 11 & 10.2996 & 0.700368 \tabularnewline
249 & 11 & 10.8318 & 0.168212 \tabularnewline
250 & 11 & 10.6357 & 0.364308 \tabularnewline
251 & 11 & 10.5357 & 0.4643 \tabularnewline
252 & 11 & 10.7875 & 0.212491 \tabularnewline
253 & 11 & 10.334 & 0.666009 \tabularnewline
254 & 11 & 10.0976 & 0.902391 \tabularnewline
255 & 11 & 10.2673 & 0.732691 \tabularnewline
256 & 11 & 10.1281 & 0.871875 \tabularnewline
257 & 11 & 10.5211 & 0.478899 \tabularnewline
258 & 11 & 10.483 & 0.517049 \tabularnewline
259 & 11 & 10.0581 & 0.94194 \tabularnewline
260 & 11 & 11.0864 & -0.0864378 \tabularnewline
261 & 11 & 10.1413 & 0.858688 \tabularnewline
262 & 11 & 10.1847 & 0.815317 \tabularnewline
263 & 11 & 10.7222 & 0.27783 \tabularnewline
264 & 11 & 10.3244 & 0.675564 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221533&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]9[/C][C]9.74358[/C][C]-0.743583[/C][/ROW]
[ROW][C]2[/C][C]9[/C][C]9.73264[/C][C]-0.732641[/C][/ROW]
[ROW][C]3[/C][C]9[/C][C]9.79526[/C][C]-0.795256[/C][/ROW]
[ROW][C]4[/C][C]9[/C][C]10.328[/C][C]-1.32805[/C][/ROW]
[ROW][C]5[/C][C]9[/C][C]10.2725[/C][C]-1.27253[/C][/ROW]
[ROW][C]6[/C][C]9[/C][C]10.0544[/C][C]-1.05444[/C][/ROW]
[ROW][C]7[/C][C]9[/C][C]9.52668[/C][C]-0.526679[/C][/ROW]
[ROW][C]8[/C][C]9[/C][C]9.96808[/C][C]-0.968084[/C][/ROW]
[ROW][C]9[/C][C]9[/C][C]9.92382[/C][C]-0.923818[/C][/ROW]
[ROW][C]10[/C][C]9[/C][C]10.0618[/C][C]-1.06181[/C][/ROW]
[ROW][C]11[/C][C]9[/C][C]9.74615[/C][C]-0.746152[/C][/ROW]
[ROW][C]12[/C][C]9[/C][C]9.34481[/C][C]-0.344813[/C][/ROW]
[ROW][C]13[/C][C]9[/C][C]9.98476[/C][C]-0.984764[/C][/ROW]
[ROW][C]14[/C][C]9[/C][C]9.6327[/C][C]-0.632699[/C][/ROW]
[ROW][C]15[/C][C]9[/C][C]9.73077[/C][C]-0.730773[/C][/ROW]
[ROW][C]16[/C][C]9[/C][C]9.921[/C][C]-0.921002[/C][/ROW]
[ROW][C]17[/C][C]9[/C][C]10.1208[/C][C]-1.12076[/C][/ROW]
[ROW][C]18[/C][C]9[/C][C]9.60894[/C][C]-0.608936[/C][/ROW]
[ROW][C]19[/C][C]9[/C][C]9.51691[/C][C]-0.516912[/C][/ROW]
[ROW][C]20[/C][C]9[/C][C]9.71025[/C][C]-0.710251[/C][/ROW]
[ROW][C]21[/C][C]9[/C][C]9.68379[/C][C]-0.683794[/C][/ROW]
[ROW][C]22[/C][C]9[/C][C]10.0442[/C][C]-1.04415[/C][/ROW]
[ROW][C]23[/C][C]9[/C][C]9.39031[/C][C]-0.390313[/C][/ROW]
[ROW][C]24[/C][C]9[/C][C]9.78467[/C][C]-0.78467[/C][/ROW]
[ROW][C]25[/C][C]9[/C][C]9.7334[/C][C]-0.733402[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]9.88493[/C][C]-0.884931[/C][/ROW]
[ROW][C]27[/C][C]9[/C][C]10.0038[/C][C]-1.0038[/C][/ROW]
[ROW][C]28[/C][C]9[/C][C]9.94391[/C][C]-0.943912[/C][/ROW]
[ROW][C]29[/C][C]9[/C][C]10.1204[/C][C]-1.1204[/C][/ROW]
[ROW][C]30[/C][C]9[/C][C]10.1149[/C][C]-1.1149[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]9.95856[/C][C]-0.95856[/C][/ROW]
[ROW][C]32[/C][C]9[/C][C]10.4421[/C][C]-1.44208[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]9.84498[/C][C]-0.844979[/C][/ROW]
[ROW][C]34[/C][C]9[/C][C]9.91042[/C][C]-0.910421[/C][/ROW]
[ROW][C]35[/C][C]9[/C][C]10.1828[/C][C]-1.18278[/C][/ROW]
[ROW][C]36[/C][C]9[/C][C]10.3038[/C][C]-1.30383[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.9284[/C][C]-1.92843[/C][/ROW]
[ROW][C]38[/C][C]9[/C][C]9.94568[/C][C]-0.945683[/C][/ROW]
[ROW][C]39[/C][C]9[/C][C]9.99762[/C][C]-0.997617[/C][/ROW]
[ROW][C]40[/C][C]9[/C][C]9.92396[/C][C]-0.923962[/C][/ROW]
[ROW][C]41[/C][C]9[/C][C]9.80798[/C][C]-0.807984[/C][/ROW]
[ROW][C]42[/C][C]9[/C][C]10.1127[/C][C]-1.11274[/C][/ROW]
[ROW][C]43[/C][C]9[/C][C]9.03676[/C][C]-0.0367589[/C][/ROW]
[ROW][C]44[/C][C]9[/C][C]10.0427[/C][C]-1.04267[/C][/ROW]
[ROW][C]45[/C][C]9[/C][C]9.88309[/C][C]-0.883093[/C][/ROW]
[ROW][C]46[/C][C]9[/C][C]10.3137[/C][C]-1.31371[/C][/ROW]
[ROW][C]47[/C][C]9[/C][C]9.6047[/C][C]-0.604703[/C][/ROW]
[ROW][C]48[/C][C]9[/C][C]10.0074[/C][C]-1.00745[/C][/ROW]
[ROW][C]49[/C][C]9[/C][C]10.0321[/C][C]-1.03214[/C][/ROW]
[ROW][C]50[/C][C]9[/C][C]9.99586[/C][C]-0.995855[/C][/ROW]
[ROW][C]51[/C][C]9[/C][C]9.77712[/C][C]-0.777115[/C][/ROW]
[ROW][C]52[/C][C]9[/C][C]10.1947[/C][C]-1.19473[/C][/ROW]
[ROW][C]53[/C][C]9[/C][C]10.4726[/C][C]-1.47256[/C][/ROW]
[ROW][C]54[/C][C]9[/C][C]9.66434[/C][C]-0.664337[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]10.7128[/C][C]-1.71279[/C][/ROW]
[ROW][C]56[/C][C]9[/C][C]10.2722[/C][C]-1.27221[/C][/ROW]
[ROW][C]57[/C][C]9[/C][C]9.76498[/C][C]-0.764982[/C][/ROW]
[ROW][C]58[/C][C]9[/C][C]9.83626[/C][C]-0.836258[/C][/ROW]
[ROW][C]59[/C][C]9[/C][C]10.0413[/C][C]-1.04126[/C][/ROW]
[ROW][C]60[/C][C]9[/C][C]10.1207[/C][C]-1.1207[/C][/ROW]
[ROW][C]61[/C][C]9[/C][C]10.7367[/C][C]-1.73675[/C][/ROW]
[ROW][C]62[/C][C]9[/C][C]9.97973[/C][C]-0.979726[/C][/ROW]
[ROW][C]63[/C][C]9[/C][C]10.0887[/C][C]-1.08865[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]10.0407[/C][C]-1.04073[/C][/ROW]
[ROW][C]65[/C][C]9[/C][C]9.69762[/C][C]-0.697625[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]10.0296[/C][C]-0.0295678[/C][/ROW]
[ROW][C]67[/C][C]10[/C][C]9.82466[/C][C]0.175339[/C][/ROW]
[ROW][C]68[/C][C]10[/C][C]10.125[/C][C]-0.124964[/C][/ROW]
[ROW][C]69[/C][C]10[/C][C]9.97335[/C][C]0.0266514[/C][/ROW]
[ROW][C]70[/C][C]10[/C][C]9.90612[/C][C]0.0938757[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]10.2251[/C][C]-0.2251[/C][/ROW]
[ROW][C]72[/C][C]10[/C][C]10.0024[/C][C]-0.00236136[/C][/ROW]
[ROW][C]73[/C][C]10[/C][C]9.88867[/C][C]0.111334[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]9.59143[/C][C]0.408565[/C][/ROW]
[ROW][C]75[/C][C]10[/C][C]10.0692[/C][C]-0.0692293[/C][/ROW]
[ROW][C]76[/C][C]10[/C][C]10.2031[/C][C]-0.203149[/C][/ROW]
[ROW][C]77[/C][C]10[/C][C]9.69659[/C][C]0.303406[/C][/ROW]
[ROW][C]78[/C][C]10[/C][C]10.044[/C][C]-0.0440461[/C][/ROW]
[ROW][C]79[/C][C]10[/C][C]10.2972[/C][C]-0.297236[/C][/ROW]
[ROW][C]80[/C][C]10[/C][C]9.55281[/C][C]0.447185[/C][/ROW]
[ROW][C]81[/C][C]10[/C][C]10.0445[/C][C]-0.0445381[/C][/ROW]
[ROW][C]82[/C][C]10[/C][C]9.71568[/C][C]0.284315[/C][/ROW]
[ROW][C]83[/C][C]10[/C][C]9.88002[/C][C]0.119975[/C][/ROW]
[ROW][C]84[/C][C]10[/C][C]10.0378[/C][C]-0.0378376[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]10.1008[/C][C]-0.100803[/C][/ROW]
[ROW][C]86[/C][C]10[/C][C]10.1374[/C][C]-0.137416[/C][/ROW]
[ROW][C]87[/C][C]10[/C][C]9.92305[/C][C]0.0769539[/C][/ROW]
[ROW][C]88[/C][C]10[/C][C]9.9823[/C][C]0.0176968[/C][/ROW]
[ROW][C]89[/C][C]10[/C][C]10.5669[/C][C]-0.566852[/C][/ROW]
[ROW][C]90[/C][C]10[/C][C]10.2526[/C][C]-0.252634[/C][/ROW]
[ROW][C]91[/C][C]10[/C][C]9.60951[/C][C]0.390489[/C][/ROW]
[ROW][C]92[/C][C]10[/C][C]10.017[/C][C]-0.0170001[/C][/ROW]
[ROW][C]93[/C][C]10[/C][C]10.2755[/C][C]-0.275466[/C][/ROW]
[ROW][C]94[/C][C]10[/C][C]10.4259[/C][C]-0.425935[/C][/ROW]
[ROW][C]95[/C][C]10[/C][C]9.91918[/C][C]0.0808183[/C][/ROW]
[ROW][C]96[/C][C]10[/C][C]9.94935[/C][C]0.0506526[/C][/ROW]
[ROW][C]97[/C][C]10[/C][C]10.0917[/C][C]-0.091653[/C][/ROW]
[ROW][C]98[/C][C]10[/C][C]9.83758[/C][C]0.162416[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]10.149[/C][C]-0.14899[/C][/ROW]
[ROW][C]100[/C][C]10[/C][C]9.65398[/C][C]0.346018[/C][/ROW]
[ROW][C]101[/C][C]10[/C][C]10.0893[/C][C]-0.0892965[/C][/ROW]
[ROW][C]102[/C][C]10[/C][C]9.58006[/C][C]0.419935[/C][/ROW]
[ROW][C]103[/C][C]10[/C][C]10.0139[/C][C]-0.0138602[/C][/ROW]
[ROW][C]104[/C][C]10[/C][C]10.2209[/C][C]-0.220889[/C][/ROW]
[ROW][C]105[/C][C]10[/C][C]10.3234[/C][C]-0.323438[/C][/ROW]
[ROW][C]106[/C][C]10[/C][C]9.67195[/C][C]0.32805[/C][/ROW]
[ROW][C]107[/C][C]10[/C][C]9.84496[/C][C]0.155038[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]9.97299[/C][C]0.0270068[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]10.3512[/C][C]-0.35117[/C][/ROW]
[ROW][C]110[/C][C]10[/C][C]10.1923[/C][C]-0.192323[/C][/ROW]
[ROW][C]111[/C][C]10[/C][C]10.1953[/C][C]-0.195307[/C][/ROW]
[ROW][C]112[/C][C]10[/C][C]10.1428[/C][C]-0.142777[/C][/ROW]
[ROW][C]113[/C][C]10[/C][C]10.3275[/C][C]-0.327492[/C][/ROW]
[ROW][C]114[/C][C]10[/C][C]10.0269[/C][C]-0.0268847[/C][/ROW]
[ROW][C]115[/C][C]10[/C][C]9.66313[/C][C]0.336875[/C][/ROW]
[ROW][C]116[/C][C]10[/C][C]9.9302[/C][C]0.0697957[/C][/ROW]
[ROW][C]117[/C][C]10[/C][C]10.1141[/C][C]-0.114109[/C][/ROW]
[ROW][C]118[/C][C]10[/C][C]10.0606[/C][C]-0.0606444[/C][/ROW]
[ROW][C]119[/C][C]10[/C][C]10.1146[/C][C]-0.114552[/C][/ROW]
[ROW][C]120[/C][C]10[/C][C]10.1668[/C][C]-0.166838[/C][/ROW]
[ROW][C]121[/C][C]10[/C][C]10.0428[/C][C]-0.0427813[/C][/ROW]
[ROW][C]122[/C][C]10[/C][C]10.1542[/C][C]-0.154192[/C][/ROW]
[ROW][C]123[/C][C]10[/C][C]9.64626[/C][C]0.353736[/C][/ROW]
[ROW][C]124[/C][C]10[/C][C]9.79773[/C][C]0.202272[/C][/ROW]
[ROW][C]125[/C][C]10[/C][C]10.0078[/C][C]-0.00781739[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]9.86984[/C][C]0.130162[/C][/ROW]
[ROW][C]127[/C][C]10[/C][C]9.5397[/C][C]0.460298[/C][/ROW]
[ROW][C]128[/C][C]10[/C][C]9.88909[/C][C]0.110913[/C][/ROW]
[ROW][C]129[/C][C]10[/C][C]10.1632[/C][C]-0.163247[/C][/ROW]
[ROW][C]130[/C][C]10[/C][C]10.0993[/C][C]-0.0993271[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]10.8738[/C][C]-0.873794[/C][/ROW]
[ROW][C]132[/C][C]10[/C][C]9.92834[/C][C]0.071659[/C][/ROW]
[ROW][C]133[/C][C]10[/C][C]10.3379[/C][C]-0.337938[/C][/ROW]
[ROW][C]134[/C][C]10[/C][C]9.94118[/C][C]0.0588158[/C][/ROW]
[ROW][C]135[/C][C]10[/C][C]10.0945[/C][C]-0.0945013[/C][/ROW]
[ROW][C]136[/C][C]10[/C][C]10.5801[/C][C]-0.580132[/C][/ROW]
[ROW][C]137[/C][C]10[/C][C]9.87387[/C][C]0.12613[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]10.4025[/C][C]-0.402471[/C][/ROW]
[ROW][C]139[/C][C]10[/C][C]10.112[/C][C]-0.112048[/C][/ROW]
[ROW][C]140[/C][C]10[/C][C]10.4839[/C][C]-0.483871[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]9.84048[/C][C]0.159522[/C][/ROW]
[ROW][C]142[/C][C]10[/C][C]10.3536[/C][C]-0.353574[/C][/ROW]
[ROW][C]143[/C][C]10[/C][C]9.99372[/C][C]0.00627626[/C][/ROW]
[ROW][C]144[/C][C]10[/C][C]10.0302[/C][C]-0.0301854[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]10.3225[/C][C]-0.322487[/C][/ROW]
[ROW][C]146[/C][C]10[/C][C]9.71724[/C][C]0.28276[/C][/ROW]
[ROW][C]147[/C][C]10[/C][C]10.0395[/C][C]-0.0395463[/C][/ROW]
[ROW][C]148[/C][C]10[/C][C]10.0386[/C][C]-0.0386287[/C][/ROW]
[ROW][C]149[/C][C]10[/C][C]10.5699[/C][C]-0.569901[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]10.4359[/C][C]-0.435916[/C][/ROW]
[ROW][C]151[/C][C]10[/C][C]10.0565[/C][C]-0.0565009[/C][/ROW]
[ROW][C]152[/C][C]10[/C][C]9.96492[/C][C]0.0350763[/C][/ROW]
[ROW][C]153[/C][C]10[/C][C]10.2503[/C][C]-0.250348[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]10.4547[/C][C]-1.45474[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]10.636[/C][C]-0.635956[/C][/ROW]
[ROW][C]156[/C][C]10[/C][C]9.60951[/C][C]0.390489[/C][/ROW]
[ROW][C]157[/C][C]10[/C][C]10.4204[/C][C]-0.420418[/C][/ROW]
[ROW][C]158[/C][C]10[/C][C]9.88909[/C][C]0.110913[/C][/ROW]
[ROW][C]159[/C][C]10[/C][C]10.0444[/C][C]-0.0443843[/C][/ROW]
[ROW][C]160[/C][C]10[/C][C]10.8475[/C][C]-0.847538[/C][/ROW]
[ROW][C]161[/C][C]10[/C][C]10.2792[/C][C]-0.279237[/C][/ROW]
[ROW][C]162[/C][C]11[/C][C]10.7028[/C][C]0.297167[/C][/ROW]
[ROW][C]163[/C][C]11[/C][C]10.6073[/C][C]0.392721[/C][/ROW]
[ROW][C]164[/C][C]11[/C][C]9.94129[/C][C]1.05871[/C][/ROW]
[ROW][C]165[/C][C]11[/C][C]10.4747[/C][C]0.525345[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]10.9589[/C][C]0.0410954[/C][/ROW]
[ROW][C]167[/C][C]11[/C][C]10.2426[/C][C]0.757374[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]10.5981[/C][C]0.401929[/C][/ROW]
[ROW][C]169[/C][C]11[/C][C]10.569[/C][C]0.431017[/C][/ROW]
[ROW][C]170[/C][C]11[/C][C]10.6519[/C][C]0.348117[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.5176[/C][C]0.482376[/C][/ROW]
[ROW][C]172[/C][C]11[/C][C]9.80433[/C][C]1.19567[/C][/ROW]
[ROW][C]173[/C][C]11[/C][C]10.3561[/C][C]0.643857[/C][/ROW]
[ROW][C]174[/C][C]11[/C][C]10.721[/C][C]0.27903[/C][/ROW]
[ROW][C]175[/C][C]11[/C][C]10.0252[/C][C]0.974825[/C][/ROW]
[ROW][C]176[/C][C]11[/C][C]10.2244[/C][C]0.775551[/C][/ROW]
[ROW][C]177[/C][C]11[/C][C]10.4748[/C][C]0.525223[/C][/ROW]
[ROW][C]178[/C][C]11[/C][C]10.6444[/C][C]0.355611[/C][/ROW]
[ROW][C]179[/C][C]11[/C][C]9.99026[/C][C]1.00974[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]10.5117[/C][C]0.48833[/C][/ROW]
[ROW][C]181[/C][C]11[/C][C]9.65273[/C][C]1.34727[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]10.3127[/C][C]0.68733[/C][/ROW]
[ROW][C]183[/C][C]11[/C][C]9.57764[/C][C]1.42236[/C][/ROW]
[ROW][C]184[/C][C]11[/C][C]9.92031[/C][C]1.07969[/C][/ROW]
[ROW][C]185[/C][C]11[/C][C]10.754[/C][C]0.245986[/C][/ROW]
[ROW][C]186[/C][C]11[/C][C]10.3698[/C][C]0.630163[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]10.0065[/C][C]0.993542[/C][/ROW]
[ROW][C]188[/C][C]11[/C][C]10.3783[/C][C]0.621691[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]10.564[/C][C]0.436005[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.7948[/C][C]0.205204[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]10.3059[/C][C]0.694127[/C][/ROW]
[ROW][C]192[/C][C]11[/C][C]9.88369[/C][C]1.11631[/C][/ROW]
[ROW][C]193[/C][C]11[/C][C]10.6026[/C][C]0.397351[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]9.9836[/C][C]1.0164[/C][/ROW]
[ROW][C]195[/C][C]11[/C][C]10.2491[/C][C]0.750903[/C][/ROW]
[ROW][C]196[/C][C]11[/C][C]9.94441[/C][C]1.05559[/C][/ROW]
[ROW][C]197[/C][C]11[/C][C]10.3261[/C][C]0.6739[/C][/ROW]
[ROW][C]198[/C][C]11[/C][C]10.2292[/C][C]0.770804[/C][/ROW]
[ROW][C]199[/C][C]11[/C][C]10.567[/C][C]0.433015[/C][/ROW]
[ROW][C]200[/C][C]11[/C][C]10.3587[/C][C]0.641306[/C][/ROW]
[ROW][C]201[/C][C]11[/C][C]10.2704[/C][C]0.729622[/C][/ROW]
[ROW][C]202[/C][C]11[/C][C]10.3738[/C][C]0.626151[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]10.3406[/C][C]0.65943[/C][/ROW]
[ROW][C]204[/C][C]11[/C][C]9.99138[/C][C]1.00862[/C][/ROW]
[ROW][C]205[/C][C]11[/C][C]10.1357[/C][C]0.864317[/C][/ROW]
[ROW][C]206[/C][C]11[/C][C]10.0551[/C][C]0.944945[/C][/ROW]
[ROW][C]207[/C][C]11[/C][C]9.99293[/C][C]1.00707[/C][/ROW]
[ROW][C]208[/C][C]11[/C][C]9.72409[/C][C]1.27591[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]10.2864[/C][C]0.713568[/C][/ROW]
[ROW][C]210[/C][C]11[/C][C]10.1538[/C][C]0.846189[/C][/ROW]
[ROW][C]211[/C][C]11[/C][C]10.3997[/C][C]0.600305[/C][/ROW]
[ROW][C]212[/C][C]11[/C][C]9.99733[/C][C]1.00267[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]10.5498[/C][C]0.450199[/C][/ROW]
[ROW][C]214[/C][C]11[/C][C]10.4896[/C][C]0.510369[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]10.154[/C][C]0.845989[/C][/ROW]
[ROW][C]216[/C][C]11[/C][C]10.1055[/C][C]0.894481[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]9.92307[/C][C]1.07693[/C][/ROW]
[ROW][C]218[/C][C]11[/C][C]10.067[/C][C]0.932991[/C][/ROW]
[ROW][C]219[/C][C]11[/C][C]10.692[/C][C]0.308041[/C][/ROW]
[ROW][C]220[/C][C]11[/C][C]10.0243[/C][C]0.975708[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]10.2543[/C][C]0.745687[/C][/ROW]
[ROW][C]222[/C][C]11[/C][C]9.94396[/C][C]1.05604[/C][/ROW]
[ROW][C]223[/C][C]11[/C][C]10.3154[/C][C]0.68462[/C][/ROW]
[ROW][C]224[/C][C]11[/C][C]10.2255[/C][C]0.77446[/C][/ROW]
[ROW][C]225[/C][C]11[/C][C]10.7592[/C][C]0.240808[/C][/ROW]
[ROW][C]226[/C][C]11[/C][C]10.6984[/C][C]0.301628[/C][/ROW]
[ROW][C]227[/C][C]11[/C][C]9.76302[/C][C]1.23698[/C][/ROW]
[ROW][C]228[/C][C]11[/C][C]10.3293[/C][C]0.670658[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]10.8011[/C][C]0.198851[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]10.4177[/C][C]0.582281[/C][/ROW]
[ROW][C]231[/C][C]11[/C][C]10.3274[/C][C]0.672591[/C][/ROW]
[ROW][C]232[/C][C]11[/C][C]10.588[/C][C]0.412029[/C][/ROW]
[ROW][C]233[/C][C]11[/C][C]9.91611[/C][C]1.08389[/C][/ROW]
[ROW][C]234[/C][C]11[/C][C]9.64941[/C][C]1.35059[/C][/ROW]
[ROW][C]235[/C][C]11[/C][C]10.0016[/C][C]0.998387[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]10.3905[/C][C]0.609456[/C][/ROW]
[ROW][C]237[/C][C]11[/C][C]10.9484[/C][C]0.0516334[/C][/ROW]
[ROW][C]238[/C][C]11[/C][C]9.75747[/C][C]1.24253[/C][/ROW]
[ROW][C]239[/C][C]11[/C][C]10.2089[/C][C]0.791142[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]10.5085[/C][C]0.491527[/C][/ROW]
[ROW][C]241[/C][C]11[/C][C]10.7299[/C][C]0.270057[/C][/ROW]
[ROW][C]242[/C][C]11[/C][C]10.3816[/C][C]0.618444[/C][/ROW]
[ROW][C]243[/C][C]11[/C][C]10.846[/C][C]0.154046[/C][/ROW]
[ROW][C]244[/C][C]11[/C][C]10.4648[/C][C]0.535205[/C][/ROW]
[ROW][C]245[/C][C]11[/C][C]9.99726[/C][C]1.00274[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.8094[/C][C]0.190592[/C][/ROW]
[ROW][C]247[/C][C]11[/C][C]10.266[/C][C]0.733991[/C][/ROW]
[ROW][C]248[/C][C]11[/C][C]10.2996[/C][C]0.700368[/C][/ROW]
[ROW][C]249[/C][C]11[/C][C]10.8318[/C][C]0.168212[/C][/ROW]
[ROW][C]250[/C][C]11[/C][C]10.6357[/C][C]0.364308[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]10.5357[/C][C]0.4643[/C][/ROW]
[ROW][C]252[/C][C]11[/C][C]10.7875[/C][C]0.212491[/C][/ROW]
[ROW][C]253[/C][C]11[/C][C]10.334[/C][C]0.666009[/C][/ROW]
[ROW][C]254[/C][C]11[/C][C]10.0976[/C][C]0.902391[/C][/ROW]
[ROW][C]255[/C][C]11[/C][C]10.2673[/C][C]0.732691[/C][/ROW]
[ROW][C]256[/C][C]11[/C][C]10.1281[/C][C]0.871875[/C][/ROW]
[ROW][C]257[/C][C]11[/C][C]10.5211[/C][C]0.478899[/C][/ROW]
[ROW][C]258[/C][C]11[/C][C]10.483[/C][C]0.517049[/C][/ROW]
[ROW][C]259[/C][C]11[/C][C]10.0581[/C][C]0.94194[/C][/ROW]
[ROW][C]260[/C][C]11[/C][C]11.0864[/C][C]-0.0864378[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]10.1413[/C][C]0.858688[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]10.1847[/C][C]0.815317[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]10.7222[/C][C]0.27783[/C][/ROW]
[ROW][C]264[/C][C]11[/C][C]10.3244[/C][C]0.675564[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221533&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221533&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
199.74358-0.743583
299.73264-0.732641
399.79526-0.795256
4910.328-1.32805
5910.2725-1.27253
6910.0544-1.05444
799.52668-0.526679
899.96808-0.968084
999.92382-0.923818
10910.0618-1.06181
1199.74615-0.746152
1299.34481-0.344813
1399.98476-0.984764
1499.6327-0.632699
1599.73077-0.730773
1699.921-0.921002
17910.1208-1.12076
1899.60894-0.608936
1999.51691-0.516912
2099.71025-0.710251
2199.68379-0.683794
22910.0442-1.04415
2399.39031-0.390313
2499.78467-0.78467
2599.7334-0.733402
2699.88493-0.884931
27910.0038-1.0038
2899.94391-0.943912
29910.1204-1.1204
30910.1149-1.1149
3199.95856-0.95856
32910.4421-1.44208
3399.84498-0.844979
3499.91042-0.910421
35910.1828-1.18278
36910.3038-1.30383
37910.9284-1.92843
3899.94568-0.945683
3999.99762-0.997617
4099.92396-0.923962
4199.80798-0.807984
42910.1127-1.11274
4399.03676-0.0367589
44910.0427-1.04267
4599.88309-0.883093
46910.3137-1.31371
4799.6047-0.604703
48910.0074-1.00745
49910.0321-1.03214
5099.99586-0.995855
5199.77712-0.777115
52910.1947-1.19473
53910.4726-1.47256
5499.66434-0.664337
55910.7128-1.71279
56910.2722-1.27221
5799.76498-0.764982
5899.83626-0.836258
59910.0413-1.04126
60910.1207-1.1207
61910.7367-1.73675
6299.97973-0.979726
63910.0887-1.08865
64910.0407-1.04073
6599.69762-0.697625
661010.0296-0.0295678
67109.824660.175339
681010.125-0.124964
69109.973350.0266514
70109.906120.0938757
711010.2251-0.2251
721010.0024-0.00236136
73109.888670.111334
74109.591430.408565
751010.0692-0.0692293
761010.2031-0.203149
77109.696590.303406
781010.044-0.0440461
791010.2972-0.297236
80109.552810.447185
811010.0445-0.0445381
82109.715680.284315
83109.880020.119975
841010.0378-0.0378376
851010.1008-0.100803
861010.1374-0.137416
87109.923050.0769539
88109.98230.0176968
891010.5669-0.566852
901010.2526-0.252634
91109.609510.390489
921010.017-0.0170001
931010.2755-0.275466
941010.4259-0.425935
95109.919180.0808183
96109.949350.0506526
971010.0917-0.091653
98109.837580.162416
991010.149-0.14899
100109.653980.346018
1011010.0893-0.0892965
102109.580060.419935
1031010.0139-0.0138602
1041010.2209-0.220889
1051010.3234-0.323438
106109.671950.32805
107109.844960.155038
108109.972990.0270068
1091010.3512-0.35117
1101010.1923-0.192323
1111010.1953-0.195307
1121010.1428-0.142777
1131010.3275-0.327492
1141010.0269-0.0268847
115109.663130.336875
116109.93020.0697957
1171010.1141-0.114109
1181010.0606-0.0606444
1191010.1146-0.114552
1201010.1668-0.166838
1211010.0428-0.0427813
1221010.1542-0.154192
123109.646260.353736
124109.797730.202272
1251010.0078-0.00781739
126109.869840.130162
127109.53970.460298
128109.889090.110913
1291010.1632-0.163247
1301010.0993-0.0993271
1311010.8738-0.873794
132109.928340.071659
1331010.3379-0.337938
134109.941180.0588158
1351010.0945-0.0945013
1361010.5801-0.580132
137109.873870.12613
1381010.4025-0.402471
1391010.112-0.112048
1401010.4839-0.483871
141109.840480.159522
1421010.3536-0.353574
143109.993720.00627626
1441010.0302-0.0301854
1451010.3225-0.322487
146109.717240.28276
1471010.0395-0.0395463
1481010.0386-0.0386287
1491010.5699-0.569901
1501010.4359-0.435916
1511010.0565-0.0565009
152109.964920.0350763
1531010.2503-0.250348
154910.4547-1.45474
1551010.636-0.635956
156109.609510.390489
1571010.4204-0.420418
158109.889090.110913
1591010.0444-0.0443843
1601010.8475-0.847538
1611010.2792-0.279237
1621110.70280.297167
1631110.60730.392721
164119.941291.05871
1651110.47470.525345
1661110.95890.0410954
1671110.24260.757374
1681110.59810.401929
1691110.5690.431017
1701110.65190.348117
1711110.51760.482376
172119.804331.19567
1731110.35610.643857
1741110.7210.27903
1751110.02520.974825
1761110.22440.775551
1771110.47480.525223
1781110.64440.355611
179119.990261.00974
1801110.51170.48833
181119.652731.34727
1821110.31270.68733
183119.577641.42236
184119.920311.07969
1851110.7540.245986
1861110.36980.630163
1871110.00650.993542
1881110.37830.621691
1891110.5640.436005
1901110.79480.205204
1911110.30590.694127
192119.883691.11631
1931110.60260.397351
194119.98361.0164
1951110.24910.750903
196119.944411.05559
1971110.32610.6739
1981110.22920.770804
1991110.5670.433015
2001110.35870.641306
2011110.27040.729622
2021110.37380.626151
2031110.34060.65943
204119.991381.00862
2051110.13570.864317
2061110.05510.944945
207119.992931.00707
208119.724091.27591
2091110.28640.713568
2101110.15380.846189
2111110.39970.600305
212119.997331.00267
2131110.54980.450199
2141110.48960.510369
2151110.1540.845989
2161110.10550.894481
217119.923071.07693
2181110.0670.932991
2191110.6920.308041
2201110.02430.975708
2211110.25430.745687
222119.943961.05604
2231110.31540.68462
2241110.22550.77446
2251110.75920.240808
2261110.69840.301628
227119.763021.23698
2281110.32930.670658
2291110.80110.198851
2301110.41770.582281
2311110.32740.672591
2321110.5880.412029
233119.916111.08389
234119.649411.35059
2351110.00160.998387
2361110.39050.609456
2371110.94840.0516334
238119.757471.24253
2391110.20890.791142
2401110.50850.491527
2411110.72990.270057
2421110.38160.618444
2431110.8460.154046
2441110.46480.535205
245119.997261.00274
2461110.80940.190592
2471110.2660.733991
2481110.29960.700368
2491110.83180.168212
2501110.63570.364308
2511110.53570.4643
2521110.78750.212491
2531110.3340.666009
2541110.09760.902391
2551110.26730.732691
2561110.12810.871875
2571110.52110.478899
2581110.4830.517049
2591110.05810.94194
2601111.0864-0.0864378
2611110.14130.858688
2621110.18470.815317
2631110.72220.27783
2641110.32440.675564






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
125.5018e-461.10036e-451
138.39802e-611.6796e-601
145.12774e-731.02555e-721
151.96503e-873.93005e-871
16001
174.22911e-1178.45823e-1171
185.55375e-1331.11075e-1321
192.02686e-1484.05372e-1481
202.29765e-1704.5953e-1701
213.16024e-1806.32048e-1801
224.9844e-1939.96881e-1931
237.32207e-2051.46441e-2041
243.98502e-2277.97005e-2271
255.84942e-2411.16988e-2401
266.77694e-2591.35539e-2581
271.66572e-2693.33144e-2691
286.79586e-2831.35917e-2821
297.84603e-3081.56921e-3071
301.42307e-3042.84613e-3041
31001
32001
33001
34001
35001
36001
37001
38001
39001
40001
41001
42001
43001
44001
45001
46001
47001
48001
49001
50001
51001
52001
53001
54001
55001
56001
57001
58001
59001
60001
61001
62001
63001
64001
65001
661.65709e-223.31419e-221
678.78939e-161.75788e-151
687.05244e-131.41049e-121
693.08186e-096.16372e-091
701.38878e-072.77756e-071
715.86432e-061.17286e-050.999994
724.08778e-058.17555e-050.999959
730.0001090740.0002181480.999891
740.0001838450.000367690.999816
750.001165780.002331560.998834
760.002716140.005432280.997284
770.005400640.01080130.994599
780.0105770.0211540.989423
790.02080090.04160190.979199
800.04523870.09047740.954761
810.05962290.1192460.940377
820.08439660.1687930.915603
830.108560.2171210.89144
840.1386210.2772410.861379
850.1695350.3390710.830465
860.1977440.3954890.802256
870.2266210.4532430.773379
880.2592720.5185430.740728
890.2719820.5439650.728018
900.3158240.6316490.684176
910.3398580.6797170.660142
920.342070.684140.65793
930.3598930.7197860.640107
940.3843090.7686170.615691
950.4075720.8151440.592428
960.4186580.8373150.581342
970.4498580.8997160.550142
980.4606780.9213560.539322
990.486160.972320.51384
1000.4922160.9844320.507784
1010.5016690.9966620.498331
1020.48130.9625990.5187
1030.5357210.9285580.464279
1040.5245630.9508740.475437
1050.5459710.9080580.454029
1060.5563530.8872940.443647
1070.5508460.8983090.449154
1080.5759780.8480450.424022
1090.5913390.8173220.408661
1100.588340.823320.41166
1110.5919580.8160830.408042
1120.581860.8362810.41814
1130.6221290.7557430.377871
1140.6543990.6912020.345601
1150.6587710.6824580.341229
1160.6720250.655950.327975
1170.6899350.6201290.310065
1180.7207620.5584760.279238
1190.7133090.5733820.286691
1200.7398810.5202380.260119
1210.7582120.4835770.241788
1220.7591890.4816230.240811
1230.7669130.4661730.233087
1240.7883150.423370.211685
1250.8012210.3975580.198779
1260.8155740.3688520.184426
1270.8213860.3572280.178614
1280.8301230.3397540.169877
1290.8515660.2968690.148434
1300.8705380.2589240.129462
1310.8976370.2047250.102363
1320.9056920.1886160.094308
1330.9260120.1479760.0739881
1340.9346980.1306040.0653019
1350.9429540.1140920.0570459
1360.9620830.07583490.0379175
1370.9688340.06233280.0311664
1380.9794460.04110790.020554
1390.9859040.02819220.0140961
1400.9913460.01730740.00865369
1410.9947770.01044670.00522334
1420.9957910.008417260.00420863
1430.9971110.005777530.00288877
1440.9983630.003273930.00163697
1450.9989850.002030730.00101537
1460.999520.000960760.00048038
1470.9998080.0003840380.000192019
1480.9999340.0001326346.6317e-05
1490.9999725.56171e-052.78086e-05
1500.9999852.91208e-051.45604e-05
1510.9999968.64728e-064.32364e-06
1520.9999992.55669e-061.27835e-06
1530.9999991.01153e-065.05766e-07
15412.0053e-121.00265e-12
15513.18197e-141.59098e-14
15611.41109e-177.05544e-18
15714.12246e-202.06123e-20
15811.04192e-235.20959e-24
15915.18589e-312.59294e-31
16019.10266e-434.55133e-43
161100
162100
163100
164100
165100
166100
167100
168100
169100
170100
171100
172100
173100
174100
175100
176100
177100
178100
179100
180100
181100
182100
183100
184100
185100
186100
187100
188100
189100
190100
191100
192100
193100
194100
195100
196100
197100
198100
199100
200100
201100
202100
203100
204100
205100
206100
207100
208100
209100
210100
211100
212100
213100
214100
215100
216100
217100
218100
219100
220100
221100
222100
223100
224100
225100
226100
227100
228100
229100
230100
231100
232100
233100
23412.61599e-3041.308e-304
23519.06037e-3014.53018e-301
23611.20078e-2766.0039e-277
23715.30545e-2682.65273e-268
23815.08001e-2502.54001e-250
23912.69365e-2301.34683e-230
24011.02432e-2335.1216e-234
24114.11734e-2102.05867e-210
24211.14513e-1895.72563e-190
24319.69585e-1854.84792e-185
24416.14194e-1703.07097e-170
24511.06952e-1485.34758e-149
24619.39642e-1454.69821e-145
24711.34583e-1186.72913e-119
248100
24912.35675e-891.17837e-89
25011.08844e-725.44219e-73
25116.66525e-643.33263e-64
25211.03777e-445.18883e-45

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 5.5018e-46 & 1.10036e-45 & 1 \tabularnewline
13 & 8.39802e-61 & 1.6796e-60 & 1 \tabularnewline
14 & 5.12774e-73 & 1.02555e-72 & 1 \tabularnewline
15 & 1.96503e-87 & 3.93005e-87 & 1 \tabularnewline
16 & 0 & 0 & 1 \tabularnewline
17 & 4.22911e-117 & 8.45823e-117 & 1 \tabularnewline
18 & 5.55375e-133 & 1.11075e-132 & 1 \tabularnewline
19 & 2.02686e-148 & 4.05372e-148 & 1 \tabularnewline
20 & 2.29765e-170 & 4.5953e-170 & 1 \tabularnewline
21 & 3.16024e-180 & 6.32048e-180 & 1 \tabularnewline
22 & 4.9844e-193 & 9.96881e-193 & 1 \tabularnewline
23 & 7.32207e-205 & 1.46441e-204 & 1 \tabularnewline
24 & 3.98502e-227 & 7.97005e-227 & 1 \tabularnewline
25 & 5.84942e-241 & 1.16988e-240 & 1 \tabularnewline
26 & 6.77694e-259 & 1.35539e-258 & 1 \tabularnewline
27 & 1.66572e-269 & 3.33144e-269 & 1 \tabularnewline
28 & 6.79586e-283 & 1.35917e-282 & 1 \tabularnewline
29 & 7.84603e-308 & 1.56921e-307 & 1 \tabularnewline
30 & 1.42307e-304 & 2.84613e-304 & 1 \tabularnewline
31 & 0 & 0 & 1 \tabularnewline
32 & 0 & 0 & 1 \tabularnewline
33 & 0 & 0 & 1 \tabularnewline
34 & 0 & 0 & 1 \tabularnewline
35 & 0 & 0 & 1 \tabularnewline
36 & 0 & 0 & 1 \tabularnewline
37 & 0 & 0 & 1 \tabularnewline
38 & 0 & 0 & 1 \tabularnewline
39 & 0 & 0 & 1 \tabularnewline
40 & 0 & 0 & 1 \tabularnewline
41 & 0 & 0 & 1 \tabularnewline
42 & 0 & 0 & 1 \tabularnewline
43 & 0 & 0 & 1 \tabularnewline
44 & 0 & 0 & 1 \tabularnewline
45 & 0 & 0 & 1 \tabularnewline
46 & 0 & 0 & 1 \tabularnewline
47 & 0 & 0 & 1 \tabularnewline
48 & 0 & 0 & 1 \tabularnewline
49 & 0 & 0 & 1 \tabularnewline
50 & 0 & 0 & 1 \tabularnewline
51 & 0 & 0 & 1 \tabularnewline
52 & 0 & 0 & 1 \tabularnewline
53 & 0 & 0 & 1 \tabularnewline
54 & 0 & 0 & 1 \tabularnewline
55 & 0 & 0 & 1 \tabularnewline
56 & 0 & 0 & 1 \tabularnewline
57 & 0 & 0 & 1 \tabularnewline
58 & 0 & 0 & 1 \tabularnewline
59 & 0 & 0 & 1 \tabularnewline
60 & 0 & 0 & 1 \tabularnewline
61 & 0 & 0 & 1 \tabularnewline
62 & 0 & 0 & 1 \tabularnewline
63 & 0 & 0 & 1 \tabularnewline
64 & 0 & 0 & 1 \tabularnewline
65 & 0 & 0 & 1 \tabularnewline
66 & 1.65709e-22 & 3.31419e-22 & 1 \tabularnewline
67 & 8.78939e-16 & 1.75788e-15 & 1 \tabularnewline
68 & 7.05244e-13 & 1.41049e-12 & 1 \tabularnewline
69 & 3.08186e-09 & 6.16372e-09 & 1 \tabularnewline
70 & 1.38878e-07 & 2.77756e-07 & 1 \tabularnewline
71 & 5.86432e-06 & 1.17286e-05 & 0.999994 \tabularnewline
72 & 4.08778e-05 & 8.17555e-05 & 0.999959 \tabularnewline
73 & 0.000109074 & 0.000218148 & 0.999891 \tabularnewline
74 & 0.000183845 & 0.00036769 & 0.999816 \tabularnewline
75 & 0.00116578 & 0.00233156 & 0.998834 \tabularnewline
76 & 0.00271614 & 0.00543228 & 0.997284 \tabularnewline
77 & 0.00540064 & 0.0108013 & 0.994599 \tabularnewline
78 & 0.010577 & 0.021154 & 0.989423 \tabularnewline
79 & 0.0208009 & 0.0416019 & 0.979199 \tabularnewline
80 & 0.0452387 & 0.0904774 & 0.954761 \tabularnewline
81 & 0.0596229 & 0.119246 & 0.940377 \tabularnewline
82 & 0.0843966 & 0.168793 & 0.915603 \tabularnewline
83 & 0.10856 & 0.217121 & 0.89144 \tabularnewline
84 & 0.138621 & 0.277241 & 0.861379 \tabularnewline
85 & 0.169535 & 0.339071 & 0.830465 \tabularnewline
86 & 0.197744 & 0.395489 & 0.802256 \tabularnewline
87 & 0.226621 & 0.453243 & 0.773379 \tabularnewline
88 & 0.259272 & 0.518543 & 0.740728 \tabularnewline
89 & 0.271982 & 0.543965 & 0.728018 \tabularnewline
90 & 0.315824 & 0.631649 & 0.684176 \tabularnewline
91 & 0.339858 & 0.679717 & 0.660142 \tabularnewline
92 & 0.34207 & 0.68414 & 0.65793 \tabularnewline
93 & 0.359893 & 0.719786 & 0.640107 \tabularnewline
94 & 0.384309 & 0.768617 & 0.615691 \tabularnewline
95 & 0.407572 & 0.815144 & 0.592428 \tabularnewline
96 & 0.418658 & 0.837315 & 0.581342 \tabularnewline
97 & 0.449858 & 0.899716 & 0.550142 \tabularnewline
98 & 0.460678 & 0.921356 & 0.539322 \tabularnewline
99 & 0.48616 & 0.97232 & 0.51384 \tabularnewline
100 & 0.492216 & 0.984432 & 0.507784 \tabularnewline
101 & 0.501669 & 0.996662 & 0.498331 \tabularnewline
102 & 0.4813 & 0.962599 & 0.5187 \tabularnewline
103 & 0.535721 & 0.928558 & 0.464279 \tabularnewline
104 & 0.524563 & 0.950874 & 0.475437 \tabularnewline
105 & 0.545971 & 0.908058 & 0.454029 \tabularnewline
106 & 0.556353 & 0.887294 & 0.443647 \tabularnewline
107 & 0.550846 & 0.898309 & 0.449154 \tabularnewline
108 & 0.575978 & 0.848045 & 0.424022 \tabularnewline
109 & 0.591339 & 0.817322 & 0.408661 \tabularnewline
110 & 0.58834 & 0.82332 & 0.41166 \tabularnewline
111 & 0.591958 & 0.816083 & 0.408042 \tabularnewline
112 & 0.58186 & 0.836281 & 0.41814 \tabularnewline
113 & 0.622129 & 0.755743 & 0.377871 \tabularnewline
114 & 0.654399 & 0.691202 & 0.345601 \tabularnewline
115 & 0.658771 & 0.682458 & 0.341229 \tabularnewline
116 & 0.672025 & 0.65595 & 0.327975 \tabularnewline
117 & 0.689935 & 0.620129 & 0.310065 \tabularnewline
118 & 0.720762 & 0.558476 & 0.279238 \tabularnewline
119 & 0.713309 & 0.573382 & 0.286691 \tabularnewline
120 & 0.739881 & 0.520238 & 0.260119 \tabularnewline
121 & 0.758212 & 0.483577 & 0.241788 \tabularnewline
122 & 0.759189 & 0.481623 & 0.240811 \tabularnewline
123 & 0.766913 & 0.466173 & 0.233087 \tabularnewline
124 & 0.788315 & 0.42337 & 0.211685 \tabularnewline
125 & 0.801221 & 0.397558 & 0.198779 \tabularnewline
126 & 0.815574 & 0.368852 & 0.184426 \tabularnewline
127 & 0.821386 & 0.357228 & 0.178614 \tabularnewline
128 & 0.830123 & 0.339754 & 0.169877 \tabularnewline
129 & 0.851566 & 0.296869 & 0.148434 \tabularnewline
130 & 0.870538 & 0.258924 & 0.129462 \tabularnewline
131 & 0.897637 & 0.204725 & 0.102363 \tabularnewline
132 & 0.905692 & 0.188616 & 0.094308 \tabularnewline
133 & 0.926012 & 0.147976 & 0.0739881 \tabularnewline
134 & 0.934698 & 0.130604 & 0.0653019 \tabularnewline
135 & 0.942954 & 0.114092 & 0.0570459 \tabularnewline
136 & 0.962083 & 0.0758349 & 0.0379175 \tabularnewline
137 & 0.968834 & 0.0623328 & 0.0311664 \tabularnewline
138 & 0.979446 & 0.0411079 & 0.020554 \tabularnewline
139 & 0.985904 & 0.0281922 & 0.0140961 \tabularnewline
140 & 0.991346 & 0.0173074 & 0.00865369 \tabularnewline
141 & 0.994777 & 0.0104467 & 0.00522334 \tabularnewline
142 & 0.995791 & 0.00841726 & 0.00420863 \tabularnewline
143 & 0.997111 & 0.00577753 & 0.00288877 \tabularnewline
144 & 0.998363 & 0.00327393 & 0.00163697 \tabularnewline
145 & 0.998985 & 0.00203073 & 0.00101537 \tabularnewline
146 & 0.99952 & 0.00096076 & 0.00048038 \tabularnewline
147 & 0.999808 & 0.000384038 & 0.000192019 \tabularnewline
148 & 0.999934 & 0.000132634 & 6.6317e-05 \tabularnewline
149 & 0.999972 & 5.56171e-05 & 2.78086e-05 \tabularnewline
150 & 0.999985 & 2.91208e-05 & 1.45604e-05 \tabularnewline
151 & 0.999996 & 8.64728e-06 & 4.32364e-06 \tabularnewline
152 & 0.999999 & 2.55669e-06 & 1.27835e-06 \tabularnewline
153 & 0.999999 & 1.01153e-06 & 5.05766e-07 \tabularnewline
154 & 1 & 2.0053e-12 & 1.00265e-12 \tabularnewline
155 & 1 & 3.18197e-14 & 1.59098e-14 \tabularnewline
156 & 1 & 1.41109e-17 & 7.05544e-18 \tabularnewline
157 & 1 & 4.12246e-20 & 2.06123e-20 \tabularnewline
158 & 1 & 1.04192e-23 & 5.20959e-24 \tabularnewline
159 & 1 & 5.18589e-31 & 2.59294e-31 \tabularnewline
160 & 1 & 9.10266e-43 & 4.55133e-43 \tabularnewline
161 & 1 & 0 & 0 \tabularnewline
162 & 1 & 0 & 0 \tabularnewline
163 & 1 & 0 & 0 \tabularnewline
164 & 1 & 0 & 0 \tabularnewline
165 & 1 & 0 & 0 \tabularnewline
166 & 1 & 0 & 0 \tabularnewline
167 & 1 & 0 & 0 \tabularnewline
168 & 1 & 0 & 0 \tabularnewline
169 & 1 & 0 & 0 \tabularnewline
170 & 1 & 0 & 0 \tabularnewline
171 & 1 & 0 & 0 \tabularnewline
172 & 1 & 0 & 0 \tabularnewline
173 & 1 & 0 & 0 \tabularnewline
174 & 1 & 0 & 0 \tabularnewline
175 & 1 & 0 & 0 \tabularnewline
176 & 1 & 0 & 0 \tabularnewline
177 & 1 & 0 & 0 \tabularnewline
178 & 1 & 0 & 0 \tabularnewline
179 & 1 & 0 & 0 \tabularnewline
180 & 1 & 0 & 0 \tabularnewline
181 & 1 & 0 & 0 \tabularnewline
182 & 1 & 0 & 0 \tabularnewline
183 & 1 & 0 & 0 \tabularnewline
184 & 1 & 0 & 0 \tabularnewline
185 & 1 & 0 & 0 \tabularnewline
186 & 1 & 0 & 0 \tabularnewline
187 & 1 & 0 & 0 \tabularnewline
188 & 1 & 0 & 0 \tabularnewline
189 & 1 & 0 & 0 \tabularnewline
190 & 1 & 0 & 0 \tabularnewline
191 & 1 & 0 & 0 \tabularnewline
192 & 1 & 0 & 0 \tabularnewline
193 & 1 & 0 & 0 \tabularnewline
194 & 1 & 0 & 0 \tabularnewline
195 & 1 & 0 & 0 \tabularnewline
196 & 1 & 0 & 0 \tabularnewline
197 & 1 & 0 & 0 \tabularnewline
198 & 1 & 0 & 0 \tabularnewline
199 & 1 & 0 & 0 \tabularnewline
200 & 1 & 0 & 0 \tabularnewline
201 & 1 & 0 & 0 \tabularnewline
202 & 1 & 0 & 0 \tabularnewline
203 & 1 & 0 & 0 \tabularnewline
204 & 1 & 0 & 0 \tabularnewline
205 & 1 & 0 & 0 \tabularnewline
206 & 1 & 0 & 0 \tabularnewline
207 & 1 & 0 & 0 \tabularnewline
208 & 1 & 0 & 0 \tabularnewline
209 & 1 & 0 & 0 \tabularnewline
210 & 1 & 0 & 0 \tabularnewline
211 & 1 & 0 & 0 \tabularnewline
212 & 1 & 0 & 0 \tabularnewline
213 & 1 & 0 & 0 \tabularnewline
214 & 1 & 0 & 0 \tabularnewline
215 & 1 & 0 & 0 \tabularnewline
216 & 1 & 0 & 0 \tabularnewline
217 & 1 & 0 & 0 \tabularnewline
218 & 1 & 0 & 0 \tabularnewline
219 & 1 & 0 & 0 \tabularnewline
220 & 1 & 0 & 0 \tabularnewline
221 & 1 & 0 & 0 \tabularnewline
222 & 1 & 0 & 0 \tabularnewline
223 & 1 & 0 & 0 \tabularnewline
224 & 1 & 0 & 0 \tabularnewline
225 & 1 & 0 & 0 \tabularnewline
226 & 1 & 0 & 0 \tabularnewline
227 & 1 & 0 & 0 \tabularnewline
228 & 1 & 0 & 0 \tabularnewline
229 & 1 & 0 & 0 \tabularnewline
230 & 1 & 0 & 0 \tabularnewline
231 & 1 & 0 & 0 \tabularnewline
232 & 1 & 0 & 0 \tabularnewline
233 & 1 & 0 & 0 \tabularnewline
234 & 1 & 2.61599e-304 & 1.308e-304 \tabularnewline
235 & 1 & 9.06037e-301 & 4.53018e-301 \tabularnewline
236 & 1 & 1.20078e-276 & 6.0039e-277 \tabularnewline
237 & 1 & 5.30545e-268 & 2.65273e-268 \tabularnewline
238 & 1 & 5.08001e-250 & 2.54001e-250 \tabularnewline
239 & 1 & 2.69365e-230 & 1.34683e-230 \tabularnewline
240 & 1 & 1.02432e-233 & 5.1216e-234 \tabularnewline
241 & 1 & 4.11734e-210 & 2.05867e-210 \tabularnewline
242 & 1 & 1.14513e-189 & 5.72563e-190 \tabularnewline
243 & 1 & 9.69585e-185 & 4.84792e-185 \tabularnewline
244 & 1 & 6.14194e-170 & 3.07097e-170 \tabularnewline
245 & 1 & 1.06952e-148 & 5.34758e-149 \tabularnewline
246 & 1 & 9.39642e-145 & 4.69821e-145 \tabularnewline
247 & 1 & 1.34583e-118 & 6.72913e-119 \tabularnewline
248 & 1 & 0 & 0 \tabularnewline
249 & 1 & 2.35675e-89 & 1.17837e-89 \tabularnewline
250 & 1 & 1.08844e-72 & 5.44219e-73 \tabularnewline
251 & 1 & 6.66525e-64 & 3.33263e-64 \tabularnewline
252 & 1 & 1.03777e-44 & 5.18883e-45 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221533&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]12[/C][C]5.5018e-46[/C][C]1.10036e-45[/C][C]1[/C][/ROW]
[ROW][C]13[/C][C]8.39802e-61[/C][C]1.6796e-60[/C][C]1[/C][/ROW]
[ROW][C]14[/C][C]5.12774e-73[/C][C]1.02555e-72[/C][C]1[/C][/ROW]
[ROW][C]15[/C][C]1.96503e-87[/C][C]3.93005e-87[/C][C]1[/C][/ROW]
[ROW][C]16[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]17[/C][C]4.22911e-117[/C][C]8.45823e-117[/C][C]1[/C][/ROW]
[ROW][C]18[/C][C]5.55375e-133[/C][C]1.11075e-132[/C][C]1[/C][/ROW]
[ROW][C]19[/C][C]2.02686e-148[/C][C]4.05372e-148[/C][C]1[/C][/ROW]
[ROW][C]20[/C][C]2.29765e-170[/C][C]4.5953e-170[/C][C]1[/C][/ROW]
[ROW][C]21[/C][C]3.16024e-180[/C][C]6.32048e-180[/C][C]1[/C][/ROW]
[ROW][C]22[/C][C]4.9844e-193[/C][C]9.96881e-193[/C][C]1[/C][/ROW]
[ROW][C]23[/C][C]7.32207e-205[/C][C]1.46441e-204[/C][C]1[/C][/ROW]
[ROW][C]24[/C][C]3.98502e-227[/C][C]7.97005e-227[/C][C]1[/C][/ROW]
[ROW][C]25[/C][C]5.84942e-241[/C][C]1.16988e-240[/C][C]1[/C][/ROW]
[ROW][C]26[/C][C]6.77694e-259[/C][C]1.35539e-258[/C][C]1[/C][/ROW]
[ROW][C]27[/C][C]1.66572e-269[/C][C]3.33144e-269[/C][C]1[/C][/ROW]
[ROW][C]28[/C][C]6.79586e-283[/C][C]1.35917e-282[/C][C]1[/C][/ROW]
[ROW][C]29[/C][C]7.84603e-308[/C][C]1.56921e-307[/C][C]1[/C][/ROW]
[ROW][C]30[/C][C]1.42307e-304[/C][C]2.84613e-304[/C][C]1[/C][/ROW]
[ROW][C]31[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]32[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]33[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]34[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]35[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]36[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]37[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]38[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]39[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]42[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]44[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]45[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]46[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]47[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]48[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]49[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]50[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]51[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]54[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]55[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]56[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]58[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]60[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]61[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]63[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]64[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]65[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]66[/C][C]1.65709e-22[/C][C]3.31419e-22[/C][C]1[/C][/ROW]
[ROW][C]67[/C][C]8.78939e-16[/C][C]1.75788e-15[/C][C]1[/C][/ROW]
[ROW][C]68[/C][C]7.05244e-13[/C][C]1.41049e-12[/C][C]1[/C][/ROW]
[ROW][C]69[/C][C]3.08186e-09[/C][C]6.16372e-09[/C][C]1[/C][/ROW]
[ROW][C]70[/C][C]1.38878e-07[/C][C]2.77756e-07[/C][C]1[/C][/ROW]
[ROW][C]71[/C][C]5.86432e-06[/C][C]1.17286e-05[/C][C]0.999994[/C][/ROW]
[ROW][C]72[/C][C]4.08778e-05[/C][C]8.17555e-05[/C][C]0.999959[/C][/ROW]
[ROW][C]73[/C][C]0.000109074[/C][C]0.000218148[/C][C]0.999891[/C][/ROW]
[ROW][C]74[/C][C]0.000183845[/C][C]0.00036769[/C][C]0.999816[/C][/ROW]
[ROW][C]75[/C][C]0.00116578[/C][C]0.00233156[/C][C]0.998834[/C][/ROW]
[ROW][C]76[/C][C]0.00271614[/C][C]0.00543228[/C][C]0.997284[/C][/ROW]
[ROW][C]77[/C][C]0.00540064[/C][C]0.0108013[/C][C]0.994599[/C][/ROW]
[ROW][C]78[/C][C]0.010577[/C][C]0.021154[/C][C]0.989423[/C][/ROW]
[ROW][C]79[/C][C]0.0208009[/C][C]0.0416019[/C][C]0.979199[/C][/ROW]
[ROW][C]80[/C][C]0.0452387[/C][C]0.0904774[/C][C]0.954761[/C][/ROW]
[ROW][C]81[/C][C]0.0596229[/C][C]0.119246[/C][C]0.940377[/C][/ROW]
[ROW][C]82[/C][C]0.0843966[/C][C]0.168793[/C][C]0.915603[/C][/ROW]
[ROW][C]83[/C][C]0.10856[/C][C]0.217121[/C][C]0.89144[/C][/ROW]
[ROW][C]84[/C][C]0.138621[/C][C]0.277241[/C][C]0.861379[/C][/ROW]
[ROW][C]85[/C][C]0.169535[/C][C]0.339071[/C][C]0.830465[/C][/ROW]
[ROW][C]86[/C][C]0.197744[/C][C]0.395489[/C][C]0.802256[/C][/ROW]
[ROW][C]87[/C][C]0.226621[/C][C]0.453243[/C][C]0.773379[/C][/ROW]
[ROW][C]88[/C][C]0.259272[/C][C]0.518543[/C][C]0.740728[/C][/ROW]
[ROW][C]89[/C][C]0.271982[/C][C]0.543965[/C][C]0.728018[/C][/ROW]
[ROW][C]90[/C][C]0.315824[/C][C]0.631649[/C][C]0.684176[/C][/ROW]
[ROW][C]91[/C][C]0.339858[/C][C]0.679717[/C][C]0.660142[/C][/ROW]
[ROW][C]92[/C][C]0.34207[/C][C]0.68414[/C][C]0.65793[/C][/ROW]
[ROW][C]93[/C][C]0.359893[/C][C]0.719786[/C][C]0.640107[/C][/ROW]
[ROW][C]94[/C][C]0.384309[/C][C]0.768617[/C][C]0.615691[/C][/ROW]
[ROW][C]95[/C][C]0.407572[/C][C]0.815144[/C][C]0.592428[/C][/ROW]
[ROW][C]96[/C][C]0.418658[/C][C]0.837315[/C][C]0.581342[/C][/ROW]
[ROW][C]97[/C][C]0.449858[/C][C]0.899716[/C][C]0.550142[/C][/ROW]
[ROW][C]98[/C][C]0.460678[/C][C]0.921356[/C][C]0.539322[/C][/ROW]
[ROW][C]99[/C][C]0.48616[/C][C]0.97232[/C][C]0.51384[/C][/ROW]
[ROW][C]100[/C][C]0.492216[/C][C]0.984432[/C][C]0.507784[/C][/ROW]
[ROW][C]101[/C][C]0.501669[/C][C]0.996662[/C][C]0.498331[/C][/ROW]
[ROW][C]102[/C][C]0.4813[/C][C]0.962599[/C][C]0.5187[/C][/ROW]
[ROW][C]103[/C][C]0.535721[/C][C]0.928558[/C][C]0.464279[/C][/ROW]
[ROW][C]104[/C][C]0.524563[/C][C]0.950874[/C][C]0.475437[/C][/ROW]
[ROW][C]105[/C][C]0.545971[/C][C]0.908058[/C][C]0.454029[/C][/ROW]
[ROW][C]106[/C][C]0.556353[/C][C]0.887294[/C][C]0.443647[/C][/ROW]
[ROW][C]107[/C][C]0.550846[/C][C]0.898309[/C][C]0.449154[/C][/ROW]
[ROW][C]108[/C][C]0.575978[/C][C]0.848045[/C][C]0.424022[/C][/ROW]
[ROW][C]109[/C][C]0.591339[/C][C]0.817322[/C][C]0.408661[/C][/ROW]
[ROW][C]110[/C][C]0.58834[/C][C]0.82332[/C][C]0.41166[/C][/ROW]
[ROW][C]111[/C][C]0.591958[/C][C]0.816083[/C][C]0.408042[/C][/ROW]
[ROW][C]112[/C][C]0.58186[/C][C]0.836281[/C][C]0.41814[/C][/ROW]
[ROW][C]113[/C][C]0.622129[/C][C]0.755743[/C][C]0.377871[/C][/ROW]
[ROW][C]114[/C][C]0.654399[/C][C]0.691202[/C][C]0.345601[/C][/ROW]
[ROW][C]115[/C][C]0.658771[/C][C]0.682458[/C][C]0.341229[/C][/ROW]
[ROW][C]116[/C][C]0.672025[/C][C]0.65595[/C][C]0.327975[/C][/ROW]
[ROW][C]117[/C][C]0.689935[/C][C]0.620129[/C][C]0.310065[/C][/ROW]
[ROW][C]118[/C][C]0.720762[/C][C]0.558476[/C][C]0.279238[/C][/ROW]
[ROW][C]119[/C][C]0.713309[/C][C]0.573382[/C][C]0.286691[/C][/ROW]
[ROW][C]120[/C][C]0.739881[/C][C]0.520238[/C][C]0.260119[/C][/ROW]
[ROW][C]121[/C][C]0.758212[/C][C]0.483577[/C][C]0.241788[/C][/ROW]
[ROW][C]122[/C][C]0.759189[/C][C]0.481623[/C][C]0.240811[/C][/ROW]
[ROW][C]123[/C][C]0.766913[/C][C]0.466173[/C][C]0.233087[/C][/ROW]
[ROW][C]124[/C][C]0.788315[/C][C]0.42337[/C][C]0.211685[/C][/ROW]
[ROW][C]125[/C][C]0.801221[/C][C]0.397558[/C][C]0.198779[/C][/ROW]
[ROW][C]126[/C][C]0.815574[/C][C]0.368852[/C][C]0.184426[/C][/ROW]
[ROW][C]127[/C][C]0.821386[/C][C]0.357228[/C][C]0.178614[/C][/ROW]
[ROW][C]128[/C][C]0.830123[/C][C]0.339754[/C][C]0.169877[/C][/ROW]
[ROW][C]129[/C][C]0.851566[/C][C]0.296869[/C][C]0.148434[/C][/ROW]
[ROW][C]130[/C][C]0.870538[/C][C]0.258924[/C][C]0.129462[/C][/ROW]
[ROW][C]131[/C][C]0.897637[/C][C]0.204725[/C][C]0.102363[/C][/ROW]
[ROW][C]132[/C][C]0.905692[/C][C]0.188616[/C][C]0.094308[/C][/ROW]
[ROW][C]133[/C][C]0.926012[/C][C]0.147976[/C][C]0.0739881[/C][/ROW]
[ROW][C]134[/C][C]0.934698[/C][C]0.130604[/C][C]0.0653019[/C][/ROW]
[ROW][C]135[/C][C]0.942954[/C][C]0.114092[/C][C]0.0570459[/C][/ROW]
[ROW][C]136[/C][C]0.962083[/C][C]0.0758349[/C][C]0.0379175[/C][/ROW]
[ROW][C]137[/C][C]0.968834[/C][C]0.0623328[/C][C]0.0311664[/C][/ROW]
[ROW][C]138[/C][C]0.979446[/C][C]0.0411079[/C][C]0.020554[/C][/ROW]
[ROW][C]139[/C][C]0.985904[/C][C]0.0281922[/C][C]0.0140961[/C][/ROW]
[ROW][C]140[/C][C]0.991346[/C][C]0.0173074[/C][C]0.00865369[/C][/ROW]
[ROW][C]141[/C][C]0.994777[/C][C]0.0104467[/C][C]0.00522334[/C][/ROW]
[ROW][C]142[/C][C]0.995791[/C][C]0.00841726[/C][C]0.00420863[/C][/ROW]
[ROW][C]143[/C][C]0.997111[/C][C]0.00577753[/C][C]0.00288877[/C][/ROW]
[ROW][C]144[/C][C]0.998363[/C][C]0.00327393[/C][C]0.00163697[/C][/ROW]
[ROW][C]145[/C][C]0.998985[/C][C]0.00203073[/C][C]0.00101537[/C][/ROW]
[ROW][C]146[/C][C]0.99952[/C][C]0.00096076[/C][C]0.00048038[/C][/ROW]
[ROW][C]147[/C][C]0.999808[/C][C]0.000384038[/C][C]0.000192019[/C][/ROW]
[ROW][C]148[/C][C]0.999934[/C][C]0.000132634[/C][C]6.6317e-05[/C][/ROW]
[ROW][C]149[/C][C]0.999972[/C][C]5.56171e-05[/C][C]2.78086e-05[/C][/ROW]
[ROW][C]150[/C][C]0.999985[/C][C]2.91208e-05[/C][C]1.45604e-05[/C][/ROW]
[ROW][C]151[/C][C]0.999996[/C][C]8.64728e-06[/C][C]4.32364e-06[/C][/ROW]
[ROW][C]152[/C][C]0.999999[/C][C]2.55669e-06[/C][C]1.27835e-06[/C][/ROW]
[ROW][C]153[/C][C]0.999999[/C][C]1.01153e-06[/C][C]5.05766e-07[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]2.0053e-12[/C][C]1.00265e-12[/C][/ROW]
[ROW][C]155[/C][C]1[/C][C]3.18197e-14[/C][C]1.59098e-14[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]1.41109e-17[/C][C]7.05544e-18[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]4.12246e-20[/C][C]2.06123e-20[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]1.04192e-23[/C][C]5.20959e-24[/C][/ROW]
[ROW][C]159[/C][C]1[/C][C]5.18589e-31[/C][C]2.59294e-31[/C][/ROW]
[ROW][C]160[/C][C]1[/C][C]9.10266e-43[/C][C]4.55133e-43[/C][/ROW]
[ROW][C]161[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]162[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]166[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]167[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]168[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]169[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]170[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]171[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]172[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]173[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]174[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]175[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]176[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]177[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]179[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]181[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]182[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]184[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]185[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]186[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]187[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]188[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]189[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]190[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]191[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]192[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]193[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]194[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]195[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]196[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]197[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]198[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]199[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]200[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]201[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]202[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]203[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]204[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]205[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]206[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]207[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]208[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]209[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]210[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]211[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]212[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]213[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]214[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]215[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]216[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]217[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]218[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]219[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]220[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]221[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]222[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]223[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]224[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]225[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]226[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]227[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]228[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]229[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]230[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]231[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]232[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]233[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]234[/C][C]1[/C][C]2.61599e-304[/C][C]1.308e-304[/C][/ROW]
[ROW][C]235[/C][C]1[/C][C]9.06037e-301[/C][C]4.53018e-301[/C][/ROW]
[ROW][C]236[/C][C]1[/C][C]1.20078e-276[/C][C]6.0039e-277[/C][/ROW]
[ROW][C]237[/C][C]1[/C][C]5.30545e-268[/C][C]2.65273e-268[/C][/ROW]
[ROW][C]238[/C][C]1[/C][C]5.08001e-250[/C][C]2.54001e-250[/C][/ROW]
[ROW][C]239[/C][C]1[/C][C]2.69365e-230[/C][C]1.34683e-230[/C][/ROW]
[ROW][C]240[/C][C]1[/C][C]1.02432e-233[/C][C]5.1216e-234[/C][/ROW]
[ROW][C]241[/C][C]1[/C][C]4.11734e-210[/C][C]2.05867e-210[/C][/ROW]
[ROW][C]242[/C][C]1[/C][C]1.14513e-189[/C][C]5.72563e-190[/C][/ROW]
[ROW][C]243[/C][C]1[/C][C]9.69585e-185[/C][C]4.84792e-185[/C][/ROW]
[ROW][C]244[/C][C]1[/C][C]6.14194e-170[/C][C]3.07097e-170[/C][/ROW]
[ROW][C]245[/C][C]1[/C][C]1.06952e-148[/C][C]5.34758e-149[/C][/ROW]
[ROW][C]246[/C][C]1[/C][C]9.39642e-145[/C][C]4.69821e-145[/C][/ROW]
[ROW][C]247[/C][C]1[/C][C]1.34583e-118[/C][C]6.72913e-119[/C][/ROW]
[ROW][C]248[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]249[/C][C]1[/C][C]2.35675e-89[/C][C]1.17837e-89[/C][/ROW]
[ROW][C]250[/C][C]1[/C][C]1.08844e-72[/C][C]5.44219e-73[/C][/ROW]
[ROW][C]251[/C][C]1[/C][C]6.66525e-64[/C][C]3.33263e-64[/C][/ROW]
[ROW][C]252[/C][C]1[/C][C]1.03777e-44[/C][C]5.18883e-45[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221533&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221533&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
125.5018e-461.10036e-451
138.39802e-611.6796e-601
145.12774e-731.02555e-721
151.96503e-873.93005e-871
16001
174.22911e-1178.45823e-1171
185.55375e-1331.11075e-1321
192.02686e-1484.05372e-1481
202.29765e-1704.5953e-1701
213.16024e-1806.32048e-1801
224.9844e-1939.96881e-1931
237.32207e-2051.46441e-2041
243.98502e-2277.97005e-2271
255.84942e-2411.16988e-2401
266.77694e-2591.35539e-2581
271.66572e-2693.33144e-2691
286.79586e-2831.35917e-2821
297.84603e-3081.56921e-3071
301.42307e-3042.84613e-3041
31001
32001
33001
34001
35001
36001
37001
38001
39001
40001
41001
42001
43001
44001
45001
46001
47001
48001
49001
50001
51001
52001
53001
54001
55001
56001
57001
58001
59001
60001
61001
62001
63001
64001
65001
661.65709e-223.31419e-221
678.78939e-161.75788e-151
687.05244e-131.41049e-121
693.08186e-096.16372e-091
701.38878e-072.77756e-071
715.86432e-061.17286e-050.999994
724.08778e-058.17555e-050.999959
730.0001090740.0002181480.999891
740.0001838450.000367690.999816
750.001165780.002331560.998834
760.002716140.005432280.997284
770.005400640.01080130.994599
780.0105770.0211540.989423
790.02080090.04160190.979199
800.04523870.09047740.954761
810.05962290.1192460.940377
820.08439660.1687930.915603
830.108560.2171210.89144
840.1386210.2772410.861379
850.1695350.3390710.830465
860.1977440.3954890.802256
870.2266210.4532430.773379
880.2592720.5185430.740728
890.2719820.5439650.728018
900.3158240.6316490.684176
910.3398580.6797170.660142
920.342070.684140.65793
930.3598930.7197860.640107
940.3843090.7686170.615691
950.4075720.8151440.592428
960.4186580.8373150.581342
970.4498580.8997160.550142
980.4606780.9213560.539322
990.486160.972320.51384
1000.4922160.9844320.507784
1010.5016690.9966620.498331
1020.48130.9625990.5187
1030.5357210.9285580.464279
1040.5245630.9508740.475437
1050.5459710.9080580.454029
1060.5563530.8872940.443647
1070.5508460.8983090.449154
1080.5759780.8480450.424022
1090.5913390.8173220.408661
1100.588340.823320.41166
1110.5919580.8160830.408042
1120.581860.8362810.41814
1130.6221290.7557430.377871
1140.6543990.6912020.345601
1150.6587710.6824580.341229
1160.6720250.655950.327975
1170.6899350.6201290.310065
1180.7207620.5584760.279238
1190.7133090.5733820.286691
1200.7398810.5202380.260119
1210.7582120.4835770.241788
1220.7591890.4816230.240811
1230.7669130.4661730.233087
1240.7883150.423370.211685
1250.8012210.3975580.198779
1260.8155740.3688520.184426
1270.8213860.3572280.178614
1280.8301230.3397540.169877
1290.8515660.2968690.148434
1300.8705380.2589240.129462
1310.8976370.2047250.102363
1320.9056920.1886160.094308
1330.9260120.1479760.0739881
1340.9346980.1306040.0653019
1350.9429540.1140920.0570459
1360.9620830.07583490.0379175
1370.9688340.06233280.0311664
1380.9794460.04110790.020554
1390.9859040.02819220.0140961
1400.9913460.01730740.00865369
1410.9947770.01044670.00522334
1420.9957910.008417260.00420863
1430.9971110.005777530.00288877
1440.9983630.003273930.00163697
1450.9989850.002030730.00101537
1460.999520.000960760.00048038
1470.9998080.0003840380.000192019
1480.9999340.0001326346.6317e-05
1490.9999725.56171e-052.78086e-05
1500.9999852.91208e-051.45604e-05
1510.9999968.64728e-064.32364e-06
1520.9999992.55669e-061.27835e-06
1530.9999991.01153e-065.05766e-07
15412.0053e-121.00265e-12
15513.18197e-141.59098e-14
15611.41109e-177.05544e-18
15714.12246e-202.06123e-20
15811.04192e-235.20959e-24
15915.18589e-312.59294e-31
16019.10266e-434.55133e-43
161100
162100
163100
164100
165100
166100
167100
168100
169100
170100
171100
172100
173100
174100
175100
176100
177100
178100
179100
180100
181100
182100
183100
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186100
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189100
190100
191100
192100
193100
194100
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202100
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220100
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230100
231100
232100
233100
23412.61599e-3041.308e-304
23519.06037e-3014.53018e-301
23611.20078e-2766.0039e-277
23715.30545e-2682.65273e-268
23815.08001e-2502.54001e-250
23912.69365e-2301.34683e-230
24011.02432e-2335.1216e-234
24114.11734e-2102.05867e-210
24211.14513e-1895.72563e-190
24319.69585e-1854.84792e-185
24416.14194e-1703.07097e-170
24511.06952e-1485.34758e-149
24619.39642e-1454.69821e-145
24711.34583e-1186.72913e-119
248100
24912.35675e-891.17837e-89
25011.08844e-725.44219e-73
25116.66525e-643.33263e-64
25211.03777e-445.18883e-45






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1760.73029NOK
5% type I error level1830.759336NOK
10% type I error level1860.771784NOK

\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 & 176 & 0.73029 & NOK \tabularnewline
5% type I error level & 183 & 0.759336 & NOK \tabularnewline
10% type I error level & 186 & 0.771784 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221533&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]176[/C][C]0.73029[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]183[/C][C]0.759336[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]186[/C][C]0.771784[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221533&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221533&T=6

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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 level1760.73029NOK
5% type I error level1830.759336NOK
10% type I error level1860.771784NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 9 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 9 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}