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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 computationTue, 19 Nov 2013 04:57:04 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/19/t1384855065h6bnhv29zkzy6bh.htm/, Retrieved Fri, 03 May 2024 16:02:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226347, Retrieved Fri, 03 May 2024 16:02:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Ws 7 vraag 1 ] [2013-11-19 09:57:04] [4c736a442787d42e94a9d9bc48424aaa] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'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 & 13 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226347&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226347&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226347&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Separate[t] = + 14.2973 + 0.423377Connected[t] + 0.00191855Depression[t] + 0.00852344Sport1[t] + 0.0409738Happiness[t] + 0.183642Month[t] + 0.199832Software[t] -0.00138844t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Separate[t] =  +  14.2973 +  0.423377Connected[t] +  0.00191855Depression[t] +  0.00852344Sport1[t] +  0.0409738Happiness[t] +  0.183642Month[t] +  0.199832Software[t] -0.00138844t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226347&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Separate[t] =  +  14.2973 +  0.423377Connected[t] +  0.00191855Depression[t] +  0.00852344Sport1[t] +  0.0409738Happiness[t] +  0.183642Month[t] +  0.199832Software[t] -0.00138844t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226347&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226347&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
Separate[t] = + 14.2973 + 0.423377Connected[t] + 0.00191855Depression[t] + 0.00852344Sport1[t] + 0.0409738Happiness[t] + 0.183642Month[t] + 0.199832Software[t] -0.00138844t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)14.29736.841312.090.03761820.0188091
Connected0.4233770.05541857.644.35764e-132.17882e-13
Depression0.001918550.07477660.025660.9795510.489775
Sport10.008523440.0211880.40230.6878150.343908
Happiness0.04097380.1031140.39740.6914310.345716
Month0.1836420.7172060.25610.7981170.399058
Software0.1998320.0962462.0760.03886810.019434
t-0.001388440.00763067-0.1820.8557620.427881

\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) & 14.2973 & 6.84131 & 2.09 & 0.0376182 & 0.0188091 \tabularnewline
Connected & 0.423377 & 0.0554185 & 7.64 & 4.35764e-13 & 2.17882e-13 \tabularnewline
Depression & 0.00191855 & 0.0747766 & 0.02566 & 0.979551 & 0.489775 \tabularnewline
Sport1 & 0.00852344 & 0.021188 & 0.4023 & 0.687815 & 0.343908 \tabularnewline
Happiness & 0.0409738 & 0.103114 & 0.3974 & 0.691431 & 0.345716 \tabularnewline
Month & 0.183642 & 0.717206 & 0.2561 & 0.798117 & 0.399058 \tabularnewline
Software & 0.199832 & 0.096246 & 2.076 & 0.0388681 & 0.019434 \tabularnewline
t & -0.00138844 & 0.00763067 & -0.182 & 0.855762 & 0.427881 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226347&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]14.2973[/C][C]6.84131[/C][C]2.09[/C][C]0.0376182[/C][C]0.0188091[/C][/ROW]
[ROW][C]Connected[/C][C]0.423377[/C][C]0.0554185[/C][C]7.64[/C][C]4.35764e-13[/C][C]2.17882e-13[/C][/ROW]
[ROW][C]Depression[/C][C]0.00191855[/C][C]0.0747766[/C][C]0.02566[/C][C]0.979551[/C][C]0.489775[/C][/ROW]
[ROW][C]Sport1[/C][C]0.00852344[/C][C]0.021188[/C][C]0.4023[/C][C]0.687815[/C][C]0.343908[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0409738[/C][C]0.103114[/C][C]0.3974[/C][C]0.691431[/C][C]0.345716[/C][/ROW]
[ROW][C]Month[/C][C]0.183642[/C][C]0.717206[/C][C]0.2561[/C][C]0.798117[/C][C]0.399058[/C][/ROW]
[ROW][C]Software[/C][C]0.199832[/C][C]0.096246[/C][C]2.076[/C][C]0.0388681[/C][C]0.019434[/C][/ROW]
[ROW][C]t[/C][C]-0.00138844[/C][C]0.00763067[/C][C]-0.182[/C][C]0.855762[/C][C]0.427881[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226347&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226347&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)14.29736.841312.090.03761820.0188091
Connected0.4233770.05541857.644.35764e-132.17882e-13
Depression0.001918550.07477660.025660.9795510.489775
Sport10.008523440.0211880.40230.6878150.343908
Happiness0.04097380.1031140.39740.6914310.345716
Month0.1836420.7172060.25610.7981170.399058
Software0.1998320.0962462.0760.03886810.019434
t-0.001388440.00763067-0.1820.8557620.427881






Multiple Linear Regression - Regression Statistics
Multiple R0.47514
R-squared0.225758
Adjusted R-squared0.204587
F-TEST (value)10.6637
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value8.92353e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.30348
Sum Squared Residuals2793.72

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.47514 \tabularnewline
R-squared & 0.225758 \tabularnewline
Adjusted R-squared & 0.204587 \tabularnewline
F-TEST (value) & 10.6637 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 256 \tabularnewline
p-value & 8.92353e-12 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.30348 \tabularnewline
Sum Squared Residuals & 2793.72 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226347&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.47514[/C][/ROW]
[ROW][C]R-squared[/C][C]0.225758[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.204587[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]10.6637[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]256[/C][/ROW]
[ROW][C]p-value[/C][C]8.92353e-12[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.30348[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2793.72[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226347&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226347&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 R0.47514
R-squared0.225758
Adjusted R-squared0.204587
F-TEST (value)10.6637
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value8.92353e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.30348
Sum Squared Residuals2793.72






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
13836.75361.24645
23236.1233-4.12326
33532.68482.31516
43331.3541.64599
53734.27942.72056
62934.1837-5.18366
73135.9177-4.91765
83634.40811.59193
93534.84170.158313
103834.6873.31302
113135.4106-4.41057
123434.8271-0.827111
133535.4279-0.427948
143835.78322.21678
153734.39642.60355
163332.96880.0312153
173234.4061-2.40614
183835.87912.12086
193835.77192.22811
203233.0347-1.03474
213332.98550.0145399
223132.4994-1.49939
233836.08461.91539
243934.77574.22426
253236.2758-4.27575
263236.9382-4.93818
273534.4770.523028
283733.87083.12916
293333.5856-0.585555
303333.3483-0.348309
313132.7845-1.78445
323229.95722.04279
333134.8885-3.88846
343734.04742.95263
353033.9236-3.92362
363332.12310.876901
373130.91930.0807391
383334.7797-1.77969
393131.5357-0.535725
403333.851-0.851041
413234.8191-2.81905
423334.0063-1.00629
433236.1074-4.1074
443333.6673-0.667289
452835.1981-7.1981
463535.0044-0.00441219
473935.75693.24312
483433.3280.671983
493834.67793.32214
503235.56-3.56001
513833.51354.48655
523032.5958-2.59585
533332.84480.155217
543833.91484.08524
553231.47070.529271
563534.02650.973501
573436.0919-2.0919
583431.74842.25157
593634.86441.13563
603433.80040.199586
612830.7834-2.78344
623435.5623-1.56231
633534.21070.789297
643532.22782.77221
653133.7525-2.75247
663734.57082.42917
673535.1258-0.12581
682732.0757-5.07571
694036.12423.87585
703734.48232.51769
713634.89181.10821
723832.50125.49876
733934.55484.4452
744136.13894.86112
752734.0921-7.09214
763035.5484-5.54843
773735.60771.39227
783133.7718-2.77181
793131.5724-0.572446
802735.0958-8.09579
813633.69982.30023
823734.47312.52689
833335.3822-2.38225
843433.01460.985355
853133.2404-2.24036
863935.183.82004
873433.56710.432855
883231.70920.290822
893333.3053-0.305261
903632.27573.72434
913235.2681-3.26815
924134.5186.48196
932833.252-5.252
943031.9177-1.91766
953635.87040.129576
963535.3737-0.373716
973133.8753-2.87531
983435.4687-1.46866
993632.82423.17576
1003636.2444-0.244393
1013535.0012-0.00120449
1023735.63431.36573
1032832.7713-4.77131
1043933.47765.52241
1053236.3058-4.30583
1063535.7973-0.797344
1073936.99212.00791
1083534.32230.677703
1094236.43435.5657
1103432.44631.55374
1113333.0122-0.0121824
1124133.02837.97172
1133332.64940.350634
1143435.0471-1.04706
1153235.6446-3.64462
1164033.60276.3973
1174033.13446.86559
1183533.31851.68148
1193635.82430.175651
1203733.11753.88255
1212732.9365-5.93652
1223935.8453.15504
1233835.70332.2967
1243135.0589-4.05888
1253333.3095-0.309466
1263235.9478-3.94784
1273938.13060.869373
1283633.2162.78404
1293334.2242-1.22422
1303332.65860.341444
1313230.97421.02575
1323735.77431.2257
1333030.7758-0.775817
1343835.2792.72101
1352933.2993-4.29928
1362230.5531-8.55306
1373533.6741.32604
1383531.58343.41656
1393433.53880.461188
1403532.00632.99367
1413432.17881.82125
1423731.83485.16521
1433532.96372.03635
1442332.5506-9.55058
1453135.9014-4.90143
1462733.4033-6.40329
1473634.55631.44374
1483133.0263-2.02635
1493233.571-1.57098
1503934.81574.18428
1513737.5424-0.542365
1523833.3944.60598
1533933.06695.9331
1543434.4166-0.416599
1553132.7207-1.72065
1563235.1779-3.1779
1573731.85145.14858
1583633.17432.8257
1593233.7718-1.77184
1603832.30055.6995
1613633.05522.94485
1622630.5403-4.54028
1632632.1053-6.1053
1643336.3685-3.36853
1653933.53945.46061
1663028.80171.19829
1673332.24650.753541
1682530.6392-5.63919
1693833.97394.02608
1703730.9366.06398
1713133.7019-2.70194
1723735.01041.98958
1733536.4906-1.49058
1742530.8207-5.82071
1752835.0082-7.00817
1763533.0341.96601
1773334.3143-1.31429
1783031.6844-1.68438
1793132.4377-1.4377
1803735.06261.93741
1813634.76061.23937
1823033.2029-3.20287
1833633.41782.58219
1843235.8229-3.82291
1852829.2081-1.20807
1863633.22212.77793
1873434.7287-0.728697
1883135.3461-4.34606
1892830.3281-2.32813
1903631.61174.38826
1913632.79783.20222
1924035.76924.23081
1933331.42851.57152
1943734.07422.92577
1953232.8482-0.848176
1963835.21952.78047
1973133.5206-2.5206
1983733.75583.24415
1993332.70370.29629
2003230.65941.34062
2013032.1271-2.1271
2023029.4220.577969
2033133.5858-2.58575
2043233.8467-1.84673
2053432.85221.14775
2063633.89462.10538
2073734.36752.63253
2083634.37231.62766
2093334.4233-1.42325
2103333.8135-0.813521
2113333.7641-0.764104
2124437.17216.82787
2133932.99466.00535
2143231.42830.571746
2153534.28940.710555
2162531.0639-6.06393
2173533.62781.37216
2183435.8288-1.82883
2193533.74351.25653
2203934.99194.00813
2213334.3482-1.34823
2223635.26880.731241
2233233.4332-1.43323
2243232.1751-0.175109
2253632.93123.06876
2263632.09023.90975
2273232.3851-0.385086
2283432.82241.17757
2293333.1272-0.127201
2303533.26361.73636
2313032.7923-2.79229
2323832.93565.06444
2333431.86722.13283
2343337.3276-4.32756
2353233.6708-1.67077
2363134.3038-3.30382
2373034.0243-4.02435
2382734.6103-7.61026
2393131.706-0.705991
2403034.1354-4.13536
2413230.27351.72646
2423533.81371.18629
2432829.4508-1.45079
2443333.0807-0.0807227
2453134.9809-3.98087
2463530.92964.07038
2473532.4622.53798
2483234.0059-2.0059
2492126.5399-5.5399
2502027.6338-7.6338
2513431.73052.2695
2523232.5679-0.567866
2533433.56560.434398
2543232.9059-0.905937
2553334.7305-1.7305
2563333.6464-0.646447
2573734.2252.77496
2583231.61430.385739
2593435.0353-1.03533
2603032.5066-2.50662
2613030.7265-0.726485
2623833.96364.03636
2633635.14360.856391
2643231.23760.762401

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 38 & 36.7536 & 1.24645 \tabularnewline
2 & 32 & 36.1233 & -4.12326 \tabularnewline
3 & 35 & 32.6848 & 2.31516 \tabularnewline
4 & 33 & 31.354 & 1.64599 \tabularnewline
5 & 37 & 34.2794 & 2.72056 \tabularnewline
6 & 29 & 34.1837 & -5.18366 \tabularnewline
7 & 31 & 35.9177 & -4.91765 \tabularnewline
8 & 36 & 34.4081 & 1.59193 \tabularnewline
9 & 35 & 34.8417 & 0.158313 \tabularnewline
10 & 38 & 34.687 & 3.31302 \tabularnewline
11 & 31 & 35.4106 & -4.41057 \tabularnewline
12 & 34 & 34.8271 & -0.827111 \tabularnewline
13 & 35 & 35.4279 & -0.427948 \tabularnewline
14 & 38 & 35.7832 & 2.21678 \tabularnewline
15 & 37 & 34.3964 & 2.60355 \tabularnewline
16 & 33 & 32.9688 & 0.0312153 \tabularnewline
17 & 32 & 34.4061 & -2.40614 \tabularnewline
18 & 38 & 35.8791 & 2.12086 \tabularnewline
19 & 38 & 35.7719 & 2.22811 \tabularnewline
20 & 32 & 33.0347 & -1.03474 \tabularnewline
21 & 33 & 32.9855 & 0.0145399 \tabularnewline
22 & 31 & 32.4994 & -1.49939 \tabularnewline
23 & 38 & 36.0846 & 1.91539 \tabularnewline
24 & 39 & 34.7757 & 4.22426 \tabularnewline
25 & 32 & 36.2758 & -4.27575 \tabularnewline
26 & 32 & 36.9382 & -4.93818 \tabularnewline
27 & 35 & 34.477 & 0.523028 \tabularnewline
28 & 37 & 33.8708 & 3.12916 \tabularnewline
29 & 33 & 33.5856 & -0.585555 \tabularnewline
30 & 33 & 33.3483 & -0.348309 \tabularnewline
31 & 31 & 32.7845 & -1.78445 \tabularnewline
32 & 32 & 29.9572 & 2.04279 \tabularnewline
33 & 31 & 34.8885 & -3.88846 \tabularnewline
34 & 37 & 34.0474 & 2.95263 \tabularnewline
35 & 30 & 33.9236 & -3.92362 \tabularnewline
36 & 33 & 32.1231 & 0.876901 \tabularnewline
37 & 31 & 30.9193 & 0.0807391 \tabularnewline
38 & 33 & 34.7797 & -1.77969 \tabularnewline
39 & 31 & 31.5357 & -0.535725 \tabularnewline
40 & 33 & 33.851 & -0.851041 \tabularnewline
41 & 32 & 34.8191 & -2.81905 \tabularnewline
42 & 33 & 34.0063 & -1.00629 \tabularnewline
43 & 32 & 36.1074 & -4.1074 \tabularnewline
44 & 33 & 33.6673 & -0.667289 \tabularnewline
45 & 28 & 35.1981 & -7.1981 \tabularnewline
46 & 35 & 35.0044 & -0.00441219 \tabularnewline
47 & 39 & 35.7569 & 3.24312 \tabularnewline
48 & 34 & 33.328 & 0.671983 \tabularnewline
49 & 38 & 34.6779 & 3.32214 \tabularnewline
50 & 32 & 35.56 & -3.56001 \tabularnewline
51 & 38 & 33.5135 & 4.48655 \tabularnewline
52 & 30 & 32.5958 & -2.59585 \tabularnewline
53 & 33 & 32.8448 & 0.155217 \tabularnewline
54 & 38 & 33.9148 & 4.08524 \tabularnewline
55 & 32 & 31.4707 & 0.529271 \tabularnewline
56 & 35 & 34.0265 & 0.973501 \tabularnewline
57 & 34 & 36.0919 & -2.0919 \tabularnewline
58 & 34 & 31.7484 & 2.25157 \tabularnewline
59 & 36 & 34.8644 & 1.13563 \tabularnewline
60 & 34 & 33.8004 & 0.199586 \tabularnewline
61 & 28 & 30.7834 & -2.78344 \tabularnewline
62 & 34 & 35.5623 & -1.56231 \tabularnewline
63 & 35 & 34.2107 & 0.789297 \tabularnewline
64 & 35 & 32.2278 & 2.77221 \tabularnewline
65 & 31 & 33.7525 & -2.75247 \tabularnewline
66 & 37 & 34.5708 & 2.42917 \tabularnewline
67 & 35 & 35.1258 & -0.12581 \tabularnewline
68 & 27 & 32.0757 & -5.07571 \tabularnewline
69 & 40 & 36.1242 & 3.87585 \tabularnewline
70 & 37 & 34.4823 & 2.51769 \tabularnewline
71 & 36 & 34.8918 & 1.10821 \tabularnewline
72 & 38 & 32.5012 & 5.49876 \tabularnewline
73 & 39 & 34.5548 & 4.4452 \tabularnewline
74 & 41 & 36.1389 & 4.86112 \tabularnewline
75 & 27 & 34.0921 & -7.09214 \tabularnewline
76 & 30 & 35.5484 & -5.54843 \tabularnewline
77 & 37 & 35.6077 & 1.39227 \tabularnewline
78 & 31 & 33.7718 & -2.77181 \tabularnewline
79 & 31 & 31.5724 & -0.572446 \tabularnewline
80 & 27 & 35.0958 & -8.09579 \tabularnewline
81 & 36 & 33.6998 & 2.30023 \tabularnewline
82 & 37 & 34.4731 & 2.52689 \tabularnewline
83 & 33 & 35.3822 & -2.38225 \tabularnewline
84 & 34 & 33.0146 & 0.985355 \tabularnewline
85 & 31 & 33.2404 & -2.24036 \tabularnewline
86 & 39 & 35.18 & 3.82004 \tabularnewline
87 & 34 & 33.5671 & 0.432855 \tabularnewline
88 & 32 & 31.7092 & 0.290822 \tabularnewline
89 & 33 & 33.3053 & -0.305261 \tabularnewline
90 & 36 & 32.2757 & 3.72434 \tabularnewline
91 & 32 & 35.2681 & -3.26815 \tabularnewline
92 & 41 & 34.518 & 6.48196 \tabularnewline
93 & 28 & 33.252 & -5.252 \tabularnewline
94 & 30 & 31.9177 & -1.91766 \tabularnewline
95 & 36 & 35.8704 & 0.129576 \tabularnewline
96 & 35 & 35.3737 & -0.373716 \tabularnewline
97 & 31 & 33.8753 & -2.87531 \tabularnewline
98 & 34 & 35.4687 & -1.46866 \tabularnewline
99 & 36 & 32.8242 & 3.17576 \tabularnewline
100 & 36 & 36.2444 & -0.244393 \tabularnewline
101 & 35 & 35.0012 & -0.00120449 \tabularnewline
102 & 37 & 35.6343 & 1.36573 \tabularnewline
103 & 28 & 32.7713 & -4.77131 \tabularnewline
104 & 39 & 33.4776 & 5.52241 \tabularnewline
105 & 32 & 36.3058 & -4.30583 \tabularnewline
106 & 35 & 35.7973 & -0.797344 \tabularnewline
107 & 39 & 36.9921 & 2.00791 \tabularnewline
108 & 35 & 34.3223 & 0.677703 \tabularnewline
109 & 42 & 36.4343 & 5.5657 \tabularnewline
110 & 34 & 32.4463 & 1.55374 \tabularnewline
111 & 33 & 33.0122 & -0.0121824 \tabularnewline
112 & 41 & 33.0283 & 7.97172 \tabularnewline
113 & 33 & 32.6494 & 0.350634 \tabularnewline
114 & 34 & 35.0471 & -1.04706 \tabularnewline
115 & 32 & 35.6446 & -3.64462 \tabularnewline
116 & 40 & 33.6027 & 6.3973 \tabularnewline
117 & 40 & 33.1344 & 6.86559 \tabularnewline
118 & 35 & 33.3185 & 1.68148 \tabularnewline
119 & 36 & 35.8243 & 0.175651 \tabularnewline
120 & 37 & 33.1175 & 3.88255 \tabularnewline
121 & 27 & 32.9365 & -5.93652 \tabularnewline
122 & 39 & 35.845 & 3.15504 \tabularnewline
123 & 38 & 35.7033 & 2.2967 \tabularnewline
124 & 31 & 35.0589 & -4.05888 \tabularnewline
125 & 33 & 33.3095 & -0.309466 \tabularnewline
126 & 32 & 35.9478 & -3.94784 \tabularnewline
127 & 39 & 38.1306 & 0.869373 \tabularnewline
128 & 36 & 33.216 & 2.78404 \tabularnewline
129 & 33 & 34.2242 & -1.22422 \tabularnewline
130 & 33 & 32.6586 & 0.341444 \tabularnewline
131 & 32 & 30.9742 & 1.02575 \tabularnewline
132 & 37 & 35.7743 & 1.2257 \tabularnewline
133 & 30 & 30.7758 & -0.775817 \tabularnewline
134 & 38 & 35.279 & 2.72101 \tabularnewline
135 & 29 & 33.2993 & -4.29928 \tabularnewline
136 & 22 & 30.5531 & -8.55306 \tabularnewline
137 & 35 & 33.674 & 1.32604 \tabularnewline
138 & 35 & 31.5834 & 3.41656 \tabularnewline
139 & 34 & 33.5388 & 0.461188 \tabularnewline
140 & 35 & 32.0063 & 2.99367 \tabularnewline
141 & 34 & 32.1788 & 1.82125 \tabularnewline
142 & 37 & 31.8348 & 5.16521 \tabularnewline
143 & 35 & 32.9637 & 2.03635 \tabularnewline
144 & 23 & 32.5506 & -9.55058 \tabularnewline
145 & 31 & 35.9014 & -4.90143 \tabularnewline
146 & 27 & 33.4033 & -6.40329 \tabularnewline
147 & 36 & 34.5563 & 1.44374 \tabularnewline
148 & 31 & 33.0263 & -2.02635 \tabularnewline
149 & 32 & 33.571 & -1.57098 \tabularnewline
150 & 39 & 34.8157 & 4.18428 \tabularnewline
151 & 37 & 37.5424 & -0.542365 \tabularnewline
152 & 38 & 33.394 & 4.60598 \tabularnewline
153 & 39 & 33.0669 & 5.9331 \tabularnewline
154 & 34 & 34.4166 & -0.416599 \tabularnewline
155 & 31 & 32.7207 & -1.72065 \tabularnewline
156 & 32 & 35.1779 & -3.1779 \tabularnewline
157 & 37 & 31.8514 & 5.14858 \tabularnewline
158 & 36 & 33.1743 & 2.8257 \tabularnewline
159 & 32 & 33.7718 & -1.77184 \tabularnewline
160 & 38 & 32.3005 & 5.6995 \tabularnewline
161 & 36 & 33.0552 & 2.94485 \tabularnewline
162 & 26 & 30.5403 & -4.54028 \tabularnewline
163 & 26 & 32.1053 & -6.1053 \tabularnewline
164 & 33 & 36.3685 & -3.36853 \tabularnewline
165 & 39 & 33.5394 & 5.46061 \tabularnewline
166 & 30 & 28.8017 & 1.19829 \tabularnewline
167 & 33 & 32.2465 & 0.753541 \tabularnewline
168 & 25 & 30.6392 & -5.63919 \tabularnewline
169 & 38 & 33.9739 & 4.02608 \tabularnewline
170 & 37 & 30.936 & 6.06398 \tabularnewline
171 & 31 & 33.7019 & -2.70194 \tabularnewline
172 & 37 & 35.0104 & 1.98958 \tabularnewline
173 & 35 & 36.4906 & -1.49058 \tabularnewline
174 & 25 & 30.8207 & -5.82071 \tabularnewline
175 & 28 & 35.0082 & -7.00817 \tabularnewline
176 & 35 & 33.034 & 1.96601 \tabularnewline
177 & 33 & 34.3143 & -1.31429 \tabularnewline
178 & 30 & 31.6844 & -1.68438 \tabularnewline
179 & 31 & 32.4377 & -1.4377 \tabularnewline
180 & 37 & 35.0626 & 1.93741 \tabularnewline
181 & 36 & 34.7606 & 1.23937 \tabularnewline
182 & 30 & 33.2029 & -3.20287 \tabularnewline
183 & 36 & 33.4178 & 2.58219 \tabularnewline
184 & 32 & 35.8229 & -3.82291 \tabularnewline
185 & 28 & 29.2081 & -1.20807 \tabularnewline
186 & 36 & 33.2221 & 2.77793 \tabularnewline
187 & 34 & 34.7287 & -0.728697 \tabularnewline
188 & 31 & 35.3461 & -4.34606 \tabularnewline
189 & 28 & 30.3281 & -2.32813 \tabularnewline
190 & 36 & 31.6117 & 4.38826 \tabularnewline
191 & 36 & 32.7978 & 3.20222 \tabularnewline
192 & 40 & 35.7692 & 4.23081 \tabularnewline
193 & 33 & 31.4285 & 1.57152 \tabularnewline
194 & 37 & 34.0742 & 2.92577 \tabularnewline
195 & 32 & 32.8482 & -0.848176 \tabularnewline
196 & 38 & 35.2195 & 2.78047 \tabularnewline
197 & 31 & 33.5206 & -2.5206 \tabularnewline
198 & 37 & 33.7558 & 3.24415 \tabularnewline
199 & 33 & 32.7037 & 0.29629 \tabularnewline
200 & 32 & 30.6594 & 1.34062 \tabularnewline
201 & 30 & 32.1271 & -2.1271 \tabularnewline
202 & 30 & 29.422 & 0.577969 \tabularnewline
203 & 31 & 33.5858 & -2.58575 \tabularnewline
204 & 32 & 33.8467 & -1.84673 \tabularnewline
205 & 34 & 32.8522 & 1.14775 \tabularnewline
206 & 36 & 33.8946 & 2.10538 \tabularnewline
207 & 37 & 34.3675 & 2.63253 \tabularnewline
208 & 36 & 34.3723 & 1.62766 \tabularnewline
209 & 33 & 34.4233 & -1.42325 \tabularnewline
210 & 33 & 33.8135 & -0.813521 \tabularnewline
211 & 33 & 33.7641 & -0.764104 \tabularnewline
212 & 44 & 37.1721 & 6.82787 \tabularnewline
213 & 39 & 32.9946 & 6.00535 \tabularnewline
214 & 32 & 31.4283 & 0.571746 \tabularnewline
215 & 35 & 34.2894 & 0.710555 \tabularnewline
216 & 25 & 31.0639 & -6.06393 \tabularnewline
217 & 35 & 33.6278 & 1.37216 \tabularnewline
218 & 34 & 35.8288 & -1.82883 \tabularnewline
219 & 35 & 33.7435 & 1.25653 \tabularnewline
220 & 39 & 34.9919 & 4.00813 \tabularnewline
221 & 33 & 34.3482 & -1.34823 \tabularnewline
222 & 36 & 35.2688 & 0.731241 \tabularnewline
223 & 32 & 33.4332 & -1.43323 \tabularnewline
224 & 32 & 32.1751 & -0.175109 \tabularnewline
225 & 36 & 32.9312 & 3.06876 \tabularnewline
226 & 36 & 32.0902 & 3.90975 \tabularnewline
227 & 32 & 32.3851 & -0.385086 \tabularnewline
228 & 34 & 32.8224 & 1.17757 \tabularnewline
229 & 33 & 33.1272 & -0.127201 \tabularnewline
230 & 35 & 33.2636 & 1.73636 \tabularnewline
231 & 30 & 32.7923 & -2.79229 \tabularnewline
232 & 38 & 32.9356 & 5.06444 \tabularnewline
233 & 34 & 31.8672 & 2.13283 \tabularnewline
234 & 33 & 37.3276 & -4.32756 \tabularnewline
235 & 32 & 33.6708 & -1.67077 \tabularnewline
236 & 31 & 34.3038 & -3.30382 \tabularnewline
237 & 30 & 34.0243 & -4.02435 \tabularnewline
238 & 27 & 34.6103 & -7.61026 \tabularnewline
239 & 31 & 31.706 & -0.705991 \tabularnewline
240 & 30 & 34.1354 & -4.13536 \tabularnewline
241 & 32 & 30.2735 & 1.72646 \tabularnewline
242 & 35 & 33.8137 & 1.18629 \tabularnewline
243 & 28 & 29.4508 & -1.45079 \tabularnewline
244 & 33 & 33.0807 & -0.0807227 \tabularnewline
245 & 31 & 34.9809 & -3.98087 \tabularnewline
246 & 35 & 30.9296 & 4.07038 \tabularnewline
247 & 35 & 32.462 & 2.53798 \tabularnewline
248 & 32 & 34.0059 & -2.0059 \tabularnewline
249 & 21 & 26.5399 & -5.5399 \tabularnewline
250 & 20 & 27.6338 & -7.6338 \tabularnewline
251 & 34 & 31.7305 & 2.2695 \tabularnewline
252 & 32 & 32.5679 & -0.567866 \tabularnewline
253 & 34 & 33.5656 & 0.434398 \tabularnewline
254 & 32 & 32.9059 & -0.905937 \tabularnewline
255 & 33 & 34.7305 & -1.7305 \tabularnewline
256 & 33 & 33.6464 & -0.646447 \tabularnewline
257 & 37 & 34.225 & 2.77496 \tabularnewline
258 & 32 & 31.6143 & 0.385739 \tabularnewline
259 & 34 & 35.0353 & -1.03533 \tabularnewline
260 & 30 & 32.5066 & -2.50662 \tabularnewline
261 & 30 & 30.7265 & -0.726485 \tabularnewline
262 & 38 & 33.9636 & 4.03636 \tabularnewline
263 & 36 & 35.1436 & 0.856391 \tabularnewline
264 & 32 & 31.2376 & 0.762401 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226347&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]38[/C][C]36.7536[/C][C]1.24645[/C][/ROW]
[ROW][C]2[/C][C]32[/C][C]36.1233[/C][C]-4.12326[/C][/ROW]
[ROW][C]3[/C][C]35[/C][C]32.6848[/C][C]2.31516[/C][/ROW]
[ROW][C]4[/C][C]33[/C][C]31.354[/C][C]1.64599[/C][/ROW]
[ROW][C]5[/C][C]37[/C][C]34.2794[/C][C]2.72056[/C][/ROW]
[ROW][C]6[/C][C]29[/C][C]34.1837[/C][C]-5.18366[/C][/ROW]
[ROW][C]7[/C][C]31[/C][C]35.9177[/C][C]-4.91765[/C][/ROW]
[ROW][C]8[/C][C]36[/C][C]34.4081[/C][C]1.59193[/C][/ROW]
[ROW][C]9[/C][C]35[/C][C]34.8417[/C][C]0.158313[/C][/ROW]
[ROW][C]10[/C][C]38[/C][C]34.687[/C][C]3.31302[/C][/ROW]
[ROW][C]11[/C][C]31[/C][C]35.4106[/C][C]-4.41057[/C][/ROW]
[ROW][C]12[/C][C]34[/C][C]34.8271[/C][C]-0.827111[/C][/ROW]
[ROW][C]13[/C][C]35[/C][C]35.4279[/C][C]-0.427948[/C][/ROW]
[ROW][C]14[/C][C]38[/C][C]35.7832[/C][C]2.21678[/C][/ROW]
[ROW][C]15[/C][C]37[/C][C]34.3964[/C][C]2.60355[/C][/ROW]
[ROW][C]16[/C][C]33[/C][C]32.9688[/C][C]0.0312153[/C][/ROW]
[ROW][C]17[/C][C]32[/C][C]34.4061[/C][C]-2.40614[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]35.8791[/C][C]2.12086[/C][/ROW]
[ROW][C]19[/C][C]38[/C][C]35.7719[/C][C]2.22811[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]33.0347[/C][C]-1.03474[/C][/ROW]
[ROW][C]21[/C][C]33[/C][C]32.9855[/C][C]0.0145399[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]32.4994[/C][C]-1.49939[/C][/ROW]
[ROW][C]23[/C][C]38[/C][C]36.0846[/C][C]1.91539[/C][/ROW]
[ROW][C]24[/C][C]39[/C][C]34.7757[/C][C]4.22426[/C][/ROW]
[ROW][C]25[/C][C]32[/C][C]36.2758[/C][C]-4.27575[/C][/ROW]
[ROW][C]26[/C][C]32[/C][C]36.9382[/C][C]-4.93818[/C][/ROW]
[ROW][C]27[/C][C]35[/C][C]34.477[/C][C]0.523028[/C][/ROW]
[ROW][C]28[/C][C]37[/C][C]33.8708[/C][C]3.12916[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]33.5856[/C][C]-0.585555[/C][/ROW]
[ROW][C]30[/C][C]33[/C][C]33.3483[/C][C]-0.348309[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]32.7845[/C][C]-1.78445[/C][/ROW]
[ROW][C]32[/C][C]32[/C][C]29.9572[/C][C]2.04279[/C][/ROW]
[ROW][C]33[/C][C]31[/C][C]34.8885[/C][C]-3.88846[/C][/ROW]
[ROW][C]34[/C][C]37[/C][C]34.0474[/C][C]2.95263[/C][/ROW]
[ROW][C]35[/C][C]30[/C][C]33.9236[/C][C]-3.92362[/C][/ROW]
[ROW][C]36[/C][C]33[/C][C]32.1231[/C][C]0.876901[/C][/ROW]
[ROW][C]37[/C][C]31[/C][C]30.9193[/C][C]0.0807391[/C][/ROW]
[ROW][C]38[/C][C]33[/C][C]34.7797[/C][C]-1.77969[/C][/ROW]
[ROW][C]39[/C][C]31[/C][C]31.5357[/C][C]-0.535725[/C][/ROW]
[ROW][C]40[/C][C]33[/C][C]33.851[/C][C]-0.851041[/C][/ROW]
[ROW][C]41[/C][C]32[/C][C]34.8191[/C][C]-2.81905[/C][/ROW]
[ROW][C]42[/C][C]33[/C][C]34.0063[/C][C]-1.00629[/C][/ROW]
[ROW][C]43[/C][C]32[/C][C]36.1074[/C][C]-4.1074[/C][/ROW]
[ROW][C]44[/C][C]33[/C][C]33.6673[/C][C]-0.667289[/C][/ROW]
[ROW][C]45[/C][C]28[/C][C]35.1981[/C][C]-7.1981[/C][/ROW]
[ROW][C]46[/C][C]35[/C][C]35.0044[/C][C]-0.00441219[/C][/ROW]
[ROW][C]47[/C][C]39[/C][C]35.7569[/C][C]3.24312[/C][/ROW]
[ROW][C]48[/C][C]34[/C][C]33.328[/C][C]0.671983[/C][/ROW]
[ROW][C]49[/C][C]38[/C][C]34.6779[/C][C]3.32214[/C][/ROW]
[ROW][C]50[/C][C]32[/C][C]35.56[/C][C]-3.56001[/C][/ROW]
[ROW][C]51[/C][C]38[/C][C]33.5135[/C][C]4.48655[/C][/ROW]
[ROW][C]52[/C][C]30[/C][C]32.5958[/C][C]-2.59585[/C][/ROW]
[ROW][C]53[/C][C]33[/C][C]32.8448[/C][C]0.155217[/C][/ROW]
[ROW][C]54[/C][C]38[/C][C]33.9148[/C][C]4.08524[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]31.4707[/C][C]0.529271[/C][/ROW]
[ROW][C]56[/C][C]35[/C][C]34.0265[/C][C]0.973501[/C][/ROW]
[ROW][C]57[/C][C]34[/C][C]36.0919[/C][C]-2.0919[/C][/ROW]
[ROW][C]58[/C][C]34[/C][C]31.7484[/C][C]2.25157[/C][/ROW]
[ROW][C]59[/C][C]36[/C][C]34.8644[/C][C]1.13563[/C][/ROW]
[ROW][C]60[/C][C]34[/C][C]33.8004[/C][C]0.199586[/C][/ROW]
[ROW][C]61[/C][C]28[/C][C]30.7834[/C][C]-2.78344[/C][/ROW]
[ROW][C]62[/C][C]34[/C][C]35.5623[/C][C]-1.56231[/C][/ROW]
[ROW][C]63[/C][C]35[/C][C]34.2107[/C][C]0.789297[/C][/ROW]
[ROW][C]64[/C][C]35[/C][C]32.2278[/C][C]2.77221[/C][/ROW]
[ROW][C]65[/C][C]31[/C][C]33.7525[/C][C]-2.75247[/C][/ROW]
[ROW][C]66[/C][C]37[/C][C]34.5708[/C][C]2.42917[/C][/ROW]
[ROW][C]67[/C][C]35[/C][C]35.1258[/C][C]-0.12581[/C][/ROW]
[ROW][C]68[/C][C]27[/C][C]32.0757[/C][C]-5.07571[/C][/ROW]
[ROW][C]69[/C][C]40[/C][C]36.1242[/C][C]3.87585[/C][/ROW]
[ROW][C]70[/C][C]37[/C][C]34.4823[/C][C]2.51769[/C][/ROW]
[ROW][C]71[/C][C]36[/C][C]34.8918[/C][C]1.10821[/C][/ROW]
[ROW][C]72[/C][C]38[/C][C]32.5012[/C][C]5.49876[/C][/ROW]
[ROW][C]73[/C][C]39[/C][C]34.5548[/C][C]4.4452[/C][/ROW]
[ROW][C]74[/C][C]41[/C][C]36.1389[/C][C]4.86112[/C][/ROW]
[ROW][C]75[/C][C]27[/C][C]34.0921[/C][C]-7.09214[/C][/ROW]
[ROW][C]76[/C][C]30[/C][C]35.5484[/C][C]-5.54843[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.6077[/C][C]1.39227[/C][/ROW]
[ROW][C]78[/C][C]31[/C][C]33.7718[/C][C]-2.77181[/C][/ROW]
[ROW][C]79[/C][C]31[/C][C]31.5724[/C][C]-0.572446[/C][/ROW]
[ROW][C]80[/C][C]27[/C][C]35.0958[/C][C]-8.09579[/C][/ROW]
[ROW][C]81[/C][C]36[/C][C]33.6998[/C][C]2.30023[/C][/ROW]
[ROW][C]82[/C][C]37[/C][C]34.4731[/C][C]2.52689[/C][/ROW]
[ROW][C]83[/C][C]33[/C][C]35.3822[/C][C]-2.38225[/C][/ROW]
[ROW][C]84[/C][C]34[/C][C]33.0146[/C][C]0.985355[/C][/ROW]
[ROW][C]85[/C][C]31[/C][C]33.2404[/C][C]-2.24036[/C][/ROW]
[ROW][C]86[/C][C]39[/C][C]35.18[/C][C]3.82004[/C][/ROW]
[ROW][C]87[/C][C]34[/C][C]33.5671[/C][C]0.432855[/C][/ROW]
[ROW][C]88[/C][C]32[/C][C]31.7092[/C][C]0.290822[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]33.3053[/C][C]-0.305261[/C][/ROW]
[ROW][C]90[/C][C]36[/C][C]32.2757[/C][C]3.72434[/C][/ROW]
[ROW][C]91[/C][C]32[/C][C]35.2681[/C][C]-3.26815[/C][/ROW]
[ROW][C]92[/C][C]41[/C][C]34.518[/C][C]6.48196[/C][/ROW]
[ROW][C]93[/C][C]28[/C][C]33.252[/C][C]-5.252[/C][/ROW]
[ROW][C]94[/C][C]30[/C][C]31.9177[/C][C]-1.91766[/C][/ROW]
[ROW][C]95[/C][C]36[/C][C]35.8704[/C][C]0.129576[/C][/ROW]
[ROW][C]96[/C][C]35[/C][C]35.3737[/C][C]-0.373716[/C][/ROW]
[ROW][C]97[/C][C]31[/C][C]33.8753[/C][C]-2.87531[/C][/ROW]
[ROW][C]98[/C][C]34[/C][C]35.4687[/C][C]-1.46866[/C][/ROW]
[ROW][C]99[/C][C]36[/C][C]32.8242[/C][C]3.17576[/C][/ROW]
[ROW][C]100[/C][C]36[/C][C]36.2444[/C][C]-0.244393[/C][/ROW]
[ROW][C]101[/C][C]35[/C][C]35.0012[/C][C]-0.00120449[/C][/ROW]
[ROW][C]102[/C][C]37[/C][C]35.6343[/C][C]1.36573[/C][/ROW]
[ROW][C]103[/C][C]28[/C][C]32.7713[/C][C]-4.77131[/C][/ROW]
[ROW][C]104[/C][C]39[/C][C]33.4776[/C][C]5.52241[/C][/ROW]
[ROW][C]105[/C][C]32[/C][C]36.3058[/C][C]-4.30583[/C][/ROW]
[ROW][C]106[/C][C]35[/C][C]35.7973[/C][C]-0.797344[/C][/ROW]
[ROW][C]107[/C][C]39[/C][C]36.9921[/C][C]2.00791[/C][/ROW]
[ROW][C]108[/C][C]35[/C][C]34.3223[/C][C]0.677703[/C][/ROW]
[ROW][C]109[/C][C]42[/C][C]36.4343[/C][C]5.5657[/C][/ROW]
[ROW][C]110[/C][C]34[/C][C]32.4463[/C][C]1.55374[/C][/ROW]
[ROW][C]111[/C][C]33[/C][C]33.0122[/C][C]-0.0121824[/C][/ROW]
[ROW][C]112[/C][C]41[/C][C]33.0283[/C][C]7.97172[/C][/ROW]
[ROW][C]113[/C][C]33[/C][C]32.6494[/C][C]0.350634[/C][/ROW]
[ROW][C]114[/C][C]34[/C][C]35.0471[/C][C]-1.04706[/C][/ROW]
[ROW][C]115[/C][C]32[/C][C]35.6446[/C][C]-3.64462[/C][/ROW]
[ROW][C]116[/C][C]40[/C][C]33.6027[/C][C]6.3973[/C][/ROW]
[ROW][C]117[/C][C]40[/C][C]33.1344[/C][C]6.86559[/C][/ROW]
[ROW][C]118[/C][C]35[/C][C]33.3185[/C][C]1.68148[/C][/ROW]
[ROW][C]119[/C][C]36[/C][C]35.8243[/C][C]0.175651[/C][/ROW]
[ROW][C]120[/C][C]37[/C][C]33.1175[/C][C]3.88255[/C][/ROW]
[ROW][C]121[/C][C]27[/C][C]32.9365[/C][C]-5.93652[/C][/ROW]
[ROW][C]122[/C][C]39[/C][C]35.845[/C][C]3.15504[/C][/ROW]
[ROW][C]123[/C][C]38[/C][C]35.7033[/C][C]2.2967[/C][/ROW]
[ROW][C]124[/C][C]31[/C][C]35.0589[/C][C]-4.05888[/C][/ROW]
[ROW][C]125[/C][C]33[/C][C]33.3095[/C][C]-0.309466[/C][/ROW]
[ROW][C]126[/C][C]32[/C][C]35.9478[/C][C]-3.94784[/C][/ROW]
[ROW][C]127[/C][C]39[/C][C]38.1306[/C][C]0.869373[/C][/ROW]
[ROW][C]128[/C][C]36[/C][C]33.216[/C][C]2.78404[/C][/ROW]
[ROW][C]129[/C][C]33[/C][C]34.2242[/C][C]-1.22422[/C][/ROW]
[ROW][C]130[/C][C]33[/C][C]32.6586[/C][C]0.341444[/C][/ROW]
[ROW][C]131[/C][C]32[/C][C]30.9742[/C][C]1.02575[/C][/ROW]
[ROW][C]132[/C][C]37[/C][C]35.7743[/C][C]1.2257[/C][/ROW]
[ROW][C]133[/C][C]30[/C][C]30.7758[/C][C]-0.775817[/C][/ROW]
[ROW][C]134[/C][C]38[/C][C]35.279[/C][C]2.72101[/C][/ROW]
[ROW][C]135[/C][C]29[/C][C]33.2993[/C][C]-4.29928[/C][/ROW]
[ROW][C]136[/C][C]22[/C][C]30.5531[/C][C]-8.55306[/C][/ROW]
[ROW][C]137[/C][C]35[/C][C]33.674[/C][C]1.32604[/C][/ROW]
[ROW][C]138[/C][C]35[/C][C]31.5834[/C][C]3.41656[/C][/ROW]
[ROW][C]139[/C][C]34[/C][C]33.5388[/C][C]0.461188[/C][/ROW]
[ROW][C]140[/C][C]35[/C][C]32.0063[/C][C]2.99367[/C][/ROW]
[ROW][C]141[/C][C]34[/C][C]32.1788[/C][C]1.82125[/C][/ROW]
[ROW][C]142[/C][C]37[/C][C]31.8348[/C][C]5.16521[/C][/ROW]
[ROW][C]143[/C][C]35[/C][C]32.9637[/C][C]2.03635[/C][/ROW]
[ROW][C]144[/C][C]23[/C][C]32.5506[/C][C]-9.55058[/C][/ROW]
[ROW][C]145[/C][C]31[/C][C]35.9014[/C][C]-4.90143[/C][/ROW]
[ROW][C]146[/C][C]27[/C][C]33.4033[/C][C]-6.40329[/C][/ROW]
[ROW][C]147[/C][C]36[/C][C]34.5563[/C][C]1.44374[/C][/ROW]
[ROW][C]148[/C][C]31[/C][C]33.0263[/C][C]-2.02635[/C][/ROW]
[ROW][C]149[/C][C]32[/C][C]33.571[/C][C]-1.57098[/C][/ROW]
[ROW][C]150[/C][C]39[/C][C]34.8157[/C][C]4.18428[/C][/ROW]
[ROW][C]151[/C][C]37[/C][C]37.5424[/C][C]-0.542365[/C][/ROW]
[ROW][C]152[/C][C]38[/C][C]33.394[/C][C]4.60598[/C][/ROW]
[ROW][C]153[/C][C]39[/C][C]33.0669[/C][C]5.9331[/C][/ROW]
[ROW][C]154[/C][C]34[/C][C]34.4166[/C][C]-0.416599[/C][/ROW]
[ROW][C]155[/C][C]31[/C][C]32.7207[/C][C]-1.72065[/C][/ROW]
[ROW][C]156[/C][C]32[/C][C]35.1779[/C][C]-3.1779[/C][/ROW]
[ROW][C]157[/C][C]37[/C][C]31.8514[/C][C]5.14858[/C][/ROW]
[ROW][C]158[/C][C]36[/C][C]33.1743[/C][C]2.8257[/C][/ROW]
[ROW][C]159[/C][C]32[/C][C]33.7718[/C][C]-1.77184[/C][/ROW]
[ROW][C]160[/C][C]38[/C][C]32.3005[/C][C]5.6995[/C][/ROW]
[ROW][C]161[/C][C]36[/C][C]33.0552[/C][C]2.94485[/C][/ROW]
[ROW][C]162[/C][C]26[/C][C]30.5403[/C][C]-4.54028[/C][/ROW]
[ROW][C]163[/C][C]26[/C][C]32.1053[/C][C]-6.1053[/C][/ROW]
[ROW][C]164[/C][C]33[/C][C]36.3685[/C][C]-3.36853[/C][/ROW]
[ROW][C]165[/C][C]39[/C][C]33.5394[/C][C]5.46061[/C][/ROW]
[ROW][C]166[/C][C]30[/C][C]28.8017[/C][C]1.19829[/C][/ROW]
[ROW][C]167[/C][C]33[/C][C]32.2465[/C][C]0.753541[/C][/ROW]
[ROW][C]168[/C][C]25[/C][C]30.6392[/C][C]-5.63919[/C][/ROW]
[ROW][C]169[/C][C]38[/C][C]33.9739[/C][C]4.02608[/C][/ROW]
[ROW][C]170[/C][C]37[/C][C]30.936[/C][C]6.06398[/C][/ROW]
[ROW][C]171[/C][C]31[/C][C]33.7019[/C][C]-2.70194[/C][/ROW]
[ROW][C]172[/C][C]37[/C][C]35.0104[/C][C]1.98958[/C][/ROW]
[ROW][C]173[/C][C]35[/C][C]36.4906[/C][C]-1.49058[/C][/ROW]
[ROW][C]174[/C][C]25[/C][C]30.8207[/C][C]-5.82071[/C][/ROW]
[ROW][C]175[/C][C]28[/C][C]35.0082[/C][C]-7.00817[/C][/ROW]
[ROW][C]176[/C][C]35[/C][C]33.034[/C][C]1.96601[/C][/ROW]
[ROW][C]177[/C][C]33[/C][C]34.3143[/C][C]-1.31429[/C][/ROW]
[ROW][C]178[/C][C]30[/C][C]31.6844[/C][C]-1.68438[/C][/ROW]
[ROW][C]179[/C][C]31[/C][C]32.4377[/C][C]-1.4377[/C][/ROW]
[ROW][C]180[/C][C]37[/C][C]35.0626[/C][C]1.93741[/C][/ROW]
[ROW][C]181[/C][C]36[/C][C]34.7606[/C][C]1.23937[/C][/ROW]
[ROW][C]182[/C][C]30[/C][C]33.2029[/C][C]-3.20287[/C][/ROW]
[ROW][C]183[/C][C]36[/C][C]33.4178[/C][C]2.58219[/C][/ROW]
[ROW][C]184[/C][C]32[/C][C]35.8229[/C][C]-3.82291[/C][/ROW]
[ROW][C]185[/C][C]28[/C][C]29.2081[/C][C]-1.20807[/C][/ROW]
[ROW][C]186[/C][C]36[/C][C]33.2221[/C][C]2.77793[/C][/ROW]
[ROW][C]187[/C][C]34[/C][C]34.7287[/C][C]-0.728697[/C][/ROW]
[ROW][C]188[/C][C]31[/C][C]35.3461[/C][C]-4.34606[/C][/ROW]
[ROW][C]189[/C][C]28[/C][C]30.3281[/C][C]-2.32813[/C][/ROW]
[ROW][C]190[/C][C]36[/C][C]31.6117[/C][C]4.38826[/C][/ROW]
[ROW][C]191[/C][C]36[/C][C]32.7978[/C][C]3.20222[/C][/ROW]
[ROW][C]192[/C][C]40[/C][C]35.7692[/C][C]4.23081[/C][/ROW]
[ROW][C]193[/C][C]33[/C][C]31.4285[/C][C]1.57152[/C][/ROW]
[ROW][C]194[/C][C]37[/C][C]34.0742[/C][C]2.92577[/C][/ROW]
[ROW][C]195[/C][C]32[/C][C]32.8482[/C][C]-0.848176[/C][/ROW]
[ROW][C]196[/C][C]38[/C][C]35.2195[/C][C]2.78047[/C][/ROW]
[ROW][C]197[/C][C]31[/C][C]33.5206[/C][C]-2.5206[/C][/ROW]
[ROW][C]198[/C][C]37[/C][C]33.7558[/C][C]3.24415[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]32.7037[/C][C]0.29629[/C][/ROW]
[ROW][C]200[/C][C]32[/C][C]30.6594[/C][C]1.34062[/C][/ROW]
[ROW][C]201[/C][C]30[/C][C]32.1271[/C][C]-2.1271[/C][/ROW]
[ROW][C]202[/C][C]30[/C][C]29.422[/C][C]0.577969[/C][/ROW]
[ROW][C]203[/C][C]31[/C][C]33.5858[/C][C]-2.58575[/C][/ROW]
[ROW][C]204[/C][C]32[/C][C]33.8467[/C][C]-1.84673[/C][/ROW]
[ROW][C]205[/C][C]34[/C][C]32.8522[/C][C]1.14775[/C][/ROW]
[ROW][C]206[/C][C]36[/C][C]33.8946[/C][C]2.10538[/C][/ROW]
[ROW][C]207[/C][C]37[/C][C]34.3675[/C][C]2.63253[/C][/ROW]
[ROW][C]208[/C][C]36[/C][C]34.3723[/C][C]1.62766[/C][/ROW]
[ROW][C]209[/C][C]33[/C][C]34.4233[/C][C]-1.42325[/C][/ROW]
[ROW][C]210[/C][C]33[/C][C]33.8135[/C][C]-0.813521[/C][/ROW]
[ROW][C]211[/C][C]33[/C][C]33.7641[/C][C]-0.764104[/C][/ROW]
[ROW][C]212[/C][C]44[/C][C]37.1721[/C][C]6.82787[/C][/ROW]
[ROW][C]213[/C][C]39[/C][C]32.9946[/C][C]6.00535[/C][/ROW]
[ROW][C]214[/C][C]32[/C][C]31.4283[/C][C]0.571746[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]34.2894[/C][C]0.710555[/C][/ROW]
[ROW][C]216[/C][C]25[/C][C]31.0639[/C][C]-6.06393[/C][/ROW]
[ROW][C]217[/C][C]35[/C][C]33.6278[/C][C]1.37216[/C][/ROW]
[ROW][C]218[/C][C]34[/C][C]35.8288[/C][C]-1.82883[/C][/ROW]
[ROW][C]219[/C][C]35[/C][C]33.7435[/C][C]1.25653[/C][/ROW]
[ROW][C]220[/C][C]39[/C][C]34.9919[/C][C]4.00813[/C][/ROW]
[ROW][C]221[/C][C]33[/C][C]34.3482[/C][C]-1.34823[/C][/ROW]
[ROW][C]222[/C][C]36[/C][C]35.2688[/C][C]0.731241[/C][/ROW]
[ROW][C]223[/C][C]32[/C][C]33.4332[/C][C]-1.43323[/C][/ROW]
[ROW][C]224[/C][C]32[/C][C]32.1751[/C][C]-0.175109[/C][/ROW]
[ROW][C]225[/C][C]36[/C][C]32.9312[/C][C]3.06876[/C][/ROW]
[ROW][C]226[/C][C]36[/C][C]32.0902[/C][C]3.90975[/C][/ROW]
[ROW][C]227[/C][C]32[/C][C]32.3851[/C][C]-0.385086[/C][/ROW]
[ROW][C]228[/C][C]34[/C][C]32.8224[/C][C]1.17757[/C][/ROW]
[ROW][C]229[/C][C]33[/C][C]33.1272[/C][C]-0.127201[/C][/ROW]
[ROW][C]230[/C][C]35[/C][C]33.2636[/C][C]1.73636[/C][/ROW]
[ROW][C]231[/C][C]30[/C][C]32.7923[/C][C]-2.79229[/C][/ROW]
[ROW][C]232[/C][C]38[/C][C]32.9356[/C][C]5.06444[/C][/ROW]
[ROW][C]233[/C][C]34[/C][C]31.8672[/C][C]2.13283[/C][/ROW]
[ROW][C]234[/C][C]33[/C][C]37.3276[/C][C]-4.32756[/C][/ROW]
[ROW][C]235[/C][C]32[/C][C]33.6708[/C][C]-1.67077[/C][/ROW]
[ROW][C]236[/C][C]31[/C][C]34.3038[/C][C]-3.30382[/C][/ROW]
[ROW][C]237[/C][C]30[/C][C]34.0243[/C][C]-4.02435[/C][/ROW]
[ROW][C]238[/C][C]27[/C][C]34.6103[/C][C]-7.61026[/C][/ROW]
[ROW][C]239[/C][C]31[/C][C]31.706[/C][C]-0.705991[/C][/ROW]
[ROW][C]240[/C][C]30[/C][C]34.1354[/C][C]-4.13536[/C][/ROW]
[ROW][C]241[/C][C]32[/C][C]30.2735[/C][C]1.72646[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]33.8137[/C][C]1.18629[/C][/ROW]
[ROW][C]243[/C][C]28[/C][C]29.4508[/C][C]-1.45079[/C][/ROW]
[ROW][C]244[/C][C]33[/C][C]33.0807[/C][C]-0.0807227[/C][/ROW]
[ROW][C]245[/C][C]31[/C][C]34.9809[/C][C]-3.98087[/C][/ROW]
[ROW][C]246[/C][C]35[/C][C]30.9296[/C][C]4.07038[/C][/ROW]
[ROW][C]247[/C][C]35[/C][C]32.462[/C][C]2.53798[/C][/ROW]
[ROW][C]248[/C][C]32[/C][C]34.0059[/C][C]-2.0059[/C][/ROW]
[ROW][C]249[/C][C]21[/C][C]26.5399[/C][C]-5.5399[/C][/ROW]
[ROW][C]250[/C][C]20[/C][C]27.6338[/C][C]-7.6338[/C][/ROW]
[ROW][C]251[/C][C]34[/C][C]31.7305[/C][C]2.2695[/C][/ROW]
[ROW][C]252[/C][C]32[/C][C]32.5679[/C][C]-0.567866[/C][/ROW]
[ROW][C]253[/C][C]34[/C][C]33.5656[/C][C]0.434398[/C][/ROW]
[ROW][C]254[/C][C]32[/C][C]32.9059[/C][C]-0.905937[/C][/ROW]
[ROW][C]255[/C][C]33[/C][C]34.7305[/C][C]-1.7305[/C][/ROW]
[ROW][C]256[/C][C]33[/C][C]33.6464[/C][C]-0.646447[/C][/ROW]
[ROW][C]257[/C][C]37[/C][C]34.225[/C][C]2.77496[/C][/ROW]
[ROW][C]258[/C][C]32[/C][C]31.6143[/C][C]0.385739[/C][/ROW]
[ROW][C]259[/C][C]34[/C][C]35.0353[/C][C]-1.03533[/C][/ROW]
[ROW][C]260[/C][C]30[/C][C]32.5066[/C][C]-2.50662[/C][/ROW]
[ROW][C]261[/C][C]30[/C][C]30.7265[/C][C]-0.726485[/C][/ROW]
[ROW][C]262[/C][C]38[/C][C]33.9636[/C][C]4.03636[/C][/ROW]
[ROW][C]263[/C][C]36[/C][C]35.1436[/C][C]0.856391[/C][/ROW]
[ROW][C]264[/C][C]32[/C][C]31.2376[/C][C]0.762401[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226347&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226347&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
13836.75361.24645
23236.1233-4.12326
33532.68482.31516
43331.3541.64599
53734.27942.72056
62934.1837-5.18366
73135.9177-4.91765
83634.40811.59193
93534.84170.158313
103834.6873.31302
113135.4106-4.41057
123434.8271-0.827111
133535.4279-0.427948
143835.78322.21678
153734.39642.60355
163332.96880.0312153
173234.4061-2.40614
183835.87912.12086
193835.77192.22811
203233.0347-1.03474
213332.98550.0145399
223132.4994-1.49939
233836.08461.91539
243934.77574.22426
253236.2758-4.27575
263236.9382-4.93818
273534.4770.523028
283733.87083.12916
293333.5856-0.585555
303333.3483-0.348309
313132.7845-1.78445
323229.95722.04279
333134.8885-3.88846
343734.04742.95263
353033.9236-3.92362
363332.12310.876901
373130.91930.0807391
383334.7797-1.77969
393131.5357-0.535725
403333.851-0.851041
413234.8191-2.81905
423334.0063-1.00629
433236.1074-4.1074
443333.6673-0.667289
452835.1981-7.1981
463535.0044-0.00441219
473935.75693.24312
483433.3280.671983
493834.67793.32214
503235.56-3.56001
513833.51354.48655
523032.5958-2.59585
533332.84480.155217
543833.91484.08524
553231.47070.529271
563534.02650.973501
573436.0919-2.0919
583431.74842.25157
593634.86441.13563
603433.80040.199586
612830.7834-2.78344
623435.5623-1.56231
633534.21070.789297
643532.22782.77221
653133.7525-2.75247
663734.57082.42917
673535.1258-0.12581
682732.0757-5.07571
694036.12423.87585
703734.48232.51769
713634.89181.10821
723832.50125.49876
733934.55484.4452
744136.13894.86112
752734.0921-7.09214
763035.5484-5.54843
773735.60771.39227
783133.7718-2.77181
793131.5724-0.572446
802735.0958-8.09579
813633.69982.30023
823734.47312.52689
833335.3822-2.38225
843433.01460.985355
853133.2404-2.24036
863935.183.82004
873433.56710.432855
883231.70920.290822
893333.3053-0.305261
903632.27573.72434
913235.2681-3.26815
924134.5186.48196
932833.252-5.252
943031.9177-1.91766
953635.87040.129576
963535.3737-0.373716
973133.8753-2.87531
983435.4687-1.46866
993632.82423.17576
1003636.2444-0.244393
1013535.0012-0.00120449
1023735.63431.36573
1032832.7713-4.77131
1043933.47765.52241
1053236.3058-4.30583
1063535.7973-0.797344
1073936.99212.00791
1083534.32230.677703
1094236.43435.5657
1103432.44631.55374
1113333.0122-0.0121824
1124133.02837.97172
1133332.64940.350634
1143435.0471-1.04706
1153235.6446-3.64462
1164033.60276.3973
1174033.13446.86559
1183533.31851.68148
1193635.82430.175651
1203733.11753.88255
1212732.9365-5.93652
1223935.8453.15504
1233835.70332.2967
1243135.0589-4.05888
1253333.3095-0.309466
1263235.9478-3.94784
1273938.13060.869373
1283633.2162.78404
1293334.2242-1.22422
1303332.65860.341444
1313230.97421.02575
1323735.77431.2257
1333030.7758-0.775817
1343835.2792.72101
1352933.2993-4.29928
1362230.5531-8.55306
1373533.6741.32604
1383531.58343.41656
1393433.53880.461188
1403532.00632.99367
1413432.17881.82125
1423731.83485.16521
1433532.96372.03635
1442332.5506-9.55058
1453135.9014-4.90143
1462733.4033-6.40329
1473634.55631.44374
1483133.0263-2.02635
1493233.571-1.57098
1503934.81574.18428
1513737.5424-0.542365
1523833.3944.60598
1533933.06695.9331
1543434.4166-0.416599
1553132.7207-1.72065
1563235.1779-3.1779
1573731.85145.14858
1583633.17432.8257
1593233.7718-1.77184
1603832.30055.6995
1613633.05522.94485
1622630.5403-4.54028
1632632.1053-6.1053
1643336.3685-3.36853
1653933.53945.46061
1663028.80171.19829
1673332.24650.753541
1682530.6392-5.63919
1693833.97394.02608
1703730.9366.06398
1713133.7019-2.70194
1723735.01041.98958
1733536.4906-1.49058
1742530.8207-5.82071
1752835.0082-7.00817
1763533.0341.96601
1773334.3143-1.31429
1783031.6844-1.68438
1793132.4377-1.4377
1803735.06261.93741
1813634.76061.23937
1823033.2029-3.20287
1833633.41782.58219
1843235.8229-3.82291
1852829.2081-1.20807
1863633.22212.77793
1873434.7287-0.728697
1883135.3461-4.34606
1892830.3281-2.32813
1903631.61174.38826
1913632.79783.20222
1924035.76924.23081
1933331.42851.57152
1943734.07422.92577
1953232.8482-0.848176
1963835.21952.78047
1973133.5206-2.5206
1983733.75583.24415
1993332.70370.29629
2003230.65941.34062
2013032.1271-2.1271
2023029.4220.577969
2033133.5858-2.58575
2043233.8467-1.84673
2053432.85221.14775
2063633.89462.10538
2073734.36752.63253
2083634.37231.62766
2093334.4233-1.42325
2103333.8135-0.813521
2113333.7641-0.764104
2124437.17216.82787
2133932.99466.00535
2143231.42830.571746
2153534.28940.710555
2162531.0639-6.06393
2173533.62781.37216
2183435.8288-1.82883
2193533.74351.25653
2203934.99194.00813
2213334.3482-1.34823
2223635.26880.731241
2233233.4332-1.43323
2243232.1751-0.175109
2253632.93123.06876
2263632.09023.90975
2273232.3851-0.385086
2283432.82241.17757
2293333.1272-0.127201
2303533.26361.73636
2313032.7923-2.79229
2323832.93565.06444
2333431.86722.13283
2343337.3276-4.32756
2353233.6708-1.67077
2363134.3038-3.30382
2373034.0243-4.02435
2382734.6103-7.61026
2393131.706-0.705991
2403034.1354-4.13536
2413230.27351.72646
2423533.81371.18629
2432829.4508-1.45079
2443333.0807-0.0807227
2453134.9809-3.98087
2463530.92964.07038
2473532.4622.53798
2483234.0059-2.0059
2492126.5399-5.5399
2502027.6338-7.6338
2513431.73052.2695
2523232.5679-0.567866
2533433.56560.434398
2543232.9059-0.905937
2553334.7305-1.7305
2563333.6464-0.646447
2573734.2252.77496
2583231.61430.385739
2593435.0353-1.03533
2603032.5066-2.50662
2613030.7265-0.726485
2623833.96364.03636
2633635.14360.856391
2643231.23760.762401






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.7932470.4135060.206753
120.8332950.3334090.166705
130.7629860.4740280.237014
140.7523970.4952070.247603
150.68370.6326010.3163
160.6279430.7441140.372057
170.5687420.8625170.431258
180.5427260.9145470.457274
190.472570.9451410.52743
200.4159890.8319780.584011
210.3343940.6687880.665606
220.3438030.6876050.656197
230.2835640.5671290.716436
240.2862470.5724950.713753
250.3186540.6373080.681346
260.430940.8618790.56906
270.377570.7551410.62243
280.3426750.685350.657325
290.2863890.5727770.713611
300.2348250.4696510.765175
310.2073050.4146110.792695
320.1660270.3320540.833973
330.1558620.3117230.844138
340.1693480.3386970.830652
350.1873530.3747050.812647
360.1585980.3171970.841402
370.1268010.2536020.873199
380.1018760.2037520.898124
390.07907610.1581520.920924
400.06015860.1203170.939841
410.04801230.09602450.951988
420.03572310.07144610.964277
430.03930010.07860020.9607
440.02905660.05811320.970943
450.04722890.09445790.952771
460.03937540.07875080.960625
470.06223160.1244630.937768
480.05198420.1039680.948016
490.07654670.1530930.923453
500.06880510.137610.931195
510.08154290.1630860.918457
520.07510870.1502170.924891
530.05930150.1186030.940699
540.06625010.13250.93375
550.05588330.1117670.944117
560.05580750.1116150.944193
570.04536860.09073720.954631
580.03649710.07299420.963503
590.0311030.0622060.968897
600.02391660.04783330.976083
610.02610680.05221360.973893
620.02046080.04092160.979539
630.01554520.03109040.984455
640.01281120.02562240.987189
650.01324230.02648470.986758
660.01011740.02023490.989883
670.00821890.01643780.991781
680.01611120.03222240.983889
690.02408710.04817430.975913
700.02094780.04189550.979052
710.01704710.03409410.982953
720.01893440.03786880.981066
730.0186380.03727610.981362
740.01970820.03941640.980292
750.07010750.1402150.929893
760.08951860.1790370.910481
770.07471650.1494330.925283
780.07548150.1509630.924519
790.06646260.1329250.933537
800.1902650.3805310.809735
810.1760450.352090.823955
820.1647240.3294490.835276
830.1531090.3062180.846891
840.1315390.2630780.868461
850.1199360.2398710.880064
860.1444740.2889480.855526
870.1233130.2466270.876687
880.1073240.2146480.892676
890.09067990.181360.90932
900.0910340.1820680.908966
910.09969290.1993860.900307
920.1544210.3088430.845579
930.2052730.4105460.794727
940.1932520.3865050.806748
950.170280.3405610.82972
960.1478320.2956630.852168
970.1412720.2825450.858728
980.1250780.2501560.874922
990.1218090.2436190.878191
1000.1040620.2081240.895938
1010.08916460.1783290.910835
1020.07655930.1531190.923441
1030.09682920.1936580.903171
1040.1242420.2484840.875758
1050.1341510.2683030.865849
1060.1166550.233310.883345
1070.1072990.2145990.892701
1080.09323650.1864730.906763
1090.1274440.2548870.872556
1100.1109080.2218170.889092
1110.09483130.1896630.905169
1120.1917850.383570.808215
1130.1709520.3419040.829048
1140.1540240.3080480.845976
1150.1624520.3249050.837548
1160.2086960.4173910.791304
1170.2877320.5754630.712268
1180.2612160.5224330.738784
1190.2326630.4653270.767337
1200.2315280.4630570.768472
1210.326640.653280.67336
1220.3218820.6437650.678118
1230.3014150.602830.698585
1240.3296050.659210.670395
1250.2994090.5988180.700591
1260.3175350.635070.682465
1270.2881410.5762820.711859
1280.272440.544880.72756
1290.25160.5031990.7484
1300.2238130.4476250.776187
1310.198760.3975210.80124
1320.1773360.3546710.822664
1330.1641830.3283650.835817
1340.1536090.3072180.846391
1350.177570.355140.82243
1360.3687830.7375650.631217
1370.3379290.6758570.662071
1380.3313460.6626920.668654
1390.2995630.5991260.700437
1400.2876460.5752930.712354
1410.2656020.5312030.734398
1420.3017830.6035660.698217
1430.2802080.5604170.719792
1440.5470650.905870.452935
1450.600390.799220.39961
1460.7124850.5750290.287515
1470.6841560.6316870.315844
1480.6765050.6469890.323495
1490.6640850.671830.335915
1500.6716550.656690.328345
1510.6501520.6996970.349848
1520.6619060.6761880.338094
1530.7131860.5736270.286814
1540.7000030.5999930.299997
1550.6956750.608650.304325
1560.7372950.525410.262705
1570.7424770.5150470.257523
1580.7187130.5625740.281287
1590.7470940.5058120.252906
1600.7529810.4940380.247019
1610.7271320.5457360.272868
1620.7632570.4734860.236743
1630.8338740.3322510.166126
1640.8478070.3043850.152193
1650.8750660.2498680.124934
1660.8591210.2817570.140879
1670.8373540.3252930.162646
1680.8902520.2194960.109748
1690.8904520.2190960.109548
1700.920130.159740.0798698
1710.9149970.1700050.0850026
1720.9038530.1922950.0961473
1730.8942640.2114710.105736
1740.9264360.1471280.073564
1750.9701660.05966830.0298341
1760.9646670.0706660.035333
1770.959380.08123970.0406198
1780.9548190.09036110.0451805
1790.9473470.1053060.0526528
1800.9377430.1245150.0622574
1810.9259250.148150.0740748
1820.9268410.1463180.0731588
1830.9183570.1632850.0816427
1840.9355540.1288920.064446
1850.9264170.1471670.0735833
1860.9165290.1669420.0834709
1870.9049610.1900780.095039
1880.9396210.1207570.0603786
1890.9353130.1293740.0646869
1900.9393750.121250.060625
1910.9423560.1152880.0576442
1920.943170.113660.0568298
1930.9323510.1352990.0676493
1940.9277520.1444960.072248
1950.9146320.1707360.0853678
1960.9061870.1876260.0938131
1970.9162030.1675950.0837974
1980.9043330.1913340.0956672
1990.8843290.2313420.115671
2000.8634490.2731020.136551
2010.854370.291260.14563
2020.8290760.3418470.170924
2030.8304350.3391310.169565
2040.8083710.3832590.191629
2050.7772330.4455350.222767
2060.7479760.5040480.252024
2070.7185420.5629160.281458
2080.6951090.6097820.304891
2090.6677080.6645840.332292
2100.6426620.7146770.357338
2110.6029730.7940550.397027
2120.6914950.617010.308505
2130.7405120.5189760.259488
2140.7001280.5997440.299872
2150.6590320.6819370.340968
2160.7483860.5032280.251614
2170.7095330.5809340.290467
2180.6908950.6182090.309105
2190.6472310.7055370.352769
2200.6573780.6852440.342622
2210.6161190.7677630.383881
2220.5743170.8513660.425683
2230.5332380.9335250.466762
2240.4801370.9602730.519863
2250.5248890.9502220.475111
2260.5580310.8839380.441969
2270.533070.933860.46693
2280.5165720.9668560.483428
2290.4603670.9207350.539633
2300.4491810.8983620.550819
2310.4015520.8031040.598448
2320.6011240.7977520.398876
2330.7550310.4899370.244969
2340.7558080.4883850.244192
2350.7153050.569390.284695
2360.6679260.6641480.332074
2370.6814260.6371480.318574
2380.7359970.5280060.264003
2390.6739960.6520080.326004
2400.7022380.5955240.297762
2410.6586380.6827240.341362
2420.6316530.7366940.368347
2430.5748280.8503450.425172
2440.5155970.9688060.484403
2450.7357450.528510.264255
2460.8229230.3541530.177077
2470.8791110.2417780.120889
2480.8139660.3720690.186034
2490.7328070.5343860.267193
2500.8145290.3709420.185471
2510.8198380.3603240.180162
2520.7051360.5897290.294864
2530.7937940.4124110.206206

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.793247 & 0.413506 & 0.206753 \tabularnewline
12 & 0.833295 & 0.333409 & 0.166705 \tabularnewline
13 & 0.762986 & 0.474028 & 0.237014 \tabularnewline
14 & 0.752397 & 0.495207 & 0.247603 \tabularnewline
15 & 0.6837 & 0.632601 & 0.3163 \tabularnewline
16 & 0.627943 & 0.744114 & 0.372057 \tabularnewline
17 & 0.568742 & 0.862517 & 0.431258 \tabularnewline
18 & 0.542726 & 0.914547 & 0.457274 \tabularnewline
19 & 0.47257 & 0.945141 & 0.52743 \tabularnewline
20 & 0.415989 & 0.831978 & 0.584011 \tabularnewline
21 & 0.334394 & 0.668788 & 0.665606 \tabularnewline
22 & 0.343803 & 0.687605 & 0.656197 \tabularnewline
23 & 0.283564 & 0.567129 & 0.716436 \tabularnewline
24 & 0.286247 & 0.572495 & 0.713753 \tabularnewline
25 & 0.318654 & 0.637308 & 0.681346 \tabularnewline
26 & 0.43094 & 0.861879 & 0.56906 \tabularnewline
27 & 0.37757 & 0.755141 & 0.62243 \tabularnewline
28 & 0.342675 & 0.68535 & 0.657325 \tabularnewline
29 & 0.286389 & 0.572777 & 0.713611 \tabularnewline
30 & 0.234825 & 0.469651 & 0.765175 \tabularnewline
31 & 0.207305 & 0.414611 & 0.792695 \tabularnewline
32 & 0.166027 & 0.332054 & 0.833973 \tabularnewline
33 & 0.155862 & 0.311723 & 0.844138 \tabularnewline
34 & 0.169348 & 0.338697 & 0.830652 \tabularnewline
35 & 0.187353 & 0.374705 & 0.812647 \tabularnewline
36 & 0.158598 & 0.317197 & 0.841402 \tabularnewline
37 & 0.126801 & 0.253602 & 0.873199 \tabularnewline
38 & 0.101876 & 0.203752 & 0.898124 \tabularnewline
39 & 0.0790761 & 0.158152 & 0.920924 \tabularnewline
40 & 0.0601586 & 0.120317 & 0.939841 \tabularnewline
41 & 0.0480123 & 0.0960245 & 0.951988 \tabularnewline
42 & 0.0357231 & 0.0714461 & 0.964277 \tabularnewline
43 & 0.0393001 & 0.0786002 & 0.9607 \tabularnewline
44 & 0.0290566 & 0.0581132 & 0.970943 \tabularnewline
45 & 0.0472289 & 0.0944579 & 0.952771 \tabularnewline
46 & 0.0393754 & 0.0787508 & 0.960625 \tabularnewline
47 & 0.0622316 & 0.124463 & 0.937768 \tabularnewline
48 & 0.0519842 & 0.103968 & 0.948016 \tabularnewline
49 & 0.0765467 & 0.153093 & 0.923453 \tabularnewline
50 & 0.0688051 & 0.13761 & 0.931195 \tabularnewline
51 & 0.0815429 & 0.163086 & 0.918457 \tabularnewline
52 & 0.0751087 & 0.150217 & 0.924891 \tabularnewline
53 & 0.0593015 & 0.118603 & 0.940699 \tabularnewline
54 & 0.0662501 & 0.1325 & 0.93375 \tabularnewline
55 & 0.0558833 & 0.111767 & 0.944117 \tabularnewline
56 & 0.0558075 & 0.111615 & 0.944193 \tabularnewline
57 & 0.0453686 & 0.0907372 & 0.954631 \tabularnewline
58 & 0.0364971 & 0.0729942 & 0.963503 \tabularnewline
59 & 0.031103 & 0.062206 & 0.968897 \tabularnewline
60 & 0.0239166 & 0.0478333 & 0.976083 \tabularnewline
61 & 0.0261068 & 0.0522136 & 0.973893 \tabularnewline
62 & 0.0204608 & 0.0409216 & 0.979539 \tabularnewline
63 & 0.0155452 & 0.0310904 & 0.984455 \tabularnewline
64 & 0.0128112 & 0.0256224 & 0.987189 \tabularnewline
65 & 0.0132423 & 0.0264847 & 0.986758 \tabularnewline
66 & 0.0101174 & 0.0202349 & 0.989883 \tabularnewline
67 & 0.0082189 & 0.0164378 & 0.991781 \tabularnewline
68 & 0.0161112 & 0.0322224 & 0.983889 \tabularnewline
69 & 0.0240871 & 0.0481743 & 0.975913 \tabularnewline
70 & 0.0209478 & 0.0418955 & 0.979052 \tabularnewline
71 & 0.0170471 & 0.0340941 & 0.982953 \tabularnewline
72 & 0.0189344 & 0.0378688 & 0.981066 \tabularnewline
73 & 0.018638 & 0.0372761 & 0.981362 \tabularnewline
74 & 0.0197082 & 0.0394164 & 0.980292 \tabularnewline
75 & 0.0701075 & 0.140215 & 0.929893 \tabularnewline
76 & 0.0895186 & 0.179037 & 0.910481 \tabularnewline
77 & 0.0747165 & 0.149433 & 0.925283 \tabularnewline
78 & 0.0754815 & 0.150963 & 0.924519 \tabularnewline
79 & 0.0664626 & 0.132925 & 0.933537 \tabularnewline
80 & 0.190265 & 0.380531 & 0.809735 \tabularnewline
81 & 0.176045 & 0.35209 & 0.823955 \tabularnewline
82 & 0.164724 & 0.329449 & 0.835276 \tabularnewline
83 & 0.153109 & 0.306218 & 0.846891 \tabularnewline
84 & 0.131539 & 0.263078 & 0.868461 \tabularnewline
85 & 0.119936 & 0.239871 & 0.880064 \tabularnewline
86 & 0.144474 & 0.288948 & 0.855526 \tabularnewline
87 & 0.123313 & 0.246627 & 0.876687 \tabularnewline
88 & 0.107324 & 0.214648 & 0.892676 \tabularnewline
89 & 0.0906799 & 0.18136 & 0.90932 \tabularnewline
90 & 0.091034 & 0.182068 & 0.908966 \tabularnewline
91 & 0.0996929 & 0.199386 & 0.900307 \tabularnewline
92 & 0.154421 & 0.308843 & 0.845579 \tabularnewline
93 & 0.205273 & 0.410546 & 0.794727 \tabularnewline
94 & 0.193252 & 0.386505 & 0.806748 \tabularnewline
95 & 0.17028 & 0.340561 & 0.82972 \tabularnewline
96 & 0.147832 & 0.295663 & 0.852168 \tabularnewline
97 & 0.141272 & 0.282545 & 0.858728 \tabularnewline
98 & 0.125078 & 0.250156 & 0.874922 \tabularnewline
99 & 0.121809 & 0.243619 & 0.878191 \tabularnewline
100 & 0.104062 & 0.208124 & 0.895938 \tabularnewline
101 & 0.0891646 & 0.178329 & 0.910835 \tabularnewline
102 & 0.0765593 & 0.153119 & 0.923441 \tabularnewline
103 & 0.0968292 & 0.193658 & 0.903171 \tabularnewline
104 & 0.124242 & 0.248484 & 0.875758 \tabularnewline
105 & 0.134151 & 0.268303 & 0.865849 \tabularnewline
106 & 0.116655 & 0.23331 & 0.883345 \tabularnewline
107 & 0.107299 & 0.214599 & 0.892701 \tabularnewline
108 & 0.0932365 & 0.186473 & 0.906763 \tabularnewline
109 & 0.127444 & 0.254887 & 0.872556 \tabularnewline
110 & 0.110908 & 0.221817 & 0.889092 \tabularnewline
111 & 0.0948313 & 0.189663 & 0.905169 \tabularnewline
112 & 0.191785 & 0.38357 & 0.808215 \tabularnewline
113 & 0.170952 & 0.341904 & 0.829048 \tabularnewline
114 & 0.154024 & 0.308048 & 0.845976 \tabularnewline
115 & 0.162452 & 0.324905 & 0.837548 \tabularnewline
116 & 0.208696 & 0.417391 & 0.791304 \tabularnewline
117 & 0.287732 & 0.575463 & 0.712268 \tabularnewline
118 & 0.261216 & 0.522433 & 0.738784 \tabularnewline
119 & 0.232663 & 0.465327 & 0.767337 \tabularnewline
120 & 0.231528 & 0.463057 & 0.768472 \tabularnewline
121 & 0.32664 & 0.65328 & 0.67336 \tabularnewline
122 & 0.321882 & 0.643765 & 0.678118 \tabularnewline
123 & 0.301415 & 0.60283 & 0.698585 \tabularnewline
124 & 0.329605 & 0.65921 & 0.670395 \tabularnewline
125 & 0.299409 & 0.598818 & 0.700591 \tabularnewline
126 & 0.317535 & 0.63507 & 0.682465 \tabularnewline
127 & 0.288141 & 0.576282 & 0.711859 \tabularnewline
128 & 0.27244 & 0.54488 & 0.72756 \tabularnewline
129 & 0.2516 & 0.503199 & 0.7484 \tabularnewline
130 & 0.223813 & 0.447625 & 0.776187 \tabularnewline
131 & 0.19876 & 0.397521 & 0.80124 \tabularnewline
132 & 0.177336 & 0.354671 & 0.822664 \tabularnewline
133 & 0.164183 & 0.328365 & 0.835817 \tabularnewline
134 & 0.153609 & 0.307218 & 0.846391 \tabularnewline
135 & 0.17757 & 0.35514 & 0.82243 \tabularnewline
136 & 0.368783 & 0.737565 & 0.631217 \tabularnewline
137 & 0.337929 & 0.675857 & 0.662071 \tabularnewline
138 & 0.331346 & 0.662692 & 0.668654 \tabularnewline
139 & 0.299563 & 0.599126 & 0.700437 \tabularnewline
140 & 0.287646 & 0.575293 & 0.712354 \tabularnewline
141 & 0.265602 & 0.531203 & 0.734398 \tabularnewline
142 & 0.301783 & 0.603566 & 0.698217 \tabularnewline
143 & 0.280208 & 0.560417 & 0.719792 \tabularnewline
144 & 0.547065 & 0.90587 & 0.452935 \tabularnewline
145 & 0.60039 & 0.79922 & 0.39961 \tabularnewline
146 & 0.712485 & 0.575029 & 0.287515 \tabularnewline
147 & 0.684156 & 0.631687 & 0.315844 \tabularnewline
148 & 0.676505 & 0.646989 & 0.323495 \tabularnewline
149 & 0.664085 & 0.67183 & 0.335915 \tabularnewline
150 & 0.671655 & 0.65669 & 0.328345 \tabularnewline
151 & 0.650152 & 0.699697 & 0.349848 \tabularnewline
152 & 0.661906 & 0.676188 & 0.338094 \tabularnewline
153 & 0.713186 & 0.573627 & 0.286814 \tabularnewline
154 & 0.700003 & 0.599993 & 0.299997 \tabularnewline
155 & 0.695675 & 0.60865 & 0.304325 \tabularnewline
156 & 0.737295 & 0.52541 & 0.262705 \tabularnewline
157 & 0.742477 & 0.515047 & 0.257523 \tabularnewline
158 & 0.718713 & 0.562574 & 0.281287 \tabularnewline
159 & 0.747094 & 0.505812 & 0.252906 \tabularnewline
160 & 0.752981 & 0.494038 & 0.247019 \tabularnewline
161 & 0.727132 & 0.545736 & 0.272868 \tabularnewline
162 & 0.763257 & 0.473486 & 0.236743 \tabularnewline
163 & 0.833874 & 0.332251 & 0.166126 \tabularnewline
164 & 0.847807 & 0.304385 & 0.152193 \tabularnewline
165 & 0.875066 & 0.249868 & 0.124934 \tabularnewline
166 & 0.859121 & 0.281757 & 0.140879 \tabularnewline
167 & 0.837354 & 0.325293 & 0.162646 \tabularnewline
168 & 0.890252 & 0.219496 & 0.109748 \tabularnewline
169 & 0.890452 & 0.219096 & 0.109548 \tabularnewline
170 & 0.92013 & 0.15974 & 0.0798698 \tabularnewline
171 & 0.914997 & 0.170005 & 0.0850026 \tabularnewline
172 & 0.903853 & 0.192295 & 0.0961473 \tabularnewline
173 & 0.894264 & 0.211471 & 0.105736 \tabularnewline
174 & 0.926436 & 0.147128 & 0.073564 \tabularnewline
175 & 0.970166 & 0.0596683 & 0.0298341 \tabularnewline
176 & 0.964667 & 0.070666 & 0.035333 \tabularnewline
177 & 0.95938 & 0.0812397 & 0.0406198 \tabularnewline
178 & 0.954819 & 0.0903611 & 0.0451805 \tabularnewline
179 & 0.947347 & 0.105306 & 0.0526528 \tabularnewline
180 & 0.937743 & 0.124515 & 0.0622574 \tabularnewline
181 & 0.925925 & 0.14815 & 0.0740748 \tabularnewline
182 & 0.926841 & 0.146318 & 0.0731588 \tabularnewline
183 & 0.918357 & 0.163285 & 0.0816427 \tabularnewline
184 & 0.935554 & 0.128892 & 0.064446 \tabularnewline
185 & 0.926417 & 0.147167 & 0.0735833 \tabularnewline
186 & 0.916529 & 0.166942 & 0.0834709 \tabularnewline
187 & 0.904961 & 0.190078 & 0.095039 \tabularnewline
188 & 0.939621 & 0.120757 & 0.0603786 \tabularnewline
189 & 0.935313 & 0.129374 & 0.0646869 \tabularnewline
190 & 0.939375 & 0.12125 & 0.060625 \tabularnewline
191 & 0.942356 & 0.115288 & 0.0576442 \tabularnewline
192 & 0.94317 & 0.11366 & 0.0568298 \tabularnewline
193 & 0.932351 & 0.135299 & 0.0676493 \tabularnewline
194 & 0.927752 & 0.144496 & 0.072248 \tabularnewline
195 & 0.914632 & 0.170736 & 0.0853678 \tabularnewline
196 & 0.906187 & 0.187626 & 0.0938131 \tabularnewline
197 & 0.916203 & 0.167595 & 0.0837974 \tabularnewline
198 & 0.904333 & 0.191334 & 0.0956672 \tabularnewline
199 & 0.884329 & 0.231342 & 0.115671 \tabularnewline
200 & 0.863449 & 0.273102 & 0.136551 \tabularnewline
201 & 0.85437 & 0.29126 & 0.14563 \tabularnewline
202 & 0.829076 & 0.341847 & 0.170924 \tabularnewline
203 & 0.830435 & 0.339131 & 0.169565 \tabularnewline
204 & 0.808371 & 0.383259 & 0.191629 \tabularnewline
205 & 0.777233 & 0.445535 & 0.222767 \tabularnewline
206 & 0.747976 & 0.504048 & 0.252024 \tabularnewline
207 & 0.718542 & 0.562916 & 0.281458 \tabularnewline
208 & 0.695109 & 0.609782 & 0.304891 \tabularnewline
209 & 0.667708 & 0.664584 & 0.332292 \tabularnewline
210 & 0.642662 & 0.714677 & 0.357338 \tabularnewline
211 & 0.602973 & 0.794055 & 0.397027 \tabularnewline
212 & 0.691495 & 0.61701 & 0.308505 \tabularnewline
213 & 0.740512 & 0.518976 & 0.259488 \tabularnewline
214 & 0.700128 & 0.599744 & 0.299872 \tabularnewline
215 & 0.659032 & 0.681937 & 0.340968 \tabularnewline
216 & 0.748386 & 0.503228 & 0.251614 \tabularnewline
217 & 0.709533 & 0.580934 & 0.290467 \tabularnewline
218 & 0.690895 & 0.618209 & 0.309105 \tabularnewline
219 & 0.647231 & 0.705537 & 0.352769 \tabularnewline
220 & 0.657378 & 0.685244 & 0.342622 \tabularnewline
221 & 0.616119 & 0.767763 & 0.383881 \tabularnewline
222 & 0.574317 & 0.851366 & 0.425683 \tabularnewline
223 & 0.533238 & 0.933525 & 0.466762 \tabularnewline
224 & 0.480137 & 0.960273 & 0.519863 \tabularnewline
225 & 0.524889 & 0.950222 & 0.475111 \tabularnewline
226 & 0.558031 & 0.883938 & 0.441969 \tabularnewline
227 & 0.53307 & 0.93386 & 0.46693 \tabularnewline
228 & 0.516572 & 0.966856 & 0.483428 \tabularnewline
229 & 0.460367 & 0.920735 & 0.539633 \tabularnewline
230 & 0.449181 & 0.898362 & 0.550819 \tabularnewline
231 & 0.401552 & 0.803104 & 0.598448 \tabularnewline
232 & 0.601124 & 0.797752 & 0.398876 \tabularnewline
233 & 0.755031 & 0.489937 & 0.244969 \tabularnewline
234 & 0.755808 & 0.488385 & 0.244192 \tabularnewline
235 & 0.715305 & 0.56939 & 0.284695 \tabularnewline
236 & 0.667926 & 0.664148 & 0.332074 \tabularnewline
237 & 0.681426 & 0.637148 & 0.318574 \tabularnewline
238 & 0.735997 & 0.528006 & 0.264003 \tabularnewline
239 & 0.673996 & 0.652008 & 0.326004 \tabularnewline
240 & 0.702238 & 0.595524 & 0.297762 \tabularnewline
241 & 0.658638 & 0.682724 & 0.341362 \tabularnewline
242 & 0.631653 & 0.736694 & 0.368347 \tabularnewline
243 & 0.574828 & 0.850345 & 0.425172 \tabularnewline
244 & 0.515597 & 0.968806 & 0.484403 \tabularnewline
245 & 0.735745 & 0.52851 & 0.264255 \tabularnewline
246 & 0.822923 & 0.354153 & 0.177077 \tabularnewline
247 & 0.879111 & 0.241778 & 0.120889 \tabularnewline
248 & 0.813966 & 0.372069 & 0.186034 \tabularnewline
249 & 0.732807 & 0.534386 & 0.267193 \tabularnewline
250 & 0.814529 & 0.370942 & 0.185471 \tabularnewline
251 & 0.819838 & 0.360324 & 0.180162 \tabularnewline
252 & 0.705136 & 0.589729 & 0.294864 \tabularnewline
253 & 0.793794 & 0.412411 & 0.206206 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226347&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]11[/C][C]0.793247[/C][C]0.413506[/C][C]0.206753[/C][/ROW]
[ROW][C]12[/C][C]0.833295[/C][C]0.333409[/C][C]0.166705[/C][/ROW]
[ROW][C]13[/C][C]0.762986[/C][C]0.474028[/C][C]0.237014[/C][/ROW]
[ROW][C]14[/C][C]0.752397[/C][C]0.495207[/C][C]0.247603[/C][/ROW]
[ROW][C]15[/C][C]0.6837[/C][C]0.632601[/C][C]0.3163[/C][/ROW]
[ROW][C]16[/C][C]0.627943[/C][C]0.744114[/C][C]0.372057[/C][/ROW]
[ROW][C]17[/C][C]0.568742[/C][C]0.862517[/C][C]0.431258[/C][/ROW]
[ROW][C]18[/C][C]0.542726[/C][C]0.914547[/C][C]0.457274[/C][/ROW]
[ROW][C]19[/C][C]0.47257[/C][C]0.945141[/C][C]0.52743[/C][/ROW]
[ROW][C]20[/C][C]0.415989[/C][C]0.831978[/C][C]0.584011[/C][/ROW]
[ROW][C]21[/C][C]0.334394[/C][C]0.668788[/C][C]0.665606[/C][/ROW]
[ROW][C]22[/C][C]0.343803[/C][C]0.687605[/C][C]0.656197[/C][/ROW]
[ROW][C]23[/C][C]0.283564[/C][C]0.567129[/C][C]0.716436[/C][/ROW]
[ROW][C]24[/C][C]0.286247[/C][C]0.572495[/C][C]0.713753[/C][/ROW]
[ROW][C]25[/C][C]0.318654[/C][C]0.637308[/C][C]0.681346[/C][/ROW]
[ROW][C]26[/C][C]0.43094[/C][C]0.861879[/C][C]0.56906[/C][/ROW]
[ROW][C]27[/C][C]0.37757[/C][C]0.755141[/C][C]0.62243[/C][/ROW]
[ROW][C]28[/C][C]0.342675[/C][C]0.68535[/C][C]0.657325[/C][/ROW]
[ROW][C]29[/C][C]0.286389[/C][C]0.572777[/C][C]0.713611[/C][/ROW]
[ROW][C]30[/C][C]0.234825[/C][C]0.469651[/C][C]0.765175[/C][/ROW]
[ROW][C]31[/C][C]0.207305[/C][C]0.414611[/C][C]0.792695[/C][/ROW]
[ROW][C]32[/C][C]0.166027[/C][C]0.332054[/C][C]0.833973[/C][/ROW]
[ROW][C]33[/C][C]0.155862[/C][C]0.311723[/C][C]0.844138[/C][/ROW]
[ROW][C]34[/C][C]0.169348[/C][C]0.338697[/C][C]0.830652[/C][/ROW]
[ROW][C]35[/C][C]0.187353[/C][C]0.374705[/C][C]0.812647[/C][/ROW]
[ROW][C]36[/C][C]0.158598[/C][C]0.317197[/C][C]0.841402[/C][/ROW]
[ROW][C]37[/C][C]0.126801[/C][C]0.253602[/C][C]0.873199[/C][/ROW]
[ROW][C]38[/C][C]0.101876[/C][C]0.203752[/C][C]0.898124[/C][/ROW]
[ROW][C]39[/C][C]0.0790761[/C][C]0.158152[/C][C]0.920924[/C][/ROW]
[ROW][C]40[/C][C]0.0601586[/C][C]0.120317[/C][C]0.939841[/C][/ROW]
[ROW][C]41[/C][C]0.0480123[/C][C]0.0960245[/C][C]0.951988[/C][/ROW]
[ROW][C]42[/C][C]0.0357231[/C][C]0.0714461[/C][C]0.964277[/C][/ROW]
[ROW][C]43[/C][C]0.0393001[/C][C]0.0786002[/C][C]0.9607[/C][/ROW]
[ROW][C]44[/C][C]0.0290566[/C][C]0.0581132[/C][C]0.970943[/C][/ROW]
[ROW][C]45[/C][C]0.0472289[/C][C]0.0944579[/C][C]0.952771[/C][/ROW]
[ROW][C]46[/C][C]0.0393754[/C][C]0.0787508[/C][C]0.960625[/C][/ROW]
[ROW][C]47[/C][C]0.0622316[/C][C]0.124463[/C][C]0.937768[/C][/ROW]
[ROW][C]48[/C][C]0.0519842[/C][C]0.103968[/C][C]0.948016[/C][/ROW]
[ROW][C]49[/C][C]0.0765467[/C][C]0.153093[/C][C]0.923453[/C][/ROW]
[ROW][C]50[/C][C]0.0688051[/C][C]0.13761[/C][C]0.931195[/C][/ROW]
[ROW][C]51[/C][C]0.0815429[/C][C]0.163086[/C][C]0.918457[/C][/ROW]
[ROW][C]52[/C][C]0.0751087[/C][C]0.150217[/C][C]0.924891[/C][/ROW]
[ROW][C]53[/C][C]0.0593015[/C][C]0.118603[/C][C]0.940699[/C][/ROW]
[ROW][C]54[/C][C]0.0662501[/C][C]0.1325[/C][C]0.93375[/C][/ROW]
[ROW][C]55[/C][C]0.0558833[/C][C]0.111767[/C][C]0.944117[/C][/ROW]
[ROW][C]56[/C][C]0.0558075[/C][C]0.111615[/C][C]0.944193[/C][/ROW]
[ROW][C]57[/C][C]0.0453686[/C][C]0.0907372[/C][C]0.954631[/C][/ROW]
[ROW][C]58[/C][C]0.0364971[/C][C]0.0729942[/C][C]0.963503[/C][/ROW]
[ROW][C]59[/C][C]0.031103[/C][C]0.062206[/C][C]0.968897[/C][/ROW]
[ROW][C]60[/C][C]0.0239166[/C][C]0.0478333[/C][C]0.976083[/C][/ROW]
[ROW][C]61[/C][C]0.0261068[/C][C]0.0522136[/C][C]0.973893[/C][/ROW]
[ROW][C]62[/C][C]0.0204608[/C][C]0.0409216[/C][C]0.979539[/C][/ROW]
[ROW][C]63[/C][C]0.0155452[/C][C]0.0310904[/C][C]0.984455[/C][/ROW]
[ROW][C]64[/C][C]0.0128112[/C][C]0.0256224[/C][C]0.987189[/C][/ROW]
[ROW][C]65[/C][C]0.0132423[/C][C]0.0264847[/C][C]0.986758[/C][/ROW]
[ROW][C]66[/C][C]0.0101174[/C][C]0.0202349[/C][C]0.989883[/C][/ROW]
[ROW][C]67[/C][C]0.0082189[/C][C]0.0164378[/C][C]0.991781[/C][/ROW]
[ROW][C]68[/C][C]0.0161112[/C][C]0.0322224[/C][C]0.983889[/C][/ROW]
[ROW][C]69[/C][C]0.0240871[/C][C]0.0481743[/C][C]0.975913[/C][/ROW]
[ROW][C]70[/C][C]0.0209478[/C][C]0.0418955[/C][C]0.979052[/C][/ROW]
[ROW][C]71[/C][C]0.0170471[/C][C]0.0340941[/C][C]0.982953[/C][/ROW]
[ROW][C]72[/C][C]0.0189344[/C][C]0.0378688[/C][C]0.981066[/C][/ROW]
[ROW][C]73[/C][C]0.018638[/C][C]0.0372761[/C][C]0.981362[/C][/ROW]
[ROW][C]74[/C][C]0.0197082[/C][C]0.0394164[/C][C]0.980292[/C][/ROW]
[ROW][C]75[/C][C]0.0701075[/C][C]0.140215[/C][C]0.929893[/C][/ROW]
[ROW][C]76[/C][C]0.0895186[/C][C]0.179037[/C][C]0.910481[/C][/ROW]
[ROW][C]77[/C][C]0.0747165[/C][C]0.149433[/C][C]0.925283[/C][/ROW]
[ROW][C]78[/C][C]0.0754815[/C][C]0.150963[/C][C]0.924519[/C][/ROW]
[ROW][C]79[/C][C]0.0664626[/C][C]0.132925[/C][C]0.933537[/C][/ROW]
[ROW][C]80[/C][C]0.190265[/C][C]0.380531[/C][C]0.809735[/C][/ROW]
[ROW][C]81[/C][C]0.176045[/C][C]0.35209[/C][C]0.823955[/C][/ROW]
[ROW][C]82[/C][C]0.164724[/C][C]0.329449[/C][C]0.835276[/C][/ROW]
[ROW][C]83[/C][C]0.153109[/C][C]0.306218[/C][C]0.846891[/C][/ROW]
[ROW][C]84[/C][C]0.131539[/C][C]0.263078[/C][C]0.868461[/C][/ROW]
[ROW][C]85[/C][C]0.119936[/C][C]0.239871[/C][C]0.880064[/C][/ROW]
[ROW][C]86[/C][C]0.144474[/C][C]0.288948[/C][C]0.855526[/C][/ROW]
[ROW][C]87[/C][C]0.123313[/C][C]0.246627[/C][C]0.876687[/C][/ROW]
[ROW][C]88[/C][C]0.107324[/C][C]0.214648[/C][C]0.892676[/C][/ROW]
[ROW][C]89[/C][C]0.0906799[/C][C]0.18136[/C][C]0.90932[/C][/ROW]
[ROW][C]90[/C][C]0.091034[/C][C]0.182068[/C][C]0.908966[/C][/ROW]
[ROW][C]91[/C][C]0.0996929[/C][C]0.199386[/C][C]0.900307[/C][/ROW]
[ROW][C]92[/C][C]0.154421[/C][C]0.308843[/C][C]0.845579[/C][/ROW]
[ROW][C]93[/C][C]0.205273[/C][C]0.410546[/C][C]0.794727[/C][/ROW]
[ROW][C]94[/C][C]0.193252[/C][C]0.386505[/C][C]0.806748[/C][/ROW]
[ROW][C]95[/C][C]0.17028[/C][C]0.340561[/C][C]0.82972[/C][/ROW]
[ROW][C]96[/C][C]0.147832[/C][C]0.295663[/C][C]0.852168[/C][/ROW]
[ROW][C]97[/C][C]0.141272[/C][C]0.282545[/C][C]0.858728[/C][/ROW]
[ROW][C]98[/C][C]0.125078[/C][C]0.250156[/C][C]0.874922[/C][/ROW]
[ROW][C]99[/C][C]0.121809[/C][C]0.243619[/C][C]0.878191[/C][/ROW]
[ROW][C]100[/C][C]0.104062[/C][C]0.208124[/C][C]0.895938[/C][/ROW]
[ROW][C]101[/C][C]0.0891646[/C][C]0.178329[/C][C]0.910835[/C][/ROW]
[ROW][C]102[/C][C]0.0765593[/C][C]0.153119[/C][C]0.923441[/C][/ROW]
[ROW][C]103[/C][C]0.0968292[/C][C]0.193658[/C][C]0.903171[/C][/ROW]
[ROW][C]104[/C][C]0.124242[/C][C]0.248484[/C][C]0.875758[/C][/ROW]
[ROW][C]105[/C][C]0.134151[/C][C]0.268303[/C][C]0.865849[/C][/ROW]
[ROW][C]106[/C][C]0.116655[/C][C]0.23331[/C][C]0.883345[/C][/ROW]
[ROW][C]107[/C][C]0.107299[/C][C]0.214599[/C][C]0.892701[/C][/ROW]
[ROW][C]108[/C][C]0.0932365[/C][C]0.186473[/C][C]0.906763[/C][/ROW]
[ROW][C]109[/C][C]0.127444[/C][C]0.254887[/C][C]0.872556[/C][/ROW]
[ROW][C]110[/C][C]0.110908[/C][C]0.221817[/C][C]0.889092[/C][/ROW]
[ROW][C]111[/C][C]0.0948313[/C][C]0.189663[/C][C]0.905169[/C][/ROW]
[ROW][C]112[/C][C]0.191785[/C][C]0.38357[/C][C]0.808215[/C][/ROW]
[ROW][C]113[/C][C]0.170952[/C][C]0.341904[/C][C]0.829048[/C][/ROW]
[ROW][C]114[/C][C]0.154024[/C][C]0.308048[/C][C]0.845976[/C][/ROW]
[ROW][C]115[/C][C]0.162452[/C][C]0.324905[/C][C]0.837548[/C][/ROW]
[ROW][C]116[/C][C]0.208696[/C][C]0.417391[/C][C]0.791304[/C][/ROW]
[ROW][C]117[/C][C]0.287732[/C][C]0.575463[/C][C]0.712268[/C][/ROW]
[ROW][C]118[/C][C]0.261216[/C][C]0.522433[/C][C]0.738784[/C][/ROW]
[ROW][C]119[/C][C]0.232663[/C][C]0.465327[/C][C]0.767337[/C][/ROW]
[ROW][C]120[/C][C]0.231528[/C][C]0.463057[/C][C]0.768472[/C][/ROW]
[ROW][C]121[/C][C]0.32664[/C][C]0.65328[/C][C]0.67336[/C][/ROW]
[ROW][C]122[/C][C]0.321882[/C][C]0.643765[/C][C]0.678118[/C][/ROW]
[ROW][C]123[/C][C]0.301415[/C][C]0.60283[/C][C]0.698585[/C][/ROW]
[ROW][C]124[/C][C]0.329605[/C][C]0.65921[/C][C]0.670395[/C][/ROW]
[ROW][C]125[/C][C]0.299409[/C][C]0.598818[/C][C]0.700591[/C][/ROW]
[ROW][C]126[/C][C]0.317535[/C][C]0.63507[/C][C]0.682465[/C][/ROW]
[ROW][C]127[/C][C]0.288141[/C][C]0.576282[/C][C]0.711859[/C][/ROW]
[ROW][C]128[/C][C]0.27244[/C][C]0.54488[/C][C]0.72756[/C][/ROW]
[ROW][C]129[/C][C]0.2516[/C][C]0.503199[/C][C]0.7484[/C][/ROW]
[ROW][C]130[/C][C]0.223813[/C][C]0.447625[/C][C]0.776187[/C][/ROW]
[ROW][C]131[/C][C]0.19876[/C][C]0.397521[/C][C]0.80124[/C][/ROW]
[ROW][C]132[/C][C]0.177336[/C][C]0.354671[/C][C]0.822664[/C][/ROW]
[ROW][C]133[/C][C]0.164183[/C][C]0.328365[/C][C]0.835817[/C][/ROW]
[ROW][C]134[/C][C]0.153609[/C][C]0.307218[/C][C]0.846391[/C][/ROW]
[ROW][C]135[/C][C]0.17757[/C][C]0.35514[/C][C]0.82243[/C][/ROW]
[ROW][C]136[/C][C]0.368783[/C][C]0.737565[/C][C]0.631217[/C][/ROW]
[ROW][C]137[/C][C]0.337929[/C][C]0.675857[/C][C]0.662071[/C][/ROW]
[ROW][C]138[/C][C]0.331346[/C][C]0.662692[/C][C]0.668654[/C][/ROW]
[ROW][C]139[/C][C]0.299563[/C][C]0.599126[/C][C]0.700437[/C][/ROW]
[ROW][C]140[/C][C]0.287646[/C][C]0.575293[/C][C]0.712354[/C][/ROW]
[ROW][C]141[/C][C]0.265602[/C][C]0.531203[/C][C]0.734398[/C][/ROW]
[ROW][C]142[/C][C]0.301783[/C][C]0.603566[/C][C]0.698217[/C][/ROW]
[ROW][C]143[/C][C]0.280208[/C][C]0.560417[/C][C]0.719792[/C][/ROW]
[ROW][C]144[/C][C]0.547065[/C][C]0.90587[/C][C]0.452935[/C][/ROW]
[ROW][C]145[/C][C]0.60039[/C][C]0.79922[/C][C]0.39961[/C][/ROW]
[ROW][C]146[/C][C]0.712485[/C][C]0.575029[/C][C]0.287515[/C][/ROW]
[ROW][C]147[/C][C]0.684156[/C][C]0.631687[/C][C]0.315844[/C][/ROW]
[ROW][C]148[/C][C]0.676505[/C][C]0.646989[/C][C]0.323495[/C][/ROW]
[ROW][C]149[/C][C]0.664085[/C][C]0.67183[/C][C]0.335915[/C][/ROW]
[ROW][C]150[/C][C]0.671655[/C][C]0.65669[/C][C]0.328345[/C][/ROW]
[ROW][C]151[/C][C]0.650152[/C][C]0.699697[/C][C]0.349848[/C][/ROW]
[ROW][C]152[/C][C]0.661906[/C][C]0.676188[/C][C]0.338094[/C][/ROW]
[ROW][C]153[/C][C]0.713186[/C][C]0.573627[/C][C]0.286814[/C][/ROW]
[ROW][C]154[/C][C]0.700003[/C][C]0.599993[/C][C]0.299997[/C][/ROW]
[ROW][C]155[/C][C]0.695675[/C][C]0.60865[/C][C]0.304325[/C][/ROW]
[ROW][C]156[/C][C]0.737295[/C][C]0.52541[/C][C]0.262705[/C][/ROW]
[ROW][C]157[/C][C]0.742477[/C][C]0.515047[/C][C]0.257523[/C][/ROW]
[ROW][C]158[/C][C]0.718713[/C][C]0.562574[/C][C]0.281287[/C][/ROW]
[ROW][C]159[/C][C]0.747094[/C][C]0.505812[/C][C]0.252906[/C][/ROW]
[ROW][C]160[/C][C]0.752981[/C][C]0.494038[/C][C]0.247019[/C][/ROW]
[ROW][C]161[/C][C]0.727132[/C][C]0.545736[/C][C]0.272868[/C][/ROW]
[ROW][C]162[/C][C]0.763257[/C][C]0.473486[/C][C]0.236743[/C][/ROW]
[ROW][C]163[/C][C]0.833874[/C][C]0.332251[/C][C]0.166126[/C][/ROW]
[ROW][C]164[/C][C]0.847807[/C][C]0.304385[/C][C]0.152193[/C][/ROW]
[ROW][C]165[/C][C]0.875066[/C][C]0.249868[/C][C]0.124934[/C][/ROW]
[ROW][C]166[/C][C]0.859121[/C][C]0.281757[/C][C]0.140879[/C][/ROW]
[ROW][C]167[/C][C]0.837354[/C][C]0.325293[/C][C]0.162646[/C][/ROW]
[ROW][C]168[/C][C]0.890252[/C][C]0.219496[/C][C]0.109748[/C][/ROW]
[ROW][C]169[/C][C]0.890452[/C][C]0.219096[/C][C]0.109548[/C][/ROW]
[ROW][C]170[/C][C]0.92013[/C][C]0.15974[/C][C]0.0798698[/C][/ROW]
[ROW][C]171[/C][C]0.914997[/C][C]0.170005[/C][C]0.0850026[/C][/ROW]
[ROW][C]172[/C][C]0.903853[/C][C]0.192295[/C][C]0.0961473[/C][/ROW]
[ROW][C]173[/C][C]0.894264[/C][C]0.211471[/C][C]0.105736[/C][/ROW]
[ROW][C]174[/C][C]0.926436[/C][C]0.147128[/C][C]0.073564[/C][/ROW]
[ROW][C]175[/C][C]0.970166[/C][C]0.0596683[/C][C]0.0298341[/C][/ROW]
[ROW][C]176[/C][C]0.964667[/C][C]0.070666[/C][C]0.035333[/C][/ROW]
[ROW][C]177[/C][C]0.95938[/C][C]0.0812397[/C][C]0.0406198[/C][/ROW]
[ROW][C]178[/C][C]0.954819[/C][C]0.0903611[/C][C]0.0451805[/C][/ROW]
[ROW][C]179[/C][C]0.947347[/C][C]0.105306[/C][C]0.0526528[/C][/ROW]
[ROW][C]180[/C][C]0.937743[/C][C]0.124515[/C][C]0.0622574[/C][/ROW]
[ROW][C]181[/C][C]0.925925[/C][C]0.14815[/C][C]0.0740748[/C][/ROW]
[ROW][C]182[/C][C]0.926841[/C][C]0.146318[/C][C]0.0731588[/C][/ROW]
[ROW][C]183[/C][C]0.918357[/C][C]0.163285[/C][C]0.0816427[/C][/ROW]
[ROW][C]184[/C][C]0.935554[/C][C]0.128892[/C][C]0.064446[/C][/ROW]
[ROW][C]185[/C][C]0.926417[/C][C]0.147167[/C][C]0.0735833[/C][/ROW]
[ROW][C]186[/C][C]0.916529[/C][C]0.166942[/C][C]0.0834709[/C][/ROW]
[ROW][C]187[/C][C]0.904961[/C][C]0.190078[/C][C]0.095039[/C][/ROW]
[ROW][C]188[/C][C]0.939621[/C][C]0.120757[/C][C]0.0603786[/C][/ROW]
[ROW][C]189[/C][C]0.935313[/C][C]0.129374[/C][C]0.0646869[/C][/ROW]
[ROW][C]190[/C][C]0.939375[/C][C]0.12125[/C][C]0.060625[/C][/ROW]
[ROW][C]191[/C][C]0.942356[/C][C]0.115288[/C][C]0.0576442[/C][/ROW]
[ROW][C]192[/C][C]0.94317[/C][C]0.11366[/C][C]0.0568298[/C][/ROW]
[ROW][C]193[/C][C]0.932351[/C][C]0.135299[/C][C]0.0676493[/C][/ROW]
[ROW][C]194[/C][C]0.927752[/C][C]0.144496[/C][C]0.072248[/C][/ROW]
[ROW][C]195[/C][C]0.914632[/C][C]0.170736[/C][C]0.0853678[/C][/ROW]
[ROW][C]196[/C][C]0.906187[/C][C]0.187626[/C][C]0.0938131[/C][/ROW]
[ROW][C]197[/C][C]0.916203[/C][C]0.167595[/C][C]0.0837974[/C][/ROW]
[ROW][C]198[/C][C]0.904333[/C][C]0.191334[/C][C]0.0956672[/C][/ROW]
[ROW][C]199[/C][C]0.884329[/C][C]0.231342[/C][C]0.115671[/C][/ROW]
[ROW][C]200[/C][C]0.863449[/C][C]0.273102[/C][C]0.136551[/C][/ROW]
[ROW][C]201[/C][C]0.85437[/C][C]0.29126[/C][C]0.14563[/C][/ROW]
[ROW][C]202[/C][C]0.829076[/C][C]0.341847[/C][C]0.170924[/C][/ROW]
[ROW][C]203[/C][C]0.830435[/C][C]0.339131[/C][C]0.169565[/C][/ROW]
[ROW][C]204[/C][C]0.808371[/C][C]0.383259[/C][C]0.191629[/C][/ROW]
[ROW][C]205[/C][C]0.777233[/C][C]0.445535[/C][C]0.222767[/C][/ROW]
[ROW][C]206[/C][C]0.747976[/C][C]0.504048[/C][C]0.252024[/C][/ROW]
[ROW][C]207[/C][C]0.718542[/C][C]0.562916[/C][C]0.281458[/C][/ROW]
[ROW][C]208[/C][C]0.695109[/C][C]0.609782[/C][C]0.304891[/C][/ROW]
[ROW][C]209[/C][C]0.667708[/C][C]0.664584[/C][C]0.332292[/C][/ROW]
[ROW][C]210[/C][C]0.642662[/C][C]0.714677[/C][C]0.357338[/C][/ROW]
[ROW][C]211[/C][C]0.602973[/C][C]0.794055[/C][C]0.397027[/C][/ROW]
[ROW][C]212[/C][C]0.691495[/C][C]0.61701[/C][C]0.308505[/C][/ROW]
[ROW][C]213[/C][C]0.740512[/C][C]0.518976[/C][C]0.259488[/C][/ROW]
[ROW][C]214[/C][C]0.700128[/C][C]0.599744[/C][C]0.299872[/C][/ROW]
[ROW][C]215[/C][C]0.659032[/C][C]0.681937[/C][C]0.340968[/C][/ROW]
[ROW][C]216[/C][C]0.748386[/C][C]0.503228[/C][C]0.251614[/C][/ROW]
[ROW][C]217[/C][C]0.709533[/C][C]0.580934[/C][C]0.290467[/C][/ROW]
[ROW][C]218[/C][C]0.690895[/C][C]0.618209[/C][C]0.309105[/C][/ROW]
[ROW][C]219[/C][C]0.647231[/C][C]0.705537[/C][C]0.352769[/C][/ROW]
[ROW][C]220[/C][C]0.657378[/C][C]0.685244[/C][C]0.342622[/C][/ROW]
[ROW][C]221[/C][C]0.616119[/C][C]0.767763[/C][C]0.383881[/C][/ROW]
[ROW][C]222[/C][C]0.574317[/C][C]0.851366[/C][C]0.425683[/C][/ROW]
[ROW][C]223[/C][C]0.533238[/C][C]0.933525[/C][C]0.466762[/C][/ROW]
[ROW][C]224[/C][C]0.480137[/C][C]0.960273[/C][C]0.519863[/C][/ROW]
[ROW][C]225[/C][C]0.524889[/C][C]0.950222[/C][C]0.475111[/C][/ROW]
[ROW][C]226[/C][C]0.558031[/C][C]0.883938[/C][C]0.441969[/C][/ROW]
[ROW][C]227[/C][C]0.53307[/C][C]0.93386[/C][C]0.46693[/C][/ROW]
[ROW][C]228[/C][C]0.516572[/C][C]0.966856[/C][C]0.483428[/C][/ROW]
[ROW][C]229[/C][C]0.460367[/C][C]0.920735[/C][C]0.539633[/C][/ROW]
[ROW][C]230[/C][C]0.449181[/C][C]0.898362[/C][C]0.550819[/C][/ROW]
[ROW][C]231[/C][C]0.401552[/C][C]0.803104[/C][C]0.598448[/C][/ROW]
[ROW][C]232[/C][C]0.601124[/C][C]0.797752[/C][C]0.398876[/C][/ROW]
[ROW][C]233[/C][C]0.755031[/C][C]0.489937[/C][C]0.244969[/C][/ROW]
[ROW][C]234[/C][C]0.755808[/C][C]0.488385[/C][C]0.244192[/C][/ROW]
[ROW][C]235[/C][C]0.715305[/C][C]0.56939[/C][C]0.284695[/C][/ROW]
[ROW][C]236[/C][C]0.667926[/C][C]0.664148[/C][C]0.332074[/C][/ROW]
[ROW][C]237[/C][C]0.681426[/C][C]0.637148[/C][C]0.318574[/C][/ROW]
[ROW][C]238[/C][C]0.735997[/C][C]0.528006[/C][C]0.264003[/C][/ROW]
[ROW][C]239[/C][C]0.673996[/C][C]0.652008[/C][C]0.326004[/C][/ROW]
[ROW][C]240[/C][C]0.702238[/C][C]0.595524[/C][C]0.297762[/C][/ROW]
[ROW][C]241[/C][C]0.658638[/C][C]0.682724[/C][C]0.341362[/C][/ROW]
[ROW][C]242[/C][C]0.631653[/C][C]0.736694[/C][C]0.368347[/C][/ROW]
[ROW][C]243[/C][C]0.574828[/C][C]0.850345[/C][C]0.425172[/C][/ROW]
[ROW][C]244[/C][C]0.515597[/C][C]0.968806[/C][C]0.484403[/C][/ROW]
[ROW][C]245[/C][C]0.735745[/C][C]0.52851[/C][C]0.264255[/C][/ROW]
[ROW][C]246[/C][C]0.822923[/C][C]0.354153[/C][C]0.177077[/C][/ROW]
[ROW][C]247[/C][C]0.879111[/C][C]0.241778[/C][C]0.120889[/C][/ROW]
[ROW][C]248[/C][C]0.813966[/C][C]0.372069[/C][C]0.186034[/C][/ROW]
[ROW][C]249[/C][C]0.732807[/C][C]0.534386[/C][C]0.267193[/C][/ROW]
[ROW][C]250[/C][C]0.814529[/C][C]0.370942[/C][C]0.185471[/C][/ROW]
[ROW][C]251[/C][C]0.819838[/C][C]0.360324[/C][C]0.180162[/C][/ROW]
[ROW][C]252[/C][C]0.705136[/C][C]0.589729[/C][C]0.294864[/C][/ROW]
[ROW][C]253[/C][C]0.793794[/C][C]0.412411[/C][C]0.206206[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226347&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226347&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.7932470.4135060.206753
120.8332950.3334090.166705
130.7629860.4740280.237014
140.7523970.4952070.247603
150.68370.6326010.3163
160.6279430.7441140.372057
170.5687420.8625170.431258
180.5427260.9145470.457274
190.472570.9451410.52743
200.4159890.8319780.584011
210.3343940.6687880.665606
220.3438030.6876050.656197
230.2835640.5671290.716436
240.2862470.5724950.713753
250.3186540.6373080.681346
260.430940.8618790.56906
270.377570.7551410.62243
280.3426750.685350.657325
290.2863890.5727770.713611
300.2348250.4696510.765175
310.2073050.4146110.792695
320.1660270.3320540.833973
330.1558620.3117230.844138
340.1693480.3386970.830652
350.1873530.3747050.812647
360.1585980.3171970.841402
370.1268010.2536020.873199
380.1018760.2037520.898124
390.07907610.1581520.920924
400.06015860.1203170.939841
410.04801230.09602450.951988
420.03572310.07144610.964277
430.03930010.07860020.9607
440.02905660.05811320.970943
450.04722890.09445790.952771
460.03937540.07875080.960625
470.06223160.1244630.937768
480.05198420.1039680.948016
490.07654670.1530930.923453
500.06880510.137610.931195
510.08154290.1630860.918457
520.07510870.1502170.924891
530.05930150.1186030.940699
540.06625010.13250.93375
550.05588330.1117670.944117
560.05580750.1116150.944193
570.04536860.09073720.954631
580.03649710.07299420.963503
590.0311030.0622060.968897
600.02391660.04783330.976083
610.02610680.05221360.973893
620.02046080.04092160.979539
630.01554520.03109040.984455
640.01281120.02562240.987189
650.01324230.02648470.986758
660.01011740.02023490.989883
670.00821890.01643780.991781
680.01611120.03222240.983889
690.02408710.04817430.975913
700.02094780.04189550.979052
710.01704710.03409410.982953
720.01893440.03786880.981066
730.0186380.03727610.981362
740.01970820.03941640.980292
750.07010750.1402150.929893
760.08951860.1790370.910481
770.07471650.1494330.925283
780.07548150.1509630.924519
790.06646260.1329250.933537
800.1902650.3805310.809735
810.1760450.352090.823955
820.1647240.3294490.835276
830.1531090.3062180.846891
840.1315390.2630780.868461
850.1199360.2398710.880064
860.1444740.2889480.855526
870.1233130.2466270.876687
880.1073240.2146480.892676
890.09067990.181360.90932
900.0910340.1820680.908966
910.09969290.1993860.900307
920.1544210.3088430.845579
930.2052730.4105460.794727
940.1932520.3865050.806748
950.170280.3405610.82972
960.1478320.2956630.852168
970.1412720.2825450.858728
980.1250780.2501560.874922
990.1218090.2436190.878191
1000.1040620.2081240.895938
1010.08916460.1783290.910835
1020.07655930.1531190.923441
1030.09682920.1936580.903171
1040.1242420.2484840.875758
1050.1341510.2683030.865849
1060.1166550.233310.883345
1070.1072990.2145990.892701
1080.09323650.1864730.906763
1090.1274440.2548870.872556
1100.1109080.2218170.889092
1110.09483130.1896630.905169
1120.1917850.383570.808215
1130.1709520.3419040.829048
1140.1540240.3080480.845976
1150.1624520.3249050.837548
1160.2086960.4173910.791304
1170.2877320.5754630.712268
1180.2612160.5224330.738784
1190.2326630.4653270.767337
1200.2315280.4630570.768472
1210.326640.653280.67336
1220.3218820.6437650.678118
1230.3014150.602830.698585
1240.3296050.659210.670395
1250.2994090.5988180.700591
1260.3175350.635070.682465
1270.2881410.5762820.711859
1280.272440.544880.72756
1290.25160.5031990.7484
1300.2238130.4476250.776187
1310.198760.3975210.80124
1320.1773360.3546710.822664
1330.1641830.3283650.835817
1340.1536090.3072180.846391
1350.177570.355140.82243
1360.3687830.7375650.631217
1370.3379290.6758570.662071
1380.3313460.6626920.668654
1390.2995630.5991260.700437
1400.2876460.5752930.712354
1410.2656020.5312030.734398
1420.3017830.6035660.698217
1430.2802080.5604170.719792
1440.5470650.905870.452935
1450.600390.799220.39961
1460.7124850.5750290.287515
1470.6841560.6316870.315844
1480.6765050.6469890.323495
1490.6640850.671830.335915
1500.6716550.656690.328345
1510.6501520.6996970.349848
1520.6619060.6761880.338094
1530.7131860.5736270.286814
1540.7000030.5999930.299997
1550.6956750.608650.304325
1560.7372950.525410.262705
1570.7424770.5150470.257523
1580.7187130.5625740.281287
1590.7470940.5058120.252906
1600.7529810.4940380.247019
1610.7271320.5457360.272868
1620.7632570.4734860.236743
1630.8338740.3322510.166126
1640.8478070.3043850.152193
1650.8750660.2498680.124934
1660.8591210.2817570.140879
1670.8373540.3252930.162646
1680.8902520.2194960.109748
1690.8904520.2190960.109548
1700.920130.159740.0798698
1710.9149970.1700050.0850026
1720.9038530.1922950.0961473
1730.8942640.2114710.105736
1740.9264360.1471280.073564
1750.9701660.05966830.0298341
1760.9646670.0706660.035333
1770.959380.08123970.0406198
1780.9548190.09036110.0451805
1790.9473470.1053060.0526528
1800.9377430.1245150.0622574
1810.9259250.148150.0740748
1820.9268410.1463180.0731588
1830.9183570.1632850.0816427
1840.9355540.1288920.064446
1850.9264170.1471670.0735833
1860.9165290.1669420.0834709
1870.9049610.1900780.095039
1880.9396210.1207570.0603786
1890.9353130.1293740.0646869
1900.9393750.121250.060625
1910.9423560.1152880.0576442
1920.943170.113660.0568298
1930.9323510.1352990.0676493
1940.9277520.1444960.072248
1950.9146320.1707360.0853678
1960.9061870.1876260.0938131
1970.9162030.1675950.0837974
1980.9043330.1913340.0956672
1990.8843290.2313420.115671
2000.8634490.2731020.136551
2010.854370.291260.14563
2020.8290760.3418470.170924
2030.8304350.3391310.169565
2040.8083710.3832590.191629
2050.7772330.4455350.222767
2060.7479760.5040480.252024
2070.7185420.5629160.281458
2080.6951090.6097820.304891
2090.6677080.6645840.332292
2100.6426620.7146770.357338
2110.6029730.7940550.397027
2120.6914950.617010.308505
2130.7405120.5189760.259488
2140.7001280.5997440.299872
2150.6590320.6819370.340968
2160.7483860.5032280.251614
2170.7095330.5809340.290467
2180.6908950.6182090.309105
2190.6472310.7055370.352769
2200.6573780.6852440.342622
2210.6161190.7677630.383881
2220.5743170.8513660.425683
2230.5332380.9335250.466762
2240.4801370.9602730.519863
2250.5248890.9502220.475111
2260.5580310.8839380.441969
2270.533070.933860.46693
2280.5165720.9668560.483428
2290.4603670.9207350.539633
2300.4491810.8983620.550819
2310.4015520.8031040.598448
2320.6011240.7977520.398876
2330.7550310.4899370.244969
2340.7558080.4883850.244192
2350.7153050.569390.284695
2360.6679260.6641480.332074
2370.6814260.6371480.318574
2380.7359970.5280060.264003
2390.6739960.6520080.326004
2400.7022380.5955240.297762
2410.6586380.6827240.341362
2420.6316530.7366940.368347
2430.5748280.8503450.425172
2440.5155970.9688060.484403
2450.7357450.528510.264255
2460.8229230.3541530.177077
2470.8791110.2417780.120889
2480.8139660.3720690.186034
2490.7328070.5343860.267193
2500.8145290.3709420.185471
2510.8198380.3603240.180162
2520.7051360.5897290.294864
2530.7937940.4124110.206206






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level140.0576132NOK
10% type I error level280.115226NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 14 & 0.0576132 & NOK \tabularnewline
10% type I error level & 28 & 0.115226 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226347&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]14[/C][C]0.0576132[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]28[/C][C]0.115226[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226347&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226347&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level140.0576132NOK
10% type I error level280.115226NOK


Figures (Output of Computation)

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

Parameters (Session):
par1 = 7 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 7 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
R code (references can be found in the software module):
par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- ''
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')
}