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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 computationMon, 18 Nov 2013 11:34:44 -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/18/t1384794042ahwmgu63ppv13e5.htm/, Retrieved Sat, 27 Apr 2024 12:52:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226169, Retrieved Sat, 27 Apr 2024 12:52:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact49

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-11-17 09:14:55] [b98453cac15ba1066b407e146608df68]
- R PD    [Multiple Regression] [WS7 Hapiness] [2013-11-18 16:34:44] [2e4b2f9d3944a9ae720fcdd8099335ae] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 14 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226169&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]14 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226169&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226169&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 time14 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 15.3696 + 0.0183209Connected[t] + 0.0150345Separate[t] + 0.0624141Software[t] -0.386905Depression[t] + 0.00847557Sport1[t] + 0.0238625Sport2[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  15.3696 +  0.0183209Connected[t] +  0.0150345Separate[t] +  0.0624141Software[t] -0.386905Depression[t] +  0.00847557Sport1[t] +  0.0238625Sport2[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226169&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  15.3696 +  0.0183209Connected[t] +  0.0150345Separate[t] +  0.0624141Software[t] -0.386905Depression[t] +  0.00847557Sport1[t] +  0.0238625Sport2[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226169&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226169&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 15.3696 + 0.0183209Connected[t] + 0.0150345Separate[t] + 0.0624141Software[t] -0.386905Depression[t] + 0.00847557Sport1[t] + 0.0238625Sport2[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.36961.827528.412.86009e-151.43005e-15
Connected0.01832090.03741980.48960.6248320.312416
Separate0.01503450.03835260.3920.6953780.347689
Software0.06241410.05565851.1210.2631750.131587
Depression-0.3869050.038924-9.946.5519e-203.27595e-20
Sport10.008475570.04072210.20810.8352910.417645
Sport20.02386250.06072570.3930.6946780.347339

\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) & 15.3696 & 1.82752 & 8.41 & 2.86009e-15 & 1.43005e-15 \tabularnewline
Connected & 0.0183209 & 0.0374198 & 0.4896 & 0.624832 & 0.312416 \tabularnewline
Separate & 0.0150345 & 0.0383526 & 0.392 & 0.695378 & 0.347689 \tabularnewline
Software & 0.0624141 & 0.0556585 & 1.121 & 0.263175 & 0.131587 \tabularnewline
Depression & -0.386905 & 0.038924 & -9.94 & 6.5519e-20 & 3.27595e-20 \tabularnewline
Sport1 & 0.00847557 & 0.0407221 & 0.2081 & 0.835291 & 0.417645 \tabularnewline
Sport2 & 0.0238625 & 0.0607257 & 0.393 & 0.694678 & 0.347339 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226169&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]15.3696[/C][C]1.82752[/C][C]8.41[/C][C]2.86009e-15[/C][C]1.43005e-15[/C][/ROW]
[ROW][C]Connected[/C][C]0.0183209[/C][C]0.0374198[/C][C]0.4896[/C][C]0.624832[/C][C]0.312416[/C][/ROW]
[ROW][C]Separate[/C][C]0.0150345[/C][C]0.0383526[/C][C]0.392[/C][C]0.695378[/C][C]0.347689[/C][/ROW]
[ROW][C]Software[/C][C]0.0624141[/C][C]0.0556585[/C][C]1.121[/C][C]0.263175[/C][C]0.131587[/C][/ROW]
[ROW][C]Depression[/C][C]-0.386905[/C][C]0.038924[/C][C]-9.94[/C][C]6.5519e-20[/C][C]3.27595e-20[/C][/ROW]
[ROW][C]Sport1[/C][C]0.00847557[/C][C]0.0407221[/C][C]0.2081[/C][C]0.835291[/C][C]0.417645[/C][/ROW]
[ROW][C]Sport2[/C][C]0.0238625[/C][C]0.0607257[/C][C]0.393[/C][C]0.694678[/C][C]0.347339[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226169&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226169&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)15.36961.827528.412.86009e-151.43005e-15
Connected0.01832090.03741980.48960.6248320.312416
Separate0.01503450.03835260.3920.6953780.347689
Software0.06241410.05565851.1210.2631750.131587
Depression-0.3869050.038924-9.946.5519e-203.27595e-20
Sport10.008475570.04072210.20810.8352910.417645
Sport20.02386250.06072570.3930.6946780.347339






Multiple Linear Regression - Regression Statistics
Multiple R0.596874
R-squared0.356259
Adjusted R-squared0.34123
F-TEST (value)23.7048
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.02802
Sum Squared Residuals1057

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.596874 \tabularnewline
R-squared & 0.356259 \tabularnewline
Adjusted R-squared & 0.34123 \tabularnewline
F-TEST (value) & 23.7048 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 257 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.02802 \tabularnewline
Sum Squared Residuals & 1057 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226169&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.596874[/C][/ROW]
[ROW][C]R-squared[/C][C]0.356259[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.34123[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]23.7048[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]257[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.02802[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1057[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226169&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226169&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 R0.596874
R-squared0.356259
Adjusted R-squared0.34123
F-TEST (value)23.7048
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.02802
Sum Squared Residuals1057






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.0109-0.0109338
21814.91623.08377
31113.5265-2.52654
41213.7115-1.71149
51610.97695.02307
61814.21073.7893
71410.11933.88069
81414.9989-0.998855
91515.1362-0.136236
101513.91641.08362
111715.12571.87426
121915.43923.56085
131013.1074-3.10743
141613.17042.82959
151815.59972.40033
161413.13490.86511
171413.42720.572841
181715.16451.8355
191414.9937-0.993682
201613.49832.50171
211815.00072.99933
221113.3622-2.36216
231414.069-0.0690442
241213.2612-1.2612
251715.02791.97207
26915.7306-6.73063
271614.59371.40627
281413.23540.764596
291513.53751.46251
301113.7008-2.70079
311615.51770.482298
321312.28620.7138
331714.89642.10356
341515.0423-0.0422763
351413.79210.207882
361615.44530.554666
37910.6074-1.60742
381514.25920.740795
391714.86382.13616
401314.8491-1.84905
411515.3715-0.371531
421613.50652.49348
431615.6330.367034
441212.8949-0.894859
451514.44190.558063
461113.8237-2.82368
471515.5583-0.55833
481514.64930.350742
491713.11283.88719
501314.7493-1.74934
511615.19210.807929
521413.13670.863311
531111.6535-0.65351
541213.5816-1.58165
551213.8861-1.88605
561513.10371.89633
571614.01541.98455
581515.2489-0.248944
591215.051-3.05098
601212.9619-0.961899
61810.2517-2.25175
621314.4095-1.40946
631114.5731-3.57305
641412.91411.08594
651513.42291.57712
661014.9698-4.9698
671112.4133-1.41333
681213.9659-1.96588
691513.84541.15461
701513.48641.5136
711413.69430.305651
721612.63693.36307
731514.25480.745239
741515.2262-0.226223
751314.7965-1.79648
761211.59290.40706
771714.00472.9953
781312.20250.797535
791513.8421.15803
801314.9653-1.96532
811514.77560.224357
821515.5095-0.509463
831614.29451.70552
841514.17090.82912
851413.80870.191257
861513.89351.10647
871414.1785-0.178463
881312.57250.427502
89710.3267-3.32671
901713.72713.27291
911312.8880.112013
921514.09670.903304
931413.16260.837424
941314.0641-1.06413
951614.79311.20692
961212.8054-0.805436
971414.5414-0.541394
981714.88352.11647
991514.9940.0060275
1001715.32971.67031
1011212.7622-0.762235
1021614.841.15999
1031114.369-3.369
1041512.84772.15233
105911.536-2.53596
1061614.85061.14935
1071512.89342.10661
1081012.6834-2.68343
109109.045730.954275
1101513.72391.27608
1111113.181-2.181
1121315.0611-2.06112
1131411.91952.0805
1141814.30563.69444
1151615.46450.535525
1161413.21540.784623
1171413.68120.318797
1181415.2918-1.2918
1191413.62760.37238
1201212.6585-0.65854
1211413.480.520038
1221515.188-0.188007
1231516.163-1.16298
1241514.74310.256869
1251314.905-1.905
1261716.16930.830688
1271715.25671.74334
1281914.77244.22761
1291513.82391.1761
1301314.4241-1.42414
131910.826-1.82598
1321515.0392-0.0392216
1331512.70362.29636
1341514.44970.550288
1351613.70932.29074
136119.121351.87865
1371413.32470.67526
1381112.1719-1.17191
1391514.26230.737749
1401313.9458-0.945751
1411514.34240.6576
1421613.54942.45055
1431414.7323-0.732349
1441514.07730.922718
1451614.87861.12142
1461614.2961.70404
1471113.7049-2.70486
1481214.6482-2.64825
149911.4188-2.41881
1501614.43131.56873
1511312.72040.27959
1521615.22350.776516
1531213.9889-1.98894
154911.3359-2.33594
1551311.85331.14669
1561312.8880.112013
1571413.08080.919187
1581914.77244.22761
1591315.6069-2.60691
1601211.96720.0327746
1611312.5250.474975
162109.179010.820995
1631413.21910.780903
1641611.58574.4143
1651011.875-1.87499
166119.105931.89407
1671414.2655-0.265507
1681213.2312-1.2312
169913.0104-4.01038
170911.8022-2.80225
1711110.36490.635056
1721614.35171.64832
173914.4108-5.41083
1741311.47151.52852
1751613.82952.17054
1761315.3975-2.39748
177912.4548-3.45482
1781211.53080.469175
1791614.70491.29511
1801113.3965-2.3965
1811414.3085-0.308504
1821314.9004-1.90038
1831514.80220.197762
1841415.2502-1.25022
1851614.75341.24664
1861311.58891.41107
1871413.46340.536559
1881514.32240.6776
1891312.49730.502713
1901110.13180.868228
1911112.8008-1.80083
1921415.2327-1.23266
1931512.42272.57734
1941112.567-1.56698
1951513.30461.69541
1961214.3681-2.36809
1971411.4842.51597
1981413.47790.522102
199811.0892-3.08921
2001313.7488-0.748772
201912.1766-3.17656
2021513.78091.21912
2031714.40222.5978
2041313.0987-0.0987329
2051514.3650.634999
2061513.89151.1085
2071414.6436-0.643616
2081612.67793.32211
2091313.376-0.375953
2101614.3751.62505
211912.1571-3.15712
2121615.25190.748098
2131112.2904-1.29038
2141013.7087-3.70866
2151112.2309-1.23094
2161513.3821.61795
2171714.89222.10778
2181414.5208-0.520843
21989.91877-1.91877
2201513.88361.1164
2211114.3548-3.35485
2221613.81962.18041
2231012.287-2.28702
2241515.1584-0.158377
22599.55498-0.554982
2261614.76131.23873
2271914.03194.96807
2281213.7495-1.74947
22989.71312-1.71312
2301113.67-2.67001
2311413.8030.197025
232912.5969-3.59693
2331514.710.290033
2341312.62120.378826
2351615.27580.724246
2361113.322-2.32202
2371212.1328-0.132826
2381313.3655-0.36548
2391014.4963-4.49627
2401113.9527-2.95269
2411214.9861-2.98615
242811.1329-3.13288
2431211.6270.372966
2441212.2048-0.204813
2451513.68071.31933
2461110.77530.224685
2471312.84260.157395
248149.238054.76195
2491010.1283-0.128265
2501211.59130.408694
2511513.06441.93558
2521312.09740.90261
2531314.3105-1.31052
2541313.6713-0.671261
2551212.2166-0.216607
2561212.9655-0.965531
257910.8528-1.85278
258911.4336-2.43361
2591512.98782.0122
2601015.4981-5.49814
2611413.80820.191843
2621514.22460.775416
263710.0247-3.02474
2641413.93720.0628428

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 14.0109 & -0.0109338 \tabularnewline
2 & 18 & 14.9162 & 3.08377 \tabularnewline
3 & 11 & 13.5265 & -2.52654 \tabularnewline
4 & 12 & 13.7115 & -1.71149 \tabularnewline
5 & 16 & 10.9769 & 5.02307 \tabularnewline
6 & 18 & 14.2107 & 3.7893 \tabularnewline
7 & 14 & 10.1193 & 3.88069 \tabularnewline
8 & 14 & 14.9989 & -0.998855 \tabularnewline
9 & 15 & 15.1362 & -0.136236 \tabularnewline
10 & 15 & 13.9164 & 1.08362 \tabularnewline
11 & 17 & 15.1257 & 1.87426 \tabularnewline
12 & 19 & 15.4392 & 3.56085 \tabularnewline
13 & 10 & 13.1074 & -3.10743 \tabularnewline
14 & 16 & 13.1704 & 2.82959 \tabularnewline
15 & 18 & 15.5997 & 2.40033 \tabularnewline
16 & 14 & 13.1349 & 0.86511 \tabularnewline
17 & 14 & 13.4272 & 0.572841 \tabularnewline
18 & 17 & 15.1645 & 1.8355 \tabularnewline
19 & 14 & 14.9937 & -0.993682 \tabularnewline
20 & 16 & 13.4983 & 2.50171 \tabularnewline
21 & 18 & 15.0007 & 2.99933 \tabularnewline
22 & 11 & 13.3622 & -2.36216 \tabularnewline
23 & 14 & 14.069 & -0.0690442 \tabularnewline
24 & 12 & 13.2612 & -1.2612 \tabularnewline
25 & 17 & 15.0279 & 1.97207 \tabularnewline
26 & 9 & 15.7306 & -6.73063 \tabularnewline
27 & 16 & 14.5937 & 1.40627 \tabularnewline
28 & 14 & 13.2354 & 0.764596 \tabularnewline
29 & 15 & 13.5375 & 1.46251 \tabularnewline
30 & 11 & 13.7008 & -2.70079 \tabularnewline
31 & 16 & 15.5177 & 0.482298 \tabularnewline
32 & 13 & 12.2862 & 0.7138 \tabularnewline
33 & 17 & 14.8964 & 2.10356 \tabularnewline
34 & 15 & 15.0423 & -0.0422763 \tabularnewline
35 & 14 & 13.7921 & 0.207882 \tabularnewline
36 & 16 & 15.4453 & 0.554666 \tabularnewline
37 & 9 & 10.6074 & -1.60742 \tabularnewline
38 & 15 & 14.2592 & 0.740795 \tabularnewline
39 & 17 & 14.8638 & 2.13616 \tabularnewline
40 & 13 & 14.8491 & -1.84905 \tabularnewline
41 & 15 & 15.3715 & -0.371531 \tabularnewline
42 & 16 & 13.5065 & 2.49348 \tabularnewline
43 & 16 & 15.633 & 0.367034 \tabularnewline
44 & 12 & 12.8949 & -0.894859 \tabularnewline
45 & 15 & 14.4419 & 0.558063 \tabularnewline
46 & 11 & 13.8237 & -2.82368 \tabularnewline
47 & 15 & 15.5583 & -0.55833 \tabularnewline
48 & 15 & 14.6493 & 0.350742 \tabularnewline
49 & 17 & 13.1128 & 3.88719 \tabularnewline
50 & 13 & 14.7493 & -1.74934 \tabularnewline
51 & 16 & 15.1921 & 0.807929 \tabularnewline
52 & 14 & 13.1367 & 0.863311 \tabularnewline
53 & 11 & 11.6535 & -0.65351 \tabularnewline
54 & 12 & 13.5816 & -1.58165 \tabularnewline
55 & 12 & 13.8861 & -1.88605 \tabularnewline
56 & 15 & 13.1037 & 1.89633 \tabularnewline
57 & 16 & 14.0154 & 1.98455 \tabularnewline
58 & 15 & 15.2489 & -0.248944 \tabularnewline
59 & 12 & 15.051 & -3.05098 \tabularnewline
60 & 12 & 12.9619 & -0.961899 \tabularnewline
61 & 8 & 10.2517 & -2.25175 \tabularnewline
62 & 13 & 14.4095 & -1.40946 \tabularnewline
63 & 11 & 14.5731 & -3.57305 \tabularnewline
64 & 14 & 12.9141 & 1.08594 \tabularnewline
65 & 15 & 13.4229 & 1.57712 \tabularnewline
66 & 10 & 14.9698 & -4.9698 \tabularnewline
67 & 11 & 12.4133 & -1.41333 \tabularnewline
68 & 12 & 13.9659 & -1.96588 \tabularnewline
69 & 15 & 13.8454 & 1.15461 \tabularnewline
70 & 15 & 13.4864 & 1.5136 \tabularnewline
71 & 14 & 13.6943 & 0.305651 \tabularnewline
72 & 16 & 12.6369 & 3.36307 \tabularnewline
73 & 15 & 14.2548 & 0.745239 \tabularnewline
74 & 15 & 15.2262 & -0.226223 \tabularnewline
75 & 13 & 14.7965 & -1.79648 \tabularnewline
76 & 12 & 11.5929 & 0.40706 \tabularnewline
77 & 17 & 14.0047 & 2.9953 \tabularnewline
78 & 13 & 12.2025 & 0.797535 \tabularnewline
79 & 15 & 13.842 & 1.15803 \tabularnewline
80 & 13 & 14.9653 & -1.96532 \tabularnewline
81 & 15 & 14.7756 & 0.224357 \tabularnewline
82 & 15 & 15.5095 & -0.509463 \tabularnewline
83 & 16 & 14.2945 & 1.70552 \tabularnewline
84 & 15 & 14.1709 & 0.82912 \tabularnewline
85 & 14 & 13.8087 & 0.191257 \tabularnewline
86 & 15 & 13.8935 & 1.10647 \tabularnewline
87 & 14 & 14.1785 & -0.178463 \tabularnewline
88 & 13 & 12.5725 & 0.427502 \tabularnewline
89 & 7 & 10.3267 & -3.32671 \tabularnewline
90 & 17 & 13.7271 & 3.27291 \tabularnewline
91 & 13 & 12.888 & 0.112013 \tabularnewline
92 & 15 & 14.0967 & 0.903304 \tabularnewline
93 & 14 & 13.1626 & 0.837424 \tabularnewline
94 & 13 & 14.0641 & -1.06413 \tabularnewline
95 & 16 & 14.7931 & 1.20692 \tabularnewline
96 & 12 & 12.8054 & -0.805436 \tabularnewline
97 & 14 & 14.5414 & -0.541394 \tabularnewline
98 & 17 & 14.8835 & 2.11647 \tabularnewline
99 & 15 & 14.994 & 0.0060275 \tabularnewline
100 & 17 & 15.3297 & 1.67031 \tabularnewline
101 & 12 & 12.7622 & -0.762235 \tabularnewline
102 & 16 & 14.84 & 1.15999 \tabularnewline
103 & 11 & 14.369 & -3.369 \tabularnewline
104 & 15 & 12.8477 & 2.15233 \tabularnewline
105 & 9 & 11.536 & -2.53596 \tabularnewline
106 & 16 & 14.8506 & 1.14935 \tabularnewline
107 & 15 & 12.8934 & 2.10661 \tabularnewline
108 & 10 & 12.6834 & -2.68343 \tabularnewline
109 & 10 & 9.04573 & 0.954275 \tabularnewline
110 & 15 & 13.7239 & 1.27608 \tabularnewline
111 & 11 & 13.181 & -2.181 \tabularnewline
112 & 13 & 15.0611 & -2.06112 \tabularnewline
113 & 14 & 11.9195 & 2.0805 \tabularnewline
114 & 18 & 14.3056 & 3.69444 \tabularnewline
115 & 16 & 15.4645 & 0.535525 \tabularnewline
116 & 14 & 13.2154 & 0.784623 \tabularnewline
117 & 14 & 13.6812 & 0.318797 \tabularnewline
118 & 14 & 15.2918 & -1.2918 \tabularnewline
119 & 14 & 13.6276 & 0.37238 \tabularnewline
120 & 12 & 12.6585 & -0.65854 \tabularnewline
121 & 14 & 13.48 & 0.520038 \tabularnewline
122 & 15 & 15.188 & -0.188007 \tabularnewline
123 & 15 & 16.163 & -1.16298 \tabularnewline
124 & 15 & 14.7431 & 0.256869 \tabularnewline
125 & 13 & 14.905 & -1.905 \tabularnewline
126 & 17 & 16.1693 & 0.830688 \tabularnewline
127 & 17 & 15.2567 & 1.74334 \tabularnewline
128 & 19 & 14.7724 & 4.22761 \tabularnewline
129 & 15 & 13.8239 & 1.1761 \tabularnewline
130 & 13 & 14.4241 & -1.42414 \tabularnewline
131 & 9 & 10.826 & -1.82598 \tabularnewline
132 & 15 & 15.0392 & -0.0392216 \tabularnewline
133 & 15 & 12.7036 & 2.29636 \tabularnewline
134 & 15 & 14.4497 & 0.550288 \tabularnewline
135 & 16 & 13.7093 & 2.29074 \tabularnewline
136 & 11 & 9.12135 & 1.87865 \tabularnewline
137 & 14 & 13.3247 & 0.67526 \tabularnewline
138 & 11 & 12.1719 & -1.17191 \tabularnewline
139 & 15 & 14.2623 & 0.737749 \tabularnewline
140 & 13 & 13.9458 & -0.945751 \tabularnewline
141 & 15 & 14.3424 & 0.6576 \tabularnewline
142 & 16 & 13.5494 & 2.45055 \tabularnewline
143 & 14 & 14.7323 & -0.732349 \tabularnewline
144 & 15 & 14.0773 & 0.922718 \tabularnewline
145 & 16 & 14.8786 & 1.12142 \tabularnewline
146 & 16 & 14.296 & 1.70404 \tabularnewline
147 & 11 & 13.7049 & -2.70486 \tabularnewline
148 & 12 & 14.6482 & -2.64825 \tabularnewline
149 & 9 & 11.4188 & -2.41881 \tabularnewline
150 & 16 & 14.4313 & 1.56873 \tabularnewline
151 & 13 & 12.7204 & 0.27959 \tabularnewline
152 & 16 & 15.2235 & 0.776516 \tabularnewline
153 & 12 & 13.9889 & -1.98894 \tabularnewline
154 & 9 & 11.3359 & -2.33594 \tabularnewline
155 & 13 & 11.8533 & 1.14669 \tabularnewline
156 & 13 & 12.888 & 0.112013 \tabularnewline
157 & 14 & 13.0808 & 0.919187 \tabularnewline
158 & 19 & 14.7724 & 4.22761 \tabularnewline
159 & 13 & 15.6069 & -2.60691 \tabularnewline
160 & 12 & 11.9672 & 0.0327746 \tabularnewline
161 & 13 & 12.525 & 0.474975 \tabularnewline
162 & 10 & 9.17901 & 0.820995 \tabularnewline
163 & 14 & 13.2191 & 0.780903 \tabularnewline
164 & 16 & 11.5857 & 4.4143 \tabularnewline
165 & 10 & 11.875 & -1.87499 \tabularnewline
166 & 11 & 9.10593 & 1.89407 \tabularnewline
167 & 14 & 14.2655 & -0.265507 \tabularnewline
168 & 12 & 13.2312 & -1.2312 \tabularnewline
169 & 9 & 13.0104 & -4.01038 \tabularnewline
170 & 9 & 11.8022 & -2.80225 \tabularnewline
171 & 11 & 10.3649 & 0.635056 \tabularnewline
172 & 16 & 14.3517 & 1.64832 \tabularnewline
173 & 9 & 14.4108 & -5.41083 \tabularnewline
174 & 13 & 11.4715 & 1.52852 \tabularnewline
175 & 16 & 13.8295 & 2.17054 \tabularnewline
176 & 13 & 15.3975 & -2.39748 \tabularnewline
177 & 9 & 12.4548 & -3.45482 \tabularnewline
178 & 12 & 11.5308 & 0.469175 \tabularnewline
179 & 16 & 14.7049 & 1.29511 \tabularnewline
180 & 11 & 13.3965 & -2.3965 \tabularnewline
181 & 14 & 14.3085 & -0.308504 \tabularnewline
182 & 13 & 14.9004 & -1.90038 \tabularnewline
183 & 15 & 14.8022 & 0.197762 \tabularnewline
184 & 14 & 15.2502 & -1.25022 \tabularnewline
185 & 16 & 14.7534 & 1.24664 \tabularnewline
186 & 13 & 11.5889 & 1.41107 \tabularnewline
187 & 14 & 13.4634 & 0.536559 \tabularnewline
188 & 15 & 14.3224 & 0.6776 \tabularnewline
189 & 13 & 12.4973 & 0.502713 \tabularnewline
190 & 11 & 10.1318 & 0.868228 \tabularnewline
191 & 11 & 12.8008 & -1.80083 \tabularnewline
192 & 14 & 15.2327 & -1.23266 \tabularnewline
193 & 15 & 12.4227 & 2.57734 \tabularnewline
194 & 11 & 12.567 & -1.56698 \tabularnewline
195 & 15 & 13.3046 & 1.69541 \tabularnewline
196 & 12 & 14.3681 & -2.36809 \tabularnewline
197 & 14 & 11.484 & 2.51597 \tabularnewline
198 & 14 & 13.4779 & 0.522102 \tabularnewline
199 & 8 & 11.0892 & -3.08921 \tabularnewline
200 & 13 & 13.7488 & -0.748772 \tabularnewline
201 & 9 & 12.1766 & -3.17656 \tabularnewline
202 & 15 & 13.7809 & 1.21912 \tabularnewline
203 & 17 & 14.4022 & 2.5978 \tabularnewline
204 & 13 & 13.0987 & -0.0987329 \tabularnewline
205 & 15 & 14.365 & 0.634999 \tabularnewline
206 & 15 & 13.8915 & 1.1085 \tabularnewline
207 & 14 & 14.6436 & -0.643616 \tabularnewline
208 & 16 & 12.6779 & 3.32211 \tabularnewline
209 & 13 & 13.376 & -0.375953 \tabularnewline
210 & 16 & 14.375 & 1.62505 \tabularnewline
211 & 9 & 12.1571 & -3.15712 \tabularnewline
212 & 16 & 15.2519 & 0.748098 \tabularnewline
213 & 11 & 12.2904 & -1.29038 \tabularnewline
214 & 10 & 13.7087 & -3.70866 \tabularnewline
215 & 11 & 12.2309 & -1.23094 \tabularnewline
216 & 15 & 13.382 & 1.61795 \tabularnewline
217 & 17 & 14.8922 & 2.10778 \tabularnewline
218 & 14 & 14.5208 & -0.520843 \tabularnewline
219 & 8 & 9.91877 & -1.91877 \tabularnewline
220 & 15 & 13.8836 & 1.1164 \tabularnewline
221 & 11 & 14.3548 & -3.35485 \tabularnewline
222 & 16 & 13.8196 & 2.18041 \tabularnewline
223 & 10 & 12.287 & -2.28702 \tabularnewline
224 & 15 & 15.1584 & -0.158377 \tabularnewline
225 & 9 & 9.55498 & -0.554982 \tabularnewline
226 & 16 & 14.7613 & 1.23873 \tabularnewline
227 & 19 & 14.0319 & 4.96807 \tabularnewline
228 & 12 & 13.7495 & -1.74947 \tabularnewline
229 & 8 & 9.71312 & -1.71312 \tabularnewline
230 & 11 & 13.67 & -2.67001 \tabularnewline
231 & 14 & 13.803 & 0.197025 \tabularnewline
232 & 9 & 12.5969 & -3.59693 \tabularnewline
233 & 15 & 14.71 & 0.290033 \tabularnewline
234 & 13 & 12.6212 & 0.378826 \tabularnewline
235 & 16 & 15.2758 & 0.724246 \tabularnewline
236 & 11 & 13.322 & -2.32202 \tabularnewline
237 & 12 & 12.1328 & -0.132826 \tabularnewline
238 & 13 & 13.3655 & -0.36548 \tabularnewline
239 & 10 & 14.4963 & -4.49627 \tabularnewline
240 & 11 & 13.9527 & -2.95269 \tabularnewline
241 & 12 & 14.9861 & -2.98615 \tabularnewline
242 & 8 & 11.1329 & -3.13288 \tabularnewline
243 & 12 & 11.627 & 0.372966 \tabularnewline
244 & 12 & 12.2048 & -0.204813 \tabularnewline
245 & 15 & 13.6807 & 1.31933 \tabularnewline
246 & 11 & 10.7753 & 0.224685 \tabularnewline
247 & 13 & 12.8426 & 0.157395 \tabularnewline
248 & 14 & 9.23805 & 4.76195 \tabularnewline
249 & 10 & 10.1283 & -0.128265 \tabularnewline
250 & 12 & 11.5913 & 0.408694 \tabularnewline
251 & 15 & 13.0644 & 1.93558 \tabularnewline
252 & 13 & 12.0974 & 0.90261 \tabularnewline
253 & 13 & 14.3105 & -1.31052 \tabularnewline
254 & 13 & 13.6713 & -0.671261 \tabularnewline
255 & 12 & 12.2166 & -0.216607 \tabularnewline
256 & 12 & 12.9655 & -0.965531 \tabularnewline
257 & 9 & 10.8528 & -1.85278 \tabularnewline
258 & 9 & 11.4336 & -2.43361 \tabularnewline
259 & 15 & 12.9878 & 2.0122 \tabularnewline
260 & 10 & 15.4981 & -5.49814 \tabularnewline
261 & 14 & 13.8082 & 0.191843 \tabularnewline
262 & 15 & 14.2246 & 0.775416 \tabularnewline
263 & 7 & 10.0247 & -3.02474 \tabularnewline
264 & 14 & 13.9372 & 0.0628428 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226169&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]14[/C][C]14.0109[/C][C]-0.0109338[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]14.9162[/C][C]3.08377[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]13.5265[/C][C]-2.52654[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]13.7115[/C][C]-1.71149[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]10.9769[/C][C]5.02307[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.2107[/C][C]3.7893[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.1193[/C][C]3.88069[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]14.9989[/C][C]-0.998855[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]15.1362[/C][C]-0.136236[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]13.9164[/C][C]1.08362[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.1257[/C][C]1.87426[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.4392[/C][C]3.56085[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.1074[/C][C]-3.10743[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.1704[/C][C]2.82959[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.5997[/C][C]2.40033[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.1349[/C][C]0.86511[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.4272[/C][C]0.572841[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.1645[/C][C]1.8355[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]14.9937[/C][C]-0.993682[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.4983[/C][C]2.50171[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.0007[/C][C]2.99933[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.3622[/C][C]-2.36216[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.069[/C][C]-0.0690442[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.2612[/C][C]-1.2612[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.0279[/C][C]1.97207[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.7306[/C][C]-6.73063[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.5937[/C][C]1.40627[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.2354[/C][C]0.764596[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]13.5375[/C][C]1.46251[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]13.7008[/C][C]-2.70079[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.5177[/C][C]0.482298[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.2862[/C][C]0.7138[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]14.8964[/C][C]2.10356[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.0423[/C][C]-0.0422763[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]13.7921[/C][C]0.207882[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.4453[/C][C]0.554666[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.6074[/C][C]-1.60742[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.2592[/C][C]0.740795[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]14.8638[/C][C]2.13616[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]14.8491[/C][C]-1.84905[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.3715[/C][C]-0.371531[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.5065[/C][C]2.49348[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]15.633[/C][C]0.367034[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]12.8949[/C][C]-0.894859[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.4419[/C][C]0.558063[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.8237[/C][C]-2.82368[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.5583[/C][C]-0.55833[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.6493[/C][C]0.350742[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.1128[/C][C]3.88719[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.7493[/C][C]-1.74934[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.1921[/C][C]0.807929[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.1367[/C][C]0.863311[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.6535[/C][C]-0.65351[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.5816[/C][C]-1.58165[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]13.8861[/C][C]-1.88605[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.1037[/C][C]1.89633[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.0154[/C][C]1.98455[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.2489[/C][C]-0.248944[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.051[/C][C]-3.05098[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]12.9619[/C][C]-0.961899[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.2517[/C][C]-2.25175[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.4095[/C][C]-1.40946[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.5731[/C][C]-3.57305[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]12.9141[/C][C]1.08594[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.4229[/C][C]1.57712[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]14.9698[/C][C]-4.9698[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.4133[/C][C]-1.41333[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]13.9659[/C][C]-1.96588[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.8454[/C][C]1.15461[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.4864[/C][C]1.5136[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.6943[/C][C]0.305651[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.6369[/C][C]3.36307[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.2548[/C][C]0.745239[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.2262[/C][C]-0.226223[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.7965[/C][C]-1.79648[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]11.5929[/C][C]0.40706[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]14.0047[/C][C]2.9953[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.2025[/C][C]0.797535[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.842[/C][C]1.15803[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]14.9653[/C][C]-1.96532[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.7756[/C][C]0.224357[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.5095[/C][C]-0.509463[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.2945[/C][C]1.70552[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.1709[/C][C]0.82912[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]13.8087[/C][C]0.191257[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.8935[/C][C]1.10647[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.1785[/C][C]-0.178463[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.5725[/C][C]0.427502[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.3267[/C][C]-3.32671[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.7271[/C][C]3.27291[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]12.888[/C][C]0.112013[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.0967[/C][C]0.903304[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.1626[/C][C]0.837424[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.0641[/C][C]-1.06413[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.7931[/C][C]1.20692[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.8054[/C][C]-0.805436[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.5414[/C][C]-0.541394[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.8835[/C][C]2.11647[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]14.994[/C][C]0.0060275[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.3297[/C][C]1.67031[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]12.7622[/C][C]-0.762235[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]14.84[/C][C]1.15999[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.369[/C][C]-3.369[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]12.8477[/C][C]2.15233[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.536[/C][C]-2.53596[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.8506[/C][C]1.14935[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.8934[/C][C]2.10661[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.6834[/C][C]-2.68343[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.04573[/C][C]0.954275[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.7239[/C][C]1.27608[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.181[/C][C]-2.181[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.0611[/C][C]-2.06112[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]11.9195[/C][C]2.0805[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.3056[/C][C]3.69444[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.4645[/C][C]0.535525[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.2154[/C][C]0.784623[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.6812[/C][C]0.318797[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.2918[/C][C]-1.2918[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.6276[/C][C]0.37238[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.6585[/C][C]-0.65854[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.48[/C][C]0.520038[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]15.188[/C][C]-0.188007[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]16.163[/C][C]-1.16298[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.7431[/C][C]0.256869[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.905[/C][C]-1.905[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.1693[/C][C]0.830688[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.2567[/C][C]1.74334[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.7724[/C][C]4.22761[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.8239[/C][C]1.1761[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.4241[/C][C]-1.42414[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.826[/C][C]-1.82598[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.0392[/C][C]-0.0392216[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.7036[/C][C]2.29636[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.4497[/C][C]0.550288[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.7093[/C][C]2.29074[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.12135[/C][C]1.87865[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.3247[/C][C]0.67526[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]12.1719[/C][C]-1.17191[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.2623[/C][C]0.737749[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.9458[/C][C]-0.945751[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.3424[/C][C]0.6576[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.5494[/C][C]2.45055[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.7323[/C][C]-0.732349[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.0773[/C][C]0.922718[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.8786[/C][C]1.12142[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.296[/C][C]1.70404[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.7049[/C][C]-2.70486[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.6482[/C][C]-2.64825[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.4188[/C][C]-2.41881[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]14.4313[/C][C]1.56873[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.7204[/C][C]0.27959[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.2235[/C][C]0.776516[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]13.9889[/C][C]-1.98894[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.3359[/C][C]-2.33594[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.8533[/C][C]1.14669[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.888[/C][C]0.112013[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.0808[/C][C]0.919187[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.7724[/C][C]4.22761[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.6069[/C][C]-2.60691[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]11.9672[/C][C]0.0327746[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.525[/C][C]0.474975[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.17901[/C][C]0.820995[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.2191[/C][C]0.780903[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.5857[/C][C]4.4143[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.875[/C][C]-1.87499[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]9.10593[/C][C]1.89407[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.2655[/C][C]-0.265507[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]13.2312[/C][C]-1.2312[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]13.0104[/C][C]-4.01038[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.8022[/C][C]-2.80225[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.3649[/C][C]0.635056[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.3517[/C][C]1.64832[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]14.4108[/C][C]-5.41083[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.4715[/C][C]1.52852[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.8295[/C][C]2.17054[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.3975[/C][C]-2.39748[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.4548[/C][C]-3.45482[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.5308[/C][C]0.469175[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.7049[/C][C]1.29511[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.3965[/C][C]-2.3965[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]14.3085[/C][C]-0.308504[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.9004[/C][C]-1.90038[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]14.8022[/C][C]0.197762[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]15.2502[/C][C]-1.25022[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]14.7534[/C][C]1.24664[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.5889[/C][C]1.41107[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.4634[/C][C]0.536559[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.3224[/C][C]0.6776[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.4973[/C][C]0.502713[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.1318[/C][C]0.868228[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]12.8008[/C][C]-1.80083[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]15.2327[/C][C]-1.23266[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.4227[/C][C]2.57734[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.567[/C][C]-1.56698[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]13.3046[/C][C]1.69541[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.3681[/C][C]-2.36809[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.484[/C][C]2.51597[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.4779[/C][C]0.522102[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.0892[/C][C]-3.08921[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.7488[/C][C]-0.748772[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]12.1766[/C][C]-3.17656[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.7809[/C][C]1.21912[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]14.4022[/C][C]2.5978[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]13.0987[/C][C]-0.0987329[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.365[/C][C]0.634999[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.8915[/C][C]1.1085[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.6436[/C][C]-0.643616[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.6779[/C][C]3.32211[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]13.376[/C][C]-0.375953[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.375[/C][C]1.62505[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]12.1571[/C][C]-3.15712[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]15.2519[/C][C]0.748098[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.2904[/C][C]-1.29038[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.7087[/C][C]-3.70866[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]12.2309[/C][C]-1.23094[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.382[/C][C]1.61795[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.8922[/C][C]2.10778[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.5208[/C][C]-0.520843[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.91877[/C][C]-1.91877[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.8836[/C][C]1.1164[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]14.3548[/C][C]-3.35485[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]13.8196[/C][C]2.18041[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]12.287[/C][C]-2.28702[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]15.1584[/C][C]-0.158377[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.55498[/C][C]-0.554982[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.7613[/C][C]1.23873[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]14.0319[/C][C]4.96807[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.7495[/C][C]-1.74947[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.71312[/C][C]-1.71312[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.67[/C][C]-2.67001[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.803[/C][C]0.197025[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]12.5969[/C][C]-3.59693[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]14.71[/C][C]0.290033[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.6212[/C][C]0.378826[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]15.2758[/C][C]0.724246[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.322[/C][C]-2.32202[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]12.1328[/C][C]-0.132826[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13.3655[/C][C]-0.36548[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.4963[/C][C]-4.49627[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.9527[/C][C]-2.95269[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.9861[/C][C]-2.98615[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]11.1329[/C][C]-3.13288[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.627[/C][C]0.372966[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.2048[/C][C]-0.204813[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.6807[/C][C]1.31933[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.7753[/C][C]0.224685[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.8426[/C][C]0.157395[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]9.23805[/C][C]4.76195[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]10.1283[/C][C]-0.128265[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.5913[/C][C]0.408694[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]13.0644[/C][C]1.93558[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]12.0974[/C][C]0.90261[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.3105[/C][C]-1.31052[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.6713[/C][C]-0.671261[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]12.2166[/C][C]-0.216607[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.9655[/C][C]-0.965531[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.8528[/C][C]-1.85278[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.4336[/C][C]-2.43361[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.9878[/C][C]2.0122[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]15.4981[/C][C]-5.49814[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.8082[/C][C]0.191843[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]14.2246[/C][C]0.775416[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]10.0247[/C][C]-3.02474[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.9372[/C][C]0.0628428[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226169&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226169&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
11414.0109-0.0109338
21814.91623.08377
31113.5265-2.52654
41213.7115-1.71149
51610.97695.02307
61814.21073.7893
71410.11933.88069
81414.9989-0.998855
91515.1362-0.136236
101513.91641.08362
111715.12571.87426
121915.43923.56085
131013.1074-3.10743
141613.17042.82959
151815.59972.40033
161413.13490.86511
171413.42720.572841
181715.16451.8355
191414.9937-0.993682
201613.49832.50171
211815.00072.99933
221113.3622-2.36216
231414.069-0.0690442
241213.2612-1.2612
251715.02791.97207
26915.7306-6.73063
271614.59371.40627
281413.23540.764596
291513.53751.46251
301113.7008-2.70079
311615.51770.482298
321312.28620.7138
331714.89642.10356
341515.0423-0.0422763
351413.79210.207882
361615.44530.554666
37910.6074-1.60742
381514.25920.740795
391714.86382.13616
401314.8491-1.84905
411515.3715-0.371531
421613.50652.49348
431615.6330.367034
441212.8949-0.894859
451514.44190.558063
461113.8237-2.82368
471515.5583-0.55833
481514.64930.350742
491713.11283.88719
501314.7493-1.74934
511615.19210.807929
521413.13670.863311
531111.6535-0.65351
541213.5816-1.58165
551213.8861-1.88605
561513.10371.89633
571614.01541.98455
581515.2489-0.248944
591215.051-3.05098
601212.9619-0.961899
61810.2517-2.25175
621314.4095-1.40946
631114.5731-3.57305
641412.91411.08594
651513.42291.57712
661014.9698-4.9698
671112.4133-1.41333
681213.9659-1.96588
691513.84541.15461
701513.48641.5136
711413.69430.305651
721612.63693.36307
731514.25480.745239
741515.2262-0.226223
751314.7965-1.79648
761211.59290.40706
771714.00472.9953
781312.20250.797535
791513.8421.15803
801314.9653-1.96532
811514.77560.224357
821515.5095-0.509463
831614.29451.70552
841514.17090.82912
851413.80870.191257
861513.89351.10647
871414.1785-0.178463
881312.57250.427502
89710.3267-3.32671
901713.72713.27291
911312.8880.112013
921514.09670.903304
931413.16260.837424
941314.0641-1.06413
951614.79311.20692
961212.8054-0.805436
971414.5414-0.541394
981714.88352.11647
991514.9940.0060275
1001715.32971.67031
1011212.7622-0.762235
1021614.841.15999
1031114.369-3.369
1041512.84772.15233
105911.536-2.53596
1061614.85061.14935
1071512.89342.10661
1081012.6834-2.68343
109109.045730.954275
1101513.72391.27608
1111113.181-2.181
1121315.0611-2.06112
1131411.91952.0805
1141814.30563.69444
1151615.46450.535525
1161413.21540.784623
1171413.68120.318797
1181415.2918-1.2918
1191413.62760.37238
1201212.6585-0.65854
1211413.480.520038
1221515.188-0.188007
1231516.163-1.16298
1241514.74310.256869
1251314.905-1.905
1261716.16930.830688
1271715.25671.74334
1281914.77244.22761
1291513.82391.1761
1301314.4241-1.42414
131910.826-1.82598
1321515.0392-0.0392216
1331512.70362.29636
1341514.44970.550288
1351613.70932.29074
136119.121351.87865
1371413.32470.67526
1381112.1719-1.17191
1391514.26230.737749
1401313.9458-0.945751
1411514.34240.6576
1421613.54942.45055
1431414.7323-0.732349
1441514.07730.922718
1451614.87861.12142
1461614.2961.70404
1471113.7049-2.70486
1481214.6482-2.64825
149911.4188-2.41881
1501614.43131.56873
1511312.72040.27959
1521615.22350.776516
1531213.9889-1.98894
154911.3359-2.33594
1551311.85331.14669
1561312.8880.112013
1571413.08080.919187
1581914.77244.22761
1591315.6069-2.60691
1601211.96720.0327746
1611312.5250.474975
162109.179010.820995
1631413.21910.780903
1641611.58574.4143
1651011.875-1.87499
166119.105931.89407
1671414.2655-0.265507
1681213.2312-1.2312
169913.0104-4.01038
170911.8022-2.80225
1711110.36490.635056
1721614.35171.64832
173914.4108-5.41083
1741311.47151.52852
1751613.82952.17054
1761315.3975-2.39748
177912.4548-3.45482
1781211.53080.469175
1791614.70491.29511
1801113.3965-2.3965
1811414.3085-0.308504
1821314.9004-1.90038
1831514.80220.197762
1841415.2502-1.25022
1851614.75341.24664
1861311.58891.41107
1871413.46340.536559
1881514.32240.6776
1891312.49730.502713
1901110.13180.868228
1911112.8008-1.80083
1921415.2327-1.23266
1931512.42272.57734
1941112.567-1.56698
1951513.30461.69541
1961214.3681-2.36809
1971411.4842.51597
1981413.47790.522102
199811.0892-3.08921
2001313.7488-0.748772
201912.1766-3.17656
2021513.78091.21912
2031714.40222.5978
2041313.0987-0.0987329
2051514.3650.634999
2061513.89151.1085
2071414.6436-0.643616
2081612.67793.32211
2091313.376-0.375953
2101614.3751.62505
211912.1571-3.15712
2121615.25190.748098
2131112.2904-1.29038
2141013.7087-3.70866
2151112.2309-1.23094
2161513.3821.61795
2171714.89222.10778
2181414.5208-0.520843
21989.91877-1.91877
2201513.88361.1164
2211114.3548-3.35485
2221613.81962.18041
2231012.287-2.28702
2241515.1584-0.158377
22599.55498-0.554982
2261614.76131.23873
2271914.03194.96807
2281213.7495-1.74947
22989.71312-1.71312
2301113.67-2.67001
2311413.8030.197025
232912.5969-3.59693
2331514.710.290033
2341312.62120.378826
2351615.27580.724246
2361113.322-2.32202
2371212.1328-0.132826
2381313.3655-0.36548
2391014.4963-4.49627
2401113.9527-2.95269
2411214.9861-2.98615
242811.1329-3.13288
2431211.6270.372966
2441212.2048-0.204813
2451513.68071.31933
2461110.77530.224685
2471312.84260.157395
248149.238054.76195
2491010.1283-0.128265
2501211.59130.408694
2511513.06441.93558
2521312.09740.90261
2531314.3105-1.31052
2541313.6713-0.671261
2551212.2166-0.216607
2561212.9655-0.965531
257910.8528-1.85278
258911.4336-2.43361
2591512.98782.0122
2601015.4981-5.49814
2611413.80820.191843
2621514.22460.775416
263710.0247-3.02474
2641413.93720.0628428






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.0238240.04764810.976176
110.005114450.01022890.994886
120.695650.60870.30435
130.941760.1164790.0582397
140.9221270.1557460.0778729
150.9468590.1062830.0531413
160.917180.165640.08282
170.9244290.1511420.0755712
180.8987360.2025280.101264
190.8586180.2827630.141382
200.8565310.2869380.143469
210.8897360.2205280.110264
220.9059340.1881330.0940665
230.8862930.2274130.113707
240.8502870.2994260.149713
250.8212560.3574880.178744
260.9982710.003457370.00172868
270.9973060.005388140.00269407
280.9958330.008333430.00416672
290.9938650.01227080.00613539
300.9954250.009149150.00457458
310.9932710.0134570.00672851
320.9905610.01887840.00943922
330.9888760.02224830.0111242
340.9843470.03130540.0156527
350.9809450.03810910.0190546
360.9742980.05140490.0257024
370.9823470.03530540.0176527
380.9761190.04776180.0238809
390.9739410.0521180.026059
400.9737430.05251430.0262571
410.9660590.0678830.0339415
420.9626030.0747950.0373975
430.9519860.09602790.0480139
440.9442010.1115970.0557985
450.9296350.1407290.0703647
460.9490520.1018960.0509482
470.9357330.1285350.0642674
480.9197210.1605570.0802787
490.9369750.1260490.0630246
500.9371760.1256480.0628241
510.9232750.153450.0767251
520.9064270.1871460.0935731
530.8981850.2036310.101815
540.8849710.2300580.115029
550.8863690.2272610.113631
560.8734180.2531650.126582
570.8617830.2764330.138217
580.8363180.3273650.163682
590.8734330.2531330.126567
600.8625970.2748050.137403
610.8754780.2490450.124522
620.8724020.2551960.127598
630.9202930.1594130.0797067
640.908910.182180.0910898
650.9017050.196590.0982948
660.9624220.07515620.0375781
670.9592710.08145820.0407291
680.958850.08229990.0411499
690.9513230.09735380.0486769
700.9448910.1102180.0551091
710.9328560.1342880.0671438
720.947580.104840.0524201
730.9368280.1263440.0631722
740.9241850.151630.0758152
750.9183720.1632560.0816281
760.9030230.1939540.096977
770.915890.168220.08411
780.9013680.1972650.0986323
790.8895490.2209010.110451
800.8809430.2381150.119057
810.860690.2786210.13931
820.8391350.3217290.160865
830.8297730.3404530.170227
840.8077350.384530.192265
850.7804720.4390570.219528
860.7554540.4890920.244546
870.7248810.5502390.275119
880.6932440.6135120.306756
890.7701980.4596040.229802
900.8011770.3976470.198823
910.7744250.451150.225575
920.74910.50180.2509
930.7237150.552570.276285
940.6997870.6004270.300213
950.6740440.6519120.325956
960.6473370.7053260.352663
970.6158010.7683970.384199
980.6156140.7687720.384386
990.5807820.8384370.419218
1000.5684310.8631380.431569
1010.5418970.9162060.458103
1020.5166070.9667860.483393
1030.561670.8766610.43833
1040.5541060.8917870.445894
1050.5795740.8408520.420426
1060.5546250.890750.445375
1070.5487740.9024510.451226
1080.5807170.8385670.419283
1090.5534540.8930930.446546
1100.5294990.9410020.470501
1110.5346210.9307570.465379
1120.5561770.8876470.443823
1130.549680.9006410.45032
1140.6275450.744910.372455
1150.5966270.8067450.403373
1160.5679060.8641880.432094
1170.5347960.9304090.465204
1180.513630.972740.48637
1190.4804490.9608980.519551
1200.4504310.9008620.549569
1210.4207380.8414760.579262
1220.390730.7814610.60927
1230.3664930.7329860.633507
1240.3348380.6696760.665162
1250.3264280.6528560.673572
1260.2997720.5995430.700228
1270.2929340.5858690.707066
1280.4010790.8021590.598921
1290.3791310.7582620.620869
1300.3634770.7269540.636523
1310.3584280.7168560.641572
1320.3321860.6643720.667814
1330.3450060.6900120.654994
1340.3175230.6350460.682477
1350.329830.6596590.67017
1360.3223810.6447620.677619
1370.295280.5905590.70472
1380.2759450.5518890.724055
1390.2508550.501710.749145
1400.2311060.4622120.768894
1410.2077370.4154750.792263
1420.217350.4346990.78265
1430.1937110.3874220.806289
1440.1755980.3511950.824402
1450.1612380.3224760.838762
1460.158830.317660.84117
1470.1727960.3455910.827204
1480.1857160.3714330.814284
1490.2016530.4033060.798347
1500.1963310.3926610.803669
1510.176680.353360.82332
1520.1603490.3206970.839651
1530.1644190.3288380.835581
1540.174210.348420.82579
1550.1583750.3167510.841625
1560.137880.275760.86212
1570.1234470.2468950.876553
1580.2071360.4142730.792864
1590.2189950.4379890.781005
1600.1988480.3976950.801152
1610.1782110.3564220.821789
1620.1571190.3142380.842881
1630.1386120.2772230.861388
1640.2475910.4951820.752409
1650.2423790.4847580.757621
1660.2335210.4670420.766479
1670.2068340.4136680.793166
1680.1899770.3799540.810023
1690.2544940.5089870.745506
1700.2760460.5520920.723954
1710.2513940.5027890.748606
1720.2486890.4973780.751311
1730.4268950.8537890.573105
1740.4077430.8154860.592257
1750.4201620.8403240.579838
1760.4284510.8569020.571549
1770.487590.975180.51241
1780.4531990.9063980.546801
1790.4317030.8634050.568297
1800.4366970.8733930.563303
1810.3991450.7982890.600855
1820.392490.7849790.60751
1830.3567980.7135970.643202
1840.3301330.6602650.669867
1850.3137510.6275030.686249
1860.3081170.6162330.691883
1870.2797620.5595250.720238
1880.2556680.5113350.744332
1890.2258520.4517040.774148
1900.2056660.4113330.794334
1910.2165540.4331080.783446
1920.1975380.3950750.802462
1930.2291870.4583750.770813
1940.2126030.4252060.787397
1950.2097250.419450.790275
1960.2197560.4395110.780244
1970.286380.572760.71362
1980.2691110.5382210.730889
1990.2973350.594670.702665
2000.2637210.5274420.736279
2010.2946260.5892530.705374
2020.2717280.5434560.728272
2030.3150920.6301840.684908
2040.2839530.5679070.716047
2050.2550250.510050.744975
2060.2357230.4714470.764277
2070.205020.4100410.79498
2080.2304470.4608950.769553
2090.1985050.397010.801495
2100.2210190.4420390.778981
2110.2621010.5242010.737899
2120.2395960.4791930.760404
2130.2116830.4233660.788317
2140.2468110.4936210.753189
2150.217580.435160.78242
2160.2070040.4140070.792996
2170.256920.513840.74308
2180.2275470.4550930.772453
2190.2099530.4199050.790047
2200.2207460.4414910.779254
2210.2358570.4717130.764143
2220.2375280.4750570.762472
2230.2196590.4393180.780341
2240.1851640.3703280.814836
2250.171920.343840.82808
2260.1889190.3778370.811081
2270.3805120.7610240.619488
2280.360770.7215410.63923
2290.3359630.6719270.664037
2300.3260590.6521180.673941
2310.2879870.5759740.712013
2320.3510180.7020370.648982
2330.3062980.6125970.693702
2340.2615240.5230480.738476
2350.2615340.5230680.738466
2360.2362380.4724750.763762
2370.2008850.401770.799115
2380.1604610.3209210.839539
2390.2866980.5733970.713302
2400.2867510.5735020.713249
2410.2554260.5108520.744574
2420.4837630.9675260.516237
2430.4380450.876090.561955
2440.3696690.7393380.630331
2450.4884990.9769970.511501
2460.4077980.8155950.592202
2470.3264290.6528590.673571
2480.512420.9751610.48758
2490.4199320.8398650.580068
2500.3238540.6477080.676146
2510.480630.961260.51937
2520.8903430.2193140.109657
2530.8161920.3676160.183808
2540.6916290.6167420.308371

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.023824 & 0.0476481 & 0.976176 \tabularnewline
11 & 0.00511445 & 0.0102289 & 0.994886 \tabularnewline
12 & 0.69565 & 0.6087 & 0.30435 \tabularnewline
13 & 0.94176 & 0.116479 & 0.0582397 \tabularnewline
14 & 0.922127 & 0.155746 & 0.0778729 \tabularnewline
15 & 0.946859 & 0.106283 & 0.0531413 \tabularnewline
16 & 0.91718 & 0.16564 & 0.08282 \tabularnewline
17 & 0.924429 & 0.151142 & 0.0755712 \tabularnewline
18 & 0.898736 & 0.202528 & 0.101264 \tabularnewline
19 & 0.858618 & 0.282763 & 0.141382 \tabularnewline
20 & 0.856531 & 0.286938 & 0.143469 \tabularnewline
21 & 0.889736 & 0.220528 & 0.110264 \tabularnewline
22 & 0.905934 & 0.188133 & 0.0940665 \tabularnewline
23 & 0.886293 & 0.227413 & 0.113707 \tabularnewline
24 & 0.850287 & 0.299426 & 0.149713 \tabularnewline
25 & 0.821256 & 0.357488 & 0.178744 \tabularnewline
26 & 0.998271 & 0.00345737 & 0.00172868 \tabularnewline
27 & 0.997306 & 0.00538814 & 0.00269407 \tabularnewline
28 & 0.995833 & 0.00833343 & 0.00416672 \tabularnewline
29 & 0.993865 & 0.0122708 & 0.00613539 \tabularnewline
30 & 0.995425 & 0.00914915 & 0.00457458 \tabularnewline
31 & 0.993271 & 0.013457 & 0.00672851 \tabularnewline
32 & 0.990561 & 0.0188784 & 0.00943922 \tabularnewline
33 & 0.988876 & 0.0222483 & 0.0111242 \tabularnewline
34 & 0.984347 & 0.0313054 & 0.0156527 \tabularnewline
35 & 0.980945 & 0.0381091 & 0.0190546 \tabularnewline
36 & 0.974298 & 0.0514049 & 0.0257024 \tabularnewline
37 & 0.982347 & 0.0353054 & 0.0176527 \tabularnewline
38 & 0.976119 & 0.0477618 & 0.0238809 \tabularnewline
39 & 0.973941 & 0.052118 & 0.026059 \tabularnewline
40 & 0.973743 & 0.0525143 & 0.0262571 \tabularnewline
41 & 0.966059 & 0.067883 & 0.0339415 \tabularnewline
42 & 0.962603 & 0.074795 & 0.0373975 \tabularnewline
43 & 0.951986 & 0.0960279 & 0.0480139 \tabularnewline
44 & 0.944201 & 0.111597 & 0.0557985 \tabularnewline
45 & 0.929635 & 0.140729 & 0.0703647 \tabularnewline
46 & 0.949052 & 0.101896 & 0.0509482 \tabularnewline
47 & 0.935733 & 0.128535 & 0.0642674 \tabularnewline
48 & 0.919721 & 0.160557 & 0.0802787 \tabularnewline
49 & 0.936975 & 0.126049 & 0.0630246 \tabularnewline
50 & 0.937176 & 0.125648 & 0.0628241 \tabularnewline
51 & 0.923275 & 0.15345 & 0.0767251 \tabularnewline
52 & 0.906427 & 0.187146 & 0.0935731 \tabularnewline
53 & 0.898185 & 0.203631 & 0.101815 \tabularnewline
54 & 0.884971 & 0.230058 & 0.115029 \tabularnewline
55 & 0.886369 & 0.227261 & 0.113631 \tabularnewline
56 & 0.873418 & 0.253165 & 0.126582 \tabularnewline
57 & 0.861783 & 0.276433 & 0.138217 \tabularnewline
58 & 0.836318 & 0.327365 & 0.163682 \tabularnewline
59 & 0.873433 & 0.253133 & 0.126567 \tabularnewline
60 & 0.862597 & 0.274805 & 0.137403 \tabularnewline
61 & 0.875478 & 0.249045 & 0.124522 \tabularnewline
62 & 0.872402 & 0.255196 & 0.127598 \tabularnewline
63 & 0.920293 & 0.159413 & 0.0797067 \tabularnewline
64 & 0.90891 & 0.18218 & 0.0910898 \tabularnewline
65 & 0.901705 & 0.19659 & 0.0982948 \tabularnewline
66 & 0.962422 & 0.0751562 & 0.0375781 \tabularnewline
67 & 0.959271 & 0.0814582 & 0.0407291 \tabularnewline
68 & 0.95885 & 0.0822999 & 0.0411499 \tabularnewline
69 & 0.951323 & 0.0973538 & 0.0486769 \tabularnewline
70 & 0.944891 & 0.110218 & 0.0551091 \tabularnewline
71 & 0.932856 & 0.134288 & 0.0671438 \tabularnewline
72 & 0.94758 & 0.10484 & 0.0524201 \tabularnewline
73 & 0.936828 & 0.126344 & 0.0631722 \tabularnewline
74 & 0.924185 & 0.15163 & 0.0758152 \tabularnewline
75 & 0.918372 & 0.163256 & 0.0816281 \tabularnewline
76 & 0.903023 & 0.193954 & 0.096977 \tabularnewline
77 & 0.91589 & 0.16822 & 0.08411 \tabularnewline
78 & 0.901368 & 0.197265 & 0.0986323 \tabularnewline
79 & 0.889549 & 0.220901 & 0.110451 \tabularnewline
80 & 0.880943 & 0.238115 & 0.119057 \tabularnewline
81 & 0.86069 & 0.278621 & 0.13931 \tabularnewline
82 & 0.839135 & 0.321729 & 0.160865 \tabularnewline
83 & 0.829773 & 0.340453 & 0.170227 \tabularnewline
84 & 0.807735 & 0.38453 & 0.192265 \tabularnewline
85 & 0.780472 & 0.439057 & 0.219528 \tabularnewline
86 & 0.755454 & 0.489092 & 0.244546 \tabularnewline
87 & 0.724881 & 0.550239 & 0.275119 \tabularnewline
88 & 0.693244 & 0.613512 & 0.306756 \tabularnewline
89 & 0.770198 & 0.459604 & 0.229802 \tabularnewline
90 & 0.801177 & 0.397647 & 0.198823 \tabularnewline
91 & 0.774425 & 0.45115 & 0.225575 \tabularnewline
92 & 0.7491 & 0.5018 & 0.2509 \tabularnewline
93 & 0.723715 & 0.55257 & 0.276285 \tabularnewline
94 & 0.699787 & 0.600427 & 0.300213 \tabularnewline
95 & 0.674044 & 0.651912 & 0.325956 \tabularnewline
96 & 0.647337 & 0.705326 & 0.352663 \tabularnewline
97 & 0.615801 & 0.768397 & 0.384199 \tabularnewline
98 & 0.615614 & 0.768772 & 0.384386 \tabularnewline
99 & 0.580782 & 0.838437 & 0.419218 \tabularnewline
100 & 0.568431 & 0.863138 & 0.431569 \tabularnewline
101 & 0.541897 & 0.916206 & 0.458103 \tabularnewline
102 & 0.516607 & 0.966786 & 0.483393 \tabularnewline
103 & 0.56167 & 0.876661 & 0.43833 \tabularnewline
104 & 0.554106 & 0.891787 & 0.445894 \tabularnewline
105 & 0.579574 & 0.840852 & 0.420426 \tabularnewline
106 & 0.554625 & 0.89075 & 0.445375 \tabularnewline
107 & 0.548774 & 0.902451 & 0.451226 \tabularnewline
108 & 0.580717 & 0.838567 & 0.419283 \tabularnewline
109 & 0.553454 & 0.893093 & 0.446546 \tabularnewline
110 & 0.529499 & 0.941002 & 0.470501 \tabularnewline
111 & 0.534621 & 0.930757 & 0.465379 \tabularnewline
112 & 0.556177 & 0.887647 & 0.443823 \tabularnewline
113 & 0.54968 & 0.900641 & 0.45032 \tabularnewline
114 & 0.627545 & 0.74491 & 0.372455 \tabularnewline
115 & 0.596627 & 0.806745 & 0.403373 \tabularnewline
116 & 0.567906 & 0.864188 & 0.432094 \tabularnewline
117 & 0.534796 & 0.930409 & 0.465204 \tabularnewline
118 & 0.51363 & 0.97274 & 0.48637 \tabularnewline
119 & 0.480449 & 0.960898 & 0.519551 \tabularnewline
120 & 0.450431 & 0.900862 & 0.549569 \tabularnewline
121 & 0.420738 & 0.841476 & 0.579262 \tabularnewline
122 & 0.39073 & 0.781461 & 0.60927 \tabularnewline
123 & 0.366493 & 0.732986 & 0.633507 \tabularnewline
124 & 0.334838 & 0.669676 & 0.665162 \tabularnewline
125 & 0.326428 & 0.652856 & 0.673572 \tabularnewline
126 & 0.299772 & 0.599543 & 0.700228 \tabularnewline
127 & 0.292934 & 0.585869 & 0.707066 \tabularnewline
128 & 0.401079 & 0.802159 & 0.598921 \tabularnewline
129 & 0.379131 & 0.758262 & 0.620869 \tabularnewline
130 & 0.363477 & 0.726954 & 0.636523 \tabularnewline
131 & 0.358428 & 0.716856 & 0.641572 \tabularnewline
132 & 0.332186 & 0.664372 & 0.667814 \tabularnewline
133 & 0.345006 & 0.690012 & 0.654994 \tabularnewline
134 & 0.317523 & 0.635046 & 0.682477 \tabularnewline
135 & 0.32983 & 0.659659 & 0.67017 \tabularnewline
136 & 0.322381 & 0.644762 & 0.677619 \tabularnewline
137 & 0.29528 & 0.590559 & 0.70472 \tabularnewline
138 & 0.275945 & 0.551889 & 0.724055 \tabularnewline
139 & 0.250855 & 0.50171 & 0.749145 \tabularnewline
140 & 0.231106 & 0.462212 & 0.768894 \tabularnewline
141 & 0.207737 & 0.415475 & 0.792263 \tabularnewline
142 & 0.21735 & 0.434699 & 0.78265 \tabularnewline
143 & 0.193711 & 0.387422 & 0.806289 \tabularnewline
144 & 0.175598 & 0.351195 & 0.824402 \tabularnewline
145 & 0.161238 & 0.322476 & 0.838762 \tabularnewline
146 & 0.15883 & 0.31766 & 0.84117 \tabularnewline
147 & 0.172796 & 0.345591 & 0.827204 \tabularnewline
148 & 0.185716 & 0.371433 & 0.814284 \tabularnewline
149 & 0.201653 & 0.403306 & 0.798347 \tabularnewline
150 & 0.196331 & 0.392661 & 0.803669 \tabularnewline
151 & 0.17668 & 0.35336 & 0.82332 \tabularnewline
152 & 0.160349 & 0.320697 & 0.839651 \tabularnewline
153 & 0.164419 & 0.328838 & 0.835581 \tabularnewline
154 & 0.17421 & 0.34842 & 0.82579 \tabularnewline
155 & 0.158375 & 0.316751 & 0.841625 \tabularnewline
156 & 0.13788 & 0.27576 & 0.86212 \tabularnewline
157 & 0.123447 & 0.246895 & 0.876553 \tabularnewline
158 & 0.207136 & 0.414273 & 0.792864 \tabularnewline
159 & 0.218995 & 0.437989 & 0.781005 \tabularnewline
160 & 0.198848 & 0.397695 & 0.801152 \tabularnewline
161 & 0.178211 & 0.356422 & 0.821789 \tabularnewline
162 & 0.157119 & 0.314238 & 0.842881 \tabularnewline
163 & 0.138612 & 0.277223 & 0.861388 \tabularnewline
164 & 0.247591 & 0.495182 & 0.752409 \tabularnewline
165 & 0.242379 & 0.484758 & 0.757621 \tabularnewline
166 & 0.233521 & 0.467042 & 0.766479 \tabularnewline
167 & 0.206834 & 0.413668 & 0.793166 \tabularnewline
168 & 0.189977 & 0.379954 & 0.810023 \tabularnewline
169 & 0.254494 & 0.508987 & 0.745506 \tabularnewline
170 & 0.276046 & 0.552092 & 0.723954 \tabularnewline
171 & 0.251394 & 0.502789 & 0.748606 \tabularnewline
172 & 0.248689 & 0.497378 & 0.751311 \tabularnewline
173 & 0.426895 & 0.853789 & 0.573105 \tabularnewline
174 & 0.407743 & 0.815486 & 0.592257 \tabularnewline
175 & 0.420162 & 0.840324 & 0.579838 \tabularnewline
176 & 0.428451 & 0.856902 & 0.571549 \tabularnewline
177 & 0.48759 & 0.97518 & 0.51241 \tabularnewline
178 & 0.453199 & 0.906398 & 0.546801 \tabularnewline
179 & 0.431703 & 0.863405 & 0.568297 \tabularnewline
180 & 0.436697 & 0.873393 & 0.563303 \tabularnewline
181 & 0.399145 & 0.798289 & 0.600855 \tabularnewline
182 & 0.39249 & 0.784979 & 0.60751 \tabularnewline
183 & 0.356798 & 0.713597 & 0.643202 \tabularnewline
184 & 0.330133 & 0.660265 & 0.669867 \tabularnewline
185 & 0.313751 & 0.627503 & 0.686249 \tabularnewline
186 & 0.308117 & 0.616233 & 0.691883 \tabularnewline
187 & 0.279762 & 0.559525 & 0.720238 \tabularnewline
188 & 0.255668 & 0.511335 & 0.744332 \tabularnewline
189 & 0.225852 & 0.451704 & 0.774148 \tabularnewline
190 & 0.205666 & 0.411333 & 0.794334 \tabularnewline
191 & 0.216554 & 0.433108 & 0.783446 \tabularnewline
192 & 0.197538 & 0.395075 & 0.802462 \tabularnewline
193 & 0.229187 & 0.458375 & 0.770813 \tabularnewline
194 & 0.212603 & 0.425206 & 0.787397 \tabularnewline
195 & 0.209725 & 0.41945 & 0.790275 \tabularnewline
196 & 0.219756 & 0.439511 & 0.780244 \tabularnewline
197 & 0.28638 & 0.57276 & 0.71362 \tabularnewline
198 & 0.269111 & 0.538221 & 0.730889 \tabularnewline
199 & 0.297335 & 0.59467 & 0.702665 \tabularnewline
200 & 0.263721 & 0.527442 & 0.736279 \tabularnewline
201 & 0.294626 & 0.589253 & 0.705374 \tabularnewline
202 & 0.271728 & 0.543456 & 0.728272 \tabularnewline
203 & 0.315092 & 0.630184 & 0.684908 \tabularnewline
204 & 0.283953 & 0.567907 & 0.716047 \tabularnewline
205 & 0.255025 & 0.51005 & 0.744975 \tabularnewline
206 & 0.235723 & 0.471447 & 0.764277 \tabularnewline
207 & 0.20502 & 0.410041 & 0.79498 \tabularnewline
208 & 0.230447 & 0.460895 & 0.769553 \tabularnewline
209 & 0.198505 & 0.39701 & 0.801495 \tabularnewline
210 & 0.221019 & 0.442039 & 0.778981 \tabularnewline
211 & 0.262101 & 0.524201 & 0.737899 \tabularnewline
212 & 0.239596 & 0.479193 & 0.760404 \tabularnewline
213 & 0.211683 & 0.423366 & 0.788317 \tabularnewline
214 & 0.246811 & 0.493621 & 0.753189 \tabularnewline
215 & 0.21758 & 0.43516 & 0.78242 \tabularnewline
216 & 0.207004 & 0.414007 & 0.792996 \tabularnewline
217 & 0.25692 & 0.51384 & 0.74308 \tabularnewline
218 & 0.227547 & 0.455093 & 0.772453 \tabularnewline
219 & 0.209953 & 0.419905 & 0.790047 \tabularnewline
220 & 0.220746 & 0.441491 & 0.779254 \tabularnewline
221 & 0.235857 & 0.471713 & 0.764143 \tabularnewline
222 & 0.237528 & 0.475057 & 0.762472 \tabularnewline
223 & 0.219659 & 0.439318 & 0.780341 \tabularnewline
224 & 0.185164 & 0.370328 & 0.814836 \tabularnewline
225 & 0.17192 & 0.34384 & 0.82808 \tabularnewline
226 & 0.188919 & 0.377837 & 0.811081 \tabularnewline
227 & 0.380512 & 0.761024 & 0.619488 \tabularnewline
228 & 0.36077 & 0.721541 & 0.63923 \tabularnewline
229 & 0.335963 & 0.671927 & 0.664037 \tabularnewline
230 & 0.326059 & 0.652118 & 0.673941 \tabularnewline
231 & 0.287987 & 0.575974 & 0.712013 \tabularnewline
232 & 0.351018 & 0.702037 & 0.648982 \tabularnewline
233 & 0.306298 & 0.612597 & 0.693702 \tabularnewline
234 & 0.261524 & 0.523048 & 0.738476 \tabularnewline
235 & 0.261534 & 0.523068 & 0.738466 \tabularnewline
236 & 0.236238 & 0.472475 & 0.763762 \tabularnewline
237 & 0.200885 & 0.40177 & 0.799115 \tabularnewline
238 & 0.160461 & 0.320921 & 0.839539 \tabularnewline
239 & 0.286698 & 0.573397 & 0.713302 \tabularnewline
240 & 0.286751 & 0.573502 & 0.713249 \tabularnewline
241 & 0.255426 & 0.510852 & 0.744574 \tabularnewline
242 & 0.483763 & 0.967526 & 0.516237 \tabularnewline
243 & 0.438045 & 0.87609 & 0.561955 \tabularnewline
244 & 0.369669 & 0.739338 & 0.630331 \tabularnewline
245 & 0.488499 & 0.976997 & 0.511501 \tabularnewline
246 & 0.407798 & 0.815595 & 0.592202 \tabularnewline
247 & 0.326429 & 0.652859 & 0.673571 \tabularnewline
248 & 0.51242 & 0.975161 & 0.48758 \tabularnewline
249 & 0.419932 & 0.839865 & 0.580068 \tabularnewline
250 & 0.323854 & 0.647708 & 0.676146 \tabularnewline
251 & 0.48063 & 0.96126 & 0.51937 \tabularnewline
252 & 0.890343 & 0.219314 & 0.109657 \tabularnewline
253 & 0.816192 & 0.367616 & 0.183808 \tabularnewline
254 & 0.691629 & 0.616742 & 0.308371 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226169&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]10[/C][C]0.023824[/C][C]0.0476481[/C][C]0.976176[/C][/ROW]
[ROW][C]11[/C][C]0.00511445[/C][C]0.0102289[/C][C]0.994886[/C][/ROW]
[ROW][C]12[/C][C]0.69565[/C][C]0.6087[/C][C]0.30435[/C][/ROW]
[ROW][C]13[/C][C]0.94176[/C][C]0.116479[/C][C]0.0582397[/C][/ROW]
[ROW][C]14[/C][C]0.922127[/C][C]0.155746[/C][C]0.0778729[/C][/ROW]
[ROW][C]15[/C][C]0.946859[/C][C]0.106283[/C][C]0.0531413[/C][/ROW]
[ROW][C]16[/C][C]0.91718[/C][C]0.16564[/C][C]0.08282[/C][/ROW]
[ROW][C]17[/C][C]0.924429[/C][C]0.151142[/C][C]0.0755712[/C][/ROW]
[ROW][C]18[/C][C]0.898736[/C][C]0.202528[/C][C]0.101264[/C][/ROW]
[ROW][C]19[/C][C]0.858618[/C][C]0.282763[/C][C]0.141382[/C][/ROW]
[ROW][C]20[/C][C]0.856531[/C][C]0.286938[/C][C]0.143469[/C][/ROW]
[ROW][C]21[/C][C]0.889736[/C][C]0.220528[/C][C]0.110264[/C][/ROW]
[ROW][C]22[/C][C]0.905934[/C][C]0.188133[/C][C]0.0940665[/C][/ROW]
[ROW][C]23[/C][C]0.886293[/C][C]0.227413[/C][C]0.113707[/C][/ROW]
[ROW][C]24[/C][C]0.850287[/C][C]0.299426[/C][C]0.149713[/C][/ROW]
[ROW][C]25[/C][C]0.821256[/C][C]0.357488[/C][C]0.178744[/C][/ROW]
[ROW][C]26[/C][C]0.998271[/C][C]0.00345737[/C][C]0.00172868[/C][/ROW]
[ROW][C]27[/C][C]0.997306[/C][C]0.00538814[/C][C]0.00269407[/C][/ROW]
[ROW][C]28[/C][C]0.995833[/C][C]0.00833343[/C][C]0.00416672[/C][/ROW]
[ROW][C]29[/C][C]0.993865[/C][C]0.0122708[/C][C]0.00613539[/C][/ROW]
[ROW][C]30[/C][C]0.995425[/C][C]0.00914915[/C][C]0.00457458[/C][/ROW]
[ROW][C]31[/C][C]0.993271[/C][C]0.013457[/C][C]0.00672851[/C][/ROW]
[ROW][C]32[/C][C]0.990561[/C][C]0.0188784[/C][C]0.00943922[/C][/ROW]
[ROW][C]33[/C][C]0.988876[/C][C]0.0222483[/C][C]0.0111242[/C][/ROW]
[ROW][C]34[/C][C]0.984347[/C][C]0.0313054[/C][C]0.0156527[/C][/ROW]
[ROW][C]35[/C][C]0.980945[/C][C]0.0381091[/C][C]0.0190546[/C][/ROW]
[ROW][C]36[/C][C]0.974298[/C][C]0.0514049[/C][C]0.0257024[/C][/ROW]
[ROW][C]37[/C][C]0.982347[/C][C]0.0353054[/C][C]0.0176527[/C][/ROW]
[ROW][C]38[/C][C]0.976119[/C][C]0.0477618[/C][C]0.0238809[/C][/ROW]
[ROW][C]39[/C][C]0.973941[/C][C]0.052118[/C][C]0.026059[/C][/ROW]
[ROW][C]40[/C][C]0.973743[/C][C]0.0525143[/C][C]0.0262571[/C][/ROW]
[ROW][C]41[/C][C]0.966059[/C][C]0.067883[/C][C]0.0339415[/C][/ROW]
[ROW][C]42[/C][C]0.962603[/C][C]0.074795[/C][C]0.0373975[/C][/ROW]
[ROW][C]43[/C][C]0.951986[/C][C]0.0960279[/C][C]0.0480139[/C][/ROW]
[ROW][C]44[/C][C]0.944201[/C][C]0.111597[/C][C]0.0557985[/C][/ROW]
[ROW][C]45[/C][C]0.929635[/C][C]0.140729[/C][C]0.0703647[/C][/ROW]
[ROW][C]46[/C][C]0.949052[/C][C]0.101896[/C][C]0.0509482[/C][/ROW]
[ROW][C]47[/C][C]0.935733[/C][C]0.128535[/C][C]0.0642674[/C][/ROW]
[ROW][C]48[/C][C]0.919721[/C][C]0.160557[/C][C]0.0802787[/C][/ROW]
[ROW][C]49[/C][C]0.936975[/C][C]0.126049[/C][C]0.0630246[/C][/ROW]
[ROW][C]50[/C][C]0.937176[/C][C]0.125648[/C][C]0.0628241[/C][/ROW]
[ROW][C]51[/C][C]0.923275[/C][C]0.15345[/C][C]0.0767251[/C][/ROW]
[ROW][C]52[/C][C]0.906427[/C][C]0.187146[/C][C]0.0935731[/C][/ROW]
[ROW][C]53[/C][C]0.898185[/C][C]0.203631[/C][C]0.101815[/C][/ROW]
[ROW][C]54[/C][C]0.884971[/C][C]0.230058[/C][C]0.115029[/C][/ROW]
[ROW][C]55[/C][C]0.886369[/C][C]0.227261[/C][C]0.113631[/C][/ROW]
[ROW][C]56[/C][C]0.873418[/C][C]0.253165[/C][C]0.126582[/C][/ROW]
[ROW][C]57[/C][C]0.861783[/C][C]0.276433[/C][C]0.138217[/C][/ROW]
[ROW][C]58[/C][C]0.836318[/C][C]0.327365[/C][C]0.163682[/C][/ROW]
[ROW][C]59[/C][C]0.873433[/C][C]0.253133[/C][C]0.126567[/C][/ROW]
[ROW][C]60[/C][C]0.862597[/C][C]0.274805[/C][C]0.137403[/C][/ROW]
[ROW][C]61[/C][C]0.875478[/C][C]0.249045[/C][C]0.124522[/C][/ROW]
[ROW][C]62[/C][C]0.872402[/C][C]0.255196[/C][C]0.127598[/C][/ROW]
[ROW][C]63[/C][C]0.920293[/C][C]0.159413[/C][C]0.0797067[/C][/ROW]
[ROW][C]64[/C][C]0.90891[/C][C]0.18218[/C][C]0.0910898[/C][/ROW]
[ROW][C]65[/C][C]0.901705[/C][C]0.19659[/C][C]0.0982948[/C][/ROW]
[ROW][C]66[/C][C]0.962422[/C][C]0.0751562[/C][C]0.0375781[/C][/ROW]
[ROW][C]67[/C][C]0.959271[/C][C]0.0814582[/C][C]0.0407291[/C][/ROW]
[ROW][C]68[/C][C]0.95885[/C][C]0.0822999[/C][C]0.0411499[/C][/ROW]
[ROW][C]69[/C][C]0.951323[/C][C]0.0973538[/C][C]0.0486769[/C][/ROW]
[ROW][C]70[/C][C]0.944891[/C][C]0.110218[/C][C]0.0551091[/C][/ROW]
[ROW][C]71[/C][C]0.932856[/C][C]0.134288[/C][C]0.0671438[/C][/ROW]
[ROW][C]72[/C][C]0.94758[/C][C]0.10484[/C][C]0.0524201[/C][/ROW]
[ROW][C]73[/C][C]0.936828[/C][C]0.126344[/C][C]0.0631722[/C][/ROW]
[ROW][C]74[/C][C]0.924185[/C][C]0.15163[/C][C]0.0758152[/C][/ROW]
[ROW][C]75[/C][C]0.918372[/C][C]0.163256[/C][C]0.0816281[/C][/ROW]
[ROW][C]76[/C][C]0.903023[/C][C]0.193954[/C][C]0.096977[/C][/ROW]
[ROW][C]77[/C][C]0.91589[/C][C]0.16822[/C][C]0.08411[/C][/ROW]
[ROW][C]78[/C][C]0.901368[/C][C]0.197265[/C][C]0.0986323[/C][/ROW]
[ROW][C]79[/C][C]0.889549[/C][C]0.220901[/C][C]0.110451[/C][/ROW]
[ROW][C]80[/C][C]0.880943[/C][C]0.238115[/C][C]0.119057[/C][/ROW]
[ROW][C]81[/C][C]0.86069[/C][C]0.278621[/C][C]0.13931[/C][/ROW]
[ROW][C]82[/C][C]0.839135[/C][C]0.321729[/C][C]0.160865[/C][/ROW]
[ROW][C]83[/C][C]0.829773[/C][C]0.340453[/C][C]0.170227[/C][/ROW]
[ROW][C]84[/C][C]0.807735[/C][C]0.38453[/C][C]0.192265[/C][/ROW]
[ROW][C]85[/C][C]0.780472[/C][C]0.439057[/C][C]0.219528[/C][/ROW]
[ROW][C]86[/C][C]0.755454[/C][C]0.489092[/C][C]0.244546[/C][/ROW]
[ROW][C]87[/C][C]0.724881[/C][C]0.550239[/C][C]0.275119[/C][/ROW]
[ROW][C]88[/C][C]0.693244[/C][C]0.613512[/C][C]0.306756[/C][/ROW]
[ROW][C]89[/C][C]0.770198[/C][C]0.459604[/C][C]0.229802[/C][/ROW]
[ROW][C]90[/C][C]0.801177[/C][C]0.397647[/C][C]0.198823[/C][/ROW]
[ROW][C]91[/C][C]0.774425[/C][C]0.45115[/C][C]0.225575[/C][/ROW]
[ROW][C]92[/C][C]0.7491[/C][C]0.5018[/C][C]0.2509[/C][/ROW]
[ROW][C]93[/C][C]0.723715[/C][C]0.55257[/C][C]0.276285[/C][/ROW]
[ROW][C]94[/C][C]0.699787[/C][C]0.600427[/C][C]0.300213[/C][/ROW]
[ROW][C]95[/C][C]0.674044[/C][C]0.651912[/C][C]0.325956[/C][/ROW]
[ROW][C]96[/C][C]0.647337[/C][C]0.705326[/C][C]0.352663[/C][/ROW]
[ROW][C]97[/C][C]0.615801[/C][C]0.768397[/C][C]0.384199[/C][/ROW]
[ROW][C]98[/C][C]0.615614[/C][C]0.768772[/C][C]0.384386[/C][/ROW]
[ROW][C]99[/C][C]0.580782[/C][C]0.838437[/C][C]0.419218[/C][/ROW]
[ROW][C]100[/C][C]0.568431[/C][C]0.863138[/C][C]0.431569[/C][/ROW]
[ROW][C]101[/C][C]0.541897[/C][C]0.916206[/C][C]0.458103[/C][/ROW]
[ROW][C]102[/C][C]0.516607[/C][C]0.966786[/C][C]0.483393[/C][/ROW]
[ROW][C]103[/C][C]0.56167[/C][C]0.876661[/C][C]0.43833[/C][/ROW]
[ROW][C]104[/C][C]0.554106[/C][C]0.891787[/C][C]0.445894[/C][/ROW]
[ROW][C]105[/C][C]0.579574[/C][C]0.840852[/C][C]0.420426[/C][/ROW]
[ROW][C]106[/C][C]0.554625[/C][C]0.89075[/C][C]0.445375[/C][/ROW]
[ROW][C]107[/C][C]0.548774[/C][C]0.902451[/C][C]0.451226[/C][/ROW]
[ROW][C]108[/C][C]0.580717[/C][C]0.838567[/C][C]0.419283[/C][/ROW]
[ROW][C]109[/C][C]0.553454[/C][C]0.893093[/C][C]0.446546[/C][/ROW]
[ROW][C]110[/C][C]0.529499[/C][C]0.941002[/C][C]0.470501[/C][/ROW]
[ROW][C]111[/C][C]0.534621[/C][C]0.930757[/C][C]0.465379[/C][/ROW]
[ROW][C]112[/C][C]0.556177[/C][C]0.887647[/C][C]0.443823[/C][/ROW]
[ROW][C]113[/C][C]0.54968[/C][C]0.900641[/C][C]0.45032[/C][/ROW]
[ROW][C]114[/C][C]0.627545[/C][C]0.74491[/C][C]0.372455[/C][/ROW]
[ROW][C]115[/C][C]0.596627[/C][C]0.806745[/C][C]0.403373[/C][/ROW]
[ROW][C]116[/C][C]0.567906[/C][C]0.864188[/C][C]0.432094[/C][/ROW]
[ROW][C]117[/C][C]0.534796[/C][C]0.930409[/C][C]0.465204[/C][/ROW]
[ROW][C]118[/C][C]0.51363[/C][C]0.97274[/C][C]0.48637[/C][/ROW]
[ROW][C]119[/C][C]0.480449[/C][C]0.960898[/C][C]0.519551[/C][/ROW]
[ROW][C]120[/C][C]0.450431[/C][C]0.900862[/C][C]0.549569[/C][/ROW]
[ROW][C]121[/C][C]0.420738[/C][C]0.841476[/C][C]0.579262[/C][/ROW]
[ROW][C]122[/C][C]0.39073[/C][C]0.781461[/C][C]0.60927[/C][/ROW]
[ROW][C]123[/C][C]0.366493[/C][C]0.732986[/C][C]0.633507[/C][/ROW]
[ROW][C]124[/C][C]0.334838[/C][C]0.669676[/C][C]0.665162[/C][/ROW]
[ROW][C]125[/C][C]0.326428[/C][C]0.652856[/C][C]0.673572[/C][/ROW]
[ROW][C]126[/C][C]0.299772[/C][C]0.599543[/C][C]0.700228[/C][/ROW]
[ROW][C]127[/C][C]0.292934[/C][C]0.585869[/C][C]0.707066[/C][/ROW]
[ROW][C]128[/C][C]0.401079[/C][C]0.802159[/C][C]0.598921[/C][/ROW]
[ROW][C]129[/C][C]0.379131[/C][C]0.758262[/C][C]0.620869[/C][/ROW]
[ROW][C]130[/C][C]0.363477[/C][C]0.726954[/C][C]0.636523[/C][/ROW]
[ROW][C]131[/C][C]0.358428[/C][C]0.716856[/C][C]0.641572[/C][/ROW]
[ROW][C]132[/C][C]0.332186[/C][C]0.664372[/C][C]0.667814[/C][/ROW]
[ROW][C]133[/C][C]0.345006[/C][C]0.690012[/C][C]0.654994[/C][/ROW]
[ROW][C]134[/C][C]0.317523[/C][C]0.635046[/C][C]0.682477[/C][/ROW]
[ROW][C]135[/C][C]0.32983[/C][C]0.659659[/C][C]0.67017[/C][/ROW]
[ROW][C]136[/C][C]0.322381[/C][C]0.644762[/C][C]0.677619[/C][/ROW]
[ROW][C]137[/C][C]0.29528[/C][C]0.590559[/C][C]0.70472[/C][/ROW]
[ROW][C]138[/C][C]0.275945[/C][C]0.551889[/C][C]0.724055[/C][/ROW]
[ROW][C]139[/C][C]0.250855[/C][C]0.50171[/C][C]0.749145[/C][/ROW]
[ROW][C]140[/C][C]0.231106[/C][C]0.462212[/C][C]0.768894[/C][/ROW]
[ROW][C]141[/C][C]0.207737[/C][C]0.415475[/C][C]0.792263[/C][/ROW]
[ROW][C]142[/C][C]0.21735[/C][C]0.434699[/C][C]0.78265[/C][/ROW]
[ROW][C]143[/C][C]0.193711[/C][C]0.387422[/C][C]0.806289[/C][/ROW]
[ROW][C]144[/C][C]0.175598[/C][C]0.351195[/C][C]0.824402[/C][/ROW]
[ROW][C]145[/C][C]0.161238[/C][C]0.322476[/C][C]0.838762[/C][/ROW]
[ROW][C]146[/C][C]0.15883[/C][C]0.31766[/C][C]0.84117[/C][/ROW]
[ROW][C]147[/C][C]0.172796[/C][C]0.345591[/C][C]0.827204[/C][/ROW]
[ROW][C]148[/C][C]0.185716[/C][C]0.371433[/C][C]0.814284[/C][/ROW]
[ROW][C]149[/C][C]0.201653[/C][C]0.403306[/C][C]0.798347[/C][/ROW]
[ROW][C]150[/C][C]0.196331[/C][C]0.392661[/C][C]0.803669[/C][/ROW]
[ROW][C]151[/C][C]0.17668[/C][C]0.35336[/C][C]0.82332[/C][/ROW]
[ROW][C]152[/C][C]0.160349[/C][C]0.320697[/C][C]0.839651[/C][/ROW]
[ROW][C]153[/C][C]0.164419[/C][C]0.328838[/C][C]0.835581[/C][/ROW]
[ROW][C]154[/C][C]0.17421[/C][C]0.34842[/C][C]0.82579[/C][/ROW]
[ROW][C]155[/C][C]0.158375[/C][C]0.316751[/C][C]0.841625[/C][/ROW]
[ROW][C]156[/C][C]0.13788[/C][C]0.27576[/C][C]0.86212[/C][/ROW]
[ROW][C]157[/C][C]0.123447[/C][C]0.246895[/C][C]0.876553[/C][/ROW]
[ROW][C]158[/C][C]0.207136[/C][C]0.414273[/C][C]0.792864[/C][/ROW]
[ROW][C]159[/C][C]0.218995[/C][C]0.437989[/C][C]0.781005[/C][/ROW]
[ROW][C]160[/C][C]0.198848[/C][C]0.397695[/C][C]0.801152[/C][/ROW]
[ROW][C]161[/C][C]0.178211[/C][C]0.356422[/C][C]0.821789[/C][/ROW]
[ROW][C]162[/C][C]0.157119[/C][C]0.314238[/C][C]0.842881[/C][/ROW]
[ROW][C]163[/C][C]0.138612[/C][C]0.277223[/C][C]0.861388[/C][/ROW]
[ROW][C]164[/C][C]0.247591[/C][C]0.495182[/C][C]0.752409[/C][/ROW]
[ROW][C]165[/C][C]0.242379[/C][C]0.484758[/C][C]0.757621[/C][/ROW]
[ROW][C]166[/C][C]0.233521[/C][C]0.467042[/C][C]0.766479[/C][/ROW]
[ROW][C]167[/C][C]0.206834[/C][C]0.413668[/C][C]0.793166[/C][/ROW]
[ROW][C]168[/C][C]0.189977[/C][C]0.379954[/C][C]0.810023[/C][/ROW]
[ROW][C]169[/C][C]0.254494[/C][C]0.508987[/C][C]0.745506[/C][/ROW]
[ROW][C]170[/C][C]0.276046[/C][C]0.552092[/C][C]0.723954[/C][/ROW]
[ROW][C]171[/C][C]0.251394[/C][C]0.502789[/C][C]0.748606[/C][/ROW]
[ROW][C]172[/C][C]0.248689[/C][C]0.497378[/C][C]0.751311[/C][/ROW]
[ROW][C]173[/C][C]0.426895[/C][C]0.853789[/C][C]0.573105[/C][/ROW]
[ROW][C]174[/C][C]0.407743[/C][C]0.815486[/C][C]0.592257[/C][/ROW]
[ROW][C]175[/C][C]0.420162[/C][C]0.840324[/C][C]0.579838[/C][/ROW]
[ROW][C]176[/C][C]0.428451[/C][C]0.856902[/C][C]0.571549[/C][/ROW]
[ROW][C]177[/C][C]0.48759[/C][C]0.97518[/C][C]0.51241[/C][/ROW]
[ROW][C]178[/C][C]0.453199[/C][C]0.906398[/C][C]0.546801[/C][/ROW]
[ROW][C]179[/C][C]0.431703[/C][C]0.863405[/C][C]0.568297[/C][/ROW]
[ROW][C]180[/C][C]0.436697[/C][C]0.873393[/C][C]0.563303[/C][/ROW]
[ROW][C]181[/C][C]0.399145[/C][C]0.798289[/C][C]0.600855[/C][/ROW]
[ROW][C]182[/C][C]0.39249[/C][C]0.784979[/C][C]0.60751[/C][/ROW]
[ROW][C]183[/C][C]0.356798[/C][C]0.713597[/C][C]0.643202[/C][/ROW]
[ROW][C]184[/C][C]0.330133[/C][C]0.660265[/C][C]0.669867[/C][/ROW]
[ROW][C]185[/C][C]0.313751[/C][C]0.627503[/C][C]0.686249[/C][/ROW]
[ROW][C]186[/C][C]0.308117[/C][C]0.616233[/C][C]0.691883[/C][/ROW]
[ROW][C]187[/C][C]0.279762[/C][C]0.559525[/C][C]0.720238[/C][/ROW]
[ROW][C]188[/C][C]0.255668[/C][C]0.511335[/C][C]0.744332[/C][/ROW]
[ROW][C]189[/C][C]0.225852[/C][C]0.451704[/C][C]0.774148[/C][/ROW]
[ROW][C]190[/C][C]0.205666[/C][C]0.411333[/C][C]0.794334[/C][/ROW]
[ROW][C]191[/C][C]0.216554[/C][C]0.433108[/C][C]0.783446[/C][/ROW]
[ROW][C]192[/C][C]0.197538[/C][C]0.395075[/C][C]0.802462[/C][/ROW]
[ROW][C]193[/C][C]0.229187[/C][C]0.458375[/C][C]0.770813[/C][/ROW]
[ROW][C]194[/C][C]0.212603[/C][C]0.425206[/C][C]0.787397[/C][/ROW]
[ROW][C]195[/C][C]0.209725[/C][C]0.41945[/C][C]0.790275[/C][/ROW]
[ROW][C]196[/C][C]0.219756[/C][C]0.439511[/C][C]0.780244[/C][/ROW]
[ROW][C]197[/C][C]0.28638[/C][C]0.57276[/C][C]0.71362[/C][/ROW]
[ROW][C]198[/C][C]0.269111[/C][C]0.538221[/C][C]0.730889[/C][/ROW]
[ROW][C]199[/C][C]0.297335[/C][C]0.59467[/C][C]0.702665[/C][/ROW]
[ROW][C]200[/C][C]0.263721[/C][C]0.527442[/C][C]0.736279[/C][/ROW]
[ROW][C]201[/C][C]0.294626[/C][C]0.589253[/C][C]0.705374[/C][/ROW]
[ROW][C]202[/C][C]0.271728[/C][C]0.543456[/C][C]0.728272[/C][/ROW]
[ROW][C]203[/C][C]0.315092[/C][C]0.630184[/C][C]0.684908[/C][/ROW]
[ROW][C]204[/C][C]0.283953[/C][C]0.567907[/C][C]0.716047[/C][/ROW]
[ROW][C]205[/C][C]0.255025[/C][C]0.51005[/C][C]0.744975[/C][/ROW]
[ROW][C]206[/C][C]0.235723[/C][C]0.471447[/C][C]0.764277[/C][/ROW]
[ROW][C]207[/C][C]0.20502[/C][C]0.410041[/C][C]0.79498[/C][/ROW]
[ROW][C]208[/C][C]0.230447[/C][C]0.460895[/C][C]0.769553[/C][/ROW]
[ROW][C]209[/C][C]0.198505[/C][C]0.39701[/C][C]0.801495[/C][/ROW]
[ROW][C]210[/C][C]0.221019[/C][C]0.442039[/C][C]0.778981[/C][/ROW]
[ROW][C]211[/C][C]0.262101[/C][C]0.524201[/C][C]0.737899[/C][/ROW]
[ROW][C]212[/C][C]0.239596[/C][C]0.479193[/C][C]0.760404[/C][/ROW]
[ROW][C]213[/C][C]0.211683[/C][C]0.423366[/C][C]0.788317[/C][/ROW]
[ROW][C]214[/C][C]0.246811[/C][C]0.493621[/C][C]0.753189[/C][/ROW]
[ROW][C]215[/C][C]0.21758[/C][C]0.43516[/C][C]0.78242[/C][/ROW]
[ROW][C]216[/C][C]0.207004[/C][C]0.414007[/C][C]0.792996[/C][/ROW]
[ROW][C]217[/C][C]0.25692[/C][C]0.51384[/C][C]0.74308[/C][/ROW]
[ROW][C]218[/C][C]0.227547[/C][C]0.455093[/C][C]0.772453[/C][/ROW]
[ROW][C]219[/C][C]0.209953[/C][C]0.419905[/C][C]0.790047[/C][/ROW]
[ROW][C]220[/C][C]0.220746[/C][C]0.441491[/C][C]0.779254[/C][/ROW]
[ROW][C]221[/C][C]0.235857[/C][C]0.471713[/C][C]0.764143[/C][/ROW]
[ROW][C]222[/C][C]0.237528[/C][C]0.475057[/C][C]0.762472[/C][/ROW]
[ROW][C]223[/C][C]0.219659[/C][C]0.439318[/C][C]0.780341[/C][/ROW]
[ROW][C]224[/C][C]0.185164[/C][C]0.370328[/C][C]0.814836[/C][/ROW]
[ROW][C]225[/C][C]0.17192[/C][C]0.34384[/C][C]0.82808[/C][/ROW]
[ROW][C]226[/C][C]0.188919[/C][C]0.377837[/C][C]0.811081[/C][/ROW]
[ROW][C]227[/C][C]0.380512[/C][C]0.761024[/C][C]0.619488[/C][/ROW]
[ROW][C]228[/C][C]0.36077[/C][C]0.721541[/C][C]0.63923[/C][/ROW]
[ROW][C]229[/C][C]0.335963[/C][C]0.671927[/C][C]0.664037[/C][/ROW]
[ROW][C]230[/C][C]0.326059[/C][C]0.652118[/C][C]0.673941[/C][/ROW]
[ROW][C]231[/C][C]0.287987[/C][C]0.575974[/C][C]0.712013[/C][/ROW]
[ROW][C]232[/C][C]0.351018[/C][C]0.702037[/C][C]0.648982[/C][/ROW]
[ROW][C]233[/C][C]0.306298[/C][C]0.612597[/C][C]0.693702[/C][/ROW]
[ROW][C]234[/C][C]0.261524[/C][C]0.523048[/C][C]0.738476[/C][/ROW]
[ROW][C]235[/C][C]0.261534[/C][C]0.523068[/C][C]0.738466[/C][/ROW]
[ROW][C]236[/C][C]0.236238[/C][C]0.472475[/C][C]0.763762[/C][/ROW]
[ROW][C]237[/C][C]0.200885[/C][C]0.40177[/C][C]0.799115[/C][/ROW]
[ROW][C]238[/C][C]0.160461[/C][C]0.320921[/C][C]0.839539[/C][/ROW]
[ROW][C]239[/C][C]0.286698[/C][C]0.573397[/C][C]0.713302[/C][/ROW]
[ROW][C]240[/C][C]0.286751[/C][C]0.573502[/C][C]0.713249[/C][/ROW]
[ROW][C]241[/C][C]0.255426[/C][C]0.510852[/C][C]0.744574[/C][/ROW]
[ROW][C]242[/C][C]0.483763[/C][C]0.967526[/C][C]0.516237[/C][/ROW]
[ROW][C]243[/C][C]0.438045[/C][C]0.87609[/C][C]0.561955[/C][/ROW]
[ROW][C]244[/C][C]0.369669[/C][C]0.739338[/C][C]0.630331[/C][/ROW]
[ROW][C]245[/C][C]0.488499[/C][C]0.976997[/C][C]0.511501[/C][/ROW]
[ROW][C]246[/C][C]0.407798[/C][C]0.815595[/C][C]0.592202[/C][/ROW]
[ROW][C]247[/C][C]0.326429[/C][C]0.652859[/C][C]0.673571[/C][/ROW]
[ROW][C]248[/C][C]0.51242[/C][C]0.975161[/C][C]0.48758[/C][/ROW]
[ROW][C]249[/C][C]0.419932[/C][C]0.839865[/C][C]0.580068[/C][/ROW]
[ROW][C]250[/C][C]0.323854[/C][C]0.647708[/C][C]0.676146[/C][/ROW]
[ROW][C]251[/C][C]0.48063[/C][C]0.96126[/C][C]0.51937[/C][/ROW]
[ROW][C]252[/C][C]0.890343[/C][C]0.219314[/C][C]0.109657[/C][/ROW]
[ROW][C]253[/C][C]0.816192[/C][C]0.367616[/C][C]0.183808[/C][/ROW]
[ROW][C]254[/C][C]0.691629[/C][C]0.616742[/C][C]0.308371[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226169&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226169&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
100.0238240.04764810.976176
110.005114450.01022890.994886
120.695650.60870.30435
130.941760.1164790.0582397
140.9221270.1557460.0778729
150.9468590.1062830.0531413
160.917180.165640.08282
170.9244290.1511420.0755712
180.8987360.2025280.101264
190.8586180.2827630.141382
200.8565310.2869380.143469
210.8897360.2205280.110264
220.9059340.1881330.0940665
230.8862930.2274130.113707
240.8502870.2994260.149713
250.8212560.3574880.178744
260.9982710.003457370.00172868
270.9973060.005388140.00269407
280.9958330.008333430.00416672
290.9938650.01227080.00613539
300.9954250.009149150.00457458
310.9932710.0134570.00672851
320.9905610.01887840.00943922
330.9888760.02224830.0111242
340.9843470.03130540.0156527
350.9809450.03810910.0190546
360.9742980.05140490.0257024
370.9823470.03530540.0176527
380.9761190.04776180.0238809
390.9739410.0521180.026059
400.9737430.05251430.0262571
410.9660590.0678830.0339415
420.9626030.0747950.0373975
430.9519860.09602790.0480139
440.9442010.1115970.0557985
450.9296350.1407290.0703647
460.9490520.1018960.0509482
470.9357330.1285350.0642674
480.9197210.1605570.0802787
490.9369750.1260490.0630246
500.9371760.1256480.0628241
510.9232750.153450.0767251
520.9064270.1871460.0935731
530.8981850.2036310.101815
540.8849710.2300580.115029
550.8863690.2272610.113631
560.8734180.2531650.126582
570.8617830.2764330.138217
580.8363180.3273650.163682
590.8734330.2531330.126567
600.8625970.2748050.137403
610.8754780.2490450.124522
620.8724020.2551960.127598
630.9202930.1594130.0797067
640.908910.182180.0910898
650.9017050.196590.0982948
660.9624220.07515620.0375781
670.9592710.08145820.0407291
680.958850.08229990.0411499
690.9513230.09735380.0486769
700.9448910.1102180.0551091
710.9328560.1342880.0671438
720.947580.104840.0524201
730.9368280.1263440.0631722
740.9241850.151630.0758152
750.9183720.1632560.0816281
760.9030230.1939540.096977
770.915890.168220.08411
780.9013680.1972650.0986323
790.8895490.2209010.110451
800.8809430.2381150.119057
810.860690.2786210.13931
820.8391350.3217290.160865
830.8297730.3404530.170227
840.8077350.384530.192265
850.7804720.4390570.219528
860.7554540.4890920.244546
870.7248810.5502390.275119
880.6932440.6135120.306756
890.7701980.4596040.229802
900.8011770.3976470.198823
910.7744250.451150.225575
920.74910.50180.2509
930.7237150.552570.276285
940.6997870.6004270.300213
950.6740440.6519120.325956
960.6473370.7053260.352663
970.6158010.7683970.384199
980.6156140.7687720.384386
990.5807820.8384370.419218
1000.5684310.8631380.431569
1010.5418970.9162060.458103
1020.5166070.9667860.483393
1030.561670.8766610.43833
1040.5541060.8917870.445894
1050.5795740.8408520.420426
1060.5546250.890750.445375
1070.5487740.9024510.451226
1080.5807170.8385670.419283
1090.5534540.8930930.446546
1100.5294990.9410020.470501
1110.5346210.9307570.465379
1120.5561770.8876470.443823
1130.549680.9006410.45032
1140.6275450.744910.372455
1150.5966270.8067450.403373
1160.5679060.8641880.432094
1170.5347960.9304090.465204
1180.513630.972740.48637
1190.4804490.9608980.519551
1200.4504310.9008620.549569
1210.4207380.8414760.579262
1220.390730.7814610.60927
1230.3664930.7329860.633507
1240.3348380.6696760.665162
1250.3264280.6528560.673572
1260.2997720.5995430.700228
1270.2929340.5858690.707066
1280.4010790.8021590.598921
1290.3791310.7582620.620869
1300.3634770.7269540.636523
1310.3584280.7168560.641572
1320.3321860.6643720.667814
1330.3450060.6900120.654994
1340.3175230.6350460.682477
1350.329830.6596590.67017
1360.3223810.6447620.677619
1370.295280.5905590.70472
1380.2759450.5518890.724055
1390.2508550.501710.749145
1400.2311060.4622120.768894
1410.2077370.4154750.792263
1420.217350.4346990.78265
1430.1937110.3874220.806289
1440.1755980.3511950.824402
1450.1612380.3224760.838762
1460.158830.317660.84117
1470.1727960.3455910.827204
1480.1857160.3714330.814284
1490.2016530.4033060.798347
1500.1963310.3926610.803669
1510.176680.353360.82332
1520.1603490.3206970.839651
1530.1644190.3288380.835581
1540.174210.348420.82579
1550.1583750.3167510.841625
1560.137880.275760.86212
1570.1234470.2468950.876553
1580.2071360.4142730.792864
1590.2189950.4379890.781005
1600.1988480.3976950.801152
1610.1782110.3564220.821789
1620.1571190.3142380.842881
1630.1386120.2772230.861388
1640.2475910.4951820.752409
1650.2423790.4847580.757621
1660.2335210.4670420.766479
1670.2068340.4136680.793166
1680.1899770.3799540.810023
1690.2544940.5089870.745506
1700.2760460.5520920.723954
1710.2513940.5027890.748606
1720.2486890.4973780.751311
1730.4268950.8537890.573105
1740.4077430.8154860.592257
1750.4201620.8403240.579838
1760.4284510.8569020.571549
1770.487590.975180.51241
1780.4531990.9063980.546801
1790.4317030.8634050.568297
1800.4366970.8733930.563303
1810.3991450.7982890.600855
1820.392490.7849790.60751
1830.3567980.7135970.643202
1840.3301330.6602650.669867
1850.3137510.6275030.686249
1860.3081170.6162330.691883
1870.2797620.5595250.720238
1880.2556680.5113350.744332
1890.2258520.4517040.774148
1900.2056660.4113330.794334
1910.2165540.4331080.783446
1920.1975380.3950750.802462
1930.2291870.4583750.770813
1940.2126030.4252060.787397
1950.2097250.419450.790275
1960.2197560.4395110.780244
1970.286380.572760.71362
1980.2691110.5382210.730889
1990.2973350.594670.702665
2000.2637210.5274420.736279
2010.2946260.5892530.705374
2020.2717280.5434560.728272
2030.3150920.6301840.684908
2040.2839530.5679070.716047
2050.2550250.510050.744975
2060.2357230.4714470.764277
2070.205020.4100410.79498
2080.2304470.4608950.769553
2090.1985050.397010.801495
2100.2210190.4420390.778981
2110.2621010.5242010.737899
2120.2395960.4791930.760404
2130.2116830.4233660.788317
2140.2468110.4936210.753189
2150.217580.435160.78242
2160.2070040.4140070.792996
2170.256920.513840.74308
2180.2275470.4550930.772453
2190.2099530.4199050.790047
2200.2207460.4414910.779254
2210.2358570.4717130.764143
2220.2375280.4750570.762472
2230.2196590.4393180.780341
2240.1851640.3703280.814836
2250.171920.343840.82808
2260.1889190.3778370.811081
2270.3805120.7610240.619488
2280.360770.7215410.63923
2290.3359630.6719270.664037
2300.3260590.6521180.673941
2310.2879870.5759740.712013
2320.3510180.7020370.648982
2330.3062980.6125970.693702
2340.2615240.5230480.738476
2350.2615340.5230680.738466
2360.2362380.4724750.763762
2370.2008850.401770.799115
2380.1604610.3209210.839539
2390.2866980.5733970.713302
2400.2867510.5735020.713249
2410.2554260.5108520.744574
2420.4837630.9675260.516237
2430.4380450.876090.561955
2440.3696690.7393380.630331
2450.4884990.9769970.511501
2460.4077980.8155950.592202
2470.3264290.6528590.673571
2480.512420.9751610.48758
2490.4199320.8398650.580068
2500.3238540.6477080.676146
2510.480630.961260.51937
2520.8903430.2193140.109657
2530.8161920.3676160.183808
2540.6916290.6167420.308371






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level40.0163265NOK
5% type I error level140.0571429NOK
10% type I error level240.0979592OK

\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 & 4 & 0.0163265 & NOK \tabularnewline
5% type I error level & 14 & 0.0571429 & NOK \tabularnewline
10% type I error level & 24 & 0.0979592 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226169&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]4[/C][C]0.0163265[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]14[/C][C]0.0571429[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]24[/C][C]0.0979592[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226169&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226169&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 level40.0163265NOK
5% type I error level140.0571429NOK
10% type I error level240.0979592OK


Figures (Output of Computation)

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

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