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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationThu, 11 Dec 2014 23:12:41 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/11/t14183408014yzdvh748xccxcb.htm/, Retrieved Thu, 16 May 2024 21:42:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266421, Retrieved Thu, 16 May 2024 21:42:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact76

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-11 23:12:41] [ec71b09431fe59ba6fc828a3f51756a9] [Current]
- R  D    [Multiple Regression] [] [2014-12-12 10:56:18] [02fb6cbf799bcf1e525e4e01c2f27ada]
-    D    [Multiple Regression] [] [2014-12-12 11:05:51] [02fb6cbf799bcf1e525e4e01c2f27ada]
- R PD      [Multiple Regression] [] [2014-12-12 11:49:48] [02fb6cbf799bcf1e525e4e01c2f27ada]
- RMP       [Kendall tau Correlation Matrix] [] [2014-12-12 14:22:12] [02fb6cbf799bcf1e525e4e01c2f27ada]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1 0.56 12.9
1 0.79 7.4
1 0.68 12.2
1 0.66 12.8
1 0.37 7.4
1 0.71 6.7
1 0.35 12.6
1 0.55 14.8
1 0.76 13.3
1 0.49 11.1
1 0.56 8.2
1 0.60 11.4
1 0.44 6.4
1 0.55 10.6
1 0.58 12.0
1 0.40 6.3
0 0.42 11.3
1 0.58 11.9
1 0.64 9.3
0 0.58 9.6
1 0.44 10.0
1 0.46 6.4
1 0.64 13.8
1 0.59 10.8
1 0.54 13.8
1 0.71 11.7
1 0.20 10.9
0 0.89 16.1
0 0.55 13.4
1 0.71 9.9
1 0.48 11.5
1 0.49 8.3
1 0.58 11.7
1 0.78 6.1
1 0.71 9.0
1 0.51 9.7
1 0.65 10.8
1 0.68 10.3
1 0.24 10.4
0 0.36 12.7
1 0.65 9.3
1 0.79 11.8
1 0.67 5.9
1 0.74 11.4
1 0.72 13.0
1 0.73 10.8
0 0.58 12.3
1 0.67 11.3
1 0.43 11.8
0 0.59 7.9
1 0.43 12.7
0 0.80 12.3
0 0.74 11.6
0 0.43 6.7
1 0.72 10.9
0 0.50 12.1
1 0.45 13.3
1 0.88 10.1
0 0.67 5.7
1 0.32 14.3
0 0.20 8.0
0 0.84 13.3
1 0.83 9.3
1 0.65 12.5
1 0.74 7.6
1 0.53 15.9
1 0.58 9.2
0 0.65 9.1
1 0.64 11.1
1 0.60 13.0
1 0.52 14.5
0 0.53 12.2
1 0.73 12.3
1 0.52 11.4
0 0.61 8.8
0 0.73 14.6
1 0.79 7.3
1 0.29 12.6
1 0.86 NA
1 0.37 13.0
0 0.68 12.6
1 0.52 13.2
0 0.26 9.9
1 0.74 7.7
0 0.72 10.5
0 0.24 13.4
0 0.71 10.9
0 0.59 4.3
0 0.27 10.3
0 0.57 11.8
0 0.51 11.2
0 0.69 11.4
0 0.69 8.6
0 0.50 13.2
0 0.63 12.6
0 0.65 5.6
0 0.54 9.9
0 0.69 8.8
0 0.52 7.7
0 0.53 9.0
0 0.74 7.3
0 0.73 11.4
0 0.75 13.6
0 0.70 7.9
0 0.69 10.7
0 0.57 10.3
0 0.14 8.3
0 0.42 9.6
0 0.48 14.2
0 0.27 8.5
0 0.21 13.5
0 0.41 4.9
0 0.56 6.4
0 0.44 9.6
0 0.52 11.6
0 0.59 11.1
1 0.73 4.35
1 0.79 12.7
1 0.67 18.1
1 0.88 17.85
0 0.96 16.6
0 0.43 12.6
1 0.84 17.1
1 0.81 19.1
1 0.67 16.1
1 0.45 13.35
1 0.58 18.4
1 0.70 14.7
1 0.61 10.6
1 0.44 12.6
1 0.54 16.2
1 0.41 13.6
0 0.66 18.9
1 0.83 14.1
1 0.88 14.5
1 0.40 16.15
1 0.54 14.75
1 0.60 14.8
1 0.57 12.45
1 0.59 12.65
1 0.81 17.35
1 0.51 8.6
1 0.65 18.4
1 0.59 16.1
0 0.68 11.6
1 0.65 17.75
1 0.06 15.25
1 0.74 17.65
1 0.29 15.6
1 0.73 16.35
1 0.54 17.65
1 0.39 13.6
1 0.27 11.7
1 0.40 14.35
1 0.20 14.75
1 0.85 18.25
1 0.42 9.9
1 0.68 16
1 0.72 18.25
1 0.52 16.85
0 0.78 14.6
0 0.60 13.85
1 0.93 18.95
1 0.73 15.6
0 0.81 14.85
0 0.51 11.75
0 0.86 18.45
0 0.67 15.9
1 0.50 17.1
1 0.74 16.1
0 0.85 19.9
0 0.75 10.95
0 0.83 18.45
0 0.82 15.1
0 0.58 15
0 0.72 11.35
0 0.89 15.95
0 0.51 18.1
0 0.75 14.6
1 0.84 15.4
1 0.84 15.4
0 0.59 17.6
1 0.64 13.35
1 0.45 19.1
0 0.57 15.35
1 0.58 7.6
0 0.72 13.4
0 0.38 13.9
1 0.68 19.1
0 0.45 15.25
0 0.55 12.9
0 0.73 16.1
0 0.73 17.35
0 0.73 13.15
0 0.71 12.15
0 0.38 12.6
0 0.79 10.35
0 0.32 15.4
0 0.62 9.6
0 0.42 18.2
0 0.45 13.6
0 0.97 14.85
1 0.67 14.75
0 0.08 14.1
0 0.49 14.9
0 0.66 16.25
1 0.67 19.25
0 0.55 13.6
1 0.55 13.6
0 0.49 15.65
1 0.56 12.75
0 0.69 14.6
1 0.47 9.85
0 0.68 12.65
0 0.43 11.9
0 0.00 19.2
0 0.48 16.6
0 0.77 11.2
1 0.71 15.25
1 0.43 11.9
0 0.50 13.2
1 0.68 16.35
1 0.34 12.4
0 0.47 15.85
1 0.33 14.35
1 0.80 18.15
0 0.74 11.15
0 0.82 15.65
1 0.57 17.75
0 0.46 7.65
1 0.91 12.35
1 0.41 15.6
1 0.64 19.3
0 0.58 15.2
1 0.45 17.1
0 0.77 15.6
1 0.67 18.4
1 0.53 19.05
1 0.07 18.55
1 0.65 19.1
0 0.76 13.1
1 0.56 12.85
1 0.07 9.5
1 0.72 4.5
0 0.61 11.85
1 0.47 13.6
1 0.06 11.7
0 0.37 12.4
1 0.76 13.35
0 0.47 11.4
0 0.55 14.9
0 0.85 19.9
1 0.77 17.75
0 0.79 11.2
0 0.70 14.6
1 0.46 17.6
1 0.51 14.05
1 0.65 16.1
1 0.57 13.35
1 0.68 11.85
1 0.52 11.95
0 0.70 14.75
0 0.46 15.15
1 0.88 13.2
0 0.76 16.85
0 0.74 7.85
1 0.56 7.7
0 0.47 12.6
0 0.44 7.85
0 0.75 10.95
0 0.78 12.35
0 0.26 9.95
0 0.55 14.9
0 0.49 16.65
0 0.81 13.4
0 0.45 13.95
0 0.39 15.7
0 0.89 16.85
0 0.66 10.95
0 0.34 15.35
0 0.84 12.2
0 0.05 15.1
0 0.79 17.75
0 0.60 15.2
1 0.69 14.6
0 0.58 16.65
0 0.66 8.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266421&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266421&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266421&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 time9 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Bin_Course_id[t] = + 0.434429 -0.0436117Totaal[t] + 0.00867603TOT[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Bin_Course_id[t] =  +  0.434429 -0.0436117Totaal[t] +  0.00867603TOT[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266421&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Bin_Course_id[t] =  +  0.434429 -0.0436117Totaal[t] +  0.00867603TOT[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266421&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266421&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
Bin_Course_id[t] = + 0.434429 -0.0436117Totaal[t] + 0.00867603TOT[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)0.4344290.1430733.0360.002617130.00130856
Totaal-0.04361170.163601-0.26660.7899920.394996
TOT0.008676030.008734730.99330.3214220.160711

\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) & 0.434429 & 0.143073 & 3.036 & 0.00261713 & 0.00130856 \tabularnewline
Totaal & -0.0436117 & 0.163601 & -0.2666 & 0.789992 & 0.394996 \tabularnewline
TOT & 0.00867603 & 0.00873473 & 0.9933 & 0.321422 & 0.160711 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266421&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]0.434429[/C][C]0.143073[/C][C]3.036[/C][C]0.00261713[/C][C]0.00130856[/C][/ROW]
[ROW][C]Totaal[/C][C]-0.0436117[/C][C]0.163601[/C][C]-0.2666[/C][C]0.789992[/C][C]0.394996[/C][/ROW]
[ROW][C]TOT[/C][C]0.00867603[/C][C]0.00873473[/C][C]0.9933[/C][C]0.321422[/C][C]0.160711[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266421&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266421&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)0.4344290.1430733.0360.002617130.00130856
Totaal-0.04361170.163601-0.26660.7899920.394996
TOT0.008676030.008734730.99330.3214220.160711






Multiple Linear Regression - Regression Statistics
Multiple R0.0596618
R-squared0.00355953
Adjusted R-squared-0.00348245
F-TEST (value)0.505473
F-TEST (DF numerator)2
F-TEST (DF denominator)283
p-value0.603764
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.501306
Sum Squared Residuals71.1201

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.0596618 \tabularnewline
R-squared & 0.00355953 \tabularnewline
Adjusted R-squared & -0.00348245 \tabularnewline
F-TEST (value) & 0.505473 \tabularnewline
F-TEST (DF numerator) & 2 \tabularnewline
F-TEST (DF denominator) & 283 \tabularnewline
p-value & 0.603764 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.501306 \tabularnewline
Sum Squared Residuals & 71.1201 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266421&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.0596618[/C][/ROW]
[ROW][C]R-squared[/C][C]0.00355953[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]-0.00348245[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]0.505473[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]2[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]283[/C][/ROW]
[ROW][C]p-value[/C][C]0.603764[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.501306[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]71.1201[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266421&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266421&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 R0.0596618
R-squared0.00355953
Adjusted R-squared-0.00348245
F-TEST (value)0.505473
F-TEST (DF numerator)2
F-TEST (DF denominator)283
p-value0.603764
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.501306
Sum Squared Residuals71.1201






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
110.5219280.478072
210.4641790.535821
310.5106210.489379
410.5166990.483301
510.4824960.517504
610.4615940.538406
710.5284830.471517
810.5388480.461152
910.5166760.483324
1010.5093640.490636
1110.481150.51885
1210.5071690.492831
1310.4707670.529233
1410.5024090.497591
1510.5132470.486753
1610.4716440.528356
1700.514152-0.514152
1810.5123790.487621
1910.4872050.512795
2000.492424-0.492424
2110.5020.498
2210.4698950.530105
2310.5262470.473753
2410.50240.4976
2510.5306080.469392
2610.5049750.495025
2710.5202760.479724
2800.535299-0.535299
2900.526702-0.526702
3010.4893580.510642
3110.513270.48673
3210.4850710.514929
3310.5106440.489356
3410.4533360.546664
3510.4815490.518451
3610.4963450.503655
3710.4997830.500217
3810.4941360.505864
3910.5141930.485807
4000.528915-0.528915
4110.4867690.513231
4210.5023530.497647
4310.4563980.543602
4410.5010630.498937
4510.5158170.484183
4610.4962940.503706
4700.51585-0.51585
4810.5032490.496751
4910.5180530.481947
5000.477239-0.477239
5110.5258620.474138
5200.506255-0.506255
5300.502799-0.502799
5400.473806-0.473806
5510.4975980.502402
5600.517603-0.517603
5710.5301950.469805
5810.4836790.516321
5900.454663-0.454663
6010.5445410.455459
6100.495115-0.495115
6200.513187-0.513187
6310.4789190.521081
6410.5145320.485468
6510.4680950.531905
6610.5492640.450736
6710.4889540.511046
6800.485034-0.485034
6910.5028220.497178
7010.5210510.478949
7110.5375540.462446
7200.517163-0.517163
7310.5093080.490692
7410.5106580.489342
7500.484175-0.484175
7600.529263-0.529263
7710.4633110.536689
7810.53110.4689
7910.5310810.468919
8011.51409-0.514091
810-0.4737250.473725
8211.50898-0.508983
830-0.5310380.531038
8411.49413-0.494127
8500.540221-0.540221
8600.498034-0.498034
8700.446005-0.446005
8800.512017-0.512017
8900.511948-0.511948
9000.509359-0.509359
9100.503244-0.503244
9200.478951-0.478951
9300.527147-0.527147
9400.516272-0.516272
9500.454668-0.454668
9600.496772-0.496772
9700.480686-0.480686
9800.478557-0.478557
9900.489399-0.489399
10000.465492-0.465492
10100.5015-0.5015
10200.519715-0.519715
10300.472442-0.472442
10400.497171-0.497171
10500.498934-0.498934
10600.500335-0.500335
10700.499402-0.499402
10800.536695-0.536695
10900.4964-0.4964
11000.542397-0.542397
11100.459061-0.459061
11200.465533-0.465533
11300.49853-0.49853
11400.512393-0.512393
11500.505002-0.505002
1160-0.5596660.559666
11710.5101620.489838
11810.5622460.437754
11910.5509180.449082
12011.53658-0.536584
12100.524994-0.524994
1220-0.4538440.453844
12310.5648160.435184
12410.5448940.455106
12510.5306290.469371
12610.5687730.431227
12710.5314390.468561
12810.4997920.500208
12910.5245580.475442
13010.5514310.448569
13110.5345430.465457
13211.56962-0.569623
1330-0.4794360.479436
13410.5218530.478147
13510.5571030.442897
13610.538850.46115
13710.5366680.463332
13810.5175870.482413
13910.518450.48155
14010.5496330.450367
14110.4868010.513199
14210.5657210.434279
14310.5483820.451618
14411.50542-0.505415
1450-0.4399190.439919
14610.5641220.435878
14710.5552890.444711
14810.5571280.442872
14910.5444460.455554
15010.5640110.435989
15110.5354150.464585
15210.5241640.475836
15310.5414860.458514
15410.5536780.446322
15510.5556970.444303
15610.5020050.497995
15710.543590.45641
15810.5613660.438634
15910.5579420.442058
16011.52708-0.527082
16100.528425-0.528425
1620-0.4417190.441719
16310.5379390.462061
16411.52794-0.527943
16500.514131-0.514131
16600.556996-0.556996
16700.543158-0.543158
1680-0.4390160.439016
16910.5418410.458159
17011.57001-0.570012
17100.496723-0.496723
17200.558304-0.558304
17300.529676-0.529676
17400.539275-0.539275
17500.501502-0.501502
17600.533998-0.533998
17700.569223-0.569223
17800.528391-0.528391
1790-0.4685940.468594
18010.5314060.468594
18111.5614-0.561397
1820-0.4776570.477657
18310.5805160.419484
18411.54275-0.542748
1850-0.5249280.524928
18611.51929-0.519288
18700.538454-0.538454
1880-0.4295140.429514
18911.54711-0.547114
19000.522364-0.522364
19100.542277-0.542277
19200.553122-0.553122
19300.516683-0.516683
19400.508879-0.508879
19500.527175-0.527175
19600.489773-0.489773
19700.554084-0.554084
19800.49068-0.49068
19900.574016-0.574016
20000.532798-0.532798
20100.520965-0.520965
2020-0.4668190.466819
20311.55327-0.553272
20400.542332-0.542332
20500.546631-0.546631
2060-0.4277770.427777
20711.52844-0.528437
2080-0.4715630.471563
20911.54884-0.548839
2100-0.4793740.479374
21111.53101-0.531007
2120-0.5006090.500609
21311.51453-0.514525
21400.518921-0.518921
21500.601009-0.601009
21600.557518-0.557518
21700.49802-0.49802
2180-0.4642260.464226
21910.5189210.481079
22011.52715-0.527147
2210-0.4533740.453374
22210.5271840.472816
22311.55145-0.551447
2240-0.4554620.455462
22510.557010.44299
22611.49889-0.498894
22700.534448-0.534448
2280-0.436430.43643
22911.48074-0.48074
2300-0.4981080.498108
23110.5518950.448105
23210.5739650.426035
23311.54101-0.54101
2340-0.4368360.436836
23511.53619-0.536194
2360-0.4351520.435152
23710.5765930.423407
23810.5923170.407683
23910.5717940.428206
24011.51494-0.51494
2410-0.4785060.478506
24210.5137990.486201
24310.4420710.557929
24411.51064-0.510637
2450-0.4680740.468074
24610.5333220.466678
24711.52588-0.525876
2480-0.4828910.482891
24911.51284-0.512839
25000.539716-0.539716
25100.570012-0.570012
2520-0.4451520.445152
25311.49715-0.497148
25400.530571-0.530571
2550-0.4329340.432934
25610.5340860.465914
25710.5457660.454234
25810.5253960.474604
25910.5075840.492416
26010.515430.48457
26111.53187-0.531873
26200.54581-0.54581
2630-0.4894250.489425
26411.54748-0.547476
26500.470264-0.470264
2660-0.5231880.523188
26711.52325-0.52325
26800.483347-0.483347
26900.496723-0.496723
27000.507561-0.507561
27100.509417-0.509417
27200.539716-0.539716
27300.557515-0.557515
27400.515363-0.515363
27500.535835-0.535835
27600.553634-0.553634
27700.541806-0.541806
27800.500648-0.500648
27900.552778-0.552778
28000.503643-0.503643
28100.563257-0.563257
28200.553976-0.553976
28300.540138-0.540138
2840-0.4689930.468993
28511.55359-0.55359
28600.475921-0.475921
2870NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1 & 0.521928 & 0.478072 \tabularnewline
2 & 1 & 0.464179 & 0.535821 \tabularnewline
3 & 1 & 0.510621 & 0.489379 \tabularnewline
4 & 1 & 0.516699 & 0.483301 \tabularnewline
5 & 1 & 0.482496 & 0.517504 \tabularnewline
6 & 1 & 0.461594 & 0.538406 \tabularnewline
7 & 1 & 0.528483 & 0.471517 \tabularnewline
8 & 1 & 0.538848 & 0.461152 \tabularnewline
9 & 1 & 0.516676 & 0.483324 \tabularnewline
10 & 1 & 0.509364 & 0.490636 \tabularnewline
11 & 1 & 0.48115 & 0.51885 \tabularnewline
12 & 1 & 0.507169 & 0.492831 \tabularnewline
13 & 1 & 0.470767 & 0.529233 \tabularnewline
14 & 1 & 0.502409 & 0.497591 \tabularnewline
15 & 1 & 0.513247 & 0.486753 \tabularnewline
16 & 1 & 0.471644 & 0.528356 \tabularnewline
17 & 0 & 0.514152 & -0.514152 \tabularnewline
18 & 1 & 0.512379 & 0.487621 \tabularnewline
19 & 1 & 0.487205 & 0.512795 \tabularnewline
20 & 0 & 0.492424 & -0.492424 \tabularnewline
21 & 1 & 0.502 & 0.498 \tabularnewline
22 & 1 & 0.469895 & 0.530105 \tabularnewline
23 & 1 & 0.526247 & 0.473753 \tabularnewline
24 & 1 & 0.5024 & 0.4976 \tabularnewline
25 & 1 & 0.530608 & 0.469392 \tabularnewline
26 & 1 & 0.504975 & 0.495025 \tabularnewline
27 & 1 & 0.520276 & 0.479724 \tabularnewline
28 & 0 & 0.535299 & -0.535299 \tabularnewline
29 & 0 & 0.526702 & -0.526702 \tabularnewline
30 & 1 & 0.489358 & 0.510642 \tabularnewline
31 & 1 & 0.51327 & 0.48673 \tabularnewline
32 & 1 & 0.485071 & 0.514929 \tabularnewline
33 & 1 & 0.510644 & 0.489356 \tabularnewline
34 & 1 & 0.453336 & 0.546664 \tabularnewline
35 & 1 & 0.481549 & 0.518451 \tabularnewline
36 & 1 & 0.496345 & 0.503655 \tabularnewline
37 & 1 & 0.499783 & 0.500217 \tabularnewline
38 & 1 & 0.494136 & 0.505864 \tabularnewline
39 & 1 & 0.514193 & 0.485807 \tabularnewline
40 & 0 & 0.528915 & -0.528915 \tabularnewline
41 & 1 & 0.486769 & 0.513231 \tabularnewline
42 & 1 & 0.502353 & 0.497647 \tabularnewline
43 & 1 & 0.456398 & 0.543602 \tabularnewline
44 & 1 & 0.501063 & 0.498937 \tabularnewline
45 & 1 & 0.515817 & 0.484183 \tabularnewline
46 & 1 & 0.496294 & 0.503706 \tabularnewline
47 & 0 & 0.51585 & -0.51585 \tabularnewline
48 & 1 & 0.503249 & 0.496751 \tabularnewline
49 & 1 & 0.518053 & 0.481947 \tabularnewline
50 & 0 & 0.477239 & -0.477239 \tabularnewline
51 & 1 & 0.525862 & 0.474138 \tabularnewline
52 & 0 & 0.506255 & -0.506255 \tabularnewline
53 & 0 & 0.502799 & -0.502799 \tabularnewline
54 & 0 & 0.473806 & -0.473806 \tabularnewline
55 & 1 & 0.497598 & 0.502402 \tabularnewline
56 & 0 & 0.517603 & -0.517603 \tabularnewline
57 & 1 & 0.530195 & 0.469805 \tabularnewline
58 & 1 & 0.483679 & 0.516321 \tabularnewline
59 & 0 & 0.454663 & -0.454663 \tabularnewline
60 & 1 & 0.544541 & 0.455459 \tabularnewline
61 & 0 & 0.495115 & -0.495115 \tabularnewline
62 & 0 & 0.513187 & -0.513187 \tabularnewline
63 & 1 & 0.478919 & 0.521081 \tabularnewline
64 & 1 & 0.514532 & 0.485468 \tabularnewline
65 & 1 & 0.468095 & 0.531905 \tabularnewline
66 & 1 & 0.549264 & 0.450736 \tabularnewline
67 & 1 & 0.488954 & 0.511046 \tabularnewline
68 & 0 & 0.485034 & -0.485034 \tabularnewline
69 & 1 & 0.502822 & 0.497178 \tabularnewline
70 & 1 & 0.521051 & 0.478949 \tabularnewline
71 & 1 & 0.537554 & 0.462446 \tabularnewline
72 & 0 & 0.517163 & -0.517163 \tabularnewline
73 & 1 & 0.509308 & 0.490692 \tabularnewline
74 & 1 & 0.510658 & 0.489342 \tabularnewline
75 & 0 & 0.484175 & -0.484175 \tabularnewline
76 & 0 & 0.529263 & -0.529263 \tabularnewline
77 & 1 & 0.463311 & 0.536689 \tabularnewline
78 & 1 & 0.5311 & 0.4689 \tabularnewline
79 & 1 & 0.531081 & 0.468919 \tabularnewline
80 & 1 & 1.51409 & -0.514091 \tabularnewline
81 & 0 & -0.473725 & 0.473725 \tabularnewline
82 & 1 & 1.50898 & -0.508983 \tabularnewline
83 & 0 & -0.531038 & 0.531038 \tabularnewline
84 & 1 & 1.49413 & -0.494127 \tabularnewline
85 & 0 & 0.540221 & -0.540221 \tabularnewline
86 & 0 & 0.498034 & -0.498034 \tabularnewline
87 & 0 & 0.446005 & -0.446005 \tabularnewline
88 & 0 & 0.512017 & -0.512017 \tabularnewline
89 & 0 & 0.511948 & -0.511948 \tabularnewline
90 & 0 & 0.509359 & -0.509359 \tabularnewline
91 & 0 & 0.503244 & -0.503244 \tabularnewline
92 & 0 & 0.478951 & -0.478951 \tabularnewline
93 & 0 & 0.527147 & -0.527147 \tabularnewline
94 & 0 & 0.516272 & -0.516272 \tabularnewline
95 & 0 & 0.454668 & -0.454668 \tabularnewline
96 & 0 & 0.496772 & -0.496772 \tabularnewline
97 & 0 & 0.480686 & -0.480686 \tabularnewline
98 & 0 & 0.478557 & -0.478557 \tabularnewline
99 & 0 & 0.489399 & -0.489399 \tabularnewline
100 & 0 & 0.465492 & -0.465492 \tabularnewline
101 & 0 & 0.5015 & -0.5015 \tabularnewline
102 & 0 & 0.519715 & -0.519715 \tabularnewline
103 & 0 & 0.472442 & -0.472442 \tabularnewline
104 & 0 & 0.497171 & -0.497171 \tabularnewline
105 & 0 & 0.498934 & -0.498934 \tabularnewline
106 & 0 & 0.500335 & -0.500335 \tabularnewline
107 & 0 & 0.499402 & -0.499402 \tabularnewline
108 & 0 & 0.536695 & -0.536695 \tabularnewline
109 & 0 & 0.4964 & -0.4964 \tabularnewline
110 & 0 & 0.542397 & -0.542397 \tabularnewline
111 & 0 & 0.459061 & -0.459061 \tabularnewline
112 & 0 & 0.465533 & -0.465533 \tabularnewline
113 & 0 & 0.49853 & -0.49853 \tabularnewline
114 & 0 & 0.512393 & -0.512393 \tabularnewline
115 & 0 & 0.505002 & -0.505002 \tabularnewline
116 & 0 & -0.559666 & 0.559666 \tabularnewline
117 & 1 & 0.510162 & 0.489838 \tabularnewline
118 & 1 & 0.562246 & 0.437754 \tabularnewline
119 & 1 & 0.550918 & 0.449082 \tabularnewline
120 & 1 & 1.53658 & -0.536584 \tabularnewline
121 & 0 & 0.524994 & -0.524994 \tabularnewline
122 & 0 & -0.453844 & 0.453844 \tabularnewline
123 & 1 & 0.564816 & 0.435184 \tabularnewline
124 & 1 & 0.544894 & 0.455106 \tabularnewline
125 & 1 & 0.530629 & 0.469371 \tabularnewline
126 & 1 & 0.568773 & 0.431227 \tabularnewline
127 & 1 & 0.531439 & 0.468561 \tabularnewline
128 & 1 & 0.499792 & 0.500208 \tabularnewline
129 & 1 & 0.524558 & 0.475442 \tabularnewline
130 & 1 & 0.551431 & 0.448569 \tabularnewline
131 & 1 & 0.534543 & 0.465457 \tabularnewline
132 & 1 & 1.56962 & -0.569623 \tabularnewline
133 & 0 & -0.479436 & 0.479436 \tabularnewline
134 & 1 & 0.521853 & 0.478147 \tabularnewline
135 & 1 & 0.557103 & 0.442897 \tabularnewline
136 & 1 & 0.53885 & 0.46115 \tabularnewline
137 & 1 & 0.536668 & 0.463332 \tabularnewline
138 & 1 & 0.517587 & 0.482413 \tabularnewline
139 & 1 & 0.51845 & 0.48155 \tabularnewline
140 & 1 & 0.549633 & 0.450367 \tabularnewline
141 & 1 & 0.486801 & 0.513199 \tabularnewline
142 & 1 & 0.565721 & 0.434279 \tabularnewline
143 & 1 & 0.548382 & 0.451618 \tabularnewline
144 & 1 & 1.50542 & -0.505415 \tabularnewline
145 & 0 & -0.439919 & 0.439919 \tabularnewline
146 & 1 & 0.564122 & 0.435878 \tabularnewline
147 & 1 & 0.555289 & 0.444711 \tabularnewline
148 & 1 & 0.557128 & 0.442872 \tabularnewline
149 & 1 & 0.544446 & 0.455554 \tabularnewline
150 & 1 & 0.564011 & 0.435989 \tabularnewline
151 & 1 & 0.535415 & 0.464585 \tabularnewline
152 & 1 & 0.524164 & 0.475836 \tabularnewline
153 & 1 & 0.541486 & 0.458514 \tabularnewline
154 & 1 & 0.553678 & 0.446322 \tabularnewline
155 & 1 & 0.555697 & 0.444303 \tabularnewline
156 & 1 & 0.502005 & 0.497995 \tabularnewline
157 & 1 & 0.54359 & 0.45641 \tabularnewline
158 & 1 & 0.561366 & 0.438634 \tabularnewline
159 & 1 & 0.557942 & 0.442058 \tabularnewline
160 & 1 & 1.52708 & -0.527082 \tabularnewline
161 & 0 & 0.528425 & -0.528425 \tabularnewline
162 & 0 & -0.441719 & 0.441719 \tabularnewline
163 & 1 & 0.537939 & 0.462061 \tabularnewline
164 & 1 & 1.52794 & -0.527943 \tabularnewline
165 & 0 & 0.514131 & -0.514131 \tabularnewline
166 & 0 & 0.556996 & -0.556996 \tabularnewline
167 & 0 & 0.543158 & -0.543158 \tabularnewline
168 & 0 & -0.439016 & 0.439016 \tabularnewline
169 & 1 & 0.541841 & 0.458159 \tabularnewline
170 & 1 & 1.57001 & -0.570012 \tabularnewline
171 & 0 & 0.496723 & -0.496723 \tabularnewline
172 & 0 & 0.558304 & -0.558304 \tabularnewline
173 & 0 & 0.529676 & -0.529676 \tabularnewline
174 & 0 & 0.539275 & -0.539275 \tabularnewline
175 & 0 & 0.501502 & -0.501502 \tabularnewline
176 & 0 & 0.533998 & -0.533998 \tabularnewline
177 & 0 & 0.569223 & -0.569223 \tabularnewline
178 & 0 & 0.528391 & -0.528391 \tabularnewline
179 & 0 & -0.468594 & 0.468594 \tabularnewline
180 & 1 & 0.531406 & 0.468594 \tabularnewline
181 & 1 & 1.5614 & -0.561397 \tabularnewline
182 & 0 & -0.477657 & 0.477657 \tabularnewline
183 & 1 & 0.580516 & 0.419484 \tabularnewline
184 & 1 & 1.54275 & -0.542748 \tabularnewline
185 & 0 & -0.524928 & 0.524928 \tabularnewline
186 & 1 & 1.51929 & -0.519288 \tabularnewline
187 & 0 & 0.538454 & -0.538454 \tabularnewline
188 & 0 & -0.429514 & 0.429514 \tabularnewline
189 & 1 & 1.54711 & -0.547114 \tabularnewline
190 & 0 & 0.522364 & -0.522364 \tabularnewline
191 & 0 & 0.542277 & -0.542277 \tabularnewline
192 & 0 & 0.553122 & -0.553122 \tabularnewline
193 & 0 & 0.516683 & -0.516683 \tabularnewline
194 & 0 & 0.508879 & -0.508879 \tabularnewline
195 & 0 & 0.527175 & -0.527175 \tabularnewline
196 & 0 & 0.489773 & -0.489773 \tabularnewline
197 & 0 & 0.554084 & -0.554084 \tabularnewline
198 & 0 & 0.49068 & -0.49068 \tabularnewline
199 & 0 & 0.574016 & -0.574016 \tabularnewline
200 & 0 & 0.532798 & -0.532798 \tabularnewline
201 & 0 & 0.520965 & -0.520965 \tabularnewline
202 & 0 & -0.466819 & 0.466819 \tabularnewline
203 & 1 & 1.55327 & -0.553272 \tabularnewline
204 & 0 & 0.542332 & -0.542332 \tabularnewline
205 & 0 & 0.546631 & -0.546631 \tabularnewline
206 & 0 & -0.427777 & 0.427777 \tabularnewline
207 & 1 & 1.52844 & -0.528437 \tabularnewline
208 & 0 & -0.471563 & 0.471563 \tabularnewline
209 & 1 & 1.54884 & -0.548839 \tabularnewline
210 & 0 & -0.479374 & 0.479374 \tabularnewline
211 & 1 & 1.53101 & -0.531007 \tabularnewline
212 & 0 & -0.500609 & 0.500609 \tabularnewline
213 & 1 & 1.51453 & -0.514525 \tabularnewline
214 & 0 & 0.518921 & -0.518921 \tabularnewline
215 & 0 & 0.601009 & -0.601009 \tabularnewline
216 & 0 & 0.557518 & -0.557518 \tabularnewline
217 & 0 & 0.49802 & -0.49802 \tabularnewline
218 & 0 & -0.464226 & 0.464226 \tabularnewline
219 & 1 & 0.518921 & 0.481079 \tabularnewline
220 & 1 & 1.52715 & -0.527147 \tabularnewline
221 & 0 & -0.453374 & 0.453374 \tabularnewline
222 & 1 & 0.527184 & 0.472816 \tabularnewline
223 & 1 & 1.55145 & -0.551447 \tabularnewline
224 & 0 & -0.455462 & 0.455462 \tabularnewline
225 & 1 & 0.55701 & 0.44299 \tabularnewline
226 & 1 & 1.49889 & -0.498894 \tabularnewline
227 & 0 & 0.534448 & -0.534448 \tabularnewline
228 & 0 & -0.43643 & 0.43643 \tabularnewline
229 & 1 & 1.48074 & -0.48074 \tabularnewline
230 & 0 & -0.498108 & 0.498108 \tabularnewline
231 & 1 & 0.551895 & 0.448105 \tabularnewline
232 & 1 & 0.573965 & 0.426035 \tabularnewline
233 & 1 & 1.54101 & -0.54101 \tabularnewline
234 & 0 & -0.436836 & 0.436836 \tabularnewline
235 & 1 & 1.53619 & -0.536194 \tabularnewline
236 & 0 & -0.435152 & 0.435152 \tabularnewline
237 & 1 & 0.576593 & 0.423407 \tabularnewline
238 & 1 & 0.592317 & 0.407683 \tabularnewline
239 & 1 & 0.571794 & 0.428206 \tabularnewline
240 & 1 & 1.51494 & -0.51494 \tabularnewline
241 & 0 & -0.478506 & 0.478506 \tabularnewline
242 & 1 & 0.513799 & 0.486201 \tabularnewline
243 & 1 & 0.442071 & 0.557929 \tabularnewline
244 & 1 & 1.51064 & -0.510637 \tabularnewline
245 & 0 & -0.468074 & 0.468074 \tabularnewline
246 & 1 & 0.533322 & 0.466678 \tabularnewline
247 & 1 & 1.52588 & -0.525876 \tabularnewline
248 & 0 & -0.482891 & 0.482891 \tabularnewline
249 & 1 & 1.51284 & -0.512839 \tabularnewline
250 & 0 & 0.539716 & -0.539716 \tabularnewline
251 & 0 & 0.570012 & -0.570012 \tabularnewline
252 & 0 & -0.445152 & 0.445152 \tabularnewline
253 & 1 & 1.49715 & -0.497148 \tabularnewline
254 & 0 & 0.530571 & -0.530571 \tabularnewline
255 & 0 & -0.432934 & 0.432934 \tabularnewline
256 & 1 & 0.534086 & 0.465914 \tabularnewline
257 & 1 & 0.545766 & 0.454234 \tabularnewline
258 & 1 & 0.525396 & 0.474604 \tabularnewline
259 & 1 & 0.507584 & 0.492416 \tabularnewline
260 & 1 & 0.51543 & 0.48457 \tabularnewline
261 & 1 & 1.53187 & -0.531873 \tabularnewline
262 & 0 & 0.54581 & -0.54581 \tabularnewline
263 & 0 & -0.489425 & 0.489425 \tabularnewline
264 & 1 & 1.54748 & -0.547476 \tabularnewline
265 & 0 & 0.470264 & -0.470264 \tabularnewline
266 & 0 & -0.523188 & 0.523188 \tabularnewline
267 & 1 & 1.52325 & -0.52325 \tabularnewline
268 & 0 & 0.483347 & -0.483347 \tabularnewline
269 & 0 & 0.496723 & -0.496723 \tabularnewline
270 & 0 & 0.507561 & -0.507561 \tabularnewline
271 & 0 & 0.509417 & -0.509417 \tabularnewline
272 & 0 & 0.539716 & -0.539716 \tabularnewline
273 & 0 & 0.557515 & -0.557515 \tabularnewline
274 & 0 & 0.515363 & -0.515363 \tabularnewline
275 & 0 & 0.535835 & -0.535835 \tabularnewline
276 & 0 & 0.553634 & -0.553634 \tabularnewline
277 & 0 & 0.541806 & -0.541806 \tabularnewline
278 & 0 & 0.500648 & -0.500648 \tabularnewline
279 & 0 & 0.552778 & -0.552778 \tabularnewline
280 & 0 & 0.503643 & -0.503643 \tabularnewline
281 & 0 & 0.563257 & -0.563257 \tabularnewline
282 & 0 & 0.553976 & -0.553976 \tabularnewline
283 & 0 & 0.540138 & -0.540138 \tabularnewline
284 & 0 & -0.468993 & 0.468993 \tabularnewline
285 & 1 & 1.55359 & -0.55359 \tabularnewline
286 & 0 & 0.475921 & -0.475921 \tabularnewline
287 & 0 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266421&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]1[/C][C]0.521928[/C][C]0.478072[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]0.464179[/C][C]0.535821[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]0.510621[/C][C]0.489379[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]0.516699[/C][C]0.483301[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]0.482496[/C][C]0.517504[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]0.461594[/C][C]0.538406[/C][/ROW]
[ROW][C]7[/C][C]1[/C][C]0.528483[/C][C]0.471517[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]0.538848[/C][C]0.461152[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]0.516676[/C][C]0.483324[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]0.509364[/C][C]0.490636[/C][/ROW]
[ROW][C]11[/C][C]1[/C][C]0.48115[/C][C]0.51885[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]0.507169[/C][C]0.492831[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]0.470767[/C][C]0.529233[/C][/ROW]
[ROW][C]14[/C][C]1[/C][C]0.502409[/C][C]0.497591[/C][/ROW]
[ROW][C]15[/C][C]1[/C][C]0.513247[/C][C]0.486753[/C][/ROW]
[ROW][C]16[/C][C]1[/C][C]0.471644[/C][C]0.528356[/C][/ROW]
[ROW][C]17[/C][C]0[/C][C]0.514152[/C][C]-0.514152[/C][/ROW]
[ROW][C]18[/C][C]1[/C][C]0.512379[/C][C]0.487621[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]0.487205[/C][C]0.512795[/C][/ROW]
[ROW][C]20[/C][C]0[/C][C]0.492424[/C][C]-0.492424[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]0.502[/C][C]0.498[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]0.469895[/C][C]0.530105[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]0.526247[/C][C]0.473753[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]0.5024[/C][C]0.4976[/C][/ROW]
[ROW][C]25[/C][C]1[/C][C]0.530608[/C][C]0.469392[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]0.504975[/C][C]0.495025[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]0.520276[/C][C]0.479724[/C][/ROW]
[ROW][C]28[/C][C]0[/C][C]0.535299[/C][C]-0.535299[/C][/ROW]
[ROW][C]29[/C][C]0[/C][C]0.526702[/C][C]-0.526702[/C][/ROW]
[ROW][C]30[/C][C]1[/C][C]0.489358[/C][C]0.510642[/C][/ROW]
[ROW][C]31[/C][C]1[/C][C]0.51327[/C][C]0.48673[/C][/ROW]
[ROW][C]32[/C][C]1[/C][C]0.485071[/C][C]0.514929[/C][/ROW]
[ROW][C]33[/C][C]1[/C][C]0.510644[/C][C]0.489356[/C][/ROW]
[ROW][C]34[/C][C]1[/C][C]0.453336[/C][C]0.546664[/C][/ROW]
[ROW][C]35[/C][C]1[/C][C]0.481549[/C][C]0.518451[/C][/ROW]
[ROW][C]36[/C][C]1[/C][C]0.496345[/C][C]0.503655[/C][/ROW]
[ROW][C]37[/C][C]1[/C][C]0.499783[/C][C]0.500217[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]0.494136[/C][C]0.505864[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]0.514193[/C][C]0.485807[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]0.528915[/C][C]-0.528915[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.486769[/C][C]0.513231[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]0.502353[/C][C]0.497647[/C][/ROW]
[ROW][C]43[/C][C]1[/C][C]0.456398[/C][C]0.543602[/C][/ROW]
[ROW][C]44[/C][C]1[/C][C]0.501063[/C][C]0.498937[/C][/ROW]
[ROW][C]45[/C][C]1[/C][C]0.515817[/C][C]0.484183[/C][/ROW]
[ROW][C]46[/C][C]1[/C][C]0.496294[/C][C]0.503706[/C][/ROW]
[ROW][C]47[/C][C]0[/C][C]0.51585[/C][C]-0.51585[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]0.503249[/C][C]0.496751[/C][/ROW]
[ROW][C]49[/C][C]1[/C][C]0.518053[/C][C]0.481947[/C][/ROW]
[ROW][C]50[/C][C]0[/C][C]0.477239[/C][C]-0.477239[/C][/ROW]
[ROW][C]51[/C][C]1[/C][C]0.525862[/C][C]0.474138[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0.506255[/C][C]-0.506255[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]0.502799[/C][C]-0.502799[/C][/ROW]
[ROW][C]54[/C][C]0[/C][C]0.473806[/C][C]-0.473806[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]0.497598[/C][C]0.502402[/C][/ROW]
[ROW][C]56[/C][C]0[/C][C]0.517603[/C][C]-0.517603[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]0.530195[/C][C]0.469805[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]0.483679[/C][C]0.516321[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]0.454663[/C][C]-0.454663[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]0.544541[/C][C]0.455459[/C][/ROW]
[ROW][C]61[/C][C]0[/C][C]0.495115[/C][C]-0.495115[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0.513187[/C][C]-0.513187[/C][/ROW]
[ROW][C]63[/C][C]1[/C][C]0.478919[/C][C]0.521081[/C][/ROW]
[ROW][C]64[/C][C]1[/C][C]0.514532[/C][C]0.485468[/C][/ROW]
[ROW][C]65[/C][C]1[/C][C]0.468095[/C][C]0.531905[/C][/ROW]
[ROW][C]66[/C][C]1[/C][C]0.549264[/C][C]0.450736[/C][/ROW]
[ROW][C]67[/C][C]1[/C][C]0.488954[/C][C]0.511046[/C][/ROW]
[ROW][C]68[/C][C]0[/C][C]0.485034[/C][C]-0.485034[/C][/ROW]
[ROW][C]69[/C][C]1[/C][C]0.502822[/C][C]0.497178[/C][/ROW]
[ROW][C]70[/C][C]1[/C][C]0.521051[/C][C]0.478949[/C][/ROW]
[ROW][C]71[/C][C]1[/C][C]0.537554[/C][C]0.462446[/C][/ROW]
[ROW][C]72[/C][C]0[/C][C]0.517163[/C][C]-0.517163[/C][/ROW]
[ROW][C]73[/C][C]1[/C][C]0.509308[/C][C]0.490692[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]0.510658[/C][C]0.489342[/C][/ROW]
[ROW][C]75[/C][C]0[/C][C]0.484175[/C][C]-0.484175[/C][/ROW]
[ROW][C]76[/C][C]0[/C][C]0.529263[/C][C]-0.529263[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]0.463311[/C][C]0.536689[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]0.5311[/C][C]0.4689[/C][/ROW]
[ROW][C]79[/C][C]1[/C][C]0.531081[/C][C]0.468919[/C][/ROW]
[ROW][C]80[/C][C]1[/C][C]1.51409[/C][C]-0.514091[/C][/ROW]
[ROW][C]81[/C][C]0[/C][C]-0.473725[/C][C]0.473725[/C][/ROW]
[ROW][C]82[/C][C]1[/C][C]1.50898[/C][C]-0.508983[/C][/ROW]
[ROW][C]83[/C][C]0[/C][C]-0.531038[/C][C]0.531038[/C][/ROW]
[ROW][C]84[/C][C]1[/C][C]1.49413[/C][C]-0.494127[/C][/ROW]
[ROW][C]85[/C][C]0[/C][C]0.540221[/C][C]-0.540221[/C][/ROW]
[ROW][C]86[/C][C]0[/C][C]0.498034[/C][C]-0.498034[/C][/ROW]
[ROW][C]87[/C][C]0[/C][C]0.446005[/C][C]-0.446005[/C][/ROW]
[ROW][C]88[/C][C]0[/C][C]0.512017[/C][C]-0.512017[/C][/ROW]
[ROW][C]89[/C][C]0[/C][C]0.511948[/C][C]-0.511948[/C][/ROW]
[ROW][C]90[/C][C]0[/C][C]0.509359[/C][C]-0.509359[/C][/ROW]
[ROW][C]91[/C][C]0[/C][C]0.503244[/C][C]-0.503244[/C][/ROW]
[ROW][C]92[/C][C]0[/C][C]0.478951[/C][C]-0.478951[/C][/ROW]
[ROW][C]93[/C][C]0[/C][C]0.527147[/C][C]-0.527147[/C][/ROW]
[ROW][C]94[/C][C]0[/C][C]0.516272[/C][C]-0.516272[/C][/ROW]
[ROW][C]95[/C][C]0[/C][C]0.454668[/C][C]-0.454668[/C][/ROW]
[ROW][C]96[/C][C]0[/C][C]0.496772[/C][C]-0.496772[/C][/ROW]
[ROW][C]97[/C][C]0[/C][C]0.480686[/C][C]-0.480686[/C][/ROW]
[ROW][C]98[/C][C]0[/C][C]0.478557[/C][C]-0.478557[/C][/ROW]
[ROW][C]99[/C][C]0[/C][C]0.489399[/C][C]-0.489399[/C][/ROW]
[ROW][C]100[/C][C]0[/C][C]0.465492[/C][C]-0.465492[/C][/ROW]
[ROW][C]101[/C][C]0[/C][C]0.5015[/C][C]-0.5015[/C][/ROW]
[ROW][C]102[/C][C]0[/C][C]0.519715[/C][C]-0.519715[/C][/ROW]
[ROW][C]103[/C][C]0[/C][C]0.472442[/C][C]-0.472442[/C][/ROW]
[ROW][C]104[/C][C]0[/C][C]0.497171[/C][C]-0.497171[/C][/ROW]
[ROW][C]105[/C][C]0[/C][C]0.498934[/C][C]-0.498934[/C][/ROW]
[ROW][C]106[/C][C]0[/C][C]0.500335[/C][C]-0.500335[/C][/ROW]
[ROW][C]107[/C][C]0[/C][C]0.499402[/C][C]-0.499402[/C][/ROW]
[ROW][C]108[/C][C]0[/C][C]0.536695[/C][C]-0.536695[/C][/ROW]
[ROW][C]109[/C][C]0[/C][C]0.4964[/C][C]-0.4964[/C][/ROW]
[ROW][C]110[/C][C]0[/C][C]0.542397[/C][C]-0.542397[/C][/ROW]
[ROW][C]111[/C][C]0[/C][C]0.459061[/C][C]-0.459061[/C][/ROW]
[ROW][C]112[/C][C]0[/C][C]0.465533[/C][C]-0.465533[/C][/ROW]
[ROW][C]113[/C][C]0[/C][C]0.49853[/C][C]-0.49853[/C][/ROW]
[ROW][C]114[/C][C]0[/C][C]0.512393[/C][C]-0.512393[/C][/ROW]
[ROW][C]115[/C][C]0[/C][C]0.505002[/C][C]-0.505002[/C][/ROW]
[ROW][C]116[/C][C]0[/C][C]-0.559666[/C][C]0.559666[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]0.510162[/C][C]0.489838[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]0.562246[/C][C]0.437754[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]0.550918[/C][C]0.449082[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]1.53658[/C][C]-0.536584[/C][/ROW]
[ROW][C]121[/C][C]0[/C][C]0.524994[/C][C]-0.524994[/C][/ROW]
[ROW][C]122[/C][C]0[/C][C]-0.453844[/C][C]0.453844[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]0.564816[/C][C]0.435184[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]0.544894[/C][C]0.455106[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]0.530629[/C][C]0.469371[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]0.568773[/C][C]0.431227[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]0.531439[/C][C]0.468561[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]0.499792[/C][C]0.500208[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]0.524558[/C][C]0.475442[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]0.551431[/C][C]0.448569[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]0.534543[/C][C]0.465457[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]1.56962[/C][C]-0.569623[/C][/ROW]
[ROW][C]133[/C][C]0[/C][C]-0.479436[/C][C]0.479436[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]0.521853[/C][C]0.478147[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]0.557103[/C][C]0.442897[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]0.53885[/C][C]0.46115[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]0.536668[/C][C]0.463332[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]0.517587[/C][C]0.482413[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]0.51845[/C][C]0.48155[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]0.549633[/C][C]0.450367[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]0.486801[/C][C]0.513199[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]0.565721[/C][C]0.434279[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]0.548382[/C][C]0.451618[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]1.50542[/C][C]-0.505415[/C][/ROW]
[ROW][C]145[/C][C]0[/C][C]-0.439919[/C][C]0.439919[/C][/ROW]
[ROW][C]146[/C][C]1[/C][C]0.564122[/C][C]0.435878[/C][/ROW]
[ROW][C]147[/C][C]1[/C][C]0.555289[/C][C]0.444711[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]0.557128[/C][C]0.442872[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]0.544446[/C][C]0.455554[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]0.564011[/C][C]0.435989[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]0.535415[/C][C]0.464585[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]0.524164[/C][C]0.475836[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]0.541486[/C][C]0.458514[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]0.553678[/C][C]0.446322[/C][/ROW]
[ROW][C]155[/C][C]1[/C][C]0.555697[/C][C]0.444303[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]0.502005[/C][C]0.497995[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]0.54359[/C][C]0.45641[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]0.561366[/C][C]0.438634[/C][/ROW]
[ROW][C]159[/C][C]1[/C][C]0.557942[/C][C]0.442058[/C][/ROW]
[ROW][C]160[/C][C]1[/C][C]1.52708[/C][C]-0.527082[/C][/ROW]
[ROW][C]161[/C][C]0[/C][C]0.528425[/C][C]-0.528425[/C][/ROW]
[ROW][C]162[/C][C]0[/C][C]-0.441719[/C][C]0.441719[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]0.537939[/C][C]0.462061[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]1.52794[/C][C]-0.527943[/C][/ROW]
[ROW][C]165[/C][C]0[/C][C]0.514131[/C][C]-0.514131[/C][/ROW]
[ROW][C]166[/C][C]0[/C][C]0.556996[/C][C]-0.556996[/C][/ROW]
[ROW][C]167[/C][C]0[/C][C]0.543158[/C][C]-0.543158[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]-0.439016[/C][C]0.439016[/C][/ROW]
[ROW][C]169[/C][C]1[/C][C]0.541841[/C][C]0.458159[/C][/ROW]
[ROW][C]170[/C][C]1[/C][C]1.57001[/C][C]-0.570012[/C][/ROW]
[ROW][C]171[/C][C]0[/C][C]0.496723[/C][C]-0.496723[/C][/ROW]
[ROW][C]172[/C][C]0[/C][C]0.558304[/C][C]-0.558304[/C][/ROW]
[ROW][C]173[/C][C]0[/C][C]0.529676[/C][C]-0.529676[/C][/ROW]
[ROW][C]174[/C][C]0[/C][C]0.539275[/C][C]-0.539275[/C][/ROW]
[ROW][C]175[/C][C]0[/C][C]0.501502[/C][C]-0.501502[/C][/ROW]
[ROW][C]176[/C][C]0[/C][C]0.533998[/C][C]-0.533998[/C][/ROW]
[ROW][C]177[/C][C]0[/C][C]0.569223[/C][C]-0.569223[/C][/ROW]
[ROW][C]178[/C][C]0[/C][C]0.528391[/C][C]-0.528391[/C][/ROW]
[ROW][C]179[/C][C]0[/C][C]-0.468594[/C][C]0.468594[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]0.531406[/C][C]0.468594[/C][/ROW]
[ROW][C]181[/C][C]1[/C][C]1.5614[/C][C]-0.561397[/C][/ROW]
[ROW][C]182[/C][C]0[/C][C]-0.477657[/C][C]0.477657[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]0.580516[/C][C]0.419484[/C][/ROW]
[ROW][C]184[/C][C]1[/C][C]1.54275[/C][C]-0.542748[/C][/ROW]
[ROW][C]185[/C][C]0[/C][C]-0.524928[/C][C]0.524928[/C][/ROW]
[ROW][C]186[/C][C]1[/C][C]1.51929[/C][C]-0.519288[/C][/ROW]
[ROW][C]187[/C][C]0[/C][C]0.538454[/C][C]-0.538454[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]-0.429514[/C][C]0.429514[/C][/ROW]
[ROW][C]189[/C][C]1[/C][C]1.54711[/C][C]-0.547114[/C][/ROW]
[ROW][C]190[/C][C]0[/C][C]0.522364[/C][C]-0.522364[/C][/ROW]
[ROW][C]191[/C][C]0[/C][C]0.542277[/C][C]-0.542277[/C][/ROW]
[ROW][C]192[/C][C]0[/C][C]0.553122[/C][C]-0.553122[/C][/ROW]
[ROW][C]193[/C][C]0[/C][C]0.516683[/C][C]-0.516683[/C][/ROW]
[ROW][C]194[/C][C]0[/C][C]0.508879[/C][C]-0.508879[/C][/ROW]
[ROW][C]195[/C][C]0[/C][C]0.527175[/C][C]-0.527175[/C][/ROW]
[ROW][C]196[/C][C]0[/C][C]0.489773[/C][C]-0.489773[/C][/ROW]
[ROW][C]197[/C][C]0[/C][C]0.554084[/C][C]-0.554084[/C][/ROW]
[ROW][C]198[/C][C]0[/C][C]0.49068[/C][C]-0.49068[/C][/ROW]
[ROW][C]199[/C][C]0[/C][C]0.574016[/C][C]-0.574016[/C][/ROW]
[ROW][C]200[/C][C]0[/C][C]0.532798[/C][C]-0.532798[/C][/ROW]
[ROW][C]201[/C][C]0[/C][C]0.520965[/C][C]-0.520965[/C][/ROW]
[ROW][C]202[/C][C]0[/C][C]-0.466819[/C][C]0.466819[/C][/ROW]
[ROW][C]203[/C][C]1[/C][C]1.55327[/C][C]-0.553272[/C][/ROW]
[ROW][C]204[/C][C]0[/C][C]0.542332[/C][C]-0.542332[/C][/ROW]
[ROW][C]205[/C][C]0[/C][C]0.546631[/C][C]-0.546631[/C][/ROW]
[ROW][C]206[/C][C]0[/C][C]-0.427777[/C][C]0.427777[/C][/ROW]
[ROW][C]207[/C][C]1[/C][C]1.52844[/C][C]-0.528437[/C][/ROW]
[ROW][C]208[/C][C]0[/C][C]-0.471563[/C][C]0.471563[/C][/ROW]
[ROW][C]209[/C][C]1[/C][C]1.54884[/C][C]-0.548839[/C][/ROW]
[ROW][C]210[/C][C]0[/C][C]-0.479374[/C][C]0.479374[/C][/ROW]
[ROW][C]211[/C][C]1[/C][C]1.53101[/C][C]-0.531007[/C][/ROW]
[ROW][C]212[/C][C]0[/C][C]-0.500609[/C][C]0.500609[/C][/ROW]
[ROW][C]213[/C][C]1[/C][C]1.51453[/C][C]-0.514525[/C][/ROW]
[ROW][C]214[/C][C]0[/C][C]0.518921[/C][C]-0.518921[/C][/ROW]
[ROW][C]215[/C][C]0[/C][C]0.601009[/C][C]-0.601009[/C][/ROW]
[ROW][C]216[/C][C]0[/C][C]0.557518[/C][C]-0.557518[/C][/ROW]
[ROW][C]217[/C][C]0[/C][C]0.49802[/C][C]-0.49802[/C][/ROW]
[ROW][C]218[/C][C]0[/C][C]-0.464226[/C][C]0.464226[/C][/ROW]
[ROW][C]219[/C][C]1[/C][C]0.518921[/C][C]0.481079[/C][/ROW]
[ROW][C]220[/C][C]1[/C][C]1.52715[/C][C]-0.527147[/C][/ROW]
[ROW][C]221[/C][C]0[/C][C]-0.453374[/C][C]0.453374[/C][/ROW]
[ROW][C]222[/C][C]1[/C][C]0.527184[/C][C]0.472816[/C][/ROW]
[ROW][C]223[/C][C]1[/C][C]1.55145[/C][C]-0.551447[/C][/ROW]
[ROW][C]224[/C][C]0[/C][C]-0.455462[/C][C]0.455462[/C][/ROW]
[ROW][C]225[/C][C]1[/C][C]0.55701[/C][C]0.44299[/C][/ROW]
[ROW][C]226[/C][C]1[/C][C]1.49889[/C][C]-0.498894[/C][/ROW]
[ROW][C]227[/C][C]0[/C][C]0.534448[/C][C]-0.534448[/C][/ROW]
[ROW][C]228[/C][C]0[/C][C]-0.43643[/C][C]0.43643[/C][/ROW]
[ROW][C]229[/C][C]1[/C][C]1.48074[/C][C]-0.48074[/C][/ROW]
[ROW][C]230[/C][C]0[/C][C]-0.498108[/C][C]0.498108[/C][/ROW]
[ROW][C]231[/C][C]1[/C][C]0.551895[/C][C]0.448105[/C][/ROW]
[ROW][C]232[/C][C]1[/C][C]0.573965[/C][C]0.426035[/C][/ROW]
[ROW][C]233[/C][C]1[/C][C]1.54101[/C][C]-0.54101[/C][/ROW]
[ROW][C]234[/C][C]0[/C][C]-0.436836[/C][C]0.436836[/C][/ROW]
[ROW][C]235[/C][C]1[/C][C]1.53619[/C][C]-0.536194[/C][/ROW]
[ROW][C]236[/C][C]0[/C][C]-0.435152[/C][C]0.435152[/C][/ROW]
[ROW][C]237[/C][C]1[/C][C]0.576593[/C][C]0.423407[/C][/ROW]
[ROW][C]238[/C][C]1[/C][C]0.592317[/C][C]0.407683[/C][/ROW]
[ROW][C]239[/C][C]1[/C][C]0.571794[/C][C]0.428206[/C][/ROW]
[ROW][C]240[/C][C]1[/C][C]1.51494[/C][C]-0.51494[/C][/ROW]
[ROW][C]241[/C][C]0[/C][C]-0.478506[/C][C]0.478506[/C][/ROW]
[ROW][C]242[/C][C]1[/C][C]0.513799[/C][C]0.486201[/C][/ROW]
[ROW][C]243[/C][C]1[/C][C]0.442071[/C][C]0.557929[/C][/ROW]
[ROW][C]244[/C][C]1[/C][C]1.51064[/C][C]-0.510637[/C][/ROW]
[ROW][C]245[/C][C]0[/C][C]-0.468074[/C][C]0.468074[/C][/ROW]
[ROW][C]246[/C][C]1[/C][C]0.533322[/C][C]0.466678[/C][/ROW]
[ROW][C]247[/C][C]1[/C][C]1.52588[/C][C]-0.525876[/C][/ROW]
[ROW][C]248[/C][C]0[/C][C]-0.482891[/C][C]0.482891[/C][/ROW]
[ROW][C]249[/C][C]1[/C][C]1.51284[/C][C]-0.512839[/C][/ROW]
[ROW][C]250[/C][C]0[/C][C]0.539716[/C][C]-0.539716[/C][/ROW]
[ROW][C]251[/C][C]0[/C][C]0.570012[/C][C]-0.570012[/C][/ROW]
[ROW][C]252[/C][C]0[/C][C]-0.445152[/C][C]0.445152[/C][/ROW]
[ROW][C]253[/C][C]1[/C][C]1.49715[/C][C]-0.497148[/C][/ROW]
[ROW][C]254[/C][C]0[/C][C]0.530571[/C][C]-0.530571[/C][/ROW]
[ROW][C]255[/C][C]0[/C][C]-0.432934[/C][C]0.432934[/C][/ROW]
[ROW][C]256[/C][C]1[/C][C]0.534086[/C][C]0.465914[/C][/ROW]
[ROW][C]257[/C][C]1[/C][C]0.545766[/C][C]0.454234[/C][/ROW]
[ROW][C]258[/C][C]1[/C][C]0.525396[/C][C]0.474604[/C][/ROW]
[ROW][C]259[/C][C]1[/C][C]0.507584[/C][C]0.492416[/C][/ROW]
[ROW][C]260[/C][C]1[/C][C]0.51543[/C][C]0.48457[/C][/ROW]
[ROW][C]261[/C][C]1[/C][C]1.53187[/C][C]-0.531873[/C][/ROW]
[ROW][C]262[/C][C]0[/C][C]0.54581[/C][C]-0.54581[/C][/ROW]
[ROW][C]263[/C][C]0[/C][C]-0.489425[/C][C]0.489425[/C][/ROW]
[ROW][C]264[/C][C]1[/C][C]1.54748[/C][C]-0.547476[/C][/ROW]
[ROW][C]265[/C][C]0[/C][C]0.470264[/C][C]-0.470264[/C][/ROW]
[ROW][C]266[/C][C]0[/C][C]-0.523188[/C][C]0.523188[/C][/ROW]
[ROW][C]267[/C][C]1[/C][C]1.52325[/C][C]-0.52325[/C][/ROW]
[ROW][C]268[/C][C]0[/C][C]0.483347[/C][C]-0.483347[/C][/ROW]
[ROW][C]269[/C][C]0[/C][C]0.496723[/C][C]-0.496723[/C][/ROW]
[ROW][C]270[/C][C]0[/C][C]0.507561[/C][C]-0.507561[/C][/ROW]
[ROW][C]271[/C][C]0[/C][C]0.509417[/C][C]-0.509417[/C][/ROW]
[ROW][C]272[/C][C]0[/C][C]0.539716[/C][C]-0.539716[/C][/ROW]
[ROW][C]273[/C][C]0[/C][C]0.557515[/C][C]-0.557515[/C][/ROW]
[ROW][C]274[/C][C]0[/C][C]0.515363[/C][C]-0.515363[/C][/ROW]
[ROW][C]275[/C][C]0[/C][C]0.535835[/C][C]-0.535835[/C][/ROW]
[ROW][C]276[/C][C]0[/C][C]0.553634[/C][C]-0.553634[/C][/ROW]
[ROW][C]277[/C][C]0[/C][C]0.541806[/C][C]-0.541806[/C][/ROW]
[ROW][C]278[/C][C]0[/C][C]0.500648[/C][C]-0.500648[/C][/ROW]
[ROW][C]279[/C][C]0[/C][C]0.552778[/C][C]-0.552778[/C][/ROW]
[ROW][C]280[/C][C]0[/C][C]0.503643[/C][C]-0.503643[/C][/ROW]
[ROW][C]281[/C][C]0[/C][C]0.563257[/C][C]-0.563257[/C][/ROW]
[ROW][C]282[/C][C]0[/C][C]0.553976[/C][C]-0.553976[/C][/ROW]
[ROW][C]283[/C][C]0[/C][C]0.540138[/C][C]-0.540138[/C][/ROW]
[ROW][C]284[/C][C]0[/C][C]-0.468993[/C][C]0.468993[/C][/ROW]
[ROW][C]285[/C][C]1[/C][C]1.55359[/C][C]-0.55359[/C][/ROW]
[ROW][C]286[/C][C]0[/C][C]0.475921[/C][C]-0.475921[/C][/ROW]
[ROW][C]287[/C][C]0[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266421&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266421&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
110.5219280.478072
210.4641790.535821
310.5106210.489379
410.5166990.483301
510.4824960.517504
610.4615940.538406
710.5284830.471517
810.5388480.461152
910.5166760.483324
1010.5093640.490636
1110.481150.51885
1210.5071690.492831
1310.4707670.529233
1410.5024090.497591
1510.5132470.486753
1610.4716440.528356
1700.514152-0.514152
1810.5123790.487621
1910.4872050.512795
2000.492424-0.492424
2110.5020.498
2210.4698950.530105
2310.5262470.473753
2410.50240.4976
2510.5306080.469392
2610.5049750.495025
2710.5202760.479724
2800.535299-0.535299
2900.526702-0.526702
3010.4893580.510642
3110.513270.48673
3210.4850710.514929
3310.5106440.489356
3410.4533360.546664
3510.4815490.518451
3610.4963450.503655
3710.4997830.500217
3810.4941360.505864
3910.5141930.485807
4000.528915-0.528915
4110.4867690.513231
4210.5023530.497647
4310.4563980.543602
4410.5010630.498937
4510.5158170.484183
4610.4962940.503706
4700.51585-0.51585
4810.5032490.496751
4910.5180530.481947
5000.477239-0.477239
5110.5258620.474138
5200.506255-0.506255
5300.502799-0.502799
5400.473806-0.473806
5510.4975980.502402
5600.517603-0.517603
5710.5301950.469805
5810.4836790.516321
5900.454663-0.454663
6010.5445410.455459
6100.495115-0.495115
6200.513187-0.513187
6310.4789190.521081
6410.5145320.485468
6510.4680950.531905
6610.5492640.450736
6710.4889540.511046
6800.485034-0.485034
6910.5028220.497178
7010.5210510.478949
7110.5375540.462446
7200.517163-0.517163
7310.5093080.490692
7410.5106580.489342
7500.484175-0.484175
7600.529263-0.529263
7710.4633110.536689
7810.53110.4689
7910.5310810.468919
8011.51409-0.514091
810-0.4737250.473725
8211.50898-0.508983
830-0.5310380.531038
8411.49413-0.494127
8500.540221-0.540221
8600.498034-0.498034
8700.446005-0.446005
8800.512017-0.512017
8900.511948-0.511948
9000.509359-0.509359
9100.503244-0.503244
9200.478951-0.478951
9300.527147-0.527147
9400.516272-0.516272
9500.454668-0.454668
9600.496772-0.496772
9700.480686-0.480686
9800.478557-0.478557
9900.489399-0.489399
10000.465492-0.465492
10100.5015-0.5015
10200.519715-0.519715
10300.472442-0.472442
10400.497171-0.497171
10500.498934-0.498934
10600.500335-0.500335
10700.499402-0.499402
10800.536695-0.536695
10900.4964-0.4964
11000.542397-0.542397
11100.459061-0.459061
11200.465533-0.465533
11300.49853-0.49853
11400.512393-0.512393
11500.505002-0.505002
1160-0.5596660.559666
11710.5101620.489838
11810.5622460.437754
11910.5509180.449082
12011.53658-0.536584
12100.524994-0.524994
1220-0.4538440.453844
12310.5648160.435184
12410.5448940.455106
12510.5306290.469371
12610.5687730.431227
12710.5314390.468561
12810.4997920.500208
12910.5245580.475442
13010.5514310.448569
13110.5345430.465457
13211.56962-0.569623
1330-0.4794360.479436
13410.5218530.478147
13510.5571030.442897
13610.538850.46115
13710.5366680.463332
13810.5175870.482413
13910.518450.48155
14010.5496330.450367
14110.4868010.513199
14210.5657210.434279
14310.5483820.451618
14411.50542-0.505415
1450-0.4399190.439919
14610.5641220.435878
14710.5552890.444711
14810.5571280.442872
14910.5444460.455554
15010.5640110.435989
15110.5354150.464585
15210.5241640.475836
15310.5414860.458514
15410.5536780.446322
15510.5556970.444303
15610.5020050.497995
15710.543590.45641
15810.5613660.438634
15910.5579420.442058
16011.52708-0.527082
16100.528425-0.528425
1620-0.4417190.441719
16310.5379390.462061
16411.52794-0.527943
16500.514131-0.514131
16600.556996-0.556996
16700.543158-0.543158
1680-0.4390160.439016
16910.5418410.458159
17011.57001-0.570012
17100.496723-0.496723
17200.558304-0.558304
17300.529676-0.529676
17400.539275-0.539275
17500.501502-0.501502
17600.533998-0.533998
17700.569223-0.569223
17800.528391-0.528391
1790-0.4685940.468594
18010.5314060.468594
18111.5614-0.561397
1820-0.4776570.477657
18310.5805160.419484
18411.54275-0.542748
1850-0.5249280.524928
18611.51929-0.519288
18700.538454-0.538454
1880-0.4295140.429514
18911.54711-0.547114
19000.522364-0.522364
19100.542277-0.542277
19200.553122-0.553122
19300.516683-0.516683
19400.508879-0.508879
19500.527175-0.527175
19600.489773-0.489773
19700.554084-0.554084
19800.49068-0.49068
19900.574016-0.574016
20000.532798-0.532798
20100.520965-0.520965
2020-0.4668190.466819
20311.55327-0.553272
20400.542332-0.542332
20500.546631-0.546631
2060-0.4277770.427777
20711.52844-0.528437
2080-0.4715630.471563
20911.54884-0.548839
2100-0.4793740.479374
21111.53101-0.531007
2120-0.5006090.500609
21311.51453-0.514525
21400.518921-0.518921
21500.601009-0.601009
21600.557518-0.557518
21700.49802-0.49802
2180-0.4642260.464226
21910.5189210.481079
22011.52715-0.527147
2210-0.4533740.453374
22210.5271840.472816
22311.55145-0.551447
2240-0.4554620.455462
22510.557010.44299
22611.49889-0.498894
22700.534448-0.534448
2280-0.436430.43643
22911.48074-0.48074
2300-0.4981080.498108
23110.5518950.448105
23210.5739650.426035
23311.54101-0.54101
2340-0.4368360.436836
23511.53619-0.536194
2360-0.4351520.435152
23710.5765930.423407
23810.5923170.407683
23910.5717940.428206
24011.51494-0.51494
2410-0.4785060.478506
24210.5137990.486201
24310.4420710.557929
24411.51064-0.510637
2450-0.4680740.468074
24610.5333220.466678
24711.52588-0.525876
2480-0.4828910.482891
24911.51284-0.512839
25000.539716-0.539716
25100.570012-0.570012
2520-0.4451520.445152
25311.49715-0.497148
25400.530571-0.530571
2550-0.4329340.432934
25610.5340860.465914
25710.5457660.454234
25810.5253960.474604
25910.5075840.492416
26010.515430.48457
26111.53187-0.531873
26200.54581-0.54581
2630-0.4894250.489425
26411.54748-0.547476
26500.470264-0.470264
2660-0.5231880.523188
26711.52325-0.52325
26800.483347-0.483347
26900.496723-0.496723
27000.507561-0.507561
27100.509417-0.509417
27200.539716-0.539716
27300.557515-0.557515
27400.515363-0.515363
27500.535835-0.535835
27600.553634-0.553634
27700.541806-0.541806
27800.500648-0.500648
27900.552778-0.552778
28000.503643-0.503643
28100.563257-0.563257
28200.553976-0.553976
28300.540138-0.540138
2840-0.4689930.468993
28511.55359-0.55359
28600.475921-0.475921
2870NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
61.55942e-463.11885e-461
7001
89.98385e-771.99677e-761
9001
10001
113.19725e-1226.39449e-1221
121.14106e-1342.28213e-1341
13001
14001
157.61696e-1831.52339e-1821
16001
170.002209250.004418490.997791
180.00107530.002150610.998925
190.0005001590.001000320.9995
200.01757190.03514370.982428
210.01157090.02314190.988429
220.007344120.01468820.992656
230.004439150.00887830.995561
240.002650960.005301920.997349
250.001577560.003155120.998422
260.0008939310.001787860.999106
270.0005765490.00115310.999423
280.004830760.009661530.995169
290.01746660.03493320.982533
300.01252830.02505660.987472
310.008971160.01794230.991029
320.006144160.01228830.993856
330.004374540.008749090.995625
340.002967890.005935770.997032
350.002011140.004022270.997989
360.001344410.002688820.998656
370.0009165420.001833080.999083
380.0006154950.001230990.999385
390.0003993760.0007987510.999601
400.001812340.003624680.998188
410.001258370.002516740.998742
420.0008982940.001796590.999102
430.000645040.001290080.999355
440.0004541620.0009083250.999546
450.0003327280.0006654560.999667
460.0002289930.0004579860.999771
470.0009732020.00194640.999027
480.0007176950.001435390.999282
490.0005545970.001109190.999445
500.003325820.006651630.996674
510.002704920.005409840.997295
520.00664480.01328960.993355
530.01337950.02675890.986621
540.03369880.06739760.966301
550.02913940.05827880.970861
560.04535350.0907070.954646
570.04045330.08090660.959547
580.03540460.07080920.964595
590.06330620.1266120.936694
600.05566890.1113380.944331
610.08022260.1604450.919777
620.1085640.2171270.891436
630.1002070.2004140.899793
640.09141410.1828280.908586
650.08509840.1701970.914902
660.07683130.1536630.923169
670.07099460.1419890.929005
680.09653430.1930690.903466
690.0893760.1787520.910624
700.0817080.1634160.918292
710.07372880.1474580.926271
720.09770410.1954080.902296
730.0905510.1811020.909449
740.08423820.1684760.915762
750.1082750.2165490.891725
760.1355310.2710620.864469
770.133280.2665610.86672
780.1244480.2488950.875552
790.1159390.2318780.884061
800.1408170.2816330.859183
810.1326340.2652690.867366
820.1615240.3230490.838476
830.1608280.3216560.839172
840.188530.377060.81147
850.2149390.4298770.785061
860.243580.4871590.75642
870.2716940.5433880.728306
880.2929180.5858360.707082
890.318190.636380.68181
900.3402390.6804790.659761
910.364710.7294210.63529
920.3848590.7697180.615141
930.4053920.8107830.594608
940.42480.84960.5752
950.4382180.8764360.561782
960.4509480.9018970.549052
970.4621170.9242330.537883
980.4679270.9358550.532073
990.474370.9487410.52563
1000.4775550.955110.522445
1010.4885030.9770060.511497
1020.5029560.9940880.497044
1030.5030810.9938370.496919
1040.5080580.9838850.491942
1050.5123320.9753350.487668
1060.5125930.9748140.487407
1070.5132290.9735430.486771
1080.5251670.9496660.474833
1090.5205410.9589170.479459
1100.5253760.9492480.474624
1110.5127730.9744550.487227
1120.5039810.9920380.496019
1130.5003720.9992560.499628
1140.5030440.9939120.496956
1150.5052840.9894310.494716
1160.5222360.9555280.477764
1170.5172840.9654320.482716
1180.5004540.9990930.499546
1190.4835760.9671520.516424
1200.510090.9798210.48991
1210.5124080.9751830.487592
1220.4992780.9985570.500722
1230.4822860.9645730.517714
1240.4708440.9416890.529156
1250.466240.9324810.53376
1260.4496820.8993640.550318
1270.4411050.8822090.558895
1280.4435980.8871960.556402
1290.440980.8819590.55902
1300.4287110.8574210.571289
1310.4231420.8462830.576858
1320.4541390.9082770.545861
1330.449620.8992410.55038
1340.4453360.8906730.554664
1350.4338320.8676640.566168
1360.4263480.8526960.573652
1370.4192370.8384740.580763
1380.4191340.8382680.580866
1390.4190250.838050.580975
1400.4085120.8170230.591488
1410.4238260.8476520.576174
1420.409060.8181190.59094
1430.3999790.7999580.600021
1440.4036720.8073450.596328
1450.3916430.7832860.608357
1460.3815950.7631890.618405
1470.3719380.7438760.628062
1480.3623590.7247190.637641
1490.3566030.7132060.643397
1500.3458110.6916230.654189
1510.3437660.6875310.656234
1520.3471130.6942260.652887
1530.3443380.6886760.655662
1540.3396480.6792950.660352
1550.3333480.6666960.666652
1560.3470290.6940580.652971
1570.3450030.6900070.654997
1580.339280.678560.66072
1590.3352250.6704510.664775
1600.3491330.6982670.650867
1610.3590390.7180780.640961
1620.3573860.7147720.642614
1630.361170.722340.63883
1640.3730290.7460580.626971
1650.374610.749220.62539
1660.3976310.7952620.602369
1670.4103460.8206920.589654
1680.4080290.8160590.591971
1690.412680.825360.58732
1700.4358230.8716470.564177
1710.4303750.860750.569625
1720.4452360.8904710.554764
1730.4486680.8973370.551332
1740.4544410.9088830.545559
1750.4484630.8969250.551537
1760.4514690.9029370.548531
1770.4655820.9311630.534418
1780.4659280.9318560.534072
1790.4720870.9441730.527913
1800.4803050.960610.519695
1810.489550.9791010.51045
1820.5006180.9987650.499382
1830.4957620.9915230.504238
1840.4982390.9964770.501761
1850.527380.9452410.47262
1860.5221310.9557380.477869
1870.5229250.9541490.477075
1880.5219710.9560570.478029
1890.5244510.9510980.475549
1900.5196260.9607480.480374
1910.5189950.962010.481005
1920.5212490.9575030.478751
1930.513870.972260.48613
1940.5046690.9906610.495331
1950.5007320.9985370.499268
1960.4873150.9746290.512685
1970.4904480.9808970.509552
1980.4778430.9556850.522157
1990.4858450.9716890.514155
2000.4830970.9661930.516903
2010.4755610.9511220.524439
2020.4813830.9627670.518617
2030.4865620.9731240.513438
2040.4861260.9722530.513874
2050.4853730.9707450.514627
2060.4812090.9624190.518791
2070.4766910.9533820.523309
2080.4826940.9653890.517306
2090.4832980.9665970.516702
2100.4923320.9846650.507668
2110.4860460.9720930.513954
2120.502330.995340.49767
2130.4916870.9833740.508313
2140.4841880.9683760.515812
2150.5162330.9675350.483767
2160.5242770.9514460.475723
2170.5073230.9853530.492677
2180.5139650.9720690.486035
2190.5208570.9582870.479143
2200.5159650.9680690.484035
2210.5191350.9617290.480865
2220.5216150.9567690.478385
2230.5255330.9489340.474467
2240.5217960.9564080.478204
2250.5263160.9473670.473684
2260.5067940.9864130.493206
2270.4957490.9914970.504251
2280.4929440.9858890.507056
2290.4749290.9498580.525071
2300.5113970.9772060.488603
2310.5098870.9802260.490113
2320.5153370.9693250.484663
2330.505790.9884210.49421
2340.5079080.9841840.492092
2350.4910180.9820350.508982
2360.5068610.9862770.493139
2370.5221110.9557780.477889
2380.5257450.9485090.474255
2390.5713810.8572380.428619
2400.5500040.8999920.449996
2410.5777740.8444510.422226
2420.5921510.8156990.407849
2430.6204920.7590160.379508
2440.5966770.8066470.403323
2450.6377350.724530.362265
2460.7033860.5932280.296614
2470.6730520.6538960.326948
2480.716660.566680.28334
2490.6876310.6247380.312369
2500.660050.6798990.33995
2510.6416260.7167490.358374
2520.6857760.6284480.314224
2530.658290.6834210.34171
2540.6291230.7417540.370877
2550.7095570.5808860.290443
2560.7863020.4273970.213698
2570.8651640.2696730.134836
2580.9259940.1480120.0740062
2590.9630750.07385080.0369254
2600.9901360.01972820.00986409
2610.9855460.02890820.0144541
2620.9784020.04319660.0215983
2630.9959750.008049150.00402457
2640.9932540.01349140.00674569
2650.990380.01924030.00962017
2660.999620.0007591180.000379559
2670.9991980.001604810.000802404
2680.9983240.003351060.00167553
2690.9966730.006653090.00332655
2700.9936730.01265480.00632738
2710.9878480.02430320.0121516
2720.9778710.0442580.022129
2730.9610370.07792590.0389629
2740.9351460.1297090.0648543
2750.8924920.2150160.107508
2760.8293050.341390.170695
2770.7564630.4870730.243537
2780.6457110.7085790.354289
2790.5060790.9878430.493921
2800.3734230.7468460.626577
2810.2150480.4300970.784952

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
6 & 1.55942e-46 & 3.11885e-46 & 1 \tabularnewline
7 & 0 & 0 & 1 \tabularnewline
8 & 9.98385e-77 & 1.99677e-76 & 1 \tabularnewline
9 & 0 & 0 & 1 \tabularnewline
10 & 0 & 0 & 1 \tabularnewline
11 & 3.19725e-122 & 6.39449e-122 & 1 \tabularnewline
12 & 1.14106e-134 & 2.28213e-134 & 1 \tabularnewline
13 & 0 & 0 & 1 \tabularnewline
14 & 0 & 0 & 1 \tabularnewline
15 & 7.61696e-183 & 1.52339e-182 & 1 \tabularnewline
16 & 0 & 0 & 1 \tabularnewline
17 & 0.00220925 & 0.00441849 & 0.997791 \tabularnewline
18 & 0.0010753 & 0.00215061 & 0.998925 \tabularnewline
19 & 0.000500159 & 0.00100032 & 0.9995 \tabularnewline
20 & 0.0175719 & 0.0351437 & 0.982428 \tabularnewline
21 & 0.0115709 & 0.0231419 & 0.988429 \tabularnewline
22 & 0.00734412 & 0.0146882 & 0.992656 \tabularnewline
23 & 0.00443915 & 0.0088783 & 0.995561 \tabularnewline
24 & 0.00265096 & 0.00530192 & 0.997349 \tabularnewline
25 & 0.00157756 & 0.00315512 & 0.998422 \tabularnewline
26 & 0.000893931 & 0.00178786 & 0.999106 \tabularnewline
27 & 0.000576549 & 0.0011531 & 0.999423 \tabularnewline
28 & 0.00483076 & 0.00966153 & 0.995169 \tabularnewline
29 & 0.0174666 & 0.0349332 & 0.982533 \tabularnewline
30 & 0.0125283 & 0.0250566 & 0.987472 \tabularnewline
31 & 0.00897116 & 0.0179423 & 0.991029 \tabularnewline
32 & 0.00614416 & 0.0122883 & 0.993856 \tabularnewline
33 & 0.00437454 & 0.00874909 & 0.995625 \tabularnewline
34 & 0.00296789 & 0.00593577 & 0.997032 \tabularnewline
35 & 0.00201114 & 0.00402227 & 0.997989 \tabularnewline
36 & 0.00134441 & 0.00268882 & 0.998656 \tabularnewline
37 & 0.000916542 & 0.00183308 & 0.999083 \tabularnewline
38 & 0.000615495 & 0.00123099 & 0.999385 \tabularnewline
39 & 0.000399376 & 0.000798751 & 0.999601 \tabularnewline
40 & 0.00181234 & 0.00362468 & 0.998188 \tabularnewline
41 & 0.00125837 & 0.00251674 & 0.998742 \tabularnewline
42 & 0.000898294 & 0.00179659 & 0.999102 \tabularnewline
43 & 0.00064504 & 0.00129008 & 0.999355 \tabularnewline
44 & 0.000454162 & 0.000908325 & 0.999546 \tabularnewline
45 & 0.000332728 & 0.000665456 & 0.999667 \tabularnewline
46 & 0.000228993 & 0.000457986 & 0.999771 \tabularnewline
47 & 0.000973202 & 0.0019464 & 0.999027 \tabularnewline
48 & 0.000717695 & 0.00143539 & 0.999282 \tabularnewline
49 & 0.000554597 & 0.00110919 & 0.999445 \tabularnewline
50 & 0.00332582 & 0.00665163 & 0.996674 \tabularnewline
51 & 0.00270492 & 0.00540984 & 0.997295 \tabularnewline
52 & 0.0066448 & 0.0132896 & 0.993355 \tabularnewline
53 & 0.0133795 & 0.0267589 & 0.986621 \tabularnewline
54 & 0.0336988 & 0.0673976 & 0.966301 \tabularnewline
55 & 0.0291394 & 0.0582788 & 0.970861 \tabularnewline
56 & 0.0453535 & 0.090707 & 0.954646 \tabularnewline
57 & 0.0404533 & 0.0809066 & 0.959547 \tabularnewline
58 & 0.0354046 & 0.0708092 & 0.964595 \tabularnewline
59 & 0.0633062 & 0.126612 & 0.936694 \tabularnewline
60 & 0.0556689 & 0.111338 & 0.944331 \tabularnewline
61 & 0.0802226 & 0.160445 & 0.919777 \tabularnewline
62 & 0.108564 & 0.217127 & 0.891436 \tabularnewline
63 & 0.100207 & 0.200414 & 0.899793 \tabularnewline
64 & 0.0914141 & 0.182828 & 0.908586 \tabularnewline
65 & 0.0850984 & 0.170197 & 0.914902 \tabularnewline
66 & 0.0768313 & 0.153663 & 0.923169 \tabularnewline
67 & 0.0709946 & 0.141989 & 0.929005 \tabularnewline
68 & 0.0965343 & 0.193069 & 0.903466 \tabularnewline
69 & 0.089376 & 0.178752 & 0.910624 \tabularnewline
70 & 0.081708 & 0.163416 & 0.918292 \tabularnewline
71 & 0.0737288 & 0.147458 & 0.926271 \tabularnewline
72 & 0.0977041 & 0.195408 & 0.902296 \tabularnewline
73 & 0.090551 & 0.181102 & 0.909449 \tabularnewline
74 & 0.0842382 & 0.168476 & 0.915762 \tabularnewline
75 & 0.108275 & 0.216549 & 0.891725 \tabularnewline
76 & 0.135531 & 0.271062 & 0.864469 \tabularnewline
77 & 0.13328 & 0.266561 & 0.86672 \tabularnewline
78 & 0.124448 & 0.248895 & 0.875552 \tabularnewline
79 & 0.115939 & 0.231878 & 0.884061 \tabularnewline
80 & 0.140817 & 0.281633 & 0.859183 \tabularnewline
81 & 0.132634 & 0.265269 & 0.867366 \tabularnewline
82 & 0.161524 & 0.323049 & 0.838476 \tabularnewline
83 & 0.160828 & 0.321656 & 0.839172 \tabularnewline
84 & 0.18853 & 0.37706 & 0.81147 \tabularnewline
85 & 0.214939 & 0.429877 & 0.785061 \tabularnewline
86 & 0.24358 & 0.487159 & 0.75642 \tabularnewline
87 & 0.271694 & 0.543388 & 0.728306 \tabularnewline
88 & 0.292918 & 0.585836 & 0.707082 \tabularnewline
89 & 0.31819 & 0.63638 & 0.68181 \tabularnewline
90 & 0.340239 & 0.680479 & 0.659761 \tabularnewline
91 & 0.36471 & 0.729421 & 0.63529 \tabularnewline
92 & 0.384859 & 0.769718 & 0.615141 \tabularnewline
93 & 0.405392 & 0.810783 & 0.594608 \tabularnewline
94 & 0.4248 & 0.8496 & 0.5752 \tabularnewline
95 & 0.438218 & 0.876436 & 0.561782 \tabularnewline
96 & 0.450948 & 0.901897 & 0.549052 \tabularnewline
97 & 0.462117 & 0.924233 & 0.537883 \tabularnewline
98 & 0.467927 & 0.935855 & 0.532073 \tabularnewline
99 & 0.47437 & 0.948741 & 0.52563 \tabularnewline
100 & 0.477555 & 0.95511 & 0.522445 \tabularnewline
101 & 0.488503 & 0.977006 & 0.511497 \tabularnewline
102 & 0.502956 & 0.994088 & 0.497044 \tabularnewline
103 & 0.503081 & 0.993837 & 0.496919 \tabularnewline
104 & 0.508058 & 0.983885 & 0.491942 \tabularnewline
105 & 0.512332 & 0.975335 & 0.487668 \tabularnewline
106 & 0.512593 & 0.974814 & 0.487407 \tabularnewline
107 & 0.513229 & 0.973543 & 0.486771 \tabularnewline
108 & 0.525167 & 0.949666 & 0.474833 \tabularnewline
109 & 0.520541 & 0.958917 & 0.479459 \tabularnewline
110 & 0.525376 & 0.949248 & 0.474624 \tabularnewline
111 & 0.512773 & 0.974455 & 0.487227 \tabularnewline
112 & 0.503981 & 0.992038 & 0.496019 \tabularnewline
113 & 0.500372 & 0.999256 & 0.499628 \tabularnewline
114 & 0.503044 & 0.993912 & 0.496956 \tabularnewline
115 & 0.505284 & 0.989431 & 0.494716 \tabularnewline
116 & 0.522236 & 0.955528 & 0.477764 \tabularnewline
117 & 0.517284 & 0.965432 & 0.482716 \tabularnewline
118 & 0.500454 & 0.999093 & 0.499546 \tabularnewline
119 & 0.483576 & 0.967152 & 0.516424 \tabularnewline
120 & 0.51009 & 0.979821 & 0.48991 \tabularnewline
121 & 0.512408 & 0.975183 & 0.487592 \tabularnewline
122 & 0.499278 & 0.998557 & 0.500722 \tabularnewline
123 & 0.482286 & 0.964573 & 0.517714 \tabularnewline
124 & 0.470844 & 0.941689 & 0.529156 \tabularnewline
125 & 0.46624 & 0.932481 & 0.53376 \tabularnewline
126 & 0.449682 & 0.899364 & 0.550318 \tabularnewline
127 & 0.441105 & 0.882209 & 0.558895 \tabularnewline
128 & 0.443598 & 0.887196 & 0.556402 \tabularnewline
129 & 0.44098 & 0.881959 & 0.55902 \tabularnewline
130 & 0.428711 & 0.857421 & 0.571289 \tabularnewline
131 & 0.423142 & 0.846283 & 0.576858 \tabularnewline
132 & 0.454139 & 0.908277 & 0.545861 \tabularnewline
133 & 0.44962 & 0.899241 & 0.55038 \tabularnewline
134 & 0.445336 & 0.890673 & 0.554664 \tabularnewline
135 & 0.433832 & 0.867664 & 0.566168 \tabularnewline
136 & 0.426348 & 0.852696 & 0.573652 \tabularnewline
137 & 0.419237 & 0.838474 & 0.580763 \tabularnewline
138 & 0.419134 & 0.838268 & 0.580866 \tabularnewline
139 & 0.419025 & 0.83805 & 0.580975 \tabularnewline
140 & 0.408512 & 0.817023 & 0.591488 \tabularnewline
141 & 0.423826 & 0.847652 & 0.576174 \tabularnewline
142 & 0.40906 & 0.818119 & 0.59094 \tabularnewline
143 & 0.399979 & 0.799958 & 0.600021 \tabularnewline
144 & 0.403672 & 0.807345 & 0.596328 \tabularnewline
145 & 0.391643 & 0.783286 & 0.608357 \tabularnewline
146 & 0.381595 & 0.763189 & 0.618405 \tabularnewline
147 & 0.371938 & 0.743876 & 0.628062 \tabularnewline
148 & 0.362359 & 0.724719 & 0.637641 \tabularnewline
149 & 0.356603 & 0.713206 & 0.643397 \tabularnewline
150 & 0.345811 & 0.691623 & 0.654189 \tabularnewline
151 & 0.343766 & 0.687531 & 0.656234 \tabularnewline
152 & 0.347113 & 0.694226 & 0.652887 \tabularnewline
153 & 0.344338 & 0.688676 & 0.655662 \tabularnewline
154 & 0.339648 & 0.679295 & 0.660352 \tabularnewline
155 & 0.333348 & 0.666696 & 0.666652 \tabularnewline
156 & 0.347029 & 0.694058 & 0.652971 \tabularnewline
157 & 0.345003 & 0.690007 & 0.654997 \tabularnewline
158 & 0.33928 & 0.67856 & 0.66072 \tabularnewline
159 & 0.335225 & 0.670451 & 0.664775 \tabularnewline
160 & 0.349133 & 0.698267 & 0.650867 \tabularnewline
161 & 0.359039 & 0.718078 & 0.640961 \tabularnewline
162 & 0.357386 & 0.714772 & 0.642614 \tabularnewline
163 & 0.36117 & 0.72234 & 0.63883 \tabularnewline
164 & 0.373029 & 0.746058 & 0.626971 \tabularnewline
165 & 0.37461 & 0.74922 & 0.62539 \tabularnewline
166 & 0.397631 & 0.795262 & 0.602369 \tabularnewline
167 & 0.410346 & 0.820692 & 0.589654 \tabularnewline
168 & 0.408029 & 0.816059 & 0.591971 \tabularnewline
169 & 0.41268 & 0.82536 & 0.58732 \tabularnewline
170 & 0.435823 & 0.871647 & 0.564177 \tabularnewline
171 & 0.430375 & 0.86075 & 0.569625 \tabularnewline
172 & 0.445236 & 0.890471 & 0.554764 \tabularnewline
173 & 0.448668 & 0.897337 & 0.551332 \tabularnewline
174 & 0.454441 & 0.908883 & 0.545559 \tabularnewline
175 & 0.448463 & 0.896925 & 0.551537 \tabularnewline
176 & 0.451469 & 0.902937 & 0.548531 \tabularnewline
177 & 0.465582 & 0.931163 & 0.534418 \tabularnewline
178 & 0.465928 & 0.931856 & 0.534072 \tabularnewline
179 & 0.472087 & 0.944173 & 0.527913 \tabularnewline
180 & 0.480305 & 0.96061 & 0.519695 \tabularnewline
181 & 0.48955 & 0.979101 & 0.51045 \tabularnewline
182 & 0.500618 & 0.998765 & 0.499382 \tabularnewline
183 & 0.495762 & 0.991523 & 0.504238 \tabularnewline
184 & 0.498239 & 0.996477 & 0.501761 \tabularnewline
185 & 0.52738 & 0.945241 & 0.47262 \tabularnewline
186 & 0.522131 & 0.955738 & 0.477869 \tabularnewline
187 & 0.522925 & 0.954149 & 0.477075 \tabularnewline
188 & 0.521971 & 0.956057 & 0.478029 \tabularnewline
189 & 0.524451 & 0.951098 & 0.475549 \tabularnewline
190 & 0.519626 & 0.960748 & 0.480374 \tabularnewline
191 & 0.518995 & 0.96201 & 0.481005 \tabularnewline
192 & 0.521249 & 0.957503 & 0.478751 \tabularnewline
193 & 0.51387 & 0.97226 & 0.48613 \tabularnewline
194 & 0.504669 & 0.990661 & 0.495331 \tabularnewline
195 & 0.500732 & 0.998537 & 0.499268 \tabularnewline
196 & 0.487315 & 0.974629 & 0.512685 \tabularnewline
197 & 0.490448 & 0.980897 & 0.509552 \tabularnewline
198 & 0.477843 & 0.955685 & 0.522157 \tabularnewline
199 & 0.485845 & 0.971689 & 0.514155 \tabularnewline
200 & 0.483097 & 0.966193 & 0.516903 \tabularnewline
201 & 0.475561 & 0.951122 & 0.524439 \tabularnewline
202 & 0.481383 & 0.962767 & 0.518617 \tabularnewline
203 & 0.486562 & 0.973124 & 0.513438 \tabularnewline
204 & 0.486126 & 0.972253 & 0.513874 \tabularnewline
205 & 0.485373 & 0.970745 & 0.514627 \tabularnewline
206 & 0.481209 & 0.962419 & 0.518791 \tabularnewline
207 & 0.476691 & 0.953382 & 0.523309 \tabularnewline
208 & 0.482694 & 0.965389 & 0.517306 \tabularnewline
209 & 0.483298 & 0.966597 & 0.516702 \tabularnewline
210 & 0.492332 & 0.984665 & 0.507668 \tabularnewline
211 & 0.486046 & 0.972093 & 0.513954 \tabularnewline
212 & 0.50233 & 0.99534 & 0.49767 \tabularnewline
213 & 0.491687 & 0.983374 & 0.508313 \tabularnewline
214 & 0.484188 & 0.968376 & 0.515812 \tabularnewline
215 & 0.516233 & 0.967535 & 0.483767 \tabularnewline
216 & 0.524277 & 0.951446 & 0.475723 \tabularnewline
217 & 0.507323 & 0.985353 & 0.492677 \tabularnewline
218 & 0.513965 & 0.972069 & 0.486035 \tabularnewline
219 & 0.520857 & 0.958287 & 0.479143 \tabularnewline
220 & 0.515965 & 0.968069 & 0.484035 \tabularnewline
221 & 0.519135 & 0.961729 & 0.480865 \tabularnewline
222 & 0.521615 & 0.956769 & 0.478385 \tabularnewline
223 & 0.525533 & 0.948934 & 0.474467 \tabularnewline
224 & 0.521796 & 0.956408 & 0.478204 \tabularnewline
225 & 0.526316 & 0.947367 & 0.473684 \tabularnewline
226 & 0.506794 & 0.986413 & 0.493206 \tabularnewline
227 & 0.495749 & 0.991497 & 0.504251 \tabularnewline
228 & 0.492944 & 0.985889 & 0.507056 \tabularnewline
229 & 0.474929 & 0.949858 & 0.525071 \tabularnewline
230 & 0.511397 & 0.977206 & 0.488603 \tabularnewline
231 & 0.509887 & 0.980226 & 0.490113 \tabularnewline
232 & 0.515337 & 0.969325 & 0.484663 \tabularnewline
233 & 0.50579 & 0.988421 & 0.49421 \tabularnewline
234 & 0.507908 & 0.984184 & 0.492092 \tabularnewline
235 & 0.491018 & 0.982035 & 0.508982 \tabularnewline
236 & 0.506861 & 0.986277 & 0.493139 \tabularnewline
237 & 0.522111 & 0.955778 & 0.477889 \tabularnewline
238 & 0.525745 & 0.948509 & 0.474255 \tabularnewline
239 & 0.571381 & 0.857238 & 0.428619 \tabularnewline
240 & 0.550004 & 0.899992 & 0.449996 \tabularnewline
241 & 0.577774 & 0.844451 & 0.422226 \tabularnewline
242 & 0.592151 & 0.815699 & 0.407849 \tabularnewline
243 & 0.620492 & 0.759016 & 0.379508 \tabularnewline
244 & 0.596677 & 0.806647 & 0.403323 \tabularnewline
245 & 0.637735 & 0.72453 & 0.362265 \tabularnewline
246 & 0.703386 & 0.593228 & 0.296614 \tabularnewline
247 & 0.673052 & 0.653896 & 0.326948 \tabularnewline
248 & 0.71666 & 0.56668 & 0.28334 \tabularnewline
249 & 0.687631 & 0.624738 & 0.312369 \tabularnewline
250 & 0.66005 & 0.679899 & 0.33995 \tabularnewline
251 & 0.641626 & 0.716749 & 0.358374 \tabularnewline
252 & 0.685776 & 0.628448 & 0.314224 \tabularnewline
253 & 0.65829 & 0.683421 & 0.34171 \tabularnewline
254 & 0.629123 & 0.741754 & 0.370877 \tabularnewline
255 & 0.709557 & 0.580886 & 0.290443 \tabularnewline
256 & 0.786302 & 0.427397 & 0.213698 \tabularnewline
257 & 0.865164 & 0.269673 & 0.134836 \tabularnewline
258 & 0.925994 & 0.148012 & 0.0740062 \tabularnewline
259 & 0.963075 & 0.0738508 & 0.0369254 \tabularnewline
260 & 0.990136 & 0.0197282 & 0.00986409 \tabularnewline
261 & 0.985546 & 0.0289082 & 0.0144541 \tabularnewline
262 & 0.978402 & 0.0431966 & 0.0215983 \tabularnewline
263 & 0.995975 & 0.00804915 & 0.00402457 \tabularnewline
264 & 0.993254 & 0.0134914 & 0.00674569 \tabularnewline
265 & 0.99038 & 0.0192403 & 0.00962017 \tabularnewline
266 & 0.99962 & 0.000759118 & 0.000379559 \tabularnewline
267 & 0.999198 & 0.00160481 & 0.000802404 \tabularnewline
268 & 0.998324 & 0.00335106 & 0.00167553 \tabularnewline
269 & 0.996673 & 0.00665309 & 0.00332655 \tabularnewline
270 & 0.993673 & 0.0126548 & 0.00632738 \tabularnewline
271 & 0.987848 & 0.0243032 & 0.0121516 \tabularnewline
272 & 0.977871 & 0.044258 & 0.022129 \tabularnewline
273 & 0.961037 & 0.0779259 & 0.0389629 \tabularnewline
274 & 0.935146 & 0.129709 & 0.0648543 \tabularnewline
275 & 0.892492 & 0.215016 & 0.107508 \tabularnewline
276 & 0.829305 & 0.34139 & 0.170695 \tabularnewline
277 & 0.756463 & 0.487073 & 0.243537 \tabularnewline
278 & 0.645711 & 0.708579 & 0.354289 \tabularnewline
279 & 0.506079 & 0.987843 & 0.493921 \tabularnewline
280 & 0.373423 & 0.746846 & 0.626577 \tabularnewline
281 & 0.215048 & 0.430097 & 0.784952 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266421&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]6[/C][C]1.55942e-46[/C][C]3.11885e-46[/C][C]1[/C][/ROW]
[ROW][C]7[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]8[/C][C]9.98385e-77[/C][C]1.99677e-76[/C][C]1[/C][/ROW]
[ROW][C]9[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]10[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]11[/C][C]3.19725e-122[/C][C]6.39449e-122[/C][C]1[/C][/ROW]
[ROW][C]12[/C][C]1.14106e-134[/C][C]2.28213e-134[/C][C]1[/C][/ROW]
[ROW][C]13[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]14[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]15[/C][C]7.61696e-183[/C][C]1.52339e-182[/C][C]1[/C][/ROW]
[ROW][C]16[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]17[/C][C]0.00220925[/C][C]0.00441849[/C][C]0.997791[/C][/ROW]
[ROW][C]18[/C][C]0.0010753[/C][C]0.00215061[/C][C]0.998925[/C][/ROW]
[ROW][C]19[/C][C]0.000500159[/C][C]0.00100032[/C][C]0.9995[/C][/ROW]
[ROW][C]20[/C][C]0.0175719[/C][C]0.0351437[/C][C]0.982428[/C][/ROW]
[ROW][C]21[/C][C]0.0115709[/C][C]0.0231419[/C][C]0.988429[/C][/ROW]
[ROW][C]22[/C][C]0.00734412[/C][C]0.0146882[/C][C]0.992656[/C][/ROW]
[ROW][C]23[/C][C]0.00443915[/C][C]0.0088783[/C][C]0.995561[/C][/ROW]
[ROW][C]24[/C][C]0.00265096[/C][C]0.00530192[/C][C]0.997349[/C][/ROW]
[ROW][C]25[/C][C]0.00157756[/C][C]0.00315512[/C][C]0.998422[/C][/ROW]
[ROW][C]26[/C][C]0.000893931[/C][C]0.00178786[/C][C]0.999106[/C][/ROW]
[ROW][C]27[/C][C]0.000576549[/C][C]0.0011531[/C][C]0.999423[/C][/ROW]
[ROW][C]28[/C][C]0.00483076[/C][C]0.00966153[/C][C]0.995169[/C][/ROW]
[ROW][C]29[/C][C]0.0174666[/C][C]0.0349332[/C][C]0.982533[/C][/ROW]
[ROW][C]30[/C][C]0.0125283[/C][C]0.0250566[/C][C]0.987472[/C][/ROW]
[ROW][C]31[/C][C]0.00897116[/C][C]0.0179423[/C][C]0.991029[/C][/ROW]
[ROW][C]32[/C][C]0.00614416[/C][C]0.0122883[/C][C]0.993856[/C][/ROW]
[ROW][C]33[/C][C]0.00437454[/C][C]0.00874909[/C][C]0.995625[/C][/ROW]
[ROW][C]34[/C][C]0.00296789[/C][C]0.00593577[/C][C]0.997032[/C][/ROW]
[ROW][C]35[/C][C]0.00201114[/C][C]0.00402227[/C][C]0.997989[/C][/ROW]
[ROW][C]36[/C][C]0.00134441[/C][C]0.00268882[/C][C]0.998656[/C][/ROW]
[ROW][C]37[/C][C]0.000916542[/C][C]0.00183308[/C][C]0.999083[/C][/ROW]
[ROW][C]38[/C][C]0.000615495[/C][C]0.00123099[/C][C]0.999385[/C][/ROW]
[ROW][C]39[/C][C]0.000399376[/C][C]0.000798751[/C][C]0.999601[/C][/ROW]
[ROW][C]40[/C][C]0.00181234[/C][C]0.00362468[/C][C]0.998188[/C][/ROW]
[ROW][C]41[/C][C]0.00125837[/C][C]0.00251674[/C][C]0.998742[/C][/ROW]
[ROW][C]42[/C][C]0.000898294[/C][C]0.00179659[/C][C]0.999102[/C][/ROW]
[ROW][C]43[/C][C]0.00064504[/C][C]0.00129008[/C][C]0.999355[/C][/ROW]
[ROW][C]44[/C][C]0.000454162[/C][C]0.000908325[/C][C]0.999546[/C][/ROW]
[ROW][C]45[/C][C]0.000332728[/C][C]0.000665456[/C][C]0.999667[/C][/ROW]
[ROW][C]46[/C][C]0.000228993[/C][C]0.000457986[/C][C]0.999771[/C][/ROW]
[ROW][C]47[/C][C]0.000973202[/C][C]0.0019464[/C][C]0.999027[/C][/ROW]
[ROW][C]48[/C][C]0.000717695[/C][C]0.00143539[/C][C]0.999282[/C][/ROW]
[ROW][C]49[/C][C]0.000554597[/C][C]0.00110919[/C][C]0.999445[/C][/ROW]
[ROW][C]50[/C][C]0.00332582[/C][C]0.00665163[/C][C]0.996674[/C][/ROW]
[ROW][C]51[/C][C]0.00270492[/C][C]0.00540984[/C][C]0.997295[/C][/ROW]
[ROW][C]52[/C][C]0.0066448[/C][C]0.0132896[/C][C]0.993355[/C][/ROW]
[ROW][C]53[/C][C]0.0133795[/C][C]0.0267589[/C][C]0.986621[/C][/ROW]
[ROW][C]54[/C][C]0.0336988[/C][C]0.0673976[/C][C]0.966301[/C][/ROW]
[ROW][C]55[/C][C]0.0291394[/C][C]0.0582788[/C][C]0.970861[/C][/ROW]
[ROW][C]56[/C][C]0.0453535[/C][C]0.090707[/C][C]0.954646[/C][/ROW]
[ROW][C]57[/C][C]0.0404533[/C][C]0.0809066[/C][C]0.959547[/C][/ROW]
[ROW][C]58[/C][C]0.0354046[/C][C]0.0708092[/C][C]0.964595[/C][/ROW]
[ROW][C]59[/C][C]0.0633062[/C][C]0.126612[/C][C]0.936694[/C][/ROW]
[ROW][C]60[/C][C]0.0556689[/C][C]0.111338[/C][C]0.944331[/C][/ROW]
[ROW][C]61[/C][C]0.0802226[/C][C]0.160445[/C][C]0.919777[/C][/ROW]
[ROW][C]62[/C][C]0.108564[/C][C]0.217127[/C][C]0.891436[/C][/ROW]
[ROW][C]63[/C][C]0.100207[/C][C]0.200414[/C][C]0.899793[/C][/ROW]
[ROW][C]64[/C][C]0.0914141[/C][C]0.182828[/C][C]0.908586[/C][/ROW]
[ROW][C]65[/C][C]0.0850984[/C][C]0.170197[/C][C]0.914902[/C][/ROW]
[ROW][C]66[/C][C]0.0768313[/C][C]0.153663[/C][C]0.923169[/C][/ROW]
[ROW][C]67[/C][C]0.0709946[/C][C]0.141989[/C][C]0.929005[/C][/ROW]
[ROW][C]68[/C][C]0.0965343[/C][C]0.193069[/C][C]0.903466[/C][/ROW]
[ROW][C]69[/C][C]0.089376[/C][C]0.178752[/C][C]0.910624[/C][/ROW]
[ROW][C]70[/C][C]0.081708[/C][C]0.163416[/C][C]0.918292[/C][/ROW]
[ROW][C]71[/C][C]0.0737288[/C][C]0.147458[/C][C]0.926271[/C][/ROW]
[ROW][C]72[/C][C]0.0977041[/C][C]0.195408[/C][C]0.902296[/C][/ROW]
[ROW][C]73[/C][C]0.090551[/C][C]0.181102[/C][C]0.909449[/C][/ROW]
[ROW][C]74[/C][C]0.0842382[/C][C]0.168476[/C][C]0.915762[/C][/ROW]
[ROW][C]75[/C][C]0.108275[/C][C]0.216549[/C][C]0.891725[/C][/ROW]
[ROW][C]76[/C][C]0.135531[/C][C]0.271062[/C][C]0.864469[/C][/ROW]
[ROW][C]77[/C][C]0.13328[/C][C]0.266561[/C][C]0.86672[/C][/ROW]
[ROW][C]78[/C][C]0.124448[/C][C]0.248895[/C][C]0.875552[/C][/ROW]
[ROW][C]79[/C][C]0.115939[/C][C]0.231878[/C][C]0.884061[/C][/ROW]
[ROW][C]80[/C][C]0.140817[/C][C]0.281633[/C][C]0.859183[/C][/ROW]
[ROW][C]81[/C][C]0.132634[/C][C]0.265269[/C][C]0.867366[/C][/ROW]
[ROW][C]82[/C][C]0.161524[/C][C]0.323049[/C][C]0.838476[/C][/ROW]
[ROW][C]83[/C][C]0.160828[/C][C]0.321656[/C][C]0.839172[/C][/ROW]
[ROW][C]84[/C][C]0.18853[/C][C]0.37706[/C][C]0.81147[/C][/ROW]
[ROW][C]85[/C][C]0.214939[/C][C]0.429877[/C][C]0.785061[/C][/ROW]
[ROW][C]86[/C][C]0.24358[/C][C]0.487159[/C][C]0.75642[/C][/ROW]
[ROW][C]87[/C][C]0.271694[/C][C]0.543388[/C][C]0.728306[/C][/ROW]
[ROW][C]88[/C][C]0.292918[/C][C]0.585836[/C][C]0.707082[/C][/ROW]
[ROW][C]89[/C][C]0.31819[/C][C]0.63638[/C][C]0.68181[/C][/ROW]
[ROW][C]90[/C][C]0.340239[/C][C]0.680479[/C][C]0.659761[/C][/ROW]
[ROW][C]91[/C][C]0.36471[/C][C]0.729421[/C][C]0.63529[/C][/ROW]
[ROW][C]92[/C][C]0.384859[/C][C]0.769718[/C][C]0.615141[/C][/ROW]
[ROW][C]93[/C][C]0.405392[/C][C]0.810783[/C][C]0.594608[/C][/ROW]
[ROW][C]94[/C][C]0.4248[/C][C]0.8496[/C][C]0.5752[/C][/ROW]
[ROW][C]95[/C][C]0.438218[/C][C]0.876436[/C][C]0.561782[/C][/ROW]
[ROW][C]96[/C][C]0.450948[/C][C]0.901897[/C][C]0.549052[/C][/ROW]
[ROW][C]97[/C][C]0.462117[/C][C]0.924233[/C][C]0.537883[/C][/ROW]
[ROW][C]98[/C][C]0.467927[/C][C]0.935855[/C][C]0.532073[/C][/ROW]
[ROW][C]99[/C][C]0.47437[/C][C]0.948741[/C][C]0.52563[/C][/ROW]
[ROW][C]100[/C][C]0.477555[/C][C]0.95511[/C][C]0.522445[/C][/ROW]
[ROW][C]101[/C][C]0.488503[/C][C]0.977006[/C][C]0.511497[/C][/ROW]
[ROW][C]102[/C][C]0.502956[/C][C]0.994088[/C][C]0.497044[/C][/ROW]
[ROW][C]103[/C][C]0.503081[/C][C]0.993837[/C][C]0.496919[/C][/ROW]
[ROW][C]104[/C][C]0.508058[/C][C]0.983885[/C][C]0.491942[/C][/ROW]
[ROW][C]105[/C][C]0.512332[/C][C]0.975335[/C][C]0.487668[/C][/ROW]
[ROW][C]106[/C][C]0.512593[/C][C]0.974814[/C][C]0.487407[/C][/ROW]
[ROW][C]107[/C][C]0.513229[/C][C]0.973543[/C][C]0.486771[/C][/ROW]
[ROW][C]108[/C][C]0.525167[/C][C]0.949666[/C][C]0.474833[/C][/ROW]
[ROW][C]109[/C][C]0.520541[/C][C]0.958917[/C][C]0.479459[/C][/ROW]
[ROW][C]110[/C][C]0.525376[/C][C]0.949248[/C][C]0.474624[/C][/ROW]
[ROW][C]111[/C][C]0.512773[/C][C]0.974455[/C][C]0.487227[/C][/ROW]
[ROW][C]112[/C][C]0.503981[/C][C]0.992038[/C][C]0.496019[/C][/ROW]
[ROW][C]113[/C][C]0.500372[/C][C]0.999256[/C][C]0.499628[/C][/ROW]
[ROW][C]114[/C][C]0.503044[/C][C]0.993912[/C][C]0.496956[/C][/ROW]
[ROW][C]115[/C][C]0.505284[/C][C]0.989431[/C][C]0.494716[/C][/ROW]
[ROW][C]116[/C][C]0.522236[/C][C]0.955528[/C][C]0.477764[/C][/ROW]
[ROW][C]117[/C][C]0.517284[/C][C]0.965432[/C][C]0.482716[/C][/ROW]
[ROW][C]118[/C][C]0.500454[/C][C]0.999093[/C][C]0.499546[/C][/ROW]
[ROW][C]119[/C][C]0.483576[/C][C]0.967152[/C][C]0.516424[/C][/ROW]
[ROW][C]120[/C][C]0.51009[/C][C]0.979821[/C][C]0.48991[/C][/ROW]
[ROW][C]121[/C][C]0.512408[/C][C]0.975183[/C][C]0.487592[/C][/ROW]
[ROW][C]122[/C][C]0.499278[/C][C]0.998557[/C][C]0.500722[/C][/ROW]
[ROW][C]123[/C][C]0.482286[/C][C]0.964573[/C][C]0.517714[/C][/ROW]
[ROW][C]124[/C][C]0.470844[/C][C]0.941689[/C][C]0.529156[/C][/ROW]
[ROW][C]125[/C][C]0.46624[/C][C]0.932481[/C][C]0.53376[/C][/ROW]
[ROW][C]126[/C][C]0.449682[/C][C]0.899364[/C][C]0.550318[/C][/ROW]
[ROW][C]127[/C][C]0.441105[/C][C]0.882209[/C][C]0.558895[/C][/ROW]
[ROW][C]128[/C][C]0.443598[/C][C]0.887196[/C][C]0.556402[/C][/ROW]
[ROW][C]129[/C][C]0.44098[/C][C]0.881959[/C][C]0.55902[/C][/ROW]
[ROW][C]130[/C][C]0.428711[/C][C]0.857421[/C][C]0.571289[/C][/ROW]
[ROW][C]131[/C][C]0.423142[/C][C]0.846283[/C][C]0.576858[/C][/ROW]
[ROW][C]132[/C][C]0.454139[/C][C]0.908277[/C][C]0.545861[/C][/ROW]
[ROW][C]133[/C][C]0.44962[/C][C]0.899241[/C][C]0.55038[/C][/ROW]
[ROW][C]134[/C][C]0.445336[/C][C]0.890673[/C][C]0.554664[/C][/ROW]
[ROW][C]135[/C][C]0.433832[/C][C]0.867664[/C][C]0.566168[/C][/ROW]
[ROW][C]136[/C][C]0.426348[/C][C]0.852696[/C][C]0.573652[/C][/ROW]
[ROW][C]137[/C][C]0.419237[/C][C]0.838474[/C][C]0.580763[/C][/ROW]
[ROW][C]138[/C][C]0.419134[/C][C]0.838268[/C][C]0.580866[/C][/ROW]
[ROW][C]139[/C][C]0.419025[/C][C]0.83805[/C][C]0.580975[/C][/ROW]
[ROW][C]140[/C][C]0.408512[/C][C]0.817023[/C][C]0.591488[/C][/ROW]
[ROW][C]141[/C][C]0.423826[/C][C]0.847652[/C][C]0.576174[/C][/ROW]
[ROW][C]142[/C][C]0.40906[/C][C]0.818119[/C][C]0.59094[/C][/ROW]
[ROW][C]143[/C][C]0.399979[/C][C]0.799958[/C][C]0.600021[/C][/ROW]
[ROW][C]144[/C][C]0.403672[/C][C]0.807345[/C][C]0.596328[/C][/ROW]
[ROW][C]145[/C][C]0.391643[/C][C]0.783286[/C][C]0.608357[/C][/ROW]
[ROW][C]146[/C][C]0.381595[/C][C]0.763189[/C][C]0.618405[/C][/ROW]
[ROW][C]147[/C][C]0.371938[/C][C]0.743876[/C][C]0.628062[/C][/ROW]
[ROW][C]148[/C][C]0.362359[/C][C]0.724719[/C][C]0.637641[/C][/ROW]
[ROW][C]149[/C][C]0.356603[/C][C]0.713206[/C][C]0.643397[/C][/ROW]
[ROW][C]150[/C][C]0.345811[/C][C]0.691623[/C][C]0.654189[/C][/ROW]
[ROW][C]151[/C][C]0.343766[/C][C]0.687531[/C][C]0.656234[/C][/ROW]
[ROW][C]152[/C][C]0.347113[/C][C]0.694226[/C][C]0.652887[/C][/ROW]
[ROW][C]153[/C][C]0.344338[/C][C]0.688676[/C][C]0.655662[/C][/ROW]
[ROW][C]154[/C][C]0.339648[/C][C]0.679295[/C][C]0.660352[/C][/ROW]
[ROW][C]155[/C][C]0.333348[/C][C]0.666696[/C][C]0.666652[/C][/ROW]
[ROW][C]156[/C][C]0.347029[/C][C]0.694058[/C][C]0.652971[/C][/ROW]
[ROW][C]157[/C][C]0.345003[/C][C]0.690007[/C][C]0.654997[/C][/ROW]
[ROW][C]158[/C][C]0.33928[/C][C]0.67856[/C][C]0.66072[/C][/ROW]
[ROW][C]159[/C][C]0.335225[/C][C]0.670451[/C][C]0.664775[/C][/ROW]
[ROW][C]160[/C][C]0.349133[/C][C]0.698267[/C][C]0.650867[/C][/ROW]
[ROW][C]161[/C][C]0.359039[/C][C]0.718078[/C][C]0.640961[/C][/ROW]
[ROW][C]162[/C][C]0.357386[/C][C]0.714772[/C][C]0.642614[/C][/ROW]
[ROW][C]163[/C][C]0.36117[/C][C]0.72234[/C][C]0.63883[/C][/ROW]
[ROW][C]164[/C][C]0.373029[/C][C]0.746058[/C][C]0.626971[/C][/ROW]
[ROW][C]165[/C][C]0.37461[/C][C]0.74922[/C][C]0.62539[/C][/ROW]
[ROW][C]166[/C][C]0.397631[/C][C]0.795262[/C][C]0.602369[/C][/ROW]
[ROW][C]167[/C][C]0.410346[/C][C]0.820692[/C][C]0.589654[/C][/ROW]
[ROW][C]168[/C][C]0.408029[/C][C]0.816059[/C][C]0.591971[/C][/ROW]
[ROW][C]169[/C][C]0.41268[/C][C]0.82536[/C][C]0.58732[/C][/ROW]
[ROW][C]170[/C][C]0.435823[/C][C]0.871647[/C][C]0.564177[/C][/ROW]
[ROW][C]171[/C][C]0.430375[/C][C]0.86075[/C][C]0.569625[/C][/ROW]
[ROW][C]172[/C][C]0.445236[/C][C]0.890471[/C][C]0.554764[/C][/ROW]
[ROW][C]173[/C][C]0.448668[/C][C]0.897337[/C][C]0.551332[/C][/ROW]
[ROW][C]174[/C][C]0.454441[/C][C]0.908883[/C][C]0.545559[/C][/ROW]
[ROW][C]175[/C][C]0.448463[/C][C]0.896925[/C][C]0.551537[/C][/ROW]
[ROW][C]176[/C][C]0.451469[/C][C]0.902937[/C][C]0.548531[/C][/ROW]
[ROW][C]177[/C][C]0.465582[/C][C]0.931163[/C][C]0.534418[/C][/ROW]
[ROW][C]178[/C][C]0.465928[/C][C]0.931856[/C][C]0.534072[/C][/ROW]
[ROW][C]179[/C][C]0.472087[/C][C]0.944173[/C][C]0.527913[/C][/ROW]
[ROW][C]180[/C][C]0.480305[/C][C]0.96061[/C][C]0.519695[/C][/ROW]
[ROW][C]181[/C][C]0.48955[/C][C]0.979101[/C][C]0.51045[/C][/ROW]
[ROW][C]182[/C][C]0.500618[/C][C]0.998765[/C][C]0.499382[/C][/ROW]
[ROW][C]183[/C][C]0.495762[/C][C]0.991523[/C][C]0.504238[/C][/ROW]
[ROW][C]184[/C][C]0.498239[/C][C]0.996477[/C][C]0.501761[/C][/ROW]
[ROW][C]185[/C][C]0.52738[/C][C]0.945241[/C][C]0.47262[/C][/ROW]
[ROW][C]186[/C][C]0.522131[/C][C]0.955738[/C][C]0.477869[/C][/ROW]
[ROW][C]187[/C][C]0.522925[/C][C]0.954149[/C][C]0.477075[/C][/ROW]
[ROW][C]188[/C][C]0.521971[/C][C]0.956057[/C][C]0.478029[/C][/ROW]
[ROW][C]189[/C][C]0.524451[/C][C]0.951098[/C][C]0.475549[/C][/ROW]
[ROW][C]190[/C][C]0.519626[/C][C]0.960748[/C][C]0.480374[/C][/ROW]
[ROW][C]191[/C][C]0.518995[/C][C]0.96201[/C][C]0.481005[/C][/ROW]
[ROW][C]192[/C][C]0.521249[/C][C]0.957503[/C][C]0.478751[/C][/ROW]
[ROW][C]193[/C][C]0.51387[/C][C]0.97226[/C][C]0.48613[/C][/ROW]
[ROW][C]194[/C][C]0.504669[/C][C]0.990661[/C][C]0.495331[/C][/ROW]
[ROW][C]195[/C][C]0.500732[/C][C]0.998537[/C][C]0.499268[/C][/ROW]
[ROW][C]196[/C][C]0.487315[/C][C]0.974629[/C][C]0.512685[/C][/ROW]
[ROW][C]197[/C][C]0.490448[/C][C]0.980897[/C][C]0.509552[/C][/ROW]
[ROW][C]198[/C][C]0.477843[/C][C]0.955685[/C][C]0.522157[/C][/ROW]
[ROW][C]199[/C][C]0.485845[/C][C]0.971689[/C][C]0.514155[/C][/ROW]
[ROW][C]200[/C][C]0.483097[/C][C]0.966193[/C][C]0.516903[/C][/ROW]
[ROW][C]201[/C][C]0.475561[/C][C]0.951122[/C][C]0.524439[/C][/ROW]
[ROW][C]202[/C][C]0.481383[/C][C]0.962767[/C][C]0.518617[/C][/ROW]
[ROW][C]203[/C][C]0.486562[/C][C]0.973124[/C][C]0.513438[/C][/ROW]
[ROW][C]204[/C][C]0.486126[/C][C]0.972253[/C][C]0.513874[/C][/ROW]
[ROW][C]205[/C][C]0.485373[/C][C]0.970745[/C][C]0.514627[/C][/ROW]
[ROW][C]206[/C][C]0.481209[/C][C]0.962419[/C][C]0.518791[/C][/ROW]
[ROW][C]207[/C][C]0.476691[/C][C]0.953382[/C][C]0.523309[/C][/ROW]
[ROW][C]208[/C][C]0.482694[/C][C]0.965389[/C][C]0.517306[/C][/ROW]
[ROW][C]209[/C][C]0.483298[/C][C]0.966597[/C][C]0.516702[/C][/ROW]
[ROW][C]210[/C][C]0.492332[/C][C]0.984665[/C][C]0.507668[/C][/ROW]
[ROW][C]211[/C][C]0.486046[/C][C]0.972093[/C][C]0.513954[/C][/ROW]
[ROW][C]212[/C][C]0.50233[/C][C]0.99534[/C][C]0.49767[/C][/ROW]
[ROW][C]213[/C][C]0.491687[/C][C]0.983374[/C][C]0.508313[/C][/ROW]
[ROW][C]214[/C][C]0.484188[/C][C]0.968376[/C][C]0.515812[/C][/ROW]
[ROW][C]215[/C][C]0.516233[/C][C]0.967535[/C][C]0.483767[/C][/ROW]
[ROW][C]216[/C][C]0.524277[/C][C]0.951446[/C][C]0.475723[/C][/ROW]
[ROW][C]217[/C][C]0.507323[/C][C]0.985353[/C][C]0.492677[/C][/ROW]
[ROW][C]218[/C][C]0.513965[/C][C]0.972069[/C][C]0.486035[/C][/ROW]
[ROW][C]219[/C][C]0.520857[/C][C]0.958287[/C][C]0.479143[/C][/ROW]
[ROW][C]220[/C][C]0.515965[/C][C]0.968069[/C][C]0.484035[/C][/ROW]
[ROW][C]221[/C][C]0.519135[/C][C]0.961729[/C][C]0.480865[/C][/ROW]
[ROW][C]222[/C][C]0.521615[/C][C]0.956769[/C][C]0.478385[/C][/ROW]
[ROW][C]223[/C][C]0.525533[/C][C]0.948934[/C][C]0.474467[/C][/ROW]
[ROW][C]224[/C][C]0.521796[/C][C]0.956408[/C][C]0.478204[/C][/ROW]
[ROW][C]225[/C][C]0.526316[/C][C]0.947367[/C][C]0.473684[/C][/ROW]
[ROW][C]226[/C][C]0.506794[/C][C]0.986413[/C][C]0.493206[/C][/ROW]
[ROW][C]227[/C][C]0.495749[/C][C]0.991497[/C][C]0.504251[/C][/ROW]
[ROW][C]228[/C][C]0.492944[/C][C]0.985889[/C][C]0.507056[/C][/ROW]
[ROW][C]229[/C][C]0.474929[/C][C]0.949858[/C][C]0.525071[/C][/ROW]
[ROW][C]230[/C][C]0.511397[/C][C]0.977206[/C][C]0.488603[/C][/ROW]
[ROW][C]231[/C][C]0.509887[/C][C]0.980226[/C][C]0.490113[/C][/ROW]
[ROW][C]232[/C][C]0.515337[/C][C]0.969325[/C][C]0.484663[/C][/ROW]
[ROW][C]233[/C][C]0.50579[/C][C]0.988421[/C][C]0.49421[/C][/ROW]
[ROW][C]234[/C][C]0.507908[/C][C]0.984184[/C][C]0.492092[/C][/ROW]
[ROW][C]235[/C][C]0.491018[/C][C]0.982035[/C][C]0.508982[/C][/ROW]
[ROW][C]236[/C][C]0.506861[/C][C]0.986277[/C][C]0.493139[/C][/ROW]
[ROW][C]237[/C][C]0.522111[/C][C]0.955778[/C][C]0.477889[/C][/ROW]
[ROW][C]238[/C][C]0.525745[/C][C]0.948509[/C][C]0.474255[/C][/ROW]
[ROW][C]239[/C][C]0.571381[/C][C]0.857238[/C][C]0.428619[/C][/ROW]
[ROW][C]240[/C][C]0.550004[/C][C]0.899992[/C][C]0.449996[/C][/ROW]
[ROW][C]241[/C][C]0.577774[/C][C]0.844451[/C][C]0.422226[/C][/ROW]
[ROW][C]242[/C][C]0.592151[/C][C]0.815699[/C][C]0.407849[/C][/ROW]
[ROW][C]243[/C][C]0.620492[/C][C]0.759016[/C][C]0.379508[/C][/ROW]
[ROW][C]244[/C][C]0.596677[/C][C]0.806647[/C][C]0.403323[/C][/ROW]
[ROW][C]245[/C][C]0.637735[/C][C]0.72453[/C][C]0.362265[/C][/ROW]
[ROW][C]246[/C][C]0.703386[/C][C]0.593228[/C][C]0.296614[/C][/ROW]
[ROW][C]247[/C][C]0.673052[/C][C]0.653896[/C][C]0.326948[/C][/ROW]
[ROW][C]248[/C][C]0.71666[/C][C]0.56668[/C][C]0.28334[/C][/ROW]
[ROW][C]249[/C][C]0.687631[/C][C]0.624738[/C][C]0.312369[/C][/ROW]
[ROW][C]250[/C][C]0.66005[/C][C]0.679899[/C][C]0.33995[/C][/ROW]
[ROW][C]251[/C][C]0.641626[/C][C]0.716749[/C][C]0.358374[/C][/ROW]
[ROW][C]252[/C][C]0.685776[/C][C]0.628448[/C][C]0.314224[/C][/ROW]
[ROW][C]253[/C][C]0.65829[/C][C]0.683421[/C][C]0.34171[/C][/ROW]
[ROW][C]254[/C][C]0.629123[/C][C]0.741754[/C][C]0.370877[/C][/ROW]
[ROW][C]255[/C][C]0.709557[/C][C]0.580886[/C][C]0.290443[/C][/ROW]
[ROW][C]256[/C][C]0.786302[/C][C]0.427397[/C][C]0.213698[/C][/ROW]
[ROW][C]257[/C][C]0.865164[/C][C]0.269673[/C][C]0.134836[/C][/ROW]
[ROW][C]258[/C][C]0.925994[/C][C]0.148012[/C][C]0.0740062[/C][/ROW]
[ROW][C]259[/C][C]0.963075[/C][C]0.0738508[/C][C]0.0369254[/C][/ROW]
[ROW][C]260[/C][C]0.990136[/C][C]0.0197282[/C][C]0.00986409[/C][/ROW]
[ROW][C]261[/C][C]0.985546[/C][C]0.0289082[/C][C]0.0144541[/C][/ROW]
[ROW][C]262[/C][C]0.978402[/C][C]0.0431966[/C][C]0.0215983[/C][/ROW]
[ROW][C]263[/C][C]0.995975[/C][C]0.00804915[/C][C]0.00402457[/C][/ROW]
[ROW][C]264[/C][C]0.993254[/C][C]0.0134914[/C][C]0.00674569[/C][/ROW]
[ROW][C]265[/C][C]0.99038[/C][C]0.0192403[/C][C]0.00962017[/C][/ROW]
[ROW][C]266[/C][C]0.99962[/C][C]0.000759118[/C][C]0.000379559[/C][/ROW]
[ROW][C]267[/C][C]0.999198[/C][C]0.00160481[/C][C]0.000802404[/C][/ROW]
[ROW][C]268[/C][C]0.998324[/C][C]0.00335106[/C][C]0.00167553[/C][/ROW]
[ROW][C]269[/C][C]0.996673[/C][C]0.00665309[/C][C]0.00332655[/C][/ROW]
[ROW][C]270[/C][C]0.993673[/C][C]0.0126548[/C][C]0.00632738[/C][/ROW]
[ROW][C]271[/C][C]0.987848[/C][C]0.0243032[/C][C]0.0121516[/C][/ROW]
[ROW][C]272[/C][C]0.977871[/C][C]0.044258[/C][C]0.022129[/C][/ROW]
[ROW][C]273[/C][C]0.961037[/C][C]0.0779259[/C][C]0.0389629[/C][/ROW]
[ROW][C]274[/C][C]0.935146[/C][C]0.129709[/C][C]0.0648543[/C][/ROW]
[ROW][C]275[/C][C]0.892492[/C][C]0.215016[/C][C]0.107508[/C][/ROW]
[ROW][C]276[/C][C]0.829305[/C][C]0.34139[/C][C]0.170695[/C][/ROW]
[ROW][C]277[/C][C]0.756463[/C][C]0.487073[/C][C]0.243537[/C][/ROW]
[ROW][C]278[/C][C]0.645711[/C][C]0.708579[/C][C]0.354289[/C][/ROW]
[ROW][C]279[/C][C]0.506079[/C][C]0.987843[/C][C]0.493921[/C][/ROW]
[ROW][C]280[/C][C]0.373423[/C][C]0.746846[/C][C]0.626577[/C][/ROW]
[ROW][C]281[/C][C]0.215048[/C][C]0.430097[/C][C]0.784952[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266421&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266421&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
61.55942e-463.11885e-461
7001
89.98385e-771.99677e-761
9001
10001
113.19725e-1226.39449e-1221
121.14106e-1342.28213e-1341
13001
14001
157.61696e-1831.52339e-1821
16001
170.002209250.004418490.997791
180.00107530.002150610.998925
190.0005001590.001000320.9995
200.01757190.03514370.982428
210.01157090.02314190.988429
220.007344120.01468820.992656
230.004439150.00887830.995561
240.002650960.005301920.997349
250.001577560.003155120.998422
260.0008939310.001787860.999106
270.0005765490.00115310.999423
280.004830760.009661530.995169
290.01746660.03493320.982533
300.01252830.02505660.987472
310.008971160.01794230.991029
320.006144160.01228830.993856
330.004374540.008749090.995625
340.002967890.005935770.997032
350.002011140.004022270.997989
360.001344410.002688820.998656
370.0009165420.001833080.999083
380.0006154950.001230990.999385
390.0003993760.0007987510.999601
400.001812340.003624680.998188
410.001258370.002516740.998742
420.0008982940.001796590.999102
430.000645040.001290080.999355
440.0004541620.0009083250.999546
450.0003327280.0006654560.999667
460.0002289930.0004579860.999771
470.0009732020.00194640.999027
480.0007176950.001435390.999282
490.0005545970.001109190.999445
500.003325820.006651630.996674
510.002704920.005409840.997295
520.00664480.01328960.993355
530.01337950.02675890.986621
540.03369880.06739760.966301
550.02913940.05827880.970861
560.04535350.0907070.954646
570.04045330.08090660.959547
580.03540460.07080920.964595
590.06330620.1266120.936694
600.05566890.1113380.944331
610.08022260.1604450.919777
620.1085640.2171270.891436
630.1002070.2004140.899793
640.09141410.1828280.908586
650.08509840.1701970.914902
660.07683130.1536630.923169
670.07099460.1419890.929005
680.09653430.1930690.903466
690.0893760.1787520.910624
700.0817080.1634160.918292
710.07372880.1474580.926271
720.09770410.1954080.902296
730.0905510.1811020.909449
740.08423820.1684760.915762
750.1082750.2165490.891725
760.1355310.2710620.864469
770.133280.2665610.86672
780.1244480.2488950.875552
790.1159390.2318780.884061
800.1408170.2816330.859183
810.1326340.2652690.867366
820.1615240.3230490.838476
830.1608280.3216560.839172
840.188530.377060.81147
850.2149390.4298770.785061
860.243580.4871590.75642
870.2716940.5433880.728306
880.2929180.5858360.707082
890.318190.636380.68181
900.3402390.6804790.659761
910.364710.7294210.63529
920.3848590.7697180.615141
930.4053920.8107830.594608
940.42480.84960.5752
950.4382180.8764360.561782
960.4509480.9018970.549052
970.4621170.9242330.537883
980.4679270.9358550.532073
990.474370.9487410.52563
1000.4775550.955110.522445
1010.4885030.9770060.511497
1020.5029560.9940880.497044
1030.5030810.9938370.496919
1040.5080580.9838850.491942
1050.5123320.9753350.487668
1060.5125930.9748140.487407
1070.5132290.9735430.486771
1080.5251670.9496660.474833
1090.5205410.9589170.479459
1100.5253760.9492480.474624
1110.5127730.9744550.487227
1120.5039810.9920380.496019
1130.5003720.9992560.499628
1140.5030440.9939120.496956
1150.5052840.9894310.494716
1160.5222360.9555280.477764
1170.5172840.9654320.482716
1180.5004540.9990930.499546
1190.4835760.9671520.516424
1200.510090.9798210.48991
1210.5124080.9751830.487592
1220.4992780.9985570.500722
1230.4822860.9645730.517714
1240.4708440.9416890.529156
1250.466240.9324810.53376
1260.4496820.8993640.550318
1270.4411050.8822090.558895
1280.4435980.8871960.556402
1290.440980.8819590.55902
1300.4287110.8574210.571289
1310.4231420.8462830.576858
1320.4541390.9082770.545861
1330.449620.8992410.55038
1340.4453360.8906730.554664
1350.4338320.8676640.566168
1360.4263480.8526960.573652
1370.4192370.8384740.580763
1380.4191340.8382680.580866
1390.4190250.838050.580975
1400.4085120.8170230.591488
1410.4238260.8476520.576174
1420.409060.8181190.59094
1430.3999790.7999580.600021
1440.4036720.8073450.596328
1450.3916430.7832860.608357
1460.3815950.7631890.618405
1470.3719380.7438760.628062
1480.3623590.7247190.637641
1490.3566030.7132060.643397
1500.3458110.6916230.654189
1510.3437660.6875310.656234
1520.3471130.6942260.652887
1530.3443380.6886760.655662
1540.3396480.6792950.660352
1550.3333480.6666960.666652
1560.3470290.6940580.652971
1570.3450030.6900070.654997
1580.339280.678560.66072
1590.3352250.6704510.664775
1600.3491330.6982670.650867
1610.3590390.7180780.640961
1620.3573860.7147720.642614
1630.361170.722340.63883
1640.3730290.7460580.626971
1650.374610.749220.62539
1660.3976310.7952620.602369
1670.4103460.8206920.589654
1680.4080290.8160590.591971
1690.412680.825360.58732
1700.4358230.8716470.564177
1710.4303750.860750.569625
1720.4452360.8904710.554764
1730.4486680.8973370.551332
1740.4544410.9088830.545559
1750.4484630.8969250.551537
1760.4514690.9029370.548531
1770.4655820.9311630.534418
1780.4659280.9318560.534072
1790.4720870.9441730.527913
1800.4803050.960610.519695
1810.489550.9791010.51045
1820.5006180.9987650.499382
1830.4957620.9915230.504238
1840.4982390.9964770.501761
1850.527380.9452410.47262
1860.5221310.9557380.477869
1870.5229250.9541490.477075
1880.5219710.9560570.478029
1890.5244510.9510980.475549
1900.5196260.9607480.480374
1910.5189950.962010.481005
1920.5212490.9575030.478751
1930.513870.972260.48613
1940.5046690.9906610.495331
1950.5007320.9985370.499268
1960.4873150.9746290.512685
1970.4904480.9808970.509552
1980.4778430.9556850.522157
1990.4858450.9716890.514155
2000.4830970.9661930.516903
2010.4755610.9511220.524439
2020.4813830.9627670.518617
2030.4865620.9731240.513438
2040.4861260.9722530.513874
2050.4853730.9707450.514627
2060.4812090.9624190.518791
2070.4766910.9533820.523309
2080.4826940.9653890.517306
2090.4832980.9665970.516702
2100.4923320.9846650.507668
2110.4860460.9720930.513954
2120.502330.995340.49767
2130.4916870.9833740.508313
2140.4841880.9683760.515812
2150.5162330.9675350.483767
2160.5242770.9514460.475723
2170.5073230.9853530.492677
2180.5139650.9720690.486035
2190.5208570.9582870.479143
2200.5159650.9680690.484035
2210.5191350.9617290.480865
2220.5216150.9567690.478385
2230.5255330.9489340.474467
2240.5217960.9564080.478204
2250.5263160.9473670.473684
2260.5067940.9864130.493206
2270.4957490.9914970.504251
2280.4929440.9858890.507056
2290.4749290.9498580.525071
2300.5113970.9772060.488603
2310.5098870.9802260.490113
2320.5153370.9693250.484663
2330.505790.9884210.49421
2340.5079080.9841840.492092
2350.4910180.9820350.508982
2360.5068610.9862770.493139
2370.5221110.9557780.477889
2380.5257450.9485090.474255
2390.5713810.8572380.428619
2400.5500040.8999920.449996
2410.5777740.8444510.422226
2420.5921510.8156990.407849
2430.6204920.7590160.379508
2440.5966770.8066470.403323
2450.6377350.724530.362265
2460.7033860.5932280.296614
2470.6730520.6538960.326948
2480.716660.566680.28334
2490.6876310.6247380.312369
2500.660050.6798990.33995
2510.6416260.7167490.358374
2520.6857760.6284480.314224
2530.658290.6834210.34171
2540.6291230.7417540.370877
2550.7095570.5808860.290443
2560.7863020.4273970.213698
2570.8651640.2696730.134836
2580.9259940.1480120.0740062
2590.9630750.07385080.0369254
2600.9901360.01972820.00986409
2610.9855460.02890820.0144541
2620.9784020.04319660.0215983
2630.9959750.008049150.00402457
2640.9932540.01349140.00674569
2650.990380.01924030.00962017
2660.999620.0007591180.000379559
2670.9991980.001604810.000802404
2680.9983240.003351060.00167553
2690.9966730.006653090.00332655
2700.9936730.01265480.00632738
2710.9878480.02430320.0121516
2720.9778710.0442580.022129
2730.9610370.07792590.0389629
2740.9351460.1297090.0648543
2750.8924920.2150160.107508
2760.8293050.341390.170695
2770.7564630.4870730.243537
2780.6457110.7085790.354289
2790.5060790.9878430.493921
2800.3734230.7468460.626577
2810.2150480.4300970.784952






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level440.15942NOK
5% type I error level610.221014NOK
10% type I error level680.246377NOK

\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 & 44 & 0.15942 & NOK \tabularnewline
5% type I error level & 61 & 0.221014 & NOK \tabularnewline
10% type I error level & 68 & 0.246377 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266421&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]44[/C][C]0.15942[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]61[/C][C]0.221014[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]68[/C][C]0.246377[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266421&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266421&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level440.15942NOK
5% type I error level610.221014NOK
10% type I error level680.246377NOK


Figures (Output of Computation)

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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')
}