FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationWed, 17 Dec 2014 10:36:11 +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/17/t1418812663jpahb7139vdl5j2.htm/, Retrieved Thu, 16 May 2024 13:57:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270029, Retrieved Thu, 16 May 2024 13:57:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact70

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [multiple regressi...] [2014-12-17 10:36:11] [d71ad52285d92a63edfc83f9fb1da7a1] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7.5 50 21 21 68
2.5 68 23 26 55
6 62 22 22 39
6.5 54 21 22 32
1 71 21 18 62
1 54 21 23 33
5.5 65 21 12 52
8.5 73 21 20 62
6.5 52 23 22 77
4.5 84 22 21 76
2 42 25 19 41
5 66 21 22 48
0.5 65 23 15 63
5 78 22 20 30
5 73 21 19 78
2.5 75 21 18 19
5 72 25 15 31
5.5 66 21 20 66
3.5 70 21 21 35
3 61 20 21 42
4 81 24 15 45
0.5 71 23 16 21
6.5 69 21 23 25
4.5 71 24 21 44
7.5 72 23 18 69
5.5 68 21 25 54
4 70 22 9 74
7.5 68 20 30 80
7 61 18 20 42
4 67 21 23 61
5.5 76 22 16 41
2.5 70 22 16 46
5.5 60 21 19 39
0.5 77 23 25 63
3.5 72 21 25 34
2.5 69 25 18 51
4.5 71 22 23 42
4.5 62 22 21 31
4.5 70 20 10 39
6 64 21 14 20
2.5 58 21 22 49
5 76 21 26 53
0 52 22 23 31
5 59 21 23 39
6.5 68 24 24 54
5 76 22 24 49
6 65 22 18 34
4.5 67 21 23 46
5.5 59 22 15 55
1 69 19 19 42
7.5 76 22 16 50
6 63 23 25 13
5 75 20 23 37
1 63 20 17 25
5 60 23 19 30
6.5 73 20 21 28
7 63 23 18 45
4.5 70 21 27 35
0 75 22 21 28
8.5 66 21 13 41
3.5 63 21 8 6
7.5 63 19 29 45
3.5 64 22 28 73
6 70 21 23 17
1.5 75 21 21 40
9 61 21 19 64
3.5 60 21 19 37
3.5 62 21 20 25
4 73 21 18 65
6.5 61 22 19 100
7.5 66 22 17 28
6 64 18 19 35
5 59 21 25 56
5.5 64 23 19 29
3.5 60 19 22 43
7.5 56 19 23 59
1 66 23 26 52
6.5 78 21 14 50
6.5 67 21 16 59
6.5 59 21 24 27
7 66 20 20 61
3.5 68 19 12 28
1.5 71 21 24 51
4 66 19 22 35
7.5 73 19 12 29
4.5 72 19 22 48
0 71 20 20 25
3.5 59 19 10 44
5.5 64 19 23 64
5 66 19 17 32
4.5 78 20 22 20
2.5 68 19 24 28
7.5 73 18 18 34
7 62 19 21 31
0 65 21 20 26
4.5 68 18 20 58
3 65 18 22 23
1.5 60 19 19 21
3.5 71 21 20 21
2.5 65 20 26 33
5.5 68 24 23 16
8 64 22 24 20
1 74 21 21 37
5 69 21 21 35
4.5 76 19 19 33
3 68 19 8 27
3 72 20 17 41
8 67 18 20 40
2.5 63 19 11 35
7 59 19 8 28
0 73 20 15 32
1 66 21 18 22
3.5 62 18 18 44
5.5 69 19 19 27
5.5 66 19 19 17
0.5 51 22 23 12
7.5 56 22 22 45
9 67 22 21 37
9.5 69 20 25 37
8.5 57 19 30 108
7 56 20 17 10
8 55 22 27 68
10 63 21 23 72
7 67 21 23 143
8.5 65 21 18 9
9 47 21 18 55
9.5 76 21 23 17
4 64 21 19 37
6 68 21 15 27
8 64 22 20 37
5.5 65 24 16 58
9.5 71 21 24 66
7.5 63 22 25 21
7 60 20 25 19
7.5 68 21 19 78
8 72 24 19 35
7 70 25 16 48
7 61 22 19 27
6 61 21 19 43
10 62 21 23 30
2.5 71 22 21 25
9 71 23 22 69
8 51 24 19 72
6 56 20 20 23
8.5 70 22 20 13
6 73 25 3 61
9 76 22 23 43
8 59 22 14 22
8 68 21 23 51
9 48 21 20 67
5.5 52 21 15 36
5 59 22 13 21
7 60 22 16 44
5.5 59 22 7 45
9 57 21 24 34
2 79 22 17 36
8.5 60 23 24 72
9 60 21 24 39
8.5 59 21 19 43
9 62 21 25 25
7.5 59 19 20 56
10 61 21 28 80
9 71 21 23 40
7.5 57 19 27 73
6 66 18 18 34
10.5 63 19 28 72
8.5 69 21 21 42
8 58 22 19 61
10 59 22 23 23
10.5 48 19 27 74
6.5 66 20 22 16
9.5 73 19 28 66
8.5 67 21 25 9
7.5 61 19 21 41
5 68 20 22 57
8 75 21 28 48
10 62 19 20 51
7 69 21 29 53
7.5 58 21 25 29
7.5 60 21 25 29
9.5 74 19 20 55
6 55 25 20 54
10 62 21 16 43
7 63 20 20 51
3 69 25 20 20
6 58 19 23 79
7 58 20 18 39
10 68 22 25 61
7 72 19 18 55
3.5 62 20 19 30
8 62 19 25 55
10 65 19 25 22
5.5 69 18 25 37
6 66 19 24 2
6.5 72 21 19 38
6.5 62 19 26 27
8.5 75 20 10 56
4 58 20 17 25
9.5 66 19 13 39
8 55 19 17 33
8.5 47 22 30 43
5.5 72 21 25 57
7 62 19 4 43
9 64 19 16 23
8 64 19 21 44
10 19 23 23 54
8 50 19 22 28
6 68 20 17 36
8 70 19 20 39
5 79 22 20 16
9 69 19 22 23
4.5 71 25 16 40
8.5 48 19 23 24
7 66 20 16 29
9.5 73 19 0 78
8.5 74 19 18 57
7.5 66 20 25 37
7.5 71 20 23 27
5 74 21 12 61
7 78 19 18 27
8 75 21 24 69
5.5 53 23 11 34
8.5 60 19 18 44
7.5 50 21 14 21
9.5 70 22 23 34
7 69 20 24 39
8 65 18 29 51
8.5 78 21 18 34
3.5 78 20 15 31
6.5 59 21 29 13
6.5 72 21 16 12
10.5 70 21 19 51
8.5 63 19 22 24
8 63 21 16 19
10 71 19 23 30
10 74 21 23 81
9.5 67 21 19 42
9 66 22 4 22
10 62 21 20 85
7.5 80 22 24 27
4.5 73 22 20 25
4.5 67 22 4 22
0.5 61 22 24 19
6.5 73 21 22 14
4.5 74 22 16 45
5.5 32 23 3 45
5 69 19 15 28
6 69 22 24 51
4 84 21 17 41
8 64 19 20 31
10.5 58 19 27 74
8.5 60 20 23 24
6.5 59 20 26 19
8 78 18 23 51
8.5 57 21 17 73
5.5 60 21 20 24
7 68 20 22 61
5 68 20 19 23
3.5 73 21 24 14
5 69 21 19 54
9 67 19 23 51
8.5 60 19 15 62
5 65 21 27 36
9.5 66 19 26 59
3 74 19 22 24
1.5 81 24 22 26
6 72 19 18 54
0.5 55 19 15 39
6.5 49 20 22 16
7.5 74 19 27 36
4.5 53 19 10 31
8 64 19 20 31
9 65 19 17 42
7.5 57 19 23 39
8.5 51 19 19 25
7 80 20 13 31
9.5 67 20 27 38
6.5 70 19 23 31
9.5 74 21 16 17
6 75 19 25 22
8 70 19 2 55
9.5 69 19 26 62
8 65 21 20 51
8 55 22 23 30
9 71 19 22 49
5 65 19 24 16

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 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 & 10 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270029&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]10 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=270029&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270029&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 time10 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 13.1993 -0.0447671AMS.E[t] -0.302993age[t] + 0.0492973NUMERACYTOT[t] + 0.0285858CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  13.1993 -0.0447671AMS.E[t] -0.302993age[t] +  0.0492973NUMERACYTOT[t] +  0.0285858CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270029&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  13.1993 -0.0447671AMS.E[t] -0.302993age[t] +  0.0492973NUMERACYTOT[t] +  0.0285858CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270029&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270029&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
Ex[t] = + 13.1993 -0.0447671AMS.E[t] -0.302993age[t] + 0.0492973NUMERACYTOT[t] + 0.0285858CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)13.19932.344615.634.3733e-082.18665e-08
AMS.E-0.04476710.0176337-2.5390.01166550.00583276
age-0.3029930.0913296-3.3180.001027640.000513821
NUMERACYTOT0.04929730.02820061.7480.08153980.0407699
CH0.02858580.007595213.7640.0002038550.000101928

\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) & 13.1993 & 2.34461 & 5.63 & 4.3733e-08 & 2.18665e-08 \tabularnewline
AMS.E & -0.0447671 & 0.0176337 & -2.539 & 0.0116655 & 0.00583276 \tabularnewline
age & -0.302993 & 0.0913296 & -3.318 & 0.00102764 & 0.000513821 \tabularnewline
NUMERACYTOT & 0.0492973 & 0.0282006 & 1.748 & 0.0815398 & 0.0407699 \tabularnewline
CH & 0.0285858 & 0.00759521 & 3.764 & 0.000203855 & 0.000101928 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270029&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]13.1993[/C][C]2.34461[/C][C]5.63[/C][C]4.3733e-08[/C][C]2.18665e-08[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0447671[/C][C]0.0176337[/C][C]-2.539[/C][C]0.0116655[/C][C]0.00583276[/C][/ROW]
[ROW][C]age[/C][C]-0.302993[/C][C]0.0913296[/C][C]-3.318[/C][C]0.00102764[/C][C]0.000513821[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0492973[/C][C]0.0282006[/C][C]1.748[/C][C]0.0815398[/C][C]0.0407699[/C][/ROW]
[ROW][C]CH[/C][C]0.0285858[/C][C]0.00759521[/C][C]3.764[/C][C]0.000203855[/C][C]0.000101928[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270029&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270029&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)13.19932.344615.634.3733e-082.18665e-08
AMS.E-0.04476710.0176337-2.5390.01166550.00583276
age-0.3029930.0913296-3.3180.001027640.000513821
NUMERACYTOT0.04929730.02820061.7480.08153980.0407699
CH0.02858580.007595213.7640.0002038550.000101928






Multiple Linear Regression - Regression Statistics
Multiple R0.339445
R-squared0.115223
Adjusted R-squared0.102628
F-TEST (value)9.14855
F-TEST (DF numerator)4
F-TEST (DF denominator)281
p-value5.82629e-07
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.422
Sum Squared Residuals1648.37

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.339445 \tabularnewline
R-squared & 0.115223 \tabularnewline
Adjusted R-squared & 0.102628 \tabularnewline
F-TEST (value) & 9.14855 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 281 \tabularnewline
p-value & 5.82629e-07 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.422 \tabularnewline
Sum Squared Residuals & 1648.37 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270029&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.339445[/C][/ROW]
[ROW][C]R-squared[/C][C]0.115223[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.102628[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]9.14855[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]281[/C][/ROW]
[ROW][C]p-value[/C][C]5.82629e-07[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.422[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1648.37[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270029&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270029&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 R0.339445
R-squared0.115223
Adjusted R-squared0.102628
F-TEST (value)9.14855
F-TEST (DF numerator)4
F-TEST (DF denominator)281
p-value5.82629e-07
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.422
Sum Squared Residuals1648.37






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.57.57716-0.077161
22.56.04024-3.54024
365.957270.042727
46.56.41830.0816984
516.31765-5.31765
616.49618-5.49618
75.56.00461-0.504607
88.56.326712.17329
96.57.18821-0.688211
104.55.98077-1.48077
1125.85292-3.85292
1256.33847-1.33847
130.55.86096-5.36096
1454.885130.114867
1556.73478-1.73478
162.54.90939-2.40939
1754.026860.973143
185.56.75442-1.25442
193.55.73849-2.23849
2036.64449-3.64449
2144.32715-0.327147
220.54.44105-3.94105
236.55.595990.904008
244.55.04202-0.542016
257.55.866991.63301
265.56.56834-1.06834
2745.95877-1.95877
287.57.86105-0.361051
2977.20117-0.201173
3046.71461-2.71461
315.55.091920.408078
322.55.50345-3.00345
335.56.20191-0.701908
340.55.81673-5.31673
353.55.81756-2.31756
362.54.88077-2.38077
374.55.68942-1.18942
384.55.67929-1.17929
394.55.61355-1.11355
4065.233220.766777
412.56.72519-4.22519
4256.23092-1.23092
4306.22555-6.22555
4456.44386-1.44386
456.55.610070.889933
4655.71499-0.714987
4765.482850.517146
484.56.28583-1.78583
495.56.20387-0.703866
5016.49075-5.49075
517.55.349192.15081
5265.014170.985825
5355.97341-0.973412
5415.8718-4.8718
5555.33865-0.338651
566.55.707080.79292
5775.583841.41616
584.56.03427-1.53427
5905.01156-5.01156
608.55.694692.80531
613.54.58201-1.08201
627.57.338080.16192
633.57.13544-3.63544
6465.322540.677461
651.55.65758-4.15758
6696.871792.12821
673.56.14474-2.64474
683.55.76147-2.26147
6946.31387-2.31387
706.57.59788-1.09788
717.55.217272.28273
7266.81747-0.817474
7357.02842-2.02842
745.55.1310.369003
753.57.07013-3.57013
767.57.75587-0.255866
7716.04402-5.04402
786.55.464061.03594
796.56.312360.187638
806.56.150130.349868
8176.914480.0855172
823.55.79023-2.29023
831.56.29899-4.79899
8446.57284-2.57284
857.55.594981.90502
864.56.67585-2.17585
8705.66156-5.66156
883.56.55191-3.05191
895.57.54066-2.04066
9056.2406-1.2406
914.55.30386-0.803855
922.56.3818-3.8818
937.56.336691.16331
9476.588270.411733
9505.65575-5.65575
964.57.34518-2.84518
9736.57757-3.57757
981.56.29335-4.79335
993.55.24422-1.74422
1002.56.45463-3.95463
1015.54.474511.02549
10285.42322.5768
10315.61659-4.61659
10455.78326-0.783256
1054.55.92011-1.42011
10635.56446-2.56446
10735.92627-2.92627
10886.87541.1246
1092.56.16487-3.66487
11075.995951.00405
11105.52564-5.52564
11215.39805-4.39805
1133.57.11498-3.61498
1145.56.06196-0.56196
1155.55.9104-0.410403
1160.55.72719-5.22719
1177.56.397391.10261
11895.626973.37303
1199.56.340613.15939
1208.59.45688-0.956884
12175.756391.24361
12287.346120.653883
123107.208132.79187
12479.05865-2.05865
1258.55.07123.4288
12697.191961.80804
1279.55.053944.44606
12845.96567-1.96567
12965.303550.696447
13085.711972.28803
1315.55.464330.0356671
1329.56.727772.77223
1337.55.545851.95415
13476.228970.771032
1357.56.958620.541383
13684.641383.35862
13774.651652.34835
13875.511121.48888
13966.27148-0.271484
140106.052293.94771
1412.55.10487-2.60487
14296.108952.89105
14386.639161.36084
14466.27589-0.275893
1458.54.757313.74269
14664.24811.7519
14795.494173.50583
14885.211242.78876
14986.383991.61601
15097.588811.41119
1515.56.2771-0.777098
15255.13335-0.133354
15375.893951.10605
1545.55.52363-0.0236298
15596.439772.56023
15624.86399-2.86399
1578.56.785741.71426
15896.448392.55161
1598.56.361022.13898
16096.007962.99204
1617.57.387920.112084
162107.772832.22717
16395.935253.06475
1647.58.30849-0.808489
16566.65006-0.650057
16610.58.06062.4394
1678.55.983362.51664
16886.617341.38266
169105.68354.3165
17010.58.739981.76002
1716.55.726720.773283
1729.57.441412.05859
1738.55.326753.17325
1747.56.918890.581108
17556.8092-1.8092
17686.231351.76865
177107.110692.88931
17876.692180.307822
1797.56.301371.19863
1807.56.211831.28817
1819.56.687822.81218
18265.691860.308143
183106.078833.92117
18476.762930.237074
18534.0932-1.0932
18668.23805-2.23805
18776.545140.454863
188106.465453.53455
18976.678760.321236
1903.56.15809-2.65809
19187.471520.528485
192106.393883.60612
1935.56.94659-1.44659
19465.72810.271897
1956.55.636120.863883
1966.56.72041-0.220411
1978.55.875682.62432
19846.09564-2.09564
1999.56.243513.25649
20086.761621.23838
2018.57.13751.3625
2025.56.47503-0.975031
20376.093240.906757
20496.023562.97644
20586.870351.12965
206108.057351.94265
20787.089010.910988
20865.962410.0375879
20986.409521.59048
21054.440170.559835
21196.095512.90449
2124.54.378190.121806
2138.57.11351.3865
21475.802551.19745
2159.56.404123.09588
2168.56.64641.8536
2177.56.474911.02509
2187.55.866621.63338
21955.85898-0.858975
22075.609761.39024
22186.634461.36554
2225.55.371980.128015
2238.56.901521.59848
2247.55.888551.61145
2259.55.50553.9945
22676.348480.651517
22787.723050.276947
2288.55.203873.29613
2293.55.27322-1.77322
2306.55.996420.503583
2316.54.7451.755
23210.56.097274.40273
2338.56.39272.1073
23485.3482.652
235106.255373.74463
236106.972963.02704
2379.55.97433.5257
23894.40494.5951
239107.476622.52338
2407.54.907032.59297
2414.54.96604-0.46604
2424.54.360130.139872
2430.55.52892-5.02892
2446.55.053181.44682
2454.55.2958-0.795799
2465.56.23216-0.732159
24755.89336-0.893357
24866.08553-0.0855276
24945.08608-1.08608
25086.449441.55056
25110.58.292312.20769
2528.56.27332.2267
2536.56.323030.176967
25486.84531.1547
2558.57.209531.29047
2565.55.82242-0.322418
25776.923540.0764567
25855.68939-0.689391
2593.55.15178-1.65178
26056.22779-1.22779
26197.034741.96526
2628.57.268181.23182
26356.28669-1.28669
2649.57.456092.04391
26535.90026-2.90026
2661.54.1291-2.6291
26766.65018-0.650178
2680.56.83454-6.33454
2696.56.487760.012243
2707.56.489781.01022
2714.56.4489-1.9489
27286.449441.55056
27396.571222.42878
2747.57.139380.360616
2758.56.81061.6894
27675.085091.91491
2779.56.557322.94268
2786.56.328730.171275
2799.54.798394.70161
28065.946210.0537875
28185.979542.02046
2829.57.407542.09246
28386.37041.6296
28486.062671.93733
28596.749212.25079
28656.17307-1.17307

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 7.57716 & -0.077161 \tabularnewline
2 & 2.5 & 6.04024 & -3.54024 \tabularnewline
3 & 6 & 5.95727 & 0.042727 \tabularnewline
4 & 6.5 & 6.4183 & 0.0816984 \tabularnewline
5 & 1 & 6.31765 & -5.31765 \tabularnewline
6 & 1 & 6.49618 & -5.49618 \tabularnewline
7 & 5.5 & 6.00461 & -0.504607 \tabularnewline
8 & 8.5 & 6.32671 & 2.17329 \tabularnewline
9 & 6.5 & 7.18821 & -0.688211 \tabularnewline
10 & 4.5 & 5.98077 & -1.48077 \tabularnewline
11 & 2 & 5.85292 & -3.85292 \tabularnewline
12 & 5 & 6.33847 & -1.33847 \tabularnewline
13 & 0.5 & 5.86096 & -5.36096 \tabularnewline
14 & 5 & 4.88513 & 0.114867 \tabularnewline
15 & 5 & 6.73478 & -1.73478 \tabularnewline
16 & 2.5 & 4.90939 & -2.40939 \tabularnewline
17 & 5 & 4.02686 & 0.973143 \tabularnewline
18 & 5.5 & 6.75442 & -1.25442 \tabularnewline
19 & 3.5 & 5.73849 & -2.23849 \tabularnewline
20 & 3 & 6.64449 & -3.64449 \tabularnewline
21 & 4 & 4.32715 & -0.327147 \tabularnewline
22 & 0.5 & 4.44105 & -3.94105 \tabularnewline
23 & 6.5 & 5.59599 & 0.904008 \tabularnewline
24 & 4.5 & 5.04202 & -0.542016 \tabularnewline
25 & 7.5 & 5.86699 & 1.63301 \tabularnewline
26 & 5.5 & 6.56834 & -1.06834 \tabularnewline
27 & 4 & 5.95877 & -1.95877 \tabularnewline
28 & 7.5 & 7.86105 & -0.361051 \tabularnewline
29 & 7 & 7.20117 & -0.201173 \tabularnewline
30 & 4 & 6.71461 & -2.71461 \tabularnewline
31 & 5.5 & 5.09192 & 0.408078 \tabularnewline
32 & 2.5 & 5.50345 & -3.00345 \tabularnewline
33 & 5.5 & 6.20191 & -0.701908 \tabularnewline
34 & 0.5 & 5.81673 & -5.31673 \tabularnewline
35 & 3.5 & 5.81756 & -2.31756 \tabularnewline
36 & 2.5 & 4.88077 & -2.38077 \tabularnewline
37 & 4.5 & 5.68942 & -1.18942 \tabularnewline
38 & 4.5 & 5.67929 & -1.17929 \tabularnewline
39 & 4.5 & 5.61355 & -1.11355 \tabularnewline
40 & 6 & 5.23322 & 0.766777 \tabularnewline
41 & 2.5 & 6.72519 & -4.22519 \tabularnewline
42 & 5 & 6.23092 & -1.23092 \tabularnewline
43 & 0 & 6.22555 & -6.22555 \tabularnewline
44 & 5 & 6.44386 & -1.44386 \tabularnewline
45 & 6.5 & 5.61007 & 0.889933 \tabularnewline
46 & 5 & 5.71499 & -0.714987 \tabularnewline
47 & 6 & 5.48285 & 0.517146 \tabularnewline
48 & 4.5 & 6.28583 & -1.78583 \tabularnewline
49 & 5.5 & 6.20387 & -0.703866 \tabularnewline
50 & 1 & 6.49075 & -5.49075 \tabularnewline
51 & 7.5 & 5.34919 & 2.15081 \tabularnewline
52 & 6 & 5.01417 & 0.985825 \tabularnewline
53 & 5 & 5.97341 & -0.973412 \tabularnewline
54 & 1 & 5.8718 & -4.8718 \tabularnewline
55 & 5 & 5.33865 & -0.338651 \tabularnewline
56 & 6.5 & 5.70708 & 0.79292 \tabularnewline
57 & 7 & 5.58384 & 1.41616 \tabularnewline
58 & 4.5 & 6.03427 & -1.53427 \tabularnewline
59 & 0 & 5.01156 & -5.01156 \tabularnewline
60 & 8.5 & 5.69469 & 2.80531 \tabularnewline
61 & 3.5 & 4.58201 & -1.08201 \tabularnewline
62 & 7.5 & 7.33808 & 0.16192 \tabularnewline
63 & 3.5 & 7.13544 & -3.63544 \tabularnewline
64 & 6 & 5.32254 & 0.677461 \tabularnewline
65 & 1.5 & 5.65758 & -4.15758 \tabularnewline
66 & 9 & 6.87179 & 2.12821 \tabularnewline
67 & 3.5 & 6.14474 & -2.64474 \tabularnewline
68 & 3.5 & 5.76147 & -2.26147 \tabularnewline
69 & 4 & 6.31387 & -2.31387 \tabularnewline
70 & 6.5 & 7.59788 & -1.09788 \tabularnewline
71 & 7.5 & 5.21727 & 2.28273 \tabularnewline
72 & 6 & 6.81747 & -0.817474 \tabularnewline
73 & 5 & 7.02842 & -2.02842 \tabularnewline
74 & 5.5 & 5.131 & 0.369003 \tabularnewline
75 & 3.5 & 7.07013 & -3.57013 \tabularnewline
76 & 7.5 & 7.75587 & -0.255866 \tabularnewline
77 & 1 & 6.04402 & -5.04402 \tabularnewline
78 & 6.5 & 5.46406 & 1.03594 \tabularnewline
79 & 6.5 & 6.31236 & 0.187638 \tabularnewline
80 & 6.5 & 6.15013 & 0.349868 \tabularnewline
81 & 7 & 6.91448 & 0.0855172 \tabularnewline
82 & 3.5 & 5.79023 & -2.29023 \tabularnewline
83 & 1.5 & 6.29899 & -4.79899 \tabularnewline
84 & 4 & 6.57284 & -2.57284 \tabularnewline
85 & 7.5 & 5.59498 & 1.90502 \tabularnewline
86 & 4.5 & 6.67585 & -2.17585 \tabularnewline
87 & 0 & 5.66156 & -5.66156 \tabularnewline
88 & 3.5 & 6.55191 & -3.05191 \tabularnewline
89 & 5.5 & 7.54066 & -2.04066 \tabularnewline
90 & 5 & 6.2406 & -1.2406 \tabularnewline
91 & 4.5 & 5.30386 & -0.803855 \tabularnewline
92 & 2.5 & 6.3818 & -3.8818 \tabularnewline
93 & 7.5 & 6.33669 & 1.16331 \tabularnewline
94 & 7 & 6.58827 & 0.411733 \tabularnewline
95 & 0 & 5.65575 & -5.65575 \tabularnewline
96 & 4.5 & 7.34518 & -2.84518 \tabularnewline
97 & 3 & 6.57757 & -3.57757 \tabularnewline
98 & 1.5 & 6.29335 & -4.79335 \tabularnewline
99 & 3.5 & 5.24422 & -1.74422 \tabularnewline
100 & 2.5 & 6.45463 & -3.95463 \tabularnewline
101 & 5.5 & 4.47451 & 1.02549 \tabularnewline
102 & 8 & 5.4232 & 2.5768 \tabularnewline
103 & 1 & 5.61659 & -4.61659 \tabularnewline
104 & 5 & 5.78326 & -0.783256 \tabularnewline
105 & 4.5 & 5.92011 & -1.42011 \tabularnewline
106 & 3 & 5.56446 & -2.56446 \tabularnewline
107 & 3 & 5.92627 & -2.92627 \tabularnewline
108 & 8 & 6.8754 & 1.1246 \tabularnewline
109 & 2.5 & 6.16487 & -3.66487 \tabularnewline
110 & 7 & 5.99595 & 1.00405 \tabularnewline
111 & 0 & 5.52564 & -5.52564 \tabularnewline
112 & 1 & 5.39805 & -4.39805 \tabularnewline
113 & 3.5 & 7.11498 & -3.61498 \tabularnewline
114 & 5.5 & 6.06196 & -0.56196 \tabularnewline
115 & 5.5 & 5.9104 & -0.410403 \tabularnewline
116 & 0.5 & 5.72719 & -5.22719 \tabularnewline
117 & 7.5 & 6.39739 & 1.10261 \tabularnewline
118 & 9 & 5.62697 & 3.37303 \tabularnewline
119 & 9.5 & 6.34061 & 3.15939 \tabularnewline
120 & 8.5 & 9.45688 & -0.956884 \tabularnewline
121 & 7 & 5.75639 & 1.24361 \tabularnewline
122 & 8 & 7.34612 & 0.653883 \tabularnewline
123 & 10 & 7.20813 & 2.79187 \tabularnewline
124 & 7 & 9.05865 & -2.05865 \tabularnewline
125 & 8.5 & 5.0712 & 3.4288 \tabularnewline
126 & 9 & 7.19196 & 1.80804 \tabularnewline
127 & 9.5 & 5.05394 & 4.44606 \tabularnewline
128 & 4 & 5.96567 & -1.96567 \tabularnewline
129 & 6 & 5.30355 & 0.696447 \tabularnewline
130 & 8 & 5.71197 & 2.28803 \tabularnewline
131 & 5.5 & 5.46433 & 0.0356671 \tabularnewline
132 & 9.5 & 6.72777 & 2.77223 \tabularnewline
133 & 7.5 & 5.54585 & 1.95415 \tabularnewline
134 & 7 & 6.22897 & 0.771032 \tabularnewline
135 & 7.5 & 6.95862 & 0.541383 \tabularnewline
136 & 8 & 4.64138 & 3.35862 \tabularnewline
137 & 7 & 4.65165 & 2.34835 \tabularnewline
138 & 7 & 5.51112 & 1.48888 \tabularnewline
139 & 6 & 6.27148 & -0.271484 \tabularnewline
140 & 10 & 6.05229 & 3.94771 \tabularnewline
141 & 2.5 & 5.10487 & -2.60487 \tabularnewline
142 & 9 & 6.10895 & 2.89105 \tabularnewline
143 & 8 & 6.63916 & 1.36084 \tabularnewline
144 & 6 & 6.27589 & -0.275893 \tabularnewline
145 & 8.5 & 4.75731 & 3.74269 \tabularnewline
146 & 6 & 4.2481 & 1.7519 \tabularnewline
147 & 9 & 5.49417 & 3.50583 \tabularnewline
148 & 8 & 5.21124 & 2.78876 \tabularnewline
149 & 8 & 6.38399 & 1.61601 \tabularnewline
150 & 9 & 7.58881 & 1.41119 \tabularnewline
151 & 5.5 & 6.2771 & -0.777098 \tabularnewline
152 & 5 & 5.13335 & -0.133354 \tabularnewline
153 & 7 & 5.89395 & 1.10605 \tabularnewline
154 & 5.5 & 5.52363 & -0.0236298 \tabularnewline
155 & 9 & 6.43977 & 2.56023 \tabularnewline
156 & 2 & 4.86399 & -2.86399 \tabularnewline
157 & 8.5 & 6.78574 & 1.71426 \tabularnewline
158 & 9 & 6.44839 & 2.55161 \tabularnewline
159 & 8.5 & 6.36102 & 2.13898 \tabularnewline
160 & 9 & 6.00796 & 2.99204 \tabularnewline
161 & 7.5 & 7.38792 & 0.112084 \tabularnewline
162 & 10 & 7.77283 & 2.22717 \tabularnewline
163 & 9 & 5.93525 & 3.06475 \tabularnewline
164 & 7.5 & 8.30849 & -0.808489 \tabularnewline
165 & 6 & 6.65006 & -0.650057 \tabularnewline
166 & 10.5 & 8.0606 & 2.4394 \tabularnewline
167 & 8.5 & 5.98336 & 2.51664 \tabularnewline
168 & 8 & 6.61734 & 1.38266 \tabularnewline
169 & 10 & 5.6835 & 4.3165 \tabularnewline
170 & 10.5 & 8.73998 & 1.76002 \tabularnewline
171 & 6.5 & 5.72672 & 0.773283 \tabularnewline
172 & 9.5 & 7.44141 & 2.05859 \tabularnewline
173 & 8.5 & 5.32675 & 3.17325 \tabularnewline
174 & 7.5 & 6.91889 & 0.581108 \tabularnewline
175 & 5 & 6.8092 & -1.8092 \tabularnewline
176 & 8 & 6.23135 & 1.76865 \tabularnewline
177 & 10 & 7.11069 & 2.88931 \tabularnewline
178 & 7 & 6.69218 & 0.307822 \tabularnewline
179 & 7.5 & 6.30137 & 1.19863 \tabularnewline
180 & 7.5 & 6.21183 & 1.28817 \tabularnewline
181 & 9.5 & 6.68782 & 2.81218 \tabularnewline
182 & 6 & 5.69186 & 0.308143 \tabularnewline
183 & 10 & 6.07883 & 3.92117 \tabularnewline
184 & 7 & 6.76293 & 0.237074 \tabularnewline
185 & 3 & 4.0932 & -1.0932 \tabularnewline
186 & 6 & 8.23805 & -2.23805 \tabularnewline
187 & 7 & 6.54514 & 0.454863 \tabularnewline
188 & 10 & 6.46545 & 3.53455 \tabularnewline
189 & 7 & 6.67876 & 0.321236 \tabularnewline
190 & 3.5 & 6.15809 & -2.65809 \tabularnewline
191 & 8 & 7.47152 & 0.528485 \tabularnewline
192 & 10 & 6.39388 & 3.60612 \tabularnewline
193 & 5.5 & 6.94659 & -1.44659 \tabularnewline
194 & 6 & 5.7281 & 0.271897 \tabularnewline
195 & 6.5 & 5.63612 & 0.863883 \tabularnewline
196 & 6.5 & 6.72041 & -0.220411 \tabularnewline
197 & 8.5 & 5.87568 & 2.62432 \tabularnewline
198 & 4 & 6.09564 & -2.09564 \tabularnewline
199 & 9.5 & 6.24351 & 3.25649 \tabularnewline
200 & 8 & 6.76162 & 1.23838 \tabularnewline
201 & 8.5 & 7.1375 & 1.3625 \tabularnewline
202 & 5.5 & 6.47503 & -0.975031 \tabularnewline
203 & 7 & 6.09324 & 0.906757 \tabularnewline
204 & 9 & 6.02356 & 2.97644 \tabularnewline
205 & 8 & 6.87035 & 1.12965 \tabularnewline
206 & 10 & 8.05735 & 1.94265 \tabularnewline
207 & 8 & 7.08901 & 0.910988 \tabularnewline
208 & 6 & 5.96241 & 0.0375879 \tabularnewline
209 & 8 & 6.40952 & 1.59048 \tabularnewline
210 & 5 & 4.44017 & 0.559835 \tabularnewline
211 & 9 & 6.09551 & 2.90449 \tabularnewline
212 & 4.5 & 4.37819 & 0.121806 \tabularnewline
213 & 8.5 & 7.1135 & 1.3865 \tabularnewline
214 & 7 & 5.80255 & 1.19745 \tabularnewline
215 & 9.5 & 6.40412 & 3.09588 \tabularnewline
216 & 8.5 & 6.6464 & 1.8536 \tabularnewline
217 & 7.5 & 6.47491 & 1.02509 \tabularnewline
218 & 7.5 & 5.86662 & 1.63338 \tabularnewline
219 & 5 & 5.85898 & -0.858975 \tabularnewline
220 & 7 & 5.60976 & 1.39024 \tabularnewline
221 & 8 & 6.63446 & 1.36554 \tabularnewline
222 & 5.5 & 5.37198 & 0.128015 \tabularnewline
223 & 8.5 & 6.90152 & 1.59848 \tabularnewline
224 & 7.5 & 5.88855 & 1.61145 \tabularnewline
225 & 9.5 & 5.5055 & 3.9945 \tabularnewline
226 & 7 & 6.34848 & 0.651517 \tabularnewline
227 & 8 & 7.72305 & 0.276947 \tabularnewline
228 & 8.5 & 5.20387 & 3.29613 \tabularnewline
229 & 3.5 & 5.27322 & -1.77322 \tabularnewline
230 & 6.5 & 5.99642 & 0.503583 \tabularnewline
231 & 6.5 & 4.745 & 1.755 \tabularnewline
232 & 10.5 & 6.09727 & 4.40273 \tabularnewline
233 & 8.5 & 6.3927 & 2.1073 \tabularnewline
234 & 8 & 5.348 & 2.652 \tabularnewline
235 & 10 & 6.25537 & 3.74463 \tabularnewline
236 & 10 & 6.97296 & 3.02704 \tabularnewline
237 & 9.5 & 5.9743 & 3.5257 \tabularnewline
238 & 9 & 4.4049 & 4.5951 \tabularnewline
239 & 10 & 7.47662 & 2.52338 \tabularnewline
240 & 7.5 & 4.90703 & 2.59297 \tabularnewline
241 & 4.5 & 4.96604 & -0.46604 \tabularnewline
242 & 4.5 & 4.36013 & 0.139872 \tabularnewline
243 & 0.5 & 5.52892 & -5.02892 \tabularnewline
244 & 6.5 & 5.05318 & 1.44682 \tabularnewline
245 & 4.5 & 5.2958 & -0.795799 \tabularnewline
246 & 5.5 & 6.23216 & -0.732159 \tabularnewline
247 & 5 & 5.89336 & -0.893357 \tabularnewline
248 & 6 & 6.08553 & -0.0855276 \tabularnewline
249 & 4 & 5.08608 & -1.08608 \tabularnewline
250 & 8 & 6.44944 & 1.55056 \tabularnewline
251 & 10.5 & 8.29231 & 2.20769 \tabularnewline
252 & 8.5 & 6.2733 & 2.2267 \tabularnewline
253 & 6.5 & 6.32303 & 0.176967 \tabularnewline
254 & 8 & 6.8453 & 1.1547 \tabularnewline
255 & 8.5 & 7.20953 & 1.29047 \tabularnewline
256 & 5.5 & 5.82242 & -0.322418 \tabularnewline
257 & 7 & 6.92354 & 0.0764567 \tabularnewline
258 & 5 & 5.68939 & -0.689391 \tabularnewline
259 & 3.5 & 5.15178 & -1.65178 \tabularnewline
260 & 5 & 6.22779 & -1.22779 \tabularnewline
261 & 9 & 7.03474 & 1.96526 \tabularnewline
262 & 8.5 & 7.26818 & 1.23182 \tabularnewline
263 & 5 & 6.28669 & -1.28669 \tabularnewline
264 & 9.5 & 7.45609 & 2.04391 \tabularnewline
265 & 3 & 5.90026 & -2.90026 \tabularnewline
266 & 1.5 & 4.1291 & -2.6291 \tabularnewline
267 & 6 & 6.65018 & -0.650178 \tabularnewline
268 & 0.5 & 6.83454 & -6.33454 \tabularnewline
269 & 6.5 & 6.48776 & 0.012243 \tabularnewline
270 & 7.5 & 6.48978 & 1.01022 \tabularnewline
271 & 4.5 & 6.4489 & -1.9489 \tabularnewline
272 & 8 & 6.44944 & 1.55056 \tabularnewline
273 & 9 & 6.57122 & 2.42878 \tabularnewline
274 & 7.5 & 7.13938 & 0.360616 \tabularnewline
275 & 8.5 & 6.8106 & 1.6894 \tabularnewline
276 & 7 & 5.08509 & 1.91491 \tabularnewline
277 & 9.5 & 6.55732 & 2.94268 \tabularnewline
278 & 6.5 & 6.32873 & 0.171275 \tabularnewline
279 & 9.5 & 4.79839 & 4.70161 \tabularnewline
280 & 6 & 5.94621 & 0.0537875 \tabularnewline
281 & 8 & 5.97954 & 2.02046 \tabularnewline
282 & 9.5 & 7.40754 & 2.09246 \tabularnewline
283 & 8 & 6.3704 & 1.6296 \tabularnewline
284 & 8 & 6.06267 & 1.93733 \tabularnewline
285 & 9 & 6.74921 & 2.25079 \tabularnewline
286 & 5 & 6.17307 & -1.17307 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270029&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]7.5[/C][C]7.57716[/C][C]-0.077161[/C][/ROW]
[ROW][C]2[/C][C]2.5[/C][C]6.04024[/C][C]-3.54024[/C][/ROW]
[ROW][C]3[/C][C]6[/C][C]5.95727[/C][C]0.042727[/C][/ROW]
[ROW][C]4[/C][C]6.5[/C][C]6.4183[/C][C]0.0816984[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]6.31765[/C][C]-5.31765[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]6.49618[/C][C]-5.49618[/C][/ROW]
[ROW][C]7[/C][C]5.5[/C][C]6.00461[/C][C]-0.504607[/C][/ROW]
[ROW][C]8[/C][C]8.5[/C][C]6.32671[/C][C]2.17329[/C][/ROW]
[ROW][C]9[/C][C]6.5[/C][C]7.18821[/C][C]-0.688211[/C][/ROW]
[ROW][C]10[/C][C]4.5[/C][C]5.98077[/C][C]-1.48077[/C][/ROW]
[ROW][C]11[/C][C]2[/C][C]5.85292[/C][C]-3.85292[/C][/ROW]
[ROW][C]12[/C][C]5[/C][C]6.33847[/C][C]-1.33847[/C][/ROW]
[ROW][C]13[/C][C]0.5[/C][C]5.86096[/C][C]-5.36096[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]4.88513[/C][C]0.114867[/C][/ROW]
[ROW][C]15[/C][C]5[/C][C]6.73478[/C][C]-1.73478[/C][/ROW]
[ROW][C]16[/C][C]2.5[/C][C]4.90939[/C][C]-2.40939[/C][/ROW]
[ROW][C]17[/C][C]5[/C][C]4.02686[/C][C]0.973143[/C][/ROW]
[ROW][C]18[/C][C]5.5[/C][C]6.75442[/C][C]-1.25442[/C][/ROW]
[ROW][C]19[/C][C]3.5[/C][C]5.73849[/C][C]-2.23849[/C][/ROW]
[ROW][C]20[/C][C]3[/C][C]6.64449[/C][C]-3.64449[/C][/ROW]
[ROW][C]21[/C][C]4[/C][C]4.32715[/C][C]-0.327147[/C][/ROW]
[ROW][C]22[/C][C]0.5[/C][C]4.44105[/C][C]-3.94105[/C][/ROW]
[ROW][C]23[/C][C]6.5[/C][C]5.59599[/C][C]0.904008[/C][/ROW]
[ROW][C]24[/C][C]4.5[/C][C]5.04202[/C][C]-0.542016[/C][/ROW]
[ROW][C]25[/C][C]7.5[/C][C]5.86699[/C][C]1.63301[/C][/ROW]
[ROW][C]26[/C][C]5.5[/C][C]6.56834[/C][C]-1.06834[/C][/ROW]
[ROW][C]27[/C][C]4[/C][C]5.95877[/C][C]-1.95877[/C][/ROW]
[ROW][C]28[/C][C]7.5[/C][C]7.86105[/C][C]-0.361051[/C][/ROW]
[ROW][C]29[/C][C]7[/C][C]7.20117[/C][C]-0.201173[/C][/ROW]
[ROW][C]30[/C][C]4[/C][C]6.71461[/C][C]-2.71461[/C][/ROW]
[ROW][C]31[/C][C]5.5[/C][C]5.09192[/C][C]0.408078[/C][/ROW]
[ROW][C]32[/C][C]2.5[/C][C]5.50345[/C][C]-3.00345[/C][/ROW]
[ROW][C]33[/C][C]5.5[/C][C]6.20191[/C][C]-0.701908[/C][/ROW]
[ROW][C]34[/C][C]0.5[/C][C]5.81673[/C][C]-5.31673[/C][/ROW]
[ROW][C]35[/C][C]3.5[/C][C]5.81756[/C][C]-2.31756[/C][/ROW]
[ROW][C]36[/C][C]2.5[/C][C]4.88077[/C][C]-2.38077[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]5.68942[/C][C]-1.18942[/C][/ROW]
[ROW][C]38[/C][C]4.5[/C][C]5.67929[/C][C]-1.17929[/C][/ROW]
[ROW][C]39[/C][C]4.5[/C][C]5.61355[/C][C]-1.11355[/C][/ROW]
[ROW][C]40[/C][C]6[/C][C]5.23322[/C][C]0.766777[/C][/ROW]
[ROW][C]41[/C][C]2.5[/C][C]6.72519[/C][C]-4.22519[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]6.23092[/C][C]-1.23092[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]6.22555[/C][C]-6.22555[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]6.44386[/C][C]-1.44386[/C][/ROW]
[ROW][C]45[/C][C]6.5[/C][C]5.61007[/C][C]0.889933[/C][/ROW]
[ROW][C]46[/C][C]5[/C][C]5.71499[/C][C]-0.714987[/C][/ROW]
[ROW][C]47[/C][C]6[/C][C]5.48285[/C][C]0.517146[/C][/ROW]
[ROW][C]48[/C][C]4.5[/C][C]6.28583[/C][C]-1.78583[/C][/ROW]
[ROW][C]49[/C][C]5.5[/C][C]6.20387[/C][C]-0.703866[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]6.49075[/C][C]-5.49075[/C][/ROW]
[ROW][C]51[/C][C]7.5[/C][C]5.34919[/C][C]2.15081[/C][/ROW]
[ROW][C]52[/C][C]6[/C][C]5.01417[/C][C]0.985825[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]5.97341[/C][C]-0.973412[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]5.8718[/C][C]-4.8718[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]5.33865[/C][C]-0.338651[/C][/ROW]
[ROW][C]56[/C][C]6.5[/C][C]5.70708[/C][C]0.79292[/C][/ROW]
[ROW][C]57[/C][C]7[/C][C]5.58384[/C][C]1.41616[/C][/ROW]
[ROW][C]58[/C][C]4.5[/C][C]6.03427[/C][C]-1.53427[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]5.01156[/C][C]-5.01156[/C][/ROW]
[ROW][C]60[/C][C]8.5[/C][C]5.69469[/C][C]2.80531[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]4.58201[/C][C]-1.08201[/C][/ROW]
[ROW][C]62[/C][C]7.5[/C][C]7.33808[/C][C]0.16192[/C][/ROW]
[ROW][C]63[/C][C]3.5[/C][C]7.13544[/C][C]-3.63544[/C][/ROW]
[ROW][C]64[/C][C]6[/C][C]5.32254[/C][C]0.677461[/C][/ROW]
[ROW][C]65[/C][C]1.5[/C][C]5.65758[/C][C]-4.15758[/C][/ROW]
[ROW][C]66[/C][C]9[/C][C]6.87179[/C][C]2.12821[/C][/ROW]
[ROW][C]67[/C][C]3.5[/C][C]6.14474[/C][C]-2.64474[/C][/ROW]
[ROW][C]68[/C][C]3.5[/C][C]5.76147[/C][C]-2.26147[/C][/ROW]
[ROW][C]69[/C][C]4[/C][C]6.31387[/C][C]-2.31387[/C][/ROW]
[ROW][C]70[/C][C]6.5[/C][C]7.59788[/C][C]-1.09788[/C][/ROW]
[ROW][C]71[/C][C]7.5[/C][C]5.21727[/C][C]2.28273[/C][/ROW]
[ROW][C]72[/C][C]6[/C][C]6.81747[/C][C]-0.817474[/C][/ROW]
[ROW][C]73[/C][C]5[/C][C]7.02842[/C][C]-2.02842[/C][/ROW]
[ROW][C]74[/C][C]5.5[/C][C]5.131[/C][C]0.369003[/C][/ROW]
[ROW][C]75[/C][C]3.5[/C][C]7.07013[/C][C]-3.57013[/C][/ROW]
[ROW][C]76[/C][C]7.5[/C][C]7.75587[/C][C]-0.255866[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]6.04402[/C][C]-5.04402[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]5.46406[/C][C]1.03594[/C][/ROW]
[ROW][C]79[/C][C]6.5[/C][C]6.31236[/C][C]0.187638[/C][/ROW]
[ROW][C]80[/C][C]6.5[/C][C]6.15013[/C][C]0.349868[/C][/ROW]
[ROW][C]81[/C][C]7[/C][C]6.91448[/C][C]0.0855172[/C][/ROW]
[ROW][C]82[/C][C]3.5[/C][C]5.79023[/C][C]-2.29023[/C][/ROW]
[ROW][C]83[/C][C]1.5[/C][C]6.29899[/C][C]-4.79899[/C][/ROW]
[ROW][C]84[/C][C]4[/C][C]6.57284[/C][C]-2.57284[/C][/ROW]
[ROW][C]85[/C][C]7.5[/C][C]5.59498[/C][C]1.90502[/C][/ROW]
[ROW][C]86[/C][C]4.5[/C][C]6.67585[/C][C]-2.17585[/C][/ROW]
[ROW][C]87[/C][C]0[/C][C]5.66156[/C][C]-5.66156[/C][/ROW]
[ROW][C]88[/C][C]3.5[/C][C]6.55191[/C][C]-3.05191[/C][/ROW]
[ROW][C]89[/C][C]5.5[/C][C]7.54066[/C][C]-2.04066[/C][/ROW]
[ROW][C]90[/C][C]5[/C][C]6.2406[/C][C]-1.2406[/C][/ROW]
[ROW][C]91[/C][C]4.5[/C][C]5.30386[/C][C]-0.803855[/C][/ROW]
[ROW][C]92[/C][C]2.5[/C][C]6.3818[/C][C]-3.8818[/C][/ROW]
[ROW][C]93[/C][C]7.5[/C][C]6.33669[/C][C]1.16331[/C][/ROW]
[ROW][C]94[/C][C]7[/C][C]6.58827[/C][C]0.411733[/C][/ROW]
[ROW][C]95[/C][C]0[/C][C]5.65575[/C][C]-5.65575[/C][/ROW]
[ROW][C]96[/C][C]4.5[/C][C]7.34518[/C][C]-2.84518[/C][/ROW]
[ROW][C]97[/C][C]3[/C][C]6.57757[/C][C]-3.57757[/C][/ROW]
[ROW][C]98[/C][C]1.5[/C][C]6.29335[/C][C]-4.79335[/C][/ROW]
[ROW][C]99[/C][C]3.5[/C][C]5.24422[/C][C]-1.74422[/C][/ROW]
[ROW][C]100[/C][C]2.5[/C][C]6.45463[/C][C]-3.95463[/C][/ROW]
[ROW][C]101[/C][C]5.5[/C][C]4.47451[/C][C]1.02549[/C][/ROW]
[ROW][C]102[/C][C]8[/C][C]5.4232[/C][C]2.5768[/C][/ROW]
[ROW][C]103[/C][C]1[/C][C]5.61659[/C][C]-4.61659[/C][/ROW]
[ROW][C]104[/C][C]5[/C][C]5.78326[/C][C]-0.783256[/C][/ROW]
[ROW][C]105[/C][C]4.5[/C][C]5.92011[/C][C]-1.42011[/C][/ROW]
[ROW][C]106[/C][C]3[/C][C]5.56446[/C][C]-2.56446[/C][/ROW]
[ROW][C]107[/C][C]3[/C][C]5.92627[/C][C]-2.92627[/C][/ROW]
[ROW][C]108[/C][C]8[/C][C]6.8754[/C][C]1.1246[/C][/ROW]
[ROW][C]109[/C][C]2.5[/C][C]6.16487[/C][C]-3.66487[/C][/ROW]
[ROW][C]110[/C][C]7[/C][C]5.99595[/C][C]1.00405[/C][/ROW]
[ROW][C]111[/C][C]0[/C][C]5.52564[/C][C]-5.52564[/C][/ROW]
[ROW][C]112[/C][C]1[/C][C]5.39805[/C][C]-4.39805[/C][/ROW]
[ROW][C]113[/C][C]3.5[/C][C]7.11498[/C][C]-3.61498[/C][/ROW]
[ROW][C]114[/C][C]5.5[/C][C]6.06196[/C][C]-0.56196[/C][/ROW]
[ROW][C]115[/C][C]5.5[/C][C]5.9104[/C][C]-0.410403[/C][/ROW]
[ROW][C]116[/C][C]0.5[/C][C]5.72719[/C][C]-5.22719[/C][/ROW]
[ROW][C]117[/C][C]7.5[/C][C]6.39739[/C][C]1.10261[/C][/ROW]
[ROW][C]118[/C][C]9[/C][C]5.62697[/C][C]3.37303[/C][/ROW]
[ROW][C]119[/C][C]9.5[/C][C]6.34061[/C][C]3.15939[/C][/ROW]
[ROW][C]120[/C][C]8.5[/C][C]9.45688[/C][C]-0.956884[/C][/ROW]
[ROW][C]121[/C][C]7[/C][C]5.75639[/C][C]1.24361[/C][/ROW]
[ROW][C]122[/C][C]8[/C][C]7.34612[/C][C]0.653883[/C][/ROW]
[ROW][C]123[/C][C]10[/C][C]7.20813[/C][C]2.79187[/C][/ROW]
[ROW][C]124[/C][C]7[/C][C]9.05865[/C][C]-2.05865[/C][/ROW]
[ROW][C]125[/C][C]8.5[/C][C]5.0712[/C][C]3.4288[/C][/ROW]
[ROW][C]126[/C][C]9[/C][C]7.19196[/C][C]1.80804[/C][/ROW]
[ROW][C]127[/C][C]9.5[/C][C]5.05394[/C][C]4.44606[/C][/ROW]
[ROW][C]128[/C][C]4[/C][C]5.96567[/C][C]-1.96567[/C][/ROW]
[ROW][C]129[/C][C]6[/C][C]5.30355[/C][C]0.696447[/C][/ROW]
[ROW][C]130[/C][C]8[/C][C]5.71197[/C][C]2.28803[/C][/ROW]
[ROW][C]131[/C][C]5.5[/C][C]5.46433[/C][C]0.0356671[/C][/ROW]
[ROW][C]132[/C][C]9.5[/C][C]6.72777[/C][C]2.77223[/C][/ROW]
[ROW][C]133[/C][C]7.5[/C][C]5.54585[/C][C]1.95415[/C][/ROW]
[ROW][C]134[/C][C]7[/C][C]6.22897[/C][C]0.771032[/C][/ROW]
[ROW][C]135[/C][C]7.5[/C][C]6.95862[/C][C]0.541383[/C][/ROW]
[ROW][C]136[/C][C]8[/C][C]4.64138[/C][C]3.35862[/C][/ROW]
[ROW][C]137[/C][C]7[/C][C]4.65165[/C][C]2.34835[/C][/ROW]
[ROW][C]138[/C][C]7[/C][C]5.51112[/C][C]1.48888[/C][/ROW]
[ROW][C]139[/C][C]6[/C][C]6.27148[/C][C]-0.271484[/C][/ROW]
[ROW][C]140[/C][C]10[/C][C]6.05229[/C][C]3.94771[/C][/ROW]
[ROW][C]141[/C][C]2.5[/C][C]5.10487[/C][C]-2.60487[/C][/ROW]
[ROW][C]142[/C][C]9[/C][C]6.10895[/C][C]2.89105[/C][/ROW]
[ROW][C]143[/C][C]8[/C][C]6.63916[/C][C]1.36084[/C][/ROW]
[ROW][C]144[/C][C]6[/C][C]6.27589[/C][C]-0.275893[/C][/ROW]
[ROW][C]145[/C][C]8.5[/C][C]4.75731[/C][C]3.74269[/C][/ROW]
[ROW][C]146[/C][C]6[/C][C]4.2481[/C][C]1.7519[/C][/ROW]
[ROW][C]147[/C][C]9[/C][C]5.49417[/C][C]3.50583[/C][/ROW]
[ROW][C]148[/C][C]8[/C][C]5.21124[/C][C]2.78876[/C][/ROW]
[ROW][C]149[/C][C]8[/C][C]6.38399[/C][C]1.61601[/C][/ROW]
[ROW][C]150[/C][C]9[/C][C]7.58881[/C][C]1.41119[/C][/ROW]
[ROW][C]151[/C][C]5.5[/C][C]6.2771[/C][C]-0.777098[/C][/ROW]
[ROW][C]152[/C][C]5[/C][C]5.13335[/C][C]-0.133354[/C][/ROW]
[ROW][C]153[/C][C]7[/C][C]5.89395[/C][C]1.10605[/C][/ROW]
[ROW][C]154[/C][C]5.5[/C][C]5.52363[/C][C]-0.0236298[/C][/ROW]
[ROW][C]155[/C][C]9[/C][C]6.43977[/C][C]2.56023[/C][/ROW]
[ROW][C]156[/C][C]2[/C][C]4.86399[/C][C]-2.86399[/C][/ROW]
[ROW][C]157[/C][C]8.5[/C][C]6.78574[/C][C]1.71426[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]6.44839[/C][C]2.55161[/C][/ROW]
[ROW][C]159[/C][C]8.5[/C][C]6.36102[/C][C]2.13898[/C][/ROW]
[ROW][C]160[/C][C]9[/C][C]6.00796[/C][C]2.99204[/C][/ROW]
[ROW][C]161[/C][C]7.5[/C][C]7.38792[/C][C]0.112084[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]7.77283[/C][C]2.22717[/C][/ROW]
[ROW][C]163[/C][C]9[/C][C]5.93525[/C][C]3.06475[/C][/ROW]
[ROW][C]164[/C][C]7.5[/C][C]8.30849[/C][C]-0.808489[/C][/ROW]
[ROW][C]165[/C][C]6[/C][C]6.65006[/C][C]-0.650057[/C][/ROW]
[ROW][C]166[/C][C]10.5[/C][C]8.0606[/C][C]2.4394[/C][/ROW]
[ROW][C]167[/C][C]8.5[/C][C]5.98336[/C][C]2.51664[/C][/ROW]
[ROW][C]168[/C][C]8[/C][C]6.61734[/C][C]1.38266[/C][/ROW]
[ROW][C]169[/C][C]10[/C][C]5.6835[/C][C]4.3165[/C][/ROW]
[ROW][C]170[/C][C]10.5[/C][C]8.73998[/C][C]1.76002[/C][/ROW]
[ROW][C]171[/C][C]6.5[/C][C]5.72672[/C][C]0.773283[/C][/ROW]
[ROW][C]172[/C][C]9.5[/C][C]7.44141[/C][C]2.05859[/C][/ROW]
[ROW][C]173[/C][C]8.5[/C][C]5.32675[/C][C]3.17325[/C][/ROW]
[ROW][C]174[/C][C]7.5[/C][C]6.91889[/C][C]0.581108[/C][/ROW]
[ROW][C]175[/C][C]5[/C][C]6.8092[/C][C]-1.8092[/C][/ROW]
[ROW][C]176[/C][C]8[/C][C]6.23135[/C][C]1.76865[/C][/ROW]
[ROW][C]177[/C][C]10[/C][C]7.11069[/C][C]2.88931[/C][/ROW]
[ROW][C]178[/C][C]7[/C][C]6.69218[/C][C]0.307822[/C][/ROW]
[ROW][C]179[/C][C]7.5[/C][C]6.30137[/C][C]1.19863[/C][/ROW]
[ROW][C]180[/C][C]7.5[/C][C]6.21183[/C][C]1.28817[/C][/ROW]
[ROW][C]181[/C][C]9.5[/C][C]6.68782[/C][C]2.81218[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]5.69186[/C][C]0.308143[/C][/ROW]
[ROW][C]183[/C][C]10[/C][C]6.07883[/C][C]3.92117[/C][/ROW]
[ROW][C]184[/C][C]7[/C][C]6.76293[/C][C]0.237074[/C][/ROW]
[ROW][C]185[/C][C]3[/C][C]4.0932[/C][C]-1.0932[/C][/ROW]
[ROW][C]186[/C][C]6[/C][C]8.23805[/C][C]-2.23805[/C][/ROW]
[ROW][C]187[/C][C]7[/C][C]6.54514[/C][C]0.454863[/C][/ROW]
[ROW][C]188[/C][C]10[/C][C]6.46545[/C][C]3.53455[/C][/ROW]
[ROW][C]189[/C][C]7[/C][C]6.67876[/C][C]0.321236[/C][/ROW]
[ROW][C]190[/C][C]3.5[/C][C]6.15809[/C][C]-2.65809[/C][/ROW]
[ROW][C]191[/C][C]8[/C][C]7.47152[/C][C]0.528485[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]6.39388[/C][C]3.60612[/C][/ROW]
[ROW][C]193[/C][C]5.5[/C][C]6.94659[/C][C]-1.44659[/C][/ROW]
[ROW][C]194[/C][C]6[/C][C]5.7281[/C][C]0.271897[/C][/ROW]
[ROW][C]195[/C][C]6.5[/C][C]5.63612[/C][C]0.863883[/C][/ROW]
[ROW][C]196[/C][C]6.5[/C][C]6.72041[/C][C]-0.220411[/C][/ROW]
[ROW][C]197[/C][C]8.5[/C][C]5.87568[/C][C]2.62432[/C][/ROW]
[ROW][C]198[/C][C]4[/C][C]6.09564[/C][C]-2.09564[/C][/ROW]
[ROW][C]199[/C][C]9.5[/C][C]6.24351[/C][C]3.25649[/C][/ROW]
[ROW][C]200[/C][C]8[/C][C]6.76162[/C][C]1.23838[/C][/ROW]
[ROW][C]201[/C][C]8.5[/C][C]7.1375[/C][C]1.3625[/C][/ROW]
[ROW][C]202[/C][C]5.5[/C][C]6.47503[/C][C]-0.975031[/C][/ROW]
[ROW][C]203[/C][C]7[/C][C]6.09324[/C][C]0.906757[/C][/ROW]
[ROW][C]204[/C][C]9[/C][C]6.02356[/C][C]2.97644[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]6.87035[/C][C]1.12965[/C][/ROW]
[ROW][C]206[/C][C]10[/C][C]8.05735[/C][C]1.94265[/C][/ROW]
[ROW][C]207[/C][C]8[/C][C]7.08901[/C][C]0.910988[/C][/ROW]
[ROW][C]208[/C][C]6[/C][C]5.96241[/C][C]0.0375879[/C][/ROW]
[ROW][C]209[/C][C]8[/C][C]6.40952[/C][C]1.59048[/C][/ROW]
[ROW][C]210[/C][C]5[/C][C]4.44017[/C][C]0.559835[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]6.09551[/C][C]2.90449[/C][/ROW]
[ROW][C]212[/C][C]4.5[/C][C]4.37819[/C][C]0.121806[/C][/ROW]
[ROW][C]213[/C][C]8.5[/C][C]7.1135[/C][C]1.3865[/C][/ROW]
[ROW][C]214[/C][C]7[/C][C]5.80255[/C][C]1.19745[/C][/ROW]
[ROW][C]215[/C][C]9.5[/C][C]6.40412[/C][C]3.09588[/C][/ROW]
[ROW][C]216[/C][C]8.5[/C][C]6.6464[/C][C]1.8536[/C][/ROW]
[ROW][C]217[/C][C]7.5[/C][C]6.47491[/C][C]1.02509[/C][/ROW]
[ROW][C]218[/C][C]7.5[/C][C]5.86662[/C][C]1.63338[/C][/ROW]
[ROW][C]219[/C][C]5[/C][C]5.85898[/C][C]-0.858975[/C][/ROW]
[ROW][C]220[/C][C]7[/C][C]5.60976[/C][C]1.39024[/C][/ROW]
[ROW][C]221[/C][C]8[/C][C]6.63446[/C][C]1.36554[/C][/ROW]
[ROW][C]222[/C][C]5.5[/C][C]5.37198[/C][C]0.128015[/C][/ROW]
[ROW][C]223[/C][C]8.5[/C][C]6.90152[/C][C]1.59848[/C][/ROW]
[ROW][C]224[/C][C]7.5[/C][C]5.88855[/C][C]1.61145[/C][/ROW]
[ROW][C]225[/C][C]9.5[/C][C]5.5055[/C][C]3.9945[/C][/ROW]
[ROW][C]226[/C][C]7[/C][C]6.34848[/C][C]0.651517[/C][/ROW]
[ROW][C]227[/C][C]8[/C][C]7.72305[/C][C]0.276947[/C][/ROW]
[ROW][C]228[/C][C]8.5[/C][C]5.20387[/C][C]3.29613[/C][/ROW]
[ROW][C]229[/C][C]3.5[/C][C]5.27322[/C][C]-1.77322[/C][/ROW]
[ROW][C]230[/C][C]6.5[/C][C]5.99642[/C][C]0.503583[/C][/ROW]
[ROW][C]231[/C][C]6.5[/C][C]4.745[/C][C]1.755[/C][/ROW]
[ROW][C]232[/C][C]10.5[/C][C]6.09727[/C][C]4.40273[/C][/ROW]
[ROW][C]233[/C][C]8.5[/C][C]6.3927[/C][C]2.1073[/C][/ROW]
[ROW][C]234[/C][C]8[/C][C]5.348[/C][C]2.652[/C][/ROW]
[ROW][C]235[/C][C]10[/C][C]6.25537[/C][C]3.74463[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]6.97296[/C][C]3.02704[/C][/ROW]
[ROW][C]237[/C][C]9.5[/C][C]5.9743[/C][C]3.5257[/C][/ROW]
[ROW][C]238[/C][C]9[/C][C]4.4049[/C][C]4.5951[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]7.47662[/C][C]2.52338[/C][/ROW]
[ROW][C]240[/C][C]7.5[/C][C]4.90703[/C][C]2.59297[/C][/ROW]
[ROW][C]241[/C][C]4.5[/C][C]4.96604[/C][C]-0.46604[/C][/ROW]
[ROW][C]242[/C][C]4.5[/C][C]4.36013[/C][C]0.139872[/C][/ROW]
[ROW][C]243[/C][C]0.5[/C][C]5.52892[/C][C]-5.02892[/C][/ROW]
[ROW][C]244[/C][C]6.5[/C][C]5.05318[/C][C]1.44682[/C][/ROW]
[ROW][C]245[/C][C]4.5[/C][C]5.2958[/C][C]-0.795799[/C][/ROW]
[ROW][C]246[/C][C]5.5[/C][C]6.23216[/C][C]-0.732159[/C][/ROW]
[ROW][C]247[/C][C]5[/C][C]5.89336[/C][C]-0.893357[/C][/ROW]
[ROW][C]248[/C][C]6[/C][C]6.08553[/C][C]-0.0855276[/C][/ROW]
[ROW][C]249[/C][C]4[/C][C]5.08608[/C][C]-1.08608[/C][/ROW]
[ROW][C]250[/C][C]8[/C][C]6.44944[/C][C]1.55056[/C][/ROW]
[ROW][C]251[/C][C]10.5[/C][C]8.29231[/C][C]2.20769[/C][/ROW]
[ROW][C]252[/C][C]8.5[/C][C]6.2733[/C][C]2.2267[/C][/ROW]
[ROW][C]253[/C][C]6.5[/C][C]6.32303[/C][C]0.176967[/C][/ROW]
[ROW][C]254[/C][C]8[/C][C]6.8453[/C][C]1.1547[/C][/ROW]
[ROW][C]255[/C][C]8.5[/C][C]7.20953[/C][C]1.29047[/C][/ROW]
[ROW][C]256[/C][C]5.5[/C][C]5.82242[/C][C]-0.322418[/C][/ROW]
[ROW][C]257[/C][C]7[/C][C]6.92354[/C][C]0.0764567[/C][/ROW]
[ROW][C]258[/C][C]5[/C][C]5.68939[/C][C]-0.689391[/C][/ROW]
[ROW][C]259[/C][C]3.5[/C][C]5.15178[/C][C]-1.65178[/C][/ROW]
[ROW][C]260[/C][C]5[/C][C]6.22779[/C][C]-1.22779[/C][/ROW]
[ROW][C]261[/C][C]9[/C][C]7.03474[/C][C]1.96526[/C][/ROW]
[ROW][C]262[/C][C]8.5[/C][C]7.26818[/C][C]1.23182[/C][/ROW]
[ROW][C]263[/C][C]5[/C][C]6.28669[/C][C]-1.28669[/C][/ROW]
[ROW][C]264[/C][C]9.5[/C][C]7.45609[/C][C]2.04391[/C][/ROW]
[ROW][C]265[/C][C]3[/C][C]5.90026[/C][C]-2.90026[/C][/ROW]
[ROW][C]266[/C][C]1.5[/C][C]4.1291[/C][C]-2.6291[/C][/ROW]
[ROW][C]267[/C][C]6[/C][C]6.65018[/C][C]-0.650178[/C][/ROW]
[ROW][C]268[/C][C]0.5[/C][C]6.83454[/C][C]-6.33454[/C][/ROW]
[ROW][C]269[/C][C]6.5[/C][C]6.48776[/C][C]0.012243[/C][/ROW]
[ROW][C]270[/C][C]7.5[/C][C]6.48978[/C][C]1.01022[/C][/ROW]
[ROW][C]271[/C][C]4.5[/C][C]6.4489[/C][C]-1.9489[/C][/ROW]
[ROW][C]272[/C][C]8[/C][C]6.44944[/C][C]1.55056[/C][/ROW]
[ROW][C]273[/C][C]9[/C][C]6.57122[/C][C]2.42878[/C][/ROW]
[ROW][C]274[/C][C]7.5[/C][C]7.13938[/C][C]0.360616[/C][/ROW]
[ROW][C]275[/C][C]8.5[/C][C]6.8106[/C][C]1.6894[/C][/ROW]
[ROW][C]276[/C][C]7[/C][C]5.08509[/C][C]1.91491[/C][/ROW]
[ROW][C]277[/C][C]9.5[/C][C]6.55732[/C][C]2.94268[/C][/ROW]
[ROW][C]278[/C][C]6.5[/C][C]6.32873[/C][C]0.171275[/C][/ROW]
[ROW][C]279[/C][C]9.5[/C][C]4.79839[/C][C]4.70161[/C][/ROW]
[ROW][C]280[/C][C]6[/C][C]5.94621[/C][C]0.0537875[/C][/ROW]
[ROW][C]281[/C][C]8[/C][C]5.97954[/C][C]2.02046[/C][/ROW]
[ROW][C]282[/C][C]9.5[/C][C]7.40754[/C][C]2.09246[/C][/ROW]
[ROW][C]283[/C][C]8[/C][C]6.3704[/C][C]1.6296[/C][/ROW]
[ROW][C]284[/C][C]8[/C][C]6.06267[/C][C]1.93733[/C][/ROW]
[ROW][C]285[/C][C]9[/C][C]6.74921[/C][C]2.25079[/C][/ROW]
[ROW][C]286[/C][C]5[/C][C]6.17307[/C][C]-1.17307[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270029&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270029&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
17.57.57716-0.077161
22.56.04024-3.54024
365.957270.042727
46.56.41830.0816984
516.31765-5.31765
616.49618-5.49618
75.56.00461-0.504607
88.56.326712.17329
96.57.18821-0.688211
104.55.98077-1.48077
1125.85292-3.85292
1256.33847-1.33847
130.55.86096-5.36096
1454.885130.114867
1556.73478-1.73478
162.54.90939-2.40939
1754.026860.973143
185.56.75442-1.25442
193.55.73849-2.23849
2036.64449-3.64449
2144.32715-0.327147
220.54.44105-3.94105
236.55.595990.904008
244.55.04202-0.542016
257.55.866991.63301
265.56.56834-1.06834
2745.95877-1.95877
287.57.86105-0.361051
2977.20117-0.201173
3046.71461-2.71461
315.55.091920.408078
322.55.50345-3.00345
335.56.20191-0.701908
340.55.81673-5.31673
353.55.81756-2.31756
362.54.88077-2.38077
374.55.68942-1.18942
384.55.67929-1.17929
394.55.61355-1.11355
4065.233220.766777
412.56.72519-4.22519
4256.23092-1.23092
4306.22555-6.22555
4456.44386-1.44386
456.55.610070.889933
4655.71499-0.714987
4765.482850.517146
484.56.28583-1.78583
495.56.20387-0.703866
5016.49075-5.49075
517.55.349192.15081
5265.014170.985825
5355.97341-0.973412
5415.8718-4.8718
5555.33865-0.338651
566.55.707080.79292
5775.583841.41616
584.56.03427-1.53427
5905.01156-5.01156
608.55.694692.80531
613.54.58201-1.08201
627.57.338080.16192
633.57.13544-3.63544
6465.322540.677461
651.55.65758-4.15758
6696.871792.12821
673.56.14474-2.64474
683.55.76147-2.26147
6946.31387-2.31387
706.57.59788-1.09788
717.55.217272.28273
7266.81747-0.817474
7357.02842-2.02842
745.55.1310.369003
753.57.07013-3.57013
767.57.75587-0.255866
7716.04402-5.04402
786.55.464061.03594
796.56.312360.187638
806.56.150130.349868
8176.914480.0855172
823.55.79023-2.29023
831.56.29899-4.79899
8446.57284-2.57284
857.55.594981.90502
864.56.67585-2.17585
8705.66156-5.66156
883.56.55191-3.05191
895.57.54066-2.04066
9056.2406-1.2406
914.55.30386-0.803855
922.56.3818-3.8818
937.56.336691.16331
9476.588270.411733
9505.65575-5.65575
964.57.34518-2.84518
9736.57757-3.57757
981.56.29335-4.79335
993.55.24422-1.74422
1002.56.45463-3.95463
1015.54.474511.02549
10285.42322.5768
10315.61659-4.61659
10455.78326-0.783256
1054.55.92011-1.42011
10635.56446-2.56446
10735.92627-2.92627
10886.87541.1246
1092.56.16487-3.66487
11075.995951.00405
11105.52564-5.52564
11215.39805-4.39805
1133.57.11498-3.61498
1145.56.06196-0.56196
1155.55.9104-0.410403
1160.55.72719-5.22719
1177.56.397391.10261
11895.626973.37303
1199.56.340613.15939
1208.59.45688-0.956884
12175.756391.24361
12287.346120.653883
123107.208132.79187
12479.05865-2.05865
1258.55.07123.4288
12697.191961.80804
1279.55.053944.44606
12845.96567-1.96567
12965.303550.696447
13085.711972.28803
1315.55.464330.0356671
1329.56.727772.77223
1337.55.545851.95415
13476.228970.771032
1357.56.958620.541383
13684.641383.35862
13774.651652.34835
13875.511121.48888
13966.27148-0.271484
140106.052293.94771
1412.55.10487-2.60487
14296.108952.89105
14386.639161.36084
14466.27589-0.275893
1458.54.757313.74269
14664.24811.7519
14795.494173.50583
14885.211242.78876
14986.383991.61601
15097.588811.41119
1515.56.2771-0.777098
15255.13335-0.133354
15375.893951.10605
1545.55.52363-0.0236298
15596.439772.56023
15624.86399-2.86399
1578.56.785741.71426
15896.448392.55161
1598.56.361022.13898
16096.007962.99204
1617.57.387920.112084
162107.772832.22717
16395.935253.06475
1647.58.30849-0.808489
16566.65006-0.650057
16610.58.06062.4394
1678.55.983362.51664
16886.617341.38266
169105.68354.3165
17010.58.739981.76002
1716.55.726720.773283
1729.57.441412.05859
1738.55.326753.17325
1747.56.918890.581108
17556.8092-1.8092
17686.231351.76865
177107.110692.88931
17876.692180.307822
1797.56.301371.19863
1807.56.211831.28817
1819.56.687822.81218
18265.691860.308143
183106.078833.92117
18476.762930.237074
18534.0932-1.0932
18668.23805-2.23805
18776.545140.454863
188106.465453.53455
18976.678760.321236
1903.56.15809-2.65809
19187.471520.528485
192106.393883.60612
1935.56.94659-1.44659
19465.72810.271897
1956.55.636120.863883
1966.56.72041-0.220411
1978.55.875682.62432
19846.09564-2.09564
1999.56.243513.25649
20086.761621.23838
2018.57.13751.3625
2025.56.47503-0.975031
20376.093240.906757
20496.023562.97644
20586.870351.12965
206108.057351.94265
20787.089010.910988
20865.962410.0375879
20986.409521.59048
21054.440170.559835
21196.095512.90449
2124.54.378190.121806
2138.57.11351.3865
21475.802551.19745
2159.56.404123.09588
2168.56.64641.8536
2177.56.474911.02509
2187.55.866621.63338
21955.85898-0.858975
22075.609761.39024
22186.634461.36554
2225.55.371980.128015
2238.56.901521.59848
2247.55.888551.61145
2259.55.50553.9945
22676.348480.651517
22787.723050.276947
2288.55.203873.29613
2293.55.27322-1.77322
2306.55.996420.503583
2316.54.7451.755
23210.56.097274.40273
2338.56.39272.1073
23485.3482.652
235106.255373.74463
236106.972963.02704
2379.55.97433.5257
23894.40494.5951
239107.476622.52338
2407.54.907032.59297
2414.54.96604-0.46604
2424.54.360130.139872
2430.55.52892-5.02892
2446.55.053181.44682
2454.55.2958-0.795799
2465.56.23216-0.732159
24755.89336-0.893357
24866.08553-0.0855276
24945.08608-1.08608
25086.449441.55056
25110.58.292312.20769
2528.56.27332.2267
2536.56.323030.176967
25486.84531.1547
2558.57.209531.29047
2565.55.82242-0.322418
25776.923540.0764567
25855.68939-0.689391
2593.55.15178-1.65178
26056.22779-1.22779
26197.034741.96526
2628.57.268181.23182
26356.28669-1.28669
2649.57.456092.04391
26535.90026-2.90026
2661.54.1291-2.6291
26766.65018-0.650178
2680.56.83454-6.33454
2696.56.487760.012243
2707.56.489781.01022
2714.56.4489-1.9489
27286.449441.55056
27396.571222.42878
2747.57.139380.360616
2758.56.81061.6894
27675.085091.91491
2779.56.557322.94268
2786.56.328730.171275
2799.54.798394.70161
28065.946210.0537875
28185.979542.02046
2829.57.407542.09246
28386.37041.6296
28486.062671.93733
28596.749212.25079
28656.17307-1.17307






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.97120.0575990.0287995
90.9395680.1208630.0604316
100.8920230.2159540.107977
110.8423630.3152740.157637
120.7682710.4634580.231729
130.7942350.411530.205765
140.7920140.4159730.207986
150.7258480.5483040.274152
160.6589030.6821930.341097
170.7296240.5407530.270376
180.6610440.6779130.338956
190.5978760.8042480.402124
200.5693220.8613570.430678
210.4985760.9971520.501424
220.5039790.9920420.496021
230.5105510.9788970.489449
240.4484010.8968020.551599
250.4724610.9449220.527539
260.4083680.8167370.591632
270.3507460.7014920.649254
280.2942090.5884180.705791
290.2708390.5416780.729161
300.2471920.4943840.752808
310.2210320.4420630.778968
320.2033890.4067780.796611
330.1736750.3473510.826325
340.2924790.5849580.707521
350.2573040.5146080.742696
360.2232050.4464110.776795
370.1867530.3735050.813247
380.1554960.3109920.844504
390.126040.252080.87396
400.1191990.2383990.880801
410.1339810.2679620.866019
420.109220.2184390.89078
430.1879880.3759750.812012
440.1601870.3203750.839813
450.1790380.3580760.820962
460.1511340.3022690.848866
470.1456260.2912510.854374
480.1226890.2453770.877311
490.1051530.2103060.894847
500.183540.3670790.81646
510.2081160.4162320.791884
520.2170490.4340980.782951
530.1861350.372270.813865
540.2337170.4674340.766283
550.2110960.4221920.788904
560.2027080.4054160.797292
570.2160010.4320030.783999
580.1887360.3774720.811264
590.2799420.5598850.720058
600.351720.703440.64828
610.3149340.6298690.685066
620.3087630.6175260.691237
630.3173010.6346020.682699
640.302030.6040610.69797
650.351880.703760.64812
660.4027360.8054730.597264
670.385960.771920.61404
680.361970.7239410.63803
690.3461730.6923470.653827
700.3185790.6371590.681421
710.3548510.7097010.645149
720.3212320.6424640.678768
730.2980520.5961040.701948
740.2781720.5563440.721828
750.2826490.5652990.717351
760.2663870.5327740.733613
770.3556830.7113660.644317
780.3346450.669290.665355
790.3084080.6168160.691592
800.2986450.5972910.701355
810.2764820.5529640.723518
820.2660080.5320160.733992
830.3432930.6865850.656707
840.3290150.658030.670985
850.3312570.6625140.668743
860.3133640.6267290.686636
870.455170.9103390.54483
880.4653110.9306210.534689
890.444760.8895190.55524
900.4130860.8261720.586914
910.382790.7655790.61721
920.410110.8202190.58989
930.4074020.8148030.592598
940.3943720.7887440.605628
950.5449970.9100070.455003
960.5452760.9094490.454724
970.5616530.8766940.438347
980.637570.7248590.36243
990.6205270.7589450.379473
1000.6617640.6764730.338236
1010.6589690.6820610.341031
1020.7147870.5704250.285213
1030.7986270.4027470.201373
1040.7816970.4366050.218303
1050.7657410.4685180.234259
1060.7678460.4643070.232154
1070.7837640.4324720.216236
1080.7905130.4189750.209487
1090.8212340.3575330.178766
1100.814020.3719590.18598
1110.9133980.1732040.0866021
1120.9477570.1044860.0522432
1130.9590140.08197280.0409864
1140.9545880.09082360.0454118
1150.9497230.1005540.0502771
1160.9789210.04215870.0210794
1170.9792070.04158560.0207928
1180.9873610.02527850.0126392
1190.9926140.01477160.00738578
1200.9919970.01600620.00800312
1210.9920460.01590760.00795381
1220.9914150.0171690.00858452
1230.9936370.0127260.00636302
1240.994710.01058060.0052903
1250.9970270.005945610.00297281
1260.9971390.005722230.00286112
1270.998980.002039910.00101996
1280.9990360.001927130.000963566
1290.9988260.002348820.00117441
1300.9989210.002158990.00107949
1310.9986870.002626680.00131334
1320.998950.002099270.00104964
1330.9989520.002096210.0010481
1340.9987670.002466810.0012334
1350.9985480.002904470.00145223
1360.9988780.002243040.00112152
1370.998780.002440630.00122031
1380.9986080.00278440.0013922
1390.9983040.003392140.00169607
1400.9991410.001718020.00085901
1410.9993690.001261040.000630519
1420.9994240.001152310.000576155
1430.9992850.001430740.00071537
1440.9991020.001796930.000898464
1450.9994570.001085890.000542947
1460.9993050.001390230.000695115
1470.9995040.0009928230.000496412
1480.9995690.0008614770.000430738
1490.9995060.0009889120.000494456
1500.9994250.001150130.000575063
1510.9992990.001401160.000700582
1520.9990830.001834020.000917012
1530.9988420.002315650.00115783
1540.9985160.00296830.00148415
1550.9986330.002734520.00136726
1560.9991460.001707260.00085363
1570.9989660.002067790.00103389
1580.9990240.0019520.000975998
1590.998960.00208020.0010401
1600.9991490.00170140.000850702
1610.9989520.002096730.00104837
1620.9988790.002241370.00112068
1630.9990640.001872590.000936297
1640.9989620.00207510.00103755
1650.9987860.002428560.00121428
1660.9988050.002389070.00119453
1670.9988070.002386640.00119332
1680.9984960.003007660.00150383
1690.9992610.001477670.000738835
1700.9991290.001741730.000870865
1710.9988750.00225060.0011253
1720.9987670.002466280.00123314
1730.9990550.001889450.000944727
1740.9987820.002436350.00121817
1750.9989290.002142420.00107121
1760.998710.002580040.00129002
1770.9988270.002346310.00117315
1780.9984590.003082690.00154134
1790.9980390.003922460.00196123
1800.9975390.004921910.00246096
1810.9976620.004675240.00233762
1820.9969170.006165830.00308291
1830.9979750.00404960.0020248
1840.9974010.005197520.00259876
1850.996950.006100290.00305015
1860.9978940.004211860.00210593
1870.9972540.005491330.00274567
1880.9976880.004623830.00231192
1890.9971450.005710260.00285513
1900.997920.004160260.00208013
1910.9973240.005351120.00267556
1920.9981590.003681460.00184073
1930.9981840.003631570.00181579
1940.9975670.004866230.00243312
1950.9968220.006355960.00317798
1960.9959470.008106960.00405348
1970.9957640.008471720.00423586
1980.9962420.007515640.00375782
1990.9967360.006527810.0032639
2000.9958390.00832270.00416135
2010.9947040.01059180.0052959
2020.9943780.0112440.00562198
2030.9929180.01416350.00708175
2040.9935550.01288920.00644458
2050.991780.01643930.00821967
2060.9906960.01860720.00930362
2070.9881260.0237490.0118745
2080.985230.02953910.0147696
2090.9820690.03586180.0179309
2100.9772910.04541790.0227089
2110.9783090.04338160.0216908
2120.9727820.05443640.0272182
2130.9680130.06397470.0319873
2140.9610540.07789270.0389463
2150.9589510.08209780.0410489
2160.9515570.09688510.0484426
2170.9410240.1179510.0589755
2180.9315260.1369480.0684739
2190.930480.139040.0695201
2200.9177330.1645340.082267
2210.9026890.1946210.0973106
2220.8835250.2329490.116475
2230.8659950.268010.134005
2240.8531870.2936270.146813
2250.8817970.2364060.118203
2260.8594620.2810770.140538
2270.8364380.3271250.163562
2280.8435230.3129540.156477
2290.8509940.2980130.149006
2300.8268740.3462520.173126
2310.8103880.3792240.189612
2320.8495020.3009950.150498
2330.8393580.3212850.160642
2340.8485350.3029310.151465
2350.8756870.2486270.124313
2360.8632530.2734940.136747
2370.8830080.2339840.116992
2380.9481730.1036550.0518274
2390.9392930.1214140.0607071
2400.9461980.1076050.0538024
2410.9309210.1381580.0690792
2420.9167790.1664410.0832205
2430.9633710.07325770.0366288
2440.959190.081620.04081
2450.9478790.1042420.0521212
2460.9320620.1358760.0679379
2470.9167220.1665570.0832783
2480.8951460.2097080.104854
2490.8799730.2400540.120027
2500.8588650.2822710.141135
2510.8301610.3396780.169839
2520.829390.341220.17061
2530.7911740.4176520.208826
2540.7478220.5043560.252178
2550.6999750.600050.300025
2560.6453480.7093040.354652
2570.5985170.8029650.401483
2580.5415540.9168910.458446
2590.5050770.9898460.494923
2600.4935940.9871880.506406
2610.4391230.8782450.560877
2620.3758730.7517460.624127
2630.351180.7023610.64882
2640.2953210.5906410.704679
2650.3608950.721790.639105
2660.750360.499280.24964
2670.733470.533060.26653
2680.9916180.01676390.00838197
2690.9840380.03192310.0159615
2700.9716960.05660870.0283043
2710.9838970.03220580.0161029
2720.9703170.05936640.0296832
2730.9552050.0895890.0447945
2740.9180720.1638550.0819275
2750.9378620.1242750.0621375
2760.936020.1279610.0639805
2770.9170930.1658140.082907
2780.8166990.3666020.183301

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.9712 & 0.057599 & 0.0287995 \tabularnewline
9 & 0.939568 & 0.120863 & 0.0604316 \tabularnewline
10 & 0.892023 & 0.215954 & 0.107977 \tabularnewline
11 & 0.842363 & 0.315274 & 0.157637 \tabularnewline
12 & 0.768271 & 0.463458 & 0.231729 \tabularnewline
13 & 0.794235 & 0.41153 & 0.205765 \tabularnewline
14 & 0.792014 & 0.415973 & 0.207986 \tabularnewline
15 & 0.725848 & 0.548304 & 0.274152 \tabularnewline
16 & 0.658903 & 0.682193 & 0.341097 \tabularnewline
17 & 0.729624 & 0.540753 & 0.270376 \tabularnewline
18 & 0.661044 & 0.677913 & 0.338956 \tabularnewline
19 & 0.597876 & 0.804248 & 0.402124 \tabularnewline
20 & 0.569322 & 0.861357 & 0.430678 \tabularnewline
21 & 0.498576 & 0.997152 & 0.501424 \tabularnewline
22 & 0.503979 & 0.992042 & 0.496021 \tabularnewline
23 & 0.510551 & 0.978897 & 0.489449 \tabularnewline
24 & 0.448401 & 0.896802 & 0.551599 \tabularnewline
25 & 0.472461 & 0.944922 & 0.527539 \tabularnewline
26 & 0.408368 & 0.816737 & 0.591632 \tabularnewline
27 & 0.350746 & 0.701492 & 0.649254 \tabularnewline
28 & 0.294209 & 0.588418 & 0.705791 \tabularnewline
29 & 0.270839 & 0.541678 & 0.729161 \tabularnewline
30 & 0.247192 & 0.494384 & 0.752808 \tabularnewline
31 & 0.221032 & 0.442063 & 0.778968 \tabularnewline
32 & 0.203389 & 0.406778 & 0.796611 \tabularnewline
33 & 0.173675 & 0.347351 & 0.826325 \tabularnewline
34 & 0.292479 & 0.584958 & 0.707521 \tabularnewline
35 & 0.257304 & 0.514608 & 0.742696 \tabularnewline
36 & 0.223205 & 0.446411 & 0.776795 \tabularnewline
37 & 0.186753 & 0.373505 & 0.813247 \tabularnewline
38 & 0.155496 & 0.310992 & 0.844504 \tabularnewline
39 & 0.12604 & 0.25208 & 0.87396 \tabularnewline
40 & 0.119199 & 0.238399 & 0.880801 \tabularnewline
41 & 0.133981 & 0.267962 & 0.866019 \tabularnewline
42 & 0.10922 & 0.218439 & 0.89078 \tabularnewline
43 & 0.187988 & 0.375975 & 0.812012 \tabularnewline
44 & 0.160187 & 0.320375 & 0.839813 \tabularnewline
45 & 0.179038 & 0.358076 & 0.820962 \tabularnewline
46 & 0.151134 & 0.302269 & 0.848866 \tabularnewline
47 & 0.145626 & 0.291251 & 0.854374 \tabularnewline
48 & 0.122689 & 0.245377 & 0.877311 \tabularnewline
49 & 0.105153 & 0.210306 & 0.894847 \tabularnewline
50 & 0.18354 & 0.367079 & 0.81646 \tabularnewline
51 & 0.208116 & 0.416232 & 0.791884 \tabularnewline
52 & 0.217049 & 0.434098 & 0.782951 \tabularnewline
53 & 0.186135 & 0.37227 & 0.813865 \tabularnewline
54 & 0.233717 & 0.467434 & 0.766283 \tabularnewline
55 & 0.211096 & 0.422192 & 0.788904 \tabularnewline
56 & 0.202708 & 0.405416 & 0.797292 \tabularnewline
57 & 0.216001 & 0.432003 & 0.783999 \tabularnewline
58 & 0.188736 & 0.377472 & 0.811264 \tabularnewline
59 & 0.279942 & 0.559885 & 0.720058 \tabularnewline
60 & 0.35172 & 0.70344 & 0.64828 \tabularnewline
61 & 0.314934 & 0.629869 & 0.685066 \tabularnewline
62 & 0.308763 & 0.617526 & 0.691237 \tabularnewline
63 & 0.317301 & 0.634602 & 0.682699 \tabularnewline
64 & 0.30203 & 0.604061 & 0.69797 \tabularnewline
65 & 0.35188 & 0.70376 & 0.64812 \tabularnewline
66 & 0.402736 & 0.805473 & 0.597264 \tabularnewline
67 & 0.38596 & 0.77192 & 0.61404 \tabularnewline
68 & 0.36197 & 0.723941 & 0.63803 \tabularnewline
69 & 0.346173 & 0.692347 & 0.653827 \tabularnewline
70 & 0.318579 & 0.637159 & 0.681421 \tabularnewline
71 & 0.354851 & 0.709701 & 0.645149 \tabularnewline
72 & 0.321232 & 0.642464 & 0.678768 \tabularnewline
73 & 0.298052 & 0.596104 & 0.701948 \tabularnewline
74 & 0.278172 & 0.556344 & 0.721828 \tabularnewline
75 & 0.282649 & 0.565299 & 0.717351 \tabularnewline
76 & 0.266387 & 0.532774 & 0.733613 \tabularnewline
77 & 0.355683 & 0.711366 & 0.644317 \tabularnewline
78 & 0.334645 & 0.66929 & 0.665355 \tabularnewline
79 & 0.308408 & 0.616816 & 0.691592 \tabularnewline
80 & 0.298645 & 0.597291 & 0.701355 \tabularnewline
81 & 0.276482 & 0.552964 & 0.723518 \tabularnewline
82 & 0.266008 & 0.532016 & 0.733992 \tabularnewline
83 & 0.343293 & 0.686585 & 0.656707 \tabularnewline
84 & 0.329015 & 0.65803 & 0.670985 \tabularnewline
85 & 0.331257 & 0.662514 & 0.668743 \tabularnewline
86 & 0.313364 & 0.626729 & 0.686636 \tabularnewline
87 & 0.45517 & 0.910339 & 0.54483 \tabularnewline
88 & 0.465311 & 0.930621 & 0.534689 \tabularnewline
89 & 0.44476 & 0.889519 & 0.55524 \tabularnewline
90 & 0.413086 & 0.826172 & 0.586914 \tabularnewline
91 & 0.38279 & 0.765579 & 0.61721 \tabularnewline
92 & 0.41011 & 0.820219 & 0.58989 \tabularnewline
93 & 0.407402 & 0.814803 & 0.592598 \tabularnewline
94 & 0.394372 & 0.788744 & 0.605628 \tabularnewline
95 & 0.544997 & 0.910007 & 0.455003 \tabularnewline
96 & 0.545276 & 0.909449 & 0.454724 \tabularnewline
97 & 0.561653 & 0.876694 & 0.438347 \tabularnewline
98 & 0.63757 & 0.724859 & 0.36243 \tabularnewline
99 & 0.620527 & 0.758945 & 0.379473 \tabularnewline
100 & 0.661764 & 0.676473 & 0.338236 \tabularnewline
101 & 0.658969 & 0.682061 & 0.341031 \tabularnewline
102 & 0.714787 & 0.570425 & 0.285213 \tabularnewline
103 & 0.798627 & 0.402747 & 0.201373 \tabularnewline
104 & 0.781697 & 0.436605 & 0.218303 \tabularnewline
105 & 0.765741 & 0.468518 & 0.234259 \tabularnewline
106 & 0.767846 & 0.464307 & 0.232154 \tabularnewline
107 & 0.783764 & 0.432472 & 0.216236 \tabularnewline
108 & 0.790513 & 0.418975 & 0.209487 \tabularnewline
109 & 0.821234 & 0.357533 & 0.178766 \tabularnewline
110 & 0.81402 & 0.371959 & 0.18598 \tabularnewline
111 & 0.913398 & 0.173204 & 0.0866021 \tabularnewline
112 & 0.947757 & 0.104486 & 0.0522432 \tabularnewline
113 & 0.959014 & 0.0819728 & 0.0409864 \tabularnewline
114 & 0.954588 & 0.0908236 & 0.0454118 \tabularnewline
115 & 0.949723 & 0.100554 & 0.0502771 \tabularnewline
116 & 0.978921 & 0.0421587 & 0.0210794 \tabularnewline
117 & 0.979207 & 0.0415856 & 0.0207928 \tabularnewline
118 & 0.987361 & 0.0252785 & 0.0126392 \tabularnewline
119 & 0.992614 & 0.0147716 & 0.00738578 \tabularnewline
120 & 0.991997 & 0.0160062 & 0.00800312 \tabularnewline
121 & 0.992046 & 0.0159076 & 0.00795381 \tabularnewline
122 & 0.991415 & 0.017169 & 0.00858452 \tabularnewline
123 & 0.993637 & 0.012726 & 0.00636302 \tabularnewline
124 & 0.99471 & 0.0105806 & 0.0052903 \tabularnewline
125 & 0.997027 & 0.00594561 & 0.00297281 \tabularnewline
126 & 0.997139 & 0.00572223 & 0.00286112 \tabularnewline
127 & 0.99898 & 0.00203991 & 0.00101996 \tabularnewline
128 & 0.999036 & 0.00192713 & 0.000963566 \tabularnewline
129 & 0.998826 & 0.00234882 & 0.00117441 \tabularnewline
130 & 0.998921 & 0.00215899 & 0.00107949 \tabularnewline
131 & 0.998687 & 0.00262668 & 0.00131334 \tabularnewline
132 & 0.99895 & 0.00209927 & 0.00104964 \tabularnewline
133 & 0.998952 & 0.00209621 & 0.0010481 \tabularnewline
134 & 0.998767 & 0.00246681 & 0.0012334 \tabularnewline
135 & 0.998548 & 0.00290447 & 0.00145223 \tabularnewline
136 & 0.998878 & 0.00224304 & 0.00112152 \tabularnewline
137 & 0.99878 & 0.00244063 & 0.00122031 \tabularnewline
138 & 0.998608 & 0.0027844 & 0.0013922 \tabularnewline
139 & 0.998304 & 0.00339214 & 0.00169607 \tabularnewline
140 & 0.999141 & 0.00171802 & 0.00085901 \tabularnewline
141 & 0.999369 & 0.00126104 & 0.000630519 \tabularnewline
142 & 0.999424 & 0.00115231 & 0.000576155 \tabularnewline
143 & 0.999285 & 0.00143074 & 0.00071537 \tabularnewline
144 & 0.999102 & 0.00179693 & 0.000898464 \tabularnewline
145 & 0.999457 & 0.00108589 & 0.000542947 \tabularnewline
146 & 0.999305 & 0.00139023 & 0.000695115 \tabularnewline
147 & 0.999504 & 0.000992823 & 0.000496412 \tabularnewline
148 & 0.999569 & 0.000861477 & 0.000430738 \tabularnewline
149 & 0.999506 & 0.000988912 & 0.000494456 \tabularnewline
150 & 0.999425 & 0.00115013 & 0.000575063 \tabularnewline
151 & 0.999299 & 0.00140116 & 0.000700582 \tabularnewline
152 & 0.999083 & 0.00183402 & 0.000917012 \tabularnewline
153 & 0.998842 & 0.00231565 & 0.00115783 \tabularnewline
154 & 0.998516 & 0.0029683 & 0.00148415 \tabularnewline
155 & 0.998633 & 0.00273452 & 0.00136726 \tabularnewline
156 & 0.999146 & 0.00170726 & 0.00085363 \tabularnewline
157 & 0.998966 & 0.00206779 & 0.00103389 \tabularnewline
158 & 0.999024 & 0.001952 & 0.000975998 \tabularnewline
159 & 0.99896 & 0.0020802 & 0.0010401 \tabularnewline
160 & 0.999149 & 0.0017014 & 0.000850702 \tabularnewline
161 & 0.998952 & 0.00209673 & 0.00104837 \tabularnewline
162 & 0.998879 & 0.00224137 & 0.00112068 \tabularnewline
163 & 0.999064 & 0.00187259 & 0.000936297 \tabularnewline
164 & 0.998962 & 0.0020751 & 0.00103755 \tabularnewline
165 & 0.998786 & 0.00242856 & 0.00121428 \tabularnewline
166 & 0.998805 & 0.00238907 & 0.00119453 \tabularnewline
167 & 0.998807 & 0.00238664 & 0.00119332 \tabularnewline
168 & 0.998496 & 0.00300766 & 0.00150383 \tabularnewline
169 & 0.999261 & 0.00147767 & 0.000738835 \tabularnewline
170 & 0.999129 & 0.00174173 & 0.000870865 \tabularnewline
171 & 0.998875 & 0.0022506 & 0.0011253 \tabularnewline
172 & 0.998767 & 0.00246628 & 0.00123314 \tabularnewline
173 & 0.999055 & 0.00188945 & 0.000944727 \tabularnewline
174 & 0.998782 & 0.00243635 & 0.00121817 \tabularnewline
175 & 0.998929 & 0.00214242 & 0.00107121 \tabularnewline
176 & 0.99871 & 0.00258004 & 0.00129002 \tabularnewline
177 & 0.998827 & 0.00234631 & 0.00117315 \tabularnewline
178 & 0.998459 & 0.00308269 & 0.00154134 \tabularnewline
179 & 0.998039 & 0.00392246 & 0.00196123 \tabularnewline
180 & 0.997539 & 0.00492191 & 0.00246096 \tabularnewline
181 & 0.997662 & 0.00467524 & 0.00233762 \tabularnewline
182 & 0.996917 & 0.00616583 & 0.00308291 \tabularnewline
183 & 0.997975 & 0.0040496 & 0.0020248 \tabularnewline
184 & 0.997401 & 0.00519752 & 0.00259876 \tabularnewline
185 & 0.99695 & 0.00610029 & 0.00305015 \tabularnewline
186 & 0.997894 & 0.00421186 & 0.00210593 \tabularnewline
187 & 0.997254 & 0.00549133 & 0.00274567 \tabularnewline
188 & 0.997688 & 0.00462383 & 0.00231192 \tabularnewline
189 & 0.997145 & 0.00571026 & 0.00285513 \tabularnewline
190 & 0.99792 & 0.00416026 & 0.00208013 \tabularnewline
191 & 0.997324 & 0.00535112 & 0.00267556 \tabularnewline
192 & 0.998159 & 0.00368146 & 0.00184073 \tabularnewline
193 & 0.998184 & 0.00363157 & 0.00181579 \tabularnewline
194 & 0.997567 & 0.00486623 & 0.00243312 \tabularnewline
195 & 0.996822 & 0.00635596 & 0.00317798 \tabularnewline
196 & 0.995947 & 0.00810696 & 0.00405348 \tabularnewline
197 & 0.995764 & 0.00847172 & 0.00423586 \tabularnewline
198 & 0.996242 & 0.00751564 & 0.00375782 \tabularnewline
199 & 0.996736 & 0.00652781 & 0.0032639 \tabularnewline
200 & 0.995839 & 0.0083227 & 0.00416135 \tabularnewline
201 & 0.994704 & 0.0105918 & 0.0052959 \tabularnewline
202 & 0.994378 & 0.011244 & 0.00562198 \tabularnewline
203 & 0.992918 & 0.0141635 & 0.00708175 \tabularnewline
204 & 0.993555 & 0.0128892 & 0.00644458 \tabularnewline
205 & 0.99178 & 0.0164393 & 0.00821967 \tabularnewline
206 & 0.990696 & 0.0186072 & 0.00930362 \tabularnewline
207 & 0.988126 & 0.023749 & 0.0118745 \tabularnewline
208 & 0.98523 & 0.0295391 & 0.0147696 \tabularnewline
209 & 0.982069 & 0.0358618 & 0.0179309 \tabularnewline
210 & 0.977291 & 0.0454179 & 0.0227089 \tabularnewline
211 & 0.978309 & 0.0433816 & 0.0216908 \tabularnewline
212 & 0.972782 & 0.0544364 & 0.0272182 \tabularnewline
213 & 0.968013 & 0.0639747 & 0.0319873 \tabularnewline
214 & 0.961054 & 0.0778927 & 0.0389463 \tabularnewline
215 & 0.958951 & 0.0820978 & 0.0410489 \tabularnewline
216 & 0.951557 & 0.0968851 & 0.0484426 \tabularnewline
217 & 0.941024 & 0.117951 & 0.0589755 \tabularnewline
218 & 0.931526 & 0.136948 & 0.0684739 \tabularnewline
219 & 0.93048 & 0.13904 & 0.0695201 \tabularnewline
220 & 0.917733 & 0.164534 & 0.082267 \tabularnewline
221 & 0.902689 & 0.194621 & 0.0973106 \tabularnewline
222 & 0.883525 & 0.232949 & 0.116475 \tabularnewline
223 & 0.865995 & 0.26801 & 0.134005 \tabularnewline
224 & 0.853187 & 0.293627 & 0.146813 \tabularnewline
225 & 0.881797 & 0.236406 & 0.118203 \tabularnewline
226 & 0.859462 & 0.281077 & 0.140538 \tabularnewline
227 & 0.836438 & 0.327125 & 0.163562 \tabularnewline
228 & 0.843523 & 0.312954 & 0.156477 \tabularnewline
229 & 0.850994 & 0.298013 & 0.149006 \tabularnewline
230 & 0.826874 & 0.346252 & 0.173126 \tabularnewline
231 & 0.810388 & 0.379224 & 0.189612 \tabularnewline
232 & 0.849502 & 0.300995 & 0.150498 \tabularnewline
233 & 0.839358 & 0.321285 & 0.160642 \tabularnewline
234 & 0.848535 & 0.302931 & 0.151465 \tabularnewline
235 & 0.875687 & 0.248627 & 0.124313 \tabularnewline
236 & 0.863253 & 0.273494 & 0.136747 \tabularnewline
237 & 0.883008 & 0.233984 & 0.116992 \tabularnewline
238 & 0.948173 & 0.103655 & 0.0518274 \tabularnewline
239 & 0.939293 & 0.121414 & 0.0607071 \tabularnewline
240 & 0.946198 & 0.107605 & 0.0538024 \tabularnewline
241 & 0.930921 & 0.138158 & 0.0690792 \tabularnewline
242 & 0.916779 & 0.166441 & 0.0832205 \tabularnewline
243 & 0.963371 & 0.0732577 & 0.0366288 \tabularnewline
244 & 0.95919 & 0.08162 & 0.04081 \tabularnewline
245 & 0.947879 & 0.104242 & 0.0521212 \tabularnewline
246 & 0.932062 & 0.135876 & 0.0679379 \tabularnewline
247 & 0.916722 & 0.166557 & 0.0832783 \tabularnewline
248 & 0.895146 & 0.209708 & 0.104854 \tabularnewline
249 & 0.879973 & 0.240054 & 0.120027 \tabularnewline
250 & 0.858865 & 0.282271 & 0.141135 \tabularnewline
251 & 0.830161 & 0.339678 & 0.169839 \tabularnewline
252 & 0.82939 & 0.34122 & 0.17061 \tabularnewline
253 & 0.791174 & 0.417652 & 0.208826 \tabularnewline
254 & 0.747822 & 0.504356 & 0.252178 \tabularnewline
255 & 0.699975 & 0.60005 & 0.300025 \tabularnewline
256 & 0.645348 & 0.709304 & 0.354652 \tabularnewline
257 & 0.598517 & 0.802965 & 0.401483 \tabularnewline
258 & 0.541554 & 0.916891 & 0.458446 \tabularnewline
259 & 0.505077 & 0.989846 & 0.494923 \tabularnewline
260 & 0.493594 & 0.987188 & 0.506406 \tabularnewline
261 & 0.439123 & 0.878245 & 0.560877 \tabularnewline
262 & 0.375873 & 0.751746 & 0.624127 \tabularnewline
263 & 0.35118 & 0.702361 & 0.64882 \tabularnewline
264 & 0.295321 & 0.590641 & 0.704679 \tabularnewline
265 & 0.360895 & 0.72179 & 0.639105 \tabularnewline
266 & 0.75036 & 0.49928 & 0.24964 \tabularnewline
267 & 0.73347 & 0.53306 & 0.26653 \tabularnewline
268 & 0.991618 & 0.0167639 & 0.00838197 \tabularnewline
269 & 0.984038 & 0.0319231 & 0.0159615 \tabularnewline
270 & 0.971696 & 0.0566087 & 0.0283043 \tabularnewline
271 & 0.983897 & 0.0322058 & 0.0161029 \tabularnewline
272 & 0.970317 & 0.0593664 & 0.0296832 \tabularnewline
273 & 0.955205 & 0.089589 & 0.0447945 \tabularnewline
274 & 0.918072 & 0.163855 & 0.0819275 \tabularnewline
275 & 0.937862 & 0.124275 & 0.0621375 \tabularnewline
276 & 0.93602 & 0.127961 & 0.0639805 \tabularnewline
277 & 0.917093 & 0.165814 & 0.082907 \tabularnewline
278 & 0.816699 & 0.366602 & 0.183301 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270029&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]8[/C][C]0.9712[/C][C]0.057599[/C][C]0.0287995[/C][/ROW]
[ROW][C]9[/C][C]0.939568[/C][C]0.120863[/C][C]0.0604316[/C][/ROW]
[ROW][C]10[/C][C]0.892023[/C][C]0.215954[/C][C]0.107977[/C][/ROW]
[ROW][C]11[/C][C]0.842363[/C][C]0.315274[/C][C]0.157637[/C][/ROW]
[ROW][C]12[/C][C]0.768271[/C][C]0.463458[/C][C]0.231729[/C][/ROW]
[ROW][C]13[/C][C]0.794235[/C][C]0.41153[/C][C]0.205765[/C][/ROW]
[ROW][C]14[/C][C]0.792014[/C][C]0.415973[/C][C]0.207986[/C][/ROW]
[ROW][C]15[/C][C]0.725848[/C][C]0.548304[/C][C]0.274152[/C][/ROW]
[ROW][C]16[/C][C]0.658903[/C][C]0.682193[/C][C]0.341097[/C][/ROW]
[ROW][C]17[/C][C]0.729624[/C][C]0.540753[/C][C]0.270376[/C][/ROW]
[ROW][C]18[/C][C]0.661044[/C][C]0.677913[/C][C]0.338956[/C][/ROW]
[ROW][C]19[/C][C]0.597876[/C][C]0.804248[/C][C]0.402124[/C][/ROW]
[ROW][C]20[/C][C]0.569322[/C][C]0.861357[/C][C]0.430678[/C][/ROW]
[ROW][C]21[/C][C]0.498576[/C][C]0.997152[/C][C]0.501424[/C][/ROW]
[ROW][C]22[/C][C]0.503979[/C][C]0.992042[/C][C]0.496021[/C][/ROW]
[ROW][C]23[/C][C]0.510551[/C][C]0.978897[/C][C]0.489449[/C][/ROW]
[ROW][C]24[/C][C]0.448401[/C][C]0.896802[/C][C]0.551599[/C][/ROW]
[ROW][C]25[/C][C]0.472461[/C][C]0.944922[/C][C]0.527539[/C][/ROW]
[ROW][C]26[/C][C]0.408368[/C][C]0.816737[/C][C]0.591632[/C][/ROW]
[ROW][C]27[/C][C]0.350746[/C][C]0.701492[/C][C]0.649254[/C][/ROW]
[ROW][C]28[/C][C]0.294209[/C][C]0.588418[/C][C]0.705791[/C][/ROW]
[ROW][C]29[/C][C]0.270839[/C][C]0.541678[/C][C]0.729161[/C][/ROW]
[ROW][C]30[/C][C]0.247192[/C][C]0.494384[/C][C]0.752808[/C][/ROW]
[ROW][C]31[/C][C]0.221032[/C][C]0.442063[/C][C]0.778968[/C][/ROW]
[ROW][C]32[/C][C]0.203389[/C][C]0.406778[/C][C]0.796611[/C][/ROW]
[ROW][C]33[/C][C]0.173675[/C][C]0.347351[/C][C]0.826325[/C][/ROW]
[ROW][C]34[/C][C]0.292479[/C][C]0.584958[/C][C]0.707521[/C][/ROW]
[ROW][C]35[/C][C]0.257304[/C][C]0.514608[/C][C]0.742696[/C][/ROW]
[ROW][C]36[/C][C]0.223205[/C][C]0.446411[/C][C]0.776795[/C][/ROW]
[ROW][C]37[/C][C]0.186753[/C][C]0.373505[/C][C]0.813247[/C][/ROW]
[ROW][C]38[/C][C]0.155496[/C][C]0.310992[/C][C]0.844504[/C][/ROW]
[ROW][C]39[/C][C]0.12604[/C][C]0.25208[/C][C]0.87396[/C][/ROW]
[ROW][C]40[/C][C]0.119199[/C][C]0.238399[/C][C]0.880801[/C][/ROW]
[ROW][C]41[/C][C]0.133981[/C][C]0.267962[/C][C]0.866019[/C][/ROW]
[ROW][C]42[/C][C]0.10922[/C][C]0.218439[/C][C]0.89078[/C][/ROW]
[ROW][C]43[/C][C]0.187988[/C][C]0.375975[/C][C]0.812012[/C][/ROW]
[ROW][C]44[/C][C]0.160187[/C][C]0.320375[/C][C]0.839813[/C][/ROW]
[ROW][C]45[/C][C]0.179038[/C][C]0.358076[/C][C]0.820962[/C][/ROW]
[ROW][C]46[/C][C]0.151134[/C][C]0.302269[/C][C]0.848866[/C][/ROW]
[ROW][C]47[/C][C]0.145626[/C][C]0.291251[/C][C]0.854374[/C][/ROW]
[ROW][C]48[/C][C]0.122689[/C][C]0.245377[/C][C]0.877311[/C][/ROW]
[ROW][C]49[/C][C]0.105153[/C][C]0.210306[/C][C]0.894847[/C][/ROW]
[ROW][C]50[/C][C]0.18354[/C][C]0.367079[/C][C]0.81646[/C][/ROW]
[ROW][C]51[/C][C]0.208116[/C][C]0.416232[/C][C]0.791884[/C][/ROW]
[ROW][C]52[/C][C]0.217049[/C][C]0.434098[/C][C]0.782951[/C][/ROW]
[ROW][C]53[/C][C]0.186135[/C][C]0.37227[/C][C]0.813865[/C][/ROW]
[ROW][C]54[/C][C]0.233717[/C][C]0.467434[/C][C]0.766283[/C][/ROW]
[ROW][C]55[/C][C]0.211096[/C][C]0.422192[/C][C]0.788904[/C][/ROW]
[ROW][C]56[/C][C]0.202708[/C][C]0.405416[/C][C]0.797292[/C][/ROW]
[ROW][C]57[/C][C]0.216001[/C][C]0.432003[/C][C]0.783999[/C][/ROW]
[ROW][C]58[/C][C]0.188736[/C][C]0.377472[/C][C]0.811264[/C][/ROW]
[ROW][C]59[/C][C]0.279942[/C][C]0.559885[/C][C]0.720058[/C][/ROW]
[ROW][C]60[/C][C]0.35172[/C][C]0.70344[/C][C]0.64828[/C][/ROW]
[ROW][C]61[/C][C]0.314934[/C][C]0.629869[/C][C]0.685066[/C][/ROW]
[ROW][C]62[/C][C]0.308763[/C][C]0.617526[/C][C]0.691237[/C][/ROW]
[ROW][C]63[/C][C]0.317301[/C][C]0.634602[/C][C]0.682699[/C][/ROW]
[ROW][C]64[/C][C]0.30203[/C][C]0.604061[/C][C]0.69797[/C][/ROW]
[ROW][C]65[/C][C]0.35188[/C][C]0.70376[/C][C]0.64812[/C][/ROW]
[ROW][C]66[/C][C]0.402736[/C][C]0.805473[/C][C]0.597264[/C][/ROW]
[ROW][C]67[/C][C]0.38596[/C][C]0.77192[/C][C]0.61404[/C][/ROW]
[ROW][C]68[/C][C]0.36197[/C][C]0.723941[/C][C]0.63803[/C][/ROW]
[ROW][C]69[/C][C]0.346173[/C][C]0.692347[/C][C]0.653827[/C][/ROW]
[ROW][C]70[/C][C]0.318579[/C][C]0.637159[/C][C]0.681421[/C][/ROW]
[ROW][C]71[/C][C]0.354851[/C][C]0.709701[/C][C]0.645149[/C][/ROW]
[ROW][C]72[/C][C]0.321232[/C][C]0.642464[/C][C]0.678768[/C][/ROW]
[ROW][C]73[/C][C]0.298052[/C][C]0.596104[/C][C]0.701948[/C][/ROW]
[ROW][C]74[/C][C]0.278172[/C][C]0.556344[/C][C]0.721828[/C][/ROW]
[ROW][C]75[/C][C]0.282649[/C][C]0.565299[/C][C]0.717351[/C][/ROW]
[ROW][C]76[/C][C]0.266387[/C][C]0.532774[/C][C]0.733613[/C][/ROW]
[ROW][C]77[/C][C]0.355683[/C][C]0.711366[/C][C]0.644317[/C][/ROW]
[ROW][C]78[/C][C]0.334645[/C][C]0.66929[/C][C]0.665355[/C][/ROW]
[ROW][C]79[/C][C]0.308408[/C][C]0.616816[/C][C]0.691592[/C][/ROW]
[ROW][C]80[/C][C]0.298645[/C][C]0.597291[/C][C]0.701355[/C][/ROW]
[ROW][C]81[/C][C]0.276482[/C][C]0.552964[/C][C]0.723518[/C][/ROW]
[ROW][C]82[/C][C]0.266008[/C][C]0.532016[/C][C]0.733992[/C][/ROW]
[ROW][C]83[/C][C]0.343293[/C][C]0.686585[/C][C]0.656707[/C][/ROW]
[ROW][C]84[/C][C]0.329015[/C][C]0.65803[/C][C]0.670985[/C][/ROW]
[ROW][C]85[/C][C]0.331257[/C][C]0.662514[/C][C]0.668743[/C][/ROW]
[ROW][C]86[/C][C]0.313364[/C][C]0.626729[/C][C]0.686636[/C][/ROW]
[ROW][C]87[/C][C]0.45517[/C][C]0.910339[/C][C]0.54483[/C][/ROW]
[ROW][C]88[/C][C]0.465311[/C][C]0.930621[/C][C]0.534689[/C][/ROW]
[ROW][C]89[/C][C]0.44476[/C][C]0.889519[/C][C]0.55524[/C][/ROW]
[ROW][C]90[/C][C]0.413086[/C][C]0.826172[/C][C]0.586914[/C][/ROW]
[ROW][C]91[/C][C]0.38279[/C][C]0.765579[/C][C]0.61721[/C][/ROW]
[ROW][C]92[/C][C]0.41011[/C][C]0.820219[/C][C]0.58989[/C][/ROW]
[ROW][C]93[/C][C]0.407402[/C][C]0.814803[/C][C]0.592598[/C][/ROW]
[ROW][C]94[/C][C]0.394372[/C][C]0.788744[/C][C]0.605628[/C][/ROW]
[ROW][C]95[/C][C]0.544997[/C][C]0.910007[/C][C]0.455003[/C][/ROW]
[ROW][C]96[/C][C]0.545276[/C][C]0.909449[/C][C]0.454724[/C][/ROW]
[ROW][C]97[/C][C]0.561653[/C][C]0.876694[/C][C]0.438347[/C][/ROW]
[ROW][C]98[/C][C]0.63757[/C][C]0.724859[/C][C]0.36243[/C][/ROW]
[ROW][C]99[/C][C]0.620527[/C][C]0.758945[/C][C]0.379473[/C][/ROW]
[ROW][C]100[/C][C]0.661764[/C][C]0.676473[/C][C]0.338236[/C][/ROW]
[ROW][C]101[/C][C]0.658969[/C][C]0.682061[/C][C]0.341031[/C][/ROW]
[ROW][C]102[/C][C]0.714787[/C][C]0.570425[/C][C]0.285213[/C][/ROW]
[ROW][C]103[/C][C]0.798627[/C][C]0.402747[/C][C]0.201373[/C][/ROW]
[ROW][C]104[/C][C]0.781697[/C][C]0.436605[/C][C]0.218303[/C][/ROW]
[ROW][C]105[/C][C]0.765741[/C][C]0.468518[/C][C]0.234259[/C][/ROW]
[ROW][C]106[/C][C]0.767846[/C][C]0.464307[/C][C]0.232154[/C][/ROW]
[ROW][C]107[/C][C]0.783764[/C][C]0.432472[/C][C]0.216236[/C][/ROW]
[ROW][C]108[/C][C]0.790513[/C][C]0.418975[/C][C]0.209487[/C][/ROW]
[ROW][C]109[/C][C]0.821234[/C][C]0.357533[/C][C]0.178766[/C][/ROW]
[ROW][C]110[/C][C]0.81402[/C][C]0.371959[/C][C]0.18598[/C][/ROW]
[ROW][C]111[/C][C]0.913398[/C][C]0.173204[/C][C]0.0866021[/C][/ROW]
[ROW][C]112[/C][C]0.947757[/C][C]0.104486[/C][C]0.0522432[/C][/ROW]
[ROW][C]113[/C][C]0.959014[/C][C]0.0819728[/C][C]0.0409864[/C][/ROW]
[ROW][C]114[/C][C]0.954588[/C][C]0.0908236[/C][C]0.0454118[/C][/ROW]
[ROW][C]115[/C][C]0.949723[/C][C]0.100554[/C][C]0.0502771[/C][/ROW]
[ROW][C]116[/C][C]0.978921[/C][C]0.0421587[/C][C]0.0210794[/C][/ROW]
[ROW][C]117[/C][C]0.979207[/C][C]0.0415856[/C][C]0.0207928[/C][/ROW]
[ROW][C]118[/C][C]0.987361[/C][C]0.0252785[/C][C]0.0126392[/C][/ROW]
[ROW][C]119[/C][C]0.992614[/C][C]0.0147716[/C][C]0.00738578[/C][/ROW]
[ROW][C]120[/C][C]0.991997[/C][C]0.0160062[/C][C]0.00800312[/C][/ROW]
[ROW][C]121[/C][C]0.992046[/C][C]0.0159076[/C][C]0.00795381[/C][/ROW]
[ROW][C]122[/C][C]0.991415[/C][C]0.017169[/C][C]0.00858452[/C][/ROW]
[ROW][C]123[/C][C]0.993637[/C][C]0.012726[/C][C]0.00636302[/C][/ROW]
[ROW][C]124[/C][C]0.99471[/C][C]0.0105806[/C][C]0.0052903[/C][/ROW]
[ROW][C]125[/C][C]0.997027[/C][C]0.00594561[/C][C]0.00297281[/C][/ROW]
[ROW][C]126[/C][C]0.997139[/C][C]0.00572223[/C][C]0.00286112[/C][/ROW]
[ROW][C]127[/C][C]0.99898[/C][C]0.00203991[/C][C]0.00101996[/C][/ROW]
[ROW][C]128[/C][C]0.999036[/C][C]0.00192713[/C][C]0.000963566[/C][/ROW]
[ROW][C]129[/C][C]0.998826[/C][C]0.00234882[/C][C]0.00117441[/C][/ROW]
[ROW][C]130[/C][C]0.998921[/C][C]0.00215899[/C][C]0.00107949[/C][/ROW]
[ROW][C]131[/C][C]0.998687[/C][C]0.00262668[/C][C]0.00131334[/C][/ROW]
[ROW][C]132[/C][C]0.99895[/C][C]0.00209927[/C][C]0.00104964[/C][/ROW]
[ROW][C]133[/C][C]0.998952[/C][C]0.00209621[/C][C]0.0010481[/C][/ROW]
[ROW][C]134[/C][C]0.998767[/C][C]0.00246681[/C][C]0.0012334[/C][/ROW]
[ROW][C]135[/C][C]0.998548[/C][C]0.00290447[/C][C]0.00145223[/C][/ROW]
[ROW][C]136[/C][C]0.998878[/C][C]0.00224304[/C][C]0.00112152[/C][/ROW]
[ROW][C]137[/C][C]0.99878[/C][C]0.00244063[/C][C]0.00122031[/C][/ROW]
[ROW][C]138[/C][C]0.998608[/C][C]0.0027844[/C][C]0.0013922[/C][/ROW]
[ROW][C]139[/C][C]0.998304[/C][C]0.00339214[/C][C]0.00169607[/C][/ROW]
[ROW][C]140[/C][C]0.999141[/C][C]0.00171802[/C][C]0.00085901[/C][/ROW]
[ROW][C]141[/C][C]0.999369[/C][C]0.00126104[/C][C]0.000630519[/C][/ROW]
[ROW][C]142[/C][C]0.999424[/C][C]0.00115231[/C][C]0.000576155[/C][/ROW]
[ROW][C]143[/C][C]0.999285[/C][C]0.00143074[/C][C]0.00071537[/C][/ROW]
[ROW][C]144[/C][C]0.999102[/C][C]0.00179693[/C][C]0.000898464[/C][/ROW]
[ROW][C]145[/C][C]0.999457[/C][C]0.00108589[/C][C]0.000542947[/C][/ROW]
[ROW][C]146[/C][C]0.999305[/C][C]0.00139023[/C][C]0.000695115[/C][/ROW]
[ROW][C]147[/C][C]0.999504[/C][C]0.000992823[/C][C]0.000496412[/C][/ROW]
[ROW][C]148[/C][C]0.999569[/C][C]0.000861477[/C][C]0.000430738[/C][/ROW]
[ROW][C]149[/C][C]0.999506[/C][C]0.000988912[/C][C]0.000494456[/C][/ROW]
[ROW][C]150[/C][C]0.999425[/C][C]0.00115013[/C][C]0.000575063[/C][/ROW]
[ROW][C]151[/C][C]0.999299[/C][C]0.00140116[/C][C]0.000700582[/C][/ROW]
[ROW][C]152[/C][C]0.999083[/C][C]0.00183402[/C][C]0.000917012[/C][/ROW]
[ROW][C]153[/C][C]0.998842[/C][C]0.00231565[/C][C]0.00115783[/C][/ROW]
[ROW][C]154[/C][C]0.998516[/C][C]0.0029683[/C][C]0.00148415[/C][/ROW]
[ROW][C]155[/C][C]0.998633[/C][C]0.00273452[/C][C]0.00136726[/C][/ROW]
[ROW][C]156[/C][C]0.999146[/C][C]0.00170726[/C][C]0.00085363[/C][/ROW]
[ROW][C]157[/C][C]0.998966[/C][C]0.00206779[/C][C]0.00103389[/C][/ROW]
[ROW][C]158[/C][C]0.999024[/C][C]0.001952[/C][C]0.000975998[/C][/ROW]
[ROW][C]159[/C][C]0.99896[/C][C]0.0020802[/C][C]0.0010401[/C][/ROW]
[ROW][C]160[/C][C]0.999149[/C][C]0.0017014[/C][C]0.000850702[/C][/ROW]
[ROW][C]161[/C][C]0.998952[/C][C]0.00209673[/C][C]0.00104837[/C][/ROW]
[ROW][C]162[/C][C]0.998879[/C][C]0.00224137[/C][C]0.00112068[/C][/ROW]
[ROW][C]163[/C][C]0.999064[/C][C]0.00187259[/C][C]0.000936297[/C][/ROW]
[ROW][C]164[/C][C]0.998962[/C][C]0.0020751[/C][C]0.00103755[/C][/ROW]
[ROW][C]165[/C][C]0.998786[/C][C]0.00242856[/C][C]0.00121428[/C][/ROW]
[ROW][C]166[/C][C]0.998805[/C][C]0.00238907[/C][C]0.00119453[/C][/ROW]
[ROW][C]167[/C][C]0.998807[/C][C]0.00238664[/C][C]0.00119332[/C][/ROW]
[ROW][C]168[/C][C]0.998496[/C][C]0.00300766[/C][C]0.00150383[/C][/ROW]
[ROW][C]169[/C][C]0.999261[/C][C]0.00147767[/C][C]0.000738835[/C][/ROW]
[ROW][C]170[/C][C]0.999129[/C][C]0.00174173[/C][C]0.000870865[/C][/ROW]
[ROW][C]171[/C][C]0.998875[/C][C]0.0022506[/C][C]0.0011253[/C][/ROW]
[ROW][C]172[/C][C]0.998767[/C][C]0.00246628[/C][C]0.00123314[/C][/ROW]
[ROW][C]173[/C][C]0.999055[/C][C]0.00188945[/C][C]0.000944727[/C][/ROW]
[ROW][C]174[/C][C]0.998782[/C][C]0.00243635[/C][C]0.00121817[/C][/ROW]
[ROW][C]175[/C][C]0.998929[/C][C]0.00214242[/C][C]0.00107121[/C][/ROW]
[ROW][C]176[/C][C]0.99871[/C][C]0.00258004[/C][C]0.00129002[/C][/ROW]
[ROW][C]177[/C][C]0.998827[/C][C]0.00234631[/C][C]0.00117315[/C][/ROW]
[ROW][C]178[/C][C]0.998459[/C][C]0.00308269[/C][C]0.00154134[/C][/ROW]
[ROW][C]179[/C][C]0.998039[/C][C]0.00392246[/C][C]0.00196123[/C][/ROW]
[ROW][C]180[/C][C]0.997539[/C][C]0.00492191[/C][C]0.00246096[/C][/ROW]
[ROW][C]181[/C][C]0.997662[/C][C]0.00467524[/C][C]0.00233762[/C][/ROW]
[ROW][C]182[/C][C]0.996917[/C][C]0.00616583[/C][C]0.00308291[/C][/ROW]
[ROW][C]183[/C][C]0.997975[/C][C]0.0040496[/C][C]0.0020248[/C][/ROW]
[ROW][C]184[/C][C]0.997401[/C][C]0.00519752[/C][C]0.00259876[/C][/ROW]
[ROW][C]185[/C][C]0.99695[/C][C]0.00610029[/C][C]0.00305015[/C][/ROW]
[ROW][C]186[/C][C]0.997894[/C][C]0.00421186[/C][C]0.00210593[/C][/ROW]
[ROW][C]187[/C][C]0.997254[/C][C]0.00549133[/C][C]0.00274567[/C][/ROW]
[ROW][C]188[/C][C]0.997688[/C][C]0.00462383[/C][C]0.00231192[/C][/ROW]
[ROW][C]189[/C][C]0.997145[/C][C]0.00571026[/C][C]0.00285513[/C][/ROW]
[ROW][C]190[/C][C]0.99792[/C][C]0.00416026[/C][C]0.00208013[/C][/ROW]
[ROW][C]191[/C][C]0.997324[/C][C]0.00535112[/C][C]0.00267556[/C][/ROW]
[ROW][C]192[/C][C]0.998159[/C][C]0.00368146[/C][C]0.00184073[/C][/ROW]
[ROW][C]193[/C][C]0.998184[/C][C]0.00363157[/C][C]0.00181579[/C][/ROW]
[ROW][C]194[/C][C]0.997567[/C][C]0.00486623[/C][C]0.00243312[/C][/ROW]
[ROW][C]195[/C][C]0.996822[/C][C]0.00635596[/C][C]0.00317798[/C][/ROW]
[ROW][C]196[/C][C]0.995947[/C][C]0.00810696[/C][C]0.00405348[/C][/ROW]
[ROW][C]197[/C][C]0.995764[/C][C]0.00847172[/C][C]0.00423586[/C][/ROW]
[ROW][C]198[/C][C]0.996242[/C][C]0.00751564[/C][C]0.00375782[/C][/ROW]
[ROW][C]199[/C][C]0.996736[/C][C]0.00652781[/C][C]0.0032639[/C][/ROW]
[ROW][C]200[/C][C]0.995839[/C][C]0.0083227[/C][C]0.00416135[/C][/ROW]
[ROW][C]201[/C][C]0.994704[/C][C]0.0105918[/C][C]0.0052959[/C][/ROW]
[ROW][C]202[/C][C]0.994378[/C][C]0.011244[/C][C]0.00562198[/C][/ROW]
[ROW][C]203[/C][C]0.992918[/C][C]0.0141635[/C][C]0.00708175[/C][/ROW]
[ROW][C]204[/C][C]0.993555[/C][C]0.0128892[/C][C]0.00644458[/C][/ROW]
[ROW][C]205[/C][C]0.99178[/C][C]0.0164393[/C][C]0.00821967[/C][/ROW]
[ROW][C]206[/C][C]0.990696[/C][C]0.0186072[/C][C]0.00930362[/C][/ROW]
[ROW][C]207[/C][C]0.988126[/C][C]0.023749[/C][C]0.0118745[/C][/ROW]
[ROW][C]208[/C][C]0.98523[/C][C]0.0295391[/C][C]0.0147696[/C][/ROW]
[ROW][C]209[/C][C]0.982069[/C][C]0.0358618[/C][C]0.0179309[/C][/ROW]
[ROW][C]210[/C][C]0.977291[/C][C]0.0454179[/C][C]0.0227089[/C][/ROW]
[ROW][C]211[/C][C]0.978309[/C][C]0.0433816[/C][C]0.0216908[/C][/ROW]
[ROW][C]212[/C][C]0.972782[/C][C]0.0544364[/C][C]0.0272182[/C][/ROW]
[ROW][C]213[/C][C]0.968013[/C][C]0.0639747[/C][C]0.0319873[/C][/ROW]
[ROW][C]214[/C][C]0.961054[/C][C]0.0778927[/C][C]0.0389463[/C][/ROW]
[ROW][C]215[/C][C]0.958951[/C][C]0.0820978[/C][C]0.0410489[/C][/ROW]
[ROW][C]216[/C][C]0.951557[/C][C]0.0968851[/C][C]0.0484426[/C][/ROW]
[ROW][C]217[/C][C]0.941024[/C][C]0.117951[/C][C]0.0589755[/C][/ROW]
[ROW][C]218[/C][C]0.931526[/C][C]0.136948[/C][C]0.0684739[/C][/ROW]
[ROW][C]219[/C][C]0.93048[/C][C]0.13904[/C][C]0.0695201[/C][/ROW]
[ROW][C]220[/C][C]0.917733[/C][C]0.164534[/C][C]0.082267[/C][/ROW]
[ROW][C]221[/C][C]0.902689[/C][C]0.194621[/C][C]0.0973106[/C][/ROW]
[ROW][C]222[/C][C]0.883525[/C][C]0.232949[/C][C]0.116475[/C][/ROW]
[ROW][C]223[/C][C]0.865995[/C][C]0.26801[/C][C]0.134005[/C][/ROW]
[ROW][C]224[/C][C]0.853187[/C][C]0.293627[/C][C]0.146813[/C][/ROW]
[ROW][C]225[/C][C]0.881797[/C][C]0.236406[/C][C]0.118203[/C][/ROW]
[ROW][C]226[/C][C]0.859462[/C][C]0.281077[/C][C]0.140538[/C][/ROW]
[ROW][C]227[/C][C]0.836438[/C][C]0.327125[/C][C]0.163562[/C][/ROW]
[ROW][C]228[/C][C]0.843523[/C][C]0.312954[/C][C]0.156477[/C][/ROW]
[ROW][C]229[/C][C]0.850994[/C][C]0.298013[/C][C]0.149006[/C][/ROW]
[ROW][C]230[/C][C]0.826874[/C][C]0.346252[/C][C]0.173126[/C][/ROW]
[ROW][C]231[/C][C]0.810388[/C][C]0.379224[/C][C]0.189612[/C][/ROW]
[ROW][C]232[/C][C]0.849502[/C][C]0.300995[/C][C]0.150498[/C][/ROW]
[ROW][C]233[/C][C]0.839358[/C][C]0.321285[/C][C]0.160642[/C][/ROW]
[ROW][C]234[/C][C]0.848535[/C][C]0.302931[/C][C]0.151465[/C][/ROW]
[ROW][C]235[/C][C]0.875687[/C][C]0.248627[/C][C]0.124313[/C][/ROW]
[ROW][C]236[/C][C]0.863253[/C][C]0.273494[/C][C]0.136747[/C][/ROW]
[ROW][C]237[/C][C]0.883008[/C][C]0.233984[/C][C]0.116992[/C][/ROW]
[ROW][C]238[/C][C]0.948173[/C][C]0.103655[/C][C]0.0518274[/C][/ROW]
[ROW][C]239[/C][C]0.939293[/C][C]0.121414[/C][C]0.0607071[/C][/ROW]
[ROW][C]240[/C][C]0.946198[/C][C]0.107605[/C][C]0.0538024[/C][/ROW]
[ROW][C]241[/C][C]0.930921[/C][C]0.138158[/C][C]0.0690792[/C][/ROW]
[ROW][C]242[/C][C]0.916779[/C][C]0.166441[/C][C]0.0832205[/C][/ROW]
[ROW][C]243[/C][C]0.963371[/C][C]0.0732577[/C][C]0.0366288[/C][/ROW]
[ROW][C]244[/C][C]0.95919[/C][C]0.08162[/C][C]0.04081[/C][/ROW]
[ROW][C]245[/C][C]0.947879[/C][C]0.104242[/C][C]0.0521212[/C][/ROW]
[ROW][C]246[/C][C]0.932062[/C][C]0.135876[/C][C]0.0679379[/C][/ROW]
[ROW][C]247[/C][C]0.916722[/C][C]0.166557[/C][C]0.0832783[/C][/ROW]
[ROW][C]248[/C][C]0.895146[/C][C]0.209708[/C][C]0.104854[/C][/ROW]
[ROW][C]249[/C][C]0.879973[/C][C]0.240054[/C][C]0.120027[/C][/ROW]
[ROW][C]250[/C][C]0.858865[/C][C]0.282271[/C][C]0.141135[/C][/ROW]
[ROW][C]251[/C][C]0.830161[/C][C]0.339678[/C][C]0.169839[/C][/ROW]
[ROW][C]252[/C][C]0.82939[/C][C]0.34122[/C][C]0.17061[/C][/ROW]
[ROW][C]253[/C][C]0.791174[/C][C]0.417652[/C][C]0.208826[/C][/ROW]
[ROW][C]254[/C][C]0.747822[/C][C]0.504356[/C][C]0.252178[/C][/ROW]
[ROW][C]255[/C][C]0.699975[/C][C]0.60005[/C][C]0.300025[/C][/ROW]
[ROW][C]256[/C][C]0.645348[/C][C]0.709304[/C][C]0.354652[/C][/ROW]
[ROW][C]257[/C][C]0.598517[/C][C]0.802965[/C][C]0.401483[/C][/ROW]
[ROW][C]258[/C][C]0.541554[/C][C]0.916891[/C][C]0.458446[/C][/ROW]
[ROW][C]259[/C][C]0.505077[/C][C]0.989846[/C][C]0.494923[/C][/ROW]
[ROW][C]260[/C][C]0.493594[/C][C]0.987188[/C][C]0.506406[/C][/ROW]
[ROW][C]261[/C][C]0.439123[/C][C]0.878245[/C][C]0.560877[/C][/ROW]
[ROW][C]262[/C][C]0.375873[/C][C]0.751746[/C][C]0.624127[/C][/ROW]
[ROW][C]263[/C][C]0.35118[/C][C]0.702361[/C][C]0.64882[/C][/ROW]
[ROW][C]264[/C][C]0.295321[/C][C]0.590641[/C][C]0.704679[/C][/ROW]
[ROW][C]265[/C][C]0.360895[/C][C]0.72179[/C][C]0.639105[/C][/ROW]
[ROW][C]266[/C][C]0.75036[/C][C]0.49928[/C][C]0.24964[/C][/ROW]
[ROW][C]267[/C][C]0.73347[/C][C]0.53306[/C][C]0.26653[/C][/ROW]
[ROW][C]268[/C][C]0.991618[/C][C]0.0167639[/C][C]0.00838197[/C][/ROW]
[ROW][C]269[/C][C]0.984038[/C][C]0.0319231[/C][C]0.0159615[/C][/ROW]
[ROW][C]270[/C][C]0.971696[/C][C]0.0566087[/C][C]0.0283043[/C][/ROW]
[ROW][C]271[/C][C]0.983897[/C][C]0.0322058[/C][C]0.0161029[/C][/ROW]
[ROW][C]272[/C][C]0.970317[/C][C]0.0593664[/C][C]0.0296832[/C][/ROW]
[ROW][C]273[/C][C]0.955205[/C][C]0.089589[/C][C]0.0447945[/C][/ROW]
[ROW][C]274[/C][C]0.918072[/C][C]0.163855[/C][C]0.0819275[/C][/ROW]
[ROW][C]275[/C][C]0.937862[/C][C]0.124275[/C][C]0.0621375[/C][/ROW]
[ROW][C]276[/C][C]0.93602[/C][C]0.127961[/C][C]0.0639805[/C][/ROW]
[ROW][C]277[/C][C]0.917093[/C][C]0.165814[/C][C]0.082907[/C][/ROW]
[ROW][C]278[/C][C]0.816699[/C][C]0.366602[/C][C]0.183301[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270029&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270029&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
80.97120.0575990.0287995
90.9395680.1208630.0604316
100.8920230.2159540.107977
110.8423630.3152740.157637
120.7682710.4634580.231729
130.7942350.411530.205765
140.7920140.4159730.207986
150.7258480.5483040.274152
160.6589030.6821930.341097
170.7296240.5407530.270376
180.6610440.6779130.338956
190.5978760.8042480.402124
200.5693220.8613570.430678
210.4985760.9971520.501424
220.5039790.9920420.496021
230.5105510.9788970.489449
240.4484010.8968020.551599
250.4724610.9449220.527539
260.4083680.8167370.591632
270.3507460.7014920.649254
280.2942090.5884180.705791
290.2708390.5416780.729161
300.2471920.4943840.752808
310.2210320.4420630.778968
320.2033890.4067780.796611
330.1736750.3473510.826325
340.2924790.5849580.707521
350.2573040.5146080.742696
360.2232050.4464110.776795
370.1867530.3735050.813247
380.1554960.3109920.844504
390.126040.252080.87396
400.1191990.2383990.880801
410.1339810.2679620.866019
420.109220.2184390.89078
430.1879880.3759750.812012
440.1601870.3203750.839813
450.1790380.3580760.820962
460.1511340.3022690.848866
470.1456260.2912510.854374
480.1226890.2453770.877311
490.1051530.2103060.894847
500.183540.3670790.81646
510.2081160.4162320.791884
520.2170490.4340980.782951
530.1861350.372270.813865
540.2337170.4674340.766283
550.2110960.4221920.788904
560.2027080.4054160.797292
570.2160010.4320030.783999
580.1887360.3774720.811264
590.2799420.5598850.720058
600.351720.703440.64828
610.3149340.6298690.685066
620.3087630.6175260.691237
630.3173010.6346020.682699
640.302030.6040610.69797
650.351880.703760.64812
660.4027360.8054730.597264
670.385960.771920.61404
680.361970.7239410.63803
690.3461730.6923470.653827
700.3185790.6371590.681421
710.3548510.7097010.645149
720.3212320.6424640.678768
730.2980520.5961040.701948
740.2781720.5563440.721828
750.2826490.5652990.717351
760.2663870.5327740.733613
770.3556830.7113660.644317
780.3346450.669290.665355
790.3084080.6168160.691592
800.2986450.5972910.701355
810.2764820.5529640.723518
820.2660080.5320160.733992
830.3432930.6865850.656707
840.3290150.658030.670985
850.3312570.6625140.668743
860.3133640.6267290.686636
870.455170.9103390.54483
880.4653110.9306210.534689
890.444760.8895190.55524
900.4130860.8261720.586914
910.382790.7655790.61721
920.410110.8202190.58989
930.4074020.8148030.592598
940.3943720.7887440.605628
950.5449970.9100070.455003
960.5452760.9094490.454724
970.5616530.8766940.438347
980.637570.7248590.36243
990.6205270.7589450.379473
1000.6617640.6764730.338236
1010.6589690.6820610.341031
1020.7147870.5704250.285213
1030.7986270.4027470.201373
1040.7816970.4366050.218303
1050.7657410.4685180.234259
1060.7678460.4643070.232154
1070.7837640.4324720.216236
1080.7905130.4189750.209487
1090.8212340.3575330.178766
1100.814020.3719590.18598
1110.9133980.1732040.0866021
1120.9477570.1044860.0522432
1130.9590140.08197280.0409864
1140.9545880.09082360.0454118
1150.9497230.1005540.0502771
1160.9789210.04215870.0210794
1170.9792070.04158560.0207928
1180.9873610.02527850.0126392
1190.9926140.01477160.00738578
1200.9919970.01600620.00800312
1210.9920460.01590760.00795381
1220.9914150.0171690.00858452
1230.9936370.0127260.00636302
1240.994710.01058060.0052903
1250.9970270.005945610.00297281
1260.9971390.005722230.00286112
1270.998980.002039910.00101996
1280.9990360.001927130.000963566
1290.9988260.002348820.00117441
1300.9989210.002158990.00107949
1310.9986870.002626680.00131334
1320.998950.002099270.00104964
1330.9989520.002096210.0010481
1340.9987670.002466810.0012334
1350.9985480.002904470.00145223
1360.9988780.002243040.00112152
1370.998780.002440630.00122031
1380.9986080.00278440.0013922
1390.9983040.003392140.00169607
1400.9991410.001718020.00085901
1410.9993690.001261040.000630519
1420.9994240.001152310.000576155
1430.9992850.001430740.00071537
1440.9991020.001796930.000898464
1450.9994570.001085890.000542947
1460.9993050.001390230.000695115
1470.9995040.0009928230.000496412
1480.9995690.0008614770.000430738
1490.9995060.0009889120.000494456
1500.9994250.001150130.000575063
1510.9992990.001401160.000700582
1520.9990830.001834020.000917012
1530.9988420.002315650.00115783
1540.9985160.00296830.00148415
1550.9986330.002734520.00136726
1560.9991460.001707260.00085363
1570.9989660.002067790.00103389
1580.9990240.0019520.000975998
1590.998960.00208020.0010401
1600.9991490.00170140.000850702
1610.9989520.002096730.00104837
1620.9988790.002241370.00112068
1630.9990640.001872590.000936297
1640.9989620.00207510.00103755
1650.9987860.002428560.00121428
1660.9988050.002389070.00119453
1670.9988070.002386640.00119332
1680.9984960.003007660.00150383
1690.9992610.001477670.000738835
1700.9991290.001741730.000870865
1710.9988750.00225060.0011253
1720.9987670.002466280.00123314
1730.9990550.001889450.000944727
1740.9987820.002436350.00121817
1750.9989290.002142420.00107121
1760.998710.002580040.00129002
1770.9988270.002346310.00117315
1780.9984590.003082690.00154134
1790.9980390.003922460.00196123
1800.9975390.004921910.00246096
1810.9976620.004675240.00233762
1820.9969170.006165830.00308291
1830.9979750.00404960.0020248
1840.9974010.005197520.00259876
1850.996950.006100290.00305015
1860.9978940.004211860.00210593
1870.9972540.005491330.00274567
1880.9976880.004623830.00231192
1890.9971450.005710260.00285513
1900.997920.004160260.00208013
1910.9973240.005351120.00267556
1920.9981590.003681460.00184073
1930.9981840.003631570.00181579
1940.9975670.004866230.00243312
1950.9968220.006355960.00317798
1960.9959470.008106960.00405348
1970.9957640.008471720.00423586
1980.9962420.007515640.00375782
1990.9967360.006527810.0032639
2000.9958390.00832270.00416135
2010.9947040.01059180.0052959
2020.9943780.0112440.00562198
2030.9929180.01416350.00708175
2040.9935550.01288920.00644458
2050.991780.01643930.00821967
2060.9906960.01860720.00930362
2070.9881260.0237490.0118745
2080.985230.02953910.0147696
2090.9820690.03586180.0179309
2100.9772910.04541790.0227089
2110.9783090.04338160.0216908
2120.9727820.05443640.0272182
2130.9680130.06397470.0319873
2140.9610540.07789270.0389463
2150.9589510.08209780.0410489
2160.9515570.09688510.0484426
2170.9410240.1179510.0589755
2180.9315260.1369480.0684739
2190.930480.139040.0695201
2200.9177330.1645340.082267
2210.9026890.1946210.0973106
2220.8835250.2329490.116475
2230.8659950.268010.134005
2240.8531870.2936270.146813
2250.8817970.2364060.118203
2260.8594620.2810770.140538
2270.8364380.3271250.163562
2280.8435230.3129540.156477
2290.8509940.2980130.149006
2300.8268740.3462520.173126
2310.8103880.3792240.189612
2320.8495020.3009950.150498
2330.8393580.3212850.160642
2340.8485350.3029310.151465
2350.8756870.2486270.124313
2360.8632530.2734940.136747
2370.8830080.2339840.116992
2380.9481730.1036550.0518274
2390.9392930.1214140.0607071
2400.9461980.1076050.0538024
2410.9309210.1381580.0690792
2420.9167790.1664410.0832205
2430.9633710.07325770.0366288
2440.959190.081620.04081
2450.9478790.1042420.0521212
2460.9320620.1358760.0679379
2470.9167220.1665570.0832783
2480.8951460.2097080.104854
2490.8799730.2400540.120027
2500.8588650.2822710.141135
2510.8301610.3396780.169839
2520.829390.341220.17061
2530.7911740.4176520.208826
2540.7478220.5043560.252178
2550.6999750.600050.300025
2560.6453480.7093040.354652
2570.5985170.8029650.401483
2580.5415540.9168910.458446
2590.5050770.9898460.494923
2600.4935940.9871880.506406
2610.4391230.8782450.560877
2620.3758730.7517460.624127
2630.351180.7023610.64882
2640.2953210.5906410.704679
2650.3608950.721790.639105
2660.750360.499280.24964
2670.733470.533060.26653
2680.9916180.01676390.00838197
2690.9840380.03192310.0159615
2700.9716960.05660870.0283043
2710.9838970.03220580.0161029
2720.9703170.05936640.0296832
2730.9552050.0895890.0447945
2740.9180720.1638550.0819275
2750.9378620.1242750.0621375
2760.936020.1279610.0639805
2770.9170930.1658140.082907
2780.8166990.3666020.183301






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level760.280443NOK
5% type I error level990.365314NOK
10% type I error level1120.413284NOK

\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 & 76 & 0.280443 & NOK \tabularnewline
5% type I error level & 99 & 0.365314 & NOK \tabularnewline
10% type I error level & 112 & 0.413284 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270029&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]76[/C][C]0.280443[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]99[/C][C]0.365314[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]112[/C][C]0.413284[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270029&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270029&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level760.280443NOK
5% type I error level990.365314NOK
10% type I error level1120.413284NOK


Figures (Output of Computation)

Figure 1
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 2
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 3
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 4
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 5
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 6
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 7
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 8
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 9
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 10
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


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')
}