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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 08 Dec 2014 11:29:20 +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/08/t1418038417mmd88k4q00er31h.htm/, Retrieved Fri, 17 May 2024 07:17:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263940, Retrieved Fri, 17 May 2024 07:17:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-08 11:29:20] [d3a85ea23f6d8881e8b5a834ebd3a404] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
13 12 26 50 4 12.9
8 8 57 62 4 12.2
14 11 37 54 5 12.8
16 13 67 71 4 7.4
14 11 43 54 4 6.7
13 10 52 65 9 12.6
15 7 52 73 8 14.8
13 10 43 52 11 13.3
20 15 84 84 4 11.1
17 12 67 42 4 8.2
15 12 49 66 6 11.4
16 10 70 65 4 6.4
12 10 52 78 8 10.6
17 14 58 73 4 12
11 6 68 75 4 6.3
16 12 62 72 11 11.3
16 14 43 66 4 11.9
15 11 56 70 4 9.3
13 8 56 61 6 9.6
14 12 74 81 6 10
19 15 65 71 4 6.4
16 13 63 69 8 13.8
17 11 58 71 5 10.8
10 12 57 72 4 13.8
15 7 63 68 9 11.7
14 11 53 70 4 10.9
14 7 57 68 7 16.1
16 12 51 61 10 13.4
15 12 64 67 4 9.9
17 13 53 76 4 11.5
14 9 29 70 7 8.3
16 11 54 60 12 11.7
15 12 58 72 7 9
16 15 43 69 5 9.7
16 12 51 71 8 10.8
10 6 53 62 5 10.3
8 5 54 70 4 10.4
17 13 56 64 9 12.7
14 11 61 58 7 9.3
10 6 47 76 4 11.8
14 12 39 52 4 5.9
12 10 48 59 4 11.4
16 6 50 68 4 13
16 12 35 76 4 10.8
16 11 30 65 7 12.3
8 6 68 67 4 11.3
16 12 49 59 7 11.8
15 12 61 69 4 7.9
8 8 67 76 4 12.7
13 10 47 63 4 12.3
14 11 56 75 4 11.6
13 7 50 63 8 6.7
16 12 43 60 4 10.9
19 13 67 73 4 12.1
19 14 62 63 4 13.3
14 12 57 70 4 10.1
15 6 41 75 7 5.7
13 14 54 66 12 14.3
10 10 45 63 4 8
16 12 48 63 4 13.3
15 11 61 64 4 9.3
11 10 56 70 5 12.5
9 7 41 75 15 7.6
16 12 43 61 5 15.9
12 7 53 60 10 9.2
12 12 44 62 9 9.1
14 12 66 73 8 11.1
14 10 58 61 4 13
13 10 46 66 5 14.5
15 12 37 64 4 12.2
17 12 51 59 9 12.3
14 12 51 64 4 11.4
11 8 56 60 10 8.8
9 10 66 56 4 14.6
7 5 37 78 4 12.6
13 10 59 53 6 NA
15 10 42 67 7 13
12 12 38 59 5 12.6
15 11 66 66 4 13.2
14 9 34 68 4 9.9
16 12 53 71 4 7.7
14 11 49 66 4 10.5
13 10 55 73 4 13.4
16 12 49 72 4 10.9
13 10 59 71 6 4.3
16 9 40 59 10 10.3
16 11 58 64 7 11.8
16 12 60 66 4 11.2
10 7 63 78 4 11.4
12 11 56 68 7 8.6
12 12 54 73 4 13.2
12 6 52 62 8 12.6
12 9 34 65 11 5.6
19 15 69 68 6 9.9
14 10 32 65 14 8.8
13 11 48 60 5 7.7
16 12 67 71 4 9
15 12 58 65 8 7.3
12 12 57 68 9 11.4
8 11 42 64 4 13.6
10 9 64 74 4 7.9
16 11 58 69 5 10.7
16 12 66 76 4 10.3
10 12 26 68 5 8.3
18 14 61 72 4 9.6
12 8 52 67 4 14.2
16 10 51 63 7 8.5
10 9 55 59 10 13.5
14 10 50 73 4 4.9
12 9 60 66 5 6.4
11 10 56 62 4 9.6
15 12 63 69 4 11.6
7 11 61 66 4 11.1
16 9 52 51 6 4.35
16 11 16 56 4 12.7
16 12 46 67 8 18.1
16 12 56 69 5 17.85
12 7 52 57 4 16.6
15 12 55 56 17 12.6
14 12 50 55 4 17.1
15 12 59 63 4 19.1
16 10 60 67 8 16.1
13 15 52 65 4 13.35
10 10 44 47 7 18.4
17 15 67 76 4 14.7
15 10 52 64 4 10.6
18 15 55 68 5 12.6
16 9 37 64 7 16.2
20 15 54 65 4 13.6
16 12 72 71 4 18.9
17 13 51 63 7 14.1
16 12 48 60 11 14.5
15 12 60 68 7 16.15
13 8 50 72 4 14.75
16 9 63 70 4 14.8
16 15 33 61 4 12.45
16 12 67 61 4 12.65
17 12 46 62 4 17.35
20 15 54 71 4 8.6
14 11 59 71 6 18.4
17 12 61 51 8 16.1
6 6 33 56 23 11.6
16 14 47 70 4 17.75
15 12 69 73 8 15.25
16 12 52 76 6 17.65
16 12 55 68 4 16.35
14 11 41 48 7 17.65
16 12 73 52 4 13.6
16 12 52 60 4 14.35
16 12 50 59 4 14.75
14 12 51 57 10 18.25
14 8 60 79 6 9.9
16 8 56 60 5 16
16 12 56 60 5 18.25
15 12 29 59 4 16.85
16 11 66 62 4 14.6
16 10 66 59 5 13.85
18 11 73 61 5 18.95
15 12 55 71 5 15.6
16 13 64 57 5 14.85
16 12 40 66 4 11.75
16 12 46 63 6 18.45
17 10 58 69 4 15.9
14 10 43 58 4 17.1
18 11 61 59 4 16.1
9 8 51 48 9 19.9
15 12 50 66 18 10.95
14 9 52 73 6 18.45
15 12 54 67 5 15.1
13 9 66 61 4 15
16 11 61 68 11 11.35
20 15 80 75 4 15.95
14 8 51 62 10 18.1
12 8 56 69 6 14.6
15 11 56 58 8 15.4
15 11 56 60 8 15.4
15 11 53 74 6 17.6
16 13 47 55 8 13.35
11 7 25 62 4 19.1
16 12 47 63 4 15.35
7 8 46 69 9 7.6
11 8 50 58 9 13.4
9 4 39 58 5 13.9
15 11 51 68 4 19.1
16 10 58 72 4 15.25
14 7 35 62 15 12.9
15 12 58 62 10 16.1
13 11 60 65 9 17.35
13 9 62 69 7 13.15
12 10 63 66 9 12.15
16 8 53 72 6 12.6
14 8 46 62 4 10.35
16 11 67 75 7 15.4
14 12 59 58 4 9.6
15 10 64 66 7 18.2
10 10 38 55 4 13.6
16 12 50 47 15 14.85
14 8 48 72 4 14.75
16 11 48 62 9 14.1
12 8 47 64 4 14.9
16 10 66 64 4 16.25
16 14 47 19 28 19.25
15 9 63 50 4 13.6
14 9 58 68 4 13.6
16 10 44 70 4 15.65
11 13 51 79 5 12.75
15 12 43 69 4 14.6
18 13 55 71 4 9.85
13 8 38 48 12 12.65
7 3 45 73 4 19.2
7 8 50 74 6 16.6
17 12 54 66 6 11.2
18 11 57 71 5 15.25
15 9 60 74 4 11.9
8 12 55 78 4 13.2
13 12 56 75 4 16.35
13 12 49 53 10 12.4
15 10 37 60 7 15.85
18 13 59 70 4 18.15
16 9 46 69 7 11.15
14 12 51 65 4 15.65
15 11 58 78 4 17.75
19 14 64 78 12 7.65
16 11 53 59 5 12.35
12 9 48 72 8 15.6
16 12 51 70 6 19.3
11 8 47 63 17 15.2
16 15 59 63 4 17.1
15 12 62 71 5 15.6
19 14 62 74 4 18.4
15 12 51 67 5 19.05
14 9 64 66 5 18.55
14 9 52 62 6 19.1
17 13 67 80 4 13.1
16 13 50 73 4 12.85
20 15 54 67 4 9.5
16 11 58 61 6 4.5
9 7 56 73 8 11.85
13 10 63 74 10 13.6
15 11 31 32 4 11.7
19 14 65 69 5 12.4
16 14 71 69 4 13.35
17 13 50 84 4 11.4
16 12 57 64 4 14.9
9 8 47 58 16 19.9
11 13 47 59 7 11.2
14 9 57 78 4 14.6
19 12 43 57 4 17.6
13 13 41 60 14 14.05
14 11 63 68 5 16.1
15 11 63 68 5 13.35
15 13 56 73 5 11.85
14 12 51 69 5 11.95
16 12 50 67 7 14.75
17 10 22 60 19 15.15
12 9 41 65 16 13.2
15 10 59 66 4 16.85
17 13 56 74 4 7.85
15 13 66 81 7 7.7
10 9 53 72 9 12.6
16 11 42 55 5 7.85
15 12 52 49 14 10.95
11 8 54 74 4 12.35
16 12 44 53 16 9.95
16 12 62 64 10 14.9
16 12 53 65 5 16.65
14 9 50 57 6 13.4
14 12 36 51 4 13.95
16 12 76 80 4 15.7
16 11 66 67 4 16.85
18 12 62 70 5 10.95
14 6 59 74 4 15.35
20 7 47 75 4 12.2
15 10 55 70 5 15.1
16 12 58 69 4 17.75
16 10 60 65 4 15.2
16 12 44 55 5 14.6
12 9 57 71 8 16.65
8 3 45 65 15 8.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263940&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263940&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263940&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 time8 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 15.3032 + 0.0908958CONFSTATTOT[t] -0.048414CONFSOFTTOT[t] + 0.0167329AMS.I[t] -0.0588309AMS.E[t] -0.0236781AMS.A[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  15.3032 +  0.0908958CONFSTATTOT[t] -0.048414CONFSOFTTOT[t] +  0.0167329AMS.I[t] -0.0588309AMS.E[t] -0.0236781AMS.A[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263940&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  15.3032 +  0.0908958CONFSTATTOT[t] -0.048414CONFSOFTTOT[t] +  0.0167329AMS.I[t] -0.0588309AMS.E[t] -0.0236781AMS.A[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263940&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263940&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
TOT[t] = + 15.3032 + 0.0908958CONFSTATTOT[t] -0.048414CONFSOFTTOT[t] + 0.0167329AMS.I[t] -0.0588309AMS.E[t] -0.0236781AMS.A[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.30322.325596.582.40255e-101.20127e-10
CONFSTATTOT0.09089580.0966660.94030.3478940.173947
CONFSOFTTOT-0.0484140.114843-0.42160.6736730.336837
AMS.I0.01673290.02186880.76510.4448460.222423
AMS.E-0.05883090.0279103-2.1080.03595850.0179793
AMS.A-0.02367810.0633013-0.37410.7086560.354328

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 15.3032 & 2.32559 & 6.58 & 2.40255e-10 & 1.20127e-10 \tabularnewline
CONFSTATTOT & 0.0908958 & 0.096666 & 0.9403 & 0.347894 & 0.173947 \tabularnewline
CONFSOFTTOT & -0.048414 & 0.114843 & -0.4216 & 0.673673 & 0.336837 \tabularnewline
AMS.I & 0.0167329 & 0.0218688 & 0.7651 & 0.444846 & 0.222423 \tabularnewline
AMS.E & -0.0588309 & 0.0279103 & -2.108 & 0.0359585 & 0.0179793 \tabularnewline
AMS.A & -0.0236781 & 0.0633013 & -0.3741 & 0.708656 & 0.354328 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263940&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]15.3032[/C][C]2.32559[/C][C]6.58[/C][C]2.40255e-10[/C][C]1.20127e-10[/C][/ROW]
[ROW][C]CONFSTATTOT[/C][C]0.0908958[/C][C]0.096666[/C][C]0.9403[/C][C]0.347894[/C][C]0.173947[/C][/ROW]
[ROW][C]CONFSOFTTOT[/C][C]-0.048414[/C][C]0.114843[/C][C]-0.4216[/C][C]0.673673[/C][C]0.336837[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.0167329[/C][C]0.0218688[/C][C]0.7651[/C][C]0.444846[/C][C]0.222423[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0588309[/C][C]0.0279103[/C][C]-2.108[/C][C]0.0359585[/C][C]0.0179793[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0236781[/C][C]0.0633013[/C][C]-0.3741[/C][C]0.708656[/C][C]0.354328[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263940&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263940&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.30322.325596.582.40255e-101.20127e-10
CONFSTATTOT0.09089580.0966660.94030.3478940.173947
CONFSOFTTOT-0.0484140.114843-0.42160.6736730.336837
AMS.I0.01673290.02186880.76510.4448460.222423
AMS.E-0.05883090.0279103-2.1080.03595850.0179793
AMS.A-0.02367810.0633013-0.37410.7086560.354328






Multiple Linear Regression - Regression Statistics
Multiple R0.143539
R-squared0.0206036
Adjusted R-squared0.00259997
F-TEST (value)1.14441
F-TEST (DF numerator)5
F-TEST (DF denominator)272
p-value0.33716
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.38994
Sum Squared Residuals3125.75

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.143539 \tabularnewline
R-squared & 0.0206036 \tabularnewline
Adjusted R-squared & 0.00259997 \tabularnewline
F-TEST (value) & 1.14441 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 272 \tabularnewline
p-value & 0.33716 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.38994 \tabularnewline
Sum Squared Residuals & 3125.75 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263940&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.143539[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0206036[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.00259997[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]1.14441[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]272[/C][/ROW]
[ROW][C]p-value[/C][C]0.33716[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.38994[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3125.75[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263940&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263940&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 R0.143539
R-squared0.0206036
Adjusted R-squared0.00259997
F-TEST (value)1.14441
F-TEST (DF numerator)5
F-TEST (DF denominator)272
p-value0.33716
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.38994
Sum Squared Residuals3125.75






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.3027-0.402664
212.212.8546-0.65459
312.813.367-0.567034
47.412.9775-5.57754
56.713.4911-6.79111
612.612.8337-0.233693
714.812.71382.08624
813.313.4005-0.100543
911.112.7639-1.66395
108.214.8229-6.62294
1111.412.8807-1.48066
126.413.526-7.12596
1310.612.0017-1.40167
141212.7518-0.751761
156.312.6434-6.34337
1611.312.7177-1.41771
1711.912.8217-0.921688
189.312.8582-3.55824
199.613.3038-3.70381
201012.3256-2.32562
216.413.1199-6.71993
2213.812.93360.866445
2310.812.991-2.19099
2413.812.25441.54558
2511.713.1683-1.4683
2610.912.7171-1.81714
2716.113.02443.07564
2813.413.20450.195535
299.913.1202-3.22018
3011.512.54-1.04002
318.312.3413-4.04135
3211.713.3146-1.61455
33912.6546-3.65459
349.712.5731-2.8731
3510.812.6635-1.86351
3610.313.0426-2.7426
3710.412.479-2.07899
3812.713.1778-0.477797
399.313.4859-4.18594
4011.812.1422-0.342248
415.913.4934-7.59343
4211.413.1472-1.74724
431313.2085-0.208468
4410.812.1963-1.39634
4512.312.7372-0.437199
4611.312.8413-1.54133
4711.813.3597-1.5597
487.912.9523-5.05232
4912.712.19830.501714
5012.312.9861-0.686081
5111.612.4732-0.873188
526.713.0868-6.38681
5310.913.2715-2.3715
5412.113.1326-1.03256
5513.313.5888-0.288793
5610.112.7357-2.63566
575.712.4841-6.78413
5814.312.54361.75636
59812.6799-4.67993
6013.313.17870.121327
619.313.2949-3.99489
6212.512.5194-0.0193911
637.611.7009-4.10091
6415.913.1892.71101
659.213.1752-3.97525
669.112.6886-3.5886
6711.112.6151-1.51505
681313.3787-0.3787
6914.512.76921.73082
7012.212.8449-0.644884
7112.313.4367-1.1367
7211.412.9882-1.58825
738.813.0861-4.28614
7414.613.35221.24776
7512.611.6330.967017
76NANA0.22215
771313.2594-0.259407
7812.612.6609-0.060891
7913.215.9137-2.71371
809.914.9917-5.09169
817.710.0855-2.38554
8210.59.631640.868365
8313.415.1659-1.76593
8410.919.2689-8.36887
854.37.28331-2.98331
8610.311.7646-1.46455
8711.813.803-2.00298
8811.212.0439-0.843898
8911.415.4322-4.03218
908.67.727180.872822
9113.213.7366-0.536624
9212.619.4427-6.84266
935.69.016-3.416
949.913.5715-3.67154
958.814.2072-5.40721
967.711.726-4.02595
97914.7427-5.74273
987.38.45314-1.15314
9911.410.14071.25931
10013.618.0991-4.49913
1017.910.2178-2.31775
10210.713.1151-2.41506
10310.313.9473-3.64734
1048.311.6517-3.35169
1059.68.240351.35965
10614.218.9547-4.75467
1078.57.988930.511074
10813.521.1389-7.63887
1094.911.461-6.56096
1106.49.81372-3.41372
1119.610.9858-1.38579
11211.612.9501-1.35006
11311.120.7995-9.69946
1144.354.75345-0.40345
11512.77.415175.28483
11618.113.18594.91413
11717.8514.72713.12292
11816.617.3089-0.708909
11912.69.000993.59901
12017.111.27185.82816
12119.116.14632.95374
12216.115.460.639986
12313.358.483464.86654
12418.416.37752.02255
12514.717.2927-2.59271
12610.611.0145-0.414521
12712.69.409993.19001
12816.215.97970.22025
12913.67.809625.79038
13018.918.00030.899681
13114.112.78941.31058
13214.511.27343.22662
13316.1514.00362.14637
13414.7513.11311.63691
13514.815.2501-0.450099
13612.4513.4143-0.96426
13712.658.594934.05507
13817.3521.7768-4.42676
1398.62.911355.68865
14018.416.39842.00164
14116.116.7711-0.671138
14211.66.50335.0967
14317.7515.25612.49385
14415.2510.03345.21655
14517.6514.30163.34835
14616.3512.43963.91041
14717.6518.2941-0.644136
14813.612.67210.927902
14914.3513.04751.30254
15014.759.7584.992
15118.2520.7527-2.50268
1529.97.559012.34099
1531611.21544.78465
15418.2514.40523.84482
15516.8515.83711.01289
15614.614.53830.061661
15713.858.821195.02881
15818.9516.06062.88942
15915.614.47731.12271
16014.8515.9683-1.11832
16111.756.397855.35215
16218.4515.73072.71926
16315.912.10423.7958
16417.114.86172.23827
16516.19.750336.34967
16619.921.5633-1.66326
16710.955.073395.87661
16818.4516.27922.17083
16915.113.57011.52992
1701516.6347-1.63471
17111.358.62652.7235
17215.9511.00754.9425
17318.116.24231.85773
17414.612.66951.9305
17515.413.35182.04817
17615.410.32545.07464
17717.617.7395-0.139461
17813.356.890246.45976
17919.116.91192.18806
18015.3519.7994-4.44943
1817.67.327080.27292
18213.412.54960.850405
18313.97.692246.20776
18419.116.76342.33665
18515.2515.16980.0802045
18612.99.971872.92813
18716.111.66914.43086
18817.3517.06150.288531
18913.1513.868-0.718028
19012.1512.4292-0.279159
19112.615.4659-2.8659
19210.357.718012.63199
19315.419.2751-3.8751
1949.64.60484.9952
19518.217.63340.566555
19613.612.6430.957026
19714.8512.76112.08894
19814.7513.81750.932472
19914.112.13321.96682
20014.912.16792.73214
20116.2512.08544.1646
20219.2519.8988-0.648815
20313.613.01530.584702
20413.610.74682.85325
20515.6514.6610.988994
20612.7510.80111.94887
20714.617.7085-3.10853
2089.8510.8254-0.975352
20912.655.607837.04217
21019.214.49324.70676
21116.618.5461-1.94612
21211.29.015152.18485
21315.2516.1367-0.886674
21411.910.38621.51383
21513.29.183884.01612
21616.3517.319-0.968959
21712.49.6562.744
21815.8510.78435.0657
21918.1519.8664-1.71643
22011.158.429422.72058
22115.6510.32115.32894
22217.7522.6504-4.90037
2237.658.8224-1.1724
22412.359.086143.26386
22515.69.06976.5303
22619.316.69332.6067
22715.211.31753.88251
22817.114.32772.77229
22915.610.14175.45835
23018.412.2296.17103
23119.0513.70975.34032
23218.5512.67055.87947
23319.118.5390.561045
23413.112.82540.274584
23512.8516.6121-3.76209
2369.518.4647-8.96472
2374.54.88531-0.385314
23811.8510.71461.1354
23913.616.5755-2.97549
24011.712.5623-0.862328
24112.412.16370.236283
24213.3513.9692-0.619172
24311.49.770441.62956
24414.97.729347.17066
24519.921.5233-1.62334
24611.29.010262.18974
24714.610.72073.87932
24817.616.23021.36985
24914.0510.92853.12154
25016.115.81940.280648
25113.3514.0612-0.71124
25211.8512.5704-0.720417
25311.9510.10581.84422
25414.7512.35272.39734
25515.1514.39140.758597
25613.29.542173.65783
25716.8521.7079-4.85788
2587.8512.3606-4.51057
2597.77.314340.385664
26012.618.3237-5.72366
2617.8510.6416-2.79156
26210.9510.9711-0.0211076
26312.3515.8159-3.46591
2649.958.262031.68797
26514.911.3713.529
26616.6516.7312-0.0812186
26713.412.95210.447942
26813.9510.89713.05293
26915.712.1433.55704
27016.8519.0592-2.20923
27110.958.424292.52571
27215.3516.2116-0.861622
27312.29.966242.23376
27415.110.3434.75698
27517.7515.90861.84137
27615.214.15871.04129
27714.610.49564.10443
27816.6521.0089-4.35891
2798.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.3027 & -0.402664 \tabularnewline
2 & 12.2 & 12.8546 & -0.65459 \tabularnewline
3 & 12.8 & 13.367 & -0.567034 \tabularnewline
4 & 7.4 & 12.9775 & -5.57754 \tabularnewline
5 & 6.7 & 13.4911 & -6.79111 \tabularnewline
6 & 12.6 & 12.8337 & -0.233693 \tabularnewline
7 & 14.8 & 12.7138 & 2.08624 \tabularnewline
8 & 13.3 & 13.4005 & -0.100543 \tabularnewline
9 & 11.1 & 12.7639 & -1.66395 \tabularnewline
10 & 8.2 & 14.8229 & -6.62294 \tabularnewline
11 & 11.4 & 12.8807 & -1.48066 \tabularnewline
12 & 6.4 & 13.526 & -7.12596 \tabularnewline
13 & 10.6 & 12.0017 & -1.40167 \tabularnewline
14 & 12 & 12.7518 & -0.751761 \tabularnewline
15 & 6.3 & 12.6434 & -6.34337 \tabularnewline
16 & 11.3 & 12.7177 & -1.41771 \tabularnewline
17 & 11.9 & 12.8217 & -0.921688 \tabularnewline
18 & 9.3 & 12.8582 & -3.55824 \tabularnewline
19 & 9.6 & 13.3038 & -3.70381 \tabularnewline
20 & 10 & 12.3256 & -2.32562 \tabularnewline
21 & 6.4 & 13.1199 & -6.71993 \tabularnewline
22 & 13.8 & 12.9336 & 0.866445 \tabularnewline
23 & 10.8 & 12.991 & -2.19099 \tabularnewline
24 & 13.8 & 12.2544 & 1.54558 \tabularnewline
25 & 11.7 & 13.1683 & -1.4683 \tabularnewline
26 & 10.9 & 12.7171 & -1.81714 \tabularnewline
27 & 16.1 & 13.0244 & 3.07564 \tabularnewline
28 & 13.4 & 13.2045 & 0.195535 \tabularnewline
29 & 9.9 & 13.1202 & -3.22018 \tabularnewline
30 & 11.5 & 12.54 & -1.04002 \tabularnewline
31 & 8.3 & 12.3413 & -4.04135 \tabularnewline
32 & 11.7 & 13.3146 & -1.61455 \tabularnewline
33 & 9 & 12.6546 & -3.65459 \tabularnewline
34 & 9.7 & 12.5731 & -2.8731 \tabularnewline
35 & 10.8 & 12.6635 & -1.86351 \tabularnewline
36 & 10.3 & 13.0426 & -2.7426 \tabularnewline
37 & 10.4 & 12.479 & -2.07899 \tabularnewline
38 & 12.7 & 13.1778 & -0.477797 \tabularnewline
39 & 9.3 & 13.4859 & -4.18594 \tabularnewline
40 & 11.8 & 12.1422 & -0.342248 \tabularnewline
41 & 5.9 & 13.4934 & -7.59343 \tabularnewline
42 & 11.4 & 13.1472 & -1.74724 \tabularnewline
43 & 13 & 13.2085 & -0.208468 \tabularnewline
44 & 10.8 & 12.1963 & -1.39634 \tabularnewline
45 & 12.3 & 12.7372 & -0.437199 \tabularnewline
46 & 11.3 & 12.8413 & -1.54133 \tabularnewline
47 & 11.8 & 13.3597 & -1.5597 \tabularnewline
48 & 7.9 & 12.9523 & -5.05232 \tabularnewline
49 & 12.7 & 12.1983 & 0.501714 \tabularnewline
50 & 12.3 & 12.9861 & -0.686081 \tabularnewline
51 & 11.6 & 12.4732 & -0.873188 \tabularnewline
52 & 6.7 & 13.0868 & -6.38681 \tabularnewline
53 & 10.9 & 13.2715 & -2.3715 \tabularnewline
54 & 12.1 & 13.1326 & -1.03256 \tabularnewline
55 & 13.3 & 13.5888 & -0.288793 \tabularnewline
56 & 10.1 & 12.7357 & -2.63566 \tabularnewline
57 & 5.7 & 12.4841 & -6.78413 \tabularnewline
58 & 14.3 & 12.5436 & 1.75636 \tabularnewline
59 & 8 & 12.6799 & -4.67993 \tabularnewline
60 & 13.3 & 13.1787 & 0.121327 \tabularnewline
61 & 9.3 & 13.2949 & -3.99489 \tabularnewline
62 & 12.5 & 12.5194 & -0.0193911 \tabularnewline
63 & 7.6 & 11.7009 & -4.10091 \tabularnewline
64 & 15.9 & 13.189 & 2.71101 \tabularnewline
65 & 9.2 & 13.1752 & -3.97525 \tabularnewline
66 & 9.1 & 12.6886 & -3.5886 \tabularnewline
67 & 11.1 & 12.6151 & -1.51505 \tabularnewline
68 & 13 & 13.3787 & -0.3787 \tabularnewline
69 & 14.5 & 12.7692 & 1.73082 \tabularnewline
70 & 12.2 & 12.8449 & -0.644884 \tabularnewline
71 & 12.3 & 13.4367 & -1.1367 \tabularnewline
72 & 11.4 & 12.9882 & -1.58825 \tabularnewline
73 & 8.8 & 13.0861 & -4.28614 \tabularnewline
74 & 14.6 & 13.3522 & 1.24776 \tabularnewline
75 & 12.6 & 11.633 & 0.967017 \tabularnewline
76 & NA & NA & 0.22215 \tabularnewline
77 & 13 & 13.2594 & -0.259407 \tabularnewline
78 & 12.6 & 12.6609 & -0.060891 \tabularnewline
79 & 13.2 & 15.9137 & -2.71371 \tabularnewline
80 & 9.9 & 14.9917 & -5.09169 \tabularnewline
81 & 7.7 & 10.0855 & -2.38554 \tabularnewline
82 & 10.5 & 9.63164 & 0.868365 \tabularnewline
83 & 13.4 & 15.1659 & -1.76593 \tabularnewline
84 & 10.9 & 19.2689 & -8.36887 \tabularnewline
85 & 4.3 & 7.28331 & -2.98331 \tabularnewline
86 & 10.3 & 11.7646 & -1.46455 \tabularnewline
87 & 11.8 & 13.803 & -2.00298 \tabularnewline
88 & 11.2 & 12.0439 & -0.843898 \tabularnewline
89 & 11.4 & 15.4322 & -4.03218 \tabularnewline
90 & 8.6 & 7.72718 & 0.872822 \tabularnewline
91 & 13.2 & 13.7366 & -0.536624 \tabularnewline
92 & 12.6 & 19.4427 & -6.84266 \tabularnewline
93 & 5.6 & 9.016 & -3.416 \tabularnewline
94 & 9.9 & 13.5715 & -3.67154 \tabularnewline
95 & 8.8 & 14.2072 & -5.40721 \tabularnewline
96 & 7.7 & 11.726 & -4.02595 \tabularnewline
97 & 9 & 14.7427 & -5.74273 \tabularnewline
98 & 7.3 & 8.45314 & -1.15314 \tabularnewline
99 & 11.4 & 10.1407 & 1.25931 \tabularnewline
100 & 13.6 & 18.0991 & -4.49913 \tabularnewline
101 & 7.9 & 10.2178 & -2.31775 \tabularnewline
102 & 10.7 & 13.1151 & -2.41506 \tabularnewline
103 & 10.3 & 13.9473 & -3.64734 \tabularnewline
104 & 8.3 & 11.6517 & -3.35169 \tabularnewline
105 & 9.6 & 8.24035 & 1.35965 \tabularnewline
106 & 14.2 & 18.9547 & -4.75467 \tabularnewline
107 & 8.5 & 7.98893 & 0.511074 \tabularnewline
108 & 13.5 & 21.1389 & -7.63887 \tabularnewline
109 & 4.9 & 11.461 & -6.56096 \tabularnewline
110 & 6.4 & 9.81372 & -3.41372 \tabularnewline
111 & 9.6 & 10.9858 & -1.38579 \tabularnewline
112 & 11.6 & 12.9501 & -1.35006 \tabularnewline
113 & 11.1 & 20.7995 & -9.69946 \tabularnewline
114 & 4.35 & 4.75345 & -0.40345 \tabularnewline
115 & 12.7 & 7.41517 & 5.28483 \tabularnewline
116 & 18.1 & 13.1859 & 4.91413 \tabularnewline
117 & 17.85 & 14.7271 & 3.12292 \tabularnewline
118 & 16.6 & 17.3089 & -0.708909 \tabularnewline
119 & 12.6 & 9.00099 & 3.59901 \tabularnewline
120 & 17.1 & 11.2718 & 5.82816 \tabularnewline
121 & 19.1 & 16.1463 & 2.95374 \tabularnewline
122 & 16.1 & 15.46 & 0.639986 \tabularnewline
123 & 13.35 & 8.48346 & 4.86654 \tabularnewline
124 & 18.4 & 16.3775 & 2.02255 \tabularnewline
125 & 14.7 & 17.2927 & -2.59271 \tabularnewline
126 & 10.6 & 11.0145 & -0.414521 \tabularnewline
127 & 12.6 & 9.40999 & 3.19001 \tabularnewline
128 & 16.2 & 15.9797 & 0.22025 \tabularnewline
129 & 13.6 & 7.80962 & 5.79038 \tabularnewline
130 & 18.9 & 18.0003 & 0.899681 \tabularnewline
131 & 14.1 & 12.7894 & 1.31058 \tabularnewline
132 & 14.5 & 11.2734 & 3.22662 \tabularnewline
133 & 16.15 & 14.0036 & 2.14637 \tabularnewline
134 & 14.75 & 13.1131 & 1.63691 \tabularnewline
135 & 14.8 & 15.2501 & -0.450099 \tabularnewline
136 & 12.45 & 13.4143 & -0.96426 \tabularnewline
137 & 12.65 & 8.59493 & 4.05507 \tabularnewline
138 & 17.35 & 21.7768 & -4.42676 \tabularnewline
139 & 8.6 & 2.91135 & 5.68865 \tabularnewline
140 & 18.4 & 16.3984 & 2.00164 \tabularnewline
141 & 16.1 & 16.7711 & -0.671138 \tabularnewline
142 & 11.6 & 6.5033 & 5.0967 \tabularnewline
143 & 17.75 & 15.2561 & 2.49385 \tabularnewline
144 & 15.25 & 10.0334 & 5.21655 \tabularnewline
145 & 17.65 & 14.3016 & 3.34835 \tabularnewline
146 & 16.35 & 12.4396 & 3.91041 \tabularnewline
147 & 17.65 & 18.2941 & -0.644136 \tabularnewline
148 & 13.6 & 12.6721 & 0.927902 \tabularnewline
149 & 14.35 & 13.0475 & 1.30254 \tabularnewline
150 & 14.75 & 9.758 & 4.992 \tabularnewline
151 & 18.25 & 20.7527 & -2.50268 \tabularnewline
152 & 9.9 & 7.55901 & 2.34099 \tabularnewline
153 & 16 & 11.2154 & 4.78465 \tabularnewline
154 & 18.25 & 14.4052 & 3.84482 \tabularnewline
155 & 16.85 & 15.8371 & 1.01289 \tabularnewline
156 & 14.6 & 14.5383 & 0.061661 \tabularnewline
157 & 13.85 & 8.82119 & 5.02881 \tabularnewline
158 & 18.95 & 16.0606 & 2.88942 \tabularnewline
159 & 15.6 & 14.4773 & 1.12271 \tabularnewline
160 & 14.85 & 15.9683 & -1.11832 \tabularnewline
161 & 11.75 & 6.39785 & 5.35215 \tabularnewline
162 & 18.45 & 15.7307 & 2.71926 \tabularnewline
163 & 15.9 & 12.1042 & 3.7958 \tabularnewline
164 & 17.1 & 14.8617 & 2.23827 \tabularnewline
165 & 16.1 & 9.75033 & 6.34967 \tabularnewline
166 & 19.9 & 21.5633 & -1.66326 \tabularnewline
167 & 10.95 & 5.07339 & 5.87661 \tabularnewline
168 & 18.45 & 16.2792 & 2.17083 \tabularnewline
169 & 15.1 & 13.5701 & 1.52992 \tabularnewline
170 & 15 & 16.6347 & -1.63471 \tabularnewline
171 & 11.35 & 8.6265 & 2.7235 \tabularnewline
172 & 15.95 & 11.0075 & 4.9425 \tabularnewline
173 & 18.1 & 16.2423 & 1.85773 \tabularnewline
174 & 14.6 & 12.6695 & 1.9305 \tabularnewline
175 & 15.4 & 13.3518 & 2.04817 \tabularnewline
176 & 15.4 & 10.3254 & 5.07464 \tabularnewline
177 & 17.6 & 17.7395 & -0.139461 \tabularnewline
178 & 13.35 & 6.89024 & 6.45976 \tabularnewline
179 & 19.1 & 16.9119 & 2.18806 \tabularnewline
180 & 15.35 & 19.7994 & -4.44943 \tabularnewline
181 & 7.6 & 7.32708 & 0.27292 \tabularnewline
182 & 13.4 & 12.5496 & 0.850405 \tabularnewline
183 & 13.9 & 7.69224 & 6.20776 \tabularnewline
184 & 19.1 & 16.7634 & 2.33665 \tabularnewline
185 & 15.25 & 15.1698 & 0.0802045 \tabularnewline
186 & 12.9 & 9.97187 & 2.92813 \tabularnewline
187 & 16.1 & 11.6691 & 4.43086 \tabularnewline
188 & 17.35 & 17.0615 & 0.288531 \tabularnewline
189 & 13.15 & 13.868 & -0.718028 \tabularnewline
190 & 12.15 & 12.4292 & -0.279159 \tabularnewline
191 & 12.6 & 15.4659 & -2.8659 \tabularnewline
192 & 10.35 & 7.71801 & 2.63199 \tabularnewline
193 & 15.4 & 19.2751 & -3.8751 \tabularnewline
194 & 9.6 & 4.6048 & 4.9952 \tabularnewline
195 & 18.2 & 17.6334 & 0.566555 \tabularnewline
196 & 13.6 & 12.643 & 0.957026 \tabularnewline
197 & 14.85 & 12.7611 & 2.08894 \tabularnewline
198 & 14.75 & 13.8175 & 0.932472 \tabularnewline
199 & 14.1 & 12.1332 & 1.96682 \tabularnewline
200 & 14.9 & 12.1679 & 2.73214 \tabularnewline
201 & 16.25 & 12.0854 & 4.1646 \tabularnewline
202 & 19.25 & 19.8988 & -0.648815 \tabularnewline
203 & 13.6 & 13.0153 & 0.584702 \tabularnewline
204 & 13.6 & 10.7468 & 2.85325 \tabularnewline
205 & 15.65 & 14.661 & 0.988994 \tabularnewline
206 & 12.75 & 10.8011 & 1.94887 \tabularnewline
207 & 14.6 & 17.7085 & -3.10853 \tabularnewline
208 & 9.85 & 10.8254 & -0.975352 \tabularnewline
209 & 12.65 & 5.60783 & 7.04217 \tabularnewline
210 & 19.2 & 14.4932 & 4.70676 \tabularnewline
211 & 16.6 & 18.5461 & -1.94612 \tabularnewline
212 & 11.2 & 9.01515 & 2.18485 \tabularnewline
213 & 15.25 & 16.1367 & -0.886674 \tabularnewline
214 & 11.9 & 10.3862 & 1.51383 \tabularnewline
215 & 13.2 & 9.18388 & 4.01612 \tabularnewline
216 & 16.35 & 17.319 & -0.968959 \tabularnewline
217 & 12.4 & 9.656 & 2.744 \tabularnewline
218 & 15.85 & 10.7843 & 5.0657 \tabularnewline
219 & 18.15 & 19.8664 & -1.71643 \tabularnewline
220 & 11.15 & 8.42942 & 2.72058 \tabularnewline
221 & 15.65 & 10.3211 & 5.32894 \tabularnewline
222 & 17.75 & 22.6504 & -4.90037 \tabularnewline
223 & 7.65 & 8.8224 & -1.1724 \tabularnewline
224 & 12.35 & 9.08614 & 3.26386 \tabularnewline
225 & 15.6 & 9.0697 & 6.5303 \tabularnewline
226 & 19.3 & 16.6933 & 2.6067 \tabularnewline
227 & 15.2 & 11.3175 & 3.88251 \tabularnewline
228 & 17.1 & 14.3277 & 2.77229 \tabularnewline
229 & 15.6 & 10.1417 & 5.45835 \tabularnewline
230 & 18.4 & 12.229 & 6.17103 \tabularnewline
231 & 19.05 & 13.7097 & 5.34032 \tabularnewline
232 & 18.55 & 12.6705 & 5.87947 \tabularnewline
233 & 19.1 & 18.539 & 0.561045 \tabularnewline
234 & 13.1 & 12.8254 & 0.274584 \tabularnewline
235 & 12.85 & 16.6121 & -3.76209 \tabularnewline
236 & 9.5 & 18.4647 & -8.96472 \tabularnewline
237 & 4.5 & 4.88531 & -0.385314 \tabularnewline
238 & 11.85 & 10.7146 & 1.1354 \tabularnewline
239 & 13.6 & 16.5755 & -2.97549 \tabularnewline
240 & 11.7 & 12.5623 & -0.862328 \tabularnewline
241 & 12.4 & 12.1637 & 0.236283 \tabularnewline
242 & 13.35 & 13.9692 & -0.619172 \tabularnewline
243 & 11.4 & 9.77044 & 1.62956 \tabularnewline
244 & 14.9 & 7.72934 & 7.17066 \tabularnewline
245 & 19.9 & 21.5233 & -1.62334 \tabularnewline
246 & 11.2 & 9.01026 & 2.18974 \tabularnewline
247 & 14.6 & 10.7207 & 3.87932 \tabularnewline
248 & 17.6 & 16.2302 & 1.36985 \tabularnewline
249 & 14.05 & 10.9285 & 3.12154 \tabularnewline
250 & 16.1 & 15.8194 & 0.280648 \tabularnewline
251 & 13.35 & 14.0612 & -0.71124 \tabularnewline
252 & 11.85 & 12.5704 & -0.720417 \tabularnewline
253 & 11.95 & 10.1058 & 1.84422 \tabularnewline
254 & 14.75 & 12.3527 & 2.39734 \tabularnewline
255 & 15.15 & 14.3914 & 0.758597 \tabularnewline
256 & 13.2 & 9.54217 & 3.65783 \tabularnewline
257 & 16.85 & 21.7079 & -4.85788 \tabularnewline
258 & 7.85 & 12.3606 & -4.51057 \tabularnewline
259 & 7.7 & 7.31434 & 0.385664 \tabularnewline
260 & 12.6 & 18.3237 & -5.72366 \tabularnewline
261 & 7.85 & 10.6416 & -2.79156 \tabularnewline
262 & 10.95 & 10.9711 & -0.0211076 \tabularnewline
263 & 12.35 & 15.8159 & -3.46591 \tabularnewline
264 & 9.95 & 8.26203 & 1.68797 \tabularnewline
265 & 14.9 & 11.371 & 3.529 \tabularnewline
266 & 16.65 & 16.7312 & -0.0812186 \tabularnewline
267 & 13.4 & 12.9521 & 0.447942 \tabularnewline
268 & 13.95 & 10.8971 & 3.05293 \tabularnewline
269 & 15.7 & 12.143 & 3.55704 \tabularnewline
270 & 16.85 & 19.0592 & -2.20923 \tabularnewline
271 & 10.95 & 8.42429 & 2.52571 \tabularnewline
272 & 15.35 & 16.2116 & -0.861622 \tabularnewline
273 & 12.2 & 9.96624 & 2.23376 \tabularnewline
274 & 15.1 & 10.343 & 4.75698 \tabularnewline
275 & 17.75 & 15.9086 & 1.84137 \tabularnewline
276 & 15.2 & 14.1587 & 1.04129 \tabularnewline
277 & 14.6 & 10.4956 & 4.10443 \tabularnewline
278 & 16.65 & 21.0089 & -4.35891 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263940&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]12.9[/C][C]13.3027[/C][C]-0.402664[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]12.8546[/C][C]-0.65459[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]13.367[/C][C]-0.567034[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]12.9775[/C][C]-5.57754[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]13.4911[/C][C]-6.79111[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]12.8337[/C][C]-0.233693[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.7138[/C][C]2.08624[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]13.4005[/C][C]-0.100543[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.7639[/C][C]-1.66395[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.8229[/C][C]-6.62294[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]12.8807[/C][C]-1.48066[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]13.526[/C][C]-7.12596[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]12.0017[/C][C]-1.40167[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]12.7518[/C][C]-0.751761[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]12.6434[/C][C]-6.34337[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]12.7177[/C][C]-1.41771[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]12.8217[/C][C]-0.921688[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.8582[/C][C]-3.55824[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]13.3038[/C][C]-3.70381[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]12.3256[/C][C]-2.32562[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]13.1199[/C][C]-6.71993[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.9336[/C][C]0.866445[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]12.991[/C][C]-2.19099[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.2544[/C][C]1.54558[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]13.1683[/C][C]-1.4683[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.7171[/C][C]-1.81714[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.0244[/C][C]3.07564[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]13.2045[/C][C]0.195535[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]13.1202[/C][C]-3.22018[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]12.54[/C][C]-1.04002[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]12.3413[/C][C]-4.04135[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.3146[/C][C]-1.61455[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.6546[/C][C]-3.65459[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]12.5731[/C][C]-2.8731[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.6635[/C][C]-1.86351[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]13.0426[/C][C]-2.7426[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]12.479[/C][C]-2.07899[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]13.1778[/C][C]-0.477797[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]13.4859[/C][C]-4.18594[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.1422[/C][C]-0.342248[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]13.4934[/C][C]-7.59343[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.1472[/C][C]-1.74724[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]13.2085[/C][C]-0.208468[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]12.1963[/C][C]-1.39634[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]12.7372[/C][C]-0.437199[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]12.8413[/C][C]-1.54133[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]13.3597[/C][C]-1.5597[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]12.9523[/C][C]-5.05232[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]12.1983[/C][C]0.501714[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]12.9861[/C][C]-0.686081[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]12.4732[/C][C]-0.873188[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]13.0868[/C][C]-6.38681[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.2715[/C][C]-2.3715[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]13.1326[/C][C]-1.03256[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.5888[/C][C]-0.288793[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]12.7357[/C][C]-2.63566[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]12.4841[/C][C]-6.78413[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.5436[/C][C]1.75636[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]12.6799[/C][C]-4.67993[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]13.1787[/C][C]0.121327[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]13.2949[/C][C]-3.99489[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]12.5194[/C][C]-0.0193911[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]11.7009[/C][C]-4.10091[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.189[/C][C]2.71101[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.1752[/C][C]-3.97525[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]12.6886[/C][C]-3.5886[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.6151[/C][C]-1.51505[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.3787[/C][C]-0.3787[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]12.7692[/C][C]1.73082[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.8449[/C][C]-0.644884[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.4367[/C][C]-1.1367[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]12.9882[/C][C]-1.58825[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]13.0861[/C][C]-4.28614[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]13.3522[/C][C]1.24776[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]11.633[/C][C]0.967017[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]0.22215[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]13.2594[/C][C]-0.259407[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]12.6609[/C][C]-0.060891[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]15.9137[/C][C]-2.71371[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]14.9917[/C][C]-5.09169[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]10.0855[/C][C]-2.38554[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]9.63164[/C][C]0.868365[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]15.1659[/C][C]-1.76593[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]19.2689[/C][C]-8.36887[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]7.28331[/C][C]-2.98331[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]11.7646[/C][C]-1.46455[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]13.803[/C][C]-2.00298[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]12.0439[/C][C]-0.843898[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]15.4322[/C][C]-4.03218[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]7.72718[/C][C]0.872822[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]13.7366[/C][C]-0.536624[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]19.4427[/C][C]-6.84266[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]9.016[/C][C]-3.416[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]13.5715[/C][C]-3.67154[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]14.2072[/C][C]-5.40721[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]11.726[/C][C]-4.02595[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]14.7427[/C][C]-5.74273[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]8.45314[/C][C]-1.15314[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]10.1407[/C][C]1.25931[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]18.0991[/C][C]-4.49913[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]10.2178[/C][C]-2.31775[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]13.1151[/C][C]-2.41506[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]13.9473[/C][C]-3.64734[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]11.6517[/C][C]-3.35169[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]8.24035[/C][C]1.35965[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]18.9547[/C][C]-4.75467[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]7.98893[/C][C]0.511074[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]21.1389[/C][C]-7.63887[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]11.461[/C][C]-6.56096[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]9.81372[/C][C]-3.41372[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]10.9858[/C][C]-1.38579[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]12.9501[/C][C]-1.35006[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]20.7995[/C][C]-9.69946[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]4.75345[/C][C]-0.40345[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]7.41517[/C][C]5.28483[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]13.1859[/C][C]4.91413[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]14.7271[/C][C]3.12292[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]17.3089[/C][C]-0.708909[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]9.00099[/C][C]3.59901[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]11.2718[/C][C]5.82816[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]16.1463[/C][C]2.95374[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]15.46[/C][C]0.639986[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]8.48346[/C][C]4.86654[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]16.3775[/C][C]2.02255[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.2927[/C][C]-2.59271[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]11.0145[/C][C]-0.414521[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]9.40999[/C][C]3.19001[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]15.9797[/C][C]0.22025[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]7.80962[/C][C]5.79038[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]18.0003[/C][C]0.899681[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]12.7894[/C][C]1.31058[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]11.2734[/C][C]3.22662[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]14.0036[/C][C]2.14637[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]13.1131[/C][C]1.63691[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]15.2501[/C][C]-0.450099[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]13.4143[/C][C]-0.96426[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]8.59493[/C][C]4.05507[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]21.7768[/C][C]-4.42676[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]2.91135[/C][C]5.68865[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]16.3984[/C][C]2.00164[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]16.7711[/C][C]-0.671138[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]6.5033[/C][C]5.0967[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]15.2561[/C][C]2.49385[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]10.0334[/C][C]5.21655[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]14.3016[/C][C]3.34835[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]12.4396[/C][C]3.91041[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]18.2941[/C][C]-0.644136[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.6721[/C][C]0.927902[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]13.0475[/C][C]1.30254[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]9.758[/C][C]4.992[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]20.7527[/C][C]-2.50268[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]7.55901[/C][C]2.34099[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.2154[/C][C]4.78465[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]14.4052[/C][C]3.84482[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]15.8371[/C][C]1.01289[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]14.5383[/C][C]0.061661[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]8.82119[/C][C]5.02881[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]16.0606[/C][C]2.88942[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]14.4773[/C][C]1.12271[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]15.9683[/C][C]-1.11832[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]6.39785[/C][C]5.35215[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]15.7307[/C][C]2.71926[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]12.1042[/C][C]3.7958[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]14.8617[/C][C]2.23827[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]9.75033[/C][C]6.34967[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]21.5633[/C][C]-1.66326[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]5.07339[/C][C]5.87661[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]16.2792[/C][C]2.17083[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]13.5701[/C][C]1.52992[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]16.6347[/C][C]-1.63471[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]8.6265[/C][C]2.7235[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]11.0075[/C][C]4.9425[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]16.2423[/C][C]1.85773[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]12.6695[/C][C]1.9305[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]13.3518[/C][C]2.04817[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]10.3254[/C][C]5.07464[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]17.7395[/C][C]-0.139461[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]6.89024[/C][C]6.45976[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]16.9119[/C][C]2.18806[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]19.7994[/C][C]-4.44943[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]7.32708[/C][C]0.27292[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]12.5496[/C][C]0.850405[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]7.69224[/C][C]6.20776[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]16.7634[/C][C]2.33665[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]15.1698[/C][C]0.0802045[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]9.97187[/C][C]2.92813[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]11.6691[/C][C]4.43086[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]17.0615[/C][C]0.288531[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]13.868[/C][C]-0.718028[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]12.4292[/C][C]-0.279159[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]15.4659[/C][C]-2.8659[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]7.71801[/C][C]2.63199[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]19.2751[/C][C]-3.8751[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]4.6048[/C][C]4.9952[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]17.6334[/C][C]0.566555[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]12.643[/C][C]0.957026[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]12.7611[/C][C]2.08894[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]13.8175[/C][C]0.932472[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]12.1332[/C][C]1.96682[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]12.1679[/C][C]2.73214[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]12.0854[/C][C]4.1646[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]19.8988[/C][C]-0.648815[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]13.0153[/C][C]0.584702[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]10.7468[/C][C]2.85325[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]14.661[/C][C]0.988994[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]10.8011[/C][C]1.94887[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]17.7085[/C][C]-3.10853[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]10.8254[/C][C]-0.975352[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]5.60783[/C][C]7.04217[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]14.4932[/C][C]4.70676[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]18.5461[/C][C]-1.94612[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]9.01515[/C][C]2.18485[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]16.1367[/C][C]-0.886674[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]10.3862[/C][C]1.51383[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]9.18388[/C][C]4.01612[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]17.319[/C][C]-0.968959[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]9.656[/C][C]2.744[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]10.7843[/C][C]5.0657[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]19.8664[/C][C]-1.71643[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]8.42942[/C][C]2.72058[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]10.3211[/C][C]5.32894[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]22.6504[/C][C]-4.90037[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]8.8224[/C][C]-1.1724[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]9.08614[/C][C]3.26386[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]9.0697[/C][C]6.5303[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]16.6933[/C][C]2.6067[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]11.3175[/C][C]3.88251[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]14.3277[/C][C]2.77229[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]10.1417[/C][C]5.45835[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]12.229[/C][C]6.17103[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]13.7097[/C][C]5.34032[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]12.6705[/C][C]5.87947[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]18.539[/C][C]0.561045[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]12.8254[/C][C]0.274584[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]16.6121[/C][C]-3.76209[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]18.4647[/C][C]-8.96472[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]4.88531[/C][C]-0.385314[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]10.7146[/C][C]1.1354[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]16.5755[/C][C]-2.97549[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]12.5623[/C][C]-0.862328[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]12.1637[/C][C]0.236283[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]13.9692[/C][C]-0.619172[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]9.77044[/C][C]1.62956[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]7.72934[/C][C]7.17066[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]21.5233[/C][C]-1.62334[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]9.01026[/C][C]2.18974[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]10.7207[/C][C]3.87932[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]16.2302[/C][C]1.36985[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]10.9285[/C][C]3.12154[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]15.8194[/C][C]0.280648[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]14.0612[/C][C]-0.71124[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]12.5704[/C][C]-0.720417[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]10.1058[/C][C]1.84422[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]12.3527[/C][C]2.39734[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]14.3914[/C][C]0.758597[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]9.54217[/C][C]3.65783[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]21.7079[/C][C]-4.85788[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]12.3606[/C][C]-4.51057[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]7.31434[/C][C]0.385664[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]18.3237[/C][C]-5.72366[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]10.6416[/C][C]-2.79156[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]10.9711[/C][C]-0.0211076[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]15.8159[/C][C]-3.46591[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]8.26203[/C][C]1.68797[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]11.371[/C][C]3.529[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.7312[/C][C]-0.0812186[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]12.9521[/C][C]0.447942[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]10.8971[/C][C]3.05293[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]12.143[/C][C]3.55704[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]19.0592[/C][C]-2.20923[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]8.42429[/C][C]2.52571[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]16.2116[/C][C]-0.861622[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]9.96624[/C][C]2.23376[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]10.343[/C][C]4.75698[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]15.9086[/C][C]1.84137[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]14.1587[/C][C]1.04129[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]10.4956[/C][C]4.10443[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]21.0089[/C][C]-4.35891[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263940&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263940&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
112.913.3027-0.402664
212.212.8546-0.65459
312.813.367-0.567034
47.412.9775-5.57754
56.713.4911-6.79111
612.612.8337-0.233693
714.812.71382.08624
813.313.4005-0.100543
911.112.7639-1.66395
108.214.8229-6.62294
1111.412.8807-1.48066
126.413.526-7.12596
1310.612.0017-1.40167
141212.7518-0.751761
156.312.6434-6.34337
1611.312.7177-1.41771
1711.912.8217-0.921688
189.312.8582-3.55824
199.613.3038-3.70381
201012.3256-2.32562
216.413.1199-6.71993
2213.812.93360.866445
2310.812.991-2.19099
2413.812.25441.54558
2511.713.1683-1.4683
2610.912.7171-1.81714
2716.113.02443.07564
2813.413.20450.195535
299.913.1202-3.22018
3011.512.54-1.04002
318.312.3413-4.04135
3211.713.3146-1.61455
33912.6546-3.65459
349.712.5731-2.8731
3510.812.6635-1.86351
3610.313.0426-2.7426
3710.412.479-2.07899
3812.713.1778-0.477797
399.313.4859-4.18594
4011.812.1422-0.342248
415.913.4934-7.59343
4211.413.1472-1.74724
431313.2085-0.208468
4410.812.1963-1.39634
4512.312.7372-0.437199
4611.312.8413-1.54133
4711.813.3597-1.5597
487.912.9523-5.05232
4912.712.19830.501714
5012.312.9861-0.686081
5111.612.4732-0.873188
526.713.0868-6.38681
5310.913.2715-2.3715
5412.113.1326-1.03256
5513.313.5888-0.288793
5610.112.7357-2.63566
575.712.4841-6.78413
5814.312.54361.75636
59812.6799-4.67993
6013.313.17870.121327
619.313.2949-3.99489
6212.512.5194-0.0193911
637.611.7009-4.10091
6415.913.1892.71101
659.213.1752-3.97525
669.112.6886-3.5886
6711.112.6151-1.51505
681313.3787-0.3787
6914.512.76921.73082
7012.212.8449-0.644884
7112.313.4367-1.1367
7211.412.9882-1.58825
738.813.0861-4.28614
7414.613.35221.24776
7512.611.6330.967017
76NANA0.22215
771313.2594-0.259407
7812.612.6609-0.060891
7913.215.9137-2.71371
809.914.9917-5.09169
817.710.0855-2.38554
8210.59.631640.868365
8313.415.1659-1.76593
8410.919.2689-8.36887
854.37.28331-2.98331
8610.311.7646-1.46455
8711.813.803-2.00298
8811.212.0439-0.843898
8911.415.4322-4.03218
908.67.727180.872822
9113.213.7366-0.536624
9212.619.4427-6.84266
935.69.016-3.416
949.913.5715-3.67154
958.814.2072-5.40721
967.711.726-4.02595
97914.7427-5.74273
987.38.45314-1.15314
9911.410.14071.25931
10013.618.0991-4.49913
1017.910.2178-2.31775
10210.713.1151-2.41506
10310.313.9473-3.64734
1048.311.6517-3.35169
1059.68.240351.35965
10614.218.9547-4.75467
1078.57.988930.511074
10813.521.1389-7.63887
1094.911.461-6.56096
1106.49.81372-3.41372
1119.610.9858-1.38579
11211.612.9501-1.35006
11311.120.7995-9.69946
1144.354.75345-0.40345
11512.77.415175.28483
11618.113.18594.91413
11717.8514.72713.12292
11816.617.3089-0.708909
11912.69.000993.59901
12017.111.27185.82816
12119.116.14632.95374
12216.115.460.639986
12313.358.483464.86654
12418.416.37752.02255
12514.717.2927-2.59271
12610.611.0145-0.414521
12712.69.409993.19001
12816.215.97970.22025
12913.67.809625.79038
13018.918.00030.899681
13114.112.78941.31058
13214.511.27343.22662
13316.1514.00362.14637
13414.7513.11311.63691
13514.815.2501-0.450099
13612.4513.4143-0.96426
13712.658.594934.05507
13817.3521.7768-4.42676
1398.62.911355.68865
14018.416.39842.00164
14116.116.7711-0.671138
14211.66.50335.0967
14317.7515.25612.49385
14415.2510.03345.21655
14517.6514.30163.34835
14616.3512.43963.91041
14717.6518.2941-0.644136
14813.612.67210.927902
14914.3513.04751.30254
15014.759.7584.992
15118.2520.7527-2.50268
1529.97.559012.34099
1531611.21544.78465
15418.2514.40523.84482
15516.8515.83711.01289
15614.614.53830.061661
15713.858.821195.02881
15818.9516.06062.88942
15915.614.47731.12271
16014.8515.9683-1.11832
16111.756.397855.35215
16218.4515.73072.71926
16315.912.10423.7958
16417.114.86172.23827
16516.19.750336.34967
16619.921.5633-1.66326
16710.955.073395.87661
16818.4516.27922.17083
16915.113.57011.52992
1701516.6347-1.63471
17111.358.62652.7235
17215.9511.00754.9425
17318.116.24231.85773
17414.612.66951.9305
17515.413.35182.04817
17615.410.32545.07464
17717.617.7395-0.139461
17813.356.890246.45976
17919.116.91192.18806
18015.3519.7994-4.44943
1817.67.327080.27292
18213.412.54960.850405
18313.97.692246.20776
18419.116.76342.33665
18515.2515.16980.0802045
18612.99.971872.92813
18716.111.66914.43086
18817.3517.06150.288531
18913.1513.868-0.718028
19012.1512.4292-0.279159
19112.615.4659-2.8659
19210.357.718012.63199
19315.419.2751-3.8751
1949.64.60484.9952
19518.217.63340.566555
19613.612.6430.957026
19714.8512.76112.08894
19814.7513.81750.932472
19914.112.13321.96682
20014.912.16792.73214
20116.2512.08544.1646
20219.2519.8988-0.648815
20313.613.01530.584702
20413.610.74682.85325
20515.6514.6610.988994
20612.7510.80111.94887
20714.617.7085-3.10853
2089.8510.8254-0.975352
20912.655.607837.04217
21019.214.49324.70676
21116.618.5461-1.94612
21211.29.015152.18485
21315.2516.1367-0.886674
21411.910.38621.51383
21513.29.183884.01612
21616.3517.319-0.968959
21712.49.6562.744
21815.8510.78435.0657
21918.1519.8664-1.71643
22011.158.429422.72058
22115.6510.32115.32894
22217.7522.6504-4.90037
2237.658.8224-1.1724
22412.359.086143.26386
22515.69.06976.5303
22619.316.69332.6067
22715.211.31753.88251
22817.114.32772.77229
22915.610.14175.45835
23018.412.2296.17103
23119.0513.70975.34032
23218.5512.67055.87947
23319.118.5390.561045
23413.112.82540.274584
23512.8516.6121-3.76209
2369.518.4647-8.96472
2374.54.88531-0.385314
23811.8510.71461.1354
23913.616.5755-2.97549
24011.712.5623-0.862328
24112.412.16370.236283
24213.3513.9692-0.619172
24311.49.770441.62956
24414.97.729347.17066
24519.921.5233-1.62334
24611.29.010262.18974
24714.610.72073.87932
24817.616.23021.36985
24914.0510.92853.12154
25016.115.81940.280648
25113.3514.0612-0.71124
25211.8512.5704-0.720417
25311.9510.10581.84422
25414.7512.35272.39734
25515.1514.39140.758597
25613.29.542173.65783
25716.8521.7079-4.85788
2587.8512.3606-4.51057
2597.77.314340.385664
26012.618.3237-5.72366
2617.8510.6416-2.79156
26210.9510.9711-0.0211076
26312.3515.8159-3.46591
2649.958.262031.68797
26514.911.3713.529
26616.6516.7312-0.0812186
26713.412.95210.447942
26813.9510.89713.05293
26915.712.1433.55704
27016.8519.0592-2.20923
27110.958.424292.52571
27215.3516.2116-0.861622
27312.29.966242.23376
27415.110.3434.75698
27517.7515.90861.84137
27615.214.15871.04129
27714.610.49564.10443
27816.6521.0089-4.35891
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.4039920.8079830.596008
100.40190.8037990.5981
110.264850.5297010.73515
120.2676510.5353010.732349
130.2586080.5172160.741392
140.1974480.3948960.802552
150.1842970.3685940.815703
160.1423560.2847110.857644
170.09320460.1864090.906795
180.06271010.125420.93729
190.03960630.07921250.960394
200.02392450.04784910.976075
210.03209370.06418730.967906
220.03010570.06021140.969894
230.01938140.03876280.980619
240.0195860.0391720.980414
250.01347220.02694440.986528
260.008286320.01657260.991714
270.02700150.05400310.972998
280.0177570.0355140.982243
290.01193860.02387720.988061
300.007632180.01526440.992368
310.02144240.04288480.978558
320.01645650.03291290.983544
330.01549390.03098790.984506
340.01203170.02406350.987968
350.008449950.01689990.99155
360.005706590.01141320.994293
370.003744130.007488270.996256
380.002493780.004987560.997506
390.001952730.003905460.998047
400.00127340.00254680.998727
410.002865350.005730710.997135
420.002079230.004158460.997921
430.002199670.004399350.9978
440.001441620.002883250.998558
450.0009147220.001829440.999085
460.0006312250.001262450.999369
470.0004186580.0008373160.999581
480.0003728640.0007457270.999627
490.0002902620.0005805240.99971
500.0002255020.0004510040.999774
510.0001490860.0002981710.999851
520.0005788630.001157730.999421
530.0004034120.0008068240.999597
540.0003836230.0007672450.999616
550.0005500940.001100190.99945
560.0003783970.0007567940.999622
570.001588430.003176860.998412
580.001124210.002248420.998876
590.001282830.002565660.998717
600.001337610.002675210.998662
610.001061930.002123860.998938
620.000793940.001587880.999206
630.00230130.004602590.997699
640.004245180.008490360.995755
650.003814390.007628780.996186
660.003699960.007399920.9963
670.002713220.005426430.997287
680.002480110.004960210.99752
690.002845830.005691650.997154
700.002130090.004260190.99787
710.001593630.003187270.998406
720.001168170.002336350.998832
730.001138470.002276940.998862
740.001392870.002785750.998607
750.00110410.00220820.998896
760.0008876120.001775220.999112
770.0006447940.001289590.999355
780.0005747560.001149510.999425
790.0004525140.0009050280.999547
800.0005909010.00118180.999409
810.0004482270.0008964550.999552
820.0003951780.0007903550.999605
830.0002860670.0005721340.999714
840.001747450.003494890.998253
850.001414640.002829280.998585
860.001095810.002191620.998904
870.0008444860.001688970.999156
880.0006423340.001284670.999358
890.0006966040.001393210.999303
900.0005644480.00112890.999436
910.0004723150.0009446310.999528
920.001490250.00298050.99851
930.001283680.002567360.998716
940.001232830.002465650.998767
950.00180620.00361240.998194
960.001824550.00364910.998175
970.002800330.005600650.9972
980.002193610.004387220.997806
990.001832880.003665760.998167
1000.00245190.00490380.997548
1010.002043080.004086170.997957
1020.001734510.003469010.998265
1030.002159370.004318730.997841
1040.002026640.004053290.997973
1050.002103980.004207970.997896
1060.002472260.004944510.997528
1070.002237660.004475330.997762
1080.008529340.01705870.991471
1090.01852440.03704880.981476
1100.01984390.03968780.980156
1110.01757690.03515380.982423
1120.01663710.03327430.983363
1130.0720160.1440320.927984
1140.0655720.1311440.934428
1150.1306180.2612350.869382
1160.2106570.4213130.789343
1170.2623090.5246170.737691
1180.2413850.4827710.758615
1190.2893910.5787820.710609
1200.4297390.8594770.570261
1210.4681420.9362850.531858
1220.4415170.8830350.558483
1230.5106940.9786130.489306
1240.5054470.9891070.494553
1250.5030550.993890.496945
1260.4746630.9493260.525337
1270.5105030.9789950.489497
1280.4852770.9705530.514723
1290.6065620.7868760.393438
1300.5849290.8301430.415071
1310.5674680.8650640.432532
1320.5828790.8342410.417121
1330.5814360.8371280.418564
1340.5754420.8491170.424558
1350.5468840.9062320.453116
1360.5251180.9497640.474882
1370.5625410.8749180.437459
1380.6000620.7998760.399938
1390.6830490.6339020.316951
1400.6752840.6494330.324716
1410.6494050.701190.350595
1420.698020.6039610.30198
1430.6909040.6181920.309096
1440.7437820.5124370.256218
1450.7494030.5011940.250597
1460.7664650.467070.233535
1470.7482280.5035440.251772
1480.7258960.5482080.274104
1490.704180.591640.29582
1500.743780.512440.25622
1510.7457270.5085460.254273
1520.7409880.5180230.259012
1530.772430.455140.22757
1540.7807360.4385290.219264
1550.7602810.4794380.239719
1560.7390070.5219870.260993
1570.775610.4487790.22439
1580.7685890.4628230.231411
1590.7436060.5127890.256394
1600.7226440.5547130.277356
1610.7677530.4644940.232247
1620.7596650.480670.240335
1630.7637030.4725940.236297
1640.7468280.5063440.253172
1650.8027680.3944640.197232
1660.7857630.4284740.214237
1670.8340940.3318120.165906
1680.8190480.3619040.180952
1690.7991350.401730.200865
1700.7853350.4293310.214665
1710.7738660.4522670.226134
1720.8009350.398130.199065
1730.7827960.4344090.217204
1740.7619790.4760420.238021
1750.7411680.5176650.258832
1760.7716390.4567230.228361
1770.7438160.5123680.256184
1780.8082820.3834350.191718
1790.7912410.4175180.208759
1800.8430670.3138670.156933
1810.823180.3536390.17682
1820.8019330.3961330.198067
1830.8518080.2963840.148192
1840.8376140.3247710.162386
1850.8148260.3703470.185174
1860.8041220.3917550.195878
1870.8119620.3760760.188038
1880.7898810.4202380.210119
1890.7741260.4517470.225874
1900.7486510.5026990.251349
1910.756610.4867810.24339
1920.7389760.5220470.261024
1930.772820.4543590.22718
1940.7914730.4170530.208527
1950.7667460.4665090.233254
1960.7377190.5245610.262281
1970.712360.5752810.28764
1980.6796080.6407830.320392
1990.6494050.7011910.350595
2000.6268080.7463840.373192
2010.7167420.5665150.283258
2020.6860560.6278880.313944
2030.6547980.6904030.345202
2040.6320240.7359520.367976
2050.6042970.7914070.395703
2060.570460.8590810.42954
2070.5759550.8480910.424045
2080.5401410.9197190.459859
2090.5797150.840570.420285
2100.5712340.8575320.428766
2110.5503650.899270.449635
2120.520440.959120.47956
2130.4975170.9950330.502483
2140.4694610.9389220.530539
2150.4539470.9078930.546053
2160.4179780.8359560.582022
2170.3950720.7901440.604928
2180.4322490.8644980.567751
2190.409320.818640.59068
2200.3792570.7585140.620743
2210.4021980.8043970.597802
2220.4484890.8969790.551511
2230.4144570.8289130.585543
2240.3910380.7820770.608962
2250.4861230.9722460.513877
2260.4570860.9141720.542914
2270.4610560.9221120.538944
2280.4318750.8637510.568125
2290.4982540.9965080.501746
2300.5981910.8036190.401809
2310.6286970.7426070.371303
2320.701340.5973190.29866
2330.6570760.6858480.342924
2340.6102170.7795660.389783
2350.6075490.7849010.392451
2360.8818710.2362570.118129
2370.8613520.2772960.138648
2380.8300410.3399190.169959
2390.8257660.3484690.174234
2400.7941230.4117550.205877
2410.7544760.4910470.245524
2420.7084270.5831450.291573
2430.6618070.6763850.338193
2440.8318310.3363390.168169
2450.8013580.3972830.198642
2460.7645360.4709290.235464
2470.7670720.4658560.232928
2480.7408940.5182120.259106
2490.7162640.5674730.283736
2500.6603910.6792190.339609
2510.6047770.7904460.395223
2520.5465280.9069450.453472
2530.4950840.9901690.504916
2540.6983230.6033550.301677
2550.8122090.3755830.187791
2560.7678680.4642650.232132
2570.8191370.3617270.180863
2580.9450670.1098650.0549326
2590.9196910.1606170.0803085
2600.9814090.0371830.0185915
2610.9691930.06161420.0308071
2620.9775590.04488210.022441
2630.9600280.07994470.0399724
2640.9696710.06065860.0303293
2650.9599520.08009550.0400478
2660.9195470.1609070.0804533
2670.949170.101660.0508302
2680.8937890.2124230.106211
2690.8753530.2492930.124647
2700.9086430.1827130.0913567

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.403992 & 0.807983 & 0.596008 \tabularnewline
10 & 0.4019 & 0.803799 & 0.5981 \tabularnewline
11 & 0.26485 & 0.529701 & 0.73515 \tabularnewline
12 & 0.267651 & 0.535301 & 0.732349 \tabularnewline
13 & 0.258608 & 0.517216 & 0.741392 \tabularnewline
14 & 0.197448 & 0.394896 & 0.802552 \tabularnewline
15 & 0.184297 & 0.368594 & 0.815703 \tabularnewline
16 & 0.142356 & 0.284711 & 0.857644 \tabularnewline
17 & 0.0932046 & 0.186409 & 0.906795 \tabularnewline
18 & 0.0627101 & 0.12542 & 0.93729 \tabularnewline
19 & 0.0396063 & 0.0792125 & 0.960394 \tabularnewline
20 & 0.0239245 & 0.0478491 & 0.976075 \tabularnewline
21 & 0.0320937 & 0.0641873 & 0.967906 \tabularnewline
22 & 0.0301057 & 0.0602114 & 0.969894 \tabularnewline
23 & 0.0193814 & 0.0387628 & 0.980619 \tabularnewline
24 & 0.019586 & 0.039172 & 0.980414 \tabularnewline
25 & 0.0134722 & 0.0269444 & 0.986528 \tabularnewline
26 & 0.00828632 & 0.0165726 & 0.991714 \tabularnewline
27 & 0.0270015 & 0.0540031 & 0.972998 \tabularnewline
28 & 0.017757 & 0.035514 & 0.982243 \tabularnewline
29 & 0.0119386 & 0.0238772 & 0.988061 \tabularnewline
30 & 0.00763218 & 0.0152644 & 0.992368 \tabularnewline
31 & 0.0214424 & 0.0428848 & 0.978558 \tabularnewline
32 & 0.0164565 & 0.0329129 & 0.983544 \tabularnewline
33 & 0.0154939 & 0.0309879 & 0.984506 \tabularnewline
34 & 0.0120317 & 0.0240635 & 0.987968 \tabularnewline
35 & 0.00844995 & 0.0168999 & 0.99155 \tabularnewline
36 & 0.00570659 & 0.0114132 & 0.994293 \tabularnewline
37 & 0.00374413 & 0.00748827 & 0.996256 \tabularnewline
38 & 0.00249378 & 0.00498756 & 0.997506 \tabularnewline
39 & 0.00195273 & 0.00390546 & 0.998047 \tabularnewline
40 & 0.0012734 & 0.0025468 & 0.998727 \tabularnewline
41 & 0.00286535 & 0.00573071 & 0.997135 \tabularnewline
42 & 0.00207923 & 0.00415846 & 0.997921 \tabularnewline
43 & 0.00219967 & 0.00439935 & 0.9978 \tabularnewline
44 & 0.00144162 & 0.00288325 & 0.998558 \tabularnewline
45 & 0.000914722 & 0.00182944 & 0.999085 \tabularnewline
46 & 0.000631225 & 0.00126245 & 0.999369 \tabularnewline
47 & 0.000418658 & 0.000837316 & 0.999581 \tabularnewline
48 & 0.000372864 & 0.000745727 & 0.999627 \tabularnewline
49 & 0.000290262 & 0.000580524 & 0.99971 \tabularnewline
50 & 0.000225502 & 0.000451004 & 0.999774 \tabularnewline
51 & 0.000149086 & 0.000298171 & 0.999851 \tabularnewline
52 & 0.000578863 & 0.00115773 & 0.999421 \tabularnewline
53 & 0.000403412 & 0.000806824 & 0.999597 \tabularnewline
54 & 0.000383623 & 0.000767245 & 0.999616 \tabularnewline
55 & 0.000550094 & 0.00110019 & 0.99945 \tabularnewline
56 & 0.000378397 & 0.000756794 & 0.999622 \tabularnewline
57 & 0.00158843 & 0.00317686 & 0.998412 \tabularnewline
58 & 0.00112421 & 0.00224842 & 0.998876 \tabularnewline
59 & 0.00128283 & 0.00256566 & 0.998717 \tabularnewline
60 & 0.00133761 & 0.00267521 & 0.998662 \tabularnewline
61 & 0.00106193 & 0.00212386 & 0.998938 \tabularnewline
62 & 0.00079394 & 0.00158788 & 0.999206 \tabularnewline
63 & 0.0023013 & 0.00460259 & 0.997699 \tabularnewline
64 & 0.00424518 & 0.00849036 & 0.995755 \tabularnewline
65 & 0.00381439 & 0.00762878 & 0.996186 \tabularnewline
66 & 0.00369996 & 0.00739992 & 0.9963 \tabularnewline
67 & 0.00271322 & 0.00542643 & 0.997287 \tabularnewline
68 & 0.00248011 & 0.00496021 & 0.99752 \tabularnewline
69 & 0.00284583 & 0.00569165 & 0.997154 \tabularnewline
70 & 0.00213009 & 0.00426019 & 0.99787 \tabularnewline
71 & 0.00159363 & 0.00318727 & 0.998406 \tabularnewline
72 & 0.00116817 & 0.00233635 & 0.998832 \tabularnewline
73 & 0.00113847 & 0.00227694 & 0.998862 \tabularnewline
74 & 0.00139287 & 0.00278575 & 0.998607 \tabularnewline
75 & 0.0011041 & 0.0022082 & 0.998896 \tabularnewline
76 & 0.000887612 & 0.00177522 & 0.999112 \tabularnewline
77 & 0.000644794 & 0.00128959 & 0.999355 \tabularnewline
78 & 0.000574756 & 0.00114951 & 0.999425 \tabularnewline
79 & 0.000452514 & 0.000905028 & 0.999547 \tabularnewline
80 & 0.000590901 & 0.0011818 & 0.999409 \tabularnewline
81 & 0.000448227 & 0.000896455 & 0.999552 \tabularnewline
82 & 0.000395178 & 0.000790355 & 0.999605 \tabularnewline
83 & 0.000286067 & 0.000572134 & 0.999714 \tabularnewline
84 & 0.00174745 & 0.00349489 & 0.998253 \tabularnewline
85 & 0.00141464 & 0.00282928 & 0.998585 \tabularnewline
86 & 0.00109581 & 0.00219162 & 0.998904 \tabularnewline
87 & 0.000844486 & 0.00168897 & 0.999156 \tabularnewline
88 & 0.000642334 & 0.00128467 & 0.999358 \tabularnewline
89 & 0.000696604 & 0.00139321 & 0.999303 \tabularnewline
90 & 0.000564448 & 0.0011289 & 0.999436 \tabularnewline
91 & 0.000472315 & 0.000944631 & 0.999528 \tabularnewline
92 & 0.00149025 & 0.0029805 & 0.99851 \tabularnewline
93 & 0.00128368 & 0.00256736 & 0.998716 \tabularnewline
94 & 0.00123283 & 0.00246565 & 0.998767 \tabularnewline
95 & 0.0018062 & 0.0036124 & 0.998194 \tabularnewline
96 & 0.00182455 & 0.0036491 & 0.998175 \tabularnewline
97 & 0.00280033 & 0.00560065 & 0.9972 \tabularnewline
98 & 0.00219361 & 0.00438722 & 0.997806 \tabularnewline
99 & 0.00183288 & 0.00366576 & 0.998167 \tabularnewline
100 & 0.0024519 & 0.0049038 & 0.997548 \tabularnewline
101 & 0.00204308 & 0.00408617 & 0.997957 \tabularnewline
102 & 0.00173451 & 0.00346901 & 0.998265 \tabularnewline
103 & 0.00215937 & 0.00431873 & 0.997841 \tabularnewline
104 & 0.00202664 & 0.00405329 & 0.997973 \tabularnewline
105 & 0.00210398 & 0.00420797 & 0.997896 \tabularnewline
106 & 0.00247226 & 0.00494451 & 0.997528 \tabularnewline
107 & 0.00223766 & 0.00447533 & 0.997762 \tabularnewline
108 & 0.00852934 & 0.0170587 & 0.991471 \tabularnewline
109 & 0.0185244 & 0.0370488 & 0.981476 \tabularnewline
110 & 0.0198439 & 0.0396878 & 0.980156 \tabularnewline
111 & 0.0175769 & 0.0351538 & 0.982423 \tabularnewline
112 & 0.0166371 & 0.0332743 & 0.983363 \tabularnewline
113 & 0.072016 & 0.144032 & 0.927984 \tabularnewline
114 & 0.065572 & 0.131144 & 0.934428 \tabularnewline
115 & 0.130618 & 0.261235 & 0.869382 \tabularnewline
116 & 0.210657 & 0.421313 & 0.789343 \tabularnewline
117 & 0.262309 & 0.524617 & 0.737691 \tabularnewline
118 & 0.241385 & 0.482771 & 0.758615 \tabularnewline
119 & 0.289391 & 0.578782 & 0.710609 \tabularnewline
120 & 0.429739 & 0.859477 & 0.570261 \tabularnewline
121 & 0.468142 & 0.936285 & 0.531858 \tabularnewline
122 & 0.441517 & 0.883035 & 0.558483 \tabularnewline
123 & 0.510694 & 0.978613 & 0.489306 \tabularnewline
124 & 0.505447 & 0.989107 & 0.494553 \tabularnewline
125 & 0.503055 & 0.99389 & 0.496945 \tabularnewline
126 & 0.474663 & 0.949326 & 0.525337 \tabularnewline
127 & 0.510503 & 0.978995 & 0.489497 \tabularnewline
128 & 0.485277 & 0.970553 & 0.514723 \tabularnewline
129 & 0.606562 & 0.786876 & 0.393438 \tabularnewline
130 & 0.584929 & 0.830143 & 0.415071 \tabularnewline
131 & 0.567468 & 0.865064 & 0.432532 \tabularnewline
132 & 0.582879 & 0.834241 & 0.417121 \tabularnewline
133 & 0.581436 & 0.837128 & 0.418564 \tabularnewline
134 & 0.575442 & 0.849117 & 0.424558 \tabularnewline
135 & 0.546884 & 0.906232 & 0.453116 \tabularnewline
136 & 0.525118 & 0.949764 & 0.474882 \tabularnewline
137 & 0.562541 & 0.874918 & 0.437459 \tabularnewline
138 & 0.600062 & 0.799876 & 0.399938 \tabularnewline
139 & 0.683049 & 0.633902 & 0.316951 \tabularnewline
140 & 0.675284 & 0.649433 & 0.324716 \tabularnewline
141 & 0.649405 & 0.70119 & 0.350595 \tabularnewline
142 & 0.69802 & 0.603961 & 0.30198 \tabularnewline
143 & 0.690904 & 0.618192 & 0.309096 \tabularnewline
144 & 0.743782 & 0.512437 & 0.256218 \tabularnewline
145 & 0.749403 & 0.501194 & 0.250597 \tabularnewline
146 & 0.766465 & 0.46707 & 0.233535 \tabularnewline
147 & 0.748228 & 0.503544 & 0.251772 \tabularnewline
148 & 0.725896 & 0.548208 & 0.274104 \tabularnewline
149 & 0.70418 & 0.59164 & 0.29582 \tabularnewline
150 & 0.74378 & 0.51244 & 0.25622 \tabularnewline
151 & 0.745727 & 0.508546 & 0.254273 \tabularnewline
152 & 0.740988 & 0.518023 & 0.259012 \tabularnewline
153 & 0.77243 & 0.45514 & 0.22757 \tabularnewline
154 & 0.780736 & 0.438529 & 0.219264 \tabularnewline
155 & 0.760281 & 0.479438 & 0.239719 \tabularnewline
156 & 0.739007 & 0.521987 & 0.260993 \tabularnewline
157 & 0.77561 & 0.448779 & 0.22439 \tabularnewline
158 & 0.768589 & 0.462823 & 0.231411 \tabularnewline
159 & 0.743606 & 0.512789 & 0.256394 \tabularnewline
160 & 0.722644 & 0.554713 & 0.277356 \tabularnewline
161 & 0.767753 & 0.464494 & 0.232247 \tabularnewline
162 & 0.759665 & 0.48067 & 0.240335 \tabularnewline
163 & 0.763703 & 0.472594 & 0.236297 \tabularnewline
164 & 0.746828 & 0.506344 & 0.253172 \tabularnewline
165 & 0.802768 & 0.394464 & 0.197232 \tabularnewline
166 & 0.785763 & 0.428474 & 0.214237 \tabularnewline
167 & 0.834094 & 0.331812 & 0.165906 \tabularnewline
168 & 0.819048 & 0.361904 & 0.180952 \tabularnewline
169 & 0.799135 & 0.40173 & 0.200865 \tabularnewline
170 & 0.785335 & 0.429331 & 0.214665 \tabularnewline
171 & 0.773866 & 0.452267 & 0.226134 \tabularnewline
172 & 0.800935 & 0.39813 & 0.199065 \tabularnewline
173 & 0.782796 & 0.434409 & 0.217204 \tabularnewline
174 & 0.761979 & 0.476042 & 0.238021 \tabularnewline
175 & 0.741168 & 0.517665 & 0.258832 \tabularnewline
176 & 0.771639 & 0.456723 & 0.228361 \tabularnewline
177 & 0.743816 & 0.512368 & 0.256184 \tabularnewline
178 & 0.808282 & 0.383435 & 0.191718 \tabularnewline
179 & 0.791241 & 0.417518 & 0.208759 \tabularnewline
180 & 0.843067 & 0.313867 & 0.156933 \tabularnewline
181 & 0.82318 & 0.353639 & 0.17682 \tabularnewline
182 & 0.801933 & 0.396133 & 0.198067 \tabularnewline
183 & 0.851808 & 0.296384 & 0.148192 \tabularnewline
184 & 0.837614 & 0.324771 & 0.162386 \tabularnewline
185 & 0.814826 & 0.370347 & 0.185174 \tabularnewline
186 & 0.804122 & 0.391755 & 0.195878 \tabularnewline
187 & 0.811962 & 0.376076 & 0.188038 \tabularnewline
188 & 0.789881 & 0.420238 & 0.210119 \tabularnewline
189 & 0.774126 & 0.451747 & 0.225874 \tabularnewline
190 & 0.748651 & 0.502699 & 0.251349 \tabularnewline
191 & 0.75661 & 0.486781 & 0.24339 \tabularnewline
192 & 0.738976 & 0.522047 & 0.261024 \tabularnewline
193 & 0.77282 & 0.454359 & 0.22718 \tabularnewline
194 & 0.791473 & 0.417053 & 0.208527 \tabularnewline
195 & 0.766746 & 0.466509 & 0.233254 \tabularnewline
196 & 0.737719 & 0.524561 & 0.262281 \tabularnewline
197 & 0.71236 & 0.575281 & 0.28764 \tabularnewline
198 & 0.679608 & 0.640783 & 0.320392 \tabularnewline
199 & 0.649405 & 0.701191 & 0.350595 \tabularnewline
200 & 0.626808 & 0.746384 & 0.373192 \tabularnewline
201 & 0.716742 & 0.566515 & 0.283258 \tabularnewline
202 & 0.686056 & 0.627888 & 0.313944 \tabularnewline
203 & 0.654798 & 0.690403 & 0.345202 \tabularnewline
204 & 0.632024 & 0.735952 & 0.367976 \tabularnewline
205 & 0.604297 & 0.791407 & 0.395703 \tabularnewline
206 & 0.57046 & 0.859081 & 0.42954 \tabularnewline
207 & 0.575955 & 0.848091 & 0.424045 \tabularnewline
208 & 0.540141 & 0.919719 & 0.459859 \tabularnewline
209 & 0.579715 & 0.84057 & 0.420285 \tabularnewline
210 & 0.571234 & 0.857532 & 0.428766 \tabularnewline
211 & 0.550365 & 0.89927 & 0.449635 \tabularnewline
212 & 0.52044 & 0.95912 & 0.47956 \tabularnewline
213 & 0.497517 & 0.995033 & 0.502483 \tabularnewline
214 & 0.469461 & 0.938922 & 0.530539 \tabularnewline
215 & 0.453947 & 0.907893 & 0.546053 \tabularnewline
216 & 0.417978 & 0.835956 & 0.582022 \tabularnewline
217 & 0.395072 & 0.790144 & 0.604928 \tabularnewline
218 & 0.432249 & 0.864498 & 0.567751 \tabularnewline
219 & 0.40932 & 0.81864 & 0.59068 \tabularnewline
220 & 0.379257 & 0.758514 & 0.620743 \tabularnewline
221 & 0.402198 & 0.804397 & 0.597802 \tabularnewline
222 & 0.448489 & 0.896979 & 0.551511 \tabularnewline
223 & 0.414457 & 0.828913 & 0.585543 \tabularnewline
224 & 0.391038 & 0.782077 & 0.608962 \tabularnewline
225 & 0.486123 & 0.972246 & 0.513877 \tabularnewline
226 & 0.457086 & 0.914172 & 0.542914 \tabularnewline
227 & 0.461056 & 0.922112 & 0.538944 \tabularnewline
228 & 0.431875 & 0.863751 & 0.568125 \tabularnewline
229 & 0.498254 & 0.996508 & 0.501746 \tabularnewline
230 & 0.598191 & 0.803619 & 0.401809 \tabularnewline
231 & 0.628697 & 0.742607 & 0.371303 \tabularnewline
232 & 0.70134 & 0.597319 & 0.29866 \tabularnewline
233 & 0.657076 & 0.685848 & 0.342924 \tabularnewline
234 & 0.610217 & 0.779566 & 0.389783 \tabularnewline
235 & 0.607549 & 0.784901 & 0.392451 \tabularnewline
236 & 0.881871 & 0.236257 & 0.118129 \tabularnewline
237 & 0.861352 & 0.277296 & 0.138648 \tabularnewline
238 & 0.830041 & 0.339919 & 0.169959 \tabularnewline
239 & 0.825766 & 0.348469 & 0.174234 \tabularnewline
240 & 0.794123 & 0.411755 & 0.205877 \tabularnewline
241 & 0.754476 & 0.491047 & 0.245524 \tabularnewline
242 & 0.708427 & 0.583145 & 0.291573 \tabularnewline
243 & 0.661807 & 0.676385 & 0.338193 \tabularnewline
244 & 0.831831 & 0.336339 & 0.168169 \tabularnewline
245 & 0.801358 & 0.397283 & 0.198642 \tabularnewline
246 & 0.764536 & 0.470929 & 0.235464 \tabularnewline
247 & 0.767072 & 0.465856 & 0.232928 \tabularnewline
248 & 0.740894 & 0.518212 & 0.259106 \tabularnewline
249 & 0.716264 & 0.567473 & 0.283736 \tabularnewline
250 & 0.660391 & 0.679219 & 0.339609 \tabularnewline
251 & 0.604777 & 0.790446 & 0.395223 \tabularnewline
252 & 0.546528 & 0.906945 & 0.453472 \tabularnewline
253 & 0.495084 & 0.990169 & 0.504916 \tabularnewline
254 & 0.698323 & 0.603355 & 0.301677 \tabularnewline
255 & 0.812209 & 0.375583 & 0.187791 \tabularnewline
256 & 0.767868 & 0.464265 & 0.232132 \tabularnewline
257 & 0.819137 & 0.361727 & 0.180863 \tabularnewline
258 & 0.945067 & 0.109865 & 0.0549326 \tabularnewline
259 & 0.919691 & 0.160617 & 0.0803085 \tabularnewline
260 & 0.981409 & 0.037183 & 0.0185915 \tabularnewline
261 & 0.969193 & 0.0616142 & 0.0308071 \tabularnewline
262 & 0.977559 & 0.0448821 & 0.022441 \tabularnewline
263 & 0.960028 & 0.0799447 & 0.0399724 \tabularnewline
264 & 0.969671 & 0.0606586 & 0.0303293 \tabularnewline
265 & 0.959952 & 0.0800955 & 0.0400478 \tabularnewline
266 & 0.919547 & 0.160907 & 0.0804533 \tabularnewline
267 & 0.94917 & 0.10166 & 0.0508302 \tabularnewline
268 & 0.893789 & 0.212423 & 0.106211 \tabularnewline
269 & 0.875353 & 0.249293 & 0.124647 \tabularnewline
270 & 0.908643 & 0.182713 & 0.0913567 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263940&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]9[/C][C]0.403992[/C][C]0.807983[/C][C]0.596008[/C][/ROW]
[ROW][C]10[/C][C]0.4019[/C][C]0.803799[/C][C]0.5981[/C][/ROW]
[ROW][C]11[/C][C]0.26485[/C][C]0.529701[/C][C]0.73515[/C][/ROW]
[ROW][C]12[/C][C]0.267651[/C][C]0.535301[/C][C]0.732349[/C][/ROW]
[ROW][C]13[/C][C]0.258608[/C][C]0.517216[/C][C]0.741392[/C][/ROW]
[ROW][C]14[/C][C]0.197448[/C][C]0.394896[/C][C]0.802552[/C][/ROW]
[ROW][C]15[/C][C]0.184297[/C][C]0.368594[/C][C]0.815703[/C][/ROW]
[ROW][C]16[/C][C]0.142356[/C][C]0.284711[/C][C]0.857644[/C][/ROW]
[ROW][C]17[/C][C]0.0932046[/C][C]0.186409[/C][C]0.906795[/C][/ROW]
[ROW][C]18[/C][C]0.0627101[/C][C]0.12542[/C][C]0.93729[/C][/ROW]
[ROW][C]19[/C][C]0.0396063[/C][C]0.0792125[/C][C]0.960394[/C][/ROW]
[ROW][C]20[/C][C]0.0239245[/C][C]0.0478491[/C][C]0.976075[/C][/ROW]
[ROW][C]21[/C][C]0.0320937[/C][C]0.0641873[/C][C]0.967906[/C][/ROW]
[ROW][C]22[/C][C]0.0301057[/C][C]0.0602114[/C][C]0.969894[/C][/ROW]
[ROW][C]23[/C][C]0.0193814[/C][C]0.0387628[/C][C]0.980619[/C][/ROW]
[ROW][C]24[/C][C]0.019586[/C][C]0.039172[/C][C]0.980414[/C][/ROW]
[ROW][C]25[/C][C]0.0134722[/C][C]0.0269444[/C][C]0.986528[/C][/ROW]
[ROW][C]26[/C][C]0.00828632[/C][C]0.0165726[/C][C]0.991714[/C][/ROW]
[ROW][C]27[/C][C]0.0270015[/C][C]0.0540031[/C][C]0.972998[/C][/ROW]
[ROW][C]28[/C][C]0.017757[/C][C]0.035514[/C][C]0.982243[/C][/ROW]
[ROW][C]29[/C][C]0.0119386[/C][C]0.0238772[/C][C]0.988061[/C][/ROW]
[ROW][C]30[/C][C]0.00763218[/C][C]0.0152644[/C][C]0.992368[/C][/ROW]
[ROW][C]31[/C][C]0.0214424[/C][C]0.0428848[/C][C]0.978558[/C][/ROW]
[ROW][C]32[/C][C]0.0164565[/C][C]0.0329129[/C][C]0.983544[/C][/ROW]
[ROW][C]33[/C][C]0.0154939[/C][C]0.0309879[/C][C]0.984506[/C][/ROW]
[ROW][C]34[/C][C]0.0120317[/C][C]0.0240635[/C][C]0.987968[/C][/ROW]
[ROW][C]35[/C][C]0.00844995[/C][C]0.0168999[/C][C]0.99155[/C][/ROW]
[ROW][C]36[/C][C]0.00570659[/C][C]0.0114132[/C][C]0.994293[/C][/ROW]
[ROW][C]37[/C][C]0.00374413[/C][C]0.00748827[/C][C]0.996256[/C][/ROW]
[ROW][C]38[/C][C]0.00249378[/C][C]0.00498756[/C][C]0.997506[/C][/ROW]
[ROW][C]39[/C][C]0.00195273[/C][C]0.00390546[/C][C]0.998047[/C][/ROW]
[ROW][C]40[/C][C]0.0012734[/C][C]0.0025468[/C][C]0.998727[/C][/ROW]
[ROW][C]41[/C][C]0.00286535[/C][C]0.00573071[/C][C]0.997135[/C][/ROW]
[ROW][C]42[/C][C]0.00207923[/C][C]0.00415846[/C][C]0.997921[/C][/ROW]
[ROW][C]43[/C][C]0.00219967[/C][C]0.00439935[/C][C]0.9978[/C][/ROW]
[ROW][C]44[/C][C]0.00144162[/C][C]0.00288325[/C][C]0.998558[/C][/ROW]
[ROW][C]45[/C][C]0.000914722[/C][C]0.00182944[/C][C]0.999085[/C][/ROW]
[ROW][C]46[/C][C]0.000631225[/C][C]0.00126245[/C][C]0.999369[/C][/ROW]
[ROW][C]47[/C][C]0.000418658[/C][C]0.000837316[/C][C]0.999581[/C][/ROW]
[ROW][C]48[/C][C]0.000372864[/C][C]0.000745727[/C][C]0.999627[/C][/ROW]
[ROW][C]49[/C][C]0.000290262[/C][C]0.000580524[/C][C]0.99971[/C][/ROW]
[ROW][C]50[/C][C]0.000225502[/C][C]0.000451004[/C][C]0.999774[/C][/ROW]
[ROW][C]51[/C][C]0.000149086[/C][C]0.000298171[/C][C]0.999851[/C][/ROW]
[ROW][C]52[/C][C]0.000578863[/C][C]0.00115773[/C][C]0.999421[/C][/ROW]
[ROW][C]53[/C][C]0.000403412[/C][C]0.000806824[/C][C]0.999597[/C][/ROW]
[ROW][C]54[/C][C]0.000383623[/C][C]0.000767245[/C][C]0.999616[/C][/ROW]
[ROW][C]55[/C][C]0.000550094[/C][C]0.00110019[/C][C]0.99945[/C][/ROW]
[ROW][C]56[/C][C]0.000378397[/C][C]0.000756794[/C][C]0.999622[/C][/ROW]
[ROW][C]57[/C][C]0.00158843[/C][C]0.00317686[/C][C]0.998412[/C][/ROW]
[ROW][C]58[/C][C]0.00112421[/C][C]0.00224842[/C][C]0.998876[/C][/ROW]
[ROW][C]59[/C][C]0.00128283[/C][C]0.00256566[/C][C]0.998717[/C][/ROW]
[ROW][C]60[/C][C]0.00133761[/C][C]0.00267521[/C][C]0.998662[/C][/ROW]
[ROW][C]61[/C][C]0.00106193[/C][C]0.00212386[/C][C]0.998938[/C][/ROW]
[ROW][C]62[/C][C]0.00079394[/C][C]0.00158788[/C][C]0.999206[/C][/ROW]
[ROW][C]63[/C][C]0.0023013[/C][C]0.00460259[/C][C]0.997699[/C][/ROW]
[ROW][C]64[/C][C]0.00424518[/C][C]0.00849036[/C][C]0.995755[/C][/ROW]
[ROW][C]65[/C][C]0.00381439[/C][C]0.00762878[/C][C]0.996186[/C][/ROW]
[ROW][C]66[/C][C]0.00369996[/C][C]0.00739992[/C][C]0.9963[/C][/ROW]
[ROW][C]67[/C][C]0.00271322[/C][C]0.00542643[/C][C]0.997287[/C][/ROW]
[ROW][C]68[/C][C]0.00248011[/C][C]0.00496021[/C][C]0.99752[/C][/ROW]
[ROW][C]69[/C][C]0.00284583[/C][C]0.00569165[/C][C]0.997154[/C][/ROW]
[ROW][C]70[/C][C]0.00213009[/C][C]0.00426019[/C][C]0.99787[/C][/ROW]
[ROW][C]71[/C][C]0.00159363[/C][C]0.00318727[/C][C]0.998406[/C][/ROW]
[ROW][C]72[/C][C]0.00116817[/C][C]0.00233635[/C][C]0.998832[/C][/ROW]
[ROW][C]73[/C][C]0.00113847[/C][C]0.00227694[/C][C]0.998862[/C][/ROW]
[ROW][C]74[/C][C]0.00139287[/C][C]0.00278575[/C][C]0.998607[/C][/ROW]
[ROW][C]75[/C][C]0.0011041[/C][C]0.0022082[/C][C]0.998896[/C][/ROW]
[ROW][C]76[/C][C]0.000887612[/C][C]0.00177522[/C][C]0.999112[/C][/ROW]
[ROW][C]77[/C][C]0.000644794[/C][C]0.00128959[/C][C]0.999355[/C][/ROW]
[ROW][C]78[/C][C]0.000574756[/C][C]0.00114951[/C][C]0.999425[/C][/ROW]
[ROW][C]79[/C][C]0.000452514[/C][C]0.000905028[/C][C]0.999547[/C][/ROW]
[ROW][C]80[/C][C]0.000590901[/C][C]0.0011818[/C][C]0.999409[/C][/ROW]
[ROW][C]81[/C][C]0.000448227[/C][C]0.000896455[/C][C]0.999552[/C][/ROW]
[ROW][C]82[/C][C]0.000395178[/C][C]0.000790355[/C][C]0.999605[/C][/ROW]
[ROW][C]83[/C][C]0.000286067[/C][C]0.000572134[/C][C]0.999714[/C][/ROW]
[ROW][C]84[/C][C]0.00174745[/C][C]0.00349489[/C][C]0.998253[/C][/ROW]
[ROW][C]85[/C][C]0.00141464[/C][C]0.00282928[/C][C]0.998585[/C][/ROW]
[ROW][C]86[/C][C]0.00109581[/C][C]0.00219162[/C][C]0.998904[/C][/ROW]
[ROW][C]87[/C][C]0.000844486[/C][C]0.00168897[/C][C]0.999156[/C][/ROW]
[ROW][C]88[/C][C]0.000642334[/C][C]0.00128467[/C][C]0.999358[/C][/ROW]
[ROW][C]89[/C][C]0.000696604[/C][C]0.00139321[/C][C]0.999303[/C][/ROW]
[ROW][C]90[/C][C]0.000564448[/C][C]0.0011289[/C][C]0.999436[/C][/ROW]
[ROW][C]91[/C][C]0.000472315[/C][C]0.000944631[/C][C]0.999528[/C][/ROW]
[ROW][C]92[/C][C]0.00149025[/C][C]0.0029805[/C][C]0.99851[/C][/ROW]
[ROW][C]93[/C][C]0.00128368[/C][C]0.00256736[/C][C]0.998716[/C][/ROW]
[ROW][C]94[/C][C]0.00123283[/C][C]0.00246565[/C][C]0.998767[/C][/ROW]
[ROW][C]95[/C][C]0.0018062[/C][C]0.0036124[/C][C]0.998194[/C][/ROW]
[ROW][C]96[/C][C]0.00182455[/C][C]0.0036491[/C][C]0.998175[/C][/ROW]
[ROW][C]97[/C][C]0.00280033[/C][C]0.00560065[/C][C]0.9972[/C][/ROW]
[ROW][C]98[/C][C]0.00219361[/C][C]0.00438722[/C][C]0.997806[/C][/ROW]
[ROW][C]99[/C][C]0.00183288[/C][C]0.00366576[/C][C]0.998167[/C][/ROW]
[ROW][C]100[/C][C]0.0024519[/C][C]0.0049038[/C][C]0.997548[/C][/ROW]
[ROW][C]101[/C][C]0.00204308[/C][C]0.00408617[/C][C]0.997957[/C][/ROW]
[ROW][C]102[/C][C]0.00173451[/C][C]0.00346901[/C][C]0.998265[/C][/ROW]
[ROW][C]103[/C][C]0.00215937[/C][C]0.00431873[/C][C]0.997841[/C][/ROW]
[ROW][C]104[/C][C]0.00202664[/C][C]0.00405329[/C][C]0.997973[/C][/ROW]
[ROW][C]105[/C][C]0.00210398[/C][C]0.00420797[/C][C]0.997896[/C][/ROW]
[ROW][C]106[/C][C]0.00247226[/C][C]0.00494451[/C][C]0.997528[/C][/ROW]
[ROW][C]107[/C][C]0.00223766[/C][C]0.00447533[/C][C]0.997762[/C][/ROW]
[ROW][C]108[/C][C]0.00852934[/C][C]0.0170587[/C][C]0.991471[/C][/ROW]
[ROW][C]109[/C][C]0.0185244[/C][C]0.0370488[/C][C]0.981476[/C][/ROW]
[ROW][C]110[/C][C]0.0198439[/C][C]0.0396878[/C][C]0.980156[/C][/ROW]
[ROW][C]111[/C][C]0.0175769[/C][C]0.0351538[/C][C]0.982423[/C][/ROW]
[ROW][C]112[/C][C]0.0166371[/C][C]0.0332743[/C][C]0.983363[/C][/ROW]
[ROW][C]113[/C][C]0.072016[/C][C]0.144032[/C][C]0.927984[/C][/ROW]
[ROW][C]114[/C][C]0.065572[/C][C]0.131144[/C][C]0.934428[/C][/ROW]
[ROW][C]115[/C][C]0.130618[/C][C]0.261235[/C][C]0.869382[/C][/ROW]
[ROW][C]116[/C][C]0.210657[/C][C]0.421313[/C][C]0.789343[/C][/ROW]
[ROW][C]117[/C][C]0.262309[/C][C]0.524617[/C][C]0.737691[/C][/ROW]
[ROW][C]118[/C][C]0.241385[/C][C]0.482771[/C][C]0.758615[/C][/ROW]
[ROW][C]119[/C][C]0.289391[/C][C]0.578782[/C][C]0.710609[/C][/ROW]
[ROW][C]120[/C][C]0.429739[/C][C]0.859477[/C][C]0.570261[/C][/ROW]
[ROW][C]121[/C][C]0.468142[/C][C]0.936285[/C][C]0.531858[/C][/ROW]
[ROW][C]122[/C][C]0.441517[/C][C]0.883035[/C][C]0.558483[/C][/ROW]
[ROW][C]123[/C][C]0.510694[/C][C]0.978613[/C][C]0.489306[/C][/ROW]
[ROW][C]124[/C][C]0.505447[/C][C]0.989107[/C][C]0.494553[/C][/ROW]
[ROW][C]125[/C][C]0.503055[/C][C]0.99389[/C][C]0.496945[/C][/ROW]
[ROW][C]126[/C][C]0.474663[/C][C]0.949326[/C][C]0.525337[/C][/ROW]
[ROW][C]127[/C][C]0.510503[/C][C]0.978995[/C][C]0.489497[/C][/ROW]
[ROW][C]128[/C][C]0.485277[/C][C]0.970553[/C][C]0.514723[/C][/ROW]
[ROW][C]129[/C][C]0.606562[/C][C]0.786876[/C][C]0.393438[/C][/ROW]
[ROW][C]130[/C][C]0.584929[/C][C]0.830143[/C][C]0.415071[/C][/ROW]
[ROW][C]131[/C][C]0.567468[/C][C]0.865064[/C][C]0.432532[/C][/ROW]
[ROW][C]132[/C][C]0.582879[/C][C]0.834241[/C][C]0.417121[/C][/ROW]
[ROW][C]133[/C][C]0.581436[/C][C]0.837128[/C][C]0.418564[/C][/ROW]
[ROW][C]134[/C][C]0.575442[/C][C]0.849117[/C][C]0.424558[/C][/ROW]
[ROW][C]135[/C][C]0.546884[/C][C]0.906232[/C][C]0.453116[/C][/ROW]
[ROW][C]136[/C][C]0.525118[/C][C]0.949764[/C][C]0.474882[/C][/ROW]
[ROW][C]137[/C][C]0.562541[/C][C]0.874918[/C][C]0.437459[/C][/ROW]
[ROW][C]138[/C][C]0.600062[/C][C]0.799876[/C][C]0.399938[/C][/ROW]
[ROW][C]139[/C][C]0.683049[/C][C]0.633902[/C][C]0.316951[/C][/ROW]
[ROW][C]140[/C][C]0.675284[/C][C]0.649433[/C][C]0.324716[/C][/ROW]
[ROW][C]141[/C][C]0.649405[/C][C]0.70119[/C][C]0.350595[/C][/ROW]
[ROW][C]142[/C][C]0.69802[/C][C]0.603961[/C][C]0.30198[/C][/ROW]
[ROW][C]143[/C][C]0.690904[/C][C]0.618192[/C][C]0.309096[/C][/ROW]
[ROW][C]144[/C][C]0.743782[/C][C]0.512437[/C][C]0.256218[/C][/ROW]
[ROW][C]145[/C][C]0.749403[/C][C]0.501194[/C][C]0.250597[/C][/ROW]
[ROW][C]146[/C][C]0.766465[/C][C]0.46707[/C][C]0.233535[/C][/ROW]
[ROW][C]147[/C][C]0.748228[/C][C]0.503544[/C][C]0.251772[/C][/ROW]
[ROW][C]148[/C][C]0.725896[/C][C]0.548208[/C][C]0.274104[/C][/ROW]
[ROW][C]149[/C][C]0.70418[/C][C]0.59164[/C][C]0.29582[/C][/ROW]
[ROW][C]150[/C][C]0.74378[/C][C]0.51244[/C][C]0.25622[/C][/ROW]
[ROW][C]151[/C][C]0.745727[/C][C]0.508546[/C][C]0.254273[/C][/ROW]
[ROW][C]152[/C][C]0.740988[/C][C]0.518023[/C][C]0.259012[/C][/ROW]
[ROW][C]153[/C][C]0.77243[/C][C]0.45514[/C][C]0.22757[/C][/ROW]
[ROW][C]154[/C][C]0.780736[/C][C]0.438529[/C][C]0.219264[/C][/ROW]
[ROW][C]155[/C][C]0.760281[/C][C]0.479438[/C][C]0.239719[/C][/ROW]
[ROW][C]156[/C][C]0.739007[/C][C]0.521987[/C][C]0.260993[/C][/ROW]
[ROW][C]157[/C][C]0.77561[/C][C]0.448779[/C][C]0.22439[/C][/ROW]
[ROW][C]158[/C][C]0.768589[/C][C]0.462823[/C][C]0.231411[/C][/ROW]
[ROW][C]159[/C][C]0.743606[/C][C]0.512789[/C][C]0.256394[/C][/ROW]
[ROW][C]160[/C][C]0.722644[/C][C]0.554713[/C][C]0.277356[/C][/ROW]
[ROW][C]161[/C][C]0.767753[/C][C]0.464494[/C][C]0.232247[/C][/ROW]
[ROW][C]162[/C][C]0.759665[/C][C]0.48067[/C][C]0.240335[/C][/ROW]
[ROW][C]163[/C][C]0.763703[/C][C]0.472594[/C][C]0.236297[/C][/ROW]
[ROW][C]164[/C][C]0.746828[/C][C]0.506344[/C][C]0.253172[/C][/ROW]
[ROW][C]165[/C][C]0.802768[/C][C]0.394464[/C][C]0.197232[/C][/ROW]
[ROW][C]166[/C][C]0.785763[/C][C]0.428474[/C][C]0.214237[/C][/ROW]
[ROW][C]167[/C][C]0.834094[/C][C]0.331812[/C][C]0.165906[/C][/ROW]
[ROW][C]168[/C][C]0.819048[/C][C]0.361904[/C][C]0.180952[/C][/ROW]
[ROW][C]169[/C][C]0.799135[/C][C]0.40173[/C][C]0.200865[/C][/ROW]
[ROW][C]170[/C][C]0.785335[/C][C]0.429331[/C][C]0.214665[/C][/ROW]
[ROW][C]171[/C][C]0.773866[/C][C]0.452267[/C][C]0.226134[/C][/ROW]
[ROW][C]172[/C][C]0.800935[/C][C]0.39813[/C][C]0.199065[/C][/ROW]
[ROW][C]173[/C][C]0.782796[/C][C]0.434409[/C][C]0.217204[/C][/ROW]
[ROW][C]174[/C][C]0.761979[/C][C]0.476042[/C][C]0.238021[/C][/ROW]
[ROW][C]175[/C][C]0.741168[/C][C]0.517665[/C][C]0.258832[/C][/ROW]
[ROW][C]176[/C][C]0.771639[/C][C]0.456723[/C][C]0.228361[/C][/ROW]
[ROW][C]177[/C][C]0.743816[/C][C]0.512368[/C][C]0.256184[/C][/ROW]
[ROW][C]178[/C][C]0.808282[/C][C]0.383435[/C][C]0.191718[/C][/ROW]
[ROW][C]179[/C][C]0.791241[/C][C]0.417518[/C][C]0.208759[/C][/ROW]
[ROW][C]180[/C][C]0.843067[/C][C]0.313867[/C][C]0.156933[/C][/ROW]
[ROW][C]181[/C][C]0.82318[/C][C]0.353639[/C][C]0.17682[/C][/ROW]
[ROW][C]182[/C][C]0.801933[/C][C]0.396133[/C][C]0.198067[/C][/ROW]
[ROW][C]183[/C][C]0.851808[/C][C]0.296384[/C][C]0.148192[/C][/ROW]
[ROW][C]184[/C][C]0.837614[/C][C]0.324771[/C][C]0.162386[/C][/ROW]
[ROW][C]185[/C][C]0.814826[/C][C]0.370347[/C][C]0.185174[/C][/ROW]
[ROW][C]186[/C][C]0.804122[/C][C]0.391755[/C][C]0.195878[/C][/ROW]
[ROW][C]187[/C][C]0.811962[/C][C]0.376076[/C][C]0.188038[/C][/ROW]
[ROW][C]188[/C][C]0.789881[/C][C]0.420238[/C][C]0.210119[/C][/ROW]
[ROW][C]189[/C][C]0.774126[/C][C]0.451747[/C][C]0.225874[/C][/ROW]
[ROW][C]190[/C][C]0.748651[/C][C]0.502699[/C][C]0.251349[/C][/ROW]
[ROW][C]191[/C][C]0.75661[/C][C]0.486781[/C][C]0.24339[/C][/ROW]
[ROW][C]192[/C][C]0.738976[/C][C]0.522047[/C][C]0.261024[/C][/ROW]
[ROW][C]193[/C][C]0.77282[/C][C]0.454359[/C][C]0.22718[/C][/ROW]
[ROW][C]194[/C][C]0.791473[/C][C]0.417053[/C][C]0.208527[/C][/ROW]
[ROW][C]195[/C][C]0.766746[/C][C]0.466509[/C][C]0.233254[/C][/ROW]
[ROW][C]196[/C][C]0.737719[/C][C]0.524561[/C][C]0.262281[/C][/ROW]
[ROW][C]197[/C][C]0.71236[/C][C]0.575281[/C][C]0.28764[/C][/ROW]
[ROW][C]198[/C][C]0.679608[/C][C]0.640783[/C][C]0.320392[/C][/ROW]
[ROW][C]199[/C][C]0.649405[/C][C]0.701191[/C][C]0.350595[/C][/ROW]
[ROW][C]200[/C][C]0.626808[/C][C]0.746384[/C][C]0.373192[/C][/ROW]
[ROW][C]201[/C][C]0.716742[/C][C]0.566515[/C][C]0.283258[/C][/ROW]
[ROW][C]202[/C][C]0.686056[/C][C]0.627888[/C][C]0.313944[/C][/ROW]
[ROW][C]203[/C][C]0.654798[/C][C]0.690403[/C][C]0.345202[/C][/ROW]
[ROW][C]204[/C][C]0.632024[/C][C]0.735952[/C][C]0.367976[/C][/ROW]
[ROW][C]205[/C][C]0.604297[/C][C]0.791407[/C][C]0.395703[/C][/ROW]
[ROW][C]206[/C][C]0.57046[/C][C]0.859081[/C][C]0.42954[/C][/ROW]
[ROW][C]207[/C][C]0.575955[/C][C]0.848091[/C][C]0.424045[/C][/ROW]
[ROW][C]208[/C][C]0.540141[/C][C]0.919719[/C][C]0.459859[/C][/ROW]
[ROW][C]209[/C][C]0.579715[/C][C]0.84057[/C][C]0.420285[/C][/ROW]
[ROW][C]210[/C][C]0.571234[/C][C]0.857532[/C][C]0.428766[/C][/ROW]
[ROW][C]211[/C][C]0.550365[/C][C]0.89927[/C][C]0.449635[/C][/ROW]
[ROW][C]212[/C][C]0.52044[/C][C]0.95912[/C][C]0.47956[/C][/ROW]
[ROW][C]213[/C][C]0.497517[/C][C]0.995033[/C][C]0.502483[/C][/ROW]
[ROW][C]214[/C][C]0.469461[/C][C]0.938922[/C][C]0.530539[/C][/ROW]
[ROW][C]215[/C][C]0.453947[/C][C]0.907893[/C][C]0.546053[/C][/ROW]
[ROW][C]216[/C][C]0.417978[/C][C]0.835956[/C][C]0.582022[/C][/ROW]
[ROW][C]217[/C][C]0.395072[/C][C]0.790144[/C][C]0.604928[/C][/ROW]
[ROW][C]218[/C][C]0.432249[/C][C]0.864498[/C][C]0.567751[/C][/ROW]
[ROW][C]219[/C][C]0.40932[/C][C]0.81864[/C][C]0.59068[/C][/ROW]
[ROW][C]220[/C][C]0.379257[/C][C]0.758514[/C][C]0.620743[/C][/ROW]
[ROW][C]221[/C][C]0.402198[/C][C]0.804397[/C][C]0.597802[/C][/ROW]
[ROW][C]222[/C][C]0.448489[/C][C]0.896979[/C][C]0.551511[/C][/ROW]
[ROW][C]223[/C][C]0.414457[/C][C]0.828913[/C][C]0.585543[/C][/ROW]
[ROW][C]224[/C][C]0.391038[/C][C]0.782077[/C][C]0.608962[/C][/ROW]
[ROW][C]225[/C][C]0.486123[/C][C]0.972246[/C][C]0.513877[/C][/ROW]
[ROW][C]226[/C][C]0.457086[/C][C]0.914172[/C][C]0.542914[/C][/ROW]
[ROW][C]227[/C][C]0.461056[/C][C]0.922112[/C][C]0.538944[/C][/ROW]
[ROW][C]228[/C][C]0.431875[/C][C]0.863751[/C][C]0.568125[/C][/ROW]
[ROW][C]229[/C][C]0.498254[/C][C]0.996508[/C][C]0.501746[/C][/ROW]
[ROW][C]230[/C][C]0.598191[/C][C]0.803619[/C][C]0.401809[/C][/ROW]
[ROW][C]231[/C][C]0.628697[/C][C]0.742607[/C][C]0.371303[/C][/ROW]
[ROW][C]232[/C][C]0.70134[/C][C]0.597319[/C][C]0.29866[/C][/ROW]
[ROW][C]233[/C][C]0.657076[/C][C]0.685848[/C][C]0.342924[/C][/ROW]
[ROW][C]234[/C][C]0.610217[/C][C]0.779566[/C][C]0.389783[/C][/ROW]
[ROW][C]235[/C][C]0.607549[/C][C]0.784901[/C][C]0.392451[/C][/ROW]
[ROW][C]236[/C][C]0.881871[/C][C]0.236257[/C][C]0.118129[/C][/ROW]
[ROW][C]237[/C][C]0.861352[/C][C]0.277296[/C][C]0.138648[/C][/ROW]
[ROW][C]238[/C][C]0.830041[/C][C]0.339919[/C][C]0.169959[/C][/ROW]
[ROW][C]239[/C][C]0.825766[/C][C]0.348469[/C][C]0.174234[/C][/ROW]
[ROW][C]240[/C][C]0.794123[/C][C]0.411755[/C][C]0.205877[/C][/ROW]
[ROW][C]241[/C][C]0.754476[/C][C]0.491047[/C][C]0.245524[/C][/ROW]
[ROW][C]242[/C][C]0.708427[/C][C]0.583145[/C][C]0.291573[/C][/ROW]
[ROW][C]243[/C][C]0.661807[/C][C]0.676385[/C][C]0.338193[/C][/ROW]
[ROW][C]244[/C][C]0.831831[/C][C]0.336339[/C][C]0.168169[/C][/ROW]
[ROW][C]245[/C][C]0.801358[/C][C]0.397283[/C][C]0.198642[/C][/ROW]
[ROW][C]246[/C][C]0.764536[/C][C]0.470929[/C][C]0.235464[/C][/ROW]
[ROW][C]247[/C][C]0.767072[/C][C]0.465856[/C][C]0.232928[/C][/ROW]
[ROW][C]248[/C][C]0.740894[/C][C]0.518212[/C][C]0.259106[/C][/ROW]
[ROW][C]249[/C][C]0.716264[/C][C]0.567473[/C][C]0.283736[/C][/ROW]
[ROW][C]250[/C][C]0.660391[/C][C]0.679219[/C][C]0.339609[/C][/ROW]
[ROW][C]251[/C][C]0.604777[/C][C]0.790446[/C][C]0.395223[/C][/ROW]
[ROW][C]252[/C][C]0.546528[/C][C]0.906945[/C][C]0.453472[/C][/ROW]
[ROW][C]253[/C][C]0.495084[/C][C]0.990169[/C][C]0.504916[/C][/ROW]
[ROW][C]254[/C][C]0.698323[/C][C]0.603355[/C][C]0.301677[/C][/ROW]
[ROW][C]255[/C][C]0.812209[/C][C]0.375583[/C][C]0.187791[/C][/ROW]
[ROW][C]256[/C][C]0.767868[/C][C]0.464265[/C][C]0.232132[/C][/ROW]
[ROW][C]257[/C][C]0.819137[/C][C]0.361727[/C][C]0.180863[/C][/ROW]
[ROW][C]258[/C][C]0.945067[/C][C]0.109865[/C][C]0.0549326[/C][/ROW]
[ROW][C]259[/C][C]0.919691[/C][C]0.160617[/C][C]0.0803085[/C][/ROW]
[ROW][C]260[/C][C]0.981409[/C][C]0.037183[/C][C]0.0185915[/C][/ROW]
[ROW][C]261[/C][C]0.969193[/C][C]0.0616142[/C][C]0.0308071[/C][/ROW]
[ROW][C]262[/C][C]0.977559[/C][C]0.0448821[/C][C]0.022441[/C][/ROW]
[ROW][C]263[/C][C]0.960028[/C][C]0.0799447[/C][C]0.0399724[/C][/ROW]
[ROW][C]264[/C][C]0.969671[/C][C]0.0606586[/C][C]0.0303293[/C][/ROW]
[ROW][C]265[/C][C]0.959952[/C][C]0.0800955[/C][C]0.0400478[/C][/ROW]
[ROW][C]266[/C][C]0.919547[/C][C]0.160907[/C][C]0.0804533[/C][/ROW]
[ROW][C]267[/C][C]0.94917[/C][C]0.10166[/C][C]0.0508302[/C][/ROW]
[ROW][C]268[/C][C]0.893789[/C][C]0.212423[/C][C]0.106211[/C][/ROW]
[ROW][C]269[/C][C]0.875353[/C][C]0.249293[/C][C]0.124647[/C][/ROW]
[ROW][C]270[/C][C]0.908643[/C][C]0.182713[/C][C]0.0913567[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263940&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263940&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
90.4039920.8079830.596008
100.40190.8037990.5981
110.264850.5297010.73515
120.2676510.5353010.732349
130.2586080.5172160.741392
140.1974480.3948960.802552
150.1842970.3685940.815703
160.1423560.2847110.857644
170.09320460.1864090.906795
180.06271010.125420.93729
190.03960630.07921250.960394
200.02392450.04784910.976075
210.03209370.06418730.967906
220.03010570.06021140.969894
230.01938140.03876280.980619
240.0195860.0391720.980414
250.01347220.02694440.986528
260.008286320.01657260.991714
270.02700150.05400310.972998
280.0177570.0355140.982243
290.01193860.02387720.988061
300.007632180.01526440.992368
310.02144240.04288480.978558
320.01645650.03291290.983544
330.01549390.03098790.984506
340.01203170.02406350.987968
350.008449950.01689990.99155
360.005706590.01141320.994293
370.003744130.007488270.996256
380.002493780.004987560.997506
390.001952730.003905460.998047
400.00127340.00254680.998727
410.002865350.005730710.997135
420.002079230.004158460.997921
430.002199670.004399350.9978
440.001441620.002883250.998558
450.0009147220.001829440.999085
460.0006312250.001262450.999369
470.0004186580.0008373160.999581
480.0003728640.0007457270.999627
490.0002902620.0005805240.99971
500.0002255020.0004510040.999774
510.0001490860.0002981710.999851
520.0005788630.001157730.999421
530.0004034120.0008068240.999597
540.0003836230.0007672450.999616
550.0005500940.001100190.99945
560.0003783970.0007567940.999622
570.001588430.003176860.998412
580.001124210.002248420.998876
590.001282830.002565660.998717
600.001337610.002675210.998662
610.001061930.002123860.998938
620.000793940.001587880.999206
630.00230130.004602590.997699
640.004245180.008490360.995755
650.003814390.007628780.996186
660.003699960.007399920.9963
670.002713220.005426430.997287
680.002480110.004960210.99752
690.002845830.005691650.997154
700.002130090.004260190.99787
710.001593630.003187270.998406
720.001168170.002336350.998832
730.001138470.002276940.998862
740.001392870.002785750.998607
750.00110410.00220820.998896
760.0008876120.001775220.999112
770.0006447940.001289590.999355
780.0005747560.001149510.999425
790.0004525140.0009050280.999547
800.0005909010.00118180.999409
810.0004482270.0008964550.999552
820.0003951780.0007903550.999605
830.0002860670.0005721340.999714
840.001747450.003494890.998253
850.001414640.002829280.998585
860.001095810.002191620.998904
870.0008444860.001688970.999156
880.0006423340.001284670.999358
890.0006966040.001393210.999303
900.0005644480.00112890.999436
910.0004723150.0009446310.999528
920.001490250.00298050.99851
930.001283680.002567360.998716
940.001232830.002465650.998767
950.00180620.00361240.998194
960.001824550.00364910.998175
970.002800330.005600650.9972
980.002193610.004387220.997806
990.001832880.003665760.998167
1000.00245190.00490380.997548
1010.002043080.004086170.997957
1020.001734510.003469010.998265
1030.002159370.004318730.997841
1040.002026640.004053290.997973
1050.002103980.004207970.997896
1060.002472260.004944510.997528
1070.002237660.004475330.997762
1080.008529340.01705870.991471
1090.01852440.03704880.981476
1100.01984390.03968780.980156
1110.01757690.03515380.982423
1120.01663710.03327430.983363
1130.0720160.1440320.927984
1140.0655720.1311440.934428
1150.1306180.2612350.869382
1160.2106570.4213130.789343
1170.2623090.5246170.737691
1180.2413850.4827710.758615
1190.2893910.5787820.710609
1200.4297390.8594770.570261
1210.4681420.9362850.531858
1220.4415170.8830350.558483
1230.5106940.9786130.489306
1240.5054470.9891070.494553
1250.5030550.993890.496945
1260.4746630.9493260.525337
1270.5105030.9789950.489497
1280.4852770.9705530.514723
1290.6065620.7868760.393438
1300.5849290.8301430.415071
1310.5674680.8650640.432532
1320.5828790.8342410.417121
1330.5814360.8371280.418564
1340.5754420.8491170.424558
1350.5468840.9062320.453116
1360.5251180.9497640.474882
1370.5625410.8749180.437459
1380.6000620.7998760.399938
1390.6830490.6339020.316951
1400.6752840.6494330.324716
1410.6494050.701190.350595
1420.698020.6039610.30198
1430.6909040.6181920.309096
1440.7437820.5124370.256218
1450.7494030.5011940.250597
1460.7664650.467070.233535
1470.7482280.5035440.251772
1480.7258960.5482080.274104
1490.704180.591640.29582
1500.743780.512440.25622
1510.7457270.5085460.254273
1520.7409880.5180230.259012
1530.772430.455140.22757
1540.7807360.4385290.219264
1550.7602810.4794380.239719
1560.7390070.5219870.260993
1570.775610.4487790.22439
1580.7685890.4628230.231411
1590.7436060.5127890.256394
1600.7226440.5547130.277356
1610.7677530.4644940.232247
1620.7596650.480670.240335
1630.7637030.4725940.236297
1640.7468280.5063440.253172
1650.8027680.3944640.197232
1660.7857630.4284740.214237
1670.8340940.3318120.165906
1680.8190480.3619040.180952
1690.7991350.401730.200865
1700.7853350.4293310.214665
1710.7738660.4522670.226134
1720.8009350.398130.199065
1730.7827960.4344090.217204
1740.7619790.4760420.238021
1750.7411680.5176650.258832
1760.7716390.4567230.228361
1770.7438160.5123680.256184
1780.8082820.3834350.191718
1790.7912410.4175180.208759
1800.8430670.3138670.156933
1810.823180.3536390.17682
1820.8019330.3961330.198067
1830.8518080.2963840.148192
1840.8376140.3247710.162386
1850.8148260.3703470.185174
1860.8041220.3917550.195878
1870.8119620.3760760.188038
1880.7898810.4202380.210119
1890.7741260.4517470.225874
1900.7486510.5026990.251349
1910.756610.4867810.24339
1920.7389760.5220470.261024
1930.772820.4543590.22718
1940.7914730.4170530.208527
1950.7667460.4665090.233254
1960.7377190.5245610.262281
1970.712360.5752810.28764
1980.6796080.6407830.320392
1990.6494050.7011910.350595
2000.6268080.7463840.373192
2010.7167420.5665150.283258
2020.6860560.6278880.313944
2030.6547980.6904030.345202
2040.6320240.7359520.367976
2050.6042970.7914070.395703
2060.570460.8590810.42954
2070.5759550.8480910.424045
2080.5401410.9197190.459859
2090.5797150.840570.420285
2100.5712340.8575320.428766
2110.5503650.899270.449635
2120.520440.959120.47956
2130.4975170.9950330.502483
2140.4694610.9389220.530539
2150.4539470.9078930.546053
2160.4179780.8359560.582022
2170.3950720.7901440.604928
2180.4322490.8644980.567751
2190.409320.818640.59068
2200.3792570.7585140.620743
2210.4021980.8043970.597802
2220.4484890.8969790.551511
2230.4144570.8289130.585543
2240.3910380.7820770.608962
2250.4861230.9722460.513877
2260.4570860.9141720.542914
2270.4610560.9221120.538944
2280.4318750.8637510.568125
2290.4982540.9965080.501746
2300.5981910.8036190.401809
2310.6286970.7426070.371303
2320.701340.5973190.29866
2330.6570760.6858480.342924
2340.6102170.7795660.389783
2350.6075490.7849010.392451
2360.8818710.2362570.118129
2370.8613520.2772960.138648
2380.8300410.3399190.169959
2390.8257660.3484690.174234
2400.7941230.4117550.205877
2410.7544760.4910470.245524
2420.7084270.5831450.291573
2430.6618070.6763850.338193
2440.8318310.3363390.168169
2450.8013580.3972830.198642
2460.7645360.4709290.235464
2470.7670720.4658560.232928
2480.7408940.5182120.259106
2490.7162640.5674730.283736
2500.6603910.6792190.339609
2510.6047770.7904460.395223
2520.5465280.9069450.453472
2530.4950840.9901690.504916
2540.6983230.6033550.301677
2550.8122090.3755830.187791
2560.7678680.4642650.232132
2570.8191370.3617270.180863
2580.9450670.1098650.0549326
2590.9196910.1606170.0803085
2600.9814090.0371830.0185915
2610.9691930.06161420.0308071
2620.9775590.04488210.022441
2630.9600280.07994470.0399724
2640.9696710.06065860.0303293
2650.9599520.08009550.0400478
2660.9195470.1609070.0804533
2670.949170.101660.0508302
2680.8937890.2124230.106211
2690.8753530.2492930.124647
2700.9086430.1827130.0913567






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level710.270992NOK
5% type I error level920.351145NOK
10% type I error level1000.381679NOK

\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 & 71 & 0.270992 & NOK \tabularnewline
5% type I error level & 92 & 0.351145 & NOK \tabularnewline
10% type I error level & 100 & 0.381679 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263940&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]71[/C][C]0.270992[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]92[/C][C]0.351145[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]100[/C][C]0.381679[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263940&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263940&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level710.270992NOK
5% type I error level920.351145NOK
10% type I error level1000.381679NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = Pearson Chi-Squared ;
Parameters (R input):
par1 = 6 ; 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')
}