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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 computationSun, 30 Aug 2015 16:12:11 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Aug/30/t1440947545gx3jcsgzeseknhz.htm/, Retrieved Thu, 16 May 2024 13:19:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=280357, Retrieved Thu, 16 May 2024 13:19:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7.5 11 8 7 18 12 20 4
6 19 18 20 23 20 19 4
6.5 16 12 9 22 14 18 5
1 24 24 19 22 25 24 4
1 15 16 12 19 15 20 4
5.5 17 19 16 25 20 20 9
8.5 19 16 17 28 21 24 8
6.5 19 15 9 16 15 21 11
4.5 28 28 28 28 28 28 4
2 26 21 20 21 11 10 4
5 15 18 16 22 22 22 6
0.5 26 22 22 24 22 19 4
5 16 19 17 24 27 27 8
5 24 22 12 26 24 23 4
2.5 25 25 18 28 23 24 4
5 22 20 20 24 24 24 11
5.5 15 16 12 20 21 25 4
3.5 21 19 16 26 20 24 4
3 22 18 16 21 19 21 6
4 27 26 21 28 25 28 6
0.5 26 24 15 27 16 28 4
6.5 26 20 17 23 24 22 8
4.5 22 19 17 24 21 26 5
7.5 21 19 17 24 22 26 4
5.5 22 23 18 22 25 21 9
4 20 18 15 21 23 26 4
7.5 21 16 20 25 20 23 7
7 20 18 13 20 21 20 10
4 22 21 21 21 22 24 4
5.5 21 20 12 26 25 25 4
2.5 8 15 6 23 23 24 7
5.5 22 19 13 21 19 20 12
3.5 20 19 19 27 21 24 7
2.5 24 7 12 25 19 25 5
4.5 17 20 14 23 25 23 8
4.5 20 20 13 25 16 21 5
4.5 23 19 12 23 24 23 4
6 20 19 17 19 24 21 9
2.5 22 20 19 22 18 18 7
5 19 18 10 24 28 24 4
0 15 14 10 19 15 18 4
5 20 17 11 21 17 21 4
6.5 22 17 11 27 18 23 4
5 17 8 10 25 26 25 4
6 14 9 7 25 18 22 7
4.5 24 22 22 23 22 22 4
5.5 17 20 12 17 19 23 7
1 23 20 18 28 17 24 4
7.5 25 22 20 25 26 25 4
6 16 22 9 20 21 22 4
5 18 22 16 25 26 24 4
1 20 16 14 21 21 21 8
5 18 14 11 24 12 24 4
6.5 23 24 20 28 20 25 4
7 24 21 17 20 20 23 4
4.5 23 20 14 19 24 27 4
0 13 20 8 24 24 27 7
8.5 20 18 16 21 22 23 12
3.5 20 14 11 24 21 18 4
7.5 19 19 10 23 20 20 4
3.5 22 24 15 18 23 23 4
6 22 19 15 27 19 24 5
1.5 15 16 10 25 24 26 15
9 17 16 10 20 21 20 5
3.5 19 16 18 21 16 23 10
3.5 20 14 10 23 17 22 9
4 22 22 22 27 23 23 8
6.5 21 21 16 24 20 17 4
7.5 21 15 10 27 19 20 5
6 16 14 7 24 18 22 4
5 20 15 16 23 18 18 9
5.5 21 14 16 24 21 19 4
3.5 20 20 16 21 20 19 10
7.5 23 21 22 23 17 16 4
6.5 18 14 5 27 25 26 4
6.5 16 16 10 25 17 25 7
6.5 17 13 8 19 17 23 5
7 24 26 16 24 24 18 4
3.5 13 13 8 25 21 22 4
1.5 19 18 16 23 22 26 4
4 20 15 14 23 18 25 4
7.5 22 18 15 25 22 26 4
4.5 19 21 9 26 20 26 4
0 21 17 21 26 21 24 6
3.5 15 18 7 16 21 22 10
5.5 21 20 17 23 20 21 7
5 24 18 18 26 18 22 4
4.5 22 25 16 25 25 28 4
2.5 20 20 16 23 23 22 7
7.5 21 19 14 26 21 26 4
7 19 18 15 22 20 20 8
0 14 12 8 20 21 24 11
4.5 25 22 22 27 20 21 6
3 11 16 5 20 22 23 14
1.5 17 18 13 22 15 23 5
3.5 22 23 22 24 24 23 4
2.5 20 20 18 21 22 22 8
5.5 22 20 15 24 21 23 9
8 15 16 11 26 17 21 4
1 23 22 19 24 23 27 4
5 20 19 19 24 22 23 5
4.5 22 23 21 27 23 26 4
3 16 6 4 25 16 27 5
3 25 19 17 27 18 27 4
8 18 24 10 19 25 23 4
2.5 19 19 13 22 18 23 7
7 25 15 15 22 14 23 10
0 21 18 11 25 20 28 4
1 22 18 20 23 19 24 5
3.5 21 22 13 24 18 20 4
5.5 22 23 18 24 22 23 4
5.5 23 18 20 23 21 22 4
0.5 20 17 15 22 14 15 6
7.5 6 6 4 24 5 27 4
9 15 22 9 19 25 23 8
9.5 18 20 18 25 21 23 5
8.5 24 16 12 26 11 20 4
7 22 16 17 18 20 18 17
8 21 17 12 24 9 22 4
10 23 20 16 28 15 20 4
7 20 23 17 23 23 21 8
8.5 20 18 14 19 21 25 4
9 18 13 13 19 9 19 7
9.5 25 22 20 27 24 25 4
4 16 20 16 24 16 24 4
6 20 20 15 26 20 22 5
8 14 13 10 21 15 28 7
5.5 22 16 16 25 18 22 4
9.5 26 25 21 28 22 21 4
7.5 20 16 15 19 21 23 7
7 17 15 16 20 21 19 11
7.5 22 19 19 26 21 21 7
8 22 19 9 27 20 25 4
7 20 24 19 23 24 23 4
7 17 9 7 18 15 28 4
6 22 22 23 23 24 14 4
10 17 15 14 21 18 23 4
2.5 22 22 10 23 24 24 4
9 21 22 16 22 24 25 6
8 25 24 12 21 15 15 8
6 11 12 10 14 19 23 23
8.5 19 21 7 24 20 26 4
6 24 25 20 26 26 21 8
9 17 26 9 24 26 26 6
8 22 19 14 26 18 15 4
9 17 14 10 20 13 15 7
5.5 26 28 19 20 16 16 4
5 19 16 16 20 19 20 4
5.5 19 16 15 18 21 20 4
9 21 16 14 25 11 21 10
2 24 25 11 28 23 28 6
8.5 21 21 14 23 18 19 5
9 19 22 15 20 19 21 5
8.5 13 9 7 22 15 22 4
9 24 20 22 27 8 27 4
7.5 28 19 19 24 15 20 5
10 27 24 22 23 21 17 5
9 22 22 11 20 25 26 5
7.5 23 22 19 22 14 21 5
6 19 12 9 21 21 24 4
10.5 18 17 11 24 18 21 6
8.5 23 18 17 26 18 25 4
8 21 10 12 24 12 22 4
10 22 22 17 18 24 17 4
10.5 17 24 10 17 17 14 9
6.5 15 18 17 23 20 23 18
9.5 21 18 13 21 24 28 6
8.5 20 23 11 21 22 24 5
7.5 26 21 19 24 15 22 4
5 19 21 21 22 22 24 11
8 28 28 24 24 26 25 4
10 21 17 13 24 17 21 10
7 19 21 16 24 23 22 6
7.5 22 21 13 23 19 16 8
7.5 21 20 15 21 21 18 8
9.5 20 18 15 24 23 27 6
6 19 17 11 19 19 17 8
10 11 7 7 19 18 25 4
7 17 17 13 23 16 24 4
3 19 14 13 25 23 21 9
6 20 18 12 24 13 21 9
7 17 14 8 21 18 19 5
10 21 23 7 18 23 27 4
7 21 20 17 23 21 28 4
3.5 12 14 9 20 23 19 15
8 23 17 18 23 16 23 10
10 22 21 17 23 17 25 9
5.5 22 23 17 23 20 26 7
6 21 24 18 23 18 25 9
6.5 20 21 12 27 20 25 6
6.5 18 14 14 19 19 24 4
8.5 21 24 22 25 26 24 7
4 24 16 19 25 9 24 4
9.5 22 21 21 21 23 22 7
8 20 8 10 25 9 21 4
8.5 17 17 16 17 13 17 15
5.5 19 18 11 22 27 23 4
7 16 17 15 23 22 17 9
9 19 16 12 27 12 25 4
8 23 22 21 27 18 19 4
10 8 17 22 5 6 8 28
8 22 21 20 19 17 14 4
6 23 20 15 24 22 22 4
8 15 20 9 23 22 25 4
5 17 19 15 28 23 28 5
9 21 8 14 25 19 25 4
4.5 25 19 11 27 20 24 4
8.5 18 11 9 16 17 15 12
7 23 15 18 23 18 25 5
8.5 21 18 11 26 20 28 6
7.5 21 19 14 24 18 24 6
7.5 24 23 10 23 23 25 5
5 22 20 18 24 27 23 4
7 22 22 11 27 25 26 4
8 23 19 14 25 24 26 4
5.5 17 16 16 19 12 22 10
8.5 15 11 11 19 16 25 7
7.5 24 11 8 14 16 20 4
7 19 14 13 20 23 26 7
8 18 21 12 21 24 20 4
8.5 21 20 17 28 24 26 4
3.5 20 21 23 26 26 26 12
6.5 19 20 14 19 19 21 5
6.5 19 19 10 23 28 21 8
10.5 16 19 16 23 23 24 6
8.5 18 18 11 21 21 21 17
8 23 20 16 26 19 18 4
10 22 21 19 25 23 23 5
10 23 22 17 25 23 26 4
9.5 20 19 12 24 20 23 5
9 24 23 17 23 18 25 5
10 25 16 11 22 20 20 6
7.5 25 23 19 27 28 25 4
4.5 20 18 12 26 21 26 4
4.5 23 23 8 23 25 19 4
0.5 21 20 17 22 18 21 6
6.5 23 20 13 26 24 23 8
4.5 23 23 17 22 28 24 10
5.5 11 13 7 17 9 6 4
5 21 21 23 25 22 22 5
6 27 26 18 22 26 21 4
4 19 18 13 28 28 28 4
8 21 19 17 22 18 24 4
10.5 16 18 13 21 23 14 16
8.5 22 19 13 21 22 17 4
8 22 19 16 26 24 28 4
8.5 16 13 14 26 12 19 4
5.5 18 10 13 24 12 24 14
7 23 21 19 27 20 21 5
5 24 24 15 22 25 21 5
3.5 20 21 15 23 24 26 5
5 20 23 8 22 23 24 5
9 18 18 14 23 18 26 7
8.5 4 11 7 15 20 25 19
5 14 16 11 20 22 23 16
9.5 22 20 17 22 20 24 4
3 17 20 19 25 25 24 4
1.5 23 26 17 27 28 26 7
6 20 21 12 24 25 23 9
0.5 18 12 12 21 14 20 5
6.5 19 15 18 17 16 16 14
7.5 20 18 16 26 24 24 4
4.5 15 14 15 20 13 20 16
8 24 18 20 22 19 23 10
9 21 16 16 24 18 23 5
7.5 19 19 12 23 16 18 6
8.5 19 7 10 22 8 21 4
7 27 21 28 28 27 25 4
9.5 23 24 19 21 23 23 4
6.5 23 21 18 24 20 26 5
9.5 20 20 19 28 20 26 4
6 17 22 8 25 26 24 4
8 21 17 17 24 23 23 5
9.5 23 19 16 24 24 21 4
8 22 20 18 21 21 23 4
8 16 16 12 20 15 20 5
9 20 20 17 26 22 23 8
5 16 16 13 16 25 24 15

Tables (Output of Computation)





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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280357&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280357&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280357&T=0

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


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

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






Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 8.75483 + 0.0502345AMS.I1[t] + 0.0274333AMS.I2[t] -0.0293258AMS.I3[t] -0.0690228AMS.E1[t] -0.0664993AMS.E2[t] -0.0328728AMS.E3[t] -0.00340108AMS.A[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  8.75483 +  0.0502345AMS.I1[t] +  0.0274333AMS.I2[t] -0.0293258AMS.I3[t] -0.0690228AMS.E1[t] -0.0664993AMS.E2[t] -0.0328728AMS.E3[t] -0.00340108AMS.A[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280357&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  8.75483 +  0.0502345AMS.I1[t] +  0.0274333AMS.I2[t] -0.0293258AMS.I3[t] -0.0690228AMS.E1[t] -0.0664993AMS.E2[t] -0.0328728AMS.E3[t] -0.00340108AMS.A[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280357&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280357&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 8.75483 + 0.0502345AMS.I1[t] + 0.0274333AMS.I2[t] -0.0293258AMS.I3[t] -0.0690228AMS.E1[t] -0.0664993AMS.E2[t] -0.0328728AMS.E3[t] -0.00340108AMS.A[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.754831.720275.0896.74541e-073.3727e-07
AMS.I10.05023450.06107410.82250.4115080.205754
AMS.I20.02743330.05324120.51530.606790.303395
AMS.I3-0.02932580.0465531-0.62990.5292650.264632
AMS.E1-0.06902280.0623091-1.1080.2689560.134478
AMS.E2-0.06649930.0440553-1.5090.1323530.0661765
AMS.E3-0.03287280.051824-0.63430.5264110.263206
AMS.A-0.003401080.052701-0.064540.9485920.474296

\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) & 8.75483 & 1.72027 & 5.089 & 6.74541e-07 & 3.3727e-07 \tabularnewline
AMS.I1 & 0.0502345 & 0.0610741 & 0.8225 & 0.411508 & 0.205754 \tabularnewline
AMS.I2 & 0.0274333 & 0.0532412 & 0.5153 & 0.60679 & 0.303395 \tabularnewline
AMS.I3 & -0.0293258 & 0.0465531 & -0.6299 & 0.529265 & 0.264632 \tabularnewline
AMS.E1 & -0.0690228 & 0.0623091 & -1.108 & 0.268956 & 0.134478 \tabularnewline
AMS.E2 & -0.0664993 & 0.0440553 & -1.509 & 0.132353 & 0.0661765 \tabularnewline
AMS.E3 & -0.0328728 & 0.051824 & -0.6343 & 0.526411 & 0.263206 \tabularnewline
AMS.A & -0.00340108 & 0.052701 & -0.06454 & 0.948592 & 0.474296 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280357&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]8.75483[/C][C]1.72027[/C][C]5.089[/C][C]6.74541e-07[/C][C]3.3727e-07[/C][/ROW]
[ROW][C]AMS.I1[/C][C]0.0502345[/C][C]0.0610741[/C][C]0.8225[/C][C]0.411508[/C][C]0.205754[/C][/ROW]
[ROW][C]AMS.I2[/C][C]0.0274333[/C][C]0.0532412[/C][C]0.5153[/C][C]0.60679[/C][C]0.303395[/C][/ROW]
[ROW][C]AMS.I3[/C][C]-0.0293258[/C][C]0.0465531[/C][C]-0.6299[/C][C]0.529265[/C][C]0.264632[/C][/ROW]
[ROW][C]AMS.E1[/C][C]-0.0690228[/C][C]0.0623091[/C][C]-1.108[/C][C]0.268956[/C][C]0.134478[/C][/ROW]
[ROW][C]AMS.E2[/C][C]-0.0664993[/C][C]0.0440553[/C][C]-1.509[/C][C]0.132353[/C][C]0.0661765[/C][/ROW]
[ROW][C]AMS.E3[/C][C]-0.0328728[/C][C]0.051824[/C][C]-0.6343[/C][C]0.526411[/C][C]0.263206[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.00340108[/C][C]0.052701[/C][C]-0.06454[/C][C]0.948592[/C][C]0.474296[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280357&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280357&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)8.754831.720275.0896.74541e-073.3727e-07
AMS.I10.05023450.06107410.82250.4115080.205754
AMS.I20.02743330.05324120.51530.606790.303395
AMS.I3-0.02932580.0465531-0.62990.5292650.264632
AMS.E1-0.06902280.0623091-1.1080.2689560.134478
AMS.E2-0.06649930.0440553-1.5090.1323530.0661765
AMS.E3-0.03287280.051824-0.63430.5264110.263206
AMS.A-0.003401080.052701-0.064540.9485920.474296






Multiple Linear Regression - Regression Statistics
Multiple R0.1673
R-squared0.0279893
Adjusted R-squared0.00278898
F-TEST (value)1.11067
F-TEST (DF numerator)7
F-TEST (DF denominator)270
p-value0.356496
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.52035
Sum Squared Residuals1715.09

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.1673 \tabularnewline
R-squared & 0.0279893 \tabularnewline
Adjusted R-squared & 0.00278898 \tabularnewline
F-TEST (value) & 1.11067 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 270 \tabularnewline
p-value & 0.356496 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.52035 \tabularnewline
Sum Squared Residuals & 1715.09 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280357&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.1673[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0279893[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.00278898[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]1.11067[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]270[/C][/ROW]
[ROW][C]p-value[/C][C]0.356496[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.52035[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1715.09[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280357&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280357&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 R0.1673
R-squared0.0279893
Adjusted R-squared0.00278898
F-TEST (value)1.11067
F-TEST (DF numerator)7
F-TEST (DF denominator)270
p-value0.356496
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.52035
Sum Squared Residuals1715.09






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.56.610140.889865
266.06087-0.0608734
36.56.56564-0.0656442
416.07813-5.07813
516.61539-5.61539
65.55.91722-0.417217
78.55.50442.9956
86.57.02726-0.52726
94.55.37975-0.879747
1027.52721-5.52721
1155.80784-0.807842
120.56.26158-5.76158
1355.21448-0.214476
1456.05183-1.05183
152.55.90399-3.40399
1655.74325-0.743252
175.55.98301-0.483007
183.55.93465-2.43465
1936.46088-3.46088
2045.67262-1.67262
210.56.41779-5.91779
226.56.177140.322861
234.55.95795-1.45795
247.55.844621.65538
255.56.06117-0.56117
2645.96617-1.96617
277.55.826741.67326
2876.403680.596322
2946.10523-2.10523
305.55.71401-0.214013
312.55.46249-2.96249
325.56.58875-1.08875
333.55.65071-2.15071
342.55.9727-3.4727
354.55.71363-1.21363
364.56.43006-1.93006
374.56.12636-1.62636
3866.15386-0.153862
392.56.52046-4.02046
4055.58875-0.58875
4106.68492-6.68492
4256.6194-1.6194
436.56.173490.326508
4455.24505-0.245051
4565.830170.169832
464.56.13151-1.63151
475.56.58882-1.08882
4816.06535-5.06535
497.55.737741.76226
5066.38444-0.384437
5155.53627-0.53627
5216.22439-5.22439
5356.46345-1.46345
546.55.884060.61594
5576.55790.4421
564.56.23974-1.73974
5705.55804-5.55804
588.56.074762.42524
593.56.16266-2.66266
607.56.348691.15131
613.56.53693-3.03693
6266.00828-0.00828202
631.55.42676-3.92676
6496.303092.69691
653.56.3168-2.8168
663.56.37851-2.87851
6745.64197-1.64197
686.56.357670.142332
697.56.126431.37357
7066.14703-0.147029
7156.29498-1.29498
725.56.03339-0.53339
733.56.40092-2.90092
747.56.583580.916424
756.55.50210.997905
766.56.002570.497427
776.56.51584-0.0158443
7876.346670.653332
793.55.67105-2.17105
801.55.81507-4.31507
8146.14052-2.14052
827.55.857051.64295
834.56.02858-1.52858
8405.65985-5.65985
853.56.53881-3.03881
865.56.22824-0.728238
8756.19801-1.19801
884.55.75452-1.25452
892.55.97496-3.47496
907.55.861051.63895
9176.230050.769952
9205.94941-5.94941
934.56.06472-1.56472
9435.95259-2.95259
951.56.43231-4.93231
963.55.82358-2.32358
972.56.11745-3.61745
985.56.12905-0.629054
9985.995682.00432
10015.86937-4.86937
10155.83095-0.830953
1024.55.61372-1.11372
10335.91175-2.91175
10436.07162-3.07162
10586.28061.7194
1062.56.35391-3.85391
10776.742730.257269
10805.99137-5.99137
10916.11031-5.11031
1103.56.50746-3.00746
1115.56.07388-0.573882
1125.56.09669-0.596694
1130.56.82301-6.32301
1147.56.213321.28668
11596.090752.90925
1169.55.784723.71528
1178.56.850341.64966
11876.578460.421539
11986.932371.06763
120106.388493.61151
12176.05740.942596
1228.56.299422.20058
12397.076131.92387
1249.55.732693.76731
12546.11495-2.11495
12666.00352-0.00351543
12786.130281.86972
1285.56.17035-0.670348
1299.56.031363.46864
1307.56.270771.22923
13176.112170.887831
1327.55.918821.58118
13386.088271.91173
13475.907541.09246
13576.47650.523505
13666.1317-0.1317
137106.193613.80639
1382.56.18421-3.68421
13995.987373.01263
14087.349920.650084
14166.27925-0.279248
1428.56.225282.27472
14365.818660.181335
14495.797523.20248
14586.472391.52761
14696.937782.06222
1475.57.28786-1.78786
14856.36401-1.36401
1495.56.39838-0.898378
15096.656732.34327
15125.92074-3.92074
1528.56.549191.95081
15396.521662.47834
1548.56.19672.3033
15596.567182.43282
1567.56.796940.703057
157106.564543.43546
15896.22632.7737
1597.56.799740.700258
16066.12604-0.12604
16110.56.238574.26143
1628.56.078482.42152
16386.540841.45916
164106.554153.44585
16510.57.179263.32074
1666.55.768810.731194
1679.55.936013.56399
1688.56.349492.15051
1697.56.6890.811004
17055.8617-0.8617
17186.004761.99524
172106.383513.61649
17375.886541.11346
1747.56.650670.849329
1757.56.453651.04635
1769.55.719433.78057
17766.6921-0.692104
178105.950324.04968
17976.239880.760115
18035.73613-2.73613
18166.65944-0.659435
18276.470220.529776
183106.562383.43762
18475.941831.05817
1853.55.89224-2.39224
18686.407131.59287
187106.367113.63289
1885.56.19641-0.696408
18966.30335-0.30335
1906.55.947880.552116
1916.56.255090.244913
1928.55.555682.94432
19346.71559-2.71559
1949.56.094283.40572
19586.657731.34227
1968.56.958241.54176
1975.55.79684-0.296842
19875.945111.05489
19996.299282.70072
20086.199131.80087
201107.875582.12442
20286.933831.06617
20366.16267-0.162667
20485.907152.09285
20555.2906-0.290598
20695.794183.20582
2074.56.21319-1.71319
2088.56.928131.57187
20976.170520.829476
2108.55.915552.58445
2117.56.257541.24246
2127.56.342331.15767
21355.65909-0.659086
21475.746541.25346
21585.831052.16895
2165.56.7119-1.2119
2178.56.266482.23352
2187.57.326250.173748
21975.923681.07632
22086.166721.83328
2218.55.462973.03703
2223.55.24205-1.74205
2236.56.56514-0.0651386
2246.55.770220.72978
22510.55.684244.81576
2268.56.236162.26384
22786.326281.67372
228105.850774.14923
229105.891874.10813
2309.56.169233.33077
23196.469552.53045
232106.600693.39931
2337.55.523451.97655
2344.55.84204-1.34204
2354.56.41839-1.91839
2360.56.43366-5.93366
2376.55.90380.596203
2384.55.83921-1.33921
2395.57.47604-1.97604
24055.7826-0.782601
24166.34515-0.345149
24245.09319-1.09319
24386.314411.68559
24410.56.177554.32245
2458.56.515081.98492
24685.587392.41261
2478.56.273882.22612
2485.56.26105-0.76105
24976.02820.971801
25056.29065-1.29065
2513.55.84053-2.34053
25256.30194-1.30194
25396.079282.92072
2548.55.800492.69951
25555.92053-0.920532
2569.56.259083.24092
25735.40969-2.40969
2581.55.52086-4.02086
25965.8780.122002
2600.56.58141-6.08141
2616.56.78197-0.281967
2627.55.590981.90902
2634.56.49571-1.99571
26486.295671.70433
26596.152862.84714
2667.56.614980.885019
2678.56.853631.64637
26875.30261.6974
2699.56.262793.23721
2706.56.100230.399771
2719.55.620083.87992
27265.720640.279359
27385.818472.18153
2749.56.005783.49422
27586.265151.73485
27686.59321.4068
27795.768793.23121
27856.00947-1.00947

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 6.61014 & 0.889865 \tabularnewline
2 & 6 & 6.06087 & -0.0608734 \tabularnewline
3 & 6.5 & 6.56564 & -0.0656442 \tabularnewline
4 & 1 & 6.07813 & -5.07813 \tabularnewline
5 & 1 & 6.61539 & -5.61539 \tabularnewline
6 & 5.5 & 5.91722 & -0.417217 \tabularnewline
7 & 8.5 & 5.5044 & 2.9956 \tabularnewline
8 & 6.5 & 7.02726 & -0.52726 \tabularnewline
9 & 4.5 & 5.37975 & -0.879747 \tabularnewline
10 & 2 & 7.52721 & -5.52721 \tabularnewline
11 & 5 & 5.80784 & -0.807842 \tabularnewline
12 & 0.5 & 6.26158 & -5.76158 \tabularnewline
13 & 5 & 5.21448 & -0.214476 \tabularnewline
14 & 5 & 6.05183 & -1.05183 \tabularnewline
15 & 2.5 & 5.90399 & -3.40399 \tabularnewline
16 & 5 & 5.74325 & -0.743252 \tabularnewline
17 & 5.5 & 5.98301 & -0.483007 \tabularnewline
18 & 3.5 & 5.93465 & -2.43465 \tabularnewline
19 & 3 & 6.46088 & -3.46088 \tabularnewline
20 & 4 & 5.67262 & -1.67262 \tabularnewline
21 & 0.5 & 6.41779 & -5.91779 \tabularnewline
22 & 6.5 & 6.17714 & 0.322861 \tabularnewline
23 & 4.5 & 5.95795 & -1.45795 \tabularnewline
24 & 7.5 & 5.84462 & 1.65538 \tabularnewline
25 & 5.5 & 6.06117 & -0.56117 \tabularnewline
26 & 4 & 5.96617 & -1.96617 \tabularnewline
27 & 7.5 & 5.82674 & 1.67326 \tabularnewline
28 & 7 & 6.40368 & 0.596322 \tabularnewline
29 & 4 & 6.10523 & -2.10523 \tabularnewline
30 & 5.5 & 5.71401 & -0.214013 \tabularnewline
31 & 2.5 & 5.46249 & -2.96249 \tabularnewline
32 & 5.5 & 6.58875 & -1.08875 \tabularnewline
33 & 3.5 & 5.65071 & -2.15071 \tabularnewline
34 & 2.5 & 5.9727 & -3.4727 \tabularnewline
35 & 4.5 & 5.71363 & -1.21363 \tabularnewline
36 & 4.5 & 6.43006 & -1.93006 \tabularnewline
37 & 4.5 & 6.12636 & -1.62636 \tabularnewline
38 & 6 & 6.15386 & -0.153862 \tabularnewline
39 & 2.5 & 6.52046 & -4.02046 \tabularnewline
40 & 5 & 5.58875 & -0.58875 \tabularnewline
41 & 0 & 6.68492 & -6.68492 \tabularnewline
42 & 5 & 6.6194 & -1.6194 \tabularnewline
43 & 6.5 & 6.17349 & 0.326508 \tabularnewline
44 & 5 & 5.24505 & -0.245051 \tabularnewline
45 & 6 & 5.83017 & 0.169832 \tabularnewline
46 & 4.5 & 6.13151 & -1.63151 \tabularnewline
47 & 5.5 & 6.58882 & -1.08882 \tabularnewline
48 & 1 & 6.06535 & -5.06535 \tabularnewline
49 & 7.5 & 5.73774 & 1.76226 \tabularnewline
50 & 6 & 6.38444 & -0.384437 \tabularnewline
51 & 5 & 5.53627 & -0.53627 \tabularnewline
52 & 1 & 6.22439 & -5.22439 \tabularnewline
53 & 5 & 6.46345 & -1.46345 \tabularnewline
54 & 6.5 & 5.88406 & 0.61594 \tabularnewline
55 & 7 & 6.5579 & 0.4421 \tabularnewline
56 & 4.5 & 6.23974 & -1.73974 \tabularnewline
57 & 0 & 5.55804 & -5.55804 \tabularnewline
58 & 8.5 & 6.07476 & 2.42524 \tabularnewline
59 & 3.5 & 6.16266 & -2.66266 \tabularnewline
60 & 7.5 & 6.34869 & 1.15131 \tabularnewline
61 & 3.5 & 6.53693 & -3.03693 \tabularnewline
62 & 6 & 6.00828 & -0.00828202 \tabularnewline
63 & 1.5 & 5.42676 & -3.92676 \tabularnewline
64 & 9 & 6.30309 & 2.69691 \tabularnewline
65 & 3.5 & 6.3168 & -2.8168 \tabularnewline
66 & 3.5 & 6.37851 & -2.87851 \tabularnewline
67 & 4 & 5.64197 & -1.64197 \tabularnewline
68 & 6.5 & 6.35767 & 0.142332 \tabularnewline
69 & 7.5 & 6.12643 & 1.37357 \tabularnewline
70 & 6 & 6.14703 & -0.147029 \tabularnewline
71 & 5 & 6.29498 & -1.29498 \tabularnewline
72 & 5.5 & 6.03339 & -0.53339 \tabularnewline
73 & 3.5 & 6.40092 & -2.90092 \tabularnewline
74 & 7.5 & 6.58358 & 0.916424 \tabularnewline
75 & 6.5 & 5.5021 & 0.997905 \tabularnewline
76 & 6.5 & 6.00257 & 0.497427 \tabularnewline
77 & 6.5 & 6.51584 & -0.0158443 \tabularnewline
78 & 7 & 6.34667 & 0.653332 \tabularnewline
79 & 3.5 & 5.67105 & -2.17105 \tabularnewline
80 & 1.5 & 5.81507 & -4.31507 \tabularnewline
81 & 4 & 6.14052 & -2.14052 \tabularnewline
82 & 7.5 & 5.85705 & 1.64295 \tabularnewline
83 & 4.5 & 6.02858 & -1.52858 \tabularnewline
84 & 0 & 5.65985 & -5.65985 \tabularnewline
85 & 3.5 & 6.53881 & -3.03881 \tabularnewline
86 & 5.5 & 6.22824 & -0.728238 \tabularnewline
87 & 5 & 6.19801 & -1.19801 \tabularnewline
88 & 4.5 & 5.75452 & -1.25452 \tabularnewline
89 & 2.5 & 5.97496 & -3.47496 \tabularnewline
90 & 7.5 & 5.86105 & 1.63895 \tabularnewline
91 & 7 & 6.23005 & 0.769952 \tabularnewline
92 & 0 & 5.94941 & -5.94941 \tabularnewline
93 & 4.5 & 6.06472 & -1.56472 \tabularnewline
94 & 3 & 5.95259 & -2.95259 \tabularnewline
95 & 1.5 & 6.43231 & -4.93231 \tabularnewline
96 & 3.5 & 5.82358 & -2.32358 \tabularnewline
97 & 2.5 & 6.11745 & -3.61745 \tabularnewline
98 & 5.5 & 6.12905 & -0.629054 \tabularnewline
99 & 8 & 5.99568 & 2.00432 \tabularnewline
100 & 1 & 5.86937 & -4.86937 \tabularnewline
101 & 5 & 5.83095 & -0.830953 \tabularnewline
102 & 4.5 & 5.61372 & -1.11372 \tabularnewline
103 & 3 & 5.91175 & -2.91175 \tabularnewline
104 & 3 & 6.07162 & -3.07162 \tabularnewline
105 & 8 & 6.2806 & 1.7194 \tabularnewline
106 & 2.5 & 6.35391 & -3.85391 \tabularnewline
107 & 7 & 6.74273 & 0.257269 \tabularnewline
108 & 0 & 5.99137 & -5.99137 \tabularnewline
109 & 1 & 6.11031 & -5.11031 \tabularnewline
110 & 3.5 & 6.50746 & -3.00746 \tabularnewline
111 & 5.5 & 6.07388 & -0.573882 \tabularnewline
112 & 5.5 & 6.09669 & -0.596694 \tabularnewline
113 & 0.5 & 6.82301 & -6.32301 \tabularnewline
114 & 7.5 & 6.21332 & 1.28668 \tabularnewline
115 & 9 & 6.09075 & 2.90925 \tabularnewline
116 & 9.5 & 5.78472 & 3.71528 \tabularnewline
117 & 8.5 & 6.85034 & 1.64966 \tabularnewline
118 & 7 & 6.57846 & 0.421539 \tabularnewline
119 & 8 & 6.93237 & 1.06763 \tabularnewline
120 & 10 & 6.38849 & 3.61151 \tabularnewline
121 & 7 & 6.0574 & 0.942596 \tabularnewline
122 & 8.5 & 6.29942 & 2.20058 \tabularnewline
123 & 9 & 7.07613 & 1.92387 \tabularnewline
124 & 9.5 & 5.73269 & 3.76731 \tabularnewline
125 & 4 & 6.11495 & -2.11495 \tabularnewline
126 & 6 & 6.00352 & -0.00351543 \tabularnewline
127 & 8 & 6.13028 & 1.86972 \tabularnewline
128 & 5.5 & 6.17035 & -0.670348 \tabularnewline
129 & 9.5 & 6.03136 & 3.46864 \tabularnewline
130 & 7.5 & 6.27077 & 1.22923 \tabularnewline
131 & 7 & 6.11217 & 0.887831 \tabularnewline
132 & 7.5 & 5.91882 & 1.58118 \tabularnewline
133 & 8 & 6.08827 & 1.91173 \tabularnewline
134 & 7 & 5.90754 & 1.09246 \tabularnewline
135 & 7 & 6.4765 & 0.523505 \tabularnewline
136 & 6 & 6.1317 & -0.1317 \tabularnewline
137 & 10 & 6.19361 & 3.80639 \tabularnewline
138 & 2.5 & 6.18421 & -3.68421 \tabularnewline
139 & 9 & 5.98737 & 3.01263 \tabularnewline
140 & 8 & 7.34992 & 0.650084 \tabularnewline
141 & 6 & 6.27925 & -0.279248 \tabularnewline
142 & 8.5 & 6.22528 & 2.27472 \tabularnewline
143 & 6 & 5.81866 & 0.181335 \tabularnewline
144 & 9 & 5.79752 & 3.20248 \tabularnewline
145 & 8 & 6.47239 & 1.52761 \tabularnewline
146 & 9 & 6.93778 & 2.06222 \tabularnewline
147 & 5.5 & 7.28786 & -1.78786 \tabularnewline
148 & 5 & 6.36401 & -1.36401 \tabularnewline
149 & 5.5 & 6.39838 & -0.898378 \tabularnewline
150 & 9 & 6.65673 & 2.34327 \tabularnewline
151 & 2 & 5.92074 & -3.92074 \tabularnewline
152 & 8.5 & 6.54919 & 1.95081 \tabularnewline
153 & 9 & 6.52166 & 2.47834 \tabularnewline
154 & 8.5 & 6.1967 & 2.3033 \tabularnewline
155 & 9 & 6.56718 & 2.43282 \tabularnewline
156 & 7.5 & 6.79694 & 0.703057 \tabularnewline
157 & 10 & 6.56454 & 3.43546 \tabularnewline
158 & 9 & 6.2263 & 2.7737 \tabularnewline
159 & 7.5 & 6.79974 & 0.700258 \tabularnewline
160 & 6 & 6.12604 & -0.12604 \tabularnewline
161 & 10.5 & 6.23857 & 4.26143 \tabularnewline
162 & 8.5 & 6.07848 & 2.42152 \tabularnewline
163 & 8 & 6.54084 & 1.45916 \tabularnewline
164 & 10 & 6.55415 & 3.44585 \tabularnewline
165 & 10.5 & 7.17926 & 3.32074 \tabularnewline
166 & 6.5 & 5.76881 & 0.731194 \tabularnewline
167 & 9.5 & 5.93601 & 3.56399 \tabularnewline
168 & 8.5 & 6.34949 & 2.15051 \tabularnewline
169 & 7.5 & 6.689 & 0.811004 \tabularnewline
170 & 5 & 5.8617 & -0.8617 \tabularnewline
171 & 8 & 6.00476 & 1.99524 \tabularnewline
172 & 10 & 6.38351 & 3.61649 \tabularnewline
173 & 7 & 5.88654 & 1.11346 \tabularnewline
174 & 7.5 & 6.65067 & 0.849329 \tabularnewline
175 & 7.5 & 6.45365 & 1.04635 \tabularnewline
176 & 9.5 & 5.71943 & 3.78057 \tabularnewline
177 & 6 & 6.6921 & -0.692104 \tabularnewline
178 & 10 & 5.95032 & 4.04968 \tabularnewline
179 & 7 & 6.23988 & 0.760115 \tabularnewline
180 & 3 & 5.73613 & -2.73613 \tabularnewline
181 & 6 & 6.65944 & -0.659435 \tabularnewline
182 & 7 & 6.47022 & 0.529776 \tabularnewline
183 & 10 & 6.56238 & 3.43762 \tabularnewline
184 & 7 & 5.94183 & 1.05817 \tabularnewline
185 & 3.5 & 5.89224 & -2.39224 \tabularnewline
186 & 8 & 6.40713 & 1.59287 \tabularnewline
187 & 10 & 6.36711 & 3.63289 \tabularnewline
188 & 5.5 & 6.19641 & -0.696408 \tabularnewline
189 & 6 & 6.30335 & -0.30335 \tabularnewline
190 & 6.5 & 5.94788 & 0.552116 \tabularnewline
191 & 6.5 & 6.25509 & 0.244913 \tabularnewline
192 & 8.5 & 5.55568 & 2.94432 \tabularnewline
193 & 4 & 6.71559 & -2.71559 \tabularnewline
194 & 9.5 & 6.09428 & 3.40572 \tabularnewline
195 & 8 & 6.65773 & 1.34227 \tabularnewline
196 & 8.5 & 6.95824 & 1.54176 \tabularnewline
197 & 5.5 & 5.79684 & -0.296842 \tabularnewline
198 & 7 & 5.94511 & 1.05489 \tabularnewline
199 & 9 & 6.29928 & 2.70072 \tabularnewline
200 & 8 & 6.19913 & 1.80087 \tabularnewline
201 & 10 & 7.87558 & 2.12442 \tabularnewline
202 & 8 & 6.93383 & 1.06617 \tabularnewline
203 & 6 & 6.16267 & -0.162667 \tabularnewline
204 & 8 & 5.90715 & 2.09285 \tabularnewline
205 & 5 & 5.2906 & -0.290598 \tabularnewline
206 & 9 & 5.79418 & 3.20582 \tabularnewline
207 & 4.5 & 6.21319 & -1.71319 \tabularnewline
208 & 8.5 & 6.92813 & 1.57187 \tabularnewline
209 & 7 & 6.17052 & 0.829476 \tabularnewline
210 & 8.5 & 5.91555 & 2.58445 \tabularnewline
211 & 7.5 & 6.25754 & 1.24246 \tabularnewline
212 & 7.5 & 6.34233 & 1.15767 \tabularnewline
213 & 5 & 5.65909 & -0.659086 \tabularnewline
214 & 7 & 5.74654 & 1.25346 \tabularnewline
215 & 8 & 5.83105 & 2.16895 \tabularnewline
216 & 5.5 & 6.7119 & -1.2119 \tabularnewline
217 & 8.5 & 6.26648 & 2.23352 \tabularnewline
218 & 7.5 & 7.32625 & 0.173748 \tabularnewline
219 & 7 & 5.92368 & 1.07632 \tabularnewline
220 & 8 & 6.16672 & 1.83328 \tabularnewline
221 & 8.5 & 5.46297 & 3.03703 \tabularnewline
222 & 3.5 & 5.24205 & -1.74205 \tabularnewline
223 & 6.5 & 6.56514 & -0.0651386 \tabularnewline
224 & 6.5 & 5.77022 & 0.72978 \tabularnewline
225 & 10.5 & 5.68424 & 4.81576 \tabularnewline
226 & 8.5 & 6.23616 & 2.26384 \tabularnewline
227 & 8 & 6.32628 & 1.67372 \tabularnewline
228 & 10 & 5.85077 & 4.14923 \tabularnewline
229 & 10 & 5.89187 & 4.10813 \tabularnewline
230 & 9.5 & 6.16923 & 3.33077 \tabularnewline
231 & 9 & 6.46955 & 2.53045 \tabularnewline
232 & 10 & 6.60069 & 3.39931 \tabularnewline
233 & 7.5 & 5.52345 & 1.97655 \tabularnewline
234 & 4.5 & 5.84204 & -1.34204 \tabularnewline
235 & 4.5 & 6.41839 & -1.91839 \tabularnewline
236 & 0.5 & 6.43366 & -5.93366 \tabularnewline
237 & 6.5 & 5.9038 & 0.596203 \tabularnewline
238 & 4.5 & 5.83921 & -1.33921 \tabularnewline
239 & 5.5 & 7.47604 & -1.97604 \tabularnewline
240 & 5 & 5.7826 & -0.782601 \tabularnewline
241 & 6 & 6.34515 & -0.345149 \tabularnewline
242 & 4 & 5.09319 & -1.09319 \tabularnewline
243 & 8 & 6.31441 & 1.68559 \tabularnewline
244 & 10.5 & 6.17755 & 4.32245 \tabularnewline
245 & 8.5 & 6.51508 & 1.98492 \tabularnewline
246 & 8 & 5.58739 & 2.41261 \tabularnewline
247 & 8.5 & 6.27388 & 2.22612 \tabularnewline
248 & 5.5 & 6.26105 & -0.76105 \tabularnewline
249 & 7 & 6.0282 & 0.971801 \tabularnewline
250 & 5 & 6.29065 & -1.29065 \tabularnewline
251 & 3.5 & 5.84053 & -2.34053 \tabularnewline
252 & 5 & 6.30194 & -1.30194 \tabularnewline
253 & 9 & 6.07928 & 2.92072 \tabularnewline
254 & 8.5 & 5.80049 & 2.69951 \tabularnewline
255 & 5 & 5.92053 & -0.920532 \tabularnewline
256 & 9.5 & 6.25908 & 3.24092 \tabularnewline
257 & 3 & 5.40969 & -2.40969 \tabularnewline
258 & 1.5 & 5.52086 & -4.02086 \tabularnewline
259 & 6 & 5.878 & 0.122002 \tabularnewline
260 & 0.5 & 6.58141 & -6.08141 \tabularnewline
261 & 6.5 & 6.78197 & -0.281967 \tabularnewline
262 & 7.5 & 5.59098 & 1.90902 \tabularnewline
263 & 4.5 & 6.49571 & -1.99571 \tabularnewline
264 & 8 & 6.29567 & 1.70433 \tabularnewline
265 & 9 & 6.15286 & 2.84714 \tabularnewline
266 & 7.5 & 6.61498 & 0.885019 \tabularnewline
267 & 8.5 & 6.85363 & 1.64637 \tabularnewline
268 & 7 & 5.3026 & 1.6974 \tabularnewline
269 & 9.5 & 6.26279 & 3.23721 \tabularnewline
270 & 6.5 & 6.10023 & 0.399771 \tabularnewline
271 & 9.5 & 5.62008 & 3.87992 \tabularnewline
272 & 6 & 5.72064 & 0.279359 \tabularnewline
273 & 8 & 5.81847 & 2.18153 \tabularnewline
274 & 9.5 & 6.00578 & 3.49422 \tabularnewline
275 & 8 & 6.26515 & 1.73485 \tabularnewline
276 & 8 & 6.5932 & 1.4068 \tabularnewline
277 & 9 & 5.76879 & 3.23121 \tabularnewline
278 & 5 & 6.00947 & -1.00947 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280357&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]7.5[/C][C]6.61014[/C][C]0.889865[/C][/ROW]
[ROW][C]2[/C][C]6[/C][C]6.06087[/C][C]-0.0608734[/C][/ROW]
[ROW][C]3[/C][C]6.5[/C][C]6.56564[/C][C]-0.0656442[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]6.07813[/C][C]-5.07813[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]6.61539[/C][C]-5.61539[/C][/ROW]
[ROW][C]6[/C][C]5.5[/C][C]5.91722[/C][C]-0.417217[/C][/ROW]
[ROW][C]7[/C][C]8.5[/C][C]5.5044[/C][C]2.9956[/C][/ROW]
[ROW][C]8[/C][C]6.5[/C][C]7.02726[/C][C]-0.52726[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]5.37975[/C][C]-0.879747[/C][/ROW]
[ROW][C]10[/C][C]2[/C][C]7.52721[/C][C]-5.52721[/C][/ROW]
[ROW][C]11[/C][C]5[/C][C]5.80784[/C][C]-0.807842[/C][/ROW]
[ROW][C]12[/C][C]0.5[/C][C]6.26158[/C][C]-5.76158[/C][/ROW]
[ROW][C]13[/C][C]5[/C][C]5.21448[/C][C]-0.214476[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]6.05183[/C][C]-1.05183[/C][/ROW]
[ROW][C]15[/C][C]2.5[/C][C]5.90399[/C][C]-3.40399[/C][/ROW]
[ROW][C]16[/C][C]5[/C][C]5.74325[/C][C]-0.743252[/C][/ROW]
[ROW][C]17[/C][C]5.5[/C][C]5.98301[/C][C]-0.483007[/C][/ROW]
[ROW][C]18[/C][C]3.5[/C][C]5.93465[/C][C]-2.43465[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]6.46088[/C][C]-3.46088[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]5.67262[/C][C]-1.67262[/C][/ROW]
[ROW][C]21[/C][C]0.5[/C][C]6.41779[/C][C]-5.91779[/C][/ROW]
[ROW][C]22[/C][C]6.5[/C][C]6.17714[/C][C]0.322861[/C][/ROW]
[ROW][C]23[/C][C]4.5[/C][C]5.95795[/C][C]-1.45795[/C][/ROW]
[ROW][C]24[/C][C]7.5[/C][C]5.84462[/C][C]1.65538[/C][/ROW]
[ROW][C]25[/C][C]5.5[/C][C]6.06117[/C][C]-0.56117[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]5.96617[/C][C]-1.96617[/C][/ROW]
[ROW][C]27[/C][C]7.5[/C][C]5.82674[/C][C]1.67326[/C][/ROW]
[ROW][C]28[/C][C]7[/C][C]6.40368[/C][C]0.596322[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]6.10523[/C][C]-2.10523[/C][/ROW]
[ROW][C]30[/C][C]5.5[/C][C]5.71401[/C][C]-0.214013[/C][/ROW]
[ROW][C]31[/C][C]2.5[/C][C]5.46249[/C][C]-2.96249[/C][/ROW]
[ROW][C]32[/C][C]5.5[/C][C]6.58875[/C][C]-1.08875[/C][/ROW]
[ROW][C]33[/C][C]3.5[/C][C]5.65071[/C][C]-2.15071[/C][/ROW]
[ROW][C]34[/C][C]2.5[/C][C]5.9727[/C][C]-3.4727[/C][/ROW]
[ROW][C]35[/C][C]4.5[/C][C]5.71363[/C][C]-1.21363[/C][/ROW]
[ROW][C]36[/C][C]4.5[/C][C]6.43006[/C][C]-1.93006[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]6.12636[/C][C]-1.62636[/C][/ROW]
[ROW][C]38[/C][C]6[/C][C]6.15386[/C][C]-0.153862[/C][/ROW]
[ROW][C]39[/C][C]2.5[/C][C]6.52046[/C][C]-4.02046[/C][/ROW]
[ROW][C]40[/C][C]5[/C][C]5.58875[/C][C]-0.58875[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]6.68492[/C][C]-6.68492[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]6.6194[/C][C]-1.6194[/C][/ROW]
[ROW][C]43[/C][C]6.5[/C][C]6.17349[/C][C]0.326508[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]5.24505[/C][C]-0.245051[/C][/ROW]
[ROW][C]45[/C][C]6[/C][C]5.83017[/C][C]0.169832[/C][/ROW]
[ROW][C]46[/C][C]4.5[/C][C]6.13151[/C][C]-1.63151[/C][/ROW]
[ROW][C]47[/C][C]5.5[/C][C]6.58882[/C][C]-1.08882[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]6.06535[/C][C]-5.06535[/C][/ROW]
[ROW][C]49[/C][C]7.5[/C][C]5.73774[/C][C]1.76226[/C][/ROW]
[ROW][C]50[/C][C]6[/C][C]6.38444[/C][C]-0.384437[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]5.53627[/C][C]-0.53627[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]6.22439[/C][C]-5.22439[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]6.46345[/C][C]-1.46345[/C][/ROW]
[ROW][C]54[/C][C]6.5[/C][C]5.88406[/C][C]0.61594[/C][/ROW]
[ROW][C]55[/C][C]7[/C][C]6.5579[/C][C]0.4421[/C][/ROW]
[ROW][C]56[/C][C]4.5[/C][C]6.23974[/C][C]-1.73974[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]5.55804[/C][C]-5.55804[/C][/ROW]
[ROW][C]58[/C][C]8.5[/C][C]6.07476[/C][C]2.42524[/C][/ROW]
[ROW][C]59[/C][C]3.5[/C][C]6.16266[/C][C]-2.66266[/C][/ROW]
[ROW][C]60[/C][C]7.5[/C][C]6.34869[/C][C]1.15131[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]6.53693[/C][C]-3.03693[/C][/ROW]
[ROW][C]62[/C][C]6[/C][C]6.00828[/C][C]-0.00828202[/C][/ROW]
[ROW][C]63[/C][C]1.5[/C][C]5.42676[/C][C]-3.92676[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]6.30309[/C][C]2.69691[/C][/ROW]
[ROW][C]65[/C][C]3.5[/C][C]6.3168[/C][C]-2.8168[/C][/ROW]
[ROW][C]66[/C][C]3.5[/C][C]6.37851[/C][C]-2.87851[/C][/ROW]
[ROW][C]67[/C][C]4[/C][C]5.64197[/C][C]-1.64197[/C][/ROW]
[ROW][C]68[/C][C]6.5[/C][C]6.35767[/C][C]0.142332[/C][/ROW]
[ROW][C]69[/C][C]7.5[/C][C]6.12643[/C][C]1.37357[/C][/ROW]
[ROW][C]70[/C][C]6[/C][C]6.14703[/C][C]-0.147029[/C][/ROW]
[ROW][C]71[/C][C]5[/C][C]6.29498[/C][C]-1.29498[/C][/ROW]
[ROW][C]72[/C][C]5.5[/C][C]6.03339[/C][C]-0.53339[/C][/ROW]
[ROW][C]73[/C][C]3.5[/C][C]6.40092[/C][C]-2.90092[/C][/ROW]
[ROW][C]74[/C][C]7.5[/C][C]6.58358[/C][C]0.916424[/C][/ROW]
[ROW][C]75[/C][C]6.5[/C][C]5.5021[/C][C]0.997905[/C][/ROW]
[ROW][C]76[/C][C]6.5[/C][C]6.00257[/C][C]0.497427[/C][/ROW]
[ROW][C]77[/C][C]6.5[/C][C]6.51584[/C][C]-0.0158443[/C][/ROW]
[ROW][C]78[/C][C]7[/C][C]6.34667[/C][C]0.653332[/C][/ROW]
[ROW][C]79[/C][C]3.5[/C][C]5.67105[/C][C]-2.17105[/C][/ROW]
[ROW][C]80[/C][C]1.5[/C][C]5.81507[/C][C]-4.31507[/C][/ROW]
[ROW][C]81[/C][C]4[/C][C]6.14052[/C][C]-2.14052[/C][/ROW]
[ROW][C]82[/C][C]7.5[/C][C]5.85705[/C][C]1.64295[/C][/ROW]
[ROW][C]83[/C][C]4.5[/C][C]6.02858[/C][C]-1.52858[/C][/ROW]
[ROW][C]84[/C][C]0[/C][C]5.65985[/C][C]-5.65985[/C][/ROW]
[ROW][C]85[/C][C]3.5[/C][C]6.53881[/C][C]-3.03881[/C][/ROW]
[ROW][C]86[/C][C]5.5[/C][C]6.22824[/C][C]-0.728238[/C][/ROW]
[ROW][C]87[/C][C]5[/C][C]6.19801[/C][C]-1.19801[/C][/ROW]
[ROW][C]88[/C][C]4.5[/C][C]5.75452[/C][C]-1.25452[/C][/ROW]
[ROW][C]89[/C][C]2.5[/C][C]5.97496[/C][C]-3.47496[/C][/ROW]
[ROW][C]90[/C][C]7.5[/C][C]5.86105[/C][C]1.63895[/C][/ROW]
[ROW][C]91[/C][C]7[/C][C]6.23005[/C][C]0.769952[/C][/ROW]
[ROW][C]92[/C][C]0[/C][C]5.94941[/C][C]-5.94941[/C][/ROW]
[ROW][C]93[/C][C]4.5[/C][C]6.06472[/C][C]-1.56472[/C][/ROW]
[ROW][C]94[/C][C]3[/C][C]5.95259[/C][C]-2.95259[/C][/ROW]
[ROW][C]95[/C][C]1.5[/C][C]6.43231[/C][C]-4.93231[/C][/ROW]
[ROW][C]96[/C][C]3.5[/C][C]5.82358[/C][C]-2.32358[/C][/ROW]
[ROW][C]97[/C][C]2.5[/C][C]6.11745[/C][C]-3.61745[/C][/ROW]
[ROW][C]98[/C][C]5.5[/C][C]6.12905[/C][C]-0.629054[/C][/ROW]
[ROW][C]99[/C][C]8[/C][C]5.99568[/C][C]2.00432[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]5.86937[/C][C]-4.86937[/C][/ROW]
[ROW][C]101[/C][C]5[/C][C]5.83095[/C][C]-0.830953[/C][/ROW]
[ROW][C]102[/C][C]4.5[/C][C]5.61372[/C][C]-1.11372[/C][/ROW]
[ROW][C]103[/C][C]3[/C][C]5.91175[/C][C]-2.91175[/C][/ROW]
[ROW][C]104[/C][C]3[/C][C]6.07162[/C][C]-3.07162[/C][/ROW]
[ROW][C]105[/C][C]8[/C][C]6.2806[/C][C]1.7194[/C][/ROW]
[ROW][C]106[/C][C]2.5[/C][C]6.35391[/C][C]-3.85391[/C][/ROW]
[ROW][C]107[/C][C]7[/C][C]6.74273[/C][C]0.257269[/C][/ROW]
[ROW][C]108[/C][C]0[/C][C]5.99137[/C][C]-5.99137[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]6.11031[/C][C]-5.11031[/C][/ROW]
[ROW][C]110[/C][C]3.5[/C][C]6.50746[/C][C]-3.00746[/C][/ROW]
[ROW][C]111[/C][C]5.5[/C][C]6.07388[/C][C]-0.573882[/C][/ROW]
[ROW][C]112[/C][C]5.5[/C][C]6.09669[/C][C]-0.596694[/C][/ROW]
[ROW][C]113[/C][C]0.5[/C][C]6.82301[/C][C]-6.32301[/C][/ROW]
[ROW][C]114[/C][C]7.5[/C][C]6.21332[/C][C]1.28668[/C][/ROW]
[ROW][C]115[/C][C]9[/C][C]6.09075[/C][C]2.90925[/C][/ROW]
[ROW][C]116[/C][C]9.5[/C][C]5.78472[/C][C]3.71528[/C][/ROW]
[ROW][C]117[/C][C]8.5[/C][C]6.85034[/C][C]1.64966[/C][/ROW]
[ROW][C]118[/C][C]7[/C][C]6.57846[/C][C]0.421539[/C][/ROW]
[ROW][C]119[/C][C]8[/C][C]6.93237[/C][C]1.06763[/C][/ROW]
[ROW][C]120[/C][C]10[/C][C]6.38849[/C][C]3.61151[/C][/ROW]
[ROW][C]121[/C][C]7[/C][C]6.0574[/C][C]0.942596[/C][/ROW]
[ROW][C]122[/C][C]8.5[/C][C]6.29942[/C][C]2.20058[/C][/ROW]
[ROW][C]123[/C][C]9[/C][C]7.07613[/C][C]1.92387[/C][/ROW]
[ROW][C]124[/C][C]9.5[/C][C]5.73269[/C][C]3.76731[/C][/ROW]
[ROW][C]125[/C][C]4[/C][C]6.11495[/C][C]-2.11495[/C][/ROW]
[ROW][C]126[/C][C]6[/C][C]6.00352[/C][C]-0.00351543[/C][/ROW]
[ROW][C]127[/C][C]8[/C][C]6.13028[/C][C]1.86972[/C][/ROW]
[ROW][C]128[/C][C]5.5[/C][C]6.17035[/C][C]-0.670348[/C][/ROW]
[ROW][C]129[/C][C]9.5[/C][C]6.03136[/C][C]3.46864[/C][/ROW]
[ROW][C]130[/C][C]7.5[/C][C]6.27077[/C][C]1.22923[/C][/ROW]
[ROW][C]131[/C][C]7[/C][C]6.11217[/C][C]0.887831[/C][/ROW]
[ROW][C]132[/C][C]7.5[/C][C]5.91882[/C][C]1.58118[/C][/ROW]
[ROW][C]133[/C][C]8[/C][C]6.08827[/C][C]1.91173[/C][/ROW]
[ROW][C]134[/C][C]7[/C][C]5.90754[/C][C]1.09246[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]6.4765[/C][C]0.523505[/C][/ROW]
[ROW][C]136[/C][C]6[/C][C]6.1317[/C][C]-0.1317[/C][/ROW]
[ROW][C]137[/C][C]10[/C][C]6.19361[/C][C]3.80639[/C][/ROW]
[ROW][C]138[/C][C]2.5[/C][C]6.18421[/C][C]-3.68421[/C][/ROW]
[ROW][C]139[/C][C]9[/C][C]5.98737[/C][C]3.01263[/C][/ROW]
[ROW][C]140[/C][C]8[/C][C]7.34992[/C][C]0.650084[/C][/ROW]
[ROW][C]141[/C][C]6[/C][C]6.27925[/C][C]-0.279248[/C][/ROW]
[ROW][C]142[/C][C]8.5[/C][C]6.22528[/C][C]2.27472[/C][/ROW]
[ROW][C]143[/C][C]6[/C][C]5.81866[/C][C]0.181335[/C][/ROW]
[ROW][C]144[/C][C]9[/C][C]5.79752[/C][C]3.20248[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]6.47239[/C][C]1.52761[/C][/ROW]
[ROW][C]146[/C][C]9[/C][C]6.93778[/C][C]2.06222[/C][/ROW]
[ROW][C]147[/C][C]5.5[/C][C]7.28786[/C][C]-1.78786[/C][/ROW]
[ROW][C]148[/C][C]5[/C][C]6.36401[/C][C]-1.36401[/C][/ROW]
[ROW][C]149[/C][C]5.5[/C][C]6.39838[/C][C]-0.898378[/C][/ROW]
[ROW][C]150[/C][C]9[/C][C]6.65673[/C][C]2.34327[/C][/ROW]
[ROW][C]151[/C][C]2[/C][C]5.92074[/C][C]-3.92074[/C][/ROW]
[ROW][C]152[/C][C]8.5[/C][C]6.54919[/C][C]1.95081[/C][/ROW]
[ROW][C]153[/C][C]9[/C][C]6.52166[/C][C]2.47834[/C][/ROW]
[ROW][C]154[/C][C]8.5[/C][C]6.1967[/C][C]2.3033[/C][/ROW]
[ROW][C]155[/C][C]9[/C][C]6.56718[/C][C]2.43282[/C][/ROW]
[ROW][C]156[/C][C]7.5[/C][C]6.79694[/C][C]0.703057[/C][/ROW]
[ROW][C]157[/C][C]10[/C][C]6.56454[/C][C]3.43546[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]6.2263[/C][C]2.7737[/C][/ROW]
[ROW][C]159[/C][C]7.5[/C][C]6.79974[/C][C]0.700258[/C][/ROW]
[ROW][C]160[/C][C]6[/C][C]6.12604[/C][C]-0.12604[/C][/ROW]
[ROW][C]161[/C][C]10.5[/C][C]6.23857[/C][C]4.26143[/C][/ROW]
[ROW][C]162[/C][C]8.5[/C][C]6.07848[/C][C]2.42152[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]6.54084[/C][C]1.45916[/C][/ROW]
[ROW][C]164[/C][C]10[/C][C]6.55415[/C][C]3.44585[/C][/ROW]
[ROW][C]165[/C][C]10.5[/C][C]7.17926[/C][C]3.32074[/C][/ROW]
[ROW][C]166[/C][C]6.5[/C][C]5.76881[/C][C]0.731194[/C][/ROW]
[ROW][C]167[/C][C]9.5[/C][C]5.93601[/C][C]3.56399[/C][/ROW]
[ROW][C]168[/C][C]8.5[/C][C]6.34949[/C][C]2.15051[/C][/ROW]
[ROW][C]169[/C][C]7.5[/C][C]6.689[/C][C]0.811004[/C][/ROW]
[ROW][C]170[/C][C]5[/C][C]5.8617[/C][C]-0.8617[/C][/ROW]
[ROW][C]171[/C][C]8[/C][C]6.00476[/C][C]1.99524[/C][/ROW]
[ROW][C]172[/C][C]10[/C][C]6.38351[/C][C]3.61649[/C][/ROW]
[ROW][C]173[/C][C]7[/C][C]5.88654[/C][C]1.11346[/C][/ROW]
[ROW][C]174[/C][C]7.5[/C][C]6.65067[/C][C]0.849329[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]6.45365[/C][C]1.04635[/C][/ROW]
[ROW][C]176[/C][C]9.5[/C][C]5.71943[/C][C]3.78057[/C][/ROW]
[ROW][C]177[/C][C]6[/C][C]6.6921[/C][C]-0.692104[/C][/ROW]
[ROW][C]178[/C][C]10[/C][C]5.95032[/C][C]4.04968[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]6.23988[/C][C]0.760115[/C][/ROW]
[ROW][C]180[/C][C]3[/C][C]5.73613[/C][C]-2.73613[/C][/ROW]
[ROW][C]181[/C][C]6[/C][C]6.65944[/C][C]-0.659435[/C][/ROW]
[ROW][C]182[/C][C]7[/C][C]6.47022[/C][C]0.529776[/C][/ROW]
[ROW][C]183[/C][C]10[/C][C]6.56238[/C][C]3.43762[/C][/ROW]
[ROW][C]184[/C][C]7[/C][C]5.94183[/C][C]1.05817[/C][/ROW]
[ROW][C]185[/C][C]3.5[/C][C]5.89224[/C][C]-2.39224[/C][/ROW]
[ROW][C]186[/C][C]8[/C][C]6.40713[/C][C]1.59287[/C][/ROW]
[ROW][C]187[/C][C]10[/C][C]6.36711[/C][C]3.63289[/C][/ROW]
[ROW][C]188[/C][C]5.5[/C][C]6.19641[/C][C]-0.696408[/C][/ROW]
[ROW][C]189[/C][C]6[/C][C]6.30335[/C][C]-0.30335[/C][/ROW]
[ROW][C]190[/C][C]6.5[/C][C]5.94788[/C][C]0.552116[/C][/ROW]
[ROW][C]191[/C][C]6.5[/C][C]6.25509[/C][C]0.244913[/C][/ROW]
[ROW][C]192[/C][C]8.5[/C][C]5.55568[/C][C]2.94432[/C][/ROW]
[ROW][C]193[/C][C]4[/C][C]6.71559[/C][C]-2.71559[/C][/ROW]
[ROW][C]194[/C][C]9.5[/C][C]6.09428[/C][C]3.40572[/C][/ROW]
[ROW][C]195[/C][C]8[/C][C]6.65773[/C][C]1.34227[/C][/ROW]
[ROW][C]196[/C][C]8.5[/C][C]6.95824[/C][C]1.54176[/C][/ROW]
[ROW][C]197[/C][C]5.5[/C][C]5.79684[/C][C]-0.296842[/C][/ROW]
[ROW][C]198[/C][C]7[/C][C]5.94511[/C][C]1.05489[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]6.29928[/C][C]2.70072[/C][/ROW]
[ROW][C]200[/C][C]8[/C][C]6.19913[/C][C]1.80087[/C][/ROW]
[ROW][C]201[/C][C]10[/C][C]7.87558[/C][C]2.12442[/C][/ROW]
[ROW][C]202[/C][C]8[/C][C]6.93383[/C][C]1.06617[/C][/ROW]
[ROW][C]203[/C][C]6[/C][C]6.16267[/C][C]-0.162667[/C][/ROW]
[ROW][C]204[/C][C]8[/C][C]5.90715[/C][C]2.09285[/C][/ROW]
[ROW][C]205[/C][C]5[/C][C]5.2906[/C][C]-0.290598[/C][/ROW]
[ROW][C]206[/C][C]9[/C][C]5.79418[/C][C]3.20582[/C][/ROW]
[ROW][C]207[/C][C]4.5[/C][C]6.21319[/C][C]-1.71319[/C][/ROW]
[ROW][C]208[/C][C]8.5[/C][C]6.92813[/C][C]1.57187[/C][/ROW]
[ROW][C]209[/C][C]7[/C][C]6.17052[/C][C]0.829476[/C][/ROW]
[ROW][C]210[/C][C]8.5[/C][C]5.91555[/C][C]2.58445[/C][/ROW]
[ROW][C]211[/C][C]7.5[/C][C]6.25754[/C][C]1.24246[/C][/ROW]
[ROW][C]212[/C][C]7.5[/C][C]6.34233[/C][C]1.15767[/C][/ROW]
[ROW][C]213[/C][C]5[/C][C]5.65909[/C][C]-0.659086[/C][/ROW]
[ROW][C]214[/C][C]7[/C][C]5.74654[/C][C]1.25346[/C][/ROW]
[ROW][C]215[/C][C]8[/C][C]5.83105[/C][C]2.16895[/C][/ROW]
[ROW][C]216[/C][C]5.5[/C][C]6.7119[/C][C]-1.2119[/C][/ROW]
[ROW][C]217[/C][C]8.5[/C][C]6.26648[/C][C]2.23352[/C][/ROW]
[ROW][C]218[/C][C]7.5[/C][C]7.32625[/C][C]0.173748[/C][/ROW]
[ROW][C]219[/C][C]7[/C][C]5.92368[/C][C]1.07632[/C][/ROW]
[ROW][C]220[/C][C]8[/C][C]6.16672[/C][C]1.83328[/C][/ROW]
[ROW][C]221[/C][C]8.5[/C][C]5.46297[/C][C]3.03703[/C][/ROW]
[ROW][C]222[/C][C]3.5[/C][C]5.24205[/C][C]-1.74205[/C][/ROW]
[ROW][C]223[/C][C]6.5[/C][C]6.56514[/C][C]-0.0651386[/C][/ROW]
[ROW][C]224[/C][C]6.5[/C][C]5.77022[/C][C]0.72978[/C][/ROW]
[ROW][C]225[/C][C]10.5[/C][C]5.68424[/C][C]4.81576[/C][/ROW]
[ROW][C]226[/C][C]8.5[/C][C]6.23616[/C][C]2.26384[/C][/ROW]
[ROW][C]227[/C][C]8[/C][C]6.32628[/C][C]1.67372[/C][/ROW]
[ROW][C]228[/C][C]10[/C][C]5.85077[/C][C]4.14923[/C][/ROW]
[ROW][C]229[/C][C]10[/C][C]5.89187[/C][C]4.10813[/C][/ROW]
[ROW][C]230[/C][C]9.5[/C][C]6.16923[/C][C]3.33077[/C][/ROW]
[ROW][C]231[/C][C]9[/C][C]6.46955[/C][C]2.53045[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]6.60069[/C][C]3.39931[/C][/ROW]
[ROW][C]233[/C][C]7.5[/C][C]5.52345[/C][C]1.97655[/C][/ROW]
[ROW][C]234[/C][C]4.5[/C][C]5.84204[/C][C]-1.34204[/C][/ROW]
[ROW][C]235[/C][C]4.5[/C][C]6.41839[/C][C]-1.91839[/C][/ROW]
[ROW][C]236[/C][C]0.5[/C][C]6.43366[/C][C]-5.93366[/C][/ROW]
[ROW][C]237[/C][C]6.5[/C][C]5.9038[/C][C]0.596203[/C][/ROW]
[ROW][C]238[/C][C]4.5[/C][C]5.83921[/C][C]-1.33921[/C][/ROW]
[ROW][C]239[/C][C]5.5[/C][C]7.47604[/C][C]-1.97604[/C][/ROW]
[ROW][C]240[/C][C]5[/C][C]5.7826[/C][C]-0.782601[/C][/ROW]
[ROW][C]241[/C][C]6[/C][C]6.34515[/C][C]-0.345149[/C][/ROW]
[ROW][C]242[/C][C]4[/C][C]5.09319[/C][C]-1.09319[/C][/ROW]
[ROW][C]243[/C][C]8[/C][C]6.31441[/C][C]1.68559[/C][/ROW]
[ROW][C]244[/C][C]10.5[/C][C]6.17755[/C][C]4.32245[/C][/ROW]
[ROW][C]245[/C][C]8.5[/C][C]6.51508[/C][C]1.98492[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]5.58739[/C][C]2.41261[/C][/ROW]
[ROW][C]247[/C][C]8.5[/C][C]6.27388[/C][C]2.22612[/C][/ROW]
[ROW][C]248[/C][C]5.5[/C][C]6.26105[/C][C]-0.76105[/C][/ROW]
[ROW][C]249[/C][C]7[/C][C]6.0282[/C][C]0.971801[/C][/ROW]
[ROW][C]250[/C][C]5[/C][C]6.29065[/C][C]-1.29065[/C][/ROW]
[ROW][C]251[/C][C]3.5[/C][C]5.84053[/C][C]-2.34053[/C][/ROW]
[ROW][C]252[/C][C]5[/C][C]6.30194[/C][C]-1.30194[/C][/ROW]
[ROW][C]253[/C][C]9[/C][C]6.07928[/C][C]2.92072[/C][/ROW]
[ROW][C]254[/C][C]8.5[/C][C]5.80049[/C][C]2.69951[/C][/ROW]
[ROW][C]255[/C][C]5[/C][C]5.92053[/C][C]-0.920532[/C][/ROW]
[ROW][C]256[/C][C]9.5[/C][C]6.25908[/C][C]3.24092[/C][/ROW]
[ROW][C]257[/C][C]3[/C][C]5.40969[/C][C]-2.40969[/C][/ROW]
[ROW][C]258[/C][C]1.5[/C][C]5.52086[/C][C]-4.02086[/C][/ROW]
[ROW][C]259[/C][C]6[/C][C]5.878[/C][C]0.122002[/C][/ROW]
[ROW][C]260[/C][C]0.5[/C][C]6.58141[/C][C]-6.08141[/C][/ROW]
[ROW][C]261[/C][C]6.5[/C][C]6.78197[/C][C]-0.281967[/C][/ROW]
[ROW][C]262[/C][C]7.5[/C][C]5.59098[/C][C]1.90902[/C][/ROW]
[ROW][C]263[/C][C]4.5[/C][C]6.49571[/C][C]-1.99571[/C][/ROW]
[ROW][C]264[/C][C]8[/C][C]6.29567[/C][C]1.70433[/C][/ROW]
[ROW][C]265[/C][C]9[/C][C]6.15286[/C][C]2.84714[/C][/ROW]
[ROW][C]266[/C][C]7.5[/C][C]6.61498[/C][C]0.885019[/C][/ROW]
[ROW][C]267[/C][C]8.5[/C][C]6.85363[/C][C]1.64637[/C][/ROW]
[ROW][C]268[/C][C]7[/C][C]5.3026[/C][C]1.6974[/C][/ROW]
[ROW][C]269[/C][C]9.5[/C][C]6.26279[/C][C]3.23721[/C][/ROW]
[ROW][C]270[/C][C]6.5[/C][C]6.10023[/C][C]0.399771[/C][/ROW]
[ROW][C]271[/C][C]9.5[/C][C]5.62008[/C][C]3.87992[/C][/ROW]
[ROW][C]272[/C][C]6[/C][C]5.72064[/C][C]0.279359[/C][/ROW]
[ROW][C]273[/C][C]8[/C][C]5.81847[/C][C]2.18153[/C][/ROW]
[ROW][C]274[/C][C]9.5[/C][C]6.00578[/C][C]3.49422[/C][/ROW]
[ROW][C]275[/C][C]8[/C][C]6.26515[/C][C]1.73485[/C][/ROW]
[ROW][C]276[/C][C]8[/C][C]6.5932[/C][C]1.4068[/C][/ROW]
[ROW][C]277[/C][C]9[/C][C]5.76879[/C][C]3.23121[/C][/ROW]
[ROW][C]278[/C][C]5[/C][C]6.00947[/C][C]-1.00947[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280357&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280357&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.56.610140.889865
266.06087-0.0608734
36.56.56564-0.0656442
416.07813-5.07813
516.61539-5.61539
65.55.91722-0.417217
78.55.50442.9956
86.57.02726-0.52726
94.55.37975-0.879747
1027.52721-5.52721
1155.80784-0.807842
120.56.26158-5.76158
1355.21448-0.214476
1456.05183-1.05183
152.55.90399-3.40399
1655.74325-0.743252
175.55.98301-0.483007
183.55.93465-2.43465
1936.46088-3.46088
2045.67262-1.67262
210.56.41779-5.91779
226.56.177140.322861
234.55.95795-1.45795
247.55.844621.65538
255.56.06117-0.56117
2645.96617-1.96617
277.55.826741.67326
2876.403680.596322
2946.10523-2.10523
305.55.71401-0.214013
312.55.46249-2.96249
325.56.58875-1.08875
333.55.65071-2.15071
342.55.9727-3.4727
354.55.71363-1.21363
364.56.43006-1.93006
374.56.12636-1.62636
3866.15386-0.153862
392.56.52046-4.02046
4055.58875-0.58875
4106.68492-6.68492
4256.6194-1.6194
436.56.173490.326508
4455.24505-0.245051
4565.830170.169832
464.56.13151-1.63151
475.56.58882-1.08882
4816.06535-5.06535
497.55.737741.76226
5066.38444-0.384437
5155.53627-0.53627
5216.22439-5.22439
5356.46345-1.46345
546.55.884060.61594
5576.55790.4421
564.56.23974-1.73974
5705.55804-5.55804
588.56.074762.42524
593.56.16266-2.66266
607.56.348691.15131
613.56.53693-3.03693
6266.00828-0.00828202
631.55.42676-3.92676
6496.303092.69691
653.56.3168-2.8168
663.56.37851-2.87851
6745.64197-1.64197
686.56.357670.142332
697.56.126431.37357
7066.14703-0.147029
7156.29498-1.29498
725.56.03339-0.53339
733.56.40092-2.90092
747.56.583580.916424
756.55.50210.997905
766.56.002570.497427
776.56.51584-0.0158443
7876.346670.653332
793.55.67105-2.17105
801.55.81507-4.31507
8146.14052-2.14052
827.55.857051.64295
834.56.02858-1.52858
8405.65985-5.65985
853.56.53881-3.03881
865.56.22824-0.728238
8756.19801-1.19801
884.55.75452-1.25452
892.55.97496-3.47496
907.55.861051.63895
9176.230050.769952
9205.94941-5.94941
934.56.06472-1.56472
9435.95259-2.95259
951.56.43231-4.93231
963.55.82358-2.32358
972.56.11745-3.61745
985.56.12905-0.629054
9985.995682.00432
10015.86937-4.86937
10155.83095-0.830953
1024.55.61372-1.11372
10335.91175-2.91175
10436.07162-3.07162
10586.28061.7194
1062.56.35391-3.85391
10776.742730.257269
10805.99137-5.99137
10916.11031-5.11031
1103.56.50746-3.00746
1115.56.07388-0.573882
1125.56.09669-0.596694
1130.56.82301-6.32301
1147.56.213321.28668
11596.090752.90925
1169.55.784723.71528
1178.56.850341.64966
11876.578460.421539
11986.932371.06763
120106.388493.61151
12176.05740.942596
1228.56.299422.20058
12397.076131.92387
1249.55.732693.76731
12546.11495-2.11495
12666.00352-0.00351543
12786.130281.86972
1285.56.17035-0.670348
1299.56.031363.46864
1307.56.270771.22923
13176.112170.887831
1327.55.918821.58118
13386.088271.91173
13475.907541.09246
13576.47650.523505
13666.1317-0.1317
137106.193613.80639
1382.56.18421-3.68421
13995.987373.01263
14087.349920.650084
14166.27925-0.279248
1428.56.225282.27472
14365.818660.181335
14495.797523.20248
14586.472391.52761
14696.937782.06222
1475.57.28786-1.78786
14856.36401-1.36401
1495.56.39838-0.898378
15096.656732.34327
15125.92074-3.92074
1528.56.549191.95081
15396.521662.47834
1548.56.19672.3033
15596.567182.43282
1567.56.796940.703057
157106.564543.43546
15896.22632.7737
1597.56.799740.700258
16066.12604-0.12604
16110.56.238574.26143
1628.56.078482.42152
16386.540841.45916
164106.554153.44585
16510.57.179263.32074
1666.55.768810.731194
1679.55.936013.56399
1688.56.349492.15051
1697.56.6890.811004
17055.8617-0.8617
17186.004761.99524
172106.383513.61649
17375.886541.11346
1747.56.650670.849329
1757.56.453651.04635
1769.55.719433.78057
17766.6921-0.692104
178105.950324.04968
17976.239880.760115
18035.73613-2.73613
18166.65944-0.659435
18276.470220.529776
183106.562383.43762
18475.941831.05817
1853.55.89224-2.39224
18686.407131.59287
187106.367113.63289
1885.56.19641-0.696408
18966.30335-0.30335
1906.55.947880.552116
1916.56.255090.244913
1928.55.555682.94432
19346.71559-2.71559
1949.56.094283.40572
19586.657731.34227
1968.56.958241.54176
1975.55.79684-0.296842
19875.945111.05489
19996.299282.70072
20086.199131.80087
201107.875582.12442
20286.933831.06617
20366.16267-0.162667
20485.907152.09285
20555.2906-0.290598
20695.794183.20582
2074.56.21319-1.71319
2088.56.928131.57187
20976.170520.829476
2108.55.915552.58445
2117.56.257541.24246
2127.56.342331.15767
21355.65909-0.659086
21475.746541.25346
21585.831052.16895
2165.56.7119-1.2119
2178.56.266482.23352
2187.57.326250.173748
21975.923681.07632
22086.166721.83328
2218.55.462973.03703
2223.55.24205-1.74205
2236.56.56514-0.0651386
2246.55.770220.72978
22510.55.684244.81576
2268.56.236162.26384
22786.326281.67372
228105.850774.14923
229105.891874.10813
2309.56.169233.33077
23196.469552.53045
232106.600693.39931
2337.55.523451.97655
2344.55.84204-1.34204
2354.56.41839-1.91839
2360.56.43366-5.93366
2376.55.90380.596203
2384.55.83921-1.33921
2395.57.47604-1.97604
24055.7826-0.782601
24166.34515-0.345149
24245.09319-1.09319
24386.314411.68559
24410.56.177554.32245
2458.56.515081.98492
24685.587392.41261
2478.56.273882.22612
2485.56.26105-0.76105
24976.02820.971801
25056.29065-1.29065
2513.55.84053-2.34053
25256.30194-1.30194
25396.079282.92072
2548.55.800492.69951
25555.92053-0.920532
2569.56.259083.24092
25735.40969-2.40969
2581.55.52086-4.02086
25965.8780.122002
2600.56.58141-6.08141
2616.56.78197-0.281967
2627.55.590981.90902
2634.56.49571-1.99571
26486.295671.70433
26596.152862.84714
2667.56.614980.885019
2678.56.853631.64637
26875.30261.6974
2699.56.262793.23721
2706.56.100230.399771
2719.55.620083.87992
27265.720640.279359
27385.818472.18153
2749.56.005783.49422
27586.265151.73485
27686.59321.4068
27795.768793.23121
27856.00947-1.00947






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.1393270.2786530.860673
120.3559240.7118470.644076
130.2460310.4920610.753969
140.2827180.5654360.717282
150.2059150.411830.794085
160.166750.3334990.83325
170.1172530.2345070.882747
180.1089290.2178580.891071
190.08669070.1733810.913309
200.05496890.1099380.945031
210.05569180.1113840.944308
220.03725010.07450030.96275
230.02291020.04582040.97709
240.0347640.06952810.965236
250.03107150.06214310.968928
260.02134220.04268430.978658
270.0133560.02671190.986644
280.009563460.01912690.990437
290.00672880.01345760.993271
300.003997690.007995380.996002
310.007436360.01487270.992564
320.004590630.009181270.995409
330.004970950.009941890.995029
340.09504020.190080.90496
350.07474080.1494820.925259
360.06022240.1204450.939778
370.04658860.09317720.953411
380.03404690.06809380.965953
390.03419230.06838460.965808
400.02473270.04946540.975267
410.05831330.1166270.941687
420.05206510.104130.947935
430.05344430.1068890.946556
440.04588750.09177510.954112
450.03463470.06926940.965365
460.0281710.0563420.971829
470.02340750.04681510.976592
480.03065190.06130380.969348
490.04371190.08742370.956288
500.04483530.08967060.955165
510.03496160.06992320.965038
520.07786860.1557370.922131
530.06664990.13330.93335
540.07266140.1453230.927339
550.08659930.1731990.913401
560.07172270.1434450.928277
570.1627580.3255150.837242
580.1648610.3297230.835139
590.1475370.2950730.852463
600.1829530.3659060.817047
610.1687010.3374020.831299
620.1536290.3072590.846371
630.2411470.4822950.758853
640.3063560.6127110.693644
650.2930470.5860940.706953
660.2791770.5583550.720823
670.2504080.5008170.749592
680.239560.479120.76044
690.2418070.4836140.758193
700.2173090.4346180.782691
710.1908560.3817120.809144
720.1647990.3295980.835201
730.1566850.3133690.843315
740.1634680.3269350.836532
750.1448930.2897860.855107
760.1376850.275370.862315
770.1239340.2478670.876066
780.1180.2360010.882
790.1129330.2258660.887067
800.1393590.2787170.860641
810.1256290.2512580.874371
820.1306910.2613820.869309
830.1145880.2291770.885412
840.1972230.3944450.802777
850.1954560.3909110.804544
860.1747360.3494720.825264
870.1553630.3107250.844637
880.1378850.2757690.862115
890.1509030.3018050.849097
900.1577880.3155770.842212
910.14990.29980.8501
920.2683490.5366980.731651
930.2461330.4922660.753867
940.2448620.4897250.755138
950.2991210.5982430.700879
960.2911970.5823950.708803
970.3133380.6266760.686662
980.2877880.5755760.712212
990.3046320.6092640.695368
1000.3880330.7760660.611967
1010.3632930.7265850.636707
1020.3420560.6841130.657944
1030.3522740.7045480.647726
1040.3606720.7213430.639328
1050.369860.7397210.63014
1060.4047720.8095440.595228
1070.4106820.8213640.589318
1080.5920150.815970.407985
1090.7043140.5913730.295686
1100.721110.557780.27889
1110.703640.5927190.29636
1120.6850860.6298280.314914
1130.8508520.2982970.149148
1140.8775010.2449980.122499
1150.9007310.1985380.0992692
1160.9324650.135070.067535
1170.9391270.1217460.0608732
1180.9352860.1294290.0647144
1190.9381290.1237420.061871
1200.9565380.08692380.0434619
1210.9519230.09615430.0480772
1220.9592920.08141560.0407078
1230.9637280.07254310.0362716
1240.9755920.0488160.024408
1250.9774930.0450140.022507
1260.9734290.05314280.0265714
1270.9746450.05071030.0253551
1280.9711650.057670.028835
1290.9781310.04373850.0218692
1300.9768960.04620720.0231036
1310.9736970.0526060.026303
1320.9711260.05774780.0288739
1330.9694640.06107230.0305361
1340.9659980.0680050.0340025
1350.9632210.07355760.0367788
1360.9569950.08601010.043005
1370.9684670.06306610.031533
1380.9785690.04286270.0214313
1390.9819920.03601610.018008
1400.9792760.04144710.0207236
1410.9755840.04883160.0244158
1420.9753710.04925720.0246286
1430.9704010.05919870.0295993
1440.9739290.05214280.0260714
1450.9703460.05930740.0296537
1460.9690870.06182520.0309126
1470.9686630.06267330.0313366
1480.9680330.06393430.0319672
1490.9663260.06734790.0336739
1500.9674530.06509370.0325468
1510.9792480.04150470.0207524
1520.9774430.04511330.0225566
1530.9774510.04509710.0225485
1540.976130.04773940.0238697
1550.9763870.04722660.0236133
1560.972230.05554050.0277702
1570.9770050.04598930.0229946
1580.9782840.04343170.0217159
1590.9742070.05158520.0257926
1600.9699710.06005730.0300287
1610.9796290.04074160.0203708
1620.9788590.04228240.0211412
1630.9752780.04944480.0247224
1640.978570.04286060.0214303
1650.9819340.03613120.0180656
1660.9782570.04348630.0217431
1670.9819760.03604860.0180243
1680.9802760.03944730.0197236
1690.976090.04782050.0239103
1700.973510.05297940.0264897
1710.9705920.05881530.0294077
1720.976850.04630090.0231504
1730.9721640.05567280.0278364
1740.9665450.06691080.0334554
1750.960080.07983960.0399198
1760.9668380.06632430.0331621
1770.9607430.07851380.0392569
1780.9684790.06304250.0315212
1790.961860.07627930.0381396
1800.9670880.06582480.0329124
1810.9610070.07798650.0389933
1820.9525460.09490740.0474537
1830.9598170.08036540.0401827
1840.9521980.09560370.0478018
1850.9557950.08841080.0442054
1860.9490410.1019190.0509594
1870.9577810.08443880.0422194
1880.95050.09899940.0494997
1890.9409360.1181270.0590637
1900.9289950.142010.0710049
1910.9167990.1664010.0832006
1920.9162750.167450.0837251
1930.9346360.1307280.0653642
1940.9393410.1213170.0606587
1950.9284190.1431610.0715805
1960.9173490.1653010.0826506
1970.903380.193240.09662
1980.8869140.2261720.113086
1990.8808920.2382160.119108
2000.865410.269180.13459
2010.8666940.2666130.133306
2020.8468220.3063560.153178
2030.8253810.3492380.174619
2040.811370.3772590.18863
2050.7929210.4141570.207079
2060.7839290.4321430.216071
2070.7891830.4216350.210817
2080.7677070.4645850.232293
2090.7381590.5236820.261841
2100.7212930.5574140.278707
2110.6881660.6236680.311834
2120.6544480.6911030.345552
2130.6347760.7304480.365224
2140.5975770.8048460.402423
2150.5688360.8623280.431164
2160.5409420.9181150.459058
2170.5140130.9719730.485987
2180.4711780.9423550.528822
2190.4302660.8605330.569734
2200.4036690.8073370.596331
2210.3918570.7837150.608143
2220.4054740.8109480.594526
2230.3625430.7250860.637457
2240.3220090.6440180.677991
2250.3993940.7987880.600606
2260.3844820.7689640.615518
2270.3479320.6958630.652068
2280.3823520.7647030.617648
2290.4242090.8484190.575791
2300.4458790.8917570.554121
2310.4498320.8996640.550168
2320.4691490.9382980.530851
2330.4328330.8656660.567167
2340.4045540.8091080.595446
2350.3701380.7402760.629862
2360.6290810.7418380.370919
2370.5787970.8424060.421203
2380.54910.9017990.4509
2390.5585370.8829270.441463
2400.5625610.8748770.437439
2410.5125540.9748910.487446
2420.4798840.9597690.520116
2430.4312230.8624450.568777
2440.5436750.912650.456325
2450.5278250.944350.472175
2460.4828960.9657920.517104
2470.4327520.8655050.567248
2480.3847850.769570.615215
2490.3271370.6542740.672863
2500.2779670.5559350.722033
2510.322510.6450190.67749
2520.285320.570640.71468
2530.2454250.490850.754575
2540.3394520.6789030.660548
2550.2908950.5817890.709105
2560.2544670.5089350.745533
2570.3063920.6127850.693608
2580.616580.766840.38342
2590.5507440.8985130.449256
2600.9866960.02660880.0133044
2610.9733450.05331070.0266553
2620.9506210.09875750.0493788
2630.9451340.1097310.0548656
2640.898240.2035210.10176
2650.8369150.3261690.163085
2660.8570450.285910.142955
2670.7278350.5443310.272165

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.139327 & 0.278653 & 0.860673 \tabularnewline
12 & 0.355924 & 0.711847 & 0.644076 \tabularnewline
13 & 0.246031 & 0.492061 & 0.753969 \tabularnewline
14 & 0.282718 & 0.565436 & 0.717282 \tabularnewline
15 & 0.205915 & 0.41183 & 0.794085 \tabularnewline
16 & 0.16675 & 0.333499 & 0.83325 \tabularnewline
17 & 0.117253 & 0.234507 & 0.882747 \tabularnewline
18 & 0.108929 & 0.217858 & 0.891071 \tabularnewline
19 & 0.0866907 & 0.173381 & 0.913309 \tabularnewline
20 & 0.0549689 & 0.109938 & 0.945031 \tabularnewline
21 & 0.0556918 & 0.111384 & 0.944308 \tabularnewline
22 & 0.0372501 & 0.0745003 & 0.96275 \tabularnewline
23 & 0.0229102 & 0.0458204 & 0.97709 \tabularnewline
24 & 0.034764 & 0.0695281 & 0.965236 \tabularnewline
25 & 0.0310715 & 0.0621431 & 0.968928 \tabularnewline
26 & 0.0213422 & 0.0426843 & 0.978658 \tabularnewline
27 & 0.013356 & 0.0267119 & 0.986644 \tabularnewline
28 & 0.00956346 & 0.0191269 & 0.990437 \tabularnewline
29 & 0.0067288 & 0.0134576 & 0.993271 \tabularnewline
30 & 0.00399769 & 0.00799538 & 0.996002 \tabularnewline
31 & 0.00743636 & 0.0148727 & 0.992564 \tabularnewline
32 & 0.00459063 & 0.00918127 & 0.995409 \tabularnewline
33 & 0.00497095 & 0.00994189 & 0.995029 \tabularnewline
34 & 0.0950402 & 0.19008 & 0.90496 \tabularnewline
35 & 0.0747408 & 0.149482 & 0.925259 \tabularnewline
36 & 0.0602224 & 0.120445 & 0.939778 \tabularnewline
37 & 0.0465886 & 0.0931772 & 0.953411 \tabularnewline
38 & 0.0340469 & 0.0680938 & 0.965953 \tabularnewline
39 & 0.0341923 & 0.0683846 & 0.965808 \tabularnewline
40 & 0.0247327 & 0.0494654 & 0.975267 \tabularnewline
41 & 0.0583133 & 0.116627 & 0.941687 \tabularnewline
42 & 0.0520651 & 0.10413 & 0.947935 \tabularnewline
43 & 0.0534443 & 0.106889 & 0.946556 \tabularnewline
44 & 0.0458875 & 0.0917751 & 0.954112 \tabularnewline
45 & 0.0346347 & 0.0692694 & 0.965365 \tabularnewline
46 & 0.028171 & 0.056342 & 0.971829 \tabularnewline
47 & 0.0234075 & 0.0468151 & 0.976592 \tabularnewline
48 & 0.0306519 & 0.0613038 & 0.969348 \tabularnewline
49 & 0.0437119 & 0.0874237 & 0.956288 \tabularnewline
50 & 0.0448353 & 0.0896706 & 0.955165 \tabularnewline
51 & 0.0349616 & 0.0699232 & 0.965038 \tabularnewline
52 & 0.0778686 & 0.155737 & 0.922131 \tabularnewline
53 & 0.0666499 & 0.1333 & 0.93335 \tabularnewline
54 & 0.0726614 & 0.145323 & 0.927339 \tabularnewline
55 & 0.0865993 & 0.173199 & 0.913401 \tabularnewline
56 & 0.0717227 & 0.143445 & 0.928277 \tabularnewline
57 & 0.162758 & 0.325515 & 0.837242 \tabularnewline
58 & 0.164861 & 0.329723 & 0.835139 \tabularnewline
59 & 0.147537 & 0.295073 & 0.852463 \tabularnewline
60 & 0.182953 & 0.365906 & 0.817047 \tabularnewline
61 & 0.168701 & 0.337402 & 0.831299 \tabularnewline
62 & 0.153629 & 0.307259 & 0.846371 \tabularnewline
63 & 0.241147 & 0.482295 & 0.758853 \tabularnewline
64 & 0.306356 & 0.612711 & 0.693644 \tabularnewline
65 & 0.293047 & 0.586094 & 0.706953 \tabularnewline
66 & 0.279177 & 0.558355 & 0.720823 \tabularnewline
67 & 0.250408 & 0.500817 & 0.749592 \tabularnewline
68 & 0.23956 & 0.47912 & 0.76044 \tabularnewline
69 & 0.241807 & 0.483614 & 0.758193 \tabularnewline
70 & 0.217309 & 0.434618 & 0.782691 \tabularnewline
71 & 0.190856 & 0.381712 & 0.809144 \tabularnewline
72 & 0.164799 & 0.329598 & 0.835201 \tabularnewline
73 & 0.156685 & 0.313369 & 0.843315 \tabularnewline
74 & 0.163468 & 0.326935 & 0.836532 \tabularnewline
75 & 0.144893 & 0.289786 & 0.855107 \tabularnewline
76 & 0.137685 & 0.27537 & 0.862315 \tabularnewline
77 & 0.123934 & 0.247867 & 0.876066 \tabularnewline
78 & 0.118 & 0.236001 & 0.882 \tabularnewline
79 & 0.112933 & 0.225866 & 0.887067 \tabularnewline
80 & 0.139359 & 0.278717 & 0.860641 \tabularnewline
81 & 0.125629 & 0.251258 & 0.874371 \tabularnewline
82 & 0.130691 & 0.261382 & 0.869309 \tabularnewline
83 & 0.114588 & 0.229177 & 0.885412 \tabularnewline
84 & 0.197223 & 0.394445 & 0.802777 \tabularnewline
85 & 0.195456 & 0.390911 & 0.804544 \tabularnewline
86 & 0.174736 & 0.349472 & 0.825264 \tabularnewline
87 & 0.155363 & 0.310725 & 0.844637 \tabularnewline
88 & 0.137885 & 0.275769 & 0.862115 \tabularnewline
89 & 0.150903 & 0.301805 & 0.849097 \tabularnewline
90 & 0.157788 & 0.315577 & 0.842212 \tabularnewline
91 & 0.1499 & 0.2998 & 0.8501 \tabularnewline
92 & 0.268349 & 0.536698 & 0.731651 \tabularnewline
93 & 0.246133 & 0.492266 & 0.753867 \tabularnewline
94 & 0.244862 & 0.489725 & 0.755138 \tabularnewline
95 & 0.299121 & 0.598243 & 0.700879 \tabularnewline
96 & 0.291197 & 0.582395 & 0.708803 \tabularnewline
97 & 0.313338 & 0.626676 & 0.686662 \tabularnewline
98 & 0.287788 & 0.575576 & 0.712212 \tabularnewline
99 & 0.304632 & 0.609264 & 0.695368 \tabularnewline
100 & 0.388033 & 0.776066 & 0.611967 \tabularnewline
101 & 0.363293 & 0.726585 & 0.636707 \tabularnewline
102 & 0.342056 & 0.684113 & 0.657944 \tabularnewline
103 & 0.352274 & 0.704548 & 0.647726 \tabularnewline
104 & 0.360672 & 0.721343 & 0.639328 \tabularnewline
105 & 0.36986 & 0.739721 & 0.63014 \tabularnewline
106 & 0.404772 & 0.809544 & 0.595228 \tabularnewline
107 & 0.410682 & 0.821364 & 0.589318 \tabularnewline
108 & 0.592015 & 0.81597 & 0.407985 \tabularnewline
109 & 0.704314 & 0.591373 & 0.295686 \tabularnewline
110 & 0.72111 & 0.55778 & 0.27889 \tabularnewline
111 & 0.70364 & 0.592719 & 0.29636 \tabularnewline
112 & 0.685086 & 0.629828 & 0.314914 \tabularnewline
113 & 0.850852 & 0.298297 & 0.149148 \tabularnewline
114 & 0.877501 & 0.244998 & 0.122499 \tabularnewline
115 & 0.900731 & 0.198538 & 0.0992692 \tabularnewline
116 & 0.932465 & 0.13507 & 0.067535 \tabularnewline
117 & 0.939127 & 0.121746 & 0.0608732 \tabularnewline
118 & 0.935286 & 0.129429 & 0.0647144 \tabularnewline
119 & 0.938129 & 0.123742 & 0.061871 \tabularnewline
120 & 0.956538 & 0.0869238 & 0.0434619 \tabularnewline
121 & 0.951923 & 0.0961543 & 0.0480772 \tabularnewline
122 & 0.959292 & 0.0814156 & 0.0407078 \tabularnewline
123 & 0.963728 & 0.0725431 & 0.0362716 \tabularnewline
124 & 0.975592 & 0.048816 & 0.024408 \tabularnewline
125 & 0.977493 & 0.045014 & 0.022507 \tabularnewline
126 & 0.973429 & 0.0531428 & 0.0265714 \tabularnewline
127 & 0.974645 & 0.0507103 & 0.0253551 \tabularnewline
128 & 0.971165 & 0.05767 & 0.028835 \tabularnewline
129 & 0.978131 & 0.0437385 & 0.0218692 \tabularnewline
130 & 0.976896 & 0.0462072 & 0.0231036 \tabularnewline
131 & 0.973697 & 0.052606 & 0.026303 \tabularnewline
132 & 0.971126 & 0.0577478 & 0.0288739 \tabularnewline
133 & 0.969464 & 0.0610723 & 0.0305361 \tabularnewline
134 & 0.965998 & 0.068005 & 0.0340025 \tabularnewline
135 & 0.963221 & 0.0735576 & 0.0367788 \tabularnewline
136 & 0.956995 & 0.0860101 & 0.043005 \tabularnewline
137 & 0.968467 & 0.0630661 & 0.031533 \tabularnewline
138 & 0.978569 & 0.0428627 & 0.0214313 \tabularnewline
139 & 0.981992 & 0.0360161 & 0.018008 \tabularnewline
140 & 0.979276 & 0.0414471 & 0.0207236 \tabularnewline
141 & 0.975584 & 0.0488316 & 0.0244158 \tabularnewline
142 & 0.975371 & 0.0492572 & 0.0246286 \tabularnewline
143 & 0.970401 & 0.0591987 & 0.0295993 \tabularnewline
144 & 0.973929 & 0.0521428 & 0.0260714 \tabularnewline
145 & 0.970346 & 0.0593074 & 0.0296537 \tabularnewline
146 & 0.969087 & 0.0618252 & 0.0309126 \tabularnewline
147 & 0.968663 & 0.0626733 & 0.0313366 \tabularnewline
148 & 0.968033 & 0.0639343 & 0.0319672 \tabularnewline
149 & 0.966326 & 0.0673479 & 0.0336739 \tabularnewline
150 & 0.967453 & 0.0650937 & 0.0325468 \tabularnewline
151 & 0.979248 & 0.0415047 & 0.0207524 \tabularnewline
152 & 0.977443 & 0.0451133 & 0.0225566 \tabularnewline
153 & 0.977451 & 0.0450971 & 0.0225485 \tabularnewline
154 & 0.97613 & 0.0477394 & 0.0238697 \tabularnewline
155 & 0.976387 & 0.0472266 & 0.0236133 \tabularnewline
156 & 0.97223 & 0.0555405 & 0.0277702 \tabularnewline
157 & 0.977005 & 0.0459893 & 0.0229946 \tabularnewline
158 & 0.978284 & 0.0434317 & 0.0217159 \tabularnewline
159 & 0.974207 & 0.0515852 & 0.0257926 \tabularnewline
160 & 0.969971 & 0.0600573 & 0.0300287 \tabularnewline
161 & 0.979629 & 0.0407416 & 0.0203708 \tabularnewline
162 & 0.978859 & 0.0422824 & 0.0211412 \tabularnewline
163 & 0.975278 & 0.0494448 & 0.0247224 \tabularnewline
164 & 0.97857 & 0.0428606 & 0.0214303 \tabularnewline
165 & 0.981934 & 0.0361312 & 0.0180656 \tabularnewline
166 & 0.978257 & 0.0434863 & 0.0217431 \tabularnewline
167 & 0.981976 & 0.0360486 & 0.0180243 \tabularnewline
168 & 0.980276 & 0.0394473 & 0.0197236 \tabularnewline
169 & 0.97609 & 0.0478205 & 0.0239103 \tabularnewline
170 & 0.97351 & 0.0529794 & 0.0264897 \tabularnewline
171 & 0.970592 & 0.0588153 & 0.0294077 \tabularnewline
172 & 0.97685 & 0.0463009 & 0.0231504 \tabularnewline
173 & 0.972164 & 0.0556728 & 0.0278364 \tabularnewline
174 & 0.966545 & 0.0669108 & 0.0334554 \tabularnewline
175 & 0.96008 & 0.0798396 & 0.0399198 \tabularnewline
176 & 0.966838 & 0.0663243 & 0.0331621 \tabularnewline
177 & 0.960743 & 0.0785138 & 0.0392569 \tabularnewline
178 & 0.968479 & 0.0630425 & 0.0315212 \tabularnewline
179 & 0.96186 & 0.0762793 & 0.0381396 \tabularnewline
180 & 0.967088 & 0.0658248 & 0.0329124 \tabularnewline
181 & 0.961007 & 0.0779865 & 0.0389933 \tabularnewline
182 & 0.952546 & 0.0949074 & 0.0474537 \tabularnewline
183 & 0.959817 & 0.0803654 & 0.0401827 \tabularnewline
184 & 0.952198 & 0.0956037 & 0.0478018 \tabularnewline
185 & 0.955795 & 0.0884108 & 0.0442054 \tabularnewline
186 & 0.949041 & 0.101919 & 0.0509594 \tabularnewline
187 & 0.957781 & 0.0844388 & 0.0422194 \tabularnewline
188 & 0.9505 & 0.0989994 & 0.0494997 \tabularnewline
189 & 0.940936 & 0.118127 & 0.0590637 \tabularnewline
190 & 0.928995 & 0.14201 & 0.0710049 \tabularnewline
191 & 0.916799 & 0.166401 & 0.0832006 \tabularnewline
192 & 0.916275 & 0.16745 & 0.0837251 \tabularnewline
193 & 0.934636 & 0.130728 & 0.0653642 \tabularnewline
194 & 0.939341 & 0.121317 & 0.0606587 \tabularnewline
195 & 0.928419 & 0.143161 & 0.0715805 \tabularnewline
196 & 0.917349 & 0.165301 & 0.0826506 \tabularnewline
197 & 0.90338 & 0.19324 & 0.09662 \tabularnewline
198 & 0.886914 & 0.226172 & 0.113086 \tabularnewline
199 & 0.880892 & 0.238216 & 0.119108 \tabularnewline
200 & 0.86541 & 0.26918 & 0.13459 \tabularnewline
201 & 0.866694 & 0.266613 & 0.133306 \tabularnewline
202 & 0.846822 & 0.306356 & 0.153178 \tabularnewline
203 & 0.825381 & 0.349238 & 0.174619 \tabularnewline
204 & 0.81137 & 0.377259 & 0.18863 \tabularnewline
205 & 0.792921 & 0.414157 & 0.207079 \tabularnewline
206 & 0.783929 & 0.432143 & 0.216071 \tabularnewline
207 & 0.789183 & 0.421635 & 0.210817 \tabularnewline
208 & 0.767707 & 0.464585 & 0.232293 \tabularnewline
209 & 0.738159 & 0.523682 & 0.261841 \tabularnewline
210 & 0.721293 & 0.557414 & 0.278707 \tabularnewline
211 & 0.688166 & 0.623668 & 0.311834 \tabularnewline
212 & 0.654448 & 0.691103 & 0.345552 \tabularnewline
213 & 0.634776 & 0.730448 & 0.365224 \tabularnewline
214 & 0.597577 & 0.804846 & 0.402423 \tabularnewline
215 & 0.568836 & 0.862328 & 0.431164 \tabularnewline
216 & 0.540942 & 0.918115 & 0.459058 \tabularnewline
217 & 0.514013 & 0.971973 & 0.485987 \tabularnewline
218 & 0.471178 & 0.942355 & 0.528822 \tabularnewline
219 & 0.430266 & 0.860533 & 0.569734 \tabularnewline
220 & 0.403669 & 0.807337 & 0.596331 \tabularnewline
221 & 0.391857 & 0.783715 & 0.608143 \tabularnewline
222 & 0.405474 & 0.810948 & 0.594526 \tabularnewline
223 & 0.362543 & 0.725086 & 0.637457 \tabularnewline
224 & 0.322009 & 0.644018 & 0.677991 \tabularnewline
225 & 0.399394 & 0.798788 & 0.600606 \tabularnewline
226 & 0.384482 & 0.768964 & 0.615518 \tabularnewline
227 & 0.347932 & 0.695863 & 0.652068 \tabularnewline
228 & 0.382352 & 0.764703 & 0.617648 \tabularnewline
229 & 0.424209 & 0.848419 & 0.575791 \tabularnewline
230 & 0.445879 & 0.891757 & 0.554121 \tabularnewline
231 & 0.449832 & 0.899664 & 0.550168 \tabularnewline
232 & 0.469149 & 0.938298 & 0.530851 \tabularnewline
233 & 0.432833 & 0.865666 & 0.567167 \tabularnewline
234 & 0.404554 & 0.809108 & 0.595446 \tabularnewline
235 & 0.370138 & 0.740276 & 0.629862 \tabularnewline
236 & 0.629081 & 0.741838 & 0.370919 \tabularnewline
237 & 0.578797 & 0.842406 & 0.421203 \tabularnewline
238 & 0.5491 & 0.901799 & 0.4509 \tabularnewline
239 & 0.558537 & 0.882927 & 0.441463 \tabularnewline
240 & 0.562561 & 0.874877 & 0.437439 \tabularnewline
241 & 0.512554 & 0.974891 & 0.487446 \tabularnewline
242 & 0.479884 & 0.959769 & 0.520116 \tabularnewline
243 & 0.431223 & 0.862445 & 0.568777 \tabularnewline
244 & 0.543675 & 0.91265 & 0.456325 \tabularnewline
245 & 0.527825 & 0.94435 & 0.472175 \tabularnewline
246 & 0.482896 & 0.965792 & 0.517104 \tabularnewline
247 & 0.432752 & 0.865505 & 0.567248 \tabularnewline
248 & 0.384785 & 0.76957 & 0.615215 \tabularnewline
249 & 0.327137 & 0.654274 & 0.672863 \tabularnewline
250 & 0.277967 & 0.555935 & 0.722033 \tabularnewline
251 & 0.32251 & 0.645019 & 0.67749 \tabularnewline
252 & 0.28532 & 0.57064 & 0.71468 \tabularnewline
253 & 0.245425 & 0.49085 & 0.754575 \tabularnewline
254 & 0.339452 & 0.678903 & 0.660548 \tabularnewline
255 & 0.290895 & 0.581789 & 0.709105 \tabularnewline
256 & 0.254467 & 0.508935 & 0.745533 \tabularnewline
257 & 0.306392 & 0.612785 & 0.693608 \tabularnewline
258 & 0.61658 & 0.76684 & 0.38342 \tabularnewline
259 & 0.550744 & 0.898513 & 0.449256 \tabularnewline
260 & 0.986696 & 0.0266088 & 0.0133044 \tabularnewline
261 & 0.973345 & 0.0533107 & 0.0266553 \tabularnewline
262 & 0.950621 & 0.0987575 & 0.0493788 \tabularnewline
263 & 0.945134 & 0.109731 & 0.0548656 \tabularnewline
264 & 0.89824 & 0.203521 & 0.10176 \tabularnewline
265 & 0.836915 & 0.326169 & 0.163085 \tabularnewline
266 & 0.857045 & 0.28591 & 0.142955 \tabularnewline
267 & 0.727835 & 0.544331 & 0.272165 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280357&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]11[/C][C]0.139327[/C][C]0.278653[/C][C]0.860673[/C][/ROW]
[ROW][C]12[/C][C]0.355924[/C][C]0.711847[/C][C]0.644076[/C][/ROW]
[ROW][C]13[/C][C]0.246031[/C][C]0.492061[/C][C]0.753969[/C][/ROW]
[ROW][C]14[/C][C]0.282718[/C][C]0.565436[/C][C]0.717282[/C][/ROW]
[ROW][C]15[/C][C]0.205915[/C][C]0.41183[/C][C]0.794085[/C][/ROW]
[ROW][C]16[/C][C]0.16675[/C][C]0.333499[/C][C]0.83325[/C][/ROW]
[ROW][C]17[/C][C]0.117253[/C][C]0.234507[/C][C]0.882747[/C][/ROW]
[ROW][C]18[/C][C]0.108929[/C][C]0.217858[/C][C]0.891071[/C][/ROW]
[ROW][C]19[/C][C]0.0866907[/C][C]0.173381[/C][C]0.913309[/C][/ROW]
[ROW][C]20[/C][C]0.0549689[/C][C]0.109938[/C][C]0.945031[/C][/ROW]
[ROW][C]21[/C][C]0.0556918[/C][C]0.111384[/C][C]0.944308[/C][/ROW]
[ROW][C]22[/C][C]0.0372501[/C][C]0.0745003[/C][C]0.96275[/C][/ROW]
[ROW][C]23[/C][C]0.0229102[/C][C]0.0458204[/C][C]0.97709[/C][/ROW]
[ROW][C]24[/C][C]0.034764[/C][C]0.0695281[/C][C]0.965236[/C][/ROW]
[ROW][C]25[/C][C]0.0310715[/C][C]0.0621431[/C][C]0.968928[/C][/ROW]
[ROW][C]26[/C][C]0.0213422[/C][C]0.0426843[/C][C]0.978658[/C][/ROW]
[ROW][C]27[/C][C]0.013356[/C][C]0.0267119[/C][C]0.986644[/C][/ROW]
[ROW][C]28[/C][C]0.00956346[/C][C]0.0191269[/C][C]0.990437[/C][/ROW]
[ROW][C]29[/C][C]0.0067288[/C][C]0.0134576[/C][C]0.993271[/C][/ROW]
[ROW][C]30[/C][C]0.00399769[/C][C]0.00799538[/C][C]0.996002[/C][/ROW]
[ROW][C]31[/C][C]0.00743636[/C][C]0.0148727[/C][C]0.992564[/C][/ROW]
[ROW][C]32[/C][C]0.00459063[/C][C]0.00918127[/C][C]0.995409[/C][/ROW]
[ROW][C]33[/C][C]0.00497095[/C][C]0.00994189[/C][C]0.995029[/C][/ROW]
[ROW][C]34[/C][C]0.0950402[/C][C]0.19008[/C][C]0.90496[/C][/ROW]
[ROW][C]35[/C][C]0.0747408[/C][C]0.149482[/C][C]0.925259[/C][/ROW]
[ROW][C]36[/C][C]0.0602224[/C][C]0.120445[/C][C]0.939778[/C][/ROW]
[ROW][C]37[/C][C]0.0465886[/C][C]0.0931772[/C][C]0.953411[/C][/ROW]
[ROW][C]38[/C][C]0.0340469[/C][C]0.0680938[/C][C]0.965953[/C][/ROW]
[ROW][C]39[/C][C]0.0341923[/C][C]0.0683846[/C][C]0.965808[/C][/ROW]
[ROW][C]40[/C][C]0.0247327[/C][C]0.0494654[/C][C]0.975267[/C][/ROW]
[ROW][C]41[/C][C]0.0583133[/C][C]0.116627[/C][C]0.941687[/C][/ROW]
[ROW][C]42[/C][C]0.0520651[/C][C]0.10413[/C][C]0.947935[/C][/ROW]
[ROW][C]43[/C][C]0.0534443[/C][C]0.106889[/C][C]0.946556[/C][/ROW]
[ROW][C]44[/C][C]0.0458875[/C][C]0.0917751[/C][C]0.954112[/C][/ROW]
[ROW][C]45[/C][C]0.0346347[/C][C]0.0692694[/C][C]0.965365[/C][/ROW]
[ROW][C]46[/C][C]0.028171[/C][C]0.056342[/C][C]0.971829[/C][/ROW]
[ROW][C]47[/C][C]0.0234075[/C][C]0.0468151[/C][C]0.976592[/C][/ROW]
[ROW][C]48[/C][C]0.0306519[/C][C]0.0613038[/C][C]0.969348[/C][/ROW]
[ROW][C]49[/C][C]0.0437119[/C][C]0.0874237[/C][C]0.956288[/C][/ROW]
[ROW][C]50[/C][C]0.0448353[/C][C]0.0896706[/C][C]0.955165[/C][/ROW]
[ROW][C]51[/C][C]0.0349616[/C][C]0.0699232[/C][C]0.965038[/C][/ROW]
[ROW][C]52[/C][C]0.0778686[/C][C]0.155737[/C][C]0.922131[/C][/ROW]
[ROW][C]53[/C][C]0.0666499[/C][C]0.1333[/C][C]0.93335[/C][/ROW]
[ROW][C]54[/C][C]0.0726614[/C][C]0.145323[/C][C]0.927339[/C][/ROW]
[ROW][C]55[/C][C]0.0865993[/C][C]0.173199[/C][C]0.913401[/C][/ROW]
[ROW][C]56[/C][C]0.0717227[/C][C]0.143445[/C][C]0.928277[/C][/ROW]
[ROW][C]57[/C][C]0.162758[/C][C]0.325515[/C][C]0.837242[/C][/ROW]
[ROW][C]58[/C][C]0.164861[/C][C]0.329723[/C][C]0.835139[/C][/ROW]
[ROW][C]59[/C][C]0.147537[/C][C]0.295073[/C][C]0.852463[/C][/ROW]
[ROW][C]60[/C][C]0.182953[/C][C]0.365906[/C][C]0.817047[/C][/ROW]
[ROW][C]61[/C][C]0.168701[/C][C]0.337402[/C][C]0.831299[/C][/ROW]
[ROW][C]62[/C][C]0.153629[/C][C]0.307259[/C][C]0.846371[/C][/ROW]
[ROW][C]63[/C][C]0.241147[/C][C]0.482295[/C][C]0.758853[/C][/ROW]
[ROW][C]64[/C][C]0.306356[/C][C]0.612711[/C][C]0.693644[/C][/ROW]
[ROW][C]65[/C][C]0.293047[/C][C]0.586094[/C][C]0.706953[/C][/ROW]
[ROW][C]66[/C][C]0.279177[/C][C]0.558355[/C][C]0.720823[/C][/ROW]
[ROW][C]67[/C][C]0.250408[/C][C]0.500817[/C][C]0.749592[/C][/ROW]
[ROW][C]68[/C][C]0.23956[/C][C]0.47912[/C][C]0.76044[/C][/ROW]
[ROW][C]69[/C][C]0.241807[/C][C]0.483614[/C][C]0.758193[/C][/ROW]
[ROW][C]70[/C][C]0.217309[/C][C]0.434618[/C][C]0.782691[/C][/ROW]
[ROW][C]71[/C][C]0.190856[/C][C]0.381712[/C][C]0.809144[/C][/ROW]
[ROW][C]72[/C][C]0.164799[/C][C]0.329598[/C][C]0.835201[/C][/ROW]
[ROW][C]73[/C][C]0.156685[/C][C]0.313369[/C][C]0.843315[/C][/ROW]
[ROW][C]74[/C][C]0.163468[/C][C]0.326935[/C][C]0.836532[/C][/ROW]
[ROW][C]75[/C][C]0.144893[/C][C]0.289786[/C][C]0.855107[/C][/ROW]
[ROW][C]76[/C][C]0.137685[/C][C]0.27537[/C][C]0.862315[/C][/ROW]
[ROW][C]77[/C][C]0.123934[/C][C]0.247867[/C][C]0.876066[/C][/ROW]
[ROW][C]78[/C][C]0.118[/C][C]0.236001[/C][C]0.882[/C][/ROW]
[ROW][C]79[/C][C]0.112933[/C][C]0.225866[/C][C]0.887067[/C][/ROW]
[ROW][C]80[/C][C]0.139359[/C][C]0.278717[/C][C]0.860641[/C][/ROW]
[ROW][C]81[/C][C]0.125629[/C][C]0.251258[/C][C]0.874371[/C][/ROW]
[ROW][C]82[/C][C]0.130691[/C][C]0.261382[/C][C]0.869309[/C][/ROW]
[ROW][C]83[/C][C]0.114588[/C][C]0.229177[/C][C]0.885412[/C][/ROW]
[ROW][C]84[/C][C]0.197223[/C][C]0.394445[/C][C]0.802777[/C][/ROW]
[ROW][C]85[/C][C]0.195456[/C][C]0.390911[/C][C]0.804544[/C][/ROW]
[ROW][C]86[/C][C]0.174736[/C][C]0.349472[/C][C]0.825264[/C][/ROW]
[ROW][C]87[/C][C]0.155363[/C][C]0.310725[/C][C]0.844637[/C][/ROW]
[ROW][C]88[/C][C]0.137885[/C][C]0.275769[/C][C]0.862115[/C][/ROW]
[ROW][C]89[/C][C]0.150903[/C][C]0.301805[/C][C]0.849097[/C][/ROW]
[ROW][C]90[/C][C]0.157788[/C][C]0.315577[/C][C]0.842212[/C][/ROW]
[ROW][C]91[/C][C]0.1499[/C][C]0.2998[/C][C]0.8501[/C][/ROW]
[ROW][C]92[/C][C]0.268349[/C][C]0.536698[/C][C]0.731651[/C][/ROW]
[ROW][C]93[/C][C]0.246133[/C][C]0.492266[/C][C]0.753867[/C][/ROW]
[ROW][C]94[/C][C]0.244862[/C][C]0.489725[/C][C]0.755138[/C][/ROW]
[ROW][C]95[/C][C]0.299121[/C][C]0.598243[/C][C]0.700879[/C][/ROW]
[ROW][C]96[/C][C]0.291197[/C][C]0.582395[/C][C]0.708803[/C][/ROW]
[ROW][C]97[/C][C]0.313338[/C][C]0.626676[/C][C]0.686662[/C][/ROW]
[ROW][C]98[/C][C]0.287788[/C][C]0.575576[/C][C]0.712212[/C][/ROW]
[ROW][C]99[/C][C]0.304632[/C][C]0.609264[/C][C]0.695368[/C][/ROW]
[ROW][C]100[/C][C]0.388033[/C][C]0.776066[/C][C]0.611967[/C][/ROW]
[ROW][C]101[/C][C]0.363293[/C][C]0.726585[/C][C]0.636707[/C][/ROW]
[ROW][C]102[/C][C]0.342056[/C][C]0.684113[/C][C]0.657944[/C][/ROW]
[ROW][C]103[/C][C]0.352274[/C][C]0.704548[/C][C]0.647726[/C][/ROW]
[ROW][C]104[/C][C]0.360672[/C][C]0.721343[/C][C]0.639328[/C][/ROW]
[ROW][C]105[/C][C]0.36986[/C][C]0.739721[/C][C]0.63014[/C][/ROW]
[ROW][C]106[/C][C]0.404772[/C][C]0.809544[/C][C]0.595228[/C][/ROW]
[ROW][C]107[/C][C]0.410682[/C][C]0.821364[/C][C]0.589318[/C][/ROW]
[ROW][C]108[/C][C]0.592015[/C][C]0.81597[/C][C]0.407985[/C][/ROW]
[ROW][C]109[/C][C]0.704314[/C][C]0.591373[/C][C]0.295686[/C][/ROW]
[ROW][C]110[/C][C]0.72111[/C][C]0.55778[/C][C]0.27889[/C][/ROW]
[ROW][C]111[/C][C]0.70364[/C][C]0.592719[/C][C]0.29636[/C][/ROW]
[ROW][C]112[/C][C]0.685086[/C][C]0.629828[/C][C]0.314914[/C][/ROW]
[ROW][C]113[/C][C]0.850852[/C][C]0.298297[/C][C]0.149148[/C][/ROW]
[ROW][C]114[/C][C]0.877501[/C][C]0.244998[/C][C]0.122499[/C][/ROW]
[ROW][C]115[/C][C]0.900731[/C][C]0.198538[/C][C]0.0992692[/C][/ROW]
[ROW][C]116[/C][C]0.932465[/C][C]0.13507[/C][C]0.067535[/C][/ROW]
[ROW][C]117[/C][C]0.939127[/C][C]0.121746[/C][C]0.0608732[/C][/ROW]
[ROW][C]118[/C][C]0.935286[/C][C]0.129429[/C][C]0.0647144[/C][/ROW]
[ROW][C]119[/C][C]0.938129[/C][C]0.123742[/C][C]0.061871[/C][/ROW]
[ROW][C]120[/C][C]0.956538[/C][C]0.0869238[/C][C]0.0434619[/C][/ROW]
[ROW][C]121[/C][C]0.951923[/C][C]0.0961543[/C][C]0.0480772[/C][/ROW]
[ROW][C]122[/C][C]0.959292[/C][C]0.0814156[/C][C]0.0407078[/C][/ROW]
[ROW][C]123[/C][C]0.963728[/C][C]0.0725431[/C][C]0.0362716[/C][/ROW]
[ROW][C]124[/C][C]0.975592[/C][C]0.048816[/C][C]0.024408[/C][/ROW]
[ROW][C]125[/C][C]0.977493[/C][C]0.045014[/C][C]0.022507[/C][/ROW]
[ROW][C]126[/C][C]0.973429[/C][C]0.0531428[/C][C]0.0265714[/C][/ROW]
[ROW][C]127[/C][C]0.974645[/C][C]0.0507103[/C][C]0.0253551[/C][/ROW]
[ROW][C]128[/C][C]0.971165[/C][C]0.05767[/C][C]0.028835[/C][/ROW]
[ROW][C]129[/C][C]0.978131[/C][C]0.0437385[/C][C]0.0218692[/C][/ROW]
[ROW][C]130[/C][C]0.976896[/C][C]0.0462072[/C][C]0.0231036[/C][/ROW]
[ROW][C]131[/C][C]0.973697[/C][C]0.052606[/C][C]0.026303[/C][/ROW]
[ROW][C]132[/C][C]0.971126[/C][C]0.0577478[/C][C]0.0288739[/C][/ROW]
[ROW][C]133[/C][C]0.969464[/C][C]0.0610723[/C][C]0.0305361[/C][/ROW]
[ROW][C]134[/C][C]0.965998[/C][C]0.068005[/C][C]0.0340025[/C][/ROW]
[ROW][C]135[/C][C]0.963221[/C][C]0.0735576[/C][C]0.0367788[/C][/ROW]
[ROW][C]136[/C][C]0.956995[/C][C]0.0860101[/C][C]0.043005[/C][/ROW]
[ROW][C]137[/C][C]0.968467[/C][C]0.0630661[/C][C]0.031533[/C][/ROW]
[ROW][C]138[/C][C]0.978569[/C][C]0.0428627[/C][C]0.0214313[/C][/ROW]
[ROW][C]139[/C][C]0.981992[/C][C]0.0360161[/C][C]0.018008[/C][/ROW]
[ROW][C]140[/C][C]0.979276[/C][C]0.0414471[/C][C]0.0207236[/C][/ROW]
[ROW][C]141[/C][C]0.975584[/C][C]0.0488316[/C][C]0.0244158[/C][/ROW]
[ROW][C]142[/C][C]0.975371[/C][C]0.0492572[/C][C]0.0246286[/C][/ROW]
[ROW][C]143[/C][C]0.970401[/C][C]0.0591987[/C][C]0.0295993[/C][/ROW]
[ROW][C]144[/C][C]0.973929[/C][C]0.0521428[/C][C]0.0260714[/C][/ROW]
[ROW][C]145[/C][C]0.970346[/C][C]0.0593074[/C][C]0.0296537[/C][/ROW]
[ROW][C]146[/C][C]0.969087[/C][C]0.0618252[/C][C]0.0309126[/C][/ROW]
[ROW][C]147[/C][C]0.968663[/C][C]0.0626733[/C][C]0.0313366[/C][/ROW]
[ROW][C]148[/C][C]0.968033[/C][C]0.0639343[/C][C]0.0319672[/C][/ROW]
[ROW][C]149[/C][C]0.966326[/C][C]0.0673479[/C][C]0.0336739[/C][/ROW]
[ROW][C]150[/C][C]0.967453[/C][C]0.0650937[/C][C]0.0325468[/C][/ROW]
[ROW][C]151[/C][C]0.979248[/C][C]0.0415047[/C][C]0.0207524[/C][/ROW]
[ROW][C]152[/C][C]0.977443[/C][C]0.0451133[/C][C]0.0225566[/C][/ROW]
[ROW][C]153[/C][C]0.977451[/C][C]0.0450971[/C][C]0.0225485[/C][/ROW]
[ROW][C]154[/C][C]0.97613[/C][C]0.0477394[/C][C]0.0238697[/C][/ROW]
[ROW][C]155[/C][C]0.976387[/C][C]0.0472266[/C][C]0.0236133[/C][/ROW]
[ROW][C]156[/C][C]0.97223[/C][C]0.0555405[/C][C]0.0277702[/C][/ROW]
[ROW][C]157[/C][C]0.977005[/C][C]0.0459893[/C][C]0.0229946[/C][/ROW]
[ROW][C]158[/C][C]0.978284[/C][C]0.0434317[/C][C]0.0217159[/C][/ROW]
[ROW][C]159[/C][C]0.974207[/C][C]0.0515852[/C][C]0.0257926[/C][/ROW]
[ROW][C]160[/C][C]0.969971[/C][C]0.0600573[/C][C]0.0300287[/C][/ROW]
[ROW][C]161[/C][C]0.979629[/C][C]0.0407416[/C][C]0.0203708[/C][/ROW]
[ROW][C]162[/C][C]0.978859[/C][C]0.0422824[/C][C]0.0211412[/C][/ROW]
[ROW][C]163[/C][C]0.975278[/C][C]0.0494448[/C][C]0.0247224[/C][/ROW]
[ROW][C]164[/C][C]0.97857[/C][C]0.0428606[/C][C]0.0214303[/C][/ROW]
[ROW][C]165[/C][C]0.981934[/C][C]0.0361312[/C][C]0.0180656[/C][/ROW]
[ROW][C]166[/C][C]0.978257[/C][C]0.0434863[/C][C]0.0217431[/C][/ROW]
[ROW][C]167[/C][C]0.981976[/C][C]0.0360486[/C][C]0.0180243[/C][/ROW]
[ROW][C]168[/C][C]0.980276[/C][C]0.0394473[/C][C]0.0197236[/C][/ROW]
[ROW][C]169[/C][C]0.97609[/C][C]0.0478205[/C][C]0.0239103[/C][/ROW]
[ROW][C]170[/C][C]0.97351[/C][C]0.0529794[/C][C]0.0264897[/C][/ROW]
[ROW][C]171[/C][C]0.970592[/C][C]0.0588153[/C][C]0.0294077[/C][/ROW]
[ROW][C]172[/C][C]0.97685[/C][C]0.0463009[/C][C]0.0231504[/C][/ROW]
[ROW][C]173[/C][C]0.972164[/C][C]0.0556728[/C][C]0.0278364[/C][/ROW]
[ROW][C]174[/C][C]0.966545[/C][C]0.0669108[/C][C]0.0334554[/C][/ROW]
[ROW][C]175[/C][C]0.96008[/C][C]0.0798396[/C][C]0.0399198[/C][/ROW]
[ROW][C]176[/C][C]0.966838[/C][C]0.0663243[/C][C]0.0331621[/C][/ROW]
[ROW][C]177[/C][C]0.960743[/C][C]0.0785138[/C][C]0.0392569[/C][/ROW]
[ROW][C]178[/C][C]0.968479[/C][C]0.0630425[/C][C]0.0315212[/C][/ROW]
[ROW][C]179[/C][C]0.96186[/C][C]0.0762793[/C][C]0.0381396[/C][/ROW]
[ROW][C]180[/C][C]0.967088[/C][C]0.0658248[/C][C]0.0329124[/C][/ROW]
[ROW][C]181[/C][C]0.961007[/C][C]0.0779865[/C][C]0.0389933[/C][/ROW]
[ROW][C]182[/C][C]0.952546[/C][C]0.0949074[/C][C]0.0474537[/C][/ROW]
[ROW][C]183[/C][C]0.959817[/C][C]0.0803654[/C][C]0.0401827[/C][/ROW]
[ROW][C]184[/C][C]0.952198[/C][C]0.0956037[/C][C]0.0478018[/C][/ROW]
[ROW][C]185[/C][C]0.955795[/C][C]0.0884108[/C][C]0.0442054[/C][/ROW]
[ROW][C]186[/C][C]0.949041[/C][C]0.101919[/C][C]0.0509594[/C][/ROW]
[ROW][C]187[/C][C]0.957781[/C][C]0.0844388[/C][C]0.0422194[/C][/ROW]
[ROW][C]188[/C][C]0.9505[/C][C]0.0989994[/C][C]0.0494997[/C][/ROW]
[ROW][C]189[/C][C]0.940936[/C][C]0.118127[/C][C]0.0590637[/C][/ROW]
[ROW][C]190[/C][C]0.928995[/C][C]0.14201[/C][C]0.0710049[/C][/ROW]
[ROW][C]191[/C][C]0.916799[/C][C]0.166401[/C][C]0.0832006[/C][/ROW]
[ROW][C]192[/C][C]0.916275[/C][C]0.16745[/C][C]0.0837251[/C][/ROW]
[ROW][C]193[/C][C]0.934636[/C][C]0.130728[/C][C]0.0653642[/C][/ROW]
[ROW][C]194[/C][C]0.939341[/C][C]0.121317[/C][C]0.0606587[/C][/ROW]
[ROW][C]195[/C][C]0.928419[/C][C]0.143161[/C][C]0.0715805[/C][/ROW]
[ROW][C]196[/C][C]0.917349[/C][C]0.165301[/C][C]0.0826506[/C][/ROW]
[ROW][C]197[/C][C]0.90338[/C][C]0.19324[/C][C]0.09662[/C][/ROW]
[ROW][C]198[/C][C]0.886914[/C][C]0.226172[/C][C]0.113086[/C][/ROW]
[ROW][C]199[/C][C]0.880892[/C][C]0.238216[/C][C]0.119108[/C][/ROW]
[ROW][C]200[/C][C]0.86541[/C][C]0.26918[/C][C]0.13459[/C][/ROW]
[ROW][C]201[/C][C]0.866694[/C][C]0.266613[/C][C]0.133306[/C][/ROW]
[ROW][C]202[/C][C]0.846822[/C][C]0.306356[/C][C]0.153178[/C][/ROW]
[ROW][C]203[/C][C]0.825381[/C][C]0.349238[/C][C]0.174619[/C][/ROW]
[ROW][C]204[/C][C]0.81137[/C][C]0.377259[/C][C]0.18863[/C][/ROW]
[ROW][C]205[/C][C]0.792921[/C][C]0.414157[/C][C]0.207079[/C][/ROW]
[ROW][C]206[/C][C]0.783929[/C][C]0.432143[/C][C]0.216071[/C][/ROW]
[ROW][C]207[/C][C]0.789183[/C][C]0.421635[/C][C]0.210817[/C][/ROW]
[ROW][C]208[/C][C]0.767707[/C][C]0.464585[/C][C]0.232293[/C][/ROW]
[ROW][C]209[/C][C]0.738159[/C][C]0.523682[/C][C]0.261841[/C][/ROW]
[ROW][C]210[/C][C]0.721293[/C][C]0.557414[/C][C]0.278707[/C][/ROW]
[ROW][C]211[/C][C]0.688166[/C][C]0.623668[/C][C]0.311834[/C][/ROW]
[ROW][C]212[/C][C]0.654448[/C][C]0.691103[/C][C]0.345552[/C][/ROW]
[ROW][C]213[/C][C]0.634776[/C][C]0.730448[/C][C]0.365224[/C][/ROW]
[ROW][C]214[/C][C]0.597577[/C][C]0.804846[/C][C]0.402423[/C][/ROW]
[ROW][C]215[/C][C]0.568836[/C][C]0.862328[/C][C]0.431164[/C][/ROW]
[ROW][C]216[/C][C]0.540942[/C][C]0.918115[/C][C]0.459058[/C][/ROW]
[ROW][C]217[/C][C]0.514013[/C][C]0.971973[/C][C]0.485987[/C][/ROW]
[ROW][C]218[/C][C]0.471178[/C][C]0.942355[/C][C]0.528822[/C][/ROW]
[ROW][C]219[/C][C]0.430266[/C][C]0.860533[/C][C]0.569734[/C][/ROW]
[ROW][C]220[/C][C]0.403669[/C][C]0.807337[/C][C]0.596331[/C][/ROW]
[ROW][C]221[/C][C]0.391857[/C][C]0.783715[/C][C]0.608143[/C][/ROW]
[ROW][C]222[/C][C]0.405474[/C][C]0.810948[/C][C]0.594526[/C][/ROW]
[ROW][C]223[/C][C]0.362543[/C][C]0.725086[/C][C]0.637457[/C][/ROW]
[ROW][C]224[/C][C]0.322009[/C][C]0.644018[/C][C]0.677991[/C][/ROW]
[ROW][C]225[/C][C]0.399394[/C][C]0.798788[/C][C]0.600606[/C][/ROW]
[ROW][C]226[/C][C]0.384482[/C][C]0.768964[/C][C]0.615518[/C][/ROW]
[ROW][C]227[/C][C]0.347932[/C][C]0.695863[/C][C]0.652068[/C][/ROW]
[ROW][C]228[/C][C]0.382352[/C][C]0.764703[/C][C]0.617648[/C][/ROW]
[ROW][C]229[/C][C]0.424209[/C][C]0.848419[/C][C]0.575791[/C][/ROW]
[ROW][C]230[/C][C]0.445879[/C][C]0.891757[/C][C]0.554121[/C][/ROW]
[ROW][C]231[/C][C]0.449832[/C][C]0.899664[/C][C]0.550168[/C][/ROW]
[ROW][C]232[/C][C]0.469149[/C][C]0.938298[/C][C]0.530851[/C][/ROW]
[ROW][C]233[/C][C]0.432833[/C][C]0.865666[/C][C]0.567167[/C][/ROW]
[ROW][C]234[/C][C]0.404554[/C][C]0.809108[/C][C]0.595446[/C][/ROW]
[ROW][C]235[/C][C]0.370138[/C][C]0.740276[/C][C]0.629862[/C][/ROW]
[ROW][C]236[/C][C]0.629081[/C][C]0.741838[/C][C]0.370919[/C][/ROW]
[ROW][C]237[/C][C]0.578797[/C][C]0.842406[/C][C]0.421203[/C][/ROW]
[ROW][C]238[/C][C]0.5491[/C][C]0.901799[/C][C]0.4509[/C][/ROW]
[ROW][C]239[/C][C]0.558537[/C][C]0.882927[/C][C]0.441463[/C][/ROW]
[ROW][C]240[/C][C]0.562561[/C][C]0.874877[/C][C]0.437439[/C][/ROW]
[ROW][C]241[/C][C]0.512554[/C][C]0.974891[/C][C]0.487446[/C][/ROW]
[ROW][C]242[/C][C]0.479884[/C][C]0.959769[/C][C]0.520116[/C][/ROW]
[ROW][C]243[/C][C]0.431223[/C][C]0.862445[/C][C]0.568777[/C][/ROW]
[ROW][C]244[/C][C]0.543675[/C][C]0.91265[/C][C]0.456325[/C][/ROW]
[ROW][C]245[/C][C]0.527825[/C][C]0.94435[/C][C]0.472175[/C][/ROW]
[ROW][C]246[/C][C]0.482896[/C][C]0.965792[/C][C]0.517104[/C][/ROW]
[ROW][C]247[/C][C]0.432752[/C][C]0.865505[/C][C]0.567248[/C][/ROW]
[ROW][C]248[/C][C]0.384785[/C][C]0.76957[/C][C]0.615215[/C][/ROW]
[ROW][C]249[/C][C]0.327137[/C][C]0.654274[/C][C]0.672863[/C][/ROW]
[ROW][C]250[/C][C]0.277967[/C][C]0.555935[/C][C]0.722033[/C][/ROW]
[ROW][C]251[/C][C]0.32251[/C][C]0.645019[/C][C]0.67749[/C][/ROW]
[ROW][C]252[/C][C]0.28532[/C][C]0.57064[/C][C]0.71468[/C][/ROW]
[ROW][C]253[/C][C]0.245425[/C][C]0.49085[/C][C]0.754575[/C][/ROW]
[ROW][C]254[/C][C]0.339452[/C][C]0.678903[/C][C]0.660548[/C][/ROW]
[ROW][C]255[/C][C]0.290895[/C][C]0.581789[/C][C]0.709105[/C][/ROW]
[ROW][C]256[/C][C]0.254467[/C][C]0.508935[/C][C]0.745533[/C][/ROW]
[ROW][C]257[/C][C]0.306392[/C][C]0.612785[/C][C]0.693608[/C][/ROW]
[ROW][C]258[/C][C]0.61658[/C][C]0.76684[/C][C]0.38342[/C][/ROW]
[ROW][C]259[/C][C]0.550744[/C][C]0.898513[/C][C]0.449256[/C][/ROW]
[ROW][C]260[/C][C]0.986696[/C][C]0.0266088[/C][C]0.0133044[/C][/ROW]
[ROW][C]261[/C][C]0.973345[/C][C]0.0533107[/C][C]0.0266553[/C][/ROW]
[ROW][C]262[/C][C]0.950621[/C][C]0.0987575[/C][C]0.0493788[/C][/ROW]
[ROW][C]263[/C][C]0.945134[/C][C]0.109731[/C][C]0.0548656[/C][/ROW]
[ROW][C]264[/C][C]0.89824[/C][C]0.203521[/C][C]0.10176[/C][/ROW]
[ROW][C]265[/C][C]0.836915[/C][C]0.326169[/C][C]0.163085[/C][/ROW]
[ROW][C]266[/C][C]0.857045[/C][C]0.28591[/C][C]0.142955[/C][/ROW]
[ROW][C]267[/C][C]0.727835[/C][C]0.544331[/C][C]0.272165[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280357&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280357&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.1393270.2786530.860673
120.3559240.7118470.644076
130.2460310.4920610.753969
140.2827180.5654360.717282
150.2059150.411830.794085
160.166750.3334990.83325
170.1172530.2345070.882747
180.1089290.2178580.891071
190.08669070.1733810.913309
200.05496890.1099380.945031
210.05569180.1113840.944308
220.03725010.07450030.96275
230.02291020.04582040.97709
240.0347640.06952810.965236
250.03107150.06214310.968928
260.02134220.04268430.978658
270.0133560.02671190.986644
280.009563460.01912690.990437
290.00672880.01345760.993271
300.003997690.007995380.996002
310.007436360.01487270.992564
320.004590630.009181270.995409
330.004970950.009941890.995029
340.09504020.190080.90496
350.07474080.1494820.925259
360.06022240.1204450.939778
370.04658860.09317720.953411
380.03404690.06809380.965953
390.03419230.06838460.965808
400.02473270.04946540.975267
410.05831330.1166270.941687
420.05206510.104130.947935
430.05344430.1068890.946556
440.04588750.09177510.954112
450.03463470.06926940.965365
460.0281710.0563420.971829
470.02340750.04681510.976592
480.03065190.06130380.969348
490.04371190.08742370.956288
500.04483530.08967060.955165
510.03496160.06992320.965038
520.07786860.1557370.922131
530.06664990.13330.93335
540.07266140.1453230.927339
550.08659930.1731990.913401
560.07172270.1434450.928277
570.1627580.3255150.837242
580.1648610.3297230.835139
590.1475370.2950730.852463
600.1829530.3659060.817047
610.1687010.3374020.831299
620.1536290.3072590.846371
630.2411470.4822950.758853
640.3063560.6127110.693644
650.2930470.5860940.706953
660.2791770.5583550.720823
670.2504080.5008170.749592
680.239560.479120.76044
690.2418070.4836140.758193
700.2173090.4346180.782691
710.1908560.3817120.809144
720.1647990.3295980.835201
730.1566850.3133690.843315
740.1634680.3269350.836532
750.1448930.2897860.855107
760.1376850.275370.862315
770.1239340.2478670.876066
780.1180.2360010.882
790.1129330.2258660.887067
800.1393590.2787170.860641
810.1256290.2512580.874371
820.1306910.2613820.869309
830.1145880.2291770.885412
840.1972230.3944450.802777
850.1954560.3909110.804544
860.1747360.3494720.825264
870.1553630.3107250.844637
880.1378850.2757690.862115
890.1509030.3018050.849097
900.1577880.3155770.842212
910.14990.29980.8501
920.2683490.5366980.731651
930.2461330.4922660.753867
940.2448620.4897250.755138
950.2991210.5982430.700879
960.2911970.5823950.708803
970.3133380.6266760.686662
980.2877880.5755760.712212
990.3046320.6092640.695368
1000.3880330.7760660.611967
1010.3632930.7265850.636707
1020.3420560.6841130.657944
1030.3522740.7045480.647726
1040.3606720.7213430.639328
1050.369860.7397210.63014
1060.4047720.8095440.595228
1070.4106820.8213640.589318
1080.5920150.815970.407985
1090.7043140.5913730.295686
1100.721110.557780.27889
1110.703640.5927190.29636
1120.6850860.6298280.314914
1130.8508520.2982970.149148
1140.8775010.2449980.122499
1150.9007310.1985380.0992692
1160.9324650.135070.067535
1170.9391270.1217460.0608732
1180.9352860.1294290.0647144
1190.9381290.1237420.061871
1200.9565380.08692380.0434619
1210.9519230.09615430.0480772
1220.9592920.08141560.0407078
1230.9637280.07254310.0362716
1240.9755920.0488160.024408
1250.9774930.0450140.022507
1260.9734290.05314280.0265714
1270.9746450.05071030.0253551
1280.9711650.057670.028835
1290.9781310.04373850.0218692
1300.9768960.04620720.0231036
1310.9736970.0526060.026303
1320.9711260.05774780.0288739
1330.9694640.06107230.0305361
1340.9659980.0680050.0340025
1350.9632210.07355760.0367788
1360.9569950.08601010.043005
1370.9684670.06306610.031533
1380.9785690.04286270.0214313
1390.9819920.03601610.018008
1400.9792760.04144710.0207236
1410.9755840.04883160.0244158
1420.9753710.04925720.0246286
1430.9704010.05919870.0295993
1440.9739290.05214280.0260714
1450.9703460.05930740.0296537
1460.9690870.06182520.0309126
1470.9686630.06267330.0313366
1480.9680330.06393430.0319672
1490.9663260.06734790.0336739
1500.9674530.06509370.0325468
1510.9792480.04150470.0207524
1520.9774430.04511330.0225566
1530.9774510.04509710.0225485
1540.976130.04773940.0238697
1550.9763870.04722660.0236133
1560.972230.05554050.0277702
1570.9770050.04598930.0229946
1580.9782840.04343170.0217159
1590.9742070.05158520.0257926
1600.9699710.06005730.0300287
1610.9796290.04074160.0203708
1620.9788590.04228240.0211412
1630.9752780.04944480.0247224
1640.978570.04286060.0214303
1650.9819340.03613120.0180656
1660.9782570.04348630.0217431
1670.9819760.03604860.0180243
1680.9802760.03944730.0197236
1690.976090.04782050.0239103
1700.973510.05297940.0264897
1710.9705920.05881530.0294077
1720.976850.04630090.0231504
1730.9721640.05567280.0278364
1740.9665450.06691080.0334554
1750.960080.07983960.0399198
1760.9668380.06632430.0331621
1770.9607430.07851380.0392569
1780.9684790.06304250.0315212
1790.961860.07627930.0381396
1800.9670880.06582480.0329124
1810.9610070.07798650.0389933
1820.9525460.09490740.0474537
1830.9598170.08036540.0401827
1840.9521980.09560370.0478018
1850.9557950.08841080.0442054
1860.9490410.1019190.0509594
1870.9577810.08443880.0422194
1880.95050.09899940.0494997
1890.9409360.1181270.0590637
1900.9289950.142010.0710049
1910.9167990.1664010.0832006
1920.9162750.167450.0837251
1930.9346360.1307280.0653642
1940.9393410.1213170.0606587
1950.9284190.1431610.0715805
1960.9173490.1653010.0826506
1970.903380.193240.09662
1980.8869140.2261720.113086
1990.8808920.2382160.119108
2000.865410.269180.13459
2010.8666940.2666130.133306
2020.8468220.3063560.153178
2030.8253810.3492380.174619
2040.811370.3772590.18863
2050.7929210.4141570.207079
2060.7839290.4321430.216071
2070.7891830.4216350.210817
2080.7677070.4645850.232293
2090.7381590.5236820.261841
2100.7212930.5574140.278707
2110.6881660.6236680.311834
2120.6544480.6911030.345552
2130.6347760.7304480.365224
2140.5975770.8048460.402423
2150.5688360.8623280.431164
2160.5409420.9181150.459058
2170.5140130.9719730.485987
2180.4711780.9423550.528822
2190.4302660.8605330.569734
2200.4036690.8073370.596331
2210.3918570.7837150.608143
2220.4054740.8109480.594526
2230.3625430.7250860.637457
2240.3220090.6440180.677991
2250.3993940.7987880.600606
2260.3844820.7689640.615518
2270.3479320.6958630.652068
2280.3823520.7647030.617648
2290.4242090.8484190.575791
2300.4458790.8917570.554121
2310.4498320.8996640.550168
2320.4691490.9382980.530851
2330.4328330.8656660.567167
2340.4045540.8091080.595446
2350.3701380.7402760.629862
2360.6290810.7418380.370919
2370.5787970.8424060.421203
2380.54910.9017990.4509
2390.5585370.8829270.441463
2400.5625610.8748770.437439
2410.5125540.9748910.487446
2420.4798840.9597690.520116
2430.4312230.8624450.568777
2440.5436750.912650.456325
2450.5278250.944350.472175
2460.4828960.9657920.517104
2470.4327520.8655050.567248
2480.3847850.769570.615215
2490.3271370.6542740.672863
2500.2779670.5559350.722033
2510.322510.6450190.67749
2520.285320.570640.71468
2530.2454250.490850.754575
2540.3394520.6789030.660548
2550.2908950.5817890.709105
2560.2544670.5089350.745533
2570.3063920.6127850.693608
2580.616580.766840.38342
2590.5507440.8985130.449256
2600.9866960.02660880.0133044
2610.9733450.05331070.0266553
2620.9506210.09875750.0493788
2630.9451340.1097310.0548656
2640.898240.2035210.10176
2650.8369150.3261690.163085
2660.8570450.285910.142955
2670.7278350.5443310.272165






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level30.0116732NOK
5% type I error level380.14786NOK
10% type I error level950.36965NOK

\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 & 3 & 0.0116732 & NOK \tabularnewline
5% type I error level & 38 & 0.14786 & NOK \tabularnewline
10% type I error level & 95 & 0.36965 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280357&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]3[/C][C]0.0116732[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]38[/C][C]0.14786[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]95[/C][C]0.36965[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280357&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280357&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 level30.0116732NOK
5% type I error level380.14786NOK
10% type I error level950.36965NOK


Figures (Output of Computation)

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Input Parameters & R Code

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