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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, 05 Dec 2010 20:18:32 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/05/t1291580231e5hcwygpxfop3zx.htm/, Retrieved Mon, 29 Apr 2024 05:47:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105492, Retrieved Mon, 29 Apr 2024 05:47:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact219

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2010-12-05 20:18:32] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
-   PD    [Multiple Regression] [MR organisatie] [2010-12-12 19:33:58] [b11c112f8986de933f8b95cd30e75cc2]
-   PD    [Multiple Regression] [MR geslacht] [2010-12-12 20:16:35] [b11c112f8986de933f8b95cd30e75cc2]
-   PD    [Multiple Regression] [MR geslacht] [2010-12-12 20:16:35] [b11c112f8986de933f8b95cd30e75cc2]
-   PD    [Multiple Regression] [Multiple Regressi...] [2010-12-19 15:50:49] [c289bfbb56808c5d93a0f55b5d39f5bd]
-   P       [Multiple Regression] [MR - Cannotdo ver...] [2010-12-19 18:20:33] [c289bfbb56808c5d93a0f55b5d39f5bd]
-   PD    [Multiple Regression] [] [2010-12-21 14:38:38] [abe7df3fc544bbb0ed435b4e9982bc91]
- R PD    [Multiple Regression] [] [2011-12-11 15:11:10] [b4c8fd31b0af00c33711722ddf8d2c4c]
- RMP     [Multiple Regression] [] [2011-12-12 13:36:27] [4c0148be6b1ebc4ef8d5b4e23a77fcfa]
- RMPD    [Kendall tau Correlation Matrix] [pearson correlati...] [2011-12-15 19:04:01] [1ed874da5cc4aa1cd1ced057f766d90b]
- RMPD    [Kendall tau Correlation Matrix] [pearson correlati...] [2011-12-15 19:04:01] [1ed874da5cc4aa1cd1ced057f766d90b]
-   P       [Kendall tau Correlation Matrix] [kendall's correla...] [2011-12-15 19:08:57] [1ed874da5cc4aa1cd1ced057f766d90b]
- RMP       [Multiple Regression] [PLC] [2011-12-15 19:15:06] [1ed874da5cc4aa1cd1ced057f766d90b]
- RMP       [Recursive Partitioning (Regression Trees)] [Recursive partiti...] [2011-12-15 19:19:40] [1ed874da5cc4aa1cd1ced057f766d90b]
- R PD    [Multiple Regression] [WS 10 Residuals] [2012-12-10 14:53:53] [69075022316765aefe76d0d287433423]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	1	41	38	13	12	14
1	1	39	32	16	11	18
1	1	30	35	19	15	11
1	0	31	33	15	6	12
1	1	34	37	14	13	16
1	1	35	29	13	10	18
1	1	39	31	19	12	14
1	1	34	36	15	14	14
1	1	36	35	14	12	15
1	1	37	38	15	9	15
1	0	38	31	16	10	17
1	1	36	34	16	12	19
1	0	38	35	16	12	10
1	1	39	38	16	11	16
1	1	33	37	17	15	18
1	0	32	33	15	12	14
1	0	36	32	15	10	14
1	1	38	38	20	12	17
1	0	39	38	18	11	14
1	1	32	32	16	12	16
1	0	32	33	16	11	18
1	1	31	31	16	12	11
1	1	39	38	19	13	14
1	1	37	39	16	11	12
1	0	39	32	17	12	17
1	1	41	32	17	13	9
1	0	36	35	16	10	16
1	1	33	37	15	14	14
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1	0	34	33	14	10	11
1	1	31	31	15	12	16
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1	1	37	31	14	10	17
1	1	34	37	16	12	15
1	0	34	30	14	12	14
1	0	32	33	10	7	16
1	0	29	31	10	9	9
1	0	36	33	14	12	15
1	1	29	31	16	10	17
1	0	35	33	16	10	13
1	0	37	32	16	10	15
1	1	34	33	14	12	16
1	0	38	32	20	15	16
1	0	35	33	14	10	12
1	1	38	28	14	10	15
1	1	37	35	11	12	11
1	1	38	39	14	13	15
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1	1	36	38	16	11	17
1	0	38	32	14	12	13
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1	0	32	33	12	12	11
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1	1	37	35	14	6	15
1	1	39	34	16	12	16
1	1	29	34	16	12	15
1	0	37	36	15	11	12
1	1	35	34	16	10	12
1	0	30	28	12	7	8
1	0	38	34	16	12	13
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1	0	35	37	17	13	10
1	1	36	35	18	14	11
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1	0	35	37	16	12	15
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1	0	38	41	18	14	15
1	0	34	27	16	12	13
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1	1	35	37	16	12	15
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1	1	33	34	16	12	14
1	1	29	32	16	12	13
1	1	33	33	15	12	7
1	1	31	36	12	9	17
1	1	36	32	17	15	13
1	1	35	41	16	12	15
1	1	32	28	15	12	14
1	1	29	30	13	12	13
1	1	39	36	16	10	16
1	1	37	35	16	13	12
1	1	35	31	16	9	14
1	0	37	34	16	12	17
1	0	32	36	14	10	15
1	1	38	36	16	14	17
1	0	37	35	16	11	12
1	1	36	37	20	15	16
1	0	32	28	15	11	11
1	1	33	39	16	11	15
1	0	40	32	13	12	9
1	1	38	35	17	12	16
1	0	41	39	16	12	15
1	0	36	35	16	11	10
1	1	43	42	12	7	10
1	1	30	34	16	12	15
1	1	31	33	16	14	11
1	1	32	41	17	11	13
1	1	37	34	12	10	18
1	0	37	32	18	13	16
1	1	33	40	14	13	14
1	1	34	40	14	8	14
1	1	33	35	13	11	14
1	1	38	36	16	12	14
1	0	33	37	13	11	12
1	1	31	27	16	13	14
1	1	38	39	13	12	15
1	1	37	38	16	14	15
1	1	36	31	15	13	15
1	1	31	33	16	15	13
1	0	39	32	15	10	17
1	1	44	39	17	11	17
1	1	33	36	15	9	19
1	1	35	33	12	11	15
1	0	32	33	16	10	13
1	0	28	32	10	11	9
1	1	40	37	16	8	15
1	0	27	30	12	11	15
1	0	37	38	14	12	15
1	1	32	29	15	12	16
1	0	28	22	13	9	11
1	0	34	35	15	11	14
1	1	30	35	11	10	11
1	1	35	34	12	8	15
1	0	31	35	11	9	13
1	1	32	34	16	8	15
1	0	30	37	15	9	16
1	1	30	35	17	15	14
1	0	31	23	16	11	15
1	1	40	31	10	8	16
1	1	32	27	18	13	16
1	0	36	36	13	12	11
1	0	32	31	16	12	12
1	0	35	32	13	9	9
1	1	38	39	10	7	16
1	1	42	37	15	13	13
1	0	34	38	16	9	16
1	1	35	39	16	6	12
1	1	38	34	14	8	9
1	1	33	31	10	8	13
1	1	32	37	13	6	14
1	1	33	36	15	9	19
1	1	34	32	16	11	13
1	1	32	38	12	8	12
0	0	27	26	13	10	10
0	0	31	26	12	8	14
0	0	38	33	17	14	16
0	1	34	39	15	10	10
0	0	24	30	10	8	11
0	0	30	33	14	11	14
0	1	26	25	11	12	12
0	1	34	38	13	12	9
0	0	27	37	16	12	9
0	0	37	31	12	5	11
0	1	36	37	16	12	16
0	0	41	35	12	10	9
0	1	29	25	9	7	13
0	1	36	28	12	12	16
0	0	32	35	15	11	13
0	1	37	33	12	8	9
0	0	30	30	12	9	12
0	1	31	31	14	10	16
0	1	38	37	12	9	11
0	1	36	36	16	12	14
0	0	35	30	11	6	13
0	0	31	36	19	15	15
0	0	38	32	15	12	14
0	1	22	28	8	12	16
0	1	32	36	16	12	13
0	0	36	34	17	11	14
0	1	39	31	12	7	15
0	0	28	28	11	7	13
0	0	32	36	11	5	11
0	1	32	36	14	12	11
0	1	38	40	16	12	14
0	1	32	33	12	3	15
0	1	35	37	16	11	11
0	1	32	32	13	10	15
0	0	37	38	15	12	12
0	1	34	31	16	9	14
0	1	33	37	16	12	14
0	0	33	33	14	9	8
0	0	30	30	16	12	9
0	0	24	30	14	10	15
0	0	34	31	11	9	17
0	0	34	32	12	12	13
0	1	33	34	15	8	15
0	1	34	36	15	11	15
0	1	35	37	16	11	14
0	0	35	36	16	12	16
0	0	36	33	11	10	13
0	0	34	33	15	10	16
0	1	34	33	12	12	9
0	0	41	44	12	12	16
0	0	32	39	15	11	11
0	0	30	32	15	8	10
0	1	35	35	16	12	11
0	0	28	25	14	10	15
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0	1	39	34	14	10	14
0	0	36	35	13	8	8
0	1	36	39	15	12	15
0	0	35	33	13	12	11
0	0	38	36	14	10	16
0	1	33	32	15	12	10
0	0	31	32	12	9	15
0	1	32	36	8	6	16
0	0	31	32	14	10	19
0	0	33	34	14	9	12
0	0	34	33	11	9	8
0	0	34	35	12	9	11
0	1	34	30	13	6	14
0	0	33	38	10	10	9
0	0	32	34	16	6	15
0	1	41	33	18	14	13
0	1	34	32	13	10	16
0	0	36	31	11	10	11
0	0	37	30	4	6	12
0	0	36	27	13	12	13
0	1	29	31	16	12	10
0	0	37	30	10	7	11
0	0	27	32	12	8	12
0	0	35	35	12	11	8
0	0	28	28	10	3	12
0	0	35	33	13	6	12
0	0	29	35	12	8	11
0	0	32	35	14	9	13
0	1	36	32	10	9	14
0	1	19	21	12	8	10
0	1	21	20	12	9	12
0	0	31	34	11	7	15
0	0	33	32	10	7	13
0	1	36	34	12	6	13
0	1	33	32	16	9	13
0	0	37	33	12	10	12
0	0	34	33	14	11	12
0	0	35	37	16	12	9
0	1	31	32	14	8	9
0	1	37	34	13	11	15
0	1	35	30	4	3	10
0	1	27	30	15	11	14
0	0	34	38	11	12	15
0	0	40	36	11	7	7
0	0	29	32	14	9	14
0	0	38	34	15	12	8
0	1	34	33	14	8	10
0	0	21	27	13	11	13
0	0	36	32	11	8	13
0	1	38	34	15	10	13
0	0	30	29	11	8	8
0	0	35	35	13	7	12
0	1	30	27	13	8	13
0	1	36	33	16	10	12
0	0	34	38	13	8	10
0	1	35	36	16	12	13
0	0	34	33	16	14	12
0	0	32	39	12	7	9
0	1	33	29	7	6	15
0	0	33	32	16	11	13
0	1	26	34	5	4	13
0	0	35	38	16	9	13
0	0	21	17	4	5	15
0	0	38	35	12	9	15
0	0	35	32	15	11	14
0	1	33	34	14	12	15
0	0	37	36	11	9	11
0	0	38	31	16	12	15
0	1	34	35	15	10	14
0	0	27	29	12	9	13
0	1	16	22	6	6	12
0	0	40	41	16	10	16
0	0	36	36	10	9	16
0	1	42	42	15	13	9
0	1	30	33	14	12	14

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time17 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 17 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105492&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]17 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105492&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105492&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 time17 seconds
R Server'George Udny Yule' @ 72.249.76.132






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 10.5667844818342 + 0.998144277551916Pop[t] + 0.790351801127384Gender[t] + 0.0273029937954519Connected[t] -0.0159940655898807Separate[t] + 0.118947366727600Learning[t] -0.0160951875172021Software[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  10.5667844818342 +  0.998144277551916Pop[t] +  0.790351801127384Gender[t] +  0.0273029937954519Connected[t] -0.0159940655898807Separate[t] +  0.118947366727600Learning[t] -0.0160951875172021Software[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105492&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  10.5667844818342 +  0.998144277551916Pop[t] +  0.790351801127384Gender[t] +  0.0273029937954519Connected[t] -0.0159940655898807Separate[t] +  0.118947366727600Learning[t] -0.0160951875172021Software[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105492&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105492&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 10.5667844818342 + 0.998144277551916Pop[t] + 0.790351801127384Gender[t] + 0.0273029937954519Connected[t] -0.0159940655898807Separate[t] + 0.118947366727600Learning[t] -0.0160951875172021Software[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)10.56678448183421.4280957.399200
Pop0.9981442775519160.3079843.24090.0013350.000667
Gender0.7903518011273840.2886972.73770.0065830.003291
Connected0.02730299379545190.0413030.6610.5091270.254563
Separate-0.01599406558988070.042953-0.37240.7099050.354953
Learning0.1189473667276000.0740591.60610.1093730.054687
Software-0.01609518751720210.079388-0.20270.8394840.419742

\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) & 10.5667844818342 & 1.428095 & 7.3992 & 0 & 0 \tabularnewline
Pop & 0.998144277551916 & 0.307984 & 3.2409 & 0.001335 & 0.000667 \tabularnewline
Gender & 0.790351801127384 & 0.288697 & 2.7377 & 0.006583 & 0.003291 \tabularnewline
Connected & 0.0273029937954519 & 0.041303 & 0.661 & 0.509127 & 0.254563 \tabularnewline
Separate & -0.0159940655898807 & 0.042953 & -0.3724 & 0.709905 & 0.354953 \tabularnewline
Learning & 0.118947366727600 & 0.074059 & 1.6061 & 0.109373 & 0.054687 \tabularnewline
Software & -0.0160951875172021 & 0.079388 & -0.2027 & 0.839484 & 0.419742 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105492&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]10.5667844818342[/C][C]1.428095[/C][C]7.3992[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Pop[/C][C]0.998144277551916[/C][C]0.307984[/C][C]3.2409[/C][C]0.001335[/C][C]0.000667[/C][/ROW]
[ROW][C]Gender[/C][C]0.790351801127384[/C][C]0.288697[/C][C]2.7377[/C][C]0.006583[/C][C]0.003291[/C][/ROW]
[ROW][C]Connected[/C][C]0.0273029937954519[/C][C]0.041303[/C][C]0.661[/C][C]0.509127[/C][C]0.254563[/C][/ROW]
[ROW][C]Separate[/C][C]-0.0159940655898807[/C][C]0.042953[/C][C]-0.3724[/C][C]0.709905[/C][C]0.354953[/C][/ROW]
[ROW][C]Learning[/C][C]0.118947366727600[/C][C]0.074059[/C][C]1.6061[/C][C]0.109373[/C][C]0.054687[/C][/ROW]
[ROW][C]Software[/C][C]-0.0160951875172021[/C][C]0.079388[/C][C]-0.2027[/C][C]0.839484[/C][C]0.419742[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105492&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105492&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)10.56678448183421.4280957.399200
Pop0.9981442775519160.3079843.24090.0013350.000667
Gender0.7903518011273840.2886972.73770.0065830.003291
Connected0.02730299379545190.0413030.6610.5091270.254563
Separate-0.01599406558988070.042953-0.37240.7099050.354953
Learning0.1189473667276000.0740591.60610.1093730.054687
Software-0.01609518751720210.079388-0.20270.8394840.419742






Multiple Linear Regression - Regression Statistics
Multiple R0.341681220105783
R-squared0.116746056172977
Adjusted R-squared0.0978865413581648
F-TEST (value)6.19030008562503
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value4.06812294373449e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.36852463154137
Sum Squared Residuals1576.38440939131

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.341681220105783 \tabularnewline
R-squared & 0.116746056172977 \tabularnewline
Adjusted R-squared & 0.0978865413581648 \tabularnewline
F-TEST (value) & 6.19030008562503 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 281 \tabularnewline
p-value & 4.06812294373449e-06 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.36852463154137 \tabularnewline
Sum Squared Residuals & 1576.38440939131 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105492&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.341681220105783[/C][/ROW]
[ROW][C]R-squared[/C][C]0.116746056172977[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0978865413581648[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]6.19030008562503[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]281[/C][/ROW]
[ROW][C]p-value[/C][C]4.06812294373449e-06[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.36852463154137[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1576.38440939131[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105492&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105492&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 R0.341681220105783
R-squared0.116746056172977
Adjusted R-squared0.0978865413581648
F-TEST (value)6.19030008562503
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value4.06812294373449e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.36852463154137
Sum Squared Residuals1576.38440939131






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.2201023309641-0.220102330964103
21814.63439802461243.3656019753876
31114.6331502337977-3.63315023379767
41213.5711567783899-1.57115677838991
51614.14782761919611.85217238080388
61814.23242133353463.76757866646538
71414.9911390028679-0.991139002867864
81414.2666738639964-0.266673863996394
91514.25051692548400.749483074516018
101514.3970706517890.602929348211001
111713.84883248279663.15116751720337
121914.50440572452914.49559427547094
131013.7526658454027-3.7526658454027
141614.53843363107311.4615663689269
151814.44517635054913.55482364945094
161413.50188864708220.498111352917848
171413.65928506288820.340714937111756
181714.97082491667082.02917508332915
191413.98597656340090.0140234365990846
201614.42718188052701.57281811947298
211813.63693120132704.36306879867305
221114.4158729523214-3.41587295232145
231414.8630853562215-0.863085356221496
241214.4678335778923-2.46783357789231
251713.94689840269543.05310159730460
26914.7757610038965-5.77576100389648
271613.73025023284622.26974976715380
281414.2233768046111-0.223376804611061
291514.43849080873260.561509191267411
301113.4697376429799-2.46973764297986
311614.29692558559381.70307441440615
321313.0889063935808-0.0889063935807798
331714.37398655667342.62601344332664
341514.40181754016850.598182459831482
351413.48552946471510.514470535284903
361612.98762775103023.01237224896984
37912.9055165257892-3.90551652578916
381513.49215325553641.50784674446364
391714.39345733976492.60654266023505
401313.7349353702305-0.734935370230512
411513.80553542341131.19446457658870
421614.22789906907281.77210093092716
431614.22815194653111.77184805346886
441213.4970406367753-1.49704063677531
451514.44927174723850.550728252761545
461113.9209778190966-2.92097781909663
471514.22505146319820.774948536801839
481514.31964456393230.68035543606769
491714.45652464968672.54347535031326
501313.5627533087171-0.562753308717143
511614.29902711195331.70097288804667
521413.46311385215860.536886147841402
531113.1450465468994-2.14504654689935
541214.3697282870614-2.36972828706143
551212.9168648249268-0.916864824926845
561514.37439104438260.625608955617353
571614.58631470591541.41368529408458
581514.31328476796090.6867152320391
591213.6065166068070-1.60651660680697
601214.5092931057680-2.50929310576802
61813.2508868248439-5.25088682484386
621313.7686599109926-0.768659910992583
631114.4016152963139-3.40161529631387
641414.1300971440239-0.130097144023925
651514.49778193370780.502218066292198
661013.7416209120470-3.74162091204698
671114.6941160173600-3.69411601735998
681213.9161843407305-1.91618434073054
691514.01456084546570.985439154534266
701513.63876873283661.36123126716341
711413.08736832951600.912631670483972
721614.08211494725431.91788505274572
731514.57553376740960.424466232590447
741513.86240581028421.13759418971578
751313.7714063949399-0.77140639493994
761214.8175238975541-2.81752389755415
771714.46763133403772.53236866596233
781314.513877121225-1.51387712122500
791513.18677006962491.81322993037510
801313.8533153763263-0.853315376326296
811513.60015681083561.39984318916444
821514.42912053396400.57087946603603
831613.63840361605942.36159638394059
841514.29234157013690.707658429863142
851414.5026693149468-0.502669314946754
861513.49908041213961.50091958786041
871414.4224967431427-0.422496743142708
881314.3452728991407-1.34527289914066
89714.319543442005-7.31954344200499
901713.90839872001323.09160127998675
911314.6070556598848-1.60705565988482
921514.36514427160440.634855728395553
931414.3722107761589-0.372210776158940
941314.0204189301376-1.02041893013762
951614.58651694977011.41348305022994
961214.4996194652174-2.49961946521743
971414.5733704900549-0.57337049005486
981713.74135691719713.25864308280287
991513.36714945861931.63285054138069
1001714.49483320590582.5051667940942
1011213.7414580391245-1.74145803912445
1021614.88392743211821.11607256788178
1031113.5979541625488-2.59795416254876
1041514.35862160271050.641378397289493
105913.4984119295804-4.49841192958045
1061614.66196501325771.33803498674231
1071513.77059856442951.22940143557046
1081013.714155045329-3.714155045329
1091014.1722606270538-4.17226062705379
1101514.34058776175640.659412238243648
1111114.3516944461073-3.35169444610728
1121314.4182778444629-1.41827784446289
1131814.08810962644853.91189037355148
1141613.99514459431492.00485540568511
1151414.0725424286310-0.0725424286310211
1161414.1803213600125-0.180321360012484
1171414.0657557648872-0.0657557648872282
1181414.5270235809402-0.527023580940206
1191213.2434158325801-1.24341583258008
1201414.4637540271638-0.463754027163767
1211514.12219928398780.877800716012237
1221514.43554208093060.564457919069411
1231514.41734536705390.582654632946097
1241314.3355992585901-1.33559925859008
1251713.74119404427463.2588059557254
1261714.77790190118812.22209809881192
1271914.31984680778704.68015319221305
1281514.03340251693030.966597483069707
1291313.6530263888442-0.653026388844156
130912.8300290913694-3.83002909136942
1311514.63001625301000.369983746989962
1321513.07260896220891.92739103779107
1331513.43948592138241.56051407861759
1341614.35621671056911.64378328943094
1351113.3790022224854-2.37900222248544
1361413.54060169101050.459398308989503
1371113.7620472375629-2.76204723756287
1381514.06569401389200.934305986107981
1391313.0150936177481-0.0150936177481430
1401514.45957449941610.540425500583935
1411613.43159195968332.56840804031667
1421414.3952555003425-0.395255500342466
1431513.76956886343031.23043113656969
1441614.01229644618371.98770355381628
1451614.72895175441441.27104824558558
1461113.3252236920391-2.32522369203912
1471213.6528241449895-1.65282414498951
148913.4101825231548-4.41018252315479
1491613.84583312139102.15416687860903
1501314.4851989362873-1.48519893628733
1511613.64375723600292.35624276399714
1521214.4937035278874-2.49370352788742
153914.3854977287336-5.38549772873358
1541313.8211754896156-0.821175489615556
1551414.0869405774980-0.0869405774980255
1561914.31984680778704.68015319221305
1571314.4978830556351-1.49788305563512
1581213.9198087701461-1.91980877014614
1591012.2734835012613-2.27348350126134
1601412.29593848475001.70406151525005
1611612.87326669072373.12673330927626
1621013.2849281397436-3.28492813974364
1631111.8029465323671-0.802946532367067
1641412.34628620272891.65371379727107
1651212.7824412656936-0.782441265693551
166913.0308370968439-4.03083709684392
167912.4222005049211-3.42220050492105
1681112.4280716821249-1.42807168212487
1691613.45827925020752.54172074979250
170912.3928314573611-3.39283145736114
1711312.70693145121070.293068548789283
1721613.12643637360602.87356362639397
1731312.48785142586770.512148574132325
174913.1381497895209-4.13814978952089
1751212.1885640410778-0.188564041077778
1761613.21202431634872.78797568365127
1771113.0853813334396-2.08538133343961
1781413.47427331579740.525726684202615
1791312.25441720587900.745582794120957
1801512.85596308332392.14403691667606
1811412.68355639789281.31644360210717
1821612.26840499355933.7315950064407
1831313.3650613406156-0.365061340615577
1841412.85095220009461.14904779990544
1851513.24083909580881.75916090419125
1861312.07918919297340.920810807026561
1871112.0926390184706-1.09263901847061
1881113.1271666071604-2.12716660716038
1891413.46490304102880.535096958971234
1901513.08211075812961.91788924187036
1911113.4470714439293-2.44707144392925
1921513.10438587782671.89561412217330
1931212.5602890105581-0.560289010558091
1941413.54792321870750.452076781292509
1951413.37637026882110.623629731178851
196812.4603855591497-4.46038555914969
197912.6160679454366-3.61606794543657
1981512.24654562424312.75345437575693
1991712.16283458394214.8371654160579
2001312.21750232252820.782497677471782
2011513.3697858489321.630214151068
2021513.31681514899611.68318485100392
2031413.44707144392930.552928556070745
2041612.65661852087453.34338147912545
2051312.16935725283600.830642747163955
2061612.59054073215553.40945926784446
207912.9918600580657-3.99186005806572
2081612.21669449201783.78330550798219
2091112.4238751635082-1.42387516350815
2101012.5295131975980-2.52951319759802
2111113.4629643875918-2.46296438759181
2121512.43572792737432.56427207262572
2131713.54340095424573.45659904575429
2141413.38246606994270.617533930057294
215812.4074542301459-4.40745423014589
2161513.30734375230011.69265624769986
2171112.3477586174614-1.34775861746139
2181612.53282314384013.46717685615989
2191013.3373932300430-3.33739323004295
2201512.18387890369352.81612109630653
2211612.51005353189803.48994646810201
2221912.40567844963156.59432155036853
2231212.4443914935598-0.444391493559812
224812.1308464527623-4.13084645276234
2251112.2178056883102-1.21780568831018
2261413.25536074666620.744639253333823
227911.8885305767727-2.88853057677268
2281512.70326879577122.29673120422883
2291313.8644748399651-0.864474839965083
2301613.15899186541762.84100813458239
2311112.2013453840158-1.20134538401581
2321211.47639162637670.523608373623256
2331312.47102600479610.528973995203875
2341013.3631226871786-3.36312268717862
2351112.1739806392251-1.17398063922514
2361212.0907621160289-0.0907621160288627
237812.2129183070712-4.21291830707123
2381212.0246225763146-0.0246225763146469
2391212.4443297425646-0.444329742564602
2401112.0973859068501-1.09738590685012
2411312.40109443417450.598905565825521
2421412.87285094034291.12714905965709
2431012.8386246882813-2.83862468828132
2441212.8931295539449-0.893129553944902
2451512.06513378082052.93486621917949
2461312.03278053286360.967219467136424
2471313.1270431051700-0.127043105169957
2481313.5046261593222-0.504626159322158
2491212.3156076133591-0.315607613359097
2501212.4554981779107-0.45549817791074
251912.6406244552847-3.64062445528467
252913.2282206257933-4.22822062579326
2531513.1928175281071.807182471893
2541012.2604230024648-2.26042300246483
2551413.22165858596720.778341414032796
2561512.00259056226132.99740943773867
257712.2788725937998-5.27887259379982
2581412.36716764955781.63283235044223
259812.6515682667131-4.65156826671306
2601013.2941355415897-3.29413554158973
2611312.07757628538150.922423714618452
2621312.21754169346030.78245830653967
2631313.4741104428749-0.474110442874854
264812.1017059274573-4.10170592745726
2651212.3962464238676-0.396246423867639
2661313.1619405932196-0.161940593219607
2671213.5544458876014-1.55444588760143
2681012.3048660457853-2.30486604578534
2691313.4469703220019-0.446970322001933
2701212.6451073488143-0.645107348814335
271912.1314138133942-3.13141381339416
2721512.5303676180952.469632381905
2731312.68208398316040.317916016839630
2741312.05357197515660.94642802484336
2751312.67291595224640.327084047753606
2761511.26356176583523.73643823416484
2771512.3270176634922.67298233650801
2781412.61774260402371.38225739597633
2791513.18645773213561.81354226786441
2801112.1647732373791-1.16477323737906
2811512.81849783021032.18150216978969
2821413.34890440210320.651095597896834
2831312.12264912528130.877350874718697
2841212.0592278159739-0.0592278159738843
2851612.74535353693683.25464646306319
2861612.0185228768563.98147712314400
287913.407084330786-4.40708433078601
2881413.12054281633910.879457183660885

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 14.2201023309641 & -0.220102330964103 \tabularnewline
2 & 18 & 14.6343980246124 & 3.3656019753876 \tabularnewline
3 & 11 & 14.6331502337977 & -3.63315023379767 \tabularnewline
4 & 12 & 13.5711567783899 & -1.57115677838991 \tabularnewline
5 & 16 & 14.1478276191961 & 1.85217238080388 \tabularnewline
6 & 18 & 14.2324213335346 & 3.76757866646538 \tabularnewline
7 & 14 & 14.9911390028679 & -0.991139002867864 \tabularnewline
8 & 14 & 14.2666738639964 & -0.266673863996394 \tabularnewline
9 & 15 & 14.2505169254840 & 0.749483074516018 \tabularnewline
10 & 15 & 14.397070651789 & 0.602929348211001 \tabularnewline
11 & 17 & 13.8488324827966 & 3.15116751720337 \tabularnewline
12 & 19 & 14.5044057245291 & 4.49559427547094 \tabularnewline
13 & 10 & 13.7526658454027 & -3.7526658454027 \tabularnewline
14 & 16 & 14.5384336310731 & 1.4615663689269 \tabularnewline
15 & 18 & 14.4451763505491 & 3.55482364945094 \tabularnewline
16 & 14 & 13.5018886470822 & 0.498111352917848 \tabularnewline
17 & 14 & 13.6592850628882 & 0.340714937111756 \tabularnewline
18 & 17 & 14.9708249166708 & 2.02917508332915 \tabularnewline
19 & 14 & 13.9859765634009 & 0.0140234365990846 \tabularnewline
20 & 16 & 14.4271818805270 & 1.57281811947298 \tabularnewline
21 & 18 & 13.6369312013270 & 4.36306879867305 \tabularnewline
22 & 11 & 14.4158729523214 & -3.41587295232145 \tabularnewline
23 & 14 & 14.8630853562215 & -0.863085356221496 \tabularnewline
24 & 12 & 14.4678335778923 & -2.46783357789231 \tabularnewline
25 & 17 & 13.9468984026954 & 3.05310159730460 \tabularnewline
26 & 9 & 14.7757610038965 & -5.77576100389648 \tabularnewline
27 & 16 & 13.7302502328462 & 2.26974976715380 \tabularnewline
28 & 14 & 14.2233768046111 & -0.223376804611061 \tabularnewline
29 & 15 & 14.4384908087326 & 0.561509191267411 \tabularnewline
30 & 11 & 13.4697376429799 & -2.46973764297986 \tabularnewline
31 & 16 & 14.2969255855938 & 1.70307441440615 \tabularnewline
32 & 13 & 13.0889063935808 & -0.0889063935807798 \tabularnewline
33 & 17 & 14.3739865566734 & 2.62601344332664 \tabularnewline
34 & 15 & 14.4018175401685 & 0.598182459831482 \tabularnewline
35 & 14 & 13.4855294647151 & 0.514470535284903 \tabularnewline
36 & 16 & 12.9876277510302 & 3.01237224896984 \tabularnewline
37 & 9 & 12.9055165257892 & -3.90551652578916 \tabularnewline
38 & 15 & 13.4921532555364 & 1.50784674446364 \tabularnewline
39 & 17 & 14.3934573397649 & 2.60654266023505 \tabularnewline
40 & 13 & 13.7349353702305 & -0.734935370230512 \tabularnewline
41 & 15 & 13.8055354234113 & 1.19446457658870 \tabularnewline
42 & 16 & 14.2278990690728 & 1.77210093092716 \tabularnewline
43 & 16 & 14.2281519465311 & 1.77184805346886 \tabularnewline
44 & 12 & 13.4970406367753 & -1.49704063677531 \tabularnewline
45 & 15 & 14.4492717472385 & 0.550728252761545 \tabularnewline
46 & 11 & 13.9209778190966 & -2.92097781909663 \tabularnewline
47 & 15 & 14.2250514631982 & 0.774948536801839 \tabularnewline
48 & 15 & 14.3196445639323 & 0.68035543606769 \tabularnewline
49 & 17 & 14.4565246496867 & 2.54347535031326 \tabularnewline
50 & 13 & 13.5627533087171 & -0.562753308717143 \tabularnewline
51 & 16 & 14.2990271119533 & 1.70097288804667 \tabularnewline
52 & 14 & 13.4631138521586 & 0.536886147841402 \tabularnewline
53 & 11 & 13.1450465468994 & -2.14504654689935 \tabularnewline
54 & 12 & 14.3697282870614 & -2.36972828706143 \tabularnewline
55 & 12 & 12.9168648249268 & -0.916864824926845 \tabularnewline
56 & 15 & 14.3743910443826 & 0.625608955617353 \tabularnewline
57 & 16 & 14.5863147059154 & 1.41368529408458 \tabularnewline
58 & 15 & 14.3132847679609 & 0.6867152320391 \tabularnewline
59 & 12 & 13.6065166068070 & -1.60651660680697 \tabularnewline
60 & 12 & 14.5092931057680 & -2.50929310576802 \tabularnewline
61 & 8 & 13.2508868248439 & -5.25088682484386 \tabularnewline
62 & 13 & 13.7686599109926 & -0.768659910992583 \tabularnewline
63 & 11 & 14.4016152963139 & -3.40161529631387 \tabularnewline
64 & 14 & 14.1300971440239 & -0.130097144023925 \tabularnewline
65 & 15 & 14.4977819337078 & 0.502218066292198 \tabularnewline
66 & 10 & 13.7416209120470 & -3.74162091204698 \tabularnewline
67 & 11 & 14.6941160173600 & -3.69411601735998 \tabularnewline
68 & 12 & 13.9161843407305 & -1.91618434073054 \tabularnewline
69 & 15 & 14.0145608454657 & 0.985439154534266 \tabularnewline
70 & 15 & 13.6387687328366 & 1.36123126716341 \tabularnewline
71 & 14 & 13.0873683295160 & 0.912631670483972 \tabularnewline
72 & 16 & 14.0821149472543 & 1.91788505274572 \tabularnewline
73 & 15 & 14.5755337674096 & 0.424466232590447 \tabularnewline
74 & 15 & 13.8624058102842 & 1.13759418971578 \tabularnewline
75 & 13 & 13.7714063949399 & -0.77140639493994 \tabularnewline
76 & 12 & 14.8175238975541 & -2.81752389755415 \tabularnewline
77 & 17 & 14.4676313340377 & 2.53236866596233 \tabularnewline
78 & 13 & 14.513877121225 & -1.51387712122500 \tabularnewline
79 & 15 & 13.1867700696249 & 1.81322993037510 \tabularnewline
80 & 13 & 13.8533153763263 & -0.853315376326296 \tabularnewline
81 & 15 & 13.6001568108356 & 1.39984318916444 \tabularnewline
82 & 15 & 14.4291205339640 & 0.57087946603603 \tabularnewline
83 & 16 & 13.6384036160594 & 2.36159638394059 \tabularnewline
84 & 15 & 14.2923415701369 & 0.707658429863142 \tabularnewline
85 & 14 & 14.5026693149468 & -0.502669314946754 \tabularnewline
86 & 15 & 13.4990804121396 & 1.50091958786041 \tabularnewline
87 & 14 & 14.4224967431427 & -0.422496743142708 \tabularnewline
88 & 13 & 14.3452728991407 & -1.34527289914066 \tabularnewline
89 & 7 & 14.319543442005 & -7.31954344200499 \tabularnewline
90 & 17 & 13.9083987200132 & 3.09160127998675 \tabularnewline
91 & 13 & 14.6070556598848 & -1.60705565988482 \tabularnewline
92 & 15 & 14.3651442716044 & 0.634855728395553 \tabularnewline
93 & 14 & 14.3722107761589 & -0.372210776158940 \tabularnewline
94 & 13 & 14.0204189301376 & -1.02041893013762 \tabularnewline
95 & 16 & 14.5865169497701 & 1.41348305022994 \tabularnewline
96 & 12 & 14.4996194652174 & -2.49961946521743 \tabularnewline
97 & 14 & 14.5733704900549 & -0.57337049005486 \tabularnewline
98 & 17 & 13.7413569171971 & 3.25864308280287 \tabularnewline
99 & 15 & 13.3671494586193 & 1.63285054138069 \tabularnewline
100 & 17 & 14.4948332059058 & 2.5051667940942 \tabularnewline
101 & 12 & 13.7414580391245 & -1.74145803912445 \tabularnewline
102 & 16 & 14.8839274321182 & 1.11607256788178 \tabularnewline
103 & 11 & 13.5979541625488 & -2.59795416254876 \tabularnewline
104 & 15 & 14.3586216027105 & 0.641378397289493 \tabularnewline
105 & 9 & 13.4984119295804 & -4.49841192958045 \tabularnewline
106 & 16 & 14.6619650132577 & 1.33803498674231 \tabularnewline
107 & 15 & 13.7705985644295 & 1.22940143557046 \tabularnewline
108 & 10 & 13.714155045329 & -3.714155045329 \tabularnewline
109 & 10 & 14.1722606270538 & -4.17226062705379 \tabularnewline
110 & 15 & 14.3405877617564 & 0.659412238243648 \tabularnewline
111 & 11 & 14.3516944461073 & -3.35169444610728 \tabularnewline
112 & 13 & 14.4182778444629 & -1.41827784446289 \tabularnewline
113 & 18 & 14.0881096264485 & 3.91189037355148 \tabularnewline
114 & 16 & 13.9951445943149 & 2.00485540568511 \tabularnewline
115 & 14 & 14.0725424286310 & -0.0725424286310211 \tabularnewline
116 & 14 & 14.1803213600125 & -0.180321360012484 \tabularnewline
117 & 14 & 14.0657557648872 & -0.0657557648872282 \tabularnewline
118 & 14 & 14.5270235809402 & -0.527023580940206 \tabularnewline
119 & 12 & 13.2434158325801 & -1.24341583258008 \tabularnewline
120 & 14 & 14.4637540271638 & -0.463754027163767 \tabularnewline
121 & 15 & 14.1221992839878 & 0.877800716012237 \tabularnewline
122 & 15 & 14.4355420809306 & 0.564457919069411 \tabularnewline
123 & 15 & 14.4173453670539 & 0.582654632946097 \tabularnewline
124 & 13 & 14.3355992585901 & -1.33559925859008 \tabularnewline
125 & 17 & 13.7411940442746 & 3.2588059557254 \tabularnewline
126 & 17 & 14.7779019011881 & 2.22209809881192 \tabularnewline
127 & 19 & 14.3198468077870 & 4.68015319221305 \tabularnewline
128 & 15 & 14.0334025169303 & 0.966597483069707 \tabularnewline
129 & 13 & 13.6530263888442 & -0.653026388844156 \tabularnewline
130 & 9 & 12.8300290913694 & -3.83002909136942 \tabularnewline
131 & 15 & 14.6300162530100 & 0.369983746989962 \tabularnewline
132 & 15 & 13.0726089622089 & 1.92739103779107 \tabularnewline
133 & 15 & 13.4394859213824 & 1.56051407861759 \tabularnewline
134 & 16 & 14.3562167105691 & 1.64378328943094 \tabularnewline
135 & 11 & 13.3790022224854 & -2.37900222248544 \tabularnewline
136 & 14 & 13.5406016910105 & 0.459398308989503 \tabularnewline
137 & 11 & 13.7620472375629 & -2.76204723756287 \tabularnewline
138 & 15 & 14.0656940138920 & 0.934305986107981 \tabularnewline
139 & 13 & 13.0150936177481 & -0.0150936177481430 \tabularnewline
140 & 15 & 14.4595744994161 & 0.540425500583935 \tabularnewline
141 & 16 & 13.4315919596833 & 2.56840804031667 \tabularnewline
142 & 14 & 14.3952555003425 & -0.395255500342466 \tabularnewline
143 & 15 & 13.7695688634303 & 1.23043113656969 \tabularnewline
144 & 16 & 14.0122964461837 & 1.98770355381628 \tabularnewline
145 & 16 & 14.7289517544144 & 1.27104824558558 \tabularnewline
146 & 11 & 13.3252236920391 & -2.32522369203912 \tabularnewline
147 & 12 & 13.6528241449895 & -1.65282414498951 \tabularnewline
148 & 9 & 13.4101825231548 & -4.41018252315479 \tabularnewline
149 & 16 & 13.8458331213910 & 2.15416687860903 \tabularnewline
150 & 13 & 14.4851989362873 & -1.48519893628733 \tabularnewline
151 & 16 & 13.6437572360029 & 2.35624276399714 \tabularnewline
152 & 12 & 14.4937035278874 & -2.49370352788742 \tabularnewline
153 & 9 & 14.3854977287336 & -5.38549772873358 \tabularnewline
154 & 13 & 13.8211754896156 & -0.821175489615556 \tabularnewline
155 & 14 & 14.0869405774980 & -0.0869405774980255 \tabularnewline
156 & 19 & 14.3198468077870 & 4.68015319221305 \tabularnewline
157 & 13 & 14.4978830556351 & -1.49788305563512 \tabularnewline
158 & 12 & 13.9198087701461 & -1.91980877014614 \tabularnewline
159 & 10 & 12.2734835012613 & -2.27348350126134 \tabularnewline
160 & 14 & 12.2959384847500 & 1.70406151525005 \tabularnewline
161 & 16 & 12.8732666907237 & 3.12673330927626 \tabularnewline
162 & 10 & 13.2849281397436 & -3.28492813974364 \tabularnewline
163 & 11 & 11.8029465323671 & -0.802946532367067 \tabularnewline
164 & 14 & 12.3462862027289 & 1.65371379727107 \tabularnewline
165 & 12 & 12.7824412656936 & -0.782441265693551 \tabularnewline
166 & 9 & 13.0308370968439 & -4.03083709684392 \tabularnewline
167 & 9 & 12.4222005049211 & -3.42220050492105 \tabularnewline
168 & 11 & 12.4280716821249 & -1.42807168212487 \tabularnewline
169 & 16 & 13.4582792502075 & 2.54172074979250 \tabularnewline
170 & 9 & 12.3928314573611 & -3.39283145736114 \tabularnewline
171 & 13 & 12.7069314512107 & 0.293068548789283 \tabularnewline
172 & 16 & 13.1264363736060 & 2.87356362639397 \tabularnewline
173 & 13 & 12.4878514258677 & 0.512148574132325 \tabularnewline
174 & 9 & 13.1381497895209 & -4.13814978952089 \tabularnewline
175 & 12 & 12.1885640410778 & -0.188564041077778 \tabularnewline
176 & 16 & 13.2120243163487 & 2.78797568365127 \tabularnewline
177 & 11 & 13.0853813334396 & -2.08538133343961 \tabularnewline
178 & 14 & 13.4742733157974 & 0.525726684202615 \tabularnewline
179 & 13 & 12.2544172058790 & 0.745582794120957 \tabularnewline
180 & 15 & 12.8559630833239 & 2.14403691667606 \tabularnewline
181 & 14 & 12.6835563978928 & 1.31644360210717 \tabularnewline
182 & 16 & 12.2684049935593 & 3.7315950064407 \tabularnewline
183 & 13 & 13.3650613406156 & -0.365061340615577 \tabularnewline
184 & 14 & 12.8509522000946 & 1.14904779990544 \tabularnewline
185 & 15 & 13.2408390958088 & 1.75916090419125 \tabularnewline
186 & 13 & 12.0791891929734 & 0.920810807026561 \tabularnewline
187 & 11 & 12.0926390184706 & -1.09263901847061 \tabularnewline
188 & 11 & 13.1271666071604 & -2.12716660716038 \tabularnewline
189 & 14 & 13.4649030410288 & 0.535096958971234 \tabularnewline
190 & 15 & 13.0821107581296 & 1.91788924187036 \tabularnewline
191 & 11 & 13.4470714439293 & -2.44707144392925 \tabularnewline
192 & 15 & 13.1043858778267 & 1.89561412217330 \tabularnewline
193 & 12 & 12.5602890105581 & -0.560289010558091 \tabularnewline
194 & 14 & 13.5479232187075 & 0.452076781292509 \tabularnewline
195 & 14 & 13.3763702688211 & 0.623629731178851 \tabularnewline
196 & 8 & 12.4603855591497 & -4.46038555914969 \tabularnewline
197 & 9 & 12.6160679454366 & -3.61606794543657 \tabularnewline
198 & 15 & 12.2465456242431 & 2.75345437575693 \tabularnewline
199 & 17 & 12.1628345839421 & 4.8371654160579 \tabularnewline
200 & 13 & 12.2175023225282 & 0.782497677471782 \tabularnewline
201 & 15 & 13.369785848932 & 1.630214151068 \tabularnewline
202 & 15 & 13.3168151489961 & 1.68318485100392 \tabularnewline
203 & 14 & 13.4470714439293 & 0.552928556070745 \tabularnewline
204 & 16 & 12.6566185208745 & 3.34338147912545 \tabularnewline
205 & 13 & 12.1693572528360 & 0.830642747163955 \tabularnewline
206 & 16 & 12.5905407321555 & 3.40945926784446 \tabularnewline
207 & 9 & 12.9918600580657 & -3.99186005806572 \tabularnewline
208 & 16 & 12.2166944920178 & 3.78330550798219 \tabularnewline
209 & 11 & 12.4238751635082 & -1.42387516350815 \tabularnewline
210 & 10 & 12.5295131975980 & -2.52951319759802 \tabularnewline
211 & 11 & 13.4629643875918 & -2.46296438759181 \tabularnewline
212 & 15 & 12.4357279273743 & 2.56427207262572 \tabularnewline
213 & 17 & 13.5434009542457 & 3.45659904575429 \tabularnewline
214 & 14 & 13.3824660699427 & 0.617533930057294 \tabularnewline
215 & 8 & 12.4074542301459 & -4.40745423014589 \tabularnewline
216 & 15 & 13.3073437523001 & 1.69265624769986 \tabularnewline
217 & 11 & 12.3477586174614 & -1.34775861746139 \tabularnewline
218 & 16 & 12.5328231438401 & 3.46717685615989 \tabularnewline
219 & 10 & 13.3373932300430 & -3.33739323004295 \tabularnewline
220 & 15 & 12.1838789036935 & 2.81612109630653 \tabularnewline
221 & 16 & 12.5100535318980 & 3.48994646810201 \tabularnewline
222 & 19 & 12.4056784496315 & 6.59432155036853 \tabularnewline
223 & 12 & 12.4443914935598 & -0.444391493559812 \tabularnewline
224 & 8 & 12.1308464527623 & -4.13084645276234 \tabularnewline
225 & 11 & 12.2178056883102 & -1.21780568831018 \tabularnewline
226 & 14 & 13.2553607466662 & 0.744639253333823 \tabularnewline
227 & 9 & 11.8885305767727 & -2.88853057677268 \tabularnewline
228 & 15 & 12.7032687957712 & 2.29673120422883 \tabularnewline
229 & 13 & 13.8644748399651 & -0.864474839965083 \tabularnewline
230 & 16 & 13.1589918654176 & 2.84100813458239 \tabularnewline
231 & 11 & 12.2013453840158 & -1.20134538401581 \tabularnewline
232 & 12 & 11.4763916263767 & 0.523608373623256 \tabularnewline
233 & 13 & 12.4710260047961 & 0.528973995203875 \tabularnewline
234 & 10 & 13.3631226871786 & -3.36312268717862 \tabularnewline
235 & 11 & 12.1739806392251 & -1.17398063922514 \tabularnewline
236 & 12 & 12.0907621160289 & -0.0907621160288627 \tabularnewline
237 & 8 & 12.2129183070712 & -4.21291830707123 \tabularnewline
238 & 12 & 12.0246225763146 & -0.0246225763146469 \tabularnewline
239 & 12 & 12.4443297425646 & -0.444329742564602 \tabularnewline
240 & 11 & 12.0973859068501 & -1.09738590685012 \tabularnewline
241 & 13 & 12.4010944341745 & 0.598905565825521 \tabularnewline
242 & 14 & 12.8728509403429 & 1.12714905965709 \tabularnewline
243 & 10 & 12.8386246882813 & -2.83862468828132 \tabularnewline
244 & 12 & 12.8931295539449 & -0.893129553944902 \tabularnewline
245 & 15 & 12.0651337808205 & 2.93486621917949 \tabularnewline
246 & 13 & 12.0327805328636 & 0.967219467136424 \tabularnewline
247 & 13 & 13.1270431051700 & -0.127043105169957 \tabularnewline
248 & 13 & 13.5046261593222 & -0.504626159322158 \tabularnewline
249 & 12 & 12.3156076133591 & -0.315607613359097 \tabularnewline
250 & 12 & 12.4554981779107 & -0.45549817791074 \tabularnewline
251 & 9 & 12.6406244552847 & -3.64062445528467 \tabularnewline
252 & 9 & 13.2282206257933 & -4.22822062579326 \tabularnewline
253 & 15 & 13.192817528107 & 1.807182471893 \tabularnewline
254 & 10 & 12.2604230024648 & -2.26042300246483 \tabularnewline
255 & 14 & 13.2216585859672 & 0.778341414032796 \tabularnewline
256 & 15 & 12.0025905622613 & 2.99740943773867 \tabularnewline
257 & 7 & 12.2788725937998 & -5.27887259379982 \tabularnewline
258 & 14 & 12.3671676495578 & 1.63283235044223 \tabularnewline
259 & 8 & 12.6515682667131 & -4.65156826671306 \tabularnewline
260 & 10 & 13.2941355415897 & -3.29413554158973 \tabularnewline
261 & 13 & 12.0775762853815 & 0.922423714618452 \tabularnewline
262 & 13 & 12.2175416934603 & 0.78245830653967 \tabularnewline
263 & 13 & 13.4741104428749 & -0.474110442874854 \tabularnewline
264 & 8 & 12.1017059274573 & -4.10170592745726 \tabularnewline
265 & 12 & 12.3962464238676 & -0.396246423867639 \tabularnewline
266 & 13 & 13.1619405932196 & -0.161940593219607 \tabularnewline
267 & 12 & 13.5544458876014 & -1.55444588760143 \tabularnewline
268 & 10 & 12.3048660457853 & -2.30486604578534 \tabularnewline
269 & 13 & 13.4469703220019 & -0.446970322001933 \tabularnewline
270 & 12 & 12.6451073488143 & -0.645107348814335 \tabularnewline
271 & 9 & 12.1314138133942 & -3.13141381339416 \tabularnewline
272 & 15 & 12.530367618095 & 2.469632381905 \tabularnewline
273 & 13 & 12.6820839831604 & 0.317916016839630 \tabularnewline
274 & 13 & 12.0535719751566 & 0.94642802484336 \tabularnewline
275 & 13 & 12.6729159522464 & 0.327084047753606 \tabularnewline
276 & 15 & 11.2635617658352 & 3.73643823416484 \tabularnewline
277 & 15 & 12.327017663492 & 2.67298233650801 \tabularnewline
278 & 14 & 12.6177426040237 & 1.38225739597633 \tabularnewline
279 & 15 & 13.1864577321356 & 1.81354226786441 \tabularnewline
280 & 11 & 12.1647732373791 & -1.16477323737906 \tabularnewline
281 & 15 & 12.8184978302103 & 2.18150216978969 \tabularnewline
282 & 14 & 13.3489044021032 & 0.651095597896834 \tabularnewline
283 & 13 & 12.1226491252813 & 0.877350874718697 \tabularnewline
284 & 12 & 12.0592278159739 & -0.0592278159738843 \tabularnewline
285 & 16 & 12.7453535369368 & 3.25464646306319 \tabularnewline
286 & 16 & 12.018522876856 & 3.98147712314400 \tabularnewline
287 & 9 & 13.407084330786 & -4.40708433078601 \tabularnewline
288 & 14 & 13.1205428163391 & 0.879457183660885 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105492&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]14[/C][C]14.2201023309641[/C][C]-0.220102330964103[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]14.6343980246124[/C][C]3.3656019753876[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]14.6331502337977[/C][C]-3.63315023379767[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]13.5711567783899[/C][C]-1.57115677838991[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]14.1478276191961[/C][C]1.85217238080388[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.2324213335346[/C][C]3.76757866646538[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]14.9911390028679[/C][C]-0.991139002867864[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]14.2666738639964[/C][C]-0.266673863996394[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]14.2505169254840[/C][C]0.749483074516018[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.397070651789[/C][C]0.602929348211001[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]13.8488324827966[/C][C]3.15116751720337[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]14.5044057245291[/C][C]4.49559427547094[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.7526658454027[/C][C]-3.7526658454027[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]14.5384336310731[/C][C]1.4615663689269[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]14.4451763505491[/C][C]3.55482364945094[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.5018886470822[/C][C]0.498111352917848[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.6592850628882[/C][C]0.340714937111756[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]14.9708249166708[/C][C]2.02917508332915[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]13.9859765634009[/C][C]0.0140234365990846[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]14.4271818805270[/C][C]1.57281811947298[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]13.6369312013270[/C][C]4.36306879867305[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]14.4158729523214[/C][C]-3.41587295232145[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.8630853562215[/C][C]-0.863085356221496[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]14.4678335778923[/C][C]-2.46783357789231[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]13.9468984026954[/C][C]3.05310159730460[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]14.7757610038965[/C][C]-5.77576100389648[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]13.7302502328462[/C][C]2.26974976715380[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]14.2233768046111[/C][C]-0.223376804611061[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]14.4384908087326[/C][C]0.561509191267411[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]13.4697376429799[/C][C]-2.46973764297986[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]14.2969255855938[/C][C]1.70307441440615[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]13.0889063935808[/C][C]-0.0889063935807798[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]14.3739865566734[/C][C]2.62601344332664[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]14.4018175401685[/C][C]0.598182459831482[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]13.4855294647151[/C][C]0.514470535284903[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]12.9876277510302[/C][C]3.01237224896984[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]12.9055165257892[/C][C]-3.90551652578916[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]13.4921532555364[/C][C]1.50784674446364[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]14.3934573397649[/C][C]2.60654266023505[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]13.7349353702305[/C][C]-0.734935370230512[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]13.8055354234113[/C][C]1.19446457658870[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]14.2278990690728[/C][C]1.77210093092716[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]14.2281519465311[/C][C]1.77184805346886[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.4970406367753[/C][C]-1.49704063677531[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.4492717472385[/C][C]0.550728252761545[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.9209778190966[/C][C]-2.92097781909663[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]14.2250514631982[/C][C]0.774948536801839[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.3196445639323[/C][C]0.68035543606769[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]14.4565246496867[/C][C]2.54347535031326[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]13.5627533087171[/C][C]-0.562753308717143[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]14.2990271119533[/C][C]1.70097288804667[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.4631138521586[/C][C]0.536886147841402[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]13.1450465468994[/C][C]-2.14504654689935[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]14.3697282870614[/C][C]-2.36972828706143[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]12.9168648249268[/C][C]-0.916864824926845[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]14.3743910443826[/C][C]0.625608955617353[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.5863147059154[/C][C]1.41368529408458[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]14.3132847679609[/C][C]0.6867152320391[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]13.6065166068070[/C][C]-1.60651660680697[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]14.5092931057680[/C][C]-2.50929310576802[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]13.2508868248439[/C][C]-5.25088682484386[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]13.7686599109926[/C][C]-0.768659910992583[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.4016152963139[/C][C]-3.40161529631387[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.1300971440239[/C][C]-0.130097144023925[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]14.4977819337078[/C][C]0.502218066292198[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]13.7416209120470[/C][C]-3.74162091204698[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]14.6941160173600[/C][C]-3.69411601735998[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]13.9161843407305[/C][C]-1.91618434073054[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]14.0145608454657[/C][C]0.985439154534266[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.6387687328366[/C][C]1.36123126716341[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.0873683295160[/C][C]0.912631670483972[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]14.0821149472543[/C][C]1.91788505274572[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.5755337674096[/C][C]0.424466232590447[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]13.8624058102842[/C][C]1.13759418971578[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]13.7714063949399[/C][C]-0.77140639493994[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]14.8175238975541[/C][C]-2.81752389755415[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]14.4676313340377[/C][C]2.53236866596233[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]14.513877121225[/C][C]-1.51387712122500[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.1867700696249[/C][C]1.81322993037510[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]13.8533153763263[/C][C]-0.853315376326296[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]13.6001568108356[/C][C]1.39984318916444[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]14.4291205339640[/C][C]0.57087946603603[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]13.6384036160594[/C][C]2.36159638394059[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.2923415701369[/C][C]0.707658429863142[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.5026693149468[/C][C]-0.502669314946754[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.4990804121396[/C][C]1.50091958786041[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.4224967431427[/C][C]-0.422496743142708[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]14.3452728991407[/C][C]-1.34527289914066[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]14.319543442005[/C][C]-7.31954344200499[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.9083987200132[/C][C]3.09160127998675[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]14.6070556598848[/C][C]-1.60705565988482[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.3651442716044[/C][C]0.634855728395553[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]14.3722107761589[/C][C]-0.372210776158940[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.0204189301376[/C][C]-1.02041893013762[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.5865169497701[/C][C]1.41348305022994[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]14.4996194652174[/C][C]-2.49961946521743[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.5733704900549[/C][C]-0.57337049005486[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]13.7413569171971[/C][C]3.25864308280287[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]13.3671494586193[/C][C]1.63285054138069[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]14.4948332059058[/C][C]2.5051667940942[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]13.7414580391245[/C][C]-1.74145803912445[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]14.8839274321182[/C][C]1.11607256788178[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]13.5979541625488[/C][C]-2.59795416254876[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]14.3586216027105[/C][C]0.641378397289493[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]13.4984119295804[/C][C]-4.49841192958045[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.6619650132577[/C][C]1.33803498674231[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]13.7705985644295[/C][C]1.22940143557046[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]13.714155045329[/C][C]-3.714155045329[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]14.1722606270538[/C][C]-4.17226062705379[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]14.3405877617564[/C][C]0.659412238243648[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]14.3516944461073[/C][C]-3.35169444610728[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]14.4182778444629[/C][C]-1.41827784446289[/C][/ROW]
[ROW][C]113[/C][C]18[/C][C]14.0881096264485[/C][C]3.91189037355148[/C][/ROW]
[ROW][C]114[/C][C]16[/C][C]13.9951445943149[/C][C]2.00485540568511[/C][/ROW]
[ROW][C]115[/C][C]14[/C][C]14.0725424286310[/C][C]-0.0725424286310211[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]14.1803213600125[/C][C]-0.180321360012484[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]14.0657557648872[/C][C]-0.0657557648872282[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]14.5270235809402[/C][C]-0.527023580940206[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]13.2434158325801[/C][C]-1.24341583258008[/C][/ROW]
[ROW][C]120[/C][C]14[/C][C]14.4637540271638[/C][C]-0.463754027163767[/C][/ROW]
[ROW][C]121[/C][C]15[/C][C]14.1221992839878[/C][C]0.877800716012237[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.4355420809306[/C][C]0.564457919069411[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]14.4173453670539[/C][C]0.582654632946097[/C][/ROW]
[ROW][C]124[/C][C]13[/C][C]14.3355992585901[/C][C]-1.33559925859008[/C][/ROW]
[ROW][C]125[/C][C]17[/C][C]13.7411940442746[/C][C]3.2588059557254[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]14.7779019011881[/C][C]2.22209809881192[/C][/ROW]
[ROW][C]127[/C][C]19[/C][C]14.3198468077870[/C][C]4.68015319221305[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]14.0334025169303[/C][C]0.966597483069707[/C][/ROW]
[ROW][C]129[/C][C]13[/C][C]13.6530263888442[/C][C]-0.653026388844156[/C][/ROW]
[ROW][C]130[/C][C]9[/C][C]12.8300290913694[/C][C]-3.83002909136942[/C][/ROW]
[ROW][C]131[/C][C]15[/C][C]14.6300162530100[/C][C]0.369983746989962[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]13.0726089622089[/C][C]1.92739103779107[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]13.4394859213824[/C][C]1.56051407861759[/C][/ROW]
[ROW][C]134[/C][C]16[/C][C]14.3562167105691[/C][C]1.64378328943094[/C][/ROW]
[ROW][C]135[/C][C]11[/C][C]13.3790022224854[/C][C]-2.37900222248544[/C][/ROW]
[ROW][C]136[/C][C]14[/C][C]13.5406016910105[/C][C]0.459398308989503[/C][/ROW]
[ROW][C]137[/C][C]11[/C][C]13.7620472375629[/C][C]-2.76204723756287[/C][/ROW]
[ROW][C]138[/C][C]15[/C][C]14.0656940138920[/C][C]0.934305986107981[/C][/ROW]
[ROW][C]139[/C][C]13[/C][C]13.0150936177481[/C][C]-0.0150936177481430[/C][/ROW]
[ROW][C]140[/C][C]15[/C][C]14.4595744994161[/C][C]0.540425500583935[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]13.4315919596833[/C][C]2.56840804031667[/C][/ROW]
[ROW][C]142[/C][C]14[/C][C]14.3952555003425[/C][C]-0.395255500342466[/C][/ROW]
[ROW][C]143[/C][C]15[/C][C]13.7695688634303[/C][C]1.23043113656969[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.0122964461837[/C][C]1.98770355381628[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.7289517544144[/C][C]1.27104824558558[/C][/ROW]
[ROW][C]146[/C][C]11[/C][C]13.3252236920391[/C][C]-2.32522369203912[/C][/ROW]
[ROW][C]147[/C][C]12[/C][C]13.6528241449895[/C][C]-1.65282414498951[/C][/ROW]
[ROW][C]148[/C][C]9[/C][C]13.4101825231548[/C][C]-4.41018252315479[/C][/ROW]
[ROW][C]149[/C][C]16[/C][C]13.8458331213910[/C][C]2.15416687860903[/C][/ROW]
[ROW][C]150[/C][C]13[/C][C]14.4851989362873[/C][C]-1.48519893628733[/C][/ROW]
[ROW][C]151[/C][C]16[/C][C]13.6437572360029[/C][C]2.35624276399714[/C][/ROW]
[ROW][C]152[/C][C]12[/C][C]14.4937035278874[/C][C]-2.49370352788742[/C][/ROW]
[ROW][C]153[/C][C]9[/C][C]14.3854977287336[/C][C]-5.38549772873358[/C][/ROW]
[ROW][C]154[/C][C]13[/C][C]13.8211754896156[/C][C]-0.821175489615556[/C][/ROW]
[ROW][C]155[/C][C]14[/C][C]14.0869405774980[/C][C]-0.0869405774980255[/C][/ROW]
[ROW][C]156[/C][C]19[/C][C]14.3198468077870[/C][C]4.68015319221305[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]14.4978830556351[/C][C]-1.49788305563512[/C][/ROW]
[ROW][C]158[/C][C]12[/C][C]13.9198087701461[/C][C]-1.91980877014614[/C][/ROW]
[ROW][C]159[/C][C]10[/C][C]12.2734835012613[/C][C]-2.27348350126134[/C][/ROW]
[ROW][C]160[/C][C]14[/C][C]12.2959384847500[/C][C]1.70406151525005[/C][/ROW]
[ROW][C]161[/C][C]16[/C][C]12.8732666907237[/C][C]3.12673330927626[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]13.2849281397436[/C][C]-3.28492813974364[/C][/ROW]
[ROW][C]163[/C][C]11[/C][C]11.8029465323671[/C][C]-0.802946532367067[/C][/ROW]
[ROW][C]164[/C][C]14[/C][C]12.3462862027289[/C][C]1.65371379727107[/C][/ROW]
[ROW][C]165[/C][C]12[/C][C]12.7824412656936[/C][C]-0.782441265693551[/C][/ROW]
[ROW][C]166[/C][C]9[/C][C]13.0308370968439[/C][C]-4.03083709684392[/C][/ROW]
[ROW][C]167[/C][C]9[/C][C]12.4222005049211[/C][C]-3.42220050492105[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]12.4280716821249[/C][C]-1.42807168212487[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]13.4582792502075[/C][C]2.54172074979250[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]12.3928314573611[/C][C]-3.39283145736114[/C][/ROW]
[ROW][C]171[/C][C]13[/C][C]12.7069314512107[/C][C]0.293068548789283[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]13.1264363736060[/C][C]2.87356362639397[/C][/ROW]
[ROW][C]173[/C][C]13[/C][C]12.4878514258677[/C][C]0.512148574132325[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]13.1381497895209[/C][C]-4.13814978952089[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]12.1885640410778[/C][C]-0.188564041077778[/C][/ROW]
[ROW][C]176[/C][C]16[/C][C]13.2120243163487[/C][C]2.78797568365127[/C][/ROW]
[ROW][C]177[/C][C]11[/C][C]13.0853813334396[/C][C]-2.08538133343961[/C][/ROW]
[ROW][C]178[/C][C]14[/C][C]13.4742733157974[/C][C]0.525726684202615[/C][/ROW]
[ROW][C]179[/C][C]13[/C][C]12.2544172058790[/C][C]0.745582794120957[/C][/ROW]
[ROW][C]180[/C][C]15[/C][C]12.8559630833239[/C][C]2.14403691667606[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]12.6835563978928[/C][C]1.31644360210717[/C][/ROW]
[ROW][C]182[/C][C]16[/C][C]12.2684049935593[/C][C]3.7315950064407[/C][/ROW]
[ROW][C]183[/C][C]13[/C][C]13.3650613406156[/C][C]-0.365061340615577[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]12.8509522000946[/C][C]1.14904779990544[/C][/ROW]
[ROW][C]185[/C][C]15[/C][C]13.2408390958088[/C][C]1.75916090419125[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]12.0791891929734[/C][C]0.920810807026561[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]12.0926390184706[/C][C]-1.09263901847061[/C][/ROW]
[ROW][C]188[/C][C]11[/C][C]13.1271666071604[/C][C]-2.12716660716038[/C][/ROW]
[ROW][C]189[/C][C]14[/C][C]13.4649030410288[/C][C]0.535096958971234[/C][/ROW]
[ROW][C]190[/C][C]15[/C][C]13.0821107581296[/C][C]1.91788924187036[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]13.4470714439293[/C][C]-2.44707144392925[/C][/ROW]
[ROW][C]192[/C][C]15[/C][C]13.1043858778267[/C][C]1.89561412217330[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]12.5602890105581[/C][C]-0.560289010558091[/C][/ROW]
[ROW][C]194[/C][C]14[/C][C]13.5479232187075[/C][C]0.452076781292509[/C][/ROW]
[ROW][C]195[/C][C]14[/C][C]13.3763702688211[/C][C]0.623629731178851[/C][/ROW]
[ROW][C]196[/C][C]8[/C][C]12.4603855591497[/C][C]-4.46038555914969[/C][/ROW]
[ROW][C]197[/C][C]9[/C][C]12.6160679454366[/C][C]-3.61606794543657[/C][/ROW]
[ROW][C]198[/C][C]15[/C][C]12.2465456242431[/C][C]2.75345437575693[/C][/ROW]
[ROW][C]199[/C][C]17[/C][C]12.1628345839421[/C][C]4.8371654160579[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]12.2175023225282[/C][C]0.782497677471782[/C][/ROW]
[ROW][C]201[/C][C]15[/C][C]13.369785848932[/C][C]1.630214151068[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.3168151489961[/C][C]1.68318485100392[/C][/ROW]
[ROW][C]203[/C][C]14[/C][C]13.4470714439293[/C][C]0.552928556070745[/C][/ROW]
[ROW][C]204[/C][C]16[/C][C]12.6566185208745[/C][C]3.34338147912545[/C][/ROW]
[ROW][C]205[/C][C]13[/C][C]12.1693572528360[/C][C]0.830642747163955[/C][/ROW]
[ROW][C]206[/C][C]16[/C][C]12.5905407321555[/C][C]3.40945926784446[/C][/ROW]
[ROW][C]207[/C][C]9[/C][C]12.9918600580657[/C][C]-3.99186005806572[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.2166944920178[/C][C]3.78330550798219[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]12.4238751635082[/C][C]-1.42387516350815[/C][/ROW]
[ROW][C]210[/C][C]10[/C][C]12.5295131975980[/C][C]-2.52951319759802[/C][/ROW]
[ROW][C]211[/C][C]11[/C][C]13.4629643875918[/C][C]-2.46296438759181[/C][/ROW]
[ROW][C]212[/C][C]15[/C][C]12.4357279273743[/C][C]2.56427207262572[/C][/ROW]
[ROW][C]213[/C][C]17[/C][C]13.5434009542457[/C][C]3.45659904575429[/C][/ROW]
[ROW][C]214[/C][C]14[/C][C]13.3824660699427[/C][C]0.617533930057294[/C][/ROW]
[ROW][C]215[/C][C]8[/C][C]12.4074542301459[/C][C]-4.40745423014589[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.3073437523001[/C][C]1.69265624769986[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]12.3477586174614[/C][C]-1.34775861746139[/C][/ROW]
[ROW][C]218[/C][C]16[/C][C]12.5328231438401[/C][C]3.46717685615989[/C][/ROW]
[ROW][C]219[/C][C]10[/C][C]13.3373932300430[/C][C]-3.33739323004295[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]12.1838789036935[/C][C]2.81612109630653[/C][/ROW]
[ROW][C]221[/C][C]16[/C][C]12.5100535318980[/C][C]3.48994646810201[/C][/ROW]
[ROW][C]222[/C][C]19[/C][C]12.4056784496315[/C][C]6.59432155036853[/C][/ROW]
[ROW][C]223[/C][C]12[/C][C]12.4443914935598[/C][C]-0.444391493559812[/C][/ROW]
[ROW][C]224[/C][C]8[/C][C]12.1308464527623[/C][C]-4.13084645276234[/C][/ROW]
[ROW][C]225[/C][C]11[/C][C]12.2178056883102[/C][C]-1.21780568831018[/C][/ROW]
[ROW][C]226[/C][C]14[/C][C]13.2553607466662[/C][C]0.744639253333823[/C][/ROW]
[ROW][C]227[/C][C]9[/C][C]11.8885305767727[/C][C]-2.88853057677268[/C][/ROW]
[ROW][C]228[/C][C]15[/C][C]12.7032687957712[/C][C]2.29673120422883[/C][/ROW]
[ROW][C]229[/C][C]13[/C][C]13.8644748399651[/C][C]-0.864474839965083[/C][/ROW]
[ROW][C]230[/C][C]16[/C][C]13.1589918654176[/C][C]2.84100813458239[/C][/ROW]
[ROW][C]231[/C][C]11[/C][C]12.2013453840158[/C][C]-1.20134538401581[/C][/ROW]
[ROW][C]232[/C][C]12[/C][C]11.4763916263767[/C][C]0.523608373623256[/C][/ROW]
[ROW][C]233[/C][C]13[/C][C]12.4710260047961[/C][C]0.528973995203875[/C][/ROW]
[ROW][C]234[/C][C]10[/C][C]13.3631226871786[/C][C]-3.36312268717862[/C][/ROW]
[ROW][C]235[/C][C]11[/C][C]12.1739806392251[/C][C]-1.17398063922514[/C][/ROW]
[ROW][C]236[/C][C]12[/C][C]12.0907621160289[/C][C]-0.0907621160288627[/C][/ROW]
[ROW][C]237[/C][C]8[/C][C]12.2129183070712[/C][C]-4.21291830707123[/C][/ROW]
[ROW][C]238[/C][C]12[/C][C]12.0246225763146[/C][C]-0.0246225763146469[/C][/ROW]
[ROW][C]239[/C][C]12[/C][C]12.4443297425646[/C][C]-0.444329742564602[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]12.0973859068501[/C][C]-1.09738590685012[/C][/ROW]
[ROW][C]241[/C][C]13[/C][C]12.4010944341745[/C][C]0.598905565825521[/C][/ROW]
[ROW][C]242[/C][C]14[/C][C]12.8728509403429[/C][C]1.12714905965709[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]12.8386246882813[/C][C]-2.83862468828132[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.8931295539449[/C][C]-0.893129553944902[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]12.0651337808205[/C][C]2.93486621917949[/C][/ROW]
[ROW][C]246[/C][C]13[/C][C]12.0327805328636[/C][C]0.967219467136424[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]13.1270431051700[/C][C]-0.127043105169957[/C][/ROW]
[ROW][C]248[/C][C]13[/C][C]13.5046261593222[/C][C]-0.504626159322158[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]12.3156076133591[/C][C]-0.315607613359097[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]12.4554981779107[/C][C]-0.45549817791074[/C][/ROW]
[ROW][C]251[/C][C]9[/C][C]12.6406244552847[/C][C]-3.64062445528467[/C][/ROW]
[ROW][C]252[/C][C]9[/C][C]13.2282206257933[/C][C]-4.22822062579326[/C][/ROW]
[ROW][C]253[/C][C]15[/C][C]13.192817528107[/C][C]1.807182471893[/C][/ROW]
[ROW][C]254[/C][C]10[/C][C]12.2604230024648[/C][C]-2.26042300246483[/C][/ROW]
[ROW][C]255[/C][C]14[/C][C]13.2216585859672[/C][C]0.778341414032796[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]12.0025905622613[/C][C]2.99740943773867[/C][/ROW]
[ROW][C]257[/C][C]7[/C][C]12.2788725937998[/C][C]-5.27887259379982[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]12.3671676495578[/C][C]1.63283235044223[/C][/ROW]
[ROW][C]259[/C][C]8[/C][C]12.6515682667131[/C][C]-4.65156826671306[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]13.2941355415897[/C][C]-3.29413554158973[/C][/ROW]
[ROW][C]261[/C][C]13[/C][C]12.0775762853815[/C][C]0.922423714618452[/C][/ROW]
[ROW][C]262[/C][C]13[/C][C]12.2175416934603[/C][C]0.78245830653967[/C][/ROW]
[ROW][C]263[/C][C]13[/C][C]13.4741104428749[/C][C]-0.474110442874854[/C][/ROW]
[ROW][C]264[/C][C]8[/C][C]12.1017059274573[/C][C]-4.10170592745726[/C][/ROW]
[ROW][C]265[/C][C]12[/C][C]12.3962464238676[/C][C]-0.396246423867639[/C][/ROW]
[ROW][C]266[/C][C]13[/C][C]13.1619405932196[/C][C]-0.161940593219607[/C][/ROW]
[ROW][C]267[/C][C]12[/C][C]13.5544458876014[/C][C]-1.55444588760143[/C][/ROW]
[ROW][C]268[/C][C]10[/C][C]12.3048660457853[/C][C]-2.30486604578534[/C][/ROW]
[ROW][C]269[/C][C]13[/C][C]13.4469703220019[/C][C]-0.446970322001933[/C][/ROW]
[ROW][C]270[/C][C]12[/C][C]12.6451073488143[/C][C]-0.645107348814335[/C][/ROW]
[ROW][C]271[/C][C]9[/C][C]12.1314138133942[/C][C]-3.13141381339416[/C][/ROW]
[ROW][C]272[/C][C]15[/C][C]12.530367618095[/C][C]2.469632381905[/C][/ROW]
[ROW][C]273[/C][C]13[/C][C]12.6820839831604[/C][C]0.317916016839630[/C][/ROW]
[ROW][C]274[/C][C]13[/C][C]12.0535719751566[/C][C]0.94642802484336[/C][/ROW]
[ROW][C]275[/C][C]13[/C][C]12.6729159522464[/C][C]0.327084047753606[/C][/ROW]
[ROW][C]276[/C][C]15[/C][C]11.2635617658352[/C][C]3.73643823416484[/C][/ROW]
[ROW][C]277[/C][C]15[/C][C]12.327017663492[/C][C]2.67298233650801[/C][/ROW]
[ROW][C]278[/C][C]14[/C][C]12.6177426040237[/C][C]1.38225739597633[/C][/ROW]
[ROW][C]279[/C][C]15[/C][C]13.1864577321356[/C][C]1.81354226786441[/C][/ROW]
[ROW][C]280[/C][C]11[/C][C]12.1647732373791[/C][C]-1.16477323737906[/C][/ROW]
[ROW][C]281[/C][C]15[/C][C]12.8184978302103[/C][C]2.18150216978969[/C][/ROW]
[ROW][C]282[/C][C]14[/C][C]13.3489044021032[/C][C]0.651095597896834[/C][/ROW]
[ROW][C]283[/C][C]13[/C][C]12.1226491252813[/C][C]0.877350874718697[/C][/ROW]
[ROW][C]284[/C][C]12[/C][C]12.0592278159739[/C][C]-0.0592278159738843[/C][/ROW]
[ROW][C]285[/C][C]16[/C][C]12.7453535369368[/C][C]3.25464646306319[/C][/ROW]
[ROW][C]286[/C][C]16[/C][C]12.018522876856[/C][C]3.98147712314400[/C][/ROW]
[ROW][C]287[/C][C]9[/C][C]13.407084330786[/C][C]-4.40708433078601[/C][/ROW]
[ROW][C]288[/C][C]14[/C][C]13.1205428163391[/C][C]0.879457183660885[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105492&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105492&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.2201023309641-0.220102330964103
21814.63439802461243.3656019753876
31114.6331502337977-3.63315023379767
41213.5711567783899-1.57115677838991
51614.14782761919611.85217238080388
61814.23242133353463.76757866646538
71414.9911390028679-0.991139002867864
81414.2666738639964-0.266673863996394
91514.25051692548400.749483074516018
101514.3970706517890.602929348211001
111713.84883248279663.15116751720337
121914.50440572452914.49559427547094
131013.7526658454027-3.7526658454027
141614.53843363107311.4615663689269
151814.44517635054913.55482364945094
161413.50188864708220.498111352917848
171413.65928506288820.340714937111756
181714.97082491667082.02917508332915
191413.98597656340090.0140234365990846
201614.42718188052701.57281811947298
211813.63693120132704.36306879867305
221114.4158729523214-3.41587295232145
231414.8630853562215-0.863085356221496
241214.4678335778923-2.46783357789231
251713.94689840269543.05310159730460
26914.7757610038965-5.77576100389648
271613.73025023284622.26974976715380
281414.2233768046111-0.223376804611061
291514.43849080873260.561509191267411
301113.4697376429799-2.46973764297986
311614.29692558559381.70307441440615
321313.0889063935808-0.0889063935807798
331714.37398655667342.62601344332664
341514.40181754016850.598182459831482
351413.48552946471510.514470535284903
361612.98762775103023.01237224896984
37912.9055165257892-3.90551652578916
381513.49215325553641.50784674446364
391714.39345733976492.60654266023505
401313.7349353702305-0.734935370230512
411513.80553542341131.19446457658870
421614.22789906907281.77210093092716
431614.22815194653111.77184805346886
441213.4970406367753-1.49704063677531
451514.44927174723850.550728252761545
461113.9209778190966-2.92097781909663
471514.22505146319820.774948536801839
481514.31964456393230.68035543606769
491714.45652464968672.54347535031326
501313.5627533087171-0.562753308717143
511614.29902711195331.70097288804667
521413.46311385215860.536886147841402
531113.1450465468994-2.14504654689935
541214.3697282870614-2.36972828706143
551212.9168648249268-0.916864824926845
561514.37439104438260.625608955617353
571614.58631470591541.41368529408458
581514.31328476796090.6867152320391
591213.6065166068070-1.60651660680697
601214.5092931057680-2.50929310576802
61813.2508868248439-5.25088682484386
621313.7686599109926-0.768659910992583
631114.4016152963139-3.40161529631387
641414.1300971440239-0.130097144023925
651514.49778193370780.502218066292198
661013.7416209120470-3.74162091204698
671114.6941160173600-3.69411601735998
681213.9161843407305-1.91618434073054
691514.01456084546570.985439154534266
701513.63876873283661.36123126716341
711413.08736832951600.912631670483972
721614.08211494725431.91788505274572
731514.57553376740960.424466232590447
741513.86240581028421.13759418971578
751313.7714063949399-0.77140639493994
761214.8175238975541-2.81752389755415
771714.46763133403772.53236866596233
781314.513877121225-1.51387712122500
791513.18677006962491.81322993037510
801313.8533153763263-0.853315376326296
811513.60015681083561.39984318916444
821514.42912053396400.57087946603603
831613.63840361605942.36159638394059
841514.29234157013690.707658429863142
851414.5026693149468-0.502669314946754
861513.49908041213961.50091958786041
871414.4224967431427-0.422496743142708
881314.3452728991407-1.34527289914066
89714.319543442005-7.31954344200499
901713.90839872001323.09160127998675
911314.6070556598848-1.60705565988482
921514.36514427160440.634855728395553
931414.3722107761589-0.372210776158940
941314.0204189301376-1.02041893013762
951614.58651694977011.41348305022994
961214.4996194652174-2.49961946521743
971414.5733704900549-0.57337049005486
981713.74135691719713.25864308280287
991513.36714945861931.63285054138069
1001714.49483320590582.5051667940942
1011213.7414580391245-1.74145803912445
1021614.88392743211821.11607256788178
1031113.5979541625488-2.59795416254876
1041514.35862160271050.641378397289493
105913.4984119295804-4.49841192958045
1061614.66196501325771.33803498674231
1071513.77059856442951.22940143557046
1081013.714155045329-3.714155045329
1091014.1722606270538-4.17226062705379
1101514.34058776175640.659412238243648
1111114.3516944461073-3.35169444610728
1121314.4182778444629-1.41827784446289
1131814.08810962644853.91189037355148
1141613.99514459431492.00485540568511
1151414.0725424286310-0.0725424286310211
1161414.1803213600125-0.180321360012484
1171414.0657557648872-0.0657557648872282
1181414.5270235809402-0.527023580940206
1191213.2434158325801-1.24341583258008
1201414.4637540271638-0.463754027163767
1211514.12219928398780.877800716012237
1221514.43554208093060.564457919069411
1231514.41734536705390.582654632946097
1241314.3355992585901-1.33559925859008
1251713.74119404427463.2588059557254
1261714.77790190118812.22209809881192
1271914.31984680778704.68015319221305
1281514.03340251693030.966597483069707
1291313.6530263888442-0.653026388844156
130912.8300290913694-3.83002909136942
1311514.63001625301000.369983746989962
1321513.07260896220891.92739103779107
1331513.43948592138241.56051407861759
1341614.35621671056911.64378328943094
1351113.3790022224854-2.37900222248544
1361413.54060169101050.459398308989503
1371113.7620472375629-2.76204723756287
1381514.06569401389200.934305986107981
1391313.0150936177481-0.0150936177481430
1401514.45957449941610.540425500583935
1411613.43159195968332.56840804031667
1421414.3952555003425-0.395255500342466
1431513.76956886343031.23043113656969
1441614.01229644618371.98770355381628
1451614.72895175441441.27104824558558
1461113.3252236920391-2.32522369203912
1471213.6528241449895-1.65282414498951
148913.4101825231548-4.41018252315479
1491613.84583312139102.15416687860903
1501314.4851989362873-1.48519893628733
1511613.64375723600292.35624276399714
1521214.4937035278874-2.49370352788742
153914.3854977287336-5.38549772873358
1541313.8211754896156-0.821175489615556
1551414.0869405774980-0.0869405774980255
1561914.31984680778704.68015319221305
1571314.4978830556351-1.49788305563512
1581213.9198087701461-1.91980877014614
1591012.2734835012613-2.27348350126134
1601412.29593848475001.70406151525005
1611612.87326669072373.12673330927626
1621013.2849281397436-3.28492813974364
1631111.8029465323671-0.802946532367067
1641412.34628620272891.65371379727107
1651212.7824412656936-0.782441265693551
166913.0308370968439-4.03083709684392
167912.4222005049211-3.42220050492105
1681112.4280716821249-1.42807168212487
1691613.45827925020752.54172074979250
170912.3928314573611-3.39283145736114
1711312.70693145121070.293068548789283
1721613.12643637360602.87356362639397
1731312.48785142586770.512148574132325
174913.1381497895209-4.13814978952089
1751212.1885640410778-0.188564041077778
1761613.21202431634872.78797568365127
1771113.0853813334396-2.08538133343961
1781413.47427331579740.525726684202615
1791312.25441720587900.745582794120957
1801512.85596308332392.14403691667606
1811412.68355639789281.31644360210717
1821612.26840499355933.7315950064407
1831313.3650613406156-0.365061340615577
1841412.85095220009461.14904779990544
1851513.24083909580881.75916090419125
1861312.07918919297340.920810807026561
1871112.0926390184706-1.09263901847061
1881113.1271666071604-2.12716660716038
1891413.46490304102880.535096958971234
1901513.08211075812961.91788924187036
1911113.4470714439293-2.44707144392925
1921513.10438587782671.89561412217330
1931212.5602890105581-0.560289010558091
1941413.54792321870750.452076781292509
1951413.37637026882110.623629731178851
196812.4603855591497-4.46038555914969
197912.6160679454366-3.61606794543657
1981512.24654562424312.75345437575693
1991712.16283458394214.8371654160579
2001312.21750232252820.782497677471782
2011513.3697858489321.630214151068
2021513.31681514899611.68318485100392
2031413.44707144392930.552928556070745
2041612.65661852087453.34338147912545
2051312.16935725283600.830642747163955
2061612.59054073215553.40945926784446
207912.9918600580657-3.99186005806572
2081612.21669449201783.78330550798219
2091112.4238751635082-1.42387516350815
2101012.5295131975980-2.52951319759802
2111113.4629643875918-2.46296438759181
2121512.43572792737432.56427207262572
2131713.54340095424573.45659904575429
2141413.38246606994270.617533930057294
215812.4074542301459-4.40745423014589
2161513.30734375230011.69265624769986
2171112.3477586174614-1.34775861746139
2181612.53282314384013.46717685615989
2191013.3373932300430-3.33739323004295
2201512.18387890369352.81612109630653
2211612.51005353189803.48994646810201
2221912.40567844963156.59432155036853
2231212.4443914935598-0.444391493559812
224812.1308464527623-4.13084645276234
2251112.2178056883102-1.21780568831018
2261413.25536074666620.744639253333823
227911.8885305767727-2.88853057677268
2281512.70326879577122.29673120422883
2291313.8644748399651-0.864474839965083
2301613.15899186541762.84100813458239
2311112.2013453840158-1.20134538401581
2321211.47639162637670.523608373623256
2331312.47102600479610.528973995203875
2341013.3631226871786-3.36312268717862
2351112.1739806392251-1.17398063922514
2361212.0907621160289-0.0907621160288627
237812.2129183070712-4.21291830707123
2381212.0246225763146-0.0246225763146469
2391212.4443297425646-0.444329742564602
2401112.0973859068501-1.09738590685012
2411312.40109443417450.598905565825521
2421412.87285094034291.12714905965709
2431012.8386246882813-2.83862468828132
2441212.8931295539449-0.893129553944902
2451512.06513378082052.93486621917949
2461312.03278053286360.967219467136424
2471313.1270431051700-0.127043105169957
2481313.5046261593222-0.504626159322158
2491212.3156076133591-0.315607613359097
2501212.4554981779107-0.45549817791074
251912.6406244552847-3.64062445528467
252913.2282206257933-4.22822062579326
2531513.1928175281071.807182471893
2541012.2604230024648-2.26042300246483
2551413.22165858596720.778341414032796
2561512.00259056226132.99740943773867
257712.2788725937998-5.27887259379982
2581412.36716764955781.63283235044223
259812.6515682667131-4.65156826671306
2601013.2941355415897-3.29413554158973
2611312.07757628538150.922423714618452
2621312.21754169346030.78245830653967
2631313.4741104428749-0.474110442874854
264812.1017059274573-4.10170592745726
2651212.3962464238676-0.396246423867639
2661313.1619405932196-0.161940593219607
2671213.5544458876014-1.55444588760143
2681012.3048660457853-2.30486604578534
2691313.4469703220019-0.446970322001933
2701212.6451073488143-0.645107348814335
271912.1314138133942-3.13141381339416
2721512.5303676180952.469632381905
2731312.68208398316040.317916016839630
2741312.05357197515660.94642802484336
2751312.67291595224640.327084047753606
2761511.26356176583523.73643823416484
2771512.3270176634922.67298233650801
2781412.61774260402371.38225739597633
2791513.18645773213561.81354226786441
2801112.1647732373791-1.16477323737906
2811512.81849783021032.18150216978969
2821413.34890440210320.651095597896834
2831312.12264912528130.877350874718697
2841212.0592278159739-0.0592278159738843
2851612.74535353693683.25464646306319
2861612.0185228768563.98147712314400
287913.407084330786-4.40708433078601
2881413.12054281633910.879457183660885






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.3589301962955220.7178603925910450.641069803704478
110.4487396876855560.8974793753711110.551260312314444
120.676362865935150.64727426812970.32363713406485
130.6959734867083030.6080530265833940.304026513291697
140.6341850059269370.7316299881461250.365814994073063
150.8302230627583580.3395538744832840.169776937241642
160.7738065304946030.4523869390107940.226193469505397
170.6983294533030150.603341093393970.301670546696985
180.7191537171461880.5616925657076230.280846282853812
190.6660026814180970.6679946371638070.333997318581903
200.5904267733496440.8191464533007110.409573226650356
210.7546014188235550.490797162352890.245398581176445
220.8652311654344620.2695376691310760.134768834565538
230.8315993598352470.3368012803295060.168400640164753
240.8378553427362720.3242893145274570.162144657263728
250.8168597219195340.3662805561609310.183140278080466
260.968551520659460.06289695868108010.0314484793405401
270.9608336624262170.0783326751475650.0391663375737825
280.9467241720787240.1065516558425510.0532758279212756
290.9284088656786070.1431822686427860.0715911343213932
300.9438271774300670.1123456451398660.0561728225699328
310.9291333034983180.1417333930033630.0708666965016816
320.9124993263194140.1750013473611720.087500673680586
330.8982220830356550.203555833928690.101777916964345
340.8720176947565470.2559646104869060.127982305243453
350.8416220143207010.3167559713585980.158377985679299
360.8215886607646540.3568226784706920.178411339235346
370.900462703375630.1990745932487410.0995372966243703
380.8818460420093280.2363079159813430.118153957990672
390.8734002203748460.2531995592503080.126599779625154
400.8504716250900350.2990567498199290.149528374909965
410.821997821582560.3560043568348790.178002178417440
420.7957494837921810.4085010324156390.204250516207819
430.778570480601810.442859038796380.22142951939819
440.7635465968151270.4729068063697460.236453403184873
450.7312693739187080.5374612521625830.268730626081292
460.7537136926558720.4925726146882560.246286307344128
470.7208576261279070.5582847477441860.279142373872093
480.680279122976030.639441754047940.31972087702397
490.6725254466873540.6549491066252920.327474553312646
500.6318152810322010.7363694379355980.368184718967799
510.6079403635105720.7841192729788560.392059636489428
520.5635953527425080.8728092945149850.436404647257492
530.5444565894529960.9110868210940080.455543410547004
540.5495369763390490.9009260473219020.450463023660951
550.5154499881338380.9691000237323240.484550011866162
560.474046038039220.948092076078440.52595396196078
570.4372026684110200.8744053368220410.56279733158898
580.3949176341961660.7898352683923310.605082365803834
590.3692218517886130.7384437035772260.630778148211387
600.4044744472561930.8089488945123860.595525552743807
610.5756277666817000.8487444666365990.424372233318300
620.5381879071980540.923624185603890.461812092801946
630.5885733832630170.8228532334739670.411426616736983
640.5470751894879780.9058496210240450.452924810512023
650.5059578918205860.9880842163588270.494042108179414
660.5515108243963890.8969783512072230.448489175603611
670.6187969067742870.7624061864514260.381203093225713
680.6037398125263790.7925203749472420.396260187473621
690.5698908132998820.8602183734002350.430109186700118
700.550651461975650.89869707604870.44934853802435
710.5157733782003230.9684532435993540.484226621799677
720.5010413104029550.997917379194090.498958689597045
730.4620034216494790.9240068432989590.53799657835052
740.4339341257260540.8678682514521080.566065874273946
750.3964259470560430.7928518941120870.603574052943957
760.4314173027950760.8628346055901520.568582697204924
770.4289944175642120.8579888351284250.571005582435788
780.4066677511441070.8133355022882130.593332248855893
790.4021973578828380.8043947157656760.597802642117162
800.36708515871030.73417031742060.6329148412897
810.3437648218731850.687529643746370.656235178126815
820.3098324399174680.6196648798349360.690167560082532
830.3109567491220750.621913498244150.689043250877925
840.2801975282161060.5603950564322110.719802471783894
850.2500262471477820.5000524942955640.749973752852218
860.2277907686762490.4555815373524970.772209231323751
870.2010981076546890.4021962153093770.798901892345311
880.1816289684830050.363257936966010.818371031516995
890.4511523591322010.9023047182644020.548847640867799
900.4707897929123550.941579585824710.529210207087645
910.4454848233103920.8909696466207850.554515176689607
920.4105699926502760.8211399853005520.589430007349724
930.3758668149939840.7517336299879690.624133185006016
940.3441655051020040.6883310102040080.655834494897996
950.317936720649880.635873441299760.68206327935012
960.3227240358812070.6454480717624140.677275964118793
970.2922936381388600.5845872762777190.70770636186114
980.3186216950297520.6372433900595040.681378304970248
990.2984189399220420.5968378798440840.701581060077958
1000.3005779362387990.6011558724775980.699422063761201
1010.2905822309114930.5811644618229860.709417769088507
1020.2665905655731930.5331811311463850.733409434426807
1030.2629071912177950.5258143824355910.737092808782205
1040.2357555602390990.4715111204781980.764244439760901
1050.3097611498963740.6195222997927470.690238850103626
1060.2867121705487310.5734243410974620.713287829451269
1070.2612791190392620.5225582380785250.738720880960738
1080.3110634766648070.6221269533296150.688936523335193
1090.4144415147256980.8288830294513960.585558485274302
1100.3824582429462990.7649164858925980.617541757053701
1110.4129733794621660.8259467589243320.587026620537834
1120.3997615191835740.7995230383671490.600238480816426
1130.4582833707856130.9165667415712270.541716629214387
1140.4492122867866670.8984245735733330.550787713213333
1150.4153309314918560.8306618629837120.584669068508144
1160.383279935184240.766559870368480.61672006481576
1170.3502916292782120.7005832585564230.649708370721788
1180.3205532640351350.641106528070270.679446735964865
1190.2986424234429780.5972848468859560.701357576557022
1200.2703321771503180.5406643543006350.729667822849682
1210.2451851206908340.4903702413816670.754814879309166
1220.2196815668102110.4393631336204220.780318433189789
1230.1968589079258730.3937178158517460.803141092074127
1240.1796395477917170.3592790955834340.820360452208283
1250.1988475034553790.3976950069107580.801152496544621
1260.1913689923741290.3827379847482570.808631007625871
1270.2652101485545720.5304202971091440.734789851445428
1280.2436786629588770.4873573259177540.756321337041123
1290.2187630842445110.4375261684890220.781236915755489
1300.2491278350974650.4982556701949290.750872164902535
1310.2254430757206770.4508861514413540.774556924279323
1320.2250179617351040.4500359234702080.774982038264896
1330.2110282611727630.4220565223455260.788971738827237
1340.2028393766962820.4056787533925640.797160623303718
1350.1969463159430630.3938926318861260.803053684056937
1360.1751378119111260.3502756238222530.824862188088874
1370.1790655644781420.3581311289562840.820934435521858
1380.1613724822964200.3227449645928410.83862751770358
1390.1413174840716060.2826349681432120.858682515928394
1400.1244634309122150.2489268618244310.875536569087785
1410.1290266619181690.2580533238363380.870973338081831
1420.1118698566598220.2237397133196440.888130143340178
1430.1039925436060670.2079850872121330.896007456393933
1440.1025279516111210.2050559032222420.897472048388879
1450.09577651483069860.1915530296613970.904223485169301
1460.09157717678398020.1831543535679600.90842282321602
1470.0821068409013030.1642136818026060.917893159098697
1480.1152641285025410.2305282570050830.884735871497459
1490.1141472991057340.2282945982114670.885852700894266
1500.1041892300364450.208378460072890.895810769963555
1510.1059221476028360.2118442952056720.894077852397164
1520.1105126333465090.2210252666930190.88948736665349
1530.1894046162188570.3788092324377140.810595383781143
1540.1708524131125780.3417048262251560.829147586887422
1550.1502181275477370.3004362550954740.849781872452263
1560.2242553727377080.4485107454754160.775744627262292
1570.2040471767683050.408094353536610.795952823231695
1580.1893269393635490.3786538787270980.810673060636451
1590.1840338767182240.3680677534364480.815966123281776
1600.1782227832919070.3564455665838130.821777216708093
1610.1821194538170060.3642389076340110.817880546182994
1620.2107979017727890.4215958035455770.789202098227211
1630.1902158946426300.3804317892852610.80978410535737
1640.1773464860552170.3546929721104350.822653513944783
1650.1601001197366060.3202002394732110.839899880263394
1660.2003486231673870.4006972463347740.799651376832613
1670.2246868111919780.4493736223839570.775313188808022
1680.2036561757266050.407312351453210.796343824273395
1690.2131016564483290.4262033128966580.786898343551671
1700.2323268519401950.4646537038803910.767673148059805
1710.2112122394872660.4224244789745310.788787760512734
1720.2278865022934660.4557730045869330.772113497706534
1730.2041882302066070.4083764604132140.795811769793393
1740.2459034817404630.4918069634809250.754096518259537
1750.2208419399473020.4416838798946040.779158060052698
1760.2352845394926220.4705690789852450.764715460507378
1770.2245265340596280.4490530681192560.775473465940372
1780.2013422514911960.4026845029823920.798657748508804
1790.1811453784836450.362290756967290.818854621516355
1800.1768970288023880.3537940576047750.823102971197612
1810.1618709399883840.3237418799767680.838129060011616
1820.194232816546320.388465633092640.80576718345368
1830.1712324968270360.3424649936540720.828767503172964
1840.1547100124723000.3094200249445990.8452899875277
1850.1459958457873580.2919916915747160.854004154212642
1860.1289647256596880.2579294513193760.871035274340312
1870.1153172074296920.2306344148593840.884682792570308
1880.1108497019095010.2216994038190020.8891502980905
1890.09619140273331660.1923828054666330.903808597266683
1900.09171579861847130.1834315972369430.908284201381529
1910.09060778478997530.1812155695799510.909392215210025
1920.08548081693262710.1709616338652540.914519183067373
1930.07289972743172770.1457994548634550.927100272568272
1940.0622633959402280.1245267918804560.937736604059772
1950.05281755121050650.1056351024210130.947182448789494
1960.08002637952435880.1600527590487180.919973620475641
1970.09942236500929340.1988447300185870.900577634990707
1980.1014482031834510.2028964063669030.898551796816549
1990.1552252079560810.3104504159121630.844774792043919
2000.1357511690871780.2715023381743570.864248830912822
2010.1273830495936410.2547660991872810.87261695040636
2020.1197249324367920.2394498648735840.880275067563208
2030.1044023537335460.2088047074670920.895597646266454
2040.1197604275925770.2395208551851550.880239572407423
2050.1034361502474650.2068723004949300.896563849752535
2060.1209188393967460.2418376787934930.879081160603254
2070.1552191057965270.3104382115930530.844780894203473
2080.1907902893509990.3815805787019990.809209710649
2090.1730808250499020.3461616500998050.826919174950098
2100.1747906371131140.3495812742262270.825209362886887
2110.1709108530279330.3418217060558650.829089146972067
2120.1706323918487470.3412647836974950.829367608151253
2130.2073421837494090.4146843674988190.79265781625059
2140.1855575985868470.3711151971736950.814442401413153
2150.2482182833272390.4964365666544780.751781716672761
2160.2434727325053610.4869454650107230.756527267494639
2170.2222557238310570.4445114476621140.777744276168943
2180.2607927950199270.5215855900398540.739207204980073
2190.2782722690881970.5565445381763940.721727730911803
2200.2880153737978660.5760307475957320.711984626202134
2210.3408463191168510.6816926382337030.659153680883149
2220.6145075393897140.7709849212205730.385492460610286
2230.5746800132705150.850639973458970.425319986729485
2240.6560901846674050.687819630665190.343909815332595
2250.6246902452952730.7506195094094550.375309754704728
2260.59399781343150.8120043731370.4060021865685
2270.6179735421595530.7640529156808950.382026457840447
2280.6534662918060670.6930674163878670.346533708193933
2290.614358043397540.7712839132049190.385641956602460
2300.65385643724620.69228712550760.3461435627538
2310.6294620874156560.7410758251686870.370537912584344
2320.5908710789173440.8182578421653120.409128921082656
2330.5467358474500650.906528305099870.453264152549935
2340.5666843272791470.8666313454417060.433315672720853
2350.5341049240368060.9317901519263880.465895075963194
2360.4880195836187340.9760391672374680.511980416381266
2370.6268889850950410.7462220298099180.373111014904959
2380.5862898299207030.8274203401585940.413710170079297
2390.5434589520265900.9130820959468190.456541047973410
2400.5048087107187540.9903825785624930.495191289281246
2410.4642500516037340.9285001032074690.535749948396266
2420.4241249743320130.8482499486640270.575875025667987
2430.4414760114946050.882952022989210.558523988505395
2440.4126702554442550.825340510888510.587329744555745
2450.4488692141220890.8977384282441770.551130785877911
2460.4077425012565760.8154850025131520.592257498743424
2470.3783275167284250.7566550334568510.621672483271575
2480.3390859197654620.6781718395309250.660914080234538
2490.2956718673312470.5913437346624950.704328132668753
2500.2556258754795840.5112517509591690.744374124520416
2510.3116615578374460.6233231156748930.688338442162554
2520.3458447209159720.6916894418319440.654155279084028
2530.3260536084980630.6521072169961250.673946391501937
2540.3029283829282260.6058567658564530.697071617071773
2550.2593668075715240.5187336151430490.740633192428475
2560.249802070586590.499604141173180.75019792941341
2570.4419941835470340.8839883670940670.558005816452966
2580.4167138472125370.8334276944250750.583286152787463
2590.6640369454638620.6719261090722750.335963054536138
2600.6806229760068840.6387540479862320.319377023993116
2610.6287773662458140.7424452675083720.371222633754186
2620.5678354847762640.8643290304474720.432164515223736
2630.5047340813222370.9905318373555260.495265918677763
2640.7847746949329940.4304506101340130.215225305067006
2650.7368351983049980.5263296033900040.263164801695002
2660.6893183944565490.6213632110869020.310681605543451
2670.7092402447859660.5815195104280670.290759755214033
2680.7110422236851270.5779155526297450.288957776314873
2690.6336116610236150.732776677952770.366388338976385
2700.5554921133413310.8890157733173380.444507886658669
2710.6611961466867690.6776077066264620.338803853313231
2720.5734496719002750.853100656199450.426550328099725
2730.5028867468554290.9942265062891410.497113253144571
2740.4071283621693680.8142567243387360.592871637830632
2750.351473991581980.702947983163960.64852600841802
2760.2640967836558390.5281935673116780.735903216344161
2770.1897393914425700.3794787828851410.81026060855743
2780.1120300953590880.2240601907181770.887969904640912

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.358930196295522 & 0.717860392591045 & 0.641069803704478 \tabularnewline
11 & 0.448739687685556 & 0.897479375371111 & 0.551260312314444 \tabularnewline
12 & 0.67636286593515 & 0.6472742681297 & 0.32363713406485 \tabularnewline
13 & 0.695973486708303 & 0.608053026583394 & 0.304026513291697 \tabularnewline
14 & 0.634185005926937 & 0.731629988146125 & 0.365814994073063 \tabularnewline
15 & 0.830223062758358 & 0.339553874483284 & 0.169776937241642 \tabularnewline
16 & 0.773806530494603 & 0.452386939010794 & 0.226193469505397 \tabularnewline
17 & 0.698329453303015 & 0.60334109339397 & 0.301670546696985 \tabularnewline
18 & 0.719153717146188 & 0.561692565707623 & 0.280846282853812 \tabularnewline
19 & 0.666002681418097 & 0.667994637163807 & 0.333997318581903 \tabularnewline
20 & 0.590426773349644 & 0.819146453300711 & 0.409573226650356 \tabularnewline
21 & 0.754601418823555 & 0.49079716235289 & 0.245398581176445 \tabularnewline
22 & 0.865231165434462 & 0.269537669131076 & 0.134768834565538 \tabularnewline
23 & 0.831599359835247 & 0.336801280329506 & 0.168400640164753 \tabularnewline
24 & 0.837855342736272 & 0.324289314527457 & 0.162144657263728 \tabularnewline
25 & 0.816859721919534 & 0.366280556160931 & 0.183140278080466 \tabularnewline
26 & 0.96855152065946 & 0.0628969586810801 & 0.0314484793405401 \tabularnewline
27 & 0.960833662426217 & 0.078332675147565 & 0.0391663375737825 \tabularnewline
28 & 0.946724172078724 & 0.106551655842551 & 0.0532758279212756 \tabularnewline
29 & 0.928408865678607 & 0.143182268642786 & 0.0715911343213932 \tabularnewline
30 & 0.943827177430067 & 0.112345645139866 & 0.0561728225699328 \tabularnewline
31 & 0.929133303498318 & 0.141733393003363 & 0.0708666965016816 \tabularnewline
32 & 0.912499326319414 & 0.175001347361172 & 0.087500673680586 \tabularnewline
33 & 0.898222083035655 & 0.20355583392869 & 0.101777916964345 \tabularnewline
34 & 0.872017694756547 & 0.255964610486906 & 0.127982305243453 \tabularnewline
35 & 0.841622014320701 & 0.316755971358598 & 0.158377985679299 \tabularnewline
36 & 0.821588660764654 & 0.356822678470692 & 0.178411339235346 \tabularnewline
37 & 0.90046270337563 & 0.199074593248741 & 0.0995372966243703 \tabularnewline
38 & 0.881846042009328 & 0.236307915981343 & 0.118153957990672 \tabularnewline
39 & 0.873400220374846 & 0.253199559250308 & 0.126599779625154 \tabularnewline
40 & 0.850471625090035 & 0.299056749819929 & 0.149528374909965 \tabularnewline
41 & 0.82199782158256 & 0.356004356834879 & 0.178002178417440 \tabularnewline
42 & 0.795749483792181 & 0.408501032415639 & 0.204250516207819 \tabularnewline
43 & 0.77857048060181 & 0.44285903879638 & 0.22142951939819 \tabularnewline
44 & 0.763546596815127 & 0.472906806369746 & 0.236453403184873 \tabularnewline
45 & 0.731269373918708 & 0.537461252162583 & 0.268730626081292 \tabularnewline
46 & 0.753713692655872 & 0.492572614688256 & 0.246286307344128 \tabularnewline
47 & 0.720857626127907 & 0.558284747744186 & 0.279142373872093 \tabularnewline
48 & 0.68027912297603 & 0.63944175404794 & 0.31972087702397 \tabularnewline
49 & 0.672525446687354 & 0.654949106625292 & 0.327474553312646 \tabularnewline
50 & 0.631815281032201 & 0.736369437935598 & 0.368184718967799 \tabularnewline
51 & 0.607940363510572 & 0.784119272978856 & 0.392059636489428 \tabularnewline
52 & 0.563595352742508 & 0.872809294514985 & 0.436404647257492 \tabularnewline
53 & 0.544456589452996 & 0.911086821094008 & 0.455543410547004 \tabularnewline
54 & 0.549536976339049 & 0.900926047321902 & 0.450463023660951 \tabularnewline
55 & 0.515449988133838 & 0.969100023732324 & 0.484550011866162 \tabularnewline
56 & 0.47404603803922 & 0.94809207607844 & 0.52595396196078 \tabularnewline
57 & 0.437202668411020 & 0.874405336822041 & 0.56279733158898 \tabularnewline
58 & 0.394917634196166 & 0.789835268392331 & 0.605082365803834 \tabularnewline
59 & 0.369221851788613 & 0.738443703577226 & 0.630778148211387 \tabularnewline
60 & 0.404474447256193 & 0.808948894512386 & 0.595525552743807 \tabularnewline
61 & 0.575627766681700 & 0.848744466636599 & 0.424372233318300 \tabularnewline
62 & 0.538187907198054 & 0.92362418560389 & 0.461812092801946 \tabularnewline
63 & 0.588573383263017 & 0.822853233473967 & 0.411426616736983 \tabularnewline
64 & 0.547075189487978 & 0.905849621024045 & 0.452924810512023 \tabularnewline
65 & 0.505957891820586 & 0.988084216358827 & 0.494042108179414 \tabularnewline
66 & 0.551510824396389 & 0.896978351207223 & 0.448489175603611 \tabularnewline
67 & 0.618796906774287 & 0.762406186451426 & 0.381203093225713 \tabularnewline
68 & 0.603739812526379 & 0.792520374947242 & 0.396260187473621 \tabularnewline
69 & 0.569890813299882 & 0.860218373400235 & 0.430109186700118 \tabularnewline
70 & 0.55065146197565 & 0.8986970760487 & 0.44934853802435 \tabularnewline
71 & 0.515773378200323 & 0.968453243599354 & 0.484226621799677 \tabularnewline
72 & 0.501041310402955 & 0.99791737919409 & 0.498958689597045 \tabularnewline
73 & 0.462003421649479 & 0.924006843298959 & 0.53799657835052 \tabularnewline
74 & 0.433934125726054 & 0.867868251452108 & 0.566065874273946 \tabularnewline
75 & 0.396425947056043 & 0.792851894112087 & 0.603574052943957 \tabularnewline
76 & 0.431417302795076 & 0.862834605590152 & 0.568582697204924 \tabularnewline
77 & 0.428994417564212 & 0.857988835128425 & 0.571005582435788 \tabularnewline
78 & 0.406667751144107 & 0.813335502288213 & 0.593332248855893 \tabularnewline
79 & 0.402197357882838 & 0.804394715765676 & 0.597802642117162 \tabularnewline
80 & 0.3670851587103 & 0.7341703174206 & 0.6329148412897 \tabularnewline
81 & 0.343764821873185 & 0.68752964374637 & 0.656235178126815 \tabularnewline
82 & 0.309832439917468 & 0.619664879834936 & 0.690167560082532 \tabularnewline
83 & 0.310956749122075 & 0.62191349824415 & 0.689043250877925 \tabularnewline
84 & 0.280197528216106 & 0.560395056432211 & 0.719802471783894 \tabularnewline
85 & 0.250026247147782 & 0.500052494295564 & 0.749973752852218 \tabularnewline
86 & 0.227790768676249 & 0.455581537352497 & 0.772209231323751 \tabularnewline
87 & 0.201098107654689 & 0.402196215309377 & 0.798901892345311 \tabularnewline
88 & 0.181628968483005 & 0.36325793696601 & 0.818371031516995 \tabularnewline
89 & 0.451152359132201 & 0.902304718264402 & 0.548847640867799 \tabularnewline
90 & 0.470789792912355 & 0.94157958582471 & 0.529210207087645 \tabularnewline
91 & 0.445484823310392 & 0.890969646620785 & 0.554515176689607 \tabularnewline
92 & 0.410569992650276 & 0.821139985300552 & 0.589430007349724 \tabularnewline
93 & 0.375866814993984 & 0.751733629987969 & 0.624133185006016 \tabularnewline
94 & 0.344165505102004 & 0.688331010204008 & 0.655834494897996 \tabularnewline
95 & 0.31793672064988 & 0.63587344129976 & 0.68206327935012 \tabularnewline
96 & 0.322724035881207 & 0.645448071762414 & 0.677275964118793 \tabularnewline
97 & 0.292293638138860 & 0.584587276277719 & 0.70770636186114 \tabularnewline
98 & 0.318621695029752 & 0.637243390059504 & 0.681378304970248 \tabularnewline
99 & 0.298418939922042 & 0.596837879844084 & 0.701581060077958 \tabularnewline
100 & 0.300577936238799 & 0.601155872477598 & 0.699422063761201 \tabularnewline
101 & 0.290582230911493 & 0.581164461822986 & 0.709417769088507 \tabularnewline
102 & 0.266590565573193 & 0.533181131146385 & 0.733409434426807 \tabularnewline
103 & 0.262907191217795 & 0.525814382435591 & 0.737092808782205 \tabularnewline
104 & 0.235755560239099 & 0.471511120478198 & 0.764244439760901 \tabularnewline
105 & 0.309761149896374 & 0.619522299792747 & 0.690238850103626 \tabularnewline
106 & 0.286712170548731 & 0.573424341097462 & 0.713287829451269 \tabularnewline
107 & 0.261279119039262 & 0.522558238078525 & 0.738720880960738 \tabularnewline
108 & 0.311063476664807 & 0.622126953329615 & 0.688936523335193 \tabularnewline
109 & 0.414441514725698 & 0.828883029451396 & 0.585558485274302 \tabularnewline
110 & 0.382458242946299 & 0.764916485892598 & 0.617541757053701 \tabularnewline
111 & 0.412973379462166 & 0.825946758924332 & 0.587026620537834 \tabularnewline
112 & 0.399761519183574 & 0.799523038367149 & 0.600238480816426 \tabularnewline
113 & 0.458283370785613 & 0.916566741571227 & 0.541716629214387 \tabularnewline
114 & 0.449212286786667 & 0.898424573573333 & 0.550787713213333 \tabularnewline
115 & 0.415330931491856 & 0.830661862983712 & 0.584669068508144 \tabularnewline
116 & 0.38327993518424 & 0.76655987036848 & 0.61672006481576 \tabularnewline
117 & 0.350291629278212 & 0.700583258556423 & 0.649708370721788 \tabularnewline
118 & 0.320553264035135 & 0.64110652807027 & 0.679446735964865 \tabularnewline
119 & 0.298642423442978 & 0.597284846885956 & 0.701357576557022 \tabularnewline
120 & 0.270332177150318 & 0.540664354300635 & 0.729667822849682 \tabularnewline
121 & 0.245185120690834 & 0.490370241381667 & 0.754814879309166 \tabularnewline
122 & 0.219681566810211 & 0.439363133620422 & 0.780318433189789 \tabularnewline
123 & 0.196858907925873 & 0.393717815851746 & 0.803141092074127 \tabularnewline
124 & 0.179639547791717 & 0.359279095583434 & 0.820360452208283 \tabularnewline
125 & 0.198847503455379 & 0.397695006910758 & 0.801152496544621 \tabularnewline
126 & 0.191368992374129 & 0.382737984748257 & 0.808631007625871 \tabularnewline
127 & 0.265210148554572 & 0.530420297109144 & 0.734789851445428 \tabularnewline
128 & 0.243678662958877 & 0.487357325917754 & 0.756321337041123 \tabularnewline
129 & 0.218763084244511 & 0.437526168489022 & 0.781236915755489 \tabularnewline
130 & 0.249127835097465 & 0.498255670194929 & 0.750872164902535 \tabularnewline
131 & 0.225443075720677 & 0.450886151441354 & 0.774556924279323 \tabularnewline
132 & 0.225017961735104 & 0.450035923470208 & 0.774982038264896 \tabularnewline
133 & 0.211028261172763 & 0.422056522345526 & 0.788971738827237 \tabularnewline
134 & 0.202839376696282 & 0.405678753392564 & 0.797160623303718 \tabularnewline
135 & 0.196946315943063 & 0.393892631886126 & 0.803053684056937 \tabularnewline
136 & 0.175137811911126 & 0.350275623822253 & 0.824862188088874 \tabularnewline
137 & 0.179065564478142 & 0.358131128956284 & 0.820934435521858 \tabularnewline
138 & 0.161372482296420 & 0.322744964592841 & 0.83862751770358 \tabularnewline
139 & 0.141317484071606 & 0.282634968143212 & 0.858682515928394 \tabularnewline
140 & 0.124463430912215 & 0.248926861824431 & 0.875536569087785 \tabularnewline
141 & 0.129026661918169 & 0.258053323836338 & 0.870973338081831 \tabularnewline
142 & 0.111869856659822 & 0.223739713319644 & 0.888130143340178 \tabularnewline
143 & 0.103992543606067 & 0.207985087212133 & 0.896007456393933 \tabularnewline
144 & 0.102527951611121 & 0.205055903222242 & 0.897472048388879 \tabularnewline
145 & 0.0957765148306986 & 0.191553029661397 & 0.904223485169301 \tabularnewline
146 & 0.0915771767839802 & 0.183154353567960 & 0.90842282321602 \tabularnewline
147 & 0.082106840901303 & 0.164213681802606 & 0.917893159098697 \tabularnewline
148 & 0.115264128502541 & 0.230528257005083 & 0.884735871497459 \tabularnewline
149 & 0.114147299105734 & 0.228294598211467 & 0.885852700894266 \tabularnewline
150 & 0.104189230036445 & 0.20837846007289 & 0.895810769963555 \tabularnewline
151 & 0.105922147602836 & 0.211844295205672 & 0.894077852397164 \tabularnewline
152 & 0.110512633346509 & 0.221025266693019 & 0.88948736665349 \tabularnewline
153 & 0.189404616218857 & 0.378809232437714 & 0.810595383781143 \tabularnewline
154 & 0.170852413112578 & 0.341704826225156 & 0.829147586887422 \tabularnewline
155 & 0.150218127547737 & 0.300436255095474 & 0.849781872452263 \tabularnewline
156 & 0.224255372737708 & 0.448510745475416 & 0.775744627262292 \tabularnewline
157 & 0.204047176768305 & 0.40809435353661 & 0.795952823231695 \tabularnewline
158 & 0.189326939363549 & 0.378653878727098 & 0.810673060636451 \tabularnewline
159 & 0.184033876718224 & 0.368067753436448 & 0.815966123281776 \tabularnewline
160 & 0.178222783291907 & 0.356445566583813 & 0.821777216708093 \tabularnewline
161 & 0.182119453817006 & 0.364238907634011 & 0.817880546182994 \tabularnewline
162 & 0.210797901772789 & 0.421595803545577 & 0.789202098227211 \tabularnewline
163 & 0.190215894642630 & 0.380431789285261 & 0.80978410535737 \tabularnewline
164 & 0.177346486055217 & 0.354692972110435 & 0.822653513944783 \tabularnewline
165 & 0.160100119736606 & 0.320200239473211 & 0.839899880263394 \tabularnewline
166 & 0.200348623167387 & 0.400697246334774 & 0.799651376832613 \tabularnewline
167 & 0.224686811191978 & 0.449373622383957 & 0.775313188808022 \tabularnewline
168 & 0.203656175726605 & 0.40731235145321 & 0.796343824273395 \tabularnewline
169 & 0.213101656448329 & 0.426203312896658 & 0.786898343551671 \tabularnewline
170 & 0.232326851940195 & 0.464653703880391 & 0.767673148059805 \tabularnewline
171 & 0.211212239487266 & 0.422424478974531 & 0.788787760512734 \tabularnewline
172 & 0.227886502293466 & 0.455773004586933 & 0.772113497706534 \tabularnewline
173 & 0.204188230206607 & 0.408376460413214 & 0.795811769793393 \tabularnewline
174 & 0.245903481740463 & 0.491806963480925 & 0.754096518259537 \tabularnewline
175 & 0.220841939947302 & 0.441683879894604 & 0.779158060052698 \tabularnewline
176 & 0.235284539492622 & 0.470569078985245 & 0.764715460507378 \tabularnewline
177 & 0.224526534059628 & 0.449053068119256 & 0.775473465940372 \tabularnewline
178 & 0.201342251491196 & 0.402684502982392 & 0.798657748508804 \tabularnewline
179 & 0.181145378483645 & 0.36229075696729 & 0.818854621516355 \tabularnewline
180 & 0.176897028802388 & 0.353794057604775 & 0.823102971197612 \tabularnewline
181 & 0.161870939988384 & 0.323741879976768 & 0.838129060011616 \tabularnewline
182 & 0.19423281654632 & 0.38846563309264 & 0.80576718345368 \tabularnewline
183 & 0.171232496827036 & 0.342464993654072 & 0.828767503172964 \tabularnewline
184 & 0.154710012472300 & 0.309420024944599 & 0.8452899875277 \tabularnewline
185 & 0.145995845787358 & 0.291991691574716 & 0.854004154212642 \tabularnewline
186 & 0.128964725659688 & 0.257929451319376 & 0.871035274340312 \tabularnewline
187 & 0.115317207429692 & 0.230634414859384 & 0.884682792570308 \tabularnewline
188 & 0.110849701909501 & 0.221699403819002 & 0.8891502980905 \tabularnewline
189 & 0.0961914027333166 & 0.192382805466633 & 0.903808597266683 \tabularnewline
190 & 0.0917157986184713 & 0.183431597236943 & 0.908284201381529 \tabularnewline
191 & 0.0906077847899753 & 0.181215569579951 & 0.909392215210025 \tabularnewline
192 & 0.0854808169326271 & 0.170961633865254 & 0.914519183067373 \tabularnewline
193 & 0.0728997274317277 & 0.145799454863455 & 0.927100272568272 \tabularnewline
194 & 0.062263395940228 & 0.124526791880456 & 0.937736604059772 \tabularnewline
195 & 0.0528175512105065 & 0.105635102421013 & 0.947182448789494 \tabularnewline
196 & 0.0800263795243588 & 0.160052759048718 & 0.919973620475641 \tabularnewline
197 & 0.0994223650092934 & 0.198844730018587 & 0.900577634990707 \tabularnewline
198 & 0.101448203183451 & 0.202896406366903 & 0.898551796816549 \tabularnewline
199 & 0.155225207956081 & 0.310450415912163 & 0.844774792043919 \tabularnewline
200 & 0.135751169087178 & 0.271502338174357 & 0.864248830912822 \tabularnewline
201 & 0.127383049593641 & 0.254766099187281 & 0.87261695040636 \tabularnewline
202 & 0.119724932436792 & 0.239449864873584 & 0.880275067563208 \tabularnewline
203 & 0.104402353733546 & 0.208804707467092 & 0.895597646266454 \tabularnewline
204 & 0.119760427592577 & 0.239520855185155 & 0.880239572407423 \tabularnewline
205 & 0.103436150247465 & 0.206872300494930 & 0.896563849752535 \tabularnewline
206 & 0.120918839396746 & 0.241837678793493 & 0.879081160603254 \tabularnewline
207 & 0.155219105796527 & 0.310438211593053 & 0.844780894203473 \tabularnewline
208 & 0.190790289350999 & 0.381580578701999 & 0.809209710649 \tabularnewline
209 & 0.173080825049902 & 0.346161650099805 & 0.826919174950098 \tabularnewline
210 & 0.174790637113114 & 0.349581274226227 & 0.825209362886887 \tabularnewline
211 & 0.170910853027933 & 0.341821706055865 & 0.829089146972067 \tabularnewline
212 & 0.170632391848747 & 0.341264783697495 & 0.829367608151253 \tabularnewline
213 & 0.207342183749409 & 0.414684367498819 & 0.79265781625059 \tabularnewline
214 & 0.185557598586847 & 0.371115197173695 & 0.814442401413153 \tabularnewline
215 & 0.248218283327239 & 0.496436566654478 & 0.751781716672761 \tabularnewline
216 & 0.243472732505361 & 0.486945465010723 & 0.756527267494639 \tabularnewline
217 & 0.222255723831057 & 0.444511447662114 & 0.777744276168943 \tabularnewline
218 & 0.260792795019927 & 0.521585590039854 & 0.739207204980073 \tabularnewline
219 & 0.278272269088197 & 0.556544538176394 & 0.721727730911803 \tabularnewline
220 & 0.288015373797866 & 0.576030747595732 & 0.711984626202134 \tabularnewline
221 & 0.340846319116851 & 0.681692638233703 & 0.659153680883149 \tabularnewline
222 & 0.614507539389714 & 0.770984921220573 & 0.385492460610286 \tabularnewline
223 & 0.574680013270515 & 0.85063997345897 & 0.425319986729485 \tabularnewline
224 & 0.656090184667405 & 0.68781963066519 & 0.343909815332595 \tabularnewline
225 & 0.624690245295273 & 0.750619509409455 & 0.375309754704728 \tabularnewline
226 & 0.5939978134315 & 0.812004373137 & 0.4060021865685 \tabularnewline
227 & 0.617973542159553 & 0.764052915680895 & 0.382026457840447 \tabularnewline
228 & 0.653466291806067 & 0.693067416387867 & 0.346533708193933 \tabularnewline
229 & 0.61435804339754 & 0.771283913204919 & 0.385641956602460 \tabularnewline
230 & 0.6538564372462 & 0.6922871255076 & 0.3461435627538 \tabularnewline
231 & 0.629462087415656 & 0.741075825168687 & 0.370537912584344 \tabularnewline
232 & 0.590871078917344 & 0.818257842165312 & 0.409128921082656 \tabularnewline
233 & 0.546735847450065 & 0.90652830509987 & 0.453264152549935 \tabularnewline
234 & 0.566684327279147 & 0.866631345441706 & 0.433315672720853 \tabularnewline
235 & 0.534104924036806 & 0.931790151926388 & 0.465895075963194 \tabularnewline
236 & 0.488019583618734 & 0.976039167237468 & 0.511980416381266 \tabularnewline
237 & 0.626888985095041 & 0.746222029809918 & 0.373111014904959 \tabularnewline
238 & 0.586289829920703 & 0.827420340158594 & 0.413710170079297 \tabularnewline
239 & 0.543458952026590 & 0.913082095946819 & 0.456541047973410 \tabularnewline
240 & 0.504808710718754 & 0.990382578562493 & 0.495191289281246 \tabularnewline
241 & 0.464250051603734 & 0.928500103207469 & 0.535749948396266 \tabularnewline
242 & 0.424124974332013 & 0.848249948664027 & 0.575875025667987 \tabularnewline
243 & 0.441476011494605 & 0.88295202298921 & 0.558523988505395 \tabularnewline
244 & 0.412670255444255 & 0.82534051088851 & 0.587329744555745 \tabularnewline
245 & 0.448869214122089 & 0.897738428244177 & 0.551130785877911 \tabularnewline
246 & 0.407742501256576 & 0.815485002513152 & 0.592257498743424 \tabularnewline
247 & 0.378327516728425 & 0.756655033456851 & 0.621672483271575 \tabularnewline
248 & 0.339085919765462 & 0.678171839530925 & 0.660914080234538 \tabularnewline
249 & 0.295671867331247 & 0.591343734662495 & 0.704328132668753 \tabularnewline
250 & 0.255625875479584 & 0.511251750959169 & 0.744374124520416 \tabularnewline
251 & 0.311661557837446 & 0.623323115674893 & 0.688338442162554 \tabularnewline
252 & 0.345844720915972 & 0.691689441831944 & 0.654155279084028 \tabularnewline
253 & 0.326053608498063 & 0.652107216996125 & 0.673946391501937 \tabularnewline
254 & 0.302928382928226 & 0.605856765856453 & 0.697071617071773 \tabularnewline
255 & 0.259366807571524 & 0.518733615143049 & 0.740633192428475 \tabularnewline
256 & 0.24980207058659 & 0.49960414117318 & 0.75019792941341 \tabularnewline
257 & 0.441994183547034 & 0.883988367094067 & 0.558005816452966 \tabularnewline
258 & 0.416713847212537 & 0.833427694425075 & 0.583286152787463 \tabularnewline
259 & 0.664036945463862 & 0.671926109072275 & 0.335963054536138 \tabularnewline
260 & 0.680622976006884 & 0.638754047986232 & 0.319377023993116 \tabularnewline
261 & 0.628777366245814 & 0.742445267508372 & 0.371222633754186 \tabularnewline
262 & 0.567835484776264 & 0.864329030447472 & 0.432164515223736 \tabularnewline
263 & 0.504734081322237 & 0.990531837355526 & 0.495265918677763 \tabularnewline
264 & 0.784774694932994 & 0.430450610134013 & 0.215225305067006 \tabularnewline
265 & 0.736835198304998 & 0.526329603390004 & 0.263164801695002 \tabularnewline
266 & 0.689318394456549 & 0.621363211086902 & 0.310681605543451 \tabularnewline
267 & 0.709240244785966 & 0.581519510428067 & 0.290759755214033 \tabularnewline
268 & 0.711042223685127 & 0.577915552629745 & 0.288957776314873 \tabularnewline
269 & 0.633611661023615 & 0.73277667795277 & 0.366388338976385 \tabularnewline
270 & 0.555492113341331 & 0.889015773317338 & 0.444507886658669 \tabularnewline
271 & 0.661196146686769 & 0.677607706626462 & 0.338803853313231 \tabularnewline
272 & 0.573449671900275 & 0.85310065619945 & 0.426550328099725 \tabularnewline
273 & 0.502886746855429 & 0.994226506289141 & 0.497113253144571 \tabularnewline
274 & 0.407128362169368 & 0.814256724338736 & 0.592871637830632 \tabularnewline
275 & 0.35147399158198 & 0.70294798316396 & 0.64852600841802 \tabularnewline
276 & 0.264096783655839 & 0.528193567311678 & 0.735903216344161 \tabularnewline
277 & 0.189739391442570 & 0.379478782885141 & 0.81026060855743 \tabularnewline
278 & 0.112030095359088 & 0.224060190718177 & 0.887969904640912 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105492&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]10[/C][C]0.358930196295522[/C][C]0.717860392591045[/C][C]0.641069803704478[/C][/ROW]
[ROW][C]11[/C][C]0.448739687685556[/C][C]0.897479375371111[/C][C]0.551260312314444[/C][/ROW]
[ROW][C]12[/C][C]0.67636286593515[/C][C]0.6472742681297[/C][C]0.32363713406485[/C][/ROW]
[ROW][C]13[/C][C]0.695973486708303[/C][C]0.608053026583394[/C][C]0.304026513291697[/C][/ROW]
[ROW][C]14[/C][C]0.634185005926937[/C][C]0.731629988146125[/C][C]0.365814994073063[/C][/ROW]
[ROW][C]15[/C][C]0.830223062758358[/C][C]0.339553874483284[/C][C]0.169776937241642[/C][/ROW]
[ROW][C]16[/C][C]0.773806530494603[/C][C]0.452386939010794[/C][C]0.226193469505397[/C][/ROW]
[ROW][C]17[/C][C]0.698329453303015[/C][C]0.60334109339397[/C][C]0.301670546696985[/C][/ROW]
[ROW][C]18[/C][C]0.719153717146188[/C][C]0.561692565707623[/C][C]0.280846282853812[/C][/ROW]
[ROW][C]19[/C][C]0.666002681418097[/C][C]0.667994637163807[/C][C]0.333997318581903[/C][/ROW]
[ROW][C]20[/C][C]0.590426773349644[/C][C]0.819146453300711[/C][C]0.409573226650356[/C][/ROW]
[ROW][C]21[/C][C]0.754601418823555[/C][C]0.49079716235289[/C][C]0.245398581176445[/C][/ROW]
[ROW][C]22[/C][C]0.865231165434462[/C][C]0.269537669131076[/C][C]0.134768834565538[/C][/ROW]
[ROW][C]23[/C][C]0.831599359835247[/C][C]0.336801280329506[/C][C]0.168400640164753[/C][/ROW]
[ROW][C]24[/C][C]0.837855342736272[/C][C]0.324289314527457[/C][C]0.162144657263728[/C][/ROW]
[ROW][C]25[/C][C]0.816859721919534[/C][C]0.366280556160931[/C][C]0.183140278080466[/C][/ROW]
[ROW][C]26[/C][C]0.96855152065946[/C][C]0.0628969586810801[/C][C]0.0314484793405401[/C][/ROW]
[ROW][C]27[/C][C]0.960833662426217[/C][C]0.078332675147565[/C][C]0.0391663375737825[/C][/ROW]
[ROW][C]28[/C][C]0.946724172078724[/C][C]0.106551655842551[/C][C]0.0532758279212756[/C][/ROW]
[ROW][C]29[/C][C]0.928408865678607[/C][C]0.143182268642786[/C][C]0.0715911343213932[/C][/ROW]
[ROW][C]30[/C][C]0.943827177430067[/C][C]0.112345645139866[/C][C]0.0561728225699328[/C][/ROW]
[ROW][C]31[/C][C]0.929133303498318[/C][C]0.141733393003363[/C][C]0.0708666965016816[/C][/ROW]
[ROW][C]32[/C][C]0.912499326319414[/C][C]0.175001347361172[/C][C]0.087500673680586[/C][/ROW]
[ROW][C]33[/C][C]0.898222083035655[/C][C]0.20355583392869[/C][C]0.101777916964345[/C][/ROW]
[ROW][C]34[/C][C]0.872017694756547[/C][C]0.255964610486906[/C][C]0.127982305243453[/C][/ROW]
[ROW][C]35[/C][C]0.841622014320701[/C][C]0.316755971358598[/C][C]0.158377985679299[/C][/ROW]
[ROW][C]36[/C][C]0.821588660764654[/C][C]0.356822678470692[/C][C]0.178411339235346[/C][/ROW]
[ROW][C]37[/C][C]0.90046270337563[/C][C]0.199074593248741[/C][C]0.0995372966243703[/C][/ROW]
[ROW][C]38[/C][C]0.881846042009328[/C][C]0.236307915981343[/C][C]0.118153957990672[/C][/ROW]
[ROW][C]39[/C][C]0.873400220374846[/C][C]0.253199559250308[/C][C]0.126599779625154[/C][/ROW]
[ROW][C]40[/C][C]0.850471625090035[/C][C]0.299056749819929[/C][C]0.149528374909965[/C][/ROW]
[ROW][C]41[/C][C]0.82199782158256[/C][C]0.356004356834879[/C][C]0.178002178417440[/C][/ROW]
[ROW][C]42[/C][C]0.795749483792181[/C][C]0.408501032415639[/C][C]0.204250516207819[/C][/ROW]
[ROW][C]43[/C][C]0.77857048060181[/C][C]0.44285903879638[/C][C]0.22142951939819[/C][/ROW]
[ROW][C]44[/C][C]0.763546596815127[/C][C]0.472906806369746[/C][C]0.236453403184873[/C][/ROW]
[ROW][C]45[/C][C]0.731269373918708[/C][C]0.537461252162583[/C][C]0.268730626081292[/C][/ROW]
[ROW][C]46[/C][C]0.753713692655872[/C][C]0.492572614688256[/C][C]0.246286307344128[/C][/ROW]
[ROW][C]47[/C][C]0.720857626127907[/C][C]0.558284747744186[/C][C]0.279142373872093[/C][/ROW]
[ROW][C]48[/C][C]0.68027912297603[/C][C]0.63944175404794[/C][C]0.31972087702397[/C][/ROW]
[ROW][C]49[/C][C]0.672525446687354[/C][C]0.654949106625292[/C][C]0.327474553312646[/C][/ROW]
[ROW][C]50[/C][C]0.631815281032201[/C][C]0.736369437935598[/C][C]0.368184718967799[/C][/ROW]
[ROW][C]51[/C][C]0.607940363510572[/C][C]0.784119272978856[/C][C]0.392059636489428[/C][/ROW]
[ROW][C]52[/C][C]0.563595352742508[/C][C]0.872809294514985[/C][C]0.436404647257492[/C][/ROW]
[ROW][C]53[/C][C]0.544456589452996[/C][C]0.911086821094008[/C][C]0.455543410547004[/C][/ROW]
[ROW][C]54[/C][C]0.549536976339049[/C][C]0.900926047321902[/C][C]0.450463023660951[/C][/ROW]
[ROW][C]55[/C][C]0.515449988133838[/C][C]0.969100023732324[/C][C]0.484550011866162[/C][/ROW]
[ROW][C]56[/C][C]0.47404603803922[/C][C]0.94809207607844[/C][C]0.52595396196078[/C][/ROW]
[ROW][C]57[/C][C]0.437202668411020[/C][C]0.874405336822041[/C][C]0.56279733158898[/C][/ROW]
[ROW][C]58[/C][C]0.394917634196166[/C][C]0.789835268392331[/C][C]0.605082365803834[/C][/ROW]
[ROW][C]59[/C][C]0.369221851788613[/C][C]0.738443703577226[/C][C]0.630778148211387[/C][/ROW]
[ROW][C]60[/C][C]0.404474447256193[/C][C]0.808948894512386[/C][C]0.595525552743807[/C][/ROW]
[ROW][C]61[/C][C]0.575627766681700[/C][C]0.848744466636599[/C][C]0.424372233318300[/C][/ROW]
[ROW][C]62[/C][C]0.538187907198054[/C][C]0.92362418560389[/C][C]0.461812092801946[/C][/ROW]
[ROW][C]63[/C][C]0.588573383263017[/C][C]0.822853233473967[/C][C]0.411426616736983[/C][/ROW]
[ROW][C]64[/C][C]0.547075189487978[/C][C]0.905849621024045[/C][C]0.452924810512023[/C][/ROW]
[ROW][C]65[/C][C]0.505957891820586[/C][C]0.988084216358827[/C][C]0.494042108179414[/C][/ROW]
[ROW][C]66[/C][C]0.551510824396389[/C][C]0.896978351207223[/C][C]0.448489175603611[/C][/ROW]
[ROW][C]67[/C][C]0.618796906774287[/C][C]0.762406186451426[/C][C]0.381203093225713[/C][/ROW]
[ROW][C]68[/C][C]0.603739812526379[/C][C]0.792520374947242[/C][C]0.396260187473621[/C][/ROW]
[ROW][C]69[/C][C]0.569890813299882[/C][C]0.860218373400235[/C][C]0.430109186700118[/C][/ROW]
[ROW][C]70[/C][C]0.55065146197565[/C][C]0.8986970760487[/C][C]0.44934853802435[/C][/ROW]
[ROW][C]71[/C][C]0.515773378200323[/C][C]0.968453243599354[/C][C]0.484226621799677[/C][/ROW]
[ROW][C]72[/C][C]0.501041310402955[/C][C]0.99791737919409[/C][C]0.498958689597045[/C][/ROW]
[ROW][C]73[/C][C]0.462003421649479[/C][C]0.924006843298959[/C][C]0.53799657835052[/C][/ROW]
[ROW][C]74[/C][C]0.433934125726054[/C][C]0.867868251452108[/C][C]0.566065874273946[/C][/ROW]
[ROW][C]75[/C][C]0.396425947056043[/C][C]0.792851894112087[/C][C]0.603574052943957[/C][/ROW]
[ROW][C]76[/C][C]0.431417302795076[/C][C]0.862834605590152[/C][C]0.568582697204924[/C][/ROW]
[ROW][C]77[/C][C]0.428994417564212[/C][C]0.857988835128425[/C][C]0.571005582435788[/C][/ROW]
[ROW][C]78[/C][C]0.406667751144107[/C][C]0.813335502288213[/C][C]0.593332248855893[/C][/ROW]
[ROW][C]79[/C][C]0.402197357882838[/C][C]0.804394715765676[/C][C]0.597802642117162[/C][/ROW]
[ROW][C]80[/C][C]0.3670851587103[/C][C]0.7341703174206[/C][C]0.6329148412897[/C][/ROW]
[ROW][C]81[/C][C]0.343764821873185[/C][C]0.68752964374637[/C][C]0.656235178126815[/C][/ROW]
[ROW][C]82[/C][C]0.309832439917468[/C][C]0.619664879834936[/C][C]0.690167560082532[/C][/ROW]
[ROW][C]83[/C][C]0.310956749122075[/C][C]0.62191349824415[/C][C]0.689043250877925[/C][/ROW]
[ROW][C]84[/C][C]0.280197528216106[/C][C]0.560395056432211[/C][C]0.719802471783894[/C][/ROW]
[ROW][C]85[/C][C]0.250026247147782[/C][C]0.500052494295564[/C][C]0.749973752852218[/C][/ROW]
[ROW][C]86[/C][C]0.227790768676249[/C][C]0.455581537352497[/C][C]0.772209231323751[/C][/ROW]
[ROW][C]87[/C][C]0.201098107654689[/C][C]0.402196215309377[/C][C]0.798901892345311[/C][/ROW]
[ROW][C]88[/C][C]0.181628968483005[/C][C]0.36325793696601[/C][C]0.818371031516995[/C][/ROW]
[ROW][C]89[/C][C]0.451152359132201[/C][C]0.902304718264402[/C][C]0.548847640867799[/C][/ROW]
[ROW][C]90[/C][C]0.470789792912355[/C][C]0.94157958582471[/C][C]0.529210207087645[/C][/ROW]
[ROW][C]91[/C][C]0.445484823310392[/C][C]0.890969646620785[/C][C]0.554515176689607[/C][/ROW]
[ROW][C]92[/C][C]0.410569992650276[/C][C]0.821139985300552[/C][C]0.589430007349724[/C][/ROW]
[ROW][C]93[/C][C]0.375866814993984[/C][C]0.751733629987969[/C][C]0.624133185006016[/C][/ROW]
[ROW][C]94[/C][C]0.344165505102004[/C][C]0.688331010204008[/C][C]0.655834494897996[/C][/ROW]
[ROW][C]95[/C][C]0.31793672064988[/C][C]0.63587344129976[/C][C]0.68206327935012[/C][/ROW]
[ROW][C]96[/C][C]0.322724035881207[/C][C]0.645448071762414[/C][C]0.677275964118793[/C][/ROW]
[ROW][C]97[/C][C]0.292293638138860[/C][C]0.584587276277719[/C][C]0.70770636186114[/C][/ROW]
[ROW][C]98[/C][C]0.318621695029752[/C][C]0.637243390059504[/C][C]0.681378304970248[/C][/ROW]
[ROW][C]99[/C][C]0.298418939922042[/C][C]0.596837879844084[/C][C]0.701581060077958[/C][/ROW]
[ROW][C]100[/C][C]0.300577936238799[/C][C]0.601155872477598[/C][C]0.699422063761201[/C][/ROW]
[ROW][C]101[/C][C]0.290582230911493[/C][C]0.581164461822986[/C][C]0.709417769088507[/C][/ROW]
[ROW][C]102[/C][C]0.266590565573193[/C][C]0.533181131146385[/C][C]0.733409434426807[/C][/ROW]
[ROW][C]103[/C][C]0.262907191217795[/C][C]0.525814382435591[/C][C]0.737092808782205[/C][/ROW]
[ROW][C]104[/C][C]0.235755560239099[/C][C]0.471511120478198[/C][C]0.764244439760901[/C][/ROW]
[ROW][C]105[/C][C]0.309761149896374[/C][C]0.619522299792747[/C][C]0.690238850103626[/C][/ROW]
[ROW][C]106[/C][C]0.286712170548731[/C][C]0.573424341097462[/C][C]0.713287829451269[/C][/ROW]
[ROW][C]107[/C][C]0.261279119039262[/C][C]0.522558238078525[/C][C]0.738720880960738[/C][/ROW]
[ROW][C]108[/C][C]0.311063476664807[/C][C]0.622126953329615[/C][C]0.688936523335193[/C][/ROW]
[ROW][C]109[/C][C]0.414441514725698[/C][C]0.828883029451396[/C][C]0.585558485274302[/C][/ROW]
[ROW][C]110[/C][C]0.382458242946299[/C][C]0.764916485892598[/C][C]0.617541757053701[/C][/ROW]
[ROW][C]111[/C][C]0.412973379462166[/C][C]0.825946758924332[/C][C]0.587026620537834[/C][/ROW]
[ROW][C]112[/C][C]0.399761519183574[/C][C]0.799523038367149[/C][C]0.600238480816426[/C][/ROW]
[ROW][C]113[/C][C]0.458283370785613[/C][C]0.916566741571227[/C][C]0.541716629214387[/C][/ROW]
[ROW][C]114[/C][C]0.449212286786667[/C][C]0.898424573573333[/C][C]0.550787713213333[/C][/ROW]
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[ROW][C]124[/C][C]0.179639547791717[/C][C]0.359279095583434[/C][C]0.820360452208283[/C][/ROW]
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[ROW][C]188[/C][C]0.110849701909501[/C][C]0.221699403819002[/C][C]0.8891502980905[/C][/ROW]
[ROW][C]189[/C][C]0.0961914027333166[/C][C]0.192382805466633[/C][C]0.903808597266683[/C][/ROW]
[ROW][C]190[/C][C]0.0917157986184713[/C][C]0.183431597236943[/C][C]0.908284201381529[/C][/ROW]
[ROW][C]191[/C][C]0.0906077847899753[/C][C]0.181215569579951[/C][C]0.909392215210025[/C][/ROW]
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[ROW][C]195[/C][C]0.0528175512105065[/C][C]0.105635102421013[/C][C]0.947182448789494[/C][/ROW]
[ROW][C]196[/C][C]0.0800263795243588[/C][C]0.160052759048718[/C][C]0.919973620475641[/C][/ROW]
[ROW][C]197[/C][C]0.0994223650092934[/C][C]0.198844730018587[/C][C]0.900577634990707[/C][/ROW]
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[ROW][C]207[/C][C]0.155219105796527[/C][C]0.310438211593053[/C][C]0.844780894203473[/C][/ROW]
[ROW][C]208[/C][C]0.190790289350999[/C][C]0.381580578701999[/C][C]0.809209710649[/C][/ROW]
[ROW][C]209[/C][C]0.173080825049902[/C][C]0.346161650099805[/C][C]0.826919174950098[/C][/ROW]
[ROW][C]210[/C][C]0.174790637113114[/C][C]0.349581274226227[/C][C]0.825209362886887[/C][/ROW]
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[ROW][C]218[/C][C]0.260792795019927[/C][C]0.521585590039854[/C][C]0.739207204980073[/C][/ROW]
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[ROW][C]248[/C][C]0.339085919765462[/C][C]0.678171839530925[/C][C]0.660914080234538[/C][/ROW]
[ROW][C]249[/C][C]0.295671867331247[/C][C]0.591343734662495[/C][C]0.704328132668753[/C][/ROW]
[ROW][C]250[/C][C]0.255625875479584[/C][C]0.511251750959169[/C][C]0.744374124520416[/C][/ROW]
[ROW][C]251[/C][C]0.311661557837446[/C][C]0.623323115674893[/C][C]0.688338442162554[/C][/ROW]
[ROW][C]252[/C][C]0.345844720915972[/C][C]0.691689441831944[/C][C]0.654155279084028[/C][/ROW]
[ROW][C]253[/C][C]0.326053608498063[/C][C]0.652107216996125[/C][C]0.673946391501937[/C][/ROW]
[ROW][C]254[/C][C]0.302928382928226[/C][C]0.605856765856453[/C][C]0.697071617071773[/C][/ROW]
[ROW][C]255[/C][C]0.259366807571524[/C][C]0.518733615143049[/C][C]0.740633192428475[/C][/ROW]
[ROW][C]256[/C][C]0.24980207058659[/C][C]0.49960414117318[/C][C]0.75019792941341[/C][/ROW]
[ROW][C]257[/C][C]0.441994183547034[/C][C]0.883988367094067[/C][C]0.558005816452966[/C][/ROW]
[ROW][C]258[/C][C]0.416713847212537[/C][C]0.833427694425075[/C][C]0.583286152787463[/C][/ROW]
[ROW][C]259[/C][C]0.664036945463862[/C][C]0.671926109072275[/C][C]0.335963054536138[/C][/ROW]
[ROW][C]260[/C][C]0.680622976006884[/C][C]0.638754047986232[/C][C]0.319377023993116[/C][/ROW]
[ROW][C]261[/C][C]0.628777366245814[/C][C]0.742445267508372[/C][C]0.371222633754186[/C][/ROW]
[ROW][C]262[/C][C]0.567835484776264[/C][C]0.864329030447472[/C][C]0.432164515223736[/C][/ROW]
[ROW][C]263[/C][C]0.504734081322237[/C][C]0.990531837355526[/C][C]0.495265918677763[/C][/ROW]
[ROW][C]264[/C][C]0.784774694932994[/C][C]0.430450610134013[/C][C]0.215225305067006[/C][/ROW]
[ROW][C]265[/C][C]0.736835198304998[/C][C]0.526329603390004[/C][C]0.263164801695002[/C][/ROW]
[ROW][C]266[/C][C]0.689318394456549[/C][C]0.621363211086902[/C][C]0.310681605543451[/C][/ROW]
[ROW][C]267[/C][C]0.709240244785966[/C][C]0.581519510428067[/C][C]0.290759755214033[/C][/ROW]
[ROW][C]268[/C][C]0.711042223685127[/C][C]0.577915552629745[/C][C]0.288957776314873[/C][/ROW]
[ROW][C]269[/C][C]0.633611661023615[/C][C]0.73277667795277[/C][C]0.366388338976385[/C][/ROW]
[ROW][C]270[/C][C]0.555492113341331[/C][C]0.889015773317338[/C][C]0.444507886658669[/C][/ROW]
[ROW][C]271[/C][C]0.661196146686769[/C][C]0.677607706626462[/C][C]0.338803853313231[/C][/ROW]
[ROW][C]272[/C][C]0.573449671900275[/C][C]0.85310065619945[/C][C]0.426550328099725[/C][/ROW]
[ROW][C]273[/C][C]0.502886746855429[/C][C]0.994226506289141[/C][C]0.497113253144571[/C][/ROW]
[ROW][C]274[/C][C]0.407128362169368[/C][C]0.814256724338736[/C][C]0.592871637830632[/C][/ROW]
[ROW][C]275[/C][C]0.35147399158198[/C][C]0.70294798316396[/C][C]0.64852600841802[/C][/ROW]
[ROW][C]276[/C][C]0.264096783655839[/C][C]0.528193567311678[/C][C]0.735903216344161[/C][/ROW]
[ROW][C]277[/C][C]0.189739391442570[/C][C]0.379478782885141[/C][C]0.81026060855743[/C][/ROW]
[ROW][C]278[/C][C]0.112030095359088[/C][C]0.224060190718177[/C][C]0.887969904640912[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105492&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105492&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.3589301962955220.7178603925910450.641069803704478
110.4487396876855560.8974793753711110.551260312314444
120.676362865935150.64727426812970.32363713406485
130.6959734867083030.6080530265833940.304026513291697
140.6341850059269370.7316299881461250.365814994073063
150.8302230627583580.3395538744832840.169776937241642
160.7738065304946030.4523869390107940.226193469505397
170.6983294533030150.603341093393970.301670546696985
180.7191537171461880.5616925657076230.280846282853812
190.6660026814180970.6679946371638070.333997318581903
200.5904267733496440.8191464533007110.409573226650356
210.7546014188235550.490797162352890.245398581176445
220.8652311654344620.2695376691310760.134768834565538
230.8315993598352470.3368012803295060.168400640164753
240.8378553427362720.3242893145274570.162144657263728
250.8168597219195340.3662805561609310.183140278080466
260.968551520659460.06289695868108010.0314484793405401
270.9608336624262170.0783326751475650.0391663375737825
280.9467241720787240.1065516558425510.0532758279212756
290.9284088656786070.1431822686427860.0715911343213932
300.9438271774300670.1123456451398660.0561728225699328
310.9291333034983180.1417333930033630.0708666965016816
320.9124993263194140.1750013473611720.087500673680586
330.8982220830356550.203555833928690.101777916964345
340.8720176947565470.2559646104869060.127982305243453
350.8416220143207010.3167559713585980.158377985679299
360.8215886607646540.3568226784706920.178411339235346
370.900462703375630.1990745932487410.0995372966243703
380.8818460420093280.2363079159813430.118153957990672
390.8734002203748460.2531995592503080.126599779625154
400.8504716250900350.2990567498199290.149528374909965
410.821997821582560.3560043568348790.178002178417440
420.7957494837921810.4085010324156390.204250516207819
430.778570480601810.442859038796380.22142951939819
440.7635465968151270.4729068063697460.236453403184873
450.7312693739187080.5374612521625830.268730626081292
460.7537136926558720.4925726146882560.246286307344128
470.7208576261279070.5582847477441860.279142373872093
480.680279122976030.639441754047940.31972087702397
490.6725254466873540.6549491066252920.327474553312646
500.6318152810322010.7363694379355980.368184718967799
510.6079403635105720.7841192729788560.392059636489428
520.5635953527425080.8728092945149850.436404647257492
530.5444565894529960.9110868210940080.455543410547004
540.5495369763390490.9009260473219020.450463023660951
550.5154499881338380.9691000237323240.484550011866162
560.474046038039220.948092076078440.52595396196078
570.4372026684110200.8744053368220410.56279733158898
580.3949176341961660.7898352683923310.605082365803834
590.3692218517886130.7384437035772260.630778148211387
600.4044744472561930.8089488945123860.595525552743807
610.5756277666817000.8487444666365990.424372233318300
620.5381879071980540.923624185603890.461812092801946
630.5885733832630170.8228532334739670.411426616736983
640.5470751894879780.9058496210240450.452924810512023
650.5059578918205860.9880842163588270.494042108179414
660.5515108243963890.8969783512072230.448489175603611
670.6187969067742870.7624061864514260.381203093225713
680.6037398125263790.7925203749472420.396260187473621
690.5698908132998820.8602183734002350.430109186700118
700.550651461975650.89869707604870.44934853802435
710.5157733782003230.9684532435993540.484226621799677
720.5010413104029550.997917379194090.498958689597045
730.4620034216494790.9240068432989590.53799657835052
740.4339341257260540.8678682514521080.566065874273946
750.3964259470560430.7928518941120870.603574052943957
760.4314173027950760.8628346055901520.568582697204924
770.4289944175642120.8579888351284250.571005582435788
780.4066677511441070.8133355022882130.593332248855893
790.4021973578828380.8043947157656760.597802642117162
800.36708515871030.73417031742060.6329148412897
810.3437648218731850.687529643746370.656235178126815
820.3098324399174680.6196648798349360.690167560082532
830.3109567491220750.621913498244150.689043250877925
840.2801975282161060.5603950564322110.719802471783894
850.2500262471477820.5000524942955640.749973752852218
860.2277907686762490.4555815373524970.772209231323751
870.2010981076546890.4021962153093770.798901892345311
880.1816289684830050.363257936966010.818371031516995
890.4511523591322010.9023047182644020.548847640867799
900.4707897929123550.941579585824710.529210207087645
910.4454848233103920.8909696466207850.554515176689607
920.4105699926502760.8211399853005520.589430007349724
930.3758668149939840.7517336299879690.624133185006016
940.3441655051020040.6883310102040080.655834494897996
950.317936720649880.635873441299760.68206327935012
960.3227240358812070.6454480717624140.677275964118793
970.2922936381388600.5845872762777190.70770636186114
980.3186216950297520.6372433900595040.681378304970248
990.2984189399220420.5968378798440840.701581060077958
1000.3005779362387990.6011558724775980.699422063761201
1010.2905822309114930.5811644618229860.709417769088507
1020.2665905655731930.5331811311463850.733409434426807
1030.2629071912177950.5258143824355910.737092808782205
1040.2357555602390990.4715111204781980.764244439760901
1050.3097611498963740.6195222997927470.690238850103626
1060.2867121705487310.5734243410974620.713287829451269
1070.2612791190392620.5225582380785250.738720880960738
1080.3110634766648070.6221269533296150.688936523335193
1090.4144415147256980.8288830294513960.585558485274302
1100.3824582429462990.7649164858925980.617541757053701
1110.4129733794621660.8259467589243320.587026620537834
1120.3997615191835740.7995230383671490.600238480816426
1130.4582833707856130.9165667415712270.541716629214387
1140.4492122867866670.8984245735733330.550787713213333
1150.4153309314918560.8306618629837120.584669068508144
1160.383279935184240.766559870368480.61672006481576
1170.3502916292782120.7005832585564230.649708370721788
1180.3205532640351350.641106528070270.679446735964865
1190.2986424234429780.5972848468859560.701357576557022
1200.2703321771503180.5406643543006350.729667822849682
1210.2451851206908340.4903702413816670.754814879309166
1220.2196815668102110.4393631336204220.780318433189789
1230.1968589079258730.3937178158517460.803141092074127
1240.1796395477917170.3592790955834340.820360452208283
1250.1988475034553790.3976950069107580.801152496544621
1260.1913689923741290.3827379847482570.808631007625871
1270.2652101485545720.5304202971091440.734789851445428
1280.2436786629588770.4873573259177540.756321337041123
1290.2187630842445110.4375261684890220.781236915755489
1300.2491278350974650.4982556701949290.750872164902535
1310.2254430757206770.4508861514413540.774556924279323
1320.2250179617351040.4500359234702080.774982038264896
1330.2110282611727630.4220565223455260.788971738827237
1340.2028393766962820.4056787533925640.797160623303718
1350.1969463159430630.3938926318861260.803053684056937
1360.1751378119111260.3502756238222530.824862188088874
1370.1790655644781420.3581311289562840.820934435521858
1380.1613724822964200.3227449645928410.83862751770358
1390.1413174840716060.2826349681432120.858682515928394
1400.1244634309122150.2489268618244310.875536569087785
1410.1290266619181690.2580533238363380.870973338081831
1420.1118698566598220.2237397133196440.888130143340178
1430.1039925436060670.2079850872121330.896007456393933
1440.1025279516111210.2050559032222420.897472048388879
1450.09577651483069860.1915530296613970.904223485169301
1460.09157717678398020.1831543535679600.90842282321602
1470.0821068409013030.1642136818026060.917893159098697
1480.1152641285025410.2305282570050830.884735871497459
1490.1141472991057340.2282945982114670.885852700894266
1500.1041892300364450.208378460072890.895810769963555
1510.1059221476028360.2118442952056720.894077852397164
1520.1105126333465090.2210252666930190.88948736665349
1530.1894046162188570.3788092324377140.810595383781143
1540.1708524131125780.3417048262251560.829147586887422
1550.1502181275477370.3004362550954740.849781872452263
1560.2242553727377080.4485107454754160.775744627262292
1570.2040471767683050.408094353536610.795952823231695
1580.1893269393635490.3786538787270980.810673060636451
1590.1840338767182240.3680677534364480.815966123281776
1600.1782227832919070.3564455665838130.821777216708093
1610.1821194538170060.3642389076340110.817880546182994
1620.2107979017727890.4215958035455770.789202098227211
1630.1902158946426300.3804317892852610.80978410535737
1640.1773464860552170.3546929721104350.822653513944783
1650.1601001197366060.3202002394732110.839899880263394
1660.2003486231673870.4006972463347740.799651376832613
1670.2246868111919780.4493736223839570.775313188808022
1680.2036561757266050.407312351453210.796343824273395
1690.2131016564483290.4262033128966580.786898343551671
1700.2323268519401950.4646537038803910.767673148059805
1710.2112122394872660.4224244789745310.788787760512734
1720.2278865022934660.4557730045869330.772113497706534
1730.2041882302066070.4083764604132140.795811769793393
1740.2459034817404630.4918069634809250.754096518259537
1750.2208419399473020.4416838798946040.779158060052698
1760.2352845394926220.4705690789852450.764715460507378
1770.2245265340596280.4490530681192560.775473465940372
1780.2013422514911960.4026845029823920.798657748508804
1790.1811453784836450.362290756967290.818854621516355
1800.1768970288023880.3537940576047750.823102971197612
1810.1618709399883840.3237418799767680.838129060011616
1820.194232816546320.388465633092640.80576718345368
1830.1712324968270360.3424649936540720.828767503172964
1840.1547100124723000.3094200249445990.8452899875277
1850.1459958457873580.2919916915747160.854004154212642
1860.1289647256596880.2579294513193760.871035274340312
1870.1153172074296920.2306344148593840.884682792570308
1880.1108497019095010.2216994038190020.8891502980905
1890.09619140273331660.1923828054666330.903808597266683
1900.09171579861847130.1834315972369430.908284201381529
1910.09060778478997530.1812155695799510.909392215210025
1920.08548081693262710.1709616338652540.914519183067373
1930.07289972743172770.1457994548634550.927100272568272
1940.0622633959402280.1245267918804560.937736604059772
1950.05281755121050650.1056351024210130.947182448789494
1960.08002637952435880.1600527590487180.919973620475641
1970.09942236500929340.1988447300185870.900577634990707
1980.1014482031834510.2028964063669030.898551796816549
1990.1552252079560810.3104504159121630.844774792043919
2000.1357511690871780.2715023381743570.864248830912822
2010.1273830495936410.2547660991872810.87261695040636
2020.1197249324367920.2394498648735840.880275067563208
2030.1044023537335460.2088047074670920.895597646266454
2040.1197604275925770.2395208551851550.880239572407423
2050.1034361502474650.2068723004949300.896563849752535
2060.1209188393967460.2418376787934930.879081160603254
2070.1552191057965270.3104382115930530.844780894203473
2080.1907902893509990.3815805787019990.809209710649
2090.1730808250499020.3461616500998050.826919174950098
2100.1747906371131140.3495812742262270.825209362886887
2110.1709108530279330.3418217060558650.829089146972067
2120.1706323918487470.3412647836974950.829367608151253
2130.2073421837494090.4146843674988190.79265781625059
2140.1855575985868470.3711151971736950.814442401413153
2150.2482182833272390.4964365666544780.751781716672761
2160.2434727325053610.4869454650107230.756527267494639
2170.2222557238310570.4445114476621140.777744276168943
2180.2607927950199270.5215855900398540.739207204980073
2190.2782722690881970.5565445381763940.721727730911803
2200.2880153737978660.5760307475957320.711984626202134
2210.3408463191168510.6816926382337030.659153680883149
2220.6145075393897140.7709849212205730.385492460610286
2230.5746800132705150.850639973458970.425319986729485
2240.6560901846674050.687819630665190.343909815332595
2250.6246902452952730.7506195094094550.375309754704728
2260.59399781343150.8120043731370.4060021865685
2270.6179735421595530.7640529156808950.382026457840447
2280.6534662918060670.6930674163878670.346533708193933
2290.614358043397540.7712839132049190.385641956602460
2300.65385643724620.69228712550760.3461435627538
2310.6294620874156560.7410758251686870.370537912584344
2320.5908710789173440.8182578421653120.409128921082656
2330.5467358474500650.906528305099870.453264152549935
2340.5666843272791470.8666313454417060.433315672720853
2350.5341049240368060.9317901519263880.465895075963194
2360.4880195836187340.9760391672374680.511980416381266
2370.6268889850950410.7462220298099180.373111014904959
2380.5862898299207030.8274203401585940.413710170079297
2390.5434589520265900.9130820959468190.456541047973410
2400.5048087107187540.9903825785624930.495191289281246
2410.4642500516037340.9285001032074690.535749948396266
2420.4241249743320130.8482499486640270.575875025667987
2430.4414760114946050.882952022989210.558523988505395
2440.4126702554442550.825340510888510.587329744555745
2450.4488692141220890.8977384282441770.551130785877911
2460.4077425012565760.8154850025131520.592257498743424
2470.3783275167284250.7566550334568510.621672483271575
2480.3390859197654620.6781718395309250.660914080234538
2490.2956718673312470.5913437346624950.704328132668753
2500.2556258754795840.5112517509591690.744374124520416
2510.3116615578374460.6233231156748930.688338442162554
2520.3458447209159720.6916894418319440.654155279084028
2530.3260536084980630.6521072169961250.673946391501937
2540.3029283829282260.6058567658564530.697071617071773
2550.2593668075715240.5187336151430490.740633192428475
2560.249802070586590.499604141173180.75019792941341
2570.4419941835470340.8839883670940670.558005816452966
2580.4167138472125370.8334276944250750.583286152787463
2590.6640369454638620.6719261090722750.335963054536138
2600.6806229760068840.6387540479862320.319377023993116
2610.6287773662458140.7424452675083720.371222633754186
2620.5678354847762640.8643290304474720.432164515223736
2630.5047340813222370.9905318373555260.495265918677763
2640.7847746949329940.4304506101340130.215225305067006
2650.7368351983049980.5263296033900040.263164801695002
2660.6893183944565490.6213632110869020.310681605543451
2670.7092402447859660.5815195104280670.290759755214033
2680.7110422236851270.5779155526297450.288957776314873
2690.6336116610236150.732776677952770.366388338976385
2700.5554921133413310.8890157733173380.444507886658669
2710.6611961466867690.6776077066264620.338803853313231
2720.5734496719002750.853100656199450.426550328099725
2730.5028867468554290.9942265062891410.497113253144571
2740.4071283621693680.8142567243387360.592871637830632
2750.351473991581980.702947983163960.64852600841802
2760.2640967836558390.5281935673116780.735903216344161
2770.1897393914425700.3794787828851410.81026060855743
2780.1120300953590880.2240601907181770.887969904640912






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level20.00743494423791822OK

\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 & 0 & 0 & OK \tabularnewline
5% type I error level & 0 & 0 & OK \tabularnewline
10% type I error level & 2 & 0.00743494423791822 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105492&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]2[/C][C]0.00743494423791822[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105492&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105492&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 level00OK
5% type I error level00OK
10% type I error level20.00743494423791822OK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 3 ; par2 = equal ; par3 = 2 ; par4 = no ;
Parameters (R input):
par1 = 7 ; 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$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], 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,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
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, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
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,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
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,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
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,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
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,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
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')
}