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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, 09 Dec 2012 05:16:25 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/09/t1355048273hef1m8cremilhp1.htm/, Retrieved Thu, 31 Oct 2024 23:31:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197780, Retrieved Thu, 31 Oct 2024 23:31:21 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact177
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-12-05 18:56:24] [b98453cac15ba1066b407e146608df68]
- R P     [Multiple Regression] [Workshop 10: Mult...] [2012-12-09 10:16:25] [02d90269174925f788b5f8bc5e12639b] [Current]
-   PD      [Multiple Regression] [Workshop 10 Peer ...] [2012-12-15 11:19:24] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
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
1	1	33	33	16	12	15
1	0	34	33	14	10	11
1	1	31	31	15	12	16
1	0	27	32	12	8	13
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
1	1	33	34	15	11	15
1	1	36	38	16	11	17
1	0	38	32	14	12	13
1	1	32	38	16	14	16
1	0	32	30	14	10	14
1	0	32	33	12	12	11
1	1	34	38	16	13	12
1	0	32	32	9	5	12
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
1	1	34	35	16	14	11
1	1	31	35	14	11	14
1	1	34	31	16	12	15
1	0	35	37	17	13	10
1	1	36	35	18	14	11
1	0	30	27	18	11	12
1	1	39	40	12	12	15
1	0	35	37	16	12	15
1	0	38	36	10	8	14
1	1	31	38	14	11	16
1	1	34	39	18	14	15
1	0	38	41	18	14	15
1	0	34	27	16	12	13
1	1	39	30	17	9	12
1	1	37	37	16	13	17
1	1	34	31	16	11	13
1	0	28	31	13	12	15
1	0	37	27	16	12	13
1	0	33	36	16	12	15
1	1	35	37	16	12	15
1	0	37	33	15	12	16
1	1	32	34	15	11	15
1	1	33	31	16	10	14
1	0	38	39	14	9	15
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
0	1	33	35	17	11	17
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




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 14 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197780&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]14 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197780&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197780&T=0

As an alternative you can also use a 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 time14 seconds
R Server'George Udny Yule' @ yule.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 2.06285134721187 + 0.452576036791378Pop[t] + 0.239169812731858Gender[t] -0.0132555507413535Connected[t] + 0.0243562014396463Separate[t] + 0.547343442009791Learning[t] -0.0090869319144845Happiness[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Software[t] =  +  2.06285134721187 +  0.452576036791378Pop[t] +  0.239169812731858Gender[t] -0.0132555507413535Connected[t] +  0.0243562014396463Separate[t] +  0.547343442009791Learning[t] -0.0090869319144845Happiness[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197780&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Software[t] =  +  2.06285134721187 +  0.452576036791378Pop[t] +  0.239169812731858Gender[t] -0.0132555507413535Connected[t] +  0.0243562014396463Separate[t] +  0.547343442009791Learning[t] -0.0090869319144845Happiness[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197780&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197780&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 2.06285134721187 + 0.452576036791378Pop[t] + 0.239169812731858Gender[t] -0.0132555507413535Connected[t] + 0.0243562014396463Separate[t] + 0.547343442009791Learning[t] -0.0090869319144845Happiness[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)2.062851347211871.1664551.76850.0780660.039033
Pop0.4525760367913780.2341481.93290.0542570.027129
Gender0.2391698127318580.2193321.09040.276450.138225
Connected-0.01325555074135350.031048-0.42690.6697550.334878
Separate0.02435620143964630.0322490.75520.4507360.225368
Learning0.5473434420097910.04537512.062700
Happiness-0.00908693191448450.04482-0.20270.8394840.419742

\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) & 2.06285134721187 & 1.166455 & 1.7685 & 0.078066 & 0.039033 \tabularnewline
Pop & 0.452576036791378 & 0.234148 & 1.9329 & 0.054257 & 0.027129 \tabularnewline
Gender & 0.239169812731858 & 0.219332 & 1.0904 & 0.27645 & 0.138225 \tabularnewline
Connected & -0.0132555507413535 & 0.031048 & -0.4269 & 0.669755 & 0.334878 \tabularnewline
Separate & 0.0243562014396463 & 0.032249 & 0.7552 & 0.450736 & 0.225368 \tabularnewline
Learning & 0.547343442009791 & 0.045375 & 12.0627 & 0 & 0 \tabularnewline
Happiness & -0.0090869319144845 & 0.04482 & -0.2027 & 0.839484 & 0.419742 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197780&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]2.06285134721187[/C][C]1.166455[/C][C]1.7685[/C][C]0.078066[/C][C]0.039033[/C][/ROW]
[ROW][C]Pop[/C][C]0.452576036791378[/C][C]0.234148[/C][C]1.9329[/C][C]0.054257[/C][C]0.027129[/C][/ROW]
[ROW][C]Gender[/C][C]0.239169812731858[/C][C]0.219332[/C][C]1.0904[/C][C]0.27645[/C][C]0.138225[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0132555507413535[/C][C]0.031048[/C][C]-0.4269[/C][C]0.669755[/C][C]0.334878[/C][/ROW]
[ROW][C]Separate[/C][C]0.0243562014396463[/C][C]0.032249[/C][C]0.7552[/C][C]0.450736[/C][C]0.225368[/C][/ROW]
[ROW][C]Learning[/C][C]0.547343442009791[/C][C]0.045375[/C][C]12.0627[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.0090869319144845[/C][C]0.04482[/C][C]-0.2027[/C][C]0.839484[/C][C]0.419742[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197780&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197780&T=2

As an alternative you can also use a 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)2.062851347211871.1664551.76850.0780660.039033
Pop0.4525760367913780.2341481.93290.0542570.027129
Gender0.2391698127318580.2193321.09040.276450.138225
Connected-0.01325555074135350.031048-0.42690.6697550.334878
Separate0.02435620143964630.0322490.75520.4507360.225368
Learning0.5473434420097910.04537512.062700
Happiness-0.00908693191448450.04482-0.20270.8394840.419742







Multiple Linear Regression - Regression Statistics
Multiple R0.664438564389672
R-squared0.441478605848209
Adjusted R-squared0.429552882129665
F-TEST (value)37.0190200835982
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.77966607666687
Sum Squared Residuals889.986387787312

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.664438564389672 \tabularnewline
R-squared & 0.441478605848209 \tabularnewline
Adjusted R-squared & 0.429552882129665 \tabularnewline
F-TEST (value) & 37.0190200835982 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 281 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.77966607666687 \tabularnewline
Sum Squared Residuals & 889.986387787312 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197780&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.664438564389672[/C][/ROW]
[ROW][C]R-squared[/C][C]0.441478605848209[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.429552882129665[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]37.0190200835982[/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]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]1.77966607666687[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]889.986387787312[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197780&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197780&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.664438564389672
R-squared0.441478605848209
Adjusted R-squared0.429552882129665
F-TEST (value)37.0190200835982
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.77966607666687
Sum Squared Residuals889.986387787312







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11210.12490297037071.87509702962934
21111.6109594615869-0.610959461586933
31513.50896687200881.49103312799118
4611.0093684057027-5.00936840570267
51310.72250520230132.27749479769868
6109.948882734204040.0511172657959643
71213.2649813138346-1.2649813138346
81411.26366630670042.73633369329957
91210.65636862985381.3436313701462
10911.2635251254412-2.26352512544118
111011.3697759300713-1.36977593007127
121211.69035158477580.309648415224199
131211.53080925923120.469190740768758
141111.7752705340538-0.775270534053779
151512.35961721524312.64038278475692
161210.97793899113231.02206100886766
171010.9005605867273-0.900560586727282
181213.9688129209198-1.96881292091981
191112.6489614691705-1.64896146917047
201211.72192218060540.278077819394624
211111.4889347054842-0.488934705484195
221211.75625618947950.243743810520494
231313.4354747239121-0.435474723912122
241111.8624855646341-0.862485564634071
251211.92822002277930.07177997722065
261312.21357418934440.786425810655623
271011.502798769227-1.50279876922704
281411.30127805888142.69872194111857
291211.74210976321820.257890236781847
301010.4313452433833-0.431345243383298
311211.16347808789730.836521912102708
3289.38691714928457-1.38691714928458
331010.5275144095249-0.527514409524896
341211.82627901823540.173720981764615
351210.33101584332091.66898415667909
3678.22304791725442-1.22304791725442
3798.277710690000580.722289309999422
381210.36848641424271.63151358575735
391011.7282456994753-1.72824569947531
401011.4946027128326-1.49460271283256
411011.4255615460812-1.42556154608123
421210.62508039654271.37491960345727
431513.59259283146461.40740716853544
441010.4090027607275-0.40900276072746
451010.4593641182936-0.459364118293572
46129.037430480741022.96256951925899
471310.72728233412972.27271766587032
481111.219122522648-0.219122522648008
491111.8059502543634-0.805950254363355
501210.33579297514931.66420702485073
511411.86805938924332.13194061075675
521010.3575269448036-0.357526944803612
53129.363169460846422.63683053915358
541311.87789601541851.12210398458152
5557.68769600146292-2.68769600146292
56610.6431130791124-4.64311307911245
571211.67784572829520.322154271704806
581211.81948816762320.180511832376786
591111.0029037055735-0.00290370557348264
601011.7672156589185-1.76721565891855
6179.29516035087435-2.29516035087435
621211.47919226204810.520807737951857
631411.8139143430142.18608565698597
641110.73173331547510.268266684524945
651211.68014180959750.319858190402493
661312.16663175634440.833368243655612
671412.88209012555091.11790987444909
681112.5185170738355-1.51851707383551
69129.643696100808392.35630389919161
701211.57385365476220.426146345237827
7188.23475708095421-0.234757080954205
721110.7866280559650.213371944034975
731412.96967830513431.03032169486574
741412.72619869231631.27380130768372
751211.3617210549360.638278945063967
76912.1641120922043-3.16411209220434
771311.76833850218241.23166149781764
781111.6983156734265-0.698315673426476
79129.87847497528442.1215250247156
801211.3219544027120.678045597288028
811211.57600855480520.423991445194766
821211.8130234674940.186976532505969
831210.89348737359661.10651262640339
841111.2323780733894-0.232378073389362
851011.7024842922533-1.70248429225335
86910.4881125213978-1.48811252139782
871211.77555289657230.224447103427716
881211.78894962857290.21105037142711
891211.26746177652420.732538223475762
9099.63414183715167-0.634141837151667
911512.24350421539322.75649578460679
921211.91044827325260.0895517267473835
931211.0953277966660.904672203334031
941210.09820689966421.90179310033578
951011.7265581311745-1.72655813117449
961311.76506075887551.23493924112451
97911.6759731907706-2.67597319077064
981211.45610008513160.543899914868442
991010.494577221527-0.494577221527006
1001411.73072675000142.26927324999864
1011111.5258909461436-0.525890946143627
1021513.98005475287741.01994524712264
1031110.88341877967760.116581220322435
1041111.888246971856-0.888246971856031
105129.798286159314712.20171384068529
1061212.262800922486-0.262800922485985
1071211.54303275319330.456967246806655
1081111.557320360714-0.55732036071395
10979.68482096029469-2.68482096029469
1101211.80623261688190.19376738311814
1111411.80496859235882.1950314076412
1121112.5157322313154-1.51573223131544
113109.496809197909770.503190802090232
1141312.51116149818630.488838501813667
1151310.82700322119062.17299677880942
116810.8137476704492-2.81374767044923
1171110.15787877198260.842121228017443
1181211.75798754574480.242012454255191
119119.985595225958961.01440477404104
1201311.63157058797751.36842941202253
1211210.17993889211991.82006110788011
1221411.8108685674512.18913143254903
1231311.1062872661051.89371273389499
1241511.78679472852983.21320527147017
1251010.8335331387598-0.833533138759768
1261112.271605491882-1.27160549188196
127911.2314871978694-2.23148719786936
128119.526224893696281.47377510630372
1291011.5343693650566-1.53436936505662
130118.315322442181582.68467755781842
131811.7467457137873-3.74674571378726
132119.320030882576311.67996911742369
1331210.47701187069951.52298812930047
1341211.10151013427660.898489865723354
13599.69561688998552-0.695616889985519
1361111.0001402925289-0.000140292528927792
137109.130219335930490.86978066406951
13889.55058109513593-1.55058109513593
13998.859620108628310.140379891371691
140811.7797215153992-3.77972151539915
141911.0837010345447-2.08370103454467
1421512.38701919224582.61298080775422
1431111.2858890375725-0.285889037572539
14488.30746092117616-0.307460921176156
1451312.69482805742670.305171942573273
146129.930559304209742.06944069579026
1471211.49474389409180.50525610590819
14899.86456391302148-0.864563913021476
14978.52882163417603-1.52882163417603
1501311.19106503412371.80893496587626
151911.6023784750287-2.60237847502869
152611.8889966661168-5.88899666611678
153810.6600229184184-2.66002291841836
15488.42751057210908-0.427510572109084
155610.2198467256032-4.2198467256032
156911.2314871978694-2.23148719786936
1571111.7226718748661-0.722671874866123
15889.71503334886203-1.71503334886203
159109.362808141608560.637191858391436
16088.72609476897542-0.726094768975421
1611411.52234267008352.47765732991654
1621010.9205066018859-0.92050660188593
16387.848882341647350.151117658352648
1641110.00453061381390.99546938618612
165128.478016555793583.52198344420642
166129.810550448341192.18944955165881
1671211.28184361538850.718156384611469
16858.79560326746898-3.79560326746898
1691211.33810494804680.661895051953185
170108.858179734091121.14182026590888
17177.33447608763545-0.334476087635451
172128.929525367050843.07047463294917
1731110.58316228913470.416837710865259
17489.10165934690911-1.1016593469091
17598.854948989304330.145051010695672
1761010.1635586090961-0.163558609096123
17799.16765473809737-0.167654738097367
1781211.33192261043610.668077389563862
17968.23224086167328-2.23224086167328
1801512.79197394552592.20802605447407
1811210.42147344845321.5785265515468
182126.925729309390625.07427069060938
1831211.3940317453160.605968254683964
1841111.5913838368348-0.591383836834778
18578.9719142510602-1.9719142510602
18678.27631731398347-1.27631731398347
18758.43631858636419-3.43631858636419
1881210.31751872512541.68248127487458
1891211.4028363147120.597163685287984
19039.11341550912896-6.11341550912896
1911111.3967951583606-0.396795158360591
192109.636402749699110.363597250300891
1931210.59904007166141.4009599283386
194911.2366527047206-2.23665270472061
1951211.39604546409980.603954535900155
196910.0192855530767-1.01928555307673
1971211.07158355308690.928416446913054
1981010.0019083820286-0.0019083820285777
19998.233504886196350.766495113803653
200128.841552257303723.15844774269628
201810.7665464858566-2.76654648585663
2021110.80200333799460.197996662005431
2031111.3695343626171-0.369534362617138
2041211.08783448461670.912165515383335
205108.292053915250871.70794608474913
2061010.4806779890293-0.480677989029288
207129.141425999133162.85857400086684
208129.013777023646552.98622297635345
2091110.69876095872230.301239041277705
210810.563865582042-2.56386558204196
2111211.34808275548130.651917244518701
212109.827105171864930.172894828135068
2131111.8674157074869-0.867415707486889
2141010.1487566713132-0.148756671313203
21589.48088786172217-1.48088786172217
2161210.84856084083081.1514391591692
217129.418170213840772.58182978615923
218109.953380948373020.0466190516269781
2191210.76326874254981.23673125745024
22098.863145045698810.136854954301186
22166.98802341349426-0.988023413494256
222109.921484202060460.0785157979395421
223910.0072940268584-1.00729402685843
22498.3639996763060.636000323694
22598.932794725451630.0672052745483697
22669.57026617725159-3.57026617725159
227107.942605860321312.05739413967869
228611.0879756658759-5.08797566587592
2291412.29635006834451.7036499316555
230109.600804716301920.399195283698082
231108.261515376200551.73848462379945
23264.383412598036531.61658740196347
233129.240603590632572.75939640936743
2341211.33927818608530.660721813914681
23577.67656018200976-0.676560182009757
23688.94342804440768-0.943428044407682
237118.946799970453732.05320002954627
23837.73806080388816-4.73806080388816
23969.40908328192629-3.40908328192629
24088.9990724791584-0.999072479158398
241910.035818847125-1.03581884712495
24297.950437152618811.04956284738119
24389.03889791106323-1.03889791106323
24498.96985674431190.0301432556880949
24578.36451400656832-1.36451400656832
24677.76012092402549-0.760120924025494
24769.10292337143217-3.10292337143217
248911.2833513888161-2.2833513888161
249108.835228738433791.16477126156621
250119.969682274677441.03031772532256
2511211.17579920945770.824200790542298
252810.2515233339372-2.25152333393716
253119.618837398871631.38116260112837
25434.66726737608006-1.66726737608006
2551110.75774191646070.242258083539349
256128.422172160102843.57782783989716
25778.3666219080913-1.3666219080913
25899.99342996311559-0.993429963115588
2591210.52470744281941.4752925571806
260810.2270259512383-2.22702595123826
261119.439436851752881.56056314824712
26288.26769771381122-0.267697713811224
2631010.7184425959788-0.718442595978832
26488.31959707351283-0.319597073512829
26579.45779568480558-2.45779568480558
26689.55930670781255-1.55930670781255
2671011.2770278699462-1.27702786994617
26889.56229370369484-1.56229370369484
2691211.3542650930920.645734906908024
2701411.0643691586972.93563084130298
27179.07490449652189-2.07490449652189
27266.26601794258007-0.266017942580071
2731111.0441815760842-0.0441815760842398
27445.40407478477717-1.40407478477717
275911.1638076832394-2.16380768323941
27654.251609995439330.748390004560673
27798.843424794828280.156575205171722
2781110.46124010067730.538759899322743
2791210.21920304384681.78079695615316
28098.370040832657430.629959167342575
2811210.93537375710891.06462624289114
2821010.7867340684694-0.786734068469408
28398.861272508174260.138727491825742
28465.800786248839220.199213751160781
2851011.1433377381081-1.14333773810813
28697.790518281816571.20948171818344
2871310.89661773218852.10338226781147
2881210.24370042654571.75629957345426

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 10.1249029703707 & 1.87509702962934 \tabularnewline
2 & 11 & 11.6109594615869 & -0.610959461586933 \tabularnewline
3 & 15 & 13.5089668720088 & 1.49103312799118 \tabularnewline
4 & 6 & 11.0093684057027 & -5.00936840570267 \tabularnewline
5 & 13 & 10.7225052023013 & 2.27749479769868 \tabularnewline
6 & 10 & 9.94888273420404 & 0.0511172657959643 \tabularnewline
7 & 12 & 13.2649813138346 & -1.2649813138346 \tabularnewline
8 & 14 & 11.2636663067004 & 2.73633369329957 \tabularnewline
9 & 12 & 10.6563686298538 & 1.3436313701462 \tabularnewline
10 & 9 & 11.2635251254412 & -2.26352512544118 \tabularnewline
11 & 10 & 11.3697759300713 & -1.36977593007127 \tabularnewline
12 & 12 & 11.6903515847758 & 0.309648415224199 \tabularnewline
13 & 12 & 11.5308092592312 & 0.469190740768758 \tabularnewline
14 & 11 & 11.7752705340538 & -0.775270534053779 \tabularnewline
15 & 15 & 12.3596172152431 & 2.64038278475692 \tabularnewline
16 & 12 & 10.9779389911323 & 1.02206100886766 \tabularnewline
17 & 10 & 10.9005605867273 & -0.900560586727282 \tabularnewline
18 & 12 & 13.9688129209198 & -1.96881292091981 \tabularnewline
19 & 11 & 12.6489614691705 & -1.64896146917047 \tabularnewline
20 & 12 & 11.7219221806054 & 0.278077819394624 \tabularnewline
21 & 11 & 11.4889347054842 & -0.488934705484195 \tabularnewline
22 & 12 & 11.7562561894795 & 0.243743810520494 \tabularnewline
23 & 13 & 13.4354747239121 & -0.435474723912122 \tabularnewline
24 & 11 & 11.8624855646341 & -0.862485564634071 \tabularnewline
25 & 12 & 11.9282200227793 & 0.07177997722065 \tabularnewline
26 & 13 & 12.2135741893444 & 0.786425810655623 \tabularnewline
27 & 10 & 11.502798769227 & -1.50279876922704 \tabularnewline
28 & 14 & 11.3012780588814 & 2.69872194111857 \tabularnewline
29 & 12 & 11.7421097632182 & 0.257890236781847 \tabularnewline
30 & 10 & 10.4313452433833 & -0.431345243383298 \tabularnewline
31 & 12 & 11.1634780878973 & 0.836521912102708 \tabularnewline
32 & 8 & 9.38691714928457 & -1.38691714928458 \tabularnewline
33 & 10 & 10.5275144095249 & -0.527514409524896 \tabularnewline
34 & 12 & 11.8262790182354 & 0.173720981764615 \tabularnewline
35 & 12 & 10.3310158433209 & 1.66898415667909 \tabularnewline
36 & 7 & 8.22304791725442 & -1.22304791725442 \tabularnewline
37 & 9 & 8.27771069000058 & 0.722289309999422 \tabularnewline
38 & 12 & 10.3684864142427 & 1.63151358575735 \tabularnewline
39 & 10 & 11.7282456994753 & -1.72824569947531 \tabularnewline
40 & 10 & 11.4946027128326 & -1.49460271283256 \tabularnewline
41 & 10 & 11.4255615460812 & -1.42556154608123 \tabularnewline
42 & 12 & 10.6250803965427 & 1.37491960345727 \tabularnewline
43 & 15 & 13.5925928314646 & 1.40740716853544 \tabularnewline
44 & 10 & 10.4090027607275 & -0.40900276072746 \tabularnewline
45 & 10 & 10.4593641182936 & -0.459364118293572 \tabularnewline
46 & 12 & 9.03743048074102 & 2.96256951925899 \tabularnewline
47 & 13 & 10.7272823341297 & 2.27271766587032 \tabularnewline
48 & 11 & 11.219122522648 & -0.219122522648008 \tabularnewline
49 & 11 & 11.8059502543634 & -0.805950254363355 \tabularnewline
50 & 12 & 10.3357929751493 & 1.66420702485073 \tabularnewline
51 & 14 & 11.8680593892433 & 2.13194061075675 \tabularnewline
52 & 10 & 10.3575269448036 & -0.357526944803612 \tabularnewline
53 & 12 & 9.36316946084642 & 2.63683053915358 \tabularnewline
54 & 13 & 11.8778960154185 & 1.12210398458152 \tabularnewline
55 & 5 & 7.68769600146292 & -2.68769600146292 \tabularnewline
56 & 6 & 10.6431130791124 & -4.64311307911245 \tabularnewline
57 & 12 & 11.6778457282952 & 0.322154271704806 \tabularnewline
58 & 12 & 11.8194881676232 & 0.180511832376786 \tabularnewline
59 & 11 & 11.0029037055735 & -0.00290370557348264 \tabularnewline
60 & 10 & 11.7672156589185 & -1.76721565891855 \tabularnewline
61 & 7 & 9.29516035087435 & -2.29516035087435 \tabularnewline
62 & 12 & 11.4791922620481 & 0.520807737951857 \tabularnewline
63 & 14 & 11.813914343014 & 2.18608565698597 \tabularnewline
64 & 11 & 10.7317333154751 & 0.268266684524945 \tabularnewline
65 & 12 & 11.6801418095975 & 0.319858190402493 \tabularnewline
66 & 13 & 12.1666317563444 & 0.833368243655612 \tabularnewline
67 & 14 & 12.8820901255509 & 1.11790987444909 \tabularnewline
68 & 11 & 12.5185170738355 & -1.51851707383551 \tabularnewline
69 & 12 & 9.64369610080839 & 2.35630389919161 \tabularnewline
70 & 12 & 11.5738536547622 & 0.426146345237827 \tabularnewline
71 & 8 & 8.23475708095421 & -0.234757080954205 \tabularnewline
72 & 11 & 10.786628055965 & 0.213371944034975 \tabularnewline
73 & 14 & 12.9696783051343 & 1.03032169486574 \tabularnewline
74 & 14 & 12.7261986923163 & 1.27380130768372 \tabularnewline
75 & 12 & 11.361721054936 & 0.638278945063967 \tabularnewline
76 & 9 & 12.1641120922043 & -3.16411209220434 \tabularnewline
77 & 13 & 11.7683385021824 & 1.23166149781764 \tabularnewline
78 & 11 & 11.6983156734265 & -0.698315673426476 \tabularnewline
79 & 12 & 9.8784749752844 & 2.1215250247156 \tabularnewline
80 & 12 & 11.321954402712 & 0.678045597288028 \tabularnewline
81 & 12 & 11.5760085548052 & 0.423991445194766 \tabularnewline
82 & 12 & 11.813023467494 & 0.186976532505969 \tabularnewline
83 & 12 & 10.8934873735966 & 1.10651262640339 \tabularnewline
84 & 11 & 11.2323780733894 & -0.232378073389362 \tabularnewline
85 & 10 & 11.7024842922533 & -1.70248429225335 \tabularnewline
86 & 9 & 10.4881125213978 & -1.48811252139782 \tabularnewline
87 & 12 & 11.7755528965723 & 0.224447103427716 \tabularnewline
88 & 12 & 11.7889496285729 & 0.21105037142711 \tabularnewline
89 & 12 & 11.2674617765242 & 0.732538223475762 \tabularnewline
90 & 9 & 9.63414183715167 & -0.634141837151667 \tabularnewline
91 & 15 & 12.2435042153932 & 2.75649578460679 \tabularnewline
92 & 12 & 11.9104482732526 & 0.0895517267473835 \tabularnewline
93 & 12 & 11.095327796666 & 0.904672203334031 \tabularnewline
94 & 12 & 10.0982068996642 & 1.90179310033578 \tabularnewline
95 & 10 & 11.7265581311745 & -1.72655813117449 \tabularnewline
96 & 13 & 11.7650607588755 & 1.23493924112451 \tabularnewline
97 & 9 & 11.6759731907706 & -2.67597319077064 \tabularnewline
98 & 12 & 11.4561000851316 & 0.543899914868442 \tabularnewline
99 & 10 & 10.494577221527 & -0.494577221527006 \tabularnewline
100 & 14 & 11.7307267500014 & 2.26927324999864 \tabularnewline
101 & 11 & 11.5258909461436 & -0.525890946143627 \tabularnewline
102 & 15 & 13.9800547528774 & 1.01994524712264 \tabularnewline
103 & 11 & 10.8834187796776 & 0.116581220322435 \tabularnewline
104 & 11 & 11.888246971856 & -0.888246971856031 \tabularnewline
105 & 12 & 9.79828615931471 & 2.20171384068529 \tabularnewline
106 & 12 & 12.262800922486 & -0.262800922485985 \tabularnewline
107 & 12 & 11.5430327531933 & 0.456967246806655 \tabularnewline
108 & 11 & 11.557320360714 & -0.55732036071395 \tabularnewline
109 & 7 & 9.68482096029469 & -2.68482096029469 \tabularnewline
110 & 12 & 11.8062326168819 & 0.19376738311814 \tabularnewline
111 & 14 & 11.8049685923588 & 2.1950314076412 \tabularnewline
112 & 11 & 12.5157322313154 & -1.51573223131544 \tabularnewline
113 & 10 & 9.49680919790977 & 0.503190802090232 \tabularnewline
114 & 13 & 12.5111614981863 & 0.488838501813667 \tabularnewline
115 & 13 & 10.8270032211906 & 2.17299677880942 \tabularnewline
116 & 8 & 10.8137476704492 & -2.81374767044923 \tabularnewline
117 & 11 & 10.1578787719826 & 0.842121228017443 \tabularnewline
118 & 12 & 11.7579875457448 & 0.242012454255191 \tabularnewline
119 & 11 & 9.98559522595896 & 1.01440477404104 \tabularnewline
120 & 13 & 11.6315705879775 & 1.36842941202253 \tabularnewline
121 & 12 & 10.1799388921199 & 1.82006110788011 \tabularnewline
122 & 14 & 11.810868567451 & 2.18913143254903 \tabularnewline
123 & 13 & 11.106287266105 & 1.89371273389499 \tabularnewline
124 & 15 & 11.7867947285298 & 3.21320527147017 \tabularnewline
125 & 10 & 10.8335331387598 & -0.833533138759768 \tabularnewline
126 & 11 & 12.271605491882 & -1.27160549188196 \tabularnewline
127 & 9 & 11.2314871978694 & -2.23148719786936 \tabularnewline
128 & 11 & 9.52622489369628 & 1.47377510630372 \tabularnewline
129 & 10 & 11.5343693650566 & -1.53436936505662 \tabularnewline
130 & 11 & 8.31532244218158 & 2.68467755781842 \tabularnewline
131 & 8 & 11.7467457137873 & -3.74674571378726 \tabularnewline
132 & 11 & 9.32003088257631 & 1.67996911742369 \tabularnewline
133 & 12 & 10.4770118706995 & 1.52298812930047 \tabularnewline
134 & 12 & 11.1015101342766 & 0.898489865723354 \tabularnewline
135 & 9 & 9.69561688998552 & -0.695616889985519 \tabularnewline
136 & 11 & 11.0001402925289 & -0.000140292528927792 \tabularnewline
137 & 10 & 9.13021933593049 & 0.86978066406951 \tabularnewline
138 & 8 & 9.55058109513593 & -1.55058109513593 \tabularnewline
139 & 9 & 8.85962010862831 & 0.140379891371691 \tabularnewline
140 & 8 & 11.7797215153992 & -3.77972151539915 \tabularnewline
141 & 9 & 11.0837010345447 & -2.08370103454467 \tabularnewline
142 & 15 & 12.3870191922458 & 2.61298080775422 \tabularnewline
143 & 11 & 11.2858890375725 & -0.285889037572539 \tabularnewline
144 & 8 & 8.30746092117616 & -0.307460921176156 \tabularnewline
145 & 13 & 12.6948280574267 & 0.305171942573273 \tabularnewline
146 & 12 & 9.93055930420974 & 2.06944069579026 \tabularnewline
147 & 12 & 11.4947438940918 & 0.50525610590819 \tabularnewline
148 & 9 & 9.86456391302148 & -0.864563913021476 \tabularnewline
149 & 7 & 8.52882163417603 & -1.52882163417603 \tabularnewline
150 & 13 & 11.1910650341237 & 1.80893496587626 \tabularnewline
151 & 9 & 11.6023784750287 & -2.60237847502869 \tabularnewline
152 & 6 & 11.8889966661168 & -5.88899666611678 \tabularnewline
153 & 8 & 10.6600229184184 & -2.66002291841836 \tabularnewline
154 & 8 & 8.42751057210908 & -0.427510572109084 \tabularnewline
155 & 6 & 10.2198467256032 & -4.2198467256032 \tabularnewline
156 & 9 & 11.2314871978694 & -2.23148719786936 \tabularnewline
157 & 11 & 11.7226718748661 & -0.722671874866123 \tabularnewline
158 & 8 & 9.71503334886203 & -1.71503334886203 \tabularnewline
159 & 10 & 9.36280814160856 & 0.637191858391436 \tabularnewline
160 & 8 & 8.72609476897542 & -0.726094768975421 \tabularnewline
161 & 14 & 11.5223426700835 & 2.47765732991654 \tabularnewline
162 & 10 & 10.9205066018859 & -0.92050660188593 \tabularnewline
163 & 8 & 7.84888234164735 & 0.151117658352648 \tabularnewline
164 & 11 & 10.0045306138139 & 0.99546938618612 \tabularnewline
165 & 12 & 8.47801655579358 & 3.52198344420642 \tabularnewline
166 & 12 & 9.81055044834119 & 2.18944955165881 \tabularnewline
167 & 12 & 11.2818436153885 & 0.718156384611469 \tabularnewline
168 & 5 & 8.79560326746898 & -3.79560326746898 \tabularnewline
169 & 12 & 11.3381049480468 & 0.661895051953185 \tabularnewline
170 & 10 & 8.85817973409112 & 1.14182026590888 \tabularnewline
171 & 7 & 7.33447608763545 & -0.334476087635451 \tabularnewline
172 & 12 & 8.92952536705084 & 3.07047463294917 \tabularnewline
173 & 11 & 10.5831622891347 & 0.416837710865259 \tabularnewline
174 & 8 & 9.10165934690911 & -1.1016593469091 \tabularnewline
175 & 9 & 8.85494898930433 & 0.145051010695672 \tabularnewline
176 & 10 & 10.1635586090961 & -0.163558609096123 \tabularnewline
177 & 9 & 9.16765473809737 & -0.167654738097367 \tabularnewline
178 & 12 & 11.3319226104361 & 0.668077389563862 \tabularnewline
179 & 6 & 8.23224086167328 & -2.23224086167328 \tabularnewline
180 & 15 & 12.7919739455259 & 2.20802605447407 \tabularnewline
181 & 12 & 10.4214734484532 & 1.5785265515468 \tabularnewline
182 & 12 & 6.92572930939062 & 5.07427069060938 \tabularnewline
183 & 12 & 11.394031745316 & 0.605968254683964 \tabularnewline
184 & 11 & 11.5913838368348 & -0.591383836834778 \tabularnewline
185 & 7 & 8.9719142510602 & -1.9719142510602 \tabularnewline
186 & 7 & 8.27631731398347 & -1.27631731398347 \tabularnewline
187 & 5 & 8.43631858636419 & -3.43631858636419 \tabularnewline
188 & 12 & 10.3175187251254 & 1.68248127487458 \tabularnewline
189 & 12 & 11.402836314712 & 0.597163685287984 \tabularnewline
190 & 3 & 9.11341550912896 & -6.11341550912896 \tabularnewline
191 & 11 & 11.3967951583606 & -0.396795158360591 \tabularnewline
192 & 10 & 9.63640274969911 & 0.363597250300891 \tabularnewline
193 & 12 & 10.5990400716614 & 1.4009599283386 \tabularnewline
194 & 9 & 11.2366527047206 & -2.23665270472061 \tabularnewline
195 & 12 & 11.3960454640998 & 0.603954535900155 \tabularnewline
196 & 9 & 10.0192855530767 & -1.01928555307673 \tabularnewline
197 & 12 & 11.0715835530869 & 0.928416446913054 \tabularnewline
198 & 10 & 10.0019083820286 & -0.0019083820285777 \tabularnewline
199 & 9 & 8.23350488619635 & 0.766495113803653 \tabularnewline
200 & 12 & 8.84155225730372 & 3.15844774269628 \tabularnewline
201 & 8 & 10.7665464858566 & -2.76654648585663 \tabularnewline
202 & 11 & 10.8020033379946 & 0.197996662005431 \tabularnewline
203 & 11 & 11.3695343626171 & -0.369534362617138 \tabularnewline
204 & 12 & 11.0878344846167 & 0.912165515383335 \tabularnewline
205 & 10 & 8.29205391525087 & 1.70794608474913 \tabularnewline
206 & 10 & 10.4806779890293 & -0.480677989029288 \tabularnewline
207 & 12 & 9.14142599913316 & 2.85857400086684 \tabularnewline
208 & 12 & 9.01377702364655 & 2.98622297635345 \tabularnewline
209 & 11 & 10.6987609587223 & 0.301239041277705 \tabularnewline
210 & 8 & 10.563865582042 & -2.56386558204196 \tabularnewline
211 & 12 & 11.3480827554813 & 0.651917244518701 \tabularnewline
212 & 10 & 9.82710517186493 & 0.172894828135068 \tabularnewline
213 & 11 & 11.8674157074869 & -0.867415707486889 \tabularnewline
214 & 10 & 10.1487566713132 & -0.148756671313203 \tabularnewline
215 & 8 & 9.48088786172217 & -1.48088786172217 \tabularnewline
216 & 12 & 10.8485608408308 & 1.1514391591692 \tabularnewline
217 & 12 & 9.41817021384077 & 2.58182978615923 \tabularnewline
218 & 10 & 9.95338094837302 & 0.0466190516269781 \tabularnewline
219 & 12 & 10.7632687425498 & 1.23673125745024 \tabularnewline
220 & 9 & 8.86314504569881 & 0.136854954301186 \tabularnewline
221 & 6 & 6.98802341349426 & -0.988023413494256 \tabularnewline
222 & 10 & 9.92148420206046 & 0.0785157979395421 \tabularnewline
223 & 9 & 10.0072940268584 & -1.00729402685843 \tabularnewline
224 & 9 & 8.363999676306 & 0.636000323694 \tabularnewline
225 & 9 & 8.93279472545163 & 0.0672052745483697 \tabularnewline
226 & 6 & 9.57026617725159 & -3.57026617725159 \tabularnewline
227 & 10 & 7.94260586032131 & 2.05739413967869 \tabularnewline
228 & 6 & 11.0879756658759 & -5.08797566587592 \tabularnewline
229 & 14 & 12.2963500683445 & 1.7036499316555 \tabularnewline
230 & 10 & 9.60080471630192 & 0.399195283698082 \tabularnewline
231 & 10 & 8.26151537620055 & 1.73848462379945 \tabularnewline
232 & 6 & 4.38341259803653 & 1.61658740196347 \tabularnewline
233 & 12 & 9.24060359063257 & 2.75939640936743 \tabularnewline
234 & 12 & 11.3392781860853 & 0.660721813914681 \tabularnewline
235 & 7 & 7.67656018200976 & -0.676560182009757 \tabularnewline
236 & 8 & 8.94342804440768 & -0.943428044407682 \tabularnewline
237 & 11 & 8.94679997045373 & 2.05320002954627 \tabularnewline
238 & 3 & 7.73806080388816 & -4.73806080388816 \tabularnewline
239 & 6 & 9.40908328192629 & -3.40908328192629 \tabularnewline
240 & 8 & 8.9990724791584 & -0.999072479158398 \tabularnewline
241 & 9 & 10.035818847125 & -1.03581884712495 \tabularnewline
242 & 9 & 7.95043715261881 & 1.04956284738119 \tabularnewline
243 & 8 & 9.03889791106323 & -1.03889791106323 \tabularnewline
244 & 9 & 8.9698567443119 & 0.0301432556880949 \tabularnewline
245 & 7 & 8.36451400656832 & -1.36451400656832 \tabularnewline
246 & 7 & 7.76012092402549 & -0.760120924025494 \tabularnewline
247 & 6 & 9.10292337143217 & -3.10292337143217 \tabularnewline
248 & 9 & 11.2833513888161 & -2.2833513888161 \tabularnewline
249 & 10 & 8.83522873843379 & 1.16477126156621 \tabularnewline
250 & 11 & 9.96968227467744 & 1.03031772532256 \tabularnewline
251 & 12 & 11.1757992094577 & 0.824200790542298 \tabularnewline
252 & 8 & 10.2515233339372 & -2.25152333393716 \tabularnewline
253 & 11 & 9.61883739887163 & 1.38116260112837 \tabularnewline
254 & 3 & 4.66726737608006 & -1.66726737608006 \tabularnewline
255 & 11 & 10.7577419164607 & 0.242258083539349 \tabularnewline
256 & 12 & 8.42217216010284 & 3.57782783989716 \tabularnewline
257 & 7 & 8.3666219080913 & -1.3666219080913 \tabularnewline
258 & 9 & 9.99342996311559 & -0.993429963115588 \tabularnewline
259 & 12 & 10.5247074428194 & 1.4752925571806 \tabularnewline
260 & 8 & 10.2270259512383 & -2.22702595123826 \tabularnewline
261 & 11 & 9.43943685175288 & 1.56056314824712 \tabularnewline
262 & 8 & 8.26769771381122 & -0.267697713811224 \tabularnewline
263 & 10 & 10.7184425959788 & -0.718442595978832 \tabularnewline
264 & 8 & 8.31959707351283 & -0.319597073512829 \tabularnewline
265 & 7 & 9.45779568480558 & -2.45779568480558 \tabularnewline
266 & 8 & 9.55930670781255 & -1.55930670781255 \tabularnewline
267 & 10 & 11.2770278699462 & -1.27702786994617 \tabularnewline
268 & 8 & 9.56229370369484 & -1.56229370369484 \tabularnewline
269 & 12 & 11.354265093092 & 0.645734906908024 \tabularnewline
270 & 14 & 11.064369158697 & 2.93563084130298 \tabularnewline
271 & 7 & 9.07490449652189 & -2.07490449652189 \tabularnewline
272 & 6 & 6.26601794258007 & -0.266017942580071 \tabularnewline
273 & 11 & 11.0441815760842 & -0.0441815760842398 \tabularnewline
274 & 4 & 5.40407478477717 & -1.40407478477717 \tabularnewline
275 & 9 & 11.1638076832394 & -2.16380768323941 \tabularnewline
276 & 5 & 4.25160999543933 & 0.748390004560673 \tabularnewline
277 & 9 & 8.84342479482828 & 0.156575205171722 \tabularnewline
278 & 11 & 10.4612401006773 & 0.538759899322743 \tabularnewline
279 & 12 & 10.2192030438468 & 1.78079695615316 \tabularnewline
280 & 9 & 8.37004083265743 & 0.629959167342575 \tabularnewline
281 & 12 & 10.9353737571089 & 1.06462624289114 \tabularnewline
282 & 10 & 10.7867340684694 & -0.786734068469408 \tabularnewline
283 & 9 & 8.86127250817426 & 0.138727491825742 \tabularnewline
284 & 6 & 5.80078624883922 & 0.199213751160781 \tabularnewline
285 & 10 & 11.1433377381081 & -1.14333773810813 \tabularnewline
286 & 9 & 7.79051828181657 & 1.20948171818344 \tabularnewline
287 & 13 & 10.8966177321885 & 2.10338226781147 \tabularnewline
288 & 12 & 10.2437004265457 & 1.75629957345426 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197780&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12[/C][C]10.1249029703707[/C][C]1.87509702962934[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]11.6109594615869[/C][C]-0.610959461586933[/C][/ROW]
[ROW][C]3[/C][C]15[/C][C]13.5089668720088[/C][C]1.49103312799118[/C][/ROW]
[ROW][C]4[/C][C]6[/C][C]11.0093684057027[/C][C]-5.00936840570267[/C][/ROW]
[ROW][C]5[/C][C]13[/C][C]10.7225052023013[/C][C]2.27749479769868[/C][/ROW]
[ROW][C]6[/C][C]10[/C][C]9.94888273420404[/C][C]0.0511172657959643[/C][/ROW]
[ROW][C]7[/C][C]12[/C][C]13.2649813138346[/C][C]-1.2649813138346[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]11.2636663067004[/C][C]2.73633369329957[/C][/ROW]
[ROW][C]9[/C][C]12[/C][C]10.6563686298538[/C][C]1.3436313701462[/C][/ROW]
[ROW][C]10[/C][C]9[/C][C]11.2635251254412[/C][C]-2.26352512544118[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]11.3697759300713[/C][C]-1.36977593007127[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]11.6903515847758[/C][C]0.309648415224199[/C][/ROW]
[ROW][C]13[/C][C]12[/C][C]11.5308092592312[/C][C]0.469190740768758[/C][/ROW]
[ROW][C]14[/C][C]11[/C][C]11.7752705340538[/C][C]-0.775270534053779[/C][/ROW]
[ROW][C]15[/C][C]15[/C][C]12.3596172152431[/C][C]2.64038278475692[/C][/ROW]
[ROW][C]16[/C][C]12[/C][C]10.9779389911323[/C][C]1.02206100886766[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]10.9005605867273[/C][C]-0.900560586727282[/C][/ROW]
[ROW][C]18[/C][C]12[/C][C]13.9688129209198[/C][C]-1.96881292091981[/C][/ROW]
[ROW][C]19[/C][C]11[/C][C]12.6489614691705[/C][C]-1.64896146917047[/C][/ROW]
[ROW][C]20[/C][C]12[/C][C]11.7219221806054[/C][C]0.278077819394624[/C][/ROW]
[ROW][C]21[/C][C]11[/C][C]11.4889347054842[/C][C]-0.488934705484195[/C][/ROW]
[ROW][C]22[/C][C]12[/C][C]11.7562561894795[/C][C]0.243743810520494[/C][/ROW]
[ROW][C]23[/C][C]13[/C][C]13.4354747239121[/C][C]-0.435474723912122[/C][/ROW]
[ROW][C]24[/C][C]11[/C][C]11.8624855646341[/C][C]-0.862485564634071[/C][/ROW]
[ROW][C]25[/C][C]12[/C][C]11.9282200227793[/C][C]0.07177997722065[/C][/ROW]
[ROW][C]26[/C][C]13[/C][C]12.2135741893444[/C][C]0.786425810655623[/C][/ROW]
[ROW][C]27[/C][C]10[/C][C]11.502798769227[/C][C]-1.50279876922704[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]11.3012780588814[/C][C]2.69872194111857[/C][/ROW]
[ROW][C]29[/C][C]12[/C][C]11.7421097632182[/C][C]0.257890236781847[/C][/ROW]
[ROW][C]30[/C][C]10[/C][C]10.4313452433833[/C][C]-0.431345243383298[/C][/ROW]
[ROW][C]31[/C][C]12[/C][C]11.1634780878973[/C][C]0.836521912102708[/C][/ROW]
[ROW][C]32[/C][C]8[/C][C]9.38691714928457[/C][C]-1.38691714928458[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.5275144095249[/C][C]-0.527514409524896[/C][/ROW]
[ROW][C]34[/C][C]12[/C][C]11.8262790182354[/C][C]0.173720981764615[/C][/ROW]
[ROW][C]35[/C][C]12[/C][C]10.3310158433209[/C][C]1.66898415667909[/C][/ROW]
[ROW][C]36[/C][C]7[/C][C]8.22304791725442[/C][C]-1.22304791725442[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]8.27771069000058[/C][C]0.722289309999422[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]10.3684864142427[/C][C]1.63151358575735[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]11.7282456994753[/C][C]-1.72824569947531[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]11.4946027128326[/C][C]-1.49460271283256[/C][/ROW]
[ROW][C]41[/C][C]10[/C][C]11.4255615460812[/C][C]-1.42556154608123[/C][/ROW]
[ROW][C]42[/C][C]12[/C][C]10.6250803965427[/C][C]1.37491960345727[/C][/ROW]
[ROW][C]43[/C][C]15[/C][C]13.5925928314646[/C][C]1.40740716853544[/C][/ROW]
[ROW][C]44[/C][C]10[/C][C]10.4090027607275[/C][C]-0.40900276072746[/C][/ROW]
[ROW][C]45[/C][C]10[/C][C]10.4593641182936[/C][C]-0.459364118293572[/C][/ROW]
[ROW][C]46[/C][C]12[/C][C]9.03743048074102[/C][C]2.96256951925899[/C][/ROW]
[ROW][C]47[/C][C]13[/C][C]10.7272823341297[/C][C]2.27271766587032[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]11.219122522648[/C][C]-0.219122522648008[/C][/ROW]
[ROW][C]49[/C][C]11[/C][C]11.8059502543634[/C][C]-0.805950254363355[/C][/ROW]
[ROW][C]50[/C][C]12[/C][C]10.3357929751493[/C][C]1.66420702485073[/C][/ROW]
[ROW][C]51[/C][C]14[/C][C]11.8680593892433[/C][C]2.13194061075675[/C][/ROW]
[ROW][C]52[/C][C]10[/C][C]10.3575269448036[/C][C]-0.357526944803612[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]9.36316946084642[/C][C]2.63683053915358[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]11.8778960154185[/C][C]1.12210398458152[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]7.68769600146292[/C][C]-2.68769600146292[/C][/ROW]
[ROW][C]56[/C][C]6[/C][C]10.6431130791124[/C][C]-4.64311307911245[/C][/ROW]
[ROW][C]57[/C][C]12[/C][C]11.6778457282952[/C][C]0.322154271704806[/C][/ROW]
[ROW][C]58[/C][C]12[/C][C]11.8194881676232[/C][C]0.180511832376786[/C][/ROW]
[ROW][C]59[/C][C]11[/C][C]11.0029037055735[/C][C]-0.00290370557348264[/C][/ROW]
[ROW][C]60[/C][C]10[/C][C]11.7672156589185[/C][C]-1.76721565891855[/C][/ROW]
[ROW][C]61[/C][C]7[/C][C]9.29516035087435[/C][C]-2.29516035087435[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]11.4791922620481[/C][C]0.520807737951857[/C][/ROW]
[ROW][C]63[/C][C]14[/C][C]11.813914343014[/C][C]2.18608565698597[/C][/ROW]
[ROW][C]64[/C][C]11[/C][C]10.7317333154751[/C][C]0.268266684524945[/C][/ROW]
[ROW][C]65[/C][C]12[/C][C]11.6801418095975[/C][C]0.319858190402493[/C][/ROW]
[ROW][C]66[/C][C]13[/C][C]12.1666317563444[/C][C]0.833368243655612[/C][/ROW]
[ROW][C]67[/C][C]14[/C][C]12.8820901255509[/C][C]1.11790987444909[/C][/ROW]
[ROW][C]68[/C][C]11[/C][C]12.5185170738355[/C][C]-1.51851707383551[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]9.64369610080839[/C][C]2.35630389919161[/C][/ROW]
[ROW][C]70[/C][C]12[/C][C]11.5738536547622[/C][C]0.426146345237827[/C][/ROW]
[ROW][C]71[/C][C]8[/C][C]8.23475708095421[/C][C]-0.234757080954205[/C][/ROW]
[ROW][C]72[/C][C]11[/C][C]10.786628055965[/C][C]0.213371944034975[/C][/ROW]
[ROW][C]73[/C][C]14[/C][C]12.9696783051343[/C][C]1.03032169486574[/C][/ROW]
[ROW][C]74[/C][C]14[/C][C]12.7261986923163[/C][C]1.27380130768372[/C][/ROW]
[ROW][C]75[/C][C]12[/C][C]11.361721054936[/C][C]0.638278945063967[/C][/ROW]
[ROW][C]76[/C][C]9[/C][C]12.1641120922043[/C][C]-3.16411209220434[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.7683385021824[/C][C]1.23166149781764[/C][/ROW]
[ROW][C]78[/C][C]11[/C][C]11.6983156734265[/C][C]-0.698315673426476[/C][/ROW]
[ROW][C]79[/C][C]12[/C][C]9.8784749752844[/C][C]2.1215250247156[/C][/ROW]
[ROW][C]80[/C][C]12[/C][C]11.321954402712[/C][C]0.678045597288028[/C][/ROW]
[ROW][C]81[/C][C]12[/C][C]11.5760085548052[/C][C]0.423991445194766[/C][/ROW]
[ROW][C]82[/C][C]12[/C][C]11.813023467494[/C][C]0.186976532505969[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]10.8934873735966[/C][C]1.10651262640339[/C][/ROW]
[ROW][C]84[/C][C]11[/C][C]11.2323780733894[/C][C]-0.232378073389362[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]11.7024842922533[/C][C]-1.70248429225335[/C][/ROW]
[ROW][C]86[/C][C]9[/C][C]10.4881125213978[/C][C]-1.48811252139782[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]11.7755528965723[/C][C]0.224447103427716[/C][/ROW]
[ROW][C]88[/C][C]12[/C][C]11.7889496285729[/C][C]0.21105037142711[/C][/ROW]
[ROW][C]89[/C][C]12[/C][C]11.2674617765242[/C][C]0.732538223475762[/C][/ROW]
[ROW][C]90[/C][C]9[/C][C]9.63414183715167[/C][C]-0.634141837151667[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]12.2435042153932[/C][C]2.75649578460679[/C][/ROW]
[ROW][C]92[/C][C]12[/C][C]11.9104482732526[/C][C]0.0895517267473835[/C][/ROW]
[ROW][C]93[/C][C]12[/C][C]11.095327796666[/C][C]0.904672203334031[/C][/ROW]
[ROW][C]94[/C][C]12[/C][C]10.0982068996642[/C][C]1.90179310033578[/C][/ROW]
[ROW][C]95[/C][C]10[/C][C]11.7265581311745[/C][C]-1.72655813117449[/C][/ROW]
[ROW][C]96[/C][C]13[/C][C]11.7650607588755[/C][C]1.23493924112451[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]11.6759731907706[/C][C]-2.67597319077064[/C][/ROW]
[ROW][C]98[/C][C]12[/C][C]11.4561000851316[/C][C]0.543899914868442[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]10.494577221527[/C][C]-0.494577221527006[/C][/ROW]
[ROW][C]100[/C][C]14[/C][C]11.7307267500014[/C][C]2.26927324999864[/C][/ROW]
[ROW][C]101[/C][C]11[/C][C]11.5258909461436[/C][C]-0.525890946143627[/C][/ROW]
[ROW][C]102[/C][C]15[/C][C]13.9800547528774[/C][C]1.01994524712264[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]10.8834187796776[/C][C]0.116581220322435[/C][/ROW]
[ROW][C]104[/C][C]11[/C][C]11.888246971856[/C][C]-0.888246971856031[/C][/ROW]
[ROW][C]105[/C][C]12[/C][C]9.79828615931471[/C][C]2.20171384068529[/C][/ROW]
[ROW][C]106[/C][C]12[/C][C]12.262800922486[/C][C]-0.262800922485985[/C][/ROW]
[ROW][C]107[/C][C]12[/C][C]11.5430327531933[/C][C]0.456967246806655[/C][/ROW]
[ROW][C]108[/C][C]11[/C][C]11.557320360714[/C][C]-0.55732036071395[/C][/ROW]
[ROW][C]109[/C][C]7[/C][C]9.68482096029469[/C][C]-2.68482096029469[/C][/ROW]
[ROW][C]110[/C][C]12[/C][C]11.8062326168819[/C][C]0.19376738311814[/C][/ROW]
[ROW][C]111[/C][C]14[/C][C]11.8049685923588[/C][C]2.1950314076412[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]12.5157322313154[/C][C]-1.51573223131544[/C][/ROW]
[ROW][C]113[/C][C]10[/C][C]9.49680919790977[/C][C]0.503190802090232[/C][/ROW]
[ROW][C]114[/C][C]13[/C][C]12.5111614981863[/C][C]0.488838501813667[/C][/ROW]
[ROW][C]115[/C][C]13[/C][C]10.8270032211906[/C][C]2.17299677880942[/C][/ROW]
[ROW][C]116[/C][C]8[/C][C]10.8137476704492[/C][C]-2.81374767044923[/C][/ROW]
[ROW][C]117[/C][C]11[/C][C]10.1578787719826[/C][C]0.842121228017443[/C][/ROW]
[ROW][C]118[/C][C]12[/C][C]11.7579875457448[/C][C]0.242012454255191[/C][/ROW]
[ROW][C]119[/C][C]11[/C][C]9.98559522595896[/C][C]1.01440477404104[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]11.6315705879775[/C][C]1.36842941202253[/C][/ROW]
[ROW][C]121[/C][C]12[/C][C]10.1799388921199[/C][C]1.82006110788011[/C][/ROW]
[ROW][C]122[/C][C]14[/C][C]11.810868567451[/C][C]2.18913143254903[/C][/ROW]
[ROW][C]123[/C][C]13[/C][C]11.106287266105[/C][C]1.89371273389499[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]11.7867947285298[/C][C]3.21320527147017[/C][/ROW]
[ROW][C]125[/C][C]10[/C][C]10.8335331387598[/C][C]-0.833533138759768[/C][/ROW]
[ROW][C]126[/C][C]11[/C][C]12.271605491882[/C][C]-1.27160549188196[/C][/ROW]
[ROW][C]127[/C][C]9[/C][C]11.2314871978694[/C][C]-2.23148719786936[/C][/ROW]
[ROW][C]128[/C][C]11[/C][C]9.52622489369628[/C][C]1.47377510630372[/C][/ROW]
[ROW][C]129[/C][C]10[/C][C]11.5343693650566[/C][C]-1.53436936505662[/C][/ROW]
[ROW][C]130[/C][C]11[/C][C]8.31532244218158[/C][C]2.68467755781842[/C][/ROW]
[ROW][C]131[/C][C]8[/C][C]11.7467457137873[/C][C]-3.74674571378726[/C][/ROW]
[ROW][C]132[/C][C]11[/C][C]9.32003088257631[/C][C]1.67996911742369[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]10.4770118706995[/C][C]1.52298812930047[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]11.1015101342766[/C][C]0.898489865723354[/C][/ROW]
[ROW][C]135[/C][C]9[/C][C]9.69561688998552[/C][C]-0.695616889985519[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]11.0001402925289[/C][C]-0.000140292528927792[/C][/ROW]
[ROW][C]137[/C][C]10[/C][C]9.13021933593049[/C][C]0.86978066406951[/C][/ROW]
[ROW][C]138[/C][C]8[/C][C]9.55058109513593[/C][C]-1.55058109513593[/C][/ROW]
[ROW][C]139[/C][C]9[/C][C]8.85962010862831[/C][C]0.140379891371691[/C][/ROW]
[ROW][C]140[/C][C]8[/C][C]11.7797215153992[/C][C]-3.77972151539915[/C][/ROW]
[ROW][C]141[/C][C]9[/C][C]11.0837010345447[/C][C]-2.08370103454467[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]12.3870191922458[/C][C]2.61298080775422[/C][/ROW]
[ROW][C]143[/C][C]11[/C][C]11.2858890375725[/C][C]-0.285889037572539[/C][/ROW]
[ROW][C]144[/C][C]8[/C][C]8.30746092117616[/C][C]-0.307460921176156[/C][/ROW]
[ROW][C]145[/C][C]13[/C][C]12.6948280574267[/C][C]0.305171942573273[/C][/ROW]
[ROW][C]146[/C][C]12[/C][C]9.93055930420974[/C][C]2.06944069579026[/C][/ROW]
[ROW][C]147[/C][C]12[/C][C]11.4947438940918[/C][C]0.50525610590819[/C][/ROW]
[ROW][C]148[/C][C]9[/C][C]9.86456391302148[/C][C]-0.864563913021476[/C][/ROW]
[ROW][C]149[/C][C]7[/C][C]8.52882163417603[/C][C]-1.52882163417603[/C][/ROW]
[ROW][C]150[/C][C]13[/C][C]11.1910650341237[/C][C]1.80893496587626[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]11.6023784750287[/C][C]-2.60237847502869[/C][/ROW]
[ROW][C]152[/C][C]6[/C][C]11.8889966661168[/C][C]-5.88899666611678[/C][/ROW]
[ROW][C]153[/C][C]8[/C][C]10.6600229184184[/C][C]-2.66002291841836[/C][/ROW]
[ROW][C]154[/C][C]8[/C][C]8.42751057210908[/C][C]-0.427510572109084[/C][/ROW]
[ROW][C]155[/C][C]6[/C][C]10.2198467256032[/C][C]-4.2198467256032[/C][/ROW]
[ROW][C]156[/C][C]9[/C][C]11.2314871978694[/C][C]-2.23148719786936[/C][/ROW]
[ROW][C]157[/C][C]11[/C][C]11.7226718748661[/C][C]-0.722671874866123[/C][/ROW]
[ROW][C]158[/C][C]8[/C][C]9.71503334886203[/C][C]-1.71503334886203[/C][/ROW]
[ROW][C]159[/C][C]10[/C][C]9.36280814160856[/C][C]0.637191858391436[/C][/ROW]
[ROW][C]160[/C][C]8[/C][C]8.72609476897542[/C][C]-0.726094768975421[/C][/ROW]
[ROW][C]161[/C][C]14[/C][C]11.5223426700835[/C][C]2.47765732991654[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]10.9205066018859[/C][C]-0.92050660188593[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]7.84888234164735[/C][C]0.151117658352648[/C][/ROW]
[ROW][C]164[/C][C]11[/C][C]10.0045306138139[/C][C]0.99546938618612[/C][/ROW]
[ROW][C]165[/C][C]12[/C][C]8.47801655579358[/C][C]3.52198344420642[/C][/ROW]
[ROW][C]166[/C][C]12[/C][C]9.81055044834119[/C][C]2.18944955165881[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]11.2818436153885[/C][C]0.718156384611469[/C][/ROW]
[ROW][C]168[/C][C]5[/C][C]8.79560326746898[/C][C]-3.79560326746898[/C][/ROW]
[ROW][C]169[/C][C]12[/C][C]11.3381049480468[/C][C]0.661895051953185[/C][/ROW]
[ROW][C]170[/C][C]10[/C][C]8.85817973409112[/C][C]1.14182026590888[/C][/ROW]
[ROW][C]171[/C][C]7[/C][C]7.33447608763545[/C][C]-0.334476087635451[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]8.92952536705084[/C][C]3.07047463294917[/C][/ROW]
[ROW][C]173[/C][C]11[/C][C]10.5831622891347[/C][C]0.416837710865259[/C][/ROW]
[ROW][C]174[/C][C]8[/C][C]9.10165934690911[/C][C]-1.1016593469091[/C][/ROW]
[ROW][C]175[/C][C]9[/C][C]8.85494898930433[/C][C]0.145051010695672[/C][/ROW]
[ROW][C]176[/C][C]10[/C][C]10.1635586090961[/C][C]-0.163558609096123[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]9.16765473809737[/C][C]-0.167654738097367[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.3319226104361[/C][C]0.668077389563862[/C][/ROW]
[ROW][C]179[/C][C]6[/C][C]8.23224086167328[/C][C]-2.23224086167328[/C][/ROW]
[ROW][C]180[/C][C]15[/C][C]12.7919739455259[/C][C]2.20802605447407[/C][/ROW]
[ROW][C]181[/C][C]12[/C][C]10.4214734484532[/C][C]1.5785265515468[/C][/ROW]
[ROW][C]182[/C][C]12[/C][C]6.92572930939062[/C][C]5.07427069060938[/C][/ROW]
[ROW][C]183[/C][C]12[/C][C]11.394031745316[/C][C]0.605968254683964[/C][/ROW]
[ROW][C]184[/C][C]11[/C][C]11.5913838368348[/C][C]-0.591383836834778[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]8.9719142510602[/C][C]-1.9719142510602[/C][/ROW]
[ROW][C]186[/C][C]7[/C][C]8.27631731398347[/C][C]-1.27631731398347[/C][/ROW]
[ROW][C]187[/C][C]5[/C][C]8.43631858636419[/C][C]-3.43631858636419[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]10.3175187251254[/C][C]1.68248127487458[/C][/ROW]
[ROW][C]189[/C][C]12[/C][C]11.402836314712[/C][C]0.597163685287984[/C][/ROW]
[ROW][C]190[/C][C]3[/C][C]9.11341550912896[/C][C]-6.11341550912896[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]11.3967951583606[/C][C]-0.396795158360591[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]9.63640274969911[/C][C]0.363597250300891[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]10.5990400716614[/C][C]1.4009599283386[/C][/ROW]
[ROW][C]194[/C][C]9[/C][C]11.2366527047206[/C][C]-2.23665270472061[/C][/ROW]
[ROW][C]195[/C][C]12[/C][C]11.3960454640998[/C][C]0.603954535900155[/C][/ROW]
[ROW][C]196[/C][C]9[/C][C]10.0192855530767[/C][C]-1.01928555307673[/C][/ROW]
[ROW][C]197[/C][C]12[/C][C]11.0715835530869[/C][C]0.928416446913054[/C][/ROW]
[ROW][C]198[/C][C]10[/C][C]10.0019083820286[/C][C]-0.0019083820285777[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]8.23350488619635[/C][C]0.766495113803653[/C][/ROW]
[ROW][C]200[/C][C]12[/C][C]8.84155225730372[/C][C]3.15844774269628[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]10.7665464858566[/C][C]-2.76654648585663[/C][/ROW]
[ROW][C]202[/C][C]11[/C][C]10.8020033379946[/C][C]0.197996662005431[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]11.3695343626171[/C][C]-0.369534362617138[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]11.0878344846167[/C][C]0.912165515383335[/C][/ROW]
[ROW][C]205[/C][C]10[/C][C]8.29205391525087[/C][C]1.70794608474913[/C][/ROW]
[ROW][C]206[/C][C]10[/C][C]10.4806779890293[/C][C]-0.480677989029288[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]9.14142599913316[/C][C]2.85857400086684[/C][/ROW]
[ROW][C]208[/C][C]12[/C][C]9.01377702364655[/C][C]2.98622297635345[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]10.6987609587223[/C][C]0.301239041277705[/C][/ROW]
[ROW][C]210[/C][C]8[/C][C]10.563865582042[/C][C]-2.56386558204196[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]11.3480827554813[/C][C]0.651917244518701[/C][/ROW]
[ROW][C]212[/C][C]10[/C][C]9.82710517186493[/C][C]0.172894828135068[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]11.8674157074869[/C][C]-0.867415707486889[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]10.1487566713132[/C][C]-0.148756671313203[/C][/ROW]
[ROW][C]215[/C][C]8[/C][C]9.48088786172217[/C][C]-1.48088786172217[/C][/ROW]
[ROW][C]216[/C][C]12[/C][C]10.8485608408308[/C][C]1.1514391591692[/C][/ROW]
[ROW][C]217[/C][C]12[/C][C]9.41817021384077[/C][C]2.58182978615923[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]9.95338094837302[/C][C]0.0466190516269781[/C][/ROW]
[ROW][C]219[/C][C]12[/C][C]10.7632687425498[/C][C]1.23673125745024[/C][/ROW]
[ROW][C]220[/C][C]9[/C][C]8.86314504569881[/C][C]0.136854954301186[/C][/ROW]
[ROW][C]221[/C][C]6[/C][C]6.98802341349426[/C][C]-0.988023413494256[/C][/ROW]
[ROW][C]222[/C][C]10[/C][C]9.92148420206046[/C][C]0.0785157979395421[/C][/ROW]
[ROW][C]223[/C][C]9[/C][C]10.0072940268584[/C][C]-1.00729402685843[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]8.363999676306[/C][C]0.636000323694[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]8.93279472545163[/C][C]0.0672052745483697[/C][/ROW]
[ROW][C]226[/C][C]6[/C][C]9.57026617725159[/C][C]-3.57026617725159[/C][/ROW]
[ROW][C]227[/C][C]10[/C][C]7.94260586032131[/C][C]2.05739413967869[/C][/ROW]
[ROW][C]228[/C][C]6[/C][C]11.0879756658759[/C][C]-5.08797566587592[/C][/ROW]
[ROW][C]229[/C][C]14[/C][C]12.2963500683445[/C][C]1.7036499316555[/C][/ROW]
[ROW][C]230[/C][C]10[/C][C]9.60080471630192[/C][C]0.399195283698082[/C][/ROW]
[ROW][C]231[/C][C]10[/C][C]8.26151537620055[/C][C]1.73848462379945[/C][/ROW]
[ROW][C]232[/C][C]6[/C][C]4.38341259803653[/C][C]1.61658740196347[/C][/ROW]
[ROW][C]233[/C][C]12[/C][C]9.24060359063257[/C][C]2.75939640936743[/C][/ROW]
[ROW][C]234[/C][C]12[/C][C]11.3392781860853[/C][C]0.660721813914681[/C][/ROW]
[ROW][C]235[/C][C]7[/C][C]7.67656018200976[/C][C]-0.676560182009757[/C][/ROW]
[ROW][C]236[/C][C]8[/C][C]8.94342804440768[/C][C]-0.943428044407682[/C][/ROW]
[ROW][C]237[/C][C]11[/C][C]8.94679997045373[/C][C]2.05320002954627[/C][/ROW]
[ROW][C]238[/C][C]3[/C][C]7.73806080388816[/C][C]-4.73806080388816[/C][/ROW]
[ROW][C]239[/C][C]6[/C][C]9.40908328192629[/C][C]-3.40908328192629[/C][/ROW]
[ROW][C]240[/C][C]8[/C][C]8.9990724791584[/C][C]-0.999072479158398[/C][/ROW]
[ROW][C]241[/C][C]9[/C][C]10.035818847125[/C][C]-1.03581884712495[/C][/ROW]
[ROW][C]242[/C][C]9[/C][C]7.95043715261881[/C][C]1.04956284738119[/C][/ROW]
[ROW][C]243[/C][C]8[/C][C]9.03889791106323[/C][C]-1.03889791106323[/C][/ROW]
[ROW][C]244[/C][C]9[/C][C]8.9698567443119[/C][C]0.0301432556880949[/C][/ROW]
[ROW][C]245[/C][C]7[/C][C]8.36451400656832[/C][C]-1.36451400656832[/C][/ROW]
[ROW][C]246[/C][C]7[/C][C]7.76012092402549[/C][C]-0.760120924025494[/C][/ROW]
[ROW][C]247[/C][C]6[/C][C]9.10292337143217[/C][C]-3.10292337143217[/C][/ROW]
[ROW][C]248[/C][C]9[/C][C]11.2833513888161[/C][C]-2.2833513888161[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]8.83522873843379[/C][C]1.16477126156621[/C][/ROW]
[ROW][C]250[/C][C]11[/C][C]9.96968227467744[/C][C]1.03031772532256[/C][/ROW]
[ROW][C]251[/C][C]12[/C][C]11.1757992094577[/C][C]0.824200790542298[/C][/ROW]
[ROW][C]252[/C][C]8[/C][C]10.2515233339372[/C][C]-2.25152333393716[/C][/ROW]
[ROW][C]253[/C][C]11[/C][C]9.61883739887163[/C][C]1.38116260112837[/C][/ROW]
[ROW][C]254[/C][C]3[/C][C]4.66726737608006[/C][C]-1.66726737608006[/C][/ROW]
[ROW][C]255[/C][C]11[/C][C]10.7577419164607[/C][C]0.242258083539349[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]8.42217216010284[/C][C]3.57782783989716[/C][/ROW]
[ROW][C]257[/C][C]7[/C][C]8.3666219080913[/C][C]-1.3666219080913[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]9.99342996311559[/C][C]-0.993429963115588[/C][/ROW]
[ROW][C]259[/C][C]12[/C][C]10.5247074428194[/C][C]1.4752925571806[/C][/ROW]
[ROW][C]260[/C][C]8[/C][C]10.2270259512383[/C][C]-2.22702595123826[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]9.43943685175288[/C][C]1.56056314824712[/C][/ROW]
[ROW][C]262[/C][C]8[/C][C]8.26769771381122[/C][C]-0.267697713811224[/C][/ROW]
[ROW][C]263[/C][C]10[/C][C]10.7184425959788[/C][C]-0.718442595978832[/C][/ROW]
[ROW][C]264[/C][C]8[/C][C]8.31959707351283[/C][C]-0.319597073512829[/C][/ROW]
[ROW][C]265[/C][C]7[/C][C]9.45779568480558[/C][C]-2.45779568480558[/C][/ROW]
[ROW][C]266[/C][C]8[/C][C]9.55930670781255[/C][C]-1.55930670781255[/C][/ROW]
[ROW][C]267[/C][C]10[/C][C]11.2770278699462[/C][C]-1.27702786994617[/C][/ROW]
[ROW][C]268[/C][C]8[/C][C]9.56229370369484[/C][C]-1.56229370369484[/C][/ROW]
[ROW][C]269[/C][C]12[/C][C]11.354265093092[/C][C]0.645734906908024[/C][/ROW]
[ROW][C]270[/C][C]14[/C][C]11.064369158697[/C][C]2.93563084130298[/C][/ROW]
[ROW][C]271[/C][C]7[/C][C]9.07490449652189[/C][C]-2.07490449652189[/C][/ROW]
[ROW][C]272[/C][C]6[/C][C]6.26601794258007[/C][C]-0.266017942580071[/C][/ROW]
[ROW][C]273[/C][C]11[/C][C]11.0441815760842[/C][C]-0.0441815760842398[/C][/ROW]
[ROW][C]274[/C][C]4[/C][C]5.40407478477717[/C][C]-1.40407478477717[/C][/ROW]
[ROW][C]275[/C][C]9[/C][C]11.1638076832394[/C][C]-2.16380768323941[/C][/ROW]
[ROW][C]276[/C][C]5[/C][C]4.25160999543933[/C][C]0.748390004560673[/C][/ROW]
[ROW][C]277[/C][C]9[/C][C]8.84342479482828[/C][C]0.156575205171722[/C][/ROW]
[ROW][C]278[/C][C]11[/C][C]10.4612401006773[/C][C]0.538759899322743[/C][/ROW]
[ROW][C]279[/C][C]12[/C][C]10.2192030438468[/C][C]1.78079695615316[/C][/ROW]
[ROW][C]280[/C][C]9[/C][C]8.37004083265743[/C][C]0.629959167342575[/C][/ROW]
[ROW][C]281[/C][C]12[/C][C]10.9353737571089[/C][C]1.06462624289114[/C][/ROW]
[ROW][C]282[/C][C]10[/C][C]10.7867340684694[/C][C]-0.786734068469408[/C][/ROW]
[ROW][C]283[/C][C]9[/C][C]8.86127250817426[/C][C]0.138727491825742[/C][/ROW]
[ROW][C]284[/C][C]6[/C][C]5.80078624883922[/C][C]0.199213751160781[/C][/ROW]
[ROW][C]285[/C][C]10[/C][C]11.1433377381081[/C][C]-1.14333773810813[/C][/ROW]
[ROW][C]286[/C][C]9[/C][C]7.79051828181657[/C][C]1.20948171818344[/C][/ROW]
[ROW][C]287[/C][C]13[/C][C]10.8966177321885[/C][C]2.10338226781147[/C][/ROW]
[ROW][C]288[/C][C]12[/C][C]10.2437004265457[/C][C]1.75629957345426[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197780&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197780&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11210.12490297037071.87509702962934
21111.6109594615869-0.610959461586933
31513.50896687200881.49103312799118
4611.0093684057027-5.00936840570267
51310.72250520230132.27749479769868
6109.948882734204040.0511172657959643
71213.2649813138346-1.2649813138346
81411.26366630670042.73633369329957
91210.65636862985381.3436313701462
10911.2635251254412-2.26352512544118
111011.3697759300713-1.36977593007127
121211.69035158477580.309648415224199
131211.53080925923120.469190740768758
141111.7752705340538-0.775270534053779
151512.35961721524312.64038278475692
161210.97793899113231.02206100886766
171010.9005605867273-0.900560586727282
181213.9688129209198-1.96881292091981
191112.6489614691705-1.64896146917047
201211.72192218060540.278077819394624
211111.4889347054842-0.488934705484195
221211.75625618947950.243743810520494
231313.4354747239121-0.435474723912122
241111.8624855646341-0.862485564634071
251211.92822002277930.07177997722065
261312.21357418934440.786425810655623
271011.502798769227-1.50279876922704
281411.30127805888142.69872194111857
291211.74210976321820.257890236781847
301010.4313452433833-0.431345243383298
311211.16347808789730.836521912102708
3289.38691714928457-1.38691714928458
331010.5275144095249-0.527514409524896
341211.82627901823540.173720981764615
351210.33101584332091.66898415667909
3678.22304791725442-1.22304791725442
3798.277710690000580.722289309999422
381210.36848641424271.63151358575735
391011.7282456994753-1.72824569947531
401011.4946027128326-1.49460271283256
411011.4255615460812-1.42556154608123
421210.62508039654271.37491960345727
431513.59259283146461.40740716853544
441010.4090027607275-0.40900276072746
451010.4593641182936-0.459364118293572
46129.037430480741022.96256951925899
471310.72728233412972.27271766587032
481111.219122522648-0.219122522648008
491111.8059502543634-0.805950254363355
501210.33579297514931.66420702485073
511411.86805938924332.13194061075675
521010.3575269448036-0.357526944803612
53129.363169460846422.63683053915358
541311.87789601541851.12210398458152
5557.68769600146292-2.68769600146292
56610.6431130791124-4.64311307911245
571211.67784572829520.322154271704806
581211.81948816762320.180511832376786
591111.0029037055735-0.00290370557348264
601011.7672156589185-1.76721565891855
6179.29516035087435-2.29516035087435
621211.47919226204810.520807737951857
631411.8139143430142.18608565698597
641110.73173331547510.268266684524945
651211.68014180959750.319858190402493
661312.16663175634440.833368243655612
671412.88209012555091.11790987444909
681112.5185170738355-1.51851707383551
69129.643696100808392.35630389919161
701211.57385365476220.426146345237827
7188.23475708095421-0.234757080954205
721110.7866280559650.213371944034975
731412.96967830513431.03032169486574
741412.72619869231631.27380130768372
751211.3617210549360.638278945063967
76912.1641120922043-3.16411209220434
771311.76833850218241.23166149781764
781111.6983156734265-0.698315673426476
79129.87847497528442.1215250247156
801211.3219544027120.678045597288028
811211.57600855480520.423991445194766
821211.8130234674940.186976532505969
831210.89348737359661.10651262640339
841111.2323780733894-0.232378073389362
851011.7024842922533-1.70248429225335
86910.4881125213978-1.48811252139782
871211.77555289657230.224447103427716
881211.78894962857290.21105037142711
891211.26746177652420.732538223475762
9099.63414183715167-0.634141837151667
911512.24350421539322.75649578460679
921211.91044827325260.0895517267473835
931211.0953277966660.904672203334031
941210.09820689966421.90179310033578
951011.7265581311745-1.72655813117449
961311.76506075887551.23493924112451
97911.6759731907706-2.67597319077064
981211.45610008513160.543899914868442
991010.494577221527-0.494577221527006
1001411.73072675000142.26927324999864
1011111.5258909461436-0.525890946143627
1021513.98005475287741.01994524712264
1031110.88341877967760.116581220322435
1041111.888246971856-0.888246971856031
105129.798286159314712.20171384068529
1061212.262800922486-0.262800922485985
1071211.54303275319330.456967246806655
1081111.557320360714-0.55732036071395
10979.68482096029469-2.68482096029469
1101211.80623261688190.19376738311814
1111411.80496859235882.1950314076412
1121112.5157322313154-1.51573223131544
113109.496809197909770.503190802090232
1141312.51116149818630.488838501813667
1151310.82700322119062.17299677880942
116810.8137476704492-2.81374767044923
1171110.15787877198260.842121228017443
1181211.75798754574480.242012454255191
119119.985595225958961.01440477404104
1201311.63157058797751.36842941202253
1211210.17993889211991.82006110788011
1221411.8108685674512.18913143254903
1231311.1062872661051.89371273389499
1241511.78679472852983.21320527147017
1251010.8335331387598-0.833533138759768
1261112.271605491882-1.27160549188196
127911.2314871978694-2.23148719786936
128119.526224893696281.47377510630372
1291011.5343693650566-1.53436936505662
130118.315322442181582.68467755781842
131811.7467457137873-3.74674571378726
132119.320030882576311.67996911742369
1331210.47701187069951.52298812930047
1341211.10151013427660.898489865723354
13599.69561688998552-0.695616889985519
1361111.0001402925289-0.000140292528927792
137109.130219335930490.86978066406951
13889.55058109513593-1.55058109513593
13998.859620108628310.140379891371691
140811.7797215153992-3.77972151539915
141911.0837010345447-2.08370103454467
1421512.38701919224582.61298080775422
1431111.2858890375725-0.285889037572539
14488.30746092117616-0.307460921176156
1451312.69482805742670.305171942573273
146129.930559304209742.06944069579026
1471211.49474389409180.50525610590819
14899.86456391302148-0.864563913021476
14978.52882163417603-1.52882163417603
1501311.19106503412371.80893496587626
151911.6023784750287-2.60237847502869
152611.8889966661168-5.88899666611678
153810.6600229184184-2.66002291841836
15488.42751057210908-0.427510572109084
155610.2198467256032-4.2198467256032
156911.2314871978694-2.23148719786936
1571111.7226718748661-0.722671874866123
15889.71503334886203-1.71503334886203
159109.362808141608560.637191858391436
16088.72609476897542-0.726094768975421
1611411.52234267008352.47765732991654
1621010.9205066018859-0.92050660188593
16387.848882341647350.151117658352648
1641110.00453061381390.99546938618612
165128.478016555793583.52198344420642
166129.810550448341192.18944955165881
1671211.28184361538850.718156384611469
16858.79560326746898-3.79560326746898
1691211.33810494804680.661895051953185
170108.858179734091121.14182026590888
17177.33447608763545-0.334476087635451
172128.929525367050843.07047463294917
1731110.58316228913470.416837710865259
17489.10165934690911-1.1016593469091
17598.854948989304330.145051010695672
1761010.1635586090961-0.163558609096123
17799.16765473809737-0.167654738097367
1781211.33192261043610.668077389563862
17968.23224086167328-2.23224086167328
1801512.79197394552592.20802605447407
1811210.42147344845321.5785265515468
182126.925729309390625.07427069060938
1831211.3940317453160.605968254683964
1841111.5913838368348-0.591383836834778
18578.9719142510602-1.9719142510602
18678.27631731398347-1.27631731398347
18758.43631858636419-3.43631858636419
1881210.31751872512541.68248127487458
1891211.4028363147120.597163685287984
19039.11341550912896-6.11341550912896
1911111.3967951583606-0.396795158360591
192109.636402749699110.363597250300891
1931210.59904007166141.4009599283386
194911.2366527047206-2.23665270472061
1951211.39604546409980.603954535900155
196910.0192855530767-1.01928555307673
1971211.07158355308690.928416446913054
1981010.0019083820286-0.0019083820285777
19998.233504886196350.766495113803653
200128.841552257303723.15844774269628
201810.7665464858566-2.76654648585663
2021110.80200333799460.197996662005431
2031111.3695343626171-0.369534362617138
2041211.08783448461670.912165515383335
205108.292053915250871.70794608474913
2061010.4806779890293-0.480677989029288
207129.141425999133162.85857400086684
208129.013777023646552.98622297635345
2091110.69876095872230.301239041277705
210810.563865582042-2.56386558204196
2111211.34808275548130.651917244518701
212109.827105171864930.172894828135068
2131111.8674157074869-0.867415707486889
2141010.1487566713132-0.148756671313203
21589.48088786172217-1.48088786172217
2161210.84856084083081.1514391591692
217129.418170213840772.58182978615923
218109.953380948373020.0466190516269781
2191210.76326874254981.23673125745024
22098.863145045698810.136854954301186
22166.98802341349426-0.988023413494256
222109.921484202060460.0785157979395421
223910.0072940268584-1.00729402685843
22498.3639996763060.636000323694
22598.932794725451630.0672052745483697
22669.57026617725159-3.57026617725159
227107.942605860321312.05739413967869
228611.0879756658759-5.08797566587592
2291412.29635006834451.7036499316555
230109.600804716301920.399195283698082
231108.261515376200551.73848462379945
23264.383412598036531.61658740196347
233129.240603590632572.75939640936743
2341211.33927818608530.660721813914681
23577.67656018200976-0.676560182009757
23688.94342804440768-0.943428044407682
237118.946799970453732.05320002954627
23837.73806080388816-4.73806080388816
23969.40908328192629-3.40908328192629
24088.9990724791584-0.999072479158398
241910.035818847125-1.03581884712495
24297.950437152618811.04956284738119
24389.03889791106323-1.03889791106323
24498.96985674431190.0301432556880949
24578.36451400656832-1.36451400656832
24677.76012092402549-0.760120924025494
24769.10292337143217-3.10292337143217
248911.2833513888161-2.2833513888161
249108.835228738433791.16477126156621
250119.969682274677441.03031772532256
2511211.17579920945770.824200790542298
252810.2515233339372-2.25152333393716
253119.618837398871631.38116260112837
25434.66726737608006-1.66726737608006
2551110.75774191646070.242258083539349
256128.422172160102843.57782783989716
25778.3666219080913-1.3666219080913
25899.99342996311559-0.993429963115588
2591210.52470744281941.4752925571806
260810.2270259512383-2.22702595123826
261119.439436851752881.56056314824712
26288.26769771381122-0.267697713811224
2631010.7184425959788-0.718442595978832
26488.31959707351283-0.319597073512829
26579.45779568480558-2.45779568480558
26689.55930670781255-1.55930670781255
2671011.2770278699462-1.27702786994617
26889.56229370369484-1.56229370369484
2691211.3542650930920.645734906908024
2701411.0643691586972.93563084130298
27179.07490449652189-2.07490449652189
27266.26601794258007-0.266017942580071
2731111.0441815760842-0.0441815760842398
27445.40407478477717-1.40407478477717
275911.1638076832394-2.16380768323941
27654.251609995439330.748390004560673
27798.843424794828280.156575205171722
2781110.46124010067730.538759899322743
2791210.21920304384681.78079695615316
28098.370040832657430.629959167342575
2811210.93537375710891.06462624289114
2821010.7867340684694-0.786734068469408
28398.861272508174260.138727491825742
28465.800786248839220.199213751160781
2851011.1433377381081-1.14333773810813
28697.790518281816571.20948171818344
2871310.89661773218852.10338226781147
2881210.24370042654571.75629957345426







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.728426691490350.54314661701930.27157330850965
110.9321112919614310.1357774160771380.0678887080385691
120.8839275289213580.2321449421572850.116072471078642
130.9079961172925580.1840077654148840.0920038827074422
140.8829186433667750.234162713266450.117081356633225
150.8933724166429650.213255166714070.106627583357035
160.9014442860693590.1971114278612830.0985557139306414
170.8604782306201010.2790435387597980.139521769379899
180.8508823617452920.2982352765094160.149117638254708
190.8008756739698180.3982486520603640.199124326030182
200.7415269555133630.5169460889732740.258473044486637
210.6800453745153510.6399092509692990.31995462548465
220.6119802819082640.7760394361834720.388019718091736
230.5389478376073920.9221043247852170.461052162392608
240.5146597033313840.9706805933372320.485340296668616
250.5131775092673770.9736449814652460.486822490732623
260.4799910107425950.959982021485190.520008989257405
270.421395820416830.8427916408336610.57860417958317
280.4256903631724630.8513807263449260.574309636827537
290.3650843957596650.730168791519330.634915604240335
300.3068020408982180.6136040817964370.693197959101782
310.254354709798710.508709419597420.74564529020129
320.248959157202430.497918314404860.75104084279757
330.2174211789772890.4348423579545770.782578821022711
340.1783692346491960.3567384692983930.821630765350804
350.2178678180661760.4357356361323520.782132181933824
360.2012152059909490.4024304119818980.798784794009051
370.1653564090245240.3307128180490480.834643590975476
380.1934594048543620.3869188097087250.806540595145638
390.2068940259398710.4137880518797420.793105974060129
400.1779293028297240.3558586056594470.822070697170276
410.1490263717304350.2980527434608710.850973628269565
420.1266552822212770.2533105644425550.873344717778723
430.1835683547741290.3671367095482580.816431645225871
440.1511762291226870.3023524582453740.848823770877313
450.1286755107567770.2573510215135550.871324489243223
460.1375591112586650.275118222517330.862440888741335
470.1306733439987050.261346687997410.869326656001295
480.1097714784212840.2195429568425680.890228521578716
490.09880390092218420.1976078018443680.901196099077816
500.1031235874683870.2062471749367730.896876412531613
510.1065597216673560.2131194433347110.893440278332644
520.08622554180095880.1724510836019180.913774458199041
530.1044729817361650.2089459634723310.895527018263835
540.08645604446655180.1729120889331040.913543955533448
550.147758140390660.295516280781320.85224185960934
560.4314091035587230.8628182071174450.568590896441277
570.3884689794682150.776937958936430.611531020531785
580.3468699079499770.6937398158999540.653130092050023
590.3069522568588940.6139045137177870.693047743141106
600.3247171257966640.6494342515933270.675282874203336
610.3406006838940710.6812013677881420.659399316105929
620.3115221997932640.6230443995865290.688477800206736
630.3157661192091480.6315322384182960.684233880790852
640.2796193987916860.5592387975833720.720380601208314
650.2461530182877970.4923060365755940.753846981712203
660.2211432899769630.4422865799539270.778856710023037
670.1974206427507070.3948412855014130.802579357249293
680.1761924014729630.3523848029459270.823807598527037
690.171067476201630.342134952403260.82893252379837
700.148045215729030.2960904314580590.85195478427097
710.1272340601787130.2544681203574270.872765939821287
720.108818487982060.217636975964120.89118151201794
730.09329554765377940.1865910953075590.906704452346221
740.08339927451918130.1667985490383630.916600725480819
750.08025017798420490.160500355968410.919749822015795
760.1171976838626380.2343953677252770.882802316137362
770.1037489995732580.2074979991465170.896251000426742
780.08868640869983860.1773728173996770.911313591300161
790.1029247715187840.2058495430375680.897075228481216
800.1004373233466340.2008746466932690.899562676653366
810.08471855475089570.1694371095017910.915281445249104
820.07110771063791820.1422154212758360.928892289362082
830.06551423055196130.1310284611039230.934485769448039
840.05481047517359710.1096209503471940.945189524826403
850.05322570368736660.1064514073747330.946774296312633
860.05546617958889790.1109323591777960.944533820411102
870.04552813345986370.09105626691972740.954471866540136
880.03710958428824320.07421916857648630.962890415711757
890.03063068066272570.06126136132545140.969369319337274
900.02707867232915710.05415734465831430.972921327670843
910.03859103296283650.07718206592567290.961408967037163
920.03249877590621840.06499755181243670.967501224093782
930.02851541255154420.05703082510308840.971484587448456
940.02915940317782690.05831880635565370.970840596822173
950.03035277813630080.06070555627260170.969647221863699
960.02653631062300770.05307262124601540.973463689376992
970.03546015848893480.07092031697786960.964539841511065
980.03017692647754280.06035385295508550.969823073522457
990.02498087740942310.04996175481884630.975019122590577
1000.02841728364069950.0568345672813990.9715827163593
1010.02330876145329390.04661752290658780.976691238546706
1020.01999877595214470.03999755190428950.980001224047855
1030.01626982693499960.03253965386999920.983730173065
1040.01491520976876510.02983041953753020.985084790231235
1050.01714310439454510.03428620878909030.982856895605455
1060.01375871500129180.02751743000258360.986241284998708
1070.01100706005222110.02201412010444220.988992939947779
1080.008928292232750070.01785658446550010.99107170776725
1090.01632971700451740.03265943400903490.983670282995483
1100.01308715893433880.02617431786867760.986912841065661
1110.01447506255544270.02895012511088540.985524937444557
1120.01505946363867030.03011892727734050.98494053636133
1130.01219392356744530.02438784713489050.987806076432555
1140.01004772354472340.02009544708944680.989952276455277
1150.01097868413952210.02195736827904420.989021315860478
1160.0174473667590670.0348947335181340.982552633240933
1170.01469633655813890.02939267311627770.985303663441861
1180.01180980917473840.02361961834947680.988190190825262
1190.01018432015635690.02036864031271380.989815679843643
1200.009407332732732230.01881466546546450.990592667267268
1210.009638999655231650.01927799931046330.990361000344768
1220.01129729647295360.02259459294590720.988702703527046
1230.01215868753213920.02431737506427840.987841312467861
1240.0216553215382770.04331064307655410.978344678461723
1250.01785967769921770.03571935539843530.982140322300782
1260.01577005515550860.03154011031101720.984229944844491
1270.01789476024455310.03578952048910620.982105239755447
1280.01734956644025420.03469913288050840.982650433559746
1290.01588224158520460.03176448317040930.984117758414795
1300.0215316038064480.0430632076128960.978468396193552
1310.04016094046480360.08032188092960710.959839059535196
1320.04063118122994470.08126236245988940.959368818770055
1330.04156733529495430.08313467058990870.958432664705046
1340.03768289106323230.07536578212646460.962317108936768
1350.03223857750092760.06447715500185510.967761422499072
1360.02698296810254630.05396593620509250.973017031897454
1370.02533679559898440.05067359119796880.974663204401016
1380.02425735918107630.04851471836215270.975742640818924
1390.02081257755104850.04162515510209710.979187422448952
1400.03878948378595610.07757896757191220.961210516214044
1410.03910491465395780.07820982930791560.960895085346042
1420.05659346669033130.1131869333806630.943406533309669
1430.04764978088365120.09529956176730250.952350219116349
1440.04029573603196280.08059147206392560.959704263968037
1450.03549572733728920.07099145467457840.964504272662711
1460.04603637665635420.09207275331270830.953963623343646
1470.04405055193075330.08810110386150670.955949448069247
1480.03952912245120330.07905824490240650.960470877548797
1490.03679151102358960.07358302204717910.96320848897641
1500.05132576156711670.1026515231342330.948674238432883
1510.05222282660888130.1044456532177630.947777173391119
1520.166016846319670.332033692639340.83398315368033
1530.176969113704350.3539382274086990.82303088629565
1540.1668293921000090.3336587842000190.833170607899991
1550.2375901080153860.4751802160307720.762409891984614
1560.2350140573339250.470028114667850.764985942666075
1570.2139868598704290.4279737197408580.786013140129571
1580.2030382678539270.4060765357078540.796961732146073
1590.1822089740508320.3644179481016640.817791025949168
1600.16433125478480.32866250956960.8356687452152
1610.1783401695285330.3566803390570660.821659830471467
1620.1665358980628320.3330717961256650.833464101937168
1630.1464959437387550.2929918874775110.853504056261244
1640.1316997567202380.2633995134404770.868300243279762
1650.1808647180226410.3617294360452820.819135281977359
1660.1847546246546220.3695092493092440.815245375345378
1670.1667639651585630.3335279303171260.833236034841437
1680.2725314107532920.5450628215065840.727468589246708
1690.2465796736330250.493159347266050.753420326366975
1700.2272649928730870.4545299857461740.772735007126913
1710.2061484375131110.4122968750262230.793851562486889
1720.2444807323798920.4889614647597830.755519267620108
1730.2186762871456630.4373525742913260.781323712854337
1740.2068461892243120.4136923784486250.793153810775688
1750.1835310970406930.3670621940813850.816468902959307
1760.1630162914120550.3260325828241110.836983708587945
1770.1431490615992370.2862981231984740.856850938400763
1780.1263454311898150.2526908623796310.873654568810185
1790.1406245802309430.2812491604618860.859375419769057
1800.148518312062150.29703662412430.85148168793785
1810.1404455169987510.2808910339975010.859554483001249
1820.3303910130649240.6607820261298470.669608986935076
1830.3066851186908380.6133702373816750.693314881309162
1840.2826068532255810.5652137064511630.717393146774418
1850.2998796370916840.5997592741833680.700120362908316
1860.2887430143267060.5774860286534110.711256985673294
1870.3784823693339360.7569647386678720.621517630666064
1880.3837468175566250.767493635113250.616253182443375
1890.355025911090650.71005182218130.64497408890935
1900.7196950501494070.5606098997011860.280304949850593
1910.6893073297023420.6213853405953150.310692670297658
1920.6592337874368910.6815324251262190.340766212563109
1930.6444709395269230.7110581209461550.355529060473077
1940.6632965447572120.6734069104855750.336703455242788
1950.6376650682669650.724669863466070.362334931733035
1960.6136210568359310.7727578863281380.386378943164069
1970.5907381248536150.8185237502927690.409261875146385
1980.5586687426788090.8826625146423830.441331257321191
1990.5257580670070730.9484838659858530.474241932992927
2000.5976389605448290.8047220789103420.402361039455171
2010.6420669265666910.7158661468666180.357933073433309
2020.6073079881596250.7853840236807510.392692011840375
2030.5712957483264860.8574085033470270.428704251673514
2040.5434232733270140.9131534533459720.456576726672986
2050.5340259015628020.9319481968743960.465974098437198
2060.4987890926296450.9975781852592890.501210907370355
2070.5671493059297470.8657013881405060.432850694070253
2080.6261695959705180.7476608080589640.373830404029482
2090.5957750766510420.8084498466979160.404224923348958
2100.626797660583090.746404678833820.37320233941691
2110.5978607263084050.804278547383190.402139273691595
2120.5594497059377960.8811005881244080.440550294062204
2130.5257770270646380.9484459458707240.474222972935362
2140.4868226528619960.9736453057239920.513177347138004
2150.4750732437683780.9501464875367550.524926756231622
2160.4633299274943220.9266598549886450.536670072505678
2170.501002315087370.997995369825260.49899768491263
2180.4605155671976790.9210311343953580.539484432802321
2190.4480830609586410.8961661219172830.551916939041359
2200.4088725816562820.8177451633125630.591127418343719
2210.3757271789880850.7514543579761690.624272821011915
2220.3377517496016640.6755034992033290.662248250398336
2230.309783299840620.619566599681240.69021670015938
2240.2786927991142010.5573855982284030.721307200885799
2250.2451355868289880.4902711736579750.754864413171012
2260.348811289317030.697622578634060.65118871068297
2270.3942495626042880.7884991252085770.605750437395712
2280.6983737339019050.603252532196190.301626266098095
2290.680000357306570.639999285386860.31999964269343
2300.6401456939832150.719708612033570.359854306016785
2310.6343176022642550.7313647954714910.365682397735745
2320.6314474833690720.7371050332618570.368552516630928
2330.6728825030314570.6542349939370860.327117496968543
2340.6486880123314830.7026239753370340.351311987668517
2350.6088168250208710.7823663499582580.391183174979129
2360.5707385343658530.8585229312682940.429261465634147
2370.6373057739186550.7253884521626910.362694226081345
2380.8518332866287780.2963334267424440.148166713371222
2390.9221310156055480.1557379687889030.0778689843944516
2400.9055628258076090.1888743483847810.0944371741923907
2410.893475459519380.2130490809612390.10652454048062
2420.884291041289910.2314179174201810.11570895871009
2430.8606714422989570.2786571154020850.139328557701043
2440.8308837290899020.3382325418201960.169116270910098
2450.8325447213486380.3349105573027250.167455278651362
2460.8084982312188020.3830035375623970.191501768781198
2470.8625892381056520.2748215237886960.137410761894348
2480.8835311413937540.2329377172124910.116468858606246
2490.8662658338322930.2674683323354150.133734166167707
2500.8433031512324360.3133936975351280.156696848767564
2510.827808694695850.3443826106082990.17219130530415
2520.8219107900910860.3561784198178280.178089209908914
2530.8015425668367220.3969148663265560.198457433163278
2540.7700863298065920.4598273403868170.229913670193408
2550.7221551872904840.5556896254190310.277844812709516
2560.8759561331854360.2480877336291290.124043866814564
2570.8494590410605480.3010819178789030.150540958939452
2580.8263459053595650.347308189280870.173654094640435
2590.8319232235627960.3361535528744070.168076776437204
2600.8486361751552760.3027276496894470.151363824844724
2610.8451625147717950.309674970456410.154837485228205
2620.8013960426719010.3972079146561970.198603957328099
2630.7783104904806830.4433790190386340.221689509519317
2640.7197154163573430.5605691672853140.280284583642657
2650.7723811548040380.4552376903919240.227618845195962
2660.8399226739994830.3201546520010340.160077326000517
2670.9269178104317420.1461643791365150.0730821895682577
2680.9066715179329410.1866569641341190.0933284820670593
2690.8650077801533420.2699844396933160.134992219846658
2700.9266592189458480.1466815621083050.0733407810541523
2710.9045381752660720.1909236494678570.0954618247339284
2720.9434213730557240.1131572538885530.0565786269442763
2730.9020427339345330.1959145321309330.0979572660654666
2740.9030717093493890.1938565813012230.0969282906506113
2750.8899339184209080.2201321631581830.110066081579092
2760.8117620003334170.3764759993331670.188237999666583
2770.7199776512867470.5600446974265060.280022348713253
2780.5555162358081250.8889675283837510.444483764191875

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.72842669149035 & 0.5431466170193 & 0.27157330850965 \tabularnewline
11 & 0.932111291961431 & 0.135777416077138 & 0.0678887080385691 \tabularnewline
12 & 0.883927528921358 & 0.232144942157285 & 0.116072471078642 \tabularnewline
13 & 0.907996117292558 & 0.184007765414884 & 0.0920038827074422 \tabularnewline
14 & 0.882918643366775 & 0.23416271326645 & 0.117081356633225 \tabularnewline
15 & 0.893372416642965 & 0.21325516671407 & 0.106627583357035 \tabularnewline
16 & 0.901444286069359 & 0.197111427861283 & 0.0985557139306414 \tabularnewline
17 & 0.860478230620101 & 0.279043538759798 & 0.139521769379899 \tabularnewline
18 & 0.850882361745292 & 0.298235276509416 & 0.149117638254708 \tabularnewline
19 & 0.800875673969818 & 0.398248652060364 & 0.199124326030182 \tabularnewline
20 & 0.741526955513363 & 0.516946088973274 & 0.258473044486637 \tabularnewline
21 & 0.680045374515351 & 0.639909250969299 & 0.31995462548465 \tabularnewline
22 & 0.611980281908264 & 0.776039436183472 & 0.388019718091736 \tabularnewline
23 & 0.538947837607392 & 0.922104324785217 & 0.461052162392608 \tabularnewline
24 & 0.514659703331384 & 0.970680593337232 & 0.485340296668616 \tabularnewline
25 & 0.513177509267377 & 0.973644981465246 & 0.486822490732623 \tabularnewline
26 & 0.479991010742595 & 0.95998202148519 & 0.520008989257405 \tabularnewline
27 & 0.42139582041683 & 0.842791640833661 & 0.57860417958317 \tabularnewline
28 & 0.425690363172463 & 0.851380726344926 & 0.574309636827537 \tabularnewline
29 & 0.365084395759665 & 0.73016879151933 & 0.634915604240335 \tabularnewline
30 & 0.306802040898218 & 0.613604081796437 & 0.693197959101782 \tabularnewline
31 & 0.25435470979871 & 0.50870941959742 & 0.74564529020129 \tabularnewline
32 & 0.24895915720243 & 0.49791831440486 & 0.75104084279757 \tabularnewline
33 & 0.217421178977289 & 0.434842357954577 & 0.782578821022711 \tabularnewline
34 & 0.178369234649196 & 0.356738469298393 & 0.821630765350804 \tabularnewline
35 & 0.217867818066176 & 0.435735636132352 & 0.782132181933824 \tabularnewline
36 & 0.201215205990949 & 0.402430411981898 & 0.798784794009051 \tabularnewline
37 & 0.165356409024524 & 0.330712818049048 & 0.834643590975476 \tabularnewline
38 & 0.193459404854362 & 0.386918809708725 & 0.806540595145638 \tabularnewline
39 & 0.206894025939871 & 0.413788051879742 & 0.793105974060129 \tabularnewline
40 & 0.177929302829724 & 0.355858605659447 & 0.822070697170276 \tabularnewline
41 & 0.149026371730435 & 0.298052743460871 & 0.850973628269565 \tabularnewline
42 & 0.126655282221277 & 0.253310564442555 & 0.873344717778723 \tabularnewline
43 & 0.183568354774129 & 0.367136709548258 & 0.816431645225871 \tabularnewline
44 & 0.151176229122687 & 0.302352458245374 & 0.848823770877313 \tabularnewline
45 & 0.128675510756777 & 0.257351021513555 & 0.871324489243223 \tabularnewline
46 & 0.137559111258665 & 0.27511822251733 & 0.862440888741335 \tabularnewline
47 & 0.130673343998705 & 0.26134668799741 & 0.869326656001295 \tabularnewline
48 & 0.109771478421284 & 0.219542956842568 & 0.890228521578716 \tabularnewline
49 & 0.0988039009221842 & 0.197607801844368 & 0.901196099077816 \tabularnewline
50 & 0.103123587468387 & 0.206247174936773 & 0.896876412531613 \tabularnewline
51 & 0.106559721667356 & 0.213119443334711 & 0.893440278332644 \tabularnewline
52 & 0.0862255418009588 & 0.172451083601918 & 0.913774458199041 \tabularnewline
53 & 0.104472981736165 & 0.208945963472331 & 0.895527018263835 \tabularnewline
54 & 0.0864560444665518 & 0.172912088933104 & 0.913543955533448 \tabularnewline
55 & 0.14775814039066 & 0.29551628078132 & 0.85224185960934 \tabularnewline
56 & 0.431409103558723 & 0.862818207117445 & 0.568590896441277 \tabularnewline
57 & 0.388468979468215 & 0.77693795893643 & 0.611531020531785 \tabularnewline
58 & 0.346869907949977 & 0.693739815899954 & 0.653130092050023 \tabularnewline
59 & 0.306952256858894 & 0.613904513717787 & 0.693047743141106 \tabularnewline
60 & 0.324717125796664 & 0.649434251593327 & 0.675282874203336 \tabularnewline
61 & 0.340600683894071 & 0.681201367788142 & 0.659399316105929 \tabularnewline
62 & 0.311522199793264 & 0.623044399586529 & 0.688477800206736 \tabularnewline
63 & 0.315766119209148 & 0.631532238418296 & 0.684233880790852 \tabularnewline
64 & 0.279619398791686 & 0.559238797583372 & 0.720380601208314 \tabularnewline
65 & 0.246153018287797 & 0.492306036575594 & 0.753846981712203 \tabularnewline
66 & 0.221143289976963 & 0.442286579953927 & 0.778856710023037 \tabularnewline
67 & 0.197420642750707 & 0.394841285501413 & 0.802579357249293 \tabularnewline
68 & 0.176192401472963 & 0.352384802945927 & 0.823807598527037 \tabularnewline
69 & 0.17106747620163 & 0.34213495240326 & 0.82893252379837 \tabularnewline
70 & 0.14804521572903 & 0.296090431458059 & 0.85195478427097 \tabularnewline
71 & 0.127234060178713 & 0.254468120357427 & 0.872765939821287 \tabularnewline
72 & 0.10881848798206 & 0.21763697596412 & 0.89118151201794 \tabularnewline
73 & 0.0932955476537794 & 0.186591095307559 & 0.906704452346221 \tabularnewline
74 & 0.0833992745191813 & 0.166798549038363 & 0.916600725480819 \tabularnewline
75 & 0.0802501779842049 & 0.16050035596841 & 0.919749822015795 \tabularnewline
76 & 0.117197683862638 & 0.234395367725277 & 0.882802316137362 \tabularnewline
77 & 0.103748999573258 & 0.207497999146517 & 0.896251000426742 \tabularnewline
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80 & 0.100437323346634 & 0.200874646693269 & 0.899562676653366 \tabularnewline
81 & 0.0847185547508957 & 0.169437109501791 & 0.915281445249104 \tabularnewline
82 & 0.0711077106379182 & 0.142215421275836 & 0.928892289362082 \tabularnewline
83 & 0.0655142305519613 & 0.131028461103923 & 0.934485769448039 \tabularnewline
84 & 0.0548104751735971 & 0.109620950347194 & 0.945189524826403 \tabularnewline
85 & 0.0532257036873666 & 0.106451407374733 & 0.946774296312633 \tabularnewline
86 & 0.0554661795888979 & 0.110932359177796 & 0.944533820411102 \tabularnewline
87 & 0.0455281334598637 & 0.0910562669197274 & 0.954471866540136 \tabularnewline
88 & 0.0371095842882432 & 0.0742191685764863 & 0.962890415711757 \tabularnewline
89 & 0.0306306806627257 & 0.0612613613254514 & 0.969369319337274 \tabularnewline
90 & 0.0270786723291571 & 0.0541573446583143 & 0.972921327670843 \tabularnewline
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92 & 0.0324987759062184 & 0.0649975518124367 & 0.967501224093782 \tabularnewline
93 & 0.0285154125515442 & 0.0570308251030884 & 0.971484587448456 \tabularnewline
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100 & 0.0284172836406995 & 0.056834567281399 & 0.9715827163593 \tabularnewline
101 & 0.0233087614532939 & 0.0466175229065878 & 0.976691238546706 \tabularnewline
102 & 0.0199987759521447 & 0.0399975519042895 & 0.980001224047855 \tabularnewline
103 & 0.0162698269349996 & 0.0325396538699992 & 0.983730173065 \tabularnewline
104 & 0.0149152097687651 & 0.0298304195375302 & 0.985084790231235 \tabularnewline
105 & 0.0171431043945451 & 0.0342862087890903 & 0.982856895605455 \tabularnewline
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107 & 0.0110070600522211 & 0.0220141201044422 & 0.988992939947779 \tabularnewline
108 & 0.00892829223275007 & 0.0178565844655001 & 0.99107170776725 \tabularnewline
109 & 0.0163297170045174 & 0.0326594340090349 & 0.983670282995483 \tabularnewline
110 & 0.0130871589343388 & 0.0261743178686776 & 0.986912841065661 \tabularnewline
111 & 0.0144750625554427 & 0.0289501251108854 & 0.985524937444557 \tabularnewline
112 & 0.0150594636386703 & 0.0301189272773405 & 0.98494053636133 \tabularnewline
113 & 0.0121939235674453 & 0.0243878471348905 & 0.987806076432555 \tabularnewline
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116 & 0.017447366759067 & 0.034894733518134 & 0.982552633240933 \tabularnewline
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118 & 0.0118098091747384 & 0.0236196183494768 & 0.988190190825262 \tabularnewline
119 & 0.0101843201563569 & 0.0203686403127138 & 0.989815679843643 \tabularnewline
120 & 0.00940733273273223 & 0.0188146654654645 & 0.990592667267268 \tabularnewline
121 & 0.00963899965523165 & 0.0192779993104633 & 0.990361000344768 \tabularnewline
122 & 0.0112972964729536 & 0.0225945929459072 & 0.988702703527046 \tabularnewline
123 & 0.0121586875321392 & 0.0243173750642784 & 0.987841312467861 \tabularnewline
124 & 0.021655321538277 & 0.0433106430765541 & 0.978344678461723 \tabularnewline
125 & 0.0178596776992177 & 0.0357193553984353 & 0.982140322300782 \tabularnewline
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127 & 0.0178947602445531 & 0.0357895204891062 & 0.982105239755447 \tabularnewline
128 & 0.0173495664402542 & 0.0346991328805084 & 0.982650433559746 \tabularnewline
129 & 0.0158822415852046 & 0.0317644831704093 & 0.984117758414795 \tabularnewline
130 & 0.021531603806448 & 0.043063207612896 & 0.978468396193552 \tabularnewline
131 & 0.0401609404648036 & 0.0803218809296071 & 0.959839059535196 \tabularnewline
132 & 0.0406311812299447 & 0.0812623624598894 & 0.959368818770055 \tabularnewline
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134 & 0.0376828910632323 & 0.0753657821264646 & 0.962317108936768 \tabularnewline
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137 & 0.0253367955989844 & 0.0506735911979688 & 0.974663204401016 \tabularnewline
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152 & 0.16601684631967 & 0.33203369263934 & 0.83398315368033 \tabularnewline
153 & 0.17696911370435 & 0.353938227408699 & 0.82303088629565 \tabularnewline
154 & 0.166829392100009 & 0.333658784200019 & 0.833170607899991 \tabularnewline
155 & 0.237590108015386 & 0.475180216030772 & 0.762409891984614 \tabularnewline
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157 & 0.213986859870429 & 0.427973719740858 & 0.786013140129571 \tabularnewline
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172 & 0.244480732379892 & 0.488961464759783 & 0.755519267620108 \tabularnewline
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177 & 0.143149061599237 & 0.286298123198474 & 0.856850938400763 \tabularnewline
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220 & 0.408872581656282 & 0.817745163312563 & 0.591127418343719 \tabularnewline
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222 & 0.337751749601664 & 0.675503499203329 & 0.662248250398336 \tabularnewline
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229 & 0.68000035730657 & 0.63999928538686 & 0.31999964269343 \tabularnewline
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233 & 0.672882503031457 & 0.654234993937086 & 0.327117496968543 \tabularnewline
234 & 0.648688012331483 & 0.702623975337034 & 0.351311987668517 \tabularnewline
235 & 0.608816825020871 & 0.782366349958258 & 0.391183174979129 \tabularnewline
236 & 0.570738534365853 & 0.858522931268294 & 0.429261465634147 \tabularnewline
237 & 0.637305773918655 & 0.725388452162691 & 0.362694226081345 \tabularnewline
238 & 0.851833286628778 & 0.296333426742444 & 0.148166713371222 \tabularnewline
239 & 0.922131015605548 & 0.155737968788903 & 0.0778689843944516 \tabularnewline
240 & 0.905562825807609 & 0.188874348384781 & 0.0944371741923907 \tabularnewline
241 & 0.89347545951938 & 0.213049080961239 & 0.10652454048062 \tabularnewline
242 & 0.88429104128991 & 0.231417917420181 & 0.11570895871009 \tabularnewline
243 & 0.860671442298957 & 0.278657115402085 & 0.139328557701043 \tabularnewline
244 & 0.830883729089902 & 0.338232541820196 & 0.169116270910098 \tabularnewline
245 & 0.832544721348638 & 0.334910557302725 & 0.167455278651362 \tabularnewline
246 & 0.808498231218802 & 0.383003537562397 & 0.191501768781198 \tabularnewline
247 & 0.862589238105652 & 0.274821523788696 & 0.137410761894348 \tabularnewline
248 & 0.883531141393754 & 0.232937717212491 & 0.116468858606246 \tabularnewline
249 & 0.866265833832293 & 0.267468332335415 & 0.133734166167707 \tabularnewline
250 & 0.843303151232436 & 0.313393697535128 & 0.156696848767564 \tabularnewline
251 & 0.82780869469585 & 0.344382610608299 & 0.17219130530415 \tabularnewline
252 & 0.821910790091086 & 0.356178419817828 & 0.178089209908914 \tabularnewline
253 & 0.801542566836722 & 0.396914866326556 & 0.198457433163278 \tabularnewline
254 & 0.770086329806592 & 0.459827340386817 & 0.229913670193408 \tabularnewline
255 & 0.722155187290484 & 0.555689625419031 & 0.277844812709516 \tabularnewline
256 & 0.875956133185436 & 0.248087733629129 & 0.124043866814564 \tabularnewline
257 & 0.849459041060548 & 0.301081917878903 & 0.150540958939452 \tabularnewline
258 & 0.826345905359565 & 0.34730818928087 & 0.173654094640435 \tabularnewline
259 & 0.831923223562796 & 0.336153552874407 & 0.168076776437204 \tabularnewline
260 & 0.848636175155276 & 0.302727649689447 & 0.151363824844724 \tabularnewline
261 & 0.845162514771795 & 0.30967497045641 & 0.154837485228205 \tabularnewline
262 & 0.801396042671901 & 0.397207914656197 & 0.198603957328099 \tabularnewline
263 & 0.778310490480683 & 0.443379019038634 & 0.221689509519317 \tabularnewline
264 & 0.719715416357343 & 0.560569167285314 & 0.280284583642657 \tabularnewline
265 & 0.772381154804038 & 0.455237690391924 & 0.227618845195962 \tabularnewline
266 & 0.839922673999483 & 0.320154652001034 & 0.160077326000517 \tabularnewline
267 & 0.926917810431742 & 0.146164379136515 & 0.0730821895682577 \tabularnewline
268 & 0.906671517932941 & 0.186656964134119 & 0.0933284820670593 \tabularnewline
269 & 0.865007780153342 & 0.269984439693316 & 0.134992219846658 \tabularnewline
270 & 0.926659218945848 & 0.146681562108305 & 0.0733407810541523 \tabularnewline
271 & 0.904538175266072 & 0.190923649467857 & 0.0954618247339284 \tabularnewline
272 & 0.943421373055724 & 0.113157253888553 & 0.0565786269442763 \tabularnewline
273 & 0.902042733934533 & 0.195914532130933 & 0.0979572660654666 \tabularnewline
274 & 0.903071709349389 & 0.193856581301223 & 0.0969282906506113 \tabularnewline
275 & 0.889933918420908 & 0.220132163158183 & 0.110066081579092 \tabularnewline
276 & 0.811762000333417 & 0.376475999333167 & 0.188237999666583 \tabularnewline
277 & 0.719977651286747 & 0.560044697426506 & 0.280022348713253 \tabularnewline
278 & 0.555516235808125 & 0.888967528383751 & 0.444483764191875 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197780&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]0.72842669149035[/C][C]0.5431466170193[/C][C]0.27157330850965[/C][/ROW]
[ROW][C]11[/C][C]0.932111291961431[/C][C]0.135777416077138[/C][C]0.0678887080385691[/C][/ROW]
[ROW][C]12[/C][C]0.883927528921358[/C][C]0.232144942157285[/C][C]0.116072471078642[/C][/ROW]
[ROW][C]13[/C][C]0.907996117292558[/C][C]0.184007765414884[/C][C]0.0920038827074422[/C][/ROW]
[ROW][C]14[/C][C]0.882918643366775[/C][C]0.23416271326645[/C][C]0.117081356633225[/C][/ROW]
[ROW][C]15[/C][C]0.893372416642965[/C][C]0.21325516671407[/C][C]0.106627583357035[/C][/ROW]
[ROW][C]16[/C][C]0.901444286069359[/C][C]0.197111427861283[/C][C]0.0985557139306414[/C][/ROW]
[ROW][C]17[/C][C]0.860478230620101[/C][C]0.279043538759798[/C][C]0.139521769379899[/C][/ROW]
[ROW][C]18[/C][C]0.850882361745292[/C][C]0.298235276509416[/C][C]0.149117638254708[/C][/ROW]
[ROW][C]19[/C][C]0.800875673969818[/C][C]0.398248652060364[/C][C]0.199124326030182[/C][/ROW]
[ROW][C]20[/C][C]0.741526955513363[/C][C]0.516946088973274[/C][C]0.258473044486637[/C][/ROW]
[ROW][C]21[/C][C]0.680045374515351[/C][C]0.639909250969299[/C][C]0.31995462548465[/C][/ROW]
[ROW][C]22[/C][C]0.611980281908264[/C][C]0.776039436183472[/C][C]0.388019718091736[/C][/ROW]
[ROW][C]23[/C][C]0.538947837607392[/C][C]0.922104324785217[/C][C]0.461052162392608[/C][/ROW]
[ROW][C]24[/C][C]0.514659703331384[/C][C]0.970680593337232[/C][C]0.485340296668616[/C][/ROW]
[ROW][C]25[/C][C]0.513177509267377[/C][C]0.973644981465246[/C][C]0.486822490732623[/C][/ROW]
[ROW][C]26[/C][C]0.479991010742595[/C][C]0.95998202148519[/C][C]0.520008989257405[/C][/ROW]
[ROW][C]27[/C][C]0.42139582041683[/C][C]0.842791640833661[/C][C]0.57860417958317[/C][/ROW]
[ROW][C]28[/C][C]0.425690363172463[/C][C]0.851380726344926[/C][C]0.574309636827537[/C][/ROW]
[ROW][C]29[/C][C]0.365084395759665[/C][C]0.73016879151933[/C][C]0.634915604240335[/C][/ROW]
[ROW][C]30[/C][C]0.306802040898218[/C][C]0.613604081796437[/C][C]0.693197959101782[/C][/ROW]
[ROW][C]31[/C][C]0.25435470979871[/C][C]0.50870941959742[/C][C]0.74564529020129[/C][/ROW]
[ROW][C]32[/C][C]0.24895915720243[/C][C]0.49791831440486[/C][C]0.75104084279757[/C][/ROW]
[ROW][C]33[/C][C]0.217421178977289[/C][C]0.434842357954577[/C][C]0.782578821022711[/C][/ROW]
[ROW][C]34[/C][C]0.178369234649196[/C][C]0.356738469298393[/C][C]0.821630765350804[/C][/ROW]
[ROW][C]35[/C][C]0.217867818066176[/C][C]0.435735636132352[/C][C]0.782132181933824[/C][/ROW]
[ROW][C]36[/C][C]0.201215205990949[/C][C]0.402430411981898[/C][C]0.798784794009051[/C][/ROW]
[ROW][C]37[/C][C]0.165356409024524[/C][C]0.330712818049048[/C][C]0.834643590975476[/C][/ROW]
[ROW][C]38[/C][C]0.193459404854362[/C][C]0.386918809708725[/C][C]0.806540595145638[/C][/ROW]
[ROW][C]39[/C][C]0.206894025939871[/C][C]0.413788051879742[/C][C]0.793105974060129[/C][/ROW]
[ROW][C]40[/C][C]0.177929302829724[/C][C]0.355858605659447[/C][C]0.822070697170276[/C][/ROW]
[ROW][C]41[/C][C]0.149026371730435[/C][C]0.298052743460871[/C][C]0.850973628269565[/C][/ROW]
[ROW][C]42[/C][C]0.126655282221277[/C][C]0.253310564442555[/C][C]0.873344717778723[/C][/ROW]
[ROW][C]43[/C][C]0.183568354774129[/C][C]0.367136709548258[/C][C]0.816431645225871[/C][/ROW]
[ROW][C]44[/C][C]0.151176229122687[/C][C]0.302352458245374[/C][C]0.848823770877313[/C][/ROW]
[ROW][C]45[/C][C]0.128675510756777[/C][C]0.257351021513555[/C][C]0.871324489243223[/C][/ROW]
[ROW][C]46[/C][C]0.137559111258665[/C][C]0.27511822251733[/C][C]0.862440888741335[/C][/ROW]
[ROW][C]47[/C][C]0.130673343998705[/C][C]0.26134668799741[/C][C]0.869326656001295[/C][/ROW]
[ROW][C]48[/C][C]0.109771478421284[/C][C]0.219542956842568[/C][C]0.890228521578716[/C][/ROW]
[ROW][C]49[/C][C]0.0988039009221842[/C][C]0.197607801844368[/C][C]0.901196099077816[/C][/ROW]
[ROW][C]50[/C][C]0.103123587468387[/C][C]0.206247174936773[/C][C]0.896876412531613[/C][/ROW]
[ROW][C]51[/C][C]0.106559721667356[/C][C]0.213119443334711[/C][C]0.893440278332644[/C][/ROW]
[ROW][C]52[/C][C]0.0862255418009588[/C][C]0.172451083601918[/C][C]0.913774458199041[/C][/ROW]
[ROW][C]53[/C][C]0.104472981736165[/C][C]0.208945963472331[/C][C]0.895527018263835[/C][/ROW]
[ROW][C]54[/C][C]0.0864560444665518[/C][C]0.172912088933104[/C][C]0.913543955533448[/C][/ROW]
[ROW][C]55[/C][C]0.14775814039066[/C][C]0.29551628078132[/C][C]0.85224185960934[/C][/ROW]
[ROW][C]56[/C][C]0.431409103558723[/C][C]0.862818207117445[/C][C]0.568590896441277[/C][/ROW]
[ROW][C]57[/C][C]0.388468979468215[/C][C]0.77693795893643[/C][C]0.611531020531785[/C][/ROW]
[ROW][C]58[/C][C]0.346869907949977[/C][C]0.693739815899954[/C][C]0.653130092050023[/C][/ROW]
[ROW][C]59[/C][C]0.306952256858894[/C][C]0.613904513717787[/C][C]0.693047743141106[/C][/ROW]
[ROW][C]60[/C][C]0.324717125796664[/C][C]0.649434251593327[/C][C]0.675282874203336[/C][/ROW]
[ROW][C]61[/C][C]0.340600683894071[/C][C]0.681201367788142[/C][C]0.659399316105929[/C][/ROW]
[ROW][C]62[/C][C]0.311522199793264[/C][C]0.623044399586529[/C][C]0.688477800206736[/C][/ROW]
[ROW][C]63[/C][C]0.315766119209148[/C][C]0.631532238418296[/C][C]0.684233880790852[/C][/ROW]
[ROW][C]64[/C][C]0.279619398791686[/C][C]0.559238797583372[/C][C]0.720380601208314[/C][/ROW]
[ROW][C]65[/C][C]0.246153018287797[/C][C]0.492306036575594[/C][C]0.753846981712203[/C][/ROW]
[ROW][C]66[/C][C]0.221143289976963[/C][C]0.442286579953927[/C][C]0.778856710023037[/C][/ROW]
[ROW][C]67[/C][C]0.197420642750707[/C][C]0.394841285501413[/C][C]0.802579357249293[/C][/ROW]
[ROW][C]68[/C][C]0.176192401472963[/C][C]0.352384802945927[/C][C]0.823807598527037[/C][/ROW]
[ROW][C]69[/C][C]0.17106747620163[/C][C]0.34213495240326[/C][C]0.82893252379837[/C][/ROW]
[ROW][C]70[/C][C]0.14804521572903[/C][C]0.296090431458059[/C][C]0.85195478427097[/C][/ROW]
[ROW][C]71[/C][C]0.127234060178713[/C][C]0.254468120357427[/C][C]0.872765939821287[/C][/ROW]
[ROW][C]72[/C][C]0.10881848798206[/C][C]0.21763697596412[/C][C]0.89118151201794[/C][/ROW]
[ROW][C]73[/C][C]0.0932955476537794[/C][C]0.186591095307559[/C][C]0.906704452346221[/C][/ROW]
[ROW][C]74[/C][C]0.0833992745191813[/C][C]0.166798549038363[/C][C]0.916600725480819[/C][/ROW]
[ROW][C]75[/C][C]0.0802501779842049[/C][C]0.16050035596841[/C][C]0.919749822015795[/C][/ROW]
[ROW][C]76[/C][C]0.117197683862638[/C][C]0.234395367725277[/C][C]0.882802316137362[/C][/ROW]
[ROW][C]77[/C][C]0.103748999573258[/C][C]0.207497999146517[/C][C]0.896251000426742[/C][/ROW]
[ROW][C]78[/C][C]0.0886864086998386[/C][C]0.177372817399677[/C][C]0.911313591300161[/C][/ROW]
[ROW][C]79[/C][C]0.102924771518784[/C][C]0.205849543037568[/C][C]0.897075228481216[/C][/ROW]
[ROW][C]80[/C][C]0.100437323346634[/C][C]0.200874646693269[/C][C]0.899562676653366[/C][/ROW]
[ROW][C]81[/C][C]0.0847185547508957[/C][C]0.169437109501791[/C][C]0.915281445249104[/C][/ROW]
[ROW][C]82[/C][C]0.0711077106379182[/C][C]0.142215421275836[/C][C]0.928892289362082[/C][/ROW]
[ROW][C]83[/C][C]0.0655142305519613[/C][C]0.131028461103923[/C][C]0.934485769448039[/C][/ROW]
[ROW][C]84[/C][C]0.0548104751735971[/C][C]0.109620950347194[/C][C]0.945189524826403[/C][/ROW]
[ROW][C]85[/C][C]0.0532257036873666[/C][C]0.106451407374733[/C][C]0.946774296312633[/C][/ROW]
[ROW][C]86[/C][C]0.0554661795888979[/C][C]0.110932359177796[/C][C]0.944533820411102[/C][/ROW]
[ROW][C]87[/C][C]0.0455281334598637[/C][C]0.0910562669197274[/C][C]0.954471866540136[/C][/ROW]
[ROW][C]88[/C][C]0.0371095842882432[/C][C]0.0742191685764863[/C][C]0.962890415711757[/C][/ROW]
[ROW][C]89[/C][C]0.0306306806627257[/C][C]0.0612613613254514[/C][C]0.969369319337274[/C][/ROW]
[ROW][C]90[/C][C]0.0270786723291571[/C][C]0.0541573446583143[/C][C]0.972921327670843[/C][/ROW]
[ROW][C]91[/C][C]0.0385910329628365[/C][C]0.0771820659256729[/C][C]0.961408967037163[/C][/ROW]
[ROW][C]92[/C][C]0.0324987759062184[/C][C]0.0649975518124367[/C][C]0.967501224093782[/C][/ROW]
[ROW][C]93[/C][C]0.0285154125515442[/C][C]0.0570308251030884[/C][C]0.971484587448456[/C][/ROW]
[ROW][C]94[/C][C]0.0291594031778269[/C][C]0.0583188063556537[/C][C]0.970840596822173[/C][/ROW]
[ROW][C]95[/C][C]0.0303527781363008[/C][C]0.0607055562726017[/C][C]0.969647221863699[/C][/ROW]
[ROW][C]96[/C][C]0.0265363106230077[/C][C]0.0530726212460154[/C][C]0.973463689376992[/C][/ROW]
[ROW][C]97[/C][C]0.0354601584889348[/C][C]0.0709203169778696[/C][C]0.964539841511065[/C][/ROW]
[ROW][C]98[/C][C]0.0301769264775428[/C][C]0.0603538529550855[/C][C]0.969823073522457[/C][/ROW]
[ROW][C]99[/C][C]0.0249808774094231[/C][C]0.0499617548188463[/C][C]0.975019122590577[/C][/ROW]
[ROW][C]100[/C][C]0.0284172836406995[/C][C]0.056834567281399[/C][C]0.9715827163593[/C][/ROW]
[ROW][C]101[/C][C]0.0233087614532939[/C][C]0.0466175229065878[/C][C]0.976691238546706[/C][/ROW]
[ROW][C]102[/C][C]0.0199987759521447[/C][C]0.0399975519042895[/C][C]0.980001224047855[/C][/ROW]
[ROW][C]103[/C][C]0.0162698269349996[/C][C]0.0325396538699992[/C][C]0.983730173065[/C][/ROW]
[ROW][C]104[/C][C]0.0149152097687651[/C][C]0.0298304195375302[/C][C]0.985084790231235[/C][/ROW]
[ROW][C]105[/C][C]0.0171431043945451[/C][C]0.0342862087890903[/C][C]0.982856895605455[/C][/ROW]
[ROW][C]106[/C][C]0.0137587150012918[/C][C]0.0275174300025836[/C][C]0.986241284998708[/C][/ROW]
[ROW][C]107[/C][C]0.0110070600522211[/C][C]0.0220141201044422[/C][C]0.988992939947779[/C][/ROW]
[ROW][C]108[/C][C]0.00892829223275007[/C][C]0.0178565844655001[/C][C]0.99107170776725[/C][/ROW]
[ROW][C]109[/C][C]0.0163297170045174[/C][C]0.0326594340090349[/C][C]0.983670282995483[/C][/ROW]
[ROW][C]110[/C][C]0.0130871589343388[/C][C]0.0261743178686776[/C][C]0.986912841065661[/C][/ROW]
[ROW][C]111[/C][C]0.0144750625554427[/C][C]0.0289501251108854[/C][C]0.985524937444557[/C][/ROW]
[ROW][C]112[/C][C]0.0150594636386703[/C][C]0.0301189272773405[/C][C]0.98494053636133[/C][/ROW]
[ROW][C]113[/C][C]0.0121939235674453[/C][C]0.0243878471348905[/C][C]0.987806076432555[/C][/ROW]
[ROW][C]114[/C][C]0.0100477235447234[/C][C]0.0200954470894468[/C][C]0.989952276455277[/C][/ROW]
[ROW][C]115[/C][C]0.0109786841395221[/C][C]0.0219573682790442[/C][C]0.989021315860478[/C][/ROW]
[ROW][C]116[/C][C]0.017447366759067[/C][C]0.034894733518134[/C][C]0.982552633240933[/C][/ROW]
[ROW][C]117[/C][C]0.0146963365581389[/C][C]0.0293926731162777[/C][C]0.985303663441861[/C][/ROW]
[ROW][C]118[/C][C]0.0118098091747384[/C][C]0.0236196183494768[/C][C]0.988190190825262[/C][/ROW]
[ROW][C]119[/C][C]0.0101843201563569[/C][C]0.0203686403127138[/C][C]0.989815679843643[/C][/ROW]
[ROW][C]120[/C][C]0.00940733273273223[/C][C]0.0188146654654645[/C][C]0.990592667267268[/C][/ROW]
[ROW][C]121[/C][C]0.00963899965523165[/C][C]0.0192779993104633[/C][C]0.990361000344768[/C][/ROW]
[ROW][C]122[/C][C]0.0112972964729536[/C][C]0.0225945929459072[/C][C]0.988702703527046[/C][/ROW]
[ROW][C]123[/C][C]0.0121586875321392[/C][C]0.0243173750642784[/C][C]0.987841312467861[/C][/ROW]
[ROW][C]124[/C][C]0.021655321538277[/C][C]0.0433106430765541[/C][C]0.978344678461723[/C][/ROW]
[ROW][C]125[/C][C]0.0178596776992177[/C][C]0.0357193553984353[/C][C]0.982140322300782[/C][/ROW]
[ROW][C]126[/C][C]0.0157700551555086[/C][C]0.0315401103110172[/C][C]0.984229944844491[/C][/ROW]
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[ROW][C]271[/C][C]0.904538175266072[/C][C]0.190923649467857[/C][C]0.0954618247339284[/C][/ROW]
[ROW][C]272[/C][C]0.943421373055724[/C][C]0.113157253888553[/C][C]0.0565786269442763[/C][/ROW]
[ROW][C]273[/C][C]0.902042733934533[/C][C]0.195914532130933[/C][C]0.0979572660654666[/C][/ROW]
[ROW][C]274[/C][C]0.903071709349389[/C][C]0.193856581301223[/C][C]0.0969282906506113[/C][/ROW]
[ROW][C]275[/C][C]0.889933918420908[/C][C]0.220132163158183[/C][C]0.110066081579092[/C][/ROW]
[ROW][C]276[/C][C]0.811762000333417[/C][C]0.376475999333167[/C][C]0.188237999666583[/C][/ROW]
[ROW][C]277[/C][C]0.719977651286747[/C][C]0.560044697426506[/C][C]0.280022348713253[/C][/ROW]
[ROW][C]278[/C][C]0.555516235808125[/C][C]0.888967528383751[/C][C]0.444483764191875[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197780&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197780&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.728426691490350.54314661701930.27157330850965
110.9321112919614310.1357774160771380.0678887080385691
120.8839275289213580.2321449421572850.116072471078642
130.9079961172925580.1840077654148840.0920038827074422
140.8829186433667750.234162713266450.117081356633225
150.8933724166429650.213255166714070.106627583357035
160.9014442860693590.1971114278612830.0985557139306414
170.8604782306201010.2790435387597980.139521769379899
180.8508823617452920.2982352765094160.149117638254708
190.8008756739698180.3982486520603640.199124326030182
200.7415269555133630.5169460889732740.258473044486637
210.6800453745153510.6399092509692990.31995462548465
220.6119802819082640.7760394361834720.388019718091736
230.5389478376073920.9221043247852170.461052162392608
240.5146597033313840.9706805933372320.485340296668616
250.5131775092673770.9736449814652460.486822490732623
260.4799910107425950.959982021485190.520008989257405
270.421395820416830.8427916408336610.57860417958317
280.4256903631724630.8513807263449260.574309636827537
290.3650843957596650.730168791519330.634915604240335
300.3068020408982180.6136040817964370.693197959101782
310.254354709798710.508709419597420.74564529020129
320.248959157202430.497918314404860.75104084279757
330.2174211789772890.4348423579545770.782578821022711
340.1783692346491960.3567384692983930.821630765350804
350.2178678180661760.4357356361323520.782132181933824
360.2012152059909490.4024304119818980.798784794009051
370.1653564090245240.3307128180490480.834643590975476
380.1934594048543620.3869188097087250.806540595145638
390.2068940259398710.4137880518797420.793105974060129
400.1779293028297240.3558586056594470.822070697170276
410.1490263717304350.2980527434608710.850973628269565
420.1266552822212770.2533105644425550.873344717778723
430.1835683547741290.3671367095482580.816431645225871
440.1511762291226870.3023524582453740.848823770877313
450.1286755107567770.2573510215135550.871324489243223
460.1375591112586650.275118222517330.862440888741335
470.1306733439987050.261346687997410.869326656001295
480.1097714784212840.2195429568425680.890228521578716
490.09880390092218420.1976078018443680.901196099077816
500.1031235874683870.2062471749367730.896876412531613
510.1065597216673560.2131194433347110.893440278332644
520.08622554180095880.1724510836019180.913774458199041
530.1044729817361650.2089459634723310.895527018263835
540.08645604446655180.1729120889331040.913543955533448
550.147758140390660.295516280781320.85224185960934
560.4314091035587230.8628182071174450.568590896441277
570.3884689794682150.776937958936430.611531020531785
580.3468699079499770.6937398158999540.653130092050023
590.3069522568588940.6139045137177870.693047743141106
600.3247171257966640.6494342515933270.675282874203336
610.3406006838940710.6812013677881420.659399316105929
620.3115221997932640.6230443995865290.688477800206736
630.3157661192091480.6315322384182960.684233880790852
640.2796193987916860.5592387975833720.720380601208314
650.2461530182877970.4923060365755940.753846981712203
660.2211432899769630.4422865799539270.778856710023037
670.1974206427507070.3948412855014130.802579357249293
680.1761924014729630.3523848029459270.823807598527037
690.171067476201630.342134952403260.82893252379837
700.148045215729030.2960904314580590.85195478427097
710.1272340601787130.2544681203574270.872765939821287
720.108818487982060.217636975964120.89118151201794
730.09329554765377940.1865910953075590.906704452346221
740.08339927451918130.1667985490383630.916600725480819
750.08025017798420490.160500355968410.919749822015795
760.1171976838626380.2343953677252770.882802316137362
770.1037489995732580.2074979991465170.896251000426742
780.08868640869983860.1773728173996770.911313591300161
790.1029247715187840.2058495430375680.897075228481216
800.1004373233466340.2008746466932690.899562676653366
810.08471855475089570.1694371095017910.915281445249104
820.07110771063791820.1422154212758360.928892289362082
830.06551423055196130.1310284611039230.934485769448039
840.05481047517359710.1096209503471940.945189524826403
850.05322570368736660.1064514073747330.946774296312633
860.05546617958889790.1109323591777960.944533820411102
870.04552813345986370.09105626691972740.954471866540136
880.03710958428824320.07421916857648630.962890415711757
890.03063068066272570.06126136132545140.969369319337274
900.02707867232915710.05415734465831430.972921327670843
910.03859103296283650.07718206592567290.961408967037163
920.03249877590621840.06499755181243670.967501224093782
930.02851541255154420.05703082510308840.971484587448456
940.02915940317782690.05831880635565370.970840596822173
950.03035277813630080.06070555627260170.969647221863699
960.02653631062300770.05307262124601540.973463689376992
970.03546015848893480.07092031697786960.964539841511065
980.03017692647754280.06035385295508550.969823073522457
990.02498087740942310.04996175481884630.975019122590577
1000.02841728364069950.0568345672813990.9715827163593
1010.02330876145329390.04661752290658780.976691238546706
1020.01999877595214470.03999755190428950.980001224047855
1030.01626982693499960.03253965386999920.983730173065
1040.01491520976876510.02983041953753020.985084790231235
1050.01714310439454510.03428620878909030.982856895605455
1060.01375871500129180.02751743000258360.986241284998708
1070.01100706005222110.02201412010444220.988992939947779
1080.008928292232750070.01785658446550010.99107170776725
1090.01632971700451740.03265943400903490.983670282995483
1100.01308715893433880.02617431786867760.986912841065661
1110.01447506255544270.02895012511088540.985524937444557
1120.01505946363867030.03011892727734050.98494053636133
1130.01219392356744530.02438784713489050.987806076432555
1140.01004772354472340.02009544708944680.989952276455277
1150.01097868413952210.02195736827904420.989021315860478
1160.0174473667590670.0348947335181340.982552633240933
1170.01469633655813890.02939267311627770.985303663441861
1180.01180980917473840.02361961834947680.988190190825262
1190.01018432015635690.02036864031271380.989815679843643
1200.009407332732732230.01881466546546450.990592667267268
1210.009638999655231650.01927799931046330.990361000344768
1220.01129729647295360.02259459294590720.988702703527046
1230.01215868753213920.02431737506427840.987841312467861
1240.0216553215382770.04331064307655410.978344678461723
1250.01785967769921770.03571935539843530.982140322300782
1260.01577005515550860.03154011031101720.984229944844491
1270.01789476024455310.03578952048910620.982105239755447
1280.01734956644025420.03469913288050840.982650433559746
1290.01588224158520460.03176448317040930.984117758414795
1300.0215316038064480.0430632076128960.978468396193552
1310.04016094046480360.08032188092960710.959839059535196
1320.04063118122994470.08126236245988940.959368818770055
1330.04156733529495430.08313467058990870.958432664705046
1340.03768289106323230.07536578212646460.962317108936768
1350.03223857750092760.06447715500185510.967761422499072
1360.02698296810254630.05396593620509250.973017031897454
1370.02533679559898440.05067359119796880.974663204401016
1380.02425735918107630.04851471836215270.975742640818924
1390.02081257755104850.04162515510209710.979187422448952
1400.03878948378595610.07757896757191220.961210516214044
1410.03910491465395780.07820982930791560.960895085346042
1420.05659346669033130.1131869333806630.943406533309669
1430.04764978088365120.09529956176730250.952350219116349
1440.04029573603196280.08059147206392560.959704263968037
1450.03549572733728920.07099145467457840.964504272662711
1460.04603637665635420.09207275331270830.953963623343646
1470.04405055193075330.08810110386150670.955949448069247
1480.03952912245120330.07905824490240650.960470877548797
1490.03679151102358960.07358302204717910.96320848897641
1500.05132576156711670.1026515231342330.948674238432883
1510.05222282660888130.1044456532177630.947777173391119
1520.166016846319670.332033692639340.83398315368033
1530.176969113704350.3539382274086990.82303088629565
1540.1668293921000090.3336587842000190.833170607899991
1550.2375901080153860.4751802160307720.762409891984614
1560.2350140573339250.470028114667850.764985942666075
1570.2139868598704290.4279737197408580.786013140129571
1580.2030382678539270.4060765357078540.796961732146073
1590.1822089740508320.3644179481016640.817791025949168
1600.16433125478480.32866250956960.8356687452152
1610.1783401695285330.3566803390570660.821659830471467
1620.1665358980628320.3330717961256650.833464101937168
1630.1464959437387550.2929918874775110.853504056261244
1640.1316997567202380.2633995134404770.868300243279762
1650.1808647180226410.3617294360452820.819135281977359
1660.1847546246546220.3695092493092440.815245375345378
1670.1667639651585630.3335279303171260.833236034841437
1680.2725314107532920.5450628215065840.727468589246708
1690.2465796736330250.493159347266050.753420326366975
1700.2272649928730870.4545299857461740.772735007126913
1710.2061484375131110.4122968750262230.793851562486889
1720.2444807323798920.4889614647597830.755519267620108
1730.2186762871456630.4373525742913260.781323712854337
1740.2068461892243120.4136923784486250.793153810775688
1750.1835310970406930.3670621940813850.816468902959307
1760.1630162914120550.3260325828241110.836983708587945
1770.1431490615992370.2862981231984740.856850938400763
1780.1263454311898150.2526908623796310.873654568810185
1790.1406245802309430.2812491604618860.859375419769057
1800.148518312062150.29703662412430.85148168793785
1810.1404455169987510.2808910339975010.859554483001249
1820.3303910130649240.6607820261298470.669608986935076
1830.3066851186908380.6133702373816750.693314881309162
1840.2826068532255810.5652137064511630.717393146774418
1850.2998796370916840.5997592741833680.700120362908316
1860.2887430143267060.5774860286534110.711256985673294
1870.3784823693339360.7569647386678720.621517630666064
1880.3837468175566250.767493635113250.616253182443375
1890.355025911090650.71005182218130.64497408890935
1900.7196950501494070.5606098997011860.280304949850593
1910.6893073297023420.6213853405953150.310692670297658
1920.6592337874368910.6815324251262190.340766212563109
1930.6444709395269230.7110581209461550.355529060473077
1940.6632965447572120.6734069104855750.336703455242788
1950.6376650682669650.724669863466070.362334931733035
1960.6136210568359310.7727578863281380.386378943164069
1970.5907381248536150.8185237502927690.409261875146385
1980.5586687426788090.8826625146423830.441331257321191
1990.5257580670070730.9484838659858530.474241932992927
2000.5976389605448290.8047220789103420.402361039455171
2010.6420669265666910.7158661468666180.357933073433309
2020.6073079881596250.7853840236807510.392692011840375
2030.5712957483264860.8574085033470270.428704251673514
2040.5434232733270140.9131534533459720.456576726672986
2050.5340259015628020.9319481968743960.465974098437198
2060.4987890926296450.9975781852592890.501210907370355
2070.5671493059297470.8657013881405060.432850694070253
2080.6261695959705180.7476608080589640.373830404029482
2090.5957750766510420.8084498466979160.404224923348958
2100.626797660583090.746404678833820.37320233941691
2110.5978607263084050.804278547383190.402139273691595
2120.5594497059377960.8811005881244080.440550294062204
2130.5257770270646380.9484459458707240.474222972935362
2140.4868226528619960.9736453057239920.513177347138004
2150.4750732437683780.9501464875367550.524926756231622
2160.4633299274943220.9266598549886450.536670072505678
2170.501002315087370.997995369825260.49899768491263
2180.4605155671976790.9210311343953580.539484432802321
2190.4480830609586410.8961661219172830.551916939041359
2200.4088725816562820.8177451633125630.591127418343719
2210.3757271789880850.7514543579761690.624272821011915
2220.3377517496016640.6755034992033290.662248250398336
2230.309783299840620.619566599681240.69021670015938
2240.2786927991142010.5573855982284030.721307200885799
2250.2451355868289880.4902711736579750.754864413171012
2260.348811289317030.697622578634060.65118871068297
2270.3942495626042880.7884991252085770.605750437395712
2280.6983737339019050.603252532196190.301626266098095
2290.680000357306570.639999285386860.31999964269343
2300.6401456939832150.719708612033570.359854306016785
2310.6343176022642550.7313647954714910.365682397735745
2320.6314474833690720.7371050332618570.368552516630928
2330.6728825030314570.6542349939370860.327117496968543
2340.6486880123314830.7026239753370340.351311987668517
2350.6088168250208710.7823663499582580.391183174979129
2360.5707385343658530.8585229312682940.429261465634147
2370.6373057739186550.7253884521626910.362694226081345
2380.8518332866287780.2963334267424440.148166713371222
2390.9221310156055480.1557379687889030.0778689843944516
2400.9055628258076090.1888743483847810.0944371741923907
2410.893475459519380.2130490809612390.10652454048062
2420.884291041289910.2314179174201810.11570895871009
2430.8606714422989570.2786571154020850.139328557701043
2440.8308837290899020.3382325418201960.169116270910098
2450.8325447213486380.3349105573027250.167455278651362
2460.8084982312188020.3830035375623970.191501768781198
2470.8625892381056520.2748215237886960.137410761894348
2480.8835311413937540.2329377172124910.116468858606246
2490.8662658338322930.2674683323354150.133734166167707
2500.8433031512324360.3133936975351280.156696848767564
2510.827808694695850.3443826106082990.17219130530415
2520.8219107900910860.3561784198178280.178089209908914
2530.8015425668367220.3969148663265560.198457433163278
2540.7700863298065920.4598273403868170.229913670193408
2550.7221551872904840.5556896254190310.277844812709516
2560.8759561331854360.2480877336291290.124043866814564
2570.8494590410605480.3010819178789030.150540958939452
2580.8263459053595650.347308189280870.173654094640435
2590.8319232235627960.3361535528744070.168076776437204
2600.8486361751552760.3027276496894470.151363824844724
2610.8451625147717950.309674970456410.154837485228205
2620.8013960426719010.3972079146561970.198603957328099
2630.7783104904806830.4433790190386340.221689509519317
2640.7197154163573430.5605691672853140.280284583642657
2650.7723811548040380.4552376903919240.227618845195962
2660.8399226739994830.3201546520010340.160077326000517
2670.9269178104317420.1461643791365150.0730821895682577
2680.9066715179329410.1866569641341190.0933284820670593
2690.8650077801533420.2699844396933160.134992219846658
2700.9266592189458480.1466815621083050.0733407810541523
2710.9045381752660720.1909236494678570.0954618247339284
2720.9434213730557240.1131572538885530.0565786269442763
2730.9020427339345330.1959145321309330.0979572660654666
2740.9030717093493890.1938565813012230.0969282906506113
2750.8899339184209080.2201321631581830.110066081579092
2760.8117620003334170.3764759993331670.188237999666583
2770.7199776512867470.5600446974265060.280022348713253
2780.5555162358081250.8889675283837510.444483764191875







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level330.122676579925651NOK
10% type I error level620.230483271375465NOK

\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 & 33 & 0.122676579925651 & NOK \tabularnewline
10% type I error level & 62 & 0.230483271375465 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197780&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]33[/C][C]0.122676579925651[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]62[/C][C]0.230483271375465[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197780&T=6

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Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level330.122676579925651NOK
10% type I error level620.230483271375465NOK



Parameters (Session):
par1 = 6 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 6 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$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')
}