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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 21 Dec 2010 14:38:38 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/21/t12929422581rbqkhmro1dxmgh.htm/, Retrieved Wed, 15 May 2024 03:30:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113623, Retrieved Wed, 15 May 2024 03:30:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact117

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-12-05 20:18:32] [b98453cac15ba1066b407e146608df68]
-   PD    [Multiple Regression] [] [2010-12-21 14:38:38] [29eeba0e6ce2cd83aa315a4a7ff8c4aa] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 16 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113623&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]16 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113623&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113623&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 2.06285134721188 + 0.452576036791377Populatie[t] + 0.239169812731862Geslacht[t] -0.00908693191448484Happiness[t] -0.0132555507413528Connected[t] + 0.0243562014396462Separate[t] + 0.54734344200979Learning[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Software[t] =  +  2.06285134721188 +  0.452576036791377Populatie[t] +  0.239169812731862Geslacht[t] -0.00908693191448484Happiness[t] -0.0132555507413528Connected[t] +  0.0243562014396462Separate[t] +  0.54734344200979Learning[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113623&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Software[t] =  +  2.06285134721188 +  0.452576036791377Populatie[t] +  0.239169812731862Geslacht[t] -0.00908693191448484Happiness[t] -0.0132555507413528Connected[t] +  0.0243562014396462Separate[t] +  0.54734344200979Learning[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113623&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113623&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 2.06285134721188 + 0.452576036791377Populatie[t] + 0.239169812731862Geslacht[t] -0.00908693191448484Happiness[t] -0.0132555507413528Connected[t] + 0.0243562014396462Separate[t] + 0.54734344200979Learning[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)2.062851347211881.1664551.76850.0780660.039033
Populatie0.4525760367913770.2341481.93290.0542570.027129
Geslacht0.2391698127318620.2193321.09040.276450.138225
Happiness-0.009086931914484840.04482-0.20270.8394840.419742
Connected-0.01325555074135280.031048-0.42690.6697550.334878
Separate0.02435620143964620.0322490.75520.4507360.225368
Learning0.547343442009790.04537512.062700

\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) & 2.06285134721188 & 1.166455 & 1.7685 & 0.078066 & 0.039033 \tabularnewline
Populatie & 0.452576036791377 & 0.234148 & 1.9329 & 0.054257 & 0.027129 \tabularnewline
Geslacht & 0.239169812731862 & 0.219332 & 1.0904 & 0.27645 & 0.138225 \tabularnewline
Happiness & -0.00908693191448484 & 0.04482 & -0.2027 & 0.839484 & 0.419742 \tabularnewline
Connected & -0.0132555507413528 & 0.031048 & -0.4269 & 0.669755 & 0.334878 \tabularnewline
Separate & 0.0243562014396462 & 0.032249 & 0.7552 & 0.450736 & 0.225368 \tabularnewline
Learning & 0.54734344200979 & 0.045375 & 12.0627 & 0 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113623&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]2.06285134721188[/C][C]1.166455[/C][C]1.7685[/C][C]0.078066[/C][C]0.039033[/C][/ROW]
[ROW][C]Populatie[/C][C]0.452576036791377[/C][C]0.234148[/C][C]1.9329[/C][C]0.054257[/C][C]0.027129[/C][/ROW]
[ROW][C]Geslacht[/C][C]0.239169812731862[/C][C]0.219332[/C][C]1.0904[/C][C]0.27645[/C][C]0.138225[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.00908693191448484[/C][C]0.04482[/C][C]-0.2027[/C][C]0.839484[/C][C]0.419742[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0132555507413528[/C][C]0.031048[/C][C]-0.4269[/C][C]0.669755[/C][C]0.334878[/C][/ROW]
[ROW][C]Separate[/C][C]0.0243562014396462[/C][C]0.032249[/C][C]0.7552[/C][C]0.450736[/C][C]0.225368[/C][/ROW]
[ROW][C]Learning[/C][C]0.54734344200979[/C][C]0.045375[/C][C]12.0627[/C][C]0[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113623&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113623&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)2.062851347211881.1664551.76850.0780660.039033
Populatie0.4525760367913770.2341481.93290.0542570.027129
Geslacht0.2391698127318620.2193321.09040.276450.138225
Happiness-0.009086931914484840.04482-0.20270.8394840.419742
Connected-0.01325555074135280.031048-0.42690.6697550.334878
Separate0.02435620143964620.0322490.75520.4507360.225368
Learning0.547343442009790.04537512.062700






Multiple Linear Regression - Regression Statistics
Multiple R0.664438564389672
R-squared0.441478605848208
Adjusted R-squared0.429552882129664
F-TEST (value)37.0190200835981
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.77966607666687
Sum Squared Residuals889.986387787314

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.664438564389672 \tabularnewline
R-squared & 0.441478605848208 \tabularnewline
Adjusted R-squared & 0.429552882129664 \tabularnewline
F-TEST (value) & 37.0190200835981 \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 & 889.986387787314 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113623&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]0.441478605848208[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.429552882129664[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]37.0190200835981[/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]889.986387787314[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113623&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113623&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.664438564389672
R-squared0.441478605848208
Adjusted R-squared0.429552882129664
F-TEST (value)37.0190200835981
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.77966607666687
Sum Squared Residuals889.986387787314






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11210.12490297037031.87509702962968
21111.6109594615870-0.610959461586962
31513.50896687200881.4910331279912
4611.0093684057027-5.00936840570268
51310.72250520230132.27749479769868
6109.948882734204030.0511172657959684
71213.2649813138346-1.26498131383459
81411.26366630670042.73633369329956
91210.65636862985381.34363137014619
10911.2635251254412-2.26352512544118
111011.3697759300713-1.36977593007127
121211.69035158477580.309648415224199
131211.53080925923120.469190740768752
141111.7752705340538-0.775270534053783
151512.35961721524312.64038278475693
161210.97793899113231.02206100886766
171010.9005605867273-0.900560586727283
181213.9688129209198-1.96881292091981
191112.6489614691705-1.64896146917047
201211.72192218060540.278077819394625
211111.4889347054842-0.488934705484191
221211.75625618947950.243743810520493
231313.4354747239121-0.435474723912124
241111.8624855646341-0.862485564634076
251211.92822002277930.0717799772206508
261312.21357418934440.786425810655615
271011.5027987692270-1.50279876922704
281411.30127805888142.69872194111857
291211.74210976321820.257890236781846
301010.4313452433833-0.4313452433833
311211.16347808789730.836521912102709
3289.38691714928457-1.38691714928457
331010.5275144095249-0.527514409524899
341211.82627901823540.173720981764614
351210.33101584332091.66898415667909
3678.22304791725442-1.22304791725442
3798.277710690000580.722289309999418
381210.36848641424271.63151358575735
391011.7282456994753-1.72824569947530
401011.4946027128326-1.49460271283256
411011.4255615460812-1.42556154608124
421210.62508039654271.37491960345726
431513.59259283146461.40740716853544
441010.4090027607275-0.409002760727462
451010.4593641182936-0.459364118293577
46129.037430480741022.96256951925898
471310.72728233412972.27271766587031
481111.219122522648-0.21912252264801
491111.8059502543634-0.805950254363357
501210.33579297514931.66420702485073
511411.86805938924332.13194061075675
521010.3575269448036-0.357526944803612
53129.363169460846432.63683053915357
541311.87789601541851.12210398458151
5557.68769600146292-2.68769600146292
56610.6431130791125-4.64311307911245
571211.67784572829520.322154271704802
581211.81948816762320.180511832376788
591111.0029037055735-0.00290370557348595
601011.7672156589186-1.76721565891855
6179.29516035087435-2.29516035087435
621211.47919226204810.520807737951855
631411.81391434301402.18608565698597
641110.73173331547510.268266684524943
651211.68014180959750.319858190402492
661312.16663175634440.833368243655612
671412.88209012555091.11790987444909
681112.5185170738355-1.51851707383551
69129.64369610080842.3563038991916
701211.57385365476220.426146345237827
7188.23475708095421-0.234757080954212
721110.78662805596500.213371944034974
731412.96967830513431.03032169486574
741412.72619869231631.27380130768372
751211.36172105493600.638278945063967
76912.1641120922043-3.16411209220434
771311.76833850218241.23166149781764
781111.6983156734265-0.698315673426478
79129.87847497528442.12152502471561
801211.32195440271200.678045597288026
811211.57600855480520.423991445194768
821211.81302346749400.186976532505967
831210.89348737359661.10651262640339
841111.2323780733894-0.232378073389363
851011.7024842922533-1.70248429225335
86910.4881125213978-1.48811252139783
871211.77555289657230.224447103427715
881211.78894962857290.211050371427111
891211.26746177652420.732538223475755
9099.63414183715167-0.634141837151667
911512.24350421539322.75649578460679
921211.91044827325260.0895517267473811
931211.09532779666600.90467220333403
941210.09820689966421.90179310033577
951011.7265581311745-1.72655813117449
961311.76506075887551.23493924112451
97911.6759731907706-2.67597319077064
981211.45610008513160.543899914868442
991010.494577221527-0.494577221527005
1001411.73072675000142.26927324999864
1011111.5258909461436-0.52589094614363
1021513.98005475287741.01994524712264
1031110.88341877967760.116581220322435
1041111.8882469718560-0.888246971856032
105129.798286159314722.20171384068528
1061212.2628009224860-0.262800922485987
1071211.54303275319330.456967246806652
1081111.5573203607140-0.557320360713953
10979.6848209602947-2.68482096029471
1101211.80623261688190.193767383118141
1111411.80496859235882.1950314076412
1121112.5157322313154-1.51573223131544
113109.496809197909770.503190802090228
1141312.51116149818630.48883850181367
1151310.82700322119062.17299677880942
116810.8137476704492-2.81374767044923
1171110.15787877198260.84212122801744
1181211.75798754574480.242012454255186
119119.985595225958961.01440477404104
1201311.63157058797751.36842941202253
1211210.17993889211991.82006110788010
1221411.81086856745102.18913143254903
1231311.10628726610501.89371273389499
1241511.78679472852983.21320527147017
1251010.8335331387598-0.833533138759769
1261112.2716054918820-1.27160549188197
127911.2314871978694-2.23148719786936
128119.526224893696291.47377510630371
1291011.5343693650566-1.53436936505662
130118.315322442181582.68467755781842
131811.7467457137873-3.74674571378727
132119.320030882576311.67996911742369
1331210.47701187069951.52298812930047
1341211.10151013427660.898489865723354
13599.69561688998552-0.695616889985518
1361111.0001402925289-0.000140292528927985
137109.13021933593050.869780664069505
13889.55058109513593-1.55058109513593
13998.859620108628310.140379891371689
140811.7797215153992-3.77972151539915
141911.0837010345447-2.08370103454466
1421512.38701919224582.61298080775422
1431111.2858890375725-0.285889037572535
14488.30746092117616-0.307460921176164
1451312.69482805742670.305171942573276
146129.930559304209742.06944069579026
1471211.49474389409180.505256105908191
14899.86456391302148-0.864563913021481
14978.52882163417604-1.52882163417604
1501311.19106503412371.80893496587626
151911.6023784750287-2.60237847502869
152611.8889966661168-5.88899666611678
153810.6600229184184-2.66002291841837
15488.4275105721091-0.42751057210909
155610.2198467256032-4.2198467256032
156911.2314871978694-2.23148719786936
1571111.7226718748661-0.722671874866125
15889.71503334886203-1.71503334886203
159109.362808141608560.63719185839144
16088.72609476897542-0.726094768975418
1611411.52234267008352.47765732991655
1621010.9205066018859-0.920506601885934
16387.848882341647350.151117658352652
1641110.00453061381390.995469386186124
165128.478016555793583.52198344420642
166129.810550448341192.18944955165881
1671211.28184361538850.718156384611474
16858.79560326746899-3.79560326746899
1691211.33810494804680.661895051953185
170108.858179734091131.14182026590887
17177.33447608763545-0.334476087635453
172128.929525367050843.07047463294916
1731110.58316228913470.416837710865262
17489.10165934690911-1.10165934690911
17598.854948989304330.145051010695673
1761010.1635586090961-0.163558609096121
17799.16765473809737-0.167654738097374
1781211.33192261043610.668077389563862
17968.23224086167329-2.23224086167329
1801512.79197394552592.20802605447407
1811210.42147344845321.57852655154680
182126.925729309390625.07427069060938
1831211.39403174531600.605968254683965
1841111.5913838368348-0.591383836834775
18578.9719142510602-1.97191425106020
18678.27631731398346-1.27631731398346
18758.4363185863642-3.43631858636419
1881210.31751872512541.68248127487457
1891211.40283631471200.597163685287982
19039.11341550912896-6.11341550912896
1911111.3967951583606-0.396795158360593
192109.63640274969910.363597250300891
1931210.59904007166141.40095992833860
194911.2366527047206-2.23665270472061
1951211.39604546409980.603954535900156
196910.0192855530767-1.01928555307673
1971211.07158355308690.928416446913057
1981010.0019083820286-0.00190838202856881
19998.233504886196340.766495113803655
200128.841552257303723.15844774269628
201810.7665464858566-2.76654648585663
2021110.80200333799460.197996662005431
2031111.3695343626171-0.369534362617138
2041211.08783448461670.91216551538334
205108.292053915250871.70794608474913
2061010.4806779890293-0.480677989029284
207129.141425999133172.85857400086683
208129.013777023646552.98622297635345
2091110.69876095872230.301239041277706
210810.5638655820420-2.56386558204196
2111211.34808275548130.6519172445187
212109.827105171864930.172894828135075
2131111.8674157074869-0.867415707486885
2141010.1487566713132-0.148756671313207
21589.48088786172217-1.48088786172217
2161210.84856084083081.15143915916920
217129.418170213840782.58182978615922
218109.953380948373020.0466190516269787
2191210.76326874254981.23673125745024
22098.863145045698810.136854954301189
22166.98802341349426-0.988023413494258
222109.921484202060450.0785157979395493
223910.0072940268584-1.00729402685843
22498.3639996763060.636000323693995
22598.932794725451630.067205274548368
22669.5702661772516-3.57026617725160
227107.942605860321312.05739413967869
228611.0879756658759-5.08797566587591
2291412.29635006834451.7036499316555
230109.600804716301920.399195283698082
231108.261515376200551.73848462379945
23264.383412598036531.61658740196347
233129.240603590632582.75939640936742
2341211.33927818608530.660721813914683
23577.67656018200976-0.676560182009761
23688.94342804440768-0.943428044407678
237118.946799970453742.05320002954627
23837.73806080388816-4.73806080388816
23969.4090832819263-3.40908328192629
24088.9990724791584-0.999072479158396
241910.0358188471249-1.03581884712495
24297.950437152618811.04956284738119
24389.03889791106322-1.03889791106322
24498.96985674431190.0301432556881003
24578.36451400656831-1.36451400656831
24677.7601209240255-0.760120924025495
24769.10292337143217-3.10292337143217
248911.2833513888161-2.28335138881610
249108.83522873843381.16477126156620
250119.969682274677441.03031772532257
2511211.17579920945770.824200790542298
252810.2515233339372-2.25152333393716
253119.618837398871641.38116260112836
25434.66726737608007-1.66726737608007
2551110.75774191646060.242258083539354
256128.422172160102843.57782783989716
25778.36662190809131-1.36662190809131
25899.99342996311558-0.993429963115582
2591210.52470744281941.4752925571806
260810.2270259512383-2.22702595123827
261119.439436851752871.56056314824713
26288.26769771381123-0.267697713811227
2631010.7184425959788-0.718442595978835
26488.31959707351283-0.31959707351283
26579.45779568480558-2.45779568480558
26689.55930670781255-1.55930670781255
2671011.2770278699462-1.27702786994617
26889.56229370369485-1.56229370369485
2691211.35426509309200.645734906908023
2701411.06436915869702.93563084130299
27179.0749044965219-2.07490449652189
27266.26601794258008-0.266017942580075
2731111.0441815760842-0.0441815760842363
27445.40407478477717-1.40407478477717
275911.1638076832394-2.16380768323941
27654.251609995439320.748390004560678
27798.843424794828280.156575205171720
2781110.46124010067730.538759899322745
2791210.21920304384681.78079695615316
28098.370040832657430.62995916734257
2811210.93537375710891.06462624289115
2821010.7867340684694-0.786734068469408
28398.861272508174250.138727491825746
28465.800786248839220.199213751160785
2851011.1433377381081-1.14333773810813
28697.790518281816571.20948171818343
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 & 10.1249029703703 & 1.87509702962968 \tabularnewline
2 & 11 & 11.6109594615870 & -0.610959461586962 \tabularnewline
3 & 15 & 13.5089668720088 & 1.4910331279912 \tabularnewline
4 & 6 & 11.0093684057027 & -5.00936840570268 \tabularnewline
5 & 13 & 10.7225052023013 & 2.27749479769868 \tabularnewline
6 & 10 & 9.94888273420403 & 0.0511172657959684 \tabularnewline
7 & 12 & 13.2649813138346 & -1.26498131383459 \tabularnewline
8 & 14 & 11.2636663067004 & 2.73633369329956 \tabularnewline
9 & 12 & 10.6563686298538 & 1.34363137014619 \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 & 0.469190740768752 \tabularnewline
14 & 11 & 11.7752705340538 & -0.775270534053783 \tabularnewline
15 & 15 & 12.3596172152431 & 2.64038278475693 \tabularnewline
16 & 12 & 10.9779389911323 & 1.02206100886766 \tabularnewline
17 & 10 & 10.9005605867273 & -0.900560586727283 \tabularnewline
18 & 12 & 13.9688129209198 & -1.96881292091981 \tabularnewline
19 & 11 & 12.6489614691705 & -1.64896146917047 \tabularnewline
20 & 12 & 11.7219221806054 & 0.278077819394625 \tabularnewline
21 & 11 & 11.4889347054842 & -0.488934705484191 \tabularnewline
22 & 12 & 11.7562561894795 & 0.243743810520493 \tabularnewline
23 & 13 & 13.4354747239121 & -0.435474723912124 \tabularnewline
24 & 11 & 11.8624855646341 & -0.862485564634076 \tabularnewline
25 & 12 & 11.9282200227793 & 0.0717799772206508 \tabularnewline
26 & 13 & 12.2135741893444 & 0.786425810655615 \tabularnewline
27 & 10 & 11.5027987692270 & -1.50279876922704 \tabularnewline
28 & 14 & 11.3012780588814 & 2.69872194111857 \tabularnewline
29 & 12 & 11.7421097632182 & 0.257890236781846 \tabularnewline
30 & 10 & 10.4313452433833 & -0.4313452433833 \tabularnewline
31 & 12 & 11.1634780878973 & 0.836521912102709 \tabularnewline
32 & 8 & 9.38691714928457 & -1.38691714928457 \tabularnewline
33 & 10 & 10.5275144095249 & -0.527514409524899 \tabularnewline
34 & 12 & 11.8262790182354 & 0.173720981764614 \tabularnewline
35 & 12 & 10.3310158433209 & 1.66898415667909 \tabularnewline
36 & 7 & 8.22304791725442 & -1.22304791725442 \tabularnewline
37 & 9 & 8.27771069000058 & 0.722289309999418 \tabularnewline
38 & 12 & 10.3684864142427 & 1.63151358575735 \tabularnewline
39 & 10 & 11.7282456994753 & -1.72824569947530 \tabularnewline
40 & 10 & 11.4946027128326 & -1.49460271283256 \tabularnewline
41 & 10 & 11.4255615460812 & -1.42556154608124 \tabularnewline
42 & 12 & 10.6250803965427 & 1.37491960345726 \tabularnewline
43 & 15 & 13.5925928314646 & 1.40740716853544 \tabularnewline
44 & 10 & 10.4090027607275 & -0.409002760727462 \tabularnewline
45 & 10 & 10.4593641182936 & -0.459364118293577 \tabularnewline
46 & 12 & 9.03743048074102 & 2.96256951925898 \tabularnewline
47 & 13 & 10.7272823341297 & 2.27271766587031 \tabularnewline
48 & 11 & 11.219122522648 & -0.21912252264801 \tabularnewline
49 & 11 & 11.8059502543634 & -0.805950254363357 \tabularnewline
50 & 12 & 10.3357929751493 & 1.66420702485073 \tabularnewline
51 & 14 & 11.8680593892433 & 2.13194061075675 \tabularnewline
52 & 10 & 10.3575269448036 & -0.357526944803612 \tabularnewline
53 & 12 & 9.36316946084643 & 2.63683053915357 \tabularnewline
54 & 13 & 11.8778960154185 & 1.12210398458151 \tabularnewline
55 & 5 & 7.68769600146292 & -2.68769600146292 \tabularnewline
56 & 6 & 10.6431130791125 & -4.64311307911245 \tabularnewline
57 & 12 & 11.6778457282952 & 0.322154271704802 \tabularnewline
58 & 12 & 11.8194881676232 & 0.180511832376788 \tabularnewline
59 & 11 & 11.0029037055735 & -0.00290370557348595 \tabularnewline
60 & 10 & 11.7672156589186 & -1.76721565891855 \tabularnewline
61 & 7 & 9.29516035087435 & -2.29516035087435 \tabularnewline
62 & 12 & 11.4791922620481 & 0.520807737951855 \tabularnewline
63 & 14 & 11.8139143430140 & 2.18608565698597 \tabularnewline
64 & 11 & 10.7317333154751 & 0.268266684524943 \tabularnewline
65 & 12 & 11.6801418095975 & 0.319858190402492 \tabularnewline
66 & 13 & 12.1666317563444 & 0.833368243655612 \tabularnewline
67 & 14 & 12.8820901255509 & 1.11790987444909 \tabularnewline
68 & 11 & 12.5185170738355 & -1.51851707383551 \tabularnewline
69 & 12 & 9.6436961008084 & 2.3563038991916 \tabularnewline
70 & 12 & 11.5738536547622 & 0.426146345237827 \tabularnewline
71 & 8 & 8.23475708095421 & -0.234757080954212 \tabularnewline
72 & 11 & 10.7866280559650 & 0.213371944034974 \tabularnewline
73 & 14 & 12.9696783051343 & 1.03032169486574 \tabularnewline
74 & 14 & 12.7261986923163 & 1.27380130768372 \tabularnewline
75 & 12 & 11.3617210549360 & 0.638278945063967 \tabularnewline
76 & 9 & 12.1641120922043 & -3.16411209220434 \tabularnewline
77 & 13 & 11.7683385021824 & 1.23166149781764 \tabularnewline
78 & 11 & 11.6983156734265 & -0.698315673426478 \tabularnewline
79 & 12 & 9.8784749752844 & 2.12152502471561 \tabularnewline
80 & 12 & 11.3219544027120 & 0.678045597288026 \tabularnewline
81 & 12 & 11.5760085548052 & 0.423991445194768 \tabularnewline
82 & 12 & 11.8130234674940 & 0.186976532505967 \tabularnewline
83 & 12 & 10.8934873735966 & 1.10651262640339 \tabularnewline
84 & 11 & 11.2323780733894 & -0.232378073389363 \tabularnewline
85 & 10 & 11.7024842922533 & -1.70248429225335 \tabularnewline
86 & 9 & 10.4881125213978 & -1.48811252139783 \tabularnewline
87 & 12 & 11.7755528965723 & 0.224447103427715 \tabularnewline
88 & 12 & 11.7889496285729 & 0.211050371427111 \tabularnewline
89 & 12 & 11.2674617765242 & 0.732538223475755 \tabularnewline
90 & 9 & 9.63414183715167 & -0.634141837151667 \tabularnewline
91 & 15 & 12.2435042153932 & 2.75649578460679 \tabularnewline
92 & 12 & 11.9104482732526 & 0.0895517267473811 \tabularnewline
93 & 12 & 11.0953277966660 & 0.90467220333403 \tabularnewline
94 & 12 & 10.0982068996642 & 1.90179310033577 \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 & -0.494577221527005 \tabularnewline
100 & 14 & 11.7307267500014 & 2.26927324999864 \tabularnewline
101 & 11 & 11.5258909461436 & -0.52589094614363 \tabularnewline
102 & 15 & 13.9800547528774 & 1.01994524712264 \tabularnewline
103 & 11 & 10.8834187796776 & 0.116581220322435 \tabularnewline
104 & 11 & 11.8882469718560 & -0.888246971856032 \tabularnewline
105 & 12 & 9.79828615931472 & 2.20171384068528 \tabularnewline
106 & 12 & 12.2628009224860 & -0.262800922485987 \tabularnewline
107 & 12 & 11.5430327531933 & 0.456967246806652 \tabularnewline
108 & 11 & 11.5573203607140 & -0.557320360713953 \tabularnewline
109 & 7 & 9.6848209602947 & -2.68482096029471 \tabularnewline
110 & 12 & 11.8062326168819 & 0.193767383118141 \tabularnewline
111 & 14 & 11.8049685923588 & 2.1950314076412 \tabularnewline
112 & 11 & 12.5157322313154 & -1.51573223131544 \tabularnewline
113 & 10 & 9.49680919790977 & 0.503190802090228 \tabularnewline
114 & 13 & 12.5111614981863 & 0.48883850181367 \tabularnewline
115 & 13 & 10.8270032211906 & 2.17299677880942 \tabularnewline
116 & 8 & 10.8137476704492 & -2.81374767044923 \tabularnewline
117 & 11 & 10.1578787719826 & 0.84212122801744 \tabularnewline
118 & 12 & 11.7579875457448 & 0.242012454255186 \tabularnewline
119 & 11 & 9.98559522595896 & 1.01440477404104 \tabularnewline
120 & 13 & 11.6315705879775 & 1.36842941202253 \tabularnewline
121 & 12 & 10.1799388921199 & 1.82006110788010 \tabularnewline
122 & 14 & 11.8108685674510 & 2.18913143254903 \tabularnewline
123 & 13 & 11.1062872661050 & 1.89371273389499 \tabularnewline
124 & 15 & 11.7867947285298 & 3.21320527147017 \tabularnewline
125 & 10 & 10.8335331387598 & -0.833533138759769 \tabularnewline
126 & 11 & 12.2716054918820 & -1.27160549188197 \tabularnewline
127 & 9 & 11.2314871978694 & -2.23148719786936 \tabularnewline
128 & 11 & 9.52622489369629 & 1.47377510630371 \tabularnewline
129 & 10 & 11.5343693650566 & -1.53436936505662 \tabularnewline
130 & 11 & 8.31532244218158 & 2.68467755781842 \tabularnewline
131 & 8 & 11.7467457137873 & -3.74674571378727 \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 & -0.695616889985518 \tabularnewline
136 & 11 & 11.0001402925289 & -0.000140292528927985 \tabularnewline
137 & 10 & 9.1302193359305 & 0.869780664069505 \tabularnewline
138 & 8 & 9.55058109513593 & -1.55058109513593 \tabularnewline
139 & 9 & 8.85962010862831 & 0.140379891371689 \tabularnewline
140 & 8 & 11.7797215153992 & -3.77972151539915 \tabularnewline
141 & 9 & 11.0837010345447 & -2.08370103454466 \tabularnewline
142 & 15 & 12.3870191922458 & 2.61298080775422 \tabularnewline
143 & 11 & 11.2858890375725 & -0.285889037572535 \tabularnewline
144 & 8 & 8.30746092117616 & -0.307460921176164 \tabularnewline
145 & 13 & 12.6948280574267 & 0.305171942573276 \tabularnewline
146 & 12 & 9.93055930420974 & 2.06944069579026 \tabularnewline
147 & 12 & 11.4947438940918 & 0.505256105908191 \tabularnewline
148 & 9 & 9.86456391302148 & -0.864563913021481 \tabularnewline
149 & 7 & 8.52882163417604 & -1.52882163417604 \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 & -2.66002291841837 \tabularnewline
154 & 8 & 8.4275105721091 & -0.42751057210909 \tabularnewline
155 & 6 & 10.2198467256032 & -4.2198467256032 \tabularnewline
156 & 9 & 11.2314871978694 & -2.23148719786936 \tabularnewline
157 & 11 & 11.7226718748661 & -0.722671874866125 \tabularnewline
158 & 8 & 9.71503334886203 & -1.71503334886203 \tabularnewline
159 & 10 & 9.36280814160856 & 0.63719185839144 \tabularnewline
160 & 8 & 8.72609476897542 & -0.726094768975418 \tabularnewline
161 & 14 & 11.5223426700835 & 2.47765732991655 \tabularnewline
162 & 10 & 10.9205066018859 & -0.920506601885934 \tabularnewline
163 & 8 & 7.84888234164735 & 0.151117658352652 \tabularnewline
164 & 11 & 10.0045306138139 & 0.995469386186124 \tabularnewline
165 & 12 & 8.47801655579358 & 3.52198344420642 \tabularnewline
166 & 12 & 9.81055044834119 & 2.18944955165881 \tabularnewline
167 & 12 & 11.2818436153885 & 0.718156384611474 \tabularnewline
168 & 5 & 8.79560326746899 & -3.79560326746899 \tabularnewline
169 & 12 & 11.3381049480468 & 0.661895051953185 \tabularnewline
170 & 10 & 8.85817973409113 & 1.14182026590887 \tabularnewline
171 & 7 & 7.33447608763545 & -0.334476087635453 \tabularnewline
172 & 12 & 8.92952536705084 & 3.07047463294916 \tabularnewline
173 & 11 & 10.5831622891347 & 0.416837710865262 \tabularnewline
174 & 8 & 9.10165934690911 & -1.10165934690911 \tabularnewline
175 & 9 & 8.85494898930433 & 0.145051010695673 \tabularnewline
176 & 10 & 10.1635586090961 & -0.163558609096121 \tabularnewline
177 & 9 & 9.16765473809737 & -0.167654738097374 \tabularnewline
178 & 12 & 11.3319226104361 & 0.668077389563862 \tabularnewline
179 & 6 & 8.23224086167329 & -2.23224086167329 \tabularnewline
180 & 15 & 12.7919739455259 & 2.20802605447407 \tabularnewline
181 & 12 & 10.4214734484532 & 1.57852655154680 \tabularnewline
182 & 12 & 6.92572930939062 & 5.07427069060938 \tabularnewline
183 & 12 & 11.3940317453160 & 0.605968254683965 \tabularnewline
184 & 11 & 11.5913838368348 & -0.591383836834775 \tabularnewline
185 & 7 & 8.9719142510602 & -1.97191425106020 \tabularnewline
186 & 7 & 8.27631731398346 & -1.27631731398346 \tabularnewline
187 & 5 & 8.4363185863642 & -3.43631858636419 \tabularnewline
188 & 12 & 10.3175187251254 & 1.68248127487457 \tabularnewline
189 & 12 & 11.4028363147120 & 0.597163685287982 \tabularnewline
190 & 3 & 9.11341550912896 & -6.11341550912896 \tabularnewline
191 & 11 & 11.3967951583606 & -0.396795158360593 \tabularnewline
192 & 10 & 9.6364027496991 & 0.363597250300891 \tabularnewline
193 & 12 & 10.5990400716614 & 1.40095992833860 \tabularnewline
194 & 9 & 11.2366527047206 & -2.23665270472061 \tabularnewline
195 & 12 & 11.3960454640998 & 0.603954535900156 \tabularnewline
196 & 9 & 10.0192855530767 & -1.01928555307673 \tabularnewline
197 & 12 & 11.0715835530869 & 0.928416446913057 \tabularnewline
198 & 10 & 10.0019083820286 & -0.00190838202856881 \tabularnewline
199 & 9 & 8.23350488619634 & 0.766495113803655 \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 & 0.91216551538334 \tabularnewline
205 & 10 & 8.29205391525087 & 1.70794608474913 \tabularnewline
206 & 10 & 10.4806779890293 & -0.480677989029284 \tabularnewline
207 & 12 & 9.14142599913317 & 2.85857400086683 \tabularnewline
208 & 12 & 9.01377702364655 & 2.98622297635345 \tabularnewline
209 & 11 & 10.6987609587223 & 0.301239041277706 \tabularnewline
210 & 8 & 10.5638655820420 & -2.56386558204196 \tabularnewline
211 & 12 & 11.3480827554813 & 0.6519172445187 \tabularnewline
212 & 10 & 9.82710517186493 & 0.172894828135075 \tabularnewline
213 & 11 & 11.8674157074869 & -0.867415707486885 \tabularnewline
214 & 10 & 10.1487566713132 & -0.148756671313207 \tabularnewline
215 & 8 & 9.48088786172217 & -1.48088786172217 \tabularnewline
216 & 12 & 10.8485608408308 & 1.15143915916920 \tabularnewline
217 & 12 & 9.41817021384078 & 2.58182978615922 \tabularnewline
218 & 10 & 9.95338094837302 & 0.0466190516269787 \tabularnewline
219 & 12 & 10.7632687425498 & 1.23673125745024 \tabularnewline
220 & 9 & 8.86314504569881 & 0.136854954301189 \tabularnewline
221 & 6 & 6.98802341349426 & -0.988023413494258 \tabularnewline
222 & 10 & 9.92148420206045 & 0.0785157979395493 \tabularnewline
223 & 9 & 10.0072940268584 & -1.00729402685843 \tabularnewline
224 & 9 & 8.363999676306 & 0.636000323693995 \tabularnewline
225 & 9 & 8.93279472545163 & 0.067205274548368 \tabularnewline
226 & 6 & 9.5702661772516 & -3.57026617725160 \tabularnewline
227 & 10 & 7.94260586032131 & 2.05739413967869 \tabularnewline
228 & 6 & 11.0879756658759 & -5.08797566587591 \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 & 9.24060359063258 & 2.75939640936742 \tabularnewline
234 & 12 & 11.3392781860853 & 0.660721813914683 \tabularnewline
235 & 7 & 7.67656018200976 & -0.676560182009761 \tabularnewline
236 & 8 & 8.94342804440768 & -0.943428044407678 \tabularnewline
237 & 11 & 8.94679997045374 & 2.05320002954627 \tabularnewline
238 & 3 & 7.73806080388816 & -4.73806080388816 \tabularnewline
239 & 6 & 9.4090832819263 & -3.40908328192629 \tabularnewline
240 & 8 & 8.9990724791584 & -0.999072479158396 \tabularnewline
241 & 9 & 10.0358188471249 & -1.03581884712495 \tabularnewline
242 & 9 & 7.95043715261881 & 1.04956284738119 \tabularnewline
243 & 8 & 9.03889791106322 & -1.03889791106322 \tabularnewline
244 & 9 & 8.9698567443119 & 0.0301432556881003 \tabularnewline
245 & 7 & 8.36451400656831 & -1.36451400656831 \tabularnewline
246 & 7 & 7.7601209240255 & -0.760120924025495 \tabularnewline
247 & 6 & 9.10292337143217 & -3.10292337143217 \tabularnewline
248 & 9 & 11.2833513888161 & -2.28335138881610 \tabularnewline
249 & 10 & 8.8352287384338 & 1.16477126156620 \tabularnewline
250 & 11 & 9.96968227467744 & 1.03031772532257 \tabularnewline
251 & 12 & 11.1757992094577 & 0.824200790542298 \tabularnewline
252 & 8 & 10.2515233339372 & -2.25152333393716 \tabularnewline
253 & 11 & 9.61883739887164 & 1.38116260112836 \tabularnewline
254 & 3 & 4.66726737608007 & -1.66726737608007 \tabularnewline
255 & 11 & 10.7577419164606 & 0.242258083539354 \tabularnewline
256 & 12 & 8.42217216010284 & 3.57782783989716 \tabularnewline
257 & 7 & 8.36662190809131 & -1.36662190809131 \tabularnewline
258 & 9 & 9.99342996311558 & -0.993429963115582 \tabularnewline
259 & 12 & 10.5247074428194 & 1.4752925571806 \tabularnewline
260 & 8 & 10.2270259512383 & -2.22702595123827 \tabularnewline
261 & 11 & 9.43943685175287 & 1.56056314824713 \tabularnewline
262 & 8 & 8.26769771381123 & -0.267697713811227 \tabularnewline
263 & 10 & 10.7184425959788 & -0.718442595978835 \tabularnewline
264 & 8 & 8.31959707351283 & -0.31959707351283 \tabularnewline
265 & 7 & 9.45779568480558 & -2.45779568480558 \tabularnewline
266 & 8 & 9.55930670781255 & -1.55930670781255 \tabularnewline
267 & 10 & 11.2770278699462 & -1.27702786994617 \tabularnewline
268 & 8 & 9.56229370369485 & -1.56229370369485 \tabularnewline
269 & 12 & 11.3542650930920 & 0.645734906908023 \tabularnewline
270 & 14 & 11.0643691586970 & 2.93563084130299 \tabularnewline
271 & 7 & 9.0749044965219 & -2.07490449652189 \tabularnewline
272 & 6 & 6.26601794258008 & -0.266017942580075 \tabularnewline
273 & 11 & 11.0441815760842 & -0.0441815760842363 \tabularnewline
274 & 4 & 5.40407478477717 & -1.40407478477717 \tabularnewline
275 & 9 & 11.1638076832394 & -2.16380768323941 \tabularnewline
276 & 5 & 4.25160999543932 & 0.748390004560678 \tabularnewline
277 & 9 & 8.84342479482828 & 0.156575205171720 \tabularnewline
278 & 11 & 10.4612401006773 & 0.538759899322745 \tabularnewline
279 & 12 & 10.2192030438468 & 1.78079695615316 \tabularnewline
280 & 9 & 8.37004083265743 & 0.62995916734257 \tabularnewline
281 & 12 & 10.9353737571089 & 1.06462624289115 \tabularnewline
282 & 10 & 10.7867340684694 & -0.786734068469408 \tabularnewline
283 & 9 & 8.86127250817425 & 0.138727491825746 \tabularnewline
284 & 6 & 5.80078624883922 & 0.199213751160785 \tabularnewline
285 & 10 & 11.1433377381081 & -1.14333773810813 \tabularnewline
286 & 9 & 7.79051828181657 & 1.20948171818343 \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=113623&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]10.1249029703703[/C][C]1.87509702962968[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]11.6109594615870[/C][C]-0.610959461586962[/C][/ROW]
[ROW][C]3[/C][C]15[/C][C]13.5089668720088[/C][C]1.4910331279912[/C][/ROW]
[ROW][C]4[/C][C]6[/C][C]11.0093684057027[/C][C]-5.00936840570268[/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]9.94888273420403[/C][C]0.0511172657959684[/C][/ROW]
[ROW][C]7[/C][C]12[/C][C]13.2649813138346[/C][C]-1.26498131383459[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]11.2636663067004[/C][C]2.73633369329956[/C][/ROW]
[ROW][C]9[/C][C]12[/C][C]10.6563686298538[/C][C]1.34363137014619[/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]0.469190740768752[/C][/ROW]
[ROW][C]14[/C][C]11[/C][C]11.7752705340538[/C][C]-0.775270534053783[/C][/ROW]
[ROW][C]15[/C][C]15[/C][C]12.3596172152431[/C][C]2.64038278475693[/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]-0.900560586727283[/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]0.278077819394625[/C][/ROW]
[ROW][C]21[/C][C]11[/C][C]11.4889347054842[/C][C]-0.488934705484191[/C][/ROW]
[ROW][C]22[/C][C]12[/C][C]11.7562561894795[/C][C]0.243743810520493[/C][/ROW]
[ROW][C]23[/C][C]13[/C][C]13.4354747239121[/C][C]-0.435474723912124[/C][/ROW]
[ROW][C]24[/C][C]11[/C][C]11.8624855646341[/C][C]-0.862485564634076[/C][/ROW]
[ROW][C]25[/C][C]12[/C][C]11.9282200227793[/C][C]0.0717799772206508[/C][/ROW]
[ROW][C]26[/C][C]13[/C][C]12.2135741893444[/C][C]0.786425810655615[/C][/ROW]
[ROW][C]27[/C][C]10[/C][C]11.5027987692270[/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]0.257890236781846[/C][/ROW]
[ROW][C]30[/C][C]10[/C][C]10.4313452433833[/C][C]-0.4313452433833[/C][/ROW]
[ROW][C]31[/C][C]12[/C][C]11.1634780878973[/C][C]0.836521912102709[/C][/ROW]
[ROW][C]32[/C][C]8[/C][C]9.38691714928457[/C][C]-1.38691714928457[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.5275144095249[/C][C]-0.527514409524899[/C][/ROW]
[ROW][C]34[/C][C]12[/C][C]11.8262790182354[/C][C]0.173720981764614[/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]0.722289309999418[/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]-1.72824569947530[/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]-1.42556154608124[/C][/ROW]
[ROW][C]42[/C][C]12[/C][C]10.6250803965427[/C][C]1.37491960345726[/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]-0.409002760727462[/C][/ROW]
[ROW][C]45[/C][C]10[/C][C]10.4593641182936[/C][C]-0.459364118293577[/C][/ROW]
[ROW][C]46[/C][C]12[/C][C]9.03743048074102[/C][C]2.96256951925898[/C][/ROW]
[ROW][C]47[/C][C]13[/C][C]10.7272823341297[/C][C]2.27271766587031[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]11.219122522648[/C][C]-0.21912252264801[/C][/ROW]
[ROW][C]49[/C][C]11[/C][C]11.8059502543634[/C][C]-0.805950254363357[/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]9.36316946084643[/C][C]2.63683053915357[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]11.8778960154185[/C][C]1.12210398458151[/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]10.6431130791125[/C][C]-4.64311307911245[/C][/ROW]
[ROW][C]57[/C][C]12[/C][C]11.6778457282952[/C][C]0.322154271704802[/C][/ROW]
[ROW][C]58[/C][C]12[/C][C]11.8194881676232[/C][C]0.180511832376788[/C][/ROW]
[ROW][C]59[/C][C]11[/C][C]11.0029037055735[/C][C]-0.00290370557348595[/C][/ROW]
[ROW][C]60[/C][C]10[/C][C]11.7672156589186[/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]0.520807737951855[/C][/ROW]
[ROW][C]63[/C][C]14[/C][C]11.8139143430140[/C][C]2.18608565698597[/C][/ROW]
[ROW][C]64[/C][C]11[/C][C]10.7317333154751[/C][C]0.268266684524943[/C][/ROW]
[ROW][C]65[/C][C]12[/C][C]11.6801418095975[/C][C]0.319858190402492[/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]9.6436961008084[/C][C]2.3563038991916[/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]-0.234757080954212[/C][/ROW]
[ROW][C]72[/C][C]11[/C][C]10.7866280559650[/C][C]0.213371944034974[/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]11.3617210549360[/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]-0.698315673426478[/C][/ROW]
[ROW][C]79[/C][C]12[/C][C]9.8784749752844[/C][C]2.12152502471561[/C][/ROW]
[ROW][C]80[/C][C]12[/C][C]11.3219544027120[/C][C]0.678045597288026[/C][/ROW]
[ROW][C]81[/C][C]12[/C][C]11.5760085548052[/C][C]0.423991445194768[/C][/ROW]
[ROW][C]82[/C][C]12[/C][C]11.8130234674940[/C][C]0.186976532505967[/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]-0.232378073389363[/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]-1.48811252139783[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]11.7755528965723[/C][C]0.224447103427715[/C][/ROW]
[ROW][C]88[/C][C]12[/C][C]11.7889496285729[/C][C]0.211050371427111[/C][/ROW]
[ROW][C]89[/C][C]12[/C][C]11.2674617765242[/C][C]0.732538223475755[/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]0.0895517267473811[/C][/ROW]
[ROW][C]93[/C][C]12[/C][C]11.0953277966660[/C][C]0.90467220333403[/C][/ROW]
[ROW][C]94[/C][C]12[/C][C]10.0982068996642[/C][C]1.90179310033577[/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]-0.494577221527005[/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]-0.52589094614363[/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]11.8882469718560[/C][C]-0.888246971856032[/C][/ROW]
[ROW][C]105[/C][C]12[/C][C]9.79828615931472[/C][C]2.20171384068528[/C][/ROW]
[ROW][C]106[/C][C]12[/C][C]12.2628009224860[/C][C]-0.262800922485987[/C][/ROW]
[ROW][C]107[/C][C]12[/C][C]11.5430327531933[/C][C]0.456967246806652[/C][/ROW]
[ROW][C]108[/C][C]11[/C][C]11.5573203607140[/C][C]-0.557320360713953[/C][/ROW]
[ROW][C]109[/C][C]7[/C][C]9.6848209602947[/C][C]-2.68482096029471[/C][/ROW]
[ROW][C]110[/C][C]12[/C][C]11.8062326168819[/C][C]0.193767383118141[/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]0.503190802090228[/C][/ROW]
[ROW][C]114[/C][C]13[/C][C]12.5111614981863[/C][C]0.48883850181367[/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]0.84212122801744[/C][/ROW]
[ROW][C]118[/C][C]12[/C][C]11.7579875457448[/C][C]0.242012454255186[/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]1.82006110788010[/C][/ROW]
[ROW][C]122[/C][C]14[/C][C]11.8108685674510[/C][C]2.18913143254903[/C][/ROW]
[ROW][C]123[/C][C]13[/C][C]11.1062872661050[/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]-0.833533138759769[/C][/ROW]
[ROW][C]126[/C][C]11[/C][C]12.2716054918820[/C][C]-1.27160549188197[/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]9.52622489369629[/C][C]1.47377510630371[/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]-3.74674571378727[/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]-0.695616889985518[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]11.0001402925289[/C][C]-0.000140292528927985[/C][/ROW]
[ROW][C]137[/C][C]10[/C][C]9.1302193359305[/C][C]0.869780664069505[/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]0.140379891371689[/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]-2.08370103454466[/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]-0.285889037572535[/C][/ROW]
[ROW][C]144[/C][C]8[/C][C]8.30746092117616[/C][C]-0.307460921176164[/C][/ROW]
[ROW][C]145[/C][C]13[/C][C]12.6948280574267[/C][C]0.305171942573276[/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]0.505256105908191[/C][/ROW]
[ROW][C]148[/C][C]9[/C][C]9.86456391302148[/C][C]-0.864563913021481[/C][/ROW]
[ROW][C]149[/C][C]7[/C][C]8.52882163417604[/C][C]-1.52882163417604[/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]-2.66002291841837[/C][/ROW]
[ROW][C]154[/C][C]8[/C][C]8.4275105721091[/C][C]-0.42751057210909[/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]-0.722671874866125[/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]0.63719185839144[/C][/ROW]
[ROW][C]160[/C][C]8[/C][C]8.72609476897542[/C][C]-0.726094768975418[/C][/ROW]
[ROW][C]161[/C][C]14[/C][C]11.5223426700835[/C][C]2.47765732991655[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]10.9205066018859[/C][C]-0.920506601885934[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]7.84888234164735[/C][C]0.151117658352652[/C][/ROW]
[ROW][C]164[/C][C]11[/C][C]10.0045306138139[/C][C]0.995469386186124[/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]0.718156384611474[/C][/ROW]
[ROW][C]168[/C][C]5[/C][C]8.79560326746899[/C][C]-3.79560326746899[/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]8.85817973409113[/C][C]1.14182026590887[/C][/ROW]
[ROW][C]171[/C][C]7[/C][C]7.33447608763545[/C][C]-0.334476087635453[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]8.92952536705084[/C][C]3.07047463294916[/C][/ROW]
[ROW][C]173[/C][C]11[/C][C]10.5831622891347[/C][C]0.416837710865262[/C][/ROW]
[ROW][C]174[/C][C]8[/C][C]9.10165934690911[/C][C]-1.10165934690911[/C][/ROW]
[ROW][C]175[/C][C]9[/C][C]8.85494898930433[/C][C]0.145051010695673[/C][/ROW]
[ROW][C]176[/C][C]10[/C][C]10.1635586090961[/C][C]-0.163558609096121[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]9.16765473809737[/C][C]-0.167654738097374[/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]8.23224086167329[/C][C]-2.23224086167329[/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]1.57852655154680[/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]11.3940317453160[/C][C]0.605968254683965[/C][/ROW]
[ROW][C]184[/C][C]11[/C][C]11.5913838368348[/C][C]-0.591383836834775[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]8.9719142510602[/C][C]-1.97191425106020[/C][/ROW]
[ROW][C]186[/C][C]7[/C][C]8.27631731398346[/C][C]-1.27631731398346[/C][/ROW]
[ROW][C]187[/C][C]5[/C][C]8.4363185863642[/C][C]-3.43631858636419[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]10.3175187251254[/C][C]1.68248127487457[/C][/ROW]
[ROW][C]189[/C][C]12[/C][C]11.4028363147120[/C][C]0.597163685287982[/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]-0.396795158360593[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]9.6364027496991[/C][C]0.363597250300891[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]10.5990400716614[/C][C]1.40095992833860[/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]0.603954535900156[/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]0.928416446913057[/C][/ROW]
[ROW][C]198[/C][C]10[/C][C]10.0019083820286[/C][C]-0.00190838202856881[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]8.23350488619634[/C][C]0.766495113803655[/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]0.91216551538334[/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]-0.480677989029284[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]9.14142599913317[/C][C]2.85857400086683[/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]0.301239041277706[/C][/ROW]
[ROW][C]210[/C][C]8[/C][C]10.5638655820420[/C][C]-2.56386558204196[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]11.3480827554813[/C][C]0.6519172445187[/C][/ROW]
[ROW][C]212[/C][C]10[/C][C]9.82710517186493[/C][C]0.172894828135075[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]11.8674157074869[/C][C]-0.867415707486885[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]10.1487566713132[/C][C]-0.148756671313207[/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]1.15143915916920[/C][/ROW]
[ROW][C]217[/C][C]12[/C][C]9.41817021384078[/C][C]2.58182978615922[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]9.95338094837302[/C][C]0.0466190516269787[/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]0.136854954301189[/C][/ROW]
[ROW][C]221[/C][C]6[/C][C]6.98802341349426[/C][C]-0.988023413494258[/C][/ROW]
[ROW][C]222[/C][C]10[/C][C]9.92148420206045[/C][C]0.0785157979395493[/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]0.636000323693995[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]8.93279472545163[/C][C]0.067205274548368[/C][/ROW]
[ROW][C]226[/C][C]6[/C][C]9.5702661772516[/C][C]-3.57026617725160[/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]-5.08797566587591[/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]9.24060359063258[/C][C]2.75939640936742[/C][/ROW]
[ROW][C]234[/C][C]12[/C][C]11.3392781860853[/C][C]0.660721813914683[/C][/ROW]
[ROW][C]235[/C][C]7[/C][C]7.67656018200976[/C][C]-0.676560182009761[/C][/ROW]
[ROW][C]236[/C][C]8[/C][C]8.94342804440768[/C][C]-0.943428044407678[/C][/ROW]
[ROW][C]237[/C][C]11[/C][C]8.94679997045374[/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]9.4090832819263[/C][C]-3.40908328192629[/C][/ROW]
[ROW][C]240[/C][C]8[/C][C]8.9990724791584[/C][C]-0.999072479158396[/C][/ROW]
[ROW][C]241[/C][C]9[/C][C]10.0358188471249[/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]9.03889791106322[/C][C]-1.03889791106322[/C][/ROW]
[ROW][C]244[/C][C]9[/C][C]8.9698567443119[/C][C]0.0301432556881003[/C][/ROW]
[ROW][C]245[/C][C]7[/C][C]8.36451400656831[/C][C]-1.36451400656831[/C][/ROW]
[ROW][C]246[/C][C]7[/C][C]7.7601209240255[/C][C]-0.760120924025495[/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]-2.28335138881610[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]8.8352287384338[/C][C]1.16477126156620[/C][/ROW]
[ROW][C]250[/C][C]11[/C][C]9.96968227467744[/C][C]1.03031772532257[/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]9.61883739887164[/C][C]1.38116260112836[/C][/ROW]
[ROW][C]254[/C][C]3[/C][C]4.66726737608007[/C][C]-1.66726737608007[/C][/ROW]
[ROW][C]255[/C][C]11[/C][C]10.7577419164606[/C][C]0.242258083539354[/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]8.36662190809131[/C][C]-1.36662190809131[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]9.99342996311558[/C][C]-0.993429963115582[/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]-2.22702595123827[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]9.43943685175287[/C][C]1.56056314824713[/C][/ROW]
[ROW][C]262[/C][C]8[/C][C]8.26769771381123[/C][C]-0.267697713811227[/C][/ROW]
[ROW][C]263[/C][C]10[/C][C]10.7184425959788[/C][C]-0.718442595978835[/C][/ROW]
[ROW][C]264[/C][C]8[/C][C]8.31959707351283[/C][C]-0.31959707351283[/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]9.56229370369485[/C][C]-1.56229370369485[/C][/ROW]
[ROW][C]269[/C][C]12[/C][C]11.3542650930920[/C][C]0.645734906908023[/C][/ROW]
[ROW][C]270[/C][C]14[/C][C]11.0643691586970[/C][C]2.93563084130299[/C][/ROW]
[ROW][C]271[/C][C]7[/C][C]9.0749044965219[/C][C]-2.07490449652189[/C][/ROW]
[ROW][C]272[/C][C]6[/C][C]6.26601794258008[/C][C]-0.266017942580075[/C][/ROW]
[ROW][C]273[/C][C]11[/C][C]11.0441815760842[/C][C]-0.0441815760842363[/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]4.25160999543932[/C][C]0.748390004560678[/C][/ROW]
[ROW][C]277[/C][C]9[/C][C]8.84342479482828[/C][C]0.156575205171720[/C][/ROW]
[ROW][C]278[/C][C]11[/C][C]10.4612401006773[/C][C]0.538759899322745[/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]0.62995916734257[/C][/ROW]
[ROW][C]281[/C][C]12[/C][C]10.9353737571089[/C][C]1.06462624289115[/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]8.86127250817425[/C][C]0.138727491825746[/C][/ROW]
[ROW][C]284[/C][C]6[/C][C]5.80078624883922[/C][C]0.199213751160785[/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]1.20948171818343[/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=113623&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113623&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11210.12490297037031.87509702962968
21111.6109594615870-0.610959461586962
31513.50896687200881.4910331279912
4611.0093684057027-5.00936840570268
51310.72250520230132.27749479769868
6109.948882734204030.0511172657959684
71213.2649813138346-1.26498131383459
81411.26366630670042.73633369329956
91210.65636862985381.34363137014619
10911.2635251254412-2.26352512544118
111011.3697759300713-1.36977593007127
121211.69035158477580.309648415224199
131211.53080925923120.469190740768752
141111.7752705340538-0.775270534053783
151512.35961721524312.64038278475693
161210.97793899113231.02206100886766
171010.9005605867273-0.900560586727283
181213.9688129209198-1.96881292091981
191112.6489614691705-1.64896146917047
201211.72192218060540.278077819394625
211111.4889347054842-0.488934705484191
221211.75625618947950.243743810520493
231313.4354747239121-0.435474723912124
241111.8624855646341-0.862485564634076
251211.92822002277930.0717799772206508
261312.21357418934440.786425810655615
271011.5027987692270-1.50279876922704
281411.30127805888142.69872194111857
291211.74210976321820.257890236781846
301010.4313452433833-0.4313452433833
311211.16347808789730.836521912102709
3289.38691714928457-1.38691714928457
331010.5275144095249-0.527514409524899
341211.82627901823540.173720981764614
351210.33101584332091.66898415667909
3678.22304791725442-1.22304791725442
3798.277710690000580.722289309999418
381210.36848641424271.63151358575735
391011.7282456994753-1.72824569947530
401011.4946027128326-1.49460271283256
411011.4255615460812-1.42556154608124
421210.62508039654271.37491960345726
431513.59259283146461.40740716853544
441010.4090027607275-0.409002760727462
451010.4593641182936-0.459364118293577
46129.037430480741022.96256951925898
471310.72728233412972.27271766587031
481111.219122522648-0.21912252264801
491111.8059502543634-0.805950254363357
501210.33579297514931.66420702485073
511411.86805938924332.13194061075675
521010.3575269448036-0.357526944803612
53129.363169460846432.63683053915357
541311.87789601541851.12210398458151
5557.68769600146292-2.68769600146292
56610.6431130791125-4.64311307911245
571211.67784572829520.322154271704802
581211.81948816762320.180511832376788
591111.0029037055735-0.00290370557348595
601011.7672156589186-1.76721565891855
6179.29516035087435-2.29516035087435
621211.47919226204810.520807737951855
631411.81391434301402.18608565698597
641110.73173331547510.268266684524943
651211.68014180959750.319858190402492
661312.16663175634440.833368243655612
671412.88209012555091.11790987444909
681112.5185170738355-1.51851707383551
69129.64369610080842.3563038991916
701211.57385365476220.426146345237827
7188.23475708095421-0.234757080954212
721110.78662805596500.213371944034974
731412.96967830513431.03032169486574
741412.72619869231631.27380130768372
751211.36172105493600.638278945063967
76912.1641120922043-3.16411209220434
771311.76833850218241.23166149781764
781111.6983156734265-0.698315673426478
79129.87847497528442.12152502471561
801211.32195440271200.678045597288026
811211.57600855480520.423991445194768
821211.81302346749400.186976532505967
831210.89348737359661.10651262640339
841111.2323780733894-0.232378073389363
851011.7024842922533-1.70248429225335
86910.4881125213978-1.48811252139783
871211.77555289657230.224447103427715
881211.78894962857290.211050371427111
891211.26746177652420.732538223475755
9099.63414183715167-0.634141837151667
911512.24350421539322.75649578460679
921211.91044827325260.0895517267473811
931211.09532779666600.90467220333403
941210.09820689966421.90179310033577
951011.7265581311745-1.72655813117449
961311.76506075887551.23493924112451
97911.6759731907706-2.67597319077064
981211.45610008513160.543899914868442
991010.494577221527-0.494577221527005
1001411.73072675000142.26927324999864
1011111.5258909461436-0.52589094614363
1021513.98005475287741.01994524712264
1031110.88341877967760.116581220322435
1041111.8882469718560-0.888246971856032
105129.798286159314722.20171384068528
1061212.2628009224860-0.262800922485987
1071211.54303275319330.456967246806652
1081111.5573203607140-0.557320360713953
10979.6848209602947-2.68482096029471
1101211.80623261688190.193767383118141
1111411.80496859235882.1950314076412
1121112.5157322313154-1.51573223131544
113109.496809197909770.503190802090228
1141312.51116149818630.48883850181367
1151310.82700322119062.17299677880942
116810.8137476704492-2.81374767044923
1171110.15787877198260.84212122801744
1181211.75798754574480.242012454255186
119119.985595225958961.01440477404104
1201311.63157058797751.36842941202253
1211210.17993889211991.82006110788010
1221411.81086856745102.18913143254903
1231311.10628726610501.89371273389499
1241511.78679472852983.21320527147017
1251010.8335331387598-0.833533138759769
1261112.2716054918820-1.27160549188197
127911.2314871978694-2.23148719786936
128119.526224893696291.47377510630371
1291011.5343693650566-1.53436936505662
130118.315322442181582.68467755781842
131811.7467457137873-3.74674571378727
132119.320030882576311.67996911742369
1331210.47701187069951.52298812930047
1341211.10151013427660.898489865723354
13599.69561688998552-0.695616889985518
1361111.0001402925289-0.000140292528927985
137109.13021933593050.869780664069505
13889.55058109513593-1.55058109513593
13998.859620108628310.140379891371689
140811.7797215153992-3.77972151539915
141911.0837010345447-2.08370103454466
1421512.38701919224582.61298080775422
1431111.2858890375725-0.285889037572535
14488.30746092117616-0.307460921176164
1451312.69482805742670.305171942573276
146129.930559304209742.06944069579026
1471211.49474389409180.505256105908191
14899.86456391302148-0.864563913021481
14978.52882163417604-1.52882163417604
1501311.19106503412371.80893496587626
151911.6023784750287-2.60237847502869
152611.8889966661168-5.88899666611678
153810.6600229184184-2.66002291841837
15488.4275105721091-0.42751057210909
155610.2198467256032-4.2198467256032
156911.2314871978694-2.23148719786936
1571111.7226718748661-0.722671874866125
15889.71503334886203-1.71503334886203
159109.362808141608560.63719185839144
16088.72609476897542-0.726094768975418
1611411.52234267008352.47765732991655
1621010.9205066018859-0.920506601885934
16387.848882341647350.151117658352652
1641110.00453061381390.995469386186124
165128.478016555793583.52198344420642
166129.810550448341192.18944955165881
1671211.28184361538850.718156384611474
16858.79560326746899-3.79560326746899
1691211.33810494804680.661895051953185
170108.858179734091131.14182026590887
17177.33447608763545-0.334476087635453
172128.929525367050843.07047463294916
1731110.58316228913470.416837710865262
17489.10165934690911-1.10165934690911
17598.854948989304330.145051010695673
1761010.1635586090961-0.163558609096121
17799.16765473809737-0.167654738097374
1781211.33192261043610.668077389563862
17968.23224086167329-2.23224086167329
1801512.79197394552592.20802605447407
1811210.42147344845321.57852655154680
182126.925729309390625.07427069060938
1831211.39403174531600.605968254683965
1841111.5913838368348-0.591383836834775
18578.9719142510602-1.97191425106020
18678.27631731398346-1.27631731398346
18758.4363185863642-3.43631858636419
1881210.31751872512541.68248127487457
1891211.40283631471200.597163685287982
19039.11341550912896-6.11341550912896
1911111.3967951583606-0.396795158360593
192109.63640274969910.363597250300891
1931210.59904007166141.40095992833860
194911.2366527047206-2.23665270472061
1951211.39604546409980.603954535900156
196910.0192855530767-1.01928555307673
1971211.07158355308690.928416446913057
1981010.0019083820286-0.00190838202856881
19998.233504886196340.766495113803655
200128.841552257303723.15844774269628
201810.7665464858566-2.76654648585663
2021110.80200333799460.197996662005431
2031111.3695343626171-0.369534362617138
2041211.08783448461670.91216551538334
205108.292053915250871.70794608474913
2061010.4806779890293-0.480677989029284
207129.141425999133172.85857400086683
208129.013777023646552.98622297635345
2091110.69876095872230.301239041277706
210810.5638655820420-2.56386558204196
2111211.34808275548130.6519172445187
212109.827105171864930.172894828135075
2131111.8674157074869-0.867415707486885
2141010.1487566713132-0.148756671313207
21589.48088786172217-1.48088786172217
2161210.84856084083081.15143915916920
217129.418170213840782.58182978615922
218109.953380948373020.0466190516269787
2191210.76326874254981.23673125745024
22098.863145045698810.136854954301189
22166.98802341349426-0.988023413494258
222109.921484202060450.0785157979395493
223910.0072940268584-1.00729402685843
22498.3639996763060.636000323693995
22598.932794725451630.067205274548368
22669.5702661772516-3.57026617725160
227107.942605860321312.05739413967869
228611.0879756658759-5.08797566587591
2291412.29635006834451.7036499316555
230109.600804716301920.399195283698082
231108.261515376200551.73848462379945
23264.383412598036531.61658740196347
233129.240603590632582.75939640936742
2341211.33927818608530.660721813914683
23577.67656018200976-0.676560182009761
23688.94342804440768-0.943428044407678
237118.946799970453742.05320002954627
23837.73806080388816-4.73806080388816
23969.4090832819263-3.40908328192629
24088.9990724791584-0.999072479158396
241910.0358188471249-1.03581884712495
24297.950437152618811.04956284738119
24389.03889791106322-1.03889791106322
24498.96985674431190.0301432556881003
24578.36451400656831-1.36451400656831
24677.7601209240255-0.760120924025495
24769.10292337143217-3.10292337143217
248911.2833513888161-2.28335138881610
249108.83522873843381.16477126156620
250119.969682274677441.03031772532257
2511211.17579920945770.824200790542298
252810.2515233339372-2.25152333393716
253119.618837398871641.38116260112836
25434.66726737608007-1.66726737608007
2551110.75774191646060.242258083539354
256128.422172160102843.57782783989716
25778.36662190809131-1.36662190809131
25899.99342996311558-0.993429963115582
2591210.52470744281941.4752925571806
260810.2270259512383-2.22702595123827
261119.439436851752871.56056314824713
26288.26769771381123-0.267697713811227
2631010.7184425959788-0.718442595978835
26488.31959707351283-0.31959707351283
26579.45779568480558-2.45779568480558
26689.55930670781255-1.55930670781255
2671011.2770278699462-1.27702786994617
26889.56229370369485-1.56229370369485
2691211.35426509309200.645734906908023
2701411.06436915869702.93563084130299
27179.0749044965219-2.07490449652189
27266.26601794258008-0.266017942580075
2731111.0441815760842-0.0441815760842363
27445.40407478477717-1.40407478477717
275911.1638076832394-2.16380768323941
27654.251609995439320.748390004560678
27798.843424794828280.156575205171720
2781110.46124010067730.538759899322745
2791210.21920304384681.78079695615316
28098.370040832657430.62995916734257
2811210.93537375710891.06462624289115
2821010.7867340684694-0.786734068469408
28398.861272508174250.138727491825746
28465.800786248839220.199213751160785
2851011.1433377381081-1.14333773810813
28697.790518281816571.20948171818343
2871310.89661773218852.10338226781147
2881210.24370042654571.75629957345426






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.728426691490350.5431466170193010.271573308509650
110.932111291961430.1357774160771380.0678887080385691
120.8839275289213580.2321449421572840.116072471078642
130.9079961172925580.1840077654148840.092003882707442
140.8829186433667760.2341627132664490.117081356633224
150.8933724166429650.213255166714070.106627583357035
160.9014442860693590.1971114278612820.0985557139306408
170.8604782306201020.2790435387597970.139521769379899
180.8508823617452920.2982352765094160.149117638254708
190.8008756739698190.3982486520603620.199124326030181
200.7415269555133610.5169460889732780.258473044486639
210.680045374515350.6399092509692990.319954625484650
220.6119802819082640.7760394361834720.388019718091736
230.5389478376073920.9221043247852160.461052162392608
240.5146597033313840.9706805933372320.485340296668616
250.5131775092673770.9736449814652460.486822490732623
260.4799910107425950.959982021485190.520008989257405
270.4213958204168260.8427916408336520.578604179583174
280.4256903631724630.8513807263449250.574309636827537
290.3650843957596650.7301687915193310.634915604240335
300.3068020408982180.6136040817964360.693197959101782
310.2543547097987100.5087094195974210.74564529020129
320.2489591572024310.4979183144048620.751040842797569
330.2174211789772880.4348423579545760.782578821022712
340.1783692346491960.3567384692983920.821630765350804
350.2178678180661750.4357356361323510.782132181933824
360.2012152059909480.4024304119818970.798784794009052
370.1653564090245240.3307128180490490.834643590975476
380.1934594048543620.3869188097087230.806540595145638
390.2068940259398720.4137880518797440.793105974060128
400.1779293028297230.3558586056594460.822070697170277
410.1490263717304360.2980527434608720.850973628269564
420.1266552822212770.2533105644425540.873344717778723
430.1835683547741280.3671367095482570.816431645225872
440.1511762291226880.3023524582453760.848823770877312
450.1286755107567770.2573510215135550.871324489243223
460.1375591112586640.2751182225173280.862440888741336
470.1306733439987050.261346687997410.869326656001295
480.1097714784212840.2195429568425690.890228521578716
490.09880390092218630.1976078018443730.901196099077814
500.1031235874683860.2062471749367720.896876412531614
510.1065597216673550.2131194433347100.893440278332645
520.08622554180095860.1724510836019170.913774458199041
530.1044729817361660.2089459634723310.895527018263834
540.08645604446655120.1729120889331020.913543955533449
550.1477581403906610.2955162807813220.852241859609339
560.4314091035587230.8628182071174460.568590896441277
570.3884689794682140.7769379589364280.611531020531786
580.3468699079499760.6937398158999520.653130092050024
590.3069522568588920.6139045137177840.693047743141108
600.3247171257966620.6494342515933240.675282874203338
610.3406006838940710.6812013677881420.659399316105929
620.3115221997932640.6230443995865280.688477800206736
630.3157661192091480.6315322384182960.684233880790852
640.2796193987916860.5592387975833720.720380601208314
650.2461530182877990.4923060365755970.753846981712201
660.2211432899769630.4422865799539270.778856710023037
670.1974206427507030.3948412855014050.802579357249297
680.1761924014729640.3523848029459280.823807598527036
690.171067476201630.342134952403260.82893252379837
700.1480452157290290.2960904314580570.851954784270971
710.1272340601787150.2544681203574290.872765939821285
720.1088184879820610.2176369759641220.89118151201794
730.09329554765378010.1865910953075600.90670445234622
740.08339927451918120.1667985490383620.916600725480819
750.08025017798420580.1605003559684120.919749822015794
760.1171976838626380.2343953677252760.882802316137362
770.1037489995732590.2074979991465180.89625100042674
780.0886864086998390.1773728173996780.911313591300161
790.1029247715187840.2058495430375670.897075228481216
800.1004373233466350.2008746466932700.899562676653365
810.08471855475089640.1694371095017930.915281445249104
820.07110771063791810.1422154212758360.928892289362082
830.06551423055196020.1310284611039200.93448576944804
840.05481047517359730.1096209503471950.945189524826403
850.05322570368736670.1064514073747330.946774296312633
860.05546617958889850.1109323591777970.944533820411101
870.04552813345986310.09105626691972620.954471866540137
880.03710958428824340.07421916857648680.962890415711757
890.03063068066272510.06126136132545020.969369319337275
900.02707867232915660.05415734465831310.972921327670843
910.03859103296283670.07718206592567340.961408967037163
920.03249877590621890.06499755181243780.967501224093781
930.02851541255154540.05703082510309080.971484587448455
940.02915940317782650.0583188063556530.970840596822173
950.03035277813630140.06070555627260290.969647221863699
960.02653631062300850.0530726212460170.973463689376991
970.03546015848893530.07092031697787070.964539841511065
980.03017692647754270.06035385295508540.969823073522457
990.02498087740942430.04996175481884870.975019122590576
1000.02841728364069980.05683456728139960.9715827163593
1010.02330876145329390.04661752290658770.976691238546706
1020.01999877595214470.03999755190428940.980001224047855
1030.01626982693499990.03253965386999970.983730173065
1040.01491520976876530.02983041953753060.985084790231235
1050.01714310439454570.03428620878909140.982856895605454
1060.01375871500129200.02751743000258390.986241284998708
1070.01100706005222110.02201412010444230.988992939947779
1080.008928292232749820.01785658446549960.99107170776725
1090.01632971700451680.03265943400903360.983670282995483
1100.01308715893433840.02617431786867670.986912841065662
1110.01447506255544240.02895012511088480.985524937444558
1120.01505946363867050.03011892727734110.98494053636133
1130.01219392356744540.02438784713489080.987806076432555
1140.01004772354472300.02009544708944610.989952276455277
1150.01097868413952230.02195736827904450.989021315860478
1160.01744736675906730.03489473351813450.982552633240933
1170.01469633655813840.02939267311627670.985303663441862
1180.01180980917473870.02361961834947750.988190190825261
1190.01018432015635720.02036864031271440.989815679843643
1200.009407332732732470.01881466546546490.990592667267268
1210.00963899965523180.01927799931046360.990361000344768
1220.01129729647295310.02259459294590630.988702703527047
1230.01215868753213940.02431737506427870.987841312467861
1240.02165532153827620.04331064307655240.978344678461724
1250.01785967769921780.03571935539843570.982140322300782
1260.01577005515550910.03154011031101810.98422994484449
1270.01789476024455310.03578952048910610.982105239755447
1280.01734956644025350.0346991328805070.982650433559747
1290.01588224158520420.03176448317040840.984117758414796
1300.02153160380644860.04306320761289710.978468396193551
1310.04016094046480280.08032188092960550.959839059535197
1320.04063118122994360.08126236245988720.959368818770056
1330.04156733529495420.08313467058990830.958432664705046
1340.03768289106323150.0753657821264630.962317108936768
1350.03223857750092690.06447715500185370.967761422499073
1360.02698296810254560.05396593620509110.973017031897454
1370.0253367955989850.050673591197970.974663204401015
1380.02425735918107630.04851471836215250.975742640818924
1390.02081257755104920.04162515510209850.97918742244895
1400.0387894837859570.0775789675719140.961210516214043
1410.03910491465395740.07820982930791480.960895085346043
1420.05659346669033130.1131869333806630.943406533309669
1430.04764978088365040.09529956176730090.95235021911635
1440.04029573603196250.0805914720639250.959704263968038
1450.03549572733728850.0709914546745770.964504272662712
1460.04603637665635410.09207275331270820.953963623343646
1470.04405055193075430.08810110386150870.955949448069246
1480.03952912245120220.07905824490240440.960470877548798
1490.03679151102358760.07358302204717510.963208488976412
1500.05132576156711820.1026515231342360.948674238432882
1510.05222282660888160.1044456532177630.947777173391118
1520.1660168463196660.3320336926393320.833983153680334
1530.1769691137043480.3539382274086960.823030886295652
1540.1668293921000120.3336587842000230.833170607899988
1550.2375901080153840.4751802160307670.762409891984616
1560.2350140573339290.4700281146678590.76498594266607
1570.2139868598704250.4279737197408510.786013140129575
1580.2030382678539300.4060765357078590.79696173214607
1590.1822089740508320.3644179481016640.817791025949168
1600.1643312547847970.3286625095695950.835668745215203
1610.1783401695285350.3566803390570700.821659830471465
1620.1665358980628350.3330717961256690.833464101937165
1630.1464959437387540.2929918874775090.853504056261246
1640.1316997567202360.2633995134404720.868300243279764
1650.1808647180226370.3617294360452740.819135281977363
1660.1847546246546240.3695092493092490.815245375345376
1670.1667639651585590.3335279303171170.833236034841441
1680.2725314107532940.5450628215065890.727468589246706
1690.2465796736330210.4931593472660420.753420326366979
1700.2272649928730870.4545299857461740.772735007126913
1710.2061484375131090.4122968750262170.793851562486891
1720.2444807323798920.4889614647597840.755519267620108
1730.2186762871456610.4373525742913210.78132371285434
1740.2068461892243150.413692378448630.793153810775685
1750.1835310970406970.3670621940813930.816468902959303
1760.1630162914120530.3260325828241050.836983708587947
1770.1431490615992380.2862981231984750.856850938400762
1780.1263454311898150.2526908623796290.873654568810185
1790.1406245802309400.2812491604618810.85937541976906
1800.1485183120621530.2970366241243060.851481687937847
1810.140445516998750.28089103399750.85955448300125
1820.3303910130649250.6607820261298490.669608986935075
1830.3066851186908380.6133702373816770.693314881309162
1840.2826068532255850.565213706451170.717393146774415
1850.299879637091680.599759274183360.70012036290832
1860.2887430143267010.5774860286534030.711256985673299
1870.3784823693339350.7569647386678690.621517630666065
1880.3837468175566220.7674936351132440.616253182443378
1890.3550259110906440.7100518221812890.644974088909356
1900.7196950501494060.5606098997011880.280304949850594
1910.6893073297023440.6213853405953130.310692670297656
1920.6592337874368950.681532425126210.340766212563105
1930.6444709395269240.7110581209461510.355529060473076
1940.663296544757210.673406910485580.33670345524279
1950.6376650682669580.7246698634660840.362334931733042
1960.6136210568359330.7727578863281330.386378943164067
1970.5907381248536160.8185237502927690.409261875146384
1980.5586687426788130.8826625146423750.441331257321187
1990.5257580670070750.948483865985850.474241932992925
2000.597638960544830.804722078910340.40236103945517
2010.6420669265666950.715866146866610.357933073433305
2020.6073079881596210.7853840236807580.392692011840379
2030.5712957483264820.8574085033470350.428704251673518
2040.5434232733270120.9131534533459760.456576726672988
2050.5340259015628060.9319481968743880.465974098437194
2060.4987890926296490.9975781852592980.501210907370351
2070.567149305929750.8657013881405010.432850694070251
2080.6261695959705230.7476608080589550.373830404029477
2090.5957750766510460.8084498466979070.404224923348954
2100.6267976605830880.7464046788338240.373202339416912
2110.5978607263084040.8042785473831930.402139273691596
2120.5594497059377930.8811005881244130.440550294062207
2130.5257770270646360.9484459458707280.474222972935364
2140.4868226528619980.9736453057239970.513177347138002
2150.4750732437683780.9501464875367550.524926756231622
2160.4633299274943240.9266598549886470.536670072505676
2170.501002315087370.997995369825260.49899768491263
2180.4605155671976730.9210311343953450.539484432802327
2190.4480830609586440.8961661219172890.551916939041356
2200.4088725816562810.8177451633125630.591127418343719
2210.3757271789880770.7514543579761530.624272821011923
2220.3377517496016600.6755034992033190.66224825039834
2230.3097832998406210.6195665996812430.690216700159379
2240.2786927991142020.5573855982284040.721307200885798
2250.245135586828990.490271173657980.75486441317101
2260.3488112893170320.6976225786340650.651188710682968
2270.3942495626042790.7884991252085580.605750437395721
2280.6983737339019060.6032525321961880.301626266098094
2290.680000357306570.6399992853868610.319999642693430
2300.6401456939832170.7197086120335650.359854306016783
2310.6343176022642530.7313647954714930.365682397735747
2320.6314474833690720.7371050332618550.368552516630928
2330.6728825030314580.6542349939370840.327117496968542
2340.6486880123314820.7026239753370350.351311987668518
2350.6088168250208710.7823663499582570.391183174979129
2360.5707385343658520.8585229312682960.429261465634148
2370.6373057739186530.7253884521626940.362694226081347
2380.8518332866287770.2963334267424460.148166713371223
2390.9221310156055470.1557379687889060.077868984394453
2400.9055628258076090.1888743483847820.0944371741923909
2410.8934754595193810.2130490809612380.106524540480619
2420.884291041289910.231417917420180.11570895871009
2430.8606714422989570.2786571154020870.139328557701043
2440.8308837290899010.3382325418201980.169116270910099
2450.8325447213486370.3349105573027270.167455278651363
2460.8084982312188010.3830035375623980.191501768781199
2470.8625892381056530.2748215237886940.137410761894347
2480.8835311413937540.2329377172124930.116468858606246
2490.8662658338322920.2674683323354150.133734166167708
2500.8433031512324350.3133936975351300.156696848767565
2510.827808694695850.3443826106082990.172191305304150
2520.8219107900910860.3561784198178280.178089209908914
2530.8015425668367210.3969148663265580.198457433163279
2540.7700863298065920.4598273403868150.229913670193408
2550.7221551872904880.5556896254190240.277844812709512
2560.8759561331854360.2480877336291280.124043866814564
2570.8494590410605490.3010819178789020.150540958939451
2580.8263459053595650.3473081892808700.173654094640435
2590.8319232235627960.3361535528744080.168076776437204
2600.8486361751552750.3027276496894490.151363824844725
2610.8451625147717970.3096749704564050.154837485228203
2620.8013960426719010.3972079146561980.198603957328099
2630.7783104904806820.4433790190386360.221689509519318
2640.719715416357340.5605691672853190.280284583642660
2650.7723811548040380.4552376903919250.227618845195962
2660.8399226739994820.3201546520010360.160077326000518
2670.9269178104317420.1461643791365150.0730821895682577
2680.906671517932940.1866569641341200.0933284820670598
2690.8650077801533380.2699844396933240.134992219846662
2700.9266592189458480.1466815621083040.0733407810541522
2710.9045381752660720.1909236494678570.0954618247339284
2720.9434213730557250.1131572538885510.0565786269442753
2730.9020427339345330.1959145321309340.0979572660654672
2740.9030717093493890.1938565813012220.0969282906506112
2750.889933918420910.2201321631581820.110066081579091
2760.8117620003334180.3764759993331650.188237999666582
2770.7199776512867480.5600446974265050.280022348713252
2780.5555162358081260.8889675283837480.444483764191874

\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 & 0.543146617019301 & 0.271573308509650 \tabularnewline
11 & 0.93211129196143 & 0.135777416077138 & 0.0678887080385691 \tabularnewline
12 & 0.883927528921358 & 0.232144942157284 & 0.116072471078642 \tabularnewline
13 & 0.907996117292558 & 0.184007765414884 & 0.092003882707442 \tabularnewline
14 & 0.882918643366776 & 0.234162713266449 & 0.117081356633224 \tabularnewline
15 & 0.893372416642965 & 0.21325516671407 & 0.106627583357035 \tabularnewline
16 & 0.901444286069359 & 0.197111427861282 & 0.0985557139306408 \tabularnewline
17 & 0.860478230620102 & 0.279043538759797 & 0.139521769379899 \tabularnewline
18 & 0.850882361745292 & 0.298235276509416 & 0.149117638254708 \tabularnewline
19 & 0.800875673969819 & 0.398248652060362 & 0.199124326030181 \tabularnewline
20 & 0.741526955513361 & 0.516946088973278 & 0.258473044486639 \tabularnewline
21 & 0.68004537451535 & 0.639909250969299 & 0.319954625484650 \tabularnewline
22 & 0.611980281908264 & 0.776039436183472 & 0.388019718091736 \tabularnewline
23 & 0.538947837607392 & 0.922104324785216 & 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 & 0.421395820416826 & 0.842791640833652 & 0.578604179583174 \tabularnewline
28 & 0.425690363172463 & 0.851380726344925 & 0.574309636827537 \tabularnewline
29 & 0.365084395759665 & 0.730168791519331 & 0.634915604240335 \tabularnewline
30 & 0.306802040898218 & 0.613604081796436 & 0.693197959101782 \tabularnewline
31 & 0.254354709798710 & 0.508709419597421 & 0.74564529020129 \tabularnewline
32 & 0.248959157202431 & 0.497918314404862 & 0.751040842797569 \tabularnewline
33 & 0.217421178977288 & 0.434842357954576 & 0.782578821022712 \tabularnewline
34 & 0.178369234649196 & 0.356738469298392 & 0.821630765350804 \tabularnewline
35 & 0.217867818066175 & 0.435735636132351 & 0.782132181933824 \tabularnewline
36 & 0.201215205990948 & 0.402430411981897 & 0.798784794009052 \tabularnewline
37 & 0.165356409024524 & 0.330712818049049 & 0.834643590975476 \tabularnewline
38 & 0.193459404854362 & 0.386918809708723 & 0.806540595145638 \tabularnewline
39 & 0.206894025939872 & 0.413788051879744 & 0.793105974060128 \tabularnewline
40 & 0.177929302829723 & 0.355858605659446 & 0.822070697170277 \tabularnewline
41 & 0.149026371730436 & 0.298052743460872 & 0.850973628269564 \tabularnewline
42 & 0.126655282221277 & 0.253310564442554 & 0.873344717778723 \tabularnewline
43 & 0.183568354774128 & 0.367136709548257 & 0.816431645225872 \tabularnewline
44 & 0.151176229122688 & 0.302352458245376 & 0.848823770877312 \tabularnewline
45 & 0.128675510756777 & 0.257351021513555 & 0.871324489243223 \tabularnewline
46 & 0.137559111258664 & 0.275118222517328 & 0.862440888741336 \tabularnewline
47 & 0.130673343998705 & 0.26134668799741 & 0.869326656001295 \tabularnewline
48 & 0.109771478421284 & 0.219542956842569 & 0.890228521578716 \tabularnewline
49 & 0.0988039009221863 & 0.197607801844373 & 0.901196099077814 \tabularnewline
50 & 0.103123587468386 & 0.206247174936772 & 0.896876412531614 \tabularnewline
51 & 0.106559721667355 & 0.213119443334710 & 0.893440278332645 \tabularnewline
52 & 0.0862255418009586 & 0.172451083601917 & 0.913774458199041 \tabularnewline
53 & 0.104472981736166 & 0.208945963472331 & 0.895527018263834 \tabularnewline
54 & 0.0864560444665512 & 0.172912088933102 & 0.913543955533449 \tabularnewline
55 & 0.147758140390661 & 0.295516280781322 & 0.852241859609339 \tabularnewline
56 & 0.431409103558723 & 0.862818207117446 & 0.568590896441277 \tabularnewline
57 & 0.388468979468214 & 0.776937958936428 & 0.611531020531786 \tabularnewline
58 & 0.346869907949976 & 0.693739815899952 & 0.653130092050024 \tabularnewline
59 & 0.306952256858892 & 0.613904513717784 & 0.693047743141108 \tabularnewline
60 & 0.324717125796662 & 0.649434251593324 & 0.675282874203338 \tabularnewline
61 & 0.340600683894071 & 0.681201367788142 & 0.659399316105929 \tabularnewline
62 & 0.311522199793264 & 0.623044399586528 & 0.688477800206736 \tabularnewline
63 & 0.315766119209148 & 0.631532238418296 & 0.684233880790852 \tabularnewline
64 & 0.279619398791686 & 0.559238797583372 & 0.720380601208314 \tabularnewline
65 & 0.246153018287799 & 0.492306036575597 & 0.753846981712201 \tabularnewline
66 & 0.221143289976963 & 0.442286579953927 & 0.778856710023037 \tabularnewline
67 & 0.197420642750703 & 0.394841285501405 & 0.802579357249297 \tabularnewline
68 & 0.176192401472964 & 0.352384802945928 & 0.823807598527036 \tabularnewline
69 & 0.17106747620163 & 0.34213495240326 & 0.82893252379837 \tabularnewline
70 & 0.148045215729029 & 0.296090431458057 & 0.851954784270971 \tabularnewline
71 & 0.127234060178715 & 0.254468120357429 & 0.872765939821285 \tabularnewline
72 & 0.108818487982061 & 0.217636975964122 & 0.89118151201794 \tabularnewline
73 & 0.0932955476537801 & 0.186591095307560 & 0.90670445234622 \tabularnewline
74 & 0.0833992745191812 & 0.166798549038362 & 0.916600725480819 \tabularnewline
75 & 0.0802501779842058 & 0.160500355968412 & 0.919749822015794 \tabularnewline
76 & 0.117197683862638 & 0.234395367725276 & 0.882802316137362 \tabularnewline
77 & 0.103748999573259 & 0.207497999146518 & 0.89625100042674 \tabularnewline
78 & 0.088686408699839 & 0.177372817399678 & 0.911313591300161 \tabularnewline
79 & 0.102924771518784 & 0.205849543037567 & 0.897075228481216 \tabularnewline
80 & 0.100437323346635 & 0.200874646693270 & 0.899562676653365 \tabularnewline
81 & 0.0847185547508964 & 0.169437109501793 & 0.915281445249104 \tabularnewline
82 & 0.0711077106379181 & 0.142215421275836 & 0.928892289362082 \tabularnewline
83 & 0.0655142305519602 & 0.131028461103920 & 0.93448576944804 \tabularnewline
84 & 0.0548104751735973 & 0.109620950347195 & 0.945189524826403 \tabularnewline
85 & 0.0532257036873667 & 0.106451407374733 & 0.946774296312633 \tabularnewline
86 & 0.0554661795888985 & 0.110932359177797 & 0.944533820411101 \tabularnewline
87 & 0.0455281334598631 & 0.0910562669197262 & 0.954471866540137 \tabularnewline
88 & 0.0371095842882434 & 0.0742191685764868 & 0.962890415711757 \tabularnewline
89 & 0.0306306806627251 & 0.0612613613254502 & 0.969369319337275 \tabularnewline
90 & 0.0270786723291566 & 0.0541573446583131 & 0.972921327670843 \tabularnewline
91 & 0.0385910329628367 & 0.0771820659256734 & 0.961408967037163 \tabularnewline
92 & 0.0324987759062189 & 0.0649975518124378 & 0.967501224093781 \tabularnewline
93 & 0.0285154125515454 & 0.0570308251030908 & 0.971484587448455 \tabularnewline
94 & 0.0291594031778265 & 0.058318806355653 & 0.970840596822173 \tabularnewline
95 & 0.0303527781363014 & 0.0607055562726029 & 0.969647221863699 \tabularnewline
96 & 0.0265363106230085 & 0.053072621246017 & 0.973463689376991 \tabularnewline
97 & 0.0354601584889353 & 0.0709203169778707 & 0.964539841511065 \tabularnewline
98 & 0.0301769264775427 & 0.0603538529550854 & 0.969823073522457 \tabularnewline
99 & 0.0249808774094243 & 0.0499617548188487 & 0.975019122590576 \tabularnewline
100 & 0.0284172836406998 & 0.0568345672813996 & 0.9715827163593 \tabularnewline
101 & 0.0233087614532939 & 0.0466175229065877 & 0.976691238546706 \tabularnewline
102 & 0.0199987759521447 & 0.0399975519042894 & 0.980001224047855 \tabularnewline
103 & 0.0162698269349999 & 0.0325396538699997 & 0.983730173065 \tabularnewline
104 & 0.0149152097687653 & 0.0298304195375306 & 0.985084790231235 \tabularnewline
105 & 0.0171431043945457 & 0.0342862087890914 & 0.982856895605454 \tabularnewline
106 & 0.0137587150012920 & 0.0275174300025839 & 0.986241284998708 \tabularnewline
107 & 0.0110070600522211 & 0.0220141201044423 & 0.988992939947779 \tabularnewline
108 & 0.00892829223274982 & 0.0178565844654996 & 0.99107170776725 \tabularnewline
109 & 0.0163297170045168 & 0.0326594340090336 & 0.983670282995483 \tabularnewline
110 & 0.0130871589343384 & 0.0261743178686767 & 0.986912841065662 \tabularnewline
111 & 0.0144750625554424 & 0.0289501251108848 & 0.985524937444558 \tabularnewline
112 & 0.0150594636386705 & 0.0301189272773411 & 0.98494053636133 \tabularnewline
113 & 0.0121939235674454 & 0.0243878471348908 & 0.987806076432555 \tabularnewline
114 & 0.0100477235447230 & 0.0200954470894461 & 0.989952276455277 \tabularnewline
115 & 0.0109786841395223 & 0.0219573682790445 & 0.989021315860478 \tabularnewline
116 & 0.0174473667590673 & 0.0348947335181345 & 0.982552633240933 \tabularnewline
117 & 0.0146963365581384 & 0.0293926731162767 & 0.985303663441862 \tabularnewline
118 & 0.0118098091747387 & 0.0236196183494775 & 0.988190190825261 \tabularnewline
119 & 0.0101843201563572 & 0.0203686403127144 & 0.989815679843643 \tabularnewline
120 & 0.00940733273273247 & 0.0188146654654649 & 0.990592667267268 \tabularnewline
121 & 0.0096389996552318 & 0.0192779993104636 & 0.990361000344768 \tabularnewline
122 & 0.0112972964729531 & 0.0225945929459063 & 0.988702703527047 \tabularnewline
123 & 0.0121586875321394 & 0.0243173750642787 & 0.987841312467861 \tabularnewline
124 & 0.0216553215382762 & 0.0433106430765524 & 0.978344678461724 \tabularnewline
125 & 0.0178596776992178 & 0.0357193553984357 & 0.982140322300782 \tabularnewline
126 & 0.0157700551555091 & 0.0315401103110181 & 0.98422994484449 \tabularnewline
127 & 0.0178947602445531 & 0.0357895204891061 & 0.982105239755447 \tabularnewline
128 & 0.0173495664402535 & 0.034699132880507 & 0.982650433559747 \tabularnewline
129 & 0.0158822415852042 & 0.0317644831704084 & 0.984117758414796 \tabularnewline
130 & 0.0215316038064486 & 0.0430632076128971 & 0.978468396193551 \tabularnewline
131 & 0.0401609404648028 & 0.0803218809296055 & 0.959839059535197 \tabularnewline
132 & 0.0406311812299436 & 0.0812623624598872 & 0.959368818770056 \tabularnewline
133 & 0.0415673352949542 & 0.0831346705899083 & 0.958432664705046 \tabularnewline
134 & 0.0376828910632315 & 0.075365782126463 & 0.962317108936768 \tabularnewline
135 & 0.0322385775009269 & 0.0644771550018537 & 0.967761422499073 \tabularnewline
136 & 0.0269829681025456 & 0.0539659362050911 & 0.973017031897454 \tabularnewline
137 & 0.025336795598985 & 0.05067359119797 & 0.974663204401015 \tabularnewline
138 & 0.0242573591810763 & 0.0485147183621525 & 0.975742640818924 \tabularnewline
139 & 0.0208125775510492 & 0.0416251551020985 & 0.97918742244895 \tabularnewline
140 & 0.038789483785957 & 0.077578967571914 & 0.961210516214043 \tabularnewline
141 & 0.0391049146539574 & 0.0782098293079148 & 0.960895085346043 \tabularnewline
142 & 0.0565934666903313 & 0.113186933380663 & 0.943406533309669 \tabularnewline
143 & 0.0476497808836504 & 0.0952995617673009 & 0.95235021911635 \tabularnewline
144 & 0.0402957360319625 & 0.080591472063925 & 0.959704263968038 \tabularnewline
145 & 0.0354957273372885 & 0.070991454674577 & 0.964504272662712 \tabularnewline
146 & 0.0460363766563541 & 0.0920727533127082 & 0.953963623343646 \tabularnewline
147 & 0.0440505519307543 & 0.0881011038615087 & 0.955949448069246 \tabularnewline
148 & 0.0395291224512022 & 0.0790582449024044 & 0.960470877548798 \tabularnewline
149 & 0.0367915110235876 & 0.0735830220471751 & 0.963208488976412 \tabularnewline
150 & 0.0513257615671182 & 0.102651523134236 & 0.948674238432882 \tabularnewline
151 & 0.0522228266088816 & 0.104445653217763 & 0.947777173391118 \tabularnewline
152 & 0.166016846319666 & 0.332033692639332 & 0.833983153680334 \tabularnewline
153 & 0.176969113704348 & 0.353938227408696 & 0.823030886295652 \tabularnewline
154 & 0.166829392100012 & 0.333658784200023 & 0.833170607899988 \tabularnewline
155 & 0.237590108015384 & 0.475180216030767 & 0.762409891984616 \tabularnewline
156 & 0.235014057333929 & 0.470028114667859 & 0.76498594266607 \tabularnewline
157 & 0.213986859870425 & 0.427973719740851 & 0.786013140129575 \tabularnewline
158 & 0.203038267853930 & 0.406076535707859 & 0.79696173214607 \tabularnewline
159 & 0.182208974050832 & 0.364417948101664 & 0.817791025949168 \tabularnewline
160 & 0.164331254784797 & 0.328662509569595 & 0.835668745215203 \tabularnewline
161 & 0.178340169528535 & 0.356680339057070 & 0.821659830471465 \tabularnewline
162 & 0.166535898062835 & 0.333071796125669 & 0.833464101937165 \tabularnewline
163 & 0.146495943738754 & 0.292991887477509 & 0.853504056261246 \tabularnewline
164 & 0.131699756720236 & 0.263399513440472 & 0.868300243279764 \tabularnewline
165 & 0.180864718022637 & 0.361729436045274 & 0.819135281977363 \tabularnewline
166 & 0.184754624654624 & 0.369509249309249 & 0.815245375345376 \tabularnewline
167 & 0.166763965158559 & 0.333527930317117 & 0.833236034841441 \tabularnewline
168 & 0.272531410753294 & 0.545062821506589 & 0.727468589246706 \tabularnewline
169 & 0.246579673633021 & 0.493159347266042 & 0.753420326366979 \tabularnewline
170 & 0.227264992873087 & 0.454529985746174 & 0.772735007126913 \tabularnewline
171 & 0.206148437513109 & 0.412296875026217 & 0.793851562486891 \tabularnewline
172 & 0.244480732379892 & 0.488961464759784 & 0.755519267620108 \tabularnewline
173 & 0.218676287145661 & 0.437352574291321 & 0.78132371285434 \tabularnewline
174 & 0.206846189224315 & 0.41369237844863 & 0.793153810775685 \tabularnewline
175 & 0.183531097040697 & 0.367062194081393 & 0.816468902959303 \tabularnewline
176 & 0.163016291412053 & 0.326032582824105 & 0.836983708587947 \tabularnewline
177 & 0.143149061599238 & 0.286298123198475 & 0.856850938400762 \tabularnewline
178 & 0.126345431189815 & 0.252690862379629 & 0.873654568810185 \tabularnewline
179 & 0.140624580230940 & 0.281249160461881 & 0.85937541976906 \tabularnewline
180 & 0.148518312062153 & 0.297036624124306 & 0.851481687937847 \tabularnewline
181 & 0.14044551699875 & 0.2808910339975 & 0.85955448300125 \tabularnewline
182 & 0.330391013064925 & 0.660782026129849 & 0.669608986935075 \tabularnewline
183 & 0.306685118690838 & 0.613370237381677 & 0.693314881309162 \tabularnewline
184 & 0.282606853225585 & 0.56521370645117 & 0.717393146774415 \tabularnewline
185 & 0.29987963709168 & 0.59975927418336 & 0.70012036290832 \tabularnewline
186 & 0.288743014326701 & 0.577486028653403 & 0.711256985673299 \tabularnewline
187 & 0.378482369333935 & 0.756964738667869 & 0.621517630666065 \tabularnewline
188 & 0.383746817556622 & 0.767493635113244 & 0.616253182443378 \tabularnewline
189 & 0.355025911090644 & 0.710051822181289 & 0.644974088909356 \tabularnewline
190 & 0.719695050149406 & 0.560609899701188 & 0.280304949850594 \tabularnewline
191 & 0.689307329702344 & 0.621385340595313 & 0.310692670297656 \tabularnewline
192 & 0.659233787436895 & 0.68153242512621 & 0.340766212563105 \tabularnewline
193 & 0.644470939526924 & 0.711058120946151 & 0.355529060473076 \tabularnewline
194 & 0.66329654475721 & 0.67340691048558 & 0.33670345524279 \tabularnewline
195 & 0.637665068266958 & 0.724669863466084 & 0.362334931733042 \tabularnewline
196 & 0.613621056835933 & 0.772757886328133 & 0.386378943164067 \tabularnewline
197 & 0.590738124853616 & 0.818523750292769 & 0.409261875146384 \tabularnewline
198 & 0.558668742678813 & 0.882662514642375 & 0.441331257321187 \tabularnewline
199 & 0.525758067007075 & 0.94848386598585 & 0.474241932992925 \tabularnewline
200 & 0.59763896054483 & 0.80472207891034 & 0.40236103945517 \tabularnewline
201 & 0.642066926566695 & 0.71586614686661 & 0.357933073433305 \tabularnewline
202 & 0.607307988159621 & 0.785384023680758 & 0.392692011840379 \tabularnewline
203 & 0.571295748326482 & 0.857408503347035 & 0.428704251673518 \tabularnewline
204 & 0.543423273327012 & 0.913153453345976 & 0.456576726672988 \tabularnewline
205 & 0.534025901562806 & 0.931948196874388 & 0.465974098437194 \tabularnewline
206 & 0.498789092629649 & 0.997578185259298 & 0.501210907370351 \tabularnewline
207 & 0.56714930592975 & 0.865701388140501 & 0.432850694070251 \tabularnewline
208 & 0.626169595970523 & 0.747660808058955 & 0.373830404029477 \tabularnewline
209 & 0.595775076651046 & 0.808449846697907 & 0.404224923348954 \tabularnewline
210 & 0.626797660583088 & 0.746404678833824 & 0.373202339416912 \tabularnewline
211 & 0.597860726308404 & 0.804278547383193 & 0.402139273691596 \tabularnewline
212 & 0.559449705937793 & 0.881100588124413 & 0.440550294062207 \tabularnewline
213 & 0.525777027064636 & 0.948445945870728 & 0.474222972935364 \tabularnewline
214 & 0.486822652861998 & 0.973645305723997 & 0.513177347138002 \tabularnewline
215 & 0.475073243768378 & 0.950146487536755 & 0.524926756231622 \tabularnewline
216 & 0.463329927494324 & 0.926659854988647 & 0.536670072505676 \tabularnewline
217 & 0.50100231508737 & 0.99799536982526 & 0.49899768491263 \tabularnewline
218 & 0.460515567197673 & 0.921031134395345 & 0.539484432802327 \tabularnewline
219 & 0.448083060958644 & 0.896166121917289 & 0.551916939041356 \tabularnewline
220 & 0.408872581656281 & 0.817745163312563 & 0.591127418343719 \tabularnewline
221 & 0.375727178988077 & 0.751454357976153 & 0.624272821011923 \tabularnewline
222 & 0.337751749601660 & 0.675503499203319 & 0.66224825039834 \tabularnewline
223 & 0.309783299840621 & 0.619566599681243 & 0.690216700159379 \tabularnewline
224 & 0.278692799114202 & 0.557385598228404 & 0.721307200885798 \tabularnewline
225 & 0.24513558682899 & 0.49027117365798 & 0.75486441317101 \tabularnewline
226 & 0.348811289317032 & 0.697622578634065 & 0.651188710682968 \tabularnewline
227 & 0.394249562604279 & 0.788499125208558 & 0.605750437395721 \tabularnewline
228 & 0.698373733901906 & 0.603252532196188 & 0.301626266098094 \tabularnewline
229 & 0.68000035730657 & 0.639999285386861 & 0.319999642693430 \tabularnewline
230 & 0.640145693983217 & 0.719708612033565 & 0.359854306016783 \tabularnewline
231 & 0.634317602264253 & 0.731364795471493 & 0.365682397735747 \tabularnewline
232 & 0.631447483369072 & 0.737105033261855 & 0.368552516630928 \tabularnewline
233 & 0.672882503031458 & 0.654234993937084 & 0.327117496968542 \tabularnewline
234 & 0.648688012331482 & 0.702623975337035 & 0.351311987668518 \tabularnewline
235 & 0.608816825020871 & 0.782366349958257 & 0.391183174979129 \tabularnewline
236 & 0.570738534365852 & 0.858522931268296 & 0.429261465634148 \tabularnewline
237 & 0.637305773918653 & 0.725388452162694 & 0.362694226081347 \tabularnewline
238 & 0.851833286628777 & 0.296333426742446 & 0.148166713371223 \tabularnewline
239 & 0.922131015605547 & 0.155737968788906 & 0.077868984394453 \tabularnewline
240 & 0.905562825807609 & 0.188874348384782 & 0.0944371741923909 \tabularnewline
241 & 0.893475459519381 & 0.213049080961238 & 0.106524540480619 \tabularnewline
242 & 0.88429104128991 & 0.23141791742018 & 0.11570895871009 \tabularnewline
243 & 0.860671442298957 & 0.278657115402087 & 0.139328557701043 \tabularnewline
244 & 0.830883729089901 & 0.338232541820198 & 0.169116270910099 \tabularnewline
245 & 0.832544721348637 & 0.334910557302727 & 0.167455278651363 \tabularnewline
246 & 0.808498231218801 & 0.383003537562398 & 0.191501768781199 \tabularnewline
247 & 0.862589238105653 & 0.274821523788694 & 0.137410761894347 \tabularnewline
248 & 0.883531141393754 & 0.232937717212493 & 0.116468858606246 \tabularnewline
249 & 0.866265833832292 & 0.267468332335415 & 0.133734166167708 \tabularnewline
250 & 0.843303151232435 & 0.313393697535130 & 0.156696848767565 \tabularnewline
251 & 0.82780869469585 & 0.344382610608299 & 0.172191305304150 \tabularnewline
252 & 0.821910790091086 & 0.356178419817828 & 0.178089209908914 \tabularnewline
253 & 0.801542566836721 & 0.396914866326558 & 0.198457433163279 \tabularnewline
254 & 0.770086329806592 & 0.459827340386815 & 0.229913670193408 \tabularnewline
255 & 0.722155187290488 & 0.555689625419024 & 0.277844812709512 \tabularnewline
256 & 0.875956133185436 & 0.248087733629128 & 0.124043866814564 \tabularnewline
257 & 0.849459041060549 & 0.301081917878902 & 0.150540958939451 \tabularnewline
258 & 0.826345905359565 & 0.347308189280870 & 0.173654094640435 \tabularnewline
259 & 0.831923223562796 & 0.336153552874408 & 0.168076776437204 \tabularnewline
260 & 0.848636175155275 & 0.302727649689449 & 0.151363824844725 \tabularnewline
261 & 0.845162514771797 & 0.309674970456405 & 0.154837485228203 \tabularnewline
262 & 0.801396042671901 & 0.397207914656198 & 0.198603957328099 \tabularnewline
263 & 0.778310490480682 & 0.443379019038636 & 0.221689509519318 \tabularnewline
264 & 0.71971541635734 & 0.560569167285319 & 0.280284583642660 \tabularnewline
265 & 0.772381154804038 & 0.455237690391925 & 0.227618845195962 \tabularnewline
266 & 0.839922673999482 & 0.320154652001036 & 0.160077326000518 \tabularnewline
267 & 0.926917810431742 & 0.146164379136515 & 0.0730821895682577 \tabularnewline
268 & 0.90667151793294 & 0.186656964134120 & 0.0933284820670598 \tabularnewline
269 & 0.865007780153338 & 0.269984439693324 & 0.134992219846662 \tabularnewline
270 & 0.926659218945848 & 0.146681562108304 & 0.0733407810541522 \tabularnewline
271 & 0.904538175266072 & 0.190923649467857 & 0.0954618247339284 \tabularnewline
272 & 0.943421373055725 & 0.113157253888551 & 0.0565786269442753 \tabularnewline
273 & 0.902042733934533 & 0.195914532130934 & 0.0979572660654672 \tabularnewline
274 & 0.903071709349389 & 0.193856581301222 & 0.0969282906506112 \tabularnewline
275 & 0.88993391842091 & 0.220132163158182 & 0.110066081579091 \tabularnewline
276 & 0.811762000333418 & 0.376475999333165 & 0.188237999666582 \tabularnewline
277 & 0.719977651286748 & 0.560044697426505 & 0.280022348713252 \tabularnewline
278 & 0.555516235808126 & 0.888967528383748 & 0.444483764191874 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113623&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]0.543146617019301[/C][C]0.271573308509650[/C][/ROW]
[ROW][C]11[/C][C]0.93211129196143[/C][C]0.135777416077138[/C][C]0.0678887080385691[/C][/ROW]
[ROW][C]12[/C][C]0.883927528921358[/C][C]0.232144942157284[/C][C]0.116072471078642[/C][/ROW]
[ROW][C]13[/C][C]0.907996117292558[/C][C]0.184007765414884[/C][C]0.092003882707442[/C][/ROW]
[ROW][C]14[/C][C]0.882918643366776[/C][C]0.234162713266449[/C][C]0.117081356633224[/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]0.197111427861282[/C][C]0.0985557139306408[/C][/ROW]
[ROW][C]17[/C][C]0.860478230620102[/C][C]0.279043538759797[/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]0.800875673969819[/C][C]0.398248652060362[/C][C]0.199124326030181[/C][/ROW]
[ROW][C]20[/C][C]0.741526955513361[/C][C]0.516946088973278[/C][C]0.258473044486639[/C][/ROW]
[ROW][C]21[/C][C]0.68004537451535[/C][C]0.639909250969299[/C][C]0.319954625484650[/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]0.922104324785216[/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]0.421395820416826[/C][C]0.842791640833652[/C][C]0.578604179583174[/C][/ROW]
[ROW][C]28[/C][C]0.425690363172463[/C][C]0.851380726344925[/C][C]0.574309636827537[/C][/ROW]
[ROW][C]29[/C][C]0.365084395759665[/C][C]0.730168791519331[/C][C]0.634915604240335[/C][/ROW]
[ROW][C]30[/C][C]0.306802040898218[/C][C]0.613604081796436[/C][C]0.693197959101782[/C][/ROW]
[ROW][C]31[/C][C]0.254354709798710[/C][C]0.508709419597421[/C][C]0.74564529020129[/C][/ROW]
[ROW][C]32[/C][C]0.248959157202431[/C][C]0.497918314404862[/C][C]0.751040842797569[/C][/ROW]
[ROW][C]33[/C][C]0.217421178977288[/C][C]0.434842357954576[/C][C]0.782578821022712[/C][/ROW]
[ROW][C]34[/C][C]0.178369234649196[/C][C]0.356738469298392[/C][C]0.821630765350804[/C][/ROW]
[ROW][C]35[/C][C]0.217867818066175[/C][C]0.435735636132351[/C][C]0.782132181933824[/C][/ROW]
[ROW][C]36[/C][C]0.201215205990948[/C][C]0.402430411981897[/C][C]0.798784794009052[/C][/ROW]
[ROW][C]37[/C][C]0.165356409024524[/C][C]0.330712818049049[/C][C]0.834643590975476[/C][/ROW]
[ROW][C]38[/C][C]0.193459404854362[/C][C]0.386918809708723[/C][C]0.806540595145638[/C][/ROW]
[ROW][C]39[/C][C]0.206894025939872[/C][C]0.413788051879744[/C][C]0.793105974060128[/C][/ROW]
[ROW][C]40[/C][C]0.177929302829723[/C][C]0.355858605659446[/C][C]0.822070697170277[/C][/ROW]
[ROW][C]41[/C][C]0.149026371730436[/C][C]0.298052743460872[/C][C]0.850973628269564[/C][/ROW]
[ROW][C]42[/C][C]0.126655282221277[/C][C]0.253310564442554[/C][C]0.873344717778723[/C][/ROW]
[ROW][C]43[/C][C]0.183568354774128[/C][C]0.367136709548257[/C][C]0.816431645225872[/C][/ROW]
[ROW][C]44[/C][C]0.151176229122688[/C][C]0.302352458245376[/C][C]0.848823770877312[/C][/ROW]
[ROW][C]45[/C][C]0.128675510756777[/C][C]0.257351021513555[/C][C]0.871324489243223[/C][/ROW]
[ROW][C]46[/C][C]0.137559111258664[/C][C]0.275118222517328[/C][C]0.862440888741336[/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]0.219542956842569[/C][C]0.890228521578716[/C][/ROW]
[ROW][C]49[/C][C]0.0988039009221863[/C][C]0.197607801844373[/C][C]0.901196099077814[/C][/ROW]
[ROW][C]50[/C][C]0.103123587468386[/C][C]0.206247174936772[/C][C]0.896876412531614[/C][/ROW]
[ROW][C]51[/C][C]0.106559721667355[/C][C]0.213119443334710[/C][C]0.893440278332645[/C][/ROW]
[ROW][C]52[/C][C]0.0862255418009586[/C][C]0.172451083601917[/C][C]0.913774458199041[/C][/ROW]
[ROW][C]53[/C][C]0.104472981736166[/C][C]0.208945963472331[/C][C]0.895527018263834[/C][/ROW]
[ROW][C]54[/C][C]0.0864560444665512[/C][C]0.172912088933102[/C][C]0.913543955533449[/C][/ROW]
[ROW][C]55[/C][C]0.147758140390661[/C][C]0.295516280781322[/C][C]0.852241859609339[/C][/ROW]
[ROW][C]56[/C][C]0.431409103558723[/C][C]0.862818207117446[/C][C]0.568590896441277[/C][/ROW]
[ROW][C]57[/C][C]0.388468979468214[/C][C]0.776937958936428[/C][C]0.611531020531786[/C][/ROW]
[ROW][C]58[/C][C]0.346869907949976[/C][C]0.693739815899952[/C][C]0.653130092050024[/C][/ROW]
[ROW][C]59[/C][C]0.306952256858892[/C][C]0.613904513717784[/C][C]0.693047743141108[/C][/ROW]
[ROW][C]60[/C][C]0.324717125796662[/C][C]0.649434251593324[/C][C]0.675282874203338[/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]0.623044399586528[/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]0.246153018287799[/C][C]0.492306036575597[/C][C]0.753846981712201[/C][/ROW]
[ROW][C]66[/C][C]0.221143289976963[/C][C]0.442286579953927[/C][C]0.778856710023037[/C][/ROW]
[ROW][C]67[/C][C]0.197420642750703[/C][C]0.394841285501405[/C][C]0.802579357249297[/C][/ROW]
[ROW][C]68[/C][C]0.176192401472964[/C][C]0.352384802945928[/C][C]0.823807598527036[/C][/ROW]
[ROW][C]69[/C][C]0.17106747620163[/C][C]0.34213495240326[/C][C]0.82893252379837[/C][/ROW]
[ROW][C]70[/C][C]0.148045215729029[/C][C]0.296090431458057[/C][C]0.851954784270971[/C][/ROW]
[ROW][C]71[/C][C]0.127234060178715[/C][C]0.254468120357429[/C][C]0.872765939821285[/C][/ROW]
[ROW][C]72[/C][C]0.108818487982061[/C][C]0.217636975964122[/C][C]0.89118151201794[/C][/ROW]
[ROW][C]73[/C][C]0.0932955476537801[/C][C]0.186591095307560[/C][C]0.90670445234622[/C][/ROW]
[ROW][C]74[/C][C]0.0833992745191812[/C][C]0.166798549038362[/C][C]0.916600725480819[/C][/ROW]
[ROW][C]75[/C][C]0.0802501779842058[/C][C]0.160500355968412[/C][C]0.919749822015794[/C][/ROW]
[ROW][C]76[/C][C]0.117197683862638[/C][C]0.234395367725276[/C][C]0.882802316137362[/C][/ROW]
[ROW][C]77[/C][C]0.103748999573259[/C][C]0.207497999146518[/C][C]0.89625100042674[/C][/ROW]
[ROW][C]78[/C][C]0.088686408699839[/C][C]0.177372817399678[/C][C]0.911313591300161[/C][/ROW]
[ROW][C]79[/C][C]0.102924771518784[/C][C]0.205849543037567[/C][C]0.897075228481216[/C][/ROW]
[ROW][C]80[/C][C]0.100437323346635[/C][C]0.200874646693270[/C][C]0.899562676653365[/C][/ROW]
[ROW][C]81[/C][C]0.0847185547508964[/C][C]0.169437109501793[/C][C]0.915281445249104[/C][/ROW]
[ROW][C]82[/C][C]0.0711077106379181[/C][C]0.142215421275836[/C][C]0.928892289362082[/C][/ROW]
[ROW][C]83[/C][C]0.0655142305519602[/C][C]0.131028461103920[/C][C]0.93448576944804[/C][/ROW]
[ROW][C]84[/C][C]0.0548104751735973[/C][C]0.109620950347195[/C][C]0.945189524826403[/C][/ROW]
[ROW][C]85[/C][C]0.0532257036873667[/C][C]0.106451407374733[/C][C]0.946774296312633[/C][/ROW]
[ROW][C]86[/C][C]0.0554661795888985[/C][C]0.110932359177797[/C][C]0.944533820411101[/C][/ROW]
[ROW][C]87[/C][C]0.0455281334598631[/C][C]0.0910562669197262[/C][C]0.954471866540137[/C][/ROW]
[ROW][C]88[/C][C]0.0371095842882434[/C][C]0.0742191685764868[/C][C]0.962890415711757[/C][/ROW]
[ROW][C]89[/C][C]0.0306306806627251[/C][C]0.0612613613254502[/C][C]0.969369319337275[/C][/ROW]
[ROW][C]90[/C][C]0.0270786723291566[/C][C]0.0541573446583131[/C][C]0.972921327670843[/C][/ROW]
[ROW][C]91[/C][C]0.0385910329628367[/C][C]0.0771820659256734[/C][C]0.961408967037163[/C][/ROW]
[ROW][C]92[/C][C]0.0324987759062189[/C][C]0.0649975518124378[/C][C]0.967501224093781[/C][/ROW]
[ROW][C]93[/C][C]0.0285154125515454[/C][C]0.0570308251030908[/C][C]0.971484587448455[/C][/ROW]
[ROW][C]94[/C][C]0.0291594031778265[/C][C]0.058318806355653[/C][C]0.970840596822173[/C][/ROW]
[ROW][C]95[/C][C]0.0303527781363014[/C][C]0.0607055562726029[/C][C]0.969647221863699[/C][/ROW]
[ROW][C]96[/C][C]0.0265363106230085[/C][C]0.053072621246017[/C][C]0.973463689376991[/C][/ROW]
[ROW][C]97[/C][C]0.0354601584889353[/C][C]0.0709203169778707[/C][C]0.964539841511065[/C][/ROW]
[ROW][C]98[/C][C]0.0301769264775427[/C][C]0.0603538529550854[/C][C]0.969823073522457[/C][/ROW]
[ROW][C]99[/C][C]0.0249808774094243[/C][C]0.0499617548188487[/C][C]0.975019122590576[/C][/ROW]
[ROW][C]100[/C][C]0.0284172836406998[/C][C]0.0568345672813996[/C][C]0.9715827163593[/C][/ROW]
[ROW][C]101[/C][C]0.0233087614532939[/C][C]0.0466175229065877[/C][C]0.976691238546706[/C][/ROW]
[ROW][C]102[/C][C]0.0199987759521447[/C][C]0.0399975519042894[/C][C]0.980001224047855[/C][/ROW]
[ROW][C]103[/C][C]0.0162698269349999[/C][C]0.0325396538699997[/C][C]0.983730173065[/C][/ROW]
[ROW][C]104[/C][C]0.0149152097687653[/C][C]0.0298304195375306[/C][C]0.985084790231235[/C][/ROW]
[ROW][C]105[/C][C]0.0171431043945457[/C][C]0.0342862087890914[/C][C]0.982856895605454[/C][/ROW]
[ROW][C]106[/C][C]0.0137587150012920[/C][C]0.0275174300025839[/C][C]0.986241284998708[/C][/ROW]
[ROW][C]107[/C][C]0.0110070600522211[/C][C]0.0220141201044423[/C][C]0.988992939947779[/C][/ROW]
[ROW][C]108[/C][C]0.00892829223274982[/C][C]0.0178565844654996[/C][C]0.99107170776725[/C][/ROW]
[ROW][C]109[/C][C]0.0163297170045168[/C][C]0.0326594340090336[/C][C]0.983670282995483[/C][/ROW]
[ROW][C]110[/C][C]0.0130871589343384[/C][C]0.0261743178686767[/C][C]0.986912841065662[/C][/ROW]
[ROW][C]111[/C][C]0.0144750625554424[/C][C]0.0289501251108848[/C][C]0.985524937444558[/C][/ROW]
[ROW][C]112[/C][C]0.0150594636386705[/C][C]0.0301189272773411[/C][C]0.98494053636133[/C][/ROW]
[ROW][C]113[/C][C]0.0121939235674454[/C][C]0.0243878471348908[/C][C]0.987806076432555[/C][/ROW]
[ROW][C]114[/C][C]0.0100477235447230[/C][C]0.0200954470894461[/C][C]0.989952276455277[/C][/ROW]
[ROW][C]115[/C][C]0.0109786841395223[/C][C]0.0219573682790445[/C][C]0.989021315860478[/C][/ROW]
[ROW][C]116[/C][C]0.0174473667590673[/C][C]0.0348947335181345[/C][C]0.982552633240933[/C][/ROW]
[ROW][C]117[/C][C]0.0146963365581384[/C][C]0.0293926731162767[/C][C]0.985303663441862[/C][/ROW]
[ROW][C]118[/C][C]0.0118098091747387[/C][C]0.0236196183494775[/C][C]0.988190190825261[/C][/ROW]
[ROW][C]119[/C][C]0.0101843201563572[/C][C]0.0203686403127144[/C][C]0.989815679843643[/C][/ROW]
[ROW][C]120[/C][C]0.00940733273273247[/C][C]0.0188146654654649[/C][C]0.990592667267268[/C][/ROW]
[ROW][C]121[/C][C]0.0096389996552318[/C][C]0.0192779993104636[/C][C]0.990361000344768[/C][/ROW]
[ROW][C]122[/C][C]0.0112972964729531[/C][C]0.0225945929459063[/C][C]0.988702703527047[/C][/ROW]
[ROW][C]123[/C][C]0.0121586875321394[/C][C]0.0243173750642787[/C][C]0.987841312467861[/C][/ROW]
[ROW][C]124[/C][C]0.0216553215382762[/C][C]0.0433106430765524[/C][C]0.978344678461724[/C][/ROW]
[ROW][C]125[/C][C]0.0178596776992178[/C][C]0.0357193553984357[/C][C]0.982140322300782[/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]0.943421373055725[/C][C]0.113157253888551[/C][C]0.0565786269442753[/C][/ROW]
[ROW][C]273[/C][C]0.902042733934533[/C][C]0.195914532130934[/C][C]0.0979572660654672[/C][/ROW]
[ROW][C]274[/C][C]0.903071709349389[/C][C]0.193856581301222[/C][C]0.0969282906506112[/C][/ROW]
[ROW][C]275[/C][C]0.88993391842091[/C][C]0.220132163158182[/C][C]0.110066081579091[/C][/ROW]
[ROW][C]276[/C][C]0.811762000333418[/C][C]0.376475999333165[/C][C]0.188237999666582[/C][/ROW]
[ROW][C]277[/C][C]0.719977651286748[/C][C]0.560044697426505[/C][C]0.280022348713252[/C][/ROW]
[ROW][C]278[/C][C]0.555516235808126[/C][C]0.888967528383748[/C][C]0.444483764191874[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113623&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113623&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.728426691490350.5431466170193010.271573308509650
110.932111291961430.1357774160771380.0678887080385691
120.8839275289213580.2321449421572840.116072471078642
130.9079961172925580.1840077654148840.092003882707442
140.8829186433667760.2341627132664490.117081356633224
150.8933724166429650.213255166714070.106627583357035
160.9014442860693590.1971114278612820.0985557139306408
170.8604782306201020.2790435387597970.139521769379899
180.8508823617452920.2982352765094160.149117638254708
190.8008756739698190.3982486520603620.199124326030181
200.7415269555133610.5169460889732780.258473044486639
210.680045374515350.6399092509692990.319954625484650
220.6119802819082640.7760394361834720.388019718091736
230.5389478376073920.9221043247852160.461052162392608
240.5146597033313840.9706805933372320.485340296668616
250.5131775092673770.9736449814652460.486822490732623
260.4799910107425950.959982021485190.520008989257405
270.4213958204168260.8427916408336520.578604179583174
280.4256903631724630.8513807263449250.574309636827537
290.3650843957596650.7301687915193310.634915604240335
300.3068020408982180.6136040817964360.693197959101782
310.2543547097987100.5087094195974210.74564529020129
320.2489591572024310.4979183144048620.751040842797569
330.2174211789772880.4348423579545760.782578821022712
340.1783692346491960.3567384692983920.821630765350804
350.2178678180661750.4357356361323510.782132181933824
360.2012152059909480.4024304119818970.798784794009052
370.1653564090245240.3307128180490490.834643590975476
380.1934594048543620.3869188097087230.806540595145638
390.2068940259398720.4137880518797440.793105974060128
400.1779293028297230.3558586056594460.822070697170277
410.1490263717304360.2980527434608720.850973628269564
420.1266552822212770.2533105644425540.873344717778723
430.1835683547741280.3671367095482570.816431645225872
440.1511762291226880.3023524582453760.848823770877312
450.1286755107567770.2573510215135550.871324489243223
460.1375591112586640.2751182225173280.862440888741336
470.1306733439987050.261346687997410.869326656001295
480.1097714784212840.2195429568425690.890228521578716
490.09880390092218630.1976078018443730.901196099077814
500.1031235874683860.2062471749367720.896876412531614
510.1065597216673550.2131194433347100.893440278332645
520.08622554180095860.1724510836019170.913774458199041
530.1044729817361660.2089459634723310.895527018263834
540.08645604446655120.1729120889331020.913543955533449
550.1477581403906610.2955162807813220.852241859609339
560.4314091035587230.8628182071174460.568590896441277
570.3884689794682140.7769379589364280.611531020531786
580.3468699079499760.6937398158999520.653130092050024
590.3069522568588920.6139045137177840.693047743141108
600.3247171257966620.6494342515933240.675282874203338
610.3406006838940710.6812013677881420.659399316105929
620.3115221997932640.6230443995865280.688477800206736
630.3157661192091480.6315322384182960.684233880790852
640.2796193987916860.5592387975833720.720380601208314
650.2461530182877990.4923060365755970.753846981712201
660.2211432899769630.4422865799539270.778856710023037
670.1974206427507030.3948412855014050.802579357249297
680.1761924014729640.3523848029459280.823807598527036
690.171067476201630.342134952403260.82893252379837
700.1480452157290290.2960904314580570.851954784270971
710.1272340601787150.2544681203574290.872765939821285
720.1088184879820610.2176369759641220.89118151201794
730.09329554765378010.1865910953075600.90670445234622
740.08339927451918120.1667985490383620.916600725480819
750.08025017798420580.1605003559684120.919749822015794
760.1171976838626380.2343953677252760.882802316137362
770.1037489995732590.2074979991465180.89625100042674
780.0886864086998390.1773728173996780.911313591300161
790.1029247715187840.2058495430375670.897075228481216
800.1004373233466350.2008746466932700.899562676653365
810.08471855475089640.1694371095017930.915281445249104
820.07110771063791810.1422154212758360.928892289362082
830.06551423055196020.1310284611039200.93448576944804
840.05481047517359730.1096209503471950.945189524826403
850.05322570368736670.1064514073747330.946774296312633
860.05546617958889850.1109323591777970.944533820411101
870.04552813345986310.09105626691972620.954471866540137
880.03710958428824340.07421916857648680.962890415711757
890.03063068066272510.06126136132545020.969369319337275
900.02707867232915660.05415734465831310.972921327670843
910.03859103296283670.07718206592567340.961408967037163
920.03249877590621890.06499755181243780.967501224093781
930.02851541255154540.05703082510309080.971484587448455
940.02915940317782650.0583188063556530.970840596822173
950.03035277813630140.06070555627260290.969647221863699
960.02653631062300850.0530726212460170.973463689376991
970.03546015848893530.07092031697787070.964539841511065
980.03017692647754270.06035385295508540.969823073522457
990.02498087740942430.04996175481884870.975019122590576
1000.02841728364069980.05683456728139960.9715827163593
1010.02330876145329390.04661752290658770.976691238546706
1020.01999877595214470.03999755190428940.980001224047855
1030.01626982693499990.03253965386999970.983730173065
1040.01491520976876530.02983041953753060.985084790231235
1050.01714310439454570.03428620878909140.982856895605454
1060.01375871500129200.02751743000258390.986241284998708
1070.01100706005222110.02201412010444230.988992939947779
1080.008928292232749820.01785658446549960.99107170776725
1090.01632971700451680.03265943400903360.983670282995483
1100.01308715893433840.02617431786867670.986912841065662
1110.01447506255544240.02895012511088480.985524937444558
1120.01505946363867050.03011892727734110.98494053636133
1130.01219392356744540.02438784713489080.987806076432555
1140.01004772354472300.02009544708944610.989952276455277
1150.01097868413952230.02195736827904450.989021315860478
1160.01744736675906730.03489473351813450.982552633240933
1170.01469633655813840.02939267311627670.985303663441862
1180.01180980917473870.02361961834947750.988190190825261
1190.01018432015635720.02036864031271440.989815679843643
1200.009407332732732470.01881466546546490.990592667267268
1210.00963899965523180.01927799931046360.990361000344768
1220.01129729647295310.02259459294590630.988702703527047
1230.01215868753213940.02431737506427870.987841312467861
1240.02165532153827620.04331064307655240.978344678461724
1250.01785967769921780.03571935539843570.982140322300782
1260.01577005515550910.03154011031101810.98422994484449
1270.01789476024455310.03578952048910610.982105239755447
1280.01734956644025350.0346991328805070.982650433559747
1290.01588224158520420.03176448317040840.984117758414796
1300.02153160380644860.04306320761289710.978468396193551
1310.04016094046480280.08032188092960550.959839059535197
1320.04063118122994360.08126236245988720.959368818770056
1330.04156733529495420.08313467058990830.958432664705046
1340.03768289106323150.0753657821264630.962317108936768
1350.03223857750092690.06447715500185370.967761422499073
1360.02698296810254560.05396593620509110.973017031897454
1370.0253367955989850.050673591197970.974663204401015
1380.02425735918107630.04851471836215250.975742640818924
1390.02081257755104920.04162515510209850.97918742244895
1400.0387894837859570.0775789675719140.961210516214043
1410.03910491465395740.07820982930791480.960895085346043
1420.05659346669033130.1131869333806630.943406533309669
1430.04764978088365040.09529956176730090.95235021911635
1440.04029573603196250.0805914720639250.959704263968038
1450.03549572733728850.0709914546745770.964504272662712
1460.04603637665635410.09207275331270820.953963623343646
1470.04405055193075430.08810110386150870.955949448069246
1480.03952912245120220.07905824490240440.960470877548798
1490.03679151102358760.07358302204717510.963208488976412
1500.05132576156711820.1026515231342360.948674238432882
1510.05222282660888160.1044456532177630.947777173391118
1520.1660168463196660.3320336926393320.833983153680334
1530.1769691137043480.3539382274086960.823030886295652
1540.1668293921000120.3336587842000230.833170607899988
1550.2375901080153840.4751802160307670.762409891984616
1560.2350140573339290.4700281146678590.76498594266607
1570.2139868598704250.4279737197408510.786013140129575
1580.2030382678539300.4060765357078590.79696173214607
1590.1822089740508320.3644179481016640.817791025949168
1600.1643312547847970.3286625095695950.835668745215203
1610.1783401695285350.3566803390570700.821659830471465
1620.1665358980628350.3330717961256690.833464101937165
1630.1464959437387540.2929918874775090.853504056261246
1640.1316997567202360.2633995134404720.868300243279764
1650.1808647180226370.3617294360452740.819135281977363
1660.1847546246546240.3695092493092490.815245375345376
1670.1667639651585590.3335279303171170.833236034841441
1680.2725314107532940.5450628215065890.727468589246706
1690.2465796736330210.4931593472660420.753420326366979
1700.2272649928730870.4545299857461740.772735007126913
1710.2061484375131090.4122968750262170.793851562486891
1720.2444807323798920.4889614647597840.755519267620108
1730.2186762871456610.4373525742913210.78132371285434
1740.2068461892243150.413692378448630.793153810775685
1750.1835310970406970.3670621940813930.816468902959303
1760.1630162914120530.3260325828241050.836983708587947
1770.1431490615992380.2862981231984750.856850938400762
1780.1263454311898150.2526908623796290.873654568810185
1790.1406245802309400.2812491604618810.85937541976906
1800.1485183120621530.2970366241243060.851481687937847
1810.140445516998750.28089103399750.85955448300125
1820.3303910130649250.6607820261298490.669608986935075
1830.3066851186908380.6133702373816770.693314881309162
1840.2826068532255850.565213706451170.717393146774415
1850.299879637091680.599759274183360.70012036290832
1860.2887430143267010.5774860286534030.711256985673299
1870.3784823693339350.7569647386678690.621517630666065
1880.3837468175566220.7674936351132440.616253182443378
1890.3550259110906440.7100518221812890.644974088909356
1900.7196950501494060.5606098997011880.280304949850594
1910.6893073297023440.6213853405953130.310692670297656
1920.6592337874368950.681532425126210.340766212563105
1930.6444709395269240.7110581209461510.355529060473076
1940.663296544757210.673406910485580.33670345524279
1950.6376650682669580.7246698634660840.362334931733042
1960.6136210568359330.7727578863281330.386378943164067
1970.5907381248536160.8185237502927690.409261875146384
1980.5586687426788130.8826625146423750.441331257321187
1990.5257580670070750.948483865985850.474241932992925
2000.597638960544830.804722078910340.40236103945517
2010.6420669265666950.715866146866610.357933073433305
2020.6073079881596210.7853840236807580.392692011840379
2030.5712957483264820.8574085033470350.428704251673518
2040.5434232733270120.9131534533459760.456576726672988
2050.5340259015628060.9319481968743880.465974098437194
2060.4987890926296490.9975781852592980.501210907370351
2070.567149305929750.8657013881405010.432850694070251
2080.6261695959705230.7476608080589550.373830404029477
2090.5957750766510460.8084498466979070.404224923348954
2100.6267976605830880.7464046788338240.373202339416912
2110.5978607263084040.8042785473831930.402139273691596
2120.5594497059377930.8811005881244130.440550294062207
2130.5257770270646360.9484459458707280.474222972935364
2140.4868226528619980.9736453057239970.513177347138002
2150.4750732437683780.9501464875367550.524926756231622
2160.4633299274943240.9266598549886470.536670072505676
2170.501002315087370.997995369825260.49899768491263
2180.4605155671976730.9210311343953450.539484432802327
2190.4480830609586440.8961661219172890.551916939041356
2200.4088725816562810.8177451633125630.591127418343719
2210.3757271789880770.7514543579761530.624272821011923
2220.3377517496016600.6755034992033190.66224825039834
2230.3097832998406210.6195665996812430.690216700159379
2240.2786927991142020.5573855982284040.721307200885798
2250.245135586828990.490271173657980.75486441317101
2260.3488112893170320.6976225786340650.651188710682968
2270.3942495626042790.7884991252085580.605750437395721
2280.6983737339019060.6032525321961880.301626266098094
2290.680000357306570.6399992853868610.319999642693430
2300.6401456939832170.7197086120335650.359854306016783
2310.6343176022642530.7313647954714930.365682397735747
2320.6314474833690720.7371050332618550.368552516630928
2330.6728825030314580.6542349939370840.327117496968542
2340.6486880123314820.7026239753370350.351311987668518
2350.6088168250208710.7823663499582570.391183174979129
2360.5707385343658520.8585229312682960.429261465634148
2370.6373057739186530.7253884521626940.362694226081347
2380.8518332866287770.2963334267424460.148166713371223
2390.9221310156055470.1557379687889060.077868984394453
2400.9055628258076090.1888743483847820.0944371741923909
2410.8934754595193810.2130490809612380.106524540480619
2420.884291041289910.231417917420180.11570895871009
2430.8606714422989570.2786571154020870.139328557701043
2440.8308837290899010.3382325418201980.169116270910099
2450.8325447213486370.3349105573027270.167455278651363
2460.8084982312188010.3830035375623980.191501768781199
2470.8625892381056530.2748215237886940.137410761894347
2480.8835311413937540.2329377172124930.116468858606246
2490.8662658338322920.2674683323354150.133734166167708
2500.8433031512324350.3133936975351300.156696848767565
2510.827808694695850.3443826106082990.172191305304150
2520.8219107900910860.3561784198178280.178089209908914
2530.8015425668367210.3969148663265580.198457433163279
2540.7700863298065920.4598273403868150.229913670193408
2550.7221551872904880.5556896254190240.277844812709512
2560.8759561331854360.2480877336291280.124043866814564
2570.8494590410605490.3010819178789020.150540958939451
2580.8263459053595650.3473081892808700.173654094640435
2590.8319232235627960.3361535528744080.168076776437204
2600.8486361751552750.3027276496894490.151363824844725
2610.8451625147717970.3096749704564050.154837485228203
2620.8013960426719010.3972079146561980.198603957328099
2630.7783104904806820.4433790190386360.221689509519318
2640.719715416357340.5605691672853190.280284583642660
2650.7723811548040380.4552376903919250.227618845195962
2660.8399226739994820.3201546520010360.160077326000518
2670.9269178104317420.1461643791365150.0730821895682577
2680.906671517932940.1866569641341200.0933284820670598
2690.8650077801533380.2699844396933240.134992219846662
2700.9266592189458480.1466815621083040.0733407810541522
2710.9045381752660720.1909236494678570.0954618247339284
2720.9434213730557250.1131572538885510.0565786269442753
2730.9020427339345330.1959145321309340.0979572660654672
2740.9030717093493890.1938565813012220.0969282906506112
2750.889933918420910.2201321631581820.110066081579091
2760.8117620003334180.3764759993331650.188237999666582
2770.7199776512867480.5600446974265050.280022348713252
2780.5555162358081260.8889675283837480.444483764191874






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=113623&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=113623&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113623&T=6

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

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


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 7 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par4 = no ;
Parameters (R input):
par1 = 7 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}