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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 11 Dec 2012 04:24:26 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/11/t13552181323i6zwazuny4aqxt.htm/, Retrieved Fri, 29 Mar 2024 05:02:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198371, Retrieved Fri, 29 Mar 2024 05:02:25 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Recursive Partitioning (Regression Trees)] [] [2010-12-05 18:59:57] [b98453cac15ba1066b407e146608df68]
- R P   [Recursive Partitioning (Regression Trees)] [Recursive partiti...] [2012-12-07 13:30:21] [57fcaae991493f873bcb4ee93ca06ef0]
- RMP       [Multiple Regression] [multiple regressi...] [2012-12-11 09:24:26] [91c3d91830a25c0bc67fd9a0665302b1] [Current]
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Dataseries X:
1	1	41	38	13	12	14
1	1	39	32	16	11	18
1	1	30	35	19	15	11
1	0	31	33	15	6	12
1	1	34	37	14	13	16
1	1	35	29	13	10	18
1	1	39	31	19	12	14
1	1	34	36	15	14	14
1	1	36	35	14	12	15
1	1	37	38	15	9	15
1	0	38	31	16	10	17
1	1	36	34	16	12	19
1	0	38	35	16	12	10
1	1	39	38	16	11	16
1	1	33	37	17	15	18
1	0	32	33	15	12	14
1	0	36	32	15	10	14
1	1	38	38	20	12	17
1	0	39	38	18	11	14
1	1	32	32	16	12	16
1	0	32	33	16	11	18
1	1	31	31	16	12	11
1	1	39	38	19	13	14
1	1	37	39	16	11	12
1	0	39	32	17	12	17
1	1	41	32	17	13	9
1	0	36	35	16	10	16
1	1	33	37	15	14	14
1	1	33	33	16	12	15
1	0	34	33	14	10	11
1	1	31	31	15	12	16
1	0	27	32	12	8	13
1	1	37	31	14	10	17
1	1	34	37	16	12	15
1	0	34	30	14	12	14
1	0	32	33	10	7	16
1	0	29	31	10	9	9
1	0	36	33	14	12	15
1	1	29	31	16	10	17
1	0	35	33	16	10	13
1	0	37	32	16	10	15
1	1	34	33	14	12	16
1	0	38	32	20	15	16
1	0	35	33	14	10	12
1	1	38	28	14	10	15
1	1	37	35	11	12	11
1	1	38	39	14	13	15
1	1	33	34	15	11	15
1	1	36	38	16	11	17
1	0	38	32	14	12	13
1	1	32	38	16	14	16
1	0	32	30	14	10	14
1	0	32	33	12	12	11
1	1	34	38	16	13	12
1	0	32	32	9	5	12
1	1	37	35	14	6	15
1	1	39	34	16	12	16
1	1	29	34	16	12	15
1	0	37	36	15	11	12
1	1	35	34	16	10	12
1	0	30	28	12	7	8
1	0	38	34	16	12	13
1	1	34	35	16	14	11
1	1	31	35	14	11	14
1	1	34	31	16	12	15
1	0	35	37	17	13	10
1	1	36	35	18	14	11
1	0	30	27	18	11	12
1	1	39	40	12	12	15
1	0	35	37	16	12	15
1	0	38	36	10	8	14
1	1	31	38	14	11	16
1	1	34	39	18	14	15
1	0	38	41	18	14	15
1	0	34	27	16	12	13
1	1	39	30	17	9	12
1	1	37	37	16	13	17
1	1	34	31	16	11	13
1	0	28	31	13	12	15
1	0	37	27	16	12	13
1	0	33	36	16	12	15
1	1	35	37	16	12	15
1	0	37	33	15	12	16
1	1	32	34	15	11	15
1	1	33	31	16	10	14
1	0	38	39	14	9	15
1	1	33	34	16	12	14
1	1	29	32	16	12	13
1	1	33	33	15	12	7
1	1	31	36	12	9	17
1	1	36	32	17	15	13
1	1	35	41	16	12	15
1	1	32	28	15	12	14
1	1	29	30	13	12	13
1	1	39	36	16	10	16
1	1	37	35	16	13	12
1	1	35	31	16	9	14
1	0	37	34	16	12	17
1	0	32	36	14	10	15
1	1	38	36	16	14	17
1	0	37	35	16	11	12
1	1	36	37	20	15	16
1	0	32	28	15	11	11
1	1	33	39	16	11	15
1	0	40	32	13	12	9
1	1	38	35	17	12	16
1	0	41	39	16	12	15
1	0	36	35	16	11	10
1	1	43	42	12	7	10
1	1	30	34	16	12	15
1	1	31	33	16	14	11
1	1	32	41	17	11	13
1	1	37	34	12	10	18
1	0	37	32	18	13	16
1	1	33	40	14	13	14
1	1	34	40	14	8	14
1	1	33	35	13	11	14
1	1	38	36	16	12	14
1	0	33	37	13	11	12
1	1	31	27	16	13	14
1	1	38	39	13	12	15
1	1	37	38	16	14	15
1	1	36	31	15	13	15
1	1	31	33	16	15	13
1	0	39	32	15	10	17
1	1	44	39	17	11	17
1	1	33	36	15	9	19
1	1	35	33	12	11	15
1	0	32	33	16	10	13
1	0	28	32	10	11	9
1	1	40	37	16	8	15
1	0	27	30	12	11	15
1	0	37	38	14	12	15
1	1	32	29	15	12	16
1	0	28	22	13	9	11
1	0	34	35	15	11	14
1	1	30	35	11	10	11
1	1	35	34	12	8	15
1	0	31	35	11	9	13
1	1	32	34	16	8	15
1	0	30	37	15	9	16
1	1	30	35	17	15	14
1	0	31	23	16	11	15
1	1	40	31	10	8	16
1	1	32	27	18	13	16
1	0	36	36	13	12	11
1	0	32	31	16	12	12
1	0	35	32	13	9	9
1	1	38	39	10	7	16
1	1	42	37	15	13	13
1	0	34	38	16	9	16
1	1	35	39	16	6	12
1	1	38	34	14	8	9
1	1	33	31	10	8	13
1	1	32	37	13	6	14
1	1	33	36	15	9	19
1	1	34	32	16	11	13
1	1	32	38	12	8	12
0	0	27	26	13	10	10
0	0	31	26	12	8	14
0	0	38	33	17	14	16
0	1	34	39	15	10	10
0	0	24	30	10	8	11
0	0	30	33	14	11	14
0	1	26	25	11	12	12
0	1	34	38	13	12	9
0	0	27	37	16	12	9
0	0	37	31	12	5	11
0	1	36	37	16	12	16
0	0	41	35	12	10	9
0	1	29	25	9	7	13
0	1	36	28	12	12	16
0	0	32	35	15	11	13
0	1	37	33	12	8	9
0	0	30	30	12	9	12
0	1	31	31	14	10	16
0	1	38	37	12	9	11
0	1	36	36	16	12	14
0	0	35	30	11	6	13
0	0	31	36	19	15	15
0	0	38	32	15	12	14
0	1	22	28	8	12	16
0	1	32	36	16	12	13
0	0	36	34	17	11	14
0	1	39	31	12	7	15
0	0	28	28	11	7	13
0	0	32	36	11	5	11
0	1	32	36	14	12	11
0	1	38	40	16	12	14
0	1	32	33	12	3	15
0	1	35	37	16	11	11
0	1	32	32	13	10	15
0	0	37	38	15	12	12
0	1	34	31	16	9	14
0	1	33	37	16	12	14
0	0	33	33	14	9	8
0	0	30	30	16	12	9
0	0	24	30	14	10	15
0	0	34	31	11	9	17
0	0	34	32	12	12	13
0	1	33	34	15	8	15
0	1	34	36	15	11	15
0	1	35	37	16	11	14
0	0	35	36	16	12	16
0	0	36	33	11	10	13
0	0	34	33	15	10	16
0	1	34	33	12	12	9
0	0	41	44	12	12	16
0	0	32	39	15	11	11
0	0	30	32	15	8	10
0	1	35	35	16	12	11
0	0	28	25	14	10	15
0	1	33	35	17	11	17
0	1	39	34	14	10	14
0	0	36	35	13	8	8
0	1	36	39	15	12	15
0	0	35	33	13	12	11
0	0	38	36	14	10	16
0	1	33	32	15	12	10
0	0	31	32	12	9	15
0	1	32	36	8	6	16
0	0	31	32	14	10	19
0	0	33	34	14	9	12
0	0	34	33	11	9	8
0	0	34	35	12	9	11
0	1	34	30	13	6	14
0	0	33	38	10	10	9
0	0	32	34	16	6	15
0	1	41	33	18	14	13
0	1	34	32	13	10	16
0	0	36	31	11	10	11
0	0	37	30	4	6	12
0	0	36	27	13	12	13
0	1	29	31	16	12	10
0	0	37	30	10	7	11
0	0	27	32	12	8	12
0	0	35	35	12	11	8
0	0	28	28	10	3	12
0	0	35	33	13	6	12
0	0	29	35	12	8	11
0	0	32	35	14	9	13
0	1	36	32	10	9	14
0	1	19	21	12	8	10
0	1	21	20	12	9	12
0	0	31	34	11	7	15
0	0	33	32	10	7	13
0	1	36	34	12	6	13
0	1	33	32	16	9	13
0	0	37	33	12	10	12
0	0	34	33	14	11	12
0	0	35	37	16	12	9
0	1	31	32	14	8	9
0	1	37	34	13	11	15
0	1	35	30	4	3	10
0	1	27	30	15	11	14
0	0	34	38	11	12	15
0	0	40	36	11	7	7
0	0	29	32	14	9	14
0	0	38	34	15	12	8
0	1	34	33	14	8	10
0	0	21	27	13	11	13
0	0	36	32	11	8	13
0	1	38	34	15	10	13
0	0	30	29	11	8	8
0	0	35	35	13	7	12
0	1	30	27	13	8	13
0	1	36	33	16	10	12
0	0	34	38	13	8	10
0	1	35	36	16	12	13
0	0	34	33	16	14	12
0	0	32	39	12	7	9
0	1	33	29	7	6	15
0	0	33	32	16	11	13
0	1	26	34	5	4	13
0	0	35	38	16	9	13
0	0	21	17	4	5	15
0	0	38	35	12	9	15
0	0	35	32	15	11	14
0	1	33	34	14	12	15
0	0	37	36	11	9	11
0	0	38	31	16	12	15
0	1	34	35	15	10	14
0	0	27	29	12	9	13
0	1	16	22	6	6	12
0	0	40	41	16	10	16
0	0	36	36	10	9	16
0	1	42	42	15	13	9
0	1	30	33	14	12	14




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 13 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198371&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]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198371&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198371&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Pop[t] = -1.14995038292072 + 0.0996782073881794Gender[t] + 0.0109330405479477Connected[t] -0.000911994364465981Separate[t] + 0.0367600498910606Learning[t] + 0.0289914646044682Software[t] + 0.0360988324179169Happiness[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Pop[t] =  -1.14995038292072 +  0.0996782073881794Gender[t] +  0.0109330405479477Connected[t] -0.000911994364465981Separate[t] +  0.0367600498910606Learning[t] +  0.0289914646044682Software[t] +  0.0360988324179169Happiness[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198371&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Pop[t] =  -1.14995038292072 +  0.0996782073881794Gender[t] +  0.0109330405479477Connected[t] -0.000911994364465981Separate[t] +  0.0367600498910606Learning[t] +  0.0289914646044682Software[t] +  0.0360988324179169Happiness[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198371&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198371&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
Pop[t] = -1.14995038292072 + 0.0996782073881794Gender[t] + 0.0109330405479477Connected[t] -0.000911994364465981Separate[t] + 0.0367600498910606Learning[t] + 0.0289914646044682Software[t] + 0.0360988324179169Happiness[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-1.149950382920720.288831-3.98148.7e-054.4e-05
Gender0.09967820738817940.0553111.80210.0725960.036298
Connected0.01093304054794770.0078341.39560.1639250.081963
Separate-0.0009119943644659810.00817-0.11160.9112030.455601
Learning0.03676004989106060.0139782.62990.0090110.004506
Software0.02899146460446820.0149991.93290.0542570.027129
Happiness0.03609883241791690.0111393.24090.0013350.000667

\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) & -1.14995038292072 & 0.288831 & -3.9814 & 8.7e-05 & 4.4e-05 \tabularnewline
Gender & 0.0996782073881794 & 0.055311 & 1.8021 & 0.072596 & 0.036298 \tabularnewline
Connected & 0.0109330405479477 & 0.007834 & 1.3956 & 0.163925 & 0.081963 \tabularnewline
Separate & -0.000911994364465981 & 0.00817 & -0.1116 & 0.911203 & 0.455601 \tabularnewline
Learning & 0.0367600498910606 & 0.013978 & 2.6299 & 0.009011 & 0.004506 \tabularnewline
Software & 0.0289914646044682 & 0.014999 & 1.9329 & 0.054257 & 0.027129 \tabularnewline
Happiness & 0.0360988324179169 & 0.011139 & 3.2409 & 0.001335 & 0.000667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198371&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]-1.14995038292072[/C][C]0.288831[/C][C]-3.9814[/C][C]8.7e-05[/C][C]4.4e-05[/C][/ROW]
[ROW][C]Gender[/C][C]0.0996782073881794[/C][C]0.055311[/C][C]1.8021[/C][C]0.072596[/C][C]0.036298[/C][/ROW]
[ROW][C]Connected[/C][C]0.0109330405479477[/C][C]0.007834[/C][C]1.3956[/C][C]0.163925[/C][C]0.081963[/C][/ROW]
[ROW][C]Separate[/C][C]-0.000911994364465981[/C][C]0.00817[/C][C]-0.1116[/C][C]0.911203[/C][C]0.455601[/C][/ROW]
[ROW][C]Learning[/C][C]0.0367600498910606[/C][C]0.013978[/C][C]2.6299[/C][C]0.009011[/C][C]0.004506[/C][/ROW]
[ROW][C]Software[/C][C]0.0289914646044682[/C][C]0.014999[/C][C]1.9329[/C][C]0.054257[/C][C]0.027129[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0360988324179169[/C][C]0.011139[/C][C]3.2409[/C][C]0.001335[/C][C]0.000667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198371&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198371&T=2

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-1.149950382920720.288831-3.98148.7e-054.4e-05
Gender0.09967820738817940.0553111.80210.0725960.036298
Connected0.01093304054794770.0078341.39560.1639250.081963
Separate-0.0009119943644659810.00817-0.11160.9112030.455601
Learning0.03676004989106060.0139782.62990.0090110.004506
Software0.02899146460446820.0149991.93290.0542570.027129
Happiness0.03609883241791690.0111393.24090.0013350.000667







Multiple Linear Regression - Regression Statistics
Multiple R0.44790472945712
R-squared0.200618646670056
Adjusted R-squared0.183550005673687
F-TEST (value)11.7536391276104
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value9.325318295339e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.450430533542206
Sum Squared Residuals57.0114340187397

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.44790472945712 \tabularnewline
R-squared & 0.200618646670056 \tabularnewline
Adjusted R-squared & 0.183550005673687 \tabularnewline
F-TEST (value) & 11.7536391276104 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 281 \tabularnewline
p-value & 9.325318295339e-12 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.450430533542206 \tabularnewline
Sum Squared Residuals & 57.0114340187397 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198371&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.44790472945712[/C][/ROW]
[ROW][C]R-squared[/C][C]0.200618646670056[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.183550005673687[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]11.7536391276104[/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]9.325318295339e-12[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.450430533542206[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]57.0114340187397[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198371&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198371&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.44790472945712
R-squared0.200618646670056
Adjusted R-squared0.183550005673687
F-TEST (value)11.7536391276104
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value9.325318295339e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.450430533542206
Sum Squared Residuals57.0114340187397







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
110.6944885787718530.305511421228147
210.9037784786031340.0962215213968659
310.7761993117438430.223800688256157
410.3174135850460040.682586414953996
510.7568184686320470.243181531367953
610.7235106852270910.276489314772909
710.8995667575735830.100433242426418
810.7512843126562080.248715687343792
910.7154182414344890.284581758565511
1010.6734009549666950.326599045033305
1110.7289889280090880.271011071990912
1210.9342456652527440.0657543347472557
1310.5306320528347420.469367947165258
1410.8261088475805050.173891152419495
1510.9863461718020510.0136538281979485
1610.5744930780565950.425506921943405
1710.5611543054039150.438845694596085
1811.02730630361918-0.0273063036191842
1910.7277530751386120.272246924861388
2010.7840409945361350.215959005463865
2110.7266569930148550.273343006985145
2210.5935257862630680.406474213736932
2310.9221742616267890.0778257383732112
2410.6589354424484750.341064557551525
2510.8337529532925670.166247046707433
2610.6954980470377740.304501952962226
2710.6673760370374120.332623962962588
2810.7394392777437940.260560722256206
2910.7579632083016990.242036791698301
3010.3933196827987430.606680317201257
3110.7372598984615920.262740101538408
3210.2583950291723510.741604970827649
3310.7442139950671990.255786004932801
3410.7652482713917830.234751728608217
3510.5623350923548280.437664907645172
3610.3179331704147850.682066829585215
3710.09224913978339130.907750860216609
3810.6175640227752420.382435977224758
3910.7302697704657380.269730229534262
4010.5499704879646450.450029512035355
4110.644946228260840.35505377173916
4210.7314749814854430.268525018514557
4310.9839756238132880.0160243761867116
4410.4403515557646070.559648444235393
4510.685685353872710.31431464612729
4610.4716758026375880.528324197362412
4710.7626278096769890.237372190323011
4810.6912996994417050.308700300558295
4910.8294085583545780.170591441645422
5010.568144433399770.43185556660023
5110.8365519575582750.163448042441725
5210.4824860820499960.517513917950004
5310.3559164311296620.644083568870338
5410.6850312443780340.314968755621966
5510.07970685600758620.920293143992414
5610.5524024943556280.447597505644372
5710.8587482896428370.141251710357163
5810.7133190517454420.286680948254558
5910.5252331682626330.474766831737367
6010.6126378685704410.387362131429559
6110.0853565015800050.914643498419995
6210.6398405444529590.360159455547041
6310.6806598596579840.319340140342016
6410.5956627416723660.404337258327634
6510.7707202375785790.229279762421421
6610.5617604569574960.438239543042504
6710.7760460405360.223953959464
6810.5671899833803750.432810016619625
6910.6701372914738820.329862708526118
7010.6765031045515510.323496895448448
7110.3375892303777080.662410769622292
7210.6651244234148010.334875576585199
7310.8949273116539090.105072688346091
7410.8371572777285880.162842722271412
7510.602492342812430.39750765718757
7610.6677865935066890.332213406493311
7710.8992365224759280.100763477524072
7810.6695311081382770.330468891861723
7910.4951636372295310.504836362770469
8010.6352914644562730.364708535543727
8110.6555490178201220.344450982179878
8210.7761813119397310.223818688060269
8310.7013559456321670.298644054367833
8410.6803666588937570.319633341106243
8510.6657054354037780.334294564596222
8610.5469837438709370.453016256129063
8710.7209523815193160.279047618480684
8810.642945375638540.35705462436146
8910.4324124990673030.567587500932697
9010.5715442155705930.428455784429407
9110.843211103178640.15678889682136
9210.7725333344818670.227466665518133
9310.6787312572671040.321268742732896
9410.5344892146942910.465510785305709
9510.7989413717049680.201058628295032
9610.7205663491152760.279433650884724
9710.6585800518952050.341419948104795
9810.7733028335766790.226697166423321
9910.5131129482811170.486887051718883
10010.940073021992810.0599269780071896
10110.562905212518160.43709478748184
10211.05722777828324-0.0572277782832425
10310.4417650880207060.558234911979294
10410.7234997775104350.276500222489565
10510.4088551349329370.591144865067063
10610.8836633046214840.116336695378516
10710.7402773591103060.259722640889694
10810.4797745071343780.520225492865622
10910.3865939798248150.613406020175185
11010.724252092293390.27574790770661
11110.6496847267430730.350315273256928
11210.6753051332887820.324694866711218
11310.7040567446095960.295943255390404
11410.8415395542742830.158460445725717
11510.6709517801548680.329048219845132
11610.5369274976804740.463072502319526
11710.5807687728772010.419231227122799
11810.7737935955301230.226206404469877
11910.4070689119242560.592931088075744
12010.7344617255791510.265538274420849
12110.696876295181460.30312370481854
12210.8551183278800970.144881672119903
12310.7848177333878820.215182266612118
12410.7508738561833750.249126143816625
12510.7022499243015090.297750075698491
12610.9527209382647550.0472790617352452
12710.7758881111755040.224111888824496
12810.6037976252288840.396202374771116
12910.5171713663208020.482828633679198
13010.1383870340799140.861612965920086
13110.7148806562615970.285119343738403
13210.4193910765505210.580608923449479
13310.623937091500860.37606290849914
13410.7500169277384720.249983072261528
13510.2720018630246530.727998136975347
13610.565543705819090.43445629418091
13710.3371615895930170.662838410406983
13810.5159112370510140.484088762948986
13910.2916226229841510.708377377015849
14010.6301523149714130.369847685028587
14110.5342022905252650.465797709474735
14210.8109757092154720.189024290784528
14310.6165473988578160.383452601142184
14410.5358911555199460.464108844480054
14510.8911125307450540.108887469254946
14610.4336726601191160.566327339880884
14710.5408794518407530.459120548159247
14810.2672155383797940.732784461620206
14910.4777376549038550.522262345096145
15010.7727463456529390.227253654347061
15110.613782508243650.38621749175635
15210.4921120383302390.507887961669761
15310.4056374639694760.594362536030524
15410.3510633744305610.648936625569439
15510.423054420577980.57694557942202
15610.7758881111755040.224111888824496
15710.6686191137738110.331380886226189
15810.3711676406955560.628832359304444
15900.250313477205393-0.250313477205393
16000.343697989968854-0.343697989968854
16100.843792015171172-0.843792015171172
16200.488187141473269-0.488187141473269
16300.0817021316394842-0.0817021316394842
16400.48687548246517-0.48687548246517
16500.396631132672739-0.396631132672739
16600.437463132846634-0.437463132846634
16700.372445785660468-0.372445785660468
16800.209465370367055-0.209465370367055
16900.823213184905595-0.823213184905595
17000.32230921328749-0.32230921328749
17100.247051663930037-0.247051663930037
17200.684380934621547-0.684380934621547
17300.507578792305278-0.507578792305278
17400.322096318003874-0.322096318003874
17500.285910771731677-0.285910771731677
17600.642516919361595-0.642516919361595
17700.43057051053426-0.43057051053426
17800.751927514434228-0.751927514434228
17900.252940363184867-0.252940363184867
18000.830937480210813-0.830937480210813
18100.641003315708747-0.641003315708747
18200.384278167386037-0.384278167386037
18300.67209651982452-0.67209651982452
18400.661841881061573-0.661841881061573
18500.533387917731734-0.533387917731734
18600.207224532682633-0.207224532682633
18700.113480145913926-0.113480145913926
18800.526378755206565-0.526378755206565
18900.770145618072259-0.770145618072259
19000.339066786749296-0.339066786749296
19100.602794517663595-0.602794517663595
19200.579679083236099-0.579679083236099
19300.55240064413817-0.55240064413817
19400.647647011347257-0.647647011347257
19500.718216398425918-0.718216398425918
19600.245098680392576-0.245098680392576
19700.411628867855573-0.411628867855573
19800.431120590084331-0.431120590084331
19900.472465051757526-0.472465051757526
20000.450892171425858-0.450892171425858
20100.6043253056283-0.6043253056283
20200.70040875126072-0.70040875126072
20300.711091014917346-0.711091014917346
20400.713513931333934-0.713513931333934
20500.37710327905729-0.37710327905729
20600.610573894779388-0.610573894779388
20700.405263054777903-0.405263054777903
20800.624776020141651-0.624776020141651
20900.43173315001158-0.43173315001158
21000.293177803235625-0.293177803235625
21100.633609970996995-0.633609970996995
21200.479412724098452-0.479412724098452
21300.836105469695193-0.836105469695193
21400.655047595815946-0.655047595815946
21500.210322298811958-0.210322298811958
21600.748530313867686-0.748530313867686
21700.425475602664566-0.425475602664566
21800.61481002398672-0.61481002398672
21900.54162099068552-0.54162099068552
22000.403316320804444-0.403316320804444
22100.312363830322977-0.312363830322977
22200.650223214862701-0.650223214862701
22300.388582015699777-0.388582015699777
22400.145751571267342-0.145751571267342
22500.288984129683221-0.288984129683221
22600.451304462225137-0.451304462225137
22700.158588806028389-0.158588806028389
22800.472491178374297-0.472491178374297
22900.904732896840505-0.904732896840505
23000.637643996749912-0.637643996749912
23100.306729602950388-0.306729602950388
2320-0.0186127373745780.018612737374578
23300.514078274235144-0.514078274235144
23400.535560872749256-0.535560872749256
23500.194840194158337-0.194840194158337
23600.222296196754434-0.222296196754434
23700.249603602186355-0.249603602186355
23800.018399791955783-0.018399791955783
23900.287625647455674-0.287625647455674
24000.205327462339014-0.205327462339014
24100.412835813205281-0.412835813205281
24200.448040798732323-0.448040798732323
24300.172344352932323-0.172344352932323
24400.296311557832986-0.296311557832986
24500.306749352975515-0.306749352975515
24600.221481708073448-0.221481708073448
24700.396663683554191-0.396663683554191
24800.599703144016926-0.599703144016926
24900.388697537078381-0.388697537078381
25000.458409979821127-0.458409979821127
25100.45991011004405-0.45991011004405
25200.330930168862774-0.330930168862774
25300.661511761851375-0.661511761851375
2540-0.09997266973153250.0999726697315325
25500.593250601193965-0.593250601193965
25600.480857820183835-0.480857820183835
25700.114532069834777-0.114532069834777
25800.418871507072752-0.418871507072752
25900.422586332472314-0.422586332472314
26000.398916128560068-0.398916128560068
26100.321091201411459-0.321091201411459
26200.32003234421282-0.32003234421282
26300.644775772741141-0.644775772741141
26400.0766759219289464-0.0766759219289464
26500.31479312333121-0.31479312333121
26600.432192379917764-0.432192379917764
26700.624482903482855-0.624482903482855
26800.257917899458499-0.257917899458499
26900.704895641468363-0.704895641468363
27000.618904473416653-0.618904473416653
27100.133289477084691-0.133289477084691
27200.256821949113209-0.256821949113209
27300.558007865837684-0.558007865837684
2740-0.02797000037164650.0279700003716465
27500.516419051537847-0.516419051537847
2760-0.1023804267544010.102380426754401
27700.47711162154668-0.47711162154668
27800.579212729460436-0.579212729460436
27900.683531114155112-0.683531114155112
28000.284111207071538-0.284111207071538
28100.714774192382191-0.714774192382191
28200.636230448602801-0.636230448602801
28300.290122476870217-0.290122476870217
2840-0.06771232679545210.0677123267954521
28500.705636233042407-0.705636233042407
28600.416912278722114-0.416912278722114
28700.623791044158941-0.623791044158941
28800.615545154457818-0.615545154457818

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1 & 0.694488578771853 & 0.305511421228147 \tabularnewline
2 & 1 & 0.903778478603134 & 0.0962215213968659 \tabularnewline
3 & 1 & 0.776199311743843 & 0.223800688256157 \tabularnewline
4 & 1 & 0.317413585046004 & 0.682586414953996 \tabularnewline
5 & 1 & 0.756818468632047 & 0.243181531367953 \tabularnewline
6 & 1 & 0.723510685227091 & 0.276489314772909 \tabularnewline
7 & 1 & 0.899566757573583 & 0.100433242426418 \tabularnewline
8 & 1 & 0.751284312656208 & 0.248715687343792 \tabularnewline
9 & 1 & 0.715418241434489 & 0.284581758565511 \tabularnewline
10 & 1 & 0.673400954966695 & 0.326599045033305 \tabularnewline
11 & 1 & 0.728988928009088 & 0.271011071990912 \tabularnewline
12 & 1 & 0.934245665252744 & 0.0657543347472557 \tabularnewline
13 & 1 & 0.530632052834742 & 0.469367947165258 \tabularnewline
14 & 1 & 0.826108847580505 & 0.173891152419495 \tabularnewline
15 & 1 & 0.986346171802051 & 0.0136538281979485 \tabularnewline
16 & 1 & 0.574493078056595 & 0.425506921943405 \tabularnewline
17 & 1 & 0.561154305403915 & 0.438845694596085 \tabularnewline
18 & 1 & 1.02730630361918 & -0.0273063036191842 \tabularnewline
19 & 1 & 0.727753075138612 & 0.272246924861388 \tabularnewline
20 & 1 & 0.784040994536135 & 0.215959005463865 \tabularnewline
21 & 1 & 0.726656993014855 & 0.273343006985145 \tabularnewline
22 & 1 & 0.593525786263068 & 0.406474213736932 \tabularnewline
23 & 1 & 0.922174261626789 & 0.0778257383732112 \tabularnewline
24 & 1 & 0.658935442448475 & 0.341064557551525 \tabularnewline
25 & 1 & 0.833752953292567 & 0.166247046707433 \tabularnewline
26 & 1 & 0.695498047037774 & 0.304501952962226 \tabularnewline
27 & 1 & 0.667376037037412 & 0.332623962962588 \tabularnewline
28 & 1 & 0.739439277743794 & 0.260560722256206 \tabularnewline
29 & 1 & 0.757963208301699 & 0.242036791698301 \tabularnewline
30 & 1 & 0.393319682798743 & 0.606680317201257 \tabularnewline
31 & 1 & 0.737259898461592 & 0.262740101538408 \tabularnewline
32 & 1 & 0.258395029172351 & 0.741604970827649 \tabularnewline
33 & 1 & 0.744213995067199 & 0.255786004932801 \tabularnewline
34 & 1 & 0.765248271391783 & 0.234751728608217 \tabularnewline
35 & 1 & 0.562335092354828 & 0.437664907645172 \tabularnewline
36 & 1 & 0.317933170414785 & 0.682066829585215 \tabularnewline
37 & 1 & 0.0922491397833913 & 0.907750860216609 \tabularnewline
38 & 1 & 0.617564022775242 & 0.382435977224758 \tabularnewline
39 & 1 & 0.730269770465738 & 0.269730229534262 \tabularnewline
40 & 1 & 0.549970487964645 & 0.450029512035355 \tabularnewline
41 & 1 & 0.64494622826084 & 0.35505377173916 \tabularnewline
42 & 1 & 0.731474981485443 & 0.268525018514557 \tabularnewline
43 & 1 & 0.983975623813288 & 0.0160243761867116 \tabularnewline
44 & 1 & 0.440351555764607 & 0.559648444235393 \tabularnewline
45 & 1 & 0.68568535387271 & 0.31431464612729 \tabularnewline
46 & 1 & 0.471675802637588 & 0.528324197362412 \tabularnewline
47 & 1 & 0.762627809676989 & 0.237372190323011 \tabularnewline
48 & 1 & 0.691299699441705 & 0.308700300558295 \tabularnewline
49 & 1 & 0.829408558354578 & 0.170591441645422 \tabularnewline
50 & 1 & 0.56814443339977 & 0.43185556660023 \tabularnewline
51 & 1 & 0.836551957558275 & 0.163448042441725 \tabularnewline
52 & 1 & 0.482486082049996 & 0.517513917950004 \tabularnewline
53 & 1 & 0.355916431129662 & 0.644083568870338 \tabularnewline
54 & 1 & 0.685031244378034 & 0.314968755621966 \tabularnewline
55 & 1 & 0.0797068560075862 & 0.920293143992414 \tabularnewline
56 & 1 & 0.552402494355628 & 0.447597505644372 \tabularnewline
57 & 1 & 0.858748289642837 & 0.141251710357163 \tabularnewline
58 & 1 & 0.713319051745442 & 0.286680948254558 \tabularnewline
59 & 1 & 0.525233168262633 & 0.474766831737367 \tabularnewline
60 & 1 & 0.612637868570441 & 0.387362131429559 \tabularnewline
61 & 1 & 0.085356501580005 & 0.914643498419995 \tabularnewline
62 & 1 & 0.639840544452959 & 0.360159455547041 \tabularnewline
63 & 1 & 0.680659859657984 & 0.319340140342016 \tabularnewline
64 & 1 & 0.595662741672366 & 0.404337258327634 \tabularnewline
65 & 1 & 0.770720237578579 & 0.229279762421421 \tabularnewline
66 & 1 & 0.561760456957496 & 0.438239543042504 \tabularnewline
67 & 1 & 0.776046040536 & 0.223953959464 \tabularnewline
68 & 1 & 0.567189983380375 & 0.432810016619625 \tabularnewline
69 & 1 & 0.670137291473882 & 0.329862708526118 \tabularnewline
70 & 1 & 0.676503104551551 & 0.323496895448448 \tabularnewline
71 & 1 & 0.337589230377708 & 0.662410769622292 \tabularnewline
72 & 1 & 0.665124423414801 & 0.334875576585199 \tabularnewline
73 & 1 & 0.894927311653909 & 0.105072688346091 \tabularnewline
74 & 1 & 0.837157277728588 & 0.162842722271412 \tabularnewline
75 & 1 & 0.60249234281243 & 0.39750765718757 \tabularnewline
76 & 1 & 0.667786593506689 & 0.332213406493311 \tabularnewline
77 & 1 & 0.899236522475928 & 0.100763477524072 \tabularnewline
78 & 1 & 0.669531108138277 & 0.330468891861723 \tabularnewline
79 & 1 & 0.495163637229531 & 0.504836362770469 \tabularnewline
80 & 1 & 0.635291464456273 & 0.364708535543727 \tabularnewline
81 & 1 & 0.655549017820122 & 0.344450982179878 \tabularnewline
82 & 1 & 0.776181311939731 & 0.223818688060269 \tabularnewline
83 & 1 & 0.701355945632167 & 0.298644054367833 \tabularnewline
84 & 1 & 0.680366658893757 & 0.319633341106243 \tabularnewline
85 & 1 & 0.665705435403778 & 0.334294564596222 \tabularnewline
86 & 1 & 0.546983743870937 & 0.453016256129063 \tabularnewline
87 & 1 & 0.720952381519316 & 0.279047618480684 \tabularnewline
88 & 1 & 0.64294537563854 & 0.35705462436146 \tabularnewline
89 & 1 & 0.432412499067303 & 0.567587500932697 \tabularnewline
90 & 1 & 0.571544215570593 & 0.428455784429407 \tabularnewline
91 & 1 & 0.84321110317864 & 0.15678889682136 \tabularnewline
92 & 1 & 0.772533334481867 & 0.227466665518133 \tabularnewline
93 & 1 & 0.678731257267104 & 0.321268742732896 \tabularnewline
94 & 1 & 0.534489214694291 & 0.465510785305709 \tabularnewline
95 & 1 & 0.798941371704968 & 0.201058628295032 \tabularnewline
96 & 1 & 0.720566349115276 & 0.279433650884724 \tabularnewline
97 & 1 & 0.658580051895205 & 0.341419948104795 \tabularnewline
98 & 1 & 0.773302833576679 & 0.226697166423321 \tabularnewline
99 & 1 & 0.513112948281117 & 0.486887051718883 \tabularnewline
100 & 1 & 0.94007302199281 & 0.0599269780071896 \tabularnewline
101 & 1 & 0.56290521251816 & 0.43709478748184 \tabularnewline
102 & 1 & 1.05722777828324 & -0.0572277782832425 \tabularnewline
103 & 1 & 0.441765088020706 & 0.558234911979294 \tabularnewline
104 & 1 & 0.723499777510435 & 0.276500222489565 \tabularnewline
105 & 1 & 0.408855134932937 & 0.591144865067063 \tabularnewline
106 & 1 & 0.883663304621484 & 0.116336695378516 \tabularnewline
107 & 1 & 0.740277359110306 & 0.259722640889694 \tabularnewline
108 & 1 & 0.479774507134378 & 0.520225492865622 \tabularnewline
109 & 1 & 0.386593979824815 & 0.613406020175185 \tabularnewline
110 & 1 & 0.72425209229339 & 0.27574790770661 \tabularnewline
111 & 1 & 0.649684726743073 & 0.350315273256928 \tabularnewline
112 & 1 & 0.675305133288782 & 0.324694866711218 \tabularnewline
113 & 1 & 0.704056744609596 & 0.295943255390404 \tabularnewline
114 & 1 & 0.841539554274283 & 0.158460445725717 \tabularnewline
115 & 1 & 0.670951780154868 & 0.329048219845132 \tabularnewline
116 & 1 & 0.536927497680474 & 0.463072502319526 \tabularnewline
117 & 1 & 0.580768772877201 & 0.419231227122799 \tabularnewline
118 & 1 & 0.773793595530123 & 0.226206404469877 \tabularnewline
119 & 1 & 0.407068911924256 & 0.592931088075744 \tabularnewline
120 & 1 & 0.734461725579151 & 0.265538274420849 \tabularnewline
121 & 1 & 0.69687629518146 & 0.30312370481854 \tabularnewline
122 & 1 & 0.855118327880097 & 0.144881672119903 \tabularnewline
123 & 1 & 0.784817733387882 & 0.215182266612118 \tabularnewline
124 & 1 & 0.750873856183375 & 0.249126143816625 \tabularnewline
125 & 1 & 0.702249924301509 & 0.297750075698491 \tabularnewline
126 & 1 & 0.952720938264755 & 0.0472790617352452 \tabularnewline
127 & 1 & 0.775888111175504 & 0.224111888824496 \tabularnewline
128 & 1 & 0.603797625228884 & 0.396202374771116 \tabularnewline
129 & 1 & 0.517171366320802 & 0.482828633679198 \tabularnewline
130 & 1 & 0.138387034079914 & 0.861612965920086 \tabularnewline
131 & 1 & 0.714880656261597 & 0.285119343738403 \tabularnewline
132 & 1 & 0.419391076550521 & 0.580608923449479 \tabularnewline
133 & 1 & 0.62393709150086 & 0.37606290849914 \tabularnewline
134 & 1 & 0.750016927738472 & 0.249983072261528 \tabularnewline
135 & 1 & 0.272001863024653 & 0.727998136975347 \tabularnewline
136 & 1 & 0.56554370581909 & 0.43445629418091 \tabularnewline
137 & 1 & 0.337161589593017 & 0.662838410406983 \tabularnewline
138 & 1 & 0.515911237051014 & 0.484088762948986 \tabularnewline
139 & 1 & 0.291622622984151 & 0.708377377015849 \tabularnewline
140 & 1 & 0.630152314971413 & 0.369847685028587 \tabularnewline
141 & 1 & 0.534202290525265 & 0.465797709474735 \tabularnewline
142 & 1 & 0.810975709215472 & 0.189024290784528 \tabularnewline
143 & 1 & 0.616547398857816 & 0.383452601142184 \tabularnewline
144 & 1 & 0.535891155519946 & 0.464108844480054 \tabularnewline
145 & 1 & 0.891112530745054 & 0.108887469254946 \tabularnewline
146 & 1 & 0.433672660119116 & 0.566327339880884 \tabularnewline
147 & 1 & 0.540879451840753 & 0.459120548159247 \tabularnewline
148 & 1 & 0.267215538379794 & 0.732784461620206 \tabularnewline
149 & 1 & 0.477737654903855 & 0.522262345096145 \tabularnewline
150 & 1 & 0.772746345652939 & 0.227253654347061 \tabularnewline
151 & 1 & 0.61378250824365 & 0.38621749175635 \tabularnewline
152 & 1 & 0.492112038330239 & 0.507887961669761 \tabularnewline
153 & 1 & 0.405637463969476 & 0.594362536030524 \tabularnewline
154 & 1 & 0.351063374430561 & 0.648936625569439 \tabularnewline
155 & 1 & 0.42305442057798 & 0.57694557942202 \tabularnewline
156 & 1 & 0.775888111175504 & 0.224111888824496 \tabularnewline
157 & 1 & 0.668619113773811 & 0.331380886226189 \tabularnewline
158 & 1 & 0.371167640695556 & 0.628832359304444 \tabularnewline
159 & 0 & 0.250313477205393 & -0.250313477205393 \tabularnewline
160 & 0 & 0.343697989968854 & -0.343697989968854 \tabularnewline
161 & 0 & 0.843792015171172 & -0.843792015171172 \tabularnewline
162 & 0 & 0.488187141473269 & -0.488187141473269 \tabularnewline
163 & 0 & 0.0817021316394842 & -0.0817021316394842 \tabularnewline
164 & 0 & 0.48687548246517 & -0.48687548246517 \tabularnewline
165 & 0 & 0.396631132672739 & -0.396631132672739 \tabularnewline
166 & 0 & 0.437463132846634 & -0.437463132846634 \tabularnewline
167 & 0 & 0.372445785660468 & -0.372445785660468 \tabularnewline
168 & 0 & 0.209465370367055 & -0.209465370367055 \tabularnewline
169 & 0 & 0.823213184905595 & -0.823213184905595 \tabularnewline
170 & 0 & 0.32230921328749 & -0.32230921328749 \tabularnewline
171 & 0 & 0.247051663930037 & -0.247051663930037 \tabularnewline
172 & 0 & 0.684380934621547 & -0.684380934621547 \tabularnewline
173 & 0 & 0.507578792305278 & -0.507578792305278 \tabularnewline
174 & 0 & 0.322096318003874 & -0.322096318003874 \tabularnewline
175 & 0 & 0.285910771731677 & -0.285910771731677 \tabularnewline
176 & 0 & 0.642516919361595 & -0.642516919361595 \tabularnewline
177 & 0 & 0.43057051053426 & -0.43057051053426 \tabularnewline
178 & 0 & 0.751927514434228 & -0.751927514434228 \tabularnewline
179 & 0 & 0.252940363184867 & -0.252940363184867 \tabularnewline
180 & 0 & 0.830937480210813 & -0.830937480210813 \tabularnewline
181 & 0 & 0.641003315708747 & -0.641003315708747 \tabularnewline
182 & 0 & 0.384278167386037 & -0.384278167386037 \tabularnewline
183 & 0 & 0.67209651982452 & -0.67209651982452 \tabularnewline
184 & 0 & 0.661841881061573 & -0.661841881061573 \tabularnewline
185 & 0 & 0.533387917731734 & -0.533387917731734 \tabularnewline
186 & 0 & 0.207224532682633 & -0.207224532682633 \tabularnewline
187 & 0 & 0.113480145913926 & -0.113480145913926 \tabularnewline
188 & 0 & 0.526378755206565 & -0.526378755206565 \tabularnewline
189 & 0 & 0.770145618072259 & -0.770145618072259 \tabularnewline
190 & 0 & 0.339066786749296 & -0.339066786749296 \tabularnewline
191 & 0 & 0.602794517663595 & -0.602794517663595 \tabularnewline
192 & 0 & 0.579679083236099 & -0.579679083236099 \tabularnewline
193 & 0 & 0.55240064413817 & -0.55240064413817 \tabularnewline
194 & 0 & 0.647647011347257 & -0.647647011347257 \tabularnewline
195 & 0 & 0.718216398425918 & -0.718216398425918 \tabularnewline
196 & 0 & 0.245098680392576 & -0.245098680392576 \tabularnewline
197 & 0 & 0.411628867855573 & -0.411628867855573 \tabularnewline
198 & 0 & 0.431120590084331 & -0.431120590084331 \tabularnewline
199 & 0 & 0.472465051757526 & -0.472465051757526 \tabularnewline
200 & 0 & 0.450892171425858 & -0.450892171425858 \tabularnewline
201 & 0 & 0.6043253056283 & -0.6043253056283 \tabularnewline
202 & 0 & 0.70040875126072 & -0.70040875126072 \tabularnewline
203 & 0 & 0.711091014917346 & -0.711091014917346 \tabularnewline
204 & 0 & 0.713513931333934 & -0.713513931333934 \tabularnewline
205 & 0 & 0.37710327905729 & -0.37710327905729 \tabularnewline
206 & 0 & 0.610573894779388 & -0.610573894779388 \tabularnewline
207 & 0 & 0.405263054777903 & -0.405263054777903 \tabularnewline
208 & 0 & 0.624776020141651 & -0.624776020141651 \tabularnewline
209 & 0 & 0.43173315001158 & -0.43173315001158 \tabularnewline
210 & 0 & 0.293177803235625 & -0.293177803235625 \tabularnewline
211 & 0 & 0.633609970996995 & -0.633609970996995 \tabularnewline
212 & 0 & 0.479412724098452 & -0.479412724098452 \tabularnewline
213 & 0 & 0.836105469695193 & -0.836105469695193 \tabularnewline
214 & 0 & 0.655047595815946 & -0.655047595815946 \tabularnewline
215 & 0 & 0.210322298811958 & -0.210322298811958 \tabularnewline
216 & 0 & 0.748530313867686 & -0.748530313867686 \tabularnewline
217 & 0 & 0.425475602664566 & -0.425475602664566 \tabularnewline
218 & 0 & 0.61481002398672 & -0.61481002398672 \tabularnewline
219 & 0 & 0.54162099068552 & -0.54162099068552 \tabularnewline
220 & 0 & 0.403316320804444 & -0.403316320804444 \tabularnewline
221 & 0 & 0.312363830322977 & -0.312363830322977 \tabularnewline
222 & 0 & 0.650223214862701 & -0.650223214862701 \tabularnewline
223 & 0 & 0.388582015699777 & -0.388582015699777 \tabularnewline
224 & 0 & 0.145751571267342 & -0.145751571267342 \tabularnewline
225 & 0 & 0.288984129683221 & -0.288984129683221 \tabularnewline
226 & 0 & 0.451304462225137 & -0.451304462225137 \tabularnewline
227 & 0 & 0.158588806028389 & -0.158588806028389 \tabularnewline
228 & 0 & 0.472491178374297 & -0.472491178374297 \tabularnewline
229 & 0 & 0.904732896840505 & -0.904732896840505 \tabularnewline
230 & 0 & 0.637643996749912 & -0.637643996749912 \tabularnewline
231 & 0 & 0.306729602950388 & -0.306729602950388 \tabularnewline
232 & 0 & -0.018612737374578 & 0.018612737374578 \tabularnewline
233 & 0 & 0.514078274235144 & -0.514078274235144 \tabularnewline
234 & 0 & 0.535560872749256 & -0.535560872749256 \tabularnewline
235 & 0 & 0.194840194158337 & -0.194840194158337 \tabularnewline
236 & 0 & 0.222296196754434 & -0.222296196754434 \tabularnewline
237 & 0 & 0.249603602186355 & -0.249603602186355 \tabularnewline
238 & 0 & 0.018399791955783 & -0.018399791955783 \tabularnewline
239 & 0 & 0.287625647455674 & -0.287625647455674 \tabularnewline
240 & 0 & 0.205327462339014 & -0.205327462339014 \tabularnewline
241 & 0 & 0.412835813205281 & -0.412835813205281 \tabularnewline
242 & 0 & 0.448040798732323 & -0.448040798732323 \tabularnewline
243 & 0 & 0.172344352932323 & -0.172344352932323 \tabularnewline
244 & 0 & 0.296311557832986 & -0.296311557832986 \tabularnewline
245 & 0 & 0.306749352975515 & -0.306749352975515 \tabularnewline
246 & 0 & 0.221481708073448 & -0.221481708073448 \tabularnewline
247 & 0 & 0.396663683554191 & -0.396663683554191 \tabularnewline
248 & 0 & 0.599703144016926 & -0.599703144016926 \tabularnewline
249 & 0 & 0.388697537078381 & -0.388697537078381 \tabularnewline
250 & 0 & 0.458409979821127 & -0.458409979821127 \tabularnewline
251 & 0 & 0.45991011004405 & -0.45991011004405 \tabularnewline
252 & 0 & 0.330930168862774 & -0.330930168862774 \tabularnewline
253 & 0 & 0.661511761851375 & -0.661511761851375 \tabularnewline
254 & 0 & -0.0999726697315325 & 0.0999726697315325 \tabularnewline
255 & 0 & 0.593250601193965 & -0.593250601193965 \tabularnewline
256 & 0 & 0.480857820183835 & -0.480857820183835 \tabularnewline
257 & 0 & 0.114532069834777 & -0.114532069834777 \tabularnewline
258 & 0 & 0.418871507072752 & -0.418871507072752 \tabularnewline
259 & 0 & 0.422586332472314 & -0.422586332472314 \tabularnewline
260 & 0 & 0.398916128560068 & -0.398916128560068 \tabularnewline
261 & 0 & 0.321091201411459 & -0.321091201411459 \tabularnewline
262 & 0 & 0.32003234421282 & -0.32003234421282 \tabularnewline
263 & 0 & 0.644775772741141 & -0.644775772741141 \tabularnewline
264 & 0 & 0.0766759219289464 & -0.0766759219289464 \tabularnewline
265 & 0 & 0.31479312333121 & -0.31479312333121 \tabularnewline
266 & 0 & 0.432192379917764 & -0.432192379917764 \tabularnewline
267 & 0 & 0.624482903482855 & -0.624482903482855 \tabularnewline
268 & 0 & 0.257917899458499 & -0.257917899458499 \tabularnewline
269 & 0 & 0.704895641468363 & -0.704895641468363 \tabularnewline
270 & 0 & 0.618904473416653 & -0.618904473416653 \tabularnewline
271 & 0 & 0.133289477084691 & -0.133289477084691 \tabularnewline
272 & 0 & 0.256821949113209 & -0.256821949113209 \tabularnewline
273 & 0 & 0.558007865837684 & -0.558007865837684 \tabularnewline
274 & 0 & -0.0279700003716465 & 0.0279700003716465 \tabularnewline
275 & 0 & 0.516419051537847 & -0.516419051537847 \tabularnewline
276 & 0 & -0.102380426754401 & 0.102380426754401 \tabularnewline
277 & 0 & 0.47711162154668 & -0.47711162154668 \tabularnewline
278 & 0 & 0.579212729460436 & -0.579212729460436 \tabularnewline
279 & 0 & 0.683531114155112 & -0.683531114155112 \tabularnewline
280 & 0 & 0.284111207071538 & -0.284111207071538 \tabularnewline
281 & 0 & 0.714774192382191 & -0.714774192382191 \tabularnewline
282 & 0 & 0.636230448602801 & -0.636230448602801 \tabularnewline
283 & 0 & 0.290122476870217 & -0.290122476870217 \tabularnewline
284 & 0 & -0.0677123267954521 & 0.0677123267954521 \tabularnewline
285 & 0 & 0.705636233042407 & -0.705636233042407 \tabularnewline
286 & 0 & 0.416912278722114 & -0.416912278722114 \tabularnewline
287 & 0 & 0.623791044158941 & -0.623791044158941 \tabularnewline
288 & 0 & 0.615545154457818 & -0.615545154457818 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198371&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]1[/C][C]0.694488578771853[/C][C]0.305511421228147[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]0.903778478603134[/C][C]0.0962215213968659[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]0.776199311743843[/C][C]0.223800688256157[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]0.317413585046004[/C][C]0.682586414953996[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]0.756818468632047[/C][C]0.243181531367953[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]0.723510685227091[/C][C]0.276489314772909[/C][/ROW]
[ROW][C]7[/C][C]1[/C][C]0.899566757573583[/C][C]0.100433242426418[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]0.751284312656208[/C][C]0.248715687343792[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]0.715418241434489[/C][C]0.284581758565511[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]0.673400954966695[/C][C]0.326599045033305[/C][/ROW]
[ROW][C]11[/C][C]1[/C][C]0.728988928009088[/C][C]0.271011071990912[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]0.934245665252744[/C][C]0.0657543347472557[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]0.530632052834742[/C][C]0.469367947165258[/C][/ROW]
[ROW][C]14[/C][C]1[/C][C]0.826108847580505[/C][C]0.173891152419495[/C][/ROW]
[ROW][C]15[/C][C]1[/C][C]0.986346171802051[/C][C]0.0136538281979485[/C][/ROW]
[ROW][C]16[/C][C]1[/C][C]0.574493078056595[/C][C]0.425506921943405[/C][/ROW]
[ROW][C]17[/C][C]1[/C][C]0.561154305403915[/C][C]0.438845694596085[/C][/ROW]
[ROW][C]18[/C][C]1[/C][C]1.02730630361918[/C][C]-0.0273063036191842[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]0.727753075138612[/C][C]0.272246924861388[/C][/ROW]
[ROW][C]20[/C][C]1[/C][C]0.784040994536135[/C][C]0.215959005463865[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]0.726656993014855[/C][C]0.273343006985145[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]0.593525786263068[/C][C]0.406474213736932[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]0.922174261626789[/C][C]0.0778257383732112[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]0.658935442448475[/C][C]0.341064557551525[/C][/ROW]
[ROW][C]25[/C][C]1[/C][C]0.833752953292567[/C][C]0.166247046707433[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]0.695498047037774[/C][C]0.304501952962226[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]0.667376037037412[/C][C]0.332623962962588[/C][/ROW]
[ROW][C]28[/C][C]1[/C][C]0.739439277743794[/C][C]0.260560722256206[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]0.757963208301699[/C][C]0.242036791698301[/C][/ROW]
[ROW][C]30[/C][C]1[/C][C]0.393319682798743[/C][C]0.606680317201257[/C][/ROW]
[ROW][C]31[/C][C]1[/C][C]0.737259898461592[/C][C]0.262740101538408[/C][/ROW]
[ROW][C]32[/C][C]1[/C][C]0.258395029172351[/C][C]0.741604970827649[/C][/ROW]
[ROW][C]33[/C][C]1[/C][C]0.744213995067199[/C][C]0.255786004932801[/C][/ROW]
[ROW][C]34[/C][C]1[/C][C]0.765248271391783[/C][C]0.234751728608217[/C][/ROW]
[ROW][C]35[/C][C]1[/C][C]0.562335092354828[/C][C]0.437664907645172[/C][/ROW]
[ROW][C]36[/C][C]1[/C][C]0.317933170414785[/C][C]0.682066829585215[/C][/ROW]
[ROW][C]37[/C][C]1[/C][C]0.0922491397833913[/C][C]0.907750860216609[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]0.617564022775242[/C][C]0.382435977224758[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]0.730269770465738[/C][C]0.269730229534262[/C][/ROW]
[ROW][C]40[/C][C]1[/C][C]0.549970487964645[/C][C]0.450029512035355[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.64494622826084[/C][C]0.35505377173916[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]0.731474981485443[/C][C]0.268525018514557[/C][/ROW]
[ROW][C]43[/C][C]1[/C][C]0.983975623813288[/C][C]0.0160243761867116[/C][/ROW]
[ROW][C]44[/C][C]1[/C][C]0.440351555764607[/C][C]0.559648444235393[/C][/ROW]
[ROW][C]45[/C][C]1[/C][C]0.68568535387271[/C][C]0.31431464612729[/C][/ROW]
[ROW][C]46[/C][C]1[/C][C]0.471675802637588[/C][C]0.528324197362412[/C][/ROW]
[ROW][C]47[/C][C]1[/C][C]0.762627809676989[/C][C]0.237372190323011[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]0.691299699441705[/C][C]0.308700300558295[/C][/ROW]
[ROW][C]49[/C][C]1[/C][C]0.829408558354578[/C][C]0.170591441645422[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]0.56814443339977[/C][C]0.43185556660023[/C][/ROW]
[ROW][C]51[/C][C]1[/C][C]0.836551957558275[/C][C]0.163448042441725[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]0.482486082049996[/C][C]0.517513917950004[/C][/ROW]
[ROW][C]53[/C][C]1[/C][C]0.355916431129662[/C][C]0.644083568870338[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]0.685031244378034[/C][C]0.314968755621966[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]0.0797068560075862[/C][C]0.920293143992414[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]0.552402494355628[/C][C]0.447597505644372[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]0.858748289642837[/C][C]0.141251710357163[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]0.713319051745442[/C][C]0.286680948254558[/C][/ROW]
[ROW][C]59[/C][C]1[/C][C]0.525233168262633[/C][C]0.474766831737367[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]0.612637868570441[/C][C]0.387362131429559[/C][/ROW]
[ROW][C]61[/C][C]1[/C][C]0.085356501580005[/C][C]0.914643498419995[/C][/ROW]
[ROW][C]62[/C][C]1[/C][C]0.639840544452959[/C][C]0.360159455547041[/C][/ROW]
[ROW][C]63[/C][C]1[/C][C]0.680659859657984[/C][C]0.319340140342016[/C][/ROW]
[ROW][C]64[/C][C]1[/C][C]0.595662741672366[/C][C]0.404337258327634[/C][/ROW]
[ROW][C]65[/C][C]1[/C][C]0.770720237578579[/C][C]0.229279762421421[/C][/ROW]
[ROW][C]66[/C][C]1[/C][C]0.561760456957496[/C][C]0.438239543042504[/C][/ROW]
[ROW][C]67[/C][C]1[/C][C]0.776046040536[/C][C]0.223953959464[/C][/ROW]
[ROW][C]68[/C][C]1[/C][C]0.567189983380375[/C][C]0.432810016619625[/C][/ROW]
[ROW][C]69[/C][C]1[/C][C]0.670137291473882[/C][C]0.329862708526118[/C][/ROW]
[ROW][C]70[/C][C]1[/C][C]0.676503104551551[/C][C]0.323496895448448[/C][/ROW]
[ROW][C]71[/C][C]1[/C][C]0.337589230377708[/C][C]0.662410769622292[/C][/ROW]
[ROW][C]72[/C][C]1[/C][C]0.665124423414801[/C][C]0.334875576585199[/C][/ROW]
[ROW][C]73[/C][C]1[/C][C]0.894927311653909[/C][C]0.105072688346091[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]0.837157277728588[/C][C]0.162842722271412[/C][/ROW]
[ROW][C]75[/C][C]1[/C][C]0.60249234281243[/C][C]0.39750765718757[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]0.667786593506689[/C][C]0.332213406493311[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]0.899236522475928[/C][C]0.100763477524072[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]0.669531108138277[/C][C]0.330468891861723[/C][/ROW]
[ROW][C]79[/C][C]1[/C][C]0.495163637229531[/C][C]0.504836362770469[/C][/ROW]
[ROW][C]80[/C][C]1[/C][C]0.635291464456273[/C][C]0.364708535543727[/C][/ROW]
[ROW][C]81[/C][C]1[/C][C]0.655549017820122[/C][C]0.344450982179878[/C][/ROW]
[ROW][C]82[/C][C]1[/C][C]0.776181311939731[/C][C]0.223818688060269[/C][/ROW]
[ROW][C]83[/C][C]1[/C][C]0.701355945632167[/C][C]0.298644054367833[/C][/ROW]
[ROW][C]84[/C][C]1[/C][C]0.680366658893757[/C][C]0.319633341106243[/C][/ROW]
[ROW][C]85[/C][C]1[/C][C]0.665705435403778[/C][C]0.334294564596222[/C][/ROW]
[ROW][C]86[/C][C]1[/C][C]0.546983743870937[/C][C]0.453016256129063[/C][/ROW]
[ROW][C]87[/C][C]1[/C][C]0.720952381519316[/C][C]0.279047618480684[/C][/ROW]
[ROW][C]88[/C][C]1[/C][C]0.64294537563854[/C][C]0.35705462436146[/C][/ROW]
[ROW][C]89[/C][C]1[/C][C]0.432412499067303[/C][C]0.567587500932697[/C][/ROW]
[ROW][C]90[/C][C]1[/C][C]0.571544215570593[/C][C]0.428455784429407[/C][/ROW]
[ROW][C]91[/C][C]1[/C][C]0.84321110317864[/C][C]0.15678889682136[/C][/ROW]
[ROW][C]92[/C][C]1[/C][C]0.772533334481867[/C][C]0.227466665518133[/C][/ROW]
[ROW][C]93[/C][C]1[/C][C]0.678731257267104[/C][C]0.321268742732896[/C][/ROW]
[ROW][C]94[/C][C]1[/C][C]0.534489214694291[/C][C]0.465510785305709[/C][/ROW]
[ROW][C]95[/C][C]1[/C][C]0.798941371704968[/C][C]0.201058628295032[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]0.720566349115276[/C][C]0.279433650884724[/C][/ROW]
[ROW][C]97[/C][C]1[/C][C]0.658580051895205[/C][C]0.341419948104795[/C][/ROW]
[ROW][C]98[/C][C]1[/C][C]0.773302833576679[/C][C]0.226697166423321[/C][/ROW]
[ROW][C]99[/C][C]1[/C][C]0.513112948281117[/C][C]0.486887051718883[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]0.94007302199281[/C][C]0.0599269780071896[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]0.56290521251816[/C][C]0.43709478748184[/C][/ROW]
[ROW][C]102[/C][C]1[/C][C]1.05722777828324[/C][C]-0.0572277782832425[/C][/ROW]
[ROW][C]103[/C][C]1[/C][C]0.441765088020706[/C][C]0.558234911979294[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]0.723499777510435[/C][C]0.276500222489565[/C][/ROW]
[ROW][C]105[/C][C]1[/C][C]0.408855134932937[/C][C]0.591144865067063[/C][/ROW]
[ROW][C]106[/C][C]1[/C][C]0.883663304621484[/C][C]0.116336695378516[/C][/ROW]
[ROW][C]107[/C][C]1[/C][C]0.740277359110306[/C][C]0.259722640889694[/C][/ROW]
[ROW][C]108[/C][C]1[/C][C]0.479774507134378[/C][C]0.520225492865622[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]0.386593979824815[/C][C]0.613406020175185[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]0.72425209229339[/C][C]0.27574790770661[/C][/ROW]
[ROW][C]111[/C][C]1[/C][C]0.649684726743073[/C][C]0.350315273256928[/C][/ROW]
[ROW][C]112[/C][C]1[/C][C]0.675305133288782[/C][C]0.324694866711218[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]0.704056744609596[/C][C]0.295943255390404[/C][/ROW]
[ROW][C]114[/C][C]1[/C][C]0.841539554274283[/C][C]0.158460445725717[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]0.670951780154868[/C][C]0.329048219845132[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]0.536927497680474[/C][C]0.463072502319526[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]0.580768772877201[/C][C]0.419231227122799[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]0.773793595530123[/C][C]0.226206404469877[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]0.407068911924256[/C][C]0.592931088075744[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]0.734461725579151[/C][C]0.265538274420849[/C][/ROW]
[ROW][C]121[/C][C]1[/C][C]0.69687629518146[/C][C]0.30312370481854[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]0.855118327880097[/C][C]0.144881672119903[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]0.784817733387882[/C][C]0.215182266612118[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]0.750873856183375[/C][C]0.249126143816625[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]0.702249924301509[/C][C]0.297750075698491[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]0.952720938264755[/C][C]0.0472790617352452[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]0.775888111175504[/C][C]0.224111888824496[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]0.603797625228884[/C][C]0.396202374771116[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]0.517171366320802[/C][C]0.482828633679198[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]0.138387034079914[/C][C]0.861612965920086[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]0.714880656261597[/C][C]0.285119343738403[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]0.419391076550521[/C][C]0.580608923449479[/C][/ROW]
[ROW][C]133[/C][C]1[/C][C]0.62393709150086[/C][C]0.37606290849914[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]0.750016927738472[/C][C]0.249983072261528[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]0.272001863024653[/C][C]0.727998136975347[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]0.56554370581909[/C][C]0.43445629418091[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]0.337161589593017[/C][C]0.662838410406983[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]0.515911237051014[/C][C]0.484088762948986[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]0.291622622984151[/C][C]0.708377377015849[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]0.630152314971413[/C][C]0.369847685028587[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]0.534202290525265[/C][C]0.465797709474735[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]0.810975709215472[/C][C]0.189024290784528[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]0.616547398857816[/C][C]0.383452601142184[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]0.535891155519946[/C][C]0.464108844480054[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]0.891112530745054[/C][C]0.108887469254946[/C][/ROW]
[ROW][C]146[/C][C]1[/C][C]0.433672660119116[/C][C]0.566327339880884[/C][/ROW]
[ROW][C]147[/C][C]1[/C][C]0.540879451840753[/C][C]0.459120548159247[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]0.267215538379794[/C][C]0.732784461620206[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]0.477737654903855[/C][C]0.522262345096145[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]0.772746345652939[/C][C]0.227253654347061[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]0.61378250824365[/C][C]0.38621749175635[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]0.492112038330239[/C][C]0.507887961669761[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]0.405637463969476[/C][C]0.594362536030524[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]0.351063374430561[/C][C]0.648936625569439[/C][/ROW]
[ROW][C]155[/C][C]1[/C][C]0.42305442057798[/C][C]0.57694557942202[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]0.775888111175504[/C][C]0.224111888824496[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]0.668619113773811[/C][C]0.331380886226189[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]0.371167640695556[/C][C]0.628832359304444[/C][/ROW]
[ROW][C]159[/C][C]0[/C][C]0.250313477205393[/C][C]-0.250313477205393[/C][/ROW]
[ROW][C]160[/C][C]0[/C][C]0.343697989968854[/C][C]-0.343697989968854[/C][/ROW]
[ROW][C]161[/C][C]0[/C][C]0.843792015171172[/C][C]-0.843792015171172[/C][/ROW]
[ROW][C]162[/C][C]0[/C][C]0.488187141473269[/C][C]-0.488187141473269[/C][/ROW]
[ROW][C]163[/C][C]0[/C][C]0.0817021316394842[/C][C]-0.0817021316394842[/C][/ROW]
[ROW][C]164[/C][C]0[/C][C]0.48687548246517[/C][C]-0.48687548246517[/C][/ROW]
[ROW][C]165[/C][C]0[/C][C]0.396631132672739[/C][C]-0.396631132672739[/C][/ROW]
[ROW][C]166[/C][C]0[/C][C]0.437463132846634[/C][C]-0.437463132846634[/C][/ROW]
[ROW][C]167[/C][C]0[/C][C]0.372445785660468[/C][C]-0.372445785660468[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]0.209465370367055[/C][C]-0.209465370367055[/C][/ROW]
[ROW][C]169[/C][C]0[/C][C]0.823213184905595[/C][C]-0.823213184905595[/C][/ROW]
[ROW][C]170[/C][C]0[/C][C]0.32230921328749[/C][C]-0.32230921328749[/C][/ROW]
[ROW][C]171[/C][C]0[/C][C]0.247051663930037[/C][C]-0.247051663930037[/C][/ROW]
[ROW][C]172[/C][C]0[/C][C]0.684380934621547[/C][C]-0.684380934621547[/C][/ROW]
[ROW][C]173[/C][C]0[/C][C]0.507578792305278[/C][C]-0.507578792305278[/C][/ROW]
[ROW][C]174[/C][C]0[/C][C]0.322096318003874[/C][C]-0.322096318003874[/C][/ROW]
[ROW][C]175[/C][C]0[/C][C]0.285910771731677[/C][C]-0.285910771731677[/C][/ROW]
[ROW][C]176[/C][C]0[/C][C]0.642516919361595[/C][C]-0.642516919361595[/C][/ROW]
[ROW][C]177[/C][C]0[/C][C]0.43057051053426[/C][C]-0.43057051053426[/C][/ROW]
[ROW][C]178[/C][C]0[/C][C]0.751927514434228[/C][C]-0.751927514434228[/C][/ROW]
[ROW][C]179[/C][C]0[/C][C]0.252940363184867[/C][C]-0.252940363184867[/C][/ROW]
[ROW][C]180[/C][C]0[/C][C]0.830937480210813[/C][C]-0.830937480210813[/C][/ROW]
[ROW][C]181[/C][C]0[/C][C]0.641003315708747[/C][C]-0.641003315708747[/C][/ROW]
[ROW][C]182[/C][C]0[/C][C]0.384278167386037[/C][C]-0.384278167386037[/C][/ROW]
[ROW][C]183[/C][C]0[/C][C]0.67209651982452[/C][C]-0.67209651982452[/C][/ROW]
[ROW][C]184[/C][C]0[/C][C]0.661841881061573[/C][C]-0.661841881061573[/C][/ROW]
[ROW][C]185[/C][C]0[/C][C]0.533387917731734[/C][C]-0.533387917731734[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]0.207224532682633[/C][C]-0.207224532682633[/C][/ROW]
[ROW][C]187[/C][C]0[/C][C]0.113480145913926[/C][C]-0.113480145913926[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]0.526378755206565[/C][C]-0.526378755206565[/C][/ROW]
[ROW][C]189[/C][C]0[/C][C]0.770145618072259[/C][C]-0.770145618072259[/C][/ROW]
[ROW][C]190[/C][C]0[/C][C]0.339066786749296[/C][C]-0.339066786749296[/C][/ROW]
[ROW][C]191[/C][C]0[/C][C]0.602794517663595[/C][C]-0.602794517663595[/C][/ROW]
[ROW][C]192[/C][C]0[/C][C]0.579679083236099[/C][C]-0.579679083236099[/C][/ROW]
[ROW][C]193[/C][C]0[/C][C]0.55240064413817[/C][C]-0.55240064413817[/C][/ROW]
[ROW][C]194[/C][C]0[/C][C]0.647647011347257[/C][C]-0.647647011347257[/C][/ROW]
[ROW][C]195[/C][C]0[/C][C]0.718216398425918[/C][C]-0.718216398425918[/C][/ROW]
[ROW][C]196[/C][C]0[/C][C]0.245098680392576[/C][C]-0.245098680392576[/C][/ROW]
[ROW][C]197[/C][C]0[/C][C]0.411628867855573[/C][C]-0.411628867855573[/C][/ROW]
[ROW][C]198[/C][C]0[/C][C]0.431120590084331[/C][C]-0.431120590084331[/C][/ROW]
[ROW][C]199[/C][C]0[/C][C]0.472465051757526[/C][C]-0.472465051757526[/C][/ROW]
[ROW][C]200[/C][C]0[/C][C]0.450892171425858[/C][C]-0.450892171425858[/C][/ROW]
[ROW][C]201[/C][C]0[/C][C]0.6043253056283[/C][C]-0.6043253056283[/C][/ROW]
[ROW][C]202[/C][C]0[/C][C]0.70040875126072[/C][C]-0.70040875126072[/C][/ROW]
[ROW][C]203[/C][C]0[/C][C]0.711091014917346[/C][C]-0.711091014917346[/C][/ROW]
[ROW][C]204[/C][C]0[/C][C]0.713513931333934[/C][C]-0.713513931333934[/C][/ROW]
[ROW][C]205[/C][C]0[/C][C]0.37710327905729[/C][C]-0.37710327905729[/C][/ROW]
[ROW][C]206[/C][C]0[/C][C]0.610573894779388[/C][C]-0.610573894779388[/C][/ROW]
[ROW][C]207[/C][C]0[/C][C]0.405263054777903[/C][C]-0.405263054777903[/C][/ROW]
[ROW][C]208[/C][C]0[/C][C]0.624776020141651[/C][C]-0.624776020141651[/C][/ROW]
[ROW][C]209[/C][C]0[/C][C]0.43173315001158[/C][C]-0.43173315001158[/C][/ROW]
[ROW][C]210[/C][C]0[/C][C]0.293177803235625[/C][C]-0.293177803235625[/C][/ROW]
[ROW][C]211[/C][C]0[/C][C]0.633609970996995[/C][C]-0.633609970996995[/C][/ROW]
[ROW][C]212[/C][C]0[/C][C]0.479412724098452[/C][C]-0.479412724098452[/C][/ROW]
[ROW][C]213[/C][C]0[/C][C]0.836105469695193[/C][C]-0.836105469695193[/C][/ROW]
[ROW][C]214[/C][C]0[/C][C]0.655047595815946[/C][C]-0.655047595815946[/C][/ROW]
[ROW][C]215[/C][C]0[/C][C]0.210322298811958[/C][C]-0.210322298811958[/C][/ROW]
[ROW][C]216[/C][C]0[/C][C]0.748530313867686[/C][C]-0.748530313867686[/C][/ROW]
[ROW][C]217[/C][C]0[/C][C]0.425475602664566[/C][C]-0.425475602664566[/C][/ROW]
[ROW][C]218[/C][C]0[/C][C]0.61481002398672[/C][C]-0.61481002398672[/C][/ROW]
[ROW][C]219[/C][C]0[/C][C]0.54162099068552[/C][C]-0.54162099068552[/C][/ROW]
[ROW][C]220[/C][C]0[/C][C]0.403316320804444[/C][C]-0.403316320804444[/C][/ROW]
[ROW][C]221[/C][C]0[/C][C]0.312363830322977[/C][C]-0.312363830322977[/C][/ROW]
[ROW][C]222[/C][C]0[/C][C]0.650223214862701[/C][C]-0.650223214862701[/C][/ROW]
[ROW][C]223[/C][C]0[/C][C]0.388582015699777[/C][C]-0.388582015699777[/C][/ROW]
[ROW][C]224[/C][C]0[/C][C]0.145751571267342[/C][C]-0.145751571267342[/C][/ROW]
[ROW][C]225[/C][C]0[/C][C]0.288984129683221[/C][C]-0.288984129683221[/C][/ROW]
[ROW][C]226[/C][C]0[/C][C]0.451304462225137[/C][C]-0.451304462225137[/C][/ROW]
[ROW][C]227[/C][C]0[/C][C]0.158588806028389[/C][C]-0.158588806028389[/C][/ROW]
[ROW][C]228[/C][C]0[/C][C]0.472491178374297[/C][C]-0.472491178374297[/C][/ROW]
[ROW][C]229[/C][C]0[/C][C]0.904732896840505[/C][C]-0.904732896840505[/C][/ROW]
[ROW][C]230[/C][C]0[/C][C]0.637643996749912[/C][C]-0.637643996749912[/C][/ROW]
[ROW][C]231[/C][C]0[/C][C]0.306729602950388[/C][C]-0.306729602950388[/C][/ROW]
[ROW][C]232[/C][C]0[/C][C]-0.018612737374578[/C][C]0.018612737374578[/C][/ROW]
[ROW][C]233[/C][C]0[/C][C]0.514078274235144[/C][C]-0.514078274235144[/C][/ROW]
[ROW][C]234[/C][C]0[/C][C]0.535560872749256[/C][C]-0.535560872749256[/C][/ROW]
[ROW][C]235[/C][C]0[/C][C]0.194840194158337[/C][C]-0.194840194158337[/C][/ROW]
[ROW][C]236[/C][C]0[/C][C]0.222296196754434[/C][C]-0.222296196754434[/C][/ROW]
[ROW][C]237[/C][C]0[/C][C]0.249603602186355[/C][C]-0.249603602186355[/C][/ROW]
[ROW][C]238[/C][C]0[/C][C]0.018399791955783[/C][C]-0.018399791955783[/C][/ROW]
[ROW][C]239[/C][C]0[/C][C]0.287625647455674[/C][C]-0.287625647455674[/C][/ROW]
[ROW][C]240[/C][C]0[/C][C]0.205327462339014[/C][C]-0.205327462339014[/C][/ROW]
[ROW][C]241[/C][C]0[/C][C]0.412835813205281[/C][C]-0.412835813205281[/C][/ROW]
[ROW][C]242[/C][C]0[/C][C]0.448040798732323[/C][C]-0.448040798732323[/C][/ROW]
[ROW][C]243[/C][C]0[/C][C]0.172344352932323[/C][C]-0.172344352932323[/C][/ROW]
[ROW][C]244[/C][C]0[/C][C]0.296311557832986[/C][C]-0.296311557832986[/C][/ROW]
[ROW][C]245[/C][C]0[/C][C]0.306749352975515[/C][C]-0.306749352975515[/C][/ROW]
[ROW][C]246[/C][C]0[/C][C]0.221481708073448[/C][C]-0.221481708073448[/C][/ROW]
[ROW][C]247[/C][C]0[/C][C]0.396663683554191[/C][C]-0.396663683554191[/C][/ROW]
[ROW][C]248[/C][C]0[/C][C]0.599703144016926[/C][C]-0.599703144016926[/C][/ROW]
[ROW][C]249[/C][C]0[/C][C]0.388697537078381[/C][C]-0.388697537078381[/C][/ROW]
[ROW][C]250[/C][C]0[/C][C]0.458409979821127[/C][C]-0.458409979821127[/C][/ROW]
[ROW][C]251[/C][C]0[/C][C]0.45991011004405[/C][C]-0.45991011004405[/C][/ROW]
[ROW][C]252[/C][C]0[/C][C]0.330930168862774[/C][C]-0.330930168862774[/C][/ROW]
[ROW][C]253[/C][C]0[/C][C]0.661511761851375[/C][C]-0.661511761851375[/C][/ROW]
[ROW][C]254[/C][C]0[/C][C]-0.0999726697315325[/C][C]0.0999726697315325[/C][/ROW]
[ROW][C]255[/C][C]0[/C][C]0.593250601193965[/C][C]-0.593250601193965[/C][/ROW]
[ROW][C]256[/C][C]0[/C][C]0.480857820183835[/C][C]-0.480857820183835[/C][/ROW]
[ROW][C]257[/C][C]0[/C][C]0.114532069834777[/C][C]-0.114532069834777[/C][/ROW]
[ROW][C]258[/C][C]0[/C][C]0.418871507072752[/C][C]-0.418871507072752[/C][/ROW]
[ROW][C]259[/C][C]0[/C][C]0.422586332472314[/C][C]-0.422586332472314[/C][/ROW]
[ROW][C]260[/C][C]0[/C][C]0.398916128560068[/C][C]-0.398916128560068[/C][/ROW]
[ROW][C]261[/C][C]0[/C][C]0.321091201411459[/C][C]-0.321091201411459[/C][/ROW]
[ROW][C]262[/C][C]0[/C][C]0.32003234421282[/C][C]-0.32003234421282[/C][/ROW]
[ROW][C]263[/C][C]0[/C][C]0.644775772741141[/C][C]-0.644775772741141[/C][/ROW]
[ROW][C]264[/C][C]0[/C][C]0.0766759219289464[/C][C]-0.0766759219289464[/C][/ROW]
[ROW][C]265[/C][C]0[/C][C]0.31479312333121[/C][C]-0.31479312333121[/C][/ROW]
[ROW][C]266[/C][C]0[/C][C]0.432192379917764[/C][C]-0.432192379917764[/C][/ROW]
[ROW][C]267[/C][C]0[/C][C]0.624482903482855[/C][C]-0.624482903482855[/C][/ROW]
[ROW][C]268[/C][C]0[/C][C]0.257917899458499[/C][C]-0.257917899458499[/C][/ROW]
[ROW][C]269[/C][C]0[/C][C]0.704895641468363[/C][C]-0.704895641468363[/C][/ROW]
[ROW][C]270[/C][C]0[/C][C]0.618904473416653[/C][C]-0.618904473416653[/C][/ROW]
[ROW][C]271[/C][C]0[/C][C]0.133289477084691[/C][C]-0.133289477084691[/C][/ROW]
[ROW][C]272[/C][C]0[/C][C]0.256821949113209[/C][C]-0.256821949113209[/C][/ROW]
[ROW][C]273[/C][C]0[/C][C]0.558007865837684[/C][C]-0.558007865837684[/C][/ROW]
[ROW][C]274[/C][C]0[/C][C]-0.0279700003716465[/C][C]0.0279700003716465[/C][/ROW]
[ROW][C]275[/C][C]0[/C][C]0.516419051537847[/C][C]-0.516419051537847[/C][/ROW]
[ROW][C]276[/C][C]0[/C][C]-0.102380426754401[/C][C]0.102380426754401[/C][/ROW]
[ROW][C]277[/C][C]0[/C][C]0.47711162154668[/C][C]-0.47711162154668[/C][/ROW]
[ROW][C]278[/C][C]0[/C][C]0.579212729460436[/C][C]-0.579212729460436[/C][/ROW]
[ROW][C]279[/C][C]0[/C][C]0.683531114155112[/C][C]-0.683531114155112[/C][/ROW]
[ROW][C]280[/C][C]0[/C][C]0.284111207071538[/C][C]-0.284111207071538[/C][/ROW]
[ROW][C]281[/C][C]0[/C][C]0.714774192382191[/C][C]-0.714774192382191[/C][/ROW]
[ROW][C]282[/C][C]0[/C][C]0.636230448602801[/C][C]-0.636230448602801[/C][/ROW]
[ROW][C]283[/C][C]0[/C][C]0.290122476870217[/C][C]-0.290122476870217[/C][/ROW]
[ROW][C]284[/C][C]0[/C][C]-0.0677123267954521[/C][C]0.0677123267954521[/C][/ROW]
[ROW][C]285[/C][C]0[/C][C]0.705636233042407[/C][C]-0.705636233042407[/C][/ROW]
[ROW][C]286[/C][C]0[/C][C]0.416912278722114[/C][C]-0.416912278722114[/C][/ROW]
[ROW][C]287[/C][C]0[/C][C]0.623791044158941[/C][C]-0.623791044158941[/C][/ROW]
[ROW][C]288[/C][C]0[/C][C]0.615545154457818[/C][C]-0.615545154457818[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198371&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198371&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
110.6944885787718530.305511421228147
210.9037784786031340.0962215213968659
310.7761993117438430.223800688256157
410.3174135850460040.682586414953996
510.7568184686320470.243181531367953
610.7235106852270910.276489314772909
710.8995667575735830.100433242426418
810.7512843126562080.248715687343792
910.7154182414344890.284581758565511
1010.6734009549666950.326599045033305
1110.7289889280090880.271011071990912
1210.9342456652527440.0657543347472557
1310.5306320528347420.469367947165258
1410.8261088475805050.173891152419495
1510.9863461718020510.0136538281979485
1610.5744930780565950.425506921943405
1710.5611543054039150.438845694596085
1811.02730630361918-0.0273063036191842
1910.7277530751386120.272246924861388
2010.7840409945361350.215959005463865
2110.7266569930148550.273343006985145
2210.5935257862630680.406474213736932
2310.9221742616267890.0778257383732112
2410.6589354424484750.341064557551525
2510.8337529532925670.166247046707433
2610.6954980470377740.304501952962226
2710.6673760370374120.332623962962588
2810.7394392777437940.260560722256206
2910.7579632083016990.242036791698301
3010.3933196827987430.606680317201257
3110.7372598984615920.262740101538408
3210.2583950291723510.741604970827649
3310.7442139950671990.255786004932801
3410.7652482713917830.234751728608217
3510.5623350923548280.437664907645172
3610.3179331704147850.682066829585215
3710.09224913978339130.907750860216609
3810.6175640227752420.382435977224758
3910.7302697704657380.269730229534262
4010.5499704879646450.450029512035355
4110.644946228260840.35505377173916
4210.7314749814854430.268525018514557
4310.9839756238132880.0160243761867116
4410.4403515557646070.559648444235393
4510.685685353872710.31431464612729
4610.4716758026375880.528324197362412
4710.7626278096769890.237372190323011
4810.6912996994417050.308700300558295
4910.8294085583545780.170591441645422
5010.568144433399770.43185556660023
5110.8365519575582750.163448042441725
5210.4824860820499960.517513917950004
5310.3559164311296620.644083568870338
5410.6850312443780340.314968755621966
5510.07970685600758620.920293143992414
5610.5524024943556280.447597505644372
5710.8587482896428370.141251710357163
5810.7133190517454420.286680948254558
5910.5252331682626330.474766831737367
6010.6126378685704410.387362131429559
6110.0853565015800050.914643498419995
6210.6398405444529590.360159455547041
6310.6806598596579840.319340140342016
6410.5956627416723660.404337258327634
6510.7707202375785790.229279762421421
6610.5617604569574960.438239543042504
6710.7760460405360.223953959464
6810.5671899833803750.432810016619625
6910.6701372914738820.329862708526118
7010.6765031045515510.323496895448448
7110.3375892303777080.662410769622292
7210.6651244234148010.334875576585199
7310.8949273116539090.105072688346091
7410.8371572777285880.162842722271412
7510.602492342812430.39750765718757
7610.6677865935066890.332213406493311
7710.8992365224759280.100763477524072
7810.6695311081382770.330468891861723
7910.4951636372295310.504836362770469
8010.6352914644562730.364708535543727
8110.6555490178201220.344450982179878
8210.7761813119397310.223818688060269
8310.7013559456321670.298644054367833
8410.6803666588937570.319633341106243
8510.6657054354037780.334294564596222
8610.5469837438709370.453016256129063
8710.7209523815193160.279047618480684
8810.642945375638540.35705462436146
8910.4324124990673030.567587500932697
9010.5715442155705930.428455784429407
9110.843211103178640.15678889682136
9210.7725333344818670.227466665518133
9310.6787312572671040.321268742732896
9410.5344892146942910.465510785305709
9510.7989413717049680.201058628295032
9610.7205663491152760.279433650884724
9710.6585800518952050.341419948104795
9810.7733028335766790.226697166423321
9910.5131129482811170.486887051718883
10010.940073021992810.0599269780071896
10110.562905212518160.43709478748184
10211.05722777828324-0.0572277782832425
10310.4417650880207060.558234911979294
10410.7234997775104350.276500222489565
10510.4088551349329370.591144865067063
10610.8836633046214840.116336695378516
10710.7402773591103060.259722640889694
10810.4797745071343780.520225492865622
10910.3865939798248150.613406020175185
11010.724252092293390.27574790770661
11110.6496847267430730.350315273256928
11210.6753051332887820.324694866711218
11310.7040567446095960.295943255390404
11410.8415395542742830.158460445725717
11510.6709517801548680.329048219845132
11610.5369274976804740.463072502319526
11710.5807687728772010.419231227122799
11810.7737935955301230.226206404469877
11910.4070689119242560.592931088075744
12010.7344617255791510.265538274420849
12110.696876295181460.30312370481854
12210.8551183278800970.144881672119903
12310.7848177333878820.215182266612118
12410.7508738561833750.249126143816625
12510.7022499243015090.297750075698491
12610.9527209382647550.0472790617352452
12710.7758881111755040.224111888824496
12810.6037976252288840.396202374771116
12910.5171713663208020.482828633679198
13010.1383870340799140.861612965920086
13110.7148806562615970.285119343738403
13210.4193910765505210.580608923449479
13310.623937091500860.37606290849914
13410.7500169277384720.249983072261528
13510.2720018630246530.727998136975347
13610.565543705819090.43445629418091
13710.3371615895930170.662838410406983
13810.5159112370510140.484088762948986
13910.2916226229841510.708377377015849
14010.6301523149714130.369847685028587
14110.5342022905252650.465797709474735
14210.8109757092154720.189024290784528
14310.6165473988578160.383452601142184
14410.5358911555199460.464108844480054
14510.8911125307450540.108887469254946
14610.4336726601191160.566327339880884
14710.5408794518407530.459120548159247
14810.2672155383797940.732784461620206
14910.4777376549038550.522262345096145
15010.7727463456529390.227253654347061
15110.613782508243650.38621749175635
15210.4921120383302390.507887961669761
15310.4056374639694760.594362536030524
15410.3510633744305610.648936625569439
15510.423054420577980.57694557942202
15610.7758881111755040.224111888824496
15710.6686191137738110.331380886226189
15810.3711676406955560.628832359304444
15900.250313477205393-0.250313477205393
16000.343697989968854-0.343697989968854
16100.843792015171172-0.843792015171172
16200.488187141473269-0.488187141473269
16300.0817021316394842-0.0817021316394842
16400.48687548246517-0.48687548246517
16500.396631132672739-0.396631132672739
16600.437463132846634-0.437463132846634
16700.372445785660468-0.372445785660468
16800.209465370367055-0.209465370367055
16900.823213184905595-0.823213184905595
17000.32230921328749-0.32230921328749
17100.247051663930037-0.247051663930037
17200.684380934621547-0.684380934621547
17300.507578792305278-0.507578792305278
17400.322096318003874-0.322096318003874
17500.285910771731677-0.285910771731677
17600.642516919361595-0.642516919361595
17700.43057051053426-0.43057051053426
17800.751927514434228-0.751927514434228
17900.252940363184867-0.252940363184867
18000.830937480210813-0.830937480210813
18100.641003315708747-0.641003315708747
18200.384278167386037-0.384278167386037
18300.67209651982452-0.67209651982452
18400.661841881061573-0.661841881061573
18500.533387917731734-0.533387917731734
18600.207224532682633-0.207224532682633
18700.113480145913926-0.113480145913926
18800.526378755206565-0.526378755206565
18900.770145618072259-0.770145618072259
19000.339066786749296-0.339066786749296
19100.602794517663595-0.602794517663595
19200.579679083236099-0.579679083236099
19300.55240064413817-0.55240064413817
19400.647647011347257-0.647647011347257
19500.718216398425918-0.718216398425918
19600.245098680392576-0.245098680392576
19700.411628867855573-0.411628867855573
19800.431120590084331-0.431120590084331
19900.472465051757526-0.472465051757526
20000.450892171425858-0.450892171425858
20100.6043253056283-0.6043253056283
20200.70040875126072-0.70040875126072
20300.711091014917346-0.711091014917346
20400.713513931333934-0.713513931333934
20500.37710327905729-0.37710327905729
20600.610573894779388-0.610573894779388
20700.405263054777903-0.405263054777903
20800.624776020141651-0.624776020141651
20900.43173315001158-0.43173315001158
21000.293177803235625-0.293177803235625
21100.633609970996995-0.633609970996995
21200.479412724098452-0.479412724098452
21300.836105469695193-0.836105469695193
21400.655047595815946-0.655047595815946
21500.210322298811958-0.210322298811958
21600.748530313867686-0.748530313867686
21700.425475602664566-0.425475602664566
21800.61481002398672-0.61481002398672
21900.54162099068552-0.54162099068552
22000.403316320804444-0.403316320804444
22100.312363830322977-0.312363830322977
22200.650223214862701-0.650223214862701
22300.388582015699777-0.388582015699777
22400.145751571267342-0.145751571267342
22500.288984129683221-0.288984129683221
22600.451304462225137-0.451304462225137
22700.158588806028389-0.158588806028389
22800.472491178374297-0.472491178374297
22900.904732896840505-0.904732896840505
23000.637643996749912-0.637643996749912
23100.306729602950388-0.306729602950388
2320-0.0186127373745780.018612737374578
23300.514078274235144-0.514078274235144
23400.535560872749256-0.535560872749256
23500.194840194158337-0.194840194158337
23600.222296196754434-0.222296196754434
23700.249603602186355-0.249603602186355
23800.018399791955783-0.018399791955783
23900.287625647455674-0.287625647455674
24000.205327462339014-0.205327462339014
24100.412835813205281-0.412835813205281
24200.448040798732323-0.448040798732323
24300.172344352932323-0.172344352932323
24400.296311557832986-0.296311557832986
24500.306749352975515-0.306749352975515
24600.221481708073448-0.221481708073448
24700.396663683554191-0.396663683554191
24800.599703144016926-0.599703144016926
24900.388697537078381-0.388697537078381
25000.458409979821127-0.458409979821127
25100.45991011004405-0.45991011004405
25200.330930168862774-0.330930168862774
25300.661511761851375-0.661511761851375
2540-0.09997266973153250.0999726697315325
25500.593250601193965-0.593250601193965
25600.480857820183835-0.480857820183835
25700.114532069834777-0.114532069834777
25800.418871507072752-0.418871507072752
25900.422586332472314-0.422586332472314
26000.398916128560068-0.398916128560068
26100.321091201411459-0.321091201411459
26200.32003234421282-0.32003234421282
26300.644775772741141-0.644775772741141
26400.0766759219289464-0.0766759219289464
26500.31479312333121-0.31479312333121
26600.432192379917764-0.432192379917764
26700.624482903482855-0.624482903482855
26800.257917899458499-0.257917899458499
26900.704895641468363-0.704895641468363
27000.618904473416653-0.618904473416653
27100.133289477084691-0.133289477084691
27200.256821949113209-0.256821949113209
27300.558007865837684-0.558007865837684
2740-0.02797000037164650.0279700003716465
27500.516419051537847-0.516419051537847
2760-0.1023804267544010.102380426754401
27700.47711162154668-0.47711162154668
27800.579212729460436-0.579212729460436
27900.683531114155112-0.683531114155112
28000.284111207071538-0.284111207071538
28100.714774192382191-0.714774192382191
28200.636230448602801-0.636230448602801
28300.290122476870217-0.290122476870217
2840-0.06771232679545210.0677123267954521
28500.705636233042407-0.705636233042407
28600.416912278722114-0.416912278722114
28700.623791044158941-0.623791044158941
28800.615545154457818-0.615545154457818







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
101.11110105889153e-482.22220211778305e-481
111.06991453149447e-672.13982906298894e-671
121.16078501347172e-782.32157002694344e-781
133.75955680746915e-1067.5191136149383e-1061
142.08379073501777e-1084.16758147003553e-1081
157.22329676823318e-1241.44465935364664e-1231
16001
171.96001330388058e-1663.92002660776115e-1661
187.9224583230376e-1721.58449166460752e-1711
193.39325344696583e-1866.78650689393167e-1861
203.11121968977211e-2116.22243937954423e-2111
213.81831657140507e-2457.63663314281015e-2451
221.26810792211861e-2352.53621584423722e-2351
232.81099847535037e-2475.62199695070075e-2471
248.78304411960806e-2661.75660882392161e-2651
257.35956275524374e-2851.47191255104875e-2841
26001
278.42768016228596e-3151.68553603245719e-3141
28001
29001
30001
31001
32001
33001
34001
35001
36001
37001
38001
39001
40001
41001
42001
43001
44001
45001
46001
47001
48001
49001
50001
51001
52001
53001
54001
55001
56001
57001
58001
59001
60001
61001
62001
63001
64001
65001
66001
67001
68001
69001
70001
71001
72001
73001
74001
75001
76001
77001
78001
79001
80001
81001
82001
83001
84001
85001
86001
87001
88001
89001
90001
91001
92001
93001
94001
95001
96001
97001
98001
99001
100001
101001
102001
103001
104001
105001
106001
107001
108001
109001
110001
111001
112001
113001
114001
115001
116001
117001
118001
119001
120001
121001
122001
123001
124001
125001
126001
127001
128001
129001
130001
131001
132001
133001
134001
135001
136001
137001
138001
139001
140001
141001
142001
143001
144001
145001
146001
147001
148001
149001
150001
151001
152001
153001
154001
155001
156001
157001
158100
159100
160100
161100
162100
163100
164100
165100
166100
167100
168100
169100
170100
171100
172100
173100
174100
175100
176100
177100
178100
179100
180100
181100
182100
183100
184100
185100
186100
187100
188100
189100
190100
191100
192100
193100
194100
195100
196100
197100
198100
199100
200100
201100
202100
203100
204100
205100
206100
207100
208100
209100
210100
211100
212100
213100
214100
215100
216100
217100
218100
219100
220100
221100
222100
223100
224100
225100
226100
227100
228100
229100
230100
231100
232100
233100
234100
235100
236100
237100
238100
239100
240100
241100
242100
243100
244100
245100
246100
247100
248100
249100
250100
251100
252100
253100
254100
255100
256100
257100
258100
259100
260100
261100
262100
263100
264100
265100
266100
267100
268100
269100
270100
271100
272100
273100
274100
275100
276100
277100
278100

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 1.11110105889153e-48 & 2.22220211778305e-48 & 1 \tabularnewline
11 & 1.06991453149447e-67 & 2.13982906298894e-67 & 1 \tabularnewline
12 & 1.16078501347172e-78 & 2.32157002694344e-78 & 1 \tabularnewline
13 & 3.75955680746915e-106 & 7.5191136149383e-106 & 1 \tabularnewline
14 & 2.08379073501777e-108 & 4.16758147003553e-108 & 1 \tabularnewline
15 & 7.22329676823318e-124 & 1.44465935364664e-123 & 1 \tabularnewline
16 & 0 & 0 & 1 \tabularnewline
17 & 1.96001330388058e-166 & 3.92002660776115e-166 & 1 \tabularnewline
18 & 7.9224583230376e-172 & 1.58449166460752e-171 & 1 \tabularnewline
19 & 3.39325344696583e-186 & 6.78650689393167e-186 & 1 \tabularnewline
20 & 3.11121968977211e-211 & 6.22243937954423e-211 & 1 \tabularnewline
21 & 3.81831657140507e-245 & 7.63663314281015e-245 & 1 \tabularnewline
22 & 1.26810792211861e-235 & 2.53621584423722e-235 & 1 \tabularnewline
23 & 2.81099847535037e-247 & 5.62199695070075e-247 & 1 \tabularnewline
24 & 8.78304411960806e-266 & 1.75660882392161e-265 & 1 \tabularnewline
25 & 7.35956275524374e-285 & 1.47191255104875e-284 & 1 \tabularnewline
26 & 0 & 0 & 1 \tabularnewline
27 & 8.42768016228596e-315 & 1.68553603245719e-314 & 1 \tabularnewline
28 & 0 & 0 & 1 \tabularnewline
29 & 0 & 0 & 1 \tabularnewline
30 & 0 & 0 & 1 \tabularnewline
31 & 0 & 0 & 1 \tabularnewline
32 & 0 & 0 & 1 \tabularnewline
33 & 0 & 0 & 1 \tabularnewline
34 & 0 & 0 & 1 \tabularnewline
35 & 0 & 0 & 1 \tabularnewline
36 & 0 & 0 & 1 \tabularnewline
37 & 0 & 0 & 1 \tabularnewline
38 & 0 & 0 & 1 \tabularnewline
39 & 0 & 0 & 1 \tabularnewline
40 & 0 & 0 & 1 \tabularnewline
41 & 0 & 0 & 1 \tabularnewline
42 & 0 & 0 & 1 \tabularnewline
43 & 0 & 0 & 1 \tabularnewline
44 & 0 & 0 & 1 \tabularnewline
45 & 0 & 0 & 1 \tabularnewline
46 & 0 & 0 & 1 \tabularnewline
47 & 0 & 0 & 1 \tabularnewline
48 & 0 & 0 & 1 \tabularnewline
49 & 0 & 0 & 1 \tabularnewline
50 & 0 & 0 & 1 \tabularnewline
51 & 0 & 0 & 1 \tabularnewline
52 & 0 & 0 & 1 \tabularnewline
53 & 0 & 0 & 1 \tabularnewline
54 & 0 & 0 & 1 \tabularnewline
55 & 0 & 0 & 1 \tabularnewline
56 & 0 & 0 & 1 \tabularnewline
57 & 0 & 0 & 1 \tabularnewline
58 & 0 & 0 & 1 \tabularnewline
59 & 0 & 0 & 1 \tabularnewline
60 & 0 & 0 & 1 \tabularnewline
61 & 0 & 0 & 1 \tabularnewline
62 & 0 & 0 & 1 \tabularnewline
63 & 0 & 0 & 1 \tabularnewline
64 & 0 & 0 & 1 \tabularnewline
65 & 0 & 0 & 1 \tabularnewline
66 & 0 & 0 & 1 \tabularnewline
67 & 0 & 0 & 1 \tabularnewline
68 & 0 & 0 & 1 \tabularnewline
69 & 0 & 0 & 1 \tabularnewline
70 & 0 & 0 & 1 \tabularnewline
71 & 0 & 0 & 1 \tabularnewline
72 & 0 & 0 & 1 \tabularnewline
73 & 0 & 0 & 1 \tabularnewline
74 & 0 & 0 & 1 \tabularnewline
75 & 0 & 0 & 1 \tabularnewline
76 & 0 & 0 & 1 \tabularnewline
77 & 0 & 0 & 1 \tabularnewline
78 & 0 & 0 & 1 \tabularnewline
79 & 0 & 0 & 1 \tabularnewline
80 & 0 & 0 & 1 \tabularnewline
81 & 0 & 0 & 1 \tabularnewline
82 & 0 & 0 & 1 \tabularnewline
83 & 0 & 0 & 1 \tabularnewline
84 & 0 & 0 & 1 \tabularnewline
85 & 0 & 0 & 1 \tabularnewline
86 & 0 & 0 & 1 \tabularnewline
87 & 0 & 0 & 1 \tabularnewline
88 & 0 & 0 & 1 \tabularnewline
89 & 0 & 0 & 1 \tabularnewline
90 & 0 & 0 & 1 \tabularnewline
91 & 0 & 0 & 1 \tabularnewline
92 & 0 & 0 & 1 \tabularnewline
93 & 0 & 0 & 1 \tabularnewline
94 & 0 & 0 & 1 \tabularnewline
95 & 0 & 0 & 1 \tabularnewline
96 & 0 & 0 & 1 \tabularnewline
97 & 0 & 0 & 1 \tabularnewline
98 & 0 & 0 & 1 \tabularnewline
99 & 0 & 0 & 1 \tabularnewline
100 & 0 & 0 & 1 \tabularnewline
101 & 0 & 0 & 1 \tabularnewline
102 & 0 & 0 & 1 \tabularnewline
103 & 0 & 0 & 1 \tabularnewline
104 & 0 & 0 & 1 \tabularnewline
105 & 0 & 0 & 1 \tabularnewline
106 & 0 & 0 & 1 \tabularnewline
107 & 0 & 0 & 1 \tabularnewline
108 & 0 & 0 & 1 \tabularnewline
109 & 0 & 0 & 1 \tabularnewline
110 & 0 & 0 & 1 \tabularnewline
111 & 0 & 0 & 1 \tabularnewline
112 & 0 & 0 & 1 \tabularnewline
113 & 0 & 0 & 1 \tabularnewline
114 & 0 & 0 & 1 \tabularnewline
115 & 0 & 0 & 1 \tabularnewline
116 & 0 & 0 & 1 \tabularnewline
117 & 0 & 0 & 1 \tabularnewline
118 & 0 & 0 & 1 \tabularnewline
119 & 0 & 0 & 1 \tabularnewline
120 & 0 & 0 & 1 \tabularnewline
121 & 0 & 0 & 1 \tabularnewline
122 & 0 & 0 & 1 \tabularnewline
123 & 0 & 0 & 1 \tabularnewline
124 & 0 & 0 & 1 \tabularnewline
125 & 0 & 0 & 1 \tabularnewline
126 & 0 & 0 & 1 \tabularnewline
127 & 0 & 0 & 1 \tabularnewline
128 & 0 & 0 & 1 \tabularnewline
129 & 0 & 0 & 1 \tabularnewline
130 & 0 & 0 & 1 \tabularnewline
131 & 0 & 0 & 1 \tabularnewline
132 & 0 & 0 & 1 \tabularnewline
133 & 0 & 0 & 1 \tabularnewline
134 & 0 & 0 & 1 \tabularnewline
135 & 0 & 0 & 1 \tabularnewline
136 & 0 & 0 & 1 \tabularnewline
137 & 0 & 0 & 1 \tabularnewline
138 & 0 & 0 & 1 \tabularnewline
139 & 0 & 0 & 1 \tabularnewline
140 & 0 & 0 & 1 \tabularnewline
141 & 0 & 0 & 1 \tabularnewline
142 & 0 & 0 & 1 \tabularnewline
143 & 0 & 0 & 1 \tabularnewline
144 & 0 & 0 & 1 \tabularnewline
145 & 0 & 0 & 1 \tabularnewline
146 & 0 & 0 & 1 \tabularnewline
147 & 0 & 0 & 1 \tabularnewline
148 & 0 & 0 & 1 \tabularnewline
149 & 0 & 0 & 1 \tabularnewline
150 & 0 & 0 & 1 \tabularnewline
151 & 0 & 0 & 1 \tabularnewline
152 & 0 & 0 & 1 \tabularnewline
153 & 0 & 0 & 1 \tabularnewline
154 & 0 & 0 & 1 \tabularnewline
155 & 0 & 0 & 1 \tabularnewline
156 & 0 & 0 & 1 \tabularnewline
157 & 0 & 0 & 1 \tabularnewline
158 & 1 & 0 & 0 \tabularnewline
159 & 1 & 0 & 0 \tabularnewline
160 & 1 & 0 & 0 \tabularnewline
161 & 1 & 0 & 0 \tabularnewline
162 & 1 & 0 & 0 \tabularnewline
163 & 1 & 0 & 0 \tabularnewline
164 & 1 & 0 & 0 \tabularnewline
165 & 1 & 0 & 0 \tabularnewline
166 & 1 & 0 & 0 \tabularnewline
167 & 1 & 0 & 0 \tabularnewline
168 & 1 & 0 & 0 \tabularnewline
169 & 1 & 0 & 0 \tabularnewline
170 & 1 & 0 & 0 \tabularnewline
171 & 1 & 0 & 0 \tabularnewline
172 & 1 & 0 & 0 \tabularnewline
173 & 1 & 0 & 0 \tabularnewline
174 & 1 & 0 & 0 \tabularnewline
175 & 1 & 0 & 0 \tabularnewline
176 & 1 & 0 & 0 \tabularnewline
177 & 1 & 0 & 0 \tabularnewline
178 & 1 & 0 & 0 \tabularnewline
179 & 1 & 0 & 0 \tabularnewline
180 & 1 & 0 & 0 \tabularnewline
181 & 1 & 0 & 0 \tabularnewline
182 & 1 & 0 & 0 \tabularnewline
183 & 1 & 0 & 0 \tabularnewline
184 & 1 & 0 & 0 \tabularnewline
185 & 1 & 0 & 0 \tabularnewline
186 & 1 & 0 & 0 \tabularnewline
187 & 1 & 0 & 0 \tabularnewline
188 & 1 & 0 & 0 \tabularnewline
189 & 1 & 0 & 0 \tabularnewline
190 & 1 & 0 & 0 \tabularnewline
191 & 1 & 0 & 0 \tabularnewline
192 & 1 & 0 & 0 \tabularnewline
193 & 1 & 0 & 0 \tabularnewline
194 & 1 & 0 & 0 \tabularnewline
195 & 1 & 0 & 0 \tabularnewline
196 & 1 & 0 & 0 \tabularnewline
197 & 1 & 0 & 0 \tabularnewline
198 & 1 & 0 & 0 \tabularnewline
199 & 1 & 0 & 0 \tabularnewline
200 & 1 & 0 & 0 \tabularnewline
201 & 1 & 0 & 0 \tabularnewline
202 & 1 & 0 & 0 \tabularnewline
203 & 1 & 0 & 0 \tabularnewline
204 & 1 & 0 & 0 \tabularnewline
205 & 1 & 0 & 0 \tabularnewline
206 & 1 & 0 & 0 \tabularnewline
207 & 1 & 0 & 0 \tabularnewline
208 & 1 & 0 & 0 \tabularnewline
209 & 1 & 0 & 0 \tabularnewline
210 & 1 & 0 & 0 \tabularnewline
211 & 1 & 0 & 0 \tabularnewline
212 & 1 & 0 & 0 \tabularnewline
213 & 1 & 0 & 0 \tabularnewline
214 & 1 & 0 & 0 \tabularnewline
215 & 1 & 0 & 0 \tabularnewline
216 & 1 & 0 & 0 \tabularnewline
217 & 1 & 0 & 0 \tabularnewline
218 & 1 & 0 & 0 \tabularnewline
219 & 1 & 0 & 0 \tabularnewline
220 & 1 & 0 & 0 \tabularnewline
221 & 1 & 0 & 0 \tabularnewline
222 & 1 & 0 & 0 \tabularnewline
223 & 1 & 0 & 0 \tabularnewline
224 & 1 & 0 & 0 \tabularnewline
225 & 1 & 0 & 0 \tabularnewline
226 & 1 & 0 & 0 \tabularnewline
227 & 1 & 0 & 0 \tabularnewline
228 & 1 & 0 & 0 \tabularnewline
229 & 1 & 0 & 0 \tabularnewline
230 & 1 & 0 & 0 \tabularnewline
231 & 1 & 0 & 0 \tabularnewline
232 & 1 & 0 & 0 \tabularnewline
233 & 1 & 0 & 0 \tabularnewline
234 & 1 & 0 & 0 \tabularnewline
235 & 1 & 0 & 0 \tabularnewline
236 & 1 & 0 & 0 \tabularnewline
237 & 1 & 0 & 0 \tabularnewline
238 & 1 & 0 & 0 \tabularnewline
239 & 1 & 0 & 0 \tabularnewline
240 & 1 & 0 & 0 \tabularnewline
241 & 1 & 0 & 0 \tabularnewline
242 & 1 & 0 & 0 \tabularnewline
243 & 1 & 0 & 0 \tabularnewline
244 & 1 & 0 & 0 \tabularnewline
245 & 1 & 0 & 0 \tabularnewline
246 & 1 & 0 & 0 \tabularnewline
247 & 1 & 0 & 0 \tabularnewline
248 & 1 & 0 & 0 \tabularnewline
249 & 1 & 0 & 0 \tabularnewline
250 & 1 & 0 & 0 \tabularnewline
251 & 1 & 0 & 0 \tabularnewline
252 & 1 & 0 & 0 \tabularnewline
253 & 1 & 0 & 0 \tabularnewline
254 & 1 & 0 & 0 \tabularnewline
255 & 1 & 0 & 0 \tabularnewline
256 & 1 & 0 & 0 \tabularnewline
257 & 1 & 0 & 0 \tabularnewline
258 & 1 & 0 & 0 \tabularnewline
259 & 1 & 0 & 0 \tabularnewline
260 & 1 & 0 & 0 \tabularnewline
261 & 1 & 0 & 0 \tabularnewline
262 & 1 & 0 & 0 \tabularnewline
263 & 1 & 0 & 0 \tabularnewline
264 & 1 & 0 & 0 \tabularnewline
265 & 1 & 0 & 0 \tabularnewline
266 & 1 & 0 & 0 \tabularnewline
267 & 1 & 0 & 0 \tabularnewline
268 & 1 & 0 & 0 \tabularnewline
269 & 1 & 0 & 0 \tabularnewline
270 & 1 & 0 & 0 \tabularnewline
271 & 1 & 0 & 0 \tabularnewline
272 & 1 & 0 & 0 \tabularnewline
273 & 1 & 0 & 0 \tabularnewline
274 & 1 & 0 & 0 \tabularnewline
275 & 1 & 0 & 0 \tabularnewline
276 & 1 & 0 & 0 \tabularnewline
277 & 1 & 0 & 0 \tabularnewline
278 & 1 & 0 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198371&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]1.11110105889153e-48[/C][C]2.22220211778305e-48[/C][C]1[/C][/ROW]
[ROW][C]11[/C][C]1.06991453149447e-67[/C][C]2.13982906298894e-67[/C][C]1[/C][/ROW]
[ROW][C]12[/C][C]1.16078501347172e-78[/C][C]2.32157002694344e-78[/C][C]1[/C][/ROW]
[ROW][C]13[/C][C]3.75955680746915e-106[/C][C]7.5191136149383e-106[/C][C]1[/C][/ROW]
[ROW][C]14[/C][C]2.08379073501777e-108[/C][C]4.16758147003553e-108[/C][C]1[/C][/ROW]
[ROW][C]15[/C][C]7.22329676823318e-124[/C][C]1.44465935364664e-123[/C][C]1[/C][/ROW]
[ROW][C]16[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]17[/C][C]1.96001330388058e-166[/C][C]3.92002660776115e-166[/C][C]1[/C][/ROW]
[ROW][C]18[/C][C]7.9224583230376e-172[/C][C]1.58449166460752e-171[/C][C]1[/C][/ROW]
[ROW][C]19[/C][C]3.39325344696583e-186[/C][C]6.78650689393167e-186[/C][C]1[/C][/ROW]
[ROW][C]20[/C][C]3.11121968977211e-211[/C][C]6.22243937954423e-211[/C][C]1[/C][/ROW]
[ROW][C]21[/C][C]3.81831657140507e-245[/C][C]7.63663314281015e-245[/C][C]1[/C][/ROW]
[ROW][C]22[/C][C]1.26810792211861e-235[/C][C]2.53621584423722e-235[/C][C]1[/C][/ROW]
[ROW][C]23[/C][C]2.81099847535037e-247[/C][C]5.62199695070075e-247[/C][C]1[/C][/ROW]
[ROW][C]24[/C][C]8.78304411960806e-266[/C][C]1.75660882392161e-265[/C][C]1[/C][/ROW]
[ROW][C]25[/C][C]7.35956275524374e-285[/C][C]1.47191255104875e-284[/C][C]1[/C][/ROW]
[ROW][C]26[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]27[/C][C]8.42768016228596e-315[/C][C]1.68553603245719e-314[/C][C]1[/C][/ROW]
[ROW][C]28[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]29[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]30[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]31[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]32[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]33[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]34[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]35[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]36[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]37[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]38[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]39[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]42[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]44[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]45[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]46[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]47[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]48[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]49[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]50[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]51[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]54[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]55[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]56[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]58[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]60[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]61[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]63[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]64[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]65[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]66[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]67[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]68[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]69[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]70[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]71[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]72[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]73[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]74[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]75[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]76[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]77[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]78[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]79[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]80[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]81[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]82[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]83[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]84[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]85[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]86[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]87[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]88[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]89[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]90[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]91[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]92[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]93[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]94[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]95[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]96[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]97[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]98[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]99[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]100[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]101[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]102[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]103[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]104[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]105[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]106[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]107[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]108[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]109[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]110[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]111[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]112[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]113[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]114[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]115[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]116[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]117[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]118[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]119[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]120[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]121[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]122[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]123[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]124[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]125[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]126[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]127[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]128[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]129[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]130[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]131[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]132[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]133[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]134[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]135[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]136[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]137[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]138[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]139[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]140[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]141[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]142[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]143[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]144[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]145[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]146[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]147[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]148[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]149[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]150[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]151[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]152[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]153[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]154[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]155[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]156[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]157[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]159[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]160[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]161[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]162[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]166[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]167[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]168[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]169[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]170[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]171[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]172[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]173[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]174[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]175[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]176[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]177[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]179[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]181[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]182[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]184[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]185[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]186[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]187[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]188[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]189[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]190[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]191[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]192[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]193[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]194[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]195[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]196[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]197[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]198[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]199[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]200[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]201[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]202[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]203[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]204[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]205[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]206[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]207[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]208[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]209[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]210[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]211[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]212[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]213[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]214[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]215[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]216[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]217[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]218[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]219[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]220[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]221[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]222[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]223[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]224[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]225[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]226[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]227[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]228[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]229[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]230[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]231[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]232[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]233[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]234[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]235[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]236[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]237[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]238[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]239[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]240[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]241[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]242[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]243[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]244[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]245[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]246[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]247[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]248[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]249[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]250[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]251[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]252[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]253[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]254[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]255[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]256[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]257[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]258[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]259[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]260[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]261[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]262[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]263[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]264[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]265[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]266[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]267[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]268[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]269[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]270[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]271[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]272[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]273[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]274[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]275[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]276[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]277[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]278[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198371&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198371&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
101.11110105889153e-482.22220211778305e-481
111.06991453149447e-672.13982906298894e-671
121.16078501347172e-782.32157002694344e-781
133.75955680746915e-1067.5191136149383e-1061
142.08379073501777e-1084.16758147003553e-1081
157.22329676823318e-1241.44465935364664e-1231
16001
171.96001330388058e-1663.92002660776115e-1661
187.9224583230376e-1721.58449166460752e-1711
193.39325344696583e-1866.78650689393167e-1861
203.11121968977211e-2116.22243937954423e-2111
213.81831657140507e-2457.63663314281015e-2451
221.26810792211861e-2352.53621584423722e-2351
232.81099847535037e-2475.62199695070075e-2471
248.78304411960806e-2661.75660882392161e-2651
257.35956275524374e-2851.47191255104875e-2841
26001
278.42768016228596e-3151.68553603245719e-3141
28001
29001
30001
31001
32001
33001
34001
35001
36001
37001
38001
39001
40001
41001
42001
43001
44001
45001
46001
47001
48001
49001
50001
51001
52001
53001
54001
55001
56001
57001
58001
59001
60001
61001
62001
63001
64001
65001
66001
67001
68001
69001
70001
71001
72001
73001
74001
75001
76001
77001
78001
79001
80001
81001
82001
83001
84001
85001
86001
87001
88001
89001
90001
91001
92001
93001
94001
95001
96001
97001
98001
99001
100001
101001
102001
103001
104001
105001
106001
107001
108001
109001
110001
111001
112001
113001
114001
115001
116001
117001
118001
119001
120001
121001
122001
123001
124001
125001
126001
127001
128001
129001
130001
131001
132001
133001
134001
135001
136001
137001
138001
139001
140001
141001
142001
143001
144001
145001
146001
147001
148001
149001
150001
151001
152001
153001
154001
155001
156001
157001
158100
159100
160100
161100
162100
163100
164100
165100
166100
167100
168100
169100
170100
171100
172100
173100
174100
175100
176100
177100
178100
179100
180100
181100
182100
183100
184100
185100
186100
187100
188100
189100
190100
191100
192100
193100
194100
195100
196100
197100
198100
199100
200100
201100
202100
203100
204100
205100
206100
207100
208100
209100
210100
211100
212100
213100
214100
215100
216100
217100
218100
219100
220100
221100
222100
223100
224100
225100
226100
227100
228100
229100
230100
231100
232100
233100
234100
235100
236100
237100
238100
239100
240100
241100
242100
243100
244100
245100
246100
247100
248100
249100
250100
251100
252100
253100
254100
255100
256100
257100
258100
259100
260100
261100
262100
263100
264100
265100
266100
267100
268100
269100
270100
271100
272100
273100
274100
275100
276100
277100
278100







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level2691NOK
5% type I error level2691NOK
10% type I error level2691NOK

\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 & 269 & 1 & NOK \tabularnewline
5% type I error level & 269 & 1 & NOK \tabularnewline
10% type I error level & 269 & 1 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198371&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]269[/C][C]1[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]269[/C][C]1[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]269[/C][C]1[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198371&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198371&T=6

As an alternative you can also use a QR Code:  

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 level2691NOK
5% type I error level2691NOK
10% type I error level2691NOK



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