## Free Statistics

of Irreproducible Research!

Author's title
Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSat, 03 Nov 2012 09:28:58 -0400
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/Nov/03/t1351950136kxor1dqh9nxo5md.htm/, Retrieved Sun, 03 Jul 2022 15:06:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185721, Retrieved Sun, 03 Jul 2022 15:06:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact99
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-11-17 09:20:01] [b98453cac15ba1066b407e146608df68]
-         [Multiple Regression] [] [2012-11-03 13:28:58] [54fc54845b7758f1604e617c5518fca2] [Current]
-   P       [Multiple Regression] [Paper_4.3_Model4] [2012-12-21 19:22:31] [be6dd99035eed41c2358246baf91f928]
-   P       [Multiple Regression] [Paper_4.3_Model4] [2012-12-21 19:22:31] [be6dd99035eed41c2358246baf91f928]
-   P       [Multiple Regression] [Paper_4.3_Model42] [2012-12-21 19:22:31] [be6dd99035eed41c2358246baf91f928]
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Dataseries X:
41	38	13	12	14	12	53
39	32	16	11	18	11	83
30	35	19	15	11	14	66
31	33	15	6	12	12	67
34	37	14	13	16	21	76
35	29	13	10	18	12	78
39	31	19	12	14	22	53
34	36	15	14	14	11	80
36	35	14	12	15	10	74
37	38	15	9	15	13	76
38	31	16	10	17	10	79
36	34	16	12	19	8	54
38	35	16	12	10	15	67
39	38	16	11	16	14	54
33	37	17	15	18	10	87
32	33	15	12	14	14	58
36	32	15	10	14	14	75
38	38	20	12	17	11	88
39	38	18	11	14	10	64
32	32	16	12	16	13	57
32	33	16	11	18	9.5	66
31	31	16	12	11	14	68
39	38	19	13	14	12	54
37	39	16	11	12	14	56
39	32	17	12	17	11	86
41	32	17	13	9	9	80
36	35	16	10	16	11	76
33	37	15	14	14	15	69
33	33	16	12	15	14	78
34	33	14	10	11	13	67
31	31	15	12	16	9	80
27	32	12	8	13	15	54
37	31	14	10	17	10	71
34	37	16	12	15	11	84
34	30	14	12	14	13	74
32	33	10	7	16	8	71
29	31	10	9	9	20	63
36	33	14	12	15	12	71
29	31	16	10	17	10	76
35	33	16	10	13	10	69
37	32	16	10	15	9	74
34	33	14	12	16	14	75
38	32	20	15	16	8	54
35	33	14	10	12	14	52
38	28	14	10	15	11	69
37	35	11	12	11	13	68
38	39	14	13	15	9	65
33	34	15	11	15	11	75
36	38	16	11	17	15	74
38	32	14	12	13	11	75
32	38	16	14	16	10	72
32	30	14	10	14	14	67
32	33	12	12	11	18	63
34	38	16	13	12	14	62
32	32	9	5	12	11	63
37	35	14	6	15	14.5	76
39	34	16	12	16	13	74
29	34	16	12	15	9	67
37	36	15	11	12	10	73
35	34	16	10	12	15	70
30	28	12	7	8	20	53
38	34	16	12	13	12	77
34	35	16	14	11	12	80
31	35	14	11	14	14	52
34	31	16	12	15	13	54
35	37	17	13	10	11	80
36	35	18	14	11	17	66
30	27	18	11	12	12	73
39	40	12	12	15	13	63
35	37	16	12	15	14	69
38	36	10	8	14	13	67
31	38	14	11	16	15	54
34	39	18	14	15	13	81
38	41	18	14	15	10	69
34	27	16	12	13	11	84
39	30	17	9	12	19	80
37	37	16	13	17	13	70
34	31	16	11	13	17	69
28	31	13	12	15	13	77
37	27	16	12	13	9	54
33	36	16	12	15	11	79
35	37	16	12	15	9	71
37	33	15	12	16	12	73
32	34	15	11	15	12	72
33	31	16	10	14	13	77
38	39	14	9	15	13	75
33	34	16	12	14	12	69
29	32	16	12	13	15	54
33	33	15	12	7	22	70
31	36	12	9	17	13	73
36	32	17	15	13	15	54
35	41	16	12	15	13	77
32	28	15	12	14	15	82
29	30	13	12	13	12.5	80
39	36	16	10	16	11	80
37	35	16	13	12	16	69
35	31	16	9	14	11	78
37	34	16	12	17	11	81
32	36	14	10	15	10	76
38	36	16	14	17	10	76
37	35	16	11	12	16	73
36	37	20	15	16	12	85
32	28	15	11	11	11	66
33	39	16	11	15	16	79
40	32	13	12	9	19	68
38	35	17	12	16	11	76
41	39	16	12	15	16	71
36	35	16	11	10	15	54
43	42	12	7	10	24	46
30	34	16	12	15	14	85
31	33	16	14	11	15	74
32	41	17	11	13	11	88
32	33	13	11	14	15	38
37	34	12	10	18	12	76
37	32	18	13	16	10	86
33	40	14	13	14	14	54
34	40	14	8	14	13	67
33	35	13	11	14	9	69
38	36	16	12	14	15	90
33	37	13	11	12	15	54
31	27	16	13	14	14	76
38	39	13	12	15	11	89
37	38	16	14	15	8	76
36	31	15	13	15	11	73
31	33	16	15	13	11	79
39	32	15	10	17	8	90
44	39	17	11	17	10	74
33	36	15	9	19	11	81
35	33	12	11	15	13	72
32	33	16	10	13	11	71
28	32	10	11	9	20	66
40	37	16	8	15	10	77
27	30	12	11	15	15	65
37	38	14	12	15	12	74
32	29	15	12	16	14	85
28	22	13	9	11	23	54
34	35	15	11	14	14	63
30	35	11	10	11	16	54
35	34	12	8	15	11	64
31	35	11	9	13	12	69
32	34	16	8	15	10	54
30	37	15	9	16	14	84
30	35	17	15	14	12	86
31	23	16	11	15	12	77
40	31	10	8	16	11	89
32	27	18	13	16	12	76
36	36	13	12	11	13	60
32	31	16	12	12	11	75
35	32	13	9	9	19	73
38	39	10	7	16	12	85
42	37	15	13	13	17	79
34	38	16	9	16	9	71
35	39	16	6	12	12	72
38	34	14	8	9	19	69
33	31	10	8	13	18	78
36	32	17	15	13	15	54
32	37	13	6	14	14	69
33	36	15	9	19	11	81
34	32	16	11	13	9	84
32	38	12	8	12	18	84
34	36	13	8	13	16	69
27	26	13	10	10	24	66
31	26	12	8	14	14	81
38	33	17	14	16	20	82
34	39	15	10	10	18	72
24	30	10	8	11	23	54
30	33	14	11	14	12	78
26	25	11	12	12	14	74
34	38	13	12	9	16	82
27	37	16	12	9	18	73
37	31	12	5	11	20	55
36	37	16	12	16	12	72
41	35	12	10	9	12	78
29	25	9	7	13	17	59
36	28	12	12	16	13	72
32	35	15	11	13	9	78
37	33	12	8	9	16	68
30	30	12	9	12	18	69
31	31	14	10	16	10	67
38	37	12	9	11	14	74
36	36	16	12	14	11	54
35	30	11	6	13	9	67
31	36	19	15	15	11	70
38	32	15	12	14	10	80
22	28	8	12	16	11	89
32	36	16	12	13	19	76
36	34	17	11	14	14	74
39	31	12	7	15	12	87
28	28	11	7	13	14	54
32	36	11	5	11	21	61
32	36	14	12	11	13	38
38	40	16	12	14	10	75
32	33	12	3	15	15	69
35	37	16	11	11	16	62
32	32	13	10	15	14	72
37	38	15	12	12	12	70
34	31	16	9	14	19	79
33	37	16	12	14	15	87
33	33	14	9	8	19	62
26	32	16	12	13	13	77
30	30	16	12	9	17	69
24	30	14	10	15	12	69
34	31	11	9	17	11	75
34	32	12	12	13	14	54
33	34	15	8	15	11	72
34	36	15	11	15	13	74
35	37	16	11	14	12	85
35	36	16	12	16	15	52
36	33	11	10	13	14	70
34	33	15	10	16	12	84
34	33	12	12	9	17	64
41	44	12	12	16	11	84
32	39	15	11	11	18	87
30	32	15	8	10	13	79
35	35	16	12	11	17	67
28	25	14	10	15	13	65
33	35	17	11	17	11	85
39	34	14	10	14	12	83
36	35	13	8	8	22	61
36	39	15	12	15	14	82
35	33	13	12	11	12	76
38	36	14	10	16	12	58
33	32	15	12	10	17	72
31	32	12	9	15	9	72
34	36	13	9	9	21	38
32	36	8	6	16	10	78
31	32	14	10	19	11	54
33	34	14	9	12	12	63
34	33	11	9	8	23	66
34	35	12	9	11	13	70
34	30	13	6	14	12	71
33	38	10	10	9	16	67
32	34	16	6	15	9	58
41	33	18	14	13	17	72
34	32	13	10	16	9	72
36	31	11	10	11	14	70
37	30	4	6	12	17	76
36	27	13	12	13	13	50
29	31	16	12	10	11	72
37	30	10	7	11	12	72
27	32	12	8	12	10	88
35	35	12	11	8	19	53
28	28	10	3	12	16	58
35	33	13	6	12	16	66
37	31	15	10	15	14	82
29	35	12	8	11	20	69
32	35	14	9	13	15	68
36	32	10	9	14	23	44
19	21	12	8	10	20	56
21	20	12	9	12	16	53
31	34	11	7	15	14	70
33	32	10	7	13	17	78
36	34	12	6	13	11	71
33	32	16	9	13	13	72
37	33	12	10	12	17	68
34	33	14	11	12	15	67
35	37	16	12	9	21	75
31	32	14	8	9	18	62
37	34	13	11	15	15	67
35	30	4	3	10	8	83
27	30	15	11	14	12	64
34	38	11	12	15	12	68
40	36	11	7	7	22	62
29	32	14	9	14	12	72

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 12 seconds R Server 'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 12 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185721&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]12 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185721&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185721&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 Input view raw input (R code) Raw Output view raw output of R engine Computing time 12 seconds R Server 'Herman Ole Andreas Wold' @ wold.wessa.net

 Multiple Linear Regression - Estimated Regression Equation Learning[t] = + 5.45153304933178 + 0.0321668940555693Connected[t] + 0.0427653888947305Separate[t] + 0.558489671132888Software[t] + 0.0702334998707421Happiness[t] -0.031126424436301Depression[t] + 0.00747850801958789Belonging[t] -0.00491058171792578t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  5.45153304933178 +  0.0321668940555693Connected[t] +  0.0427653888947305Separate[t] +  0.558489671132888Software[t] +  0.0702334998707421Happiness[t] -0.031126424436301Depression[t] +  0.00747850801958789Belonging[t] -0.00491058171792578t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185721&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  5.45153304933178 +  0.0321668940555693Connected[t] +  0.0427653888947305Separate[t] +  0.558489671132888Software[t] +  0.0702334998707421Happiness[t] -0.031126424436301Depression[t] +  0.00747850801958789Belonging[t] -0.00491058171792578t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185721&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185721&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 Learning[t] = + 5.45153304933178 + 0.0321668940555693Connected[t] + 0.0427653888947305Separate[t] + 0.558489671132888Software[t] + 0.0702334998707421Happiness[t] -0.031126424436301Depression[t] + 0.00747850801958789Belonging[t] -0.00491058171792578t + e[t]

 Multiple Linear Regression - Ordinary Least Squares Variable Parameter S.D. T-STATH0: parameter = 0 2-tail p-value 1-tail p-value (Intercept) 5.45153304933178 1.942794 2.806 0.005401 0.0027 Connected 0.0321668940555693 0.034424 0.9344 0.350967 0.175483 Separate 0.0427653888947305 0.035076 1.2192 0.223886 0.111943 Software 0.558489671132888 0.053726 10.3952 0 0 Happiness 0.0702334998707421 0.057809 1.2149 0.225518 0.112759 Depression -0.031126424436301 0.041759 -0.7454 0.456725 0.228362 Belonging 0.00747850801958789 0.011869 0.6301 0.529191 0.264595 t -0.00491058171792578 0.00168 -2.9227 0.00378 0.00189

\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) & 5.45153304933178 & 1.942794 & 2.806 & 0.005401 & 0.0027 \tabularnewline
Connected & 0.0321668940555693 & 0.034424 & 0.9344 & 0.350967 & 0.175483 \tabularnewline
Separate & 0.0427653888947305 & 0.035076 & 1.2192 & 0.223886 & 0.111943 \tabularnewline
Software & 0.558489671132888 & 0.053726 & 10.3952 & 0 & 0 \tabularnewline
Happiness & 0.0702334998707421 & 0.057809 & 1.2149 & 0.225518 & 0.112759 \tabularnewline
Depression & -0.031126424436301 & 0.041759 & -0.7454 & 0.456725 & 0.228362 \tabularnewline
Belonging & 0.00747850801958789 & 0.011869 & 0.6301 & 0.529191 & 0.264595 \tabularnewline
t & -0.00491058171792578 & 0.00168 & -2.9227 & 0.00378 & 0.00189 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185721&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]5.45153304933178[/C][C]1.942794[/C][C]2.806[/C][C]0.005401[/C][C]0.0027[/C][/ROW]
[ROW][C]Connected[/C][C]0.0321668940555693[/C][C]0.034424[/C][C]0.9344[/C][C]0.350967[/C][C]0.175483[/C][/ROW]
[ROW][C]Separate[/C][C]0.0427653888947305[/C][C]0.035076[/C][C]1.2192[/C][C]0.223886[/C][C]0.111943[/C][/ROW]
[ROW][C]Software[/C][C]0.558489671132888[/C][C]0.053726[/C][C]10.3952[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0702334998707421[/C][C]0.057809[/C][C]1.2149[/C][C]0.225518[/C][C]0.112759[/C][/ROW]
[ROW][C]Depression[/C][C]-0.031126424436301[/C][C]0.041759[/C][C]-0.7454[/C][C]0.456725[/C][C]0.228362[/C][/ROW]
[ROW][C]Belonging[/C][C]0.00747850801958789[/C][C]0.011869[/C][C]0.6301[/C][C]0.529191[/C][C]0.264595[/C][/ROW]
[ROW][C]t[/C][C]-0.00491058171792578[/C][C]0.00168[/C][C]-2.9227[/C][C]0.00378[/C][C]0.00189[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185721&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185721&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 Variable Parameter S.D. T-STATH0: parameter = 0 2-tail p-value 1-tail p-value (Intercept) 5.45153304933178 1.942794 2.806 0.005401 0.0027 Connected 0.0321668940555693 0.034424 0.9344 0.350967 0.175483 Separate 0.0427653888947305 0.035076 1.2192 0.223886 0.111943 Software 0.558489671132888 0.053726 10.3952 0 0 Happiness 0.0702334998707421 0.057809 1.2149 0.225518 0.112759 Depression -0.031126424436301 0.041759 -0.7454 0.456725 0.228362 Belonging 0.00747850801958789 0.011869 0.6301 0.529191 0.264595 t -0.00491058171792578 0.00168 -2.9227 0.00378 0.00189

 Multiple Linear Regression - Regression Statistics Multiple R 0.667212929789437 R-squared 0.445173093678205 Adjusted R-squared 0.430002045458468 F-TEST (value) 29.3435949336093 F-TEST (DF numerator) 7 F-TEST (DF denominator) 256 p-value 0 Multiple Linear Regression - Residual Statistics Residual Standard Deviation 1.85421524491435 Sum Squared Residuals 880.15722866503

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.667212929789437 \tabularnewline
R-squared & 0.445173093678205 \tabularnewline
F-TEST (value) & 29.3435949336093 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 256 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.85421524491435 \tabularnewline
Sum Squared Residuals & 880.15722866503 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185721&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.667212929789437[/C][/ROW]
[ROW][C]R-squared[/C][C]0.445173093678205[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]29.3435949336093[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]256[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]1.85421524491435[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]880.15722866503[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185721&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185721&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 R 0.667212929789437 R-squared 0.445173093678205 Adjusted R-squared 0.430002045458468 F-TEST (value) 29.3435949336093 F-TEST (DF numerator) 7 F-TEST (DF denominator) 256 p-value 0 Multiple Linear Regression - Residual Statistics Residual Standard Deviation 1.85421524491435 Sum Squared Residuals 880.15722866503

 Multiple Linear Regression - Actuals, Interpolation, and Residuals Time or Index Actuals InterpolationForecast ResidualsPrediction Error 1 13 16.0985387854795 -3.09853878547954 2 16 15.7506280756561 0.249371924343879 3 19 17.1063218899167 1.89367811008327 4 15 12.1616052410318 2.83839475896815 5 14 16.4017873467223 -2.40178734672232 6 13 14.8470133702108 -1.84701337021082 7 19 15.3941195404347 3.60588045956526 8 15 17.1034911605066 -2.10349116050658 9 14 16.0596585119288 -2.0596585119288 10 15 14.4613197202822 0.53868027971776 11 16 15.0039897785988 0.996010221401191 12 16 16.1957780658441 -0.195778065844102 13 16 15.5452007954959 0.454799204504098 14 16 15.497570422791 0.50242957720904 15 17 18.0026152345095 -1.00261523450953 16 15 15.4966907599622 -0.496690759962226 17 15 14.5878376596391 0.412162340360936 18 20 16.4221329188422 3.57786708115779 19 18 15.5318412924009 2.46815870759907 20 16 15.598397960354 0.40160203964601 21 16 15.3944791538427 0.605520846157265 22 16 15.2136141783933 0.786385821606707 23 19 16.4921403787265 2.50785962127348 24 16 15.1609192229515 0.839080777048499 25 17 16.1483763914647 0.851623608535261 26 17 16.22180307078 0.778196929220023 27 16 14.908352790214 1.09164720978603 28 15 16.8091087350266 -1.80910873502655 29 16 15.6848237519473 0.31517624805274 30 14 14.263029558757 -0.263029558756992 31 15 15.7659606607022 -0.765960660702232 32 12 12.8492889523859 -0.849288952385888 33 14 14.8039620225922 -0.803962022592169 34 16 16.0017496144186 -0.00174961441855281 35 14 15.4902098814983 -1.49020988149829 36 10 13.0304769205532 -3.0304769205532 37 10 13.0355345646574 -3.03553456465737 38 14 15.7470324913881 -1.74703249138812 39 16 14.554555919938 1.445444080062 40 16 14.4948939247229 1.50510607527713 41 16 14.7205377064971 1.27946229350293 42 14 15.7009510594818 -1.70095105948177 43 20 17.4871215566965 2.51287844330348 44 14 14.1533777639022 -0.153377763902224 45 14 14.4623553291315 -0.462355329131477 46 11 15.4909495615117 -4.49094956151171 47 14 16.6307612737306 -2.63076127373058 48 15 15.1467421663187 -0.146742166318652 49 16 15.417876616323 0.582123383676952 50 14 15.6302473667626 -1.63024736676259 51 16 17.0252984963352 -1.02529849633517 52 14 14.1419408813432 -0.14194088134322 53 12 15.0171855791395 -3.01718557913948 54 16 16.0361860907356 -0.0361860907355932 55 9 11.3432897998035 -2.34328979980353 56 14 12.3849781445203 1.61502185547966 57 16 15.8545401093022 0.145459890697824 58 16 15.5298832287659 0.470116771234096 59 15 15.1123930302181 -0.112393030218105 60 16 14.2210605652264 1.77893943477358 61 12 11.5595534084661 0.440446591533867 62 16 15.6406817555398 0.359318244460184 63 16 16.5488168530774 -0.548816853077399 64 14 14.7109860019853 -0.710986001985265 65 16 15.3063211583342 0.693678841665768 66 17 16.0541860332013 0.945813966798677 67 18 16.3331770798611 1.6668229201389 68 18 14.3958881874426 3.60411181255739 69 12 15.8997083739692 -3.89970837396924 70 16 15.6515786730261 0.348421326973927 71 10 13.412380608575 -3.41238060857495 72 14 14.9242951062704 -0.924295106270409 73 18 16.9280586745433 1.07194132545668 74 18 17.140983623911 0.85901637608902 75 16 15.2322948752948 0.767705124705194 76 17 13.4918869897008 3.50811301029925 77 16 16.419099992442 -0.419099992441992 78 16 14.5311988476754 1.46880115232456 79 13 15.2165773344004 -2.21657733440038 80 16 15.1421402571568 0.857859742843149 81 16 15.6586274506278 0.341372549372198 82 16 15.7632408306316 0.236759169368356 83 15 15.6434137240469 -0.64341372404695 84 15 14.8842323819227 0.115767618077311 85 16 14.1607354722341 1.83926452776585 86 14 14.1555692846506 -0.155569284650592 87 16 15.3674881780279 0.632511821972136 88 16 14.8725888488247 1.12741115117526 89 15 14.5194813902587 0.480518609741335 90 12 13.907972516408 -1.90797251640802 91 17 16.7584943754586 0.241505624541391 92 16 15.8055619194036 0.194438080596368 93 15 15.0531067912421 -0.0531067912420967 94 13 15.0298518503278 -2.02985185032776 95 16 14.7436133365348 1.25638666346519 96 16 15.7882428813297 0.21175711867026 97 16 13.6773839654895 2.32261603451052 98 16 15.7737083756365 0.22629162436346 99 14 14.4297816437613 -0.429781643761329 100 16 16.9922981106499 -0.992298110649857 101 16 14.6766246625527 1.32337533744731 102 20 17.4542184425634 2.54578155743657 103 15 14.2396603727495 0.760339627250478 104 16 14.9598584444853 1.04014155551469 105 13 14.8422042092773 -1.84220420927732 106 17 15.7017299648748 1.29827003512525 107 16 15.7011234587523 0.298876541247731 108 16 14.3586514687943 1.64134853120572 109 12 12.3043422991135 -0.30434229911349 110 16 15.2856808956604 0.71431910433959 111 16 15.9928271492344 0.00717285076563753 112 17 15.0564093690921 1.9435906309079 113 13 14.2811780773625 -1.28117807736248 114 12 14.5798742612205 -2.57987426122045 115 18 16.1614728444387 1.83852715556127 116 14 15.8657328435429 -1.86573284354287 117 14 13.228887828907 0.771112171092987 118 13 14.7929151358429 -1.79291513584291 119 16 15.520384206224 0.479615793776011 120 13 14.4292215835434 -1.42922158354341 121 16 15.3854232676415 0.614576732358463 122 13 15.8212093173508 -2.82120931735076 123 16 16.8545044640026 -0.854504464002574 124 15 15.8437647974654 -0.84376479746541 125 16 16.7849339139009 -0.784933913900918 126 15 14.6587216010757 0.341278398924287 127 17 15.4905839058456 1.50941609415437 128 15 14.0482521120088 0.951747887991231 129 12 14.6858650734517 -2.68586507345171 130 16 13.9402714795457 2.05972852045429 131 10 13.7239532443361 -3.72395324433605 132 16 13.4583321541629 2.54166784583713 133 12 14.1659890224415 -2.16598902244154 134 14 15.5440460090552 -1.54404600905523 135 15 15.0836566962205 -0.0836566962204929 136 13 12.1121127347309 0.887887265269134 137 15 14.5312778069589 0.468722193041143 138 11 13.4989500572246 -2.49895005722465 139 12 13.0064804164844 -1.00648041648441 140 11 13.339956434492 -2.33995643449198 141 16 12.8564999151223 3.14350008487773 142 15 13.6441244258235 1.35587557417654 143 17 16.8413639582837 0.158636041716298 144 16 14.1244038470475 1.87559615295252 145 10 13.266751430131 -3.26675143013095 146 18 15.497545467363 2.50245453263695 147 13 14.9457512386837 -1.94575123868367 148 16 14.843010105307 1.15698989469303 149 13 12.82722767011 0.172772329889988 150 10 12.9004577169405 -2.90045771694049 151 15 15.8784182905414 -0.878418290541449 152 16 13.8248630916881 2.17513690831192 153 16 11.8525810147495 4.1474189852505 154 14 12.3963025182653 1.60369748173469 155 10 12.4816282956809 -2.48162829568091 156 17 16.4393065637934 0.560693436206567 157 13 11.7066858547317 1.29331414526825 158 15 13.900934660471 1.099065339529 159 16 14.5373961332024 1.46260386679759 160 12 12.6989037635456 -0.698903763545609 161 13 12.6931049205989 0.306895079401113 162 13 12.670204114649 0.329795885350951 163 12 12.3813576310274 -0.381357631027421 164 17 16.2130980179022 0.78690198209781 165 15 13.6682202782511 1.33177972174891 166 10 11.6197611469958 -1.61976114699577 167 14 14.3441924705758 -0.344192470575766 168 11 14.1943469919182 -3.19434699191817 169 13 14.7895963339482 -1.78959633394817 170 16 14.3871926838976 1.61280731610237 171 12 10.4815320179531 1.5184679820469 172 16 15.3377881046553 0.66221189534468 173 12 13.8444384221823 -1.84443842218234 174 9 11.3336124343809 -2.3336124343809 175 12 14.9070414350127 -2.90704143501267 176 15 14.4730075744532 0.526992425546806 177 12 12.294327621092 -0.294327621092034 178 12 12.650368444193 -0.650368444193032 179 14 13.7938681954925 0.206131804507504 180 12 13.2889048934373 -1.28890489343725 181 16 15.0068737606415 0.993126239358508 182 11 11.4515058779588 -0.451505877958786 183 19 16.7015767685106 2.29842323148939 184 15 15.1109818809655 -0.110981880965518 185 8 14.596986586261 -6.59698658626104 186 16 14.6989355568994 1.30106444310063 187 17 14.3895807084944 2.61041929150556 188 12 12.3486229107255 -0.348622910725466 189 11 11.4120697144516 -0.4120697144516 190 11 10.4549680631895 0.545031936810458 191 14 14.4364908904417 -0.436490890441723 192 16 15.376427798282 0.623572201717984 193 12 9.72248141934327 2.27751858065673 194 16 14.0886404643777 1.9113595356223 195 13 13.632884513438 -0.632884513437976 196 15 14.9989754108533 0.00102458914674308 197 16 12.9126260121705 3.08737398782949 198 16 14.991943645066 1.00805635493403 199 14 12.4076330969111 1.59236690308889 200 16 14.4603615475735 1.53963845242654 201 16 14.0333200029035 1.96667999709652 202 14 13.2954618359923 0.704538164007681 203 11 13.3129603848872 -2.31296038488724 204 12 14.4949222642595 -2.49492226425949 205 15 12.6778762991469 2.32212370085313 206 15 14.4188365698392 0.581163430160781 207 16 14.5320147838526 1.46798521614738 208 16 14.843125446159 1.15687455384097 209 11 13.5801453187234 -2.58014531872336 210 15 13.8885534096534 1.11144659034664 211 12 14.2037853885328 -2.20378538853275 212 12 15.7224255491506 -3.7224255491506 213 15 14.109079358977 0.89092064102304 214 15 12.0905788116402 2.90942118835982 215 16 14.4647432573063 1.53525674269367 216 14 13.0805138671753 0.919486132824671 217 17 14.5748713248213 2.42512867517871 218 14 13.9049231073215 0.0950768926785438 219 13 11.8321054700474 1.16789452995262 220 15 15.1299096914369 -0.129909691436878 221 13 14.5726876835671 -1.57268768356711 222 14 13.8921489634354 0.107851036564568 223 15 14.1999876889948 0.800012311005213 224 12 13.0554532006112 -1.05545320061118 225 13 12.2689174915128 0.731082508487173 226 8 11.6573695969631 -3.65736959696312 227 14 13.6832791328481 0.316720867151928 228 14 12.8142890945427 1.18571090545735 229 11 12.197890873762 -1.19789087376205 230 12 12.8303898458872 -0.830389845887172 231 13 11.185488738365 1.81451126163496 232 10 13.2189058291037 -3.21890582910368 233 16 11.348787511322 4.65121248867802 234 18 15.7737516733149 2.22624832668511 235 13 13.7266606548843 -0.726660654884331 236 11 13.2215618348084 -2.22156183480842 237 4 10.9938193483991 -6.99381934839915 238 13 14.1796817218455 -1.17968172184545 239 16 14.1367439630088 1.86325603699123 240 10 11.5930618646107 -1.59306186461067 241 12 12.1626452683162 -0.162645268316151 242 12 13.3960154190304 -1.39601541903038 243 10 8.81036730048706 1.18963269951294 244 13 10.9797489991871 2.02025100081286 245 15 13.5802095891207 1.41979041087932 246 12 11.8071329179159 0.192867082084071 247 14 12.745833303401 1.254166696599 248 10 12.3830320431314 -2.38303204313139 249 12 10.7045626835548 1.29543731644515 250 12 11.5222473456141 0.477752654385857 251 11 11.7208297915302 -0.720829791530183 252 10 11.5207040112403 -1.52070401124025 253 12 11.2737442088263 0.726255791173704 254 16 12.7074968396979 3.29250316030215 255 12 13.2078556645355 -1.20785566453552 256 14 13.7197084126368 0.280291587363206 257 16 14.1388849696129 1.86111503038708 258 14 11.5536798517218 2.44632014827823 259 13 14.0549432381567 -1.05494323815668 260 4 9.33309354369939 -5.33309354369939 261 15 13.5531018279656 1.44689817203439 262 11 14.7741198188765 -3.7741198188765 263 11 11.1662281765916 -0.16622817659161 264 14 12.6310833706034 1.36891662939664

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 16.0985387854795 & -3.09853878547954 \tabularnewline
2 & 16 & 15.7506280756561 & 0.249371924343879 \tabularnewline
3 & 19 & 17.1063218899167 & 1.89367811008327 \tabularnewline
4 & 15 & 12.1616052410318 & 2.83839475896815 \tabularnewline
5 & 14 & 16.4017873467223 & -2.40178734672232 \tabularnewline
6 & 13 & 14.8470133702108 & -1.84701337021082 \tabularnewline
7 & 19 & 15.3941195404347 & 3.60588045956526 \tabularnewline
8 & 15 & 17.1034911605066 & -2.10349116050658 \tabularnewline
9 & 14 & 16.0596585119288 & -2.0596585119288 \tabularnewline
10 & 15 & 14.4613197202822 & 0.53868027971776 \tabularnewline
11 & 16 & 15.0039897785988 & 0.996010221401191 \tabularnewline
12 & 16 & 16.1957780658441 & -0.195778065844102 \tabularnewline
13 & 16 & 15.5452007954959 & 0.454799204504098 \tabularnewline
14 & 16 & 15.497570422791 & 0.50242957720904 \tabularnewline
15 & 17 & 18.0026152345095 & -1.00261523450953 \tabularnewline
16 & 15 & 15.4966907599622 & -0.496690759962226 \tabularnewline
17 & 15 & 14.5878376596391 & 0.412162340360936 \tabularnewline
18 & 20 & 16.4221329188422 & 3.57786708115779 \tabularnewline
19 & 18 & 15.5318412924009 & 2.46815870759907 \tabularnewline
20 & 16 & 15.598397960354 & 0.40160203964601 \tabularnewline
21 & 16 & 15.3944791538427 & 0.605520846157265 \tabularnewline
22 & 16 & 15.2136141783933 & 0.786385821606707 \tabularnewline
23 & 19 & 16.4921403787265 & 2.50785962127348 \tabularnewline
24 & 16 & 15.1609192229515 & 0.839080777048499 \tabularnewline
25 & 17 & 16.1483763914647 & 0.851623608535261 \tabularnewline
26 & 17 & 16.22180307078 & 0.778196929220023 \tabularnewline
27 & 16 & 14.908352790214 & 1.09164720978603 \tabularnewline
28 & 15 & 16.8091087350266 & -1.80910873502655 \tabularnewline
29 & 16 & 15.6848237519473 & 0.31517624805274 \tabularnewline
30 & 14 & 14.263029558757 & -0.263029558756992 \tabularnewline
31 & 15 & 15.7659606607022 & -0.765960660702232 \tabularnewline
32 & 12 & 12.8492889523859 & -0.849288952385888 \tabularnewline
33 & 14 & 14.8039620225922 & -0.803962022592169 \tabularnewline
34 & 16 & 16.0017496144186 & -0.00174961441855281 \tabularnewline
35 & 14 & 15.4902098814983 & -1.49020988149829 \tabularnewline
36 & 10 & 13.0304769205532 & -3.0304769205532 \tabularnewline
37 & 10 & 13.0355345646574 & -3.03553456465737 \tabularnewline
38 & 14 & 15.7470324913881 & -1.74703249138812 \tabularnewline
39 & 16 & 14.554555919938 & 1.445444080062 \tabularnewline
40 & 16 & 14.4948939247229 & 1.50510607527713 \tabularnewline
41 & 16 & 14.7205377064971 & 1.27946229350293 \tabularnewline
42 & 14 & 15.7009510594818 & -1.70095105948177 \tabularnewline
43 & 20 & 17.4871215566965 & 2.51287844330348 \tabularnewline
44 & 14 & 14.1533777639022 & -0.153377763902224 \tabularnewline
45 & 14 & 14.4623553291315 & -0.462355329131477 \tabularnewline
46 & 11 & 15.4909495615117 & -4.49094956151171 \tabularnewline
47 & 14 & 16.6307612737306 & -2.63076127373058 \tabularnewline
48 & 15 & 15.1467421663187 & -0.146742166318652 \tabularnewline
49 & 16 & 15.417876616323 & 0.582123383676952 \tabularnewline
50 & 14 & 15.6302473667626 & -1.63024736676259 \tabularnewline
51 & 16 & 17.0252984963352 & -1.02529849633517 \tabularnewline
52 & 14 & 14.1419408813432 & -0.14194088134322 \tabularnewline
53 & 12 & 15.0171855791395 & -3.01718557913948 \tabularnewline
54 & 16 & 16.0361860907356 & -0.0361860907355932 \tabularnewline
55 & 9 & 11.3432897998035 & -2.34328979980353 \tabularnewline
56 & 14 & 12.3849781445203 & 1.61502185547966 \tabularnewline
57 & 16 & 15.8545401093022 & 0.145459890697824 \tabularnewline
58 & 16 & 15.5298832287659 & 0.470116771234096 \tabularnewline
59 & 15 & 15.1123930302181 & -0.112393030218105 \tabularnewline
60 & 16 & 14.2210605652264 & 1.77893943477358 \tabularnewline
61 & 12 & 11.5595534084661 & 0.440446591533867 \tabularnewline
62 & 16 & 15.6406817555398 & 0.359318244460184 \tabularnewline
63 & 16 & 16.5488168530774 & -0.548816853077399 \tabularnewline
64 & 14 & 14.7109860019853 & -0.710986001985265 \tabularnewline
65 & 16 & 15.3063211583342 & 0.693678841665768 \tabularnewline
66 & 17 & 16.0541860332013 & 0.945813966798677 \tabularnewline
67 & 18 & 16.3331770798611 & 1.6668229201389 \tabularnewline
68 & 18 & 14.3958881874426 & 3.60411181255739 \tabularnewline
69 & 12 & 15.8997083739692 & -3.89970837396924 \tabularnewline
70 & 16 & 15.6515786730261 & 0.348421326973927 \tabularnewline
71 & 10 & 13.412380608575 & -3.41238060857495 \tabularnewline
72 & 14 & 14.9242951062704 & -0.924295106270409 \tabularnewline
73 & 18 & 16.9280586745433 & 1.07194132545668 \tabularnewline
74 & 18 & 17.140983623911 & 0.85901637608902 \tabularnewline
75 & 16 & 15.2322948752948 & 0.767705124705194 \tabularnewline
76 & 17 & 13.4918869897008 & 3.50811301029925 \tabularnewline
77 & 16 & 16.419099992442 & -0.419099992441992 \tabularnewline
78 & 16 & 14.5311988476754 & 1.46880115232456 \tabularnewline
79 & 13 & 15.2165773344004 & -2.21657733440038 \tabularnewline
80 & 16 & 15.1421402571568 & 0.857859742843149 \tabularnewline
81 & 16 & 15.6586274506278 & 0.341372549372198 \tabularnewline
82 & 16 & 15.7632408306316 & 0.236759169368356 \tabularnewline
83 & 15 & 15.6434137240469 & -0.64341372404695 \tabularnewline
84 & 15 & 14.8842323819227 & 0.115767618077311 \tabularnewline
85 & 16 & 14.1607354722341 & 1.83926452776585 \tabularnewline
86 & 14 & 14.1555692846506 & -0.155569284650592 \tabularnewline
87 & 16 & 15.3674881780279 & 0.632511821972136 \tabularnewline
88 & 16 & 14.8725888488247 & 1.12741115117526 \tabularnewline
89 & 15 & 14.5194813902587 & 0.480518609741335 \tabularnewline
90 & 12 & 13.907972516408 & -1.90797251640802 \tabularnewline
91 & 17 & 16.7584943754586 & 0.241505624541391 \tabularnewline
92 & 16 & 15.8055619194036 & 0.194438080596368 \tabularnewline
93 & 15 & 15.0531067912421 & -0.0531067912420967 \tabularnewline
94 & 13 & 15.0298518503278 & -2.02985185032776 \tabularnewline
95 & 16 & 14.7436133365348 & 1.25638666346519 \tabularnewline
96 & 16 & 15.7882428813297 & 0.21175711867026 \tabularnewline
97 & 16 & 13.6773839654895 & 2.32261603451052 \tabularnewline
98 & 16 & 15.7737083756365 & 0.22629162436346 \tabularnewline
99 & 14 & 14.4297816437613 & -0.429781643761329 \tabularnewline
100 & 16 & 16.9922981106499 & -0.992298110649857 \tabularnewline
101 & 16 & 14.6766246625527 & 1.32337533744731 \tabularnewline
102 & 20 & 17.4542184425634 & 2.54578155743657 \tabularnewline
103 & 15 & 14.2396603727495 & 0.760339627250478 \tabularnewline
104 & 16 & 14.9598584444853 & 1.04014155551469 \tabularnewline
105 & 13 & 14.8422042092773 & -1.84220420927732 \tabularnewline
106 & 17 & 15.7017299648748 & 1.29827003512525 \tabularnewline
107 & 16 & 15.7011234587523 & 0.298876541247731 \tabularnewline
108 & 16 & 14.3586514687943 & 1.64134853120572 \tabularnewline
109 & 12 & 12.3043422991135 & -0.30434229911349 \tabularnewline
110 & 16 & 15.2856808956604 & 0.71431910433959 \tabularnewline
111 & 16 & 15.9928271492344 & 0.00717285076563753 \tabularnewline
112 & 17 & 15.0564093690921 & 1.9435906309079 \tabularnewline
113 & 13 & 14.2811780773625 & -1.28117807736248 \tabularnewline
114 & 12 & 14.5798742612205 & -2.57987426122045 \tabularnewline
115 & 18 & 16.1614728444387 & 1.83852715556127 \tabularnewline
116 & 14 & 15.8657328435429 & -1.86573284354287 \tabularnewline
117 & 14 & 13.228887828907 & 0.771112171092987 \tabularnewline
118 & 13 & 14.7929151358429 & -1.79291513584291 \tabularnewline
119 & 16 & 15.520384206224 & 0.479615793776011 \tabularnewline
120 & 13 & 14.4292215835434 & -1.42922158354341 \tabularnewline
121 & 16 & 15.3854232676415 & 0.614576732358463 \tabularnewline
122 & 13 & 15.8212093173508 & -2.82120931735076 \tabularnewline
123 & 16 & 16.8545044640026 & -0.854504464002574 \tabularnewline
124 & 15 & 15.8437647974654 & -0.84376479746541 \tabularnewline
125 & 16 & 16.7849339139009 & -0.784933913900918 \tabularnewline
126 & 15 & 14.6587216010757 & 0.341278398924287 \tabularnewline
127 & 17 & 15.4905839058456 & 1.50941609415437 \tabularnewline
128 & 15 & 14.0482521120088 & 0.951747887991231 \tabularnewline
129 & 12 & 14.6858650734517 & -2.68586507345171 \tabularnewline
130 & 16 & 13.9402714795457 & 2.05972852045429 \tabularnewline
131 & 10 & 13.7239532443361 & -3.72395324433605 \tabularnewline
132 & 16 & 13.4583321541629 & 2.54166784583713 \tabularnewline
133 & 12 & 14.1659890224415 & -2.16598902244154 \tabularnewline
134 & 14 & 15.5440460090552 & -1.54404600905523 \tabularnewline
135 & 15 & 15.0836566962205 & -0.0836566962204929 \tabularnewline
136 & 13 & 12.1121127347309 & 0.887887265269134 \tabularnewline
137 & 15 & 14.5312778069589 & 0.468722193041143 \tabularnewline
138 & 11 & 13.4989500572246 & -2.49895005722465 \tabularnewline
139 & 12 & 13.0064804164844 & -1.00648041648441 \tabularnewline
140 & 11 & 13.339956434492 & -2.33995643449198 \tabularnewline
141 & 16 & 12.8564999151223 & 3.14350008487773 \tabularnewline
142 & 15 & 13.6441244258235 & 1.35587557417654 \tabularnewline
143 & 17 & 16.8413639582837 & 0.158636041716298 \tabularnewline
144 & 16 & 14.1244038470475 & 1.87559615295252 \tabularnewline
145 & 10 & 13.266751430131 & -3.26675143013095 \tabularnewline
146 & 18 & 15.497545467363 & 2.50245453263695 \tabularnewline
147 & 13 & 14.9457512386837 & -1.94575123868367 \tabularnewline
148 & 16 & 14.843010105307 & 1.15698989469303 \tabularnewline
149 & 13 & 12.82722767011 & 0.172772329889988 \tabularnewline
150 & 10 & 12.9004577169405 & -2.90045771694049 \tabularnewline
151 & 15 & 15.8784182905414 & -0.878418290541449 \tabularnewline
152 & 16 & 13.8248630916881 & 2.17513690831192 \tabularnewline
153 & 16 & 11.8525810147495 & 4.1474189852505 \tabularnewline
154 & 14 & 12.3963025182653 & 1.60369748173469 \tabularnewline
155 & 10 & 12.4816282956809 & -2.48162829568091 \tabularnewline
156 & 17 & 16.4393065637934 & 0.560693436206567 \tabularnewline
157 & 13 & 11.7066858547317 & 1.29331414526825 \tabularnewline
158 & 15 & 13.900934660471 & 1.099065339529 \tabularnewline
159 & 16 & 14.5373961332024 & 1.46260386679759 \tabularnewline
160 & 12 & 12.6989037635456 & -0.698903763545609 \tabularnewline
161 & 13 & 12.6931049205989 & 0.306895079401113 \tabularnewline
162 & 13 & 12.670204114649 & 0.329795885350951 \tabularnewline
163 & 12 & 12.3813576310274 & -0.381357631027421 \tabularnewline
164 & 17 & 16.2130980179022 & 0.78690198209781 \tabularnewline
165 & 15 & 13.6682202782511 & 1.33177972174891 \tabularnewline
166 & 10 & 11.6197611469958 & -1.61976114699577 \tabularnewline
167 & 14 & 14.3441924705758 & -0.344192470575766 \tabularnewline
168 & 11 & 14.1943469919182 & -3.19434699191817 \tabularnewline
169 & 13 & 14.7895963339482 & -1.78959633394817 \tabularnewline
170 & 16 & 14.3871926838976 & 1.61280731610237 \tabularnewline
171 & 12 & 10.4815320179531 & 1.5184679820469 \tabularnewline
172 & 16 & 15.3377881046553 & 0.66221189534468 \tabularnewline
173 & 12 & 13.8444384221823 & -1.84443842218234 \tabularnewline
174 & 9 & 11.3336124343809 & -2.3336124343809 \tabularnewline
175 & 12 & 14.9070414350127 & -2.90704143501267 \tabularnewline
176 & 15 & 14.4730075744532 & 0.526992425546806 \tabularnewline
177 & 12 & 12.294327621092 & -0.294327621092034 \tabularnewline
178 & 12 & 12.650368444193 & -0.650368444193032 \tabularnewline
179 & 14 & 13.7938681954925 & 0.206131804507504 \tabularnewline
180 & 12 & 13.2889048934373 & -1.28890489343725 \tabularnewline
181 & 16 & 15.0068737606415 & 0.993126239358508 \tabularnewline
182 & 11 & 11.4515058779588 & -0.451505877958786 \tabularnewline
183 & 19 & 16.7015767685106 & 2.29842323148939 \tabularnewline
184 & 15 & 15.1109818809655 & -0.110981880965518 \tabularnewline
185 & 8 & 14.596986586261 & -6.59698658626104 \tabularnewline
186 & 16 & 14.6989355568994 & 1.30106444310063 \tabularnewline
187 & 17 & 14.3895807084944 & 2.61041929150556 \tabularnewline
188 & 12 & 12.3486229107255 & -0.348622910725466 \tabularnewline
189 & 11 & 11.4120697144516 & -0.4120697144516 \tabularnewline
190 & 11 & 10.4549680631895 & 0.545031936810458 \tabularnewline
191 & 14 & 14.4364908904417 & -0.436490890441723 \tabularnewline
192 & 16 & 15.376427798282 & 0.623572201717984 \tabularnewline
193 & 12 & 9.72248141934327 & 2.27751858065673 \tabularnewline
194 & 16 & 14.0886404643777 & 1.9113595356223 \tabularnewline
195 & 13 & 13.632884513438 & -0.632884513437976 \tabularnewline
196 & 15 & 14.9989754108533 & 0.00102458914674308 \tabularnewline
197 & 16 & 12.9126260121705 & 3.08737398782949 \tabularnewline
198 & 16 & 14.991943645066 & 1.00805635493403 \tabularnewline
199 & 14 & 12.4076330969111 & 1.59236690308889 \tabularnewline
200 & 16 & 14.4603615475735 & 1.53963845242654 \tabularnewline
201 & 16 & 14.0333200029035 & 1.96667999709652 \tabularnewline
202 & 14 & 13.2954618359923 & 0.704538164007681 \tabularnewline
203 & 11 & 13.3129603848872 & -2.31296038488724 \tabularnewline
204 & 12 & 14.4949222642595 & -2.49492226425949 \tabularnewline
205 & 15 & 12.6778762991469 & 2.32212370085313 \tabularnewline
206 & 15 & 14.4188365698392 & 0.581163430160781 \tabularnewline
207 & 16 & 14.5320147838526 & 1.46798521614738 \tabularnewline
208 & 16 & 14.843125446159 & 1.15687455384097 \tabularnewline
209 & 11 & 13.5801453187234 & -2.58014531872336 \tabularnewline
210 & 15 & 13.8885534096534 & 1.11144659034664 \tabularnewline
211 & 12 & 14.2037853885328 & -2.20378538853275 \tabularnewline
212 & 12 & 15.7224255491506 & -3.7224255491506 \tabularnewline
213 & 15 & 14.109079358977 & 0.89092064102304 \tabularnewline
214 & 15 & 12.0905788116402 & 2.90942118835982 \tabularnewline
215 & 16 & 14.4647432573063 & 1.53525674269367 \tabularnewline
216 & 14 & 13.0805138671753 & 0.919486132824671 \tabularnewline
217 & 17 & 14.5748713248213 & 2.42512867517871 \tabularnewline
218 & 14 & 13.9049231073215 & 0.0950768926785438 \tabularnewline
219 & 13 & 11.8321054700474 & 1.16789452995262 \tabularnewline
220 & 15 & 15.1299096914369 & -0.129909691436878 \tabularnewline
221 & 13 & 14.5726876835671 & -1.57268768356711 \tabularnewline
222 & 14 & 13.8921489634354 & 0.107851036564568 \tabularnewline
223 & 15 & 14.1999876889948 & 0.800012311005213 \tabularnewline
224 & 12 & 13.0554532006112 & -1.05545320061118 \tabularnewline
225 & 13 & 12.2689174915128 & 0.731082508487173 \tabularnewline
226 & 8 & 11.6573695969631 & -3.65736959696312 \tabularnewline
227 & 14 & 13.6832791328481 & 0.316720867151928 \tabularnewline
228 & 14 & 12.8142890945427 & 1.18571090545735 \tabularnewline
229 & 11 & 12.197890873762 & -1.19789087376205 \tabularnewline
230 & 12 & 12.8303898458872 & -0.830389845887172 \tabularnewline
231 & 13 & 11.185488738365 & 1.81451126163496 \tabularnewline
232 & 10 & 13.2189058291037 & -3.21890582910368 \tabularnewline
233 & 16 & 11.348787511322 & 4.65121248867802 \tabularnewline
234 & 18 & 15.7737516733149 & 2.22624832668511 \tabularnewline
235 & 13 & 13.7266606548843 & -0.726660654884331 \tabularnewline
236 & 11 & 13.2215618348084 & -2.22156183480842 \tabularnewline
237 & 4 & 10.9938193483991 & -6.99381934839915 \tabularnewline
238 & 13 & 14.1796817218455 & -1.17968172184545 \tabularnewline
239 & 16 & 14.1367439630088 & 1.86325603699123 \tabularnewline
240 & 10 & 11.5930618646107 & -1.59306186461067 \tabularnewline
241 & 12 & 12.1626452683162 & -0.162645268316151 \tabularnewline
242 & 12 & 13.3960154190304 & -1.39601541903038 \tabularnewline
243 & 10 & 8.81036730048706 & 1.18963269951294 \tabularnewline
244 & 13 & 10.9797489991871 & 2.02025100081286 \tabularnewline
245 & 15 & 13.5802095891207 & 1.41979041087932 \tabularnewline
246 & 12 & 11.8071329179159 & 0.192867082084071 \tabularnewline
247 & 14 & 12.745833303401 & 1.254166696599 \tabularnewline
248 & 10 & 12.3830320431314 & -2.38303204313139 \tabularnewline
249 & 12 & 10.7045626835548 & 1.29543731644515 \tabularnewline
250 & 12 & 11.5222473456141 & 0.477752654385857 \tabularnewline
251 & 11 & 11.7208297915302 & -0.720829791530183 \tabularnewline
252 & 10 & 11.5207040112403 & -1.52070401124025 \tabularnewline
253 & 12 & 11.2737442088263 & 0.726255791173704 \tabularnewline
254 & 16 & 12.7074968396979 & 3.29250316030215 \tabularnewline
255 & 12 & 13.2078556645355 & -1.20785566453552 \tabularnewline
256 & 14 & 13.7197084126368 & 0.280291587363206 \tabularnewline
257 & 16 & 14.1388849696129 & 1.86111503038708 \tabularnewline
258 & 14 & 11.5536798517218 & 2.44632014827823 \tabularnewline
259 & 13 & 14.0549432381567 & -1.05494323815668 \tabularnewline
260 & 4 & 9.33309354369939 & -5.33309354369939 \tabularnewline
261 & 15 & 13.5531018279656 & 1.44689817203439 \tabularnewline
262 & 11 & 14.7741198188765 & -3.7741198188765 \tabularnewline
263 & 11 & 11.1662281765916 & -0.16622817659161 \tabularnewline
264 & 14 & 12.6310833706034 & 1.36891662939664 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185721&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]13[/C][C]16.0985387854795[/C][C]-3.09853878547954[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.7506280756561[/C][C]0.249371924343879[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]17.1063218899167[/C][C]1.89367811008327[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]12.1616052410318[/C][C]2.83839475896815[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.4017873467223[/C][C]-2.40178734672232[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.8470133702108[/C][C]-1.84701337021082[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.3941195404347[/C][C]3.60588045956526[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]17.1034911605066[/C][C]-2.10349116050658[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]16.0596585119288[/C][C]-2.0596585119288[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.4613197202822[/C][C]0.53868027971776[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]15.0039897785988[/C][C]0.996010221401191[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.1957780658441[/C][C]-0.195778065844102[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.5452007954959[/C][C]0.454799204504098[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.497570422791[/C][C]0.50242957720904[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]18.0026152345095[/C][C]-1.00261523450953[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.4966907599622[/C][C]-0.496690759962226[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.5878376596391[/C][C]0.412162340360936[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.4221329188422[/C][C]3.57786708115779[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.5318412924009[/C][C]2.46815870759907[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.598397960354[/C][C]0.40160203964601[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.3944791538427[/C][C]0.605520846157265[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]15.2136141783933[/C][C]0.786385821606707[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.4921403787265[/C][C]2.50785962127348[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]15.1609192229515[/C][C]0.839080777048499[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]16.1483763914647[/C][C]0.851623608535261[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.22180307078[/C][C]0.778196929220023[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.908352790214[/C][C]1.09164720978603[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.8091087350266[/C][C]-1.80910873502655[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.6848237519473[/C][C]0.31517624805274[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.263029558757[/C][C]-0.263029558756992[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.7659606607022[/C][C]-0.765960660702232[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.8492889523859[/C][C]-0.849288952385888[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.8039620225922[/C][C]-0.803962022592169[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]16.0017496144186[/C][C]-0.00174961441855281[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.4902098814983[/C][C]-1.49020988149829[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]13.0304769205532[/C][C]-3.0304769205532[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]13.0355345646574[/C][C]-3.03553456465737[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.7470324913881[/C][C]-1.74703249138812[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.554555919938[/C][C]1.445444080062[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.4948939247229[/C][C]1.50510607527713[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.7205377064971[/C][C]1.27946229350293[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.7009510594818[/C][C]-1.70095105948177[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.4871215566965[/C][C]2.51287844330348[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.1533777639022[/C][C]-0.153377763902224[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.4623553291315[/C][C]-0.462355329131477[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.4909495615117[/C][C]-4.49094956151171[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.6307612737306[/C][C]-2.63076127373058[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.1467421663187[/C][C]-0.146742166318652[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.417876616323[/C][C]0.582123383676952[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.6302473667626[/C][C]-1.63024736676259[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]17.0252984963352[/C][C]-1.02529849633517[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.1419408813432[/C][C]-0.14194088134322[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]15.0171855791395[/C][C]-3.01718557913948[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]16.0361860907356[/C][C]-0.0361860907355932[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]11.3432897998035[/C][C]-2.34328979980353[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.3849781445203[/C][C]1.61502185547966[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.8545401093022[/C][C]0.145459890697824[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.5298832287659[/C][C]0.470116771234096[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]15.1123930302181[/C][C]-0.112393030218105[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.2210605652264[/C][C]1.77893943477358[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.5595534084661[/C][C]0.440446591533867[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.6406817555398[/C][C]0.359318244460184[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.5488168530774[/C][C]-0.548816853077399[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.7109860019853[/C][C]-0.710986001985265[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.3063211583342[/C][C]0.693678841665768[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]16.0541860332013[/C][C]0.945813966798677[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.3331770798611[/C][C]1.6668229201389[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.3958881874426[/C][C]3.60411181255739[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.8997083739692[/C][C]-3.89970837396924[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.6515786730261[/C][C]0.348421326973927[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.412380608575[/C][C]-3.41238060857495[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.9242951062704[/C][C]-0.924295106270409[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.9280586745433[/C][C]1.07194132545668[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.140983623911[/C][C]0.85901637608902[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.2322948752948[/C][C]0.767705124705194[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.4918869897008[/C][C]3.50811301029925[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.419099992442[/C][C]-0.419099992441992[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.5311988476754[/C][C]1.46880115232456[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]15.2165773344004[/C][C]-2.21657733440038[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.1421402571568[/C][C]0.857859742843149[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.6586274506278[/C][C]0.341372549372198[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.7632408306316[/C][C]0.236759169368356[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.6434137240469[/C][C]-0.64341372404695[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.8842323819227[/C][C]0.115767618077311[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]14.1607354722341[/C][C]1.83926452776585[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.1555692846506[/C][C]-0.155569284650592[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.3674881780279[/C][C]0.632511821972136[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.8725888488247[/C][C]1.12741115117526[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.5194813902587[/C][C]0.480518609741335[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.907972516408[/C][C]-1.90797251640802[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.7584943754586[/C][C]0.241505624541391[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.8055619194036[/C][C]0.194438080596368[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.0531067912421[/C][C]-0.0531067912420967[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]15.0298518503278[/C][C]-2.02985185032776[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.7436133365348[/C][C]1.25638666346519[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.7882428813297[/C][C]0.21175711867026[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.6773839654895[/C][C]2.32261603451052[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.7737083756365[/C][C]0.22629162436346[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.4297816437613[/C][C]-0.429781643761329[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]16.9922981106499[/C][C]-0.992298110649857[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.6766246625527[/C][C]1.32337533744731[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.4542184425634[/C][C]2.54578155743657[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.2396603727495[/C][C]0.760339627250478[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]14.9598584444853[/C][C]1.04014155551469[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.8422042092773[/C][C]-1.84220420927732[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.7017299648748[/C][C]1.29827003512525[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.7011234587523[/C][C]0.298876541247731[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.3586514687943[/C][C]1.64134853120572[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.3043422991135[/C][C]-0.30434229911349[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.2856808956604[/C][C]0.71431910433959[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]15.9928271492344[/C][C]0.00717285076563753[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]15.0564093690921[/C][C]1.9435906309079[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.2811780773625[/C][C]-1.28117807736248[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.5798742612205[/C][C]-2.57987426122045[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.1614728444387[/C][C]1.83852715556127[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.8657328435429[/C][C]-1.86573284354287[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.228887828907[/C][C]0.771112171092987[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.7929151358429[/C][C]-1.79291513584291[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.520384206224[/C][C]0.479615793776011[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.4292215835434[/C][C]-1.42922158354341[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.3854232676415[/C][C]0.614576732358463[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.8212093173508[/C][C]-2.82120931735076[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]16.8545044640026[/C][C]-0.854504464002574[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.8437647974654[/C][C]-0.84376479746541[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.7849339139009[/C][C]-0.784933913900918[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.6587216010757[/C][C]0.341278398924287[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.4905839058456[/C][C]1.50941609415437[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]14.0482521120088[/C][C]0.951747887991231[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.6858650734517[/C][C]-2.68586507345171[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.9402714795457[/C][C]2.05972852045429[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.7239532443361[/C][C]-3.72395324433605[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4583321541629[/C][C]2.54166784583713[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.1659890224415[/C][C]-2.16598902244154[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.5440460090552[/C][C]-1.54404600905523[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.0836566962205[/C][C]-0.0836566962204929[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]12.1121127347309[/C][C]0.887887265269134[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.5312778069589[/C][C]0.468722193041143[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.4989500572246[/C][C]-2.49895005722465[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]13.0064804164844[/C][C]-1.00648041648441[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.339956434492[/C][C]-2.33995643449198[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8564999151223[/C][C]3.14350008487773[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.6441244258235[/C][C]1.35587557417654[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]16.8413639582837[/C][C]0.158636041716298[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.1244038470475[/C][C]1.87559615295252[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.266751430131[/C][C]-3.26675143013095[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.497545467363[/C][C]2.50245453263695[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]14.9457512386837[/C][C]-1.94575123868367[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.843010105307[/C][C]1.15698989469303[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.82722767011[/C][C]0.172772329889988[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.9004577169405[/C][C]-2.90045771694049[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]15.8784182905414[/C][C]-0.878418290541449[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.8248630916881[/C][C]2.17513690831192[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.8525810147495[/C][C]4.1474189852505[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.3963025182653[/C][C]1.60369748173469[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.4816282956809[/C][C]-2.48162829568091[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.4393065637934[/C][C]0.560693436206567[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.7066858547317[/C][C]1.29331414526825[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]13.900934660471[/C][C]1.099065339529[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.5373961332024[/C][C]1.46260386679759[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.6989037635456[/C][C]-0.698903763545609[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.6931049205989[/C][C]0.306895079401113[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.670204114649[/C][C]0.329795885350951[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.3813576310274[/C][C]-0.381357631027421[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.2130980179022[/C][C]0.78690198209781[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.6682202782511[/C][C]1.33177972174891[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.6197611469958[/C][C]-1.61976114699577[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.3441924705758[/C][C]-0.344192470575766[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.1943469919182[/C][C]-3.19434699191817[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.7895963339482[/C][C]-1.78959633394817[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.3871926838976[/C][C]1.61280731610237[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.4815320179531[/C][C]1.5184679820469[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.3377881046553[/C][C]0.66221189534468[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.8444384221823[/C][C]-1.84443842218234[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.3336124343809[/C][C]-2.3336124343809[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]14.9070414350127[/C][C]-2.90704143501267[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.4730075744532[/C][C]0.526992425546806[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.294327621092[/C][C]-0.294327621092034[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.650368444193[/C][C]-0.650368444193032[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.7938681954925[/C][C]0.206131804507504[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.2889048934373[/C][C]-1.28890489343725[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]15.0068737606415[/C][C]0.993126239358508[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.4515058779588[/C][C]-0.451505877958786[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]16.7015767685106[/C][C]2.29842323148939[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.1109818809655[/C][C]-0.110981880965518[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.596986586261[/C][C]-6.59698658626104[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.6989355568994[/C][C]1.30106444310063[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.3895807084944[/C][C]2.61041929150556[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.3486229107255[/C][C]-0.348622910725466[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.4120697144516[/C][C]-0.4120697144516[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.4549680631895[/C][C]0.545031936810458[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14.4364908904417[/C][C]-0.436490890441723[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.376427798282[/C][C]0.623572201717984[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.72248141934327[/C][C]2.27751858065673[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.0886404643777[/C][C]1.9113595356223[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.632884513438[/C][C]-0.632884513437976[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]14.9989754108533[/C][C]0.00102458914674308[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]12.9126260121705[/C][C]3.08737398782949[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]14.991943645066[/C][C]1.00805635493403[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4076330969111[/C][C]1.59236690308889[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.4603615475735[/C][C]1.53963845242654[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]14.0333200029035[/C][C]1.96667999709652[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.2954618359923[/C][C]0.704538164007681[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.3129603848872[/C][C]-2.31296038488724[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.4949222642595[/C][C]-2.49492226425949[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.6778762991469[/C][C]2.32212370085313[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.4188365698392[/C][C]0.581163430160781[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.5320147838526[/C][C]1.46798521614738[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]14.843125446159[/C][C]1.15687455384097[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.5801453187234[/C][C]-2.58014531872336[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]13.8885534096534[/C][C]1.11144659034664[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.2037853885328[/C][C]-2.20378538853275[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]15.7224255491506[/C][C]-3.7224255491506[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.109079358977[/C][C]0.89092064102304[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.0905788116402[/C][C]2.90942118835982[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.4647432573063[/C][C]1.53525674269367[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.0805138671753[/C][C]0.919486132824671[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.5748713248213[/C][C]2.42512867517871[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.9049231073215[/C][C]0.0950768926785438[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.8321054700474[/C][C]1.16789452995262[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.1299096914369[/C][C]-0.129909691436878[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]14.5726876835671[/C][C]-1.57268768356711[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]13.8921489634354[/C][C]0.107851036564568[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.1999876889948[/C][C]0.800012311005213[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.0554532006112[/C][C]-1.05545320061118[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.2689174915128[/C][C]0.731082508487173[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.6573695969631[/C][C]-3.65736959696312[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]13.6832791328481[/C][C]0.316720867151928[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]12.8142890945427[/C][C]1.18571090545735[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.197890873762[/C][C]-1.19789087376205[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]12.8303898458872[/C][C]-0.830389845887172[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.185488738365[/C][C]1.81451126163496[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.2189058291037[/C][C]-3.21890582910368[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.348787511322[/C][C]4.65121248867802[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]15.7737516733149[/C][C]2.22624832668511[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]13.7266606548843[/C][C]-0.726660654884331[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.2215618348084[/C][C]-2.22156183480842[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]10.9938193483991[/C][C]-6.99381934839915[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.1796817218455[/C][C]-1.17968172184545[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.1367439630088[/C][C]1.86325603699123[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.5930618646107[/C][C]-1.59306186461067[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.1626452683162[/C][C]-0.162645268316151[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.3960154190304[/C][C]-1.39601541903038[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.81036730048706[/C][C]1.18963269951294[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]10.9797489991871[/C][C]2.02025100081286[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.5802095891207[/C][C]1.41979041087932[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]11.8071329179159[/C][C]0.192867082084071[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]12.745833303401[/C][C]1.254166696599[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.3830320431314[/C][C]-2.38303204313139[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.7045626835548[/C][C]1.29543731644515[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.5222473456141[/C][C]0.477752654385857[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.7208297915302[/C][C]-0.720829791530183[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.5207040112403[/C][C]-1.52070401124025[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.2737442088263[/C][C]0.726255791173704[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]12.7074968396979[/C][C]3.29250316030215[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.2078556645355[/C][C]-1.20785566453552[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.7197084126368[/C][C]0.280291587363206[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.1388849696129[/C][C]1.86111503038708[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.5536798517218[/C][C]2.44632014827823[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.0549432381567[/C][C]-1.05494323815668[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.33309354369939[/C][C]-5.33309354369939[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.5531018279656[/C][C]1.44689817203439[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]14.7741198188765[/C][C]-3.7741198188765[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.1662281765916[/C][C]-0.16622817659161[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]12.6310833706034[/C][C]1.36891662939664[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185721&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185721&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 Index Actuals InterpolationForecast ResidualsPrediction Error 1 13 16.0985387854795 -3.09853878547954 2 16 15.7506280756561 0.249371924343879 3 19 17.1063218899167 1.89367811008327 4 15 12.1616052410318 2.83839475896815 5 14 16.4017873467223 -2.40178734672232 6 13 14.8470133702108 -1.84701337021082 7 19 15.3941195404347 3.60588045956526 8 15 17.1034911605066 -2.10349116050658 9 14 16.0596585119288 -2.0596585119288 10 15 14.4613197202822 0.53868027971776 11 16 15.0039897785988 0.996010221401191 12 16 16.1957780658441 -0.195778065844102 13 16 15.5452007954959 0.454799204504098 14 16 15.497570422791 0.50242957720904 15 17 18.0026152345095 -1.00261523450953 16 15 15.4966907599622 -0.496690759962226 17 15 14.5878376596391 0.412162340360936 18 20 16.4221329188422 3.57786708115779 19 18 15.5318412924009 2.46815870759907 20 16 15.598397960354 0.40160203964601 21 16 15.3944791538427 0.605520846157265 22 16 15.2136141783933 0.786385821606707 23 19 16.4921403787265 2.50785962127348 24 16 15.1609192229515 0.839080777048499 25 17 16.1483763914647 0.851623608535261 26 17 16.22180307078 0.778196929220023 27 16 14.908352790214 1.09164720978603 28 15 16.8091087350266 -1.80910873502655 29 16 15.6848237519473 0.31517624805274 30 14 14.263029558757 -0.263029558756992 31 15 15.7659606607022 -0.765960660702232 32 12 12.8492889523859 -0.849288952385888 33 14 14.8039620225922 -0.803962022592169 34 16 16.0017496144186 -0.00174961441855281 35 14 15.4902098814983 -1.49020988149829 36 10 13.0304769205532 -3.0304769205532 37 10 13.0355345646574 -3.03553456465737 38 14 15.7470324913881 -1.74703249138812 39 16 14.554555919938 1.445444080062 40 16 14.4948939247229 1.50510607527713 41 16 14.7205377064971 1.27946229350293 42 14 15.7009510594818 -1.70095105948177 43 20 17.4871215566965 2.51287844330348 44 14 14.1533777639022 -0.153377763902224 45 14 14.4623553291315 -0.462355329131477 46 11 15.4909495615117 -4.49094956151171 47 14 16.6307612737306 -2.63076127373058 48 15 15.1467421663187 -0.146742166318652 49 16 15.417876616323 0.582123383676952 50 14 15.6302473667626 -1.63024736676259 51 16 17.0252984963352 -1.02529849633517 52 14 14.1419408813432 -0.14194088134322 53 12 15.0171855791395 -3.01718557913948 54 16 16.0361860907356 -0.0361860907355932 55 9 11.3432897998035 -2.34328979980353 56 14 12.3849781445203 1.61502185547966 57 16 15.8545401093022 0.145459890697824 58 16 15.5298832287659 0.470116771234096 59 15 15.1123930302181 -0.112393030218105 60 16 14.2210605652264 1.77893943477358 61 12 11.5595534084661 0.440446591533867 62 16 15.6406817555398 0.359318244460184 63 16 16.5488168530774 -0.548816853077399 64 14 14.7109860019853 -0.710986001985265 65 16 15.3063211583342 0.693678841665768 66 17 16.0541860332013 0.945813966798677 67 18 16.3331770798611 1.6668229201389 68 18 14.3958881874426 3.60411181255739 69 12 15.8997083739692 -3.89970837396924 70 16 15.6515786730261 0.348421326973927 71 10 13.412380608575 -3.41238060857495 72 14 14.9242951062704 -0.924295106270409 73 18 16.9280586745433 1.07194132545668 74 18 17.140983623911 0.85901637608902 75 16 15.2322948752948 0.767705124705194 76 17 13.4918869897008 3.50811301029925 77 16 16.419099992442 -0.419099992441992 78 16 14.5311988476754 1.46880115232456 79 13 15.2165773344004 -2.21657733440038 80 16 15.1421402571568 0.857859742843149 81 16 15.6586274506278 0.341372549372198 82 16 15.7632408306316 0.236759169368356 83 15 15.6434137240469 -0.64341372404695 84 15 14.8842323819227 0.115767618077311 85 16 14.1607354722341 1.83926452776585 86 14 14.1555692846506 -0.155569284650592 87 16 15.3674881780279 0.632511821972136 88 16 14.8725888488247 1.12741115117526 89 15 14.5194813902587 0.480518609741335 90 12 13.907972516408 -1.90797251640802 91 17 16.7584943754586 0.241505624541391 92 16 15.8055619194036 0.194438080596368 93 15 15.0531067912421 -0.0531067912420967 94 13 15.0298518503278 -2.02985185032776 95 16 14.7436133365348 1.25638666346519 96 16 15.7882428813297 0.21175711867026 97 16 13.6773839654895 2.32261603451052 98 16 15.7737083756365 0.22629162436346 99 14 14.4297816437613 -0.429781643761329 100 16 16.9922981106499 -0.992298110649857 101 16 14.6766246625527 1.32337533744731 102 20 17.4542184425634 2.54578155743657 103 15 14.2396603727495 0.760339627250478 104 16 14.9598584444853 1.04014155551469 105 13 14.8422042092773 -1.84220420927732 106 17 15.7017299648748 1.29827003512525 107 16 15.7011234587523 0.298876541247731 108 16 14.3586514687943 1.64134853120572 109 12 12.3043422991135 -0.30434229911349 110 16 15.2856808956604 0.71431910433959 111 16 15.9928271492344 0.00717285076563753 112 17 15.0564093690921 1.9435906309079 113 13 14.2811780773625 -1.28117807736248 114 12 14.5798742612205 -2.57987426122045 115 18 16.1614728444387 1.83852715556127 116 14 15.8657328435429 -1.86573284354287 117 14 13.228887828907 0.771112171092987 118 13 14.7929151358429 -1.79291513584291 119 16 15.520384206224 0.479615793776011 120 13 14.4292215835434 -1.42922158354341 121 16 15.3854232676415 0.614576732358463 122 13 15.8212093173508 -2.82120931735076 123 16 16.8545044640026 -0.854504464002574 124 15 15.8437647974654 -0.84376479746541 125 16 16.7849339139009 -0.784933913900918 126 15 14.6587216010757 0.341278398924287 127 17 15.4905839058456 1.50941609415437 128 15 14.0482521120088 0.951747887991231 129 12 14.6858650734517 -2.68586507345171 130 16 13.9402714795457 2.05972852045429 131 10 13.7239532443361 -3.72395324433605 132 16 13.4583321541629 2.54166784583713 133 12 14.1659890224415 -2.16598902244154 134 14 15.5440460090552 -1.54404600905523 135 15 15.0836566962205 -0.0836566962204929 136 13 12.1121127347309 0.887887265269134 137 15 14.5312778069589 0.468722193041143 138 11 13.4989500572246 -2.49895005722465 139 12 13.0064804164844 -1.00648041648441 140 11 13.339956434492 -2.33995643449198 141 16 12.8564999151223 3.14350008487773 142 15 13.6441244258235 1.35587557417654 143 17 16.8413639582837 0.158636041716298 144 16 14.1244038470475 1.87559615295252 145 10 13.266751430131 -3.26675143013095 146 18 15.497545467363 2.50245453263695 147 13 14.9457512386837 -1.94575123868367 148 16 14.843010105307 1.15698989469303 149 13 12.82722767011 0.172772329889988 150 10 12.9004577169405 -2.90045771694049 151 15 15.8784182905414 -0.878418290541449 152 16 13.8248630916881 2.17513690831192 153 16 11.8525810147495 4.1474189852505 154 14 12.3963025182653 1.60369748173469 155 10 12.4816282956809 -2.48162829568091 156 17 16.4393065637934 0.560693436206567 157 13 11.7066858547317 1.29331414526825 158 15 13.900934660471 1.099065339529 159 16 14.5373961332024 1.46260386679759 160 12 12.6989037635456 -0.698903763545609 161 13 12.6931049205989 0.306895079401113 162 13 12.670204114649 0.329795885350951 163 12 12.3813576310274 -0.381357631027421 164 17 16.2130980179022 0.78690198209781 165 15 13.6682202782511 1.33177972174891 166 10 11.6197611469958 -1.61976114699577 167 14 14.3441924705758 -0.344192470575766 168 11 14.1943469919182 -3.19434699191817 169 13 14.7895963339482 -1.78959633394817 170 16 14.3871926838976 1.61280731610237 171 12 10.4815320179531 1.5184679820469 172 16 15.3377881046553 0.66221189534468 173 12 13.8444384221823 -1.84443842218234 174 9 11.3336124343809 -2.3336124343809 175 12 14.9070414350127 -2.90704143501267 176 15 14.4730075744532 0.526992425546806 177 12 12.294327621092 -0.294327621092034 178 12 12.650368444193 -0.650368444193032 179 14 13.7938681954925 0.206131804507504 180 12 13.2889048934373 -1.28890489343725 181 16 15.0068737606415 0.993126239358508 182 11 11.4515058779588 -0.451505877958786 183 19 16.7015767685106 2.29842323148939 184 15 15.1109818809655 -0.110981880965518 185 8 14.596986586261 -6.59698658626104 186 16 14.6989355568994 1.30106444310063 187 17 14.3895807084944 2.61041929150556 188 12 12.3486229107255 -0.348622910725466 189 11 11.4120697144516 -0.4120697144516 190 11 10.4549680631895 0.545031936810458 191 14 14.4364908904417 -0.436490890441723 192 16 15.376427798282 0.623572201717984 193 12 9.72248141934327 2.27751858065673 194 16 14.0886404643777 1.9113595356223 195 13 13.632884513438 -0.632884513437976 196 15 14.9989754108533 0.00102458914674308 197 16 12.9126260121705 3.08737398782949 198 16 14.991943645066 1.00805635493403 199 14 12.4076330969111 1.59236690308889 200 16 14.4603615475735 1.53963845242654 201 16 14.0333200029035 1.96667999709652 202 14 13.2954618359923 0.704538164007681 203 11 13.3129603848872 -2.31296038488724 204 12 14.4949222642595 -2.49492226425949 205 15 12.6778762991469 2.32212370085313 206 15 14.4188365698392 0.581163430160781 207 16 14.5320147838526 1.46798521614738 208 16 14.843125446159 1.15687455384097 209 11 13.5801453187234 -2.58014531872336 210 15 13.8885534096534 1.11144659034664 211 12 14.2037853885328 -2.20378538853275 212 12 15.7224255491506 -3.7224255491506 213 15 14.109079358977 0.89092064102304 214 15 12.0905788116402 2.90942118835982 215 16 14.4647432573063 1.53525674269367 216 14 13.0805138671753 0.919486132824671 217 17 14.5748713248213 2.42512867517871 218 14 13.9049231073215 0.0950768926785438 219 13 11.8321054700474 1.16789452995262 220 15 15.1299096914369 -0.129909691436878 221 13 14.5726876835671 -1.57268768356711 222 14 13.8921489634354 0.107851036564568 223 15 14.1999876889948 0.800012311005213 224 12 13.0554532006112 -1.05545320061118 225 13 12.2689174915128 0.731082508487173 226 8 11.6573695969631 -3.65736959696312 227 14 13.6832791328481 0.316720867151928 228 14 12.8142890945427 1.18571090545735 229 11 12.197890873762 -1.19789087376205 230 12 12.8303898458872 -0.830389845887172 231 13 11.185488738365 1.81451126163496 232 10 13.2189058291037 -3.21890582910368 233 16 11.348787511322 4.65121248867802 234 18 15.7737516733149 2.22624832668511 235 13 13.7266606548843 -0.726660654884331 236 11 13.2215618348084 -2.22156183480842 237 4 10.9938193483991 -6.99381934839915 238 13 14.1796817218455 -1.17968172184545 239 16 14.1367439630088 1.86325603699123 240 10 11.5930618646107 -1.59306186461067 241 12 12.1626452683162 -0.162645268316151 242 12 13.3960154190304 -1.39601541903038 243 10 8.81036730048706 1.18963269951294 244 13 10.9797489991871 2.02025100081286 245 15 13.5802095891207 1.41979041087932 246 12 11.8071329179159 0.192867082084071 247 14 12.745833303401 1.254166696599 248 10 12.3830320431314 -2.38303204313139 249 12 10.7045626835548 1.29543731644515 250 12 11.5222473456141 0.477752654385857 251 11 11.7208297915302 -0.720829791530183 252 10 11.5207040112403 -1.52070401124025 253 12 11.2737442088263 0.726255791173704 254 16 12.7074968396979 3.29250316030215 255 12 13.2078556645355 -1.20785566453552 256 14 13.7197084126368 0.280291587363206 257 16 14.1388849696129 1.86111503038708 258 14 11.5536798517218 2.44632014827823 259 13 14.0549432381567 -1.05494323815668 260 4 9.33309354369939 -5.33309354369939 261 15 13.5531018279656 1.44689817203439 262 11 14.7741198188765 -3.7741198188765 263 11 11.1662281765916 -0.16622817659161 264 14 12.6310833706034 1.36891662939664

 Goldfeld-Quandt test for Heteroskedasticity p-values Alternative Hypothesis breakpoint index greater 2-sided less 11 0.402475229471653 0.804950458943307 0.597524770528347 12 0.799813019552285 0.40037396089543 0.200186980447715 13 0.760826664987248 0.478346670025504 0.239173335012752 14 0.673552621178249 0.652894757643501 0.326447378821751 15 0.618114699975933 0.763770600048135 0.381885300024067 16 0.680833200974805 0.638333598050389 0.319166799025195 17 0.608142628027363 0.783714743945274 0.391857371972637 18 0.857694380421813 0.284611239156375 0.142305619578187 19 0.830980289213743 0.338039421572514 0.169019710786257 20 0.780467388615394 0.439065222769211 0.219532611384606 21 0.716435090676602 0.567129818646795 0.283564909323398 22 0.677924859700132 0.644150280599736 0.322075140299868 23 0.640080623968092 0.719838752063816 0.359919376031908 24 0.608002819411591 0.783994361176818 0.391997180588409 25 0.544602520253454 0.910794959493092 0.455397479746546 26 0.495118873916558 0.990237747833116 0.504881126083442 27 0.435695066526806 0.871390133053611 0.564304933473194 28 0.489428727652135 0.97885745530427 0.510571272347865 29 0.429531193251683 0.859062386503367 0.570468806748317 30 0.439110691341421 0.878221382682843 0.560889308658579 31 0.390777631300561 0.781555262601123 0.609222368699439 32 0.386536250945876 0.773072501891752 0.613463749054124 33 0.367573743538395 0.735147487076789 0.632426256461605 34 0.311946111516885 0.623892223033769 0.688053888483115 35 0.300790075632009 0.601580151264018 0.699209924367991 36 0.399446956221478 0.798893912442955 0.600553043778522 37 0.480233640547256 0.960467281094513 0.519766359452744 38 0.456414493869952 0.912828987739905 0.543585506130048 39 0.504036781673621 0.991926436652758 0.495963218326379 40 0.48466256434735 0.969325128694699 0.51533743565265 41 0.448981538814123 0.897963077628245 0.551018461185877 42 0.419330929144965 0.83866185828993 0.580669070855035 43 0.435488787174071 0.870977574348142 0.564511212825929 44 0.388357018766522 0.776714037533044 0.611642981233478 45 0.349784441710693 0.699568883421385 0.650215558289307 46 0.574490258949639 0.851019482100722 0.425509741050361 47 0.59251378237367 0.81497243525266 0.40748621762633 48 0.554065143583593 0.891869712832815 0.445934856416407 49 0.541344029892326 0.917311940215349 0.458655970107675 50 0.514186099361112 0.971627801277776 0.485813900638888 51 0.469970781504949 0.939941563009899 0.530029218495051 52 0.42842759941914 0.85685519883828 0.57157240058086 53 0.435661290444535 0.87132258088907 0.564338709555465 54 0.406008878029816 0.812017756059633 0.593991121970184 55 0.404277688955221 0.808555377910443 0.595722311044779 56 0.420734697246848 0.841469394493696 0.579265302753152 57 0.380141520587541 0.760283041175082 0.619858479412459 58 0.365628947608552 0.731257895217104 0.634371052391448 59 0.326508005567858 0.653016011135717 0.673491994432141 60 0.353372037232728 0.706744074465455 0.646627962767272 61 0.327220430673944 0.654440861347888 0.672779569326056 62 0.293131978019971 0.586263956039941 0.706868021980029 63 0.259117537401111 0.518235074802222 0.740882462598889 64 0.226514476962294 0.453028953924587 0.773485523037706 65 0.202909488587831 0.405818977175663 0.797090511412169 66 0.193131794747022 0.386263589494044 0.806868205252978 67 0.195831245199528 0.391662490399055 0.804168754800472 68 0.309302990917942 0.618605981835885 0.690697009082058 69 0.422218465126526 0.844436930253052 0.577781534873474 70 0.390197657422739 0.780395314845478 0.609802342577261 71 0.462670997051226 0.925341994102452 0.537329002948774 72 0.427799440490199 0.855598880980399 0.572200559509801 73 0.421024395746235 0.84204879149247 0.578975604253765 74 0.399631793508308 0.799263587016616 0.600368206491692 75 0.363591795361302 0.727183590722605 0.636408204638698 76 0.441561638540613 0.883123277081227 0.558438361459387 77 0.403416720425508 0.806833440851016 0.596583279574492 78 0.382623079741806 0.765246159483612 0.617376920258194 79 0.392051967190841 0.784103934381682 0.607948032809159 80 0.357774230719211 0.715548461438423 0.642225769280789 81 0.326049221426072 0.652098442852144 0.673950778573928 82 0.294041160294514 0.588082320589028 0.705958839705486 83 0.267059646529442 0.534119293058884 0.732940353470558 84 0.237094035748177 0.474188071496353 0.762905964251823 85 0.234219607694559 0.468439215389117 0.765780392305441 86 0.205457331994001 0.410914663988002 0.794542668005999 87 0.182360085247983 0.364720170495966 0.817639914752017 88 0.16866724698052 0.33733449396104 0.83133275301948 89 0.146035404763235 0.292070809526471 0.853964595236764 90 0.141401398675106 0.282802797350213 0.858598601324894 91 0.121453403152487 0.242906806304975 0.878546596847512 92 0.105538335362564 0.211076670725128 0.894461664637436 93 0.0904731503122692 0.180946300624538 0.909526849687731 94 0.0944517045305431 0.188903409061086 0.905548295469457 95 0.0851452882570926 0.170290576514185 0.914854711742907 96 0.07134375971094 0.14268751942188 0.92865624028906 97 0.0765390419752538 0.153078083950508 0.923460958024746 98 0.0639172957190733 0.127834591438147 0.936082704280927 99 0.0532560540094865 0.106512108018973 0.946743945990513 100 0.0471964643477645 0.094392928695529 0.952803535652236 101 0.0418237708668188 0.0836475417336376 0.958176229133181 102 0.0495646640737919 0.0991293281475839 0.950435335926208 103 0.0418159325305976 0.0836318650611953 0.958184067469402 104 0.0371546247444226 0.0743092494888452 0.962845375255577 105 0.0443799645112795 0.0887599290225591 0.95562003548872 106 0.0392467240758438 0.0784934481516876 0.960753275924156 107 0.032101540747539 0.0642030814950781 0.967898459252461 108 0.0306389619503842 0.0612779239007685 0.969361038049616 109 0.0249766509276481 0.0499533018552962 0.975023349072352 110 0.0206802880721736 0.0413605761443472 0.979319711927826 111 0.0165367018611449 0.0330734037222898 0.983463298138855 112 0.0174610968140109 0.0349221936280217 0.982538903185989 113 0.0151868048729542 0.0303736097459083 0.984813195127046 114 0.0203427840188158 0.0406855680376315 0.979657215981184 115 0.0195545789159243 0.0391091578318487 0.980445421084076 116 0.019156582817605 0.03831316563521 0.980843417182395 117 0.0161895415427563 0.0323790830855127 0.983810458457244 118 0.0161428798213067 0.0322857596426135 0.983857120178693 119 0.013111596625575 0.0262231932511501 0.986888403374425 120 0.0118512862501964 0.0237025725003928 0.988148713749804 121 0.00961138913138544 0.0192227782627709 0.990388610868615 122 0.0142976132082616 0.0285952264165232 0.985702386791738 123 0.0119182485986793 0.0238364971973587 0.988081751401321 124 0.0100417231243235 0.020083446248647 0.989958276875677 125 0.00820386346908122 0.0164077269381624 0.991796136530919 126 0.00652402141000281 0.0130480428200056 0.993475978589997 127 0.00592499471708863 0.0118499894341773 0.994075005282911 128 0.00498958031437604 0.00997916062875207 0.995010419685624 129 0.00679676778773384 0.0135935355754677 0.993203232212266 130 0.00737896470885744 0.0147579294177149 0.992621035291143 131 0.0150380035701476 0.0300760071402951 0.984961996429852 132 0.0179020011010297 0.0358040022020595 0.98209799889897 133 0.0190014277786272 0.0380028555572543 0.980998572221373 134 0.0179399512149199 0.0358799024298399 0.98206004878508 135 0.0143280831078875 0.028656166215775 0.985671916892113 136 0.0122309426263336 0.0244618852526671 0.987769057373666 137 0.00990648741823629 0.0198129748364726 0.990093512581764 138 0.0125384210857652 0.0250768421715303 0.987461578914235 139 0.0107618216212586 0.0215236432425171 0.989238178378741 140 0.01290529551809 0.0258105910361799 0.98709470448191 141 0.0201560166619618 0.0403120333239236 0.979843983338038 142 0.0185242814551167 0.0370485629102335 0.981475718544883 143 0.0150205312093496 0.0300410624186993 0.98497946879065 144 0.0157236012587875 0.031447202517575 0.984276398741213 145 0.0266974551191014 0.0533949102382028 0.973302544880899 146 0.032899283931278 0.065798567862556 0.967100716068722 147 0.0347106625346156 0.0694213250692313 0.965289337465384 148 0.0308268157911592 0.0616536315823184 0.969173184208841 149 0.0251694491161804 0.0503388982323608 0.97483055088382 150 0.0347431669180115 0.0694863338360231 0.965256833081989 151 0.0295649645330984 0.0591299290661968 0.970435035466902 152 0.0312118999658585 0.0624237999317169 0.968788100034142 153 0.0614921647203965 0.122984329440793 0.938507835279603 154 0.0592693484311577 0.118538696862315 0.940730651568842 155 0.0668514672949835 0.133702934589967 0.933148532705017 156 0.0568828372036372 0.113765674407274 0.943117162796363 157 0.0507263507797283 0.101452701559457 0.949273649220272 158 0.044306945773758 0.088613891547516 0.955693054226242 159 0.042896370559727 0.0857927411194539 0.957103629440273 160 0.0368289288531118 0.0736578577062236 0.963171071146888 161 0.0301494047603978 0.0602988095207957 0.969850595239602 162 0.0246882511172213 0.0493765022344427 0.975311748882779 163 0.0204556922545629 0.0409113845091258 0.979544307745437 164 0.0174663342278852 0.0349326684557703 0.982533665772115 165 0.0152899712295866 0.0305799424591732 0.984710028770413 166 0.0162158571129126 0.0324317142258253 0.983784142887087 167 0.0129519190795869 0.0259038381591739 0.987048080920413 168 0.0190097943455474 0.0380195886910947 0.980990205654453 169 0.0193145060535548 0.0386290121071096 0.980685493946445 170 0.0178019312531854 0.0356038625063708 0.982198068746815 171 0.016327213558843 0.032654427117686 0.983672786441157 172 0.0131776500985948 0.0263553001971896 0.986822349901405 173 0.0128128065802382 0.0256256131604764 0.987187193419762 174 0.014685951216998 0.0293719024339961 0.985314048783002 175 0.0188929908902678 0.0377859817805356 0.981107009109732 176 0.0151454063778119 0.0302908127556237 0.984854593622188 177 0.0119808719881983 0.0239617439763966 0.988019128011802 178 0.0100781507238407 0.0201563014476815 0.989921849276159 179 0.00783798740929312 0.0156759748185862 0.992162012590707 180 0.00689228384446776 0.0137845676889355 0.993107716155532 181 0.00557929233420557 0.0111585846684111 0.994420707665794 182 0.00430170227341254 0.00860340454682508 0.995698297726587 183 0.00454272486774663 0.00908544973549325 0.995457275132253 184 0.00346340780469989 0.00692681560939978 0.9965365921953 185 0.0945485528934938 0.189097105786988 0.905451447106506 186 0.0837673286341599 0.16753465726832 0.91623267136584 187 0.0937319873577452 0.18746397471549 0.906268012642255 188 0.0791422429758017 0.158284485951603 0.920857757024198 189 0.0705418654748887 0.141083730949777 0.929458134525111 190 0.0596705613214336 0.119341122642867 0.940329438678566 191 0.0516888003813329 0.103377600762666 0.948311199618667 192 0.0430109766894636 0.0860219533789271 0.956989023310536 193 0.0433120762544686 0.0866241525089373 0.956687923745531 194 0.0410696683806269 0.0821393367612539 0.958930331619373 195 0.0357027738981984 0.0714055477963968 0.964297226101802 196 0.0284550140215662 0.0569100280431325 0.971544985978434 197 0.0373222402395986 0.0746444804791971 0.962677759760401 198 0.0305194995352494 0.0610389990704987 0.969480500464751 199 0.0274057819364691 0.0548115638729382 0.972594218063531 200 0.0232765389624402 0.0465530779248805 0.97672346103756 201 0.021311355586638 0.042622711173276 0.978688644413362 202 0.0178165544415185 0.035633108883037 0.982183445558481 203 0.019846910911911 0.0396938218238221 0.980153089088089 204 0.0263675080730805 0.052735016146161 0.973632491926919 205 0.0278237067069451 0.0556474134138902 0.972176293293055 206 0.0217503282101588 0.0435006564203175 0.978249671789841 207 0.019386927081298 0.0387738541625959 0.980613072918702 208 0.0154903722401223 0.0309807444802446 0.984509627759878 209 0.0180778994705206 0.0361557989410412 0.981922100529479 210 0.0149636941222889 0.0299273882445778 0.985036305877711 211 0.0183958392351674 0.0367916784703349 0.981604160764833 212 0.0324717611190893 0.0649435222381785 0.967528238880911 213 0.0253710945551454 0.0507421891102907 0.974628905444855 214 0.0314791169033973 0.0629582338067947 0.968520883096603 215 0.0267612504796724 0.0535225009593448 0.973238749520328 216 0.020729367132908 0.041458734265816 0.979270632867092 217 0.0231370663002714 0.0462741326005427 0.976862933699729 218 0.0196067553481175 0.039213510696235 0.980393244651882 219 0.0182943903919263 0.0365887807838526 0.981705609608074 220 0.0137419038079816 0.0274838076159632 0.986258096192018 221 0.0114025137241171 0.0228050274482341 0.988597486275883 222 0.00831154801890267 0.0166230960378053 0.991688451981097 223 0.00641631381835713 0.0128326276367143 0.993583686181643 224 0.00491691159901389 0.00983382319802777 0.995083088400986 225 0.00343960111377319 0.00687920222754638 0.996560398886227 226 0.00710199123298366 0.0142039824659673 0.992898008767016 227 0.00565156735869488 0.0113031347173898 0.994348432641305 228 0.00412261775956946 0.00824523551913891 0.995877382240431 229 0.00293161983497725 0.0058632396699545 0.997068380165023 230 0.00207599045903002 0.00415198091806004 0.99792400954097 231 0.00226850989205013 0.00453701978410026 0.99773149010795 232 0.00779851916707009 0.0155970383341402 0.99220148083293 233 0.0293698404957628 0.0587396809915256 0.970630159504237 234 0.044950747243972 0.089901494487944 0.955049252756028 235 0.0330914105808944 0.0661828211617888 0.966908589419106 236 0.0271011514226526 0.0542023028453051 0.972898848577347 237 0.238959015911466 0.477918031822932 0.761040984088534 238 0.192949272019248 0.385898544038496 0.807050727980752 239 0.163289925162307 0.326579850324614 0.836710074837693 240 0.13044762066219 0.26089524132438 0.86955237933781 241 0.116817470818194 0.233634941636387 0.883182529181806 242 0.177907984064821 0.355815968129643 0.822092015935179 243 0.150453950204245 0.300907900408489 0.849546049795755 244 0.151452822534993 0.302905645069987 0.848547177465007 245 0.132852249443855 0.26570449888771 0.867147750556145 246 0.116475820843446 0.232951641686893 0.883524179156554 247 0.079256297308871 0.158512594617742 0.920743702691129 248 0.0704290884946231 0.140858176989246 0.929570911505377 249 0.0534977901152151 0.10699558023043 0.946502209884785 250 0.130779813206018 0.261559626412037 0.869220186793981 251 0.107472861596092 0.214945723192185 0.892527138403908 252 0.543978389503581 0.912043220992839 0.456021610496419 253 0.382288727481098 0.764577454962197 0.617711272518902

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.402475229471653 & 0.804950458943307 & 0.597524770528347 \tabularnewline
12 & 0.799813019552285 & 0.40037396089543 & 0.200186980447715 \tabularnewline
13 & 0.760826664987248 & 0.478346670025504 & 0.239173335012752 \tabularnewline
14 & 0.673552621178249 & 0.652894757643501 & 0.326447378821751 \tabularnewline
15 & 0.618114699975933 & 0.763770600048135 & 0.381885300024067 \tabularnewline
16 & 0.680833200974805 & 0.638333598050389 & 0.319166799025195 \tabularnewline
17 & 0.608142628027363 & 0.783714743945274 & 0.391857371972637 \tabularnewline
18 & 0.857694380421813 & 0.284611239156375 & 0.142305619578187 \tabularnewline
19 & 0.830980289213743 & 0.338039421572514 & 0.169019710786257 \tabularnewline
20 & 0.780467388615394 & 0.439065222769211 & 0.219532611384606 \tabularnewline
21 & 0.716435090676602 & 0.567129818646795 & 0.283564909323398 \tabularnewline
22 & 0.677924859700132 & 0.644150280599736 & 0.322075140299868 \tabularnewline
23 & 0.640080623968092 & 0.719838752063816 & 0.359919376031908 \tabularnewline
24 & 0.608002819411591 & 0.783994361176818 & 0.391997180588409 \tabularnewline
25 & 0.544602520253454 & 0.910794959493092 & 0.455397479746546 \tabularnewline
26 & 0.495118873916558 & 0.990237747833116 & 0.504881126083442 \tabularnewline
27 & 0.435695066526806 & 0.871390133053611 & 0.564304933473194 \tabularnewline
28 & 0.489428727652135 & 0.97885745530427 & 0.510571272347865 \tabularnewline
29 & 0.429531193251683 & 0.859062386503367 & 0.570468806748317 \tabularnewline
30 & 0.439110691341421 & 0.878221382682843 & 0.560889308658579 \tabularnewline
31 & 0.390777631300561 & 0.781555262601123 & 0.609222368699439 \tabularnewline
32 & 0.386536250945876 & 0.773072501891752 & 0.613463749054124 \tabularnewline
33 & 0.367573743538395 & 0.735147487076789 & 0.632426256461605 \tabularnewline
34 & 0.311946111516885 & 0.623892223033769 & 0.688053888483115 \tabularnewline
35 & 0.300790075632009 & 0.601580151264018 & 0.699209924367991 \tabularnewline
36 & 0.399446956221478 & 0.798893912442955 & 0.600553043778522 \tabularnewline
37 & 0.480233640547256 & 0.960467281094513 & 0.519766359452744 \tabularnewline
38 & 0.456414493869952 & 0.912828987739905 & 0.543585506130048 \tabularnewline
39 & 0.504036781673621 & 0.991926436652758 & 0.495963218326379 \tabularnewline
40 & 0.48466256434735 & 0.969325128694699 & 0.51533743565265 \tabularnewline
41 & 0.448981538814123 & 0.897963077628245 & 0.551018461185877 \tabularnewline
42 & 0.419330929144965 & 0.83866185828993 & 0.580669070855035 \tabularnewline
43 & 0.435488787174071 & 0.870977574348142 & 0.564511212825929 \tabularnewline
44 & 0.388357018766522 & 0.776714037533044 & 0.611642981233478 \tabularnewline
45 & 0.349784441710693 & 0.699568883421385 & 0.650215558289307 \tabularnewline
46 & 0.574490258949639 & 0.851019482100722 & 0.425509741050361 \tabularnewline
47 & 0.59251378237367 & 0.81497243525266 & 0.40748621762633 \tabularnewline
48 & 0.554065143583593 & 0.891869712832815 & 0.445934856416407 \tabularnewline
49 & 0.541344029892326 & 0.917311940215349 & 0.458655970107675 \tabularnewline
50 & 0.514186099361112 & 0.971627801277776 & 0.485813900638888 \tabularnewline
51 & 0.469970781504949 & 0.939941563009899 & 0.530029218495051 \tabularnewline
52 & 0.42842759941914 & 0.85685519883828 & 0.57157240058086 \tabularnewline
53 & 0.435661290444535 & 0.87132258088907 & 0.564338709555465 \tabularnewline
54 & 0.406008878029816 & 0.812017756059633 & 0.593991121970184 \tabularnewline
55 & 0.404277688955221 & 0.808555377910443 & 0.595722311044779 \tabularnewline
56 & 0.420734697246848 & 0.841469394493696 & 0.579265302753152 \tabularnewline
57 & 0.380141520587541 & 0.760283041175082 & 0.619858479412459 \tabularnewline
58 & 0.365628947608552 & 0.731257895217104 & 0.634371052391448 \tabularnewline
59 & 0.326508005567858 & 0.653016011135717 & 0.673491994432141 \tabularnewline
60 & 0.353372037232728 & 0.706744074465455 & 0.646627962767272 \tabularnewline
61 & 0.327220430673944 & 0.654440861347888 & 0.672779569326056 \tabularnewline
62 & 0.293131978019971 & 0.586263956039941 & 0.706868021980029 \tabularnewline
63 & 0.259117537401111 & 0.518235074802222 & 0.740882462598889 \tabularnewline
64 & 0.226514476962294 & 0.453028953924587 & 0.773485523037706 \tabularnewline
65 & 0.202909488587831 & 0.405818977175663 & 0.797090511412169 \tabularnewline
66 & 0.193131794747022 & 0.386263589494044 & 0.806868205252978 \tabularnewline
67 & 0.195831245199528 & 0.391662490399055 & 0.804168754800472 \tabularnewline
68 & 0.309302990917942 & 0.618605981835885 & 0.690697009082058 \tabularnewline
69 & 0.422218465126526 & 0.844436930253052 & 0.577781534873474 \tabularnewline
70 & 0.390197657422739 & 0.780395314845478 & 0.609802342577261 \tabularnewline
71 & 0.462670997051226 & 0.925341994102452 & 0.537329002948774 \tabularnewline
72 & 0.427799440490199 & 0.855598880980399 & 0.572200559509801 \tabularnewline
73 & 0.421024395746235 & 0.84204879149247 & 0.578975604253765 \tabularnewline
74 & 0.399631793508308 & 0.799263587016616 & 0.600368206491692 \tabularnewline
75 & 0.363591795361302 & 0.727183590722605 & 0.636408204638698 \tabularnewline
76 & 0.441561638540613 & 0.883123277081227 & 0.558438361459387 \tabularnewline
77 & 0.403416720425508 & 0.806833440851016 & 0.596583279574492 \tabularnewline
78 & 0.382623079741806 & 0.765246159483612 & 0.617376920258194 \tabularnewline
79 & 0.392051967190841 & 0.784103934381682 & 0.607948032809159 \tabularnewline
80 & 0.357774230719211 & 0.715548461438423 & 0.642225769280789 \tabularnewline
81 & 0.326049221426072 & 0.652098442852144 & 0.673950778573928 \tabularnewline
82 & 0.294041160294514 & 0.588082320589028 & 0.705958839705486 \tabularnewline
83 & 0.267059646529442 & 0.534119293058884 & 0.732940353470558 \tabularnewline
84 & 0.237094035748177 & 0.474188071496353 & 0.762905964251823 \tabularnewline
85 & 0.234219607694559 & 0.468439215389117 & 0.765780392305441 \tabularnewline
86 & 0.205457331994001 & 0.410914663988002 & 0.794542668005999 \tabularnewline
87 & 0.182360085247983 & 0.364720170495966 & 0.817639914752017 \tabularnewline
88 & 0.16866724698052 & 0.33733449396104 & 0.83133275301948 \tabularnewline
89 & 0.146035404763235 & 0.292070809526471 & 0.853964595236764 \tabularnewline
90 & 0.141401398675106 & 0.282802797350213 & 0.858598601324894 \tabularnewline
91 & 0.121453403152487 & 0.242906806304975 & 0.878546596847512 \tabularnewline
92 & 0.105538335362564 & 0.211076670725128 & 0.894461664637436 \tabularnewline
93 & 0.0904731503122692 & 0.180946300624538 & 0.909526849687731 \tabularnewline
94 & 0.0944517045305431 & 0.188903409061086 & 0.905548295469457 \tabularnewline
95 & 0.0851452882570926 & 0.170290576514185 & 0.914854711742907 \tabularnewline
96 & 0.07134375971094 & 0.14268751942188 & 0.92865624028906 \tabularnewline
97 & 0.0765390419752538 & 0.153078083950508 & 0.923460958024746 \tabularnewline
98 & 0.0639172957190733 & 0.127834591438147 & 0.936082704280927 \tabularnewline
99 & 0.0532560540094865 & 0.106512108018973 & 0.946743945990513 \tabularnewline
100 & 0.0471964643477645 & 0.094392928695529 & 0.952803535652236 \tabularnewline
101 & 0.0418237708668188 & 0.0836475417336376 & 0.958176229133181 \tabularnewline
102 & 0.0495646640737919 & 0.0991293281475839 & 0.950435335926208 \tabularnewline
103 & 0.0418159325305976 & 0.0836318650611953 & 0.958184067469402 \tabularnewline
104 & 0.0371546247444226 & 0.0743092494888452 & 0.962845375255577 \tabularnewline
105 & 0.0443799645112795 & 0.0887599290225591 & 0.95562003548872 \tabularnewline
106 & 0.0392467240758438 & 0.0784934481516876 & 0.960753275924156 \tabularnewline
107 & 0.032101540747539 & 0.0642030814950781 & 0.967898459252461 \tabularnewline
108 & 0.0306389619503842 & 0.0612779239007685 & 0.969361038049616 \tabularnewline
109 & 0.0249766509276481 & 0.0499533018552962 & 0.975023349072352 \tabularnewline
110 & 0.0206802880721736 & 0.0413605761443472 & 0.979319711927826 \tabularnewline
111 & 0.0165367018611449 & 0.0330734037222898 & 0.983463298138855 \tabularnewline
112 & 0.0174610968140109 & 0.0349221936280217 & 0.982538903185989 \tabularnewline
113 & 0.0151868048729542 & 0.0303736097459083 & 0.984813195127046 \tabularnewline
114 & 0.0203427840188158 & 0.0406855680376315 & 0.979657215981184 \tabularnewline
115 & 0.0195545789159243 & 0.0391091578318487 & 0.980445421084076 \tabularnewline
116 & 0.019156582817605 & 0.03831316563521 & 0.980843417182395 \tabularnewline
117 & 0.0161895415427563 & 0.0323790830855127 & 0.983810458457244 \tabularnewline
118 & 0.0161428798213067 & 0.0322857596426135 & 0.983857120178693 \tabularnewline
119 & 0.013111596625575 & 0.0262231932511501 & 0.986888403374425 \tabularnewline
120 & 0.0118512862501964 & 0.0237025725003928 & 0.988148713749804 \tabularnewline
121 & 0.00961138913138544 & 0.0192227782627709 & 0.990388610868615 \tabularnewline
122 & 0.0142976132082616 & 0.0285952264165232 & 0.985702386791738 \tabularnewline
123 & 0.0119182485986793 & 0.0238364971973587 & 0.988081751401321 \tabularnewline
124 & 0.0100417231243235 & 0.020083446248647 & 0.989958276875677 \tabularnewline
125 & 0.00820386346908122 & 0.0164077269381624 & 0.991796136530919 \tabularnewline
126 & 0.00652402141000281 & 0.0130480428200056 & 0.993475978589997 \tabularnewline
127 & 0.00592499471708863 & 0.0118499894341773 & 0.994075005282911 \tabularnewline
128 & 0.00498958031437604 & 0.00997916062875207 & 0.995010419685624 \tabularnewline
129 & 0.00679676778773384 & 0.0135935355754677 & 0.993203232212266 \tabularnewline
130 & 0.00737896470885744 & 0.0147579294177149 & 0.992621035291143 \tabularnewline
131 & 0.0150380035701476 & 0.0300760071402951 & 0.984961996429852 \tabularnewline
132 & 0.0179020011010297 & 0.0358040022020595 & 0.98209799889897 \tabularnewline
133 & 0.0190014277786272 & 0.0380028555572543 & 0.980998572221373 \tabularnewline
134 & 0.0179399512149199 & 0.0358799024298399 & 0.98206004878508 \tabularnewline
135 & 0.0143280831078875 & 0.028656166215775 & 0.985671916892113 \tabularnewline
136 & 0.0122309426263336 & 0.0244618852526671 & 0.987769057373666 \tabularnewline
137 & 0.00990648741823629 & 0.0198129748364726 & 0.990093512581764 \tabularnewline
138 & 0.0125384210857652 & 0.0250768421715303 & 0.987461578914235 \tabularnewline
139 & 0.0107618216212586 & 0.0215236432425171 & 0.989238178378741 \tabularnewline
140 & 0.01290529551809 & 0.0258105910361799 & 0.98709470448191 \tabularnewline
141 & 0.0201560166619618 & 0.0403120333239236 & 0.979843983338038 \tabularnewline
142 & 0.0185242814551167 & 0.0370485629102335 & 0.981475718544883 \tabularnewline
143 & 0.0150205312093496 & 0.0300410624186993 & 0.98497946879065 \tabularnewline
144 & 0.0157236012587875 & 0.031447202517575 & 0.984276398741213 \tabularnewline
145 & 0.0266974551191014 & 0.0533949102382028 & 0.973302544880899 \tabularnewline
146 & 0.032899283931278 & 0.065798567862556 & 0.967100716068722 \tabularnewline
147 & 0.0347106625346156 & 0.0694213250692313 & 0.965289337465384 \tabularnewline
148 & 0.0308268157911592 & 0.0616536315823184 & 0.969173184208841 \tabularnewline
149 & 0.0251694491161804 & 0.0503388982323608 & 0.97483055088382 \tabularnewline
150 & 0.0347431669180115 & 0.0694863338360231 & 0.965256833081989 \tabularnewline
151 & 0.0295649645330984 & 0.0591299290661968 & 0.970435035466902 \tabularnewline
152 & 0.0312118999658585 & 0.0624237999317169 & 0.968788100034142 \tabularnewline
153 & 0.0614921647203965 & 0.122984329440793 & 0.938507835279603 \tabularnewline
154 & 0.0592693484311577 & 0.118538696862315 & 0.940730651568842 \tabularnewline
155 & 0.0668514672949835 & 0.133702934589967 & 0.933148532705017 \tabularnewline
156 & 0.0568828372036372 & 0.113765674407274 & 0.943117162796363 \tabularnewline
157 & 0.0507263507797283 & 0.101452701559457 & 0.949273649220272 \tabularnewline
158 & 0.044306945773758 & 0.088613891547516 & 0.955693054226242 \tabularnewline
159 & 0.042896370559727 & 0.0857927411194539 & 0.957103629440273 \tabularnewline
160 & 0.0368289288531118 & 0.0736578577062236 & 0.963171071146888 \tabularnewline
161 & 0.0301494047603978 & 0.0602988095207957 & 0.969850595239602 \tabularnewline
162 & 0.0246882511172213 & 0.0493765022344427 & 0.975311748882779 \tabularnewline
163 & 0.0204556922545629 & 0.0409113845091258 & 0.979544307745437 \tabularnewline
164 & 0.0174663342278852 & 0.0349326684557703 & 0.982533665772115 \tabularnewline
165 & 0.0152899712295866 & 0.0305799424591732 & 0.984710028770413 \tabularnewline
166 & 0.0162158571129126 & 0.0324317142258253 & 0.983784142887087 \tabularnewline
167 & 0.0129519190795869 & 0.0259038381591739 & 0.987048080920413 \tabularnewline
168 & 0.0190097943455474 & 0.0380195886910947 & 0.980990205654453 \tabularnewline
169 & 0.0193145060535548 & 0.0386290121071096 & 0.980685493946445 \tabularnewline
170 & 0.0178019312531854 & 0.0356038625063708 & 0.982198068746815 \tabularnewline
171 & 0.016327213558843 & 0.032654427117686 & 0.983672786441157 \tabularnewline
172 & 0.0131776500985948 & 0.0263553001971896 & 0.986822349901405 \tabularnewline
173 & 0.0128128065802382 & 0.0256256131604764 & 0.987187193419762 \tabularnewline
174 & 0.014685951216998 & 0.0293719024339961 & 0.985314048783002 \tabularnewline
175 & 0.0188929908902678 & 0.0377859817805356 & 0.981107009109732 \tabularnewline
176 & 0.0151454063778119 & 0.0302908127556237 & 0.984854593622188 \tabularnewline
177 & 0.0119808719881983 & 0.0239617439763966 & 0.988019128011802 \tabularnewline
178 & 0.0100781507238407 & 0.0201563014476815 & 0.989921849276159 \tabularnewline
179 & 0.00783798740929312 & 0.0156759748185862 & 0.992162012590707 \tabularnewline
180 & 0.00689228384446776 & 0.0137845676889355 & 0.993107716155532 \tabularnewline
181 & 0.00557929233420557 & 0.0111585846684111 & 0.994420707665794 \tabularnewline
182 & 0.00430170227341254 & 0.00860340454682508 & 0.995698297726587 \tabularnewline
183 & 0.00454272486774663 & 0.00908544973549325 & 0.995457275132253 \tabularnewline
184 & 0.00346340780469989 & 0.00692681560939978 & 0.9965365921953 \tabularnewline
185 & 0.0945485528934938 & 0.189097105786988 & 0.905451447106506 \tabularnewline
186 & 0.0837673286341599 & 0.16753465726832 & 0.91623267136584 \tabularnewline
187 & 0.0937319873577452 & 0.18746397471549 & 0.906268012642255 \tabularnewline
188 & 0.0791422429758017 & 0.158284485951603 & 0.920857757024198 \tabularnewline
189 & 0.0705418654748887 & 0.141083730949777 & 0.929458134525111 \tabularnewline
190 & 0.0596705613214336 & 0.119341122642867 & 0.940329438678566 \tabularnewline
191 & 0.0516888003813329 & 0.103377600762666 & 0.948311199618667 \tabularnewline
192 & 0.0430109766894636 & 0.0860219533789271 & 0.956989023310536 \tabularnewline
193 & 0.0433120762544686 & 0.0866241525089373 & 0.956687923745531 \tabularnewline
194 & 0.0410696683806269 & 0.0821393367612539 & 0.958930331619373 \tabularnewline
195 & 0.0357027738981984 & 0.0714055477963968 & 0.964297226101802 \tabularnewline
196 & 0.0284550140215662 & 0.0569100280431325 & 0.971544985978434 \tabularnewline
197 & 0.0373222402395986 & 0.0746444804791971 & 0.962677759760401 \tabularnewline
198 & 0.0305194995352494 & 0.0610389990704987 & 0.969480500464751 \tabularnewline
199 & 0.0274057819364691 & 0.0548115638729382 & 0.972594218063531 \tabularnewline
200 & 0.0232765389624402 & 0.0465530779248805 & 0.97672346103756 \tabularnewline
201 & 0.021311355586638 & 0.042622711173276 & 0.978688644413362 \tabularnewline
202 & 0.0178165544415185 & 0.035633108883037 & 0.982183445558481 \tabularnewline
203 & 0.019846910911911 & 0.0396938218238221 & 0.980153089088089 \tabularnewline
204 & 0.0263675080730805 & 0.052735016146161 & 0.973632491926919 \tabularnewline
205 & 0.0278237067069451 & 0.0556474134138902 & 0.972176293293055 \tabularnewline
206 & 0.0217503282101588 & 0.0435006564203175 & 0.978249671789841 \tabularnewline
207 & 0.019386927081298 & 0.0387738541625959 & 0.980613072918702 \tabularnewline
208 & 0.0154903722401223 & 0.0309807444802446 & 0.984509627759878 \tabularnewline
209 & 0.0180778994705206 & 0.0361557989410412 & 0.981922100529479 \tabularnewline
210 & 0.0149636941222889 & 0.0299273882445778 & 0.985036305877711 \tabularnewline
211 & 0.0183958392351674 & 0.0367916784703349 & 0.981604160764833 \tabularnewline
212 & 0.0324717611190893 & 0.0649435222381785 & 0.967528238880911 \tabularnewline
213 & 0.0253710945551454 & 0.0507421891102907 & 0.974628905444855 \tabularnewline
214 & 0.0314791169033973 & 0.0629582338067947 & 0.968520883096603 \tabularnewline
215 & 0.0267612504796724 & 0.0535225009593448 & 0.973238749520328 \tabularnewline
216 & 0.020729367132908 & 0.041458734265816 & 0.979270632867092 \tabularnewline
217 & 0.0231370663002714 & 0.0462741326005427 & 0.976862933699729 \tabularnewline
218 & 0.0196067553481175 & 0.039213510696235 & 0.980393244651882 \tabularnewline
219 & 0.0182943903919263 & 0.0365887807838526 & 0.981705609608074 \tabularnewline
220 & 0.0137419038079816 & 0.0274838076159632 & 0.986258096192018 \tabularnewline
221 & 0.0114025137241171 & 0.0228050274482341 & 0.988597486275883 \tabularnewline
222 & 0.00831154801890267 & 0.0166230960378053 & 0.991688451981097 \tabularnewline
223 & 0.00641631381835713 & 0.0128326276367143 & 0.993583686181643 \tabularnewline
224 & 0.00491691159901389 & 0.00983382319802777 & 0.995083088400986 \tabularnewline
225 & 0.00343960111377319 & 0.00687920222754638 & 0.996560398886227 \tabularnewline
226 & 0.00710199123298366 & 0.0142039824659673 & 0.992898008767016 \tabularnewline
227 & 0.00565156735869488 & 0.0113031347173898 & 0.994348432641305 \tabularnewline
228 & 0.00412261775956946 & 0.00824523551913891 & 0.995877382240431 \tabularnewline
229 & 0.00293161983497725 & 0.0058632396699545 & 0.997068380165023 \tabularnewline
230 & 0.00207599045903002 & 0.00415198091806004 & 0.99792400954097 \tabularnewline
231 & 0.00226850989205013 & 0.00453701978410026 & 0.99773149010795 \tabularnewline
232 & 0.00779851916707009 & 0.0155970383341402 & 0.99220148083293 \tabularnewline
233 & 0.0293698404957628 & 0.0587396809915256 & 0.970630159504237 \tabularnewline
234 & 0.044950747243972 & 0.089901494487944 & 0.955049252756028 \tabularnewline
235 & 0.0330914105808944 & 0.0661828211617888 & 0.966908589419106 \tabularnewline
236 & 0.0271011514226526 & 0.0542023028453051 & 0.972898848577347 \tabularnewline
237 & 0.238959015911466 & 0.477918031822932 & 0.761040984088534 \tabularnewline
238 & 0.192949272019248 & 0.385898544038496 & 0.807050727980752 \tabularnewline
239 & 0.163289925162307 & 0.326579850324614 & 0.836710074837693 \tabularnewline
240 & 0.13044762066219 & 0.26089524132438 & 0.86955237933781 \tabularnewline
241 & 0.116817470818194 & 0.233634941636387 & 0.883182529181806 \tabularnewline
242 & 0.177907984064821 & 0.355815968129643 & 0.822092015935179 \tabularnewline
243 & 0.150453950204245 & 0.300907900408489 & 0.849546049795755 \tabularnewline
244 & 0.151452822534993 & 0.302905645069987 & 0.848547177465007 \tabularnewline
245 & 0.132852249443855 & 0.26570449888771 & 0.867147750556145 \tabularnewline
246 & 0.116475820843446 & 0.232951641686893 & 0.883524179156554 \tabularnewline
247 & 0.079256297308871 & 0.158512594617742 & 0.920743702691129 \tabularnewline
248 & 0.0704290884946231 & 0.140858176989246 & 0.929570911505377 \tabularnewline
249 & 0.0534977901152151 & 0.10699558023043 & 0.946502209884785 \tabularnewline
250 & 0.130779813206018 & 0.261559626412037 & 0.869220186793981 \tabularnewline
251 & 0.107472861596092 & 0.214945723192185 & 0.892527138403908 \tabularnewline
252 & 0.543978389503581 & 0.912043220992839 & 0.456021610496419 \tabularnewline
253 & 0.382288727481098 & 0.764577454962197 & 0.617711272518902 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185721&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]11[/C][C]0.402475229471653[/C][C]0.804950458943307[/C][C]0.597524770528347[/C][/ROW]
[ROW][C]12[/C][C]0.799813019552285[/C][C]0.40037396089543[/C][C]0.200186980447715[/C][/ROW]
[ROW][C]13[/C][C]0.760826664987248[/C][C]0.478346670025504[/C][C]0.239173335012752[/C][/ROW]
[ROW][C]14[/C][C]0.673552621178249[/C][C]0.652894757643501[/C][C]0.326447378821751[/C][/ROW]
[ROW][C]15[/C][C]0.618114699975933[/C][C]0.763770600048135[/C][C]0.381885300024067[/C][/ROW]
[ROW][C]16[/C][C]0.680833200974805[/C][C]0.638333598050389[/C][C]0.319166799025195[/C][/ROW]
[ROW][C]17[/C][C]0.608142628027363[/C][C]0.783714743945274[/C][C]0.391857371972637[/C][/ROW]
[ROW][C]18[/C][C]0.857694380421813[/C][C]0.284611239156375[/C][C]0.142305619578187[/C][/ROW]
[ROW][C]19[/C][C]0.830980289213743[/C][C]0.338039421572514[/C][C]0.169019710786257[/C][/ROW]
[ROW][C]20[/C][C]0.780467388615394[/C][C]0.439065222769211[/C][C]0.219532611384606[/C][/ROW]
[ROW][C]21[/C][C]0.716435090676602[/C][C]0.567129818646795[/C][C]0.283564909323398[/C][/ROW]
[ROW][C]22[/C][C]0.677924859700132[/C][C]0.644150280599736[/C][C]0.322075140299868[/C][/ROW]
[ROW][C]23[/C][C]0.640080623968092[/C][C]0.719838752063816[/C][C]0.359919376031908[/C][/ROW]
[ROW][C]24[/C][C]0.608002819411591[/C][C]0.783994361176818[/C][C]0.391997180588409[/C][/ROW]
[ROW][C]25[/C][C]0.544602520253454[/C][C]0.910794959493092[/C][C]0.455397479746546[/C][/ROW]
[ROW][C]26[/C][C]0.495118873916558[/C][C]0.990237747833116[/C][C]0.504881126083442[/C][/ROW]
[ROW][C]27[/C][C]0.435695066526806[/C][C]0.871390133053611[/C][C]0.564304933473194[/C][/ROW]
[ROW][C]28[/C][C]0.489428727652135[/C][C]0.97885745530427[/C][C]0.510571272347865[/C][/ROW]
[ROW][C]29[/C][C]0.429531193251683[/C][C]0.859062386503367[/C][C]0.570468806748317[/C][/ROW]
[ROW][C]30[/C][C]0.439110691341421[/C][C]0.878221382682843[/C][C]0.560889308658579[/C][/ROW]
[ROW][C]31[/C][C]0.390777631300561[/C][C]0.781555262601123[/C][C]0.609222368699439[/C][/ROW]
[ROW][C]32[/C][C]0.386536250945876[/C][C]0.773072501891752[/C][C]0.613463749054124[/C][/ROW]
[ROW][C]33[/C][C]0.367573743538395[/C][C]0.735147487076789[/C][C]0.632426256461605[/C][/ROW]
[ROW][C]34[/C][C]0.311946111516885[/C][C]0.623892223033769[/C][C]0.688053888483115[/C][/ROW]
[ROW][C]35[/C][C]0.300790075632009[/C][C]0.601580151264018[/C][C]0.699209924367991[/C][/ROW]
[ROW][C]36[/C][C]0.399446956221478[/C][C]0.798893912442955[/C][C]0.600553043778522[/C][/ROW]
[ROW][C]37[/C][C]0.480233640547256[/C][C]0.960467281094513[/C][C]0.519766359452744[/C][/ROW]
[ROW][C]38[/C][C]0.456414493869952[/C][C]0.912828987739905[/C][C]0.543585506130048[/C][/ROW]
[ROW][C]39[/C][C]0.504036781673621[/C][C]0.991926436652758[/C][C]0.495963218326379[/C][/ROW]
[ROW][C]40[/C][C]0.48466256434735[/C][C]0.969325128694699[/C][C]0.51533743565265[/C][/ROW]
[ROW][C]41[/C][C]0.448981538814123[/C][C]0.897963077628245[/C][C]0.551018461185877[/C][/ROW]
[ROW][C]42[/C][C]0.419330929144965[/C][C]0.83866185828993[/C][C]0.580669070855035[/C][/ROW]
[ROW][C]43[/C][C]0.435488787174071[/C][C]0.870977574348142[/C][C]0.564511212825929[/C][/ROW]
[ROW][C]44[/C][C]0.388357018766522[/C][C]0.776714037533044[/C][C]0.611642981233478[/C][/ROW]
[ROW][C]45[/C][C]0.349784441710693[/C][C]0.699568883421385[/C][C]0.650215558289307[/C][/ROW]
[ROW][C]46[/C][C]0.574490258949639[/C][C]0.851019482100722[/C][C]0.425509741050361[/C][/ROW]
[ROW][C]47[/C][C]0.59251378237367[/C][C]0.81497243525266[/C][C]0.40748621762633[/C][/ROW]
[ROW][C]48[/C][C]0.554065143583593[/C][C]0.891869712832815[/C][C]0.445934856416407[/C][/ROW]
[ROW][C]49[/C][C]0.541344029892326[/C][C]0.917311940215349[/C][C]0.458655970107675[/C][/ROW]
[ROW][C]50[/C][C]0.514186099361112[/C][C]0.971627801277776[/C][C]0.485813900638888[/C][/ROW]
[ROW][C]51[/C][C]0.469970781504949[/C][C]0.939941563009899[/C][C]0.530029218495051[/C][/ROW]
[ROW][C]52[/C][C]0.42842759941914[/C][C]0.85685519883828[/C][C]0.57157240058086[/C][/ROW]
[ROW][C]53[/C][C]0.435661290444535[/C][C]0.87132258088907[/C][C]0.564338709555465[/C][/ROW]
[ROW][C]54[/C][C]0.406008878029816[/C][C]0.812017756059633[/C][C]0.593991121970184[/C][/ROW]
[ROW][C]55[/C][C]0.404277688955221[/C][C]0.808555377910443[/C][C]0.595722311044779[/C][/ROW]
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[ROW][C]201[/C][C]0.021311355586638[/C][C]0.042622711173276[/C][C]0.978688644413362[/C][/ROW]
[ROW][C]202[/C][C]0.0178165544415185[/C][C]0.035633108883037[/C][C]0.982183445558481[/C][/ROW]
[ROW][C]203[/C][C]0.019846910911911[/C][C]0.0396938218238221[/C][C]0.980153089088089[/C][/ROW]
[ROW][C]204[/C][C]0.0263675080730805[/C][C]0.052735016146161[/C][C]0.973632491926919[/C][/ROW]
[ROW][C]205[/C][C]0.0278237067069451[/C][C]0.0556474134138902[/C][C]0.972176293293055[/C][/ROW]
[ROW][C]206[/C][C]0.0217503282101588[/C][C]0.0435006564203175[/C][C]0.978249671789841[/C][/ROW]
[ROW][C]207[/C][C]0.019386927081298[/C][C]0.0387738541625959[/C][C]0.980613072918702[/C][/ROW]
[ROW][C]208[/C][C]0.0154903722401223[/C][C]0.0309807444802446[/C][C]0.984509627759878[/C][/ROW]
[ROW][C]209[/C][C]0.0180778994705206[/C][C]0.0361557989410412[/C][C]0.981922100529479[/C][/ROW]
[ROW][C]210[/C][C]0.0149636941222889[/C][C]0.0299273882445778[/C][C]0.985036305877711[/C][/ROW]
[ROW][C]211[/C][C]0.0183958392351674[/C][C]0.0367916784703349[/C][C]0.981604160764833[/C][/ROW]
[ROW][C]212[/C][C]0.0324717611190893[/C][C]0.0649435222381785[/C][C]0.967528238880911[/C][/ROW]
[ROW][C]213[/C][C]0.0253710945551454[/C][C]0.0507421891102907[/C][C]0.974628905444855[/C][/ROW]
[ROW][C]214[/C][C]0.0314791169033973[/C][C]0.0629582338067947[/C][C]0.968520883096603[/C][/ROW]
[ROW][C]215[/C][C]0.0267612504796724[/C][C]0.0535225009593448[/C][C]0.973238749520328[/C][/ROW]
[ROW][C]216[/C][C]0.020729367132908[/C][C]0.041458734265816[/C][C]0.979270632867092[/C][/ROW]
[ROW][C]217[/C][C]0.0231370663002714[/C][C]0.0462741326005427[/C][C]0.976862933699729[/C][/ROW]
[ROW][C]218[/C][C]0.0196067553481175[/C][C]0.039213510696235[/C][C]0.980393244651882[/C][/ROW]
[ROW][C]219[/C][C]0.0182943903919263[/C][C]0.0365887807838526[/C][C]0.981705609608074[/C][/ROW]
[ROW][C]220[/C][C]0.0137419038079816[/C][C]0.0274838076159632[/C][C]0.986258096192018[/C][/ROW]
[ROW][C]221[/C][C]0.0114025137241171[/C][C]0.0228050274482341[/C][C]0.988597486275883[/C][/ROW]
[ROW][C]222[/C][C]0.00831154801890267[/C][C]0.0166230960378053[/C][C]0.991688451981097[/C][/ROW]
[ROW][C]223[/C][C]0.00641631381835713[/C][C]0.0128326276367143[/C][C]0.993583686181643[/C][/ROW]
[ROW][C]224[/C][C]0.00491691159901389[/C][C]0.00983382319802777[/C][C]0.995083088400986[/C][/ROW]
[ROW][C]225[/C][C]0.00343960111377319[/C][C]0.00687920222754638[/C][C]0.996560398886227[/C][/ROW]
[ROW][C]226[/C][C]0.00710199123298366[/C][C]0.0142039824659673[/C][C]0.992898008767016[/C][/ROW]
[ROW][C]227[/C][C]0.00565156735869488[/C][C]0.0113031347173898[/C][C]0.994348432641305[/C][/ROW]
[ROW][C]228[/C][C]0.00412261775956946[/C][C]0.00824523551913891[/C][C]0.995877382240431[/C][/ROW]
[ROW][C]229[/C][C]0.00293161983497725[/C][C]0.0058632396699545[/C][C]0.997068380165023[/C][/ROW]
[ROW][C]230[/C][C]0.00207599045903002[/C][C]0.00415198091806004[/C][C]0.99792400954097[/C][/ROW]
[ROW][C]231[/C][C]0.00226850989205013[/C][C]0.00453701978410026[/C][C]0.99773149010795[/C][/ROW]
[ROW][C]232[/C][C]0.00779851916707009[/C][C]0.0155970383341402[/C][C]0.99220148083293[/C][/ROW]
[ROW][C]233[/C][C]0.0293698404957628[/C][C]0.0587396809915256[/C][C]0.970630159504237[/C][/ROW]
[ROW][C]234[/C][C]0.044950747243972[/C][C]0.089901494487944[/C][C]0.955049252756028[/C][/ROW]
[ROW][C]235[/C][C]0.0330914105808944[/C][C]0.0661828211617888[/C][C]0.966908589419106[/C][/ROW]
[ROW][C]236[/C][C]0.0271011514226526[/C][C]0.0542023028453051[/C][C]0.972898848577347[/C][/ROW]
[ROW][C]237[/C][C]0.238959015911466[/C][C]0.477918031822932[/C][C]0.761040984088534[/C][/ROW]
[ROW][C]238[/C][C]0.192949272019248[/C][C]0.385898544038496[/C][C]0.807050727980752[/C][/ROW]
[ROW][C]239[/C][C]0.163289925162307[/C][C]0.326579850324614[/C][C]0.836710074837693[/C][/ROW]
[ROW][C]240[/C][C]0.13044762066219[/C][C]0.26089524132438[/C][C]0.86955237933781[/C][/ROW]
[ROW][C]241[/C][C]0.116817470818194[/C][C]0.233634941636387[/C][C]0.883182529181806[/C][/ROW]
[ROW][C]242[/C][C]0.177907984064821[/C][C]0.355815968129643[/C][C]0.822092015935179[/C][/ROW]
[ROW][C]243[/C][C]0.150453950204245[/C][C]0.300907900408489[/C][C]0.849546049795755[/C][/ROW]
[ROW][C]244[/C][C]0.151452822534993[/C][C]0.302905645069987[/C][C]0.848547177465007[/C][/ROW]
[ROW][C]245[/C][C]0.132852249443855[/C][C]0.26570449888771[/C][C]0.867147750556145[/C][/ROW]
[ROW][C]246[/C][C]0.116475820843446[/C][C]0.232951641686893[/C][C]0.883524179156554[/C][/ROW]
[ROW][C]247[/C][C]0.079256297308871[/C][C]0.158512594617742[/C][C]0.920743702691129[/C][/ROW]
[ROW][C]248[/C][C]0.0704290884946231[/C][C]0.140858176989246[/C][C]0.929570911505377[/C][/ROW]
[ROW][C]249[/C][C]0.0534977901152151[/C][C]0.10699558023043[/C][C]0.946502209884785[/C][/ROW]
[ROW][C]250[/C][C]0.130779813206018[/C][C]0.261559626412037[/C][C]0.869220186793981[/C][/ROW]
[ROW][C]251[/C][C]0.107472861596092[/C][C]0.214945723192185[/C][C]0.892527138403908[/C][/ROW]
[ROW][C]252[/C][C]0.543978389503581[/C][C]0.912043220992839[/C][C]0.456021610496419[/C][/ROW]
[ROW][C]253[/C][C]0.382288727481098[/C][C]0.764577454962197[/C][C]0.617711272518902[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185721&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185721&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-values Alternative Hypothesis breakpoint index greater 2-sided less 11 0.402475229471653 0.804950458943307 0.597524770528347 12 0.799813019552285 0.40037396089543 0.200186980447715 13 0.760826664987248 0.478346670025504 0.239173335012752 14 0.673552621178249 0.652894757643501 0.326447378821751 15 0.618114699975933 0.763770600048135 0.381885300024067 16 0.680833200974805 0.638333598050389 0.319166799025195 17 0.608142628027363 0.783714743945274 0.391857371972637 18 0.857694380421813 0.284611239156375 0.142305619578187 19 0.830980289213743 0.338039421572514 0.169019710786257 20 0.780467388615394 0.439065222769211 0.219532611384606 21 0.716435090676602 0.567129818646795 0.283564909323398 22 0.677924859700132 0.644150280599736 0.322075140299868 23 0.640080623968092 0.719838752063816 0.359919376031908 24 0.608002819411591 0.783994361176818 0.391997180588409 25 0.544602520253454 0.910794959493092 0.455397479746546 26 0.495118873916558 0.990237747833116 0.504881126083442 27 0.435695066526806 0.871390133053611 0.564304933473194 28 0.489428727652135 0.97885745530427 0.510571272347865 29 0.429531193251683 0.859062386503367 0.570468806748317 30 0.439110691341421 0.878221382682843 0.560889308658579 31 0.390777631300561 0.781555262601123 0.609222368699439 32 0.386536250945876 0.773072501891752 0.613463749054124 33 0.367573743538395 0.735147487076789 0.632426256461605 34 0.311946111516885 0.623892223033769 0.688053888483115 35 0.300790075632009 0.601580151264018 0.699209924367991 36 0.399446956221478 0.798893912442955 0.600553043778522 37 0.480233640547256 0.960467281094513 0.519766359452744 38 0.456414493869952 0.912828987739905 0.543585506130048 39 0.504036781673621 0.991926436652758 0.495963218326379 40 0.48466256434735 0.969325128694699 0.51533743565265 41 0.448981538814123 0.897963077628245 0.551018461185877 42 0.419330929144965 0.83866185828993 0.580669070855035 43 0.435488787174071 0.870977574348142 0.564511212825929 44 0.388357018766522 0.776714037533044 0.611642981233478 45 0.349784441710693 0.699568883421385 0.650215558289307 46 0.574490258949639 0.851019482100722 0.425509741050361 47 0.59251378237367 0.81497243525266 0.40748621762633 48 0.554065143583593 0.891869712832815 0.445934856416407 49 0.541344029892326 0.917311940215349 0.458655970107675 50 0.514186099361112 0.971627801277776 0.485813900638888 51 0.469970781504949 0.939941563009899 0.530029218495051 52 0.42842759941914 0.85685519883828 0.57157240058086 53 0.435661290444535 0.87132258088907 0.564338709555465 54 0.406008878029816 0.812017756059633 0.593991121970184 55 0.404277688955221 0.808555377910443 0.595722311044779 56 0.420734697246848 0.841469394493696 0.579265302753152 57 0.380141520587541 0.760283041175082 0.619858479412459 58 0.365628947608552 0.731257895217104 0.634371052391448 59 0.326508005567858 0.653016011135717 0.673491994432141 60 0.353372037232728 0.706744074465455 0.646627962767272 61 0.327220430673944 0.654440861347888 0.672779569326056 62 0.293131978019971 0.586263956039941 0.706868021980029 63 0.259117537401111 0.518235074802222 0.740882462598889 64 0.226514476962294 0.453028953924587 0.773485523037706 65 0.202909488587831 0.405818977175663 0.797090511412169 66 0.193131794747022 0.386263589494044 0.806868205252978 67 0.195831245199528 0.391662490399055 0.804168754800472 68 0.309302990917942 0.618605981835885 0.690697009082058 69 0.422218465126526 0.844436930253052 0.577781534873474 70 0.390197657422739 0.780395314845478 0.609802342577261 71 0.462670997051226 0.925341994102452 0.537329002948774 72 0.427799440490199 0.855598880980399 0.572200559509801 73 0.421024395746235 0.84204879149247 0.578975604253765 74 0.399631793508308 0.799263587016616 0.600368206491692 75 0.363591795361302 0.727183590722605 0.636408204638698 76 0.441561638540613 0.883123277081227 0.558438361459387 77 0.403416720425508 0.806833440851016 0.596583279574492 78 0.382623079741806 0.765246159483612 0.617376920258194 79 0.392051967190841 0.784103934381682 0.607948032809159 80 0.357774230719211 0.715548461438423 0.642225769280789 81 0.326049221426072 0.652098442852144 0.673950778573928 82 0.294041160294514 0.588082320589028 0.705958839705486 83 0.267059646529442 0.534119293058884 0.732940353470558 84 0.237094035748177 0.474188071496353 0.762905964251823 85 0.234219607694559 0.468439215389117 0.765780392305441 86 0.205457331994001 0.410914663988002 0.794542668005999 87 0.182360085247983 0.364720170495966 0.817639914752017 88 0.16866724698052 0.33733449396104 0.83133275301948 89 0.146035404763235 0.292070809526471 0.853964595236764 90 0.141401398675106 0.282802797350213 0.858598601324894 91 0.121453403152487 0.242906806304975 0.878546596847512 92 0.105538335362564 0.211076670725128 0.894461664637436 93 0.0904731503122692 0.180946300624538 0.909526849687731 94 0.0944517045305431 0.188903409061086 0.905548295469457 95 0.0851452882570926 0.170290576514185 0.914854711742907 96 0.07134375971094 0.14268751942188 0.92865624028906 97 0.0765390419752538 0.153078083950508 0.923460958024746 98 0.0639172957190733 0.127834591438147 0.936082704280927 99 0.0532560540094865 0.106512108018973 0.946743945990513 100 0.0471964643477645 0.094392928695529 0.952803535652236 101 0.0418237708668188 0.0836475417336376 0.958176229133181 102 0.0495646640737919 0.0991293281475839 0.950435335926208 103 0.0418159325305976 0.0836318650611953 0.958184067469402 104 0.0371546247444226 0.0743092494888452 0.962845375255577 105 0.0443799645112795 0.0887599290225591 0.95562003548872 106 0.0392467240758438 0.0784934481516876 0.960753275924156 107 0.032101540747539 0.0642030814950781 0.967898459252461 108 0.0306389619503842 0.0612779239007685 0.969361038049616 109 0.0249766509276481 0.0499533018552962 0.975023349072352 110 0.0206802880721736 0.0413605761443472 0.979319711927826 111 0.0165367018611449 0.0330734037222898 0.983463298138855 112 0.0174610968140109 0.0349221936280217 0.982538903185989 113 0.0151868048729542 0.0303736097459083 0.984813195127046 114 0.0203427840188158 0.0406855680376315 0.979657215981184 115 0.0195545789159243 0.0391091578318487 0.980445421084076 116 0.019156582817605 0.03831316563521 0.980843417182395 117 0.0161895415427563 0.0323790830855127 0.983810458457244 118 0.0161428798213067 0.0322857596426135 0.983857120178693 119 0.013111596625575 0.0262231932511501 0.986888403374425 120 0.0118512862501964 0.0237025725003928 0.988148713749804 121 0.00961138913138544 0.0192227782627709 0.990388610868615 122 0.0142976132082616 0.0285952264165232 0.985702386791738 123 0.0119182485986793 0.0238364971973587 0.988081751401321 124 0.0100417231243235 0.020083446248647 0.989958276875677 125 0.00820386346908122 0.0164077269381624 0.991796136530919 126 0.00652402141000281 0.0130480428200056 0.993475978589997 127 0.00592499471708863 0.0118499894341773 0.994075005282911 128 0.00498958031437604 0.00997916062875207 0.995010419685624 129 0.00679676778773384 0.0135935355754677 0.993203232212266 130 0.00737896470885744 0.0147579294177149 0.992621035291143 131 0.0150380035701476 0.0300760071402951 0.984961996429852 132 0.0179020011010297 0.0358040022020595 0.98209799889897 133 0.0190014277786272 0.0380028555572543 0.980998572221373 134 0.0179399512149199 0.0358799024298399 0.98206004878508 135 0.0143280831078875 0.028656166215775 0.985671916892113 136 0.0122309426263336 0.0244618852526671 0.987769057373666 137 0.00990648741823629 0.0198129748364726 0.990093512581764 138 0.0125384210857652 0.0250768421715303 0.987461578914235 139 0.0107618216212586 0.0215236432425171 0.989238178378741 140 0.01290529551809 0.0258105910361799 0.98709470448191 141 0.0201560166619618 0.0403120333239236 0.979843983338038 142 0.0185242814551167 0.0370485629102335 0.981475718544883 143 0.0150205312093496 0.0300410624186993 0.98497946879065 144 0.0157236012587875 0.031447202517575 0.984276398741213 145 0.0266974551191014 0.0533949102382028 0.973302544880899 146 0.032899283931278 0.065798567862556 0.967100716068722 147 0.0347106625346156 0.0694213250692313 0.965289337465384 148 0.0308268157911592 0.0616536315823184 0.969173184208841 149 0.0251694491161804 0.0503388982323608 0.97483055088382 150 0.0347431669180115 0.0694863338360231 0.965256833081989 151 0.0295649645330984 0.0591299290661968 0.970435035466902 152 0.0312118999658585 0.0624237999317169 0.968788100034142 153 0.0614921647203965 0.122984329440793 0.938507835279603 154 0.0592693484311577 0.118538696862315 0.940730651568842 155 0.0668514672949835 0.133702934589967 0.933148532705017 156 0.0568828372036372 0.113765674407274 0.943117162796363 157 0.0507263507797283 0.101452701559457 0.949273649220272 158 0.044306945773758 0.088613891547516 0.955693054226242 159 0.042896370559727 0.0857927411194539 0.957103629440273 160 0.0368289288531118 0.0736578577062236 0.963171071146888 161 0.0301494047603978 0.0602988095207957 0.969850595239602 162 0.0246882511172213 0.0493765022344427 0.975311748882779 163 0.0204556922545629 0.0409113845091258 0.979544307745437 164 0.0174663342278852 0.0349326684557703 0.982533665772115 165 0.0152899712295866 0.0305799424591732 0.984710028770413 166 0.0162158571129126 0.0324317142258253 0.983784142887087 167 0.0129519190795869 0.0259038381591739 0.987048080920413 168 0.0190097943455474 0.0380195886910947 0.980990205654453 169 0.0193145060535548 0.0386290121071096 0.980685493946445 170 0.0178019312531854 0.0356038625063708 0.982198068746815 171 0.016327213558843 0.032654427117686 0.983672786441157 172 0.0131776500985948 0.0263553001971896 0.986822349901405 173 0.0128128065802382 0.0256256131604764 0.987187193419762 174 0.014685951216998 0.0293719024339961 0.985314048783002 175 0.0188929908902678 0.0377859817805356 0.981107009109732 176 0.0151454063778119 0.0302908127556237 0.984854593622188 177 0.0119808719881983 0.0239617439763966 0.988019128011802 178 0.0100781507238407 0.0201563014476815 0.989921849276159 179 0.00783798740929312 0.0156759748185862 0.992162012590707 180 0.00689228384446776 0.0137845676889355 0.993107716155532 181 0.00557929233420557 0.0111585846684111 0.994420707665794 182 0.00430170227341254 0.00860340454682508 0.995698297726587 183 0.00454272486774663 0.00908544973549325 0.995457275132253 184 0.00346340780469989 0.00692681560939978 0.9965365921953 185 0.0945485528934938 0.189097105786988 0.905451447106506 186 0.0837673286341599 0.16753465726832 0.91623267136584 187 0.0937319873577452 0.18746397471549 0.906268012642255 188 0.0791422429758017 0.158284485951603 0.920857757024198 189 0.0705418654748887 0.141083730949777 0.929458134525111 190 0.0596705613214336 0.119341122642867 0.940329438678566 191 0.0516888003813329 0.103377600762666 0.948311199618667 192 0.0430109766894636 0.0860219533789271 0.956989023310536 193 0.0433120762544686 0.0866241525089373 0.956687923745531 194 0.0410696683806269 0.0821393367612539 0.958930331619373 195 0.0357027738981984 0.0714055477963968 0.964297226101802 196 0.0284550140215662 0.0569100280431325 0.971544985978434 197 0.0373222402395986 0.0746444804791971 0.962677759760401 198 0.0305194995352494 0.0610389990704987 0.969480500464751 199 0.0274057819364691 0.0548115638729382 0.972594218063531 200 0.0232765389624402 0.0465530779248805 0.97672346103756 201 0.021311355586638 0.042622711173276 0.978688644413362 202 0.0178165544415185 0.035633108883037 0.982183445558481 203 0.019846910911911 0.0396938218238221 0.980153089088089 204 0.0263675080730805 0.052735016146161 0.973632491926919 205 0.0278237067069451 0.0556474134138902 0.972176293293055 206 0.0217503282101588 0.0435006564203175 0.978249671789841 207 0.019386927081298 0.0387738541625959 0.980613072918702 208 0.0154903722401223 0.0309807444802446 0.984509627759878 209 0.0180778994705206 0.0361557989410412 0.981922100529479 210 0.0149636941222889 0.0299273882445778 0.985036305877711 211 0.0183958392351674 0.0367916784703349 0.981604160764833 212 0.0324717611190893 0.0649435222381785 0.967528238880911 213 0.0253710945551454 0.0507421891102907 0.974628905444855 214 0.0314791169033973 0.0629582338067947 0.968520883096603 215 0.0267612504796724 0.0535225009593448 0.973238749520328 216 0.020729367132908 0.041458734265816 0.979270632867092 217 0.0231370663002714 0.0462741326005427 0.976862933699729 218 0.0196067553481175 0.039213510696235 0.980393244651882 219 0.0182943903919263 0.0365887807838526 0.981705609608074 220 0.0137419038079816 0.0274838076159632 0.986258096192018 221 0.0114025137241171 0.0228050274482341 0.988597486275883 222 0.00831154801890267 0.0166230960378053 0.991688451981097 223 0.00641631381835713 0.0128326276367143 0.993583686181643 224 0.00491691159901389 0.00983382319802777 0.995083088400986 225 0.00343960111377319 0.00687920222754638 0.996560398886227 226 0.00710199123298366 0.0142039824659673 0.992898008767016 227 0.00565156735869488 0.0113031347173898 0.994348432641305 228 0.00412261775956946 0.00824523551913891 0.995877382240431 229 0.00293161983497725 0.0058632396699545 0.997068380165023 230 0.00207599045903002 0.00415198091806004 0.99792400954097 231 0.00226850989205013 0.00453701978410026 0.99773149010795 232 0.00779851916707009 0.0155970383341402 0.99220148083293 233 0.0293698404957628 0.0587396809915256 0.970630159504237 234 0.044950747243972 0.089901494487944 0.955049252756028 235 0.0330914105808944 0.0661828211617888 0.966908589419106 236 0.0271011514226526 0.0542023028453051 0.972898848577347 237 0.238959015911466 0.477918031822932 0.761040984088534 238 0.192949272019248 0.385898544038496 0.807050727980752 239 0.163289925162307 0.326579850324614 0.836710074837693 240 0.13044762066219 0.26089524132438 0.86955237933781 241 0.116817470818194 0.233634941636387 0.883182529181806 242 0.177907984064821 0.355815968129643 0.822092015935179 243 0.150453950204245 0.300907900408489 0.849546049795755 244 0.151452822534993 0.302905645069987 0.848547177465007 245 0.132852249443855 0.26570449888771 0.867147750556145 246 0.116475820843446 0.232951641686893 0.883524179156554 247 0.079256297308871 0.158512594617742 0.920743702691129 248 0.0704290884946231 0.140858176989246 0.929570911505377 249 0.0534977901152151 0.10699558023043 0.946502209884785 250 0.130779813206018 0.261559626412037 0.869220186793981 251 0.107472861596092 0.214945723192185 0.892527138403908 252 0.543978389503581 0.912043220992839 0.456021610496419 253 0.382288727481098 0.764577454962197 0.617711272518902

 Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity Description # significant tests % significant tests OK/NOK 1% type I error level 10 0.0411522633744856 NOK 5% type I error level 86 0.353909465020576 NOK 10% type I error level 125 0.51440329218107 NOK

\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 & 10 & 0.0411522633744856 & NOK \tabularnewline
5% type I error level & 86 & 0.353909465020576 & NOK \tabularnewline
10% type I error level & 125 & 0.51440329218107 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185721&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]10[/C][C]0.0411522633744856[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]86[/C][C]0.353909465020576[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]125[/C][C]0.51440329218107[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185721&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185721&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 tests OK/NOK 1% type I error level 10 0.0411522633744856 NOK 5% type I error level 86 0.353909465020576 NOK 10% type I error level 125 0.51440329218107 NOK

library(lattice)library(lmtest)n25 <- 25 #minimum number of obs. for Goldfeld-Quandt testpar1 <- 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 <- x1if (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'}xk <- length(x[1,])df <- as.data.frame(x)(mylm <- lm(df))(mysum <- summary(mylm))if (n > n25) {kp3 <- k + 3nmkm3 <- n - k - 3gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))numgqtests <- 0numsignificant1 <- 0numsignificant5 <- 0numsignificant10 <- 0for (mypoint in kp3:nmkm3) {j <- 0numgqtests <- numgqtests + 1for (myalt in c('greater', 'two.sided', 'less')) {j <- j + 1gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value}if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1}gqarr}bitmap(file='test0.png')plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')points(x[,1]-mysum$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)dumdum1 <- dum[2:length(myerror),]dum1z <- as.data.frame(dum1)zplot(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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')}}myeq <- paste(myeq, ' + e[t]')a<-table.row.start(a)a<-table.element(a, myeq)a<-table.row.end(a)a<-table.end(a)table.save(a,file='mytable1.tab')a<-table.start()a<-table.row.start(a)a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'Variable',header=TRUE)a<-table.element(a,'Parameter',header=TRUE)a<-table.element(a,'S.D.',header=TRUE)a<-table.element(a,'T-STATH0: parameter = 0',header=TRUE)a<-table.element(a,'2-tail p-value',header=TRUE)a<-table.element(a,'1-tail p-value',header=TRUE)a<-table.row.end(a)for (i in 1:k){a<-table.row.start(a)a<-table.element(a,rownames(mysum$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$sigma)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a, 'Sum Squared Residuals',1,TRUE)a<-table.element(a, sum(myerror*myerror))a<-table.row.end(a)a<-table.end(a)table.save(a,file='mytable3.tab')a<-table.start()a<-table.row.start(a)a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a, 'Time or Index', 1, TRUE)a<-table.element(a, 'Actuals', 1, TRUE)a<-table.element(a, 'InterpolationForecast', 1, TRUE)a<-table.element(a, 'ResidualsPrediction Error', 1, TRUE)a<-table.row.end(a)for (i in 1:n) {a<-table.row.start(a)a<-table.element(a,i, 1, TRUE)a<-table.element(a,x[i])a<-table.element(a,x[i]-mysum$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')}