## 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 computationMon, 05 Nov 2012 02:53:51 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/05/t1352102055ac6q8x5kdl22gqy.htm/, Retrieved Sat, 02 Mar 2024 00:55:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185964, Retrieved Sat, 02 Mar 2024 00:55:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- R       [Multiple Regression] [WS7] [2012-11-05 07:53:51] [8b7b8016f1e2f8f40e2fad42409dc842] [Current]
- R PD      [Multiple Regression] [Multiple Regressi...] [2012-12-17 22:30:10] [1f7cf67333ab83c872b4a4ac77f4d937]
- R  D        [Multiple Regression] [Multiple Regressi...] [2012-12-17 22:40:46] [1f7cf67333ab83c872b4a4ac77f4d937]
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Dataseries X:
41	38	13	12	14	12	53	32
39	32	16	11	18	11	83	51
30	35	19	15	11	14	66	42
31	33	15	6	12	12	67	41
34	37	14	13	16	21	76	46
35	29	13	10	18	12	78	47
39	31	19	12	14	22	53	37
34	36	15	14	14	11	80	49
36	35	14	12	15	10	74	45
37	38	15	9	15	13	76	47
38	31	16	10	17	10	79	49
36	34	16	12	19	8	54	33
38	35	16	12	10	15	67	42
39	38	16	11	16	14	54	33
33	37	17	15	18	10	87	53
32	33	15	12	14	14	58	36
36	32	15	10	14	14	75	45
38	38	20	12	17	11	88	54
39	38	18	11	14	10	64	41
32	32	16	12	16	13	57	36
32	33	16	11	18	9.5	66	41
31	31	16	12	11	14	68	44
39	38	19	13	14	12	54	33
37	39	16	11	12	14	56	37
39	32	17	12	17	11	86	52
41	32	17	13	9	9	80	47
36	35	16	10	16	11	76	43
33	37	15	14	14	15	69	44
33	33	16	12	15	14	78	45
34	33	14	10	11	13	67	44
31	31	15	12	16	9	80	49
27	32	12	8	13	15	54	33
37	31	14	10	17	10	71	43
34	37	16	12	15	11	84	54
34	30	14	12	14	13	74	42
32	33	10	7	16	8	71	44
29	31	10	9	9	20	63	37
36	33	14	12	15	12	71	43
29	31	16	10	17	10	76	46
35	33	16	10	13	10	69	42
37	32	16	10	15	9	74	45
34	33	14	12	16	14	75	44
38	32	20	15	16	8	54	33
35	33	14	10	12	14	52	31
38	28	14	10	15	11	69	42
37	35	11	12	11	13	68	40
38	39	14	13	15	9	65	43
33	34	15	11	15	11	75	46
36	38	16	11	17	15	74	42
38	32	14	12	13	11	75	45
32	38	16	14	16	10	72	44
32	30	14	10	14	14	67	40
32	33	12	12	11	18	63	37
34	38	16	13	12	14	62	46
32	32	9	5	12	11	63	36
37	35	14	6	15	14.5	76	47
39	34	16	12	16	13	74	45
29	34	16	12	15	9	67	42
37	36	15	11	12	10	73	43
35	34	16	10	12	15	70	43
30	28	12	7	8	20	53	32
38	34	16	12	13	12	77	45
34	35	16	14	11	12	80	48
31	35	14	11	14	14	52	31
34	31	16	12	15	13	54	33
35	37	17	13	10	11	80	49
36	35	18	14	11	17	66	42
30	27	18	11	12	12	73	41
39	40	12	12	15	13	63	38
35	37	16	12	15	14	69	42
38	36	10	8	14	13	67	44
31	38	14	11	16	15	54	33
34	39	18	14	15	13	81	48
38	41	18	14	15	10	69	40
34	27	16	12	13	11	84	50
39	30	17	9	12	19	80	49
37	37	16	13	17	13	70	43
34	31	16	11	13	17	69	44
28	31	13	12	15	13	77	47
37	27	16	12	13	9	54	33
33	36	16	12	15	11	79	46
35	37	16	12	15	9	71	45
37	33	15	12	16	12	73	43
32	34	15	11	15	12	72	44
33	31	16	10	14	13	77	47
38	39	14	9	15	13	75	45
33	34	16	12	14	12	69	42
29	32	16	12	13	15	54	33
33	33	15	12	7	22	70	43
31	36	12	9	17	13	73	46
36	32	17	15	13	15	54	33
35	41	16	12	15	13	77	46
32	28	15	12	14	15	82	48
29	30	13	12	13	12.5	80	47
39	36	16	10	16	11	80	47
37	35	16	13	12	16	69	43
35	31	16	9	14	11	78	46
37	34	16	12	17	11	81	48
32	36	14	10	15	10	76	46
38	36	16	14	17	10	76	45
37	35	16	11	12	16	73	45
36	37	20	15	16	12	85	52
32	28	15	11	11	11	66	42
33	39	16	11	15	16	79	47
40	32	13	12	9	19	68	41
38	35	17	12	16	11	76	47
41	39	16	12	15	16	71	43
36	35	16	11	10	15	54	33
43	42	12	7	10	24	46	30
30	34	16	12	15	14	85	52
31	33	16	14	11	15	74	44
32	41	17	11	13	11	88	55
32	33	13	11	14	15	38	11
37	34	12	10	18	12	76	47
37	32	18	13	16	10	86	53
33	40	14	13	14	14	54	33
34	40	14	8	14	13	67	44
33	35	13	11	14	9	69	42
38	36	16	12	14	15	90	55
33	37	13	11	12	15	54	33
31	27	16	13	14	14	76	46
38	39	13	12	15	11	89	54
37	38	16	14	15	8	76	47
36	31	15	13	15	11	73	45
31	33	16	15	13	11	79	47
39	32	15	10	17	8	90	55
44	39	17	11	17	10	74	44
33	36	15	9	19	11	81	53
35	33	12	11	15	13	72	44
32	33	16	10	13	11	71	42
28	32	10	11	9	20	66	40
40	37	16	8	15	10	77	46
27	30	12	11	15	15	65	40
37	38	14	12	15	12	74	46
32	29	15	12	16	14	85	53
28	22	13	9	11	23	54	33
34	35	15	11	14	14	63	42
30	35	11	10	11	16	54	35
35	34	12	8	15	11	64	40
31	35	11	9	13	12	69	41
32	34	16	8	15	10	54	33
30	37	15	9	16	14	84	51
30	35	17	15	14	12	86	53
31	23	16	11	15	12	77	46
40	31	10	8	16	11	89	55
32	27	18	13	16	12	76	47
36	36	13	12	11	13	60	38
32	31	16	12	12	11	75	46
35	32	13	9	9	19	73	46
38	39	10	7	16	12	85	53
42	37	15	13	13	17	79	47
34	38	16	9	16	9	71	41
35	39	16	6	12	12	72	44
38	34	14	8	9	19	69	43
33	31	10	8	13	18	78	51
36	32	17	15	13	15	54	33
32	37	13	6	14	14	69	43
33	36	15	9	19	11	81	53
34	32	16	11	13	9	84	51
32	38	12	8	12	18	84	50
34	36	13	8	13	16	69	46
27	26	13	10	10	24	66	43
31	26	12	8	14	14	81	47
38	33	17	14	16	20	82	50
34	39	15	10	10	18	72	43
24	30	10	8	11	23	54	33
30	33	14	11	14	12	78	48
26	25	11	12	12	14	74	44
34	38	13	12	9	16	82	50
27	37	16	12	9	18	73	41
37	31	12	5	11	20	55	34
36	37	16	12	16	12	72	44
41	35	12	10	9	12	78	47
29	25	9	7	13	17	59	35
36	28	12	12	16	13	72	44
32	35	15	11	13	9	78	44
37	33	12	8	9	16	68	43
30	30	12	9	12	18	69	41
31	31	14	10	16	10	67	41
38	37	12	9	11	14	74	42
36	36	16	12	14	11	54	33
35	30	11	6	13	9	67	41
31	36	19	15	15	11	70	44
38	32	15	12	14	10	80	48
22	28	8	12	16	11	89	55
32	36	16	12	13	19	76	44
36	34	17	11	14	14	74	43
39	31	12	7	15	12	87	52
28	28	11	7	13	14	54	30
32	36	11	5	11	21	61	39
32	36	14	12	11	13	38	11
38	40	16	12	14	10	75	44
32	33	12	3	15	15	69	42
35	37	16	11	11	16	62	41
32	32	13	10	15	14	72	44
37	38	15	12	12	12	70	44
34	31	16	9	14	19	79	48
33	37	16	12	14	15	87	53
33	33	14	9	8	19	62	37
26	32	16	12	13	13	77	44
30	30	16	12	9	17	69	44
24	30	14	10	15	12	69	40
34	31	11	9	17	11	75	42
34	32	12	12	13	14	54	35
33	34	15	8	15	11	72	43
34	36	15	11	15	13	74	45
35	37	16	11	14	12	85	55
35	36	16	12	16	15	52	31
36	33	11	10	13	14	70	44
34	33	15	10	16	12	84	50
34	33	12	12	9	17	64	40
41	44	12	12	16	11	84	53
32	39	15	11	11	18	87	54
30	32	15	8	10	13	79	49
35	35	16	12	11	17	67	40
28	25	14	10	15	13	65	41
33	35	17	11	17	11	85	52
39	34	14	10	14	12	83	52
36	35	13	8	8	22	61	36
36	39	15	12	15	14	82	52
35	33	13	12	11	12	76	46
38	36	14	10	16	12	58	31
33	32	15	12	10	17	72	44
31	32	12	9	15	9	72	44
34	36	13	9	9	21	38	11
32	36	8	6	16	10	78	46
31	32	14	10	19	11	54	33
33	34	14	9	12	12	63	34
34	33	11	9	8	23	66	42
34	35	12	9	11	13	70	43
34	30	13	6	14	12	71	43
33	38	10	10	9	16	67	44
32	34	16	6	15	9	58	36
41	33	18	14	13	17	72	46
34	32	13	10	16	9	72	44
36	31	11	10	11	14	70	43
37	30	4	6	12	17	76	50
36	27	13	12	13	13	50	33
29	31	16	12	10	11	72	43
37	30	10	7	11	12	72	44
27	32	12	8	12	10	88	53
35	35	12	11	8	19	53	34
28	28	10	3	12	16	58	35
35	33	13	6	12	16	66	40
37	31	15	10	15	14	82	53
29	35	12	8	11	20	69	42
32	35	14	9	13	15	68	43
36	32	10	9	14	23	44	29
19	21	12	8	10	20	56	36
21	20	12	9	12	16	53	30
31	34	11	7	15	14	70	42
33	32	10	7	13	17	78	47
36	34	12	6	13	11	71	44
33	32	16	9	13	13	72	45
37	33	12	10	12	17	68	44
34	33	14	11	12	15	67	43
35	37	16	12	9	21	75	43
31	32	14	8	9	18	62	40
37	34	13	11	15	15	67	41
35	30	4	3	10	8	83	52
27	30	15	11	14	12	64	38
34	38	11	12	15	12	68	41
40	36	11	7	7	22	62	39
29	32	14	9	14	12	72	43

 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 'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 12 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185964&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185964&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185964&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 'Gwilym Jenkins' @ jenkins.wessa.net

 Multiple Linear Regression - Estimated Regression Equation Learning[t] = + 3.77956658273096 + 0.0469437389403787Connected[t] + 0.0419978310517143Separate[t] + 0.607405158110716Software[t] + 0.0986310792586457Happiness[t] -0.0393791266630167Depression[t] + 0.0158660592613708Belonging[t] -0.0194154193631069Belonging_Final[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  3.77956658273096 +  0.0469437389403787Connected[t] +  0.0419978310517143Separate[t] +  0.607405158110716Software[t] +  0.0986310792586457Happiness[t] -0.0393791266630167Depression[t] +  0.0158660592613708Belonging[t] -0.0194154193631069Belonging_Final[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185964&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  3.77956658273096 +  0.0469437389403787Connected[t] +  0.0419978310517143Separate[t] +  0.607405158110716Software[t] +  0.0986310792586457Happiness[t] -0.0393791266630167Depression[t] +  0.0158660592613708Belonging[t] -0.0194154193631069Belonging_Final[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185964&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185964&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] = + 3.77956658273096 + 0.0469437389403787Connected[t] + 0.0419978310517143Separate[t] + 0.607405158110716Software[t] + 0.0986310792586457Happiness[t] -0.0393791266630167Depression[t] + 0.0158660592613708Belonging[t] -0.0194154193631069Belonging_Final[t] + 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) 3.77956658273096 1.917652 1.9709 0.049809 0.024904 Connected 0.0469437389403787 0.034787 1.3495 0.178384 0.089192 Separate 0.0419978310517143 0.035648 1.1781 0.239847 0.119923 Software 0.607405158110716 0.051845 11.7158 0 0 Happiness 0.0986310792586457 0.057963 1.7016 0.09004 0.04502 Depression -0.0393791266630167 0.042557 -0.9253 0.35567 0.177835 Belonging 0.0158660592613708 0.037843 0.4193 0.675376 0.337688 Belonging_Final -0.0194154193631069 0.056444 -0.344 0.731147 0.365573

\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) & 3.77956658273096 & 1.917652 & 1.9709 & 0.049809 & 0.024904 \tabularnewline
Connected & 0.0469437389403787 & 0.034787 & 1.3495 & 0.178384 & 0.089192 \tabularnewline
Separate & 0.0419978310517143 & 0.035648 & 1.1781 & 0.239847 & 0.119923 \tabularnewline
Software & 0.607405158110716 & 0.051845 & 11.7158 & 0 & 0 \tabularnewline
Happiness & 0.0986310792586457 & 0.057963 & 1.7016 & 0.09004 & 0.04502 \tabularnewline
Depression & -0.0393791266630167 & 0.042557 & -0.9253 & 0.35567 & 0.177835 \tabularnewline
Belonging & 0.0158660592613708 & 0.037843 & 0.4193 & 0.675376 & 0.337688 \tabularnewline
Belonging_Final & -0.0194154193631069 & 0.056444 & -0.344 & 0.731147 & 0.365573 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185964&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]3.77956658273096[/C][C]1.917652[/C][C]1.9709[/C][C]0.049809[/C][C]0.024904[/C][/ROW]
[ROW][C]Connected[/C][C]0.0469437389403787[/C][C]0.034787[/C][C]1.3495[/C][C]0.178384[/C][C]0.089192[/C][/ROW]
[ROW][C]Separate[/C][C]0.0419978310517143[/C][C]0.035648[/C][C]1.1781[/C][C]0.239847[/C][C]0.119923[/C][/ROW]
[ROW][C]Software[/C][C]0.607405158110716[/C][C]0.051845[/C][C]11.7158[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0986310792586457[/C][C]0.057963[/C][C]1.7016[/C][C]0.09004[/C][C]0.04502[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0393791266630167[/C][C]0.042557[/C][C]-0.9253[/C][C]0.35567[/C][C]0.177835[/C][/ROW]
[ROW][C]Belonging[/C][C]0.0158660592613708[/C][C]0.037843[/C][C]0.4193[/C][C]0.675376[/C][C]0.337688[/C][/ROW]
[ROW][C]Belonging_Final[/C][C]-0.0194154193631069[/C][C]0.056444[/C][C]-0.344[/C][C]0.731147[/C][C]0.365573[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185964&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185964&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) 3.77956658273096 1.917652 1.9709 0.049809 0.024904 Connected 0.0469437389403787 0.034787 1.3495 0.178384 0.089192 Separate 0.0419978310517143 0.035648 1.1781 0.239847 0.119923 Software 0.607405158110716 0.051845 11.7158 0 0 Happiness 0.0986310792586457 0.057963 1.7016 0.09004 0.04502 Depression -0.0393791266630167 0.042557 -0.9253 0.35567 0.177835 Belonging 0.0158660592613708 0.037843 0.4193 0.675376 0.337688 Belonging_Final -0.0194154193631069 0.056444 -0.344 0.731147 0.365573

 Multiple Linear Regression - Regression Statistics Multiple R 0.653394258005352 R-squared 0.426924056394364 Adjusted R-squared 0.411254011061397 F-TEST (value) 27.244596127377 F-TEST (DF numerator) 7 F-TEST (DF denominator) 256 p-value 0 Multiple Linear Regression - Residual Statistics Residual Standard Deviation 1.88446241278469 Sum Squared Residuals 909.106837810759

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.653394258005352 \tabularnewline
R-squared & 0.426924056394364 \tabularnewline
Adjusted R-squared & 0.411254011061397 \tabularnewline
F-TEST (value) & 27.244596127377 \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 & 1.88446241278469 \tabularnewline
Sum Squared Residuals & 909.106837810759 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185964&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.653394258005352[/C][/ROW]
[ROW][C]R-squared[/C][C]0.426924056394364[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]27.244596127377[/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]1.88446241278469[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]909.106837810759[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185964&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185964&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 0.653394258005352 R-squared 0.426924056394364 Adjusted R-squared 0.411254011061397 F-TEST (value) 27.244596127377 F-TEST (DF numerator) 7 F-TEST (DF denominator) 256 p-value 0 Multiple Linear Regression - Residual Statistics Residual Standard Deviation 1.88446241278469 Sum Squared Residuals 909.106837810759

 Multiple Linear Regression - Actuals, Interpolation, and Residuals Time or Index Actuals InterpolationForecast ResidualsPrediction Error 1 13 15.7169326674783 -2.71693266747828 2 16 15.3046452988162 0.69535470118377 3 19 16.5342266059759 2.46577339402408 4 15 11.2431990710256 3.75680092897442 5 14 15.8896873324328 -1.88968733243282 6 13 14.3424239462714 -1.34242394627141 7 19 14.8381920087898 4.16180799121016 8 15 16.6568417465609 -1.65684174656086 9 14 15.6143966049743 -1.61439660497434 10 15 13.8398822625452 1.16011773745481 11 16 14.5244132197985 1.47558678020148 12 16 15.9613451914131 0.0386548085868939 13 16 14.9654168965065 1.03458310349349 14 16 15.1305945765763 0.869405423423655 15 17 17.7266051778577 -0.726605177857681 16 15 15.0073602272847 -0.00736022728471113 17 15 14.0333112689484 0.966688731051579 18 20 16.0395466632557 3.96045333674426 19 18 15.09418616242 2.90581383758003 20 16 15.1861376221519 0.813862377848066 21 16 15.0015368334676 0.998463166532416 22 16 14.5838648261738 1.41613517382618 23 19 16.2269009876065 2.77309901239348 24 16 14.638251053783 1.36174894621697 25 17 15.8416021360893 1.15839786391069 26 17 15.834485132585 1.16551486741504 27 16 14.5294011985975 1.47059880140251 28 15 16.4169297769606 -1.41692977696059 29 16 15.2955174564432 0.70448254355681 30 14 13.6173944562786 0.382605543721402 31 15 15.367231470103 -0.367231470103047 32 12 12.1577948842104 -0.157794884210414 33 14 14.4670335229458 -0.46703352294582 34 16 15.5490474808797 0.450952519120262 35 14 15.1519977706766 -1.15199777067663 36 10 12.4548067707195 -2.45480677071949 37 10 12.2908025947004 -2.29080259470042 38 14 15.442875350487 -1.44287535048698 39 16 14.1125676496403 1.88743235035968 40 16 14.0503006909743 1.94969930902573 41 16 14.3599156612012 1.64008433879884 42 14 15.4129095162212 -1.41290951622121 43 20 17.4975592437466 2.50244075625335 44 14 13.7379997106144 0.262000289385567 45 14 14.1390257843911 -0.139025784391113 46 11 15.1505593881384 -4.15055938813839 47 14 16.4190959972096 -2.41909599720956 48 15 14.781233912226 0.218766087773982 49 16 15.1915977233103 0.808402276689707 50 14 15.361515363781 -1.36151536378102 51 16 16.8537398386884 -0.853739838688409 52 14 13.731689273808 0.268310726191954 53 12 14.6138653598005 -2.61386535980045 54 16 15.5906899034319 0.409310096568121 55 9 10.7137318072366 -1.7137318072366 56 14 11.8326046050634 2.16739539493663 57 16 15.6937236900134 0.306276309986645 58 16 15.2303555712627 0.769644428737286 59 15 14.8230045585446 0.17699544145538 60 16 13.7932224493505 2.20677755064948 61 12 10.8367279492074 1.1632720507926 62 16 15.4378640177442 0.562135982255831 63 16 16.2989869704333 -0.2989869704333 64 14 14.4388877335844 -0.438887733584355 65 16 15.1500442700275 0.849955729972461 66 17 15.7438538414077 1.25614615859234 67 18 16.0903465015184 1.90965349848158 68 18 14.0764904918967 3.92350950810328 69 12 15.8084608807317 -3.80846088073166 70 16 15.4728479832678 0.527152016732213 71 10 13.0122458267498 -3.01224582674976 72 14 14.7156655383903 -0.7156655383903 73 18 16.8379895442731 1.16201045572691 74 18 17.1928281858955 0.807171814104507 75 16 15.0094686892977 0.990531310702269 76 17 13.0902524925775 3.90974750742254 77 16 16.4072325443378 -0.407232544337833 78 16 14.2122817226739 1.78771827732615 79 13 14.9614853283133 -1.9614853283133 80 16 15.0831385107766 0.916861489223406 81 16 15.5360989694856 0.463901030514354 82 16 15.6432294770163 0.356770522983708 83 15 15.6201822872087 -0.620182287208743 84 15 14.6861437075647 0.313856292435276 85 16 13.8827626275351 2.11723737246488 86 14 13.9517886120021 0.0482113879978756 87 16 15.2330941862993 0.766905813700725 88 16 14.681302994534 1.31869700546596 89 15 14.1033381737051 0.896661826294862 90 12 13.6433035668958 -1.64330356689577 91 17 16.8321246414488 0.167875358551165 92 16 15.7294852307762 0.2705147692238 93 15 14.9057923352787 0.0942076647212599 94 13 14.8364568188003 -1.83645681880029 95 16 14.6980328060634 1.3019671939366 96 16 15.6960780466908 0.303921953309245 97 16 13.4832846792557 2.51671532074433 98 16 15.8300417014576 0.169958298542448 99 14 14.2661258632027 -0.26612586320274 100 16 17.1940865071683 -1.19408650716827 101 16 14.5059011287886 1.49409887121141 102 20 17.5790992836759 2.42090071632414 103 15 14.0226460140409 0.977353985959138 104 16 14.8383762518519 1.16162374814812 105 13 14.7124447739459 -1.71244477394589 106 17 15.7604373152473 1.23956268475275 107 16 15.7720645248471 0.227935475152911 108 16 14.2326042643852 1.76739573561482 109 12 12.0024802659182 -0.0024802659181661 110 16 15.1718385499616 0.828161450038385 111 16 15.9384880334039 0.0615119665961118 112 17 14.8625328282602 2.13746717173979 113 13 14.5286402413612 -1.52864024136123 114 12 14.614568460888 -2.614568460888 115 18 16.2764524443605 1.72354755563947 116 14 15.9504759627416 -1.95047596274164 117 14 12.9924621951951 1.0075378048049 118 13 14.7858242392293 -1.78582423922932 119 16 15.5144579558839 0.485542044116056 120 13 14.3730308681848 -1.37303086818476 121 16 15.4072695332184 0.592730466781632 122 13 15.9001483950515 -2.90014839505154 123 16 17.0738036864139 -1.07380368641385 124 15 15.9985652529538 -0.998565252953809 125 16 16.9217558949015 -0.921755894901496 126 15 14.7501471788131 0.249852821186913 127 17 15.7672102604739 1.23278973952609 128 15 14.0042319951691 0.995768004830927 129 12 14.7455979666711 -2.74559796667113 130 16 13.9018224660129 2.09817753398714 131 10 13.490018922728 -3.49001892272798 132 16 13.4847293488174 2.51527065118258 133 12 14.1318955712898 -2.13189557128976 134 14 15.6891601643807 -1.68916016438072 135 15 15.1349525324793 -0.13495253247934 136 13 11.8798702989229 1.12012970107706 137 15 14.5406759892864 0.459324010713607 138 11 13.3639577865016 -2.3639577865016 139 12 12.9948717800782 -0.99487178007819 140 11 13.2797734052425 -2.27977340524254 141 16 12.8706670328481 3.12933296715189 142 15 13.577797008145 1.42220299185501 143 17 17.0126296693111 -0.0126296693111288 144 16 14.2177232846361 1.78227671536387 145 10 13.3076482519713 -3.30764825197125 146 18 15.710818264639 2.28918173536104 147 13 15.057515844885 -2.05751584488498 148 16 14.9198086004653 1.08019139953472 149 13 12.6377638044032 0.362236195596834 150 10 12.8783257394112 -2.87832573941121 151 15 16.155043271253 -1.15504327125299 152 16 13.9923608515066 2.00763914849345 153 16 11.7040450513149 4.29595494868509 154 14 12.2499675462609 1.75003245373915 155 10 12.3106299805489 -2.3106299805489 156 17 16.8321246414488 0.167875358551165 157 13 11.5695393191606 1.4304606808394 158 15 14.0042319951691 0.995768004830927 159 16 14.6713955204085 1.32860447959149 160 12 12.5736517546432 -0.573651754643204 161 13 12.6006036915371 0.399396308462923 162 13 12.4665513538839 0.533448646116147 163 12 12.3881607885568 -0.38816078855682 164 17 16.573789926877 0.426210073122991 165 15 13.6726004456851 1.32739955431488 166 10 11.4206728334644 -1.42067283346442 167 14 14.4691619974894 -0.469161997489404 168 11 14.2909865799885 -3.29098657998851 169 13 14.8482927619942 -1.84829276199418 170 16 14.4308747459494 1.56912525405059 171 12 10.3653118162962 1.63468818370377 172 16 15.7059483938507 0.294051606149256 173 12 13.9883936528962 -1.98839365289616 174 9 11.3120335908731 -2.31203359087306 175 12 15.2885887877223 -3.2885887877223 176 15 14.7442131156564 0.255786884343578 177 12 12.2632972969964 -0.263297296996437 178 12 12.6879346718068 -0.687934671806849 179 14 14.0621066117256 -0.0621066117256325 180 12 13.476269705029 -1.47626970502905 181 16 15.4340480772343 0.565951922765744 182 11 11.5217489928796 -0.521748992879648 183 19 17.1604632713109 1.83953672868909 184 15 15.5206096079202 -0.520609607920211 185 8 14.7662880903322 -6.76628809033216 186 16 14.9680927196659 1.03190728033406 187 17 14.7476768686274 2.25232313137259 188 12 12.5418032885651 -0.541803288565075 189 11 11.5269675255856 -0.526967525585557 190 11 10.2993224089426 0.700677591057422 191 14 15.0449039081772 -1.04490390817719 192 16 15.8549236374795 0.145076362520501 193 12 9.65799989258033 2.34200010741967 194 16 14.30051325933 1.69948674067003 195 13 13.9159846340245 -0.915984634024546 196 15 15.3686335282855 -0.368633528285513 197 16 13.0983431475463 2.90165685245369 198 16 15.3129697531759 0.687030246824134 199 14 12.4874552007084 1.51254479929164 200 16 14.7705797810563 1.22942021894371 201 16 14.1953897769368 1.80461022306324 202 14 13.5652608133924 0.434739186607563 203 11 13.7622976777595 -2.76229767775954 204 12 14.9165699771727 -2.91656997717273 205 15 12.9696665181991 2.03033348180092 206 15 14.8369644200455 0.163035579954472 207 16 14.847026495686 1.152973504314 208 16 15.4339487103626 0.566051289637426 209 11 13.9167631437977 -2.91676314379774 210 15 14.3031594704995 0.696840529500495 211 12 14.507489606999 -2.50748960699899 212 12 16.2896849694461 -4.28968496944614 213 15 14.3091704811001 0.690829518899894 214 15 12.1674958883062 2.83250411169379 215 16 14.8832893443442 1.1167106556558 216 14 13.4207878308238 0.579212169176227 217 17 15.0626619782301 1.93733802176991 218 14 14.3279169397482 -0.327916939748237 219 13 11.9902889016349 1.00971109836511 220 15 15.6158919610783 -0.615891961078346 221 13 15.0224913327295 -2.02249133272955 222 14 14.5733033465196 -0.573303346519553 223 15 14.5664459129041 0.433554087095921 224 12 13.4585313702885 -1.45853137028853 225 13 12.8042807399044 0.195719260095626 226 8 11.9668684285413 -3.96686842854126 227 14 14.3096831383973 -0.309683138397302 228 14 13.2737435527865 0.726256447213534 229 11 12.3432695732266 -1.34326957322662 230 12 13.1609985574185 -1.16099855741853 231 13 11.4799323515281 1.52006764847187 232 10 13.4650403340904 -3.46504033409045 233 16 11.7004538222459 4.29954617775414 234 18 16.45586637075 1.54413362925002 235 13 14.305398824479 -1.30539882447903 236 11 13.6549207425401 -2.65492074254013 237 4 11.170028137282 -7.170028137282 238 13 14.8152140281387 -1.81521402813867 239 16 14.5923633054321 1.40763669456794 240 10 11.9287261285823 -1.92872612858231 241 12 12.4071970658913 -0.407197065891321 242 12 13.795600381651 -1.79560038165096 243 10 8.88634470078796 1.11365529921204 244 13 11.2770068802368 1.72299311976324 245 15 14.0926273160205 0.907372683979529 246 12 12.0467701780665 -0.0467701780665387 247 14 13.1538828662063 0.846117133793712 248 10 12.8902928435778 -2.89029284357777 249 12 10.8009658204609 1.19903417953907 250 12 11.8839336289646 0.116066371035426 251 11 12.1379198030589 -1.13791980305892 252 10 11.8622634576053 -1.86226345760534 253 12 11.663143781657 0.336856218342988 254 16 13.1782247636368 2.82177523636317 255 12 13.7152063049677 -1.71520630496768 256 14 14.264087859685 -0.264087859685033 257 16 14.6811885572799 1.31881144272009 258 14 11.8239286814975 2.17607131850249 259 13 14.78164098406 -1.78164098406003 260 4 9.48330674262234 -5.48330674262234 261 15 14.174366651485 0.825633348514997 262 11 15.5502096888069 -4.55020968880689 263 11 11.4716452522508 -0.471645252250812 264 14 13.1672908525232 0.832709147476811

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 15.7169326674783 & -2.71693266747828 \tabularnewline
2 & 16 & 15.3046452988162 & 0.69535470118377 \tabularnewline
3 & 19 & 16.5342266059759 & 2.46577339402408 \tabularnewline
4 & 15 & 11.2431990710256 & 3.75680092897442 \tabularnewline
5 & 14 & 15.8896873324328 & -1.88968733243282 \tabularnewline
6 & 13 & 14.3424239462714 & -1.34242394627141 \tabularnewline
7 & 19 & 14.8381920087898 & 4.16180799121016 \tabularnewline
8 & 15 & 16.6568417465609 & -1.65684174656086 \tabularnewline
9 & 14 & 15.6143966049743 & -1.61439660497434 \tabularnewline
10 & 15 & 13.8398822625452 & 1.16011773745481 \tabularnewline
11 & 16 & 14.5244132197985 & 1.47558678020148 \tabularnewline
12 & 16 & 15.9613451914131 & 0.0386548085868939 \tabularnewline
13 & 16 & 14.9654168965065 & 1.03458310349349 \tabularnewline
14 & 16 & 15.1305945765763 & 0.869405423423655 \tabularnewline
15 & 17 & 17.7266051778577 & -0.726605177857681 \tabularnewline
16 & 15 & 15.0073602272847 & -0.00736022728471113 \tabularnewline
17 & 15 & 14.0333112689484 & 0.966688731051579 \tabularnewline
18 & 20 & 16.0395466632557 & 3.96045333674426 \tabularnewline
19 & 18 & 15.09418616242 & 2.90581383758003 \tabularnewline
20 & 16 & 15.1861376221519 & 0.813862377848066 \tabularnewline
21 & 16 & 15.0015368334676 & 0.998463166532416 \tabularnewline
22 & 16 & 14.5838648261738 & 1.41613517382618 \tabularnewline
23 & 19 & 16.2269009876065 & 2.77309901239348 \tabularnewline
24 & 16 & 14.638251053783 & 1.36174894621697 \tabularnewline
25 & 17 & 15.8416021360893 & 1.15839786391069 \tabularnewline
26 & 17 & 15.834485132585 & 1.16551486741504 \tabularnewline
27 & 16 & 14.5294011985975 & 1.47059880140251 \tabularnewline
28 & 15 & 16.4169297769606 & -1.41692977696059 \tabularnewline
29 & 16 & 15.2955174564432 & 0.70448254355681 \tabularnewline
30 & 14 & 13.6173944562786 & 0.382605543721402 \tabularnewline
31 & 15 & 15.367231470103 & -0.367231470103047 \tabularnewline
32 & 12 & 12.1577948842104 & -0.157794884210414 \tabularnewline
33 & 14 & 14.4670335229458 & -0.46703352294582 \tabularnewline
34 & 16 & 15.5490474808797 & 0.450952519120262 \tabularnewline
35 & 14 & 15.1519977706766 & -1.15199777067663 \tabularnewline
36 & 10 & 12.4548067707195 & -2.45480677071949 \tabularnewline
37 & 10 & 12.2908025947004 & -2.29080259470042 \tabularnewline
38 & 14 & 15.442875350487 & -1.44287535048698 \tabularnewline
39 & 16 & 14.1125676496403 & 1.88743235035968 \tabularnewline
40 & 16 & 14.0503006909743 & 1.94969930902573 \tabularnewline
41 & 16 & 14.3599156612012 & 1.64008433879884 \tabularnewline
42 & 14 & 15.4129095162212 & -1.41290951622121 \tabularnewline
43 & 20 & 17.4975592437466 & 2.50244075625335 \tabularnewline
44 & 14 & 13.7379997106144 & 0.262000289385567 \tabularnewline
45 & 14 & 14.1390257843911 & -0.139025784391113 \tabularnewline
46 & 11 & 15.1505593881384 & -4.15055938813839 \tabularnewline
47 & 14 & 16.4190959972096 & -2.41909599720956 \tabularnewline
48 & 15 & 14.781233912226 & 0.218766087773982 \tabularnewline
49 & 16 & 15.1915977233103 & 0.808402276689707 \tabularnewline
50 & 14 & 15.361515363781 & -1.36151536378102 \tabularnewline
51 & 16 & 16.8537398386884 & -0.853739838688409 \tabularnewline
52 & 14 & 13.731689273808 & 0.268310726191954 \tabularnewline
53 & 12 & 14.6138653598005 & -2.61386535980045 \tabularnewline
54 & 16 & 15.5906899034319 & 0.409310096568121 \tabularnewline
55 & 9 & 10.7137318072366 & -1.7137318072366 \tabularnewline
56 & 14 & 11.8326046050634 & 2.16739539493663 \tabularnewline
57 & 16 & 15.6937236900134 & 0.306276309986645 \tabularnewline
58 & 16 & 15.2303555712627 & 0.769644428737286 \tabularnewline
59 & 15 & 14.8230045585446 & 0.17699544145538 \tabularnewline
60 & 16 & 13.7932224493505 & 2.20677755064948 \tabularnewline
61 & 12 & 10.8367279492074 & 1.1632720507926 \tabularnewline
62 & 16 & 15.4378640177442 & 0.562135982255831 \tabularnewline
63 & 16 & 16.2989869704333 & -0.2989869704333 \tabularnewline
64 & 14 & 14.4388877335844 & -0.438887733584355 \tabularnewline
65 & 16 & 15.1500442700275 & 0.849955729972461 \tabularnewline
66 & 17 & 15.7438538414077 & 1.25614615859234 \tabularnewline
67 & 18 & 16.0903465015184 & 1.90965349848158 \tabularnewline
68 & 18 & 14.0764904918967 & 3.92350950810328 \tabularnewline
69 & 12 & 15.8084608807317 & -3.80846088073166 \tabularnewline
70 & 16 & 15.4728479832678 & 0.527152016732213 \tabularnewline
71 & 10 & 13.0122458267498 & -3.01224582674976 \tabularnewline
72 & 14 & 14.7156655383903 & -0.7156655383903 \tabularnewline
73 & 18 & 16.8379895442731 & 1.16201045572691 \tabularnewline
74 & 18 & 17.1928281858955 & 0.807171814104507 \tabularnewline
75 & 16 & 15.0094686892977 & 0.990531310702269 \tabularnewline
76 & 17 & 13.0902524925775 & 3.90974750742254 \tabularnewline
77 & 16 & 16.4072325443378 & -0.407232544337833 \tabularnewline
78 & 16 & 14.2122817226739 & 1.78771827732615 \tabularnewline
79 & 13 & 14.9614853283133 & -1.9614853283133 \tabularnewline
80 & 16 & 15.0831385107766 & 0.916861489223406 \tabularnewline
81 & 16 & 15.5360989694856 & 0.463901030514354 \tabularnewline
82 & 16 & 15.6432294770163 & 0.356770522983708 \tabularnewline
83 & 15 & 15.6201822872087 & -0.620182287208743 \tabularnewline
84 & 15 & 14.6861437075647 & 0.313856292435276 \tabularnewline
85 & 16 & 13.8827626275351 & 2.11723737246488 \tabularnewline
86 & 14 & 13.9517886120021 & 0.0482113879978756 \tabularnewline
87 & 16 & 15.2330941862993 & 0.766905813700725 \tabularnewline
88 & 16 & 14.681302994534 & 1.31869700546596 \tabularnewline
89 & 15 & 14.1033381737051 & 0.896661826294862 \tabularnewline
90 & 12 & 13.6433035668958 & -1.64330356689577 \tabularnewline
91 & 17 & 16.8321246414488 & 0.167875358551165 \tabularnewline
92 & 16 & 15.7294852307762 & 0.2705147692238 \tabularnewline
93 & 15 & 14.9057923352787 & 0.0942076647212599 \tabularnewline
94 & 13 & 14.8364568188003 & -1.83645681880029 \tabularnewline
95 & 16 & 14.6980328060634 & 1.3019671939366 \tabularnewline
96 & 16 & 15.6960780466908 & 0.303921953309245 \tabularnewline
97 & 16 & 13.4832846792557 & 2.51671532074433 \tabularnewline
98 & 16 & 15.8300417014576 & 0.169958298542448 \tabularnewline
99 & 14 & 14.2661258632027 & -0.26612586320274 \tabularnewline
100 & 16 & 17.1940865071683 & -1.19408650716827 \tabularnewline
101 & 16 & 14.5059011287886 & 1.49409887121141 \tabularnewline
102 & 20 & 17.5790992836759 & 2.42090071632414 \tabularnewline
103 & 15 & 14.0226460140409 & 0.977353985959138 \tabularnewline
104 & 16 & 14.8383762518519 & 1.16162374814812 \tabularnewline
105 & 13 & 14.7124447739459 & -1.71244477394589 \tabularnewline
106 & 17 & 15.7604373152473 & 1.23956268475275 \tabularnewline
107 & 16 & 15.7720645248471 & 0.227935475152911 \tabularnewline
108 & 16 & 14.2326042643852 & 1.76739573561482 \tabularnewline
109 & 12 & 12.0024802659182 & -0.0024802659181661 \tabularnewline
110 & 16 & 15.1718385499616 & 0.828161450038385 \tabularnewline
111 & 16 & 15.9384880334039 & 0.0615119665961118 \tabularnewline
112 & 17 & 14.8625328282602 & 2.13746717173979 \tabularnewline
113 & 13 & 14.5286402413612 & -1.52864024136123 \tabularnewline
114 & 12 & 14.614568460888 & -2.614568460888 \tabularnewline
115 & 18 & 16.2764524443605 & 1.72354755563947 \tabularnewline
116 & 14 & 15.9504759627416 & -1.95047596274164 \tabularnewline
117 & 14 & 12.9924621951951 & 1.0075378048049 \tabularnewline
118 & 13 & 14.7858242392293 & -1.78582423922932 \tabularnewline
119 & 16 & 15.5144579558839 & 0.485542044116056 \tabularnewline
120 & 13 & 14.3730308681848 & -1.37303086818476 \tabularnewline
121 & 16 & 15.4072695332184 & 0.592730466781632 \tabularnewline
122 & 13 & 15.9001483950515 & -2.90014839505154 \tabularnewline
123 & 16 & 17.0738036864139 & -1.07380368641385 \tabularnewline
124 & 15 & 15.9985652529538 & -0.998565252953809 \tabularnewline
125 & 16 & 16.9217558949015 & -0.921755894901496 \tabularnewline
126 & 15 & 14.7501471788131 & 0.249852821186913 \tabularnewline
127 & 17 & 15.7672102604739 & 1.23278973952609 \tabularnewline
128 & 15 & 14.0042319951691 & 0.995768004830927 \tabularnewline
129 & 12 & 14.7455979666711 & -2.74559796667113 \tabularnewline
130 & 16 & 13.9018224660129 & 2.09817753398714 \tabularnewline
131 & 10 & 13.490018922728 & -3.49001892272798 \tabularnewline
132 & 16 & 13.4847293488174 & 2.51527065118258 \tabularnewline
133 & 12 & 14.1318955712898 & -2.13189557128976 \tabularnewline
134 & 14 & 15.6891601643807 & -1.68916016438072 \tabularnewline
135 & 15 & 15.1349525324793 & -0.13495253247934 \tabularnewline
136 & 13 & 11.8798702989229 & 1.12012970107706 \tabularnewline
137 & 15 & 14.5406759892864 & 0.459324010713607 \tabularnewline
138 & 11 & 13.3639577865016 & -2.3639577865016 \tabularnewline
139 & 12 & 12.9948717800782 & -0.99487178007819 \tabularnewline
140 & 11 & 13.2797734052425 & -2.27977340524254 \tabularnewline
141 & 16 & 12.8706670328481 & 3.12933296715189 \tabularnewline
142 & 15 & 13.577797008145 & 1.42220299185501 \tabularnewline
143 & 17 & 17.0126296693111 & -0.0126296693111288 \tabularnewline
144 & 16 & 14.2177232846361 & 1.78227671536387 \tabularnewline
145 & 10 & 13.3076482519713 & -3.30764825197125 \tabularnewline
146 & 18 & 15.710818264639 & 2.28918173536104 \tabularnewline
147 & 13 & 15.057515844885 & -2.05751584488498 \tabularnewline
148 & 16 & 14.9198086004653 & 1.08019139953472 \tabularnewline
149 & 13 & 12.6377638044032 & 0.362236195596834 \tabularnewline
150 & 10 & 12.8783257394112 & -2.87832573941121 \tabularnewline
151 & 15 & 16.155043271253 & -1.15504327125299 \tabularnewline
152 & 16 & 13.9923608515066 & 2.00763914849345 \tabularnewline
153 & 16 & 11.7040450513149 & 4.29595494868509 \tabularnewline
154 & 14 & 12.2499675462609 & 1.75003245373915 \tabularnewline
155 & 10 & 12.3106299805489 & -2.3106299805489 \tabularnewline
156 & 17 & 16.8321246414488 & 0.167875358551165 \tabularnewline
157 & 13 & 11.5695393191606 & 1.4304606808394 \tabularnewline
158 & 15 & 14.0042319951691 & 0.995768004830927 \tabularnewline
159 & 16 & 14.6713955204085 & 1.32860447959149 \tabularnewline
160 & 12 & 12.5736517546432 & -0.573651754643204 \tabularnewline
161 & 13 & 12.6006036915371 & 0.399396308462923 \tabularnewline
162 & 13 & 12.4665513538839 & 0.533448646116147 \tabularnewline
163 & 12 & 12.3881607885568 & -0.38816078855682 \tabularnewline
164 & 17 & 16.573789926877 & 0.426210073122991 \tabularnewline
165 & 15 & 13.6726004456851 & 1.32739955431488 \tabularnewline
166 & 10 & 11.4206728334644 & -1.42067283346442 \tabularnewline
167 & 14 & 14.4691619974894 & -0.469161997489404 \tabularnewline
168 & 11 & 14.2909865799885 & -3.29098657998851 \tabularnewline
169 & 13 & 14.8482927619942 & -1.84829276199418 \tabularnewline
170 & 16 & 14.4308747459494 & 1.56912525405059 \tabularnewline
171 & 12 & 10.3653118162962 & 1.63468818370377 \tabularnewline
172 & 16 & 15.7059483938507 & 0.294051606149256 \tabularnewline
173 & 12 & 13.9883936528962 & -1.98839365289616 \tabularnewline
174 & 9 & 11.3120335908731 & -2.31203359087306 \tabularnewline
175 & 12 & 15.2885887877223 & -3.2885887877223 \tabularnewline
176 & 15 & 14.7442131156564 & 0.255786884343578 \tabularnewline
177 & 12 & 12.2632972969964 & -0.263297296996437 \tabularnewline
178 & 12 & 12.6879346718068 & -0.687934671806849 \tabularnewline
179 & 14 & 14.0621066117256 & -0.0621066117256325 \tabularnewline
180 & 12 & 13.476269705029 & -1.47626970502905 \tabularnewline
181 & 16 & 15.4340480772343 & 0.565951922765744 \tabularnewline
182 & 11 & 11.5217489928796 & -0.521748992879648 \tabularnewline
183 & 19 & 17.1604632713109 & 1.83953672868909 \tabularnewline
184 & 15 & 15.5206096079202 & -0.520609607920211 \tabularnewline
185 & 8 & 14.7662880903322 & -6.76628809033216 \tabularnewline
186 & 16 & 14.9680927196659 & 1.03190728033406 \tabularnewline
187 & 17 & 14.7476768686274 & 2.25232313137259 \tabularnewline
188 & 12 & 12.5418032885651 & -0.541803288565075 \tabularnewline
189 & 11 & 11.5269675255856 & -0.526967525585557 \tabularnewline
190 & 11 & 10.2993224089426 & 0.700677591057422 \tabularnewline
191 & 14 & 15.0449039081772 & -1.04490390817719 \tabularnewline
192 & 16 & 15.8549236374795 & 0.145076362520501 \tabularnewline
193 & 12 & 9.65799989258033 & 2.34200010741967 \tabularnewline
194 & 16 & 14.30051325933 & 1.69948674067003 \tabularnewline
195 & 13 & 13.9159846340245 & -0.915984634024546 \tabularnewline
196 & 15 & 15.3686335282855 & -0.368633528285513 \tabularnewline
197 & 16 & 13.0983431475463 & 2.90165685245369 \tabularnewline
198 & 16 & 15.3129697531759 & 0.687030246824134 \tabularnewline
199 & 14 & 12.4874552007084 & 1.51254479929164 \tabularnewline
200 & 16 & 14.7705797810563 & 1.22942021894371 \tabularnewline
201 & 16 & 14.1953897769368 & 1.80461022306324 \tabularnewline
202 & 14 & 13.5652608133924 & 0.434739186607563 \tabularnewline
203 & 11 & 13.7622976777595 & -2.76229767775954 \tabularnewline
204 & 12 & 14.9165699771727 & -2.91656997717273 \tabularnewline
205 & 15 & 12.9696665181991 & 2.03033348180092 \tabularnewline
206 & 15 & 14.8369644200455 & 0.163035579954472 \tabularnewline
207 & 16 & 14.847026495686 & 1.152973504314 \tabularnewline
208 & 16 & 15.4339487103626 & 0.566051289637426 \tabularnewline
209 & 11 & 13.9167631437977 & -2.91676314379774 \tabularnewline
210 & 15 & 14.3031594704995 & 0.696840529500495 \tabularnewline
211 & 12 & 14.507489606999 & -2.50748960699899 \tabularnewline
212 & 12 & 16.2896849694461 & -4.28968496944614 \tabularnewline
213 & 15 & 14.3091704811001 & 0.690829518899894 \tabularnewline
214 & 15 & 12.1674958883062 & 2.83250411169379 \tabularnewline
215 & 16 & 14.8832893443442 & 1.1167106556558 \tabularnewline
216 & 14 & 13.4207878308238 & 0.579212169176227 \tabularnewline
217 & 17 & 15.0626619782301 & 1.93733802176991 \tabularnewline
218 & 14 & 14.3279169397482 & -0.327916939748237 \tabularnewline
219 & 13 & 11.9902889016349 & 1.00971109836511 \tabularnewline
220 & 15 & 15.6158919610783 & -0.615891961078346 \tabularnewline
221 & 13 & 15.0224913327295 & -2.02249133272955 \tabularnewline
222 & 14 & 14.5733033465196 & -0.573303346519553 \tabularnewline
223 & 15 & 14.5664459129041 & 0.433554087095921 \tabularnewline
224 & 12 & 13.4585313702885 & -1.45853137028853 \tabularnewline
225 & 13 & 12.8042807399044 & 0.195719260095626 \tabularnewline
226 & 8 & 11.9668684285413 & -3.96686842854126 \tabularnewline
227 & 14 & 14.3096831383973 & -0.309683138397302 \tabularnewline
228 & 14 & 13.2737435527865 & 0.726256447213534 \tabularnewline
229 & 11 & 12.3432695732266 & -1.34326957322662 \tabularnewline
230 & 12 & 13.1609985574185 & -1.16099855741853 \tabularnewline
231 & 13 & 11.4799323515281 & 1.52006764847187 \tabularnewline
232 & 10 & 13.4650403340904 & -3.46504033409045 \tabularnewline
233 & 16 & 11.7004538222459 & 4.29954617775414 \tabularnewline
234 & 18 & 16.45586637075 & 1.54413362925002 \tabularnewline
235 & 13 & 14.305398824479 & -1.30539882447903 \tabularnewline
236 & 11 & 13.6549207425401 & -2.65492074254013 \tabularnewline
237 & 4 & 11.170028137282 & -7.170028137282 \tabularnewline
238 & 13 & 14.8152140281387 & -1.81521402813867 \tabularnewline
239 & 16 & 14.5923633054321 & 1.40763669456794 \tabularnewline
240 & 10 & 11.9287261285823 & -1.92872612858231 \tabularnewline
241 & 12 & 12.4071970658913 & -0.407197065891321 \tabularnewline
242 & 12 & 13.795600381651 & -1.79560038165096 \tabularnewline
243 & 10 & 8.88634470078796 & 1.11365529921204 \tabularnewline
244 & 13 & 11.2770068802368 & 1.72299311976324 \tabularnewline
245 & 15 & 14.0926273160205 & 0.907372683979529 \tabularnewline
246 & 12 & 12.0467701780665 & -0.0467701780665387 \tabularnewline
247 & 14 & 13.1538828662063 & 0.846117133793712 \tabularnewline
248 & 10 & 12.8902928435778 & -2.89029284357777 \tabularnewline
249 & 12 & 10.8009658204609 & 1.19903417953907 \tabularnewline
250 & 12 & 11.8839336289646 & 0.116066371035426 \tabularnewline
251 & 11 & 12.1379198030589 & -1.13791980305892 \tabularnewline
252 & 10 & 11.8622634576053 & -1.86226345760534 \tabularnewline
253 & 12 & 11.663143781657 & 0.336856218342988 \tabularnewline
254 & 16 & 13.1782247636368 & 2.82177523636317 \tabularnewline
255 & 12 & 13.7152063049677 & -1.71520630496768 \tabularnewline
256 & 14 & 14.264087859685 & -0.264087859685033 \tabularnewline
257 & 16 & 14.6811885572799 & 1.31881144272009 \tabularnewline
258 & 14 & 11.8239286814975 & 2.17607131850249 \tabularnewline
259 & 13 & 14.78164098406 & -1.78164098406003 \tabularnewline
260 & 4 & 9.48330674262234 & -5.48330674262234 \tabularnewline
261 & 15 & 14.174366651485 & 0.825633348514997 \tabularnewline
262 & 11 & 15.5502096888069 & -4.55020968880689 \tabularnewline
263 & 11 & 11.4716452522508 & -0.471645252250812 \tabularnewline
264 & 14 & 13.1672908525232 & 0.832709147476811 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185964&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]15.7169326674783[/C][C]-2.71693266747828[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.3046452988162[/C][C]0.69535470118377[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]16.5342266059759[/C][C]2.46577339402408[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]11.2431990710256[/C][C]3.75680092897442[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]15.8896873324328[/C][C]-1.88968733243282[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.3424239462714[/C][C]-1.34242394627141[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]14.8381920087898[/C][C]4.16180799121016[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]16.6568417465609[/C][C]-1.65684174656086[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]15.6143966049743[/C][C]-1.61439660497434[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]13.8398822625452[/C][C]1.16011773745481[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.5244132197985[/C][C]1.47558678020148[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]15.9613451914131[/C][C]0.0386548085868939[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]14.9654168965065[/C][C]1.03458310349349[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.1305945765763[/C][C]0.869405423423655[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]17.7266051778577[/C][C]-0.726605177857681[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.0073602272847[/C][C]-0.00736022728471113[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.0333112689484[/C][C]0.966688731051579[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.0395466632557[/C][C]3.96045333674426[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.09418616242[/C][C]2.90581383758003[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.1861376221519[/C][C]0.813862377848066[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.0015368334676[/C][C]0.998463166532416[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]14.5838648261738[/C][C]1.41613517382618[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.2269009876065[/C][C]2.77309901239348[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]14.638251053783[/C][C]1.36174894621697[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.8416021360893[/C][C]1.15839786391069[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]15.834485132585[/C][C]1.16551486741504[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.5294011985975[/C][C]1.47059880140251[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.4169297769606[/C][C]-1.41692977696059[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.2955174564432[/C][C]0.70448254355681[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]13.6173944562786[/C][C]0.382605543721402[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.367231470103[/C][C]-0.367231470103047[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.1577948842104[/C][C]-0.157794884210414[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.4670335229458[/C][C]-0.46703352294582[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.5490474808797[/C][C]0.450952519120262[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.1519977706766[/C][C]-1.15199777067663[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.4548067707195[/C][C]-2.45480677071949[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]12.2908025947004[/C][C]-2.29080259470042[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.442875350487[/C][C]-1.44287535048698[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.1125676496403[/C][C]1.88743235035968[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.0503006909743[/C][C]1.94969930902573[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.3599156612012[/C][C]1.64008433879884[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.4129095162212[/C][C]-1.41290951622121[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.4975592437466[/C][C]2.50244075625335[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]13.7379997106144[/C][C]0.262000289385567[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.1390257843911[/C][C]-0.139025784391113[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.1505593881384[/C][C]-4.15055938813839[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.4190959972096[/C][C]-2.41909599720956[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.781233912226[/C][C]0.218766087773982[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.1915977233103[/C][C]0.808402276689707[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.361515363781[/C][C]-1.36151536378102[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]16.8537398386884[/C][C]-0.853739838688409[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.731689273808[/C][C]0.268310726191954[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]14.6138653598005[/C][C]-2.61386535980045[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.5906899034319[/C][C]0.409310096568121[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]10.7137318072366[/C][C]-1.7137318072366[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]11.8326046050634[/C][C]2.16739539493663[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.6937236900134[/C][C]0.306276309986645[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.2303555712627[/C][C]0.769644428737286[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]14.8230045585446[/C][C]0.17699544145538[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]13.7932224493505[/C][C]2.20677755064948[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]10.8367279492074[/C][C]1.1632720507926[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.4378640177442[/C][C]0.562135982255831[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.2989869704333[/C][C]-0.2989869704333[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.4388877335844[/C][C]-0.438887733584355[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.1500442700275[/C][C]0.849955729972461[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]15.7438538414077[/C][C]1.25614615859234[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.0903465015184[/C][C]1.90965349848158[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.0764904918967[/C][C]3.92350950810328[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.8084608807317[/C][C]-3.80846088073166[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.4728479832678[/C][C]0.527152016732213[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.0122458267498[/C][C]-3.01224582674976[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.7156655383903[/C][C]-0.7156655383903[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.8379895442731[/C][C]1.16201045572691[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.1928281858955[/C][C]0.807171814104507[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.0094686892977[/C][C]0.990531310702269[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.0902524925775[/C][C]3.90974750742254[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.4072325443378[/C][C]-0.407232544337833[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.2122817226739[/C][C]1.78771827732615[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]14.9614853283133[/C][C]-1.9614853283133[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.0831385107766[/C][C]0.916861489223406[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.5360989694856[/C][C]0.463901030514354[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.6432294770163[/C][C]0.356770522983708[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.6201822872087[/C][C]-0.620182287208743[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.6861437075647[/C][C]0.313856292435276[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]13.8827626275351[/C][C]2.11723737246488[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]13.9517886120021[/C][C]0.0482113879978756[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.2330941862993[/C][C]0.766905813700725[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.681302994534[/C][C]1.31869700546596[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.1033381737051[/C][C]0.896661826294862[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.6433035668958[/C][C]-1.64330356689577[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.8321246414488[/C][C]0.167875358551165[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.7294852307762[/C][C]0.2705147692238[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]14.9057923352787[/C][C]0.0942076647212599[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.8364568188003[/C][C]-1.83645681880029[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.6980328060634[/C][C]1.3019671939366[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.6960780466908[/C][C]0.303921953309245[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.4832846792557[/C][C]2.51671532074433[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.8300417014576[/C][C]0.169958298542448[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.2661258632027[/C][C]-0.26612586320274[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.1940865071683[/C][C]-1.19408650716827[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.5059011287886[/C][C]1.49409887121141[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.5790992836759[/C][C]2.42090071632414[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.0226460140409[/C][C]0.977353985959138[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]14.8383762518519[/C][C]1.16162374814812[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.7124447739459[/C][C]-1.71244477394589[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.7604373152473[/C][C]1.23956268475275[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.7720645248471[/C][C]0.227935475152911[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.2326042643852[/C][C]1.76739573561482[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.0024802659182[/C][C]-0.0024802659181661[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.1718385499616[/C][C]0.828161450038385[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]15.9384880334039[/C][C]0.0615119665961118[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]14.8625328282602[/C][C]2.13746717173979[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.5286402413612[/C][C]-1.52864024136123[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.614568460888[/C][C]-2.614568460888[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.2764524443605[/C][C]1.72354755563947[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.9504759627416[/C][C]-1.95047596274164[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]12.9924621951951[/C][C]1.0075378048049[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.7858242392293[/C][C]-1.78582423922932[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.5144579558839[/C][C]0.485542044116056[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.3730308681848[/C][C]-1.37303086818476[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.4072695332184[/C][C]0.592730466781632[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.9001483950515[/C][C]-2.90014839505154[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]17.0738036864139[/C][C]-1.07380368641385[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.9985652529538[/C][C]-0.998565252953809[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.9217558949015[/C][C]-0.921755894901496[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.7501471788131[/C][C]0.249852821186913[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.7672102604739[/C][C]1.23278973952609[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]14.0042319951691[/C][C]0.995768004830927[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.7455979666711[/C][C]-2.74559796667113[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.9018224660129[/C][C]2.09817753398714[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.490018922728[/C][C]-3.49001892272798[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4847293488174[/C][C]2.51527065118258[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.1318955712898[/C][C]-2.13189557128976[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.6891601643807[/C][C]-1.68916016438072[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.1349525324793[/C][C]-0.13495253247934[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]11.8798702989229[/C][C]1.12012970107706[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.5406759892864[/C][C]0.459324010713607[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.3639577865016[/C][C]-2.3639577865016[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]12.9948717800782[/C][C]-0.99487178007819[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.2797734052425[/C][C]-2.27977340524254[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8706670328481[/C][C]3.12933296715189[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.577797008145[/C][C]1.42220299185501[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]17.0126296693111[/C][C]-0.0126296693111288[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.2177232846361[/C][C]1.78227671536387[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.3076482519713[/C][C]-3.30764825197125[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.710818264639[/C][C]2.28918173536104[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.057515844885[/C][C]-2.05751584488498[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.9198086004653[/C][C]1.08019139953472[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.6377638044032[/C][C]0.362236195596834[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.8783257394112[/C][C]-2.87832573941121[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]16.155043271253[/C][C]-1.15504327125299[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.9923608515066[/C][C]2.00763914849345[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.7040450513149[/C][C]4.29595494868509[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.2499675462609[/C][C]1.75003245373915[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.3106299805489[/C][C]-2.3106299805489[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.8321246414488[/C][C]0.167875358551165[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.5695393191606[/C][C]1.4304606808394[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]14.0042319951691[/C][C]0.995768004830927[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.6713955204085[/C][C]1.32860447959149[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.5736517546432[/C][C]-0.573651754643204[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.6006036915371[/C][C]0.399396308462923[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.4665513538839[/C][C]0.533448646116147[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.3881607885568[/C][C]-0.38816078855682[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.573789926877[/C][C]0.426210073122991[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.6726004456851[/C][C]1.32739955431488[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.4206728334644[/C][C]-1.42067283346442[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.4691619974894[/C][C]-0.469161997489404[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.2909865799885[/C][C]-3.29098657998851[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.8482927619942[/C][C]-1.84829276199418[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.4308747459494[/C][C]1.56912525405059[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.3653118162962[/C][C]1.63468818370377[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.7059483938507[/C][C]0.294051606149256[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.9883936528962[/C][C]-1.98839365289616[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.3120335908731[/C][C]-2.31203359087306[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]15.2885887877223[/C][C]-3.2885887877223[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.7442131156564[/C][C]0.255786884343578[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.2632972969964[/C][C]-0.263297296996437[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.6879346718068[/C][C]-0.687934671806849[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]14.0621066117256[/C][C]-0.0621066117256325[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.476269705029[/C][C]-1.47626970502905[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]15.4340480772343[/C][C]0.565951922765744[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.5217489928796[/C][C]-0.521748992879648[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]17.1604632713109[/C][C]1.83953672868909[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.5206096079202[/C][C]-0.520609607920211[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.7662880903322[/C][C]-6.76628809033216[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.9680927196659[/C][C]1.03190728033406[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.7476768686274[/C][C]2.25232313137259[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.5418032885651[/C][C]-0.541803288565075[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.5269675255856[/C][C]-0.526967525585557[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.2993224089426[/C][C]0.700677591057422[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]15.0449039081772[/C][C]-1.04490390817719[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.8549236374795[/C][C]0.145076362520501[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.65799989258033[/C][C]2.34200010741967[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.30051325933[/C][C]1.69948674067003[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.9159846340245[/C][C]-0.915984634024546[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]15.3686335282855[/C][C]-0.368633528285513[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]13.0983431475463[/C][C]2.90165685245369[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.3129697531759[/C][C]0.687030246824134[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4874552007084[/C][C]1.51254479929164[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.7705797810563[/C][C]1.22942021894371[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]14.1953897769368[/C][C]1.80461022306324[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.5652608133924[/C][C]0.434739186607563[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.7622976777595[/C][C]-2.76229767775954[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.9165699771727[/C][C]-2.91656997717273[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.9696665181991[/C][C]2.03033348180092[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.8369644200455[/C][C]0.163035579954472[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.847026495686[/C][C]1.152973504314[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]15.4339487103626[/C][C]0.566051289637426[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.9167631437977[/C][C]-2.91676314379774[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]14.3031594704995[/C][C]0.696840529500495[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.507489606999[/C][C]-2.50748960699899[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]16.2896849694461[/C][C]-4.28968496944614[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.3091704811001[/C][C]0.690829518899894[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.1674958883062[/C][C]2.83250411169379[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.8832893443442[/C][C]1.1167106556558[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.4207878308238[/C][C]0.579212169176227[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]15.0626619782301[/C][C]1.93733802176991[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.3279169397482[/C][C]-0.327916939748237[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.9902889016349[/C][C]1.00971109836511[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.6158919610783[/C][C]-0.615891961078346[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]15.0224913327295[/C][C]-2.02249133272955[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]14.5733033465196[/C][C]-0.573303346519553[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.5664459129041[/C][C]0.433554087095921[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.4585313702885[/C][C]-1.45853137028853[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.8042807399044[/C][C]0.195719260095626[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.9668684285413[/C][C]-3.96686842854126[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]14.3096831383973[/C][C]-0.309683138397302[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]13.2737435527865[/C][C]0.726256447213534[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.3432695732266[/C][C]-1.34326957322662[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]13.1609985574185[/C][C]-1.16099855741853[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.4799323515281[/C][C]1.52006764847187[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.4650403340904[/C][C]-3.46504033409045[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.7004538222459[/C][C]4.29954617775414[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]16.45586637075[/C][C]1.54413362925002[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]14.305398824479[/C][C]-1.30539882447903[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.6549207425401[/C][C]-2.65492074254013[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]11.170028137282[/C][C]-7.170028137282[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.8152140281387[/C][C]-1.81521402813867[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.5923633054321[/C][C]1.40763669456794[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.9287261285823[/C][C]-1.92872612858231[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.4071970658913[/C][C]-0.407197065891321[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.795600381651[/C][C]-1.79560038165096[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.88634470078796[/C][C]1.11365529921204[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]11.2770068802368[/C][C]1.72299311976324[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]14.0926273160205[/C][C]0.907372683979529[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]12.0467701780665[/C][C]-0.0467701780665387[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]13.1538828662063[/C][C]0.846117133793712[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.8902928435778[/C][C]-2.89029284357777[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.8009658204609[/C][C]1.19903417953907[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.8839336289646[/C][C]0.116066371035426[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]12.1379198030589[/C][C]-1.13791980305892[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.8622634576053[/C][C]-1.86226345760534[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.663143781657[/C][C]0.336856218342988[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]13.1782247636368[/C][C]2.82177523636317[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.7152063049677[/C][C]-1.71520630496768[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]14.264087859685[/C][C]-0.264087859685033[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.6811885572799[/C][C]1.31881144272009[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.8239286814975[/C][C]2.17607131850249[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.78164098406[/C][C]-1.78164098406003[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.48330674262234[/C][C]-5.48330674262234[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]14.174366651485[/C][C]0.825633348514997[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]15.5502096888069[/C][C]-4.55020968880689[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.4716452522508[/C][C]-0.471645252250812[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.1672908525232[/C][C]0.832709147476811[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185964&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185964&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 15.7169326674783 -2.71693266747828 2 16 15.3046452988162 0.69535470118377 3 19 16.5342266059759 2.46577339402408 4 15 11.2431990710256 3.75680092897442 5 14 15.8896873324328 -1.88968733243282 6 13 14.3424239462714 -1.34242394627141 7 19 14.8381920087898 4.16180799121016 8 15 16.6568417465609 -1.65684174656086 9 14 15.6143966049743 -1.61439660497434 10 15 13.8398822625452 1.16011773745481 11 16 14.5244132197985 1.47558678020148 12 16 15.9613451914131 0.0386548085868939 13 16 14.9654168965065 1.03458310349349 14 16 15.1305945765763 0.869405423423655 15 17 17.7266051778577 -0.726605177857681 16 15 15.0073602272847 -0.00736022728471113 17 15 14.0333112689484 0.966688731051579 18 20 16.0395466632557 3.96045333674426 19 18 15.09418616242 2.90581383758003 20 16 15.1861376221519 0.813862377848066 21 16 15.0015368334676 0.998463166532416 22 16 14.5838648261738 1.41613517382618 23 19 16.2269009876065 2.77309901239348 24 16 14.638251053783 1.36174894621697 25 17 15.8416021360893 1.15839786391069 26 17 15.834485132585 1.16551486741504 27 16 14.5294011985975 1.47059880140251 28 15 16.4169297769606 -1.41692977696059 29 16 15.2955174564432 0.70448254355681 30 14 13.6173944562786 0.382605543721402 31 15 15.367231470103 -0.367231470103047 32 12 12.1577948842104 -0.157794884210414 33 14 14.4670335229458 -0.46703352294582 34 16 15.5490474808797 0.450952519120262 35 14 15.1519977706766 -1.15199777067663 36 10 12.4548067707195 -2.45480677071949 37 10 12.2908025947004 -2.29080259470042 38 14 15.442875350487 -1.44287535048698 39 16 14.1125676496403 1.88743235035968 40 16 14.0503006909743 1.94969930902573 41 16 14.3599156612012 1.64008433879884 42 14 15.4129095162212 -1.41290951622121 43 20 17.4975592437466 2.50244075625335 44 14 13.7379997106144 0.262000289385567 45 14 14.1390257843911 -0.139025784391113 46 11 15.1505593881384 -4.15055938813839 47 14 16.4190959972096 -2.41909599720956 48 15 14.781233912226 0.218766087773982 49 16 15.1915977233103 0.808402276689707 50 14 15.361515363781 -1.36151536378102 51 16 16.8537398386884 -0.853739838688409 52 14 13.731689273808 0.268310726191954 53 12 14.6138653598005 -2.61386535980045 54 16 15.5906899034319 0.409310096568121 55 9 10.7137318072366 -1.7137318072366 56 14 11.8326046050634 2.16739539493663 57 16 15.6937236900134 0.306276309986645 58 16 15.2303555712627 0.769644428737286 59 15 14.8230045585446 0.17699544145538 60 16 13.7932224493505 2.20677755064948 61 12 10.8367279492074 1.1632720507926 62 16 15.4378640177442 0.562135982255831 63 16 16.2989869704333 -0.2989869704333 64 14 14.4388877335844 -0.438887733584355 65 16 15.1500442700275 0.849955729972461 66 17 15.7438538414077 1.25614615859234 67 18 16.0903465015184 1.90965349848158 68 18 14.0764904918967 3.92350950810328 69 12 15.8084608807317 -3.80846088073166 70 16 15.4728479832678 0.527152016732213 71 10 13.0122458267498 -3.01224582674976 72 14 14.7156655383903 -0.7156655383903 73 18 16.8379895442731 1.16201045572691 74 18 17.1928281858955 0.807171814104507 75 16 15.0094686892977 0.990531310702269 76 17 13.0902524925775 3.90974750742254 77 16 16.4072325443378 -0.407232544337833 78 16 14.2122817226739 1.78771827732615 79 13 14.9614853283133 -1.9614853283133 80 16 15.0831385107766 0.916861489223406 81 16 15.5360989694856 0.463901030514354 82 16 15.6432294770163 0.356770522983708 83 15 15.6201822872087 -0.620182287208743 84 15 14.6861437075647 0.313856292435276 85 16 13.8827626275351 2.11723737246488 86 14 13.9517886120021 0.0482113879978756 87 16 15.2330941862993 0.766905813700725 88 16 14.681302994534 1.31869700546596 89 15 14.1033381737051 0.896661826294862 90 12 13.6433035668958 -1.64330356689577 91 17 16.8321246414488 0.167875358551165 92 16 15.7294852307762 0.2705147692238 93 15 14.9057923352787 0.0942076647212599 94 13 14.8364568188003 -1.83645681880029 95 16 14.6980328060634 1.3019671939366 96 16 15.6960780466908 0.303921953309245 97 16 13.4832846792557 2.51671532074433 98 16 15.8300417014576 0.169958298542448 99 14 14.2661258632027 -0.26612586320274 100 16 17.1940865071683 -1.19408650716827 101 16 14.5059011287886 1.49409887121141 102 20 17.5790992836759 2.42090071632414 103 15 14.0226460140409 0.977353985959138 104 16 14.8383762518519 1.16162374814812 105 13 14.7124447739459 -1.71244477394589 106 17 15.7604373152473 1.23956268475275 107 16 15.7720645248471 0.227935475152911 108 16 14.2326042643852 1.76739573561482 109 12 12.0024802659182 -0.0024802659181661 110 16 15.1718385499616 0.828161450038385 111 16 15.9384880334039 0.0615119665961118 112 17 14.8625328282602 2.13746717173979 113 13 14.5286402413612 -1.52864024136123 114 12 14.614568460888 -2.614568460888 115 18 16.2764524443605 1.72354755563947 116 14 15.9504759627416 -1.95047596274164 117 14 12.9924621951951 1.0075378048049 118 13 14.7858242392293 -1.78582423922932 119 16 15.5144579558839 0.485542044116056 120 13 14.3730308681848 -1.37303086818476 121 16 15.4072695332184 0.592730466781632 122 13 15.9001483950515 -2.90014839505154 123 16 17.0738036864139 -1.07380368641385 124 15 15.9985652529538 -0.998565252953809 125 16 16.9217558949015 -0.921755894901496 126 15 14.7501471788131 0.249852821186913 127 17 15.7672102604739 1.23278973952609 128 15 14.0042319951691 0.995768004830927 129 12 14.7455979666711 -2.74559796667113 130 16 13.9018224660129 2.09817753398714 131 10 13.490018922728 -3.49001892272798 132 16 13.4847293488174 2.51527065118258 133 12 14.1318955712898 -2.13189557128976 134 14 15.6891601643807 -1.68916016438072 135 15 15.1349525324793 -0.13495253247934 136 13 11.8798702989229 1.12012970107706 137 15 14.5406759892864 0.459324010713607 138 11 13.3639577865016 -2.3639577865016 139 12 12.9948717800782 -0.99487178007819 140 11 13.2797734052425 -2.27977340524254 141 16 12.8706670328481 3.12933296715189 142 15 13.577797008145 1.42220299185501 143 17 17.0126296693111 -0.0126296693111288 144 16 14.2177232846361 1.78227671536387 145 10 13.3076482519713 -3.30764825197125 146 18 15.710818264639 2.28918173536104 147 13 15.057515844885 -2.05751584488498 148 16 14.9198086004653 1.08019139953472 149 13 12.6377638044032 0.362236195596834 150 10 12.8783257394112 -2.87832573941121 151 15 16.155043271253 -1.15504327125299 152 16 13.9923608515066 2.00763914849345 153 16 11.7040450513149 4.29595494868509 154 14 12.2499675462609 1.75003245373915 155 10 12.3106299805489 -2.3106299805489 156 17 16.8321246414488 0.167875358551165 157 13 11.5695393191606 1.4304606808394 158 15 14.0042319951691 0.995768004830927 159 16 14.6713955204085 1.32860447959149 160 12 12.5736517546432 -0.573651754643204 161 13 12.6006036915371 0.399396308462923 162 13 12.4665513538839 0.533448646116147 163 12 12.3881607885568 -0.38816078855682 164 17 16.573789926877 0.426210073122991 165 15 13.6726004456851 1.32739955431488 166 10 11.4206728334644 -1.42067283346442 167 14 14.4691619974894 -0.469161997489404 168 11 14.2909865799885 -3.29098657998851 169 13 14.8482927619942 -1.84829276199418 170 16 14.4308747459494 1.56912525405059 171 12 10.3653118162962 1.63468818370377 172 16 15.7059483938507 0.294051606149256 173 12 13.9883936528962 -1.98839365289616 174 9 11.3120335908731 -2.31203359087306 175 12 15.2885887877223 -3.2885887877223 176 15 14.7442131156564 0.255786884343578 177 12 12.2632972969964 -0.263297296996437 178 12 12.6879346718068 -0.687934671806849 179 14 14.0621066117256 -0.0621066117256325 180 12 13.476269705029 -1.47626970502905 181 16 15.4340480772343 0.565951922765744 182 11 11.5217489928796 -0.521748992879648 183 19 17.1604632713109 1.83953672868909 184 15 15.5206096079202 -0.520609607920211 185 8 14.7662880903322 -6.76628809033216 186 16 14.9680927196659 1.03190728033406 187 17 14.7476768686274 2.25232313137259 188 12 12.5418032885651 -0.541803288565075 189 11 11.5269675255856 -0.526967525585557 190 11 10.2993224089426 0.700677591057422 191 14 15.0449039081772 -1.04490390817719 192 16 15.8549236374795 0.145076362520501 193 12 9.65799989258033 2.34200010741967 194 16 14.30051325933 1.69948674067003 195 13 13.9159846340245 -0.915984634024546 196 15 15.3686335282855 -0.368633528285513 197 16 13.0983431475463 2.90165685245369 198 16 15.3129697531759 0.687030246824134 199 14 12.4874552007084 1.51254479929164 200 16 14.7705797810563 1.22942021894371 201 16 14.1953897769368 1.80461022306324 202 14 13.5652608133924 0.434739186607563 203 11 13.7622976777595 -2.76229767775954 204 12 14.9165699771727 -2.91656997717273 205 15 12.9696665181991 2.03033348180092 206 15 14.8369644200455 0.163035579954472 207 16 14.847026495686 1.152973504314 208 16 15.4339487103626 0.566051289637426 209 11 13.9167631437977 -2.91676314379774 210 15 14.3031594704995 0.696840529500495 211 12 14.507489606999 -2.50748960699899 212 12 16.2896849694461 -4.28968496944614 213 15 14.3091704811001 0.690829518899894 214 15 12.1674958883062 2.83250411169379 215 16 14.8832893443442 1.1167106556558 216 14 13.4207878308238 0.579212169176227 217 17 15.0626619782301 1.93733802176991 218 14 14.3279169397482 -0.327916939748237 219 13 11.9902889016349 1.00971109836511 220 15 15.6158919610783 -0.615891961078346 221 13 15.0224913327295 -2.02249133272955 222 14 14.5733033465196 -0.573303346519553 223 15 14.5664459129041 0.433554087095921 224 12 13.4585313702885 -1.45853137028853 225 13 12.8042807399044 0.195719260095626 226 8 11.9668684285413 -3.96686842854126 227 14 14.3096831383973 -0.309683138397302 228 14 13.2737435527865 0.726256447213534 229 11 12.3432695732266 -1.34326957322662 230 12 13.1609985574185 -1.16099855741853 231 13 11.4799323515281 1.52006764847187 232 10 13.4650403340904 -3.46504033409045 233 16 11.7004538222459 4.29954617775414 234 18 16.45586637075 1.54413362925002 235 13 14.305398824479 -1.30539882447903 236 11 13.6549207425401 -2.65492074254013 237 4 11.170028137282 -7.170028137282 238 13 14.8152140281387 -1.81521402813867 239 16 14.5923633054321 1.40763669456794 240 10 11.9287261285823 -1.92872612858231 241 12 12.4071970658913 -0.407197065891321 242 12 13.795600381651 -1.79560038165096 243 10 8.88634470078796 1.11365529921204 244 13 11.2770068802368 1.72299311976324 245 15 14.0926273160205 0.907372683979529 246 12 12.0467701780665 -0.0467701780665387 247 14 13.1538828662063 0.846117133793712 248 10 12.8902928435778 -2.89029284357777 249 12 10.8009658204609 1.19903417953907 250 12 11.8839336289646 0.116066371035426 251 11 12.1379198030589 -1.13791980305892 252 10 11.8622634576053 -1.86226345760534 253 12 11.663143781657 0.336856218342988 254 16 13.1782247636368 2.82177523636317 255 12 13.7152063049677 -1.71520630496768 256 14 14.264087859685 -0.264087859685033 257 16 14.6811885572799 1.31881144272009 258 14 11.8239286814975 2.17607131850249 259 13 14.78164098406 -1.78164098406003 260 4 9.48330674262234 -5.48330674262234 261 15 14.174366651485 0.825633348514997 262 11 15.5502096888069 -4.55020968880689 263 11 11.4716452522508 -0.471645252250812 264 14 13.1672908525232 0.832709147476811

 Goldfeld-Quandt test for Heteroskedasticity p-values Alternative Hypothesis breakpoint index greater 2-sided less 11 0.234449524103323 0.468899048206647 0.765550475896677 12 0.120293517840556 0.240587035681113 0.879706482159444 13 0.0815541573457813 0.163108314691563 0.918445842654219 14 0.102874776497916 0.205749552995833 0.897125223502084 15 0.0587519756515484 0.117503951303097 0.941248024348452 16 0.0391686675931635 0.0783373351863269 0.960831332406836 17 0.063019118444172 0.126038236888344 0.936980881555828 18 0.255864327935305 0.511728655870609 0.744135672064695 19 0.194216632900149 0.388433265800299 0.805783367099851 20 0.13776488333464 0.275529766669281 0.86223511666536 21 0.0986062615513714 0.197212523102743 0.901393738448629 22 0.0968533990427696 0.193706798085539 0.90314660095723 23 0.257054377911142 0.514108755822284 0.742945622088858 24 0.321495418423946 0.642990836847893 0.678504581576054 25 0.294869538595026 0.589739077190051 0.705130461404974 26 0.277447857711978 0.554895715423955 0.722552142288022 27 0.352098888872553 0.704197777745105 0.647901111127447 28 0.363849648859334 0.727699297718668 0.636150351140666 29 0.346785592147584 0.693571184295169 0.653214407852416 30 0.380898386272269 0.761796772544538 0.619101613727731 31 0.328675803111158 0.657351606222317 0.671324196888842 32 0.289492867969931 0.578985735939863 0.710507132030069 33 0.262490777406895 0.524981554813791 0.737509222593105 34 0.226304417033043 0.452608834066086 0.773695582966957 35 0.18788054181459 0.37576108362918 0.81211945818541 36 0.304929814888214 0.609859629776428 0.695070185111786 37 0.334971074151201 0.669942148302402 0.665028925848799 38 0.325963622584246 0.651927245168491 0.674036377415754 39 0.356022739855431 0.712045479710862 0.643977260144569 40 0.334209449134641 0.668418898269283 0.665790550865359 41 0.298001365293739 0.596002730587479 0.701998634706261 42 0.263835728828225 0.527671457656451 0.736164271171775 43 0.278274265211435 0.55654853042287 0.721725734788565 44 0.236536521323923 0.473073042647846 0.763463478676077 45 0.214442280198157 0.428884560396314 0.785557719801843 46 0.392689717772563 0.785379435545127 0.607310282227437 47 0.545519033485656 0.908961933028687 0.454480966514344 48 0.496548776402334 0.993097552804668 0.503451223597666 49 0.48321616072475 0.9664323214495 0.51678383927525 50 0.468390230644654 0.936780461289308 0.531609769355346 51 0.423671720349913 0.847343440699825 0.576328279650087 52 0.378169197572532 0.756338395145064 0.621830802427468 53 0.386603609576094 0.773207219152188 0.613396390423906 54 0.369709551282604 0.739419102565208 0.630290448717396 55 0.360937557172321 0.721875114344642 0.639062442827679 56 0.339385238523735 0.67877047704747 0.660614761476265 57 0.299777754262651 0.599555508525302 0.700222245737349 58 0.271157720239434 0.542315440478868 0.728842279760566 59 0.236694269796537 0.473388539593074 0.763305730203463 60 0.242458614750554 0.484917229501107 0.757541385249446 61 0.218650159104954 0.437300318209908 0.781349840895046 62 0.191735670804925 0.38347134160985 0.808264329195075 63 0.163732057843761 0.327464115687522 0.836267942156239 64 0.137978888894911 0.275957777789822 0.862021111105089 65 0.119073866261542 0.238147732523085 0.880926133738458 66 0.110228851421388 0.220457702842776 0.889771148578612 67 0.105986150241297 0.211972300482594 0.894013849758703 68 0.22305867935604 0.44611735871208 0.77694132064396 69 0.313038852663478 0.626077705326956 0.686961147336522 70 0.282142509826924 0.564285019653848 0.717857490173076 71 0.397902377321227 0.795804754642453 0.602097622678773 72 0.359897835237818 0.719795670475636 0.640102164762182 73 0.351564646488888 0.703129292977775 0.648435353511112 74 0.336197027115226 0.672394054230451 0.663802972884775 75 0.304024154874088 0.608048309748175 0.695975845125912 76 0.36954472555895 0.739089451117899 0.63045527444105 77 0.333817781175647 0.667635562351294 0.666182218824353 78 0.312977052653639 0.625954105307278 0.687022947346361 79 0.326056568919716 0.652113137839433 0.673943431080284 80 0.298478347311549 0.596956694623099 0.701521652688451 81 0.270341906890839 0.540683813781679 0.729658093109161 82 0.239446042587498 0.478892085174996 0.760553957412502 83 0.215139662822707 0.430279325645414 0.784860337177293 84 0.187913722738408 0.375827445476815 0.812086277261592 85 0.184607191674078 0.369214383348156 0.815392808325922 86 0.159572512041598 0.319145024083196 0.840427487958402 87 0.140322537361322 0.280645074722645 0.859677462638678 88 0.130738801764796 0.261477603529591 0.869261198235204 89 0.112976437875893 0.225952875751786 0.887023562124107 90 0.110203114219271 0.220406228438542 0.889796885780729 91 0.0942919369448659 0.188583873889732 0.905708063055134 92 0.0814240906086617 0.162848181217323 0.918575909391338 93 0.0691622046865876 0.138324409373175 0.930837795313412 94 0.0710505619641146 0.142101123928229 0.928949438035885 95 0.0642047750978092 0.128409550195618 0.935795224902191 96 0.0537975865035413 0.107595173007083 0.946202413496459 97 0.0594315146399693 0.118863029279939 0.940568485360031 98 0.0492270511304385 0.098454102260877 0.950772948869562 99 0.0403637971239411 0.0807275942478823 0.959636202876059 100 0.0353149770686558 0.0706299541373116 0.964685022931344 101 0.0313300139468179 0.0626600278936358 0.968669986053182 102 0.0368820710846464 0.0737641421692928 0.963117928915354 103 0.0316513902506374 0.0633027805012748 0.968348609749363 104 0.0285859141191505 0.0571718282383009 0.97141408588085 105 0.0338171358137667 0.0676342716275334 0.966182864186233 106 0.0297170878687312 0.0594341757374624 0.970282912131269 107 0.0241330786284956 0.0482661572569911 0.975866921371504 108 0.0240079113500851 0.0480158227001702 0.975992088649915 109 0.0194515049063909 0.0389030098127817 0.980548495093609 110 0.0159136661421485 0.0318273322842969 0.984086333857851 111 0.0126146522719223 0.0252293045438447 0.987385347728078 112 0.0130381277586825 0.0260762555173651 0.986961872241317 113 0.0116452146478801 0.0232904292957602 0.98835478535212 114 0.0167206560872487 0.0334413121744973 0.983279343912751 115 0.0159710234451857 0.0319420468903713 0.984028976554814 116 0.015281197801685 0.03056239560337 0.984718802198315 117 0.0126390299453941 0.0252780598907883 0.987360970054606 118 0.0126219562493751 0.0252439124987502 0.987378043750625 119 0.0102612016271451 0.0205224032542903 0.989738798372855 120 0.00903802567892109 0.0180760513578422 0.990961974321079 121 0.00735356780301573 0.0147071356060315 0.992646432196984 122 0.0113195512171058 0.0226391024342117 0.988680448782894 123 0.00953849599480365 0.0190769919896073 0.990461504005196 124 0.00847311639172475 0.0169462327834495 0.991526883608275 125 0.00693555972924188 0.0138711194584838 0.993064440270758 126 0.00565042103716446 0.0113008420743289 0.994349578962835 127 0.0050871640127939 0.0101743280255878 0.994912835987206 128 0.00409879352027462 0.00819758704054924 0.995901206479725 129 0.00604886982758688 0.0120977396551738 0.993951130172413 130 0.00655323802881191 0.0131064760576238 0.993446761971188 131 0.0135402943899648 0.0270805887799297 0.986459705610035 132 0.0162987275042286 0.0325974550084572 0.983701272495771 133 0.0175823649816717 0.0351647299633434 0.982417635018328 134 0.0169833449919507 0.0339666899839014 0.983016655008049 135 0.013880374473478 0.027760748946956 0.986119625526522 136 0.0117123386997017 0.0234246773994033 0.988287661300298 137 0.0093746433382091 0.0187492866764182 0.990625356661791 138 0.0114169021588462 0.0228338043176924 0.988583097841154 139 0.00993713987951826 0.0198742797590365 0.990062860120482 140 0.0112928154997636 0.0225856309995272 0.988707184500236 141 0.0175165648200136 0.0350331296400271 0.982483435179986 142 0.0159289579009632 0.0318579158019264 0.984071042099037 143 0.0126831635932341 0.0253663271864682 0.987316836406766 144 0.0134458333059833 0.0268916666119666 0.986554166694017 145 0.0256403134895237 0.0512806269790473 0.974359686510476 146 0.0314184109533001 0.0628368219066001 0.9685815890467 147 0.0329795780363351 0.0659591560726702 0.967020421963665 148 0.0297734227101545 0.0595468454203091 0.970226577289845 149 0.0248127287409387 0.0496254574818775 0.975187271259061 150 0.0344362320643675 0.0688724641287351 0.965563767935632 151 0.0297124189393621 0.0594248378787242 0.970287581060638 152 0.0312806581649013 0.0625613163298026 0.968719341835099 153 0.0638804329782772 0.127760865956554 0.936119567021723 154 0.0627614357271258 0.125522871454252 0.937238564272874 155 0.0721747771912981 0.144349554382596 0.927825222808702 156 0.0617478574339026 0.123495714867805 0.938252142566097 157 0.0551628794160272 0.110325758832054 0.944837120583973 158 0.0482704122823341 0.0965408245646683 0.951729587717666 159 0.0472261086820222 0.0944522173640445 0.952773891317978 160 0.0404930281933104 0.0809860563866209 0.95950697180669 161 0.0334124305697173 0.0668248611394345 0.966587569430283 162 0.0274667952760025 0.0549335905520051 0.972533204723998 163 0.0228756533010376 0.0457513066020752 0.977124346698962 164 0.0192964132818175 0.0385928265636349 0.980703586718183 165 0.0169353563376047 0.0338707126752094 0.983064643662395 166 0.0171843050634622 0.0343686101269243 0.982815694936538 167 0.0138076243872407 0.0276152487744814 0.986192375612759 168 0.0203735861261564 0.0407471722523128 0.979626413873844 169 0.0201928859457744 0.0403857718915488 0.979807114054226 170 0.0188580171726759 0.0377160343453517 0.981141982827324 171 0.0181349653406303 0.0362699306812606 0.98186503465937 172 0.0146941965866962 0.0293883931733924 0.985305803413304 173 0.0147422907486942 0.0294845814973884 0.985257709251306 174 0.0164226161640716 0.0328452323281431 0.983577383835928 175 0.0219494596798679 0.0438989193597359 0.978050540320132 176 0.0176531523212622 0.0353063046425244 0.982346847678738 177 0.0143826922510691 0.0287653845021382 0.985617307748931 178 0.011742742838476 0.0234854856769521 0.988257257161524 179 0.00919215979401765 0.0183843195880353 0.990807840205982 180 0.00800536172863929 0.0160107234572786 0.991994638271361 181 0.00660360418668578 0.0132072083733716 0.993396395813314 182 0.00534521714955193 0.0106904342991039 0.994654782850448 183 0.00560936622575505 0.0112187324515101 0.994390633774245 184 0.00443647295033499 0.00887294590066997 0.995563527049665 185 0.094086539900982 0.188173079801964 0.905913460099018 186 0.0816845811721911 0.163369162344382 0.918315418827809 187 0.0928439802674425 0.185687960534885 0.907156019732557 188 0.0802127135646733 0.160425427129347 0.919787286435327 189 0.0679596339456167 0.135919267891233 0.932040366054383 190 0.0563561435032738 0.112712287006548 0.943643856496726 191 0.0497111618841623 0.0994223237683247 0.950288838115838 192 0.0419611933152222 0.0839223866304445 0.958038806684778 193 0.0487155279839555 0.097431055967911 0.951284472016044 194 0.0522890666310381 0.104578133262076 0.947710933368962 195 0.0443811738269573 0.0887623476539145 0.955618826173043 196 0.037026328217237 0.0740526564344739 0.962973671782763 197 0.0483157061172395 0.0966314122344789 0.951684293882761 198 0.0395862946218528 0.0791725892437057 0.960413705378147 199 0.0367011562951475 0.073402312590295 0.963298843704853 200 0.0310398676134198 0.0620797352268397 0.96896013238658 201 0.0292219724944833 0.0584439449889665 0.970778027505517 202 0.0243805707067277 0.0487611414134554 0.975619429293272 203 0.0313053691066302 0.0626107382132604 0.96869463089337 204 0.0356803177739391 0.0713606355478783 0.964319682226061 205 0.0389063363767213 0.0778126727534425 0.961093663623279 206 0.030879154542079 0.0617583090841579 0.969120845457921 207 0.0303422228248085 0.060684445649617 0.969657777175192 208 0.0249498727311462 0.0498997454622924 0.975050127268854 209 0.0278681412054705 0.055736282410941 0.97213185879453 210 0.0225417426210891 0.0450834852421783 0.977458257378911 211 0.0249775332931389 0.0499550665862778 0.975022466706861 212 0.0399735087423003 0.0799470174846007 0.9600264912577 213 0.0315871062441673 0.0631742124883345 0.968412893755833 214 0.0441589425989395 0.0883178851978789 0.955841057401061 215 0.0380593092869374 0.0761186185738748 0.961940690713063 216 0.0297508259210563 0.0595016518421126 0.970249174078944 217 0.0321955312729054 0.0643910625458109 0.967804468727095 218 0.0275294909822652 0.0550589819645304 0.972470509017735 219 0.0247418070044538 0.0494836140089075 0.975258192995546 220 0.0189633773705705 0.037926754741141 0.981036622629429 221 0.0168947339209676 0.0337894678419351 0.983105266079032 222 0.0124206485849153 0.0248412971698306 0.987579351415085 223 0.00931174186201657 0.0186234837240331 0.990688258137983 224 0.0075021185439771 0.0150042370879542 0.992497881456023 225 0.00654705616129089 0.0130941123225818 0.993452943838709 226 0.0149951903144663 0.0299903806289325 0.985004809685534 227 0.0115416184372466 0.0230832368744931 0.988458381562753 228 0.00835031892340794 0.0167006378468159 0.991649681076592 229 0.00609683424321092 0.0121936684864218 0.993903165756789 230 0.00441036251732994 0.00882072503465989 0.99558963748267 231 0.00439461457994107 0.00878922915988213 0.995605385420059 232 0.00814497957146648 0.016289959142933 0.991855020428533 233 0.0377565442118785 0.075513088423757 0.962243455788122 234 0.0542942200569111 0.108588440113822 0.945705779943089 235 0.0405065857547014 0.0810131715094027 0.959493414245299 236 0.0361101125951766 0.0722202251903532 0.963889887404823 237 0.246505700570201 0.493011401140403 0.753494299429799 238 0.200782130963977 0.401564261927953 0.799217869036023 239 0.18004440546804 0.360088810936079 0.81995559453196 240 0.142128535333137 0.284257070666274 0.857871464666863 241 0.113707343103352 0.227414686206704 0.886292656896648 242 0.0945301032407296 0.189060206481459 0.90546989675927 243 0.0879023187197939 0.175804637439588 0.912097681280206 244 0.153550434222245 0.307100868444491 0.846449565777755 245 0.137630339717255 0.27526067943451 0.862369660282745 246 0.110109330538686 0.220218661077371 0.889890669461314 247 0.0777706008222236 0.155541201644447 0.922229399177776 248 0.0666948470256243 0.133389694051249 0.933305152974376 249 0.0624888270323003 0.124977654064601 0.9375111729677 250 0.077380993053961 0.154761986107922 0.922619006946039 251 0.0460549764082262 0.0921099528164523 0.953945023591774 252 0.112285664162277 0.224571328324554 0.887714335837723 253 0.234998511095393 0.469997022190785 0.765001488904607

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.234449524103323 & 0.468899048206647 & 0.765550475896677 \tabularnewline
12 & 0.120293517840556 & 0.240587035681113 & 0.879706482159444 \tabularnewline
13 & 0.0815541573457813 & 0.163108314691563 & 0.918445842654219 \tabularnewline
14 & 0.102874776497916 & 0.205749552995833 & 0.897125223502084 \tabularnewline
15 & 0.0587519756515484 & 0.117503951303097 & 0.941248024348452 \tabularnewline
16 & 0.0391686675931635 & 0.0783373351863269 & 0.960831332406836 \tabularnewline
17 & 0.063019118444172 & 0.126038236888344 & 0.936980881555828 \tabularnewline
18 & 0.255864327935305 & 0.511728655870609 & 0.744135672064695 \tabularnewline
19 & 0.194216632900149 & 0.388433265800299 & 0.805783367099851 \tabularnewline
20 & 0.13776488333464 & 0.275529766669281 & 0.86223511666536 \tabularnewline
21 & 0.0986062615513714 & 0.197212523102743 & 0.901393738448629 \tabularnewline
22 & 0.0968533990427696 & 0.193706798085539 & 0.90314660095723 \tabularnewline
23 & 0.257054377911142 & 0.514108755822284 & 0.742945622088858 \tabularnewline
24 & 0.321495418423946 & 0.642990836847893 & 0.678504581576054 \tabularnewline
25 & 0.294869538595026 & 0.589739077190051 & 0.705130461404974 \tabularnewline
26 & 0.277447857711978 & 0.554895715423955 & 0.722552142288022 \tabularnewline
27 & 0.352098888872553 & 0.704197777745105 & 0.647901111127447 \tabularnewline
28 & 0.363849648859334 & 0.727699297718668 & 0.636150351140666 \tabularnewline
29 & 0.346785592147584 & 0.693571184295169 & 0.653214407852416 \tabularnewline
30 & 0.380898386272269 & 0.761796772544538 & 0.619101613727731 \tabularnewline
31 & 0.328675803111158 & 0.657351606222317 & 0.671324196888842 \tabularnewline
32 & 0.289492867969931 & 0.578985735939863 & 0.710507132030069 \tabularnewline
33 & 0.262490777406895 & 0.524981554813791 & 0.737509222593105 \tabularnewline
34 & 0.226304417033043 & 0.452608834066086 & 0.773695582966957 \tabularnewline
35 & 0.18788054181459 & 0.37576108362918 & 0.81211945818541 \tabularnewline
36 & 0.304929814888214 & 0.609859629776428 & 0.695070185111786 \tabularnewline
37 & 0.334971074151201 & 0.669942148302402 & 0.665028925848799 \tabularnewline
38 & 0.325963622584246 & 0.651927245168491 & 0.674036377415754 \tabularnewline
39 & 0.356022739855431 & 0.712045479710862 & 0.643977260144569 \tabularnewline
40 & 0.334209449134641 & 0.668418898269283 & 0.665790550865359 \tabularnewline
41 & 0.298001365293739 & 0.596002730587479 & 0.701998634706261 \tabularnewline
42 & 0.263835728828225 & 0.527671457656451 & 0.736164271171775 \tabularnewline
43 & 0.278274265211435 & 0.55654853042287 & 0.721725734788565 \tabularnewline
44 & 0.236536521323923 & 0.473073042647846 & 0.763463478676077 \tabularnewline
45 & 0.214442280198157 & 0.428884560396314 & 0.785557719801843 \tabularnewline
46 & 0.392689717772563 & 0.785379435545127 & 0.607310282227437 \tabularnewline
47 & 0.545519033485656 & 0.908961933028687 & 0.454480966514344 \tabularnewline
48 & 0.496548776402334 & 0.993097552804668 & 0.503451223597666 \tabularnewline
49 & 0.48321616072475 & 0.9664323214495 & 0.51678383927525 \tabularnewline
50 & 0.468390230644654 & 0.936780461289308 & 0.531609769355346 \tabularnewline
51 & 0.423671720349913 & 0.847343440699825 & 0.576328279650087 \tabularnewline
52 & 0.378169197572532 & 0.756338395145064 & 0.621830802427468 \tabularnewline
53 & 0.386603609576094 & 0.773207219152188 & 0.613396390423906 \tabularnewline
54 & 0.369709551282604 & 0.739419102565208 & 0.630290448717396 \tabularnewline
55 & 0.360937557172321 & 0.721875114344642 & 0.639062442827679 \tabularnewline
56 & 0.339385238523735 & 0.67877047704747 & 0.660614761476265 \tabularnewline
57 & 0.299777754262651 & 0.599555508525302 & 0.700222245737349 \tabularnewline
58 & 0.271157720239434 & 0.542315440478868 & 0.728842279760566 \tabularnewline
59 & 0.236694269796537 & 0.473388539593074 & 0.763305730203463 \tabularnewline
60 & 0.242458614750554 & 0.484917229501107 & 0.757541385249446 \tabularnewline
61 & 0.218650159104954 & 0.437300318209908 & 0.781349840895046 \tabularnewline
62 & 0.191735670804925 & 0.38347134160985 & 0.808264329195075 \tabularnewline
63 & 0.163732057843761 & 0.327464115687522 & 0.836267942156239 \tabularnewline
64 & 0.137978888894911 & 0.275957777789822 & 0.862021111105089 \tabularnewline
65 & 0.119073866261542 & 0.238147732523085 & 0.880926133738458 \tabularnewline
66 & 0.110228851421388 & 0.220457702842776 & 0.889771148578612 \tabularnewline
67 & 0.105986150241297 & 0.211972300482594 & 0.894013849758703 \tabularnewline
68 & 0.22305867935604 & 0.44611735871208 & 0.77694132064396 \tabularnewline
69 & 0.313038852663478 & 0.626077705326956 & 0.686961147336522 \tabularnewline
70 & 0.282142509826924 & 0.564285019653848 & 0.717857490173076 \tabularnewline
71 & 0.397902377321227 & 0.795804754642453 & 0.602097622678773 \tabularnewline
72 & 0.359897835237818 & 0.719795670475636 & 0.640102164762182 \tabularnewline
73 & 0.351564646488888 & 0.703129292977775 & 0.648435353511112 \tabularnewline
74 & 0.336197027115226 & 0.672394054230451 & 0.663802972884775 \tabularnewline
75 & 0.304024154874088 & 0.608048309748175 & 0.695975845125912 \tabularnewline
76 & 0.36954472555895 & 0.739089451117899 & 0.63045527444105 \tabularnewline
77 & 0.333817781175647 & 0.667635562351294 & 0.666182218824353 \tabularnewline
78 & 0.312977052653639 & 0.625954105307278 & 0.687022947346361 \tabularnewline
79 & 0.326056568919716 & 0.652113137839433 & 0.673943431080284 \tabularnewline
80 & 0.298478347311549 & 0.596956694623099 & 0.701521652688451 \tabularnewline
81 & 0.270341906890839 & 0.540683813781679 & 0.729658093109161 \tabularnewline
82 & 0.239446042587498 & 0.478892085174996 & 0.760553957412502 \tabularnewline
83 & 0.215139662822707 & 0.430279325645414 & 0.784860337177293 \tabularnewline
84 & 0.187913722738408 & 0.375827445476815 & 0.812086277261592 \tabularnewline
85 & 0.184607191674078 & 0.369214383348156 & 0.815392808325922 \tabularnewline
86 & 0.159572512041598 & 0.319145024083196 & 0.840427487958402 \tabularnewline
87 & 0.140322537361322 & 0.280645074722645 & 0.859677462638678 \tabularnewline
88 & 0.130738801764796 & 0.261477603529591 & 0.869261198235204 \tabularnewline
89 & 0.112976437875893 & 0.225952875751786 & 0.887023562124107 \tabularnewline
90 & 0.110203114219271 & 0.220406228438542 & 0.889796885780729 \tabularnewline
91 & 0.0942919369448659 & 0.188583873889732 & 0.905708063055134 \tabularnewline
92 & 0.0814240906086617 & 0.162848181217323 & 0.918575909391338 \tabularnewline
93 & 0.0691622046865876 & 0.138324409373175 & 0.930837795313412 \tabularnewline
94 & 0.0710505619641146 & 0.142101123928229 & 0.928949438035885 \tabularnewline
95 & 0.0642047750978092 & 0.128409550195618 & 0.935795224902191 \tabularnewline
96 & 0.0537975865035413 & 0.107595173007083 & 0.946202413496459 \tabularnewline
97 & 0.0594315146399693 & 0.118863029279939 & 0.940568485360031 \tabularnewline
98 & 0.0492270511304385 & 0.098454102260877 & 0.950772948869562 \tabularnewline
99 & 0.0403637971239411 & 0.0807275942478823 & 0.959636202876059 \tabularnewline
100 & 0.0353149770686558 & 0.0706299541373116 & 0.964685022931344 \tabularnewline
101 & 0.0313300139468179 & 0.0626600278936358 & 0.968669986053182 \tabularnewline
102 & 0.0368820710846464 & 0.0737641421692928 & 0.963117928915354 \tabularnewline
103 & 0.0316513902506374 & 0.0633027805012748 & 0.968348609749363 \tabularnewline
104 & 0.0285859141191505 & 0.0571718282383009 & 0.97141408588085 \tabularnewline
105 & 0.0338171358137667 & 0.0676342716275334 & 0.966182864186233 \tabularnewline
106 & 0.0297170878687312 & 0.0594341757374624 & 0.970282912131269 \tabularnewline
107 & 0.0241330786284956 & 0.0482661572569911 & 0.975866921371504 \tabularnewline
108 & 0.0240079113500851 & 0.0480158227001702 & 0.975992088649915 \tabularnewline
109 & 0.0194515049063909 & 0.0389030098127817 & 0.980548495093609 \tabularnewline
110 & 0.0159136661421485 & 0.0318273322842969 & 0.984086333857851 \tabularnewline
111 & 0.0126146522719223 & 0.0252293045438447 & 0.987385347728078 \tabularnewline
112 & 0.0130381277586825 & 0.0260762555173651 & 0.986961872241317 \tabularnewline
113 & 0.0116452146478801 & 0.0232904292957602 & 0.98835478535212 \tabularnewline
114 & 0.0167206560872487 & 0.0334413121744973 & 0.983279343912751 \tabularnewline
115 & 0.0159710234451857 & 0.0319420468903713 & 0.984028976554814 \tabularnewline
116 & 0.015281197801685 & 0.03056239560337 & 0.984718802198315 \tabularnewline
117 & 0.0126390299453941 & 0.0252780598907883 & 0.987360970054606 \tabularnewline
118 & 0.0126219562493751 & 0.0252439124987502 & 0.987378043750625 \tabularnewline
119 & 0.0102612016271451 & 0.0205224032542903 & 0.989738798372855 \tabularnewline
120 & 0.00903802567892109 & 0.0180760513578422 & 0.990961974321079 \tabularnewline
121 & 0.00735356780301573 & 0.0147071356060315 & 0.992646432196984 \tabularnewline
122 & 0.0113195512171058 & 0.0226391024342117 & 0.988680448782894 \tabularnewline
123 & 0.00953849599480365 & 0.0190769919896073 & 0.990461504005196 \tabularnewline
124 & 0.00847311639172475 & 0.0169462327834495 & 0.991526883608275 \tabularnewline
125 & 0.00693555972924188 & 0.0138711194584838 & 0.993064440270758 \tabularnewline
126 & 0.00565042103716446 & 0.0113008420743289 & 0.994349578962835 \tabularnewline
127 & 0.0050871640127939 & 0.0101743280255878 & 0.994912835987206 \tabularnewline
128 & 0.00409879352027462 & 0.00819758704054924 & 0.995901206479725 \tabularnewline
129 & 0.00604886982758688 & 0.0120977396551738 & 0.993951130172413 \tabularnewline
130 & 0.00655323802881191 & 0.0131064760576238 & 0.993446761971188 \tabularnewline
131 & 0.0135402943899648 & 0.0270805887799297 & 0.986459705610035 \tabularnewline
132 & 0.0162987275042286 & 0.0325974550084572 & 0.983701272495771 \tabularnewline
133 & 0.0175823649816717 & 0.0351647299633434 & 0.982417635018328 \tabularnewline
134 & 0.0169833449919507 & 0.0339666899839014 & 0.983016655008049 \tabularnewline
135 & 0.013880374473478 & 0.027760748946956 & 0.986119625526522 \tabularnewline
136 & 0.0117123386997017 & 0.0234246773994033 & 0.988287661300298 \tabularnewline
137 & 0.0093746433382091 & 0.0187492866764182 & 0.990625356661791 \tabularnewline
138 & 0.0114169021588462 & 0.0228338043176924 & 0.988583097841154 \tabularnewline
139 & 0.00993713987951826 & 0.0198742797590365 & 0.990062860120482 \tabularnewline
140 & 0.0112928154997636 & 0.0225856309995272 & 0.988707184500236 \tabularnewline
141 & 0.0175165648200136 & 0.0350331296400271 & 0.982483435179986 \tabularnewline
142 & 0.0159289579009632 & 0.0318579158019264 & 0.984071042099037 \tabularnewline
143 & 0.0126831635932341 & 0.0253663271864682 & 0.987316836406766 \tabularnewline
144 & 0.0134458333059833 & 0.0268916666119666 & 0.986554166694017 \tabularnewline
145 & 0.0256403134895237 & 0.0512806269790473 & 0.974359686510476 \tabularnewline
146 & 0.0314184109533001 & 0.0628368219066001 & 0.9685815890467 \tabularnewline
147 & 0.0329795780363351 & 0.0659591560726702 & 0.967020421963665 \tabularnewline
148 & 0.0297734227101545 & 0.0595468454203091 & 0.970226577289845 \tabularnewline
149 & 0.0248127287409387 & 0.0496254574818775 & 0.975187271259061 \tabularnewline
150 & 0.0344362320643675 & 0.0688724641287351 & 0.965563767935632 \tabularnewline
151 & 0.0297124189393621 & 0.0594248378787242 & 0.970287581060638 \tabularnewline
152 & 0.0312806581649013 & 0.0625613163298026 & 0.968719341835099 \tabularnewline
153 & 0.0638804329782772 & 0.127760865956554 & 0.936119567021723 \tabularnewline
154 & 0.0627614357271258 & 0.125522871454252 & 0.937238564272874 \tabularnewline
155 & 0.0721747771912981 & 0.144349554382596 & 0.927825222808702 \tabularnewline
156 & 0.0617478574339026 & 0.123495714867805 & 0.938252142566097 \tabularnewline
157 & 0.0551628794160272 & 0.110325758832054 & 0.944837120583973 \tabularnewline
158 & 0.0482704122823341 & 0.0965408245646683 & 0.951729587717666 \tabularnewline
159 & 0.0472261086820222 & 0.0944522173640445 & 0.952773891317978 \tabularnewline
160 & 0.0404930281933104 & 0.0809860563866209 & 0.95950697180669 \tabularnewline
161 & 0.0334124305697173 & 0.0668248611394345 & 0.966587569430283 \tabularnewline
162 & 0.0274667952760025 & 0.0549335905520051 & 0.972533204723998 \tabularnewline
163 & 0.0228756533010376 & 0.0457513066020752 & 0.977124346698962 \tabularnewline
164 & 0.0192964132818175 & 0.0385928265636349 & 0.980703586718183 \tabularnewline
165 & 0.0169353563376047 & 0.0338707126752094 & 0.983064643662395 \tabularnewline
166 & 0.0171843050634622 & 0.0343686101269243 & 0.982815694936538 \tabularnewline
167 & 0.0138076243872407 & 0.0276152487744814 & 0.986192375612759 \tabularnewline
168 & 0.0203735861261564 & 0.0407471722523128 & 0.979626413873844 \tabularnewline
169 & 0.0201928859457744 & 0.0403857718915488 & 0.979807114054226 \tabularnewline
170 & 0.0188580171726759 & 0.0377160343453517 & 0.981141982827324 \tabularnewline
171 & 0.0181349653406303 & 0.0362699306812606 & 0.98186503465937 \tabularnewline
172 & 0.0146941965866962 & 0.0293883931733924 & 0.985305803413304 \tabularnewline
173 & 0.0147422907486942 & 0.0294845814973884 & 0.985257709251306 \tabularnewline
174 & 0.0164226161640716 & 0.0328452323281431 & 0.983577383835928 \tabularnewline
175 & 0.0219494596798679 & 0.0438989193597359 & 0.978050540320132 \tabularnewline
176 & 0.0176531523212622 & 0.0353063046425244 & 0.982346847678738 \tabularnewline
177 & 0.0143826922510691 & 0.0287653845021382 & 0.985617307748931 \tabularnewline
178 & 0.011742742838476 & 0.0234854856769521 & 0.988257257161524 \tabularnewline
179 & 0.00919215979401765 & 0.0183843195880353 & 0.990807840205982 \tabularnewline
180 & 0.00800536172863929 & 0.0160107234572786 & 0.991994638271361 \tabularnewline
181 & 0.00660360418668578 & 0.0132072083733716 & 0.993396395813314 \tabularnewline
182 & 0.00534521714955193 & 0.0106904342991039 & 0.994654782850448 \tabularnewline
183 & 0.00560936622575505 & 0.0112187324515101 & 0.994390633774245 \tabularnewline
184 & 0.00443647295033499 & 0.00887294590066997 & 0.995563527049665 \tabularnewline
185 & 0.094086539900982 & 0.188173079801964 & 0.905913460099018 \tabularnewline
186 & 0.0816845811721911 & 0.163369162344382 & 0.918315418827809 \tabularnewline
187 & 0.0928439802674425 & 0.185687960534885 & 0.907156019732557 \tabularnewline
188 & 0.0802127135646733 & 0.160425427129347 & 0.919787286435327 \tabularnewline
189 & 0.0679596339456167 & 0.135919267891233 & 0.932040366054383 \tabularnewline
190 & 0.0563561435032738 & 0.112712287006548 & 0.943643856496726 \tabularnewline
191 & 0.0497111618841623 & 0.0994223237683247 & 0.950288838115838 \tabularnewline
192 & 0.0419611933152222 & 0.0839223866304445 & 0.958038806684778 \tabularnewline
193 & 0.0487155279839555 & 0.097431055967911 & 0.951284472016044 \tabularnewline
194 & 0.0522890666310381 & 0.104578133262076 & 0.947710933368962 \tabularnewline
195 & 0.0443811738269573 & 0.0887623476539145 & 0.955618826173043 \tabularnewline
196 & 0.037026328217237 & 0.0740526564344739 & 0.962973671782763 \tabularnewline
197 & 0.0483157061172395 & 0.0966314122344789 & 0.951684293882761 \tabularnewline
198 & 0.0395862946218528 & 0.0791725892437057 & 0.960413705378147 \tabularnewline
199 & 0.0367011562951475 & 0.073402312590295 & 0.963298843704853 \tabularnewline
200 & 0.0310398676134198 & 0.0620797352268397 & 0.96896013238658 \tabularnewline
201 & 0.0292219724944833 & 0.0584439449889665 & 0.970778027505517 \tabularnewline
202 & 0.0243805707067277 & 0.0487611414134554 & 0.975619429293272 \tabularnewline
203 & 0.0313053691066302 & 0.0626107382132604 & 0.96869463089337 \tabularnewline
204 & 0.0356803177739391 & 0.0713606355478783 & 0.964319682226061 \tabularnewline
205 & 0.0389063363767213 & 0.0778126727534425 & 0.961093663623279 \tabularnewline
206 & 0.030879154542079 & 0.0617583090841579 & 0.969120845457921 \tabularnewline
207 & 0.0303422228248085 & 0.060684445649617 & 0.969657777175192 \tabularnewline
208 & 0.0249498727311462 & 0.0498997454622924 & 0.975050127268854 \tabularnewline
209 & 0.0278681412054705 & 0.055736282410941 & 0.97213185879453 \tabularnewline
210 & 0.0225417426210891 & 0.0450834852421783 & 0.977458257378911 \tabularnewline
211 & 0.0249775332931389 & 0.0499550665862778 & 0.975022466706861 \tabularnewline
212 & 0.0399735087423003 & 0.0799470174846007 & 0.9600264912577 \tabularnewline
213 & 0.0315871062441673 & 0.0631742124883345 & 0.968412893755833 \tabularnewline
214 & 0.0441589425989395 & 0.0883178851978789 & 0.955841057401061 \tabularnewline
215 & 0.0380593092869374 & 0.0761186185738748 & 0.961940690713063 \tabularnewline
216 & 0.0297508259210563 & 0.0595016518421126 & 0.970249174078944 \tabularnewline
217 & 0.0321955312729054 & 0.0643910625458109 & 0.967804468727095 \tabularnewline
218 & 0.0275294909822652 & 0.0550589819645304 & 0.972470509017735 \tabularnewline
219 & 0.0247418070044538 & 0.0494836140089075 & 0.975258192995546 \tabularnewline
220 & 0.0189633773705705 & 0.037926754741141 & 0.981036622629429 \tabularnewline
221 & 0.0168947339209676 & 0.0337894678419351 & 0.983105266079032 \tabularnewline
222 & 0.0124206485849153 & 0.0248412971698306 & 0.987579351415085 \tabularnewline
223 & 0.00931174186201657 & 0.0186234837240331 & 0.990688258137983 \tabularnewline
224 & 0.0075021185439771 & 0.0150042370879542 & 0.992497881456023 \tabularnewline
225 & 0.00654705616129089 & 0.0130941123225818 & 0.993452943838709 \tabularnewline
226 & 0.0149951903144663 & 0.0299903806289325 & 0.985004809685534 \tabularnewline
227 & 0.0115416184372466 & 0.0230832368744931 & 0.988458381562753 \tabularnewline
228 & 0.00835031892340794 & 0.0167006378468159 & 0.991649681076592 \tabularnewline
229 & 0.00609683424321092 & 0.0121936684864218 & 0.993903165756789 \tabularnewline
230 & 0.00441036251732994 & 0.00882072503465989 & 0.99558963748267 \tabularnewline
231 & 0.00439461457994107 & 0.00878922915988213 & 0.995605385420059 \tabularnewline
232 & 0.00814497957146648 & 0.016289959142933 & 0.991855020428533 \tabularnewline
233 & 0.0377565442118785 & 0.075513088423757 & 0.962243455788122 \tabularnewline
234 & 0.0542942200569111 & 0.108588440113822 & 0.945705779943089 \tabularnewline
235 & 0.0405065857547014 & 0.0810131715094027 & 0.959493414245299 \tabularnewline
236 & 0.0361101125951766 & 0.0722202251903532 & 0.963889887404823 \tabularnewline
237 & 0.246505700570201 & 0.493011401140403 & 0.753494299429799 \tabularnewline
238 & 0.200782130963977 & 0.401564261927953 & 0.799217869036023 \tabularnewline
239 & 0.18004440546804 & 0.360088810936079 & 0.81995559453196 \tabularnewline
240 & 0.142128535333137 & 0.284257070666274 & 0.857871464666863 \tabularnewline
241 & 0.113707343103352 & 0.227414686206704 & 0.886292656896648 \tabularnewline
242 & 0.0945301032407296 & 0.189060206481459 & 0.90546989675927 \tabularnewline
243 & 0.0879023187197939 & 0.175804637439588 & 0.912097681280206 \tabularnewline
244 & 0.153550434222245 & 0.307100868444491 & 0.846449565777755 \tabularnewline
245 & 0.137630339717255 & 0.27526067943451 & 0.862369660282745 \tabularnewline
246 & 0.110109330538686 & 0.220218661077371 & 0.889890669461314 \tabularnewline
247 & 0.0777706008222236 & 0.155541201644447 & 0.922229399177776 \tabularnewline
248 & 0.0666948470256243 & 0.133389694051249 & 0.933305152974376 \tabularnewline
249 & 0.0624888270323003 & 0.124977654064601 & 0.9375111729677 \tabularnewline
250 & 0.077380993053961 & 0.154761986107922 & 0.922619006946039 \tabularnewline
251 & 0.0460549764082262 & 0.0921099528164523 & 0.953945023591774 \tabularnewline
252 & 0.112285664162277 & 0.224571328324554 & 0.887714335837723 \tabularnewline
253 & 0.234998511095393 & 0.469997022190785 & 0.765001488904607 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185964&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]0.234449524103323[/C][C]0.468899048206647[/C][C]0.765550475896677[/C][/ROW]
[ROW][C]12[/C][C]0.120293517840556[/C][C]0.240587035681113[/C][C]0.879706482159444[/C][/ROW]
[ROW][C]13[/C][C]0.0815541573457813[/C][C]0.163108314691563[/C][C]0.918445842654219[/C][/ROW]
[ROW][C]14[/C][C]0.102874776497916[/C][C]0.205749552995833[/C][C]0.897125223502084[/C][/ROW]
[ROW][C]15[/C][C]0.0587519756515484[/C][C]0.117503951303097[/C][C]0.941248024348452[/C][/ROW]
[ROW][C]16[/C][C]0.0391686675931635[/C][C]0.0783373351863269[/C][C]0.960831332406836[/C][/ROW]
[ROW][C]17[/C][C]0.063019118444172[/C][C]0.126038236888344[/C][C]0.936980881555828[/C][/ROW]
[ROW][C]18[/C][C]0.255864327935305[/C][C]0.511728655870609[/C][C]0.744135672064695[/C][/ROW]
[ROW][C]19[/C][C]0.194216632900149[/C][C]0.388433265800299[/C][C]0.805783367099851[/C][/ROW]
[ROW][C]20[/C][C]0.13776488333464[/C][C]0.275529766669281[/C][C]0.86223511666536[/C][/ROW]
[ROW][C]21[/C][C]0.0986062615513714[/C][C]0.197212523102743[/C][C]0.901393738448629[/C][/ROW]
[ROW][C]22[/C][C]0.0968533990427696[/C][C]0.193706798085539[/C][C]0.90314660095723[/C][/ROW]
[ROW][C]23[/C][C]0.257054377911142[/C][C]0.514108755822284[/C][C]0.742945622088858[/C][/ROW]
[ROW][C]24[/C][C]0.321495418423946[/C][C]0.642990836847893[/C][C]0.678504581576054[/C][/ROW]
[ROW][C]25[/C][C]0.294869538595026[/C][C]0.589739077190051[/C][C]0.705130461404974[/C][/ROW]
[ROW][C]26[/C][C]0.277447857711978[/C][C]0.554895715423955[/C][C]0.722552142288022[/C][/ROW]
[ROW][C]27[/C][C]0.352098888872553[/C][C]0.704197777745105[/C][C]0.647901111127447[/C][/ROW]
[ROW][C]28[/C][C]0.363849648859334[/C][C]0.727699297718668[/C][C]0.636150351140666[/C][/ROW]
[ROW][C]29[/C][C]0.346785592147584[/C][C]0.693571184295169[/C][C]0.653214407852416[/C][/ROW]
[ROW][C]30[/C][C]0.380898386272269[/C][C]0.761796772544538[/C][C]0.619101613727731[/C][/ROW]
[ROW][C]31[/C][C]0.328675803111158[/C][C]0.657351606222317[/C][C]0.671324196888842[/C][/ROW]
[ROW][C]32[/C][C]0.289492867969931[/C][C]0.578985735939863[/C][C]0.710507132030069[/C][/ROW]
[ROW][C]33[/C][C]0.262490777406895[/C][C]0.524981554813791[/C][C]0.737509222593105[/C][/ROW]
[ROW][C]34[/C][C]0.226304417033043[/C][C]0.452608834066086[/C][C]0.773695582966957[/C][/ROW]
[ROW][C]35[/C][C]0.18788054181459[/C][C]0.37576108362918[/C][C]0.81211945818541[/C][/ROW]
[ROW][C]36[/C][C]0.304929814888214[/C][C]0.609859629776428[/C][C]0.695070185111786[/C][/ROW]
[ROW][C]37[/C][C]0.334971074151201[/C][C]0.669942148302402[/C][C]0.665028925848799[/C][/ROW]
[ROW][C]38[/C][C]0.325963622584246[/C][C]0.651927245168491[/C][C]0.674036377415754[/C][/ROW]
[ROW][C]39[/C][C]0.356022739855431[/C][C]0.712045479710862[/C][C]0.643977260144569[/C][/ROW]
[ROW][C]40[/C][C]0.334209449134641[/C][C]0.668418898269283[/C][C]0.665790550865359[/C][/ROW]
[ROW][C]41[/C][C]0.298001365293739[/C][C]0.596002730587479[/C][C]0.701998634706261[/C][/ROW]
[ROW][C]42[/C][C]0.263835728828225[/C][C]0.527671457656451[/C][C]0.736164271171775[/C][/ROW]
[ROW][C]43[/C][C]0.278274265211435[/C][C]0.55654853042287[/C][C]0.721725734788565[/C][/ROW]
[ROW][C]44[/C][C]0.236536521323923[/C][C]0.473073042647846[/C][C]0.763463478676077[/C][/ROW]
[ROW][C]45[/C][C]0.214442280198157[/C][C]0.428884560396314[/C][C]0.785557719801843[/C][/ROW]
[ROW][C]46[/C][C]0.392689717772563[/C][C]0.785379435545127[/C][C]0.607310282227437[/C][/ROW]
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[ROW][C]130[/C][C]0.00655323802881191[/C][C]0.0131064760576238[/C][C]0.993446761971188[/C][/ROW]
[ROW][C]131[/C][C]0.0135402943899648[/C][C]0.0270805887799297[/C][C]0.986459705610035[/C][/ROW]
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[ROW][C]183[/C][C]0.00560936622575505[/C][C]0.0112187324515101[/C][C]0.994390633774245[/C][/ROW]
[ROW][C]184[/C][C]0.00443647295033499[/C][C]0.00887294590066997[/C][C]0.995563527049665[/C][/ROW]
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[ROW][C]186[/C][C]0.0816845811721911[/C][C]0.163369162344382[/C][C]0.918315418827809[/C][/ROW]
[ROW][C]187[/C][C]0.0928439802674425[/C][C]0.185687960534885[/C][C]0.907156019732557[/C][/ROW]
[ROW][C]188[/C][C]0.0802127135646733[/C][C]0.160425427129347[/C][C]0.919787286435327[/C][/ROW]
[ROW][C]189[/C][C]0.0679596339456167[/C][C]0.135919267891233[/C][C]0.932040366054383[/C][/ROW]
[ROW][C]190[/C][C]0.0563561435032738[/C][C]0.112712287006548[/C][C]0.943643856496726[/C][/ROW]
[ROW][C]191[/C][C]0.0497111618841623[/C][C]0.0994223237683247[/C][C]0.950288838115838[/C][/ROW]
[ROW][C]192[/C][C]0.0419611933152222[/C][C]0.0839223866304445[/C][C]0.958038806684778[/C][/ROW]
[ROW][C]193[/C][C]0.0487155279839555[/C][C]0.097431055967911[/C][C]0.951284472016044[/C][/ROW]
[ROW][C]194[/C][C]0.0522890666310381[/C][C]0.104578133262076[/C][C]0.947710933368962[/C][/ROW]
[ROW][C]195[/C][C]0.0443811738269573[/C][C]0.0887623476539145[/C][C]0.955618826173043[/C][/ROW]
[ROW][C]196[/C][C]0.037026328217237[/C][C]0.0740526564344739[/C][C]0.962973671782763[/C][/ROW]
[ROW][C]197[/C][C]0.0483157061172395[/C][C]0.0966314122344789[/C][C]0.951684293882761[/C][/ROW]
[ROW][C]198[/C][C]0.0395862946218528[/C][C]0.0791725892437057[/C][C]0.960413705378147[/C][/ROW]
[ROW][C]199[/C][C]0.0367011562951475[/C][C]0.073402312590295[/C][C]0.963298843704853[/C][/ROW]
[ROW][C]200[/C][C]0.0310398676134198[/C][C]0.0620797352268397[/C][C]0.96896013238658[/C][/ROW]
[ROW][C]201[/C][C]0.0292219724944833[/C][C]0.0584439449889665[/C][C]0.970778027505517[/C][/ROW]
[ROW][C]202[/C][C]0.0243805707067277[/C][C]0.0487611414134554[/C][C]0.975619429293272[/C][/ROW]
[ROW][C]203[/C][C]0.0313053691066302[/C][C]0.0626107382132604[/C][C]0.96869463089337[/C][/ROW]
[ROW][C]204[/C][C]0.0356803177739391[/C][C]0.0713606355478783[/C][C]0.964319682226061[/C][/ROW]
[ROW][C]205[/C][C]0.0389063363767213[/C][C]0.0778126727534425[/C][C]0.961093663623279[/C][/ROW]
[ROW][C]206[/C][C]0.030879154542079[/C][C]0.0617583090841579[/C][C]0.969120845457921[/C][/ROW]
[ROW][C]207[/C][C]0.0303422228248085[/C][C]0.060684445649617[/C][C]0.969657777175192[/C][/ROW]
[ROW][C]208[/C][C]0.0249498727311462[/C][C]0.0498997454622924[/C][C]0.975050127268854[/C][/ROW]
[ROW][C]209[/C][C]0.0278681412054705[/C][C]0.055736282410941[/C][C]0.97213185879453[/C][/ROW]
[ROW][C]210[/C][C]0.0225417426210891[/C][C]0.0450834852421783[/C][C]0.977458257378911[/C][/ROW]
[ROW][C]211[/C][C]0.0249775332931389[/C][C]0.0499550665862778[/C][C]0.975022466706861[/C][/ROW]
[ROW][C]212[/C][C]0.0399735087423003[/C][C]0.0799470174846007[/C][C]0.9600264912577[/C][/ROW]
[ROW][C]213[/C][C]0.0315871062441673[/C][C]0.0631742124883345[/C][C]0.968412893755833[/C][/ROW]
[ROW][C]214[/C][C]0.0441589425989395[/C][C]0.0883178851978789[/C][C]0.955841057401061[/C][/ROW]
[ROW][C]215[/C][C]0.0380593092869374[/C][C]0.0761186185738748[/C][C]0.961940690713063[/C][/ROW]
[ROW][C]216[/C][C]0.0297508259210563[/C][C]0.0595016518421126[/C][C]0.970249174078944[/C][/ROW]
[ROW][C]217[/C][C]0.0321955312729054[/C][C]0.0643910625458109[/C][C]0.967804468727095[/C][/ROW]
[ROW][C]218[/C][C]0.0275294909822652[/C][C]0.0550589819645304[/C][C]0.972470509017735[/C][/ROW]
[ROW][C]219[/C][C]0.0247418070044538[/C][C]0.0494836140089075[/C][C]0.975258192995546[/C][/ROW]
[ROW][C]220[/C][C]0.0189633773705705[/C][C]0.037926754741141[/C][C]0.981036622629429[/C][/ROW]
[ROW][C]221[/C][C]0.0168947339209676[/C][C]0.0337894678419351[/C][C]0.983105266079032[/C][/ROW]
[ROW][C]222[/C][C]0.0124206485849153[/C][C]0.0248412971698306[/C][C]0.987579351415085[/C][/ROW]
[ROW][C]223[/C][C]0.00931174186201657[/C][C]0.0186234837240331[/C][C]0.990688258137983[/C][/ROW]
[ROW][C]224[/C][C]0.0075021185439771[/C][C]0.0150042370879542[/C][C]0.992497881456023[/C][/ROW]
[ROW][C]225[/C][C]0.00654705616129089[/C][C]0.0130941123225818[/C][C]0.993452943838709[/C][/ROW]
[ROW][C]226[/C][C]0.0149951903144663[/C][C]0.0299903806289325[/C][C]0.985004809685534[/C][/ROW]
[ROW][C]227[/C][C]0.0115416184372466[/C][C]0.0230832368744931[/C][C]0.988458381562753[/C][/ROW]
[ROW][C]228[/C][C]0.00835031892340794[/C][C]0.0167006378468159[/C][C]0.991649681076592[/C][/ROW]
[ROW][C]229[/C][C]0.00609683424321092[/C][C]0.0121936684864218[/C][C]0.993903165756789[/C][/ROW]
[ROW][C]230[/C][C]0.00441036251732994[/C][C]0.00882072503465989[/C][C]0.99558963748267[/C][/ROW]
[ROW][C]231[/C][C]0.00439461457994107[/C][C]0.00878922915988213[/C][C]0.995605385420059[/C][/ROW]
[ROW][C]232[/C][C]0.00814497957146648[/C][C]0.016289959142933[/C][C]0.991855020428533[/C][/ROW]
[ROW][C]233[/C][C]0.0377565442118785[/C][C]0.075513088423757[/C][C]0.962243455788122[/C][/ROW]
[ROW][C]234[/C][C]0.0542942200569111[/C][C]0.108588440113822[/C][C]0.945705779943089[/C][/ROW]
[ROW][C]235[/C][C]0.0405065857547014[/C][C]0.0810131715094027[/C][C]0.959493414245299[/C][/ROW]
[ROW][C]236[/C][C]0.0361101125951766[/C][C]0.0722202251903532[/C][C]0.963889887404823[/C][/ROW]
[ROW][C]237[/C][C]0.246505700570201[/C][C]0.493011401140403[/C][C]0.753494299429799[/C][/ROW]
[ROW][C]238[/C][C]0.200782130963977[/C][C]0.401564261927953[/C][C]0.799217869036023[/C][/ROW]
[ROW][C]239[/C][C]0.18004440546804[/C][C]0.360088810936079[/C][C]0.81995559453196[/C][/ROW]
[ROW][C]240[/C][C]0.142128535333137[/C][C]0.284257070666274[/C][C]0.857871464666863[/C][/ROW]
[ROW][C]241[/C][C]0.113707343103352[/C][C]0.227414686206704[/C][C]0.886292656896648[/C][/ROW]
[ROW][C]242[/C][C]0.0945301032407296[/C][C]0.189060206481459[/C][C]0.90546989675927[/C][/ROW]
[ROW][C]243[/C][C]0.0879023187197939[/C][C]0.175804637439588[/C][C]0.912097681280206[/C][/ROW]
[ROW][C]244[/C][C]0.153550434222245[/C][C]0.307100868444491[/C][C]0.846449565777755[/C][/ROW]
[ROW][C]245[/C][C]0.137630339717255[/C][C]0.27526067943451[/C][C]0.862369660282745[/C][/ROW]
[ROW][C]246[/C][C]0.110109330538686[/C][C]0.220218661077371[/C][C]0.889890669461314[/C][/ROW]
[ROW][C]247[/C][C]0.0777706008222236[/C][C]0.155541201644447[/C][C]0.922229399177776[/C][/ROW]
[ROW][C]248[/C][C]0.0666948470256243[/C][C]0.133389694051249[/C][C]0.933305152974376[/C][/ROW]
[ROW][C]249[/C][C]0.0624888270323003[/C][C]0.124977654064601[/C][C]0.9375111729677[/C][/ROW]
[ROW][C]250[/C][C]0.077380993053961[/C][C]0.154761986107922[/C][C]0.922619006946039[/C][/ROW]
[ROW][C]251[/C][C]0.0460549764082262[/C][C]0.0921099528164523[/C][C]0.953945023591774[/C][/ROW]
[ROW][C]252[/C][C]0.112285664162277[/C][C]0.224571328324554[/C][C]0.887714335837723[/C][/ROW]
[ROW][C]253[/C][C]0.234998511095393[/C][C]0.469997022190785[/C][C]0.765001488904607[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185964&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185964&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 0.234449524103323 0.468899048206647 0.765550475896677 12 0.120293517840556 0.240587035681113 0.879706482159444 13 0.0815541573457813 0.163108314691563 0.918445842654219 14 0.102874776497916 0.205749552995833 0.897125223502084 15 0.0587519756515484 0.117503951303097 0.941248024348452 16 0.0391686675931635 0.0783373351863269 0.960831332406836 17 0.063019118444172 0.126038236888344 0.936980881555828 18 0.255864327935305 0.511728655870609 0.744135672064695 19 0.194216632900149 0.388433265800299 0.805783367099851 20 0.13776488333464 0.275529766669281 0.86223511666536 21 0.0986062615513714 0.197212523102743 0.901393738448629 22 0.0968533990427696 0.193706798085539 0.90314660095723 23 0.257054377911142 0.514108755822284 0.742945622088858 24 0.321495418423946 0.642990836847893 0.678504581576054 25 0.294869538595026 0.589739077190051 0.705130461404974 26 0.277447857711978 0.554895715423955 0.722552142288022 27 0.352098888872553 0.704197777745105 0.647901111127447 28 0.363849648859334 0.727699297718668 0.636150351140666 29 0.346785592147584 0.693571184295169 0.653214407852416 30 0.380898386272269 0.761796772544538 0.619101613727731 31 0.328675803111158 0.657351606222317 0.671324196888842 32 0.289492867969931 0.578985735939863 0.710507132030069 33 0.262490777406895 0.524981554813791 0.737509222593105 34 0.226304417033043 0.452608834066086 0.773695582966957 35 0.18788054181459 0.37576108362918 0.81211945818541 36 0.304929814888214 0.609859629776428 0.695070185111786 37 0.334971074151201 0.669942148302402 0.665028925848799 38 0.325963622584246 0.651927245168491 0.674036377415754 39 0.356022739855431 0.712045479710862 0.643977260144569 40 0.334209449134641 0.668418898269283 0.665790550865359 41 0.298001365293739 0.596002730587479 0.701998634706261 42 0.263835728828225 0.527671457656451 0.736164271171775 43 0.278274265211435 0.55654853042287 0.721725734788565 44 0.236536521323923 0.473073042647846 0.763463478676077 45 0.214442280198157 0.428884560396314 0.785557719801843 46 0.392689717772563 0.785379435545127 0.607310282227437 47 0.545519033485656 0.908961933028687 0.454480966514344 48 0.496548776402334 0.993097552804668 0.503451223597666 49 0.48321616072475 0.9664323214495 0.51678383927525 50 0.468390230644654 0.936780461289308 0.531609769355346 51 0.423671720349913 0.847343440699825 0.576328279650087 52 0.378169197572532 0.756338395145064 0.621830802427468 53 0.386603609576094 0.773207219152188 0.613396390423906 54 0.369709551282604 0.739419102565208 0.630290448717396 55 0.360937557172321 0.721875114344642 0.639062442827679 56 0.339385238523735 0.67877047704747 0.660614761476265 57 0.299777754262651 0.599555508525302 0.700222245737349 58 0.271157720239434 0.542315440478868 0.728842279760566 59 0.236694269796537 0.473388539593074 0.763305730203463 60 0.242458614750554 0.484917229501107 0.757541385249446 61 0.218650159104954 0.437300318209908 0.781349840895046 62 0.191735670804925 0.38347134160985 0.808264329195075 63 0.163732057843761 0.327464115687522 0.836267942156239 64 0.137978888894911 0.275957777789822 0.862021111105089 65 0.119073866261542 0.238147732523085 0.880926133738458 66 0.110228851421388 0.220457702842776 0.889771148578612 67 0.105986150241297 0.211972300482594 0.894013849758703 68 0.22305867935604 0.44611735871208 0.77694132064396 69 0.313038852663478 0.626077705326956 0.686961147336522 70 0.282142509826924 0.564285019653848 0.717857490173076 71 0.397902377321227 0.795804754642453 0.602097622678773 72 0.359897835237818 0.719795670475636 0.640102164762182 73 0.351564646488888 0.703129292977775 0.648435353511112 74 0.336197027115226 0.672394054230451 0.663802972884775 75 0.304024154874088 0.608048309748175 0.695975845125912 76 0.36954472555895 0.739089451117899 0.63045527444105 77 0.333817781175647 0.667635562351294 0.666182218824353 78 0.312977052653639 0.625954105307278 0.687022947346361 79 0.326056568919716 0.652113137839433 0.673943431080284 80 0.298478347311549 0.596956694623099 0.701521652688451 81 0.270341906890839 0.540683813781679 0.729658093109161 82 0.239446042587498 0.478892085174996 0.760553957412502 83 0.215139662822707 0.430279325645414 0.784860337177293 84 0.187913722738408 0.375827445476815 0.812086277261592 85 0.184607191674078 0.369214383348156 0.815392808325922 86 0.159572512041598 0.319145024083196 0.840427487958402 87 0.140322537361322 0.280645074722645 0.859677462638678 88 0.130738801764796 0.261477603529591 0.869261198235204 89 0.112976437875893 0.225952875751786 0.887023562124107 90 0.110203114219271 0.220406228438542 0.889796885780729 91 0.0942919369448659 0.188583873889732 0.905708063055134 92 0.0814240906086617 0.162848181217323 0.918575909391338 93 0.0691622046865876 0.138324409373175 0.930837795313412 94 0.0710505619641146 0.142101123928229 0.928949438035885 95 0.0642047750978092 0.128409550195618 0.935795224902191 96 0.0537975865035413 0.107595173007083 0.946202413496459 97 0.0594315146399693 0.118863029279939 0.940568485360031 98 0.0492270511304385 0.098454102260877 0.950772948869562 99 0.0403637971239411 0.0807275942478823 0.959636202876059 100 0.0353149770686558 0.0706299541373116 0.964685022931344 101 0.0313300139468179 0.0626600278936358 0.968669986053182 102 0.0368820710846464 0.0737641421692928 0.963117928915354 103 0.0316513902506374 0.0633027805012748 0.968348609749363 104 0.0285859141191505 0.0571718282383009 0.97141408588085 105 0.0338171358137667 0.0676342716275334 0.966182864186233 106 0.0297170878687312 0.0594341757374624 0.970282912131269 107 0.0241330786284956 0.0482661572569911 0.975866921371504 108 0.0240079113500851 0.0480158227001702 0.975992088649915 109 0.0194515049063909 0.0389030098127817 0.980548495093609 110 0.0159136661421485 0.0318273322842969 0.984086333857851 111 0.0126146522719223 0.0252293045438447 0.987385347728078 112 0.0130381277586825 0.0260762555173651 0.986961872241317 113 0.0116452146478801 0.0232904292957602 0.98835478535212 114 0.0167206560872487 0.0334413121744973 0.983279343912751 115 0.0159710234451857 0.0319420468903713 0.984028976554814 116 0.015281197801685 0.03056239560337 0.984718802198315 117 0.0126390299453941 0.0252780598907883 0.987360970054606 118 0.0126219562493751 0.0252439124987502 0.987378043750625 119 0.0102612016271451 0.0205224032542903 0.989738798372855 120 0.00903802567892109 0.0180760513578422 0.990961974321079 121 0.00735356780301573 0.0147071356060315 0.992646432196984 122 0.0113195512171058 0.0226391024342117 0.988680448782894 123 0.00953849599480365 0.0190769919896073 0.990461504005196 124 0.00847311639172475 0.0169462327834495 0.991526883608275 125 0.00693555972924188 0.0138711194584838 0.993064440270758 126 0.00565042103716446 0.0113008420743289 0.994349578962835 127 0.0050871640127939 0.0101743280255878 0.994912835987206 128 0.00409879352027462 0.00819758704054924 0.995901206479725 129 0.00604886982758688 0.0120977396551738 0.993951130172413 130 0.00655323802881191 0.0131064760576238 0.993446761971188 131 0.0135402943899648 0.0270805887799297 0.986459705610035 132 0.0162987275042286 0.0325974550084572 0.983701272495771 133 0.0175823649816717 0.0351647299633434 0.982417635018328 134 0.0169833449919507 0.0339666899839014 0.983016655008049 135 0.013880374473478 0.027760748946956 0.986119625526522 136 0.0117123386997017 0.0234246773994033 0.988287661300298 137 0.0093746433382091 0.0187492866764182 0.990625356661791 138 0.0114169021588462 0.0228338043176924 0.988583097841154 139 0.00993713987951826 0.0198742797590365 0.990062860120482 140 0.0112928154997636 0.0225856309995272 0.988707184500236 141 0.0175165648200136 0.0350331296400271 0.982483435179986 142 0.0159289579009632 0.0318579158019264 0.984071042099037 143 0.0126831635932341 0.0253663271864682 0.987316836406766 144 0.0134458333059833 0.0268916666119666 0.986554166694017 145 0.0256403134895237 0.0512806269790473 0.974359686510476 146 0.0314184109533001 0.0628368219066001 0.9685815890467 147 0.0329795780363351 0.0659591560726702 0.967020421963665 148 0.0297734227101545 0.0595468454203091 0.970226577289845 149 0.0248127287409387 0.0496254574818775 0.975187271259061 150 0.0344362320643675 0.0688724641287351 0.965563767935632 151 0.0297124189393621 0.0594248378787242 0.970287581060638 152 0.0312806581649013 0.0625613163298026 0.968719341835099 153 0.0638804329782772 0.127760865956554 0.936119567021723 154 0.0627614357271258 0.125522871454252 0.937238564272874 155 0.0721747771912981 0.144349554382596 0.927825222808702 156 0.0617478574339026 0.123495714867805 0.938252142566097 157 0.0551628794160272 0.110325758832054 0.944837120583973 158 0.0482704122823341 0.0965408245646683 0.951729587717666 159 0.0472261086820222 0.0944522173640445 0.952773891317978 160 0.0404930281933104 0.0809860563866209 0.95950697180669 161 0.0334124305697173 0.0668248611394345 0.966587569430283 162 0.0274667952760025 0.0549335905520051 0.972533204723998 163 0.0228756533010376 0.0457513066020752 0.977124346698962 164 0.0192964132818175 0.0385928265636349 0.980703586718183 165 0.0169353563376047 0.0338707126752094 0.983064643662395 166 0.0171843050634622 0.0343686101269243 0.982815694936538 167 0.0138076243872407 0.0276152487744814 0.986192375612759 168 0.0203735861261564 0.0407471722523128 0.979626413873844 169 0.0201928859457744 0.0403857718915488 0.979807114054226 170 0.0188580171726759 0.0377160343453517 0.981141982827324 171 0.0181349653406303 0.0362699306812606 0.98186503465937 172 0.0146941965866962 0.0293883931733924 0.985305803413304 173 0.0147422907486942 0.0294845814973884 0.985257709251306 174 0.0164226161640716 0.0328452323281431 0.983577383835928 175 0.0219494596798679 0.0438989193597359 0.978050540320132 176 0.0176531523212622 0.0353063046425244 0.982346847678738 177 0.0143826922510691 0.0287653845021382 0.985617307748931 178 0.011742742838476 0.0234854856769521 0.988257257161524 179 0.00919215979401765 0.0183843195880353 0.990807840205982 180 0.00800536172863929 0.0160107234572786 0.991994638271361 181 0.00660360418668578 0.0132072083733716 0.993396395813314 182 0.00534521714955193 0.0106904342991039 0.994654782850448 183 0.00560936622575505 0.0112187324515101 0.994390633774245 184 0.00443647295033499 0.00887294590066997 0.995563527049665 185 0.094086539900982 0.188173079801964 0.905913460099018 186 0.0816845811721911 0.163369162344382 0.918315418827809 187 0.0928439802674425 0.185687960534885 0.907156019732557 188 0.0802127135646733 0.160425427129347 0.919787286435327 189 0.0679596339456167 0.135919267891233 0.932040366054383 190 0.0563561435032738 0.112712287006548 0.943643856496726 191 0.0497111618841623 0.0994223237683247 0.950288838115838 192 0.0419611933152222 0.0839223866304445 0.958038806684778 193 0.0487155279839555 0.097431055967911 0.951284472016044 194 0.0522890666310381 0.104578133262076 0.947710933368962 195 0.0443811738269573 0.0887623476539145 0.955618826173043 196 0.037026328217237 0.0740526564344739 0.962973671782763 197 0.0483157061172395 0.0966314122344789 0.951684293882761 198 0.0395862946218528 0.0791725892437057 0.960413705378147 199 0.0367011562951475 0.073402312590295 0.963298843704853 200 0.0310398676134198 0.0620797352268397 0.96896013238658 201 0.0292219724944833 0.0584439449889665 0.970778027505517 202 0.0243805707067277 0.0487611414134554 0.975619429293272 203 0.0313053691066302 0.0626107382132604 0.96869463089337 204 0.0356803177739391 0.0713606355478783 0.964319682226061 205 0.0389063363767213 0.0778126727534425 0.961093663623279 206 0.030879154542079 0.0617583090841579 0.969120845457921 207 0.0303422228248085 0.060684445649617 0.969657777175192 208 0.0249498727311462 0.0498997454622924 0.975050127268854 209 0.0278681412054705 0.055736282410941 0.97213185879453 210 0.0225417426210891 0.0450834852421783 0.977458257378911 211 0.0249775332931389 0.0499550665862778 0.975022466706861 212 0.0399735087423003 0.0799470174846007 0.9600264912577 213 0.0315871062441673 0.0631742124883345 0.968412893755833 214 0.0441589425989395 0.0883178851978789 0.955841057401061 215 0.0380593092869374 0.0761186185738748 0.961940690713063 216 0.0297508259210563 0.0595016518421126 0.970249174078944 217 0.0321955312729054 0.0643910625458109 0.967804468727095 218 0.0275294909822652 0.0550589819645304 0.972470509017735 219 0.0247418070044538 0.0494836140089075 0.975258192995546 220 0.0189633773705705 0.037926754741141 0.981036622629429 221 0.0168947339209676 0.0337894678419351 0.983105266079032 222 0.0124206485849153 0.0248412971698306 0.987579351415085 223 0.00931174186201657 0.0186234837240331 0.990688258137983 224 0.0075021185439771 0.0150042370879542 0.992497881456023 225 0.00654705616129089 0.0130941123225818 0.993452943838709 226 0.0149951903144663 0.0299903806289325 0.985004809685534 227 0.0115416184372466 0.0230832368744931 0.988458381562753 228 0.00835031892340794 0.0167006378468159 0.991649681076592 229 0.00609683424321092 0.0121936684864218 0.993903165756789 230 0.00441036251732994 0.00882072503465989 0.99558963748267 231 0.00439461457994107 0.00878922915988213 0.995605385420059 232 0.00814497957146648 0.016289959142933 0.991855020428533 233 0.0377565442118785 0.075513088423757 0.962243455788122 234 0.0542942200569111 0.108588440113822 0.945705779943089 235 0.0405065857547014 0.0810131715094027 0.959493414245299 236 0.0361101125951766 0.0722202251903532 0.963889887404823 237 0.246505700570201 0.493011401140403 0.753494299429799 238 0.200782130963977 0.401564261927953 0.799217869036023 239 0.18004440546804 0.360088810936079 0.81995559453196 240 0.142128535333137 0.284257070666274 0.857871464666863 241 0.113707343103352 0.227414686206704 0.886292656896648 242 0.0945301032407296 0.189060206481459 0.90546989675927 243 0.0879023187197939 0.175804637439588 0.912097681280206 244 0.153550434222245 0.307100868444491 0.846449565777755 245 0.137630339717255 0.27526067943451 0.862369660282745 246 0.110109330538686 0.220218661077371 0.889890669461314 247 0.0777706008222236 0.155541201644447 0.922229399177776 248 0.0666948470256243 0.133389694051249 0.933305152974376 249 0.0624888270323003 0.124977654064601 0.9375111729677 250 0.077380993053961 0.154761986107922 0.922619006946039 251 0.0460549764082262 0.0921099528164523 0.953945023591774 252 0.112285664162277 0.224571328324554 0.887714335837723 253 0.234998511095393 0.469997022190785 0.765001488904607

 Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity Description # significant tests % significant tests OK/NOK 1% type I error level 4 0.0164609053497942 NOK 5% type I error level 79 0.325102880658436 NOK 10% type I error level 128 0.526748971193416 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 & 4 & 0.0164609053497942 & NOK \tabularnewline
5% type I error level & 79 & 0.325102880658436 & NOK \tabularnewline
10% type I error level & 128 & 0.526748971193416 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185964&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]4[/C][C]0.0164609053497942[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]79[/C][C]0.325102880658436[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]128[/C][C]0.526748971193416[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185964&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185964&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 4 0.0164609053497942 NOK 5% type I error level 79 0.325102880658436 NOK 10% type I error level 128 0.526748971193416 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')}