## 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 computationFri, 02 Nov 2012 18:58:34 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/02/t1351897229p8frwosg771plcy.htm/, Retrieved Mon, 27 Jun 2022 05:39:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185683, Retrieved Mon, 27 Jun 2022 05:39:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact85
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2012-11-02 22:58:34] [7338cd26db379c04f0557b08db763c32] [Current]
- RM      [Multiple Regression] [] [2012-12-21 19:25:22] [74be16979710d4c4e7c6647856088456]
- RMPD    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2012-12-21 20:08:44] [391561951b5d7f721cfaa4f5575ab127]
- RM        [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2012-12-21 20:11:23] [391561951b5d7f721cfaa4f5575ab127]
- RMPD      [Two-Way ANOVA] [] [2012-12-21 20:49:26] [391561951b5d7f721cfaa4f5575ab127]
- RMPD      [Multiple Regression] [] [2012-12-21 21:06:17] [391561951b5d7f721cfaa4f5575ab127]
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Dataseries X:
9	41	38	13	12	14	12	53	32
9	39	32	16	11	18	11	83	51
9	30	35	19	15	11	14	66	42
9	31	33	15	6	12	12	67	41
9	34	37	14	13	16	21	76	46
9	35	29	13	10	18	12	78	47
9	39	31	19	12	14	22	53	37
9	34	36	15	14	14	11	80	49
9	36	35	14	12	15	10	74	45
9	37	38	15	9	15	13	76	47
9	38	31	16	10	17	10	79	49
9	36	34	16	12	19	8	54	33
9	38	35	16	12	10	15	67	42
9	39	38	16	11	16	14	54	33
9	33	37	17	15	18	10	87	53
9	32	33	15	12	14	14	58	36
9	36	32	15	10	14	14	75	45
9	38	38	20	12	17	11	88	54
9	39	38	18	11	14	10	64	41
9	32	32	16	12	16	13	57	36
9	32	33	16	11	18	9.5	66	41
9	31	31	16	12	11	14	68	44
9	39	38	19	13	14	12	54	33
9	37	39	16	11	12	14	56	37
9	39	32	17	12	17	11	86	52
9	41	32	17	13	9	9	80	47
9	36	35	16	10	16	11	76	43
9	33	37	15	14	14	15	69	44
9	33	33	16	12	15	14	78	45
9	34	33	14	10	11	13	67	44
9	31	31	15	12	16	9	80	49
9	27	32	12	8	13	15	54	33
9	37	31	14	10	17	10	71	43
9	34	37	16	12	15	11	84	54
9	34	30	14	12	14	13	74	42
9	32	33	10	7	16	8	71	44
9	29	31	10	9	9	20	63	37
9	36	33	14	12	15	12	71	43
9	29	31	16	10	17	10	76	46
9	35	33	16	10	13	10	69	42
9	37	32	16	10	15	9	74	45
9	34	33	14	12	16	14	75	44
9	38	32	20	15	16	8	54	33
9	35	33	14	10	12	14	52	31
9	38	28	14	10	15	11	69	42
9	37	35	11	12	11	13	68	40
9	38	39	14	13	15	9	65	43
9	33	34	15	11	15	11	75	46
9	36	38	16	11	17	15	74	42
9	38	32	14	12	13	11	75	45
9	32	38	16	14	16	10	72	44
9	32	30	14	10	14	14	67	40
9	32	33	12	12	11	18	63	37
9	34	38	16	13	12	14	62	46
9	32	32	9	5	12	11	63	36
9	37	35	14	6	15	14.5	76	47
9	39	34	16	12	16	13	74	45
9	29	34	16	12	15	9	67	42
9	37	36	15	11	12	10	73	43
9	35	34	16	10	12	15	70	43
9	30	28	12	7	8	20	53	32
9	38	34	16	12	13	12	77	45
9	34	35	16	14	11	12	80	48
9	31	35	14	11	14	14	52	31
9	34	31	16	12	15	13	54	33
10	35	37	17	13	10	11	80	49
10	36	35	18	14	11	17	66	42
10	30	27	18	11	12	12	73	41
10	39	40	12	12	15	13	63	38
10	35	37	16	12	15	14	69	42
10	38	36	10	8	14	13	67	44
10	31	38	14	11	16	15	54	33
10	34	39	18	14	15	13	81	48
10	38	41	18	14	15	10	69	40
10	34	27	16	12	13	11	84	50
10	39	30	17	9	12	19	80	49
10	37	37	16	13	17	13	70	43
10	34	31	16	11	13	17	69	44
10	28	31	13	12	15	13	77	47
10	37	27	16	12	13	9	54	33
10	33	36	16	12	15	11	79	46
10	35	37	16	12	15	9	71	45
10	37	33	15	12	16	12	73	43
10	32	34	15	11	15	12	72	44
10	33	31	16	10	14	13	77	47
10	38	39	14	9	15	13	75	45
10	33	34	16	12	14	12	69	42
10	29	32	16	12	13	15	54	33
10	33	33	15	12	7	22	70	43
10	31	36	12	9	17	13	73	46
10	36	32	17	15	13	15	54	33
10	35	41	16	12	15	13	77	46
10	32	28	15	12	14	15	82	48
10	29	30	13	12	13	12.5	80	47
10	39	36	16	10	16	11	80	47
10	37	35	16	13	12	16	69	43
10	35	31	16	9	14	11	78	46
10	37	34	16	12	17	11	81	48
10	32	36	14	10	15	10	76	46
10	38	36	16	14	17	10	76	45
10	37	35	16	11	12	16	73	45
10	36	37	20	15	16	12	85	52
10	32	28	15	11	11	11	66	42
10	33	39	16	11	15	16	79	47
10	40	32	13	12	9	19	68	41
10	38	35	17	12	16	11	76	47
10	41	39	16	12	15	16	71	43
10	36	35	16	11	10	15	54	33
10	43	42	12	7	10	24	46	30
10	30	34	16	12	15	14	85	52
10	31	33	16	14	11	15	74	44
10	32	41	17	11	13	11	88	55
10	32	33	13	11	14	15	38	11
10	37	34	12	10	18	12	76	47
10	37	32	18	13	16	10	86	53
10	33	40	14	13	14	14	54	33
10	34	40	14	8	14	13	67	44
10	33	35	13	11	14	9	69	42
10	38	36	16	12	14	15	90	55
10	33	37	13	11	12	15	54	33
10	31	27	16	13	14	14	76	46
10	38	39	13	12	15	11	89	54
10	37	38	16	14	15	8	76	47
10	36	31	15	13	15	11	73	45
10	31	33	16	15	13	11	79	47
10	39	32	15	10	17	8	90	55
10	44	39	17	11	17	10	74	44
10	33	36	15	9	19	11	81	53
10	35	33	12	11	15	13	72	44
10	32	33	16	10	13	11	71	42
10	28	32	10	11	9	20	66	40
10	40	37	16	8	15	10	77	46
10	27	30	12	11	15	15	65	40
10	37	38	14	12	15	12	74	46
10	32	29	15	12	16	14	85	53
10	28	22	13	9	11	23	54	33
10	34	35	15	11	14	14	63	42
10	30	35	11	10	11	16	54	35
10	35	34	12	8	15	11	64	40
10	31	35	11	9	13	12	69	41
10	32	34	16	8	15	10	54	33
10	30	37	15	9	16	14	84	51
10	30	35	17	15	14	12	86	53
10	31	23	16	11	15	12	77	46
10	40	31	10	8	16	11	89	55
10	32	27	18	13	16	12	76	47
10	36	36	13	12	11	13	60	38
10	32	31	16	12	12	11	75	46
10	35	32	13	9	9	19	73	46
10	38	39	10	7	16	12	85	53
10	42	37	15	13	13	17	79	47
10	34	38	16	9	16	9	71	41
10	35	39	16	6	12	12	72	44
9	38	34	14	8	9	19	69	43
10	33	31	10	8	13	18	78	51
10	36	32	17	15	13	15	54	33
10	32	37	13	6	14	14	69	43
10	33	36	15	9	19	11	81	53
10	34	32	16	11	13	9	84	51
10	32	38	12	8	12	18	84	50
10	34	36	13	8	13	16	69	46
11	27	26	13	10	10	24	66	43
11	31	26	12	8	14	14	81	47
11	38	33	17	14	16	20	82	50
11	34	39	15	10	10	18	72	43
11	24	30	10	8	11	23	54	33
11	30	33	14	11	14	12	78	48
11	26	25	11	12	12	14	74	44
11	34	38	13	12	9	16	82	50
11	27	37	16	12	9	18	73	41
11	37	31	12	5	11	20	55	34
11	36	37	16	12	16	12	72	44
11	41	35	12	10	9	12	78	47
11	29	25	9	7	13	17	59	35
11	36	28	12	12	16	13	72	44
11	32	35	15	11	13	9	78	44
11	37	33	12	8	9	16	68	43
11	30	30	12	9	12	18	69	41
11	31	31	14	10	16	10	67	41
11	38	37	12	9	11	14	74	42
11	36	36	16	12	14	11	54	33
11	35	30	11	6	13	9	67	41
11	31	36	19	15	15	11	70	44
11	38	32	15	12	14	10	80	48
11	22	28	8	12	16	11	89	55
11	32	36	16	12	13	19	76	44
11	36	34	17	11	14	14	74	43
11	39	31	12	7	15	12	87	52
11	28	28	11	7	13	14	54	30
11	32	36	11	5	11	21	61	39
11	32	36	14	12	11	13	38	11
11	38	40	16	12	14	10	75	44
11	32	33	12	3	15	15	69	42
11	35	37	16	11	11	16	62	41
11	32	32	13	10	15	14	72	44
11	37	38	15	12	12	12	70	44
11	34	31	16	9	14	19	79	48
11	33	37	16	12	14	15	87	53
11	33	33	14	9	8	19	62	37
11	26	32	16	12	13	13	77	44
11	30	30	16	12	9	17	69	44
11	24	30	14	10	15	12	69	40
11	34	31	11	9	17	11	75	42
11	34	32	12	12	13	14	54	35
11	33	34	15	8	15	11	72	43
11	34	36	15	11	15	13	74	45
11	35	37	16	11	14	12	85	55
11	35	36	16	12	16	15	52	31
11	36	33	11	10	13	14	70	44
11	34	33	15	10	16	12	84	50
11	34	33	12	12	9	17	64	40
11	41	44	12	12	16	11	84	53
11	32	39	15	11	11	18	87	54
11	30	32	15	8	10	13	79	49
11	35	35	16	12	11	17	67	40
11	28	25	14	10	15	13	65	41
11	33	35	17	11	17	11	85	52
11	39	34	14	10	14	12	83	52
11	36	35	13	8	8	22	61	36
11	36	39	15	12	15	14	82	52
11	35	33	13	12	11	12	76	46
11	38	36	14	10	16	12	58	31
11	33	32	15	12	10	17	72	44
11	31	32	12	9	15	9	72	44
11	34	36	13	9	9	21	38	11
11	32	36	8	6	16	10	78	46
11	31	32	14	10	19	11	54	33
11	33	34	14	9	12	12	63	34
11	34	33	11	9	8	23	66	42
11	34	35	12	9	11	13	70	43
11	34	30	13	6	14	12	71	43
11	33	38	10	10	9	16	67	44
11	32	34	16	6	15	9	58	36
11	41	33	18	14	13	17	72	46
11	34	32	13	10	16	9	72	44
11	36	31	11	10	11	14	70	43
11	37	30	4	6	12	17	76	50
11	36	27	13	12	13	13	50	33
11	29	31	16	12	10	11	72	43
11	37	30	10	7	11	12	72	44
11	27	32	12	8	12	10	88	53
11	35	35	12	11	8	19	53	34
11	28	28	10	3	12	16	58	35
11	35	33	13	6	12	16	66	40
11	37	31	15	10	15	14	82	53
11	29	35	12	8	11	20	69	42
11	32	35	14	9	13	15	68	43
11	36	32	10	9	14	23	44	29
11	19	21	12	8	10	20	56	36
11	21	20	12	9	12	16	53	30
11	31	34	11	7	15	14	70	42
11	33	32	10	7	13	17	78	47
11	36	34	12	6	13	11	71	44
11	33	32	16	9	13	13	72	45
11	37	33	12	10	12	17	68	44
11	34	33	14	11	12	15	67	43
11	35	37	16	12	9	21	75	43
11	31	32	14	8	9	18	62	40
11	37	34	13	11	15	15	67	41
11	35	30	4	3	10	8	83	52
11	27	30	15	11	14	12	64	38
11	34	38	11	12	15	12	68	41
11	40	36	11	7	7	22	62	39
11	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 13 seconds R Server 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 13 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185683&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185683&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185683&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 13 seconds R Server 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

 Multiple Linear Regression - Estimated Regression Equation Learning[t] = + 8.35046999716967 -0.404599312019866Month[t] + 0.0347834365471906Connected[t] + 0.0433406498517761Separated[t] + 0.576062196352004Software[t] + 0.0796225833189934Happyness[t] -0.0261020091912696Depression[t] + 0.0282902834264207Beloning[t] -0.032651180900308Belonging_final[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  8.35046999716967 -0.404599312019866Month[t] +  0.0347834365471906Connected[t] +  0.0433406498517761Separated[t] +  0.576062196352004Software[t] +  0.0796225833189934Happyness[t] -0.0261020091912696Depression[t] +  0.0282902834264207Beloning[t] -0.032651180900308Belonging_final[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185683&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  8.35046999716967 -0.404599312019866Month[t] +  0.0347834365471906Connected[t] +  0.0433406498517761Separated[t] +  0.576062196352004Software[t] +  0.0796225833189934Happyness[t] -0.0261020091912696Depression[t] +  0.0282902834264207Beloning[t] -0.032651180900308Belonging_final[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185683&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185683&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] = + 8.35046999716967 -0.404599312019866Month[t] + 0.0347834365471906Connected[t] + 0.0433406498517761Separated[t] + 0.576062196352004Software[t] + 0.0796225833189934Happyness[t] -0.0261020091912696Depression[t] + 0.0282902834264207Beloning[t] -0.032651180900308Belonging_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) 8.35046999716967 2.61698 3.1909 0.001596 0.000798 Month -0.404599312019866 0.159517 -2.5364 0.011797 0.005898 Connected 0.0347834365471906 0.034756 1.0008 0.317879 0.15894 Separated 0.0433406498517761 0.03528 1.2285 0.220402 0.110201 Software 0.576062196352004 0.052771 10.9163 0 0 Happyness 0.0796225833189934 0.057845 1.3765 0.169879 0.08494 Depression -0.0261020091912696 0.042437 -0.6151 0.53905 0.269525 Beloning 0.0282902834264207 0.037766 0.7491 0.454497 0.227248 Belonging_final -0.032651180900308 0.056098 -0.582 0.561053 0.280527

\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) & 8.35046999716967 & 2.61698 & 3.1909 & 0.001596 & 0.000798 \tabularnewline
Month & -0.404599312019866 & 0.159517 & -2.5364 & 0.011797 & 0.005898 \tabularnewline
Connected & 0.0347834365471906 & 0.034756 & 1.0008 & 0.317879 & 0.15894 \tabularnewline
Separated & 0.0433406498517761 & 0.03528 & 1.2285 & 0.220402 & 0.110201 \tabularnewline
Software & 0.576062196352004 & 0.052771 & 10.9163 & 0 & 0 \tabularnewline
Happyness & 0.0796225833189934 & 0.057845 & 1.3765 & 0.169879 & 0.08494 \tabularnewline
Depression & -0.0261020091912696 & 0.042437 & -0.6151 & 0.53905 & 0.269525 \tabularnewline
Beloning & 0.0282902834264207 & 0.037766 & 0.7491 & 0.454497 & 0.227248 \tabularnewline
Belonging_final & -0.032651180900308 & 0.056098 & -0.582 & 0.561053 & 0.280527 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185683&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]8.35046999716967[/C][C]2.61698[/C][C]3.1909[/C][C]0.001596[/C][C]0.000798[/C][/ROW]
[ROW][C]Month[/C][C]-0.404599312019866[/C][C]0.159517[/C][C]-2.5364[/C][C]0.011797[/C][C]0.005898[/C][/ROW]
[ROW][C]Connected[/C][C]0.0347834365471906[/C][C]0.034756[/C][C]1.0008[/C][C]0.317879[/C][C]0.15894[/C][/ROW]
[ROW][C]Separated[/C][C]0.0433406498517761[/C][C]0.03528[/C][C]1.2285[/C][C]0.220402[/C][C]0.110201[/C][/ROW]
[ROW][C]Software[/C][C]0.576062196352004[/C][C]0.052771[/C][C]10.9163[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Happyness[/C][C]0.0796225833189934[/C][C]0.057845[/C][C]1.3765[/C][C]0.169879[/C][C]0.08494[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0261020091912696[/C][C]0.042437[/C][C]-0.6151[/C][C]0.53905[/C][C]0.269525[/C][/ROW]
[ROW][C]Beloning[/C][C]0.0282902834264207[/C][C]0.037766[/C][C]0.7491[/C][C]0.454497[/C][C]0.227248[/C][/ROW]
[ROW][C]Belonging_final[/C][C]-0.032651180900308[/C][C]0.056098[/C][C]-0.582[/C][C]0.561053[/C][C]0.280527[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185683&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185683&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) 8.35046999716967 2.61698 3.1909 0.001596 0.000798 Month -0.404599312019866 0.159517 -2.5364 0.011797 0.005898 Connected 0.0347834365471906 0.034756 1.0008 0.317879 0.15894 Separated 0.0433406498517761 0.03528 1.2285 0.220402 0.110201 Software 0.576062196352004 0.052771 10.9163 0 0 Happyness 0.0796225833189934 0.057845 1.3765 0.169879 0.08494 Depression -0.0261020091912696 0.042437 -0.6151 0.53905 0.269525 Beloning 0.0282902834264207 0.037766 0.7491 0.454497 0.227248 Belonging_final -0.032651180900308 0.056098 -0.582 0.561053 0.280527

 Multiple Linear Regression - Regression Statistics Multiple R 0.664098147499978 R-squared 0.441026349512903 Adjusted R-squared 0.423489921262327 F-TEST (value) 25.1491548456241 F-TEST (DF numerator) 8 F-TEST (DF denominator) 255 p-value 0 Multiple Linear Regression - Residual Statistics Residual Standard Deviation 1.86477720145106 Sum Squared Residuals 886.735472818167

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.664098147499978 \tabularnewline
R-squared & 0.441026349512903 \tabularnewline
Adjusted R-squared & 0.423489921262327 \tabularnewline
F-TEST (value) & 25.1491548456241 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 255 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.86477720145106 \tabularnewline
Sum Squared Residuals & 886.735472818167 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185683&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.664098147499978[/C][/ROW]
[ROW][C]R-squared[/C][C]0.441026349512903[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.423489921262327[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]25.1491548456241[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]255[/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]1.86477720145106[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]886.735472818167[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185683&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185683&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 0.664098147499978 R-squared 0.441026349512903 Adjusted R-squared 0.423489921262327 F-TEST (value) 25.1491548456241 F-TEST (DF numerator) 8 F-TEST (DF denominator) 255 p-value 0 Multiple Linear Regression - Residual Statistics Residual Standard Deviation 1.86477720145106 Sum Squared Residuals 886.735472818167

 Multiple Linear Regression - Actuals, Interpolation, and Residuals Time or Index Actuals InterpolationForecast ResidualsPrediction Error 1 13 15.9509274269783 -2.95092742697833 2 16 15.6181828665753 0.381817133424683 3 19 16.9166643716608 2.0833356283392 4 15 11.8729748073647 3.12702519263533 5 14 16.3580519877682 -2.35805198776817 6 13 14.7360162717571 -1.73601627175708 7 19 15.1537000085073 3.8462999914927 8 15 17.0077560505479 -2.00775605054786 9 14 15.9484454966394 -1.94844549663943 10 15 14.2980364711644 0.701963528835648 11 16 14.8626172377916 1.13738276220844 12 16 16.1018077007214 -0.101807700721448 13 16 15.3893109658985 0.610689034101525 14 16 15.4079786083135 0.592021391686478 15 17 18.0043950630554 -1.00439506305541 16 15 15.3798159239431 -0.379815923943083 17 15 14.5105588177224 0.489441182277558 18 20 16.383380816603 3.61661918339703 19 18 15.3748348655024 2.62516513449764 20 16 15.4935321664941 0.506467833505857 21 16 15.3027694651376 0.697230534862408 22 16 15.0411768247971 0.958823175202897 23 19 16.4530618527621 2.54693814723792 24 16 14.9892378950466 1.01076210495345 25 17 16.1668421489873 0.833157851012718 26 17 16.2212087742073 0.778791225792725 27 16 14.9717246067166 1.0282753932834 28 15 16.7639680138983 -1.76396801389828 29 16 15.7661669842349 0.23383301576509 30 14 14.0778957672031 -0.0778957672030686 31 15 15.7460272839639 -0.746027283963927 32 12 12.7373771224323 -0.737377122432317 33 14 14.7974186192348 -0.797418619234848 34 16 15.9285001202188 0.0714998797812351 35 14 15.6022003060943 -1.60220030609429 36 10 12.9219264013097 -2.92192640130967 37 10 13.0146729900312 -3.01467299003116 38 14 15.7899916900747 -1.78999169007469 39 16 14.5626490012885 1.4373509987115 40 16 14.4721133266155 1.52788667338449 41 16 14.7271846001186 1.27281539988145 42 14 15.8283533347221 -1.82835333472214 43 20 17.5740121132113 2.42598788678869 44 14 14.1663108781857 -0.166310878185677 45 14 14.4929035444449 -0.492903544444921 46 11 15.5799467762799 -4.57994677627985 47 14 16.604228985647 -2.60422898564702 48 15 15.1942294341289 -0.19422943412892 49 16 15.6290939132253 0.370906086774684 50 14 15.7309335277756 -1.73093352777565 51 16 17.1471512900765 -1.14715129007646 52 14 14.2216774089203 -0.221677408920302 53 12 15.1453403734528 -3.14534037345282 54 16 15.869552400713 0.130447599287036 55 9 11.3645521776952 -2.36455217769521 56 14 12.4006749187661 1.59932508123389 57 16 16.0107717121744 -0.0107717121744094 58 16 15.5876443588646 0.412355641135433 59 15 15.2486517151036 -0.248651715103607 60 16 14.3009604497181 1.69903955028194 61 12 11.5680405712374 0.431959428762646 62 16 15.8480933851408 0.15190661485923 63 16 16.7320968224481 -0.732096822448143 64 14 14.8491657946905 -0.849165794690456 65 16 15.4532184988394 0.546781501160583 66 17 15.786728295299 1.21327170470102 67 18 16.0663974549983 1.93360254500173 68 18 14.2236008420055 3.7763991579945 69 12 15.7039588645577 -3.70395886455773 70 16 15.4478381365797 0.552161863420334 71 10 13.0291955081803 -3.02919550818027 72 14 14.6990097947249 -0.699009794724861 73 18 16.8215387173465 1.17846128265349 74 18 17.047385836898 0.952614163101955 75 16 15.0618538666444 0.938146133355616 76 17 13.2686578002251 3.73134219977487 77 16 16.2744534843814 -0.27445348438142 78 16 14.2740950485574 1.7259049514426 79 13 15.0334785537398 -2.03347855373977 80 16 14.9247697671811 1.07523023281889 81 16 15.5655347518703 0.434465248129707 82 16 15.5369752066879 0.463024793312068 83 15 15.5563789647739 -0.556378964773851 84 15 14.7091761878919 0.290823812108053 85 16 13.9756487604527 2.02435123954728 86 14 14.0085733239176 -0.00857332391764814 87 16 15.2208307489935 0.779169251006498 88 16 14.7065934689148 1.29340653108515 89 15 14.3547510265222 0.64524897347781 90 12 13.7050807374168 -1.70508073741682 91 17 16.6782641138012 0.321735886198806 92 16 15.7430202889882 0.256979711011826 93 15 15.0195639849035 -0.0195639849034682 94 13 14.9635980286721 -1.9635980286721 95 16 14.6973726642945 1.30262733570547 96 16 15.6830629570827 0.316937042917328 97 16 13.5822989199044 2.41770108009563 98 16 15.7685105700457 0.231489429954285 99 14 14.3198580815311 -0.319858081531102 100 16 17.0247038337606 -1.02470383376056 101 16 14.5787973362837 1.42120266371627 102 20 17.4687674897041 2.53123251029595 103 15 14.0523046259387 0.947695374061321 104 16 14.956333278217 1.04366672178304 105 13 14.8011674216603 -1.80116742166032 106 17 15.6582118368939 1.34178816310611 107 16 15.7149454231364 0.285054576863643 108 16 14.2651695279915 1.73483047200847 109 12 12.1445025399444 -0.144502539944409 110 16 15.270031730108 0.729968269891964 111 16 16.0190228965521 -0.0190228965520521 112 17 14.972899124327 2.02710087567299 113 13 14.6235262603592 -1.62352626035923 114 12 14.5611065152376 -2.56110651523764 115 18 16.182566405197 1.81743359480299 116 14 15.8742392027801 -1.87423920278009 117 14 13.0634243613986 0.936575638601393 118 13 14.7664152300671 -1.76641523006708 119 16 15.57275380411 0.42724619588997 120 13 14.4067456846915 -1.40674568469149 121 16 15.4391647652899 0.560835234710133 122 13 15.8911672712233 -2.89116727122332 123 16 16.9042581868609 -0.904258186860854 124 15 15.8921534889468 -0.892153488946772 125 16 16.9022361707383 -0.902236170738301 126 15 14.703632062842 0.296367937158025 127 17 15.6113104275905 1.38868957240952 128 15 13.9838607966409 1.01613920335906 129 12 14.7440838384905 -2.74408383849047 130 16 13.9936422626156 2.00635773738435 131 10 13.7576725915982 -3.75767259159822 132 16 13.5176321144828 2.48236788551718 133 12 14.2161631177914 -2.21616311779137 134 14 15.6237963714392 -1.62379637143923 135 15 15.1698667563622 -0.169866756362222 136 13 12.1421557046257 0.857844295374259 137 15 14.5009469200994 0.499053079900598 138 11 13.4686249246835 -2.46862492468349 139 12 13.0157243738586 -1.01572437385864 140 11 13.4194465342762 -2.4194465342762 141 16 12.8831315054463 3.11686849455371 142 15 13.7558505714002 1.24414942859977 143 17 17.0097795066055 -0.00977950660548293 144 16 14.2737946583067 1.72620534169329 145 10 13.3567315625142 -3.35673156251416 146 18 15.6527462059573 2.34725379404272 147 13 15.0228847719538 -2.02288477195382 148 16 14.9620191824016 1.03798081759844 149 13 12.8772591624989 0.122740837501083 150 10 12.9838669107856 -2.98386691078565 151 15 16.1494801243129 -1.14948012431288 152 16 14.0275731378567 1.97242686214327 153 16 11.9110510150754 4.0889489849246 154 14 12.8816202965071 1.11837970349286 155 10 12.5110772982986 -2.51107729829856 156 17 16.6782641138012 0.321735886198806 157 13 11.7748408846068 1.22515911539323 158 15 13.9838607966409 1.01613920335906 159 16 14.7220477570335 1.27795224296651 160 12 12.9024487088536 -0.902448708853643 161 13 12.7234113561509 0.276588643849074 162 13 12.3594447514215 0.640555248578502 163 12 12.21971405789 -0.21971405789 164 17 16.1559256930107 0.844074306989343 165 15 13.4927110110311 1.50728898896894 166 10 11.3690856488793 -1.36908564887932 167 14 14.1511837465642 -0.151183746564223 168 11 14.0473814027883 -3.04738140278828 169 13 14.6284207569089 -1.62842075690889 170 16 14.3286401101092 1.67135988989077 171 12 10.2103695148885 1.78963048511152 172 16 15.2294173512872 0.77058264871283 173 12 13.6789589162402 -1.67895891624021 174 9 11.1422436631215 -2.14224366312148 175 12 14.8132494934299 -2.81324949342992 176 15 14.4367200872182 0.563279912781797 177 12 12.0443133302158 -0.0443133302158332 178 12 12.5271258979837 -0.527125897983652 179 14 13.6520380206879 0.347961979312088 180 12 13.2423636290015 -1.24236362900149 181 16 14.9028714322165 1.09712856778351 182 11 11.2308165908512 -0.230816590851172 183 19 16.6302449667749 2.36975503322511 184 15 15.0709573706774 -0.0709573706773562 185 8 14.5002572284975 -6.50025722849755 186 16 14.7385222746564 1.26147772534355 187 17 14.4011157681125 2.59888423188754 188 12 12.2769350009329 -0.276935000932918 189 11 11.3375926910729 -0.337592691072861 190 11 10.2335393682771 0.766460631722878 191 14 14.7383473626723 -0.738347362672255 192 16 15.4068358759607 0.593164124039307 193 12 9.55486413915182 2.44513586084818 194 16 13.9311014734646 2.06889852653535 195 13 13.589629361434 -0.589629361433986 196 15 14.9324705375573 0.067529462442679 197 16 12.897088019433 3.10291198056704 198 16 15.0180094707273 0.98199052927266 199 14 12.3494785543296 1.6505214456704 200 16 14.5413613945402 1.45863860545976 201 16 13.944593203573 2.05540679642697 202 14 13.3226184610574 0.677381538942582 203 11 13.4275177946163 -2.42751779461626 204 12 14.4367109870216 -2.43671098702159 205 15 12.6699269134548 2.33007308654516 206 15 14.4586524254313 0.541347574568722 207 16 14.4679372463901 1.53206275360993 208 16 14.93164692049 1.06835307951002 209 11 13.5562780239837 -2.5562780239837 210 15 13.9779398017969 1.02206019820312 211 12 14.2029022057862 -2.20290220578625 212 12 15.7784438651911 -3.7784438651911 213 15 14.1440201791006 0.855979820899399 214 15 12.0307032677153 2.9692967322847 215 16 14.5684829589542 1.43151704104576 216 14 13.07313463419 0.92686536580996 217 17 14.6746123754413 2.32538762455869 218 14 13.9423598225196 0.0576401774804177 219 13 11.8905028372228 1.10949716277721 220 15 15.2059654363509 -0.205965436350932 221 13 14.671017170643 -1.67101717064297 222 14 14.1319205655599 -0.131920565559881 223 15 14.3001182465164 0.69988175348359 224 12 13.1092937744911 -1.10929377449114 225 13 12.7116664065425 0.288333593457519 226 8 11.7472131342751 -3.74721313427505 227 14 13.8015801739644 0.198419826035607 228 14 13.0202674279236 0.979732572076422 229 11 12.2297591833159 -1.22975918331585 230 12 12.8968382776945 -0.896838277694454 231 13 11.2452084819542 1.75479151804577 232 10 13.2130657616632 -3.21306576166323 233 16 11.3677174009184 4.63228259908156 234 18 15.9474161696061 2.05258383039392 235 13 13.8693288638037 -0.869328863803708 236 11 13.3430027385425 -2.34300273854247 237 4 10.9726967298314 -6.97269672983141 238 13 14.2678178481433 -1.26781784814329 239 16 14.3069070865238 1.6930929134762 240 10 11.6823923405169 -1.68239234051694 241 12 12.2879119795221 -0.287911979522082 242 12 13.5011921116947 -1.50119211169468 243 10 8.85142253316745 1.14857746683254 244 13 11.1028627902225 1.89713720977749 245 15 13.7092481004796 1.2907518995204 246 12 11.9685057317415 0.0314942682585027 247 14 12.8777319860027 1.12226801399732 248 10 12.5358000227952 -2.53580002279517 249 12 10.7624130858841 1.23758691411589 250 12 11.7393909440044 0.260609055995628 251 11 11.9220624304821 -0.922062430482111 252 10 11.730463172571 -1.73046317257097 253 12 11.4019661994277 0.598033800572314 254 16 12.8825562632821 3.11744373671785 255 12 13.3765522827852 -1.37655228278524 256 14 13.9048290853521 0.0951709146478978 257 16 14.5198797799652 1.48012022003483 258 14 11.6682798848408 2.33172011515923 259 13 14.356690156603 -1.35669015660305 260 4 9.38334580594879 -5.38334580594879 261 15 13.8472593284005 1.15274067159949 262 11 15.1083609537208 -4.10836095372081 263 11 11.3476291943178 -0.347629194317833 264 14 12.9144494714043 1.08555052859574

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 15.9509274269783 & -2.95092742697833 \tabularnewline
2 & 16 & 15.6181828665753 & 0.381817133424683 \tabularnewline
3 & 19 & 16.9166643716608 & 2.0833356283392 \tabularnewline
4 & 15 & 11.8729748073647 & 3.12702519263533 \tabularnewline
5 & 14 & 16.3580519877682 & -2.35805198776817 \tabularnewline
6 & 13 & 14.7360162717571 & -1.73601627175708 \tabularnewline
7 & 19 & 15.1537000085073 & 3.8462999914927 \tabularnewline
8 & 15 & 17.0077560505479 & -2.00775605054786 \tabularnewline
9 & 14 & 15.9484454966394 & -1.94844549663943 \tabularnewline
10 & 15 & 14.2980364711644 & 0.701963528835648 \tabularnewline
11 & 16 & 14.8626172377916 & 1.13738276220844 \tabularnewline
12 & 16 & 16.1018077007214 & -0.101807700721448 \tabularnewline
13 & 16 & 15.3893109658985 & 0.610689034101525 \tabularnewline
14 & 16 & 15.4079786083135 & 0.592021391686478 \tabularnewline
15 & 17 & 18.0043950630554 & -1.00439506305541 \tabularnewline
16 & 15 & 15.3798159239431 & -0.379815923943083 \tabularnewline
17 & 15 & 14.5105588177224 & 0.489441182277558 \tabularnewline
18 & 20 & 16.383380816603 & 3.61661918339703 \tabularnewline
19 & 18 & 15.3748348655024 & 2.62516513449764 \tabularnewline
20 & 16 & 15.4935321664941 & 0.506467833505857 \tabularnewline
21 & 16 & 15.3027694651376 & 0.697230534862408 \tabularnewline
22 & 16 & 15.0411768247971 & 0.958823175202897 \tabularnewline
23 & 19 & 16.4530618527621 & 2.54693814723792 \tabularnewline
24 & 16 & 14.9892378950466 & 1.01076210495345 \tabularnewline
25 & 17 & 16.1668421489873 & 0.833157851012718 \tabularnewline
26 & 17 & 16.2212087742073 & 0.778791225792725 \tabularnewline
27 & 16 & 14.9717246067166 & 1.0282753932834 \tabularnewline
28 & 15 & 16.7639680138983 & -1.76396801389828 \tabularnewline
29 & 16 & 15.7661669842349 & 0.23383301576509 \tabularnewline
30 & 14 & 14.0778957672031 & -0.0778957672030686 \tabularnewline
31 & 15 & 15.7460272839639 & -0.746027283963927 \tabularnewline
32 & 12 & 12.7373771224323 & -0.737377122432317 \tabularnewline
33 & 14 & 14.7974186192348 & -0.797418619234848 \tabularnewline
34 & 16 & 15.9285001202188 & 0.0714998797812351 \tabularnewline
35 & 14 & 15.6022003060943 & -1.60220030609429 \tabularnewline
36 & 10 & 12.9219264013097 & -2.92192640130967 \tabularnewline
37 & 10 & 13.0146729900312 & -3.01467299003116 \tabularnewline
38 & 14 & 15.7899916900747 & -1.78999169007469 \tabularnewline
39 & 16 & 14.5626490012885 & 1.4373509987115 \tabularnewline
40 & 16 & 14.4721133266155 & 1.52788667338449 \tabularnewline
41 & 16 & 14.7271846001186 & 1.27281539988145 \tabularnewline
42 & 14 & 15.8283533347221 & -1.82835333472214 \tabularnewline
43 & 20 & 17.5740121132113 & 2.42598788678869 \tabularnewline
44 & 14 & 14.1663108781857 & -0.166310878185677 \tabularnewline
45 & 14 & 14.4929035444449 & -0.492903544444921 \tabularnewline
46 & 11 & 15.5799467762799 & -4.57994677627985 \tabularnewline
47 & 14 & 16.604228985647 & -2.60422898564702 \tabularnewline
48 & 15 & 15.1942294341289 & -0.19422943412892 \tabularnewline
49 & 16 & 15.6290939132253 & 0.370906086774684 \tabularnewline
50 & 14 & 15.7309335277756 & -1.73093352777565 \tabularnewline
51 & 16 & 17.1471512900765 & -1.14715129007646 \tabularnewline
52 & 14 & 14.2216774089203 & -0.221677408920302 \tabularnewline
53 & 12 & 15.1453403734528 & -3.14534037345282 \tabularnewline
54 & 16 & 15.869552400713 & 0.130447599287036 \tabularnewline
55 & 9 & 11.3645521776952 & -2.36455217769521 \tabularnewline
56 & 14 & 12.4006749187661 & 1.59932508123389 \tabularnewline
57 & 16 & 16.0107717121744 & -0.0107717121744094 \tabularnewline
58 & 16 & 15.5876443588646 & 0.412355641135433 \tabularnewline
59 & 15 & 15.2486517151036 & -0.248651715103607 \tabularnewline
60 & 16 & 14.3009604497181 & 1.69903955028194 \tabularnewline
61 & 12 & 11.5680405712374 & 0.431959428762646 \tabularnewline
62 & 16 & 15.8480933851408 & 0.15190661485923 \tabularnewline
63 & 16 & 16.7320968224481 & -0.732096822448143 \tabularnewline
64 & 14 & 14.8491657946905 & -0.849165794690456 \tabularnewline
65 & 16 & 15.4532184988394 & 0.546781501160583 \tabularnewline
66 & 17 & 15.786728295299 & 1.21327170470102 \tabularnewline
67 & 18 & 16.0663974549983 & 1.93360254500173 \tabularnewline
68 & 18 & 14.2236008420055 & 3.7763991579945 \tabularnewline
69 & 12 & 15.7039588645577 & -3.70395886455773 \tabularnewline
70 & 16 & 15.4478381365797 & 0.552161863420334 \tabularnewline
71 & 10 & 13.0291955081803 & -3.02919550818027 \tabularnewline
72 & 14 & 14.6990097947249 & -0.699009794724861 \tabularnewline
73 & 18 & 16.8215387173465 & 1.17846128265349 \tabularnewline
74 & 18 & 17.047385836898 & 0.952614163101955 \tabularnewline
75 & 16 & 15.0618538666444 & 0.938146133355616 \tabularnewline
76 & 17 & 13.2686578002251 & 3.73134219977487 \tabularnewline
77 & 16 & 16.2744534843814 & -0.27445348438142 \tabularnewline
78 & 16 & 14.2740950485574 & 1.7259049514426 \tabularnewline
79 & 13 & 15.0334785537398 & -2.03347855373977 \tabularnewline
80 & 16 & 14.9247697671811 & 1.07523023281889 \tabularnewline
81 & 16 & 15.5655347518703 & 0.434465248129707 \tabularnewline
82 & 16 & 15.5369752066879 & 0.463024793312068 \tabularnewline
83 & 15 & 15.5563789647739 & -0.556378964773851 \tabularnewline
84 & 15 & 14.7091761878919 & 0.290823812108053 \tabularnewline
85 & 16 & 13.9756487604527 & 2.02435123954728 \tabularnewline
86 & 14 & 14.0085733239176 & -0.00857332391764814 \tabularnewline
87 & 16 & 15.2208307489935 & 0.779169251006498 \tabularnewline
88 & 16 & 14.7065934689148 & 1.29340653108515 \tabularnewline
89 & 15 & 14.3547510265222 & 0.64524897347781 \tabularnewline
90 & 12 & 13.7050807374168 & -1.70508073741682 \tabularnewline
91 & 17 & 16.6782641138012 & 0.321735886198806 \tabularnewline
92 & 16 & 15.7430202889882 & 0.256979711011826 \tabularnewline
93 & 15 & 15.0195639849035 & -0.0195639849034682 \tabularnewline
94 & 13 & 14.9635980286721 & -1.9635980286721 \tabularnewline
95 & 16 & 14.6973726642945 & 1.30262733570547 \tabularnewline
96 & 16 & 15.6830629570827 & 0.316937042917328 \tabularnewline
97 & 16 & 13.5822989199044 & 2.41770108009563 \tabularnewline
98 & 16 & 15.7685105700457 & 0.231489429954285 \tabularnewline
99 & 14 & 14.3198580815311 & -0.319858081531102 \tabularnewline
100 & 16 & 17.0247038337606 & -1.02470383376056 \tabularnewline
101 & 16 & 14.5787973362837 & 1.42120266371627 \tabularnewline
102 & 20 & 17.4687674897041 & 2.53123251029595 \tabularnewline
103 & 15 & 14.0523046259387 & 0.947695374061321 \tabularnewline
104 & 16 & 14.956333278217 & 1.04366672178304 \tabularnewline
105 & 13 & 14.8011674216603 & -1.80116742166032 \tabularnewline
106 & 17 & 15.6582118368939 & 1.34178816310611 \tabularnewline
107 & 16 & 15.7149454231364 & 0.285054576863643 \tabularnewline
108 & 16 & 14.2651695279915 & 1.73483047200847 \tabularnewline
109 & 12 & 12.1445025399444 & -0.144502539944409 \tabularnewline
110 & 16 & 15.270031730108 & 0.729968269891964 \tabularnewline
111 & 16 & 16.0190228965521 & -0.0190228965520521 \tabularnewline
112 & 17 & 14.972899124327 & 2.02710087567299 \tabularnewline
113 & 13 & 14.6235262603592 & -1.62352626035923 \tabularnewline
114 & 12 & 14.5611065152376 & -2.56110651523764 \tabularnewline
115 & 18 & 16.182566405197 & 1.81743359480299 \tabularnewline
116 & 14 & 15.8742392027801 & -1.87423920278009 \tabularnewline
117 & 14 & 13.0634243613986 & 0.936575638601393 \tabularnewline
118 & 13 & 14.7664152300671 & -1.76641523006708 \tabularnewline
119 & 16 & 15.57275380411 & 0.42724619588997 \tabularnewline
120 & 13 & 14.4067456846915 & -1.40674568469149 \tabularnewline
121 & 16 & 15.4391647652899 & 0.560835234710133 \tabularnewline
122 & 13 & 15.8911672712233 & -2.89116727122332 \tabularnewline
123 & 16 & 16.9042581868609 & -0.904258186860854 \tabularnewline
124 & 15 & 15.8921534889468 & -0.892153488946772 \tabularnewline
125 & 16 & 16.9022361707383 & -0.902236170738301 \tabularnewline
126 & 15 & 14.703632062842 & 0.296367937158025 \tabularnewline
127 & 17 & 15.6113104275905 & 1.38868957240952 \tabularnewline
128 & 15 & 13.9838607966409 & 1.01613920335906 \tabularnewline
129 & 12 & 14.7440838384905 & -2.74408383849047 \tabularnewline
130 & 16 & 13.9936422626156 & 2.00635773738435 \tabularnewline
131 & 10 & 13.7576725915982 & -3.75767259159822 \tabularnewline
132 & 16 & 13.5176321144828 & 2.48236788551718 \tabularnewline
133 & 12 & 14.2161631177914 & -2.21616311779137 \tabularnewline
134 & 14 & 15.6237963714392 & -1.62379637143923 \tabularnewline
135 & 15 & 15.1698667563622 & -0.169866756362222 \tabularnewline
136 & 13 & 12.1421557046257 & 0.857844295374259 \tabularnewline
137 & 15 & 14.5009469200994 & 0.499053079900598 \tabularnewline
138 & 11 & 13.4686249246835 & -2.46862492468349 \tabularnewline
139 & 12 & 13.0157243738586 & -1.01572437385864 \tabularnewline
140 & 11 & 13.4194465342762 & -2.4194465342762 \tabularnewline
141 & 16 & 12.8831315054463 & 3.11686849455371 \tabularnewline
142 & 15 & 13.7558505714002 & 1.24414942859977 \tabularnewline
143 & 17 & 17.0097795066055 & -0.00977950660548293 \tabularnewline
144 & 16 & 14.2737946583067 & 1.72620534169329 \tabularnewline
145 & 10 & 13.3567315625142 & -3.35673156251416 \tabularnewline
146 & 18 & 15.6527462059573 & 2.34725379404272 \tabularnewline
147 & 13 & 15.0228847719538 & -2.02288477195382 \tabularnewline
148 & 16 & 14.9620191824016 & 1.03798081759844 \tabularnewline
149 & 13 & 12.8772591624989 & 0.122740837501083 \tabularnewline
150 & 10 & 12.9838669107856 & -2.98386691078565 \tabularnewline
151 & 15 & 16.1494801243129 & -1.14948012431288 \tabularnewline
152 & 16 & 14.0275731378567 & 1.97242686214327 \tabularnewline
153 & 16 & 11.9110510150754 & 4.0889489849246 \tabularnewline
154 & 14 & 12.8816202965071 & 1.11837970349286 \tabularnewline
155 & 10 & 12.5110772982986 & -2.51107729829856 \tabularnewline
156 & 17 & 16.6782641138012 & 0.321735886198806 \tabularnewline
157 & 13 & 11.7748408846068 & 1.22515911539323 \tabularnewline
158 & 15 & 13.9838607966409 & 1.01613920335906 \tabularnewline
159 & 16 & 14.7220477570335 & 1.27795224296651 \tabularnewline
160 & 12 & 12.9024487088536 & -0.902448708853643 \tabularnewline
161 & 13 & 12.7234113561509 & 0.276588643849074 \tabularnewline
162 & 13 & 12.3594447514215 & 0.640555248578502 \tabularnewline
163 & 12 & 12.21971405789 & -0.21971405789 \tabularnewline
164 & 17 & 16.1559256930107 & 0.844074306989343 \tabularnewline
165 & 15 & 13.4927110110311 & 1.50728898896894 \tabularnewline
166 & 10 & 11.3690856488793 & -1.36908564887932 \tabularnewline
167 & 14 & 14.1511837465642 & -0.151183746564223 \tabularnewline
168 & 11 & 14.0473814027883 & -3.04738140278828 \tabularnewline
169 & 13 & 14.6284207569089 & -1.62842075690889 \tabularnewline
170 & 16 & 14.3286401101092 & 1.67135988989077 \tabularnewline
171 & 12 & 10.2103695148885 & 1.78963048511152 \tabularnewline
172 & 16 & 15.2294173512872 & 0.77058264871283 \tabularnewline
173 & 12 & 13.6789589162402 & -1.67895891624021 \tabularnewline
174 & 9 & 11.1422436631215 & -2.14224366312148 \tabularnewline
175 & 12 & 14.8132494934299 & -2.81324949342992 \tabularnewline
176 & 15 & 14.4367200872182 & 0.563279912781797 \tabularnewline
177 & 12 & 12.0443133302158 & -0.0443133302158332 \tabularnewline
178 & 12 & 12.5271258979837 & -0.527125897983652 \tabularnewline
179 & 14 & 13.6520380206879 & 0.347961979312088 \tabularnewline
180 & 12 & 13.2423636290015 & -1.24236362900149 \tabularnewline
181 & 16 & 14.9028714322165 & 1.09712856778351 \tabularnewline
182 & 11 & 11.2308165908512 & -0.230816590851172 \tabularnewline
183 & 19 & 16.6302449667749 & 2.36975503322511 \tabularnewline
184 & 15 & 15.0709573706774 & -0.0709573706773562 \tabularnewline
185 & 8 & 14.5002572284975 & -6.50025722849755 \tabularnewline
186 & 16 & 14.7385222746564 & 1.26147772534355 \tabularnewline
187 & 17 & 14.4011157681125 & 2.59888423188754 \tabularnewline
188 & 12 & 12.2769350009329 & -0.276935000932918 \tabularnewline
189 & 11 & 11.3375926910729 & -0.337592691072861 \tabularnewline
190 & 11 & 10.2335393682771 & 0.766460631722878 \tabularnewline
191 & 14 & 14.7383473626723 & -0.738347362672255 \tabularnewline
192 & 16 & 15.4068358759607 & 0.593164124039307 \tabularnewline
193 & 12 & 9.55486413915182 & 2.44513586084818 \tabularnewline
194 & 16 & 13.9311014734646 & 2.06889852653535 \tabularnewline
195 & 13 & 13.589629361434 & -0.589629361433986 \tabularnewline
196 & 15 & 14.9324705375573 & 0.067529462442679 \tabularnewline
197 & 16 & 12.897088019433 & 3.10291198056704 \tabularnewline
198 & 16 & 15.0180094707273 & 0.98199052927266 \tabularnewline
199 & 14 & 12.3494785543296 & 1.6505214456704 \tabularnewline
200 & 16 & 14.5413613945402 & 1.45863860545976 \tabularnewline
201 & 16 & 13.944593203573 & 2.05540679642697 \tabularnewline
202 & 14 & 13.3226184610574 & 0.677381538942582 \tabularnewline
203 & 11 & 13.4275177946163 & -2.42751779461626 \tabularnewline
204 & 12 & 14.4367109870216 & -2.43671098702159 \tabularnewline
205 & 15 & 12.6699269134548 & 2.33007308654516 \tabularnewline
206 & 15 & 14.4586524254313 & 0.541347574568722 \tabularnewline
207 & 16 & 14.4679372463901 & 1.53206275360993 \tabularnewline
208 & 16 & 14.93164692049 & 1.06835307951002 \tabularnewline
209 & 11 & 13.5562780239837 & -2.5562780239837 \tabularnewline
210 & 15 & 13.9779398017969 & 1.02206019820312 \tabularnewline
211 & 12 & 14.2029022057862 & -2.20290220578625 \tabularnewline
212 & 12 & 15.7784438651911 & -3.7784438651911 \tabularnewline
213 & 15 & 14.1440201791006 & 0.855979820899399 \tabularnewline
214 & 15 & 12.0307032677153 & 2.9692967322847 \tabularnewline
215 & 16 & 14.5684829589542 & 1.43151704104576 \tabularnewline
216 & 14 & 13.07313463419 & 0.92686536580996 \tabularnewline
217 & 17 & 14.6746123754413 & 2.32538762455869 \tabularnewline
218 & 14 & 13.9423598225196 & 0.0576401774804177 \tabularnewline
219 & 13 & 11.8905028372228 & 1.10949716277721 \tabularnewline
220 & 15 & 15.2059654363509 & -0.205965436350932 \tabularnewline
221 & 13 & 14.671017170643 & -1.67101717064297 \tabularnewline
222 & 14 & 14.1319205655599 & -0.131920565559881 \tabularnewline
223 & 15 & 14.3001182465164 & 0.69988175348359 \tabularnewline
224 & 12 & 13.1092937744911 & -1.10929377449114 \tabularnewline
225 & 13 & 12.7116664065425 & 0.288333593457519 \tabularnewline
226 & 8 & 11.7472131342751 & -3.74721313427505 \tabularnewline
227 & 14 & 13.8015801739644 & 0.198419826035607 \tabularnewline
228 & 14 & 13.0202674279236 & 0.979732572076422 \tabularnewline
229 & 11 & 12.2297591833159 & -1.22975918331585 \tabularnewline
230 & 12 & 12.8968382776945 & -0.896838277694454 \tabularnewline
231 & 13 & 11.2452084819542 & 1.75479151804577 \tabularnewline
232 & 10 & 13.2130657616632 & -3.21306576166323 \tabularnewline
233 & 16 & 11.3677174009184 & 4.63228259908156 \tabularnewline
234 & 18 & 15.9474161696061 & 2.05258383039392 \tabularnewline
235 & 13 & 13.8693288638037 & -0.869328863803708 \tabularnewline
236 & 11 & 13.3430027385425 & -2.34300273854247 \tabularnewline
237 & 4 & 10.9726967298314 & -6.97269672983141 \tabularnewline
238 & 13 & 14.2678178481433 & -1.26781784814329 \tabularnewline
239 & 16 & 14.3069070865238 & 1.6930929134762 \tabularnewline
240 & 10 & 11.6823923405169 & -1.68239234051694 \tabularnewline
241 & 12 & 12.2879119795221 & -0.287911979522082 \tabularnewline
242 & 12 & 13.5011921116947 & -1.50119211169468 \tabularnewline
243 & 10 & 8.85142253316745 & 1.14857746683254 \tabularnewline
244 & 13 & 11.1028627902225 & 1.89713720977749 \tabularnewline
245 & 15 & 13.7092481004796 & 1.2907518995204 \tabularnewline
246 & 12 & 11.9685057317415 & 0.0314942682585027 \tabularnewline
247 & 14 & 12.8777319860027 & 1.12226801399732 \tabularnewline
248 & 10 & 12.5358000227952 & -2.53580002279517 \tabularnewline
249 & 12 & 10.7624130858841 & 1.23758691411589 \tabularnewline
250 & 12 & 11.7393909440044 & 0.260609055995628 \tabularnewline
251 & 11 & 11.9220624304821 & -0.922062430482111 \tabularnewline
252 & 10 & 11.730463172571 & -1.73046317257097 \tabularnewline
253 & 12 & 11.4019661994277 & 0.598033800572314 \tabularnewline
254 & 16 & 12.8825562632821 & 3.11744373671785 \tabularnewline
255 & 12 & 13.3765522827852 & -1.37655228278524 \tabularnewline
256 & 14 & 13.9048290853521 & 0.0951709146478978 \tabularnewline
257 & 16 & 14.5198797799652 & 1.48012022003483 \tabularnewline
258 & 14 & 11.6682798848408 & 2.33172011515923 \tabularnewline
259 & 13 & 14.356690156603 & -1.35669015660305 \tabularnewline
260 & 4 & 9.38334580594879 & -5.38334580594879 \tabularnewline
261 & 15 & 13.8472593284005 & 1.15274067159949 \tabularnewline
262 & 11 & 15.1083609537208 & -4.10836095372081 \tabularnewline
263 & 11 & 11.3476291943178 & -0.347629194317833 \tabularnewline
264 & 14 & 12.9144494714043 & 1.08555052859574 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185683&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]15.9509274269783[/C][C]-2.95092742697833[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.6181828665753[/C][C]0.381817133424683[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]16.9166643716608[/C][C]2.0833356283392[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]11.8729748073647[/C][C]3.12702519263533[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.3580519877682[/C][C]-2.35805198776817[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.7360162717571[/C][C]-1.73601627175708[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.1537000085073[/C][C]3.8462999914927[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]17.0077560505479[/C][C]-2.00775605054786[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]15.9484454966394[/C][C]-1.94844549663943[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.2980364711644[/C][C]0.701963528835648[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.8626172377916[/C][C]1.13738276220844[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.1018077007214[/C][C]-0.101807700721448[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.3893109658985[/C][C]0.610689034101525[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.4079786083135[/C][C]0.592021391686478[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]18.0043950630554[/C][C]-1.00439506305541[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.3798159239431[/C][C]-0.379815923943083[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.5105588177224[/C][C]0.489441182277558[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.383380816603[/C][C]3.61661918339703[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.3748348655024[/C][C]2.62516513449764[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.4935321664941[/C][C]0.506467833505857[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.3027694651376[/C][C]0.697230534862408[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]15.0411768247971[/C][C]0.958823175202897[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.4530618527621[/C][C]2.54693814723792[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]14.9892378950466[/C][C]1.01076210495345[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]16.1668421489873[/C][C]0.833157851012718[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.2212087742073[/C][C]0.778791225792725[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.9717246067166[/C][C]1.0282753932834[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.7639680138983[/C][C]-1.76396801389828[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.7661669842349[/C][C]0.23383301576509[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.0778957672031[/C][C]-0.0778957672030686[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.7460272839639[/C][C]-0.746027283963927[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.7373771224323[/C][C]-0.737377122432317[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.7974186192348[/C][C]-0.797418619234848[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.9285001202188[/C][C]0.0714998797812351[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.6022003060943[/C][C]-1.60220030609429[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.9219264013097[/C][C]-2.92192640130967[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]13.0146729900312[/C][C]-3.01467299003116[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.7899916900747[/C][C]-1.78999169007469[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.5626490012885[/C][C]1.4373509987115[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.4721133266155[/C][C]1.52788667338449[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.7271846001186[/C][C]1.27281539988145[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.8283533347221[/C][C]-1.82835333472214[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.5740121132113[/C][C]2.42598788678869[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.1663108781857[/C][C]-0.166310878185677[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.4929035444449[/C][C]-0.492903544444921[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.5799467762799[/C][C]-4.57994677627985[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.604228985647[/C][C]-2.60422898564702[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.1942294341289[/C][C]-0.19422943412892[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.6290939132253[/C][C]0.370906086774684[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.7309335277756[/C][C]-1.73093352777565[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]17.1471512900765[/C][C]-1.14715129007646[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.2216774089203[/C][C]-0.221677408920302[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]15.1453403734528[/C][C]-3.14534037345282[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.869552400713[/C][C]0.130447599287036[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]11.3645521776952[/C][C]-2.36455217769521[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.4006749187661[/C][C]1.59932508123389[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]16.0107717121744[/C][C]-0.0107717121744094[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.5876443588646[/C][C]0.412355641135433[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]15.2486517151036[/C][C]-0.248651715103607[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.3009604497181[/C][C]1.69903955028194[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.5680405712374[/C][C]0.431959428762646[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.8480933851408[/C][C]0.15190661485923[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.7320968224481[/C][C]-0.732096822448143[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.8491657946905[/C][C]-0.849165794690456[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.4532184988394[/C][C]0.546781501160583[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]15.786728295299[/C][C]1.21327170470102[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.0663974549983[/C][C]1.93360254500173[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.2236008420055[/C][C]3.7763991579945[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.7039588645577[/C][C]-3.70395886455773[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.4478381365797[/C][C]0.552161863420334[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.0291955081803[/C][C]-3.02919550818027[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.6990097947249[/C][C]-0.699009794724861[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.8215387173465[/C][C]1.17846128265349[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.047385836898[/C][C]0.952614163101955[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.0618538666444[/C][C]0.938146133355616[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.2686578002251[/C][C]3.73134219977487[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.2744534843814[/C][C]-0.27445348438142[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.2740950485574[/C][C]1.7259049514426[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]15.0334785537398[/C][C]-2.03347855373977[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]14.9247697671811[/C][C]1.07523023281889[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.5655347518703[/C][C]0.434465248129707[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.5369752066879[/C][C]0.463024793312068[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.5563789647739[/C][C]-0.556378964773851[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.7091761878919[/C][C]0.290823812108053[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]13.9756487604527[/C][C]2.02435123954728[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.0085733239176[/C][C]-0.00857332391764814[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.2208307489935[/C][C]0.779169251006498[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.7065934689148[/C][C]1.29340653108515[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.3547510265222[/C][C]0.64524897347781[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.7050807374168[/C][C]-1.70508073741682[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.6782641138012[/C][C]0.321735886198806[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.7430202889882[/C][C]0.256979711011826[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.0195639849035[/C][C]-0.0195639849034682[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.9635980286721[/C][C]-1.9635980286721[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.6973726642945[/C][C]1.30262733570547[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.6830629570827[/C][C]0.316937042917328[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.5822989199044[/C][C]2.41770108009563[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.7685105700457[/C][C]0.231489429954285[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.3198580815311[/C][C]-0.319858081531102[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.0247038337606[/C][C]-1.02470383376056[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.5787973362837[/C][C]1.42120266371627[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.4687674897041[/C][C]2.53123251029595[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.0523046259387[/C][C]0.947695374061321[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]14.956333278217[/C][C]1.04366672178304[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.8011674216603[/C][C]-1.80116742166032[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.6582118368939[/C][C]1.34178816310611[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.7149454231364[/C][C]0.285054576863643[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.2651695279915[/C][C]1.73483047200847[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.1445025399444[/C][C]-0.144502539944409[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.270031730108[/C][C]0.729968269891964[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]16.0190228965521[/C][C]-0.0190228965520521[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]14.972899124327[/C][C]2.02710087567299[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.6235262603592[/C][C]-1.62352626035923[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.5611065152376[/C][C]-2.56110651523764[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.182566405197[/C][C]1.81743359480299[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.8742392027801[/C][C]-1.87423920278009[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.0634243613986[/C][C]0.936575638601393[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.7664152300671[/C][C]-1.76641523006708[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.57275380411[/C][C]0.42724619588997[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.4067456846915[/C][C]-1.40674568469149[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.4391647652899[/C][C]0.560835234710133[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.8911672712233[/C][C]-2.89116727122332[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]16.9042581868609[/C][C]-0.904258186860854[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.8921534889468[/C][C]-0.892153488946772[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.9022361707383[/C][C]-0.902236170738301[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.703632062842[/C][C]0.296367937158025[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.6113104275905[/C][C]1.38868957240952[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]13.9838607966409[/C][C]1.01613920335906[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.7440838384905[/C][C]-2.74408383849047[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.9936422626156[/C][C]2.00635773738435[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.7576725915982[/C][C]-3.75767259159822[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.5176321144828[/C][C]2.48236788551718[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.2161631177914[/C][C]-2.21616311779137[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.6237963714392[/C][C]-1.62379637143923[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.1698667563622[/C][C]-0.169866756362222[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]12.1421557046257[/C][C]0.857844295374259[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.5009469200994[/C][C]0.499053079900598[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.4686249246835[/C][C]-2.46862492468349[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]13.0157243738586[/C][C]-1.01572437385864[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.4194465342762[/C][C]-2.4194465342762[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8831315054463[/C][C]3.11686849455371[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.7558505714002[/C][C]1.24414942859977[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]17.0097795066055[/C][C]-0.00977950660548293[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.2737946583067[/C][C]1.72620534169329[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.3567315625142[/C][C]-3.35673156251416[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.6527462059573[/C][C]2.34725379404272[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.0228847719538[/C][C]-2.02288477195382[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.9620191824016[/C][C]1.03798081759844[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.8772591624989[/C][C]0.122740837501083[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.9838669107856[/C][C]-2.98386691078565[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]16.1494801243129[/C][C]-1.14948012431288[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]14.0275731378567[/C][C]1.97242686214327[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.9110510150754[/C][C]4.0889489849246[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.8816202965071[/C][C]1.11837970349286[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.5110772982986[/C][C]-2.51107729829856[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.6782641138012[/C][C]0.321735886198806[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.7748408846068[/C][C]1.22515911539323[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]13.9838607966409[/C][C]1.01613920335906[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.7220477570335[/C][C]1.27795224296651[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.9024487088536[/C][C]-0.902448708853643[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.7234113561509[/C][C]0.276588643849074[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.3594447514215[/C][C]0.640555248578502[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.21971405789[/C][C]-0.21971405789[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.1559256930107[/C][C]0.844074306989343[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.4927110110311[/C][C]1.50728898896894[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.3690856488793[/C][C]-1.36908564887932[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.1511837465642[/C][C]-0.151183746564223[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.0473814027883[/C][C]-3.04738140278828[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.6284207569089[/C][C]-1.62842075690889[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.3286401101092[/C][C]1.67135988989077[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.2103695148885[/C][C]1.78963048511152[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.2294173512872[/C][C]0.77058264871283[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.6789589162402[/C][C]-1.67895891624021[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.1422436631215[/C][C]-2.14224366312148[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]14.8132494934299[/C][C]-2.81324949342992[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.4367200872182[/C][C]0.563279912781797[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.0443133302158[/C][C]-0.0443133302158332[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.5271258979837[/C][C]-0.527125897983652[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.6520380206879[/C][C]0.347961979312088[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.2423636290015[/C][C]-1.24236362900149[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]14.9028714322165[/C][C]1.09712856778351[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.2308165908512[/C][C]-0.230816590851172[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]16.6302449667749[/C][C]2.36975503322511[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.0709573706774[/C][C]-0.0709573706773562[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.5002572284975[/C][C]-6.50025722849755[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.7385222746564[/C][C]1.26147772534355[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.4011157681125[/C][C]2.59888423188754[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.2769350009329[/C][C]-0.276935000932918[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.3375926910729[/C][C]-0.337592691072861[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.2335393682771[/C][C]0.766460631722878[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14.7383473626723[/C][C]-0.738347362672255[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.4068358759607[/C][C]0.593164124039307[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.55486413915182[/C][C]2.44513586084818[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]13.9311014734646[/C][C]2.06889852653535[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.589629361434[/C][C]-0.589629361433986[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]14.9324705375573[/C][C]0.067529462442679[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]12.897088019433[/C][C]3.10291198056704[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.0180094707273[/C][C]0.98199052927266[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.3494785543296[/C][C]1.6505214456704[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.5413613945402[/C][C]1.45863860545976[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]13.944593203573[/C][C]2.05540679642697[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.3226184610574[/C][C]0.677381538942582[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.4275177946163[/C][C]-2.42751779461626[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.4367109870216[/C][C]-2.43671098702159[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.6699269134548[/C][C]2.33007308654516[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.4586524254313[/C][C]0.541347574568722[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.4679372463901[/C][C]1.53206275360993[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]14.93164692049[/C][C]1.06835307951002[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.5562780239837[/C][C]-2.5562780239837[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]13.9779398017969[/C][C]1.02206019820312[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.2029022057862[/C][C]-2.20290220578625[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]15.7784438651911[/C][C]-3.7784438651911[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.1440201791006[/C][C]0.855979820899399[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.0307032677153[/C][C]2.9692967322847[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.5684829589542[/C][C]1.43151704104576[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.07313463419[/C][C]0.92686536580996[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.6746123754413[/C][C]2.32538762455869[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.9423598225196[/C][C]0.0576401774804177[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.8905028372228[/C][C]1.10949716277721[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.2059654363509[/C][C]-0.205965436350932[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]14.671017170643[/C][C]-1.67101717064297[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]14.1319205655599[/C][C]-0.131920565559881[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.3001182465164[/C][C]0.69988175348359[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.1092937744911[/C][C]-1.10929377449114[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.7116664065425[/C][C]0.288333593457519[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.7472131342751[/C][C]-3.74721313427505[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]13.8015801739644[/C][C]0.198419826035607[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]13.0202674279236[/C][C]0.979732572076422[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.2297591833159[/C][C]-1.22975918331585[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]12.8968382776945[/C][C]-0.896838277694454[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.2452084819542[/C][C]1.75479151804577[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.2130657616632[/C][C]-3.21306576166323[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.3677174009184[/C][C]4.63228259908156[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]15.9474161696061[/C][C]2.05258383039392[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]13.8693288638037[/C][C]-0.869328863803708[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.3430027385425[/C][C]-2.34300273854247[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]10.9726967298314[/C][C]-6.97269672983141[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.2678178481433[/C][C]-1.26781784814329[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.3069070865238[/C][C]1.6930929134762[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.6823923405169[/C][C]-1.68239234051694[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.2879119795221[/C][C]-0.287911979522082[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.5011921116947[/C][C]-1.50119211169468[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.85142253316745[/C][C]1.14857746683254[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]11.1028627902225[/C][C]1.89713720977749[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.7092481004796[/C][C]1.2907518995204[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]11.9685057317415[/C][C]0.0314942682585027[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]12.8777319860027[/C][C]1.12226801399732[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.5358000227952[/C][C]-2.53580002279517[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.7624130858841[/C][C]1.23758691411589[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.7393909440044[/C][C]0.260609055995628[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.9220624304821[/C][C]-0.922062430482111[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.730463172571[/C][C]-1.73046317257097[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.4019661994277[/C][C]0.598033800572314[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]12.8825562632821[/C][C]3.11744373671785[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.3765522827852[/C][C]-1.37655228278524[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.9048290853521[/C][C]0.0951709146478978[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.5198797799652[/C][C]1.48012022003483[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.6682798848408[/C][C]2.33172011515923[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.356690156603[/C][C]-1.35669015660305[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.38334580594879[/C][C]-5.38334580594879[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.8472593284005[/C][C]1.15274067159949[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]15.1083609537208[/C][C]-4.10836095372081[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.3476291943178[/C][C]-0.347629194317833[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]12.9144494714043[/C][C]1.08555052859574[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185683&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185683&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 15.9509274269783 -2.95092742697833 2 16 15.6181828665753 0.381817133424683 3 19 16.9166643716608 2.0833356283392 4 15 11.8729748073647 3.12702519263533 5 14 16.3580519877682 -2.35805198776817 6 13 14.7360162717571 -1.73601627175708 7 19 15.1537000085073 3.8462999914927 8 15 17.0077560505479 -2.00775605054786 9 14 15.9484454966394 -1.94844549663943 10 15 14.2980364711644 0.701963528835648 11 16 14.8626172377916 1.13738276220844 12 16 16.1018077007214 -0.101807700721448 13 16 15.3893109658985 0.610689034101525 14 16 15.4079786083135 0.592021391686478 15 17 18.0043950630554 -1.00439506305541 16 15 15.3798159239431 -0.379815923943083 17 15 14.5105588177224 0.489441182277558 18 20 16.383380816603 3.61661918339703 19 18 15.3748348655024 2.62516513449764 20 16 15.4935321664941 0.506467833505857 21 16 15.3027694651376 0.697230534862408 22 16 15.0411768247971 0.958823175202897 23 19 16.4530618527621 2.54693814723792 24 16 14.9892378950466 1.01076210495345 25 17 16.1668421489873 0.833157851012718 26 17 16.2212087742073 0.778791225792725 27 16 14.9717246067166 1.0282753932834 28 15 16.7639680138983 -1.76396801389828 29 16 15.7661669842349 0.23383301576509 30 14 14.0778957672031 -0.0778957672030686 31 15 15.7460272839639 -0.746027283963927 32 12 12.7373771224323 -0.737377122432317 33 14 14.7974186192348 -0.797418619234848 34 16 15.9285001202188 0.0714998797812351 35 14 15.6022003060943 -1.60220030609429 36 10 12.9219264013097 -2.92192640130967 37 10 13.0146729900312 -3.01467299003116 38 14 15.7899916900747 -1.78999169007469 39 16 14.5626490012885 1.4373509987115 40 16 14.4721133266155 1.52788667338449 41 16 14.7271846001186 1.27281539988145 42 14 15.8283533347221 -1.82835333472214 43 20 17.5740121132113 2.42598788678869 44 14 14.1663108781857 -0.166310878185677 45 14 14.4929035444449 -0.492903544444921 46 11 15.5799467762799 -4.57994677627985 47 14 16.604228985647 -2.60422898564702 48 15 15.1942294341289 -0.19422943412892 49 16 15.6290939132253 0.370906086774684 50 14 15.7309335277756 -1.73093352777565 51 16 17.1471512900765 -1.14715129007646 52 14 14.2216774089203 -0.221677408920302 53 12 15.1453403734528 -3.14534037345282 54 16 15.869552400713 0.130447599287036 55 9 11.3645521776952 -2.36455217769521 56 14 12.4006749187661 1.59932508123389 57 16 16.0107717121744 -0.0107717121744094 58 16 15.5876443588646 0.412355641135433 59 15 15.2486517151036 -0.248651715103607 60 16 14.3009604497181 1.69903955028194 61 12 11.5680405712374 0.431959428762646 62 16 15.8480933851408 0.15190661485923 63 16 16.7320968224481 -0.732096822448143 64 14 14.8491657946905 -0.849165794690456 65 16 15.4532184988394 0.546781501160583 66 17 15.786728295299 1.21327170470102 67 18 16.0663974549983 1.93360254500173 68 18 14.2236008420055 3.7763991579945 69 12 15.7039588645577 -3.70395886455773 70 16 15.4478381365797 0.552161863420334 71 10 13.0291955081803 -3.02919550818027 72 14 14.6990097947249 -0.699009794724861 73 18 16.8215387173465 1.17846128265349 74 18 17.047385836898 0.952614163101955 75 16 15.0618538666444 0.938146133355616 76 17 13.2686578002251 3.73134219977487 77 16 16.2744534843814 -0.27445348438142 78 16 14.2740950485574 1.7259049514426 79 13 15.0334785537398 -2.03347855373977 80 16 14.9247697671811 1.07523023281889 81 16 15.5655347518703 0.434465248129707 82 16 15.5369752066879 0.463024793312068 83 15 15.5563789647739 -0.556378964773851 84 15 14.7091761878919 0.290823812108053 85 16 13.9756487604527 2.02435123954728 86 14 14.0085733239176 -0.00857332391764814 87 16 15.2208307489935 0.779169251006498 88 16 14.7065934689148 1.29340653108515 89 15 14.3547510265222 0.64524897347781 90 12 13.7050807374168 -1.70508073741682 91 17 16.6782641138012 0.321735886198806 92 16 15.7430202889882 0.256979711011826 93 15 15.0195639849035 -0.0195639849034682 94 13 14.9635980286721 -1.9635980286721 95 16 14.6973726642945 1.30262733570547 96 16 15.6830629570827 0.316937042917328 97 16 13.5822989199044 2.41770108009563 98 16 15.7685105700457 0.231489429954285 99 14 14.3198580815311 -0.319858081531102 100 16 17.0247038337606 -1.02470383376056 101 16 14.5787973362837 1.42120266371627 102 20 17.4687674897041 2.53123251029595 103 15 14.0523046259387 0.947695374061321 104 16 14.956333278217 1.04366672178304 105 13 14.8011674216603 -1.80116742166032 106 17 15.6582118368939 1.34178816310611 107 16 15.7149454231364 0.285054576863643 108 16 14.2651695279915 1.73483047200847 109 12 12.1445025399444 -0.144502539944409 110 16 15.270031730108 0.729968269891964 111 16 16.0190228965521 -0.0190228965520521 112 17 14.972899124327 2.02710087567299 113 13 14.6235262603592 -1.62352626035923 114 12 14.5611065152376 -2.56110651523764 115 18 16.182566405197 1.81743359480299 116 14 15.8742392027801 -1.87423920278009 117 14 13.0634243613986 0.936575638601393 118 13 14.7664152300671 -1.76641523006708 119 16 15.57275380411 0.42724619588997 120 13 14.4067456846915 -1.40674568469149 121 16 15.4391647652899 0.560835234710133 122 13 15.8911672712233 -2.89116727122332 123 16 16.9042581868609 -0.904258186860854 124 15 15.8921534889468 -0.892153488946772 125 16 16.9022361707383 -0.902236170738301 126 15 14.703632062842 0.296367937158025 127 17 15.6113104275905 1.38868957240952 128 15 13.9838607966409 1.01613920335906 129 12 14.7440838384905 -2.74408383849047 130 16 13.9936422626156 2.00635773738435 131 10 13.7576725915982 -3.75767259159822 132 16 13.5176321144828 2.48236788551718 133 12 14.2161631177914 -2.21616311779137 134 14 15.6237963714392 -1.62379637143923 135 15 15.1698667563622 -0.169866756362222 136 13 12.1421557046257 0.857844295374259 137 15 14.5009469200994 0.499053079900598 138 11 13.4686249246835 -2.46862492468349 139 12 13.0157243738586 -1.01572437385864 140 11 13.4194465342762 -2.4194465342762 141 16 12.8831315054463 3.11686849455371 142 15 13.7558505714002 1.24414942859977 143 17 17.0097795066055 -0.00977950660548293 144 16 14.2737946583067 1.72620534169329 145 10 13.3567315625142 -3.35673156251416 146 18 15.6527462059573 2.34725379404272 147 13 15.0228847719538 -2.02288477195382 148 16 14.9620191824016 1.03798081759844 149 13 12.8772591624989 0.122740837501083 150 10 12.9838669107856 -2.98386691078565 151 15 16.1494801243129 -1.14948012431288 152 16 14.0275731378567 1.97242686214327 153 16 11.9110510150754 4.0889489849246 154 14 12.8816202965071 1.11837970349286 155 10 12.5110772982986 -2.51107729829856 156 17 16.6782641138012 0.321735886198806 157 13 11.7748408846068 1.22515911539323 158 15 13.9838607966409 1.01613920335906 159 16 14.7220477570335 1.27795224296651 160 12 12.9024487088536 -0.902448708853643 161 13 12.7234113561509 0.276588643849074 162 13 12.3594447514215 0.640555248578502 163 12 12.21971405789 -0.21971405789 164 17 16.1559256930107 0.844074306989343 165 15 13.4927110110311 1.50728898896894 166 10 11.3690856488793 -1.36908564887932 167 14 14.1511837465642 -0.151183746564223 168 11 14.0473814027883 -3.04738140278828 169 13 14.6284207569089 -1.62842075690889 170 16 14.3286401101092 1.67135988989077 171 12 10.2103695148885 1.78963048511152 172 16 15.2294173512872 0.77058264871283 173 12 13.6789589162402 -1.67895891624021 174 9 11.1422436631215 -2.14224366312148 175 12 14.8132494934299 -2.81324949342992 176 15 14.4367200872182 0.563279912781797 177 12 12.0443133302158 -0.0443133302158332 178 12 12.5271258979837 -0.527125897983652 179 14 13.6520380206879 0.347961979312088 180 12 13.2423636290015 -1.24236362900149 181 16 14.9028714322165 1.09712856778351 182 11 11.2308165908512 -0.230816590851172 183 19 16.6302449667749 2.36975503322511 184 15 15.0709573706774 -0.0709573706773562 185 8 14.5002572284975 -6.50025722849755 186 16 14.7385222746564 1.26147772534355 187 17 14.4011157681125 2.59888423188754 188 12 12.2769350009329 -0.276935000932918 189 11 11.3375926910729 -0.337592691072861 190 11 10.2335393682771 0.766460631722878 191 14 14.7383473626723 -0.738347362672255 192 16 15.4068358759607 0.593164124039307 193 12 9.55486413915182 2.44513586084818 194 16 13.9311014734646 2.06889852653535 195 13 13.589629361434 -0.589629361433986 196 15 14.9324705375573 0.067529462442679 197 16 12.897088019433 3.10291198056704 198 16 15.0180094707273 0.98199052927266 199 14 12.3494785543296 1.6505214456704 200 16 14.5413613945402 1.45863860545976 201 16 13.944593203573 2.05540679642697 202 14 13.3226184610574 0.677381538942582 203 11 13.4275177946163 -2.42751779461626 204 12 14.4367109870216 -2.43671098702159 205 15 12.6699269134548 2.33007308654516 206 15 14.4586524254313 0.541347574568722 207 16 14.4679372463901 1.53206275360993 208 16 14.93164692049 1.06835307951002 209 11 13.5562780239837 -2.5562780239837 210 15 13.9779398017969 1.02206019820312 211 12 14.2029022057862 -2.20290220578625 212 12 15.7784438651911 -3.7784438651911 213 15 14.1440201791006 0.855979820899399 214 15 12.0307032677153 2.9692967322847 215 16 14.5684829589542 1.43151704104576 216 14 13.07313463419 0.92686536580996 217 17 14.6746123754413 2.32538762455869 218 14 13.9423598225196 0.0576401774804177 219 13 11.8905028372228 1.10949716277721 220 15 15.2059654363509 -0.205965436350932 221 13 14.671017170643 -1.67101717064297 222 14 14.1319205655599 -0.131920565559881 223 15 14.3001182465164 0.69988175348359 224 12 13.1092937744911 -1.10929377449114 225 13 12.7116664065425 0.288333593457519 226 8 11.7472131342751 -3.74721313427505 227 14 13.8015801739644 0.198419826035607 228 14 13.0202674279236 0.979732572076422 229 11 12.2297591833159 -1.22975918331585 230 12 12.8968382776945 -0.896838277694454 231 13 11.2452084819542 1.75479151804577 232 10 13.2130657616632 -3.21306576166323 233 16 11.3677174009184 4.63228259908156 234 18 15.9474161696061 2.05258383039392 235 13 13.8693288638037 -0.869328863803708 236 11 13.3430027385425 -2.34300273854247 237 4 10.9726967298314 -6.97269672983141 238 13 14.2678178481433 -1.26781784814329 239 16 14.3069070865238 1.6930929134762 240 10 11.6823923405169 -1.68239234051694 241 12 12.2879119795221 -0.287911979522082 242 12 13.5011921116947 -1.50119211169468 243 10 8.85142253316745 1.14857746683254 244 13 11.1028627902225 1.89713720977749 245 15 13.7092481004796 1.2907518995204 246 12 11.9685057317415 0.0314942682585027 247 14 12.8777319860027 1.12226801399732 248 10 12.5358000227952 -2.53580002279517 249 12 10.7624130858841 1.23758691411589 250 12 11.7393909440044 0.260609055995628 251 11 11.9220624304821 -0.922062430482111 252 10 11.730463172571 -1.73046317257097 253 12 11.4019661994277 0.598033800572314 254 16 12.8825562632821 3.11744373671785 255 12 13.3765522827852 -1.37655228278524 256 14 13.9048290853521 0.0951709146478978 257 16 14.5198797799652 1.48012022003483 258 14 11.6682798848408 2.33172011515923 259 13 14.356690156603 -1.35669015660305 260 4 9.38334580594879 -5.38334580594879 261 15 13.8472593284005 1.15274067159949 262 11 15.1083609537208 -4.10836095372081 263 11 11.3476291943178 -0.347629194317833 264 14 12.9144494714043 1.08555052859574

 Goldfeld-Quandt test for Heteroskedasticity p-values Alternative Hypothesis breakpoint index greater 2-sided less 12 0.249272273417128 0.498544546834257 0.750727726582872 13 0.168954109350984 0.337908218701967 0.831045890649016 14 0.188652474482694 0.377304948965389 0.811347525517306 15 0.113822199570938 0.227644399141877 0.886177800429062 16 0.0773581785451666 0.154716357090333 0.922641821454833 17 0.111089921688009 0.222179843376018 0.888910078311991 18 0.35029724400813 0.700594488016259 0.64970275599187 19 0.273076148217575 0.54615229643515 0.726923851782425 20 0.200364779799482 0.400729559598965 0.799635220200518 21 0.147329038244944 0.294658076489889 0.852670961755056 22 0.14242982215262 0.28485964430524 0.85757017784738 23 0.329613610691878 0.659227221383756 0.670386389308122 24 0.396108111170374 0.792216222340748 0.603891888829626 25 0.364643782622251 0.729287565244503 0.635356217377749 26 0.343013785262702 0.686027570525404 0.656986214737298 27 0.419522216901135 0.83904443380227 0.580477783098865 28 0.431039269566405 0.862078539132809 0.568960730433596 29 0.411178257665479 0.822356515330959 0.588821742334521 30 0.4445628643833 0.8891257287666 0.5554371356167 31 0.389182053396216 0.778364106792431 0.610817946603784 32 0.346620753254168 0.693241506508336 0.653379246745832 33 0.316677130929607 0.633354261859213 0.683322869070393 34 0.275674898300484 0.551349796600968 0.724325101699516 35 0.233139524871999 0.466279049743997 0.766860475128001 36 0.363623899560605 0.72724779912121 0.636376100439395 37 0.400480018023811 0.800960036047623 0.599519981976189 38 0.392518456881074 0.785036913762147 0.607481543118926 39 0.420646898193909 0.841293796387819 0.579353101806091 40 0.394036668820191 0.788073337640382 0.605963331179809 41 0.352608510695984 0.705217021391968 0.647391489304016 42 0.317815560782677 0.635631121565354 0.682184439217323 43 0.330602998434414 0.661205996868828 0.669397001565586 44 0.284193039977045 0.56838607995409 0.715806960022955 45 0.259307353804652 0.518614707609304 0.740692646195348 46 0.457373136543278 0.914746273086556 0.542626863456722 47 0.613015042694864 0.773969914610272 0.386984957305136 48 0.564790964894334 0.870418070211332 0.435209035105666 49 0.550115831249477 0.899768337501047 0.449884168750523 50 0.538886872116342 0.922226255767315 0.461113127883658 51 0.496029187990605 0.99205837598121 0.503970812009395 52 0.448976551667355 0.897953103334709 0.551023448332645 53 0.469409970867618 0.938819941735235 0.530590029132383 54 0.449833835993114 0.899667671986227 0.550166164006886 55 0.45206618336547 0.904132366730939 0.54793381663453 56 0.420708589827935 0.841417179655871 0.579291410172065 57 0.377122146901935 0.75424429380387 0.622877853098065 58 0.343504288197334 0.687008576394669 0.656495711802666 59 0.305381736916128 0.610763473832255 0.694618263083872 60 0.304715664842222 0.609431329684444 0.695284335157778 61 0.274885364314507 0.549770728629014 0.725114635685493 62 0.243391513321 0.486783026642 0.756608486679 63 0.213205555515493 0.426411111030986 0.786794444484507 64 0.184850255438615 0.369700510877231 0.815149744561385 65 0.159612090313773 0.319224180627547 0.840387909686227 66 0.135701682609405 0.27140336521881 0.864298317390595 67 0.118078554966231 0.236157109932462 0.881921445033769 68 0.147491712033944 0.294983424067887 0.852508287966056 69 0.347255538628955 0.69451107725791 0.652744461371045 70 0.309383520800725 0.61876704160145 0.690616479199275 71 0.466018474195671 0.932036948391342 0.533981525804329 72 0.427694883468798 0.855389766937597 0.572305116531202 73 0.415756314370459 0.831512628740918 0.584243685629541 74 0.394545848970235 0.789091697940469 0.605454151029765 75 0.359444377104182 0.718888754208365 0.640555622895818 76 0.407073802696672 0.814147605393345 0.592926197303328 77 0.374300584690814 0.748601169381629 0.625699415309186 78 0.346591344599645 0.69318268919929 0.653408655400355 79 0.375124096917485 0.75024819383497 0.624875903082515 80 0.344523836755934 0.689047673511868 0.655476163244066 81 0.311892769547428 0.623785539094855 0.688107230452572 82 0.277800972444902 0.555601944889804 0.722199027555098 83 0.254136867114177 0.508273734228354 0.745863132885823 84 0.22338179566367 0.446763591327341 0.77661820433633 85 0.21362430355121 0.42724860710242 0.78637569644879 86 0.186095183511229 0.372190367022457 0.813904816488771 87 0.162784483325638 0.325568966651276 0.837215516674362 88 0.147969314030638 0.295938628061275 0.852030685969362 89 0.127536795735546 0.255073591471092 0.872463204264454 90 0.129326332967502 0.258652665935003 0.870673667032498 91 0.111535331873573 0.223070663747147 0.888464668126427 92 0.0961283982313716 0.192256796462743 0.903871601768628 93 0.0825502956078306 0.165100591215661 0.917449704392169 94 0.0877425387684931 0.175485077536986 0.912257461231507 95 0.0780879857657512 0.156175971531502 0.921912014234249 96 0.0658294056936893 0.131658811387379 0.934170594306311 97 0.0689068074898876 0.137813614979775 0.931093192510112 98 0.0573579515440502 0.1147159030881 0.94264204845595 99 0.0475906360332547 0.0951812720665093 0.952409363966745 100 0.0425438584868558 0.0850877169737115 0.957456141513144 101 0.0369859310294413 0.0739718620588826 0.963014068970559 102 0.0420002433756055 0.084000486751211 0.957999756624395 103 0.0356653898073747 0.0713307796147493 0.964334610192625 104 0.0316665200782289 0.0633330401564578 0.968333479921771 105 0.0388094976881836 0.0776189953763671 0.961190502311816 106 0.0335801030215311 0.0671602060430622 0.966419896978469 107 0.0272903859757299 0.0545807719514598 0.97270961402427 108 0.0260134149836975 0.052026829967395 0.973986585016303 109 0.0212221299636429 0.0424442599272859 0.978777870036357 110 0.0172038184676237 0.0344076369352473 0.982796181532376 111 0.0136321859824962 0.0272643719649925 0.986367814017504 112 0.0136227566436769 0.0272455132873538 0.986377243356323 113 0.0124872959699889 0.0249745919399778 0.987512704030011 114 0.0191461758204072 0.0382923516408144 0.980853824179593 115 0.017761714329099 0.035523428658198 0.982238285670901 116 0.0176036460063923 0.0352072920127845 0.982396353993608 117 0.0143650816437962 0.0287301632875924 0.985634918356204 118 0.0149333160946056 0.0298666321892113 0.985066683905394 119 0.0120691161964736 0.0241382323929472 0.987930883803526 120 0.011017215050494 0.0220344301009879 0.988982784949506 121 0.00884927981957539 0.0176985596391508 0.991150720180425 122 0.0140520169939794 0.0281040339879588 0.985947983006021 123 0.012043124437435 0.02408624887487 0.987956875562565 124 0.0108230439579142 0.0216460879158285 0.989176956042086 125 0.0090373108212634 0.0180746216425268 0.990962689178737 126 0.00728451036486293 0.0145690207297259 0.992715489635137 127 0.00639914163591068 0.0127982832718214 0.993600858364089 128 0.0051065909934724 0.0102131819869448 0.994893409006528 129 0.00783375065335741 0.0156675013067148 0.992166249346643 130 0.00807963042126071 0.0161592608425214 0.991920369578739 131 0.0180949330914172 0.0361898661828345 0.981905066908583 132 0.0203689644007127 0.0407379288014254 0.979631035599287 133 0.0232617612230516 0.0465235224461032 0.976738238776948 134 0.0232562238225976 0.0465124476451952 0.976743776177402 135 0.0190360379134765 0.0380720758269531 0.980963962086523 136 0.0156372488519366 0.0312744977038731 0.984362751148063 137 0.0124430144348124 0.0248860288696248 0.987556985565188 138 0.0165772691347349 0.0331545382694698 0.983422730865265 139 0.0149240627111003 0.0298481254222005 0.9850759372889 140 0.0190311552513475 0.0380623105026949 0.980968844748653 141 0.0261129296616787 0.0522258593233575 0.973887070338321 142 0.0232966146305594 0.0465932292611189 0.976703385369441 143 0.0190133879411874 0.0380267758823748 0.980986612058813 144 0.0180774558323925 0.0361549116647849 0.981922544167607 145 0.0355026157921129 0.0710052315842258 0.964497384207887 146 0.0384221966721222 0.0768443933442445 0.961577803327878 147 0.0431987522006674 0.0863975044013349 0.956801247799333 148 0.0369645849533097 0.0739291699066194 0.96303541504669 149 0.0303268301811554 0.0606536603623109 0.969673169818845 150 0.0457293372484393 0.0914586744968786 0.954270662751561 151 0.041381104322207 0.0827622086444139 0.958618895677793 152 0.0410870915093941 0.0821741830187881 0.958912908490606 153 0.0717081799115342 0.143416359823068 0.928291820088466 154 0.0631597123469996 0.126319424693999 0.936840287653 155 0.0771128120061036 0.154225624012207 0.922887187993896 156 0.0648148402268 0.1296296804536 0.9351851597732 157 0.0564212903309121 0.112842580661824 0.943578709669088 158 0.0478502954782747 0.0957005909565494 0.952149704521725 159 0.0454570121941236 0.0909140243882471 0.954542987805876 160 0.0390355339078226 0.0780710678156453 0.960964466092177 161 0.0318688113299024 0.0637376226598049 0.968131188670098 162 0.0261879326304378 0.0523758652608757 0.973812067369562 163 0.0215813417593282 0.0431626835186564 0.978418658240672 164 0.018252422309859 0.036504844619718 0.981747577690141 165 0.0161383303745536 0.0322766607491072 0.983861669625446 166 0.0162516658896446 0.0325033317792892 0.983748334110355 167 0.0129568005570455 0.0259136011140909 0.987043199442954 168 0.0184794173862801 0.0369588347725603 0.98152058261372 169 0.0178942596272697 0.0357885192545395 0.98210574037273 170 0.0170189181653021 0.0340378363306043 0.982981081834698 171 0.0165616674819242 0.0331233349638483 0.983438332518076 172 0.0134360476918209 0.0268720953836419 0.986563952308179 173 0.0129583555085128 0.0259167110170255 0.987041644491487 174 0.0138774468141616 0.0277548936283232 0.986122553185838 175 0.0172407628840271 0.0344815257680543 0.982759237115973 176 0.0138951737672709 0.0277903475345418 0.986104826232729 177 0.0110519988555188 0.0221039977110376 0.988948001144481 178 0.00887074341861818 0.0177414868372364 0.991129256581382 179 0.00688321602168383 0.0137664320433677 0.993116783978316 180 0.00577443562849682 0.0115488712569936 0.994225564371503 181 0.00485393565206552 0.00970787130413104 0.995146064347935 182 0.0037887991637546 0.0075775983275092 0.996211200836245 183 0.0042414994903668 0.0084829989807336 0.995758500509633 184 0.00327054716546524 0.00654109433093048 0.996729452834535 185 0.0728407105468334 0.145681421093667 0.927159289453167 186 0.063836939009146 0.127673878018292 0.936163060990854 187 0.0755513774202359 0.151102754840472 0.924448622579764 188 0.064037138706066 0.128074277412132 0.935962861293934 189 0.0536541563999353 0.107308312799871 0.946345843600065 190 0.0443083311324273 0.0886166622648546 0.955691668867573 191 0.0387335344688042 0.0774670689376085 0.961266465531196 192 0.032480445606372 0.064960891212744 0.967519554393628 193 0.038777018804498 0.077554037608996 0.961222981195502 194 0.0425803720705005 0.085160744141001 0.9574196279295 195 0.0355414797065204 0.0710829594130408 0.96445852029348 196 0.0291430151993391 0.0582860303986782 0.970856984800661 197 0.0393432212360941 0.0786864424721881 0.960656778763906 198 0.0321751746361226 0.0643503492722451 0.967824825363877 199 0.0299691694417933 0.0599383388835865 0.970030830558207 200 0.0254685360251706 0.0509370720503413 0.974531463974829 201 0.0242099261925941 0.0484198523851882 0.975790073807406 202 0.0201830070835608 0.0403660141671215 0.979816992916439 203 0.0255271301508279 0.0510542603016559 0.974472869849172 204 0.0280598687947852 0.0561197375895705 0.971940131205215 205 0.0312224340495122 0.0624448680990244 0.968777565950488 206 0.0245716207548305 0.0491432415096609 0.97542837924517 207 0.024269912887764 0.0485398257755281 0.975730087112236 208 0.0199692881585583 0.0399385763171165 0.980030711841442 209 0.021672831963284 0.043345663926568 0.978327168036716 210 0.0174563467996669 0.0349126935993337 0.982543653200333 211 0.0189292802277184 0.0378585604554368 0.981070719772282 212 0.0292703191646911 0.0585406383293821 0.970729680835309 213 0.0228693544218274 0.0457387088436548 0.977130645578173 214 0.0330240210408287 0.0660480420816575 0.966975978959171 215 0.0284568550336946 0.0569137100673891 0.971543144966305 216 0.0220849841128488 0.0441699682256976 0.977915015887151 217 0.0243591123907342 0.0487182247814685 0.975640887609266 218 0.0204895888266629 0.0409791776533257 0.979510411173337 219 0.0183205505059486 0.0366411010118971 0.981679449494051 220 0.0137547982773797 0.0275095965547594 0.98624520172262 221 0.0119272356527667 0.0238544713055333 0.988072764347233 222 0.00858122100533879 0.0171624420106776 0.991418778994661 223 0.00634657417409723 0.0126931483481945 0.993653425825903 224 0.00496471680285496 0.00992943360570991 0.995035283197145 225 0.00429464582214449 0.00858929164428899 0.995705354177856 226 0.00994629167948218 0.0198925833589644 0.990053708320518 227 0.00753438359405262 0.0150687671881052 0.992465616405947 228 0.00537338633076864 0.0107467726615373 0.994626613669231 229 0.00380717833516546 0.00761435667033091 0.996192821664835 230 0.00266471220180086 0.00532942440360172 0.997335287798199 231 0.00267158170978458 0.00534316341956917 0.997328418290215 232 0.00494336392668184 0.00988672785336367 0.995056636073318 233 0.025946735443498 0.051893470886996 0.974053264556502 234 0.0384579406778068 0.0769158813556135 0.961542059322193 235 0.0277187884740288 0.0554375769480576 0.972281211525971 236 0.0239618139472756 0.0479236278945511 0.976038186052724 237 0.187771175358453 0.375542350716907 0.812228824641547 238 0.1470448611769 0.294089722353799 0.8529551388231 239 0.130216166245397 0.260432332490795 0.869783833754603 240 0.0988684339233101 0.19773686784662 0.90113156607669 241 0.0766001416875227 0.153200283375045 0.923399858312477 242 0.0614634178432019 0.122926835686404 0.938536582156798 243 0.056209776147019 0.112419552294038 0.943790223852981 244 0.10356267576434 0.207125351528679 0.89643732423566 245 0.0907837726734577 0.181567545346915 0.909216227326542 246 0.0696382930217302 0.13927658604346 0.93036170697827 247 0.0465296435673755 0.093059287134751 0.953470356432625 248 0.037805999878572 0.075611999757144 0.962194000121428 249 0.0340747449655487 0.0681494899310975 0.965925255034451 250 0.0414488690680374 0.0828977381360748 0.958551130931963 251 0.0218224478596723 0.0436448957193447 0.978177552140328 252 0.0547426763653307 0.109485352730661 0.945257323634669

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.249272273417128 & 0.498544546834257 & 0.750727726582872 \tabularnewline
13 & 0.168954109350984 & 0.337908218701967 & 0.831045890649016 \tabularnewline
14 & 0.188652474482694 & 0.377304948965389 & 0.811347525517306 \tabularnewline
15 & 0.113822199570938 & 0.227644399141877 & 0.886177800429062 \tabularnewline
16 & 0.0773581785451666 & 0.154716357090333 & 0.922641821454833 \tabularnewline
17 & 0.111089921688009 & 0.222179843376018 & 0.888910078311991 \tabularnewline
18 & 0.35029724400813 & 0.700594488016259 & 0.64970275599187 \tabularnewline
19 & 0.273076148217575 & 0.54615229643515 & 0.726923851782425 \tabularnewline
20 & 0.200364779799482 & 0.400729559598965 & 0.799635220200518 \tabularnewline
21 & 0.147329038244944 & 0.294658076489889 & 0.852670961755056 \tabularnewline
22 & 0.14242982215262 & 0.28485964430524 & 0.85757017784738 \tabularnewline
23 & 0.329613610691878 & 0.659227221383756 & 0.670386389308122 \tabularnewline
24 & 0.396108111170374 & 0.792216222340748 & 0.603891888829626 \tabularnewline
25 & 0.364643782622251 & 0.729287565244503 & 0.635356217377749 \tabularnewline
26 & 0.343013785262702 & 0.686027570525404 & 0.656986214737298 \tabularnewline
27 & 0.419522216901135 & 0.83904443380227 & 0.580477783098865 \tabularnewline
28 & 0.431039269566405 & 0.862078539132809 & 0.568960730433596 \tabularnewline
29 & 0.411178257665479 & 0.822356515330959 & 0.588821742334521 \tabularnewline
30 & 0.4445628643833 & 0.8891257287666 & 0.5554371356167 \tabularnewline
31 & 0.389182053396216 & 0.778364106792431 & 0.610817946603784 \tabularnewline
32 & 0.346620753254168 & 0.693241506508336 & 0.653379246745832 \tabularnewline
33 & 0.316677130929607 & 0.633354261859213 & 0.683322869070393 \tabularnewline
34 & 0.275674898300484 & 0.551349796600968 & 0.724325101699516 \tabularnewline
35 & 0.233139524871999 & 0.466279049743997 & 0.766860475128001 \tabularnewline
36 & 0.363623899560605 & 0.72724779912121 & 0.636376100439395 \tabularnewline
37 & 0.400480018023811 & 0.800960036047623 & 0.599519981976189 \tabularnewline
38 & 0.392518456881074 & 0.785036913762147 & 0.607481543118926 \tabularnewline
39 & 0.420646898193909 & 0.841293796387819 & 0.579353101806091 \tabularnewline
40 & 0.394036668820191 & 0.788073337640382 & 0.605963331179809 \tabularnewline
41 & 0.352608510695984 & 0.705217021391968 & 0.647391489304016 \tabularnewline
42 & 0.317815560782677 & 0.635631121565354 & 0.682184439217323 \tabularnewline
43 & 0.330602998434414 & 0.661205996868828 & 0.669397001565586 \tabularnewline
44 & 0.284193039977045 & 0.56838607995409 & 0.715806960022955 \tabularnewline
45 & 0.259307353804652 & 0.518614707609304 & 0.740692646195348 \tabularnewline
46 & 0.457373136543278 & 0.914746273086556 & 0.542626863456722 \tabularnewline
47 & 0.613015042694864 & 0.773969914610272 & 0.386984957305136 \tabularnewline
48 & 0.564790964894334 & 0.870418070211332 & 0.435209035105666 \tabularnewline
49 & 0.550115831249477 & 0.899768337501047 & 0.449884168750523 \tabularnewline
50 & 0.538886872116342 & 0.922226255767315 & 0.461113127883658 \tabularnewline
51 & 0.496029187990605 & 0.99205837598121 & 0.503970812009395 \tabularnewline
52 & 0.448976551667355 & 0.897953103334709 & 0.551023448332645 \tabularnewline
53 & 0.469409970867618 & 0.938819941735235 & 0.530590029132383 \tabularnewline
54 & 0.449833835993114 & 0.899667671986227 & 0.550166164006886 \tabularnewline
55 & 0.45206618336547 & 0.904132366730939 & 0.54793381663453 \tabularnewline
56 & 0.420708589827935 & 0.841417179655871 & 0.579291410172065 \tabularnewline
57 & 0.377122146901935 & 0.75424429380387 & 0.622877853098065 \tabularnewline
58 & 0.343504288197334 & 0.687008576394669 & 0.656495711802666 \tabularnewline
59 & 0.305381736916128 & 0.610763473832255 & 0.694618263083872 \tabularnewline
60 & 0.304715664842222 & 0.609431329684444 & 0.695284335157778 \tabularnewline
61 & 0.274885364314507 & 0.549770728629014 & 0.725114635685493 \tabularnewline
62 & 0.243391513321 & 0.486783026642 & 0.756608486679 \tabularnewline
63 & 0.213205555515493 & 0.426411111030986 & 0.786794444484507 \tabularnewline
64 & 0.184850255438615 & 0.369700510877231 & 0.815149744561385 \tabularnewline
65 & 0.159612090313773 & 0.319224180627547 & 0.840387909686227 \tabularnewline
66 & 0.135701682609405 & 0.27140336521881 & 0.864298317390595 \tabularnewline
67 & 0.118078554966231 & 0.236157109932462 & 0.881921445033769 \tabularnewline
68 & 0.147491712033944 & 0.294983424067887 & 0.852508287966056 \tabularnewline
69 & 0.347255538628955 & 0.69451107725791 & 0.652744461371045 \tabularnewline
70 & 0.309383520800725 & 0.61876704160145 & 0.690616479199275 \tabularnewline
71 & 0.466018474195671 & 0.932036948391342 & 0.533981525804329 \tabularnewline
72 & 0.427694883468798 & 0.855389766937597 & 0.572305116531202 \tabularnewline
73 & 0.415756314370459 & 0.831512628740918 & 0.584243685629541 \tabularnewline
74 & 0.394545848970235 & 0.789091697940469 & 0.605454151029765 \tabularnewline
75 & 0.359444377104182 & 0.718888754208365 & 0.640555622895818 \tabularnewline
76 & 0.407073802696672 & 0.814147605393345 & 0.592926197303328 \tabularnewline
77 & 0.374300584690814 & 0.748601169381629 & 0.625699415309186 \tabularnewline
78 & 0.346591344599645 & 0.69318268919929 & 0.653408655400355 \tabularnewline
79 & 0.375124096917485 & 0.75024819383497 & 0.624875903082515 \tabularnewline
80 & 0.344523836755934 & 0.689047673511868 & 0.655476163244066 \tabularnewline
81 & 0.311892769547428 & 0.623785539094855 & 0.688107230452572 \tabularnewline
82 & 0.277800972444902 & 0.555601944889804 & 0.722199027555098 \tabularnewline
83 & 0.254136867114177 & 0.508273734228354 & 0.745863132885823 \tabularnewline
84 & 0.22338179566367 & 0.446763591327341 & 0.77661820433633 \tabularnewline
85 & 0.21362430355121 & 0.42724860710242 & 0.78637569644879 \tabularnewline
86 & 0.186095183511229 & 0.372190367022457 & 0.813904816488771 \tabularnewline
87 & 0.162784483325638 & 0.325568966651276 & 0.837215516674362 \tabularnewline
88 & 0.147969314030638 & 0.295938628061275 & 0.852030685969362 \tabularnewline
89 & 0.127536795735546 & 0.255073591471092 & 0.872463204264454 \tabularnewline
90 & 0.129326332967502 & 0.258652665935003 & 0.870673667032498 \tabularnewline
91 & 0.111535331873573 & 0.223070663747147 & 0.888464668126427 \tabularnewline
92 & 0.0961283982313716 & 0.192256796462743 & 0.903871601768628 \tabularnewline
93 & 0.0825502956078306 & 0.165100591215661 & 0.917449704392169 \tabularnewline
94 & 0.0877425387684931 & 0.175485077536986 & 0.912257461231507 \tabularnewline
95 & 0.0780879857657512 & 0.156175971531502 & 0.921912014234249 \tabularnewline
96 & 0.0658294056936893 & 0.131658811387379 & 0.934170594306311 \tabularnewline
97 & 0.0689068074898876 & 0.137813614979775 & 0.931093192510112 \tabularnewline
98 & 0.0573579515440502 & 0.1147159030881 & 0.94264204845595 \tabularnewline
99 & 0.0475906360332547 & 0.0951812720665093 & 0.952409363966745 \tabularnewline
100 & 0.0425438584868558 & 0.0850877169737115 & 0.957456141513144 \tabularnewline
101 & 0.0369859310294413 & 0.0739718620588826 & 0.963014068970559 \tabularnewline
102 & 0.0420002433756055 & 0.084000486751211 & 0.957999756624395 \tabularnewline
103 & 0.0356653898073747 & 0.0713307796147493 & 0.964334610192625 \tabularnewline
104 & 0.0316665200782289 & 0.0633330401564578 & 0.968333479921771 \tabularnewline
105 & 0.0388094976881836 & 0.0776189953763671 & 0.961190502311816 \tabularnewline
106 & 0.0335801030215311 & 0.0671602060430622 & 0.966419896978469 \tabularnewline
107 & 0.0272903859757299 & 0.0545807719514598 & 0.97270961402427 \tabularnewline
108 & 0.0260134149836975 & 0.052026829967395 & 0.973986585016303 \tabularnewline
109 & 0.0212221299636429 & 0.0424442599272859 & 0.978777870036357 \tabularnewline
110 & 0.0172038184676237 & 0.0344076369352473 & 0.982796181532376 \tabularnewline
111 & 0.0136321859824962 & 0.0272643719649925 & 0.986367814017504 \tabularnewline
112 & 0.0136227566436769 & 0.0272455132873538 & 0.986377243356323 \tabularnewline
113 & 0.0124872959699889 & 0.0249745919399778 & 0.987512704030011 \tabularnewline
114 & 0.0191461758204072 & 0.0382923516408144 & 0.980853824179593 \tabularnewline
115 & 0.017761714329099 & 0.035523428658198 & 0.982238285670901 \tabularnewline
116 & 0.0176036460063923 & 0.0352072920127845 & 0.982396353993608 \tabularnewline
117 & 0.0143650816437962 & 0.0287301632875924 & 0.985634918356204 \tabularnewline
118 & 0.0149333160946056 & 0.0298666321892113 & 0.985066683905394 \tabularnewline
119 & 0.0120691161964736 & 0.0241382323929472 & 0.987930883803526 \tabularnewline
120 & 0.011017215050494 & 0.0220344301009879 & 0.988982784949506 \tabularnewline
121 & 0.00884927981957539 & 0.0176985596391508 & 0.991150720180425 \tabularnewline
122 & 0.0140520169939794 & 0.0281040339879588 & 0.985947983006021 \tabularnewline
123 & 0.012043124437435 & 0.02408624887487 & 0.987956875562565 \tabularnewline
124 & 0.0108230439579142 & 0.0216460879158285 & 0.989176956042086 \tabularnewline
125 & 0.0090373108212634 & 0.0180746216425268 & 0.990962689178737 \tabularnewline
126 & 0.00728451036486293 & 0.0145690207297259 & 0.992715489635137 \tabularnewline
127 & 0.00639914163591068 & 0.0127982832718214 & 0.993600858364089 \tabularnewline
128 & 0.0051065909934724 & 0.0102131819869448 & 0.994893409006528 \tabularnewline
129 & 0.00783375065335741 & 0.0156675013067148 & 0.992166249346643 \tabularnewline
130 & 0.00807963042126071 & 0.0161592608425214 & 0.991920369578739 \tabularnewline
131 & 0.0180949330914172 & 0.0361898661828345 & 0.981905066908583 \tabularnewline
132 & 0.0203689644007127 & 0.0407379288014254 & 0.979631035599287 \tabularnewline
133 & 0.0232617612230516 & 0.0465235224461032 & 0.976738238776948 \tabularnewline
134 & 0.0232562238225976 & 0.0465124476451952 & 0.976743776177402 \tabularnewline
135 & 0.0190360379134765 & 0.0380720758269531 & 0.980963962086523 \tabularnewline
136 & 0.0156372488519366 & 0.0312744977038731 & 0.984362751148063 \tabularnewline
137 & 0.0124430144348124 & 0.0248860288696248 & 0.987556985565188 \tabularnewline
138 & 0.0165772691347349 & 0.0331545382694698 & 0.983422730865265 \tabularnewline
139 & 0.0149240627111003 & 0.0298481254222005 & 0.9850759372889 \tabularnewline
140 & 0.0190311552513475 & 0.0380623105026949 & 0.980968844748653 \tabularnewline
141 & 0.0261129296616787 & 0.0522258593233575 & 0.973887070338321 \tabularnewline
142 & 0.0232966146305594 & 0.0465932292611189 & 0.976703385369441 \tabularnewline
143 & 0.0190133879411874 & 0.0380267758823748 & 0.980986612058813 \tabularnewline
144 & 0.0180774558323925 & 0.0361549116647849 & 0.981922544167607 \tabularnewline
145 & 0.0355026157921129 & 0.0710052315842258 & 0.964497384207887 \tabularnewline
146 & 0.0384221966721222 & 0.0768443933442445 & 0.961577803327878 \tabularnewline
147 & 0.0431987522006674 & 0.0863975044013349 & 0.956801247799333 \tabularnewline
148 & 0.0369645849533097 & 0.0739291699066194 & 0.96303541504669 \tabularnewline
149 & 0.0303268301811554 & 0.0606536603623109 & 0.969673169818845 \tabularnewline
150 & 0.0457293372484393 & 0.0914586744968786 & 0.954270662751561 \tabularnewline
151 & 0.041381104322207 & 0.0827622086444139 & 0.958618895677793 \tabularnewline
152 & 0.0410870915093941 & 0.0821741830187881 & 0.958912908490606 \tabularnewline
153 & 0.0717081799115342 & 0.143416359823068 & 0.928291820088466 \tabularnewline
154 & 0.0631597123469996 & 0.126319424693999 & 0.936840287653 \tabularnewline
155 & 0.0771128120061036 & 0.154225624012207 & 0.922887187993896 \tabularnewline
156 & 0.0648148402268 & 0.1296296804536 & 0.9351851597732 \tabularnewline
157 & 0.0564212903309121 & 0.112842580661824 & 0.943578709669088 \tabularnewline
158 & 0.0478502954782747 & 0.0957005909565494 & 0.952149704521725 \tabularnewline
159 & 0.0454570121941236 & 0.0909140243882471 & 0.954542987805876 \tabularnewline
160 & 0.0390355339078226 & 0.0780710678156453 & 0.960964466092177 \tabularnewline
161 & 0.0318688113299024 & 0.0637376226598049 & 0.968131188670098 \tabularnewline
162 & 0.0261879326304378 & 0.0523758652608757 & 0.973812067369562 \tabularnewline
163 & 0.0215813417593282 & 0.0431626835186564 & 0.978418658240672 \tabularnewline
164 & 0.018252422309859 & 0.036504844619718 & 0.981747577690141 \tabularnewline
165 & 0.0161383303745536 & 0.0322766607491072 & 0.983861669625446 \tabularnewline
166 & 0.0162516658896446 & 0.0325033317792892 & 0.983748334110355 \tabularnewline
167 & 0.0129568005570455 & 0.0259136011140909 & 0.987043199442954 \tabularnewline
168 & 0.0184794173862801 & 0.0369588347725603 & 0.98152058261372 \tabularnewline
169 & 0.0178942596272697 & 0.0357885192545395 & 0.98210574037273 \tabularnewline
170 & 0.0170189181653021 & 0.0340378363306043 & 0.982981081834698 \tabularnewline
171 & 0.0165616674819242 & 0.0331233349638483 & 0.983438332518076 \tabularnewline
172 & 0.0134360476918209 & 0.0268720953836419 & 0.986563952308179 \tabularnewline
173 & 0.0129583555085128 & 0.0259167110170255 & 0.987041644491487 \tabularnewline
174 & 0.0138774468141616 & 0.0277548936283232 & 0.986122553185838 \tabularnewline
175 & 0.0172407628840271 & 0.0344815257680543 & 0.982759237115973 \tabularnewline
176 & 0.0138951737672709 & 0.0277903475345418 & 0.986104826232729 \tabularnewline
177 & 0.0110519988555188 & 0.0221039977110376 & 0.988948001144481 \tabularnewline
178 & 0.00887074341861818 & 0.0177414868372364 & 0.991129256581382 \tabularnewline
179 & 0.00688321602168383 & 0.0137664320433677 & 0.993116783978316 \tabularnewline
180 & 0.00577443562849682 & 0.0115488712569936 & 0.994225564371503 \tabularnewline
181 & 0.00485393565206552 & 0.00970787130413104 & 0.995146064347935 \tabularnewline
182 & 0.0037887991637546 & 0.0075775983275092 & 0.996211200836245 \tabularnewline
183 & 0.0042414994903668 & 0.0084829989807336 & 0.995758500509633 \tabularnewline
184 & 0.00327054716546524 & 0.00654109433093048 & 0.996729452834535 \tabularnewline
185 & 0.0728407105468334 & 0.145681421093667 & 0.927159289453167 \tabularnewline
186 & 0.063836939009146 & 0.127673878018292 & 0.936163060990854 \tabularnewline
187 & 0.0755513774202359 & 0.151102754840472 & 0.924448622579764 \tabularnewline
188 & 0.064037138706066 & 0.128074277412132 & 0.935962861293934 \tabularnewline
189 & 0.0536541563999353 & 0.107308312799871 & 0.946345843600065 \tabularnewline
190 & 0.0443083311324273 & 0.0886166622648546 & 0.955691668867573 \tabularnewline
191 & 0.0387335344688042 & 0.0774670689376085 & 0.961266465531196 \tabularnewline
192 & 0.032480445606372 & 0.064960891212744 & 0.967519554393628 \tabularnewline
193 & 0.038777018804498 & 0.077554037608996 & 0.961222981195502 \tabularnewline
194 & 0.0425803720705005 & 0.085160744141001 & 0.9574196279295 \tabularnewline
195 & 0.0355414797065204 & 0.0710829594130408 & 0.96445852029348 \tabularnewline
196 & 0.0291430151993391 & 0.0582860303986782 & 0.970856984800661 \tabularnewline
197 & 0.0393432212360941 & 0.0786864424721881 & 0.960656778763906 \tabularnewline
198 & 0.0321751746361226 & 0.0643503492722451 & 0.967824825363877 \tabularnewline
199 & 0.0299691694417933 & 0.0599383388835865 & 0.970030830558207 \tabularnewline
200 & 0.0254685360251706 & 0.0509370720503413 & 0.974531463974829 \tabularnewline
201 & 0.0242099261925941 & 0.0484198523851882 & 0.975790073807406 \tabularnewline
202 & 0.0201830070835608 & 0.0403660141671215 & 0.979816992916439 \tabularnewline
203 & 0.0255271301508279 & 0.0510542603016559 & 0.974472869849172 \tabularnewline
204 & 0.0280598687947852 & 0.0561197375895705 & 0.971940131205215 \tabularnewline
205 & 0.0312224340495122 & 0.0624448680990244 & 0.968777565950488 \tabularnewline
206 & 0.0245716207548305 & 0.0491432415096609 & 0.97542837924517 \tabularnewline
207 & 0.024269912887764 & 0.0485398257755281 & 0.975730087112236 \tabularnewline
208 & 0.0199692881585583 & 0.0399385763171165 & 0.980030711841442 \tabularnewline
209 & 0.021672831963284 & 0.043345663926568 & 0.978327168036716 \tabularnewline
210 & 0.0174563467996669 & 0.0349126935993337 & 0.982543653200333 \tabularnewline
211 & 0.0189292802277184 & 0.0378585604554368 & 0.981070719772282 \tabularnewline
212 & 0.0292703191646911 & 0.0585406383293821 & 0.970729680835309 \tabularnewline
213 & 0.0228693544218274 & 0.0457387088436548 & 0.977130645578173 \tabularnewline
214 & 0.0330240210408287 & 0.0660480420816575 & 0.966975978959171 \tabularnewline
215 & 0.0284568550336946 & 0.0569137100673891 & 0.971543144966305 \tabularnewline
216 & 0.0220849841128488 & 0.0441699682256976 & 0.977915015887151 \tabularnewline
217 & 0.0243591123907342 & 0.0487182247814685 & 0.975640887609266 \tabularnewline
218 & 0.0204895888266629 & 0.0409791776533257 & 0.979510411173337 \tabularnewline
219 & 0.0183205505059486 & 0.0366411010118971 & 0.981679449494051 \tabularnewline
220 & 0.0137547982773797 & 0.0275095965547594 & 0.98624520172262 \tabularnewline
221 & 0.0119272356527667 & 0.0238544713055333 & 0.988072764347233 \tabularnewline
222 & 0.00858122100533879 & 0.0171624420106776 & 0.991418778994661 \tabularnewline
223 & 0.00634657417409723 & 0.0126931483481945 & 0.993653425825903 \tabularnewline
224 & 0.00496471680285496 & 0.00992943360570991 & 0.995035283197145 \tabularnewline
225 & 0.00429464582214449 & 0.00858929164428899 & 0.995705354177856 \tabularnewline
226 & 0.00994629167948218 & 0.0198925833589644 & 0.990053708320518 \tabularnewline
227 & 0.00753438359405262 & 0.0150687671881052 & 0.992465616405947 \tabularnewline
228 & 0.00537338633076864 & 0.0107467726615373 & 0.994626613669231 \tabularnewline
229 & 0.00380717833516546 & 0.00761435667033091 & 0.996192821664835 \tabularnewline
230 & 0.00266471220180086 & 0.00532942440360172 & 0.997335287798199 \tabularnewline
231 & 0.00267158170978458 & 0.00534316341956917 & 0.997328418290215 \tabularnewline
232 & 0.00494336392668184 & 0.00988672785336367 & 0.995056636073318 \tabularnewline
233 & 0.025946735443498 & 0.051893470886996 & 0.974053264556502 \tabularnewline
234 & 0.0384579406778068 & 0.0769158813556135 & 0.961542059322193 \tabularnewline
235 & 0.0277187884740288 & 0.0554375769480576 & 0.972281211525971 \tabularnewline
236 & 0.0239618139472756 & 0.0479236278945511 & 0.976038186052724 \tabularnewline
237 & 0.187771175358453 & 0.375542350716907 & 0.812228824641547 \tabularnewline
238 & 0.1470448611769 & 0.294089722353799 & 0.8529551388231 \tabularnewline
239 & 0.130216166245397 & 0.260432332490795 & 0.869783833754603 \tabularnewline
240 & 0.0988684339233101 & 0.19773686784662 & 0.90113156607669 \tabularnewline
241 & 0.0766001416875227 & 0.153200283375045 & 0.923399858312477 \tabularnewline
242 & 0.0614634178432019 & 0.122926835686404 & 0.938536582156798 \tabularnewline
243 & 0.056209776147019 & 0.112419552294038 & 0.943790223852981 \tabularnewline
244 & 0.10356267576434 & 0.207125351528679 & 0.89643732423566 \tabularnewline
245 & 0.0907837726734577 & 0.181567545346915 & 0.909216227326542 \tabularnewline
246 & 0.0696382930217302 & 0.13927658604346 & 0.93036170697827 \tabularnewline
247 & 0.0465296435673755 & 0.093059287134751 & 0.953470356432625 \tabularnewline
248 & 0.037805999878572 & 0.075611999757144 & 0.962194000121428 \tabularnewline
249 & 0.0340747449655487 & 0.0681494899310975 & 0.965925255034451 \tabularnewline
250 & 0.0414488690680374 & 0.0828977381360748 & 0.958551130931963 \tabularnewline
251 & 0.0218224478596723 & 0.0436448957193447 & 0.978177552140328 \tabularnewline
252 & 0.0547426763653307 & 0.109485352730661 & 0.945257323634669 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185683&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]12[/C][C]0.249272273417128[/C][C]0.498544546834257[/C][C]0.750727726582872[/C][/ROW]
[ROW][C]13[/C][C]0.168954109350984[/C][C]0.337908218701967[/C][C]0.831045890649016[/C][/ROW]
[ROW][C]14[/C][C]0.188652474482694[/C][C]0.377304948965389[/C][C]0.811347525517306[/C][/ROW]
[ROW][C]15[/C][C]0.113822199570938[/C][C]0.227644399141877[/C][C]0.886177800429062[/C][/ROW]
[ROW][C]16[/C][C]0.0773581785451666[/C][C]0.154716357090333[/C][C]0.922641821454833[/C][/ROW]
[ROW][C]17[/C][C]0.111089921688009[/C][C]0.222179843376018[/C][C]0.888910078311991[/C][/ROW]
[ROW][C]18[/C][C]0.35029724400813[/C][C]0.700594488016259[/C][C]0.64970275599187[/C][/ROW]
[ROW][C]19[/C][C]0.273076148217575[/C][C]0.54615229643515[/C][C]0.726923851782425[/C][/ROW]
[ROW][C]20[/C][C]0.200364779799482[/C][C]0.400729559598965[/C][C]0.799635220200518[/C][/ROW]
[ROW][C]21[/C][C]0.147329038244944[/C][C]0.294658076489889[/C][C]0.852670961755056[/C][/ROW]
[ROW][C]22[/C][C]0.14242982215262[/C][C]0.28485964430524[/C][C]0.85757017784738[/C][/ROW]
[ROW][C]23[/C][C]0.329613610691878[/C][C]0.659227221383756[/C][C]0.670386389308122[/C][/ROW]
[ROW][C]24[/C][C]0.396108111170374[/C][C]0.792216222340748[/C][C]0.603891888829626[/C][/ROW]
[ROW][C]25[/C][C]0.364643782622251[/C][C]0.729287565244503[/C][C]0.635356217377749[/C][/ROW]
[ROW][C]26[/C][C]0.343013785262702[/C][C]0.686027570525404[/C][C]0.656986214737298[/C][/ROW]
[ROW][C]27[/C][C]0.419522216901135[/C][C]0.83904443380227[/C][C]0.580477783098865[/C][/ROW]
[ROW][C]28[/C][C]0.431039269566405[/C][C]0.862078539132809[/C][C]0.568960730433596[/C][/ROW]
[ROW][C]29[/C][C]0.411178257665479[/C][C]0.822356515330959[/C][C]0.588821742334521[/C][/ROW]
[ROW][C]30[/C][C]0.4445628643833[/C][C]0.8891257287666[/C][C]0.5554371356167[/C][/ROW]
[ROW][C]31[/C][C]0.389182053396216[/C][C]0.778364106792431[/C][C]0.610817946603784[/C][/ROW]
[ROW][C]32[/C][C]0.346620753254168[/C][C]0.693241506508336[/C][C]0.653379246745832[/C][/ROW]
[ROW][C]33[/C][C]0.316677130929607[/C][C]0.633354261859213[/C][C]0.683322869070393[/C][/ROW]
[ROW][C]34[/C][C]0.275674898300484[/C][C]0.551349796600968[/C][C]0.724325101699516[/C][/ROW]
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[ROW][C]129[/C][C]0.00783375065335741[/C][C]0.0156675013067148[/C][C]0.992166249346643[/C][/ROW]
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[ROW][C]181[/C][C]0.00485393565206552[/C][C]0.00970787130413104[/C][C]0.995146064347935[/C][/ROW]
[ROW][C]182[/C][C]0.0037887991637546[/C][C]0.0075775983275092[/C][C]0.996211200836245[/C][/ROW]
[ROW][C]183[/C][C]0.0042414994903668[/C][C]0.0084829989807336[/C][C]0.995758500509633[/C][/ROW]
[ROW][C]184[/C][C]0.00327054716546524[/C][C]0.00654109433093048[/C][C]0.996729452834535[/C][/ROW]
[ROW][C]185[/C][C]0.0728407105468334[/C][C]0.145681421093667[/C][C]0.927159289453167[/C][/ROW]
[ROW][C]186[/C][C]0.063836939009146[/C][C]0.127673878018292[/C][C]0.936163060990854[/C][/ROW]
[ROW][C]187[/C][C]0.0755513774202359[/C][C]0.151102754840472[/C][C]0.924448622579764[/C][/ROW]
[ROW][C]188[/C][C]0.064037138706066[/C][C]0.128074277412132[/C][C]0.935962861293934[/C][/ROW]
[ROW][C]189[/C][C]0.0536541563999353[/C][C]0.107308312799871[/C][C]0.946345843600065[/C][/ROW]
[ROW][C]190[/C][C]0.0443083311324273[/C][C]0.0886166622648546[/C][C]0.955691668867573[/C][/ROW]
[ROW][C]191[/C][C]0.0387335344688042[/C][C]0.0774670689376085[/C][C]0.961266465531196[/C][/ROW]
[ROW][C]192[/C][C]0.032480445606372[/C][C]0.064960891212744[/C][C]0.967519554393628[/C][/ROW]
[ROW][C]193[/C][C]0.038777018804498[/C][C]0.077554037608996[/C][C]0.961222981195502[/C][/ROW]
[ROW][C]194[/C][C]0.0425803720705005[/C][C]0.085160744141001[/C][C]0.9574196279295[/C][/ROW]
[ROW][C]195[/C][C]0.0355414797065204[/C][C]0.0710829594130408[/C][C]0.96445852029348[/C][/ROW]
[ROW][C]196[/C][C]0.0291430151993391[/C][C]0.0582860303986782[/C][C]0.970856984800661[/C][/ROW]
[ROW][C]197[/C][C]0.0393432212360941[/C][C]0.0786864424721881[/C][C]0.960656778763906[/C][/ROW]
[ROW][C]198[/C][C]0.0321751746361226[/C][C]0.0643503492722451[/C][C]0.967824825363877[/C][/ROW]
[ROW][C]199[/C][C]0.0299691694417933[/C][C]0.0599383388835865[/C][C]0.970030830558207[/C][/ROW]
[ROW][C]200[/C][C]0.0254685360251706[/C][C]0.0509370720503413[/C][C]0.974531463974829[/C][/ROW]
[ROW][C]201[/C][C]0.0242099261925941[/C][C]0.0484198523851882[/C][C]0.975790073807406[/C][/ROW]
[ROW][C]202[/C][C]0.0201830070835608[/C][C]0.0403660141671215[/C][C]0.979816992916439[/C][/ROW]
[ROW][C]203[/C][C]0.0255271301508279[/C][C]0.0510542603016559[/C][C]0.974472869849172[/C][/ROW]
[ROW][C]204[/C][C]0.0280598687947852[/C][C]0.0561197375895705[/C][C]0.971940131205215[/C][/ROW]
[ROW][C]205[/C][C]0.0312224340495122[/C][C]0.0624448680990244[/C][C]0.968777565950488[/C][/ROW]
[ROW][C]206[/C][C]0.0245716207548305[/C][C]0.0491432415096609[/C][C]0.97542837924517[/C][/ROW]
[ROW][C]207[/C][C]0.024269912887764[/C][C]0.0485398257755281[/C][C]0.975730087112236[/C][/ROW]
[ROW][C]208[/C][C]0.0199692881585583[/C][C]0.0399385763171165[/C][C]0.980030711841442[/C][/ROW]
[ROW][C]209[/C][C]0.021672831963284[/C][C]0.043345663926568[/C][C]0.978327168036716[/C][/ROW]
[ROW][C]210[/C][C]0.0174563467996669[/C][C]0.0349126935993337[/C][C]0.982543653200333[/C][/ROW]
[ROW][C]211[/C][C]0.0189292802277184[/C][C]0.0378585604554368[/C][C]0.981070719772282[/C][/ROW]
[ROW][C]212[/C][C]0.0292703191646911[/C][C]0.0585406383293821[/C][C]0.970729680835309[/C][/ROW]
[ROW][C]213[/C][C]0.0228693544218274[/C][C]0.0457387088436548[/C][C]0.977130645578173[/C][/ROW]
[ROW][C]214[/C][C]0.0330240210408287[/C][C]0.0660480420816575[/C][C]0.966975978959171[/C][/ROW]
[ROW][C]215[/C][C]0.0284568550336946[/C][C]0.0569137100673891[/C][C]0.971543144966305[/C][/ROW]
[ROW][C]216[/C][C]0.0220849841128488[/C][C]0.0441699682256976[/C][C]0.977915015887151[/C][/ROW]
[ROW][C]217[/C][C]0.0243591123907342[/C][C]0.0487182247814685[/C][C]0.975640887609266[/C][/ROW]
[ROW][C]218[/C][C]0.0204895888266629[/C][C]0.0409791776533257[/C][C]0.979510411173337[/C][/ROW]
[ROW][C]219[/C][C]0.0183205505059486[/C][C]0.0366411010118971[/C][C]0.981679449494051[/C][/ROW]
[ROW][C]220[/C][C]0.0137547982773797[/C][C]0.0275095965547594[/C][C]0.98624520172262[/C][/ROW]
[ROW][C]221[/C][C]0.0119272356527667[/C][C]0.0238544713055333[/C][C]0.988072764347233[/C][/ROW]
[ROW][C]222[/C][C]0.00858122100533879[/C][C]0.0171624420106776[/C][C]0.991418778994661[/C][/ROW]
[ROW][C]223[/C][C]0.00634657417409723[/C][C]0.0126931483481945[/C][C]0.993653425825903[/C][/ROW]
[ROW][C]224[/C][C]0.00496471680285496[/C][C]0.00992943360570991[/C][C]0.995035283197145[/C][/ROW]
[ROW][C]225[/C][C]0.00429464582214449[/C][C]0.00858929164428899[/C][C]0.995705354177856[/C][/ROW]
[ROW][C]226[/C][C]0.00994629167948218[/C][C]0.0198925833589644[/C][C]0.990053708320518[/C][/ROW]
[ROW][C]227[/C][C]0.00753438359405262[/C][C]0.0150687671881052[/C][C]0.992465616405947[/C][/ROW]
[ROW][C]228[/C][C]0.00537338633076864[/C][C]0.0107467726615373[/C][C]0.994626613669231[/C][/ROW]
[ROW][C]229[/C][C]0.00380717833516546[/C][C]0.00761435667033091[/C][C]0.996192821664835[/C][/ROW]
[ROW][C]230[/C][C]0.00266471220180086[/C][C]0.00532942440360172[/C][C]0.997335287798199[/C][/ROW]
[ROW][C]231[/C][C]0.00267158170978458[/C][C]0.00534316341956917[/C][C]0.997328418290215[/C][/ROW]
[ROW][C]232[/C][C]0.00494336392668184[/C][C]0.00988672785336367[/C][C]0.995056636073318[/C][/ROW]
[ROW][C]233[/C][C]0.025946735443498[/C][C]0.051893470886996[/C][C]0.974053264556502[/C][/ROW]
[ROW][C]234[/C][C]0.0384579406778068[/C][C]0.0769158813556135[/C][C]0.961542059322193[/C][/ROW]
[ROW][C]235[/C][C]0.0277187884740288[/C][C]0.0554375769480576[/C][C]0.972281211525971[/C][/ROW]
[ROW][C]236[/C][C]0.0239618139472756[/C][C]0.0479236278945511[/C][C]0.976038186052724[/C][/ROW]
[ROW][C]237[/C][C]0.187771175358453[/C][C]0.375542350716907[/C][C]0.812228824641547[/C][/ROW]
[ROW][C]238[/C][C]0.1470448611769[/C][C]0.294089722353799[/C][C]0.8529551388231[/C][/ROW]
[ROW][C]239[/C][C]0.130216166245397[/C][C]0.260432332490795[/C][C]0.869783833754603[/C][/ROW]
[ROW][C]240[/C][C]0.0988684339233101[/C][C]0.19773686784662[/C][C]0.90113156607669[/C][/ROW]
[ROW][C]241[/C][C]0.0766001416875227[/C][C]0.153200283375045[/C][C]0.923399858312477[/C][/ROW]
[ROW][C]242[/C][C]0.0614634178432019[/C][C]0.122926835686404[/C][C]0.938536582156798[/C][/ROW]
[ROW][C]243[/C][C]0.056209776147019[/C][C]0.112419552294038[/C][C]0.943790223852981[/C][/ROW]
[ROW][C]244[/C][C]0.10356267576434[/C][C]0.207125351528679[/C][C]0.89643732423566[/C][/ROW]
[ROW][C]245[/C][C]0.0907837726734577[/C][C]0.181567545346915[/C][C]0.909216227326542[/C][/ROW]
[ROW][C]246[/C][C]0.0696382930217302[/C][C]0.13927658604346[/C][C]0.93036170697827[/C][/ROW]
[ROW][C]247[/C][C]0.0465296435673755[/C][C]0.093059287134751[/C][C]0.953470356432625[/C][/ROW]
[ROW][C]248[/C][C]0.037805999878572[/C][C]0.075611999757144[/C][C]0.962194000121428[/C][/ROW]
[ROW][C]249[/C][C]0.0340747449655487[/C][C]0.0681494899310975[/C][C]0.965925255034451[/C][/ROW]
[ROW][C]250[/C][C]0.0414488690680374[/C][C]0.0828977381360748[/C][C]0.958551130931963[/C][/ROW]
[ROW][C]251[/C][C]0.0218224478596723[/C][C]0.0436448957193447[/C][C]0.978177552140328[/C][/ROW]
[ROW][C]252[/C][C]0.0547426763653307[/C][C]0.109485352730661[/C][C]0.945257323634669[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185683&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185683&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 12 0.249272273417128 0.498544546834257 0.750727726582872 13 0.168954109350984 0.337908218701967 0.831045890649016 14 0.188652474482694 0.377304948965389 0.811347525517306 15 0.113822199570938 0.227644399141877 0.886177800429062 16 0.0773581785451666 0.154716357090333 0.922641821454833 17 0.111089921688009 0.222179843376018 0.888910078311991 18 0.35029724400813 0.700594488016259 0.64970275599187 19 0.273076148217575 0.54615229643515 0.726923851782425 20 0.200364779799482 0.400729559598965 0.799635220200518 21 0.147329038244944 0.294658076489889 0.852670961755056 22 0.14242982215262 0.28485964430524 0.85757017784738 23 0.329613610691878 0.659227221383756 0.670386389308122 24 0.396108111170374 0.792216222340748 0.603891888829626 25 0.364643782622251 0.729287565244503 0.635356217377749 26 0.343013785262702 0.686027570525404 0.656986214737298 27 0.419522216901135 0.83904443380227 0.580477783098865 28 0.431039269566405 0.862078539132809 0.568960730433596 29 0.411178257665479 0.822356515330959 0.588821742334521 30 0.4445628643833 0.8891257287666 0.5554371356167 31 0.389182053396216 0.778364106792431 0.610817946603784 32 0.346620753254168 0.693241506508336 0.653379246745832 33 0.316677130929607 0.633354261859213 0.683322869070393 34 0.275674898300484 0.551349796600968 0.724325101699516 35 0.233139524871999 0.466279049743997 0.766860475128001 36 0.363623899560605 0.72724779912121 0.636376100439395 37 0.400480018023811 0.800960036047623 0.599519981976189 38 0.392518456881074 0.785036913762147 0.607481543118926 39 0.420646898193909 0.841293796387819 0.579353101806091 40 0.394036668820191 0.788073337640382 0.605963331179809 41 0.352608510695984 0.705217021391968 0.647391489304016 42 0.317815560782677 0.635631121565354 0.682184439217323 43 0.330602998434414 0.661205996868828 0.669397001565586 44 0.284193039977045 0.56838607995409 0.715806960022955 45 0.259307353804652 0.518614707609304 0.740692646195348 46 0.457373136543278 0.914746273086556 0.542626863456722 47 0.613015042694864 0.773969914610272 0.386984957305136 48 0.564790964894334 0.870418070211332 0.435209035105666 49 0.550115831249477 0.899768337501047 0.449884168750523 50 0.538886872116342 0.922226255767315 0.461113127883658 51 0.496029187990605 0.99205837598121 0.503970812009395 52 0.448976551667355 0.897953103334709 0.551023448332645 53 0.469409970867618 0.938819941735235 0.530590029132383 54 0.449833835993114 0.899667671986227 0.550166164006886 55 0.45206618336547 0.904132366730939 0.54793381663453 56 0.420708589827935 0.841417179655871 0.579291410172065 57 0.377122146901935 0.75424429380387 0.622877853098065 58 0.343504288197334 0.687008576394669 0.656495711802666 59 0.305381736916128 0.610763473832255 0.694618263083872 60 0.304715664842222 0.609431329684444 0.695284335157778 61 0.274885364314507 0.549770728629014 0.725114635685493 62 0.243391513321 0.486783026642 0.756608486679 63 0.213205555515493 0.426411111030986 0.786794444484507 64 0.184850255438615 0.369700510877231 0.815149744561385 65 0.159612090313773 0.319224180627547 0.840387909686227 66 0.135701682609405 0.27140336521881 0.864298317390595 67 0.118078554966231 0.236157109932462 0.881921445033769 68 0.147491712033944 0.294983424067887 0.852508287966056 69 0.347255538628955 0.69451107725791 0.652744461371045 70 0.309383520800725 0.61876704160145 0.690616479199275 71 0.466018474195671 0.932036948391342 0.533981525804329 72 0.427694883468798 0.855389766937597 0.572305116531202 73 0.415756314370459 0.831512628740918 0.584243685629541 74 0.394545848970235 0.789091697940469 0.605454151029765 75 0.359444377104182 0.718888754208365 0.640555622895818 76 0.407073802696672 0.814147605393345 0.592926197303328 77 0.374300584690814 0.748601169381629 0.625699415309186 78 0.346591344599645 0.69318268919929 0.653408655400355 79 0.375124096917485 0.75024819383497 0.624875903082515 80 0.344523836755934 0.689047673511868 0.655476163244066 81 0.311892769547428 0.623785539094855 0.688107230452572 82 0.277800972444902 0.555601944889804 0.722199027555098 83 0.254136867114177 0.508273734228354 0.745863132885823 84 0.22338179566367 0.446763591327341 0.77661820433633 85 0.21362430355121 0.42724860710242 0.78637569644879 86 0.186095183511229 0.372190367022457 0.813904816488771 87 0.162784483325638 0.325568966651276 0.837215516674362 88 0.147969314030638 0.295938628061275 0.852030685969362 89 0.127536795735546 0.255073591471092 0.872463204264454 90 0.129326332967502 0.258652665935003 0.870673667032498 91 0.111535331873573 0.223070663747147 0.888464668126427 92 0.0961283982313716 0.192256796462743 0.903871601768628 93 0.0825502956078306 0.165100591215661 0.917449704392169 94 0.0877425387684931 0.175485077536986 0.912257461231507 95 0.0780879857657512 0.156175971531502 0.921912014234249 96 0.0658294056936893 0.131658811387379 0.934170594306311 97 0.0689068074898876 0.137813614979775 0.931093192510112 98 0.0573579515440502 0.1147159030881 0.94264204845595 99 0.0475906360332547 0.0951812720665093 0.952409363966745 100 0.0425438584868558 0.0850877169737115 0.957456141513144 101 0.0369859310294413 0.0739718620588826 0.963014068970559 102 0.0420002433756055 0.084000486751211 0.957999756624395 103 0.0356653898073747 0.0713307796147493 0.964334610192625 104 0.0316665200782289 0.0633330401564578 0.968333479921771 105 0.0388094976881836 0.0776189953763671 0.961190502311816 106 0.0335801030215311 0.0671602060430622 0.966419896978469 107 0.0272903859757299 0.0545807719514598 0.97270961402427 108 0.0260134149836975 0.052026829967395 0.973986585016303 109 0.0212221299636429 0.0424442599272859 0.978777870036357 110 0.0172038184676237 0.0344076369352473 0.982796181532376 111 0.0136321859824962 0.0272643719649925 0.986367814017504 112 0.0136227566436769 0.0272455132873538 0.986377243356323 113 0.0124872959699889 0.0249745919399778 0.987512704030011 114 0.0191461758204072 0.0382923516408144 0.980853824179593 115 0.017761714329099 0.035523428658198 0.982238285670901 116 0.0176036460063923 0.0352072920127845 0.982396353993608 117 0.0143650816437962 0.0287301632875924 0.985634918356204 118 0.0149333160946056 0.0298666321892113 0.985066683905394 119 0.0120691161964736 0.0241382323929472 0.987930883803526 120 0.011017215050494 0.0220344301009879 0.988982784949506 121 0.00884927981957539 0.0176985596391508 0.991150720180425 122 0.0140520169939794 0.0281040339879588 0.985947983006021 123 0.012043124437435 0.02408624887487 0.987956875562565 124 0.0108230439579142 0.0216460879158285 0.989176956042086 125 0.0090373108212634 0.0180746216425268 0.990962689178737 126 0.00728451036486293 0.0145690207297259 0.992715489635137 127 0.00639914163591068 0.0127982832718214 0.993600858364089 128 0.0051065909934724 0.0102131819869448 0.994893409006528 129 0.00783375065335741 0.0156675013067148 0.992166249346643 130 0.00807963042126071 0.0161592608425214 0.991920369578739 131 0.0180949330914172 0.0361898661828345 0.981905066908583 132 0.0203689644007127 0.0407379288014254 0.979631035599287 133 0.0232617612230516 0.0465235224461032 0.976738238776948 134 0.0232562238225976 0.0465124476451952 0.976743776177402 135 0.0190360379134765 0.0380720758269531 0.980963962086523 136 0.0156372488519366 0.0312744977038731 0.984362751148063 137 0.0124430144348124 0.0248860288696248 0.987556985565188 138 0.0165772691347349 0.0331545382694698 0.983422730865265 139 0.0149240627111003 0.0298481254222005 0.9850759372889 140 0.0190311552513475 0.0380623105026949 0.980968844748653 141 0.0261129296616787 0.0522258593233575 0.973887070338321 142 0.0232966146305594 0.0465932292611189 0.976703385369441 143 0.0190133879411874 0.0380267758823748 0.980986612058813 144 0.0180774558323925 0.0361549116647849 0.981922544167607 145 0.0355026157921129 0.0710052315842258 0.964497384207887 146 0.0384221966721222 0.0768443933442445 0.961577803327878 147 0.0431987522006674 0.0863975044013349 0.956801247799333 148 0.0369645849533097 0.0739291699066194 0.96303541504669 149 0.0303268301811554 0.0606536603623109 0.969673169818845 150 0.0457293372484393 0.0914586744968786 0.954270662751561 151 0.041381104322207 0.0827622086444139 0.958618895677793 152 0.0410870915093941 0.0821741830187881 0.958912908490606 153 0.0717081799115342 0.143416359823068 0.928291820088466 154 0.0631597123469996 0.126319424693999 0.936840287653 155 0.0771128120061036 0.154225624012207 0.922887187993896 156 0.0648148402268 0.1296296804536 0.9351851597732 157 0.0564212903309121 0.112842580661824 0.943578709669088 158 0.0478502954782747 0.0957005909565494 0.952149704521725 159 0.0454570121941236 0.0909140243882471 0.954542987805876 160 0.0390355339078226 0.0780710678156453 0.960964466092177 161 0.0318688113299024 0.0637376226598049 0.968131188670098 162 0.0261879326304378 0.0523758652608757 0.973812067369562 163 0.0215813417593282 0.0431626835186564 0.978418658240672 164 0.018252422309859 0.036504844619718 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0.00485393565206552 0.00970787130413104 0.995146064347935 182 0.0037887991637546 0.0075775983275092 0.996211200836245 183 0.0042414994903668 0.0084829989807336 0.995758500509633 184 0.00327054716546524 0.00654109433093048 0.996729452834535 185 0.0728407105468334 0.145681421093667 0.927159289453167 186 0.063836939009146 0.127673878018292 0.936163060990854 187 0.0755513774202359 0.151102754840472 0.924448622579764 188 0.064037138706066 0.128074277412132 0.935962861293934 189 0.0536541563999353 0.107308312799871 0.946345843600065 190 0.0443083311324273 0.0886166622648546 0.955691668867573 191 0.0387335344688042 0.0774670689376085 0.961266465531196 192 0.032480445606372 0.064960891212744 0.967519554393628 193 0.038777018804498 0.077554037608996 0.961222981195502 194 0.0425803720705005 0.085160744141001 0.9574196279295 195 0.0355414797065204 0.0710829594130408 0.96445852029348 196 0.0291430151993391 0.0582860303986782 0.970856984800661 197 0.0393432212360941 0.0786864424721881 0.960656778763906 198 0.0321751746361226 0.0643503492722451 0.967824825363877 199 0.0299691694417933 0.0599383388835865 0.970030830558207 200 0.0254685360251706 0.0509370720503413 0.974531463974829 201 0.0242099261925941 0.0484198523851882 0.975790073807406 202 0.0201830070835608 0.0403660141671215 0.979816992916439 203 0.0255271301508279 0.0510542603016559 0.974472869849172 204 0.0280598687947852 0.0561197375895705 0.971940131205215 205 0.0312224340495122 0.0624448680990244 0.968777565950488 206 0.0245716207548305 0.0491432415096609 0.97542837924517 207 0.024269912887764 0.0485398257755281 0.975730087112236 208 0.0199692881585583 0.0399385763171165 0.980030711841442 209 0.021672831963284 0.043345663926568 0.978327168036716 210 0.0174563467996669 0.0349126935993337 0.982543653200333 211 0.0189292802277184 0.0378585604554368 0.981070719772282 212 0.0292703191646911 0.0585406383293821 0.970729680835309 213 0.0228693544218274 0.0457387088436548 0.977130645578173 214 0.0330240210408287 0.0660480420816575 0.966975978959171 215 0.0284568550336946 0.0569137100673891 0.971543144966305 216 0.0220849841128488 0.0441699682256976 0.977915015887151 217 0.0243591123907342 0.0487182247814685 0.975640887609266 218 0.0204895888266629 0.0409791776533257 0.979510411173337 219 0.0183205505059486 0.0366411010118971 0.981679449494051 220 0.0137547982773797 0.0275095965547594 0.98624520172262 221 0.0119272356527667 0.0238544713055333 0.988072764347233 222 0.00858122100533879 0.0171624420106776 0.991418778994661 223 0.00634657417409723 0.0126931483481945 0.993653425825903 224 0.00496471680285496 0.00992943360570991 0.995035283197145 225 0.00429464582214449 0.00858929164428899 0.995705354177856 226 0.00994629167948218 0.0198925833589644 0.990053708320518 227 0.00753438359405262 0.0150687671881052 0.992465616405947 228 0.00537338633076864 0.0107467726615373 0.994626613669231 229 0.00380717833516546 0.00761435667033091 0.996192821664835 230 0.00266471220180086 0.00532942440360172 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0.953470356432625 248 0.037805999878572 0.075611999757144 0.962194000121428 249 0.0340747449655487 0.0681494899310975 0.965925255034451 250 0.0414488690680374 0.0828977381360748 0.958551130931963 251 0.0218224478596723 0.0436448957193447 0.978177552140328 252 0.0547426763653307 0.109485352730661 0.945257323634669

 Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity Description # significant tests % significant tests OK/NOK 1% type I error level 10 0.04149377593361 NOK 5% type I error level 85 0.352697095435685 NOK 10% type I error level 133 0.551867219917012 NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 10 & 0.04149377593361 & NOK \tabularnewline
5% type I error level & 85 & 0.352697095435685 & NOK \tabularnewline
10% type I error level & 133 & 0.551867219917012 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185683&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]10[/C][C]0.04149377593361[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]85[/C][C]0.352697095435685[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]133[/C][C]0.551867219917012[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185683&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185683&T=6

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

 Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity Description # significant tests % significant tests OK/NOK 1% type I error level 10 0.04149377593361 NOK 5% type I error level 85 0.352697095435685 NOK 10% type I error level 133 0.551867219917012 NOK

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Parameters (Session):
par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)library(lmtest)n25 <- 25 #minimum number of obs. for Goldfeld-Quandt 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')}