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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Module--
Title produced by softwareMultiple Regression
Date of computationMon, 26 Nov 2012 12:47:22 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/26/t1353952079n7ws09t1r9lojm4.htm/, Retrieved Fri, 15 Aug 2025 09:38:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=193404, Retrieved Fri, 15 Aug 2025 09:38:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact248

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Decreasing Compet...] [2010-11-17 09:04:39] [b98453cac15ba1066b407e146608df68]
- R  D  [Multiple Regression] [Maand effect] [2012-11-05 13:06:01] [8fc56f6caf42131500698d1cf21d4abb]
-  M        [Multiple Regression] [MR maand effect] [2012-11-26 17:47:22] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	41	38	13	12	14	12	53	32
1	39	32	16	11	18	11	83	51
1	30	35	19	15	11	14	66	42
1	31	33	15	6	12	12	67	41
1	34	37	14	13	16	21	76	46
1	35	29	13	10	18	12	78	47
1	39	31	19	12	14	22	53	37
1	34	36	15	14	14	11	80	49
1	36	35	14	12	15	10	74	45
1	37	38	15	9	15	13	76	47
1	38	31	16	10	17	10	79	49
1	36	34	16	12	19	8	54	33
1	38	35	16	12	10	15	67	42
1	39	38	16	11	16	14	54	33
1	33	37	17	15	18	10	87	53
1	32	33	15	12	14	14	58	36
1	36	32	15	10	14	14	75	45
1	38	38	20	12	17	11	88	54
1	39	38	18	11	14	10	64	41
1	32	32	16	12	16	13	57	36
1	32	33	16	11	18	9.5	66	41
1	31	31	16	12	11	14	68	44
1	39	38	19	13	14	12	54	33
1	37	39	16	11	12	14	56	37
1	39	32	17	12	17	11	86	52
1	41	32	17	13	9	9	80	47
1	36	35	16	10	16	11	76	43
1	33	37	15	14	14	15	69	44
1	33	33	16	12	15	14	78	45
1	34	33	14	10	11	13	67	44
1	31	31	15	12	16	9	80	49
1	27	32	12	8	13	15	54	33
1	37	31	14	10	17	10	71	43
1	34	37	16	12	15	11	84	54
1	34	30	14	12	14	13	74	42
1	32	33	10	7	16	8	71	44
1	29	31	10	9	9	20	63	37
1	36	33	14	12	15	12	71	43
1	29	31	16	10	17	10	76	46
1	35	33	16	10	13	10	69	42
1	37	32	16	10	15	9	74	45
1	34	33	14	12	16	14	75	44
1	38	32	20	15	16	8	54	33
1	35	33	14	10	12	14	52	31
1	38	28	14	10	15	11	69	42
1	37	35	11	12	11	13	68	40
1	38	39	14	13	15	9	65	43
1	33	34	15	11	15	11	75	46
1	36	38	16	11	17	15	74	42
1	38	32	14	12	13	11	75	45
1	32	38	16	14	16	10	72	44
1	32	30	14	10	14	14	67	40
1	32	33	12	12	11	18	63	37
1	34	38	16	13	12	14	62	46
1	32	32	9	5	12	11	63	36
1	37	35	14	6	15	14.5	76	47
1	39	34	16	12	16	13	74	45
1	29	34	16	12	15	9	67	42
1	37	36	15	11	12	10	73	43
1	35	34	16	10	12	15	70	43
1	30	28	12	7	8	20	53	32
1	38	34	16	12	13	12	77	45
1	34	35	16	14	11	12	80	48
1	31	35	14	11	14	14	52	31
1	34	31	16	12	15	13	54	33
2	35	37	17	13	10	11	80	49
2	36	35	18	14	11	17	66	42
2	30	27	18	11	12	12	73	41
2	39	40	12	12	15	13	63	38
2	35	37	16	12	15	14	69	42
2	38	36	10	8	14	13	67	44
2	31	38	14	11	16	15	54	33
2	34	39	18	14	15	13	81	48
2	38	41	18	14	15	10	69	40
2	34	27	16	12	13	11	84	50
2	39	30	17	9	12	19	80	49
2	37	37	16	13	17	13	70	43
2	34	31	16	11	13	17	69	44
2	28	31	13	12	15	13	77	47
2	37	27	16	12	13	9	54	33
2	33	36	16	12	15	11	79	46
2	35	37	16	12	15	9	71	45
2	37	33	15	12	16	12	73	43
2	32	34	15	11	15	12	72	44
2	33	31	16	10	14	13	77	47
2	38	39	14	9	15	13	75	45
2	33	34	16	12	14	12	69	42
2	29	32	16	12	13	15	54	33
2	33	33	15	12	7	22	70	43
2	31	36	12	9	17	13	73	46
2	36	32	17	15	13	15	54	33
2	35	41	16	12	15	13	77	46
2	32	28	15	12	14	15	82	48
2	29	30	13	12	13	12.5	80	47
2	39	36	16	10	16	11	80	47
2	37	35	16	13	12	16	69	43
2	35	31	16	9	14	11	78	46
2	37	34	16	12	17	11	81	48
2	32	36	14	10	15	10	76	46
2	38	36	16	14	17	10	76	45
2	37	35	16	11	12	16	73	45
2	36	37	20	15	16	12	85	52
2	32	28	15	11	11	11	66	42
2	33	39	16	11	15	16	79	47
2	40	32	13	12	9	19	68	41
2	38	35	17	12	16	11	76	47
2	41	39	16	12	15	16	71	43
2	36	35	16	11	10	15	54	33
2	43	42	12	7	10	24	46	30
2	30	34	16	12	15	14	85	52
2	31	33	16	14	11	15	74	44
2	32	41	17	11	13	11	88	55
2	32	33	13	11	14	15	38	11
2	37	34	12	10	18	12	76	47
2	37	32	18	13	16	10	86	53
2	33	40	14	13	14	14	54	33
2	34	40	14	8	14	13	67	44
2	33	35	13	11	14	9	69	42
2	38	36	16	12	14	15	90	55
2	33	37	13	11	12	15	54	33
2	31	27	16	13	14	14	76	46
2	38	39	13	12	15	11	89	54
2	37	38	16	14	15	8	76	47
2	36	31	15	13	15	11	73	45
2	31	33	16	15	13	11	79	47
2	39	32	15	10	17	8	90	55
2	44	39	17	11	17	10	74	44
2	33	36	15	9	19	11	81	53
2	35	33	12	11	15	13	72	44
2	32	33	16	10	13	11	71	42
2	28	32	10	11	9	20	66	40
2	40	37	16	8	15	10	77	46
2	27	30	12	11	15	15	65	40
2	37	38	14	12	15	12	74	46
2	32	29	15	12	16	14	85	53
2	28	22	13	9	11	23	54	33
2	34	35	15	11	14	14	63	42
2	30	35	11	10	11	16	54	35
2	35	34	12	8	15	11	64	40
2	31	35	11	9	13	12	69	41
2	32	34	16	8	15	10	54	33
2	30	37	15	9	16	14	84	51
2	30	35	17	15	14	12	86	53
2	31	23	16	11	15	12	77	46
2	40	31	10	8	16	11	89	55
2	32	27	18	13	16	12	76	47
2	36	36	13	12	11	13	60	38
2	32	31	16	12	12	11	75	46
2	35	32	13	9	9	19	73	46
2	38	39	10	7	16	12	85	53
2	42	37	15	13	13	17	79	47
2	34	38	16	9	16	9	71	41
2	35	39	16	6	12	12	72	44
1	38	34	14	8	9	19	69	43
2	33	31	10	8	13	18	78	51
2	36	32	17	15	13	15	54	33
2	32	37	13	6	14	14	69	43
2	33	36	15	9	19	11	81	53
2	34	32	16	11	13	9	84	51
2	32	38	12	8	12	18	84	50
2	34	36	13	8	13	16	69	46
3	27	26	13	10	10	24	66	43
3	31	26	12	8	14	14	81	47
3	38	33	17	14	16	20	82	50
3	34	39	15	10	10	18	72	43
3	24	30	10	8	11	23	54	33
3	30	33	14	11	14	12	78	48
3	26	25	11	12	12	14	74	44
3	34	38	13	12	9	16	82	50
3	27	37	16	12	9	18	73	41
3	37	31	12	5	11	20	55	34
3	36	37	16	12	16	12	72	44
3	41	35	12	10	9	12	78	47
3	29	25	9	7	13	17	59	35
3	36	28	12	12	16	13	72	44
3	32	35	15	11	13	9	78	44
3	37	33	12	8	9	16	68	43
3	30	30	12	9	12	18	69	41
3	31	31	14	10	16	10	67	41
3	38	37	12	9	11	14	74	42
3	36	36	16	12	14	11	54	33
3	35	30	11	6	13	9	67	41
3	31	36	19	15	15	11	70	44
3	38	32	15	12	14	10	80	48
3	22	28	8	12	16	11	89	55
3	32	36	16	12	13	19	76	44
3	36	34	17	11	14	14	74	43
3	39	31	12	7	15	12	87	52
3	28	28	11	7	13	14	54	30
3	32	36	11	5	11	21	61	39
3	32	36	14	12	11	13	38	11
3	38	40	16	12	14	10	75	44
3	32	33	12	3	15	15	69	42
3	35	37	16	11	11	16	62	41
3	32	32	13	10	15	14	72	44
3	37	38	15	12	12	12	70	44
3	34	31	16	9	14	19	79	48
3	33	37	16	12	14	15	87	53
3	33	33	14	9	8	19	62	37
3	26	32	16	12	13	13	77	44
3	30	30	16	12	9	17	69	44
3	24	30	14	10	15	12	69	40
3	34	31	11	9	17	11	75	42
3	34	32	12	12	13	14	54	35
3	33	34	15	8	15	11	72	43
3	34	36	15	11	15	13	74	45
3	35	37	16	11	14	12	85	55
3	35	36	16	12	16	15	52	31
3	36	33	11	10	13	14	70	44
3	34	33	15	10	16	12	84	50
3	34	33	12	12	9	17	64	40
3	41	44	12	12	16	11	84	53
3	32	39	15	11	11	18	87	54
3	30	32	15	8	10	13	79	49
3	35	35	16	12	11	17	67	40
3	28	25	14	10	15	13	65	41
3	33	35	17	11	17	11	85	52
3	39	34	14	10	14	12	83	52
3	36	35	13	8	8	22	61	36
3	36	39	15	12	15	14	82	52
3	35	33	13	12	11	12	76	46
3	38	36	14	10	16	12	58	31
3	33	32	15	12	10	17	72	44
3	31	32	12	9	15	9	72	44
3	34	36	13	9	9	21	38	11
3	32	36	8	6	16	10	78	46
3	31	32	14	10	19	11	54	33
3	33	34	14	9	12	12	63	34
3	34	33	11	9	8	23	66	42
3	34	35	12	9	11	13	70	43
3	34	30	13	6	14	12	71	43
3	33	38	10	10	9	16	67	44
3	32	34	16	6	15	9	58	36
3	41	33	18	14	13	17	72	46
3	34	32	13	10	16	9	72	44
3	36	31	11	10	11	14	70	43
3	37	30	4	6	12	17	76	50
3	36	27	13	12	13	13	50	33
3	29	31	16	12	10	11	72	43
3	37	30	10	7	11	12	72	44
3	27	32	12	8	12	10	88	53
3	35	35	12	11	8	19	53	34
3	28	28	10	3	12	16	58	35
3	35	33	13	6	12	16	66	40
3	37	31	15	10	15	14	82	53
3	29	35	12	8	11	20	69	42
3	32	35	14	9	13	15	68	43
3	36	32	10	9	14	23	44	29
3	19	21	12	8	10	20	56	36
3	21	20	12	9	12	16	53	30
3	31	34	11	7	15	14	70	42
3	33	32	10	7	13	17	78	47
3	36	34	12	6	13	11	71	44
3	33	32	16	9	13	13	72	45
3	37	33	12	10	12	17	68	44
3	34	33	14	11	12	15	67	43
3	35	37	16	12	9	21	75	43
3	31	32	14	8	9	18	62	40
3	37	34	13	11	15	15	67	41
3	35	30	4	3	10	8	83	52
3	27	30	15	11	14	12	64	38
3	34	38	11	12	15	12	68	41
3	40	36	11	7	7	22	62	39
3	29	32	14	9	14	12	72	43

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 15 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193404&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]15 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193404&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193404&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 5.11367550101075 -0.404599312019866month[t] + 0.0347834365471906Connected[t] + 0.0433406498517761Separate[t] + 0.576062196352004Software[t] + 0.0796225833189934Happiness[t] -0.0261020091912696Depression[t] + 0.0282902834264207Belonging[t] -0.032651180900308Belonging_Final[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  5.11367550101075 -0.404599312019866month[t] +  0.0347834365471906Connected[t] +  0.0433406498517761Separate[t] +  0.576062196352004Software[t] +  0.0796225833189934Happiness[t] -0.0261020091912696Depression[t] +  0.0282902834264207Belonging[t] -0.032651180900308Belonging_Final[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193404&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  5.11367550101075 -0.404599312019866month[t] +  0.0347834365471906Connected[t] +  0.0433406498517761Separate[t] +  0.576062196352004Software[t] +  0.0796225833189934Happiness[t] -0.0261020091912696Depression[t] +  0.0282902834264207Belonging[t] -0.032651180900308Belonging_Final[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193404&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193404&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 5.11367550101075 -0.404599312019866month[t] + 0.0347834365471906Connected[t] + 0.0433406498517761Separate[t] + 0.576062196352004Software[t] + 0.0796225833189934Happiness[t] -0.0261020091912696Depression[t] + 0.0282902834264207Belonging[t] -0.032651180900308Belonging_Final[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)5.113675501010751.9691682.59690.0099540.004977
month-0.4045993120198660.159517-2.53640.0117970.005898
Connected0.03478343654719060.0347561.00080.3178790.15894
Separate0.04334064985177610.035281.22850.2204020.110201
Software0.5760621963520040.05277110.916300
Happiness0.07962258331899340.0578451.37650.1698790.08494
Depression-0.02610200919126960.042437-0.61510.539050.269525
Belonging0.02829028342642070.0377660.74910.4544970.227248
Belonging_Final-0.0326511809003080.056098-0.5820.5610530.280527

\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) & 5.11367550101075 & 1.969168 & 2.5969 & 0.009954 & 0.004977 \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
Separate & 0.0433406498517761 & 0.03528 & 1.2285 & 0.220402 & 0.110201 \tabularnewline
Software & 0.576062196352004 & 0.052771 & 10.9163 & 0 & 0 \tabularnewline
Happiness & 0.0796225833189934 & 0.057845 & 1.3765 & 0.169879 & 0.08494 \tabularnewline
Depression & -0.0261020091912696 & 0.042437 & -0.6151 & 0.53905 & 0.269525 \tabularnewline
Belonging & 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=193404&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]5.11367550101075[/C][C]1.969168[/C][C]2.5969[/C][C]0.009954[/C][C]0.004977[/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]Separate[/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]Happiness[/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]Belonging[/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=193404&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193404&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)5.113675501010751.9691682.59690.0099540.004977
month-0.4045993120198660.159517-2.53640.0117970.005898
Connected0.03478343654719060.0347561.00080.3178790.15894
Separate0.04334064985177610.035281.22850.2204020.110201
Software0.5760621963520040.05277110.916300
Happiness0.07962258331899340.0578451.37650.1698790.08494
Depression-0.02610200919126960.042437-0.61510.539050.269525
Belonging0.02829028342642070.0377660.74910.4544970.227248
Belonging_Final-0.0326511809003080.056098-0.5820.5610530.280527






Multiple Linear Regression - Regression Statistics
Multiple R0.664098147499978
R-squared0.441026349512903
Adjusted R-squared0.423489921262327
F-TEST (value)25.1491548456241
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.86477720145106
Sum Squared Residuals886.735472818168

\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 & 886.735472818168 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193404&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]886.735472818168[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193404&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193404&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.664098147499978
R-squared0.441026349512903
Adjusted R-squared0.423489921262327
F-TEST (value)25.1491548456241
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.86477720145106
Sum Squared Residuals886.735472818168






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11315.9509274269783-2.95092742697833
21615.61818286657530.381817133424685
31916.91666437166082.0833356283392
41511.87297480736473.12702519263533
51416.3580519877682-2.35805198776817
61314.7360162717571-1.73601627175708
71915.15370000850733.8462999914927
81517.0077560505479-2.00775605054786
91415.9484454966394-1.94844549663943
101514.29803647116440.701963528835648
111614.86261723779161.13738276220844
121616.1018077007214-0.101807700721447
131615.38931096589850.610689034101526
141615.40797860831350.592021391686478
151718.0043950630554-1.00439506305541
161515.3798159239431-0.379815923943083
171514.51055881772240.489441182277558
182016.3833808166033.61661918339703
191815.37483486550242.62516513449764
201615.49353216649410.506467833505857
211615.30276946513760.697230534862409
221615.04117682479710.958823175202897
231916.45306185276212.54693814723792
241614.98923789504661.01076210495345
251716.16684214898730.833157851012718
261716.22120877420730.778791225792725
271614.97172460671661.0282753932834
281516.7639680138983-1.76396801389828
291615.76616698423490.233833015765091
301414.0778957672031-0.0778957672030682
311515.7460272839639-0.746027283963926
321212.7373771224323-0.737377122432316
331414.7974186192348-0.797418619234848
341615.92850012021880.0714998797812352
351415.6022003060943-1.60220030609429
361012.9219264013097-2.92192640130967
371013.0146729900312-3.01467299003116
381415.7899916900747-1.78999169007469
391614.56264900128851.4373509987115
401614.47211332661551.52788667338449
411614.72718460011861.27281539988145
421415.8283533347221-1.82835333472214
432017.57401211321132.42598788678869
441414.1663108781857-0.166310878185676
451414.4929035444449-0.492903544444921
461115.5799467762799-4.57994677627985
471416.604228985647-2.60422898564702
481515.1942294341289-0.19422943412892
491615.62909391322530.370906086774685
501415.7309335277756-1.73093352777565
511617.1471512900765-1.14715129007646
521414.2216774089203-0.221677408920302
531215.1453403734528-3.14534037345282
541615.8695524007130.130447599287036
55911.3645521776952-2.3645521776952
561412.40067491876611.59932508123389
571616.0107717121744-0.0107717121744091
581615.58764435886460.412355641135433
591515.2486517151036-0.248651715103607
601614.30096044971811.69903955028194
611211.56804057123740.431959428762648
621615.84809338514080.15190661485923
631616.7320968224481-0.732096822448143
641414.8491657946905-0.849165794690457
651615.45321849883940.546781501160583
661715.7867282952991.21327170470102
671816.06639745499831.93360254500173
681814.22360084200553.7763991579945
691215.7039588645577-3.70395886455773
701615.44783813657970.552161863420334
711013.0291955081803-3.02919550818027
721414.6990097947249-0.699009794724861
731816.82153871734651.17846128265349
741817.0473858368980.952614163101955
751615.06185386664440.938146133355616
761713.26865780022513.73134219977487
771616.2744534843814-0.274453484381421
781614.27409504855741.7259049514426
791315.0334785537398-2.03347855373977
801614.92476976718111.07523023281889
811615.56553475187030.434465248129707
821615.53697520668790.463024793312068
831515.5563789647739-0.556378964773851
841514.70917618789190.290823812108052
851613.97564876045272.02435123954728
861414.0085733239176-0.00857332391764802
871615.22083074899350.779169251006497
881614.70659346891481.29340653108515
891514.35475102652220.64524897347781
901213.7050807374168-1.70508073741682
911716.67826411380120.321735886198806
921615.74302028898820.256979711011827
931515.0195639849035-0.0195639849034682
941314.9635980286721-1.9635980286721
951614.69737266429451.30262733570547
961615.68306295708270.316937042917327
971613.58229891990442.41770108009563
981615.76851057004570.231489429954284
991414.3198580815311-0.319858081531102
1001617.0247038337606-1.02470383376056
1011614.57879733628371.42120266371627
1022017.46876748970412.53123251029595
1031514.05230462593870.947695374061321
1041614.9563332782171.04366672178304
1051314.8011674216603-1.80116742166032
1061715.65821183689391.34178816310611
1071615.71494542313640.285054576863643
1081614.26516952799151.73483047200847
1091212.1445025399444-0.144502539944408
1101615.2700317301080.729968269891964
1111616.0190228965521-0.0190228965520518
1121714.9728991243272.02710087567299
1131314.6235262603592-1.62352626035923
1141214.5611065152376-2.56110651523764
1151816.1825664051971.81743359480299
1161415.8742392027801-1.87423920278009
1171413.06342436139860.936575638601393
1181314.7664152300671-1.76641523006708
1191615.572753804110.42724619588997
1201314.4067456846915-1.40674568469149
1211615.43916476528990.560835234710133
1221315.8911672712233-2.89116727122332
1231616.9042581868609-0.904258186860854
1241515.8921534889468-0.892153488946772
1251616.9022361707383-0.9022361707383
1261514.7036320628420.296367937158024
1271715.61131042759051.38868957240952
1281513.98386079664091.01613920335906
1291214.7440838384905-2.74408383849047
1301613.99364226261562.00635773738435
1311013.7576725915982-3.75767259159822
1321613.51763211448282.48236788551719
1331214.2161631177914-2.21616311779137
1341415.6237963714392-1.62379637143923
1351515.1698667563622-0.169866756362222
1361312.14215570462570.857844295374259
1371514.50094692009940.499053079900598
1381113.4686249246835-2.46862492468349
1391213.0157243738586-1.01572437385864
1401113.4194465342762-2.4194465342762
1411612.88313150544633.11686849455371
1421513.75585057140021.24414942859977
1431717.0097795066055-0.00977950660548231
1441614.27379465830671.72620534169329
1451013.3567315625142-3.35673156251416
1461815.65274620595732.34725379404272
1471315.0228847719538-2.02288477195382
1481614.96201918240161.03798081759844
1491312.87725916249890.122740837501083
1501012.9838669107856-2.98386691078565
1511516.1494801243129-1.14948012431288
1521614.02757313785671.97242686214327
1531611.91105101507544.0889489849246
1541412.88162029650711.11837970349286
1551012.5110772982986-2.51107729829856
1561716.67826411380120.321735886198806
1571311.77484088460681.22515911539323
1581513.98386079664091.01613920335906
1591614.72204775703351.27795224296651
1601212.9024487088536-0.902448708853642
1611312.72341135615090.276588643849074
1621312.35944475142150.640555248578502
1631212.21971405789-0.21971405789
1641716.15592569301070.844074306989343
1651513.49271101103111.50728898896894
1661011.3690856488793-1.36908564887932
1671414.1511837465642-0.151183746564223
1681114.0473814027883-3.04738140278828
1691314.6284207569089-1.62842075690889
1701614.32864011010921.67135988989077
1711210.21036951488851.78963048511152
1721615.22941735128720.770582648712831
1731213.6789589162402-1.67895891624021
174911.1422436631215-2.14224366312148
1751214.8132494934299-2.81324949342992
1761514.43672008721820.563279912781796
1771212.0443133302158-0.0443133302158333
1781212.5271258979837-0.527125897983653
1791413.65203802068790.347961979312088
1801213.2423636290015-1.24236362900149
1811614.90287143221651.09712856778351
1821111.2308165908512-0.230816590851172
1831916.63024496677492.36975503322511
1841515.0709573706774-0.0709573706773568
185814.5002572284975-6.50025722849755
1861614.73852227465641.26147772534355
1871714.40111576811252.59888423188754
1881212.2769350009329-0.276935000932919
1891111.3375926910729-0.33759269107286
1901110.23353936827710.766460631722878
1911414.7383473626723-0.738347362672255
1921615.40683587596070.593164124039306
193129.554864139151822.44513586084818
1941613.93110147346462.06889852653535
1951313.589629361434-0.589629361433986
1961514.93247053755730.0675294624426782
1971612.8970880194333.10291198056704
1981615.01800947072730.981990529272659
1991412.34947855432961.6505214456704
2001614.54136139454021.45863860545976
2011613.9445932035732.05540679642697
2021413.32261846105740.677381538942582
2031113.4275177946163-2.42751779461626
2041214.4367109870216-2.43671098702159
2051512.66992691345482.33007308654516
2061514.45865242543130.541347574568722
2071614.46793724639011.53206275360993
2081614.931646920491.06835307951002
2091113.5562780239837-2.5562780239837
2101513.97793980179691.02206019820312
2111214.2029022057862-2.20290220578625
2121215.7784438651911-3.7784438651911
2131514.14402017910060.855979820899399
2141512.03070326771532.9692967322847
2151614.56848295895421.43151704104576
2161413.073134634190.926865365809959
2171714.67461237544132.32538762455869
2181413.94235982251960.0576401774804177
2191311.89050283722281.1094971627772
2201515.2059654363509-0.205965436350932
2211314.671017170643-1.67101717064298
2221414.1319205655599-0.131920565559881
2231514.30011824651640.69988175348359
2241213.1092937744911-1.10929377449114
2251312.71166640654250.288333593457519
226811.7472131342751-3.74721313427506
2271413.80158017396440.198419826035607
2281413.02026742792360.979732572076422
2291112.2297591833159-1.22975918331585
2301212.8968382776945-0.896838277694454
2311311.24520848195421.75479151804577
2321013.2130657616632-3.21306576166323
2331611.36771740091844.63228259908156
2341815.94741616960612.05258383039392
2351313.8693288638037-0.869328863803709
2361113.3430027385425-2.34300273854247
237410.9726967298314-6.97269672983142
2381314.2678178481433-1.26781784814329
2391614.30690708652381.6930929134762
2401011.6823923405169-1.68239234051694
2411212.2879119795221-0.287911979522082
2421213.5011921116947-1.50119211169468
243108.851422533167451.14857746683254
2441311.10286279022251.89713720977749
2451513.70924810047961.2907518995204
2461211.96850573174150.0314942682585027
2471412.87773198600271.12226801399732
2481012.5358000227952-2.53580002279517
2491210.76241308588411.23758691411589
2501211.73939094400440.260609055995627
2511111.9220624304821-0.92206243048211
2521011.730463172571-1.73046317257097
2531211.40196619942770.598033800572313
2541612.88255626328213.11744373671785
2551213.3765522827852-1.37655228278524
2561413.90482908535210.0951709146478974
2571614.51987977996521.48012022003483
2581411.66827988484082.33172011515923
2591314.356690156603-1.35669015660305
26049.38334580594879-5.38334580594879
2611513.84725932840051.15274067159949
2621115.1083609537208-4.10836095372081
2631111.3476291943178-0.347629194317833
2641412.91444947140431.08555052859574

\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 & 0.381817133424685 \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 & -0.101807700721447 \tabularnewline
13 & 16 & 15.3893109658985 & 0.610689034101526 \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 & 0.697230534862409 \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 & 0.233833015765091 \tabularnewline
30 & 14 & 14.0778957672031 & -0.0778957672030682 \tabularnewline
31 & 15 & 15.7460272839639 & -0.746027283963926 \tabularnewline
32 & 12 & 12.7373771224323 & -0.737377122432316 \tabularnewline
33 & 14 & 14.7974186192348 & -0.797418619234848 \tabularnewline
34 & 16 & 15.9285001202188 & 0.0714998797812352 \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 & -0.166310878185676 \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 & 0.370906086774685 \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 & -2.3645521776952 \tabularnewline
56 & 14 & 12.4006749187661 & 1.59932508123389 \tabularnewline
57 & 16 & 16.0107717121744 & -0.0107717121744091 \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 & 0.431959428762648 \tabularnewline
62 & 16 & 15.8480933851408 & 0.15190661485923 \tabularnewline
63 & 16 & 16.7320968224481 & -0.732096822448143 \tabularnewline
64 & 14 & 14.8491657946905 & -0.849165794690457 \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 & -0.274453484381421 \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 & 0.290823812108052 \tabularnewline
85 & 16 & 13.9756487604527 & 2.02435123954728 \tabularnewline
86 & 14 & 14.0085733239176 & -0.00857332391764802 \tabularnewline
87 & 16 & 15.2208307489935 & 0.779169251006497 \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 & 0.256979711011827 \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 & 0.316937042917327 \tabularnewline
97 & 16 & 13.5822989199044 & 2.41770108009563 \tabularnewline
98 & 16 & 15.7685105700457 & 0.231489429954284 \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 & -0.144502539944408 \tabularnewline
110 & 16 & 15.270031730108 & 0.729968269891964 \tabularnewline
111 & 16 & 16.0190228965521 & -0.0190228965520518 \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 & -0.9022361707383 \tabularnewline
126 & 15 & 14.703632062842 & 0.296367937158024 \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 & 2.48236788551719 \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 & -0.00977950660548231 \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 & -0.902448708853642 \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 & 0.770582648712831 \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 & 0.563279912781796 \tabularnewline
177 & 12 & 12.0443133302158 & -0.0443133302158333 \tabularnewline
178 & 12 & 12.5271258979837 & -0.527125897983653 \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 & -0.0709573706773568 \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 & -0.276935000932919 \tabularnewline
189 & 11 & 11.3375926910729 & -0.33759269107286 \tabularnewline
190 & 11 & 10.2335393682771 & 0.766460631722878 \tabularnewline
191 & 14 & 14.7383473626723 & -0.738347362672255 \tabularnewline
192 & 16 & 15.4068358759607 & 0.593164124039306 \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 & 0.0675294624426782 \tabularnewline
197 & 16 & 12.897088019433 & 3.10291198056704 \tabularnewline
198 & 16 & 15.0180094707273 & 0.981990529272659 \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 & 0.926865365809959 \tabularnewline
217 & 17 & 14.6746123754413 & 2.32538762455869 \tabularnewline
218 & 14 & 13.9423598225196 & 0.0576401774804177 \tabularnewline
219 & 13 & 11.8905028372228 & 1.1094971627772 \tabularnewline
220 & 15 & 15.2059654363509 & -0.205965436350932 \tabularnewline
221 & 13 & 14.671017170643 & -1.67101717064298 \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 & -3.74721313427506 \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 & -0.869328863803709 \tabularnewline
236 & 11 & 13.3430027385425 & -2.34300273854247 \tabularnewline
237 & 4 & 10.9726967298314 & -6.97269672983142 \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 & 0.260609055995627 \tabularnewline
251 & 11 & 11.9220624304821 & -0.92206243048211 \tabularnewline
252 & 10 & 11.730463172571 & -1.73046317257097 \tabularnewline
253 & 12 & 11.4019661994277 & 0.598033800572313 \tabularnewline
254 & 16 & 12.8825562632821 & 3.11744373671785 \tabularnewline
255 & 12 & 13.3765522827852 & -1.37655228278524 \tabularnewline
256 & 14 & 13.9048290853521 & 0.0951709146478974 \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=193404&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]0.381817133424685[/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]-0.101807700721447[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.3893109658985[/C][C]0.610689034101526[/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]0.697230534862409[/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]0.233833015765091[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.0778957672031[/C][C]-0.0778957672030682[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.7460272839639[/C][C]-0.746027283963926[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.7373771224323[/C][C]-0.737377122432316[/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]0.0714998797812352[/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]-0.166310878185676[/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]0.370906086774685[/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]-2.3645521776952[/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]-0.0107717121744091[/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]0.431959428762648[/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]-0.849165794690457[/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]-0.274453484381421[/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]0.290823812108052[/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]-0.00857332391764802[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.2208307489935[/C][C]0.779169251006497[/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]0.256979711011827[/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]0.316937042917327[/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]0.231489429954284[/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]-0.144502539944408[/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]-0.0190228965520518[/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]-0.9022361707383[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.703632062842[/C][C]0.296367937158024[/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]2.48236788551719[/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]-0.00977950660548231[/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]-0.902448708853642[/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]0.770582648712831[/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]0.563279912781796[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.0443133302158[/C][C]-0.0443133302158333[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.5271258979837[/C][C]-0.527125897983653[/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]-0.0709573706773568[/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]-0.276935000932919[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.3375926910729[/C][C]-0.33759269107286[/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]0.593164124039306[/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]0.0675294624426782[/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]0.981990529272659[/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]0.926865365809959[/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]1.1094971627772[/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]-1.67101717064298[/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]-3.74721313427506[/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]-0.869328863803709[/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]-6.97269672983142[/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]0.260609055995627[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.9220624304821[/C][C]-0.92206243048211[/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]0.598033800572313[/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]0.0951709146478974[/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=193404&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193404&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11315.9509274269783-2.95092742697833
21615.61818286657530.381817133424685
31916.91666437166082.0833356283392
41511.87297480736473.12702519263533
51416.3580519877682-2.35805198776817
61314.7360162717571-1.73601627175708
71915.15370000850733.8462999914927
81517.0077560505479-2.00775605054786
91415.9484454966394-1.94844549663943
101514.29803647116440.701963528835648
111614.86261723779161.13738276220844
121616.1018077007214-0.101807700721447
131615.38931096589850.610689034101526
141615.40797860831350.592021391686478
151718.0043950630554-1.00439506305541
161515.3798159239431-0.379815923943083
171514.51055881772240.489441182277558
182016.3833808166033.61661918339703
191815.37483486550242.62516513449764
201615.49353216649410.506467833505857
211615.30276946513760.697230534862409
221615.04117682479710.958823175202897
231916.45306185276212.54693814723792
241614.98923789504661.01076210495345
251716.16684214898730.833157851012718
261716.22120877420730.778791225792725
271614.97172460671661.0282753932834
281516.7639680138983-1.76396801389828
291615.76616698423490.233833015765091
301414.0778957672031-0.0778957672030682
311515.7460272839639-0.746027283963926
321212.7373771224323-0.737377122432316
331414.7974186192348-0.797418619234848
341615.92850012021880.0714998797812352
351415.6022003060943-1.60220030609429
361012.9219264013097-2.92192640130967
371013.0146729900312-3.01467299003116
381415.7899916900747-1.78999169007469
391614.56264900128851.4373509987115
401614.47211332661551.52788667338449
411614.72718460011861.27281539988145
421415.8283533347221-1.82835333472214
432017.57401211321132.42598788678869
441414.1663108781857-0.166310878185676
451414.4929035444449-0.492903544444921
461115.5799467762799-4.57994677627985
471416.604228985647-2.60422898564702
481515.1942294341289-0.19422943412892
491615.62909391322530.370906086774685
501415.7309335277756-1.73093352777565
511617.1471512900765-1.14715129007646
521414.2216774089203-0.221677408920302
531215.1453403734528-3.14534037345282
541615.8695524007130.130447599287036
55911.3645521776952-2.3645521776952
561412.40067491876611.59932508123389
571616.0107717121744-0.0107717121744091
581615.58764435886460.412355641135433
591515.2486517151036-0.248651715103607
601614.30096044971811.69903955028194
611211.56804057123740.431959428762648
621615.84809338514080.15190661485923
631616.7320968224481-0.732096822448143
641414.8491657946905-0.849165794690457
651615.45321849883940.546781501160583
661715.7867282952991.21327170470102
671816.06639745499831.93360254500173
681814.22360084200553.7763991579945
691215.7039588645577-3.70395886455773
701615.44783813657970.552161863420334
711013.0291955081803-3.02919550818027
721414.6990097947249-0.699009794724861
731816.82153871734651.17846128265349
741817.0473858368980.952614163101955
751615.06185386664440.938146133355616
761713.26865780022513.73134219977487
771616.2744534843814-0.274453484381421
781614.27409504855741.7259049514426
791315.0334785537398-2.03347855373977
801614.92476976718111.07523023281889
811615.56553475187030.434465248129707
821615.53697520668790.463024793312068
831515.5563789647739-0.556378964773851
841514.70917618789190.290823812108052
851613.97564876045272.02435123954728
861414.0085733239176-0.00857332391764802
871615.22083074899350.779169251006497
881614.70659346891481.29340653108515
891514.35475102652220.64524897347781
901213.7050807374168-1.70508073741682
911716.67826411380120.321735886198806
921615.74302028898820.256979711011827
931515.0195639849035-0.0195639849034682
941314.9635980286721-1.9635980286721
951614.69737266429451.30262733570547
961615.68306295708270.316937042917327
971613.58229891990442.41770108009563
981615.76851057004570.231489429954284
991414.3198580815311-0.319858081531102
1001617.0247038337606-1.02470383376056
1011614.57879733628371.42120266371627
1022017.46876748970412.53123251029595
1031514.05230462593870.947695374061321
1041614.9563332782171.04366672178304
1051314.8011674216603-1.80116742166032
1061715.65821183689391.34178816310611
1071615.71494542313640.285054576863643
1081614.26516952799151.73483047200847
1091212.1445025399444-0.144502539944408
1101615.2700317301080.729968269891964
1111616.0190228965521-0.0190228965520518
1121714.9728991243272.02710087567299
1131314.6235262603592-1.62352626035923
1141214.5611065152376-2.56110651523764
1151816.1825664051971.81743359480299
1161415.8742392027801-1.87423920278009
1171413.06342436139860.936575638601393
1181314.7664152300671-1.76641523006708
1191615.572753804110.42724619588997
1201314.4067456846915-1.40674568469149
1211615.43916476528990.560835234710133
1221315.8911672712233-2.89116727122332
1231616.9042581868609-0.904258186860854
1241515.8921534889468-0.892153488946772
1251616.9022361707383-0.9022361707383
1261514.7036320628420.296367937158024
1271715.61131042759051.38868957240952
1281513.98386079664091.01613920335906
1291214.7440838384905-2.74408383849047
1301613.99364226261562.00635773738435
1311013.7576725915982-3.75767259159822
1321613.51763211448282.48236788551719
1331214.2161631177914-2.21616311779137
1341415.6237963714392-1.62379637143923
1351515.1698667563622-0.169866756362222
1361312.14215570462570.857844295374259
1371514.50094692009940.499053079900598
1381113.4686249246835-2.46862492468349
1391213.0157243738586-1.01572437385864
1401113.4194465342762-2.4194465342762
1411612.88313150544633.11686849455371
1421513.75585057140021.24414942859977
1431717.0097795066055-0.00977950660548231
1441614.27379465830671.72620534169329
1451013.3567315625142-3.35673156251416
1461815.65274620595732.34725379404272
1471315.0228847719538-2.02288477195382
1481614.96201918240161.03798081759844
1491312.87725916249890.122740837501083
1501012.9838669107856-2.98386691078565
1511516.1494801243129-1.14948012431288
1521614.02757313785671.97242686214327
1531611.91105101507544.0889489849246
1541412.88162029650711.11837970349286
1551012.5110772982986-2.51107729829856
1561716.67826411380120.321735886198806
1571311.77484088460681.22515911539323
1581513.98386079664091.01613920335906
1591614.72204775703351.27795224296651
1601212.9024487088536-0.902448708853642
1611312.72341135615090.276588643849074
1621312.35944475142150.640555248578502
1631212.21971405789-0.21971405789
1641716.15592569301070.844074306989343
1651513.49271101103111.50728898896894
1661011.3690856488793-1.36908564887932
1671414.1511837465642-0.151183746564223
1681114.0473814027883-3.04738140278828
1691314.6284207569089-1.62842075690889
1701614.32864011010921.67135988989077
1711210.21036951488851.78963048511152
1721615.22941735128720.770582648712831
1731213.6789589162402-1.67895891624021
174911.1422436631215-2.14224366312148
1751214.8132494934299-2.81324949342992
1761514.43672008721820.563279912781796
1771212.0443133302158-0.0443133302158333
1781212.5271258979837-0.527125897983653
1791413.65203802068790.347961979312088
1801213.2423636290015-1.24236362900149
1811614.90287143221651.09712856778351
1821111.2308165908512-0.230816590851172
1831916.63024496677492.36975503322511
1841515.0709573706774-0.0709573706773568
185814.5002572284975-6.50025722849755
1861614.73852227465641.26147772534355
1871714.40111576811252.59888423188754
1881212.2769350009329-0.276935000932919
1891111.3375926910729-0.33759269107286
1901110.23353936827710.766460631722878
1911414.7383473626723-0.738347362672255
1921615.40683587596070.593164124039306
193129.554864139151822.44513586084818
1941613.93110147346462.06889852653535
1951313.589629361434-0.589629361433986
1961514.93247053755730.0675294624426782
1971612.8970880194333.10291198056704
1981615.01800947072730.981990529272659
1991412.34947855432961.6505214456704
2001614.54136139454021.45863860545976
2011613.9445932035732.05540679642697
2021413.32261846105740.677381538942582
2031113.4275177946163-2.42751779461626
2041214.4367109870216-2.43671098702159
2051512.66992691345482.33007308654516
2061514.45865242543130.541347574568722
2071614.46793724639011.53206275360993
2081614.931646920491.06835307951002
2091113.5562780239837-2.5562780239837
2101513.97793980179691.02206019820312
2111214.2029022057862-2.20290220578625
2121215.7784438651911-3.7784438651911
2131514.14402017910060.855979820899399
2141512.03070326771532.9692967322847
2151614.56848295895421.43151704104576
2161413.073134634190.926865365809959
2171714.67461237544132.32538762455869
2181413.94235982251960.0576401774804177
2191311.89050283722281.1094971627772
2201515.2059654363509-0.205965436350932
2211314.671017170643-1.67101717064298
2221414.1319205655599-0.131920565559881
2231514.30011824651640.69988175348359
2241213.1092937744911-1.10929377449114
2251312.71166640654250.288333593457519
226811.7472131342751-3.74721313427506
2271413.80158017396440.198419826035607
2281413.02026742792360.979732572076422
2291112.2297591833159-1.22975918331585
2301212.8968382776945-0.896838277694454
2311311.24520848195421.75479151804577
2321013.2130657616632-3.21306576166323
2331611.36771740091844.63228259908156
2341815.94741616960612.05258383039392
2351313.8693288638037-0.869328863803709
2361113.3430027385425-2.34300273854247
237410.9726967298314-6.97269672983142
2381314.2678178481433-1.26781784814329
2391614.30690708652381.6930929134762
2401011.6823923405169-1.68239234051694
2411212.2879119795221-0.287911979522082
2421213.5011921116947-1.50119211169468
243108.851422533167451.14857746683254
2441311.10286279022251.89713720977749
2451513.70924810047961.2907518995204
2461211.96850573174150.0314942682585027
2471412.87773198600271.12226801399732
2481012.5358000227952-2.53580002279517
2491210.76241308588411.23758691411589
2501211.73939094400440.260609055995627
2511111.9220624304821-0.92206243048211
2521011.730463172571-1.73046317257097
2531211.40196619942770.598033800572313
2541612.88255626328213.11744373671785
2551213.3765522827852-1.37655228278524
2561413.90482908535210.0951709146478974
2571614.51987977996521.48012022003483
2581411.66827988484082.33172011515923
2591314.356690156603-1.35669015660305
26049.38334580594879-5.38334580594879
2611513.84725932840051.15274067159949
2621115.1083609537208-4.10836095372081
2631111.3476291943178-0.347629194317833
2641412.91444947140431.08555052859574






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.2492722734171280.4985445468342570.750727726582871
130.1689541093509840.3379082187019670.831045890649016
140.1886524744826940.3773049489653890.811347525517306
150.1138221995709380.2276443991418770.886177800429062
160.07735817854516660.1547163570903330.922641821454833
170.1110899216880090.2221798433760170.888910078311991
180.350297244008130.7005944880162590.64970275599187
190.2730761482175750.546152296435150.726923851782425
200.2003647797994820.4007295595989630.799635220200518
210.1473290382449440.2946580764898890.852670961755056
220.142429822152620.284859644305240.85757017784738
230.3296136106918780.6592272213837560.670386389308122
240.3961081111703740.7922162223407480.603891888829626
250.3646437826222510.7292875652445030.635356217377749
260.3430137852627020.6860275705254040.656986214737298
270.4195222169011350.8390444338022690.580477783098865
280.4310392695664040.8620785391328090.568960730433596
290.4111782576654790.8223565153309580.588821742334521
300.44456286438330.88912572876660.5554371356167
310.3891820533962160.7783641067924310.610817946603784
320.3466207532541680.6932415065083360.653379246745832
330.3166771309296070.6333542618592130.683322869070393
340.2756748983004840.5513497966009680.724325101699516
350.2331395248719990.4662790497439980.766860475128001
360.3636238995606040.7272477991212090.636376100439396
370.4004800180238110.8009600360476230.599519981976189
380.3925184568810740.7850369137621470.607481543118926
390.4206468981939090.8412937963878180.579353101806091
400.3940366688201910.7880733376403820.605963331179809
410.3526085106959840.7052170213919680.647391489304016
420.3178155607826770.6356311215653540.682184439217323
430.3306029984344140.6612059968688280.669397001565586
440.2841930399770450.568386079954090.715806960022955
450.2593073538046520.5186147076093040.740692646195348
460.4573731365432770.9147462730865550.542626863456723
470.6130150426948640.7739699146102720.386984957305136
480.5647909648943340.8704180702113310.435209035105666
490.5501158312494770.8997683375010470.449884168750523
500.5388868721163420.9222262557673150.461113127883658
510.4960291879906050.992058375981210.503970812009395
520.4489765516673550.8979531033347090.551023448332645
530.4694099708676180.9388199417352350.530590029132383
540.4498338359931140.8996676719862270.550166164006886
550.4520661833654690.9041323667309380.547933816634531
560.4207085898279350.8414171796558710.579291410172065
570.3771221469019350.754244293803870.622877853098065
580.3435042881973340.6870085763946690.656495711802666
590.3053817369161280.6107634738322550.694618263083872
600.3047156648422220.6094313296844440.695284335157778
610.2748853643145070.5497707286290140.725114635685493
620.2433915133210.4867830266420.756608486679
630.2132055555154930.4264111110309870.786794444484507
640.1848502554386150.3697005108772310.815149744561385
650.1596120903137730.3192241806275470.840387909686227
660.1357016826094050.2714033652188090.864298317390595
670.1180785549662310.2361571099324630.881921445033769
680.1474917120339440.2949834240678870.852508287966056
690.3472555386289560.6945110772579110.652744461371044
700.3093835208007240.6187670416014490.690616479199276
710.4660184741956710.9320369483913430.533981525804329
720.4276948834687980.8553897669375970.572305116531202
730.4157563143704590.8315126287409170.584243685629541
740.3945458489702350.7890916979404690.605454151029765
750.3594443771041820.7188887542083650.640555622895818
760.4070738026966720.8141476053933450.592926197303328
770.3743005846908150.748601169381630.625699415309185
780.3465913445996440.6931826891992890.653408655400356
790.3751240969174850.750248193834970.624875903082515
800.3445238367559340.6890476735118690.655476163244066
810.3118927695474280.6237855390948550.688107230452572
820.2778009724449010.5556019448898020.722199027555099
830.2541368671141770.5082737342283540.745863132885823
840.223381795663670.446763591327340.77661820433633
850.213624303551210.427248607102420.78637569644879
860.1860951835112290.3721903670224580.813904816488771
870.1627844833256380.3255689666512760.837215516674362
880.1479693140306370.2959386280612750.852030685969363
890.1275367957355460.2550735914710920.872463204264454
900.1293263329675020.2586526659350040.870673667032498
910.1115353318735730.2230706637471460.888464668126427
920.09612839823137160.1922567964627430.903871601768628
930.08255029560783030.1651005912156610.91744970439217
940.08774253876849330.1754850775369870.912257461231507
950.07808798576575120.1561759715315020.921912014234249
960.06582940569368910.1316588113873780.934170594306311
970.06890680748988760.1378136149797750.931093192510112
980.057357951544050.11471590308810.94264204845595
990.04759063603325450.0951812720665090.952409363966745
1000.04254385848685590.08508771697371180.957456141513144
1010.03698593102944130.07397186205888260.963014068970559
1020.04200024337560550.0840004867512110.957999756624395
1030.03566538980737470.07133077961474930.964334610192625
1040.03166652007822890.06333304015645780.968333479921771
1050.03880949768818360.07761899537636710.961190502311816
1060.0335801030215310.06716020604306190.966419896978469
1070.027290385975730.05458077195145990.97270961402427
1080.02601341498369730.05202682996739470.973986585016303
1090.02122212996364290.04244425992728590.978777870036357
1100.01720381846762350.03440763693524710.982796181532376
1110.01363218598249620.02726437196499250.986367814017504
1120.01362275664367690.02724551328735380.986377243356323
1130.0124872959699890.02497459193997790.987512704030011
1140.01914617582040730.03829235164081450.980853824179593
1150.0177617143290990.03552342865819810.982238285670901
1160.01760364600639230.03520729201278450.982396353993608
1170.01436508164379610.02873016328759220.985634918356204
1180.01493331609460550.02986663218921110.985066683905394
1190.01206911619647360.02413823239294720.987930883803526
1200.01101721505049390.02203443010098780.988982784949506
1210.008849279819575390.01769855963915080.991150720180425
1220.01405201699397940.02810403398795890.985947983006021
1230.01204312443743490.02408624887486990.987956875562565
1240.01082304395791420.02164608791582840.989176956042086
1250.00903731082126340.01807462164252680.990962689178737
1260.007284510364862930.01456902072972590.992715489635137
1270.006399141635910680.01279828327182140.993600858364089
1280.00510659099347240.01021318198694480.994893409006528
1290.007833750653357410.01566750130671480.992166249346643
1300.008079630421260740.01615926084252150.991920369578739
1310.01809493309141720.03618986618283440.981905066908583
1320.02036896440071270.04073792880142540.979631035599287
1330.02326176122305160.04652352244610320.976738238776948
1340.02325622382259760.04651244764519520.976743776177402
1350.01903603791347650.03807207582695310.980963962086523
1360.01563724885193650.03127449770387290.984362751148063
1370.01244301443481240.02488602886962480.987556985565188
1380.01657726913473490.03315453826946980.983422730865265
1390.01492406271110030.02984812542220050.9850759372889
1400.01903115525134760.03806231050269520.980968844748652
1410.02611292966167870.05222585932335750.973887070338321
1420.02329661463055940.04659322926111890.976703385369441
1430.01901338794118750.0380267758823750.980986612058812
1440.01807745583239250.03615491166478490.981922544167607
1450.03550261579211290.07100523158422580.964497384207887
1460.03842219667212220.07684439334424450.961577803327878
1470.04319875220066740.08639750440133490.956801247799333
1480.03696458495330970.07392916990661940.96303541504669
1490.03032683018115540.06065366036231090.969673169818845
1500.04572933724843960.09145867449687910.95427066275156
1510.04138110432220680.08276220864441350.958618895677793
1520.04108709150939430.08217418301878860.958912908490606
1530.07170817991153440.1434163598230690.928291820088466
1540.06315971234699960.1263194246939990.936840287653
1550.07711281200610370.1542256240122070.922887187993896
1560.06481484022680.12962968045360.9351851597732
1570.05642129033091210.1128425806618240.943578709669088
1580.04785029547827460.09570059095654920.952149704521725
1590.04545701219412340.09091402438824690.954542987805877
1600.03903553390782280.07807106781564560.960964466092177
1610.03186881132990240.06373762265980490.968131188670098
1620.02618793263043780.05237586526087570.973812067369562
1630.02158134175932820.04316268351865640.978418658240672
1640.0182524223098590.0365048446197180.981747577690141
1650.01613833037455360.03227666074910720.983861669625446
1660.01625166588964460.03250333177928920.983748334110355
1670.01295680055704550.02591360111409090.987043199442954
1680.01847941738628010.03695883477256030.98152058261372
1690.01789425962726980.03578851925453960.98210574037273
1700.01701891816530220.03403783633060440.982981081834698
1710.01656166748192420.03312333496384830.983438332518076
1720.01343604769182090.02687209538364190.986563952308179
1730.01295835550851280.02591671101702550.987041644491487
1740.01387744681416160.02775489362832310.986122553185838
1750.01724076288402710.03448152576805420.982759237115973
1760.01389517376727090.02779034753454180.986104826232729
1770.01105199885551880.02210399771103760.988948001144481
1780.008870743418618180.01774148683723640.991129256581382
1790.006883216021683830.01376643204336770.993116783978316
1800.005774435628496820.01154887125699360.994225564371503
1810.004853935652065520.009707871304131040.995146064347935
1820.00378879916375460.00757759832750920.996211200836245
1830.004241499490366780.008482998980733560.995758500509633
1840.003270547165465240.006541094330930480.996729452834535
1850.07284071054683340.1456814210936670.927159289453167
1860.06383693900914620.1276738780182920.936163060990854
1870.07555137742023590.1511027548404720.924448622579764
1880.06403713870606610.1280742774121320.935962861293934
1890.05365415639993530.1073083127998710.946345843600065
1900.04430833113242730.08861666226485460.955691668867573
1910.03873353446880420.07746706893760850.961266465531196
1920.0324804456063720.0649608912127440.967519554393628
1930.0387770188044980.0775540376089960.961222981195502
1940.04258037207050060.08516074414100120.957419627929499
1950.03554147970652030.07108295941304060.96445852029348
1960.0291430151993390.0582860303986780.970856984800661
1970.03934322123609410.07868644247218810.960656778763906
1980.03217517463612250.06435034927224490.967824825363877
1990.02996916944179330.05993833888358650.970030830558207
2000.02546853602517060.05093707205034130.974531463974829
2010.02420992619259410.04841985238518820.975790073807406
2020.02018300708356070.04036601416712140.979816992916439
2030.02552713015082790.05105426030165590.974472869849172
2040.02805986879478520.05611973758957050.971940131205215
2050.03122243404951230.06244486809902450.968777565950488
2060.02457162075483050.04914324150966090.97542837924517
2070.0242699128877640.04853982577552810.975730087112236
2080.01996928815855830.03993857631711650.980030711841442
2090.0216728319632840.0433456639265680.978327168036716
2100.01745634679966690.03491269359933370.982543653200333
2110.01892928022771840.03785856045543680.981070719772282
2120.02927031916469110.05854063832938210.970729680835309
2130.02286935442182740.04573870884365480.977130645578173
2140.03302402104082880.06604804208165760.966975978959171
2150.02845685503369460.05691371006738910.971543144966305
2160.02208498411284880.04416996822569760.977915015887151
2170.02435911239073420.04871822478146850.975640887609266
2180.02048958882666290.04097917765332580.979510411173337
2190.01832055050594860.03664110101189710.981679449494051
2200.01375479827737970.02750959655475940.98624520172262
2210.01192723565276660.02385447130553330.988072764347233
2220.008581221005338790.01716244201067760.991418778994661
2230.006346574174097220.01269314834819440.993653425825903
2240.004964716802854960.009929433605709910.995035283197145
2250.004294645822144490.008589291644288990.995705354177856
2260.009946291679482180.01989258335896440.990053708320518
2270.007534383594052640.01506876718810530.992465616405947
2280.005373386330768640.01074677266153730.994626613669231
2290.003807178335165460.007614356670330910.996192821664835
2300.002664712201800850.005329424403601710.997335287798199
2310.002671581709784580.005343163419569170.997328418290215
2320.004943363926681840.009886727853363670.995056636073318
2330.0259467354434980.0518934708869960.974053264556502
2340.03845794067780680.07691588135561350.961542059322193
2350.02771878847402890.05543757694805770.972281211525971
2360.02396181394727560.04792362789455110.976038186052724
2370.1877711753584530.3755423507169060.812228824641547
2380.14704486117690.29408972235380.8529551388231
2390.1302161662453970.2604323324907950.869783833754603
2400.09886843392331010.197736867846620.90113156607669
2410.07660014168752270.1532002833750450.923399858312477
2420.06146341784320190.1229268356864040.938536582156798
2430.0562097761470190.1124195522940380.943790223852981
2440.103562675764340.2071253515286790.89643732423566
2450.09078377267345770.1815675453469150.909216227326542
2460.06963829302173020.139276586043460.93036170697827
2470.04652964356737540.09305928713475080.953470356432625
2480.0378059998785720.0756119997571440.962194000121428
2490.03407474496554870.06814948993109750.965925255034451
2500.04144886906803740.08289773813607480.958551130931963
2510.02182244785967230.04364489571934470.978177552140328
2520.05474267636533070.1094853527306610.945257323634669

\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 & 0.750727726582871 \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 & 0.222179843376017 & 0.888910078311991 \tabularnewline
18 & 0.35029724400813 & 0.700594488016259 & 0.64970275599187 \tabularnewline
19 & 0.273076148217575 & 0.54615229643515 & 0.726923851782425 \tabularnewline
20 & 0.200364779799482 & 0.400729559598963 & 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 & 0.839044433802269 & 0.580477783098865 \tabularnewline
28 & 0.431039269566404 & 0.862078539132809 & 0.568960730433596 \tabularnewline
29 & 0.411178257665479 & 0.822356515330958 & 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 & 0.466279049743998 & 0.766860475128001 \tabularnewline
36 & 0.363623899560604 & 0.727247799121209 & 0.636376100439396 \tabularnewline
37 & 0.400480018023811 & 0.800960036047623 & 0.599519981976189 \tabularnewline
38 & 0.392518456881074 & 0.785036913762147 & 0.607481543118926 \tabularnewline
39 & 0.420646898193909 & 0.841293796387818 & 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 & 0.457373136543277 & 0.914746273086555 & 0.542626863456723 \tabularnewline
47 & 0.613015042694864 & 0.773969914610272 & 0.386984957305136 \tabularnewline
48 & 0.564790964894334 & 0.870418070211331 & 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 & 0.452066183365469 & 0.904132366730938 & 0.547933816634531 \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 & 0.426411111030987 & 0.786794444484507 \tabularnewline
64 & 0.184850255438615 & 0.369700510877231 & 0.815149744561385 \tabularnewline
65 & 0.159612090313773 & 0.319224180627547 & 0.840387909686227 \tabularnewline
66 & 0.135701682609405 & 0.271403365218809 & 0.864298317390595 \tabularnewline
67 & 0.118078554966231 & 0.236157109932463 & 0.881921445033769 \tabularnewline
68 & 0.147491712033944 & 0.294983424067887 & 0.852508287966056 \tabularnewline
69 & 0.347255538628956 & 0.694511077257911 & 0.652744461371044 \tabularnewline
70 & 0.309383520800724 & 0.618767041601449 & 0.690616479199276 \tabularnewline
71 & 0.466018474195671 & 0.932036948391343 & 0.533981525804329 \tabularnewline
72 & 0.427694883468798 & 0.855389766937597 & 0.572305116531202 \tabularnewline
73 & 0.415756314370459 & 0.831512628740917 & 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 & 0.374300584690815 & 0.74860116938163 & 0.625699415309185 \tabularnewline
78 & 0.346591344599644 & 0.693182689199289 & 0.653408655400356 \tabularnewline
79 & 0.375124096917485 & 0.75024819383497 & 0.624875903082515 \tabularnewline
80 & 0.344523836755934 & 0.689047673511869 & 0.655476163244066 \tabularnewline
81 & 0.311892769547428 & 0.623785539094855 & 0.688107230452572 \tabularnewline
82 & 0.277800972444901 & 0.555601944889802 & 0.722199027555099 \tabularnewline
83 & 0.254136867114177 & 0.508273734228354 & 0.745863132885823 \tabularnewline
84 & 0.22338179566367 & 0.44676359132734 & 0.77661820433633 \tabularnewline
85 & 0.21362430355121 & 0.42724860710242 & 0.78637569644879 \tabularnewline
86 & 0.186095183511229 & 0.372190367022458 & 0.813904816488771 \tabularnewline
87 & 0.162784483325638 & 0.325568966651276 & 0.837215516674362 \tabularnewline
88 & 0.147969314030637 & 0.295938628061275 & 0.852030685969363 \tabularnewline
89 & 0.127536795735546 & 0.255073591471092 & 0.872463204264454 \tabularnewline
90 & 0.129326332967502 & 0.258652665935004 & 0.870673667032498 \tabularnewline
91 & 0.111535331873573 & 0.223070663747146 & 0.888464668126427 \tabularnewline
92 & 0.0961283982313716 & 0.192256796462743 & 0.903871601768628 \tabularnewline
93 & 0.0825502956078303 & 0.165100591215661 & 0.91744970439217 \tabularnewline
94 & 0.0877425387684933 & 0.175485077536987 & 0.912257461231507 \tabularnewline
95 & 0.0780879857657512 & 0.156175971531502 & 0.921912014234249 \tabularnewline
96 & 0.0658294056936891 & 0.131658811387378 & 0.934170594306311 \tabularnewline
97 & 0.0689068074898876 & 0.137813614979775 & 0.931093192510112 \tabularnewline
98 & 0.05735795154405 & 0.1147159030881 & 0.94264204845595 \tabularnewline
99 & 0.0475906360332545 & 0.095181272066509 & 0.952409363966745 \tabularnewline
100 & 0.0425438584868559 & 0.0850877169737118 & 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 & 0.033580103021531 & 0.0671602060430619 & 0.966419896978469 \tabularnewline
107 & 0.02729038597573 & 0.0545807719514599 & 0.97270961402427 \tabularnewline
108 & 0.0260134149836973 & 0.0520268299673947 & 0.973986585016303 \tabularnewline
109 & 0.0212221299636429 & 0.0424442599272859 & 0.978777870036357 \tabularnewline
110 & 0.0172038184676235 & 0.0344076369352471 & 0.982796181532376 \tabularnewline
111 & 0.0136321859824962 & 0.0272643719649925 & 0.986367814017504 \tabularnewline
112 & 0.0136227566436769 & 0.0272455132873538 & 0.986377243356323 \tabularnewline
113 & 0.012487295969989 & 0.0249745919399779 & 0.987512704030011 \tabularnewline
114 & 0.0191461758204073 & 0.0382923516408145 & 0.980853824179593 \tabularnewline
115 & 0.017761714329099 & 0.0355234286581981 & 0.982238285670901 \tabularnewline
116 & 0.0176036460063923 & 0.0352072920127845 & 0.982396353993608 \tabularnewline
117 & 0.0143650816437961 & 0.0287301632875922 & 0.985634918356204 \tabularnewline
118 & 0.0149333160946055 & 0.0298666321892111 & 0.985066683905394 \tabularnewline
119 & 0.0120691161964736 & 0.0241382323929472 & 0.987930883803526 \tabularnewline
120 & 0.0110172150504939 & 0.0220344301009878 & 0.988982784949506 \tabularnewline
121 & 0.00884927981957539 & 0.0176985596391508 & 0.991150720180425 \tabularnewline
122 & 0.0140520169939794 & 0.0281040339879589 & 0.985947983006021 \tabularnewline
123 & 0.0120431244374349 & 0.0240862488748699 & 0.987956875562565 \tabularnewline
124 & 0.0108230439579142 & 0.0216460879158284 & 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 & 0.00807963042126074 & 0.0161592608425215 & 0.991920369578739 \tabularnewline
131 & 0.0180949330914172 & 0.0361898661828344 & 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 & 0.0156372488519365 & 0.0312744977038729 & 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 & 0.0190311552513476 & 0.0380623105026952 & 0.980968844748652 \tabularnewline
141 & 0.0261129296616787 & 0.0522258593233575 & 0.973887070338321 \tabularnewline
142 & 0.0232966146305594 & 0.0465932292611189 & 0.976703385369441 \tabularnewline
143 & 0.0190133879411875 & 0.038026775882375 & 0.980986612058812 \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 & 0.0457293372484396 & 0.0914586744968791 & 0.95427066275156 \tabularnewline
151 & 0.0413811043222068 & 0.0827622086444135 & 0.958618895677793 \tabularnewline
152 & 0.0410870915093943 & 0.0821741830187886 & 0.958912908490606 \tabularnewline
153 & 0.0717081799115344 & 0.143416359823069 & 0.928291820088466 \tabularnewline
154 & 0.0631597123469996 & 0.126319424693999 & 0.936840287653 \tabularnewline
155 & 0.0771128120061037 & 0.154225624012207 & 0.922887187993896 \tabularnewline
156 & 0.0648148402268 & 0.1296296804536 & 0.9351851597732 \tabularnewline
157 & 0.0564212903309121 & 0.112842580661824 & 0.943578709669088 \tabularnewline
158 & 0.0478502954782746 & 0.0957005909565492 & 0.952149704521725 \tabularnewline
159 & 0.0454570121941234 & 0.0909140243882469 & 0.954542987805877 \tabularnewline
160 & 0.0390355339078228 & 0.0780710678156456 & 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 & 0.0178942596272698 & 0.0357885192545396 & 0.98210574037273 \tabularnewline
170 & 0.0170189181653022 & 0.0340378363306044 & 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 & 0.0277548936283231 & 0.986122553185838 \tabularnewline
175 & 0.0172407628840271 & 0.0344815257680542 & 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 & 0.00424149949036678 & 0.00848299898073356 & 0.995758500509633 \tabularnewline
184 & 0.00327054716546524 & 0.00654109433093048 & 0.996729452834535 \tabularnewline
185 & 0.0728407105468334 & 0.145681421093667 & 0.927159289453167 \tabularnewline
186 & 0.0638369390091462 & 0.127673878018292 & 0.936163060990854 \tabularnewline
187 & 0.0755513774202359 & 0.151102754840472 & 0.924448622579764 \tabularnewline
188 & 0.0640371387060661 & 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 & 0.0425803720705006 & 0.0851607441410012 & 0.957419627929499 \tabularnewline
195 & 0.0355414797065203 & 0.0710829594130406 & 0.96445852029348 \tabularnewline
196 & 0.029143015199339 & 0.058286030398678 & 0.970856984800661 \tabularnewline
197 & 0.0393432212360941 & 0.0786864424721881 & 0.960656778763906 \tabularnewline
198 & 0.0321751746361225 & 0.0643503492722449 & 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 & 0.0201830070835607 & 0.0403660141671214 & 0.979816992916439 \tabularnewline
203 & 0.0255271301508279 & 0.0510542603016559 & 0.974472869849172 \tabularnewline
204 & 0.0280598687947852 & 0.0561197375895705 & 0.971940131205215 \tabularnewline
205 & 0.0312224340495123 & 0.0624448680990245 & 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 & 0.0330240210408288 & 0.0660480420816576 & 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 & 0.0409791776533258 & 0.979510411173337 \tabularnewline
219 & 0.0183205505059486 & 0.0366411010118971 & 0.981679449494051 \tabularnewline
220 & 0.0137547982773797 & 0.0275095965547594 & 0.98624520172262 \tabularnewline
221 & 0.0119272356527666 & 0.0238544713055333 & 0.988072764347233 \tabularnewline
222 & 0.00858122100533879 & 0.0171624420106776 & 0.991418778994661 \tabularnewline
223 & 0.00634657417409722 & 0.0126931483481944 & 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 & 0.00753438359405264 & 0.0150687671881053 & 0.992465616405947 \tabularnewline
228 & 0.00537338633076864 & 0.0107467726615373 & 0.994626613669231 \tabularnewline
229 & 0.00380717833516546 & 0.00761435667033091 & 0.996192821664835 \tabularnewline
230 & 0.00266471220180085 & 0.00532942440360171 & 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 & 0.0277187884740289 & 0.0554375769480577 & 0.972281211525971 \tabularnewline
236 & 0.0239618139472756 & 0.0479236278945511 & 0.976038186052724 \tabularnewline
237 & 0.187771175358453 & 0.375542350716906 & 0.812228824641547 \tabularnewline
238 & 0.1470448611769 & 0.2940897223538 & 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 & 0.0465296435673754 & 0.0930592871347508 & 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=193404&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]0.750727726582871[/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]0.222179843376017[/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]0.400729559598963[/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]0.839044433802269[/C][C]0.580477783098865[/C][/ROW]
[ROW][C]28[/C][C]0.431039269566404[/C][C]0.862078539132809[/C][C]0.568960730433596[/C][/ROW]
[ROW][C]29[/C][C]0.411178257665479[/C][C]0.822356515330958[/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]
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[ROW][C]128[/C][C]0.0051065909934724[/C][C]0.0102131819869448[/C][C]0.994893409006528[/C][/ROW]
[ROW][C]129[/C][C]0.00783375065335741[/C][C]0.0156675013067148[/C][C]0.992166249346643[/C][/ROW]
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[ROW][C]131[/C][C]0.0180949330914172[/C][C]0.0361898661828344[/C][C]0.981905066908583[/C][/ROW]
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[ROW][C]167[/C][C]0.0129568005570455[/C][C]0.0259136011140909[/C][C]0.987043199442954[/C][/ROW]
[ROW][C]168[/C][C]0.0184794173862801[/C][C]0.0369588347725603[/C][C]0.98152058261372[/C][/ROW]
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[ROW][C]172[/C][C]0.0134360476918209[/C][C]0.0268720953836419[/C][C]0.986563952308179[/C][/ROW]
[ROW][C]173[/C][C]0.0129583555085128[/C][C]0.0259167110170255[/C][C]0.987041644491487[/C][/ROW]
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[ROW][C]176[/C][C]0.0138951737672709[/C][C]0.0277903475345418[/C][C]0.986104826232729[/C][/ROW]
[ROW][C]177[/C][C]0.0110519988555188[/C][C]0.0221039977110376[/C][C]0.988948001144481[/C][/ROW]
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[ROW][C]179[/C][C]0.00688321602168383[/C][C]0.0137664320433677[/C][C]0.993116783978316[/C][/ROW]
[ROW][C]180[/C][C]0.00577443562849682[/C][C]0.0115488712569936[/C][C]0.994225564371503[/C][/ROW]
[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]0.00424149949036678[/C][C]0.00848299898073356[/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]0.0638369390091462[/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]0.0640371387060661[/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]0.0425803720705006[/C][C]0.0851607441410012[/C][C]0.957419627929499[/C][/ROW]
[ROW][C]195[/C][C]0.0355414797065203[/C][C]0.0710829594130406[/C][C]0.96445852029348[/C][/ROW]
[ROW][C]196[/C][C]0.029143015199339[/C][C]0.058286030398678[/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]0.0321751746361225[/C][C]0.0643503492722449[/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]0.0201830070835607[/C][C]0.0403660141671214[/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]0.0312224340495123[/C][C]0.0624448680990245[/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]0.0330240210408288[/C][C]0.0660480420816576[/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]0.0409791776533258[/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]0.0119272356527666[/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]0.00634657417409722[/C][C]0.0126931483481944[/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]0.00753438359405264[/C][C]0.0150687671881053[/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]0.00266471220180085[/C][C]0.00532942440360171[/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]0.0277187884740289[/C][C]0.0554375769480577[/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]0.375542350716906[/C][C]0.812228824641547[/C][/ROW]
[ROW][C]238[/C][C]0.1470448611769[/C][C]0.2940897223538[/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]0.0465296435673754[/C][C]0.0930592871347508[/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=193404&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193404&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.2492722734171280.4985445468342570.750727726582871
130.1689541093509840.3379082187019670.831045890649016
140.1886524744826940.3773049489653890.811347525517306
150.1138221995709380.2276443991418770.886177800429062
160.07735817854516660.1547163570903330.922641821454833
170.1110899216880090.2221798433760170.888910078311991
180.350297244008130.7005944880162590.64970275599187
190.2730761482175750.546152296435150.726923851782425
200.2003647797994820.4007295595989630.799635220200518
210.1473290382449440.2946580764898890.852670961755056
220.142429822152620.284859644305240.85757017784738
230.3296136106918780.6592272213837560.670386389308122
240.3961081111703740.7922162223407480.603891888829626
250.3646437826222510.7292875652445030.635356217377749
260.3430137852627020.6860275705254040.656986214737298
270.4195222169011350.8390444338022690.580477783098865
280.4310392695664040.8620785391328090.568960730433596
290.4111782576654790.8223565153309580.588821742334521
300.44456286438330.88912572876660.5554371356167
310.3891820533962160.7783641067924310.610817946603784
320.3466207532541680.6932415065083360.653379246745832
330.3166771309296070.6333542618592130.683322869070393
340.2756748983004840.5513497966009680.724325101699516
350.2331395248719990.4662790497439980.766860475128001
360.3636238995606040.7272477991212090.636376100439396
370.4004800180238110.8009600360476230.599519981976189
380.3925184568810740.7850369137621470.607481543118926
390.4206468981939090.8412937963878180.579353101806091
400.3940366688201910.7880733376403820.605963331179809
410.3526085106959840.7052170213919680.647391489304016
420.3178155607826770.6356311215653540.682184439217323
430.3306029984344140.6612059968688280.669397001565586
440.2841930399770450.568386079954090.715806960022955
450.2593073538046520.5186147076093040.740692646195348
460.4573731365432770.9147462730865550.542626863456723
470.6130150426948640.7739699146102720.386984957305136
480.5647909648943340.8704180702113310.435209035105666
490.5501158312494770.8997683375010470.449884168750523
500.5388868721163420.9222262557673150.461113127883658
510.4960291879906050.992058375981210.503970812009395
520.4489765516673550.8979531033347090.551023448332645
530.4694099708676180.9388199417352350.530590029132383
540.4498338359931140.8996676719862270.550166164006886
550.4520661833654690.9041323667309380.547933816634531
560.4207085898279350.8414171796558710.579291410172065
570.3771221469019350.754244293803870.622877853098065
580.3435042881973340.6870085763946690.656495711802666
590.3053817369161280.6107634738322550.694618263083872
600.3047156648422220.6094313296844440.695284335157778
610.2748853643145070.5497707286290140.725114635685493
620.2433915133210.4867830266420.756608486679
630.2132055555154930.4264111110309870.786794444484507
640.1848502554386150.3697005108772310.815149744561385
650.1596120903137730.3192241806275470.840387909686227
660.1357016826094050.2714033652188090.864298317390595
670.1180785549662310.2361571099324630.881921445033769
680.1474917120339440.2949834240678870.852508287966056
690.3472555386289560.6945110772579110.652744461371044
700.3093835208007240.6187670416014490.690616479199276
710.4660184741956710.9320369483913430.533981525804329
720.4276948834687980.8553897669375970.572305116531202
730.4157563143704590.8315126287409170.584243685629541
740.3945458489702350.7890916979404690.605454151029765
750.3594443771041820.7188887542083650.640555622895818
760.4070738026966720.8141476053933450.592926197303328
770.3743005846908150.748601169381630.625699415309185
780.3465913445996440.6931826891992890.653408655400356
790.3751240969174850.750248193834970.624875903082515
800.3445238367559340.6890476735118690.655476163244066
810.3118927695474280.6237855390948550.688107230452572
820.2778009724449010.5556019448898020.722199027555099
830.2541368671141770.5082737342283540.745863132885823
840.223381795663670.446763591327340.77661820433633
850.213624303551210.427248607102420.78637569644879
860.1860951835112290.3721903670224580.813904816488771
870.1627844833256380.3255689666512760.837215516674362
880.1479693140306370.2959386280612750.852030685969363
890.1275367957355460.2550735914710920.872463204264454
900.1293263329675020.2586526659350040.870673667032498
910.1115353318735730.2230706637471460.888464668126427
920.09612839823137160.1922567964627430.903871601768628
930.08255029560783030.1651005912156610.91744970439217
940.08774253876849330.1754850775369870.912257461231507
950.07808798576575120.1561759715315020.921912014234249
960.06582940569368910.1316588113873780.934170594306311
970.06890680748988760.1378136149797750.931093192510112
980.057357951544050.11471590308810.94264204845595
990.04759063603325450.0951812720665090.952409363966745
1000.04254385848685590.08508771697371180.957456141513144
1010.03698593102944130.07397186205888260.963014068970559
1020.04200024337560550.0840004867512110.957999756624395
1030.03566538980737470.07133077961474930.964334610192625
1040.03166652007822890.06333304015645780.968333479921771
1050.03880949768818360.07761899537636710.961190502311816
1060.0335801030215310.06716020604306190.966419896978469
1070.027290385975730.05458077195145990.97270961402427
1080.02601341498369730.05202682996739470.973986585016303
1090.02122212996364290.04244425992728590.978777870036357
1100.01720381846762350.03440763693524710.982796181532376
1110.01363218598249620.02726437196499250.986367814017504
1120.01362275664367690.02724551328735380.986377243356323
1130.0124872959699890.02497459193997790.987512704030011
1140.01914617582040730.03829235164081450.980853824179593
1150.0177617143290990.03552342865819810.982238285670901
1160.01760364600639230.03520729201278450.982396353993608
1170.01436508164379610.02873016328759220.985634918356204
1180.01493331609460550.02986663218921110.985066683905394
1190.01206911619647360.02413823239294720.987930883803526
1200.01101721505049390.02203443010098780.988982784949506
1210.008849279819575390.01769855963915080.991150720180425
1220.01405201699397940.02810403398795890.985947983006021
1230.01204312443743490.02408624887486990.987956875562565
1240.01082304395791420.02164608791582840.989176956042086
1250.00903731082126340.01807462164252680.990962689178737
1260.007284510364862930.01456902072972590.992715489635137
1270.006399141635910680.01279828327182140.993600858364089
1280.00510659099347240.01021318198694480.994893409006528
1290.007833750653357410.01566750130671480.992166249346643
1300.008079630421260740.01615926084252150.991920369578739
1310.01809493309141720.03618986618283440.981905066908583
1320.02036896440071270.04073792880142540.979631035599287
1330.02326176122305160.04652352244610320.976738238776948
1340.02325622382259760.04651244764519520.976743776177402
1350.01903603791347650.03807207582695310.980963962086523
1360.01563724885193650.03127449770387290.984362751148063
1370.01244301443481240.02488602886962480.987556985565188
1380.01657726913473490.03315453826946980.983422730865265
1390.01492406271110030.02984812542220050.9850759372889
1400.01903115525134760.03806231050269520.980968844748652
1410.02611292966167870.05222585932335750.973887070338321
1420.02329661463055940.04659322926111890.976703385369441
1430.01901338794118750.0380267758823750.980986612058812
1440.01807745583239250.03615491166478490.981922544167607
1450.03550261579211290.07100523158422580.964497384207887
1460.03842219667212220.07684439334424450.961577803327878
1470.04319875220066740.08639750440133490.956801247799333
1480.03696458495330970.07392916990661940.96303541504669
1490.03032683018115540.06065366036231090.969673169818845
1500.04572933724843960.09145867449687910.95427066275156
1510.04138110432220680.08276220864441350.958618895677793
1520.04108709150939430.08217418301878860.958912908490606
1530.07170817991153440.1434163598230690.928291820088466
1540.06315971234699960.1263194246939990.936840287653
1550.07711281200610370.1542256240122070.922887187993896
1560.06481484022680.12962968045360.9351851597732
1570.05642129033091210.1128425806618240.943578709669088
1580.04785029547827460.09570059095654920.952149704521725
1590.04545701219412340.09091402438824690.954542987805877
1600.03903553390782280.07807106781564560.960964466092177
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1800.005774435628496820.01154887125699360.994225564371503
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1880.06403713870606610.1280742774121320.935962861293934
1890.05365415639993530.1073083127998710.946345843600065
1900.04430833113242730.08861666226485460.955691668867573
1910.03873353446880420.07746706893760850.961266465531196
1920.0324804456063720.0649608912127440.967519554393628
1930.0387770188044980.0775540376089960.961222981195502
1940.04258037207050060.08516074414100120.957419627929499
1950.03554147970652030.07108295941304060.96445852029348
1960.0291430151993390.0582860303986780.970856984800661
1970.03934322123609410.07868644247218810.960656778763906
1980.03217517463612250.06435034927224490.967824825363877
1990.02996916944179330.05993833888358650.970030830558207
2000.02546853602517060.05093707205034130.974531463974829
2010.02420992619259410.04841985238518820.975790073807406
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2100.01745634679966690.03491269359933370.982543653200333
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2170.02435911239073420.04871822478146850.975640887609266
2180.02048958882666290.04097917765332580.979510411173337
2190.01832055050594860.03664110101189710.981679449494051
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2500.04144886906803740.08289773813607480.958551130931963
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2520.05474267636533070.1094853527306610.945257323634669






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level100.04149377593361NOK
5% type I error level850.352697095435685NOK
10% type I error level1330.551867219917012NOK

\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=193404&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=193404&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193404&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level100.04149377593361NOK
5% type I error level850.352697095435685NOK
10% type I error level1330.551867219917012NOK


Figures (Output of Computation)

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Input Parameters & R Code

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 ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}