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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Module--
Title produced by softwareMultiple Regression
Date of computationTue, 20 Nov 2012 15:17:50 -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/20/t13534431701ozffz3rhyutah7.htm/, Retrieved Thu, 31 Oct 2024 23:06:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=191274, Retrieved Thu, 31 Oct 2024 23:06:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- RM      [Multiple Regression] [multiple regression] [2012-11-20 20:17:50] [706ccf0adf4bc144f067c6c403344984] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 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 & 14 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=191274&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]14 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=191274&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=191274&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 time14 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






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

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  3.77956658273096 +  0.0469437389403787Connected[t] +  0.0419978310517143Separate[t] +  0.607405158110716Software[t] +  0.0986310792586457Happiness[t] -0.0393791266630167Depression[t] +  0.0158660592613708Belonging[t] -0.0194154193631069Belonging_Final[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=191274&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  3.77956658273096 +  0.0469437389403787Connected[t] +  0.0419978310517143Separate[t] +  0.607405158110716Software[t] +  0.0986310792586457Happiness[t] -0.0393791266630167Depression[t] +  0.0158660592613708Belonging[t] -0.0194154193631069Belonging_Final[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=191274&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=191274&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] = + 3.77956658273096 + 0.0469437389403787Connected[t] + 0.0419978310517143Separate[t] + 0.607405158110716Software[t] + 0.0986310792586457Happiness[t] -0.0393791266630167Depression[t] + 0.0158660592613708Belonging[t] -0.0194154193631069Belonging_Final[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)3.779566582730961.9176521.97090.0498090.024904
Connected0.04694373894037870.0347871.34950.1783840.089192
Separate0.04199783105171430.0356481.17810.2398470.119923
Software0.6074051581107160.05184511.715800
Happiness0.09863107925864570.0579631.70160.090040.04502
Depression-0.03937912666301670.042557-0.92530.355670.177835
Belonging0.01586605926137080.0378430.41930.6753760.337688
Belonging_Final-0.01941541936310690.056444-0.3440.7311470.365573

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 3.77956658273096 & 1.917652 & 1.9709 & 0.049809 & 0.024904 \tabularnewline
Connected & 0.0469437389403787 & 0.034787 & 1.3495 & 0.178384 & 0.089192 \tabularnewline
Separate & 0.0419978310517143 & 0.035648 & 1.1781 & 0.239847 & 0.119923 \tabularnewline
Software & 0.607405158110716 & 0.051845 & 11.7158 & 0 & 0 \tabularnewline
Happiness & 0.0986310792586457 & 0.057963 & 1.7016 & 0.09004 & 0.04502 \tabularnewline
Depression & -0.0393791266630167 & 0.042557 & -0.9253 & 0.35567 & 0.177835 \tabularnewline
Belonging & 0.0158660592613708 & 0.037843 & 0.4193 & 0.675376 & 0.337688 \tabularnewline
Belonging_Final & -0.0194154193631069 & 0.056444 & -0.344 & 0.731147 & 0.365573 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=191274&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]3.77956658273096[/C][C]1.917652[/C][C]1.9709[/C][C]0.049809[/C][C]0.024904[/C][/ROW]
[ROW][C]Connected[/C][C]0.0469437389403787[/C][C]0.034787[/C][C]1.3495[/C][C]0.178384[/C][C]0.089192[/C][/ROW]
[ROW][C]Separate[/C][C]0.0419978310517143[/C][C]0.035648[/C][C]1.1781[/C][C]0.239847[/C][C]0.119923[/C][/ROW]
[ROW][C]Software[/C][C]0.607405158110716[/C][C]0.051845[/C][C]11.7158[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0986310792586457[/C][C]0.057963[/C][C]1.7016[/C][C]0.09004[/C][C]0.04502[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0393791266630167[/C][C]0.042557[/C][C]-0.9253[/C][C]0.35567[/C][C]0.177835[/C][/ROW]
[ROW][C]Belonging[/C][C]0.0158660592613708[/C][C]0.037843[/C][C]0.4193[/C][C]0.675376[/C][C]0.337688[/C][/ROW]
[ROW][C]Belonging_Final[/C][C]-0.0194154193631069[/C][C]0.056444[/C][C]-0.344[/C][C]0.731147[/C][C]0.365573[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=191274&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=191274&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)3.779566582730961.9176521.97090.0498090.024904
Connected0.04694373894037870.0347871.34950.1783840.089192
Separate0.04199783105171430.0356481.17810.2398470.119923
Software0.6074051581107160.05184511.715800
Happiness0.09863107925864570.0579631.70160.090040.04502
Depression-0.03937912666301670.042557-0.92530.355670.177835
Belonging0.01586605926137080.0378430.41930.6753760.337688
Belonging_Final-0.01941541936310690.056444-0.3440.7311470.365573






Multiple Linear Regression - Regression Statistics
Multiple R0.653394258005352
R-squared0.426924056394364
Adjusted R-squared0.411254011061397
F-TEST (value)27.244596127377
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.88446241278469
Sum Squared Residuals909.106837810759

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.653394258005352 \tabularnewline
R-squared & 0.426924056394364 \tabularnewline
Adjusted R-squared & 0.411254011061397 \tabularnewline
F-TEST (value) & 27.244596127377 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 256 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.88446241278469 \tabularnewline
Sum Squared Residuals & 909.106837810759 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=191274&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.653394258005352[/C][/ROW]
[ROW][C]R-squared[/C][C]0.426924056394364[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.411254011061397[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]27.244596127377[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]256[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]1.88446241278469[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]909.106837810759[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=191274&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=191274&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 R0.653394258005352
R-squared0.426924056394364
Adjusted R-squared0.411254011061397
F-TEST (value)27.244596127377
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.88446241278469
Sum Squared Residuals909.106837810759






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11315.7169326674783-2.71693266747828
21615.30464529881620.69535470118377
31916.53422660597592.46577339402408
41511.24319907102563.75680092897442
51415.8896873324328-1.88968733243282
61314.3424239462714-1.34242394627141
71914.83819200878984.16180799121016
81516.6568417465609-1.65684174656086
91415.6143966049743-1.61439660497434
101513.83988226254521.16011773745481
111614.52441321979851.47558678020148
121615.96134519141310.0386548085868939
131614.96541689650651.03458310349349
141615.13059457657630.869405423423655
151717.7266051778577-0.726605177857681
161515.0073602272847-0.00736022728471113
171514.03331126894840.966688731051579
182016.03954666325573.96045333674426
191815.094186162422.90581383758003
201615.18613762215190.813862377848066
211615.00153683346760.998463166532416
221614.58386482617381.41613517382618
231916.22690098760652.77309901239348
241614.6382510537831.36174894621697
251715.84160213608931.15839786391069
261715.8344851325851.16551486741504
271614.52940119859751.47059880140251
281516.4169297769606-1.41692977696059
291615.29551745644320.70448254355681
301413.61739445627860.382605543721402
311515.367231470103-0.367231470103047
321212.1577948842104-0.157794884210414
331414.4670335229458-0.46703352294582
341615.54904748087970.450952519120262
351415.1519977706766-1.15199777067663
361012.4548067707195-2.45480677071949
371012.2908025947004-2.29080259470042
381415.442875350487-1.44287535048698
391614.11256764964031.88743235035968
401614.05030069097431.94969930902573
411614.35991566120121.64008433879884
421415.4129095162212-1.41290951622121
432017.49755924374662.50244075625335
441413.73799971061440.262000289385567
451414.1390257843911-0.139025784391113
461115.1505593881384-4.15055938813839
471416.4190959972096-2.41909599720956
481514.7812339122260.218766087773982
491615.19159772331030.808402276689707
501415.361515363781-1.36151536378102
511616.8537398386884-0.853739838688409
521413.7316892738080.268310726191954
531214.6138653598005-2.61386535980045
541615.59068990343190.409310096568121
55910.7137318072366-1.7137318072366
561411.83260460506342.16739539493663
571615.69372369001340.306276309986645
581615.23035557126270.769644428737286
591514.82300455854460.17699544145538
601613.79322244935052.20677755064948
611210.83672794920741.1632720507926
621615.43786401774420.562135982255831
631616.2989869704333-0.2989869704333
641414.4388877335844-0.438887733584355
651615.15004427002750.849955729972461
661715.74385384140771.25614615859234
671816.09034650151841.90965349848158
681814.07649049189673.92350950810328
691215.8084608807317-3.80846088073166
701615.47284798326780.527152016732213
711013.0122458267498-3.01224582674976
721414.7156655383903-0.7156655383903
731816.83798954427311.16201045572691
741817.19282818589550.807171814104507
751615.00946868929770.990531310702269
761713.09025249257753.90974750742254
771616.4072325443378-0.407232544337833
781614.21228172267391.78771827732615
791314.9614853283133-1.9614853283133
801615.08313851077660.916861489223406
811615.53609896948560.463901030514354
821615.64322947701630.356770522983708
831515.6201822872087-0.620182287208743
841514.68614370756470.313856292435276
851613.88276262753512.11723737246488
861413.95178861200210.0482113879978756
871615.23309418629930.766905813700725
881614.6813029945341.31869700546596
891514.10333817370510.896661826294862
901213.6433035668958-1.64330356689577
911716.83212464144880.167875358551165
921615.72948523077620.2705147692238
931514.90579233527870.0942076647212599
941314.8364568188003-1.83645681880029
951614.69803280606341.3019671939366
961615.69607804669080.303921953309245
971613.48328467925572.51671532074433
981615.83004170145760.169958298542448
991414.2661258632027-0.26612586320274
1001617.1940865071683-1.19408650716827
1011614.50590112878861.49409887121141
1022017.57909928367592.42090071632414
1031514.02264601404090.977353985959138
1041614.83837625185191.16162374814812
1051314.7124447739459-1.71244477394589
1061715.76043731524731.23956268475275
1071615.77206452484710.227935475152911
1081614.23260426438521.76739573561482
1091212.0024802659182-0.0024802659181661
1101615.17183854996160.828161450038385
1111615.93848803340390.0615119665961118
1121714.86253282826022.13746717173979
1131314.5286402413612-1.52864024136123
1141214.614568460888-2.614568460888
1151816.27645244436051.72354755563947
1161415.9504759627416-1.95047596274164
1171412.99246219519511.0075378048049
1181314.7858242392293-1.78582423922932
1191615.51445795588390.485542044116056
1201314.3730308681848-1.37303086818476
1211615.40726953321840.592730466781632
1221315.9001483950515-2.90014839505154
1231617.0738036864139-1.07380368641385
1241515.9985652529538-0.998565252953809
1251616.9217558949015-0.921755894901496
1261514.75014717881310.249852821186913
1271715.76721026047391.23278973952609
1281514.00423199516910.995768004830927
1291214.7455979666711-2.74559796667113
1301613.90182246601292.09817753398714
1311013.490018922728-3.49001892272798
1321613.48472934881742.51527065118258
1331214.1318955712898-2.13189557128976
1341415.6891601643807-1.68916016438072
1351515.1349525324793-0.13495253247934
1361311.87987029892291.12012970107706
1371514.54067598928640.459324010713607
1381113.3639577865016-2.3639577865016
1391212.9948717800782-0.99487178007819
1401113.2797734052425-2.27977340524254
1411612.87066703284813.12933296715189
1421513.5777970081451.42220299185501
1431717.0126296693111-0.0126296693111288
1441614.21772328463611.78227671536387
1451013.3076482519713-3.30764825197125
1461815.7108182646392.28918173536104
1471315.057515844885-2.05751584488498
1481614.91980860046531.08019139953472
1491312.63776380440320.362236195596834
1501012.8783257394112-2.87832573941121
1511516.155043271253-1.15504327125299
1521613.99236085150662.00763914849345
1531611.70404505131494.29595494868509
1541412.24996754626091.75003245373915
1551012.3106299805489-2.3106299805489
1561716.83212464144880.167875358551165
1571311.56953931916061.4304606808394
1581514.00423199516910.995768004830927
1591614.67139552040851.32860447959149
1601212.5736517546432-0.573651754643204
1611312.60060369153710.399396308462923
1621312.46655135388390.533448646116147
1631212.3881607885568-0.38816078855682
1641716.5737899268770.426210073122991
1651513.67260044568511.32739955431488
1661011.4206728334644-1.42067283346442
1671414.4691619974894-0.469161997489404
1681114.2909865799885-3.29098657998851
1691314.8482927619942-1.84829276199418
1701614.43087474594941.56912525405059
1711210.36531181629621.63468818370377
1721615.70594839385070.294051606149256
1731213.9883936528962-1.98839365289616
174911.3120335908731-2.31203359087306
1751215.2885887877223-3.2885887877223
1761514.74421311565640.255786884343578
1771212.2632972969964-0.263297296996437
1781212.6879346718068-0.687934671806849
1791414.0621066117256-0.0621066117256325
1801213.476269705029-1.47626970502905
1811615.43404807723430.565951922765744
1821111.5217489928796-0.521748992879648
1831917.16046327131091.83953672868909
1841515.5206096079202-0.520609607920211
185814.7662880903322-6.76628809033216
1861614.96809271966591.03190728033406
1871714.74767686862742.25232313137259
1881212.5418032885651-0.541803288565075
1891111.5269675255856-0.526967525585557
1901110.29932240894260.700677591057422
1911415.0449039081772-1.04490390817719
1921615.85492363747950.145076362520501
193129.657999892580332.34200010741967
1941614.300513259331.69948674067003
1951313.9159846340245-0.915984634024546
1961515.3686335282855-0.368633528285513
1971613.09834314754632.90165685245369
1981615.31296975317590.687030246824134
1991412.48745520070841.51254479929164
2001614.77057978105631.22942021894371
2011614.19538977693681.80461022306324
2021413.56526081339240.434739186607563
2031113.7622976777595-2.76229767775954
2041214.9165699771727-2.91656997717273
2051512.96966651819912.03033348180092
2061514.83696442004550.163035579954472
2071614.8470264956861.152973504314
2081615.43394871036260.566051289637426
2091113.9167631437977-2.91676314379774
2101514.30315947049950.696840529500495
2111214.507489606999-2.50748960699899
2121216.2896849694461-4.28968496944614
2131514.30917048110010.690829518899894
2141512.16749588830622.83250411169379
2151614.88328934434421.1167106556558
2161413.42078783082380.579212169176227
2171715.06266197823011.93733802176991
2181414.3279169397482-0.327916939748237
2191311.99028890163491.00971109836511
2201515.6158919610783-0.615891961078346
2211315.0224913327295-2.02249133272955
2221414.5733033465196-0.573303346519553
2231514.56644591290410.433554087095921
2241213.4585313702885-1.45853137028853
2251312.80428073990440.195719260095626
226811.9668684285413-3.96686842854126
2271414.3096831383973-0.309683138397302
2281413.27374355278650.726256447213534
2291112.3432695732266-1.34326957322662
2301213.1609985574185-1.16099855741853
2311311.47993235152811.52006764847187
2321013.4650403340904-3.46504033409045
2331611.70045382224594.29954617775414
2341816.455866370751.54413362925002
2351314.305398824479-1.30539882447903
2361113.6549207425401-2.65492074254013
237411.170028137282-7.170028137282
2381314.8152140281387-1.81521402813867
2391614.59236330543211.40763669456794
2401011.9287261285823-1.92872612858231
2411212.4071970658913-0.407197065891321
2421213.795600381651-1.79560038165096
243108.886344700787961.11365529921204
2441311.27700688023681.72299311976324
2451514.09262731602050.907372683979529
2461212.0467701780665-0.0467701780665387
2471413.15388286620630.846117133793712
2481012.8902928435778-2.89029284357777
2491210.80096582046091.19903417953907
2501211.88393362896460.116066371035426
2511112.1379198030589-1.13791980305892
2521011.8622634576053-1.86226345760534
2531211.6631437816570.336856218342988
2541613.17822476363682.82177523636317
2551213.7152063049677-1.71520630496768
2561414.264087859685-0.264087859685033
2571614.68118855727991.31881144272009
2581411.82392868149752.17607131850249
2591314.78164098406-1.78164098406003
26049.48330674262234-5.48330674262234
2611514.1743666514850.825633348514997
2621115.5502096888069-4.55020968880689
2631111.4716452522508-0.471645252250812
2641413.16729085252320.832709147476811

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 15.7169326674783 & -2.71693266747828 \tabularnewline
2 & 16 & 15.3046452988162 & 0.69535470118377 \tabularnewline
3 & 19 & 16.5342266059759 & 2.46577339402408 \tabularnewline
4 & 15 & 11.2431990710256 & 3.75680092897442 \tabularnewline
5 & 14 & 15.8896873324328 & -1.88968733243282 \tabularnewline
6 & 13 & 14.3424239462714 & -1.34242394627141 \tabularnewline
7 & 19 & 14.8381920087898 & 4.16180799121016 \tabularnewline
8 & 15 & 16.6568417465609 & -1.65684174656086 \tabularnewline
9 & 14 & 15.6143966049743 & -1.61439660497434 \tabularnewline
10 & 15 & 13.8398822625452 & 1.16011773745481 \tabularnewline
11 & 16 & 14.5244132197985 & 1.47558678020148 \tabularnewline
12 & 16 & 15.9613451914131 & 0.0386548085868939 \tabularnewline
13 & 16 & 14.9654168965065 & 1.03458310349349 \tabularnewline
14 & 16 & 15.1305945765763 & 0.869405423423655 \tabularnewline
15 & 17 & 17.7266051778577 & -0.726605177857681 \tabularnewline
16 & 15 & 15.0073602272847 & -0.00736022728471113 \tabularnewline
17 & 15 & 14.0333112689484 & 0.966688731051579 \tabularnewline
18 & 20 & 16.0395466632557 & 3.96045333674426 \tabularnewline
19 & 18 & 15.09418616242 & 2.90581383758003 \tabularnewline
20 & 16 & 15.1861376221519 & 0.813862377848066 \tabularnewline
21 & 16 & 15.0015368334676 & 0.998463166532416 \tabularnewline
22 & 16 & 14.5838648261738 & 1.41613517382618 \tabularnewline
23 & 19 & 16.2269009876065 & 2.77309901239348 \tabularnewline
24 & 16 & 14.638251053783 & 1.36174894621697 \tabularnewline
25 & 17 & 15.8416021360893 & 1.15839786391069 \tabularnewline
26 & 17 & 15.834485132585 & 1.16551486741504 \tabularnewline
27 & 16 & 14.5294011985975 & 1.47059880140251 \tabularnewline
28 & 15 & 16.4169297769606 & -1.41692977696059 \tabularnewline
29 & 16 & 15.2955174564432 & 0.70448254355681 \tabularnewline
30 & 14 & 13.6173944562786 & 0.382605543721402 \tabularnewline
31 & 15 & 15.367231470103 & -0.367231470103047 \tabularnewline
32 & 12 & 12.1577948842104 & -0.157794884210414 \tabularnewline
33 & 14 & 14.4670335229458 & -0.46703352294582 \tabularnewline
34 & 16 & 15.5490474808797 & 0.450952519120262 \tabularnewline
35 & 14 & 15.1519977706766 & -1.15199777067663 \tabularnewline
36 & 10 & 12.4548067707195 & -2.45480677071949 \tabularnewline
37 & 10 & 12.2908025947004 & -2.29080259470042 \tabularnewline
38 & 14 & 15.442875350487 & -1.44287535048698 \tabularnewline
39 & 16 & 14.1125676496403 & 1.88743235035968 \tabularnewline
40 & 16 & 14.0503006909743 & 1.94969930902573 \tabularnewline
41 & 16 & 14.3599156612012 & 1.64008433879884 \tabularnewline
42 & 14 & 15.4129095162212 & -1.41290951622121 \tabularnewline
43 & 20 & 17.4975592437466 & 2.50244075625335 \tabularnewline
44 & 14 & 13.7379997106144 & 0.262000289385567 \tabularnewline
45 & 14 & 14.1390257843911 & -0.139025784391113 \tabularnewline
46 & 11 & 15.1505593881384 & -4.15055938813839 \tabularnewline
47 & 14 & 16.4190959972096 & -2.41909599720956 \tabularnewline
48 & 15 & 14.781233912226 & 0.218766087773982 \tabularnewline
49 & 16 & 15.1915977233103 & 0.808402276689707 \tabularnewline
50 & 14 & 15.361515363781 & -1.36151536378102 \tabularnewline
51 & 16 & 16.8537398386884 & -0.853739838688409 \tabularnewline
52 & 14 & 13.731689273808 & 0.268310726191954 \tabularnewline
53 & 12 & 14.6138653598005 & -2.61386535980045 \tabularnewline
54 & 16 & 15.5906899034319 & 0.409310096568121 \tabularnewline
55 & 9 & 10.7137318072366 & -1.7137318072366 \tabularnewline
56 & 14 & 11.8326046050634 & 2.16739539493663 \tabularnewline
57 & 16 & 15.6937236900134 & 0.306276309986645 \tabularnewline
58 & 16 & 15.2303555712627 & 0.769644428737286 \tabularnewline
59 & 15 & 14.8230045585446 & 0.17699544145538 \tabularnewline
60 & 16 & 13.7932224493505 & 2.20677755064948 \tabularnewline
61 & 12 & 10.8367279492074 & 1.1632720507926 \tabularnewline
62 & 16 & 15.4378640177442 & 0.562135982255831 \tabularnewline
63 & 16 & 16.2989869704333 & -0.2989869704333 \tabularnewline
64 & 14 & 14.4388877335844 & -0.438887733584355 \tabularnewline
65 & 16 & 15.1500442700275 & 0.849955729972461 \tabularnewline
66 & 17 & 15.7438538414077 & 1.25614615859234 \tabularnewline
67 & 18 & 16.0903465015184 & 1.90965349848158 \tabularnewline
68 & 18 & 14.0764904918967 & 3.92350950810328 \tabularnewline
69 & 12 & 15.8084608807317 & -3.80846088073166 \tabularnewline
70 & 16 & 15.4728479832678 & 0.527152016732213 \tabularnewline
71 & 10 & 13.0122458267498 & -3.01224582674976 \tabularnewline
72 & 14 & 14.7156655383903 & -0.7156655383903 \tabularnewline
73 & 18 & 16.8379895442731 & 1.16201045572691 \tabularnewline
74 & 18 & 17.1928281858955 & 0.807171814104507 \tabularnewline
75 & 16 & 15.0094686892977 & 0.990531310702269 \tabularnewline
76 & 17 & 13.0902524925775 & 3.90974750742254 \tabularnewline
77 & 16 & 16.4072325443378 & -0.407232544337833 \tabularnewline
78 & 16 & 14.2122817226739 & 1.78771827732615 \tabularnewline
79 & 13 & 14.9614853283133 & -1.9614853283133 \tabularnewline
80 & 16 & 15.0831385107766 & 0.916861489223406 \tabularnewline
81 & 16 & 15.5360989694856 & 0.463901030514354 \tabularnewline
82 & 16 & 15.6432294770163 & 0.356770522983708 \tabularnewline
83 & 15 & 15.6201822872087 & -0.620182287208743 \tabularnewline
84 & 15 & 14.6861437075647 & 0.313856292435276 \tabularnewline
85 & 16 & 13.8827626275351 & 2.11723737246488 \tabularnewline
86 & 14 & 13.9517886120021 & 0.0482113879978756 \tabularnewline
87 & 16 & 15.2330941862993 & 0.766905813700725 \tabularnewline
88 & 16 & 14.681302994534 & 1.31869700546596 \tabularnewline
89 & 15 & 14.1033381737051 & 0.896661826294862 \tabularnewline
90 & 12 & 13.6433035668958 & -1.64330356689577 \tabularnewline
91 & 17 & 16.8321246414488 & 0.167875358551165 \tabularnewline
92 & 16 & 15.7294852307762 & 0.2705147692238 \tabularnewline
93 & 15 & 14.9057923352787 & 0.0942076647212599 \tabularnewline
94 & 13 & 14.8364568188003 & -1.83645681880029 \tabularnewline
95 & 16 & 14.6980328060634 & 1.3019671939366 \tabularnewline
96 & 16 & 15.6960780466908 & 0.303921953309245 \tabularnewline
97 & 16 & 13.4832846792557 & 2.51671532074433 \tabularnewline
98 & 16 & 15.8300417014576 & 0.169958298542448 \tabularnewline
99 & 14 & 14.2661258632027 & -0.26612586320274 \tabularnewline
100 & 16 & 17.1940865071683 & -1.19408650716827 \tabularnewline
101 & 16 & 14.5059011287886 & 1.49409887121141 \tabularnewline
102 & 20 & 17.5790992836759 & 2.42090071632414 \tabularnewline
103 & 15 & 14.0226460140409 & 0.977353985959138 \tabularnewline
104 & 16 & 14.8383762518519 & 1.16162374814812 \tabularnewline
105 & 13 & 14.7124447739459 & -1.71244477394589 \tabularnewline
106 & 17 & 15.7604373152473 & 1.23956268475275 \tabularnewline
107 & 16 & 15.7720645248471 & 0.227935475152911 \tabularnewline
108 & 16 & 14.2326042643852 & 1.76739573561482 \tabularnewline
109 & 12 & 12.0024802659182 & -0.0024802659181661 \tabularnewline
110 & 16 & 15.1718385499616 & 0.828161450038385 \tabularnewline
111 & 16 & 15.9384880334039 & 0.0615119665961118 \tabularnewline
112 & 17 & 14.8625328282602 & 2.13746717173979 \tabularnewline
113 & 13 & 14.5286402413612 & -1.52864024136123 \tabularnewline
114 & 12 & 14.614568460888 & -2.614568460888 \tabularnewline
115 & 18 & 16.2764524443605 & 1.72354755563947 \tabularnewline
116 & 14 & 15.9504759627416 & -1.95047596274164 \tabularnewline
117 & 14 & 12.9924621951951 & 1.0075378048049 \tabularnewline
118 & 13 & 14.7858242392293 & -1.78582423922932 \tabularnewline
119 & 16 & 15.5144579558839 & 0.485542044116056 \tabularnewline
120 & 13 & 14.3730308681848 & -1.37303086818476 \tabularnewline
121 & 16 & 15.4072695332184 & 0.592730466781632 \tabularnewline
122 & 13 & 15.9001483950515 & -2.90014839505154 \tabularnewline
123 & 16 & 17.0738036864139 & -1.07380368641385 \tabularnewline
124 & 15 & 15.9985652529538 & -0.998565252953809 \tabularnewline
125 & 16 & 16.9217558949015 & -0.921755894901496 \tabularnewline
126 & 15 & 14.7501471788131 & 0.249852821186913 \tabularnewline
127 & 17 & 15.7672102604739 & 1.23278973952609 \tabularnewline
128 & 15 & 14.0042319951691 & 0.995768004830927 \tabularnewline
129 & 12 & 14.7455979666711 & -2.74559796667113 \tabularnewline
130 & 16 & 13.9018224660129 & 2.09817753398714 \tabularnewline
131 & 10 & 13.490018922728 & -3.49001892272798 \tabularnewline
132 & 16 & 13.4847293488174 & 2.51527065118258 \tabularnewline
133 & 12 & 14.1318955712898 & -2.13189557128976 \tabularnewline
134 & 14 & 15.6891601643807 & -1.68916016438072 \tabularnewline
135 & 15 & 15.1349525324793 & -0.13495253247934 \tabularnewline
136 & 13 & 11.8798702989229 & 1.12012970107706 \tabularnewline
137 & 15 & 14.5406759892864 & 0.459324010713607 \tabularnewline
138 & 11 & 13.3639577865016 & -2.3639577865016 \tabularnewline
139 & 12 & 12.9948717800782 & -0.99487178007819 \tabularnewline
140 & 11 & 13.2797734052425 & -2.27977340524254 \tabularnewline
141 & 16 & 12.8706670328481 & 3.12933296715189 \tabularnewline
142 & 15 & 13.577797008145 & 1.42220299185501 \tabularnewline
143 & 17 & 17.0126296693111 & -0.0126296693111288 \tabularnewline
144 & 16 & 14.2177232846361 & 1.78227671536387 \tabularnewline
145 & 10 & 13.3076482519713 & -3.30764825197125 \tabularnewline
146 & 18 & 15.710818264639 & 2.28918173536104 \tabularnewline
147 & 13 & 15.057515844885 & -2.05751584488498 \tabularnewline
148 & 16 & 14.9198086004653 & 1.08019139953472 \tabularnewline
149 & 13 & 12.6377638044032 & 0.362236195596834 \tabularnewline
150 & 10 & 12.8783257394112 & -2.87832573941121 \tabularnewline
151 & 15 & 16.155043271253 & -1.15504327125299 \tabularnewline
152 & 16 & 13.9923608515066 & 2.00763914849345 \tabularnewline
153 & 16 & 11.7040450513149 & 4.29595494868509 \tabularnewline
154 & 14 & 12.2499675462609 & 1.75003245373915 \tabularnewline
155 & 10 & 12.3106299805489 & -2.3106299805489 \tabularnewline
156 & 17 & 16.8321246414488 & 0.167875358551165 \tabularnewline
157 & 13 & 11.5695393191606 & 1.4304606808394 \tabularnewline
158 & 15 & 14.0042319951691 & 0.995768004830927 \tabularnewline
159 & 16 & 14.6713955204085 & 1.32860447959149 \tabularnewline
160 & 12 & 12.5736517546432 & -0.573651754643204 \tabularnewline
161 & 13 & 12.6006036915371 & 0.399396308462923 \tabularnewline
162 & 13 & 12.4665513538839 & 0.533448646116147 \tabularnewline
163 & 12 & 12.3881607885568 & -0.38816078855682 \tabularnewline
164 & 17 & 16.573789926877 & 0.426210073122991 \tabularnewline
165 & 15 & 13.6726004456851 & 1.32739955431488 \tabularnewline
166 & 10 & 11.4206728334644 & -1.42067283346442 \tabularnewline
167 & 14 & 14.4691619974894 & -0.469161997489404 \tabularnewline
168 & 11 & 14.2909865799885 & -3.29098657998851 \tabularnewline
169 & 13 & 14.8482927619942 & -1.84829276199418 \tabularnewline
170 & 16 & 14.4308747459494 & 1.56912525405059 \tabularnewline
171 & 12 & 10.3653118162962 & 1.63468818370377 \tabularnewline
172 & 16 & 15.7059483938507 & 0.294051606149256 \tabularnewline
173 & 12 & 13.9883936528962 & -1.98839365289616 \tabularnewline
174 & 9 & 11.3120335908731 & -2.31203359087306 \tabularnewline
175 & 12 & 15.2885887877223 & -3.2885887877223 \tabularnewline
176 & 15 & 14.7442131156564 & 0.255786884343578 \tabularnewline
177 & 12 & 12.2632972969964 & -0.263297296996437 \tabularnewline
178 & 12 & 12.6879346718068 & -0.687934671806849 \tabularnewline
179 & 14 & 14.0621066117256 & -0.0621066117256325 \tabularnewline
180 & 12 & 13.476269705029 & -1.47626970502905 \tabularnewline
181 & 16 & 15.4340480772343 & 0.565951922765744 \tabularnewline
182 & 11 & 11.5217489928796 & -0.521748992879648 \tabularnewline
183 & 19 & 17.1604632713109 & 1.83953672868909 \tabularnewline
184 & 15 & 15.5206096079202 & -0.520609607920211 \tabularnewline
185 & 8 & 14.7662880903322 & -6.76628809033216 \tabularnewline
186 & 16 & 14.9680927196659 & 1.03190728033406 \tabularnewline
187 & 17 & 14.7476768686274 & 2.25232313137259 \tabularnewline
188 & 12 & 12.5418032885651 & -0.541803288565075 \tabularnewline
189 & 11 & 11.5269675255856 & -0.526967525585557 \tabularnewline
190 & 11 & 10.2993224089426 & 0.700677591057422 \tabularnewline
191 & 14 & 15.0449039081772 & -1.04490390817719 \tabularnewline
192 & 16 & 15.8549236374795 & 0.145076362520501 \tabularnewline
193 & 12 & 9.65799989258033 & 2.34200010741967 \tabularnewline
194 & 16 & 14.30051325933 & 1.69948674067003 \tabularnewline
195 & 13 & 13.9159846340245 & -0.915984634024546 \tabularnewline
196 & 15 & 15.3686335282855 & -0.368633528285513 \tabularnewline
197 & 16 & 13.0983431475463 & 2.90165685245369 \tabularnewline
198 & 16 & 15.3129697531759 & 0.687030246824134 \tabularnewline
199 & 14 & 12.4874552007084 & 1.51254479929164 \tabularnewline
200 & 16 & 14.7705797810563 & 1.22942021894371 \tabularnewline
201 & 16 & 14.1953897769368 & 1.80461022306324 \tabularnewline
202 & 14 & 13.5652608133924 & 0.434739186607563 \tabularnewline
203 & 11 & 13.7622976777595 & -2.76229767775954 \tabularnewline
204 & 12 & 14.9165699771727 & -2.91656997717273 \tabularnewline
205 & 15 & 12.9696665181991 & 2.03033348180092 \tabularnewline
206 & 15 & 14.8369644200455 & 0.163035579954472 \tabularnewline
207 & 16 & 14.847026495686 & 1.152973504314 \tabularnewline
208 & 16 & 15.4339487103626 & 0.566051289637426 \tabularnewline
209 & 11 & 13.9167631437977 & -2.91676314379774 \tabularnewline
210 & 15 & 14.3031594704995 & 0.696840529500495 \tabularnewline
211 & 12 & 14.507489606999 & -2.50748960699899 \tabularnewline
212 & 12 & 16.2896849694461 & -4.28968496944614 \tabularnewline
213 & 15 & 14.3091704811001 & 0.690829518899894 \tabularnewline
214 & 15 & 12.1674958883062 & 2.83250411169379 \tabularnewline
215 & 16 & 14.8832893443442 & 1.1167106556558 \tabularnewline
216 & 14 & 13.4207878308238 & 0.579212169176227 \tabularnewline
217 & 17 & 15.0626619782301 & 1.93733802176991 \tabularnewline
218 & 14 & 14.3279169397482 & -0.327916939748237 \tabularnewline
219 & 13 & 11.9902889016349 & 1.00971109836511 \tabularnewline
220 & 15 & 15.6158919610783 & -0.615891961078346 \tabularnewline
221 & 13 & 15.0224913327295 & -2.02249133272955 \tabularnewline
222 & 14 & 14.5733033465196 & -0.573303346519553 \tabularnewline
223 & 15 & 14.5664459129041 & 0.433554087095921 \tabularnewline
224 & 12 & 13.4585313702885 & -1.45853137028853 \tabularnewline
225 & 13 & 12.8042807399044 & 0.195719260095626 \tabularnewline
226 & 8 & 11.9668684285413 & -3.96686842854126 \tabularnewline
227 & 14 & 14.3096831383973 & -0.309683138397302 \tabularnewline
228 & 14 & 13.2737435527865 & 0.726256447213534 \tabularnewline
229 & 11 & 12.3432695732266 & -1.34326957322662 \tabularnewline
230 & 12 & 13.1609985574185 & -1.16099855741853 \tabularnewline
231 & 13 & 11.4799323515281 & 1.52006764847187 \tabularnewline
232 & 10 & 13.4650403340904 & -3.46504033409045 \tabularnewline
233 & 16 & 11.7004538222459 & 4.29954617775414 \tabularnewline
234 & 18 & 16.45586637075 & 1.54413362925002 \tabularnewline
235 & 13 & 14.305398824479 & -1.30539882447903 \tabularnewline
236 & 11 & 13.6549207425401 & -2.65492074254013 \tabularnewline
237 & 4 & 11.170028137282 & -7.170028137282 \tabularnewline
238 & 13 & 14.8152140281387 & -1.81521402813867 \tabularnewline
239 & 16 & 14.5923633054321 & 1.40763669456794 \tabularnewline
240 & 10 & 11.9287261285823 & -1.92872612858231 \tabularnewline
241 & 12 & 12.4071970658913 & -0.407197065891321 \tabularnewline
242 & 12 & 13.795600381651 & -1.79560038165096 \tabularnewline
243 & 10 & 8.88634470078796 & 1.11365529921204 \tabularnewline
244 & 13 & 11.2770068802368 & 1.72299311976324 \tabularnewline
245 & 15 & 14.0926273160205 & 0.907372683979529 \tabularnewline
246 & 12 & 12.0467701780665 & -0.0467701780665387 \tabularnewline
247 & 14 & 13.1538828662063 & 0.846117133793712 \tabularnewline
248 & 10 & 12.8902928435778 & -2.89029284357777 \tabularnewline
249 & 12 & 10.8009658204609 & 1.19903417953907 \tabularnewline
250 & 12 & 11.8839336289646 & 0.116066371035426 \tabularnewline
251 & 11 & 12.1379198030589 & -1.13791980305892 \tabularnewline
252 & 10 & 11.8622634576053 & -1.86226345760534 \tabularnewline
253 & 12 & 11.663143781657 & 0.336856218342988 \tabularnewline
254 & 16 & 13.1782247636368 & 2.82177523636317 \tabularnewline
255 & 12 & 13.7152063049677 & -1.71520630496768 \tabularnewline
256 & 14 & 14.264087859685 & -0.264087859685033 \tabularnewline
257 & 16 & 14.6811885572799 & 1.31881144272009 \tabularnewline
258 & 14 & 11.8239286814975 & 2.17607131850249 \tabularnewline
259 & 13 & 14.78164098406 & -1.78164098406003 \tabularnewline
260 & 4 & 9.48330674262234 & -5.48330674262234 \tabularnewline
261 & 15 & 14.174366651485 & 0.825633348514997 \tabularnewline
262 & 11 & 15.5502096888069 & -4.55020968880689 \tabularnewline
263 & 11 & 11.4716452522508 & -0.471645252250812 \tabularnewline
264 & 14 & 13.1672908525232 & 0.832709147476811 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=191274&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]13[/C][C]15.7169326674783[/C][C]-2.71693266747828[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.3046452988162[/C][C]0.69535470118377[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]16.5342266059759[/C][C]2.46577339402408[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]11.2431990710256[/C][C]3.75680092897442[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]15.8896873324328[/C][C]-1.88968733243282[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.3424239462714[/C][C]-1.34242394627141[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]14.8381920087898[/C][C]4.16180799121016[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]16.6568417465609[/C][C]-1.65684174656086[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]15.6143966049743[/C][C]-1.61439660497434[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]13.8398822625452[/C][C]1.16011773745481[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.5244132197985[/C][C]1.47558678020148[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]15.9613451914131[/C][C]0.0386548085868939[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]14.9654168965065[/C][C]1.03458310349349[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.1305945765763[/C][C]0.869405423423655[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]17.7266051778577[/C][C]-0.726605177857681[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.0073602272847[/C][C]-0.00736022728471113[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.0333112689484[/C][C]0.966688731051579[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.0395466632557[/C][C]3.96045333674426[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.09418616242[/C][C]2.90581383758003[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.1861376221519[/C][C]0.813862377848066[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.0015368334676[/C][C]0.998463166532416[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]14.5838648261738[/C][C]1.41613517382618[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.2269009876065[/C][C]2.77309901239348[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]14.638251053783[/C][C]1.36174894621697[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.8416021360893[/C][C]1.15839786391069[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]15.834485132585[/C][C]1.16551486741504[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.5294011985975[/C][C]1.47059880140251[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.4169297769606[/C][C]-1.41692977696059[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.2955174564432[/C][C]0.70448254355681[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]13.6173944562786[/C][C]0.382605543721402[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.367231470103[/C][C]-0.367231470103047[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.1577948842104[/C][C]-0.157794884210414[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.4670335229458[/C][C]-0.46703352294582[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.5490474808797[/C][C]0.450952519120262[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.1519977706766[/C][C]-1.15199777067663[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.4548067707195[/C][C]-2.45480677071949[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]12.2908025947004[/C][C]-2.29080259470042[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.442875350487[/C][C]-1.44287535048698[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.1125676496403[/C][C]1.88743235035968[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.0503006909743[/C][C]1.94969930902573[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.3599156612012[/C][C]1.64008433879884[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.4129095162212[/C][C]-1.41290951622121[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.4975592437466[/C][C]2.50244075625335[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]13.7379997106144[/C][C]0.262000289385567[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.1390257843911[/C][C]-0.139025784391113[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.1505593881384[/C][C]-4.15055938813839[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.4190959972096[/C][C]-2.41909599720956[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.781233912226[/C][C]0.218766087773982[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.1915977233103[/C][C]0.808402276689707[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.361515363781[/C][C]-1.36151536378102[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]16.8537398386884[/C][C]-0.853739838688409[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.731689273808[/C][C]0.268310726191954[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]14.6138653598005[/C][C]-2.61386535980045[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.5906899034319[/C][C]0.409310096568121[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]10.7137318072366[/C][C]-1.7137318072366[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]11.8326046050634[/C][C]2.16739539493663[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.6937236900134[/C][C]0.306276309986645[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.2303555712627[/C][C]0.769644428737286[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]14.8230045585446[/C][C]0.17699544145538[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]13.7932224493505[/C][C]2.20677755064948[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]10.8367279492074[/C][C]1.1632720507926[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.4378640177442[/C][C]0.562135982255831[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.2989869704333[/C][C]-0.2989869704333[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.4388877335844[/C][C]-0.438887733584355[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.1500442700275[/C][C]0.849955729972461[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]15.7438538414077[/C][C]1.25614615859234[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.0903465015184[/C][C]1.90965349848158[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.0764904918967[/C][C]3.92350950810328[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.8084608807317[/C][C]-3.80846088073166[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.4728479832678[/C][C]0.527152016732213[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.0122458267498[/C][C]-3.01224582674976[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.7156655383903[/C][C]-0.7156655383903[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.8379895442731[/C][C]1.16201045572691[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.1928281858955[/C][C]0.807171814104507[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.0094686892977[/C][C]0.990531310702269[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.0902524925775[/C][C]3.90974750742254[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.4072325443378[/C][C]-0.407232544337833[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.2122817226739[/C][C]1.78771827732615[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]14.9614853283133[/C][C]-1.9614853283133[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.0831385107766[/C][C]0.916861489223406[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.5360989694856[/C][C]0.463901030514354[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.6432294770163[/C][C]0.356770522983708[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.6201822872087[/C][C]-0.620182287208743[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.6861437075647[/C][C]0.313856292435276[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]13.8827626275351[/C][C]2.11723737246488[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]13.9517886120021[/C][C]0.0482113879978756[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.2330941862993[/C][C]0.766905813700725[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.681302994534[/C][C]1.31869700546596[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.1033381737051[/C][C]0.896661826294862[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.6433035668958[/C][C]-1.64330356689577[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.8321246414488[/C][C]0.167875358551165[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.7294852307762[/C][C]0.2705147692238[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]14.9057923352787[/C][C]0.0942076647212599[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.8364568188003[/C][C]-1.83645681880029[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.6980328060634[/C][C]1.3019671939366[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.6960780466908[/C][C]0.303921953309245[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.4832846792557[/C][C]2.51671532074433[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.8300417014576[/C][C]0.169958298542448[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.2661258632027[/C][C]-0.26612586320274[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.1940865071683[/C][C]-1.19408650716827[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.5059011287886[/C][C]1.49409887121141[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.5790992836759[/C][C]2.42090071632414[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.0226460140409[/C][C]0.977353985959138[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]14.8383762518519[/C][C]1.16162374814812[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.7124447739459[/C][C]-1.71244477394589[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.7604373152473[/C][C]1.23956268475275[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.7720645248471[/C][C]0.227935475152911[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.2326042643852[/C][C]1.76739573561482[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.0024802659182[/C][C]-0.0024802659181661[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.1718385499616[/C][C]0.828161450038385[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]15.9384880334039[/C][C]0.0615119665961118[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]14.8625328282602[/C][C]2.13746717173979[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.5286402413612[/C][C]-1.52864024136123[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.614568460888[/C][C]-2.614568460888[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.2764524443605[/C][C]1.72354755563947[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.9504759627416[/C][C]-1.95047596274164[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]12.9924621951951[/C][C]1.0075378048049[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.7858242392293[/C][C]-1.78582423922932[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.5144579558839[/C][C]0.485542044116056[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.3730308681848[/C][C]-1.37303086818476[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.4072695332184[/C][C]0.592730466781632[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.9001483950515[/C][C]-2.90014839505154[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]17.0738036864139[/C][C]-1.07380368641385[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.9985652529538[/C][C]-0.998565252953809[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.9217558949015[/C][C]-0.921755894901496[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.7501471788131[/C][C]0.249852821186913[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.7672102604739[/C][C]1.23278973952609[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]14.0042319951691[/C][C]0.995768004830927[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.7455979666711[/C][C]-2.74559796667113[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.9018224660129[/C][C]2.09817753398714[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.490018922728[/C][C]-3.49001892272798[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4847293488174[/C][C]2.51527065118258[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.1318955712898[/C][C]-2.13189557128976[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.6891601643807[/C][C]-1.68916016438072[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.1349525324793[/C][C]-0.13495253247934[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]11.8798702989229[/C][C]1.12012970107706[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.5406759892864[/C][C]0.459324010713607[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.3639577865016[/C][C]-2.3639577865016[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]12.9948717800782[/C][C]-0.99487178007819[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.2797734052425[/C][C]-2.27977340524254[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8706670328481[/C][C]3.12933296715189[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.577797008145[/C][C]1.42220299185501[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]17.0126296693111[/C][C]-0.0126296693111288[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.2177232846361[/C][C]1.78227671536387[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.3076482519713[/C][C]-3.30764825197125[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.710818264639[/C][C]2.28918173536104[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.057515844885[/C][C]-2.05751584488498[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.9198086004653[/C][C]1.08019139953472[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.6377638044032[/C][C]0.362236195596834[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.8783257394112[/C][C]-2.87832573941121[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]16.155043271253[/C][C]-1.15504327125299[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.9923608515066[/C][C]2.00763914849345[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.7040450513149[/C][C]4.29595494868509[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.2499675462609[/C][C]1.75003245373915[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.3106299805489[/C][C]-2.3106299805489[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.8321246414488[/C][C]0.167875358551165[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.5695393191606[/C][C]1.4304606808394[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]14.0042319951691[/C][C]0.995768004830927[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.6713955204085[/C][C]1.32860447959149[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.5736517546432[/C][C]-0.573651754643204[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.6006036915371[/C][C]0.399396308462923[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.4665513538839[/C][C]0.533448646116147[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.3881607885568[/C][C]-0.38816078855682[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.573789926877[/C][C]0.426210073122991[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.6726004456851[/C][C]1.32739955431488[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.4206728334644[/C][C]-1.42067283346442[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.4691619974894[/C][C]-0.469161997489404[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.2909865799885[/C][C]-3.29098657998851[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.8482927619942[/C][C]-1.84829276199418[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.4308747459494[/C][C]1.56912525405059[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.3653118162962[/C][C]1.63468818370377[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.7059483938507[/C][C]0.294051606149256[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.9883936528962[/C][C]-1.98839365289616[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.3120335908731[/C][C]-2.31203359087306[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]15.2885887877223[/C][C]-3.2885887877223[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.7442131156564[/C][C]0.255786884343578[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.2632972969964[/C][C]-0.263297296996437[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.6879346718068[/C][C]-0.687934671806849[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]14.0621066117256[/C][C]-0.0621066117256325[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.476269705029[/C][C]-1.47626970502905[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]15.4340480772343[/C][C]0.565951922765744[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.5217489928796[/C][C]-0.521748992879648[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]17.1604632713109[/C][C]1.83953672868909[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.5206096079202[/C][C]-0.520609607920211[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.7662880903322[/C][C]-6.76628809033216[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.9680927196659[/C][C]1.03190728033406[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.7476768686274[/C][C]2.25232313137259[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.5418032885651[/C][C]-0.541803288565075[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.5269675255856[/C][C]-0.526967525585557[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.2993224089426[/C][C]0.700677591057422[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]15.0449039081772[/C][C]-1.04490390817719[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.8549236374795[/C][C]0.145076362520501[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.65799989258033[/C][C]2.34200010741967[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.30051325933[/C][C]1.69948674067003[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.9159846340245[/C][C]-0.915984634024546[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]15.3686335282855[/C][C]-0.368633528285513[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]13.0983431475463[/C][C]2.90165685245369[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.3129697531759[/C][C]0.687030246824134[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4874552007084[/C][C]1.51254479929164[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.7705797810563[/C][C]1.22942021894371[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]14.1953897769368[/C][C]1.80461022306324[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.5652608133924[/C][C]0.434739186607563[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.7622976777595[/C][C]-2.76229767775954[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.9165699771727[/C][C]-2.91656997717273[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.9696665181991[/C][C]2.03033348180092[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.8369644200455[/C][C]0.163035579954472[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.847026495686[/C][C]1.152973504314[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]15.4339487103626[/C][C]0.566051289637426[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.9167631437977[/C][C]-2.91676314379774[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]14.3031594704995[/C][C]0.696840529500495[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.507489606999[/C][C]-2.50748960699899[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]16.2896849694461[/C][C]-4.28968496944614[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.3091704811001[/C][C]0.690829518899894[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.1674958883062[/C][C]2.83250411169379[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.8832893443442[/C][C]1.1167106556558[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.4207878308238[/C][C]0.579212169176227[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]15.0626619782301[/C][C]1.93733802176991[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.3279169397482[/C][C]-0.327916939748237[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.9902889016349[/C][C]1.00971109836511[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.6158919610783[/C][C]-0.615891961078346[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]15.0224913327295[/C][C]-2.02249133272955[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]14.5733033465196[/C][C]-0.573303346519553[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.5664459129041[/C][C]0.433554087095921[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.4585313702885[/C][C]-1.45853137028853[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.8042807399044[/C][C]0.195719260095626[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.9668684285413[/C][C]-3.96686842854126[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]14.3096831383973[/C][C]-0.309683138397302[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]13.2737435527865[/C][C]0.726256447213534[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.3432695732266[/C][C]-1.34326957322662[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]13.1609985574185[/C][C]-1.16099855741853[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.4799323515281[/C][C]1.52006764847187[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.4650403340904[/C][C]-3.46504033409045[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.7004538222459[/C][C]4.29954617775414[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]16.45586637075[/C][C]1.54413362925002[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]14.305398824479[/C][C]-1.30539882447903[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.6549207425401[/C][C]-2.65492074254013[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]11.170028137282[/C][C]-7.170028137282[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.8152140281387[/C][C]-1.81521402813867[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.5923633054321[/C][C]1.40763669456794[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.9287261285823[/C][C]-1.92872612858231[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.4071970658913[/C][C]-0.407197065891321[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.795600381651[/C][C]-1.79560038165096[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.88634470078796[/C][C]1.11365529921204[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]11.2770068802368[/C][C]1.72299311976324[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]14.0926273160205[/C][C]0.907372683979529[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]12.0467701780665[/C][C]-0.0467701780665387[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]13.1538828662063[/C][C]0.846117133793712[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.8902928435778[/C][C]-2.89029284357777[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.8009658204609[/C][C]1.19903417953907[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.8839336289646[/C][C]0.116066371035426[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]12.1379198030589[/C][C]-1.13791980305892[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.8622634576053[/C][C]-1.86226345760534[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.663143781657[/C][C]0.336856218342988[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]13.1782247636368[/C][C]2.82177523636317[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.7152063049677[/C][C]-1.71520630496768[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]14.264087859685[/C][C]-0.264087859685033[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.6811885572799[/C][C]1.31881144272009[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.8239286814975[/C][C]2.17607131850249[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.78164098406[/C][C]-1.78164098406003[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.48330674262234[/C][C]-5.48330674262234[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]14.174366651485[/C][C]0.825633348514997[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]15.5502096888069[/C][C]-4.55020968880689[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.4716452522508[/C][C]-0.471645252250812[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.1672908525232[/C][C]0.832709147476811[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=191274&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=191274&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
11315.7169326674783-2.71693266747828
21615.30464529881620.69535470118377
31916.53422660597592.46577339402408
41511.24319907102563.75680092897442
51415.8896873324328-1.88968733243282
61314.3424239462714-1.34242394627141
71914.83819200878984.16180799121016
81516.6568417465609-1.65684174656086
91415.6143966049743-1.61439660497434
101513.83988226254521.16011773745481
111614.52441321979851.47558678020148
121615.96134519141310.0386548085868939
131614.96541689650651.03458310349349
141615.13059457657630.869405423423655
151717.7266051778577-0.726605177857681
161515.0073602272847-0.00736022728471113
171514.03331126894840.966688731051579
182016.03954666325573.96045333674426
191815.094186162422.90581383758003
201615.18613762215190.813862377848066
211615.00153683346760.998463166532416
221614.58386482617381.41613517382618
231916.22690098760652.77309901239348
241614.6382510537831.36174894621697
251715.84160213608931.15839786391069
261715.8344851325851.16551486741504
271614.52940119859751.47059880140251
281516.4169297769606-1.41692977696059
291615.29551745644320.70448254355681
301413.61739445627860.382605543721402
311515.367231470103-0.367231470103047
321212.1577948842104-0.157794884210414
331414.4670335229458-0.46703352294582
341615.54904748087970.450952519120262
351415.1519977706766-1.15199777067663
361012.4548067707195-2.45480677071949
371012.2908025947004-2.29080259470042
381415.442875350487-1.44287535048698
391614.11256764964031.88743235035968
401614.05030069097431.94969930902573
411614.35991566120121.64008433879884
421415.4129095162212-1.41290951622121
432017.49755924374662.50244075625335
441413.73799971061440.262000289385567
451414.1390257843911-0.139025784391113
461115.1505593881384-4.15055938813839
471416.4190959972096-2.41909599720956
481514.7812339122260.218766087773982
491615.19159772331030.808402276689707
501415.361515363781-1.36151536378102
511616.8537398386884-0.853739838688409
521413.7316892738080.268310726191954
531214.6138653598005-2.61386535980045
541615.59068990343190.409310096568121
55910.7137318072366-1.7137318072366
561411.83260460506342.16739539493663
571615.69372369001340.306276309986645
581615.23035557126270.769644428737286
591514.82300455854460.17699544145538
601613.79322244935052.20677755064948
611210.83672794920741.1632720507926
621615.43786401774420.562135982255831
631616.2989869704333-0.2989869704333
641414.4388877335844-0.438887733584355
651615.15004427002750.849955729972461
661715.74385384140771.25614615859234
671816.09034650151841.90965349848158
681814.07649049189673.92350950810328
691215.8084608807317-3.80846088073166
701615.47284798326780.527152016732213
711013.0122458267498-3.01224582674976
721414.7156655383903-0.7156655383903
731816.83798954427311.16201045572691
741817.19282818589550.807171814104507
751615.00946868929770.990531310702269
761713.09025249257753.90974750742254
771616.4072325443378-0.407232544337833
781614.21228172267391.78771827732615
791314.9614853283133-1.9614853283133
801615.08313851077660.916861489223406
811615.53609896948560.463901030514354
821615.64322947701630.356770522983708
831515.6201822872087-0.620182287208743
841514.68614370756470.313856292435276
851613.88276262753512.11723737246488
861413.95178861200210.0482113879978756
871615.23309418629930.766905813700725
881614.6813029945341.31869700546596
891514.10333817370510.896661826294862
901213.6433035668958-1.64330356689577
911716.83212464144880.167875358551165
921615.72948523077620.2705147692238
931514.90579233527870.0942076647212599
941314.8364568188003-1.83645681880029
951614.69803280606341.3019671939366
961615.69607804669080.303921953309245
971613.48328467925572.51671532074433
981615.83004170145760.169958298542448
991414.2661258632027-0.26612586320274
1001617.1940865071683-1.19408650716827
1011614.50590112878861.49409887121141
1022017.57909928367592.42090071632414
1031514.02264601404090.977353985959138
1041614.83837625185191.16162374814812
1051314.7124447739459-1.71244477394589
1061715.76043731524731.23956268475275
1071615.77206452484710.227935475152911
1081614.23260426438521.76739573561482
1091212.0024802659182-0.0024802659181661
1101615.17183854996160.828161450038385
1111615.93848803340390.0615119665961118
1121714.86253282826022.13746717173979
1131314.5286402413612-1.52864024136123
1141214.614568460888-2.614568460888
1151816.27645244436051.72354755563947
1161415.9504759627416-1.95047596274164
1171412.99246219519511.0075378048049
1181314.7858242392293-1.78582423922932
1191615.51445795588390.485542044116056
1201314.3730308681848-1.37303086818476
1211615.40726953321840.592730466781632
1221315.9001483950515-2.90014839505154
1231617.0738036864139-1.07380368641385
1241515.9985652529538-0.998565252953809
1251616.9217558949015-0.921755894901496
1261514.75014717881310.249852821186913
1271715.76721026047391.23278973952609
1281514.00423199516910.995768004830927
1291214.7455979666711-2.74559796667113
1301613.90182246601292.09817753398714
1311013.490018922728-3.49001892272798
1321613.48472934881742.51527065118258
1331214.1318955712898-2.13189557128976
1341415.6891601643807-1.68916016438072
1351515.1349525324793-0.13495253247934
1361311.87987029892291.12012970107706
1371514.54067598928640.459324010713607
1381113.3639577865016-2.3639577865016
1391212.9948717800782-0.99487178007819
1401113.2797734052425-2.27977340524254
1411612.87066703284813.12933296715189
1421513.5777970081451.42220299185501
1431717.0126296693111-0.0126296693111288
1441614.21772328463611.78227671536387
1451013.3076482519713-3.30764825197125
1461815.7108182646392.28918173536104
1471315.057515844885-2.05751584488498
1481614.91980860046531.08019139953472
1491312.63776380440320.362236195596834
1501012.8783257394112-2.87832573941121
1511516.155043271253-1.15504327125299
1521613.99236085150662.00763914849345
1531611.70404505131494.29595494868509
1541412.24996754626091.75003245373915
1551012.3106299805489-2.3106299805489
1561716.83212464144880.167875358551165
1571311.56953931916061.4304606808394
1581514.00423199516910.995768004830927
1591614.67139552040851.32860447959149
1601212.5736517546432-0.573651754643204
1611312.60060369153710.399396308462923
1621312.46655135388390.533448646116147
1631212.3881607885568-0.38816078855682
1641716.5737899268770.426210073122991
1651513.67260044568511.32739955431488
1661011.4206728334644-1.42067283346442
1671414.4691619974894-0.469161997489404
1681114.2909865799885-3.29098657998851
1691314.8482927619942-1.84829276199418
1701614.43087474594941.56912525405059
1711210.36531181629621.63468818370377
1721615.70594839385070.294051606149256
1731213.9883936528962-1.98839365289616
174911.3120335908731-2.31203359087306
1751215.2885887877223-3.2885887877223
1761514.74421311565640.255786884343578
1771212.2632972969964-0.263297296996437
1781212.6879346718068-0.687934671806849
1791414.0621066117256-0.0621066117256325
1801213.476269705029-1.47626970502905
1811615.43404807723430.565951922765744
1821111.5217489928796-0.521748992879648
1831917.16046327131091.83953672868909
1841515.5206096079202-0.520609607920211
185814.7662880903322-6.76628809033216
1861614.96809271966591.03190728033406
1871714.74767686862742.25232313137259
1881212.5418032885651-0.541803288565075
1891111.5269675255856-0.526967525585557
1901110.29932240894260.700677591057422
1911415.0449039081772-1.04490390817719
1921615.85492363747950.145076362520501
193129.657999892580332.34200010741967
1941614.300513259331.69948674067003
1951313.9159846340245-0.915984634024546
1961515.3686335282855-0.368633528285513
1971613.09834314754632.90165685245369
1981615.31296975317590.687030246824134
1991412.48745520070841.51254479929164
2001614.77057978105631.22942021894371
2011614.19538977693681.80461022306324
2021413.56526081339240.434739186607563
2031113.7622976777595-2.76229767775954
2041214.9165699771727-2.91656997717273
2051512.96966651819912.03033348180092
2061514.83696442004550.163035579954472
2071614.8470264956861.152973504314
2081615.43394871036260.566051289637426
2091113.9167631437977-2.91676314379774
2101514.30315947049950.696840529500495
2111214.507489606999-2.50748960699899
2121216.2896849694461-4.28968496944614
2131514.30917048110010.690829518899894
2141512.16749588830622.83250411169379
2151614.88328934434421.1167106556558
2161413.42078783082380.579212169176227
2171715.06266197823011.93733802176991
2181414.3279169397482-0.327916939748237
2191311.99028890163491.00971109836511
2201515.6158919610783-0.615891961078346
2211315.0224913327295-2.02249133272955
2221414.5733033465196-0.573303346519553
2231514.56644591290410.433554087095921
2241213.4585313702885-1.45853137028853
2251312.80428073990440.195719260095626
226811.9668684285413-3.96686842854126
2271414.3096831383973-0.309683138397302
2281413.27374355278650.726256447213534
2291112.3432695732266-1.34326957322662
2301213.1609985574185-1.16099855741853
2311311.47993235152811.52006764847187
2321013.4650403340904-3.46504033409045
2331611.70045382224594.29954617775414
2341816.455866370751.54413362925002
2351314.305398824479-1.30539882447903
2361113.6549207425401-2.65492074254013
237411.170028137282-7.170028137282
2381314.8152140281387-1.81521402813867
2391614.59236330543211.40763669456794
2401011.9287261285823-1.92872612858231
2411212.4071970658913-0.407197065891321
2421213.795600381651-1.79560038165096
243108.886344700787961.11365529921204
2441311.27700688023681.72299311976324
2451514.09262731602050.907372683979529
2461212.0467701780665-0.0467701780665387
2471413.15388286620630.846117133793712
2481012.8902928435778-2.89029284357777
2491210.80096582046091.19903417953907
2501211.88393362896460.116066371035426
2511112.1379198030589-1.13791980305892
2521011.8622634576053-1.86226345760534
2531211.6631437816570.336856218342988
2541613.17822476363682.82177523636317
2551213.7152063049677-1.71520630496768
2561414.264087859685-0.264087859685033
2571614.68118855727991.31881144272009
2581411.82392868149752.17607131850249
2591314.78164098406-1.78164098406003
26049.48330674262234-5.48330674262234
2611514.1743666514850.825633348514997
2621115.5502096888069-4.55020968880689
2631111.4716452522508-0.471645252250812
2641413.16729085252320.832709147476811






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.2344495241033230.4688990482066470.765550475896677
120.1202935178405560.2405870356811130.879706482159444
130.08155415734578130.1631083146915630.918445842654219
140.1028747764979160.2057495529958330.897125223502084
150.05875197565154840.1175039513030970.941248024348452
160.03916866759316350.07833733518632690.960831332406836
170.0630191184441720.1260382368883440.936980881555828
180.2558643279353050.5117286558706090.744135672064695
190.1942166329001490.3884332658002990.805783367099851
200.137764883334640.2755297666692810.86223511666536
210.09860626155137140.1972125231027430.901393738448629
220.09685339904276960.1937067980855390.90314660095723
230.2570543779111420.5141087558222840.742945622088858
240.3214954184239460.6429908368478930.678504581576054
250.2948695385950260.5897390771900510.705130461404974
260.2774478577119780.5548957154239550.722552142288022
270.3520988888725530.7041977777451050.647901111127447
280.3638496488593340.7276992977186680.636150351140666
290.3467855921475840.6935711842951690.653214407852416
300.3808983862722690.7617967725445380.619101613727731
310.3286758031111580.6573516062223170.671324196888842
320.2894928679699310.5789857359398630.710507132030069
330.2624907774068950.5249815548137910.737509222593105
340.2263044170330430.4526088340660860.773695582966957
350.187880541814590.375761083629180.81211945818541
360.3049298148882140.6098596297764280.695070185111786
370.3349710741512010.6699421483024020.665028925848799
380.3259636225842460.6519272451684910.674036377415754
390.3560227398554310.7120454797108620.643977260144569
400.3342094491346410.6684188982692830.665790550865359
410.2980013652937390.5960027305874790.701998634706261
420.2638357288282250.5276714576564510.736164271171775
430.2782742652114350.556548530422870.721725734788565
440.2365365213239230.4730730426478460.763463478676077
450.2144422801981570.4288845603963140.785557719801843
460.3926897177725630.7853794355451270.607310282227437
470.5455190334856560.9089619330286870.454480966514344
480.4965487764023340.9930975528046680.503451223597666
490.483216160724750.96643232144950.51678383927525
500.4683902306446540.9367804612893080.531609769355346
510.4236717203499130.8473434406998250.576328279650087
520.3781691975725320.7563383951450640.621830802427468
530.3866036095760940.7732072191521880.613396390423906
540.3697095512826040.7394191025652080.630290448717396
550.3609375571723210.7218751143446420.639062442827679
560.3393852385237350.678770477047470.660614761476265
570.2997777542626510.5995555085253020.700222245737349
580.2711577202394340.5423154404788680.728842279760566
590.2366942697965370.4733885395930740.763305730203463
600.2424586147505540.4849172295011070.757541385249446
610.2186501591049540.4373003182099080.781349840895046
620.1917356708049250.383471341609850.808264329195075
630.1637320578437610.3274641156875220.836267942156239
640.1379788888949110.2759577777898220.862021111105089
650.1190738662615420.2381477325230850.880926133738458
660.1102288514213880.2204577028427760.889771148578612
670.1059861502412970.2119723004825940.894013849758703
680.223058679356040.446117358712080.77694132064396
690.3130388526634780.6260777053269560.686961147336522
700.2821425098269240.5642850196538480.717857490173076
710.3979023773212270.7958047546424530.602097622678773
720.3598978352378180.7197956704756360.640102164762182
730.3515646464888880.7031292929777750.648435353511112
740.3361970271152260.6723940542304510.663802972884775
750.3040241548740880.6080483097481750.695975845125912
760.369544725558950.7390894511178990.63045527444105
770.3338177811756470.6676355623512940.666182218824353
780.3129770526536390.6259541053072780.687022947346361
790.3260565689197160.6521131378394330.673943431080284
800.2984783473115490.5969566946230990.701521652688451
810.2703419068908390.5406838137816790.729658093109161
820.2394460425874980.4788920851749960.760553957412502
830.2151396628227070.4302793256454140.784860337177293
840.1879137227384080.3758274454768150.812086277261592
850.1846071916740780.3692143833481560.815392808325922
860.1595725120415980.3191450240831960.840427487958402
870.1403225373613220.2806450747226450.859677462638678
880.1307388017647960.2614776035295910.869261198235204
890.1129764378758930.2259528757517860.887023562124107
900.1102031142192710.2204062284385420.889796885780729
910.09429193694486590.1885838738897320.905708063055134
920.08142409060866170.1628481812173230.918575909391338
930.06916220468658760.1383244093731750.930837795313412
940.07105056196411460.1421011239282290.928949438035885
950.06420477509780920.1284095501956180.935795224902191
960.05379758650354130.1075951730070830.946202413496459
970.05943151463996930.1188630292799390.940568485360031
980.04922705113043850.0984541022608770.950772948869562
990.04036379712394110.08072759424788230.959636202876059
1000.03531497706865580.07062995413731160.964685022931344
1010.03133001394681790.06266002789363580.968669986053182
1020.03688207108464640.07376414216929280.963117928915354
1030.03165139025063740.06330278050127480.968348609749363
1040.02858591411915050.05717182823830090.97141408588085
1050.03381713581376670.06763427162753340.966182864186233
1060.02971708786873120.05943417573746240.970282912131269
1070.02413307862849560.04826615725699110.975866921371504
1080.02400791135008510.04801582270017020.975992088649915
1090.01945150490639090.03890300981278170.980548495093609
1100.01591366614214850.03182733228429690.984086333857851
1110.01261465227192230.02522930454384470.987385347728078
1120.01303812775868250.02607625551736510.986961872241317
1130.01164521464788010.02329042929576020.98835478535212
1140.01672065608724870.03344131217449730.983279343912751
1150.01597102344518570.03194204689037130.984028976554814
1160.0152811978016850.030562395603370.984718802198315
1170.01263902994539410.02527805989078830.987360970054606
1180.01262195624937510.02524391249875020.987378043750625
1190.01026120162714510.02052240325429030.989738798372855
1200.009038025678921090.01807605135784220.990961974321079
1210.007353567803015730.01470713560603150.992646432196984
1220.01131955121710580.02263910243421170.988680448782894
1230.009538495994803650.01907699198960730.990461504005196
1240.008473116391724750.01694623278344950.991526883608275
1250.006935559729241880.01387111945848380.993064440270758
1260.005650421037164460.01130084207432890.994349578962835
1270.00508716401279390.01017432802558780.994912835987206
1280.004098793520274620.008197587040549240.995901206479725
1290.006048869827586880.01209773965517380.993951130172413
1300.006553238028811910.01310647605762380.993446761971188
1310.01354029438996480.02708058877992970.986459705610035
1320.01629872750422860.03259745500845720.983701272495771
1330.01758236498167170.03516472996334340.982417635018328
1340.01698334499195070.03396668998390140.983016655008049
1350.0138803744734780.0277607489469560.986119625526522
1360.01171233869970170.02342467739940330.988287661300298
1370.00937464333820910.01874928667641820.990625356661791
1380.01141690215884620.02283380431769240.988583097841154
1390.009937139879518260.01987427975903650.990062860120482
1400.01129281549976360.02258563099952720.988707184500236
1410.01751656482001360.03503312964002710.982483435179986
1420.01592895790096320.03185791580192640.984071042099037
1430.01268316359323410.02536632718646820.987316836406766
1440.01344583330598330.02689166661196660.986554166694017
1450.02564031348952370.05128062697904730.974359686510476
1460.03141841095330010.06283682190660010.9685815890467
1470.03297957803633510.06595915607267020.967020421963665
1480.02977342271015450.05954684542030910.970226577289845
1490.02481272874093870.04962545748187750.975187271259061
1500.03443623206436750.06887246412873510.965563767935632
1510.02971241893936210.05942483787872420.970287581060638
1520.03128065816490130.06256131632980260.968719341835099
1530.06388043297827720.1277608659565540.936119567021723
1540.06276143572712580.1255228714542520.937238564272874
1550.07217477719129810.1443495543825960.927825222808702
1560.06174785743390260.1234957148678050.938252142566097
1570.05516287941602720.1103257588320540.944837120583973
1580.04827041228233410.09654082456466830.951729587717666
1590.04722610868202220.09445221736404450.952773891317978
1600.04049302819331040.08098605638662090.95950697180669
1610.03341243056971730.06682486113943450.966587569430283
1620.02746679527600250.05493359055200510.972533204723998
1630.02287565330103760.04575130660207520.977124346698962
1640.01929641328181750.03859282656363490.980703586718183
1650.01693535633760470.03387071267520940.983064643662395
1660.01718430506346220.03436861012692430.982815694936538
1670.01380762438724070.02761524877448140.986192375612759
1680.02037358612615640.04074717225231280.979626413873844
1690.02019288594577440.04038577189154880.979807114054226
1700.01885801717267590.03771603434535170.981141982827324
1710.01813496534063030.03626993068126060.98186503465937
1720.01469419658669620.02938839317339240.985305803413304
1730.01474229074869420.02948458149738840.985257709251306
1740.01642261616407160.03284523232814310.983577383835928
1750.02194945967986790.04389891935973590.978050540320132
1760.01765315232126220.03530630464252440.982346847678738
1770.01438269225106910.02876538450213820.985617307748931
1780.0117427428384760.02348548567695210.988257257161524
1790.009192159794017650.01838431958803530.990807840205982
1800.008005361728639290.01601072345727860.991994638271361
1810.006603604186685780.01320720837337160.993396395813314
1820.005345217149551930.01069043429910390.994654782850448
1830.005609366225755050.01121873245151010.994390633774245
1840.004436472950334990.008872945900669970.995563527049665
1850.0940865399009820.1881730798019640.905913460099018
1860.08168458117219110.1633691623443820.918315418827809
1870.09284398026744250.1856879605348850.907156019732557
1880.08021271356467330.1604254271293470.919787286435327
1890.06795963394561670.1359192678912330.932040366054383
1900.05635614350327380.1127122870065480.943643856496726
1910.04971116188416230.09942232376832470.950288838115838
1920.04196119331522220.08392238663044450.958038806684778
1930.04871552798395550.0974310559679110.951284472016044
1940.05228906663103810.1045781332620760.947710933368962
1950.04438117382695730.08876234765391450.955618826173043
1960.0370263282172370.07405265643447390.962973671782763
1970.04831570611723950.09663141223447890.951684293882761
1980.03958629462185280.07917258924370570.960413705378147
1990.03670115629514750.0734023125902950.963298843704853
2000.03103986761341980.06207973522683970.96896013238658
2010.02922197249448330.05844394498896650.970778027505517
2020.02438057070672770.04876114141345540.975619429293272
2030.03130536910663020.06261073821326040.96869463089337
2040.03568031777393910.07136063554787830.964319682226061
2050.03890633637672130.07781267275344250.961093663623279
2060.0308791545420790.06175830908415790.969120845457921
2070.03034222282480850.0606844456496170.969657777175192
2080.02494987273114620.04989974546229240.975050127268854
2090.02786814120547050.0557362824109410.97213185879453
2100.02254174262108910.04508348524217830.977458257378911
2110.02497753329313890.04995506658627780.975022466706861
2120.03997350874230030.07994701748460070.9600264912577
2130.03158710624416730.06317421248833450.968412893755833
2140.04415894259893950.08831788519787890.955841057401061
2150.03805930928693740.07611861857387480.961940690713063
2160.02975082592105630.05950165184211260.970249174078944
2170.03219553127290540.06439106254581090.967804468727095
2180.02752949098226520.05505898196453040.972470509017735
2190.02474180700445380.04948361400890750.975258192995546
2200.01896337737057050.0379267547411410.981036622629429
2210.01689473392096760.03378946784193510.983105266079032
2220.01242064858491530.02484129716983060.987579351415085
2230.009311741862016570.01862348372403310.990688258137983
2240.00750211854397710.01500423708795420.992497881456023
2250.006547056161290890.01309411232258180.993452943838709
2260.01499519031446630.02999038062893250.985004809685534
2270.01154161843724660.02308323687449310.988458381562753
2280.008350318923407940.01670063784681590.991649681076592
2290.006096834243210920.01219366848642180.993903165756789
2300.004410362517329940.008820725034659890.99558963748267
2310.004394614579941070.008789229159882130.995605385420059
2320.008144979571466480.0162899591429330.991855020428533
2330.03775654421187850.0755130884237570.962243455788122
2340.05429422005691110.1085884401138220.945705779943089
2350.04050658575470140.08101317150940270.959493414245299
2360.03611011259517660.07222022519035320.963889887404823
2370.2465057005702010.4930114011404030.753494299429799
2380.2007821309639770.4015642619279530.799217869036023
2390.180044405468040.3600888109360790.81995559453196
2400.1421285353331370.2842570706662740.857871464666863
2410.1137073431033520.2274146862067040.886292656896648
2420.09453010324072960.1890602064814590.90546989675927
2430.08790231871979390.1758046374395880.912097681280206
2440.1535504342222450.3071008684444910.846449565777755
2450.1376303397172550.275260679434510.862369660282745
2460.1101093305386860.2202186610773710.889890669461314
2470.07777060082222360.1555412016444470.922229399177776
2480.06669484702562430.1333896940512490.933305152974376
2490.06248882703230030.1249776540646010.9375111729677
2500.0773809930539610.1547619861079220.922619006946039
2510.04605497640822620.09210995281645230.953945023591774
2520.1122856641622770.2245713283245540.887714335837723
2530.2349985110953930.4699970221907850.765001488904607

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.234449524103323 & 0.468899048206647 & 0.765550475896677 \tabularnewline
12 & 0.120293517840556 & 0.240587035681113 & 0.879706482159444 \tabularnewline
13 & 0.0815541573457813 & 0.163108314691563 & 0.918445842654219 \tabularnewline
14 & 0.102874776497916 & 0.205749552995833 & 0.897125223502084 \tabularnewline
15 & 0.0587519756515484 & 0.117503951303097 & 0.941248024348452 \tabularnewline
16 & 0.0391686675931635 & 0.0783373351863269 & 0.960831332406836 \tabularnewline
17 & 0.063019118444172 & 0.126038236888344 & 0.936980881555828 \tabularnewline
18 & 0.255864327935305 & 0.511728655870609 & 0.744135672064695 \tabularnewline
19 & 0.194216632900149 & 0.388433265800299 & 0.805783367099851 \tabularnewline
20 & 0.13776488333464 & 0.275529766669281 & 0.86223511666536 \tabularnewline
21 & 0.0986062615513714 & 0.197212523102743 & 0.901393738448629 \tabularnewline
22 & 0.0968533990427696 & 0.193706798085539 & 0.90314660095723 \tabularnewline
23 & 0.257054377911142 & 0.514108755822284 & 0.742945622088858 \tabularnewline
24 & 0.321495418423946 & 0.642990836847893 & 0.678504581576054 \tabularnewline
25 & 0.294869538595026 & 0.589739077190051 & 0.705130461404974 \tabularnewline
26 & 0.277447857711978 & 0.554895715423955 & 0.722552142288022 \tabularnewline
27 & 0.352098888872553 & 0.704197777745105 & 0.647901111127447 \tabularnewline
28 & 0.363849648859334 & 0.727699297718668 & 0.636150351140666 \tabularnewline
29 & 0.346785592147584 & 0.693571184295169 & 0.653214407852416 \tabularnewline
30 & 0.380898386272269 & 0.761796772544538 & 0.619101613727731 \tabularnewline
31 & 0.328675803111158 & 0.657351606222317 & 0.671324196888842 \tabularnewline
32 & 0.289492867969931 & 0.578985735939863 & 0.710507132030069 \tabularnewline
33 & 0.262490777406895 & 0.524981554813791 & 0.737509222593105 \tabularnewline
34 & 0.226304417033043 & 0.452608834066086 & 0.773695582966957 \tabularnewline
35 & 0.18788054181459 & 0.37576108362918 & 0.81211945818541 \tabularnewline
36 & 0.304929814888214 & 0.609859629776428 & 0.695070185111786 \tabularnewline
37 & 0.334971074151201 & 0.669942148302402 & 0.665028925848799 \tabularnewline
38 & 0.325963622584246 & 0.651927245168491 & 0.674036377415754 \tabularnewline
39 & 0.356022739855431 & 0.712045479710862 & 0.643977260144569 \tabularnewline
40 & 0.334209449134641 & 0.668418898269283 & 0.665790550865359 \tabularnewline
41 & 0.298001365293739 & 0.596002730587479 & 0.701998634706261 \tabularnewline
42 & 0.263835728828225 & 0.527671457656451 & 0.736164271171775 \tabularnewline
43 & 0.278274265211435 & 0.55654853042287 & 0.721725734788565 \tabularnewline
44 & 0.236536521323923 & 0.473073042647846 & 0.763463478676077 \tabularnewline
45 & 0.214442280198157 & 0.428884560396314 & 0.785557719801843 \tabularnewline
46 & 0.392689717772563 & 0.785379435545127 & 0.607310282227437 \tabularnewline
47 & 0.545519033485656 & 0.908961933028687 & 0.454480966514344 \tabularnewline
48 & 0.496548776402334 & 0.993097552804668 & 0.503451223597666 \tabularnewline
49 & 0.48321616072475 & 0.9664323214495 & 0.51678383927525 \tabularnewline
50 & 0.468390230644654 & 0.936780461289308 & 0.531609769355346 \tabularnewline
51 & 0.423671720349913 & 0.847343440699825 & 0.576328279650087 \tabularnewline
52 & 0.378169197572532 & 0.756338395145064 & 0.621830802427468 \tabularnewline
53 & 0.386603609576094 & 0.773207219152188 & 0.613396390423906 \tabularnewline
54 & 0.369709551282604 & 0.739419102565208 & 0.630290448717396 \tabularnewline
55 & 0.360937557172321 & 0.721875114344642 & 0.639062442827679 \tabularnewline
56 & 0.339385238523735 & 0.67877047704747 & 0.660614761476265 \tabularnewline
57 & 0.299777754262651 & 0.599555508525302 & 0.700222245737349 \tabularnewline
58 & 0.271157720239434 & 0.542315440478868 & 0.728842279760566 \tabularnewline
59 & 0.236694269796537 & 0.473388539593074 & 0.763305730203463 \tabularnewline
60 & 0.242458614750554 & 0.484917229501107 & 0.757541385249446 \tabularnewline
61 & 0.218650159104954 & 0.437300318209908 & 0.781349840895046 \tabularnewline
62 & 0.191735670804925 & 0.38347134160985 & 0.808264329195075 \tabularnewline
63 & 0.163732057843761 & 0.327464115687522 & 0.836267942156239 \tabularnewline
64 & 0.137978888894911 & 0.275957777789822 & 0.862021111105089 \tabularnewline
65 & 0.119073866261542 & 0.238147732523085 & 0.880926133738458 \tabularnewline
66 & 0.110228851421388 & 0.220457702842776 & 0.889771148578612 \tabularnewline
67 & 0.105986150241297 & 0.211972300482594 & 0.894013849758703 \tabularnewline
68 & 0.22305867935604 & 0.44611735871208 & 0.77694132064396 \tabularnewline
69 & 0.313038852663478 & 0.626077705326956 & 0.686961147336522 \tabularnewline
70 & 0.282142509826924 & 0.564285019653848 & 0.717857490173076 \tabularnewline
71 & 0.397902377321227 & 0.795804754642453 & 0.602097622678773 \tabularnewline
72 & 0.359897835237818 & 0.719795670475636 & 0.640102164762182 \tabularnewline
73 & 0.351564646488888 & 0.703129292977775 & 0.648435353511112 \tabularnewline
74 & 0.336197027115226 & 0.672394054230451 & 0.663802972884775 \tabularnewline
75 & 0.304024154874088 & 0.608048309748175 & 0.695975845125912 \tabularnewline
76 & 0.36954472555895 & 0.739089451117899 & 0.63045527444105 \tabularnewline
77 & 0.333817781175647 & 0.667635562351294 & 0.666182218824353 \tabularnewline
78 & 0.312977052653639 & 0.625954105307278 & 0.687022947346361 \tabularnewline
79 & 0.326056568919716 & 0.652113137839433 & 0.673943431080284 \tabularnewline
80 & 0.298478347311549 & 0.596956694623099 & 0.701521652688451 \tabularnewline
81 & 0.270341906890839 & 0.540683813781679 & 0.729658093109161 \tabularnewline
82 & 0.239446042587498 & 0.478892085174996 & 0.760553957412502 \tabularnewline
83 & 0.215139662822707 & 0.430279325645414 & 0.784860337177293 \tabularnewline
84 & 0.187913722738408 & 0.375827445476815 & 0.812086277261592 \tabularnewline
85 & 0.184607191674078 & 0.369214383348156 & 0.815392808325922 \tabularnewline
86 & 0.159572512041598 & 0.319145024083196 & 0.840427487958402 \tabularnewline
87 & 0.140322537361322 & 0.280645074722645 & 0.859677462638678 \tabularnewline
88 & 0.130738801764796 & 0.261477603529591 & 0.869261198235204 \tabularnewline
89 & 0.112976437875893 & 0.225952875751786 & 0.887023562124107 \tabularnewline
90 & 0.110203114219271 & 0.220406228438542 & 0.889796885780729 \tabularnewline
91 & 0.0942919369448659 & 0.188583873889732 & 0.905708063055134 \tabularnewline
92 & 0.0814240906086617 & 0.162848181217323 & 0.918575909391338 \tabularnewline
93 & 0.0691622046865876 & 0.138324409373175 & 0.930837795313412 \tabularnewline
94 & 0.0710505619641146 & 0.142101123928229 & 0.928949438035885 \tabularnewline
95 & 0.0642047750978092 & 0.128409550195618 & 0.935795224902191 \tabularnewline
96 & 0.0537975865035413 & 0.107595173007083 & 0.946202413496459 \tabularnewline
97 & 0.0594315146399693 & 0.118863029279939 & 0.940568485360031 \tabularnewline
98 & 0.0492270511304385 & 0.098454102260877 & 0.950772948869562 \tabularnewline
99 & 0.0403637971239411 & 0.0807275942478823 & 0.959636202876059 \tabularnewline
100 & 0.0353149770686558 & 0.0706299541373116 & 0.964685022931344 \tabularnewline
101 & 0.0313300139468179 & 0.0626600278936358 & 0.968669986053182 \tabularnewline
102 & 0.0368820710846464 & 0.0737641421692928 & 0.963117928915354 \tabularnewline
103 & 0.0316513902506374 & 0.0633027805012748 & 0.968348609749363 \tabularnewline
104 & 0.0285859141191505 & 0.0571718282383009 & 0.97141408588085 \tabularnewline
105 & 0.0338171358137667 & 0.0676342716275334 & 0.966182864186233 \tabularnewline
106 & 0.0297170878687312 & 0.0594341757374624 & 0.970282912131269 \tabularnewline
107 & 0.0241330786284956 & 0.0482661572569911 & 0.975866921371504 \tabularnewline
108 & 0.0240079113500851 & 0.0480158227001702 & 0.975992088649915 \tabularnewline
109 & 0.0194515049063909 & 0.0389030098127817 & 0.980548495093609 \tabularnewline
110 & 0.0159136661421485 & 0.0318273322842969 & 0.984086333857851 \tabularnewline
111 & 0.0126146522719223 & 0.0252293045438447 & 0.987385347728078 \tabularnewline
112 & 0.0130381277586825 & 0.0260762555173651 & 0.986961872241317 \tabularnewline
113 & 0.0116452146478801 & 0.0232904292957602 & 0.98835478535212 \tabularnewline
114 & 0.0167206560872487 & 0.0334413121744973 & 0.983279343912751 \tabularnewline
115 & 0.0159710234451857 & 0.0319420468903713 & 0.984028976554814 \tabularnewline
116 & 0.015281197801685 & 0.03056239560337 & 0.984718802198315 \tabularnewline
117 & 0.0126390299453941 & 0.0252780598907883 & 0.987360970054606 \tabularnewline
118 & 0.0126219562493751 & 0.0252439124987502 & 0.987378043750625 \tabularnewline
119 & 0.0102612016271451 & 0.0205224032542903 & 0.989738798372855 \tabularnewline
120 & 0.00903802567892109 & 0.0180760513578422 & 0.990961974321079 \tabularnewline
121 & 0.00735356780301573 & 0.0147071356060315 & 0.992646432196984 \tabularnewline
122 & 0.0113195512171058 & 0.0226391024342117 & 0.988680448782894 \tabularnewline
123 & 0.00953849599480365 & 0.0190769919896073 & 0.990461504005196 \tabularnewline
124 & 0.00847311639172475 & 0.0169462327834495 & 0.991526883608275 \tabularnewline
125 & 0.00693555972924188 & 0.0138711194584838 & 0.993064440270758 \tabularnewline
126 & 0.00565042103716446 & 0.0113008420743289 & 0.994349578962835 \tabularnewline
127 & 0.0050871640127939 & 0.0101743280255878 & 0.994912835987206 \tabularnewline
128 & 0.00409879352027462 & 0.00819758704054924 & 0.995901206479725 \tabularnewline
129 & 0.00604886982758688 & 0.0120977396551738 & 0.993951130172413 \tabularnewline
130 & 0.00655323802881191 & 0.0131064760576238 & 0.993446761971188 \tabularnewline
131 & 0.0135402943899648 & 0.0270805887799297 & 0.986459705610035 \tabularnewline
132 & 0.0162987275042286 & 0.0325974550084572 & 0.983701272495771 \tabularnewline
133 & 0.0175823649816717 & 0.0351647299633434 & 0.982417635018328 \tabularnewline
134 & 0.0169833449919507 & 0.0339666899839014 & 0.983016655008049 \tabularnewline
135 & 0.013880374473478 & 0.027760748946956 & 0.986119625526522 \tabularnewline
136 & 0.0117123386997017 & 0.0234246773994033 & 0.988287661300298 \tabularnewline
137 & 0.0093746433382091 & 0.0187492866764182 & 0.990625356661791 \tabularnewline
138 & 0.0114169021588462 & 0.0228338043176924 & 0.988583097841154 \tabularnewline
139 & 0.00993713987951826 & 0.0198742797590365 & 0.990062860120482 \tabularnewline
140 & 0.0112928154997636 & 0.0225856309995272 & 0.988707184500236 \tabularnewline
141 & 0.0175165648200136 & 0.0350331296400271 & 0.982483435179986 \tabularnewline
142 & 0.0159289579009632 & 0.0318579158019264 & 0.984071042099037 \tabularnewline
143 & 0.0126831635932341 & 0.0253663271864682 & 0.987316836406766 \tabularnewline
144 & 0.0134458333059833 & 0.0268916666119666 & 0.986554166694017 \tabularnewline
145 & 0.0256403134895237 & 0.0512806269790473 & 0.974359686510476 \tabularnewline
146 & 0.0314184109533001 & 0.0628368219066001 & 0.9685815890467 \tabularnewline
147 & 0.0329795780363351 & 0.0659591560726702 & 0.967020421963665 \tabularnewline
148 & 0.0297734227101545 & 0.0595468454203091 & 0.970226577289845 \tabularnewline
149 & 0.0248127287409387 & 0.0496254574818775 & 0.975187271259061 \tabularnewline
150 & 0.0344362320643675 & 0.0688724641287351 & 0.965563767935632 \tabularnewline
151 & 0.0297124189393621 & 0.0594248378787242 & 0.970287581060638 \tabularnewline
152 & 0.0312806581649013 & 0.0625613163298026 & 0.968719341835099 \tabularnewline
153 & 0.0638804329782772 & 0.127760865956554 & 0.936119567021723 \tabularnewline
154 & 0.0627614357271258 & 0.125522871454252 & 0.937238564272874 \tabularnewline
155 & 0.0721747771912981 & 0.144349554382596 & 0.927825222808702 \tabularnewline
156 & 0.0617478574339026 & 0.123495714867805 & 0.938252142566097 \tabularnewline
157 & 0.0551628794160272 & 0.110325758832054 & 0.944837120583973 \tabularnewline
158 & 0.0482704122823341 & 0.0965408245646683 & 0.951729587717666 \tabularnewline
159 & 0.0472261086820222 & 0.0944522173640445 & 0.952773891317978 \tabularnewline
160 & 0.0404930281933104 & 0.0809860563866209 & 0.95950697180669 \tabularnewline
161 & 0.0334124305697173 & 0.0668248611394345 & 0.966587569430283 \tabularnewline
162 & 0.0274667952760025 & 0.0549335905520051 & 0.972533204723998 \tabularnewline
163 & 0.0228756533010376 & 0.0457513066020752 & 0.977124346698962 \tabularnewline
164 & 0.0192964132818175 & 0.0385928265636349 & 0.980703586718183 \tabularnewline
165 & 0.0169353563376047 & 0.0338707126752094 & 0.983064643662395 \tabularnewline
166 & 0.0171843050634622 & 0.0343686101269243 & 0.982815694936538 \tabularnewline
167 & 0.0138076243872407 & 0.0276152487744814 & 0.986192375612759 \tabularnewline
168 & 0.0203735861261564 & 0.0407471722523128 & 0.979626413873844 \tabularnewline
169 & 0.0201928859457744 & 0.0403857718915488 & 0.979807114054226 \tabularnewline
170 & 0.0188580171726759 & 0.0377160343453517 & 0.981141982827324 \tabularnewline
171 & 0.0181349653406303 & 0.0362699306812606 & 0.98186503465937 \tabularnewline
172 & 0.0146941965866962 & 0.0293883931733924 & 0.985305803413304 \tabularnewline
173 & 0.0147422907486942 & 0.0294845814973884 & 0.985257709251306 \tabularnewline
174 & 0.0164226161640716 & 0.0328452323281431 & 0.983577383835928 \tabularnewline
175 & 0.0219494596798679 & 0.0438989193597359 & 0.978050540320132 \tabularnewline
176 & 0.0176531523212622 & 0.0353063046425244 & 0.982346847678738 \tabularnewline
177 & 0.0143826922510691 & 0.0287653845021382 & 0.985617307748931 \tabularnewline
178 & 0.011742742838476 & 0.0234854856769521 & 0.988257257161524 \tabularnewline
179 & 0.00919215979401765 & 0.0183843195880353 & 0.990807840205982 \tabularnewline
180 & 0.00800536172863929 & 0.0160107234572786 & 0.991994638271361 \tabularnewline
181 & 0.00660360418668578 & 0.0132072083733716 & 0.993396395813314 \tabularnewline
182 & 0.00534521714955193 & 0.0106904342991039 & 0.994654782850448 \tabularnewline
183 & 0.00560936622575505 & 0.0112187324515101 & 0.994390633774245 \tabularnewline
184 & 0.00443647295033499 & 0.00887294590066997 & 0.995563527049665 \tabularnewline
185 & 0.094086539900982 & 0.188173079801964 & 0.905913460099018 \tabularnewline
186 & 0.0816845811721911 & 0.163369162344382 & 0.918315418827809 \tabularnewline
187 & 0.0928439802674425 & 0.185687960534885 & 0.907156019732557 \tabularnewline
188 & 0.0802127135646733 & 0.160425427129347 & 0.919787286435327 \tabularnewline
189 & 0.0679596339456167 & 0.135919267891233 & 0.932040366054383 \tabularnewline
190 & 0.0563561435032738 & 0.112712287006548 & 0.943643856496726 \tabularnewline
191 & 0.0497111618841623 & 0.0994223237683247 & 0.950288838115838 \tabularnewline
192 & 0.0419611933152222 & 0.0839223866304445 & 0.958038806684778 \tabularnewline
193 & 0.0487155279839555 & 0.097431055967911 & 0.951284472016044 \tabularnewline
194 & 0.0522890666310381 & 0.104578133262076 & 0.947710933368962 \tabularnewline
195 & 0.0443811738269573 & 0.0887623476539145 & 0.955618826173043 \tabularnewline
196 & 0.037026328217237 & 0.0740526564344739 & 0.962973671782763 \tabularnewline
197 & 0.0483157061172395 & 0.0966314122344789 & 0.951684293882761 \tabularnewline
198 & 0.0395862946218528 & 0.0791725892437057 & 0.960413705378147 \tabularnewline
199 & 0.0367011562951475 & 0.073402312590295 & 0.963298843704853 \tabularnewline
200 & 0.0310398676134198 & 0.0620797352268397 & 0.96896013238658 \tabularnewline
201 & 0.0292219724944833 & 0.0584439449889665 & 0.970778027505517 \tabularnewline
202 & 0.0243805707067277 & 0.0487611414134554 & 0.975619429293272 \tabularnewline
203 & 0.0313053691066302 & 0.0626107382132604 & 0.96869463089337 \tabularnewline
204 & 0.0356803177739391 & 0.0713606355478783 & 0.964319682226061 \tabularnewline
205 & 0.0389063363767213 & 0.0778126727534425 & 0.961093663623279 \tabularnewline
206 & 0.030879154542079 & 0.0617583090841579 & 0.969120845457921 \tabularnewline
207 & 0.0303422228248085 & 0.060684445649617 & 0.969657777175192 \tabularnewline
208 & 0.0249498727311462 & 0.0498997454622924 & 0.975050127268854 \tabularnewline
209 & 0.0278681412054705 & 0.055736282410941 & 0.97213185879453 \tabularnewline
210 & 0.0225417426210891 & 0.0450834852421783 & 0.977458257378911 \tabularnewline
211 & 0.0249775332931389 & 0.0499550665862778 & 0.975022466706861 \tabularnewline
212 & 0.0399735087423003 & 0.0799470174846007 & 0.9600264912577 \tabularnewline
213 & 0.0315871062441673 & 0.0631742124883345 & 0.968412893755833 \tabularnewline
214 & 0.0441589425989395 & 0.0883178851978789 & 0.955841057401061 \tabularnewline
215 & 0.0380593092869374 & 0.0761186185738748 & 0.961940690713063 \tabularnewline
216 & 0.0297508259210563 & 0.0595016518421126 & 0.970249174078944 \tabularnewline
217 & 0.0321955312729054 & 0.0643910625458109 & 0.967804468727095 \tabularnewline
218 & 0.0275294909822652 & 0.0550589819645304 & 0.972470509017735 \tabularnewline
219 & 0.0247418070044538 & 0.0494836140089075 & 0.975258192995546 \tabularnewline
220 & 0.0189633773705705 & 0.037926754741141 & 0.981036622629429 \tabularnewline
221 & 0.0168947339209676 & 0.0337894678419351 & 0.983105266079032 \tabularnewline
222 & 0.0124206485849153 & 0.0248412971698306 & 0.987579351415085 \tabularnewline
223 & 0.00931174186201657 & 0.0186234837240331 & 0.990688258137983 \tabularnewline
224 & 0.0075021185439771 & 0.0150042370879542 & 0.992497881456023 \tabularnewline
225 & 0.00654705616129089 & 0.0130941123225818 & 0.993452943838709 \tabularnewline
226 & 0.0149951903144663 & 0.0299903806289325 & 0.985004809685534 \tabularnewline
227 & 0.0115416184372466 & 0.0230832368744931 & 0.988458381562753 \tabularnewline
228 & 0.00835031892340794 & 0.0167006378468159 & 0.991649681076592 \tabularnewline
229 & 0.00609683424321092 & 0.0121936684864218 & 0.993903165756789 \tabularnewline
230 & 0.00441036251732994 & 0.00882072503465989 & 0.99558963748267 \tabularnewline
231 & 0.00439461457994107 & 0.00878922915988213 & 0.995605385420059 \tabularnewline
232 & 0.00814497957146648 & 0.016289959142933 & 0.991855020428533 \tabularnewline
233 & 0.0377565442118785 & 0.075513088423757 & 0.962243455788122 \tabularnewline
234 & 0.0542942200569111 & 0.108588440113822 & 0.945705779943089 \tabularnewline
235 & 0.0405065857547014 & 0.0810131715094027 & 0.959493414245299 \tabularnewline
236 & 0.0361101125951766 & 0.0722202251903532 & 0.963889887404823 \tabularnewline
237 & 0.246505700570201 & 0.493011401140403 & 0.753494299429799 \tabularnewline
238 & 0.200782130963977 & 0.401564261927953 & 0.799217869036023 \tabularnewline
239 & 0.18004440546804 & 0.360088810936079 & 0.81995559453196 \tabularnewline
240 & 0.142128535333137 & 0.284257070666274 & 0.857871464666863 \tabularnewline
241 & 0.113707343103352 & 0.227414686206704 & 0.886292656896648 \tabularnewline
242 & 0.0945301032407296 & 0.189060206481459 & 0.90546989675927 \tabularnewline
243 & 0.0879023187197939 & 0.175804637439588 & 0.912097681280206 \tabularnewline
244 & 0.153550434222245 & 0.307100868444491 & 0.846449565777755 \tabularnewline
245 & 0.137630339717255 & 0.27526067943451 & 0.862369660282745 \tabularnewline
246 & 0.110109330538686 & 0.220218661077371 & 0.889890669461314 \tabularnewline
247 & 0.0777706008222236 & 0.155541201644447 & 0.922229399177776 \tabularnewline
248 & 0.0666948470256243 & 0.133389694051249 & 0.933305152974376 \tabularnewline
249 & 0.0624888270323003 & 0.124977654064601 & 0.9375111729677 \tabularnewline
250 & 0.077380993053961 & 0.154761986107922 & 0.922619006946039 \tabularnewline
251 & 0.0460549764082262 & 0.0921099528164523 & 0.953945023591774 \tabularnewline
252 & 0.112285664162277 & 0.224571328324554 & 0.887714335837723 \tabularnewline
253 & 0.234998511095393 & 0.469997022190785 & 0.765001488904607 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=191274&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]11[/C][C]0.234449524103323[/C][C]0.468899048206647[/C][C]0.765550475896677[/C][/ROW]
[ROW][C]12[/C][C]0.120293517840556[/C][C]0.240587035681113[/C][C]0.879706482159444[/C][/ROW]
[ROW][C]13[/C][C]0.0815541573457813[/C][C]0.163108314691563[/C][C]0.918445842654219[/C][/ROW]
[ROW][C]14[/C][C]0.102874776497916[/C][C]0.205749552995833[/C][C]0.897125223502084[/C][/ROW]
[ROW][C]15[/C][C]0.0587519756515484[/C][C]0.117503951303097[/C][C]0.941248024348452[/C][/ROW]
[ROW][C]16[/C][C]0.0391686675931635[/C][C]0.0783373351863269[/C][C]0.960831332406836[/C][/ROW]
[ROW][C]17[/C][C]0.063019118444172[/C][C]0.126038236888344[/C][C]0.936980881555828[/C][/ROW]
[ROW][C]18[/C][C]0.255864327935305[/C][C]0.511728655870609[/C][C]0.744135672064695[/C][/ROW]
[ROW][C]19[/C][C]0.194216632900149[/C][C]0.388433265800299[/C][C]0.805783367099851[/C][/ROW]
[ROW][C]20[/C][C]0.13776488333464[/C][C]0.275529766669281[/C][C]0.86223511666536[/C][/ROW]
[ROW][C]21[/C][C]0.0986062615513714[/C][C]0.197212523102743[/C][C]0.901393738448629[/C][/ROW]
[ROW][C]22[/C][C]0.0968533990427696[/C][C]0.193706798085539[/C][C]0.90314660095723[/C][/ROW]
[ROW][C]23[/C][C]0.257054377911142[/C][C]0.514108755822284[/C][C]0.742945622088858[/C][/ROW]
[ROW][C]24[/C][C]0.321495418423946[/C][C]0.642990836847893[/C][C]0.678504581576054[/C][/ROW]
[ROW][C]25[/C][C]0.294869538595026[/C][C]0.589739077190051[/C][C]0.705130461404974[/C][/ROW]
[ROW][C]26[/C][C]0.277447857711978[/C][C]0.554895715423955[/C][C]0.722552142288022[/C][/ROW]
[ROW][C]27[/C][C]0.352098888872553[/C][C]0.704197777745105[/C][C]0.647901111127447[/C][/ROW]
[ROW][C]28[/C][C]0.363849648859334[/C][C]0.727699297718668[/C][C]0.636150351140666[/C][/ROW]
[ROW][C]29[/C][C]0.346785592147584[/C][C]0.693571184295169[/C][C]0.653214407852416[/C][/ROW]
[ROW][C]30[/C][C]0.380898386272269[/C][C]0.761796772544538[/C][C]0.619101613727731[/C][/ROW]
[ROW][C]31[/C][C]0.328675803111158[/C][C]0.657351606222317[/C][C]0.671324196888842[/C][/ROW]
[ROW][C]32[/C][C]0.289492867969931[/C][C]0.578985735939863[/C][C]0.710507132030069[/C][/ROW]
[ROW][C]33[/C][C]0.262490777406895[/C][C]0.524981554813791[/C][C]0.737509222593105[/C][/ROW]
[ROW][C]34[/C][C]0.226304417033043[/C][C]0.452608834066086[/C][C]0.773695582966957[/C][/ROW]
[ROW][C]35[/C][C]0.18788054181459[/C][C]0.37576108362918[/C][C]0.81211945818541[/C][/ROW]
[ROW][C]36[/C][C]0.304929814888214[/C][C]0.609859629776428[/C][C]0.695070185111786[/C][/ROW]
[ROW][C]37[/C][C]0.334971074151201[/C][C]0.669942148302402[/C][C]0.665028925848799[/C][/ROW]
[ROW][C]38[/C][C]0.325963622584246[/C][C]0.651927245168491[/C][C]0.674036377415754[/C][/ROW]
[ROW][C]39[/C][C]0.356022739855431[/C][C]0.712045479710862[/C][C]0.643977260144569[/C][/ROW]
[ROW][C]40[/C][C]0.334209449134641[/C][C]0.668418898269283[/C][C]0.665790550865359[/C][/ROW]
[ROW][C]41[/C][C]0.298001365293739[/C][C]0.596002730587479[/C][C]0.701998634706261[/C][/ROW]
[ROW][C]42[/C][C]0.263835728828225[/C][C]0.527671457656451[/C][C]0.736164271171775[/C][/ROW]
[ROW][C]43[/C][C]0.278274265211435[/C][C]0.55654853042287[/C][C]0.721725734788565[/C][/ROW]
[ROW][C]44[/C][C]0.236536521323923[/C][C]0.473073042647846[/C][C]0.763463478676077[/C][/ROW]
[ROW][C]45[/C][C]0.214442280198157[/C][C]0.428884560396314[/C][C]0.785557719801843[/C][/ROW]
[ROW][C]46[/C][C]0.392689717772563[/C][C]0.785379435545127[/C][C]0.607310282227437[/C][/ROW]
[ROW][C]47[/C][C]0.545519033485656[/C][C]0.908961933028687[/C][C]0.454480966514344[/C][/ROW]
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[ROW][C]125[/C][C]0.00693555972924188[/C][C]0.0138711194584838[/C][C]0.993064440270758[/C][/ROW]
[ROW][C]126[/C][C]0.00565042103716446[/C][C]0.0113008420743289[/C][C]0.994349578962835[/C][/ROW]
[ROW][C]127[/C][C]0.0050871640127939[/C][C]0.0101743280255878[/C][C]0.994912835987206[/C][/ROW]
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[ROW][C]130[/C][C]0.00655323802881191[/C][C]0.0131064760576238[/C][C]0.993446761971188[/C][/ROW]
[ROW][C]131[/C][C]0.0135402943899648[/C][C]0.0270805887799297[/C][C]0.986459705610035[/C][/ROW]
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[ROW][C]179[/C][C]0.00919215979401765[/C][C]0.0183843195880353[/C][C]0.990807840205982[/C][/ROW]
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[ROW][C]184[/C][C]0.00443647295033499[/C][C]0.00887294590066997[/C][C]0.995563527049665[/C][/ROW]
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[ROW][C]186[/C][C]0.0816845811721911[/C][C]0.163369162344382[/C][C]0.918315418827809[/C][/ROW]
[ROW][C]187[/C][C]0.0928439802674425[/C][C]0.185687960534885[/C][C]0.907156019732557[/C][/ROW]
[ROW][C]188[/C][C]0.0802127135646733[/C][C]0.160425427129347[/C][C]0.919787286435327[/C][/ROW]
[ROW][C]189[/C][C]0.0679596339456167[/C][C]0.135919267891233[/C][C]0.932040366054383[/C][/ROW]
[ROW][C]190[/C][C]0.0563561435032738[/C][C]0.112712287006548[/C][C]0.943643856496726[/C][/ROW]
[ROW][C]191[/C][C]0.0497111618841623[/C][C]0.0994223237683247[/C][C]0.950288838115838[/C][/ROW]
[ROW][C]192[/C][C]0.0419611933152222[/C][C]0.0839223866304445[/C][C]0.958038806684778[/C][/ROW]
[ROW][C]193[/C][C]0.0487155279839555[/C][C]0.097431055967911[/C][C]0.951284472016044[/C][/ROW]
[ROW][C]194[/C][C]0.0522890666310381[/C][C]0.104578133262076[/C][C]0.947710933368962[/C][/ROW]
[ROW][C]195[/C][C]0.0443811738269573[/C][C]0.0887623476539145[/C][C]0.955618826173043[/C][/ROW]
[ROW][C]196[/C][C]0.037026328217237[/C][C]0.0740526564344739[/C][C]0.962973671782763[/C][/ROW]
[ROW][C]197[/C][C]0.0483157061172395[/C][C]0.0966314122344789[/C][C]0.951684293882761[/C][/ROW]
[ROW][C]198[/C][C]0.0395862946218528[/C][C]0.0791725892437057[/C][C]0.960413705378147[/C][/ROW]
[ROW][C]199[/C][C]0.0367011562951475[/C][C]0.073402312590295[/C][C]0.963298843704853[/C][/ROW]
[ROW][C]200[/C][C]0.0310398676134198[/C][C]0.0620797352268397[/C][C]0.96896013238658[/C][/ROW]
[ROW][C]201[/C][C]0.0292219724944833[/C][C]0.0584439449889665[/C][C]0.970778027505517[/C][/ROW]
[ROW][C]202[/C][C]0.0243805707067277[/C][C]0.0487611414134554[/C][C]0.975619429293272[/C][/ROW]
[ROW][C]203[/C][C]0.0313053691066302[/C][C]0.0626107382132604[/C][C]0.96869463089337[/C][/ROW]
[ROW][C]204[/C][C]0.0356803177739391[/C][C]0.0713606355478783[/C][C]0.964319682226061[/C][/ROW]
[ROW][C]205[/C][C]0.0389063363767213[/C][C]0.0778126727534425[/C][C]0.961093663623279[/C][/ROW]
[ROW][C]206[/C][C]0.030879154542079[/C][C]0.0617583090841579[/C][C]0.969120845457921[/C][/ROW]
[ROW][C]207[/C][C]0.0303422228248085[/C][C]0.060684445649617[/C][C]0.969657777175192[/C][/ROW]
[ROW][C]208[/C][C]0.0249498727311462[/C][C]0.0498997454622924[/C][C]0.975050127268854[/C][/ROW]
[ROW][C]209[/C][C]0.0278681412054705[/C][C]0.055736282410941[/C][C]0.97213185879453[/C][/ROW]
[ROW][C]210[/C][C]0.0225417426210891[/C][C]0.0450834852421783[/C][C]0.977458257378911[/C][/ROW]
[ROW][C]211[/C][C]0.0249775332931389[/C][C]0.0499550665862778[/C][C]0.975022466706861[/C][/ROW]
[ROW][C]212[/C][C]0.0399735087423003[/C][C]0.0799470174846007[/C][C]0.9600264912577[/C][/ROW]
[ROW][C]213[/C][C]0.0315871062441673[/C][C]0.0631742124883345[/C][C]0.968412893755833[/C][/ROW]
[ROW][C]214[/C][C]0.0441589425989395[/C][C]0.0883178851978789[/C][C]0.955841057401061[/C][/ROW]
[ROW][C]215[/C][C]0.0380593092869374[/C][C]0.0761186185738748[/C][C]0.961940690713063[/C][/ROW]
[ROW][C]216[/C][C]0.0297508259210563[/C][C]0.0595016518421126[/C][C]0.970249174078944[/C][/ROW]
[ROW][C]217[/C][C]0.0321955312729054[/C][C]0.0643910625458109[/C][C]0.967804468727095[/C][/ROW]
[ROW][C]218[/C][C]0.0275294909822652[/C][C]0.0550589819645304[/C][C]0.972470509017735[/C][/ROW]
[ROW][C]219[/C][C]0.0247418070044538[/C][C]0.0494836140089075[/C][C]0.975258192995546[/C][/ROW]
[ROW][C]220[/C][C]0.0189633773705705[/C][C]0.037926754741141[/C][C]0.981036622629429[/C][/ROW]
[ROW][C]221[/C][C]0.0168947339209676[/C][C]0.0337894678419351[/C][C]0.983105266079032[/C][/ROW]
[ROW][C]222[/C][C]0.0124206485849153[/C][C]0.0248412971698306[/C][C]0.987579351415085[/C][/ROW]
[ROW][C]223[/C][C]0.00931174186201657[/C][C]0.0186234837240331[/C][C]0.990688258137983[/C][/ROW]
[ROW][C]224[/C][C]0.0075021185439771[/C][C]0.0150042370879542[/C][C]0.992497881456023[/C][/ROW]
[ROW][C]225[/C][C]0.00654705616129089[/C][C]0.0130941123225818[/C][C]0.993452943838709[/C][/ROW]
[ROW][C]226[/C][C]0.0149951903144663[/C][C]0.0299903806289325[/C][C]0.985004809685534[/C][/ROW]
[ROW][C]227[/C][C]0.0115416184372466[/C][C]0.0230832368744931[/C][C]0.988458381562753[/C][/ROW]
[ROW][C]228[/C][C]0.00835031892340794[/C][C]0.0167006378468159[/C][C]0.991649681076592[/C][/ROW]
[ROW][C]229[/C][C]0.00609683424321092[/C][C]0.0121936684864218[/C][C]0.993903165756789[/C][/ROW]
[ROW][C]230[/C][C]0.00441036251732994[/C][C]0.00882072503465989[/C][C]0.99558963748267[/C][/ROW]
[ROW][C]231[/C][C]0.00439461457994107[/C][C]0.00878922915988213[/C][C]0.995605385420059[/C][/ROW]
[ROW][C]232[/C][C]0.00814497957146648[/C][C]0.016289959142933[/C][C]0.991855020428533[/C][/ROW]
[ROW][C]233[/C][C]0.0377565442118785[/C][C]0.075513088423757[/C][C]0.962243455788122[/C][/ROW]
[ROW][C]234[/C][C]0.0542942200569111[/C][C]0.108588440113822[/C][C]0.945705779943089[/C][/ROW]
[ROW][C]235[/C][C]0.0405065857547014[/C][C]0.0810131715094027[/C][C]0.959493414245299[/C][/ROW]
[ROW][C]236[/C][C]0.0361101125951766[/C][C]0.0722202251903532[/C][C]0.963889887404823[/C][/ROW]
[ROW][C]237[/C][C]0.246505700570201[/C][C]0.493011401140403[/C][C]0.753494299429799[/C][/ROW]
[ROW][C]238[/C][C]0.200782130963977[/C][C]0.401564261927953[/C][C]0.799217869036023[/C][/ROW]
[ROW][C]239[/C][C]0.18004440546804[/C][C]0.360088810936079[/C][C]0.81995559453196[/C][/ROW]
[ROW][C]240[/C][C]0.142128535333137[/C][C]0.284257070666274[/C][C]0.857871464666863[/C][/ROW]
[ROW][C]241[/C][C]0.113707343103352[/C][C]0.227414686206704[/C][C]0.886292656896648[/C][/ROW]
[ROW][C]242[/C][C]0.0945301032407296[/C][C]0.189060206481459[/C][C]0.90546989675927[/C][/ROW]
[ROW][C]243[/C][C]0.0879023187197939[/C][C]0.175804637439588[/C][C]0.912097681280206[/C][/ROW]
[ROW][C]244[/C][C]0.153550434222245[/C][C]0.307100868444491[/C][C]0.846449565777755[/C][/ROW]
[ROW][C]245[/C][C]0.137630339717255[/C][C]0.27526067943451[/C][C]0.862369660282745[/C][/ROW]
[ROW][C]246[/C][C]0.110109330538686[/C][C]0.220218661077371[/C][C]0.889890669461314[/C][/ROW]
[ROW][C]247[/C][C]0.0777706008222236[/C][C]0.155541201644447[/C][C]0.922229399177776[/C][/ROW]
[ROW][C]248[/C][C]0.0666948470256243[/C][C]0.133389694051249[/C][C]0.933305152974376[/C][/ROW]
[ROW][C]249[/C][C]0.0624888270323003[/C][C]0.124977654064601[/C][C]0.9375111729677[/C][/ROW]
[ROW][C]250[/C][C]0.077380993053961[/C][C]0.154761986107922[/C][C]0.922619006946039[/C][/ROW]
[ROW][C]251[/C][C]0.0460549764082262[/C][C]0.0921099528164523[/C][C]0.953945023591774[/C][/ROW]
[ROW][C]252[/C][C]0.112285664162277[/C][C]0.224571328324554[/C][C]0.887714335837723[/C][/ROW]
[ROW][C]253[/C][C]0.234998511095393[/C][C]0.469997022190785[/C][C]0.765001488904607[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=191274&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=191274&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
110.2344495241033230.4688990482066470.765550475896677
120.1202935178405560.2405870356811130.879706482159444
130.08155415734578130.1631083146915630.918445842654219
140.1028747764979160.2057495529958330.897125223502084
150.05875197565154840.1175039513030970.941248024348452
160.03916866759316350.07833733518632690.960831332406836
170.0630191184441720.1260382368883440.936980881555828
180.2558643279353050.5117286558706090.744135672064695
190.1942166329001490.3884332658002990.805783367099851
200.137764883334640.2755297666692810.86223511666536
210.09860626155137140.1972125231027430.901393738448629
220.09685339904276960.1937067980855390.90314660095723
230.2570543779111420.5141087558222840.742945622088858
240.3214954184239460.6429908368478930.678504581576054
250.2948695385950260.5897390771900510.705130461404974
260.2774478577119780.5548957154239550.722552142288022
270.3520988888725530.7041977777451050.647901111127447
280.3638496488593340.7276992977186680.636150351140666
290.3467855921475840.6935711842951690.653214407852416
300.3808983862722690.7617967725445380.619101613727731
310.3286758031111580.6573516062223170.671324196888842
320.2894928679699310.5789857359398630.710507132030069
330.2624907774068950.5249815548137910.737509222593105
340.2263044170330430.4526088340660860.773695582966957
350.187880541814590.375761083629180.81211945818541
360.3049298148882140.6098596297764280.695070185111786
370.3349710741512010.6699421483024020.665028925848799
380.3259636225842460.6519272451684910.674036377415754
390.3560227398554310.7120454797108620.643977260144569
400.3342094491346410.6684188982692830.665790550865359
410.2980013652937390.5960027305874790.701998634706261
420.2638357288282250.5276714576564510.736164271171775
430.2782742652114350.556548530422870.721725734788565
440.2365365213239230.4730730426478460.763463478676077
450.2144422801981570.4288845603963140.785557719801843
460.3926897177725630.7853794355451270.607310282227437
470.5455190334856560.9089619330286870.454480966514344
480.4965487764023340.9930975528046680.503451223597666
490.483216160724750.96643232144950.51678383927525
500.4683902306446540.9367804612893080.531609769355346
510.4236717203499130.8473434406998250.576328279650087
520.3781691975725320.7563383951450640.621830802427468
530.3866036095760940.7732072191521880.613396390423906
540.3697095512826040.7394191025652080.630290448717396
550.3609375571723210.7218751143446420.639062442827679
560.3393852385237350.678770477047470.660614761476265
570.2997777542626510.5995555085253020.700222245737349
580.2711577202394340.5423154404788680.728842279760566
590.2366942697965370.4733885395930740.763305730203463
600.2424586147505540.4849172295011070.757541385249446
610.2186501591049540.4373003182099080.781349840895046
620.1917356708049250.383471341609850.808264329195075
630.1637320578437610.3274641156875220.836267942156239
640.1379788888949110.2759577777898220.862021111105089
650.1190738662615420.2381477325230850.880926133738458
660.1102288514213880.2204577028427760.889771148578612
670.1059861502412970.2119723004825940.894013849758703
680.223058679356040.446117358712080.77694132064396
690.3130388526634780.6260777053269560.686961147336522
700.2821425098269240.5642850196538480.717857490173076
710.3979023773212270.7958047546424530.602097622678773
720.3598978352378180.7197956704756360.640102164762182
730.3515646464888880.7031292929777750.648435353511112
740.3361970271152260.6723940542304510.663802972884775
750.3040241548740880.6080483097481750.695975845125912
760.369544725558950.7390894511178990.63045527444105
770.3338177811756470.6676355623512940.666182218824353
780.3129770526536390.6259541053072780.687022947346361
790.3260565689197160.6521131378394330.673943431080284
800.2984783473115490.5969566946230990.701521652688451
810.2703419068908390.5406838137816790.729658093109161
820.2394460425874980.4788920851749960.760553957412502
830.2151396628227070.4302793256454140.784860337177293
840.1879137227384080.3758274454768150.812086277261592
850.1846071916740780.3692143833481560.815392808325922
860.1595725120415980.3191450240831960.840427487958402
870.1403225373613220.2806450747226450.859677462638678
880.1307388017647960.2614776035295910.869261198235204
890.1129764378758930.2259528757517860.887023562124107
900.1102031142192710.2204062284385420.889796885780729
910.09429193694486590.1885838738897320.905708063055134
920.08142409060866170.1628481812173230.918575909391338
930.06916220468658760.1383244093731750.930837795313412
940.07105056196411460.1421011239282290.928949438035885
950.06420477509780920.1284095501956180.935795224902191
960.05379758650354130.1075951730070830.946202413496459
970.05943151463996930.1188630292799390.940568485360031
980.04922705113043850.0984541022608770.950772948869562
990.04036379712394110.08072759424788230.959636202876059
1000.03531497706865580.07062995413731160.964685022931344
1010.03133001394681790.06266002789363580.968669986053182
1020.03688207108464640.07376414216929280.963117928915354
1030.03165139025063740.06330278050127480.968348609749363
1040.02858591411915050.05717182823830090.97141408588085
1050.03381713581376670.06763427162753340.966182864186233
1060.02971708786873120.05943417573746240.970282912131269
1070.02413307862849560.04826615725699110.975866921371504
1080.02400791135008510.04801582270017020.975992088649915
1090.01945150490639090.03890300981278170.980548495093609
1100.01591366614214850.03182733228429690.984086333857851
1110.01261465227192230.02522930454384470.987385347728078
1120.01303812775868250.02607625551736510.986961872241317
1130.01164521464788010.02329042929576020.98835478535212
1140.01672065608724870.03344131217449730.983279343912751
1150.01597102344518570.03194204689037130.984028976554814
1160.0152811978016850.030562395603370.984718802198315
1170.01263902994539410.02527805989078830.987360970054606
1180.01262195624937510.02524391249875020.987378043750625
1190.01026120162714510.02052240325429030.989738798372855
1200.009038025678921090.01807605135784220.990961974321079
1210.007353567803015730.01470713560603150.992646432196984
1220.01131955121710580.02263910243421170.988680448782894
1230.009538495994803650.01907699198960730.990461504005196
1240.008473116391724750.01694623278344950.991526883608275
1250.006935559729241880.01387111945848380.993064440270758
1260.005650421037164460.01130084207432890.994349578962835
1270.00508716401279390.01017432802558780.994912835987206
1280.004098793520274620.008197587040549240.995901206479725
1290.006048869827586880.01209773965517380.993951130172413
1300.006553238028811910.01310647605762380.993446761971188
1310.01354029438996480.02708058877992970.986459705610035
1320.01629872750422860.03259745500845720.983701272495771
1330.01758236498167170.03516472996334340.982417635018328
1340.01698334499195070.03396668998390140.983016655008049
1350.0138803744734780.0277607489469560.986119625526522
1360.01171233869970170.02342467739940330.988287661300298
1370.00937464333820910.01874928667641820.990625356661791
1380.01141690215884620.02283380431769240.988583097841154
1390.009937139879518260.01987427975903650.990062860120482
1400.01129281549976360.02258563099952720.988707184500236
1410.01751656482001360.03503312964002710.982483435179986
1420.01592895790096320.03185791580192640.984071042099037
1430.01268316359323410.02536632718646820.987316836406766
1440.01344583330598330.02689166661196660.986554166694017
1450.02564031348952370.05128062697904730.974359686510476
1460.03141841095330010.06283682190660010.9685815890467
1470.03297957803633510.06595915607267020.967020421963665
1480.02977342271015450.05954684542030910.970226577289845
1490.02481272874093870.04962545748187750.975187271259061
1500.03443623206436750.06887246412873510.965563767935632
1510.02971241893936210.05942483787872420.970287581060638
1520.03128065816490130.06256131632980260.968719341835099
1530.06388043297827720.1277608659565540.936119567021723
1540.06276143572712580.1255228714542520.937238564272874
1550.07217477719129810.1443495543825960.927825222808702
1560.06174785743390260.1234957148678050.938252142566097
1570.05516287941602720.1103257588320540.944837120583973
1580.04827041228233410.09654082456466830.951729587717666
1590.04722610868202220.09445221736404450.952773891317978
1600.04049302819331040.08098605638662090.95950697180669
1610.03341243056971730.06682486113943450.966587569430283
1620.02746679527600250.05493359055200510.972533204723998
1630.02287565330103760.04575130660207520.977124346698962
1640.01929641328181750.03859282656363490.980703586718183
1650.01693535633760470.03387071267520940.983064643662395
1660.01718430506346220.03436861012692430.982815694936538
1670.01380762438724070.02761524877448140.986192375612759
1680.02037358612615640.04074717225231280.979626413873844
1690.02019288594577440.04038577189154880.979807114054226
1700.01885801717267590.03771603434535170.981141982827324
1710.01813496534063030.03626993068126060.98186503465937
1720.01469419658669620.02938839317339240.985305803413304
1730.01474229074869420.02948458149738840.985257709251306
1740.01642261616407160.03284523232814310.983577383835928
1750.02194945967986790.04389891935973590.978050540320132
1760.01765315232126220.03530630464252440.982346847678738
1770.01438269225106910.02876538450213820.985617307748931
1780.0117427428384760.02348548567695210.988257257161524
1790.009192159794017650.01838431958803530.990807840205982
1800.008005361728639290.01601072345727860.991994638271361
1810.006603604186685780.01320720837337160.993396395813314
1820.005345217149551930.01069043429910390.994654782850448
1830.005609366225755050.01121873245151010.994390633774245
1840.004436472950334990.008872945900669970.995563527049665
1850.0940865399009820.1881730798019640.905913460099018
1860.08168458117219110.1633691623443820.918315418827809
1870.09284398026744250.1856879605348850.907156019732557
1880.08021271356467330.1604254271293470.919787286435327
1890.06795963394561670.1359192678912330.932040366054383
1900.05635614350327380.1127122870065480.943643856496726
1910.04971116188416230.09942232376832470.950288838115838
1920.04196119331522220.08392238663044450.958038806684778
1930.04871552798395550.0974310559679110.951284472016044
1940.05228906663103810.1045781332620760.947710933368962
1950.04438117382695730.08876234765391450.955618826173043
1960.0370263282172370.07405265643447390.962973671782763
1970.04831570611723950.09663141223447890.951684293882761
1980.03958629462185280.07917258924370570.960413705378147
1990.03670115629514750.0734023125902950.963298843704853
2000.03103986761341980.06207973522683970.96896013238658
2010.02922197249448330.05844394498896650.970778027505517
2020.02438057070672770.04876114141345540.975619429293272
2030.03130536910663020.06261073821326040.96869463089337
2040.03568031777393910.07136063554787830.964319682226061
2050.03890633637672130.07781267275344250.961093663623279
2060.0308791545420790.06175830908415790.969120845457921
2070.03034222282480850.0606844456496170.969657777175192
2080.02494987273114620.04989974546229240.975050127268854
2090.02786814120547050.0557362824109410.97213185879453
2100.02254174262108910.04508348524217830.977458257378911
2110.02497753329313890.04995506658627780.975022466706861
2120.03997350874230030.07994701748460070.9600264912577
2130.03158710624416730.06317421248833450.968412893755833
2140.04415894259893950.08831788519787890.955841057401061
2150.03805930928693740.07611861857387480.961940690713063
2160.02975082592105630.05950165184211260.970249174078944
2170.03219553127290540.06439106254581090.967804468727095
2180.02752949098226520.05505898196453040.972470509017735
2190.02474180700445380.04948361400890750.975258192995546
2200.01896337737057050.0379267547411410.981036622629429
2210.01689473392096760.03378946784193510.983105266079032
2220.01242064858491530.02484129716983060.987579351415085
2230.009311741862016570.01862348372403310.990688258137983
2240.00750211854397710.01500423708795420.992497881456023
2250.006547056161290890.01309411232258180.993452943838709
2260.01499519031446630.02999038062893250.985004809685534
2270.01154161843724660.02308323687449310.988458381562753
2280.008350318923407940.01670063784681590.991649681076592
2290.006096834243210920.01219366848642180.993903165756789
2300.004410362517329940.008820725034659890.99558963748267
2310.004394614579941070.008789229159882130.995605385420059
2320.008144979571466480.0162899591429330.991855020428533
2330.03775654421187850.0755130884237570.962243455788122
2340.05429422005691110.1085884401138220.945705779943089
2350.04050658575470140.08101317150940270.959493414245299
2360.03611011259517660.07222022519035320.963889887404823
2370.2465057005702010.4930114011404030.753494299429799
2380.2007821309639770.4015642619279530.799217869036023
2390.180044405468040.3600888109360790.81995559453196
2400.1421285353331370.2842570706662740.857871464666863
2410.1137073431033520.2274146862067040.886292656896648
2420.09453010324072960.1890602064814590.90546989675927
2430.08790231871979390.1758046374395880.912097681280206
2440.1535504342222450.3071008684444910.846449565777755
2450.1376303397172550.275260679434510.862369660282745
2460.1101093305386860.2202186610773710.889890669461314
2470.07777060082222360.1555412016444470.922229399177776
2480.06669484702562430.1333896940512490.933305152974376
2490.06248882703230030.1249776540646010.9375111729677
2500.0773809930539610.1547619861079220.922619006946039
2510.04605497640822620.09210995281645230.953945023591774
2520.1122856641622770.2245713283245540.887714335837723
2530.2349985110953930.4699970221907850.765001488904607






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level40.0164609053497942NOK
5% type I error level790.325102880658436NOK
10% type I error level1280.526748971193416NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 4 & 0.0164609053497942 & NOK \tabularnewline
5% type I error level & 79 & 0.325102880658436 & NOK \tabularnewline
10% type I error level & 128 & 0.526748971193416 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=191274&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]4[/C][C]0.0164609053497942[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]79[/C][C]0.325102880658436[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]128[/C][C]0.526748971193416[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=191274&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=191274&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 level40.0164609053497942NOK
5% type I error level790.325102880658436NOK
10% type I error level1280.526748971193416NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 3 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 3 ; 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')
}