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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 18 Nov 2013 09:36:34 -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/2013/Nov/18/t1384785449nbcsy50ryemdm0s.htm/, Retrieved Sat, 27 Apr 2024 11:59:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226099, Retrieved Sat, 27 Apr 2024 11:59:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67

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]
- R P     [Multiple Regression] [hapiness multiple...] [2013-11-18 14:36:34] [b86744663ec671173a5f381479557f00] [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 time19 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 19 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226099&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]19 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226099&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226099&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 time19 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 14.7690790620001 + 0.0127928562711104Connected[t] + 0.010104060712745Separate[t] + 0.11339395385454Learning[t] -0.00716003363092198Software[t] -0.378112751458581Depression[t] + 0.00658166336529928Belonging[t] + 0.0257972235737178Belonging_Final[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  14.7690790620001 +  0.0127928562711104Connected[t] +  0.010104060712745Separate[t] +  0.11339395385454Learning[t] -0.00716003363092198Software[t] -0.378112751458581Depression[t] +  0.00658166336529928Belonging[t] +  0.0257972235737178Belonging_Final[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226099&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  14.7690790620001 +  0.0127928562711104Connected[t] +  0.010104060712745Separate[t] +  0.11339395385454Learning[t] -0.00716003363092198Software[t] -0.378112751458581Depression[t] +  0.00658166336529928Belonging[t] +  0.0257972235737178Belonging_Final[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226099&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226099&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
Happiness[t] = + 14.7690790620001 + 0.0127928562711104Connected[t] + 0.010104060712745Separate[t] + 0.11339395385454Learning[t] -0.00716003363092198Software[t] -0.378112751458581Depression[t] + 0.00658166336529928Belonging[t] + 0.0257972235737178Belonging_Final[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)14.76907906200011.8547017.963100
Connected0.01279285627111040.0374240.34180.7327540.366377
Separate0.0101040607127450.0383220.26370.7922510.396125
Learning0.113393953854540.0666391.70160.090040.04502
Software-0.007160033630921980.068898-0.10390.9173120.458656
Depression-0.3781127514585810.039124-9.664500
Belonging0.006581663365299280.0405880.16220.871310.435655
Belonging_Final0.02579722357371780.0605140.42630.6702440.335122

\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) & 14.7690790620001 & 1.854701 & 7.9631 & 0 & 0 \tabularnewline
Connected & 0.0127928562711104 & 0.037424 & 0.3418 & 0.732754 & 0.366377 \tabularnewline
Separate & 0.010104060712745 & 0.038322 & 0.2637 & 0.792251 & 0.396125 \tabularnewline
Learning & 0.11339395385454 & 0.066639 & 1.7016 & 0.09004 & 0.04502 \tabularnewline
Software & -0.00716003363092198 & 0.068898 & -0.1039 & 0.917312 & 0.458656 \tabularnewline
Depression & -0.378112751458581 & 0.039124 & -9.6645 & 0 & 0 \tabularnewline
Belonging & 0.00658166336529928 & 0.040588 & 0.1622 & 0.87131 & 0.435655 \tabularnewline
Belonging_Final & 0.0257972235737178 & 0.060514 & 0.4263 & 0.670244 & 0.335122 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226099&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]14.7690790620001[/C][C]1.854701[/C][C]7.9631[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Connected[/C][C]0.0127928562711104[/C][C]0.037424[/C][C]0.3418[/C][C]0.732754[/C][C]0.366377[/C][/ROW]
[ROW][C]Separate[/C][C]0.010104060712745[/C][C]0.038322[/C][C]0.2637[/C][C]0.792251[/C][C]0.396125[/C][/ROW]
[ROW][C]Learning[/C][C]0.11339395385454[/C][C]0.066639[/C][C]1.7016[/C][C]0.09004[/C][C]0.04502[/C][/ROW]
[ROW][C]Software[/C][C]-0.00716003363092198[/C][C]0.068898[/C][C]-0.1039[/C][C]0.917312[/C][C]0.458656[/C][/ROW]
[ROW][C]Depression[/C][C]-0.378112751458581[/C][C]0.039124[/C][C]-9.6645[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Belonging[/C][C]0.00658166336529928[/C][C]0.040588[/C][C]0.1622[/C][C]0.87131[/C][C]0.435655[/C][/ROW]
[ROW][C]Belonging_Final[/C][C]0.0257972235737178[/C][C]0.060514[/C][C]0.4263[/C][C]0.670244[/C][C]0.335122[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226099&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226099&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)14.76907906200011.8547017.963100
Connected0.01279285627111040.0374240.34180.7327540.366377
Separate0.0101040607127450.0383220.26370.7922510.396125
Learning0.113393953854540.0666391.70160.090040.04502
Software-0.007160033630921980.068898-0.10390.9173120.458656
Depression-0.3781127514585810.039124-9.664500
Belonging0.006581663365299280.0405880.16220.871310.435655
Belonging_Final0.02579722357371780.0605140.42630.6702440.335122






Multiple Linear Regression - Regression Statistics
Multiple R0.602874977445502
R-squared0.363458238429914
Adjusted R-squared0.346052799636982
F-TEST (value)20.8818773691305
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.02057760945311
Sum Squared Residuals1045.17987221075

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.602874977445502 \tabularnewline
R-squared & 0.363458238429914 \tabularnewline
Adjusted R-squared & 0.346052799636982 \tabularnewline
F-TEST (value) & 20.8818773691305 \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 & 2.02057760945311 \tabularnewline
Sum Squared Residuals & 1045.17987221075 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226099&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.602874977445502[/C][/ROW]
[ROW][C]R-squared[/C][C]0.363458238429914[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.346052799636982[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]20.8818773691305[/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]2.02057760945311[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1045.17987221075[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226099&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226099&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 R0.602874977445502
R-squared0.363458238429914
Adjusted R-squared0.346052799636982
F-TEST (value)20.8818773691305
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.02057760945311
Sum Squared Residuals1045.17987221075






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11413.70272776795470.297272232045301
21815.02956948664882.97043051335124
31113.7778861456376-2.77788614563764
41214.1183453104521-2.11834531045214
51610.81883225787455.18116774212549
61814.10085408891343.89914591108657
71410.63463595683333.36536404316671
81414.7998079561535-0.799807956153545
91514.95164959836220.0483504016377616
101514.06004821102120.939951788978819
111715.31402425414581.68597574585423
121915.48335899808513.51664100191486
131013.1899961470424-3.18999614704239
141613.30063733462892.69936266537112
151815.54412032398392.45587967601612
161413.14373137386430.856268626135726
171413.54318209487140.456817905128638
181715.6341167639891.365883236011
191415.312070670415-1.31207067041502
201613.61855235509942.38144764490065
211815.14743216770432.85256783229566
221113.4963187722649-2.49631877226495
231414.3827246318478-0.382724631847822
241213.4015079038249-1.40150790382488
251715.1813456205421.81865437945801
26915.7875207043101-6.78752070431007
271614.77621370145771.22378629854225
281413.0832837398740.916716260126026
291513.63372646345941.36627353654063
301113.7139687101498-2.71396871014981
311615.48145465395550.518545346044505
321312.27629022911510.723709770884887
331714.86700684180092.13299315819912
341515.0929388093125-0.0929388093124597
351413.66381365715940.336186342840604
361615.17317769383630.826822306163698
37910.3296840468942-1.32968404689425
381514.10387653677630.896123463223747
391715.10175188688871.89824811311127
401315.0494566080889-2.04945660808891
411515.5533509989246-0.553350998924619
421613.37418919835182.62581080164822
431615.92083230372730.0791676962727376
441212.9145599580245-0.914559958024524
451514.43241421417090.567585785829143
461113.3214462406336-2.3214462406336
471515.277774854148-0.277774854147969
481514.67798709180210.32201290819794
491713.24795429382643.75204570617358
501314.5753920406729-1.57539204067294
511615.1042976455590.895702354441048
521413.17676916971590.823230830284093
531111.3498040468665-0.349804046866544
541213.6103701993922-1.61037019939221
551213.670630396643-1.67063039664298
561513.37065304873331.6293469512667
571614.07237375979621.92762624020384
581515.3334328886411-0.333432888641133
591215.0369243923188-3.03692439231882
601213.2013757984478-1.20137579844777
61810.3584699444765-2.35846994447646
621314.4574386450795-1.45743864507953
631114.499187874263-3.49918787426304
641412.87643662073471.12356337926535
651513.53689734611181.46310265388822
661015.0566528144774-5.0566528144774
671112.6140711086649-1.61407110866494
681214.3887997635054-2.38879976350537
691513.42644344662021.57355655337985
701513.56310177784371.43689822215628
711413.35619656921620.643803430783824
721612.59339382529233.40660617470766
731514.39486093672980.60513906327018
741515.3152209886422-0.315220988642161
751314.8887093078901-1.88870930789014
761212.0408339374277-0.0408339374276676
771713.99201909515263.00798090484738
781312.41410078369880.585899216301242
791513.63249773435541.36750226564457
801315.0473106779085-2.04731067790845
811514.83075578691240.169244213087634
821515.5442205325884-0.544220532588382
831614.24322667363251.7567733263675
841514.2157420468290.784257953170964
851414.0509639445364-0.0509639445364413
861513.91137506363781.08862493636224
871414.2634293860804-0.263429386080431
881312.72681162255180.273188377448193
89710.3911827438664-3.39118274386635
901713.57735887673583.42264112326421
911312.90827546941140.0917245305886464
921514.13747297337060.862527026629449
931413.18262492249380.817375077506236
941313.843987895739-0.843987895738979
951614.95421187873991.04578812126011
961212.8308910559861-0.830891055986089
971414.8207196334183-0.820719633418328
981714.92647686444942.07352313555065
991514.96386285155670.0361371484432976
1001715.2129705387951.78702946120496
1011212.9231322238566-0.923132223856566
1021615.12749470113940.872505298860642
1031114.4421460066719-3.44214600667192
1041513.00346146896231.99653853103766
105911.31342124984-2.31342124984001
1061615.00406219488750.995937805112467
1071512.9428020842832.05719791571697
1081012.8538338322187-2.85383383221874
109109.056116829440480.943883170559524
1101513.83210416393191.1678958360681
1111113.1635840551618-2.16358405516181
1121315.2804472041416-2.2804472041416
1131411.76942689167862.2305731083214
1141814.05040282443423.94959717556576
1151615.66590380325570.334096196744314
1161413.00298034345680.997019656543212
1171413.79901720240090.200982797599125
1181415.0748498732362-1.07484987323622
1191413.68684237161530.313157628384654
1201212.4954815232673-0.495481523267275
1211413.55299024985290.447009750147124
1221514.85704481108530.142955188914733
1231516.028205754014-1.02820575401402
1241514.6327728609110.367227139089004
1251314.7791750149129-1.77917501491286
1261716.20693435865280.793065641347152
1271715.41595336300291.58404663699707
1281914.93258582569724.06741417430278
1291513.52572194190741.47427805809258
1301314.6461286145476-1.6461286145476
131910.4098118448911-1.40981184489109
1321515.3239994007746-0.323999400774554
1331512.48758086883122.51241913116883
1341514.26432635742810.73567364257186
1351613.71957284262962.28042715737042
136119.269374386813741.73062561318626
1371413.38437689973170.61562310026829
1381111.8907486546392-0.89074865463915
1391514.15768940521280.842310594787172
1401313.6766608422973-0.676660842297303
1411514.70460220460720.295397795392779
1421613.73812360616932.26187639383065
1431414.7227264674626-0.722726467462602
1441514.28970124054620.710298759453798
1451614.51605353445931.48394646554069
1461614.57459374032391.42540625967605
1471113.4412975987145-2.44129759871449
1481214.7411159736163-2.74111597361633
149911.4328315040723-2.43283150407231
1501614.12242648918281.87757351081724
1511312.59256228140190.407437718598127
1521615.45982294362790.540177056372089
1531214.4538350412152-2.45383504121524
154911.5082538576142-2.50825385761424
1551311.60412708903831.39587291096169
1561312.90827546941140.0917245305886464
1571413.2532987728260.746701227173977
1581914.93258582569724.06741417430278
1591315.7284123715757-2.72841237157567
1601211.90254332208360.0974566779164268
1611312.57562652519760.424373474802354
162109.248677184424880.751322815575121
1631413.18381608227680.816183917723205
1641611.68340089398594.31659910601408
1651012.0045343642407-2.0045343642407
166118.966013619498562.03398638050144
1671414.2093371942062-0.209337194206196
1681212.844250337552-0.844250337552022
169912.7559450301432-3.75594503014321
170911.948837351728-2.948837351728
1711110.55740996165240.44259003834765
1721614.40345957427531.59654042572467
173914.124841636962-5.12484163696203
1741311.22640294979221.77359705020781
1751613.48083446098392.51916553901612
1761315.3996743421093-2.39967434210932
177912.3863256239318-3.38632562393175
1781211.45806512756550.541934872434479
1791614.71232860356561.28767139643442
1801113.2022929489582-2.20229294895816
1811414.3692288651349-0.369228865134884
1821314.8199669923559-1.81996699235593
1831515.0130424176059-0.0130424176058701
1841415.1771987335337-1.17719873353371
1851614.00004189720831.99995810279168
1861311.72172148172931.27827851827073
1871413.72484197986230.275158020137724
1881514.26854087061790.731459129382128
1891312.44315400304910.556845996950947
1901110.22093537660780.779064623392213
1911112.6621984969576-1.66219849695762
1921415.2353279619688-1.23532796196885
1931512.7170587019812.28294129801903
1941112.7421674414267-1.74216744142667
1951513.21968054840821.78031945159178
1961214.299799210674-2.29979921067405
1971411.84120087599132.1587991240087
1981413.56164271372920.438357286270795
199811.2261704969156-3.22617049691562
2001313.8798062733684-0.879806273368417
201912.3456652642706-3.34566526427065
2021513.84381514919481.15618485080522
2031714.11802312348372.88197687651625
2041312.76690728709520.233092712904785
2051514.60233053187780.397669468122225
2061513.92238367964251.07761632035752
2071414.7671578346949-0.767157834694928
2081612.77922722915143.22077277084858
2091313.0410047997657-0.0410047997657329
2101614.47214703411531.52785296588467
211911.8374758449538-2.8374758449538
2121614.77384418920761.22615581079243
2131112.3542830278579-1.35428302785794
2141013.9883733237212-3.98837332372119
2151112.3437976281645-1.34379762816446
2161513.46582408936941.53417591063056
2171715.13547903531921.86452096468082
2181414.4778342061112-0.477834206111224
219810.0118061256161-2.01180612561606
2201513.82624266117191.17375733882815
2211114.0879897141983-3.08798971419825
2221613.7789661920852.22103380791495
2231012.3106029907508-2.31060299075083
2241514.99121752920640.00878247079359853
22599.57096834486942-0.57096834486942
2261614.32530258968371.67469741031625
2271914.05238050048114.94761949951888
2281213.8122538104826-1.81225381048258
22989.54164325711857-1.54164325711857
2301113.5084967240193-2.50849672401933
2311413.97754489002680.0224551099732114
232912.1637820876485-3.16378208764853
2331515.20075334751-0.200753347509997
2341312.80050614308170.199493856918331
2351615.13583001824340.864169981756649
2361112.9949994547665-1.99499945476653
2371211.31830299869890.681697001301126
2381313.1555583007782-0.155558300778199
2391014.605600743986-4.60560074398595
2401113.7009604505846-2.70096045058459
2411214.9065750123026-2.90657501230255
242810.8942297149036-2.89422971490356
2431211.75748745213080.242512547869175
2441212.3978989350542-0.39789893505416
2451513.79832032257661.20167967742343
2461110.77252432914560.227475670854387
2471312.94031008953840.0596899104615737
248148.963570454598595.03642954540141
2491010.2627939512649-0.262793951264882
2501211.60903824375960.390961756240445
2511512.95703023286832.04296976713174
2521311.89631504054571.10368495945431
2531314.3340628665977-1.33406286659775
2541313.9837252749062-0.983725274906177
2551212.019690028785-0.0196900287850413
2561212.924785950028-0.924785950028014
257910.9815997213992-1.98159972139917
258911.6531451794713-2.65314517947131
2591512.80828017855212.19171982144789
2601014.8148782408812-4.81487824088118
2611413.90392487425780.0960751257421976
2621513.71728982899081.2827101710092
26379.93742707142154-2.93742707142154
2641414.0322842464238-0.0322842464238001

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 13.7027277679547 & 0.297272232045301 \tabularnewline
2 & 18 & 15.0295694866488 & 2.97043051335124 \tabularnewline
3 & 11 & 13.7778861456376 & -2.77788614563764 \tabularnewline
4 & 12 & 14.1183453104521 & -2.11834531045214 \tabularnewline
5 & 16 & 10.8188322578745 & 5.18116774212549 \tabularnewline
6 & 18 & 14.1008540889134 & 3.89914591108657 \tabularnewline
7 & 14 & 10.6346359568333 & 3.36536404316671 \tabularnewline
8 & 14 & 14.7998079561535 & -0.799807956153545 \tabularnewline
9 & 15 & 14.9516495983622 & 0.0483504016377616 \tabularnewline
10 & 15 & 14.0600482110212 & 0.939951788978819 \tabularnewline
11 & 17 & 15.3140242541458 & 1.68597574585423 \tabularnewline
12 & 19 & 15.4833589980851 & 3.51664100191486 \tabularnewline
13 & 10 & 13.1899961470424 & -3.18999614704239 \tabularnewline
14 & 16 & 13.3006373346289 & 2.69936266537112 \tabularnewline
15 & 18 & 15.5441203239839 & 2.45587967601612 \tabularnewline
16 & 14 & 13.1437313738643 & 0.856268626135726 \tabularnewline
17 & 14 & 13.5431820948714 & 0.456817905128638 \tabularnewline
18 & 17 & 15.634116763989 & 1.365883236011 \tabularnewline
19 & 14 & 15.312070670415 & -1.31207067041502 \tabularnewline
20 & 16 & 13.6185523550994 & 2.38144764490065 \tabularnewline
21 & 18 & 15.1474321677043 & 2.85256783229566 \tabularnewline
22 & 11 & 13.4963187722649 & -2.49631877226495 \tabularnewline
23 & 14 & 14.3827246318478 & -0.382724631847822 \tabularnewline
24 & 12 & 13.4015079038249 & -1.40150790382488 \tabularnewline
25 & 17 & 15.181345620542 & 1.81865437945801 \tabularnewline
26 & 9 & 15.7875207043101 & -6.78752070431007 \tabularnewline
27 & 16 & 14.7762137014577 & 1.22378629854225 \tabularnewline
28 & 14 & 13.083283739874 & 0.916716260126026 \tabularnewline
29 & 15 & 13.6337264634594 & 1.36627353654063 \tabularnewline
30 & 11 & 13.7139687101498 & -2.71396871014981 \tabularnewline
31 & 16 & 15.4814546539555 & 0.518545346044505 \tabularnewline
32 & 13 & 12.2762902291151 & 0.723709770884887 \tabularnewline
33 & 17 & 14.8670068418009 & 2.13299315819912 \tabularnewline
34 & 15 & 15.0929388093125 & -0.0929388093124597 \tabularnewline
35 & 14 & 13.6638136571594 & 0.336186342840604 \tabularnewline
36 & 16 & 15.1731776938363 & 0.826822306163698 \tabularnewline
37 & 9 & 10.3296840468942 & -1.32968404689425 \tabularnewline
38 & 15 & 14.1038765367763 & 0.896123463223747 \tabularnewline
39 & 17 & 15.1017518868887 & 1.89824811311127 \tabularnewline
40 & 13 & 15.0494566080889 & -2.04945660808891 \tabularnewline
41 & 15 & 15.5533509989246 & -0.553350998924619 \tabularnewline
42 & 16 & 13.3741891983518 & 2.62581080164822 \tabularnewline
43 & 16 & 15.9208323037273 & 0.0791676962727376 \tabularnewline
44 & 12 & 12.9145599580245 & -0.914559958024524 \tabularnewline
45 & 15 & 14.4324142141709 & 0.567585785829143 \tabularnewline
46 & 11 & 13.3214462406336 & -2.3214462406336 \tabularnewline
47 & 15 & 15.277774854148 & -0.277774854147969 \tabularnewline
48 & 15 & 14.6779870918021 & 0.32201290819794 \tabularnewline
49 & 17 & 13.2479542938264 & 3.75204570617358 \tabularnewline
50 & 13 & 14.5753920406729 & -1.57539204067294 \tabularnewline
51 & 16 & 15.104297645559 & 0.895702354441048 \tabularnewline
52 & 14 & 13.1767691697159 & 0.823230830284093 \tabularnewline
53 & 11 & 11.3498040468665 & -0.349804046866544 \tabularnewline
54 & 12 & 13.6103701993922 & -1.61037019939221 \tabularnewline
55 & 12 & 13.670630396643 & -1.67063039664298 \tabularnewline
56 & 15 & 13.3706530487333 & 1.6293469512667 \tabularnewline
57 & 16 & 14.0723737597962 & 1.92762624020384 \tabularnewline
58 & 15 & 15.3334328886411 & -0.333432888641133 \tabularnewline
59 & 12 & 15.0369243923188 & -3.03692439231882 \tabularnewline
60 & 12 & 13.2013757984478 & -1.20137579844777 \tabularnewline
61 & 8 & 10.3584699444765 & -2.35846994447646 \tabularnewline
62 & 13 & 14.4574386450795 & -1.45743864507953 \tabularnewline
63 & 11 & 14.499187874263 & -3.49918787426304 \tabularnewline
64 & 14 & 12.8764366207347 & 1.12356337926535 \tabularnewline
65 & 15 & 13.5368973461118 & 1.46310265388822 \tabularnewline
66 & 10 & 15.0566528144774 & -5.0566528144774 \tabularnewline
67 & 11 & 12.6140711086649 & -1.61407110866494 \tabularnewline
68 & 12 & 14.3887997635054 & -2.38879976350537 \tabularnewline
69 & 15 & 13.4264434466202 & 1.57355655337985 \tabularnewline
70 & 15 & 13.5631017778437 & 1.43689822215628 \tabularnewline
71 & 14 & 13.3561965692162 & 0.643803430783824 \tabularnewline
72 & 16 & 12.5933938252923 & 3.40660617470766 \tabularnewline
73 & 15 & 14.3948609367298 & 0.60513906327018 \tabularnewline
74 & 15 & 15.3152209886422 & -0.315220988642161 \tabularnewline
75 & 13 & 14.8887093078901 & -1.88870930789014 \tabularnewline
76 & 12 & 12.0408339374277 & -0.0408339374276676 \tabularnewline
77 & 17 & 13.9920190951526 & 3.00798090484738 \tabularnewline
78 & 13 & 12.4141007836988 & 0.585899216301242 \tabularnewline
79 & 15 & 13.6324977343554 & 1.36750226564457 \tabularnewline
80 & 13 & 15.0473106779085 & -2.04731067790845 \tabularnewline
81 & 15 & 14.8307557869124 & 0.169244213087634 \tabularnewline
82 & 15 & 15.5442205325884 & -0.544220532588382 \tabularnewline
83 & 16 & 14.2432266736325 & 1.7567733263675 \tabularnewline
84 & 15 & 14.215742046829 & 0.784257953170964 \tabularnewline
85 & 14 & 14.0509639445364 & -0.0509639445364413 \tabularnewline
86 & 15 & 13.9113750636378 & 1.08862493636224 \tabularnewline
87 & 14 & 14.2634293860804 & -0.263429386080431 \tabularnewline
88 & 13 & 12.7268116225518 & 0.273188377448193 \tabularnewline
89 & 7 & 10.3911827438664 & -3.39118274386635 \tabularnewline
90 & 17 & 13.5773588767358 & 3.42264112326421 \tabularnewline
91 & 13 & 12.9082754694114 & 0.0917245305886464 \tabularnewline
92 & 15 & 14.1374729733706 & 0.862527026629449 \tabularnewline
93 & 14 & 13.1826249224938 & 0.817375077506236 \tabularnewline
94 & 13 & 13.843987895739 & -0.843987895738979 \tabularnewline
95 & 16 & 14.9542118787399 & 1.04578812126011 \tabularnewline
96 & 12 & 12.8308910559861 & -0.830891055986089 \tabularnewline
97 & 14 & 14.8207196334183 & -0.820719633418328 \tabularnewline
98 & 17 & 14.9264768644494 & 2.07352313555065 \tabularnewline
99 & 15 & 14.9638628515567 & 0.0361371484432976 \tabularnewline
100 & 17 & 15.212970538795 & 1.78702946120496 \tabularnewline
101 & 12 & 12.9231322238566 & -0.923132223856566 \tabularnewline
102 & 16 & 15.1274947011394 & 0.872505298860642 \tabularnewline
103 & 11 & 14.4421460066719 & -3.44214600667192 \tabularnewline
104 & 15 & 13.0034614689623 & 1.99653853103766 \tabularnewline
105 & 9 & 11.31342124984 & -2.31342124984001 \tabularnewline
106 & 16 & 15.0040621948875 & 0.995937805112467 \tabularnewline
107 & 15 & 12.942802084283 & 2.05719791571697 \tabularnewline
108 & 10 & 12.8538338322187 & -2.85383383221874 \tabularnewline
109 & 10 & 9.05611682944048 & 0.943883170559524 \tabularnewline
110 & 15 & 13.8321041639319 & 1.1678958360681 \tabularnewline
111 & 11 & 13.1635840551618 & -2.16358405516181 \tabularnewline
112 & 13 & 15.2804472041416 & -2.2804472041416 \tabularnewline
113 & 14 & 11.7694268916786 & 2.2305731083214 \tabularnewline
114 & 18 & 14.0504028244342 & 3.94959717556576 \tabularnewline
115 & 16 & 15.6659038032557 & 0.334096196744314 \tabularnewline
116 & 14 & 13.0029803434568 & 0.997019656543212 \tabularnewline
117 & 14 & 13.7990172024009 & 0.200982797599125 \tabularnewline
118 & 14 & 15.0748498732362 & -1.07484987323622 \tabularnewline
119 & 14 & 13.6868423716153 & 0.313157628384654 \tabularnewline
120 & 12 & 12.4954815232673 & -0.495481523267275 \tabularnewline
121 & 14 & 13.5529902498529 & 0.447009750147124 \tabularnewline
122 & 15 & 14.8570448110853 & 0.142955188914733 \tabularnewline
123 & 15 & 16.028205754014 & -1.02820575401402 \tabularnewline
124 & 15 & 14.632772860911 & 0.367227139089004 \tabularnewline
125 & 13 & 14.7791750149129 & -1.77917501491286 \tabularnewline
126 & 17 & 16.2069343586528 & 0.793065641347152 \tabularnewline
127 & 17 & 15.4159533630029 & 1.58404663699707 \tabularnewline
128 & 19 & 14.9325858256972 & 4.06741417430278 \tabularnewline
129 & 15 & 13.5257219419074 & 1.47427805809258 \tabularnewline
130 & 13 & 14.6461286145476 & -1.6461286145476 \tabularnewline
131 & 9 & 10.4098118448911 & -1.40981184489109 \tabularnewline
132 & 15 & 15.3239994007746 & -0.323999400774554 \tabularnewline
133 & 15 & 12.4875808688312 & 2.51241913116883 \tabularnewline
134 & 15 & 14.2643263574281 & 0.73567364257186 \tabularnewline
135 & 16 & 13.7195728426296 & 2.28042715737042 \tabularnewline
136 & 11 & 9.26937438681374 & 1.73062561318626 \tabularnewline
137 & 14 & 13.3843768997317 & 0.61562310026829 \tabularnewline
138 & 11 & 11.8907486546392 & -0.89074865463915 \tabularnewline
139 & 15 & 14.1576894052128 & 0.842310594787172 \tabularnewline
140 & 13 & 13.6766608422973 & -0.676660842297303 \tabularnewline
141 & 15 & 14.7046022046072 & 0.295397795392779 \tabularnewline
142 & 16 & 13.7381236061693 & 2.26187639383065 \tabularnewline
143 & 14 & 14.7227264674626 & -0.722726467462602 \tabularnewline
144 & 15 & 14.2897012405462 & 0.710298759453798 \tabularnewline
145 & 16 & 14.5160535344593 & 1.48394646554069 \tabularnewline
146 & 16 & 14.5745937403239 & 1.42540625967605 \tabularnewline
147 & 11 & 13.4412975987145 & -2.44129759871449 \tabularnewline
148 & 12 & 14.7411159736163 & -2.74111597361633 \tabularnewline
149 & 9 & 11.4328315040723 & -2.43283150407231 \tabularnewline
150 & 16 & 14.1224264891828 & 1.87757351081724 \tabularnewline
151 & 13 & 12.5925622814019 & 0.407437718598127 \tabularnewline
152 & 16 & 15.4598229436279 & 0.540177056372089 \tabularnewline
153 & 12 & 14.4538350412152 & -2.45383504121524 \tabularnewline
154 & 9 & 11.5082538576142 & -2.50825385761424 \tabularnewline
155 & 13 & 11.6041270890383 & 1.39587291096169 \tabularnewline
156 & 13 & 12.9082754694114 & 0.0917245305886464 \tabularnewline
157 & 14 & 13.253298772826 & 0.746701227173977 \tabularnewline
158 & 19 & 14.9325858256972 & 4.06741417430278 \tabularnewline
159 & 13 & 15.7284123715757 & -2.72841237157567 \tabularnewline
160 & 12 & 11.9025433220836 & 0.0974566779164268 \tabularnewline
161 & 13 & 12.5756265251976 & 0.424373474802354 \tabularnewline
162 & 10 & 9.24867718442488 & 0.751322815575121 \tabularnewline
163 & 14 & 13.1838160822768 & 0.816183917723205 \tabularnewline
164 & 16 & 11.6834008939859 & 4.31659910601408 \tabularnewline
165 & 10 & 12.0045343642407 & -2.0045343642407 \tabularnewline
166 & 11 & 8.96601361949856 & 2.03398638050144 \tabularnewline
167 & 14 & 14.2093371942062 & -0.209337194206196 \tabularnewline
168 & 12 & 12.844250337552 & -0.844250337552022 \tabularnewline
169 & 9 & 12.7559450301432 & -3.75594503014321 \tabularnewline
170 & 9 & 11.948837351728 & -2.948837351728 \tabularnewline
171 & 11 & 10.5574099616524 & 0.44259003834765 \tabularnewline
172 & 16 & 14.4034595742753 & 1.59654042572467 \tabularnewline
173 & 9 & 14.124841636962 & -5.12484163696203 \tabularnewline
174 & 13 & 11.2264029497922 & 1.77359705020781 \tabularnewline
175 & 16 & 13.4808344609839 & 2.51916553901612 \tabularnewline
176 & 13 & 15.3996743421093 & -2.39967434210932 \tabularnewline
177 & 9 & 12.3863256239318 & -3.38632562393175 \tabularnewline
178 & 12 & 11.4580651275655 & 0.541934872434479 \tabularnewline
179 & 16 & 14.7123286035656 & 1.28767139643442 \tabularnewline
180 & 11 & 13.2022929489582 & -2.20229294895816 \tabularnewline
181 & 14 & 14.3692288651349 & -0.369228865134884 \tabularnewline
182 & 13 & 14.8199669923559 & -1.81996699235593 \tabularnewline
183 & 15 & 15.0130424176059 & -0.0130424176058701 \tabularnewline
184 & 14 & 15.1771987335337 & -1.17719873353371 \tabularnewline
185 & 16 & 14.0000418972083 & 1.99995810279168 \tabularnewline
186 & 13 & 11.7217214817293 & 1.27827851827073 \tabularnewline
187 & 14 & 13.7248419798623 & 0.275158020137724 \tabularnewline
188 & 15 & 14.2685408706179 & 0.731459129382128 \tabularnewline
189 & 13 & 12.4431540030491 & 0.556845996950947 \tabularnewline
190 & 11 & 10.2209353766078 & 0.779064623392213 \tabularnewline
191 & 11 & 12.6621984969576 & -1.66219849695762 \tabularnewline
192 & 14 & 15.2353279619688 & -1.23532796196885 \tabularnewline
193 & 15 & 12.717058701981 & 2.28294129801903 \tabularnewline
194 & 11 & 12.7421674414267 & -1.74216744142667 \tabularnewline
195 & 15 & 13.2196805484082 & 1.78031945159178 \tabularnewline
196 & 12 & 14.299799210674 & -2.29979921067405 \tabularnewline
197 & 14 & 11.8412008759913 & 2.1587991240087 \tabularnewline
198 & 14 & 13.5616427137292 & 0.438357286270795 \tabularnewline
199 & 8 & 11.2261704969156 & -3.22617049691562 \tabularnewline
200 & 13 & 13.8798062733684 & -0.879806273368417 \tabularnewline
201 & 9 & 12.3456652642706 & -3.34566526427065 \tabularnewline
202 & 15 & 13.8438151491948 & 1.15618485080522 \tabularnewline
203 & 17 & 14.1180231234837 & 2.88197687651625 \tabularnewline
204 & 13 & 12.7669072870952 & 0.233092712904785 \tabularnewline
205 & 15 & 14.6023305318778 & 0.397669468122225 \tabularnewline
206 & 15 & 13.9223836796425 & 1.07761632035752 \tabularnewline
207 & 14 & 14.7671578346949 & -0.767157834694928 \tabularnewline
208 & 16 & 12.7792272291514 & 3.22077277084858 \tabularnewline
209 & 13 & 13.0410047997657 & -0.0410047997657329 \tabularnewline
210 & 16 & 14.4721470341153 & 1.52785296588467 \tabularnewline
211 & 9 & 11.8374758449538 & -2.8374758449538 \tabularnewline
212 & 16 & 14.7738441892076 & 1.22615581079243 \tabularnewline
213 & 11 & 12.3542830278579 & -1.35428302785794 \tabularnewline
214 & 10 & 13.9883733237212 & -3.98837332372119 \tabularnewline
215 & 11 & 12.3437976281645 & -1.34379762816446 \tabularnewline
216 & 15 & 13.4658240893694 & 1.53417591063056 \tabularnewline
217 & 17 & 15.1354790353192 & 1.86452096468082 \tabularnewline
218 & 14 & 14.4778342061112 & -0.477834206111224 \tabularnewline
219 & 8 & 10.0118061256161 & -2.01180612561606 \tabularnewline
220 & 15 & 13.8262426611719 & 1.17375733882815 \tabularnewline
221 & 11 & 14.0879897141983 & -3.08798971419825 \tabularnewline
222 & 16 & 13.778966192085 & 2.22103380791495 \tabularnewline
223 & 10 & 12.3106029907508 & -2.31060299075083 \tabularnewline
224 & 15 & 14.9912175292064 & 0.00878247079359853 \tabularnewline
225 & 9 & 9.57096834486942 & -0.57096834486942 \tabularnewline
226 & 16 & 14.3253025896837 & 1.67469741031625 \tabularnewline
227 & 19 & 14.0523805004811 & 4.94761949951888 \tabularnewline
228 & 12 & 13.8122538104826 & -1.81225381048258 \tabularnewline
229 & 8 & 9.54164325711857 & -1.54164325711857 \tabularnewline
230 & 11 & 13.5084967240193 & -2.50849672401933 \tabularnewline
231 & 14 & 13.9775448900268 & 0.0224551099732114 \tabularnewline
232 & 9 & 12.1637820876485 & -3.16378208764853 \tabularnewline
233 & 15 & 15.20075334751 & -0.200753347509997 \tabularnewline
234 & 13 & 12.8005061430817 & 0.199493856918331 \tabularnewline
235 & 16 & 15.1358300182434 & 0.864169981756649 \tabularnewline
236 & 11 & 12.9949994547665 & -1.99499945476653 \tabularnewline
237 & 12 & 11.3183029986989 & 0.681697001301126 \tabularnewline
238 & 13 & 13.1555583007782 & -0.155558300778199 \tabularnewline
239 & 10 & 14.605600743986 & -4.60560074398595 \tabularnewline
240 & 11 & 13.7009604505846 & -2.70096045058459 \tabularnewline
241 & 12 & 14.9065750123026 & -2.90657501230255 \tabularnewline
242 & 8 & 10.8942297149036 & -2.89422971490356 \tabularnewline
243 & 12 & 11.7574874521308 & 0.242512547869175 \tabularnewline
244 & 12 & 12.3978989350542 & -0.39789893505416 \tabularnewline
245 & 15 & 13.7983203225766 & 1.20167967742343 \tabularnewline
246 & 11 & 10.7725243291456 & 0.227475670854387 \tabularnewline
247 & 13 & 12.9403100895384 & 0.0596899104615737 \tabularnewline
248 & 14 & 8.96357045459859 & 5.03642954540141 \tabularnewline
249 & 10 & 10.2627939512649 & -0.262793951264882 \tabularnewline
250 & 12 & 11.6090382437596 & 0.390961756240445 \tabularnewline
251 & 15 & 12.9570302328683 & 2.04296976713174 \tabularnewline
252 & 13 & 11.8963150405457 & 1.10368495945431 \tabularnewline
253 & 13 & 14.3340628665977 & -1.33406286659775 \tabularnewline
254 & 13 & 13.9837252749062 & -0.983725274906177 \tabularnewline
255 & 12 & 12.019690028785 & -0.0196900287850413 \tabularnewline
256 & 12 & 12.924785950028 & -0.924785950028014 \tabularnewline
257 & 9 & 10.9815997213992 & -1.98159972139917 \tabularnewline
258 & 9 & 11.6531451794713 & -2.65314517947131 \tabularnewline
259 & 15 & 12.8082801785521 & 2.19171982144789 \tabularnewline
260 & 10 & 14.8148782408812 & -4.81487824088118 \tabularnewline
261 & 14 & 13.9039248742578 & 0.0960751257421976 \tabularnewline
262 & 15 & 13.7172898289908 & 1.2827101710092 \tabularnewline
263 & 7 & 9.93742707142154 & -2.93742707142154 \tabularnewline
264 & 14 & 14.0322842464238 & -0.0322842464238001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226099&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]14[/C][C]13.7027277679547[/C][C]0.297272232045301[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]15.0295694866488[/C][C]2.97043051335124[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]13.7778861456376[/C][C]-2.77788614563764[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.1183453104521[/C][C]-2.11834531045214[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]10.8188322578745[/C][C]5.18116774212549[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.1008540889134[/C][C]3.89914591108657[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.6346359568333[/C][C]3.36536404316671[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]14.7998079561535[/C][C]-0.799807956153545[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]14.9516495983622[/C][C]0.0483504016377616[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.0600482110212[/C][C]0.939951788978819[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.3140242541458[/C][C]1.68597574585423[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.4833589980851[/C][C]3.51664100191486[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.1899961470424[/C][C]-3.18999614704239[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.3006373346289[/C][C]2.69936266537112[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.5441203239839[/C][C]2.45587967601612[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.1437313738643[/C][C]0.856268626135726[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.5431820948714[/C][C]0.456817905128638[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.634116763989[/C][C]1.365883236011[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.312070670415[/C][C]-1.31207067041502[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.6185523550994[/C][C]2.38144764490065[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.1474321677043[/C][C]2.85256783229566[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.4963187722649[/C][C]-2.49631877226495[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.3827246318478[/C][C]-0.382724631847822[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.4015079038249[/C][C]-1.40150790382488[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.181345620542[/C][C]1.81865437945801[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.7875207043101[/C][C]-6.78752070431007[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.7762137014577[/C][C]1.22378629854225[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.083283739874[/C][C]0.916716260126026[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]13.6337264634594[/C][C]1.36627353654063[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]13.7139687101498[/C][C]-2.71396871014981[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.4814546539555[/C][C]0.518545346044505[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.2762902291151[/C][C]0.723709770884887[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]14.8670068418009[/C][C]2.13299315819912[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.0929388093125[/C][C]-0.0929388093124597[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]13.6638136571594[/C][C]0.336186342840604[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.1731776938363[/C][C]0.826822306163698[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.3296840468942[/C][C]-1.32968404689425[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.1038765367763[/C][C]0.896123463223747[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.1017518868887[/C][C]1.89824811311127[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.0494566080889[/C][C]-2.04945660808891[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.5533509989246[/C][C]-0.553350998924619[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.3741891983518[/C][C]2.62581080164822[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]15.9208323037273[/C][C]0.0791676962727376[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]12.9145599580245[/C][C]-0.914559958024524[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.4324142141709[/C][C]0.567585785829143[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.3214462406336[/C][C]-2.3214462406336[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.277774854148[/C][C]-0.277774854147969[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.6779870918021[/C][C]0.32201290819794[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.2479542938264[/C][C]3.75204570617358[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.5753920406729[/C][C]-1.57539204067294[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.104297645559[/C][C]0.895702354441048[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.1767691697159[/C][C]0.823230830284093[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.3498040468665[/C][C]-0.349804046866544[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.6103701993922[/C][C]-1.61037019939221[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]13.670630396643[/C][C]-1.67063039664298[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.3706530487333[/C][C]1.6293469512667[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.0723737597962[/C][C]1.92762624020384[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.3334328886411[/C][C]-0.333432888641133[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.0369243923188[/C][C]-3.03692439231882[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.2013757984478[/C][C]-1.20137579844777[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.3584699444765[/C][C]-2.35846994447646[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.4574386450795[/C][C]-1.45743864507953[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.499187874263[/C][C]-3.49918787426304[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]12.8764366207347[/C][C]1.12356337926535[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.5368973461118[/C][C]1.46310265388822[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]15.0566528144774[/C][C]-5.0566528144774[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.6140711086649[/C][C]-1.61407110866494[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.3887997635054[/C][C]-2.38879976350537[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.4264434466202[/C][C]1.57355655337985[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.5631017778437[/C][C]1.43689822215628[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.3561965692162[/C][C]0.643803430783824[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.5933938252923[/C][C]3.40660617470766[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.3948609367298[/C][C]0.60513906327018[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.3152209886422[/C][C]-0.315220988642161[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.8887093078901[/C][C]-1.88870930789014[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]12.0408339374277[/C][C]-0.0408339374276676[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]13.9920190951526[/C][C]3.00798090484738[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.4141007836988[/C][C]0.585899216301242[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.6324977343554[/C][C]1.36750226564457[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]15.0473106779085[/C][C]-2.04731067790845[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.8307557869124[/C][C]0.169244213087634[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.5442205325884[/C][C]-0.544220532588382[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.2432266736325[/C][C]1.7567733263675[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.215742046829[/C][C]0.784257953170964[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.0509639445364[/C][C]-0.0509639445364413[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.9113750636378[/C][C]1.08862493636224[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.2634293860804[/C][C]-0.263429386080431[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.7268116225518[/C][C]0.273188377448193[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.3911827438664[/C][C]-3.39118274386635[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.5773588767358[/C][C]3.42264112326421[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]12.9082754694114[/C][C]0.0917245305886464[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.1374729733706[/C][C]0.862527026629449[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.1826249224938[/C][C]0.817375077506236[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.843987895739[/C][C]-0.843987895738979[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.9542118787399[/C][C]1.04578812126011[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.8308910559861[/C][C]-0.830891055986089[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.8207196334183[/C][C]-0.820719633418328[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.9264768644494[/C][C]2.07352313555065[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]14.9638628515567[/C][C]0.0361371484432976[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.212970538795[/C][C]1.78702946120496[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]12.9231322238566[/C][C]-0.923132223856566[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]15.1274947011394[/C][C]0.872505298860642[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.4421460066719[/C][C]-3.44214600667192[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]13.0034614689623[/C][C]1.99653853103766[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.31342124984[/C][C]-2.31342124984001[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]15.0040621948875[/C][C]0.995937805112467[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.942802084283[/C][C]2.05719791571697[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.8538338322187[/C][C]-2.85383383221874[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.05611682944048[/C][C]0.943883170559524[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.8321041639319[/C][C]1.1678958360681[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.1635840551618[/C][C]-2.16358405516181[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.2804472041416[/C][C]-2.2804472041416[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]11.7694268916786[/C][C]2.2305731083214[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.0504028244342[/C][C]3.94959717556576[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.6659038032557[/C][C]0.334096196744314[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.0029803434568[/C][C]0.997019656543212[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.7990172024009[/C][C]0.200982797599125[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.0748498732362[/C][C]-1.07484987323622[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.6868423716153[/C][C]0.313157628384654[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.4954815232673[/C][C]-0.495481523267275[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.5529902498529[/C][C]0.447009750147124[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.8570448110853[/C][C]0.142955188914733[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]16.028205754014[/C][C]-1.02820575401402[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.632772860911[/C][C]0.367227139089004[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.7791750149129[/C][C]-1.77917501491286[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.2069343586528[/C][C]0.793065641347152[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.4159533630029[/C][C]1.58404663699707[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.9325858256972[/C][C]4.06741417430278[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.5257219419074[/C][C]1.47427805809258[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.6461286145476[/C][C]-1.6461286145476[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.4098118448911[/C][C]-1.40981184489109[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.3239994007746[/C][C]-0.323999400774554[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.4875808688312[/C][C]2.51241913116883[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.2643263574281[/C][C]0.73567364257186[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.7195728426296[/C][C]2.28042715737042[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.26937438681374[/C][C]1.73062561318626[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.3843768997317[/C][C]0.61562310026829[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]11.8907486546392[/C][C]-0.89074865463915[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.1576894052128[/C][C]0.842310594787172[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.6766608422973[/C][C]-0.676660842297303[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.7046022046072[/C][C]0.295397795392779[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.7381236061693[/C][C]2.26187639383065[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.7227264674626[/C][C]-0.722726467462602[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.2897012405462[/C][C]0.710298759453798[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.5160535344593[/C][C]1.48394646554069[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.5745937403239[/C][C]1.42540625967605[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.4412975987145[/C][C]-2.44129759871449[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.7411159736163[/C][C]-2.74111597361633[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.4328315040723[/C][C]-2.43283150407231[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]14.1224264891828[/C][C]1.87757351081724[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.5925622814019[/C][C]0.407437718598127[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.4598229436279[/C][C]0.540177056372089[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.4538350412152[/C][C]-2.45383504121524[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.5082538576142[/C][C]-2.50825385761424[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.6041270890383[/C][C]1.39587291096169[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.9082754694114[/C][C]0.0917245305886464[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.253298772826[/C][C]0.746701227173977[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.9325858256972[/C][C]4.06741417430278[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.7284123715757[/C][C]-2.72841237157567[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]11.9025433220836[/C][C]0.0974566779164268[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.5756265251976[/C][C]0.424373474802354[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.24867718442488[/C][C]0.751322815575121[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.1838160822768[/C][C]0.816183917723205[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.6834008939859[/C][C]4.31659910601408[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]12.0045343642407[/C][C]-2.0045343642407[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]8.96601361949856[/C][C]2.03398638050144[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.2093371942062[/C][C]-0.209337194206196[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]12.844250337552[/C][C]-0.844250337552022[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.7559450301432[/C][C]-3.75594503014321[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.948837351728[/C][C]-2.948837351728[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.5574099616524[/C][C]0.44259003834765[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.4034595742753[/C][C]1.59654042572467[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]14.124841636962[/C][C]-5.12484163696203[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.2264029497922[/C][C]1.77359705020781[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.4808344609839[/C][C]2.51916553901612[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.3996743421093[/C][C]-2.39967434210932[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.3863256239318[/C][C]-3.38632562393175[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.4580651275655[/C][C]0.541934872434479[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.7123286035656[/C][C]1.28767139643442[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.2022929489582[/C][C]-2.20229294895816[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]14.3692288651349[/C][C]-0.369228865134884[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.8199669923559[/C][C]-1.81996699235593[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]15.0130424176059[/C][C]-0.0130424176058701[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]15.1771987335337[/C][C]-1.17719873353371[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]14.0000418972083[/C][C]1.99995810279168[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.7217214817293[/C][C]1.27827851827073[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.7248419798623[/C][C]0.275158020137724[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.2685408706179[/C][C]0.731459129382128[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.4431540030491[/C][C]0.556845996950947[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.2209353766078[/C][C]0.779064623392213[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]12.6621984969576[/C][C]-1.66219849695762[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]15.2353279619688[/C][C]-1.23532796196885[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.717058701981[/C][C]2.28294129801903[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.7421674414267[/C][C]-1.74216744142667[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]13.2196805484082[/C][C]1.78031945159178[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.299799210674[/C][C]-2.29979921067405[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.8412008759913[/C][C]2.1587991240087[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.5616427137292[/C][C]0.438357286270795[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.2261704969156[/C][C]-3.22617049691562[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.8798062733684[/C][C]-0.879806273368417[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]12.3456652642706[/C][C]-3.34566526427065[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.8438151491948[/C][C]1.15618485080522[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]14.1180231234837[/C][C]2.88197687651625[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.7669072870952[/C][C]0.233092712904785[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.6023305318778[/C][C]0.397669468122225[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.9223836796425[/C][C]1.07761632035752[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.7671578346949[/C][C]-0.767157834694928[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.7792272291514[/C][C]3.22077277084858[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]13.0410047997657[/C][C]-0.0410047997657329[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.4721470341153[/C][C]1.52785296588467[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.8374758449538[/C][C]-2.8374758449538[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.7738441892076[/C][C]1.22615581079243[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.3542830278579[/C][C]-1.35428302785794[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.9883733237212[/C][C]-3.98837332372119[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]12.3437976281645[/C][C]-1.34379762816446[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.4658240893694[/C][C]1.53417591063056[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]15.1354790353192[/C][C]1.86452096468082[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.4778342061112[/C][C]-0.477834206111224[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]10.0118061256161[/C][C]-2.01180612561606[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.8262426611719[/C][C]1.17375733882815[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]14.0879897141983[/C][C]-3.08798971419825[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]13.778966192085[/C][C]2.22103380791495[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]12.3106029907508[/C][C]-2.31060299075083[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]14.9912175292064[/C][C]0.00878247079359853[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.57096834486942[/C][C]-0.57096834486942[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.3253025896837[/C][C]1.67469741031625[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]14.0523805004811[/C][C]4.94761949951888[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.8122538104826[/C][C]-1.81225381048258[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.54164325711857[/C][C]-1.54164325711857[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.5084967240193[/C][C]-2.50849672401933[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.9775448900268[/C][C]0.0224551099732114[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]12.1637820876485[/C][C]-3.16378208764853[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]15.20075334751[/C][C]-0.200753347509997[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.8005061430817[/C][C]0.199493856918331[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]15.1358300182434[/C][C]0.864169981756649[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.9949994547665[/C][C]-1.99499945476653[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.3183029986989[/C][C]0.681697001301126[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13.1555583007782[/C][C]-0.155558300778199[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.605600743986[/C][C]-4.60560074398595[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.7009604505846[/C][C]-2.70096045058459[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.9065750123026[/C][C]-2.90657501230255[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.8942297149036[/C][C]-2.89422971490356[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.7574874521308[/C][C]0.242512547869175[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.3978989350542[/C][C]-0.39789893505416[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.7983203225766[/C][C]1.20167967742343[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.7725243291456[/C][C]0.227475670854387[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.9403100895384[/C][C]0.0596899104615737[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]8.96357045459859[/C][C]5.03642954540141[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]10.2627939512649[/C][C]-0.262793951264882[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.6090382437596[/C][C]0.390961756240445[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.9570302328683[/C][C]2.04296976713174[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.8963150405457[/C][C]1.10368495945431[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.3340628665977[/C][C]-1.33406286659775[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.9837252749062[/C][C]-0.983725274906177[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]12.019690028785[/C][C]-0.0196900287850413[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.924785950028[/C][C]-0.924785950028014[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.9815997213992[/C][C]-1.98159972139917[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.6531451794713[/C][C]-2.65314517947131[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.8082801785521[/C][C]2.19171982144789[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.8148782408812[/C][C]-4.81487824088118[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.9039248742578[/C][C]0.0960751257421976[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.7172898289908[/C][C]1.2827101710092[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.93742707142154[/C][C]-2.93742707142154[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]14.0322842464238[/C][C]-0.0322842464238001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226099&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226099&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
11413.70272776795470.297272232045301
21815.02956948664882.97043051335124
31113.7778861456376-2.77788614563764
41214.1183453104521-2.11834531045214
51610.81883225787455.18116774212549
61814.10085408891343.89914591108657
71410.63463595683333.36536404316671
81414.7998079561535-0.799807956153545
91514.95164959836220.0483504016377616
101514.06004821102120.939951788978819
111715.31402425414581.68597574585423
121915.48335899808513.51664100191486
131013.1899961470424-3.18999614704239
141613.30063733462892.69936266537112
151815.54412032398392.45587967601612
161413.14373137386430.856268626135726
171413.54318209487140.456817905128638
181715.6341167639891.365883236011
191415.312070670415-1.31207067041502
201613.61855235509942.38144764490065
211815.14743216770432.85256783229566
221113.4963187722649-2.49631877226495
231414.3827246318478-0.382724631847822
241213.4015079038249-1.40150790382488
251715.1813456205421.81865437945801
26915.7875207043101-6.78752070431007
271614.77621370145771.22378629854225
281413.0832837398740.916716260126026
291513.63372646345941.36627353654063
301113.7139687101498-2.71396871014981
311615.48145465395550.518545346044505
321312.27629022911510.723709770884887
331714.86700684180092.13299315819912
341515.0929388093125-0.0929388093124597
351413.66381365715940.336186342840604
361615.17317769383630.826822306163698
37910.3296840468942-1.32968404689425
381514.10387653677630.896123463223747
391715.10175188688871.89824811311127
401315.0494566080889-2.04945660808891
411515.5533509989246-0.553350998924619
421613.37418919835182.62581080164822
431615.92083230372730.0791676962727376
441212.9145599580245-0.914559958024524
451514.43241421417090.567585785829143
461113.3214462406336-2.3214462406336
471515.277774854148-0.277774854147969
481514.67798709180210.32201290819794
491713.24795429382643.75204570617358
501314.5753920406729-1.57539204067294
511615.1042976455590.895702354441048
521413.17676916971590.823230830284093
531111.3498040468665-0.349804046866544
541213.6103701993922-1.61037019939221
551213.670630396643-1.67063039664298
561513.37065304873331.6293469512667
571614.07237375979621.92762624020384
581515.3334328886411-0.333432888641133
591215.0369243923188-3.03692439231882
601213.2013757984478-1.20137579844777
61810.3584699444765-2.35846994447646
621314.4574386450795-1.45743864507953
631114.499187874263-3.49918787426304
641412.87643662073471.12356337926535
651513.53689734611181.46310265388822
661015.0566528144774-5.0566528144774
671112.6140711086649-1.61407110866494
681214.3887997635054-2.38879976350537
691513.42644344662021.57355655337985
701513.56310177784371.43689822215628
711413.35619656921620.643803430783824
721612.59339382529233.40660617470766
731514.39486093672980.60513906327018
741515.3152209886422-0.315220988642161
751314.8887093078901-1.88870930789014
761212.0408339374277-0.0408339374276676
771713.99201909515263.00798090484738
781312.41410078369880.585899216301242
791513.63249773435541.36750226564457
801315.0473106779085-2.04731067790845
811514.83075578691240.169244213087634
821515.5442205325884-0.544220532588382
831614.24322667363251.7567733263675
841514.2157420468290.784257953170964
851414.0509639445364-0.0509639445364413
861513.91137506363781.08862493636224
871414.2634293860804-0.263429386080431
881312.72681162255180.273188377448193
89710.3911827438664-3.39118274386635
901713.57735887673583.42264112326421
911312.90827546941140.0917245305886464
921514.13747297337060.862527026629449
931413.18262492249380.817375077506236
941313.843987895739-0.843987895738979
951614.95421187873991.04578812126011
961212.8308910559861-0.830891055986089
971414.8207196334183-0.820719633418328
981714.92647686444942.07352313555065
991514.96386285155670.0361371484432976
1001715.2129705387951.78702946120496
1011212.9231322238566-0.923132223856566
1021615.12749470113940.872505298860642
1031114.4421460066719-3.44214600667192
1041513.00346146896231.99653853103766
105911.31342124984-2.31342124984001
1061615.00406219488750.995937805112467
1071512.9428020842832.05719791571697
1081012.8538338322187-2.85383383221874
109109.056116829440480.943883170559524
1101513.83210416393191.1678958360681
1111113.1635840551618-2.16358405516181
1121315.2804472041416-2.2804472041416
1131411.76942689167862.2305731083214
1141814.05040282443423.94959717556576
1151615.66590380325570.334096196744314
1161413.00298034345680.997019656543212
1171413.79901720240090.200982797599125
1181415.0748498732362-1.07484987323622
1191413.68684237161530.313157628384654
1201212.4954815232673-0.495481523267275
1211413.55299024985290.447009750147124
1221514.85704481108530.142955188914733
1231516.028205754014-1.02820575401402
1241514.6327728609110.367227139089004
1251314.7791750149129-1.77917501491286
1261716.20693435865280.793065641347152
1271715.41595336300291.58404663699707
1281914.93258582569724.06741417430278
1291513.52572194190741.47427805809258
1301314.6461286145476-1.6461286145476
131910.4098118448911-1.40981184489109
1321515.3239994007746-0.323999400774554
1331512.48758086883122.51241913116883
1341514.26432635742810.73567364257186
1351613.71957284262962.28042715737042
136119.269374386813741.73062561318626
1371413.38437689973170.61562310026829
1381111.8907486546392-0.89074865463915
1391514.15768940521280.842310594787172
1401313.6766608422973-0.676660842297303
1411514.70460220460720.295397795392779
1421613.73812360616932.26187639383065
1431414.7227264674626-0.722726467462602
1441514.28970124054620.710298759453798
1451614.51605353445931.48394646554069
1461614.57459374032391.42540625967605
1471113.4412975987145-2.44129759871449
1481214.7411159736163-2.74111597361633
149911.4328315040723-2.43283150407231
1501614.12242648918281.87757351081724
1511312.59256228140190.407437718598127
1521615.45982294362790.540177056372089
1531214.4538350412152-2.45383504121524
154911.5082538576142-2.50825385761424
1551311.60412708903831.39587291096169
1561312.90827546941140.0917245305886464
1571413.2532987728260.746701227173977
1581914.93258582569724.06741417430278
1591315.7284123715757-2.72841237157567
1601211.90254332208360.0974566779164268
1611312.57562652519760.424373474802354
162109.248677184424880.751322815575121
1631413.18381608227680.816183917723205
1641611.68340089398594.31659910601408
1651012.0045343642407-2.0045343642407
166118.966013619498562.03398638050144
1671414.2093371942062-0.209337194206196
1681212.844250337552-0.844250337552022
169912.7559450301432-3.75594503014321
170911.948837351728-2.948837351728
1711110.55740996165240.44259003834765
1721614.40345957427531.59654042572467
173914.124841636962-5.12484163696203
1741311.22640294979221.77359705020781
1751613.48083446098392.51916553901612
1761315.3996743421093-2.39967434210932
177912.3863256239318-3.38632562393175
1781211.45806512756550.541934872434479
1791614.71232860356561.28767139643442
1801113.2022929489582-2.20229294895816
1811414.3692288651349-0.369228865134884
1821314.8199669923559-1.81996699235593
1831515.0130424176059-0.0130424176058701
1841415.1771987335337-1.17719873353371
1851614.00004189720831.99995810279168
1861311.72172148172931.27827851827073
1871413.72484197986230.275158020137724
1881514.26854087061790.731459129382128
1891312.44315400304910.556845996950947
1901110.22093537660780.779064623392213
1911112.6621984969576-1.66219849695762
1921415.2353279619688-1.23532796196885
1931512.7170587019812.28294129801903
1941112.7421674414267-1.74216744142667
1951513.21968054840821.78031945159178
1961214.299799210674-2.29979921067405
1971411.84120087599132.1587991240087
1981413.56164271372920.438357286270795
199811.2261704969156-3.22617049691562
2001313.8798062733684-0.879806273368417
201912.3456652642706-3.34566526427065
2021513.84381514919481.15618485080522
2031714.11802312348372.88197687651625
2041312.76690728709520.233092712904785
2051514.60233053187780.397669468122225
2061513.92238367964251.07761632035752
2071414.7671578346949-0.767157834694928
2081612.77922722915143.22077277084858
2091313.0410047997657-0.0410047997657329
2101614.47214703411531.52785296588467
211911.8374758449538-2.8374758449538
2121614.77384418920761.22615581079243
2131112.3542830278579-1.35428302785794
2141013.9883733237212-3.98837332372119
2151112.3437976281645-1.34379762816446
2161513.46582408936941.53417591063056
2171715.13547903531921.86452096468082
2181414.4778342061112-0.477834206111224
219810.0118061256161-2.01180612561606
2201513.82624266117191.17375733882815
2211114.0879897141983-3.08798971419825
2221613.7789661920852.22103380791495
2231012.3106029907508-2.31060299075083
2241514.99121752920640.00878247079359853
22599.57096834486942-0.57096834486942
2261614.32530258968371.67469741031625
2271914.05238050048114.94761949951888
2281213.8122538104826-1.81225381048258
22989.54164325711857-1.54164325711857
2301113.5084967240193-2.50849672401933
2311413.97754489002680.0224551099732114
232912.1637820876485-3.16378208764853
2331515.20075334751-0.200753347509997
2341312.80050614308170.199493856918331
2351615.13583001824340.864169981756649
2361112.9949994547665-1.99499945476653
2371211.31830299869890.681697001301126
2381313.1555583007782-0.155558300778199
2391014.605600743986-4.60560074398595
2401113.7009604505846-2.70096045058459
2411214.9065750123026-2.90657501230255
242810.8942297149036-2.89422971490356
2431211.75748745213080.242512547869175
2441212.3978989350542-0.39789893505416
2451513.79832032257661.20167967742343
2461110.77252432914560.227475670854387
2471312.94031008953840.0596899104615737
248148.963570454598595.03642954540141
2491010.2627939512649-0.262793951264882
2501211.60903824375960.390961756240445
2511512.95703023286832.04296976713174
2521311.89631504054571.10368495945431
2531314.3340628665977-1.33406286659775
2541313.9837252749062-0.983725274906177
2551212.019690028785-0.0196900287850413
2561212.924785950028-0.924785950028014
257910.9815997213992-1.98159972139917
258911.6531451794713-2.65314517947131
2591512.80828017855212.19171982144789
2601014.8148782408812-4.81487824088118
2611413.90392487425780.0960751257421976
2621513.71728982899081.2827101710092
26379.93742707142154-2.93742707142154
2641414.0322842464238-0.0322842464238001






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.02376387491264080.04752774982528160.976236125087359
120.7080316718777070.5839366562445870.291968328122293
130.963511916928360.07297616614327980.0364880830716399
140.9378686851629420.1242626296741150.0621313148370576
150.9413668027250380.1172663945499230.0586331972749615
160.9103875035096880.1792249929806230.0896124964903116
170.9472942189716330.1054115620567340.0527057810283669
180.9201543268934580.1596913462130830.0798456731065415
190.8845906092839660.2308187814320670.115409390716034
200.8818691309831250.2362617380337490.118130869016875
210.9125366602403470.1749266795193060.0874633397596532
220.9102156218930070.1795687562139870.0897843781069935
230.9112363957536240.1775272084927510.0887636042463755
240.8820264129587780.2359471740824440.117973587041222
250.8586874599598070.2826250800803860.141312540040193
260.9988702631685470.002259473662905660.00112973683145283
270.9982221041106660.003555791778667280.00177789588933364
280.9971996872889280.005600625422144780.00280031271107239
290.9957488409347770.008502318130446680.00425115906522334
300.9970730836405780.005853832718844790.0029269163594224
310.9955891117714220.008821776457156830.00441088822857842
320.9936885026156660.01262299476866870.00631149738433435
330.9924190312786560.01516193744268860.00758096872134432
340.9890870290509930.02182594189801370.0109129709490068
350.9865862736129770.02682745277404580.0134137263870229
360.9814972598371250.03700548032574930.0185027401628747
370.9873632944747030.02527341105059390.0126367055252969
380.9826663199709470.03466736005810570.0173336800290529
390.9802170946642860.03956581067142780.0197829053357139
400.980552291689650.03889541662070040.0194477083103502
410.9745828960853880.05083420782922420.0254171039146121
420.9721593067655280.05568138646894450.0278406932344722
430.9634654039844290.07306919203114210.0365345960155711
440.9570869381184040.08582612376319230.0429130618815962
450.9450353182254520.1099293635490960.0549646817745481
460.9543995699407230.09120086011855370.0456004300592768
470.9420329798233330.1159340403533340.0579670201766668
480.9270449717579580.1459100564840840.0729550282420418
490.9383986856733890.1232026286532210.0616013143266105
500.934468903953650.13106219209270.0655310960463501
510.9202801279562260.1594397440875490.0797198720437744
520.9026592673327370.1946814653345250.0973407326672626
530.8886248534765570.2227502930468870.111375146523443
540.871587603017550.2568247939649010.12841239698245
550.8642655842084920.2714688315830160.135734415791508
560.8457506283021510.3084987433956970.154249371697849
570.8322903803505510.3354192392988980.167709619649449
580.803355667258780.3932886654824410.19664433274122
590.8458470001598980.3083059996802040.154152999840102
600.8414214695964290.3171570608071420.158578530403571
610.8598500333946020.2802999332107950.140149966605398
620.8586833467229550.282633306554090.141316653277045
630.9096446192918820.1807107614162360.0903553807081178
640.8968399509093930.2063200981812150.103160049090607
650.8865058268072380.2269883463855230.113494173192762
660.9590204746534780.0819590506930440.040979525346522
670.9574919714524120.08501605709517580.0425080285475879
680.9627469638762960.0745060722474070.0372530361237035
690.9577312225680790.08453755486384110.0422687774319205
700.9514005691102270.09719886177954540.0485994308897727
710.9409280766738340.1181438466523320.0590719233261661
720.9542298592850160.09154028142996860.0457701407149843
730.9441852360502610.1116295278994790.0558147639497394
740.9330715371181480.1338569257637040.066928462881852
750.9281346714797130.1437306570405740.0718653285202872
760.9144228242552020.1711543514895960.0855771757447979
770.9264444725802130.1471110548395740.0735555274197872
780.9125921606327840.1748156787344310.0874078393672156
790.9037940405445470.1924119189109070.0962059594554534
800.8968521194863210.2062957610273580.103147880513679
810.8784247374294350.243150525141130.121575262570565
820.858790013602360.282419972795280.14120998639764
830.8510202481800890.2979595036398220.148979751819911
840.8303485209441890.3393029581116230.169651479055811
850.8048463427685580.3903073144628840.195153657231442
860.7811720344361220.4376559311277560.218827965563878
870.7524248253183940.4951503493632110.247575174681606
880.7215571591026150.5568856817947690.278442840897385
890.795270416890040.4094591662199210.20472958310996
900.8293273235080850.3413453529838310.170672676491915
910.8047681599980590.3904636800038830.195231840001941
920.7811733637524290.4376532724951430.218826636247572
930.7575014451243070.4849971097513860.242498554875693
940.7324820453804640.5350359092390730.267517954619536
950.7059355433151960.5881289133696070.294064456684804
960.6801755425693810.6396489148612380.319824457430619
970.6523248693188510.6953502613622980.347675130681149
980.6508493178144680.6983013643710640.349150682185532
990.6168325304439410.7663349391121190.383167469556059
1000.6069490037186530.7861019925626940.393050996281347
1010.582450946784030.8350981064319390.41754905321597
1020.5528455794092440.8943088411815120.447154420590756
1030.6011349182093320.7977301635813360.398865081790668
1040.5899771187434240.8200457625131530.410022881256576
1050.6052701580040740.7894596839918530.394729841995926
1060.577837366245860.8443252675082790.42216263375414
1070.570148719773420.859702560453160.42985128022658
1080.6105095317147370.7789809365705260.389490468285263
1090.5829094746685580.8341810506628840.417090525331442
1100.5573263069893850.885347386021230.442673693010615
1110.5622759617704060.8754480764591870.437724038229594
1120.5909655757913380.8180688484173230.409034424208662
1130.5886919447435040.8226161105129930.411308055256496
1140.6778242717648610.6443514564702790.322175728235139
1150.6467554299484540.7064891401030910.353244570051546
1160.6221724496611080.7556551006777840.377827550338892
1170.5891821709295170.8216356581409650.410817829070483
1180.5653146637510510.8693706724978990.434685336248949
1190.5312638595572610.9374722808854780.468736140442739
1200.5001021340155270.9997957319689450.499897865984473
1210.4695037486030610.9390074972061220.530496251396939
1220.4388811019873910.8777622039747830.561118898012609
1230.4122991019651740.8245982039303480.587700898034826
1240.379910332308150.7598206646163010.62008966769185
1250.3686919677959460.7373839355918920.631308032204054
1260.3397040463668670.6794080927337340.660295953633133
1270.327022828603380.654045657206760.67297717139662
1280.4299738098885190.8599476197770370.570026190111481
1290.4133453534844620.8266907069689230.586654646515538
1300.4021804858322080.8043609716644160.597819514167792
1310.3866446916863670.7732893833727340.613355308313633
1320.3593145985954540.7186291971909080.640685401404546
1330.3800903236939310.7601806473878610.619909676306069
1340.3532285024613090.7064570049226180.646771497538691
1350.3648879146916430.7297758293832860.635112085308357
1360.3543942832590220.7087885665180450.645605716740978
1370.3252985027594230.6505970055188460.674701497240577
1380.3012694251422810.6025388502845620.698730574857719
1390.2758016816336930.5516033632673850.724198318366307
1400.2525556201058680.5051112402117360.747444379894132
1410.2255964165387670.4511928330775350.774403583461233
1420.2313564286950040.4627128573900080.768643571304996
1430.2067718582772440.4135437165544880.793228141722756
1440.1861373778476350.372274755695270.813862622152365
1450.1743181654163950.348636330832790.825681834583605
1460.166582008698690.3331640173973810.83341799130131
1470.1750264272422690.3500528544845380.824973572757731
1480.1912850076556270.3825700153112540.808714992344373
1490.2076545125378020.4153090250756040.792345487462198
1500.2085832065266080.4171664130532170.791416793473392
1510.1881788384813720.3763576769627450.811821161518628
1520.1691640156849090.3383280313698170.830835984315091
1530.1828903245591120.3657806491182230.817109675440888
1540.1981506617015410.3963013234030810.801849338298459
1550.1840271960091710.3680543920183420.815972803990829
1560.1612059074504420.3224118149008850.838794092549558
1570.1436493330907020.2872986661814050.856350666909298
1580.2254856697987910.4509713395975820.774514330201209
1590.2434830012354860.4869660024709730.756516998764514
1600.2229369473958720.4458738947917440.777063052604128
1610.2000007582854210.4000015165708430.799999241714579
1620.1768746977598940.3537493955197890.823125302240106
1630.1564517537069120.3129035074138240.843548246293088
1640.2624301006826670.5248602013653340.737569899317333
1650.2589806769637620.5179613539275250.741019323036238
1660.2550423514734810.5100847029469610.744957648526519
1670.2267772819796360.4535545639592710.773222718020364
1680.2047668084698830.4095336169397670.795233191530117
1690.2614986812125580.5229973624251170.738501318787442
1700.2863571042296320.5727142084592650.713642895770368
1710.2587920469751630.5175840939503260.741207953024837
1720.2538221287061630.5076442574123260.746177871293837
1730.4188971187807870.8377942375615730.581102881219213
1740.4049379420986030.8098758841972050.595062057901397
1750.4274318738002520.8548637476005050.572568126199748
1760.4366315132890130.8732630265780250.563368486710987
1770.4946636490933250.989327298186650.505336350906675
1780.4610640554429180.9221281108858350.538935944557082
1790.4383905801924150.876781160384830.561609419807585
1800.4378381078229790.8756762156459580.562161892177021
1810.4005406853273040.8010813706546070.599459314672696
1820.3935009663362810.7870019326725620.606499033663719
1830.3564622869590060.7129245739180120.643537713040994
1840.3297881187921080.6595762375842150.670211881207892
1850.3449767302117510.6899534604235020.655023269788249
1860.3375439304671850.6750878609343690.662456069532815
1870.3034825190067380.6069650380134760.696517480993262
1880.2765391432241990.5530782864483980.723460856775801
1890.2458084552626730.4916169105253460.754191544737327
1900.2232753314982020.4465506629964030.776724668501798
1910.2271321340797330.4542642681594670.772867865920267
1920.2090273012751060.4180546025502120.790972698724894
1930.2269388244377390.4538776488754770.773061175562261
1940.2150453328546380.4300906657092760.784954667145362
1950.2144764642924540.4289529285849080.785523535707546
1960.2258494226202740.4516988452405490.774150577379726
1970.2729703722132280.5459407444264550.727029627786772
1980.2547460233585830.5094920467171670.745253976641417
1990.2882645720863390.5765291441726780.711735427913661
2000.255383860135480.510767720270960.74461613986452
2010.2929840428058140.5859680856116270.707015957194187
2020.2713838497193830.5427676994387660.728616150280617
2030.3331418597826950.6662837195653890.666858140217305
2040.2971824046214430.5943648092428860.702817595378557
2050.2630037235299740.5260074470599470.736996276470026
2060.2415648801610870.4831297603221730.758435119838913
2070.2101927129220390.4203854258440790.789807287077961
2080.2297279570655260.4594559141310520.770272042934474
2090.1978218589797820.3956437179595640.802178141020218
2100.2145419787739480.4290839575478970.785458021226052
2110.2425619820990130.4851239641980260.757438017900987
2120.2267583105897450.4535166211794910.773241689410255
2130.1993289884888530.3986579769777050.800671011511147
2140.2489149105669760.4978298211339530.751085089433024
2150.2214953742474520.4429907484949040.778504625752548
2160.2081715005379950.4163430010759890.791828499462005
2170.241196622850630.4823932457012590.75880337714937
2180.2105090145294930.4210180290589860.789490985470507
2190.1964943610737090.3929887221474170.803505638926291
2200.2040386115070520.4080772230141040.795961388492948
2210.2122162155492440.4244324310984870.787783784450756
2220.2133140226163860.4266280452327720.786685977383614
2230.1972153627921160.3944307255842310.802784637207884
2240.1651670245528630.3303340491057260.834832975447137
2250.1495246973519580.2990493947039150.850475302648042
2260.1784143124046180.3568286248092360.821585687595382
2270.370584744610050.7411694892200990.62941525538995
2280.3471796404611320.6943592809222640.652820359538868
2290.3201211768522730.6402423537045450.679878823147727
2300.3049175554976140.6098351109952290.695082444502386
2310.2622560084292830.5245120168585660.737743991570717
2320.301634071407960.603268142815920.69836592859204
2330.2569107036217740.5138214072435480.743089296378226
2340.2151005420212740.4302010840425470.784899457978727
2350.2143202422081370.4286404844162750.785679757791863
2360.1900263331689510.3800526663379010.809973666831049
2370.1591396516991820.3182793033983640.840860348300818
2380.124004911954720.2480098239094390.87599508804528
2390.2410433606853120.4820867213706230.758956639314688
2400.2364715467585610.4729430935171220.763528453241439
2410.2043483609016190.4086967218032380.795651639098381
2420.4040873307269590.8081746614539180.595912669273041
2430.3599307492321160.7198614984642320.640069250767884
2440.3000403375400580.6000806750801160.699959662459942
2450.4298416861442850.8596833722885710.570158313855715
2460.3450923256150530.6901846512301060.654907674384947
2470.2679697955745320.5359395911490630.732030204425468
2480.4118682092053840.8237364184107680.588131790794616
2490.3188828786813260.6377657573626520.681117121318674
2500.2306012739570320.4612025479140650.769398726042968
2510.3562279728011320.7124559456022630.643772027198868
2520.8726877038393010.2546245923213990.127312296160699
2530.7503207608500710.4993584782998570.249679239149929

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.0237638749126408 & 0.0475277498252816 & 0.976236125087359 \tabularnewline
12 & 0.708031671877707 & 0.583936656244587 & 0.291968328122293 \tabularnewline
13 & 0.96351191692836 & 0.0729761661432798 & 0.0364880830716399 \tabularnewline
14 & 0.937868685162942 & 0.124262629674115 & 0.0621313148370576 \tabularnewline
15 & 0.941366802725038 & 0.117266394549923 & 0.0586331972749615 \tabularnewline
16 & 0.910387503509688 & 0.179224992980623 & 0.0896124964903116 \tabularnewline
17 & 0.947294218971633 & 0.105411562056734 & 0.0527057810283669 \tabularnewline
18 & 0.920154326893458 & 0.159691346213083 & 0.0798456731065415 \tabularnewline
19 & 0.884590609283966 & 0.230818781432067 & 0.115409390716034 \tabularnewline
20 & 0.881869130983125 & 0.236261738033749 & 0.118130869016875 \tabularnewline
21 & 0.912536660240347 & 0.174926679519306 & 0.0874633397596532 \tabularnewline
22 & 0.910215621893007 & 0.179568756213987 & 0.0897843781069935 \tabularnewline
23 & 0.911236395753624 & 0.177527208492751 & 0.0887636042463755 \tabularnewline
24 & 0.882026412958778 & 0.235947174082444 & 0.117973587041222 \tabularnewline
25 & 0.858687459959807 & 0.282625080080386 & 0.141312540040193 \tabularnewline
26 & 0.998870263168547 & 0.00225947366290566 & 0.00112973683145283 \tabularnewline
27 & 0.998222104110666 & 0.00355579177866728 & 0.00177789588933364 \tabularnewline
28 & 0.997199687288928 & 0.00560062542214478 & 0.00280031271107239 \tabularnewline
29 & 0.995748840934777 & 0.00850231813044668 & 0.00425115906522334 \tabularnewline
30 & 0.997073083640578 & 0.00585383271884479 & 0.0029269163594224 \tabularnewline
31 & 0.995589111771422 & 0.00882177645715683 & 0.00441088822857842 \tabularnewline
32 & 0.993688502615666 & 0.0126229947686687 & 0.00631149738433435 \tabularnewline
33 & 0.992419031278656 & 0.0151619374426886 & 0.00758096872134432 \tabularnewline
34 & 0.989087029050993 & 0.0218259418980137 & 0.0109129709490068 \tabularnewline
35 & 0.986586273612977 & 0.0268274527740458 & 0.0134137263870229 \tabularnewline
36 & 0.981497259837125 & 0.0370054803257493 & 0.0185027401628747 \tabularnewline
37 & 0.987363294474703 & 0.0252734110505939 & 0.0126367055252969 \tabularnewline
38 & 0.982666319970947 & 0.0346673600581057 & 0.0173336800290529 \tabularnewline
39 & 0.980217094664286 & 0.0395658106714278 & 0.0197829053357139 \tabularnewline
40 & 0.98055229168965 & 0.0388954166207004 & 0.0194477083103502 \tabularnewline
41 & 0.974582896085388 & 0.0508342078292242 & 0.0254171039146121 \tabularnewline
42 & 0.972159306765528 & 0.0556813864689445 & 0.0278406932344722 \tabularnewline
43 & 0.963465403984429 & 0.0730691920311421 & 0.0365345960155711 \tabularnewline
44 & 0.957086938118404 & 0.0858261237631923 & 0.0429130618815962 \tabularnewline
45 & 0.945035318225452 & 0.109929363549096 & 0.0549646817745481 \tabularnewline
46 & 0.954399569940723 & 0.0912008601185537 & 0.0456004300592768 \tabularnewline
47 & 0.942032979823333 & 0.115934040353334 & 0.0579670201766668 \tabularnewline
48 & 0.927044971757958 & 0.145910056484084 & 0.0729550282420418 \tabularnewline
49 & 0.938398685673389 & 0.123202628653221 & 0.0616013143266105 \tabularnewline
50 & 0.93446890395365 & 0.1310621920927 & 0.0655310960463501 \tabularnewline
51 & 0.920280127956226 & 0.159439744087549 & 0.0797198720437744 \tabularnewline
52 & 0.902659267332737 & 0.194681465334525 & 0.0973407326672626 \tabularnewline
53 & 0.888624853476557 & 0.222750293046887 & 0.111375146523443 \tabularnewline
54 & 0.87158760301755 & 0.256824793964901 & 0.12841239698245 \tabularnewline
55 & 0.864265584208492 & 0.271468831583016 & 0.135734415791508 \tabularnewline
56 & 0.845750628302151 & 0.308498743395697 & 0.154249371697849 \tabularnewline
57 & 0.832290380350551 & 0.335419239298898 & 0.167709619649449 \tabularnewline
58 & 0.80335566725878 & 0.393288665482441 & 0.19664433274122 \tabularnewline
59 & 0.845847000159898 & 0.308305999680204 & 0.154152999840102 \tabularnewline
60 & 0.841421469596429 & 0.317157060807142 & 0.158578530403571 \tabularnewline
61 & 0.859850033394602 & 0.280299933210795 & 0.140149966605398 \tabularnewline
62 & 0.858683346722955 & 0.28263330655409 & 0.141316653277045 \tabularnewline
63 & 0.909644619291882 & 0.180710761416236 & 0.0903553807081178 \tabularnewline
64 & 0.896839950909393 & 0.206320098181215 & 0.103160049090607 \tabularnewline
65 & 0.886505826807238 & 0.226988346385523 & 0.113494173192762 \tabularnewline
66 & 0.959020474653478 & 0.081959050693044 & 0.040979525346522 \tabularnewline
67 & 0.957491971452412 & 0.0850160570951758 & 0.0425080285475879 \tabularnewline
68 & 0.962746963876296 & 0.074506072247407 & 0.0372530361237035 \tabularnewline
69 & 0.957731222568079 & 0.0845375548638411 & 0.0422687774319205 \tabularnewline
70 & 0.951400569110227 & 0.0971988617795454 & 0.0485994308897727 \tabularnewline
71 & 0.940928076673834 & 0.118143846652332 & 0.0590719233261661 \tabularnewline
72 & 0.954229859285016 & 0.0915402814299686 & 0.0457701407149843 \tabularnewline
73 & 0.944185236050261 & 0.111629527899479 & 0.0558147639497394 \tabularnewline
74 & 0.933071537118148 & 0.133856925763704 & 0.066928462881852 \tabularnewline
75 & 0.928134671479713 & 0.143730657040574 & 0.0718653285202872 \tabularnewline
76 & 0.914422824255202 & 0.171154351489596 & 0.0855771757447979 \tabularnewline
77 & 0.926444472580213 & 0.147111054839574 & 0.0735555274197872 \tabularnewline
78 & 0.912592160632784 & 0.174815678734431 & 0.0874078393672156 \tabularnewline
79 & 0.903794040544547 & 0.192411918910907 & 0.0962059594554534 \tabularnewline
80 & 0.896852119486321 & 0.206295761027358 & 0.103147880513679 \tabularnewline
81 & 0.878424737429435 & 0.24315052514113 & 0.121575262570565 \tabularnewline
82 & 0.85879001360236 & 0.28241997279528 & 0.14120998639764 \tabularnewline
83 & 0.851020248180089 & 0.297959503639822 & 0.148979751819911 \tabularnewline
84 & 0.830348520944189 & 0.339302958111623 & 0.169651479055811 \tabularnewline
85 & 0.804846342768558 & 0.390307314462884 & 0.195153657231442 \tabularnewline
86 & 0.781172034436122 & 0.437655931127756 & 0.218827965563878 \tabularnewline
87 & 0.752424825318394 & 0.495150349363211 & 0.247575174681606 \tabularnewline
88 & 0.721557159102615 & 0.556885681794769 & 0.278442840897385 \tabularnewline
89 & 0.79527041689004 & 0.409459166219921 & 0.20472958310996 \tabularnewline
90 & 0.829327323508085 & 0.341345352983831 & 0.170672676491915 \tabularnewline
91 & 0.804768159998059 & 0.390463680003883 & 0.195231840001941 \tabularnewline
92 & 0.781173363752429 & 0.437653272495143 & 0.218826636247572 \tabularnewline
93 & 0.757501445124307 & 0.484997109751386 & 0.242498554875693 \tabularnewline
94 & 0.732482045380464 & 0.535035909239073 & 0.267517954619536 \tabularnewline
95 & 0.705935543315196 & 0.588128913369607 & 0.294064456684804 \tabularnewline
96 & 0.680175542569381 & 0.639648914861238 & 0.319824457430619 \tabularnewline
97 & 0.652324869318851 & 0.695350261362298 & 0.347675130681149 \tabularnewline
98 & 0.650849317814468 & 0.698301364371064 & 0.349150682185532 \tabularnewline
99 & 0.616832530443941 & 0.766334939112119 & 0.383167469556059 \tabularnewline
100 & 0.606949003718653 & 0.786101992562694 & 0.393050996281347 \tabularnewline
101 & 0.58245094678403 & 0.835098106431939 & 0.41754905321597 \tabularnewline
102 & 0.552845579409244 & 0.894308841181512 & 0.447154420590756 \tabularnewline
103 & 0.601134918209332 & 0.797730163581336 & 0.398865081790668 \tabularnewline
104 & 0.589977118743424 & 0.820045762513153 & 0.410022881256576 \tabularnewline
105 & 0.605270158004074 & 0.789459683991853 & 0.394729841995926 \tabularnewline
106 & 0.57783736624586 & 0.844325267508279 & 0.42216263375414 \tabularnewline
107 & 0.57014871977342 & 0.85970256045316 & 0.42985128022658 \tabularnewline
108 & 0.610509531714737 & 0.778980936570526 & 0.389490468285263 \tabularnewline
109 & 0.582909474668558 & 0.834181050662884 & 0.417090525331442 \tabularnewline
110 & 0.557326306989385 & 0.88534738602123 & 0.442673693010615 \tabularnewline
111 & 0.562275961770406 & 0.875448076459187 & 0.437724038229594 \tabularnewline
112 & 0.590965575791338 & 0.818068848417323 & 0.409034424208662 \tabularnewline
113 & 0.588691944743504 & 0.822616110512993 & 0.411308055256496 \tabularnewline
114 & 0.677824271764861 & 0.644351456470279 & 0.322175728235139 \tabularnewline
115 & 0.646755429948454 & 0.706489140103091 & 0.353244570051546 \tabularnewline
116 & 0.622172449661108 & 0.755655100677784 & 0.377827550338892 \tabularnewline
117 & 0.589182170929517 & 0.821635658140965 & 0.410817829070483 \tabularnewline
118 & 0.565314663751051 & 0.869370672497899 & 0.434685336248949 \tabularnewline
119 & 0.531263859557261 & 0.937472280885478 & 0.468736140442739 \tabularnewline
120 & 0.500102134015527 & 0.999795731968945 & 0.499897865984473 \tabularnewline
121 & 0.469503748603061 & 0.939007497206122 & 0.530496251396939 \tabularnewline
122 & 0.438881101987391 & 0.877762203974783 & 0.561118898012609 \tabularnewline
123 & 0.412299101965174 & 0.824598203930348 & 0.587700898034826 \tabularnewline
124 & 0.37991033230815 & 0.759820664616301 & 0.62008966769185 \tabularnewline
125 & 0.368691967795946 & 0.737383935591892 & 0.631308032204054 \tabularnewline
126 & 0.339704046366867 & 0.679408092733734 & 0.660295953633133 \tabularnewline
127 & 0.32702282860338 & 0.65404565720676 & 0.67297717139662 \tabularnewline
128 & 0.429973809888519 & 0.859947619777037 & 0.570026190111481 \tabularnewline
129 & 0.413345353484462 & 0.826690706968923 & 0.586654646515538 \tabularnewline
130 & 0.402180485832208 & 0.804360971664416 & 0.597819514167792 \tabularnewline
131 & 0.386644691686367 & 0.773289383372734 & 0.613355308313633 \tabularnewline
132 & 0.359314598595454 & 0.718629197190908 & 0.640685401404546 \tabularnewline
133 & 0.380090323693931 & 0.760180647387861 & 0.619909676306069 \tabularnewline
134 & 0.353228502461309 & 0.706457004922618 & 0.646771497538691 \tabularnewline
135 & 0.364887914691643 & 0.729775829383286 & 0.635112085308357 \tabularnewline
136 & 0.354394283259022 & 0.708788566518045 & 0.645605716740978 \tabularnewline
137 & 0.325298502759423 & 0.650597005518846 & 0.674701497240577 \tabularnewline
138 & 0.301269425142281 & 0.602538850284562 & 0.698730574857719 \tabularnewline
139 & 0.275801681633693 & 0.551603363267385 & 0.724198318366307 \tabularnewline
140 & 0.252555620105868 & 0.505111240211736 & 0.747444379894132 \tabularnewline
141 & 0.225596416538767 & 0.451192833077535 & 0.774403583461233 \tabularnewline
142 & 0.231356428695004 & 0.462712857390008 & 0.768643571304996 \tabularnewline
143 & 0.206771858277244 & 0.413543716554488 & 0.793228141722756 \tabularnewline
144 & 0.186137377847635 & 0.37227475569527 & 0.813862622152365 \tabularnewline
145 & 0.174318165416395 & 0.34863633083279 & 0.825681834583605 \tabularnewline
146 & 0.16658200869869 & 0.333164017397381 & 0.83341799130131 \tabularnewline
147 & 0.175026427242269 & 0.350052854484538 & 0.824973572757731 \tabularnewline
148 & 0.191285007655627 & 0.382570015311254 & 0.808714992344373 \tabularnewline
149 & 0.207654512537802 & 0.415309025075604 & 0.792345487462198 \tabularnewline
150 & 0.208583206526608 & 0.417166413053217 & 0.791416793473392 \tabularnewline
151 & 0.188178838481372 & 0.376357676962745 & 0.811821161518628 \tabularnewline
152 & 0.169164015684909 & 0.338328031369817 & 0.830835984315091 \tabularnewline
153 & 0.182890324559112 & 0.365780649118223 & 0.817109675440888 \tabularnewline
154 & 0.198150661701541 & 0.396301323403081 & 0.801849338298459 \tabularnewline
155 & 0.184027196009171 & 0.368054392018342 & 0.815972803990829 \tabularnewline
156 & 0.161205907450442 & 0.322411814900885 & 0.838794092549558 \tabularnewline
157 & 0.143649333090702 & 0.287298666181405 & 0.856350666909298 \tabularnewline
158 & 0.225485669798791 & 0.450971339597582 & 0.774514330201209 \tabularnewline
159 & 0.243483001235486 & 0.486966002470973 & 0.756516998764514 \tabularnewline
160 & 0.222936947395872 & 0.445873894791744 & 0.777063052604128 \tabularnewline
161 & 0.200000758285421 & 0.400001516570843 & 0.799999241714579 \tabularnewline
162 & 0.176874697759894 & 0.353749395519789 & 0.823125302240106 \tabularnewline
163 & 0.156451753706912 & 0.312903507413824 & 0.843548246293088 \tabularnewline
164 & 0.262430100682667 & 0.524860201365334 & 0.737569899317333 \tabularnewline
165 & 0.258980676963762 & 0.517961353927525 & 0.741019323036238 \tabularnewline
166 & 0.255042351473481 & 0.510084702946961 & 0.744957648526519 \tabularnewline
167 & 0.226777281979636 & 0.453554563959271 & 0.773222718020364 \tabularnewline
168 & 0.204766808469883 & 0.409533616939767 & 0.795233191530117 \tabularnewline
169 & 0.261498681212558 & 0.522997362425117 & 0.738501318787442 \tabularnewline
170 & 0.286357104229632 & 0.572714208459265 & 0.713642895770368 \tabularnewline
171 & 0.258792046975163 & 0.517584093950326 & 0.741207953024837 \tabularnewline
172 & 0.253822128706163 & 0.507644257412326 & 0.746177871293837 \tabularnewline
173 & 0.418897118780787 & 0.837794237561573 & 0.581102881219213 \tabularnewline
174 & 0.404937942098603 & 0.809875884197205 & 0.595062057901397 \tabularnewline
175 & 0.427431873800252 & 0.854863747600505 & 0.572568126199748 \tabularnewline
176 & 0.436631513289013 & 0.873263026578025 & 0.563368486710987 \tabularnewline
177 & 0.494663649093325 & 0.98932729818665 & 0.505336350906675 \tabularnewline
178 & 0.461064055442918 & 0.922128110885835 & 0.538935944557082 \tabularnewline
179 & 0.438390580192415 & 0.87678116038483 & 0.561609419807585 \tabularnewline
180 & 0.437838107822979 & 0.875676215645958 & 0.562161892177021 \tabularnewline
181 & 0.400540685327304 & 0.801081370654607 & 0.599459314672696 \tabularnewline
182 & 0.393500966336281 & 0.787001932672562 & 0.606499033663719 \tabularnewline
183 & 0.356462286959006 & 0.712924573918012 & 0.643537713040994 \tabularnewline
184 & 0.329788118792108 & 0.659576237584215 & 0.670211881207892 \tabularnewline
185 & 0.344976730211751 & 0.689953460423502 & 0.655023269788249 \tabularnewline
186 & 0.337543930467185 & 0.675087860934369 & 0.662456069532815 \tabularnewline
187 & 0.303482519006738 & 0.606965038013476 & 0.696517480993262 \tabularnewline
188 & 0.276539143224199 & 0.553078286448398 & 0.723460856775801 \tabularnewline
189 & 0.245808455262673 & 0.491616910525346 & 0.754191544737327 \tabularnewline
190 & 0.223275331498202 & 0.446550662996403 & 0.776724668501798 \tabularnewline
191 & 0.227132134079733 & 0.454264268159467 & 0.772867865920267 \tabularnewline
192 & 0.209027301275106 & 0.418054602550212 & 0.790972698724894 \tabularnewline
193 & 0.226938824437739 & 0.453877648875477 & 0.773061175562261 \tabularnewline
194 & 0.215045332854638 & 0.430090665709276 & 0.784954667145362 \tabularnewline
195 & 0.214476464292454 & 0.428952928584908 & 0.785523535707546 \tabularnewline
196 & 0.225849422620274 & 0.451698845240549 & 0.774150577379726 \tabularnewline
197 & 0.272970372213228 & 0.545940744426455 & 0.727029627786772 \tabularnewline
198 & 0.254746023358583 & 0.509492046717167 & 0.745253976641417 \tabularnewline
199 & 0.288264572086339 & 0.576529144172678 & 0.711735427913661 \tabularnewline
200 & 0.25538386013548 & 0.51076772027096 & 0.74461613986452 \tabularnewline
201 & 0.292984042805814 & 0.585968085611627 & 0.707015957194187 \tabularnewline
202 & 0.271383849719383 & 0.542767699438766 & 0.728616150280617 \tabularnewline
203 & 0.333141859782695 & 0.666283719565389 & 0.666858140217305 \tabularnewline
204 & 0.297182404621443 & 0.594364809242886 & 0.702817595378557 \tabularnewline
205 & 0.263003723529974 & 0.526007447059947 & 0.736996276470026 \tabularnewline
206 & 0.241564880161087 & 0.483129760322173 & 0.758435119838913 \tabularnewline
207 & 0.210192712922039 & 0.420385425844079 & 0.789807287077961 \tabularnewline
208 & 0.229727957065526 & 0.459455914131052 & 0.770272042934474 \tabularnewline
209 & 0.197821858979782 & 0.395643717959564 & 0.802178141020218 \tabularnewline
210 & 0.214541978773948 & 0.429083957547897 & 0.785458021226052 \tabularnewline
211 & 0.242561982099013 & 0.485123964198026 & 0.757438017900987 \tabularnewline
212 & 0.226758310589745 & 0.453516621179491 & 0.773241689410255 \tabularnewline
213 & 0.199328988488853 & 0.398657976977705 & 0.800671011511147 \tabularnewline
214 & 0.248914910566976 & 0.497829821133953 & 0.751085089433024 \tabularnewline
215 & 0.221495374247452 & 0.442990748494904 & 0.778504625752548 \tabularnewline
216 & 0.208171500537995 & 0.416343001075989 & 0.791828499462005 \tabularnewline
217 & 0.24119662285063 & 0.482393245701259 & 0.75880337714937 \tabularnewline
218 & 0.210509014529493 & 0.421018029058986 & 0.789490985470507 \tabularnewline
219 & 0.196494361073709 & 0.392988722147417 & 0.803505638926291 \tabularnewline
220 & 0.204038611507052 & 0.408077223014104 & 0.795961388492948 \tabularnewline
221 & 0.212216215549244 & 0.424432431098487 & 0.787783784450756 \tabularnewline
222 & 0.213314022616386 & 0.426628045232772 & 0.786685977383614 \tabularnewline
223 & 0.197215362792116 & 0.394430725584231 & 0.802784637207884 \tabularnewline
224 & 0.165167024552863 & 0.330334049105726 & 0.834832975447137 \tabularnewline
225 & 0.149524697351958 & 0.299049394703915 & 0.850475302648042 \tabularnewline
226 & 0.178414312404618 & 0.356828624809236 & 0.821585687595382 \tabularnewline
227 & 0.37058474461005 & 0.741169489220099 & 0.62941525538995 \tabularnewline
228 & 0.347179640461132 & 0.694359280922264 & 0.652820359538868 \tabularnewline
229 & 0.320121176852273 & 0.640242353704545 & 0.679878823147727 \tabularnewline
230 & 0.304917555497614 & 0.609835110995229 & 0.695082444502386 \tabularnewline
231 & 0.262256008429283 & 0.524512016858566 & 0.737743991570717 \tabularnewline
232 & 0.30163407140796 & 0.60326814281592 & 0.69836592859204 \tabularnewline
233 & 0.256910703621774 & 0.513821407243548 & 0.743089296378226 \tabularnewline
234 & 0.215100542021274 & 0.430201084042547 & 0.784899457978727 \tabularnewline
235 & 0.214320242208137 & 0.428640484416275 & 0.785679757791863 \tabularnewline
236 & 0.190026333168951 & 0.380052666337901 & 0.809973666831049 \tabularnewline
237 & 0.159139651699182 & 0.318279303398364 & 0.840860348300818 \tabularnewline
238 & 0.12400491195472 & 0.248009823909439 & 0.87599508804528 \tabularnewline
239 & 0.241043360685312 & 0.482086721370623 & 0.758956639314688 \tabularnewline
240 & 0.236471546758561 & 0.472943093517122 & 0.763528453241439 \tabularnewline
241 & 0.204348360901619 & 0.408696721803238 & 0.795651639098381 \tabularnewline
242 & 0.404087330726959 & 0.808174661453918 & 0.595912669273041 \tabularnewline
243 & 0.359930749232116 & 0.719861498464232 & 0.640069250767884 \tabularnewline
244 & 0.300040337540058 & 0.600080675080116 & 0.699959662459942 \tabularnewline
245 & 0.429841686144285 & 0.859683372288571 & 0.570158313855715 \tabularnewline
246 & 0.345092325615053 & 0.690184651230106 & 0.654907674384947 \tabularnewline
247 & 0.267969795574532 & 0.535939591149063 & 0.732030204425468 \tabularnewline
248 & 0.411868209205384 & 0.823736418410768 & 0.588131790794616 \tabularnewline
249 & 0.318882878681326 & 0.637765757362652 & 0.681117121318674 \tabularnewline
250 & 0.230601273957032 & 0.461202547914065 & 0.769398726042968 \tabularnewline
251 & 0.356227972801132 & 0.712455945602263 & 0.643772027198868 \tabularnewline
252 & 0.872687703839301 & 0.254624592321399 & 0.127312296160699 \tabularnewline
253 & 0.750320760850071 & 0.499358478299857 & 0.249679239149929 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226099&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]0.0237638749126408[/C][C]0.0475277498252816[/C][C]0.976236125087359[/C][/ROW]
[ROW][C]12[/C][C]0.708031671877707[/C][C]0.583936656244587[/C][C]0.291968328122293[/C][/ROW]
[ROW][C]13[/C][C]0.96351191692836[/C][C]0.0729761661432798[/C][C]0.0364880830716399[/C][/ROW]
[ROW][C]14[/C][C]0.937868685162942[/C][C]0.124262629674115[/C][C]0.0621313148370576[/C][/ROW]
[ROW][C]15[/C][C]0.941366802725038[/C][C]0.117266394549923[/C][C]0.0586331972749615[/C][/ROW]
[ROW][C]16[/C][C]0.910387503509688[/C][C]0.179224992980623[/C][C]0.0896124964903116[/C][/ROW]
[ROW][C]17[/C][C]0.947294218971633[/C][C]0.105411562056734[/C][C]0.0527057810283669[/C][/ROW]
[ROW][C]18[/C][C]0.920154326893458[/C][C]0.159691346213083[/C][C]0.0798456731065415[/C][/ROW]
[ROW][C]19[/C][C]0.884590609283966[/C][C]0.230818781432067[/C][C]0.115409390716034[/C][/ROW]
[ROW][C]20[/C][C]0.881869130983125[/C][C]0.236261738033749[/C][C]0.118130869016875[/C][/ROW]
[ROW][C]21[/C][C]0.912536660240347[/C][C]0.174926679519306[/C][C]0.0874633397596532[/C][/ROW]
[ROW][C]22[/C][C]0.910215621893007[/C][C]0.179568756213987[/C][C]0.0897843781069935[/C][/ROW]
[ROW][C]23[/C][C]0.911236395753624[/C][C]0.177527208492751[/C][C]0.0887636042463755[/C][/ROW]
[ROW][C]24[/C][C]0.882026412958778[/C][C]0.235947174082444[/C][C]0.117973587041222[/C][/ROW]
[ROW][C]25[/C][C]0.858687459959807[/C][C]0.282625080080386[/C][C]0.141312540040193[/C][/ROW]
[ROW][C]26[/C][C]0.998870263168547[/C][C]0.00225947366290566[/C][C]0.00112973683145283[/C][/ROW]
[ROW][C]27[/C][C]0.998222104110666[/C][C]0.00355579177866728[/C][C]0.00177789588933364[/C][/ROW]
[ROW][C]28[/C][C]0.997199687288928[/C][C]0.00560062542214478[/C][C]0.00280031271107239[/C][/ROW]
[ROW][C]29[/C][C]0.995748840934777[/C][C]0.00850231813044668[/C][C]0.00425115906522334[/C][/ROW]
[ROW][C]30[/C][C]0.997073083640578[/C][C]0.00585383271884479[/C][C]0.0029269163594224[/C][/ROW]
[ROW][C]31[/C][C]0.995589111771422[/C][C]0.00882177645715683[/C][C]0.00441088822857842[/C][/ROW]
[ROW][C]32[/C][C]0.993688502615666[/C][C]0.0126229947686687[/C][C]0.00631149738433435[/C][/ROW]
[ROW][C]33[/C][C]0.992419031278656[/C][C]0.0151619374426886[/C][C]0.00758096872134432[/C][/ROW]
[ROW][C]34[/C][C]0.989087029050993[/C][C]0.0218259418980137[/C][C]0.0109129709490068[/C][/ROW]
[ROW][C]35[/C][C]0.986586273612977[/C][C]0.0268274527740458[/C][C]0.0134137263870229[/C][/ROW]
[ROW][C]36[/C][C]0.981497259837125[/C][C]0.0370054803257493[/C][C]0.0185027401628747[/C][/ROW]
[ROW][C]37[/C][C]0.987363294474703[/C][C]0.0252734110505939[/C][C]0.0126367055252969[/C][/ROW]
[ROW][C]38[/C][C]0.982666319970947[/C][C]0.0346673600581057[/C][C]0.0173336800290529[/C][/ROW]
[ROW][C]39[/C][C]0.980217094664286[/C][C]0.0395658106714278[/C][C]0.0197829053357139[/C][/ROW]
[ROW][C]40[/C][C]0.98055229168965[/C][C]0.0388954166207004[/C][C]0.0194477083103502[/C][/ROW]
[ROW][C]41[/C][C]0.974582896085388[/C][C]0.0508342078292242[/C][C]0.0254171039146121[/C][/ROW]
[ROW][C]42[/C][C]0.972159306765528[/C][C]0.0556813864689445[/C][C]0.0278406932344722[/C][/ROW]
[ROW][C]43[/C][C]0.963465403984429[/C][C]0.0730691920311421[/C][C]0.0365345960155711[/C][/ROW]
[ROW][C]44[/C][C]0.957086938118404[/C][C]0.0858261237631923[/C][C]0.0429130618815962[/C][/ROW]
[ROW][C]45[/C][C]0.945035318225452[/C][C]0.109929363549096[/C][C]0.0549646817745481[/C][/ROW]
[ROW][C]46[/C][C]0.954399569940723[/C][C]0.0912008601185537[/C][C]0.0456004300592768[/C][/ROW]
[ROW][C]47[/C][C]0.942032979823333[/C][C]0.115934040353334[/C][C]0.0579670201766668[/C][/ROW]
[ROW][C]48[/C][C]0.927044971757958[/C][C]0.145910056484084[/C][C]0.0729550282420418[/C][/ROW]
[ROW][C]49[/C][C]0.938398685673389[/C][C]0.123202628653221[/C][C]0.0616013143266105[/C][/ROW]
[ROW][C]50[/C][C]0.93446890395365[/C][C]0.1310621920927[/C][C]0.0655310960463501[/C][/ROW]
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[ROW][C]184[/C][C]0.329788118792108[/C][C]0.659576237584215[/C][C]0.670211881207892[/C][/ROW]
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[ROW][C]187[/C][C]0.303482519006738[/C][C]0.606965038013476[/C][C]0.696517480993262[/C][/ROW]
[ROW][C]188[/C][C]0.276539143224199[/C][C]0.553078286448398[/C][C]0.723460856775801[/C][/ROW]
[ROW][C]189[/C][C]0.245808455262673[/C][C]0.491616910525346[/C][C]0.754191544737327[/C][/ROW]
[ROW][C]190[/C][C]0.223275331498202[/C][C]0.446550662996403[/C][C]0.776724668501798[/C][/ROW]
[ROW][C]191[/C][C]0.227132134079733[/C][C]0.454264268159467[/C][C]0.772867865920267[/C][/ROW]
[ROW][C]192[/C][C]0.209027301275106[/C][C]0.418054602550212[/C][C]0.790972698724894[/C][/ROW]
[ROW][C]193[/C][C]0.226938824437739[/C][C]0.453877648875477[/C][C]0.773061175562261[/C][/ROW]
[ROW][C]194[/C][C]0.215045332854638[/C][C]0.430090665709276[/C][C]0.784954667145362[/C][/ROW]
[ROW][C]195[/C][C]0.214476464292454[/C][C]0.428952928584908[/C][C]0.785523535707546[/C][/ROW]
[ROW][C]196[/C][C]0.225849422620274[/C][C]0.451698845240549[/C][C]0.774150577379726[/C][/ROW]
[ROW][C]197[/C][C]0.272970372213228[/C][C]0.545940744426455[/C][C]0.727029627786772[/C][/ROW]
[ROW][C]198[/C][C]0.254746023358583[/C][C]0.509492046717167[/C][C]0.745253976641417[/C][/ROW]
[ROW][C]199[/C][C]0.288264572086339[/C][C]0.576529144172678[/C][C]0.711735427913661[/C][/ROW]
[ROW][C]200[/C][C]0.25538386013548[/C][C]0.51076772027096[/C][C]0.74461613986452[/C][/ROW]
[ROW][C]201[/C][C]0.292984042805814[/C][C]0.585968085611627[/C][C]0.707015957194187[/C][/ROW]
[ROW][C]202[/C][C]0.271383849719383[/C][C]0.542767699438766[/C][C]0.728616150280617[/C][/ROW]
[ROW][C]203[/C][C]0.333141859782695[/C][C]0.666283719565389[/C][C]0.666858140217305[/C][/ROW]
[ROW][C]204[/C][C]0.297182404621443[/C][C]0.594364809242886[/C][C]0.702817595378557[/C][/ROW]
[ROW][C]205[/C][C]0.263003723529974[/C][C]0.526007447059947[/C][C]0.736996276470026[/C][/ROW]
[ROW][C]206[/C][C]0.241564880161087[/C][C]0.483129760322173[/C][C]0.758435119838913[/C][/ROW]
[ROW][C]207[/C][C]0.210192712922039[/C][C]0.420385425844079[/C][C]0.789807287077961[/C][/ROW]
[ROW][C]208[/C][C]0.229727957065526[/C][C]0.459455914131052[/C][C]0.770272042934474[/C][/ROW]
[ROW][C]209[/C][C]0.197821858979782[/C][C]0.395643717959564[/C][C]0.802178141020218[/C][/ROW]
[ROW][C]210[/C][C]0.214541978773948[/C][C]0.429083957547897[/C][C]0.785458021226052[/C][/ROW]
[ROW][C]211[/C][C]0.242561982099013[/C][C]0.485123964198026[/C][C]0.757438017900987[/C][/ROW]
[ROW][C]212[/C][C]0.226758310589745[/C][C]0.453516621179491[/C][C]0.773241689410255[/C][/ROW]
[ROW][C]213[/C][C]0.199328988488853[/C][C]0.398657976977705[/C][C]0.800671011511147[/C][/ROW]
[ROW][C]214[/C][C]0.248914910566976[/C][C]0.497829821133953[/C][C]0.751085089433024[/C][/ROW]
[ROW][C]215[/C][C]0.221495374247452[/C][C]0.442990748494904[/C][C]0.778504625752548[/C][/ROW]
[ROW][C]216[/C][C]0.208171500537995[/C][C]0.416343001075989[/C][C]0.791828499462005[/C][/ROW]
[ROW][C]217[/C][C]0.24119662285063[/C][C]0.482393245701259[/C][C]0.75880337714937[/C][/ROW]
[ROW][C]218[/C][C]0.210509014529493[/C][C]0.421018029058986[/C][C]0.789490985470507[/C][/ROW]
[ROW][C]219[/C][C]0.196494361073709[/C][C]0.392988722147417[/C][C]0.803505638926291[/C][/ROW]
[ROW][C]220[/C][C]0.204038611507052[/C][C]0.408077223014104[/C][C]0.795961388492948[/C][/ROW]
[ROW][C]221[/C][C]0.212216215549244[/C][C]0.424432431098487[/C][C]0.787783784450756[/C][/ROW]
[ROW][C]222[/C][C]0.213314022616386[/C][C]0.426628045232772[/C][C]0.786685977383614[/C][/ROW]
[ROW][C]223[/C][C]0.197215362792116[/C][C]0.394430725584231[/C][C]0.802784637207884[/C][/ROW]
[ROW][C]224[/C][C]0.165167024552863[/C][C]0.330334049105726[/C][C]0.834832975447137[/C][/ROW]
[ROW][C]225[/C][C]0.149524697351958[/C][C]0.299049394703915[/C][C]0.850475302648042[/C][/ROW]
[ROW][C]226[/C][C]0.178414312404618[/C][C]0.356828624809236[/C][C]0.821585687595382[/C][/ROW]
[ROW][C]227[/C][C]0.37058474461005[/C][C]0.741169489220099[/C][C]0.62941525538995[/C][/ROW]
[ROW][C]228[/C][C]0.347179640461132[/C][C]0.694359280922264[/C][C]0.652820359538868[/C][/ROW]
[ROW][C]229[/C][C]0.320121176852273[/C][C]0.640242353704545[/C][C]0.679878823147727[/C][/ROW]
[ROW][C]230[/C][C]0.304917555497614[/C][C]0.609835110995229[/C][C]0.695082444502386[/C][/ROW]
[ROW][C]231[/C][C]0.262256008429283[/C][C]0.524512016858566[/C][C]0.737743991570717[/C][/ROW]
[ROW][C]232[/C][C]0.30163407140796[/C][C]0.60326814281592[/C][C]0.69836592859204[/C][/ROW]
[ROW][C]233[/C][C]0.256910703621774[/C][C]0.513821407243548[/C][C]0.743089296378226[/C][/ROW]
[ROW][C]234[/C][C]0.215100542021274[/C][C]0.430201084042547[/C][C]0.784899457978727[/C][/ROW]
[ROW][C]235[/C][C]0.214320242208137[/C][C]0.428640484416275[/C][C]0.785679757791863[/C][/ROW]
[ROW][C]236[/C][C]0.190026333168951[/C][C]0.380052666337901[/C][C]0.809973666831049[/C][/ROW]
[ROW][C]237[/C][C]0.159139651699182[/C][C]0.318279303398364[/C][C]0.840860348300818[/C][/ROW]
[ROW][C]238[/C][C]0.12400491195472[/C][C]0.248009823909439[/C][C]0.87599508804528[/C][/ROW]
[ROW][C]239[/C][C]0.241043360685312[/C][C]0.482086721370623[/C][C]0.758956639314688[/C][/ROW]
[ROW][C]240[/C][C]0.236471546758561[/C][C]0.472943093517122[/C][C]0.763528453241439[/C][/ROW]
[ROW][C]241[/C][C]0.204348360901619[/C][C]0.408696721803238[/C][C]0.795651639098381[/C][/ROW]
[ROW][C]242[/C][C]0.404087330726959[/C][C]0.808174661453918[/C][C]0.595912669273041[/C][/ROW]
[ROW][C]243[/C][C]0.359930749232116[/C][C]0.719861498464232[/C][C]0.640069250767884[/C][/ROW]
[ROW][C]244[/C][C]0.300040337540058[/C][C]0.600080675080116[/C][C]0.699959662459942[/C][/ROW]
[ROW][C]245[/C][C]0.429841686144285[/C][C]0.859683372288571[/C][C]0.570158313855715[/C][/ROW]
[ROW][C]246[/C][C]0.345092325615053[/C][C]0.690184651230106[/C][C]0.654907674384947[/C][/ROW]
[ROW][C]247[/C][C]0.267969795574532[/C][C]0.535939591149063[/C][C]0.732030204425468[/C][/ROW]
[ROW][C]248[/C][C]0.411868209205384[/C][C]0.823736418410768[/C][C]0.588131790794616[/C][/ROW]
[ROW][C]249[/C][C]0.318882878681326[/C][C]0.637765757362652[/C][C]0.681117121318674[/C][/ROW]
[ROW][C]250[/C][C]0.230601273957032[/C][C]0.461202547914065[/C][C]0.769398726042968[/C][/ROW]
[ROW][C]251[/C][C]0.356227972801132[/C][C]0.712455945602263[/C][C]0.643772027198868[/C][/ROW]
[ROW][C]252[/C][C]0.872687703839301[/C][C]0.254624592321399[/C][C]0.127312296160699[/C][/ROW]
[ROW][C]253[/C][C]0.750320760850071[/C][C]0.499358478299857[/C][C]0.249679239149929[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226099&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226099&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
110.02376387491264080.04752774982528160.976236125087359
120.7080316718777070.5839366562445870.291968328122293
130.963511916928360.07297616614327980.0364880830716399
140.9378686851629420.1242626296741150.0621313148370576
150.9413668027250380.1172663945499230.0586331972749615
160.9103875035096880.1792249929806230.0896124964903116
170.9472942189716330.1054115620567340.0527057810283669
180.9201543268934580.1596913462130830.0798456731065415
190.8845906092839660.2308187814320670.115409390716034
200.8818691309831250.2362617380337490.118130869016875
210.9125366602403470.1749266795193060.0874633397596532
220.9102156218930070.1795687562139870.0897843781069935
230.9112363957536240.1775272084927510.0887636042463755
240.8820264129587780.2359471740824440.117973587041222
250.8586874599598070.2826250800803860.141312540040193
260.9988702631685470.002259473662905660.00112973683145283
270.9982221041106660.003555791778667280.00177789588933364
280.9971996872889280.005600625422144780.00280031271107239
290.9957488409347770.008502318130446680.00425115906522334
300.9970730836405780.005853832718844790.0029269163594224
310.9955891117714220.008821776457156830.00441088822857842
320.9936885026156660.01262299476866870.00631149738433435
330.9924190312786560.01516193744268860.00758096872134432
340.9890870290509930.02182594189801370.0109129709490068
350.9865862736129770.02682745277404580.0134137263870229
360.9814972598371250.03700548032574930.0185027401628747
370.9873632944747030.02527341105059390.0126367055252969
380.9826663199709470.03466736005810570.0173336800290529
390.9802170946642860.03956581067142780.0197829053357139
400.980552291689650.03889541662070040.0194477083103502
410.9745828960853880.05083420782922420.0254171039146121
420.9721593067655280.05568138646894450.0278406932344722
430.9634654039844290.07306919203114210.0365345960155711
440.9570869381184040.08582612376319230.0429130618815962
450.9450353182254520.1099293635490960.0549646817745481
460.9543995699407230.09120086011855370.0456004300592768
470.9420329798233330.1159340403533340.0579670201766668
480.9270449717579580.1459100564840840.0729550282420418
490.9383986856733890.1232026286532210.0616013143266105
500.934468903953650.13106219209270.0655310960463501
510.9202801279562260.1594397440875490.0797198720437744
520.9026592673327370.1946814653345250.0973407326672626
530.8886248534765570.2227502930468870.111375146523443
540.871587603017550.2568247939649010.12841239698245
550.8642655842084920.2714688315830160.135734415791508
560.8457506283021510.3084987433956970.154249371697849
570.8322903803505510.3354192392988980.167709619649449
580.803355667258780.3932886654824410.19664433274122
590.8458470001598980.3083059996802040.154152999840102
600.8414214695964290.3171570608071420.158578530403571
610.8598500333946020.2802999332107950.140149966605398
620.8586833467229550.282633306554090.141316653277045
630.9096446192918820.1807107614162360.0903553807081178
640.8968399509093930.2063200981812150.103160049090607
650.8865058268072380.2269883463855230.113494173192762
660.9590204746534780.0819590506930440.040979525346522
670.9574919714524120.08501605709517580.0425080285475879
680.9627469638762960.0745060722474070.0372530361237035
690.9577312225680790.08453755486384110.0422687774319205
700.9514005691102270.09719886177954540.0485994308897727
710.9409280766738340.1181438466523320.0590719233261661
720.9542298592850160.09154028142996860.0457701407149843
730.9441852360502610.1116295278994790.0558147639497394
740.9330715371181480.1338569257637040.066928462881852
750.9281346714797130.1437306570405740.0718653285202872
760.9144228242552020.1711543514895960.0855771757447979
770.9264444725802130.1471110548395740.0735555274197872
780.9125921606327840.1748156787344310.0874078393672156
790.9037940405445470.1924119189109070.0962059594554534
800.8968521194863210.2062957610273580.103147880513679
810.8784247374294350.243150525141130.121575262570565
820.858790013602360.282419972795280.14120998639764
830.8510202481800890.2979595036398220.148979751819911
840.8303485209441890.3393029581116230.169651479055811
850.8048463427685580.3903073144628840.195153657231442
860.7811720344361220.4376559311277560.218827965563878
870.7524248253183940.4951503493632110.247575174681606
880.7215571591026150.5568856817947690.278442840897385
890.795270416890040.4094591662199210.20472958310996
900.8293273235080850.3413453529838310.170672676491915
910.8047681599980590.3904636800038830.195231840001941
920.7811733637524290.4376532724951430.218826636247572
930.7575014451243070.4849971097513860.242498554875693
940.7324820453804640.5350359092390730.267517954619536
950.7059355433151960.5881289133696070.294064456684804
960.6801755425693810.6396489148612380.319824457430619
970.6523248693188510.6953502613622980.347675130681149
980.6508493178144680.6983013643710640.349150682185532
990.6168325304439410.7663349391121190.383167469556059
1000.6069490037186530.7861019925626940.393050996281347
1010.582450946784030.8350981064319390.41754905321597
1020.5528455794092440.8943088411815120.447154420590756
1030.6011349182093320.7977301635813360.398865081790668
1040.5899771187434240.8200457625131530.410022881256576
1050.6052701580040740.7894596839918530.394729841995926
1060.577837366245860.8443252675082790.42216263375414
1070.570148719773420.859702560453160.42985128022658
1080.6105095317147370.7789809365705260.389490468285263
1090.5829094746685580.8341810506628840.417090525331442
1100.5573263069893850.885347386021230.442673693010615
1110.5622759617704060.8754480764591870.437724038229594
1120.5909655757913380.8180688484173230.409034424208662
1130.5886919447435040.8226161105129930.411308055256496
1140.6778242717648610.6443514564702790.322175728235139
1150.6467554299484540.7064891401030910.353244570051546
1160.6221724496611080.7556551006777840.377827550338892
1170.5891821709295170.8216356581409650.410817829070483
1180.5653146637510510.8693706724978990.434685336248949
1190.5312638595572610.9374722808854780.468736140442739
1200.5001021340155270.9997957319689450.499897865984473
1210.4695037486030610.9390074972061220.530496251396939
1220.4388811019873910.8777622039747830.561118898012609
1230.4122991019651740.8245982039303480.587700898034826
1240.379910332308150.7598206646163010.62008966769185
1250.3686919677959460.7373839355918920.631308032204054
1260.3397040463668670.6794080927337340.660295953633133
1270.327022828603380.654045657206760.67297717139662
1280.4299738098885190.8599476197770370.570026190111481
1290.4133453534844620.8266907069689230.586654646515538
1300.4021804858322080.8043609716644160.597819514167792
1310.3866446916863670.7732893833727340.613355308313633
1320.3593145985954540.7186291971909080.640685401404546
1330.3800903236939310.7601806473878610.619909676306069
1340.3532285024613090.7064570049226180.646771497538691
1350.3648879146916430.7297758293832860.635112085308357
1360.3543942832590220.7087885665180450.645605716740978
1370.3252985027594230.6505970055188460.674701497240577
1380.3012694251422810.6025388502845620.698730574857719
1390.2758016816336930.5516033632673850.724198318366307
1400.2525556201058680.5051112402117360.747444379894132
1410.2255964165387670.4511928330775350.774403583461233
1420.2313564286950040.4627128573900080.768643571304996
1430.2067718582772440.4135437165544880.793228141722756
1440.1861373778476350.372274755695270.813862622152365
1450.1743181654163950.348636330832790.825681834583605
1460.166582008698690.3331640173973810.83341799130131
1470.1750264272422690.3500528544845380.824973572757731
1480.1912850076556270.3825700153112540.808714992344373
1490.2076545125378020.4153090250756040.792345487462198
1500.2085832065266080.4171664130532170.791416793473392
1510.1881788384813720.3763576769627450.811821161518628
1520.1691640156849090.3383280313698170.830835984315091
1530.1828903245591120.3657806491182230.817109675440888
1540.1981506617015410.3963013234030810.801849338298459
1550.1840271960091710.3680543920183420.815972803990829
1560.1612059074504420.3224118149008850.838794092549558
1570.1436493330907020.2872986661814050.856350666909298
1580.2254856697987910.4509713395975820.774514330201209
1590.2434830012354860.4869660024709730.756516998764514
1600.2229369473958720.4458738947917440.777063052604128
1610.2000007582854210.4000015165708430.799999241714579
1620.1768746977598940.3537493955197890.823125302240106
1630.1564517537069120.3129035074138240.843548246293088
1640.2624301006826670.5248602013653340.737569899317333
1650.2589806769637620.5179613539275250.741019323036238
1660.2550423514734810.5100847029469610.744957648526519
1670.2267772819796360.4535545639592710.773222718020364
1680.2047668084698830.4095336169397670.795233191530117
1690.2614986812125580.5229973624251170.738501318787442
1700.2863571042296320.5727142084592650.713642895770368
1710.2587920469751630.5175840939503260.741207953024837
1720.2538221287061630.5076442574123260.746177871293837
1730.4188971187807870.8377942375615730.581102881219213
1740.4049379420986030.8098758841972050.595062057901397
1750.4274318738002520.8548637476005050.572568126199748
1760.4366315132890130.8732630265780250.563368486710987
1770.4946636490933250.989327298186650.505336350906675
1780.4610640554429180.9221281108858350.538935944557082
1790.4383905801924150.876781160384830.561609419807585
1800.4378381078229790.8756762156459580.562161892177021
1810.4005406853273040.8010813706546070.599459314672696
1820.3935009663362810.7870019326725620.606499033663719
1830.3564622869590060.7129245739180120.643537713040994
1840.3297881187921080.6595762375842150.670211881207892
1850.3449767302117510.6899534604235020.655023269788249
1860.3375439304671850.6750878609343690.662456069532815
1870.3034825190067380.6069650380134760.696517480993262
1880.2765391432241990.5530782864483980.723460856775801
1890.2458084552626730.4916169105253460.754191544737327
1900.2232753314982020.4465506629964030.776724668501798
1910.2271321340797330.4542642681594670.772867865920267
1920.2090273012751060.4180546025502120.790972698724894
1930.2269388244377390.4538776488754770.773061175562261
1940.2150453328546380.4300906657092760.784954667145362
1950.2144764642924540.4289529285849080.785523535707546
1960.2258494226202740.4516988452405490.774150577379726
1970.2729703722132280.5459407444264550.727029627786772
1980.2547460233585830.5094920467171670.745253976641417
1990.2882645720863390.5765291441726780.711735427913661
2000.255383860135480.510767720270960.74461613986452
2010.2929840428058140.5859680856116270.707015957194187
2020.2713838497193830.5427676994387660.728616150280617
2030.3331418597826950.6662837195653890.666858140217305
2040.2971824046214430.5943648092428860.702817595378557
2050.2630037235299740.5260074470599470.736996276470026
2060.2415648801610870.4831297603221730.758435119838913
2070.2101927129220390.4203854258440790.789807287077961
2080.2297279570655260.4594559141310520.770272042934474
2090.1978218589797820.3956437179595640.802178141020218
2100.2145419787739480.4290839575478970.785458021226052
2110.2425619820990130.4851239641980260.757438017900987
2120.2267583105897450.4535166211794910.773241689410255
2130.1993289884888530.3986579769777050.800671011511147
2140.2489149105669760.4978298211339530.751085089433024
2150.2214953742474520.4429907484949040.778504625752548
2160.2081715005379950.4163430010759890.791828499462005
2170.241196622850630.4823932457012590.75880337714937
2180.2105090145294930.4210180290589860.789490985470507
2190.1964943610737090.3929887221474170.803505638926291
2200.2040386115070520.4080772230141040.795961388492948
2210.2122162155492440.4244324310984870.787783784450756
2220.2133140226163860.4266280452327720.786685977383614
2230.1972153627921160.3944307255842310.802784637207884
2240.1651670245528630.3303340491057260.834832975447137
2250.1495246973519580.2990493947039150.850475302648042
2260.1784143124046180.3568286248092360.821585687595382
2270.370584744610050.7411694892200990.62941525538995
2280.3471796404611320.6943592809222640.652820359538868
2290.3201211768522730.6402423537045450.679878823147727
2300.3049175554976140.6098351109952290.695082444502386
2310.2622560084292830.5245120168585660.737743991570717
2320.301634071407960.603268142815920.69836592859204
2330.2569107036217740.5138214072435480.743089296378226
2340.2151005420212740.4302010840425470.784899457978727
2350.2143202422081370.4286404844162750.785679757791863
2360.1900263331689510.3800526663379010.809973666831049
2370.1591396516991820.3182793033983640.840860348300818
2380.124004911954720.2480098239094390.87599508804528
2390.2410433606853120.4820867213706230.758956639314688
2400.2364715467585610.4729430935171220.763528453241439
2410.2043483609016190.4086967218032380.795651639098381
2420.4040873307269590.8081746614539180.595912669273041
2430.3599307492321160.7198614984642320.640069250767884
2440.3000403375400580.6000806750801160.699959662459942
2450.4298416861442850.8596833722885710.570158313855715
2460.3450923256150530.6901846512301060.654907674384947
2470.2679697955745320.5359395911490630.732030204425468
2480.4118682092053840.8237364184107680.588131790794616
2490.3188828786813260.6377657573626520.681117121318674
2500.2306012739570320.4612025479140650.769398726042968
2510.3562279728011320.7124559456022630.643772027198868
2520.8726877038393010.2546245923213990.127312296160699
2530.7503207608500710.4993584782998570.249679239149929






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level60.0246913580246914NOK
5% type I error level160.065843621399177NOK
10% type I error level280.11522633744856NOK

\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 & 6 & 0.0246913580246914 & NOK \tabularnewline
5% type I error level & 16 & 0.065843621399177 & NOK \tabularnewline
10% type I error level & 28 & 0.11522633744856 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226099&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]6[/C][C]0.0246913580246914[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]16[/C][C]0.065843621399177[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]28[/C][C]0.11522633744856[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226099&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226099&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 level60.0246913580246914NOK
5% type I error level160.065843621399177NOK
10% type I error level280.11522633744856NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt 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')
}