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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 computationFri, 15 Nov 2013 07:15:18 -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/15/t13845207172ba3szkf78prexa.htm/, Retrieved Tue, 30 Apr 2024 20:22:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=225459, Retrieved Tue, 30 Apr 2024 20:22:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact106

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] [WS 7] [2013-11-15 12:15:18] [a17fd0651b2d0a0974784add16174701] [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 time17 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 17 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225459&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]17 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225459&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225459&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 time17 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 1.32524824354712 -0.0106466905173504Connected[t] + 0.0375201181118368Separate[t] + 0.574624311162201Learning[t] -0.00589175215589685Happiness[t] -0.0103371273021427Depression[t] + 0.0133695427793441Belonging[t] -0.0142351346260244Belonging_Final[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Software[t] =  +  1.32524824354712 -0.0106466905173504Connected[t] +  0.0375201181118368Separate[t] +  0.574624311162201Learning[t] -0.00589175215589685Happiness[t] -0.0103371273021427Depression[t] +  0.0133695427793441Belonging[t] -0.0142351346260244Belonging_Final[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225459&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Software[t] =  +  1.32524824354712 -0.0106466905173504Connected[t] +  0.0375201181118368Separate[t] +  0.574624311162201Learning[t] -0.00589175215589685Happiness[t] -0.0103371273021427Depression[t] +  0.0133695427793441Belonging[t] -0.0142351346260244Belonging_Final[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225459&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225459&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
Software[t] = + 1.32524824354712 -0.0106466905173504Connected[t] + 0.0375201181118368Separate[t] + 0.574624311162201Learning[t] -0.00589175215589685Happiness[t] -0.0103371273021427Depression[t] + 0.0133695427793441Belonging[t] -0.0142351346260244Belonging_Final[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.325248243547121.877460.70590.4809090.240455
Connected-0.01064669051735040.033949-0.31360.7540750.377037
Separate0.03752011811183680.0346881.08160.2804270.140213
Learning0.5746243111622010.04904711.715800
Happiness-0.005891752155896850.056694-0.10390.9173120.458656
Depression-0.01033712730214270.041457-0.24930.8032930.401647
Belonging0.01336954277934410.0368110.36320.7167570.358378
Belonging_Final-0.01423513462602440.054905-0.25930.7956380.397819

\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) & 1.32524824354712 & 1.87746 & 0.7059 & 0.480909 & 0.240455 \tabularnewline
Connected & -0.0106466905173504 & 0.033949 & -0.3136 & 0.754075 & 0.377037 \tabularnewline
Separate & 0.0375201181118368 & 0.034688 & 1.0816 & 0.280427 & 0.140213 \tabularnewline
Learning & 0.574624311162201 & 0.049047 & 11.7158 & 0 & 0 \tabularnewline
Happiness & -0.00589175215589685 & 0.056694 & -0.1039 & 0.917312 & 0.458656 \tabularnewline
Depression & -0.0103371273021427 & 0.041457 & -0.2493 & 0.803293 & 0.401647 \tabularnewline
Belonging & 0.0133695427793441 & 0.036811 & 0.3632 & 0.716757 & 0.358378 \tabularnewline
Belonging_Final & -0.0142351346260244 & 0.054905 & -0.2593 & 0.795638 & 0.397819 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225459&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]1.32524824354712[/C][C]1.87746[/C][C]0.7059[/C][C]0.480909[/C][C]0.240455[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0106466905173504[/C][C]0.033949[/C][C]-0.3136[/C][C]0.754075[/C][C]0.377037[/C][/ROW]
[ROW][C]Separate[/C][C]0.0375201181118368[/C][C]0.034688[/C][C]1.0816[/C][C]0.280427[/C][C]0.140213[/C][/ROW]
[ROW][C]Learning[/C][C]0.574624311162201[/C][C]0.049047[/C][C]11.7158[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.00589175215589685[/C][C]0.056694[/C][C]-0.1039[/C][C]0.917312[/C][C]0.458656[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0103371273021427[/C][C]0.041457[/C][C]-0.2493[/C][C]0.803293[/C][C]0.401647[/C][/ROW]
[ROW][C]Belonging[/C][C]0.0133695427793441[/C][C]0.036811[/C][C]0.3632[/C][C]0.716757[/C][C]0.358378[/C][/ROW]
[ROW][C]Belonging_Final[/C][C]-0.0142351346260244[/C][C]0.054905[/C][C]-0.2593[/C][C]0.795638[/C][C]0.397819[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225459&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225459&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)1.325248243547121.877460.70590.4809090.240455
Connected-0.01064669051735040.033949-0.31360.7540750.377037
Separate0.03752011811183680.0346881.08160.2804270.140213
Learning0.5746243111622010.04904711.715800
Happiness-0.005891752155896850.056694-0.10390.9173120.458656
Depression-0.01033712730214270.041457-0.24930.8032930.401647
Belonging0.01336954277934410.0368110.36320.7167570.358378
Belonging_Final-0.01423513462602440.054905-0.25930.7956380.397819






Multiple Linear Regression - Regression Statistics
Multiple R0.626467947710299
R-squared0.392462089508353
Adjusted R-squared0.375849724768348
F-TEST (value)23.6246973655246
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.83290619779655
Sum Squared Residuals860.043553259773

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.626467947710299 \tabularnewline
R-squared & 0.392462089508353 \tabularnewline
Adjusted R-squared & 0.375849724768348 \tabularnewline
F-TEST (value) & 23.6246973655246 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 256 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.83290619779655 \tabularnewline
Sum Squared Residuals & 860.043553259773 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225459&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.626467947710299[/C][/ROW]
[ROW][C]R-squared[/C][C]0.392462089508353[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.375849724768348[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]23.6246973655246[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]256[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]1.83290619779655[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]860.043553259773[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225459&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225459&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 R0.626467947710299
R-squared0.392462089508353
Adjusted R-squared0.375849724768348
F-TEST (value)23.6246973655246
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.83290619779655
Sum Squared Residuals860.043553259773






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1129.831145867158352.16885413284165
21111.468580317173-0.468580317173051
31513.31189868722151.68810131277846
4610.9701016956855-4.97010169568547
51310.44616684295972.55383315704033
6109.654489488725570.345510511274428
71212.8629973422319-0.862997342231856
81411.10919858058262.89080141941745
91210.45692942724811.54307057275191
10911.1007248366287-2.10072483662867
111011.4329278671713-1.43292786717128
121211.46919593736680.530804062633232
131211.51177639722920.48822360277077
141111.5429888309169-0.542988830916898
151512.3300303911662.66996960883399
161210.87784703436811.12215296563194
171010.8969061698015-0.896906169801453
181214.0328790231848-2.03287902318477
191112.7651838175469-1.76518381754691
201211.40013530762940.599864692370568
211111.5112020788709-0.511202078870949
221211.42556740707690.574432592923124
231313.2993195233196-0.299319523319582
241111.5951678857416-0.595167885741614
251212.0749698742032-0.0749698742031561
261312.1124431814740.887556818526027
271011.6451585249252-1.64515852492519
281411.04012758256052.95987241743949
291211.57520754680970.424792453190322
301010.3163865339469-0.316386533946895
311210.96242881186791.03757118813209
3289.15446929297082-1.15446929297082
331010.2727804008856-0.272780400885618
341211.69775375568790.302246244312052
351210.30820799185121.69179200814885
3678.1148877171814-1.1148877171814
3797.981673890122761.01832610987724
381210.34957657733421.65042342266585
391011.5313448573675-1.53134485736747
401011.5294256981593-1.52942569815932
411011.4933081320218-1.49330813202178
421210.38354698811.61645301189998
431513.68903482122491.31096517877511
441010.2740245724197-0.274024572419661
451010.1385157821097-0.138515782109744
46128.705923846415353.29407615358465
471310.50419803020082.49580196979917
481111.0147709727017-0.0147709727016851
491111.6979746669636-0.697974666963572
501210.33789161166691.66210838833312
511411.74292946288882.25707053711115
521010.2540477153803-0.254047715380349
53129.182913427411272.81708657258873
541311.54168888422371.45831111577633
5557.50222364939796-2.50222364939796
56610.3980344801777-4.39803448017774
571211.49981472584630.500185274153718
581211.60264049680690.397359503193082
591111.0912031489452-0.0912031489451753
601011.5202863400697-1.52028634006966
6178.95108746508688-1.95108746508688
621211.57858242847150.421417571528502
631411.66787603742452.33212396257551
641110.37986806640090.620131933599058
651211.34981033617880.650189663821168
661312.3088876391250.691112360874971
671412.64238285104881.35761714895119
681112.5597178676945-1.55971786769446
69129.384910913833782.61508908616622
701211.62637415708630.373625842913699
7188.07018762509651-0.0701876250965071
721110.46857660542920.531423394570844
731412.94667053904991.05332946095015
741412.96358195876661.03641804123338
751211.39127661738550.608723382614529
76911.9091795275438-2.90917952754383
771311.60276880719531.39723119280473
781111.3642019920859-0.364201992085947
79129.79802514495692.2019748550431
801211.22092180569980.779078194300202
811211.71791369120490.282086308795064
821211.66209347527760.33790652472237
831210.93440153138181.06559846861821
841111.0034421768309-0.00344217683090933
851011.4745563780127-1.47455637801265
86910.5680746795337-1.56807467953366
871211.56167319054570.438326809454327
881211.43167315658490.568326843415071
891210.88653416149481.11346583850519
9099.32803481199869-0.328034811998688
911511.93177063412573.06822936587432
921211.83680756056640.163192439433554
931210.82995672769871.1700432723013
94129.806919032628612.19308096737139
951011.6472762040983-1.64727620409826
961311.51280640706531.48719359293469
97911.5015419289876-2.5015419289876
981211.58677200490670.413227995093293
991010.549540258362-0.549540258361995
1001411.63736036789652.36263963210347
1011111.5378143089306-0.537814308930635
1021514.00056855187540.999431448124595
1031110.76047861666160.239521383338397
1041111.7645532744037-0.764553274403709
105129.646197648725112.35380235127489
1061212.1415489165486-0.141548916548595
1071211.62936394653430.370636053465749
1081111.4873819337667-0.487381933766677
10979.21971359820331-2.21971359820331
1101211.63860859354680.361391406453196
1111411.57048777267452.42951222732553
1121112.4947784611353-1.49477846113534
113119.806748794805241.19325120519475
114109.219433301529170.780566698470834
1151312.67288131123210.327118688767926
1161310.54444409223212.45555590776793
117810.5613521042621-2.56135210426206
118119.906331757077331.09366824292267
1191211.64817224050410.351827759495924
120119.858705803744011.141294196256
1211311.33629775114451.66370224885546
1221210.07318201025231.92681798974766
1231411.72703478430162.27296521569842
1241310.85776659588152.14223340411854
1251511.62419508758993.3758049124101
1261010.9675054010245-0.967505401024485
1271112.2481609393575-1.24816093935747
128911.0468155145957-2.04681551459566
129119.199771926378271.80022807362173
1301011.5777677279679-1.57776772796791
131118.02724392321192.9727560767881
132811.6645050174388-3.66450501743877
133119.115064580625971.88493541937403
1341210.52393370183591.47606629816406
1351210.83496342400881.1650365759912
13699.27233221839196-0.272332218391959
1371110.91303079569760.0869692043023909
138108.633441372349681.36655862765032
13989.20795049536374-1.20795049536374
14098.767492020663130.232507979336874
141811.5146754534555-3.51467545345547
142911.1715184764109-2.1715184764109
1431512.27645343773432.72354656226566
1441111.2143693239249-0.214369323924928
14588.00772786405441-0.00772786405441555
1461312.46955529861810.530444701381938
147129.824853204386242.17514679561376
1481211.50515687651340.494843123486583
14999.69510314207846-0.695103142078459
15078.29383716081634-1.29383716081634
1511311.02051488937131.97948511062867
152911.761309070255-2.76130907025502
153611.7514022634679-5.75140226346793
154810.302054850673-2.30205485067298
15587.937445630959870.0625543690401274
1561511.93177063412573.06822936587432
15769.92609791268162-3.92609791268162
158911.0468155145957-2.04681551459566
1591111.5853163279229-0.585316327922916
16089.46032591404247-1.46032591404247
16189.80979650720862-1.80979650720862
162109.44669717330230.553302826697704
16389.0528929676546-1.0528929676546
1641412.01098638740361.98901361259637
1651011.151420517948-1.15142051794805
16687.891206991869450.108793008130549
1671110.44175959891940.558240401080564
168128.454884099701773.54511590029823
1691210.02526726968331.97473273031674
1701211.77326299069530.226737009304685
17158.96971454563988-3.96971454563988
1721211.64214832810330.357851671896677
173109.294131512533360.705868487466639
17477.16436534170705-0.164365341707047
175128.995632893145843.00436710685416
1761111.163974437837-0.163974437837032
17789.14357463988117-1.14357463988117
17899.10903142012653-0.109031420126534
1791010.3175443942803-0.317544394280289
18099.38635156340575-0.386351563405752
1811211.54268355246350.457316447536502
18268.54157696438228-2.54157696438228
1831513.37122438996421.62877561003581
1841210.9411036079941.05889639200603
185126.937559316706815.06244068329319
1861211.6460085085310.353991491469044
1871112.1362957548222-1.13629575482223
18879.17914412006931-2.17914412006931
18978.47216035002414-1.47216035002414
19058.63462873386742-3.63462873386742
1911210.53228297137491.46771702862507
1921211.80598168865820.194018311341756
19339.19939938424006-6.19939938424006
1941111.5499152462762-0.549915246276219
195109.758479063678550.241520936321452
1961211.09122536760050.908774632399493
197911.4143908746151-2.41439087461511
1981211.72728745211670.272712547883319
199910.3154839456045-1.31548394560453
2001211.63520048577990.364799514220089
2011211.39283564466710.6071643553329
2021010.3807428275262-0.380742827526229
20398.638223717392320.361776282607678
204129.061809317399472.93819068260053
205811.0173677482417-3.01736774824173
2061111.0593558556504-0.0593558556504032
2071111.6817960981777-0.681796098177671
2081211.50192941315380.498070586846156
209108.589208216149691.41079178385031
2101011.0137606311245-1.01376063112446
211129.154404816891782.84559518310822
212129.595713886670672.40428611332932
2131111.2107788076307-0.210778807630742
214810.9912280814446-2.99122808144456
2151211.54562073127310.454379268726853
2161010.0725050418521-0.0725050418521001
2171112.2380408288634-1.23804082886342
2181010.3933666777677-0.393366677767742
21989.7538140090542-1.7538140090542
2201211.14759610150170.852403898498348
221129.833308275331532.16669172466847
2221010.4319693578599-0.431969357859882
2231210.89552837435871.10447162564134
22499.24618707954441-0.24618707954441
22599.86545176507268-0.865451765072683
22667.12264172479158-1.12264172479158
2271010.267129149499-0.267129149499015
228910.4578718928652-1.4578718928652
22998.521918310379260.478081689620741
23099.29652191081022-0.296521910810222
23169.68957704502704-3.68957704502704
232108.196908692779991.80309130722001
233611.5357853479969-5.53578534799692
2341412.52560237609861.47439762390145
235109.782979566998660.217020433001337
236108.540186618863831.45981338113617
23764.41331781233081.5866821876692
238129.41286888240462.5871311175954
2391211.55147722791730.448522772082698
24077.95057370460939-0.950573704609391
24189.38190844361464-1.38190844361465
242119.142361697333081.85763830266692
24337.8650560344008-4.8650560344008
24469.73778339392977-3.73778339392977
2451010.8225533314636-0.822553331463583
24689.27826106412865-1.27826106412866
247910.4078670696946-1.40786706969456
24897.744056796127891.25594320387211
24988.77694481951701-0.776944819517015
25098.792998504685370.207001495314632
25178.69664855178853-1.69664855178853
25278.04224341487795-1.04224341487795
25369.2457335701095-3.2457335701095
254911.4795908036357-2.47959080363571
255109.101327121485320.898672878514683
2561110.30405566181270.695944338187263
2571211.65534690095670.344653099043277
258810.2609971797956-2.26099717979557
259119.745806409994681.25419359000532
26034.60454537359994-1.60454537359994
2611110.89094137464760.109058625352396
262128.822959256355453.17704074364455
26378.5760546338294-1.5760546338294
264910.405844587779-1.40584458777901

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 9.83114586715835 & 2.16885413284165 \tabularnewline
2 & 11 & 11.468580317173 & -0.468580317173051 \tabularnewline
3 & 15 & 13.3118986872215 & 1.68810131277846 \tabularnewline
4 & 6 & 10.9701016956855 & -4.97010169568547 \tabularnewline
5 & 13 & 10.4461668429597 & 2.55383315704033 \tabularnewline
6 & 10 & 9.65448948872557 & 0.345510511274428 \tabularnewline
7 & 12 & 12.8629973422319 & -0.862997342231856 \tabularnewline
8 & 14 & 11.1091985805826 & 2.89080141941745 \tabularnewline
9 & 12 & 10.4569294272481 & 1.54307057275191 \tabularnewline
10 & 9 & 11.1007248366287 & -2.10072483662867 \tabularnewline
11 & 10 & 11.4329278671713 & -1.43292786717128 \tabularnewline
12 & 12 & 11.4691959373668 & 0.530804062633232 \tabularnewline
13 & 12 & 11.5117763972292 & 0.48822360277077 \tabularnewline
14 & 11 & 11.5429888309169 & -0.542988830916898 \tabularnewline
15 & 15 & 12.330030391166 & 2.66996960883399 \tabularnewline
16 & 12 & 10.8778470343681 & 1.12215296563194 \tabularnewline
17 & 10 & 10.8969061698015 & -0.896906169801453 \tabularnewline
18 & 12 & 14.0328790231848 & -2.03287902318477 \tabularnewline
19 & 11 & 12.7651838175469 & -1.76518381754691 \tabularnewline
20 & 12 & 11.4001353076294 & 0.599864692370568 \tabularnewline
21 & 11 & 11.5112020788709 & -0.511202078870949 \tabularnewline
22 & 12 & 11.4255674070769 & 0.574432592923124 \tabularnewline
23 & 13 & 13.2993195233196 & -0.299319523319582 \tabularnewline
24 & 11 & 11.5951678857416 & -0.595167885741614 \tabularnewline
25 & 12 & 12.0749698742032 & -0.0749698742031561 \tabularnewline
26 & 13 & 12.112443181474 & 0.887556818526027 \tabularnewline
27 & 10 & 11.6451585249252 & -1.64515852492519 \tabularnewline
28 & 14 & 11.0401275825605 & 2.95987241743949 \tabularnewline
29 & 12 & 11.5752075468097 & 0.424792453190322 \tabularnewline
30 & 10 & 10.3163865339469 & -0.316386533946895 \tabularnewline
31 & 12 & 10.9624288118679 & 1.03757118813209 \tabularnewline
32 & 8 & 9.15446929297082 & -1.15446929297082 \tabularnewline
33 & 10 & 10.2727804008856 & -0.272780400885618 \tabularnewline
34 & 12 & 11.6977537556879 & 0.302246244312052 \tabularnewline
35 & 12 & 10.3082079918512 & 1.69179200814885 \tabularnewline
36 & 7 & 8.1148877171814 & -1.1148877171814 \tabularnewline
37 & 9 & 7.98167389012276 & 1.01832610987724 \tabularnewline
38 & 12 & 10.3495765773342 & 1.65042342266585 \tabularnewline
39 & 10 & 11.5313448573675 & -1.53134485736747 \tabularnewline
40 & 10 & 11.5294256981593 & -1.52942569815932 \tabularnewline
41 & 10 & 11.4933081320218 & -1.49330813202178 \tabularnewline
42 & 12 & 10.3835469881 & 1.61645301189998 \tabularnewline
43 & 15 & 13.6890348212249 & 1.31096517877511 \tabularnewline
44 & 10 & 10.2740245724197 & -0.274024572419661 \tabularnewline
45 & 10 & 10.1385157821097 & -0.138515782109744 \tabularnewline
46 & 12 & 8.70592384641535 & 3.29407615358465 \tabularnewline
47 & 13 & 10.5041980302008 & 2.49580196979917 \tabularnewline
48 & 11 & 11.0147709727017 & -0.0147709727016851 \tabularnewline
49 & 11 & 11.6979746669636 & -0.697974666963572 \tabularnewline
50 & 12 & 10.3378916116669 & 1.66210838833312 \tabularnewline
51 & 14 & 11.7429294628888 & 2.25707053711115 \tabularnewline
52 & 10 & 10.2540477153803 & -0.254047715380349 \tabularnewline
53 & 12 & 9.18291342741127 & 2.81708657258873 \tabularnewline
54 & 13 & 11.5416888842237 & 1.45831111577633 \tabularnewline
55 & 5 & 7.50222364939796 & -2.50222364939796 \tabularnewline
56 & 6 & 10.3980344801777 & -4.39803448017774 \tabularnewline
57 & 12 & 11.4998147258463 & 0.500185274153718 \tabularnewline
58 & 12 & 11.6026404968069 & 0.397359503193082 \tabularnewline
59 & 11 & 11.0912031489452 & -0.0912031489451753 \tabularnewline
60 & 10 & 11.5202863400697 & -1.52028634006966 \tabularnewline
61 & 7 & 8.95108746508688 & -1.95108746508688 \tabularnewline
62 & 12 & 11.5785824284715 & 0.421417571528502 \tabularnewline
63 & 14 & 11.6678760374245 & 2.33212396257551 \tabularnewline
64 & 11 & 10.3798680664009 & 0.620131933599058 \tabularnewline
65 & 12 & 11.3498103361788 & 0.650189663821168 \tabularnewline
66 & 13 & 12.308887639125 & 0.691112360874971 \tabularnewline
67 & 14 & 12.6423828510488 & 1.35761714895119 \tabularnewline
68 & 11 & 12.5597178676945 & -1.55971786769446 \tabularnewline
69 & 12 & 9.38491091383378 & 2.61508908616622 \tabularnewline
70 & 12 & 11.6263741570863 & 0.373625842913699 \tabularnewline
71 & 8 & 8.07018762509651 & -0.0701876250965071 \tabularnewline
72 & 11 & 10.4685766054292 & 0.531423394570844 \tabularnewline
73 & 14 & 12.9466705390499 & 1.05332946095015 \tabularnewline
74 & 14 & 12.9635819587666 & 1.03641804123338 \tabularnewline
75 & 12 & 11.3912766173855 & 0.608723382614529 \tabularnewline
76 & 9 & 11.9091795275438 & -2.90917952754383 \tabularnewline
77 & 13 & 11.6027688071953 & 1.39723119280473 \tabularnewline
78 & 11 & 11.3642019920859 & -0.364201992085947 \tabularnewline
79 & 12 & 9.7980251449569 & 2.2019748550431 \tabularnewline
80 & 12 & 11.2209218056998 & 0.779078194300202 \tabularnewline
81 & 12 & 11.7179136912049 & 0.282086308795064 \tabularnewline
82 & 12 & 11.6620934752776 & 0.33790652472237 \tabularnewline
83 & 12 & 10.9344015313818 & 1.06559846861821 \tabularnewline
84 & 11 & 11.0034421768309 & -0.00344217683090933 \tabularnewline
85 & 10 & 11.4745563780127 & -1.47455637801265 \tabularnewline
86 & 9 & 10.5680746795337 & -1.56807467953366 \tabularnewline
87 & 12 & 11.5616731905457 & 0.438326809454327 \tabularnewline
88 & 12 & 11.4316731565849 & 0.568326843415071 \tabularnewline
89 & 12 & 10.8865341614948 & 1.11346583850519 \tabularnewline
90 & 9 & 9.32803481199869 & -0.328034811998688 \tabularnewline
91 & 15 & 11.9317706341257 & 3.06822936587432 \tabularnewline
92 & 12 & 11.8368075605664 & 0.163192439433554 \tabularnewline
93 & 12 & 10.8299567276987 & 1.1700432723013 \tabularnewline
94 & 12 & 9.80691903262861 & 2.19308096737139 \tabularnewline
95 & 10 & 11.6472762040983 & -1.64727620409826 \tabularnewline
96 & 13 & 11.5128064070653 & 1.48719359293469 \tabularnewline
97 & 9 & 11.5015419289876 & -2.5015419289876 \tabularnewline
98 & 12 & 11.5867720049067 & 0.413227995093293 \tabularnewline
99 & 10 & 10.549540258362 & -0.549540258361995 \tabularnewline
100 & 14 & 11.6373603678965 & 2.36263963210347 \tabularnewline
101 & 11 & 11.5378143089306 & -0.537814308930635 \tabularnewline
102 & 15 & 14.0005685518754 & 0.999431448124595 \tabularnewline
103 & 11 & 10.7604786166616 & 0.239521383338397 \tabularnewline
104 & 11 & 11.7645532744037 & -0.764553274403709 \tabularnewline
105 & 12 & 9.64619764872511 & 2.35380235127489 \tabularnewline
106 & 12 & 12.1415489165486 & -0.141548916548595 \tabularnewline
107 & 12 & 11.6293639465343 & 0.370636053465749 \tabularnewline
108 & 11 & 11.4873819337667 & -0.487381933766677 \tabularnewline
109 & 7 & 9.21971359820331 & -2.21971359820331 \tabularnewline
110 & 12 & 11.6386085935468 & 0.361391406453196 \tabularnewline
111 & 14 & 11.5704877726745 & 2.42951222732553 \tabularnewline
112 & 11 & 12.4947784611353 & -1.49477846113534 \tabularnewline
113 & 11 & 9.80674879480524 & 1.19325120519475 \tabularnewline
114 & 10 & 9.21943330152917 & 0.780566698470834 \tabularnewline
115 & 13 & 12.6728813112321 & 0.327118688767926 \tabularnewline
116 & 13 & 10.5444440922321 & 2.45555590776793 \tabularnewline
117 & 8 & 10.5613521042621 & -2.56135210426206 \tabularnewline
118 & 11 & 9.90633175707733 & 1.09366824292267 \tabularnewline
119 & 12 & 11.6481722405041 & 0.351827759495924 \tabularnewline
120 & 11 & 9.85870580374401 & 1.141294196256 \tabularnewline
121 & 13 & 11.3362977511445 & 1.66370224885546 \tabularnewline
122 & 12 & 10.0731820102523 & 1.92681798974766 \tabularnewline
123 & 14 & 11.7270347843016 & 2.27296521569842 \tabularnewline
124 & 13 & 10.8577665958815 & 2.14223340411854 \tabularnewline
125 & 15 & 11.6241950875899 & 3.3758049124101 \tabularnewline
126 & 10 & 10.9675054010245 & -0.967505401024485 \tabularnewline
127 & 11 & 12.2481609393575 & -1.24816093935747 \tabularnewline
128 & 9 & 11.0468155145957 & -2.04681551459566 \tabularnewline
129 & 11 & 9.19977192637827 & 1.80022807362173 \tabularnewline
130 & 10 & 11.5777677279679 & -1.57776772796791 \tabularnewline
131 & 11 & 8.0272439232119 & 2.9727560767881 \tabularnewline
132 & 8 & 11.6645050174388 & -3.66450501743877 \tabularnewline
133 & 11 & 9.11506458062597 & 1.88493541937403 \tabularnewline
134 & 12 & 10.5239337018359 & 1.47606629816406 \tabularnewline
135 & 12 & 10.8349634240088 & 1.1650365759912 \tabularnewline
136 & 9 & 9.27233221839196 & -0.272332218391959 \tabularnewline
137 & 11 & 10.9130307956976 & 0.0869692043023909 \tabularnewline
138 & 10 & 8.63344137234968 & 1.36655862765032 \tabularnewline
139 & 8 & 9.20795049536374 & -1.20795049536374 \tabularnewline
140 & 9 & 8.76749202066313 & 0.232507979336874 \tabularnewline
141 & 8 & 11.5146754534555 & -3.51467545345547 \tabularnewline
142 & 9 & 11.1715184764109 & -2.1715184764109 \tabularnewline
143 & 15 & 12.2764534377343 & 2.72354656226566 \tabularnewline
144 & 11 & 11.2143693239249 & -0.214369323924928 \tabularnewline
145 & 8 & 8.00772786405441 & -0.00772786405441555 \tabularnewline
146 & 13 & 12.4695552986181 & 0.530444701381938 \tabularnewline
147 & 12 & 9.82485320438624 & 2.17514679561376 \tabularnewline
148 & 12 & 11.5051568765134 & 0.494843123486583 \tabularnewline
149 & 9 & 9.69510314207846 & -0.695103142078459 \tabularnewline
150 & 7 & 8.29383716081634 & -1.29383716081634 \tabularnewline
151 & 13 & 11.0205148893713 & 1.97948511062867 \tabularnewline
152 & 9 & 11.761309070255 & -2.76130907025502 \tabularnewline
153 & 6 & 11.7514022634679 & -5.75140226346793 \tabularnewline
154 & 8 & 10.302054850673 & -2.30205485067298 \tabularnewline
155 & 8 & 7.93744563095987 & 0.0625543690401274 \tabularnewline
156 & 15 & 11.9317706341257 & 3.06822936587432 \tabularnewline
157 & 6 & 9.92609791268162 & -3.92609791268162 \tabularnewline
158 & 9 & 11.0468155145957 & -2.04681551459566 \tabularnewline
159 & 11 & 11.5853163279229 & -0.585316327922916 \tabularnewline
160 & 8 & 9.46032591404247 & -1.46032591404247 \tabularnewline
161 & 8 & 9.80979650720862 & -1.80979650720862 \tabularnewline
162 & 10 & 9.4466971733023 & 0.553302826697704 \tabularnewline
163 & 8 & 9.0528929676546 & -1.0528929676546 \tabularnewline
164 & 14 & 12.0109863874036 & 1.98901361259637 \tabularnewline
165 & 10 & 11.151420517948 & -1.15142051794805 \tabularnewline
166 & 8 & 7.89120699186945 & 0.108793008130549 \tabularnewline
167 & 11 & 10.4417595989194 & 0.558240401080564 \tabularnewline
168 & 12 & 8.45488409970177 & 3.54511590029823 \tabularnewline
169 & 12 & 10.0252672696833 & 1.97473273031674 \tabularnewline
170 & 12 & 11.7732629906953 & 0.226737009304685 \tabularnewline
171 & 5 & 8.96971454563988 & -3.96971454563988 \tabularnewline
172 & 12 & 11.6421483281033 & 0.357851671896677 \tabularnewline
173 & 10 & 9.29413151253336 & 0.705868487466639 \tabularnewline
174 & 7 & 7.16436534170705 & -0.164365341707047 \tabularnewline
175 & 12 & 8.99563289314584 & 3.00436710685416 \tabularnewline
176 & 11 & 11.163974437837 & -0.163974437837032 \tabularnewline
177 & 8 & 9.14357463988117 & -1.14357463988117 \tabularnewline
178 & 9 & 9.10903142012653 & -0.109031420126534 \tabularnewline
179 & 10 & 10.3175443942803 & -0.317544394280289 \tabularnewline
180 & 9 & 9.38635156340575 & -0.386351563405752 \tabularnewline
181 & 12 & 11.5426835524635 & 0.457316447536502 \tabularnewline
182 & 6 & 8.54157696438228 & -2.54157696438228 \tabularnewline
183 & 15 & 13.3712243899642 & 1.62877561003581 \tabularnewline
184 & 12 & 10.941103607994 & 1.05889639200603 \tabularnewline
185 & 12 & 6.93755931670681 & 5.06244068329319 \tabularnewline
186 & 12 & 11.646008508531 & 0.353991491469044 \tabularnewline
187 & 11 & 12.1362957548222 & -1.13629575482223 \tabularnewline
188 & 7 & 9.17914412006931 & -2.17914412006931 \tabularnewline
189 & 7 & 8.47216035002414 & -1.47216035002414 \tabularnewline
190 & 5 & 8.63462873386742 & -3.63462873386742 \tabularnewline
191 & 12 & 10.5322829713749 & 1.46771702862507 \tabularnewline
192 & 12 & 11.8059816886582 & 0.194018311341756 \tabularnewline
193 & 3 & 9.19939938424006 & -6.19939938424006 \tabularnewline
194 & 11 & 11.5499152462762 & -0.549915246276219 \tabularnewline
195 & 10 & 9.75847906367855 & 0.241520936321452 \tabularnewline
196 & 12 & 11.0912253676005 & 0.908774632399493 \tabularnewline
197 & 9 & 11.4143908746151 & -2.41439087461511 \tabularnewline
198 & 12 & 11.7272874521167 & 0.272712547883319 \tabularnewline
199 & 9 & 10.3154839456045 & -1.31548394560453 \tabularnewline
200 & 12 & 11.6352004857799 & 0.364799514220089 \tabularnewline
201 & 12 & 11.3928356446671 & 0.6071643553329 \tabularnewline
202 & 10 & 10.3807428275262 & -0.380742827526229 \tabularnewline
203 & 9 & 8.63822371739232 & 0.361776282607678 \tabularnewline
204 & 12 & 9.06180931739947 & 2.93819068260053 \tabularnewline
205 & 8 & 11.0173677482417 & -3.01736774824173 \tabularnewline
206 & 11 & 11.0593558556504 & -0.0593558556504032 \tabularnewline
207 & 11 & 11.6817960981777 & -0.681796098177671 \tabularnewline
208 & 12 & 11.5019294131538 & 0.498070586846156 \tabularnewline
209 & 10 & 8.58920821614969 & 1.41079178385031 \tabularnewline
210 & 10 & 11.0137606311245 & -1.01376063112446 \tabularnewline
211 & 12 & 9.15440481689178 & 2.84559518310822 \tabularnewline
212 & 12 & 9.59571388667067 & 2.40428611332932 \tabularnewline
213 & 11 & 11.2107788076307 & -0.210778807630742 \tabularnewline
214 & 8 & 10.9912280814446 & -2.99122808144456 \tabularnewline
215 & 12 & 11.5456207312731 & 0.454379268726853 \tabularnewline
216 & 10 & 10.0725050418521 & -0.0725050418521001 \tabularnewline
217 & 11 & 12.2380408288634 & -1.23804082886342 \tabularnewline
218 & 10 & 10.3933666777677 & -0.393366677767742 \tabularnewline
219 & 8 & 9.7538140090542 & -1.7538140090542 \tabularnewline
220 & 12 & 11.1475961015017 & 0.852403898498348 \tabularnewline
221 & 12 & 9.83330827533153 & 2.16669172466847 \tabularnewline
222 & 10 & 10.4319693578599 & -0.431969357859882 \tabularnewline
223 & 12 & 10.8955283743587 & 1.10447162564134 \tabularnewline
224 & 9 & 9.24618707954441 & -0.24618707954441 \tabularnewline
225 & 9 & 9.86545176507268 & -0.865451765072683 \tabularnewline
226 & 6 & 7.12264172479158 & -1.12264172479158 \tabularnewline
227 & 10 & 10.267129149499 & -0.267129149499015 \tabularnewline
228 & 9 & 10.4578718928652 & -1.4578718928652 \tabularnewline
229 & 9 & 8.52191831037926 & 0.478081689620741 \tabularnewline
230 & 9 & 9.29652191081022 & -0.296521910810222 \tabularnewline
231 & 6 & 9.68957704502704 & -3.68957704502704 \tabularnewline
232 & 10 & 8.19690869277999 & 1.80309130722001 \tabularnewline
233 & 6 & 11.5357853479969 & -5.53578534799692 \tabularnewline
234 & 14 & 12.5256023760986 & 1.47439762390145 \tabularnewline
235 & 10 & 9.78297956699866 & 0.217020433001337 \tabularnewline
236 & 10 & 8.54018661886383 & 1.45981338113617 \tabularnewline
237 & 6 & 4.4133178123308 & 1.5866821876692 \tabularnewline
238 & 12 & 9.4128688824046 & 2.5871311175954 \tabularnewline
239 & 12 & 11.5514772279173 & 0.448522772082698 \tabularnewline
240 & 7 & 7.95057370460939 & -0.950573704609391 \tabularnewline
241 & 8 & 9.38190844361464 & -1.38190844361465 \tabularnewline
242 & 11 & 9.14236169733308 & 1.85763830266692 \tabularnewline
243 & 3 & 7.8650560344008 & -4.8650560344008 \tabularnewline
244 & 6 & 9.73778339392977 & -3.73778339392977 \tabularnewline
245 & 10 & 10.8225533314636 & -0.822553331463583 \tabularnewline
246 & 8 & 9.27826106412865 & -1.27826106412866 \tabularnewline
247 & 9 & 10.4078670696946 & -1.40786706969456 \tabularnewline
248 & 9 & 7.74405679612789 & 1.25594320387211 \tabularnewline
249 & 8 & 8.77694481951701 & -0.776944819517015 \tabularnewline
250 & 9 & 8.79299850468537 & 0.207001495314632 \tabularnewline
251 & 7 & 8.69664855178853 & -1.69664855178853 \tabularnewline
252 & 7 & 8.04224341487795 & -1.04224341487795 \tabularnewline
253 & 6 & 9.2457335701095 & -3.2457335701095 \tabularnewline
254 & 9 & 11.4795908036357 & -2.47959080363571 \tabularnewline
255 & 10 & 9.10132712148532 & 0.898672878514683 \tabularnewline
256 & 11 & 10.3040556618127 & 0.695944338187263 \tabularnewline
257 & 12 & 11.6553469009567 & 0.344653099043277 \tabularnewline
258 & 8 & 10.2609971797956 & -2.26099717979557 \tabularnewline
259 & 11 & 9.74580640999468 & 1.25419359000532 \tabularnewline
260 & 3 & 4.60454537359994 & -1.60454537359994 \tabularnewline
261 & 11 & 10.8909413746476 & 0.109058625352396 \tabularnewline
262 & 12 & 8.82295925635545 & 3.17704074364455 \tabularnewline
263 & 7 & 8.5760546338294 & -1.5760546338294 \tabularnewline
264 & 9 & 10.405844587779 & -1.40584458777901 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225459&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]12[/C][C]9.83114586715835[/C][C]2.16885413284165[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]11.468580317173[/C][C]-0.468580317173051[/C][/ROW]
[ROW][C]3[/C][C]15[/C][C]13.3118986872215[/C][C]1.68810131277846[/C][/ROW]
[ROW][C]4[/C][C]6[/C][C]10.9701016956855[/C][C]-4.97010169568547[/C][/ROW]
[ROW][C]5[/C][C]13[/C][C]10.4461668429597[/C][C]2.55383315704033[/C][/ROW]
[ROW][C]6[/C][C]10[/C][C]9.65448948872557[/C][C]0.345510511274428[/C][/ROW]
[ROW][C]7[/C][C]12[/C][C]12.8629973422319[/C][C]-0.862997342231856[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]11.1091985805826[/C][C]2.89080141941745[/C][/ROW]
[ROW][C]9[/C][C]12[/C][C]10.4569294272481[/C][C]1.54307057275191[/C][/ROW]
[ROW][C]10[/C][C]9[/C][C]11.1007248366287[/C][C]-2.10072483662867[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]11.4329278671713[/C][C]-1.43292786717128[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]11.4691959373668[/C][C]0.530804062633232[/C][/ROW]
[ROW][C]13[/C][C]12[/C][C]11.5117763972292[/C][C]0.48822360277077[/C][/ROW]
[ROW][C]14[/C][C]11[/C][C]11.5429888309169[/C][C]-0.542988830916898[/C][/ROW]
[ROW][C]15[/C][C]15[/C][C]12.330030391166[/C][C]2.66996960883399[/C][/ROW]
[ROW][C]16[/C][C]12[/C][C]10.8778470343681[/C][C]1.12215296563194[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]10.8969061698015[/C][C]-0.896906169801453[/C][/ROW]
[ROW][C]18[/C][C]12[/C][C]14.0328790231848[/C][C]-2.03287902318477[/C][/ROW]
[ROW][C]19[/C][C]11[/C][C]12.7651838175469[/C][C]-1.76518381754691[/C][/ROW]
[ROW][C]20[/C][C]12[/C][C]11.4001353076294[/C][C]0.599864692370568[/C][/ROW]
[ROW][C]21[/C][C]11[/C][C]11.5112020788709[/C][C]-0.511202078870949[/C][/ROW]
[ROW][C]22[/C][C]12[/C][C]11.4255674070769[/C][C]0.574432592923124[/C][/ROW]
[ROW][C]23[/C][C]13[/C][C]13.2993195233196[/C][C]-0.299319523319582[/C][/ROW]
[ROW][C]24[/C][C]11[/C][C]11.5951678857416[/C][C]-0.595167885741614[/C][/ROW]
[ROW][C]25[/C][C]12[/C][C]12.0749698742032[/C][C]-0.0749698742031561[/C][/ROW]
[ROW][C]26[/C][C]13[/C][C]12.112443181474[/C][C]0.887556818526027[/C][/ROW]
[ROW][C]27[/C][C]10[/C][C]11.6451585249252[/C][C]-1.64515852492519[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]11.0401275825605[/C][C]2.95987241743949[/C][/ROW]
[ROW][C]29[/C][C]12[/C][C]11.5752075468097[/C][C]0.424792453190322[/C][/ROW]
[ROW][C]30[/C][C]10[/C][C]10.3163865339469[/C][C]-0.316386533946895[/C][/ROW]
[ROW][C]31[/C][C]12[/C][C]10.9624288118679[/C][C]1.03757118813209[/C][/ROW]
[ROW][C]32[/C][C]8[/C][C]9.15446929297082[/C][C]-1.15446929297082[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.2727804008856[/C][C]-0.272780400885618[/C][/ROW]
[ROW][C]34[/C][C]12[/C][C]11.6977537556879[/C][C]0.302246244312052[/C][/ROW]
[ROW][C]35[/C][C]12[/C][C]10.3082079918512[/C][C]1.69179200814885[/C][/ROW]
[ROW][C]36[/C][C]7[/C][C]8.1148877171814[/C][C]-1.1148877171814[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]7.98167389012276[/C][C]1.01832610987724[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]10.3495765773342[/C][C]1.65042342266585[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]11.5313448573675[/C][C]-1.53134485736747[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]11.5294256981593[/C][C]-1.52942569815932[/C][/ROW]
[ROW][C]41[/C][C]10[/C][C]11.4933081320218[/C][C]-1.49330813202178[/C][/ROW]
[ROW][C]42[/C][C]12[/C][C]10.3835469881[/C][C]1.61645301189998[/C][/ROW]
[ROW][C]43[/C][C]15[/C][C]13.6890348212249[/C][C]1.31096517877511[/C][/ROW]
[ROW][C]44[/C][C]10[/C][C]10.2740245724197[/C][C]-0.274024572419661[/C][/ROW]
[ROW][C]45[/C][C]10[/C][C]10.1385157821097[/C][C]-0.138515782109744[/C][/ROW]
[ROW][C]46[/C][C]12[/C][C]8.70592384641535[/C][C]3.29407615358465[/C][/ROW]
[ROW][C]47[/C][C]13[/C][C]10.5041980302008[/C][C]2.49580196979917[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]11.0147709727017[/C][C]-0.0147709727016851[/C][/ROW]
[ROW][C]49[/C][C]11[/C][C]11.6979746669636[/C][C]-0.697974666963572[/C][/ROW]
[ROW][C]50[/C][C]12[/C][C]10.3378916116669[/C][C]1.66210838833312[/C][/ROW]
[ROW][C]51[/C][C]14[/C][C]11.7429294628888[/C][C]2.25707053711115[/C][/ROW]
[ROW][C]52[/C][C]10[/C][C]10.2540477153803[/C][C]-0.254047715380349[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]9.18291342741127[/C][C]2.81708657258873[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]11.5416888842237[/C][C]1.45831111577633[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]7.50222364939796[/C][C]-2.50222364939796[/C][/ROW]
[ROW][C]56[/C][C]6[/C][C]10.3980344801777[/C][C]-4.39803448017774[/C][/ROW]
[ROW][C]57[/C][C]12[/C][C]11.4998147258463[/C][C]0.500185274153718[/C][/ROW]
[ROW][C]58[/C][C]12[/C][C]11.6026404968069[/C][C]0.397359503193082[/C][/ROW]
[ROW][C]59[/C][C]11[/C][C]11.0912031489452[/C][C]-0.0912031489451753[/C][/ROW]
[ROW][C]60[/C][C]10[/C][C]11.5202863400697[/C][C]-1.52028634006966[/C][/ROW]
[ROW][C]61[/C][C]7[/C][C]8.95108746508688[/C][C]-1.95108746508688[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]11.5785824284715[/C][C]0.421417571528502[/C][/ROW]
[ROW][C]63[/C][C]14[/C][C]11.6678760374245[/C][C]2.33212396257551[/C][/ROW]
[ROW][C]64[/C][C]11[/C][C]10.3798680664009[/C][C]0.620131933599058[/C][/ROW]
[ROW][C]65[/C][C]12[/C][C]11.3498103361788[/C][C]0.650189663821168[/C][/ROW]
[ROW][C]66[/C][C]13[/C][C]12.308887639125[/C][C]0.691112360874971[/C][/ROW]
[ROW][C]67[/C][C]14[/C][C]12.6423828510488[/C][C]1.35761714895119[/C][/ROW]
[ROW][C]68[/C][C]11[/C][C]12.5597178676945[/C][C]-1.55971786769446[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]9.38491091383378[/C][C]2.61508908616622[/C][/ROW]
[ROW][C]70[/C][C]12[/C][C]11.6263741570863[/C][C]0.373625842913699[/C][/ROW]
[ROW][C]71[/C][C]8[/C][C]8.07018762509651[/C][C]-0.0701876250965071[/C][/ROW]
[ROW][C]72[/C][C]11[/C][C]10.4685766054292[/C][C]0.531423394570844[/C][/ROW]
[ROW][C]73[/C][C]14[/C][C]12.9466705390499[/C][C]1.05332946095015[/C][/ROW]
[ROW][C]74[/C][C]14[/C][C]12.9635819587666[/C][C]1.03641804123338[/C][/ROW]
[ROW][C]75[/C][C]12[/C][C]11.3912766173855[/C][C]0.608723382614529[/C][/ROW]
[ROW][C]76[/C][C]9[/C][C]11.9091795275438[/C][C]-2.90917952754383[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.6027688071953[/C][C]1.39723119280473[/C][/ROW]
[ROW][C]78[/C][C]11[/C][C]11.3642019920859[/C][C]-0.364201992085947[/C][/ROW]
[ROW][C]79[/C][C]12[/C][C]9.7980251449569[/C][C]2.2019748550431[/C][/ROW]
[ROW][C]80[/C][C]12[/C][C]11.2209218056998[/C][C]0.779078194300202[/C][/ROW]
[ROW][C]81[/C][C]12[/C][C]11.7179136912049[/C][C]0.282086308795064[/C][/ROW]
[ROW][C]82[/C][C]12[/C][C]11.6620934752776[/C][C]0.33790652472237[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]10.9344015313818[/C][C]1.06559846861821[/C][/ROW]
[ROW][C]84[/C][C]11[/C][C]11.0034421768309[/C][C]-0.00344217683090933[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]11.4745563780127[/C][C]-1.47455637801265[/C][/ROW]
[ROW][C]86[/C][C]9[/C][C]10.5680746795337[/C][C]-1.56807467953366[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]11.5616731905457[/C][C]0.438326809454327[/C][/ROW]
[ROW][C]88[/C][C]12[/C][C]11.4316731565849[/C][C]0.568326843415071[/C][/ROW]
[ROW][C]89[/C][C]12[/C][C]10.8865341614948[/C][C]1.11346583850519[/C][/ROW]
[ROW][C]90[/C][C]9[/C][C]9.32803481199869[/C][C]-0.328034811998688[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]11.9317706341257[/C][C]3.06822936587432[/C][/ROW]
[ROW][C]92[/C][C]12[/C][C]11.8368075605664[/C][C]0.163192439433554[/C][/ROW]
[ROW][C]93[/C][C]12[/C][C]10.8299567276987[/C][C]1.1700432723013[/C][/ROW]
[ROW][C]94[/C][C]12[/C][C]9.80691903262861[/C][C]2.19308096737139[/C][/ROW]
[ROW][C]95[/C][C]10[/C][C]11.6472762040983[/C][C]-1.64727620409826[/C][/ROW]
[ROW][C]96[/C][C]13[/C][C]11.5128064070653[/C][C]1.48719359293469[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]11.5015419289876[/C][C]-2.5015419289876[/C][/ROW]
[ROW][C]98[/C][C]12[/C][C]11.5867720049067[/C][C]0.413227995093293[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]10.549540258362[/C][C]-0.549540258361995[/C][/ROW]
[ROW][C]100[/C][C]14[/C][C]11.6373603678965[/C][C]2.36263963210347[/C][/ROW]
[ROW][C]101[/C][C]11[/C][C]11.5378143089306[/C][C]-0.537814308930635[/C][/ROW]
[ROW][C]102[/C][C]15[/C][C]14.0005685518754[/C][C]0.999431448124595[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]10.7604786166616[/C][C]0.239521383338397[/C][/ROW]
[ROW][C]104[/C][C]11[/C][C]11.7645532744037[/C][C]-0.764553274403709[/C][/ROW]
[ROW][C]105[/C][C]12[/C][C]9.64619764872511[/C][C]2.35380235127489[/C][/ROW]
[ROW][C]106[/C][C]12[/C][C]12.1415489165486[/C][C]-0.141548916548595[/C][/ROW]
[ROW][C]107[/C][C]12[/C][C]11.6293639465343[/C][C]0.370636053465749[/C][/ROW]
[ROW][C]108[/C][C]11[/C][C]11.4873819337667[/C][C]-0.487381933766677[/C][/ROW]
[ROW][C]109[/C][C]7[/C][C]9.21971359820331[/C][C]-2.21971359820331[/C][/ROW]
[ROW][C]110[/C][C]12[/C][C]11.6386085935468[/C][C]0.361391406453196[/C][/ROW]
[ROW][C]111[/C][C]14[/C][C]11.5704877726745[/C][C]2.42951222732553[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]12.4947784611353[/C][C]-1.49477846113534[/C][/ROW]
[ROW][C]113[/C][C]11[/C][C]9.80674879480524[/C][C]1.19325120519475[/C][/ROW]
[ROW][C]114[/C][C]10[/C][C]9.21943330152917[/C][C]0.780566698470834[/C][/ROW]
[ROW][C]115[/C][C]13[/C][C]12.6728813112321[/C][C]0.327118688767926[/C][/ROW]
[ROW][C]116[/C][C]13[/C][C]10.5444440922321[/C][C]2.45555590776793[/C][/ROW]
[ROW][C]117[/C][C]8[/C][C]10.5613521042621[/C][C]-2.56135210426206[/C][/ROW]
[ROW][C]118[/C][C]11[/C][C]9.90633175707733[/C][C]1.09366824292267[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]11.6481722405041[/C][C]0.351827759495924[/C][/ROW]
[ROW][C]120[/C][C]11[/C][C]9.85870580374401[/C][C]1.141294196256[/C][/ROW]
[ROW][C]121[/C][C]13[/C][C]11.3362977511445[/C][C]1.66370224885546[/C][/ROW]
[ROW][C]122[/C][C]12[/C][C]10.0731820102523[/C][C]1.92681798974766[/C][/ROW]
[ROW][C]123[/C][C]14[/C][C]11.7270347843016[/C][C]2.27296521569842[/C][/ROW]
[ROW][C]124[/C][C]13[/C][C]10.8577665958815[/C][C]2.14223340411854[/C][/ROW]
[ROW][C]125[/C][C]15[/C][C]11.6241950875899[/C][C]3.3758049124101[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]10.9675054010245[/C][C]-0.967505401024485[/C][/ROW]
[ROW][C]127[/C][C]11[/C][C]12.2481609393575[/C][C]-1.24816093935747[/C][/ROW]
[ROW][C]128[/C][C]9[/C][C]11.0468155145957[/C][C]-2.04681551459566[/C][/ROW]
[ROW][C]129[/C][C]11[/C][C]9.19977192637827[/C][C]1.80022807362173[/C][/ROW]
[ROW][C]130[/C][C]10[/C][C]11.5777677279679[/C][C]-1.57776772796791[/C][/ROW]
[ROW][C]131[/C][C]11[/C][C]8.0272439232119[/C][C]2.9727560767881[/C][/ROW]
[ROW][C]132[/C][C]8[/C][C]11.6645050174388[/C][C]-3.66450501743877[/C][/ROW]
[ROW][C]133[/C][C]11[/C][C]9.11506458062597[/C][C]1.88493541937403[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]10.5239337018359[/C][C]1.47606629816406[/C][/ROW]
[ROW][C]135[/C][C]12[/C][C]10.8349634240088[/C][C]1.1650365759912[/C][/ROW]
[ROW][C]136[/C][C]9[/C][C]9.27233221839196[/C][C]-0.272332218391959[/C][/ROW]
[ROW][C]137[/C][C]11[/C][C]10.9130307956976[/C][C]0.0869692043023909[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]8.63344137234968[/C][C]1.36655862765032[/C][/ROW]
[ROW][C]139[/C][C]8[/C][C]9.20795049536374[/C][C]-1.20795049536374[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]8.76749202066313[/C][C]0.232507979336874[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]11.5146754534555[/C][C]-3.51467545345547[/C][/ROW]
[ROW][C]142[/C][C]9[/C][C]11.1715184764109[/C][C]-2.1715184764109[/C][/ROW]
[ROW][C]143[/C][C]15[/C][C]12.2764534377343[/C][C]2.72354656226566[/C][/ROW]
[ROW][C]144[/C][C]11[/C][C]11.2143693239249[/C][C]-0.214369323924928[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]8.00772786405441[/C][C]-0.00772786405441555[/C][/ROW]
[ROW][C]146[/C][C]13[/C][C]12.4695552986181[/C][C]0.530444701381938[/C][/ROW]
[ROW][C]147[/C][C]12[/C][C]9.82485320438624[/C][C]2.17514679561376[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]11.5051568765134[/C][C]0.494843123486583[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]9.69510314207846[/C][C]-0.695103142078459[/C][/ROW]
[ROW][C]150[/C][C]7[/C][C]8.29383716081634[/C][C]-1.29383716081634[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]11.0205148893713[/C][C]1.97948511062867[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.761309070255[/C][C]-2.76130907025502[/C][/ROW]
[ROW][C]153[/C][C]6[/C][C]11.7514022634679[/C][C]-5.75140226346793[/C][/ROW]
[ROW][C]154[/C][C]8[/C][C]10.302054850673[/C][C]-2.30205485067298[/C][/ROW]
[ROW][C]155[/C][C]8[/C][C]7.93744563095987[/C][C]0.0625543690401274[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]11.9317706341257[/C][C]3.06822936587432[/C][/ROW]
[ROW][C]157[/C][C]6[/C][C]9.92609791268162[/C][C]-3.92609791268162[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]11.0468155145957[/C][C]-2.04681551459566[/C][/ROW]
[ROW][C]159[/C][C]11[/C][C]11.5853163279229[/C][C]-0.585316327922916[/C][/ROW]
[ROW][C]160[/C][C]8[/C][C]9.46032591404247[/C][C]-1.46032591404247[/C][/ROW]
[ROW][C]161[/C][C]8[/C][C]9.80979650720862[/C][C]-1.80979650720862[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.4466971733023[/C][C]0.553302826697704[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]9.0528929676546[/C][C]-1.0528929676546[/C][/ROW]
[ROW][C]164[/C][C]14[/C][C]12.0109863874036[/C][C]1.98901361259637[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.151420517948[/C][C]-1.15142051794805[/C][/ROW]
[ROW][C]166[/C][C]8[/C][C]7.89120699186945[/C][C]0.108793008130549[/C][/ROW]
[ROW][C]167[/C][C]11[/C][C]10.4417595989194[/C][C]0.558240401080564[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]8.45488409970177[/C][C]3.54511590029823[/C][/ROW]
[ROW][C]169[/C][C]12[/C][C]10.0252672696833[/C][C]1.97473273031674[/C][/ROW]
[ROW][C]170[/C][C]12[/C][C]11.7732629906953[/C][C]0.226737009304685[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]8.96971454563988[/C][C]-3.96971454563988[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.6421483281033[/C][C]0.357851671896677[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]9.29413151253336[/C][C]0.705868487466639[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]7.16436534170705[/C][C]-0.164365341707047[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]8.99563289314584[/C][C]3.00436710685416[/C][/ROW]
[ROW][C]176[/C][C]11[/C][C]11.163974437837[/C][C]-0.163974437837032[/C][/ROW]
[ROW][C]177[/C][C]8[/C][C]9.14357463988117[/C][C]-1.14357463988117[/C][/ROW]
[ROW][C]178[/C][C]9[/C][C]9.10903142012653[/C][C]-0.109031420126534[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]10.3175443942803[/C][C]-0.317544394280289[/C][/ROW]
[ROW][C]180[/C][C]9[/C][C]9.38635156340575[/C][C]-0.386351563405752[/C][/ROW]
[ROW][C]181[/C][C]12[/C][C]11.5426835524635[/C][C]0.457316447536502[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]8.54157696438228[/C][C]-2.54157696438228[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]13.3712243899642[/C][C]1.62877561003581[/C][/ROW]
[ROW][C]184[/C][C]12[/C][C]10.941103607994[/C][C]1.05889639200603[/C][/ROW]
[ROW][C]185[/C][C]12[/C][C]6.93755931670681[/C][C]5.06244068329319[/C][/ROW]
[ROW][C]186[/C][C]12[/C][C]11.646008508531[/C][C]0.353991491469044[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]12.1362957548222[/C][C]-1.13629575482223[/C][/ROW]
[ROW][C]188[/C][C]7[/C][C]9.17914412006931[/C][C]-2.17914412006931[/C][/ROW]
[ROW][C]189[/C][C]7[/C][C]8.47216035002414[/C][C]-1.47216035002414[/C][/ROW]
[ROW][C]190[/C][C]5[/C][C]8.63462873386742[/C][C]-3.63462873386742[/C][/ROW]
[ROW][C]191[/C][C]12[/C][C]10.5322829713749[/C][C]1.46771702862507[/C][/ROW]
[ROW][C]192[/C][C]12[/C][C]11.8059816886582[/C][C]0.194018311341756[/C][/ROW]
[ROW][C]193[/C][C]3[/C][C]9.19939938424006[/C][C]-6.19939938424006[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]11.5499152462762[/C][C]-0.549915246276219[/C][/ROW]
[ROW][C]195[/C][C]10[/C][C]9.75847906367855[/C][C]0.241520936321452[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]11.0912253676005[/C][C]0.908774632399493[/C][/ROW]
[ROW][C]197[/C][C]9[/C][C]11.4143908746151[/C][C]-2.41439087461511[/C][/ROW]
[ROW][C]198[/C][C]12[/C][C]11.7272874521167[/C][C]0.272712547883319[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]10.3154839456045[/C][C]-1.31548394560453[/C][/ROW]
[ROW][C]200[/C][C]12[/C][C]11.6352004857799[/C][C]0.364799514220089[/C][/ROW]
[ROW][C]201[/C][C]12[/C][C]11.3928356446671[/C][C]0.6071643553329[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]10.3807428275262[/C][C]-0.380742827526229[/C][/ROW]
[ROW][C]203[/C][C]9[/C][C]8.63822371739232[/C][C]0.361776282607678[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]9.06180931739947[/C][C]2.93819068260053[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]11.0173677482417[/C][C]-3.01736774824173[/C][/ROW]
[ROW][C]206[/C][C]11[/C][C]11.0593558556504[/C][C]-0.0593558556504032[/C][/ROW]
[ROW][C]207[/C][C]11[/C][C]11.6817960981777[/C][C]-0.681796098177671[/C][/ROW]
[ROW][C]208[/C][C]12[/C][C]11.5019294131538[/C][C]0.498070586846156[/C][/ROW]
[ROW][C]209[/C][C]10[/C][C]8.58920821614969[/C][C]1.41079178385031[/C][/ROW]
[ROW][C]210[/C][C]10[/C][C]11.0137606311245[/C][C]-1.01376063112446[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]9.15440481689178[/C][C]2.84559518310822[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]9.59571388667067[/C][C]2.40428611332932[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]11.2107788076307[/C][C]-0.210778807630742[/C][/ROW]
[ROW][C]214[/C][C]8[/C][C]10.9912280814446[/C][C]-2.99122808144456[/C][/ROW]
[ROW][C]215[/C][C]12[/C][C]11.5456207312731[/C][C]0.454379268726853[/C][/ROW]
[ROW][C]216[/C][C]10[/C][C]10.0725050418521[/C][C]-0.0725050418521001[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]12.2380408288634[/C][C]-1.23804082886342[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]10.3933666777677[/C][C]-0.393366677767742[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.7538140090542[/C][C]-1.7538140090542[/C][/ROW]
[ROW][C]220[/C][C]12[/C][C]11.1475961015017[/C][C]0.852403898498348[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]9.83330827533153[/C][C]2.16669172466847[/C][/ROW]
[ROW][C]222[/C][C]10[/C][C]10.4319693578599[/C][C]-0.431969357859882[/C][/ROW]
[ROW][C]223[/C][C]12[/C][C]10.8955283743587[/C][C]1.10447162564134[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]9.24618707954441[/C][C]-0.24618707954441[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.86545176507268[/C][C]-0.865451765072683[/C][/ROW]
[ROW][C]226[/C][C]6[/C][C]7.12264172479158[/C][C]-1.12264172479158[/C][/ROW]
[ROW][C]227[/C][C]10[/C][C]10.267129149499[/C][C]-0.267129149499015[/C][/ROW]
[ROW][C]228[/C][C]9[/C][C]10.4578718928652[/C][C]-1.4578718928652[/C][/ROW]
[ROW][C]229[/C][C]9[/C][C]8.52191831037926[/C][C]0.478081689620741[/C][/ROW]
[ROW][C]230[/C][C]9[/C][C]9.29652191081022[/C][C]-0.296521910810222[/C][/ROW]
[ROW][C]231[/C][C]6[/C][C]9.68957704502704[/C][C]-3.68957704502704[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]8.19690869277999[/C][C]1.80309130722001[/C][/ROW]
[ROW][C]233[/C][C]6[/C][C]11.5357853479969[/C][C]-5.53578534799692[/C][/ROW]
[ROW][C]234[/C][C]14[/C][C]12.5256023760986[/C][C]1.47439762390145[/C][/ROW]
[ROW][C]235[/C][C]10[/C][C]9.78297956699866[/C][C]0.217020433001337[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]8.54018661886383[/C][C]1.45981338113617[/C][/ROW]
[ROW][C]237[/C][C]6[/C][C]4.4133178123308[/C][C]1.5866821876692[/C][/ROW]
[ROW][C]238[/C][C]12[/C][C]9.4128688824046[/C][C]2.5871311175954[/C][/ROW]
[ROW][C]239[/C][C]12[/C][C]11.5514772279173[/C][C]0.448522772082698[/C][/ROW]
[ROW][C]240[/C][C]7[/C][C]7.95057370460939[/C][C]-0.950573704609391[/C][/ROW]
[ROW][C]241[/C][C]8[/C][C]9.38190844361464[/C][C]-1.38190844361465[/C][/ROW]
[ROW][C]242[/C][C]11[/C][C]9.14236169733308[/C][C]1.85763830266692[/C][/ROW]
[ROW][C]243[/C][C]3[/C][C]7.8650560344008[/C][C]-4.8650560344008[/C][/ROW]
[ROW][C]244[/C][C]6[/C][C]9.73778339392977[/C][C]-3.73778339392977[/C][/ROW]
[ROW][C]245[/C][C]10[/C][C]10.8225533314636[/C][C]-0.822553331463583[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]9.27826106412865[/C][C]-1.27826106412866[/C][/ROW]
[ROW][C]247[/C][C]9[/C][C]10.4078670696946[/C][C]-1.40786706969456[/C][/ROW]
[ROW][C]248[/C][C]9[/C][C]7.74405679612789[/C][C]1.25594320387211[/C][/ROW]
[ROW][C]249[/C][C]8[/C][C]8.77694481951701[/C][C]-0.776944819517015[/C][/ROW]
[ROW][C]250[/C][C]9[/C][C]8.79299850468537[/C][C]0.207001495314632[/C][/ROW]
[ROW][C]251[/C][C]7[/C][C]8.69664855178853[/C][C]-1.69664855178853[/C][/ROW]
[ROW][C]252[/C][C]7[/C][C]8.04224341487795[/C][C]-1.04224341487795[/C][/ROW]
[ROW][C]253[/C][C]6[/C][C]9.2457335701095[/C][C]-3.2457335701095[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]11.4795908036357[/C][C]-2.47959080363571[/C][/ROW]
[ROW][C]255[/C][C]10[/C][C]9.10132712148532[/C][C]0.898672878514683[/C][/ROW]
[ROW][C]256[/C][C]11[/C][C]10.3040556618127[/C][C]0.695944338187263[/C][/ROW]
[ROW][C]257[/C][C]12[/C][C]11.6553469009567[/C][C]0.344653099043277[/C][/ROW]
[ROW][C]258[/C][C]8[/C][C]10.2609971797956[/C][C]-2.26099717979557[/C][/ROW]
[ROW][C]259[/C][C]11[/C][C]9.74580640999468[/C][C]1.25419359000532[/C][/ROW]
[ROW][C]260[/C][C]3[/C][C]4.60454537359994[/C][C]-1.60454537359994[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]10.8909413746476[/C][C]0.109058625352396[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]8.82295925635545[/C][C]3.17704074364455[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]8.5760546338294[/C][C]-1.5760546338294[/C][/ROW]
[ROW][C]264[/C][C]9[/C][C]10.405844587779[/C][C]-1.40584458777901[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225459&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225459&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
1129.831145867158352.16885413284165
21111.468580317173-0.468580317173051
31513.31189868722151.68810131277846
4610.9701016956855-4.97010169568547
51310.44616684295972.55383315704033
6109.654489488725570.345510511274428
71212.8629973422319-0.862997342231856
81411.10919858058262.89080141941745
91210.45692942724811.54307057275191
10911.1007248366287-2.10072483662867
111011.4329278671713-1.43292786717128
121211.46919593736680.530804062633232
131211.51177639722920.48822360277077
141111.5429888309169-0.542988830916898
151512.3300303911662.66996960883399
161210.87784703436811.12215296563194
171010.8969061698015-0.896906169801453
181214.0328790231848-2.03287902318477
191112.7651838175469-1.76518381754691
201211.40013530762940.599864692370568
211111.5112020788709-0.511202078870949
221211.42556740707690.574432592923124
231313.2993195233196-0.299319523319582
241111.5951678857416-0.595167885741614
251212.0749698742032-0.0749698742031561
261312.1124431814740.887556818526027
271011.6451585249252-1.64515852492519
281411.04012758256052.95987241743949
291211.57520754680970.424792453190322
301010.3163865339469-0.316386533946895
311210.96242881186791.03757118813209
3289.15446929297082-1.15446929297082
331010.2727804008856-0.272780400885618
341211.69775375568790.302246244312052
351210.30820799185121.69179200814885
3678.1148877171814-1.1148877171814
3797.981673890122761.01832610987724
381210.34957657733421.65042342266585
391011.5313448573675-1.53134485736747
401011.5294256981593-1.52942569815932
411011.4933081320218-1.49330813202178
421210.38354698811.61645301189998
431513.68903482122491.31096517877511
441010.2740245724197-0.274024572419661
451010.1385157821097-0.138515782109744
46128.705923846415353.29407615358465
471310.50419803020082.49580196979917
481111.0147709727017-0.0147709727016851
491111.6979746669636-0.697974666963572
501210.33789161166691.66210838833312
511411.74292946288882.25707053711115
521010.2540477153803-0.254047715380349
53129.182913427411272.81708657258873
541311.54168888422371.45831111577633
5557.50222364939796-2.50222364939796
56610.3980344801777-4.39803448017774
571211.49981472584630.500185274153718
581211.60264049680690.397359503193082
591111.0912031489452-0.0912031489451753
601011.5202863400697-1.52028634006966
6178.95108746508688-1.95108746508688
621211.57858242847150.421417571528502
631411.66787603742452.33212396257551
641110.37986806640090.620131933599058
651211.34981033617880.650189663821168
661312.3088876391250.691112360874971
671412.64238285104881.35761714895119
681112.5597178676945-1.55971786769446
69129.384910913833782.61508908616622
701211.62637415708630.373625842913699
7188.07018762509651-0.0701876250965071
721110.46857660542920.531423394570844
731412.94667053904991.05332946095015
741412.96358195876661.03641804123338
751211.39127661738550.608723382614529
76911.9091795275438-2.90917952754383
771311.60276880719531.39723119280473
781111.3642019920859-0.364201992085947
79129.79802514495692.2019748550431
801211.22092180569980.779078194300202
811211.71791369120490.282086308795064
821211.66209347527760.33790652472237
831210.93440153138181.06559846861821
841111.0034421768309-0.00344217683090933
851011.4745563780127-1.47455637801265
86910.5680746795337-1.56807467953366
871211.56167319054570.438326809454327
881211.43167315658490.568326843415071
891210.88653416149481.11346583850519
9099.32803481199869-0.328034811998688
911511.93177063412573.06822936587432
921211.83680756056640.163192439433554
931210.82995672769871.1700432723013
94129.806919032628612.19308096737139
951011.6472762040983-1.64727620409826
961311.51280640706531.48719359293469
97911.5015419289876-2.5015419289876
981211.58677200490670.413227995093293
991010.549540258362-0.549540258361995
1001411.63736036789652.36263963210347
1011111.5378143089306-0.537814308930635
1021514.00056855187540.999431448124595
1031110.76047861666160.239521383338397
1041111.7645532744037-0.764553274403709
105129.646197648725112.35380235127489
1061212.1415489165486-0.141548916548595
1071211.62936394653430.370636053465749
1081111.4873819337667-0.487381933766677
10979.21971359820331-2.21971359820331
1101211.63860859354680.361391406453196
1111411.57048777267452.42951222732553
1121112.4947784611353-1.49477846113534
113119.806748794805241.19325120519475
114109.219433301529170.780566698470834
1151312.67288131123210.327118688767926
1161310.54444409223212.45555590776793
117810.5613521042621-2.56135210426206
118119.906331757077331.09366824292267
1191211.64817224050410.351827759495924
120119.858705803744011.141294196256
1211311.33629775114451.66370224885546
1221210.07318201025231.92681798974766
1231411.72703478430162.27296521569842
1241310.85776659588152.14223340411854
1251511.62419508758993.3758049124101
1261010.9675054010245-0.967505401024485
1271112.2481609393575-1.24816093935747
128911.0468155145957-2.04681551459566
129119.199771926378271.80022807362173
1301011.5777677279679-1.57776772796791
131118.02724392321192.9727560767881
132811.6645050174388-3.66450501743877
133119.115064580625971.88493541937403
1341210.52393370183591.47606629816406
1351210.83496342400881.1650365759912
13699.27233221839196-0.272332218391959
1371110.91303079569760.0869692043023909
138108.633441372349681.36655862765032
13989.20795049536374-1.20795049536374
14098.767492020663130.232507979336874
141811.5146754534555-3.51467545345547
142911.1715184764109-2.1715184764109
1431512.27645343773432.72354656226566
1441111.2143693239249-0.214369323924928
14588.00772786405441-0.00772786405441555
1461312.46955529861810.530444701381938
147129.824853204386242.17514679561376
1481211.50515687651340.494843123486583
14999.69510314207846-0.695103142078459
15078.29383716081634-1.29383716081634
1511311.02051488937131.97948511062867
152911.761309070255-2.76130907025502
153611.7514022634679-5.75140226346793
154810.302054850673-2.30205485067298
15587.937445630959870.0625543690401274
1561511.93177063412573.06822936587432
15769.92609791268162-3.92609791268162
158911.0468155145957-2.04681551459566
1591111.5853163279229-0.585316327922916
16089.46032591404247-1.46032591404247
16189.80979650720862-1.80979650720862
162109.44669717330230.553302826697704
16389.0528929676546-1.0528929676546
1641412.01098638740361.98901361259637
1651011.151420517948-1.15142051794805
16687.891206991869450.108793008130549
1671110.44175959891940.558240401080564
168128.454884099701773.54511590029823
1691210.02526726968331.97473273031674
1701211.77326299069530.226737009304685
17158.96971454563988-3.96971454563988
1721211.64214832810330.357851671896677
173109.294131512533360.705868487466639
17477.16436534170705-0.164365341707047
175128.995632893145843.00436710685416
1761111.163974437837-0.163974437837032
17789.14357463988117-1.14357463988117
17899.10903142012653-0.109031420126534
1791010.3175443942803-0.317544394280289
18099.38635156340575-0.386351563405752
1811211.54268355246350.457316447536502
18268.54157696438228-2.54157696438228
1831513.37122438996421.62877561003581
1841210.9411036079941.05889639200603
185126.937559316706815.06244068329319
1861211.6460085085310.353991491469044
1871112.1362957548222-1.13629575482223
18879.17914412006931-2.17914412006931
18978.47216035002414-1.47216035002414
19058.63462873386742-3.63462873386742
1911210.53228297137491.46771702862507
1921211.80598168865820.194018311341756
19339.19939938424006-6.19939938424006
1941111.5499152462762-0.549915246276219
195109.758479063678550.241520936321452
1961211.09122536760050.908774632399493
197911.4143908746151-2.41439087461511
1981211.72728745211670.272712547883319
199910.3154839456045-1.31548394560453
2001211.63520048577990.364799514220089
2011211.39283564466710.6071643553329
2021010.3807428275262-0.380742827526229
20398.638223717392320.361776282607678
204129.061809317399472.93819068260053
205811.0173677482417-3.01736774824173
2061111.0593558556504-0.0593558556504032
2071111.6817960981777-0.681796098177671
2081211.50192941315380.498070586846156
209108.589208216149691.41079178385031
2101011.0137606311245-1.01376063112446
211129.154404816891782.84559518310822
212129.595713886670672.40428611332932
2131111.2107788076307-0.210778807630742
214810.9912280814446-2.99122808144456
2151211.54562073127310.454379268726853
2161010.0725050418521-0.0725050418521001
2171112.2380408288634-1.23804082886342
2181010.3933666777677-0.393366677767742
21989.7538140090542-1.7538140090542
2201211.14759610150170.852403898498348
221129.833308275331532.16669172466847
2221010.4319693578599-0.431969357859882
2231210.89552837435871.10447162564134
22499.24618707954441-0.24618707954441
22599.86545176507268-0.865451765072683
22667.12264172479158-1.12264172479158
2271010.267129149499-0.267129149499015
228910.4578718928652-1.4578718928652
22998.521918310379260.478081689620741
23099.29652191081022-0.296521910810222
23169.68957704502704-3.68957704502704
232108.196908692779991.80309130722001
233611.5357853479969-5.53578534799692
2341412.52560237609861.47439762390145
235109.782979566998660.217020433001337
236108.540186618863831.45981338113617
23764.41331781233081.5866821876692
238129.41286888240462.5871311175954
2391211.55147722791730.448522772082698
24077.95057370460939-0.950573704609391
24189.38190844361464-1.38190844361465
242119.142361697333081.85763830266692
24337.8650560344008-4.8650560344008
24469.73778339392977-3.73778339392977
2451010.8225533314636-0.822553331463583
24689.27826106412865-1.27826106412866
247910.4078670696946-1.40786706969456
24897.744056796127891.25594320387211
24988.77694481951701-0.776944819517015
25098.792998504685370.207001495314632
25178.69664855178853-1.69664855178853
25278.04224341487795-1.04224341487795
25369.2457335701095-3.2457335701095
254911.4795908036357-2.47959080363571
255109.101327121485320.898672878514683
2561110.30405566181270.695944338187263
2571211.65534690095670.344653099043277
258810.2609971797956-2.26099717979557
259119.745806409994681.25419359000532
26034.60454537359994-1.60454537359994
2611110.89094137464760.109058625352396
262128.822959256355453.17704074364455
26378.5760546338294-1.5760546338294
264910.405844587779-1.40584458777901






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.9917400519395890.01651989612082110.00825994806041056
120.9882951095422960.02340978091540780.0117048904577039
130.9759728976804370.0480542046391260.024027102319563
140.9752408171090850.04951836578182920.0247591828909146
150.9624995774682540.07500084506349110.0375004225317455
160.9493959258780920.1012081482438170.0506040741219083
170.9216209763593480.1567580472813030.0783790236406516
180.91823761957790.16352476084420.0817623804220999
190.9014248135589670.1971503728820660.0985751864410328
200.8613710645817570.2772578708364860.138628935418243
210.827180185067710.3456396298645810.17281981493229
220.7794014850705110.4411970298589780.220598514929489
230.7339987329623350.5320025340753290.266001267037665
240.6948524959311170.6102950081377660.305147504068883
250.6429952625660710.7140094748678570.357004737433929
260.641898228431640.716203543136720.35810177156836
270.6598734786793430.6802530426413150.340126521320657
280.670256866351810.659486267296380.32974313364819
290.6101757902177650.7796484195644690.389824209782235
300.562002338835180.8759953223296410.43799766116482
310.5116445526385720.9767108947228550.488355447361427
320.5278141532381080.9443716935237830.472185846761892
330.4672258522631090.9344517045262190.532774147736891
340.4121901741372350.824380348274470.587809825862765
350.3948283675685580.7896567351371160.605171632431442
360.3816487862295930.7632975724591870.618351213770407
370.3314455471976680.6628910943953360.668554452802332
380.3154668962070960.6309337924141930.684533103792904
390.2960560777718310.5921121555436630.703943922228169
400.2709085442533580.5418170885067150.729091455746642
410.2414900988542510.4829801977085020.758509901145749
420.2146007059660390.4292014119320790.785399294033961
430.2531674038701220.5063348077402440.746832596129878
440.2151924282617430.4303848565234860.784807571738257
450.1796092666193490.3592185332386980.820390733380651
460.2173217574056950.434643514811390.782678242594305
470.2363091945937910.4726183891875820.763690805406209
480.1995873464190010.3991746928380010.800412653580999
490.1887005874401450.3774011748802890.811299412559855
500.1744029061923010.3488058123846020.825597093807699
510.1816267131811670.3632534263623340.818373286818833
520.152043162018620.3040863240372410.84795683798138
530.1582466703229980.3164933406459950.841753329677002
540.1392495235548680.2784990471097350.860750476445132
550.210538417558370.421076835116740.78946158244163
560.4752608816498880.9505217632997770.524739118350112
570.4326038115737570.8652076231475140.567396188426243
580.390375563453650.7807511269073010.60962443654635
590.3500197283655690.7000394567311390.649980271634431
600.3461280147478340.6922560294956670.653871985252166
610.349946435200860.6998928704017190.65005356479914
620.311506110511190.623012221022380.68849388948881
630.3214195931282870.6428391862565740.678580406871713
640.2853650816414090.5707301632828170.714634918358591
650.2602465077151440.5204930154302870.739753492284856
660.2277912628075110.4555825256150220.772208737192489
670.209294114035420.418588228070840.79070588596458
680.1891531197239320.3783062394478640.810846880276068
690.1884309608765720.3768619217531450.811569039123428
700.1620310126815190.3240620253630380.837968987318481
710.1429063954593450.2858127909186890.857093604540655
720.1220290800953760.2440581601907510.877970919904624
730.1041748716512090.2083497433024190.895825128348791
740.08858688207858710.1771737641571740.911413117921413
750.07953685822612590.1590737164522520.920463141773874
760.1006380591814330.2012761183628660.899361940818567
770.09005323235715470.1801064647143090.909946767642845
780.0746894181990850.149378836398170.925310581800915
790.07993073706322060.1598614741264410.920069262936779
800.07671220736174690.1534244147234940.923287792638253
810.06367406489868820.1273481297973760.936325935101312
820.05263359917747930.1052671983549590.947366400822521
830.04578323375803670.09156646751607350.954216766241963
840.03722546133758570.07445092267517140.962774538662414
850.03410665578927720.06821331157855440.965893344210723
860.03880021478793150.0776004295758630.961199785212069
870.0314259937618740.0628519875237480.968574006238126
880.02561297555723570.05122595111447150.974387024442764
890.02173118524485960.04346237048971910.97826881475514
900.01819211826699520.03638423653399040.981807881733005
910.03000138411577170.06000276823154350.969998615884228
920.02487257719445790.04974515438891570.975127422805542
930.022694736677930.04538947335585990.97730526332207
940.02440790145749430.04881580291498850.975592098542506
950.0244150429551210.04883008591024190.975584957044879
960.02215597631574060.04431195263148120.977844023684259
970.02725748653913590.05451497307827180.972742513460864
980.02209154925461530.04418309850923070.977908450745385
990.01869517232496760.03739034464993520.981304827675032
1000.02186682754582140.04373365509164290.978133172454179
1010.01805295506518810.03610591013037610.981947044934812
1020.01532292740325710.03064585480651410.984677072596743
1030.0121638978320490.02432779566409790.987836102167951
1040.01075452574899560.02150905149799120.989245474251004
1050.01205946118985310.02411892237970610.987940538810147
1060.009432810835116110.01886562167023220.990567189164884
1070.007411170900151620.01482234180030320.992588829099848
1080.006076599498846430.01215319899769290.993923400501154
1090.008539393746025890.01707878749205180.991460606253974
1100.006654244821229960.01330848964245990.99334575517877
1110.007673857229834460.01534771445966890.992326142770166
1120.008027644244020070.01605528848804010.99197235575598
1130.006654806222229630.01330961244445930.99334519377777
1140.005377912657928650.01075582531585730.994622087342071
1150.004186606413287480.008373212826574960.995813393586713
1160.004925603303489430.009851206606978860.995074396696511
1170.00709666210175680.01419332420351360.992903337898243
1180.0059333670595070.0118667341190140.994066632940493
1190.004602445317382740.009204890634765470.995397554682617
1200.003862100068749310.007724200137498610.996137899931251
1210.00371453298773620.007429065975472410.996285467012264
1220.003740026396998720.007480052793997450.996259973603001
1230.004433005748305650.00886601149661130.995566994251694
1240.005072840772026160.01014568154405230.994927159227974
1250.009115853228457480.0182317064569150.990884146771543
1260.00758379504913240.01516759009826480.992416204950868
1270.006505672428707730.01301134485741550.993494327571292
1280.006762549459663080.01352509891932620.993237450540337
1290.006667205007772020.0133344100155440.993332794992228
1300.006666249272950910.01333249854590180.993333750727049
1310.00846975154845220.01693950309690440.991530248451548
1320.01718881483686840.03437762967373680.982811185163132
1330.01677553430097690.03355106860195380.983224465699023
1340.01570689301674720.03141378603349440.984293106983253
1350.01365338369721390.02730676739442780.986346616302786
1360.01111006801601620.02222013603203250.988889931983984
1370.008812592406728920.01762518481345780.991187407593271
1380.007903894355554950.01580778871110990.992096105644445
1390.00704431644801920.01408863289603840.992955683551981
1400.005720236109087250.01144047221817450.994279763890913
1410.01087722313486590.02175444626973180.989122776865134
1420.01273609062430450.02547218124860910.987263909375695
1430.01698008899752870.03396017799505740.983019911002471
1440.01358816734000090.02717633468000180.986411832659999
1450.01076191243117610.02152382486235220.989238087568824
1460.008721014410888480.0174420288217770.991278985589112
1470.009740066586133460.01948013317226690.990259933413867
1480.007848223874565050.01569644774913010.992151776125435
1490.006593307730659580.01318661546131920.99340669226934
1500.005954085490604310.01190817098120860.994045914509396
1510.006176191370567610.01235238274113520.993823808629432
1520.008288419567910850.01657683913582170.991711580432089
1530.05326916168797610.1065383233759520.946730838312024
1540.06052227891148020.121044557822960.93947772108852
1550.05064188732921610.1012837746584320.949358112670784
1560.07289170115334570.1457834023066910.927108298846654
1570.128092227817940.256184455635880.87190777218206
1580.1294473188422060.2588946376844110.870552681157794
1590.1125466959984170.2250933919968340.887453304001583
1600.1087985890066540.2175971780133090.891201410993346
1610.1079181233340550.2158362466681090.892081876665945
1620.09369091494632070.1873818298926410.906309085053679
1630.08436256652011430.1687251330402290.915637433479886
1640.08956176836300680.1791235367260140.910438231636993
1650.0811248802593420.1622497605186840.918875119740658
1660.06902468466592830.1380493693318570.930975315334072
1670.05871237228516990.117424744570340.94128762771483
1680.09761094033939460.1952218806787890.902389059660605
1690.09912031286536750.1982406257307350.900879687134633
1700.08622592946270860.1724518589254170.913774070537291
1710.1497438236515430.2994876473030850.850256176348457
1720.1299938515598180.2599877031196360.870006148440182
1730.114476634570170.228953269140340.88552336542983
1740.09844538242913350.1968907648582670.901554617570867
1750.1358831574203270.2717663148406540.864116842579673
1760.1177877684395250.235575536879050.882212231560475
1770.1058769088953780.2117538177907570.894123091104622
1780.09080545601618970.1816109120323790.90919454398381
1790.07670846417326670.1534169283465330.923291535826733
1800.06436200172338020.128724003446760.93563799827662
1810.05378805257581710.1075761051516340.946211947424183
1820.06151113737356640.1230222747471330.938488862626434
1830.06156140530572350.1231228106114470.938438594694276
1840.057055925031130.114111850062260.94294407496887
1850.2271332378080950.454266475616190.772866762191905
1860.2092598905461410.4185197810922820.790740109453859
1870.1874608391663140.3749216783326270.812539160833686
1880.1870414541690160.3740829083380310.812958545830984
1890.1738303903628130.3476607807256270.826169609637187
1900.2573562900826790.5147125801653570.742643709917321
1910.2624984646999650.5249969293999310.737501535300035
1920.2321679869063690.4643359738127370.767832013093631
1930.6079059033635280.7841881932729440.392094096636472
1940.5773203383323860.8453593233352270.422679661667614
1950.5406294609045090.9187410781909830.459370539095491
1960.5078896895482990.9842206209034020.492110310451701
1970.5225290098238640.9549419803522720.477470990176136
1980.4865201752016270.9730403504032540.513479824798373
1990.4603498173773330.9206996347546650.539650182622667
2000.4622564441866340.9245128883732690.537743555813366
2010.4361787891068220.8723575782136440.563821210893178
2020.4156463411626830.8312926823253660.584353658837317
2030.3938794173404390.7877588346808770.606120582659561
2040.4449689771443420.8899379542886850.555031022855658
2050.4790811696465360.9581623392930730.520918830353464
2060.4363010528699890.8726021057399790.563698947130011
2070.3961967779411880.7923935558823770.603803222058812
2080.356234653185150.7124693063702990.64376534681485
2090.3373579285397610.6747158570795220.662642071460239
2100.2997629491131240.5995258982262480.700237050886876
2110.3655918495740740.7311836991481480.634408150425926
2120.3825125395245590.7650250790491180.617487460475441
2130.3404106762193330.6808213524386660.659589323780667
2140.3613028237418090.7226056474836180.638697176258191
2150.325336700204340.650673400408680.67466329979566
2160.288896710373590.577793420747180.71110328962641
2170.2531511233830960.5063022467661910.746848876616904
2180.2163342259473290.4326684518946590.783665774052671
2190.2147516356745650.429503271349130.785248364325435
2200.1905690556174510.3811381112349020.809430944382549
2210.2333580770512440.4667161541024890.766641922948756
2220.197358306939970.394716613879940.80264169306003
2230.1894164190396720.3788328380793440.810583580960328
2240.1641752130524920.3283504261049830.835824786947508
2250.1357099456257680.2714198912515370.864290054374232
2260.1111135306832860.2222270613665710.888886469316714
2270.0894339688653740.1788679377307480.910566031134626
2280.07180101951755870.1436020390351170.928198980482441
2290.05497168135111710.1099433627022340.945028318648883
2300.04199268839688850.0839853767937770.958007311603111
2310.06143839493224750.1228767898644950.938561605067753
2320.07508720097714920.1501744019542980.924912799022851
2330.2750541013621390.5501082027242780.724945898637861
2340.2440763156559360.4881526313118720.755923684344064
2350.198723531487080.397447062974160.80127646851292
2360.1976422468113170.3952844936226340.802357753188683
2370.2355538423775220.4711076847550440.764446157622478
2380.2526364124305270.5052728248610530.747363587569473
2390.2439444410551090.4878888821102190.756055558944891
2400.1995149073762140.3990298147524290.800485092623786
2410.1619427369624960.3238854739249930.838057263037504
2420.2022046727866140.4044093455732280.797795327213386
2430.4862336680527540.9724673361055080.513766331947246
2440.6802444844496210.6395110311007590.319755515550379
2450.604163231864490.791673536271020.39583676813551
2460.5339020851234380.9321958297531240.466097914876562
2470.4588969759126590.9177939518253170.541103024087341
2480.3933575094346760.7867150188693530.606642490565324
2490.3018590574828730.6037181149657470.698140942517127
2500.2447894071805710.4895788143611430.755210592819429
2510.3570066884602010.7140133769204020.642993311539799
2520.5801070190782140.8397859618435720.419892980921786
2530.5216263423714020.9567473152571960.478373657628598

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.991740051939589 & 0.0165198961208211 & 0.00825994806041056 \tabularnewline
12 & 0.988295109542296 & 0.0234097809154078 & 0.0117048904577039 \tabularnewline
13 & 0.975972897680437 & 0.048054204639126 & 0.024027102319563 \tabularnewline
14 & 0.975240817109085 & 0.0495183657818292 & 0.0247591828909146 \tabularnewline
15 & 0.962499577468254 & 0.0750008450634911 & 0.0375004225317455 \tabularnewline
16 & 0.949395925878092 & 0.101208148243817 & 0.0506040741219083 \tabularnewline
17 & 0.921620976359348 & 0.156758047281303 & 0.0783790236406516 \tabularnewline
18 & 0.9182376195779 & 0.1635247608442 & 0.0817623804220999 \tabularnewline
19 & 0.901424813558967 & 0.197150372882066 & 0.0985751864410328 \tabularnewline
20 & 0.861371064581757 & 0.277257870836486 & 0.138628935418243 \tabularnewline
21 & 0.82718018506771 & 0.345639629864581 & 0.17281981493229 \tabularnewline
22 & 0.779401485070511 & 0.441197029858978 & 0.220598514929489 \tabularnewline
23 & 0.733998732962335 & 0.532002534075329 & 0.266001267037665 \tabularnewline
24 & 0.694852495931117 & 0.610295008137766 & 0.305147504068883 \tabularnewline
25 & 0.642995262566071 & 0.714009474867857 & 0.357004737433929 \tabularnewline
26 & 0.64189822843164 & 0.71620354313672 & 0.35810177156836 \tabularnewline
27 & 0.659873478679343 & 0.680253042641315 & 0.340126521320657 \tabularnewline
28 & 0.67025686635181 & 0.65948626729638 & 0.32974313364819 \tabularnewline
29 & 0.610175790217765 & 0.779648419564469 & 0.389824209782235 \tabularnewline
30 & 0.56200233883518 & 0.875995322329641 & 0.43799766116482 \tabularnewline
31 & 0.511644552638572 & 0.976710894722855 & 0.488355447361427 \tabularnewline
32 & 0.527814153238108 & 0.944371693523783 & 0.472185846761892 \tabularnewline
33 & 0.467225852263109 & 0.934451704526219 & 0.532774147736891 \tabularnewline
34 & 0.412190174137235 & 0.82438034827447 & 0.587809825862765 \tabularnewline
35 & 0.394828367568558 & 0.789656735137116 & 0.605171632431442 \tabularnewline
36 & 0.381648786229593 & 0.763297572459187 & 0.618351213770407 \tabularnewline
37 & 0.331445547197668 & 0.662891094395336 & 0.668554452802332 \tabularnewline
38 & 0.315466896207096 & 0.630933792414193 & 0.684533103792904 \tabularnewline
39 & 0.296056077771831 & 0.592112155543663 & 0.703943922228169 \tabularnewline
40 & 0.270908544253358 & 0.541817088506715 & 0.729091455746642 \tabularnewline
41 & 0.241490098854251 & 0.482980197708502 & 0.758509901145749 \tabularnewline
42 & 0.214600705966039 & 0.429201411932079 & 0.785399294033961 \tabularnewline
43 & 0.253167403870122 & 0.506334807740244 & 0.746832596129878 \tabularnewline
44 & 0.215192428261743 & 0.430384856523486 & 0.784807571738257 \tabularnewline
45 & 0.179609266619349 & 0.359218533238698 & 0.820390733380651 \tabularnewline
46 & 0.217321757405695 & 0.43464351481139 & 0.782678242594305 \tabularnewline
47 & 0.236309194593791 & 0.472618389187582 & 0.763690805406209 \tabularnewline
48 & 0.199587346419001 & 0.399174692838001 & 0.800412653580999 \tabularnewline
49 & 0.188700587440145 & 0.377401174880289 & 0.811299412559855 \tabularnewline
50 & 0.174402906192301 & 0.348805812384602 & 0.825597093807699 \tabularnewline
51 & 0.181626713181167 & 0.363253426362334 & 0.818373286818833 \tabularnewline
52 & 0.15204316201862 & 0.304086324037241 & 0.84795683798138 \tabularnewline
53 & 0.158246670322998 & 0.316493340645995 & 0.841753329677002 \tabularnewline
54 & 0.139249523554868 & 0.278499047109735 & 0.860750476445132 \tabularnewline
55 & 0.21053841755837 & 0.42107683511674 & 0.78946158244163 \tabularnewline
56 & 0.475260881649888 & 0.950521763299777 & 0.524739118350112 \tabularnewline
57 & 0.432603811573757 & 0.865207623147514 & 0.567396188426243 \tabularnewline
58 & 0.39037556345365 & 0.780751126907301 & 0.60962443654635 \tabularnewline
59 & 0.350019728365569 & 0.700039456731139 & 0.649980271634431 \tabularnewline
60 & 0.346128014747834 & 0.692256029495667 & 0.653871985252166 \tabularnewline
61 & 0.34994643520086 & 0.699892870401719 & 0.65005356479914 \tabularnewline
62 & 0.31150611051119 & 0.62301222102238 & 0.68849388948881 \tabularnewline
63 & 0.321419593128287 & 0.642839186256574 & 0.678580406871713 \tabularnewline
64 & 0.285365081641409 & 0.570730163282817 & 0.714634918358591 \tabularnewline
65 & 0.260246507715144 & 0.520493015430287 & 0.739753492284856 \tabularnewline
66 & 0.227791262807511 & 0.455582525615022 & 0.772208737192489 \tabularnewline
67 & 0.20929411403542 & 0.41858822807084 & 0.79070588596458 \tabularnewline
68 & 0.189153119723932 & 0.378306239447864 & 0.810846880276068 \tabularnewline
69 & 0.188430960876572 & 0.376861921753145 & 0.811569039123428 \tabularnewline
70 & 0.162031012681519 & 0.324062025363038 & 0.837968987318481 \tabularnewline
71 & 0.142906395459345 & 0.285812790918689 & 0.857093604540655 \tabularnewline
72 & 0.122029080095376 & 0.244058160190751 & 0.877970919904624 \tabularnewline
73 & 0.104174871651209 & 0.208349743302419 & 0.895825128348791 \tabularnewline
74 & 0.0885868820785871 & 0.177173764157174 & 0.911413117921413 \tabularnewline
75 & 0.0795368582261259 & 0.159073716452252 & 0.920463141773874 \tabularnewline
76 & 0.100638059181433 & 0.201276118362866 & 0.899361940818567 \tabularnewline
77 & 0.0900532323571547 & 0.180106464714309 & 0.909946767642845 \tabularnewline
78 & 0.074689418199085 & 0.14937883639817 & 0.925310581800915 \tabularnewline
79 & 0.0799307370632206 & 0.159861474126441 & 0.920069262936779 \tabularnewline
80 & 0.0767122073617469 & 0.153424414723494 & 0.923287792638253 \tabularnewline
81 & 0.0636740648986882 & 0.127348129797376 & 0.936325935101312 \tabularnewline
82 & 0.0526335991774793 & 0.105267198354959 & 0.947366400822521 \tabularnewline
83 & 0.0457832337580367 & 0.0915664675160735 & 0.954216766241963 \tabularnewline
84 & 0.0372254613375857 & 0.0744509226751714 & 0.962774538662414 \tabularnewline
85 & 0.0341066557892772 & 0.0682133115785544 & 0.965893344210723 \tabularnewline
86 & 0.0388002147879315 & 0.077600429575863 & 0.961199785212069 \tabularnewline
87 & 0.031425993761874 & 0.062851987523748 & 0.968574006238126 \tabularnewline
88 & 0.0256129755572357 & 0.0512259511144715 & 0.974387024442764 \tabularnewline
89 & 0.0217311852448596 & 0.0434623704897191 & 0.97826881475514 \tabularnewline
90 & 0.0181921182669952 & 0.0363842365339904 & 0.981807881733005 \tabularnewline
91 & 0.0300013841157717 & 0.0600027682315435 & 0.969998615884228 \tabularnewline
92 & 0.0248725771944579 & 0.0497451543889157 & 0.975127422805542 \tabularnewline
93 & 0.02269473667793 & 0.0453894733558599 & 0.97730526332207 \tabularnewline
94 & 0.0244079014574943 & 0.0488158029149885 & 0.975592098542506 \tabularnewline
95 & 0.024415042955121 & 0.0488300859102419 & 0.975584957044879 \tabularnewline
96 & 0.0221559763157406 & 0.0443119526314812 & 0.977844023684259 \tabularnewline
97 & 0.0272574865391359 & 0.0545149730782718 & 0.972742513460864 \tabularnewline
98 & 0.0220915492546153 & 0.0441830985092307 & 0.977908450745385 \tabularnewline
99 & 0.0186951723249676 & 0.0373903446499352 & 0.981304827675032 \tabularnewline
100 & 0.0218668275458214 & 0.0437336550916429 & 0.978133172454179 \tabularnewline
101 & 0.0180529550651881 & 0.0361059101303761 & 0.981947044934812 \tabularnewline
102 & 0.0153229274032571 & 0.0306458548065141 & 0.984677072596743 \tabularnewline
103 & 0.012163897832049 & 0.0243277956640979 & 0.987836102167951 \tabularnewline
104 & 0.0107545257489956 & 0.0215090514979912 & 0.989245474251004 \tabularnewline
105 & 0.0120594611898531 & 0.0241189223797061 & 0.987940538810147 \tabularnewline
106 & 0.00943281083511611 & 0.0188656216702322 & 0.990567189164884 \tabularnewline
107 & 0.00741117090015162 & 0.0148223418003032 & 0.992588829099848 \tabularnewline
108 & 0.00607659949884643 & 0.0121531989976929 & 0.993923400501154 \tabularnewline
109 & 0.00853939374602589 & 0.0170787874920518 & 0.991460606253974 \tabularnewline
110 & 0.00665424482122996 & 0.0133084896424599 & 0.99334575517877 \tabularnewline
111 & 0.00767385722983446 & 0.0153477144596689 & 0.992326142770166 \tabularnewline
112 & 0.00802764424402007 & 0.0160552884880401 & 0.99197235575598 \tabularnewline
113 & 0.00665480622222963 & 0.0133096124444593 & 0.99334519377777 \tabularnewline
114 & 0.00537791265792865 & 0.0107558253158573 & 0.994622087342071 \tabularnewline
115 & 0.00418660641328748 & 0.00837321282657496 & 0.995813393586713 \tabularnewline
116 & 0.00492560330348943 & 0.00985120660697886 & 0.995074396696511 \tabularnewline
117 & 0.0070966621017568 & 0.0141933242035136 & 0.992903337898243 \tabularnewline
118 & 0.005933367059507 & 0.011866734119014 & 0.994066632940493 \tabularnewline
119 & 0.00460244531738274 & 0.00920489063476547 & 0.995397554682617 \tabularnewline
120 & 0.00386210006874931 & 0.00772420013749861 & 0.996137899931251 \tabularnewline
121 & 0.0037145329877362 & 0.00742906597547241 & 0.996285467012264 \tabularnewline
122 & 0.00374002639699872 & 0.00748005279399745 & 0.996259973603001 \tabularnewline
123 & 0.00443300574830565 & 0.0088660114966113 & 0.995566994251694 \tabularnewline
124 & 0.00507284077202616 & 0.0101456815440523 & 0.994927159227974 \tabularnewline
125 & 0.00911585322845748 & 0.018231706456915 & 0.990884146771543 \tabularnewline
126 & 0.0075837950491324 & 0.0151675900982648 & 0.992416204950868 \tabularnewline
127 & 0.00650567242870773 & 0.0130113448574155 & 0.993494327571292 \tabularnewline
128 & 0.00676254945966308 & 0.0135250989193262 & 0.993237450540337 \tabularnewline
129 & 0.00666720500777202 & 0.013334410015544 & 0.993332794992228 \tabularnewline
130 & 0.00666624927295091 & 0.0133324985459018 & 0.993333750727049 \tabularnewline
131 & 0.0084697515484522 & 0.0169395030969044 & 0.991530248451548 \tabularnewline
132 & 0.0171888148368684 & 0.0343776296737368 & 0.982811185163132 \tabularnewline
133 & 0.0167755343009769 & 0.0335510686019538 & 0.983224465699023 \tabularnewline
134 & 0.0157068930167472 & 0.0314137860334944 & 0.984293106983253 \tabularnewline
135 & 0.0136533836972139 & 0.0273067673944278 & 0.986346616302786 \tabularnewline
136 & 0.0111100680160162 & 0.0222201360320325 & 0.988889931983984 \tabularnewline
137 & 0.00881259240672892 & 0.0176251848134578 & 0.991187407593271 \tabularnewline
138 & 0.00790389435555495 & 0.0158077887111099 & 0.992096105644445 \tabularnewline
139 & 0.0070443164480192 & 0.0140886328960384 & 0.992955683551981 \tabularnewline
140 & 0.00572023610908725 & 0.0114404722181745 & 0.994279763890913 \tabularnewline
141 & 0.0108772231348659 & 0.0217544462697318 & 0.989122776865134 \tabularnewline
142 & 0.0127360906243045 & 0.0254721812486091 & 0.987263909375695 \tabularnewline
143 & 0.0169800889975287 & 0.0339601779950574 & 0.983019911002471 \tabularnewline
144 & 0.0135881673400009 & 0.0271763346800018 & 0.986411832659999 \tabularnewline
145 & 0.0107619124311761 & 0.0215238248623522 & 0.989238087568824 \tabularnewline
146 & 0.00872101441088848 & 0.017442028821777 & 0.991278985589112 \tabularnewline
147 & 0.00974006658613346 & 0.0194801331722669 & 0.990259933413867 \tabularnewline
148 & 0.00784822387456505 & 0.0156964477491301 & 0.992151776125435 \tabularnewline
149 & 0.00659330773065958 & 0.0131866154613192 & 0.99340669226934 \tabularnewline
150 & 0.00595408549060431 & 0.0119081709812086 & 0.994045914509396 \tabularnewline
151 & 0.00617619137056761 & 0.0123523827411352 & 0.993823808629432 \tabularnewline
152 & 0.00828841956791085 & 0.0165768391358217 & 0.991711580432089 \tabularnewline
153 & 0.0532691616879761 & 0.106538323375952 & 0.946730838312024 \tabularnewline
154 & 0.0605222789114802 & 0.12104455782296 & 0.93947772108852 \tabularnewline
155 & 0.0506418873292161 & 0.101283774658432 & 0.949358112670784 \tabularnewline
156 & 0.0728917011533457 & 0.145783402306691 & 0.927108298846654 \tabularnewline
157 & 0.12809222781794 & 0.25618445563588 & 0.87190777218206 \tabularnewline
158 & 0.129447318842206 & 0.258894637684411 & 0.870552681157794 \tabularnewline
159 & 0.112546695998417 & 0.225093391996834 & 0.887453304001583 \tabularnewline
160 & 0.108798589006654 & 0.217597178013309 & 0.891201410993346 \tabularnewline
161 & 0.107918123334055 & 0.215836246668109 & 0.892081876665945 \tabularnewline
162 & 0.0936909149463207 & 0.187381829892641 & 0.906309085053679 \tabularnewline
163 & 0.0843625665201143 & 0.168725133040229 & 0.915637433479886 \tabularnewline
164 & 0.0895617683630068 & 0.179123536726014 & 0.910438231636993 \tabularnewline
165 & 0.081124880259342 & 0.162249760518684 & 0.918875119740658 \tabularnewline
166 & 0.0690246846659283 & 0.138049369331857 & 0.930975315334072 \tabularnewline
167 & 0.0587123722851699 & 0.11742474457034 & 0.94128762771483 \tabularnewline
168 & 0.0976109403393946 & 0.195221880678789 & 0.902389059660605 \tabularnewline
169 & 0.0991203128653675 & 0.198240625730735 & 0.900879687134633 \tabularnewline
170 & 0.0862259294627086 & 0.172451858925417 & 0.913774070537291 \tabularnewline
171 & 0.149743823651543 & 0.299487647303085 & 0.850256176348457 \tabularnewline
172 & 0.129993851559818 & 0.259987703119636 & 0.870006148440182 \tabularnewline
173 & 0.11447663457017 & 0.22895326914034 & 0.88552336542983 \tabularnewline
174 & 0.0984453824291335 & 0.196890764858267 & 0.901554617570867 \tabularnewline
175 & 0.135883157420327 & 0.271766314840654 & 0.864116842579673 \tabularnewline
176 & 0.117787768439525 & 0.23557553687905 & 0.882212231560475 \tabularnewline
177 & 0.105876908895378 & 0.211753817790757 & 0.894123091104622 \tabularnewline
178 & 0.0908054560161897 & 0.181610912032379 & 0.90919454398381 \tabularnewline
179 & 0.0767084641732667 & 0.153416928346533 & 0.923291535826733 \tabularnewline
180 & 0.0643620017233802 & 0.12872400344676 & 0.93563799827662 \tabularnewline
181 & 0.0537880525758171 & 0.107576105151634 & 0.946211947424183 \tabularnewline
182 & 0.0615111373735664 & 0.123022274747133 & 0.938488862626434 \tabularnewline
183 & 0.0615614053057235 & 0.123122810611447 & 0.938438594694276 \tabularnewline
184 & 0.05705592503113 & 0.11411185006226 & 0.94294407496887 \tabularnewline
185 & 0.227133237808095 & 0.45426647561619 & 0.772866762191905 \tabularnewline
186 & 0.209259890546141 & 0.418519781092282 & 0.790740109453859 \tabularnewline
187 & 0.187460839166314 & 0.374921678332627 & 0.812539160833686 \tabularnewline
188 & 0.187041454169016 & 0.374082908338031 & 0.812958545830984 \tabularnewline
189 & 0.173830390362813 & 0.347660780725627 & 0.826169609637187 \tabularnewline
190 & 0.257356290082679 & 0.514712580165357 & 0.742643709917321 \tabularnewline
191 & 0.262498464699965 & 0.524996929399931 & 0.737501535300035 \tabularnewline
192 & 0.232167986906369 & 0.464335973812737 & 0.767832013093631 \tabularnewline
193 & 0.607905903363528 & 0.784188193272944 & 0.392094096636472 \tabularnewline
194 & 0.577320338332386 & 0.845359323335227 & 0.422679661667614 \tabularnewline
195 & 0.540629460904509 & 0.918741078190983 & 0.459370539095491 \tabularnewline
196 & 0.507889689548299 & 0.984220620903402 & 0.492110310451701 \tabularnewline
197 & 0.522529009823864 & 0.954941980352272 & 0.477470990176136 \tabularnewline
198 & 0.486520175201627 & 0.973040350403254 & 0.513479824798373 \tabularnewline
199 & 0.460349817377333 & 0.920699634754665 & 0.539650182622667 \tabularnewline
200 & 0.462256444186634 & 0.924512888373269 & 0.537743555813366 \tabularnewline
201 & 0.436178789106822 & 0.872357578213644 & 0.563821210893178 \tabularnewline
202 & 0.415646341162683 & 0.831292682325366 & 0.584353658837317 \tabularnewline
203 & 0.393879417340439 & 0.787758834680877 & 0.606120582659561 \tabularnewline
204 & 0.444968977144342 & 0.889937954288685 & 0.555031022855658 \tabularnewline
205 & 0.479081169646536 & 0.958162339293073 & 0.520918830353464 \tabularnewline
206 & 0.436301052869989 & 0.872602105739979 & 0.563698947130011 \tabularnewline
207 & 0.396196777941188 & 0.792393555882377 & 0.603803222058812 \tabularnewline
208 & 0.35623465318515 & 0.712469306370299 & 0.64376534681485 \tabularnewline
209 & 0.337357928539761 & 0.674715857079522 & 0.662642071460239 \tabularnewline
210 & 0.299762949113124 & 0.599525898226248 & 0.700237050886876 \tabularnewline
211 & 0.365591849574074 & 0.731183699148148 & 0.634408150425926 \tabularnewline
212 & 0.382512539524559 & 0.765025079049118 & 0.617487460475441 \tabularnewline
213 & 0.340410676219333 & 0.680821352438666 & 0.659589323780667 \tabularnewline
214 & 0.361302823741809 & 0.722605647483618 & 0.638697176258191 \tabularnewline
215 & 0.32533670020434 & 0.65067340040868 & 0.67466329979566 \tabularnewline
216 & 0.28889671037359 & 0.57779342074718 & 0.71110328962641 \tabularnewline
217 & 0.253151123383096 & 0.506302246766191 & 0.746848876616904 \tabularnewline
218 & 0.216334225947329 & 0.432668451894659 & 0.783665774052671 \tabularnewline
219 & 0.214751635674565 & 0.42950327134913 & 0.785248364325435 \tabularnewline
220 & 0.190569055617451 & 0.381138111234902 & 0.809430944382549 \tabularnewline
221 & 0.233358077051244 & 0.466716154102489 & 0.766641922948756 \tabularnewline
222 & 0.19735830693997 & 0.39471661387994 & 0.80264169306003 \tabularnewline
223 & 0.189416419039672 & 0.378832838079344 & 0.810583580960328 \tabularnewline
224 & 0.164175213052492 & 0.328350426104983 & 0.835824786947508 \tabularnewline
225 & 0.135709945625768 & 0.271419891251537 & 0.864290054374232 \tabularnewline
226 & 0.111113530683286 & 0.222227061366571 & 0.888886469316714 \tabularnewline
227 & 0.089433968865374 & 0.178867937730748 & 0.910566031134626 \tabularnewline
228 & 0.0718010195175587 & 0.143602039035117 & 0.928198980482441 \tabularnewline
229 & 0.0549716813511171 & 0.109943362702234 & 0.945028318648883 \tabularnewline
230 & 0.0419926883968885 & 0.083985376793777 & 0.958007311603111 \tabularnewline
231 & 0.0614383949322475 & 0.122876789864495 & 0.938561605067753 \tabularnewline
232 & 0.0750872009771492 & 0.150174401954298 & 0.924912799022851 \tabularnewline
233 & 0.275054101362139 & 0.550108202724278 & 0.724945898637861 \tabularnewline
234 & 0.244076315655936 & 0.488152631311872 & 0.755923684344064 \tabularnewline
235 & 0.19872353148708 & 0.39744706297416 & 0.80127646851292 \tabularnewline
236 & 0.197642246811317 & 0.395284493622634 & 0.802357753188683 \tabularnewline
237 & 0.235553842377522 & 0.471107684755044 & 0.764446157622478 \tabularnewline
238 & 0.252636412430527 & 0.505272824861053 & 0.747363587569473 \tabularnewline
239 & 0.243944441055109 & 0.487888882110219 & 0.756055558944891 \tabularnewline
240 & 0.199514907376214 & 0.399029814752429 & 0.800485092623786 \tabularnewline
241 & 0.161942736962496 & 0.323885473924993 & 0.838057263037504 \tabularnewline
242 & 0.202204672786614 & 0.404409345573228 & 0.797795327213386 \tabularnewline
243 & 0.486233668052754 & 0.972467336105508 & 0.513766331947246 \tabularnewline
244 & 0.680244484449621 & 0.639511031100759 & 0.319755515550379 \tabularnewline
245 & 0.60416323186449 & 0.79167353627102 & 0.39583676813551 \tabularnewline
246 & 0.533902085123438 & 0.932195829753124 & 0.466097914876562 \tabularnewline
247 & 0.458896975912659 & 0.917793951825317 & 0.541103024087341 \tabularnewline
248 & 0.393357509434676 & 0.786715018869353 & 0.606642490565324 \tabularnewline
249 & 0.301859057482873 & 0.603718114965747 & 0.698140942517127 \tabularnewline
250 & 0.244789407180571 & 0.489578814361143 & 0.755210592819429 \tabularnewline
251 & 0.357006688460201 & 0.714013376920402 & 0.642993311539799 \tabularnewline
252 & 0.580107019078214 & 0.839785961843572 & 0.419892980921786 \tabularnewline
253 & 0.521626342371402 & 0.956747315257196 & 0.478373657628598 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225459&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]0.991740051939589[/C][C]0.0165198961208211[/C][C]0.00825994806041056[/C][/ROW]
[ROW][C]12[/C][C]0.988295109542296[/C][C]0.0234097809154078[/C][C]0.0117048904577039[/C][/ROW]
[ROW][C]13[/C][C]0.975972897680437[/C][C]0.048054204639126[/C][C]0.024027102319563[/C][/ROW]
[ROW][C]14[/C][C]0.975240817109085[/C][C]0.0495183657818292[/C][C]0.0247591828909146[/C][/ROW]
[ROW][C]15[/C][C]0.962499577468254[/C][C]0.0750008450634911[/C][C]0.0375004225317455[/C][/ROW]
[ROW][C]16[/C][C]0.949395925878092[/C][C]0.101208148243817[/C][C]0.0506040741219083[/C][/ROW]
[ROW][C]17[/C][C]0.921620976359348[/C][C]0.156758047281303[/C][C]0.0783790236406516[/C][/ROW]
[ROW][C]18[/C][C]0.9182376195779[/C][C]0.1635247608442[/C][C]0.0817623804220999[/C][/ROW]
[ROW][C]19[/C][C]0.901424813558967[/C][C]0.197150372882066[/C][C]0.0985751864410328[/C][/ROW]
[ROW][C]20[/C][C]0.861371064581757[/C][C]0.277257870836486[/C][C]0.138628935418243[/C][/ROW]
[ROW][C]21[/C][C]0.82718018506771[/C][C]0.345639629864581[/C][C]0.17281981493229[/C][/ROW]
[ROW][C]22[/C][C]0.779401485070511[/C][C]0.441197029858978[/C][C]0.220598514929489[/C][/ROW]
[ROW][C]23[/C][C]0.733998732962335[/C][C]0.532002534075329[/C][C]0.266001267037665[/C][/ROW]
[ROW][C]24[/C][C]0.694852495931117[/C][C]0.610295008137766[/C][C]0.305147504068883[/C][/ROW]
[ROW][C]25[/C][C]0.642995262566071[/C][C]0.714009474867857[/C][C]0.357004737433929[/C][/ROW]
[ROW][C]26[/C][C]0.64189822843164[/C][C]0.71620354313672[/C][C]0.35810177156836[/C][/ROW]
[ROW][C]27[/C][C]0.659873478679343[/C][C]0.680253042641315[/C][C]0.340126521320657[/C][/ROW]
[ROW][C]28[/C][C]0.67025686635181[/C][C]0.65948626729638[/C][C]0.32974313364819[/C][/ROW]
[ROW][C]29[/C][C]0.610175790217765[/C][C]0.779648419564469[/C][C]0.389824209782235[/C][/ROW]
[ROW][C]30[/C][C]0.56200233883518[/C][C]0.875995322329641[/C][C]0.43799766116482[/C][/ROW]
[ROW][C]31[/C][C]0.511644552638572[/C][C]0.976710894722855[/C][C]0.488355447361427[/C][/ROW]
[ROW][C]32[/C][C]0.527814153238108[/C][C]0.944371693523783[/C][C]0.472185846761892[/C][/ROW]
[ROW][C]33[/C][C]0.467225852263109[/C][C]0.934451704526219[/C][C]0.532774147736891[/C][/ROW]
[ROW][C]34[/C][C]0.412190174137235[/C][C]0.82438034827447[/C][C]0.587809825862765[/C][/ROW]
[ROW][C]35[/C][C]0.394828367568558[/C][C]0.789656735137116[/C][C]0.605171632431442[/C][/ROW]
[ROW][C]36[/C][C]0.381648786229593[/C][C]0.763297572459187[/C][C]0.618351213770407[/C][/ROW]
[ROW][C]37[/C][C]0.331445547197668[/C][C]0.662891094395336[/C][C]0.668554452802332[/C][/ROW]
[ROW][C]38[/C][C]0.315466896207096[/C][C]0.630933792414193[/C][C]0.684533103792904[/C][/ROW]
[ROW][C]39[/C][C]0.296056077771831[/C][C]0.592112155543663[/C][C]0.703943922228169[/C][/ROW]
[ROW][C]40[/C][C]0.270908544253358[/C][C]0.541817088506715[/C][C]0.729091455746642[/C][/ROW]
[ROW][C]41[/C][C]0.241490098854251[/C][C]0.482980197708502[/C][C]0.758509901145749[/C][/ROW]
[ROW][C]42[/C][C]0.214600705966039[/C][C]0.429201411932079[/C][C]0.785399294033961[/C][/ROW]
[ROW][C]43[/C][C]0.253167403870122[/C][C]0.506334807740244[/C][C]0.746832596129878[/C][/ROW]
[ROW][C]44[/C][C]0.215192428261743[/C][C]0.430384856523486[/C][C]0.784807571738257[/C][/ROW]
[ROW][C]45[/C][C]0.179609266619349[/C][C]0.359218533238698[/C][C]0.820390733380651[/C][/ROW]
[ROW][C]46[/C][C]0.217321757405695[/C][C]0.43464351481139[/C][C]0.782678242594305[/C][/ROW]
[ROW][C]47[/C][C]0.236309194593791[/C][C]0.472618389187582[/C][C]0.763690805406209[/C][/ROW]
[ROW][C]48[/C][C]0.199587346419001[/C][C]0.399174692838001[/C][C]0.800412653580999[/C][/ROW]
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[ROW][C]191[/C][C]0.262498464699965[/C][C]0.524996929399931[/C][C]0.737501535300035[/C][/ROW]
[ROW][C]192[/C][C]0.232167986906369[/C][C]0.464335973812737[/C][C]0.767832013093631[/C][/ROW]
[ROW][C]193[/C][C]0.607905903363528[/C][C]0.784188193272944[/C][C]0.392094096636472[/C][/ROW]
[ROW][C]194[/C][C]0.577320338332386[/C][C]0.845359323335227[/C][C]0.422679661667614[/C][/ROW]
[ROW][C]195[/C][C]0.540629460904509[/C][C]0.918741078190983[/C][C]0.459370539095491[/C][/ROW]
[ROW][C]196[/C][C]0.507889689548299[/C][C]0.984220620903402[/C][C]0.492110310451701[/C][/ROW]
[ROW][C]197[/C][C]0.522529009823864[/C][C]0.954941980352272[/C][C]0.477470990176136[/C][/ROW]
[ROW][C]198[/C][C]0.486520175201627[/C][C]0.973040350403254[/C][C]0.513479824798373[/C][/ROW]
[ROW][C]199[/C][C]0.460349817377333[/C][C]0.920699634754665[/C][C]0.539650182622667[/C][/ROW]
[ROW][C]200[/C][C]0.462256444186634[/C][C]0.924512888373269[/C][C]0.537743555813366[/C][/ROW]
[ROW][C]201[/C][C]0.436178789106822[/C][C]0.872357578213644[/C][C]0.563821210893178[/C][/ROW]
[ROW][C]202[/C][C]0.415646341162683[/C][C]0.831292682325366[/C][C]0.584353658837317[/C][/ROW]
[ROW][C]203[/C][C]0.393879417340439[/C][C]0.787758834680877[/C][C]0.606120582659561[/C][/ROW]
[ROW][C]204[/C][C]0.444968977144342[/C][C]0.889937954288685[/C][C]0.555031022855658[/C][/ROW]
[ROW][C]205[/C][C]0.479081169646536[/C][C]0.958162339293073[/C][C]0.520918830353464[/C][/ROW]
[ROW][C]206[/C][C]0.436301052869989[/C][C]0.872602105739979[/C][C]0.563698947130011[/C][/ROW]
[ROW][C]207[/C][C]0.396196777941188[/C][C]0.792393555882377[/C][C]0.603803222058812[/C][/ROW]
[ROW][C]208[/C][C]0.35623465318515[/C][C]0.712469306370299[/C][C]0.64376534681485[/C][/ROW]
[ROW][C]209[/C][C]0.337357928539761[/C][C]0.674715857079522[/C][C]0.662642071460239[/C][/ROW]
[ROW][C]210[/C][C]0.299762949113124[/C][C]0.599525898226248[/C][C]0.700237050886876[/C][/ROW]
[ROW][C]211[/C][C]0.365591849574074[/C][C]0.731183699148148[/C][C]0.634408150425926[/C][/ROW]
[ROW][C]212[/C][C]0.382512539524559[/C][C]0.765025079049118[/C][C]0.617487460475441[/C][/ROW]
[ROW][C]213[/C][C]0.340410676219333[/C][C]0.680821352438666[/C][C]0.659589323780667[/C][/ROW]
[ROW][C]214[/C][C]0.361302823741809[/C][C]0.722605647483618[/C][C]0.638697176258191[/C][/ROW]
[ROW][C]215[/C][C]0.32533670020434[/C][C]0.65067340040868[/C][C]0.67466329979566[/C][/ROW]
[ROW][C]216[/C][C]0.28889671037359[/C][C]0.57779342074718[/C][C]0.71110328962641[/C][/ROW]
[ROW][C]217[/C][C]0.253151123383096[/C][C]0.506302246766191[/C][C]0.746848876616904[/C][/ROW]
[ROW][C]218[/C][C]0.216334225947329[/C][C]0.432668451894659[/C][C]0.783665774052671[/C][/ROW]
[ROW][C]219[/C][C]0.214751635674565[/C][C]0.42950327134913[/C][C]0.785248364325435[/C][/ROW]
[ROW][C]220[/C][C]0.190569055617451[/C][C]0.381138111234902[/C][C]0.809430944382549[/C][/ROW]
[ROW][C]221[/C][C]0.233358077051244[/C][C]0.466716154102489[/C][C]0.766641922948756[/C][/ROW]
[ROW][C]222[/C][C]0.19735830693997[/C][C]0.39471661387994[/C][C]0.80264169306003[/C][/ROW]
[ROW][C]223[/C][C]0.189416419039672[/C][C]0.378832838079344[/C][C]0.810583580960328[/C][/ROW]
[ROW][C]224[/C][C]0.164175213052492[/C][C]0.328350426104983[/C][C]0.835824786947508[/C][/ROW]
[ROW][C]225[/C][C]0.135709945625768[/C][C]0.271419891251537[/C][C]0.864290054374232[/C][/ROW]
[ROW][C]226[/C][C]0.111113530683286[/C][C]0.222227061366571[/C][C]0.888886469316714[/C][/ROW]
[ROW][C]227[/C][C]0.089433968865374[/C][C]0.178867937730748[/C][C]0.910566031134626[/C][/ROW]
[ROW][C]228[/C][C]0.0718010195175587[/C][C]0.143602039035117[/C][C]0.928198980482441[/C][/ROW]
[ROW][C]229[/C][C]0.0549716813511171[/C][C]0.109943362702234[/C][C]0.945028318648883[/C][/ROW]
[ROW][C]230[/C][C]0.0419926883968885[/C][C]0.083985376793777[/C][C]0.958007311603111[/C][/ROW]
[ROW][C]231[/C][C]0.0614383949322475[/C][C]0.122876789864495[/C][C]0.938561605067753[/C][/ROW]
[ROW][C]232[/C][C]0.0750872009771492[/C][C]0.150174401954298[/C][C]0.924912799022851[/C][/ROW]
[ROW][C]233[/C][C]0.275054101362139[/C][C]0.550108202724278[/C][C]0.724945898637861[/C][/ROW]
[ROW][C]234[/C][C]0.244076315655936[/C][C]0.488152631311872[/C][C]0.755923684344064[/C][/ROW]
[ROW][C]235[/C][C]0.19872353148708[/C][C]0.39744706297416[/C][C]0.80127646851292[/C][/ROW]
[ROW][C]236[/C][C]0.197642246811317[/C][C]0.395284493622634[/C][C]0.802357753188683[/C][/ROW]
[ROW][C]237[/C][C]0.235553842377522[/C][C]0.471107684755044[/C][C]0.764446157622478[/C][/ROW]
[ROW][C]238[/C][C]0.252636412430527[/C][C]0.505272824861053[/C][C]0.747363587569473[/C][/ROW]
[ROW][C]239[/C][C]0.243944441055109[/C][C]0.487888882110219[/C][C]0.756055558944891[/C][/ROW]
[ROW][C]240[/C][C]0.199514907376214[/C][C]0.399029814752429[/C][C]0.800485092623786[/C][/ROW]
[ROW][C]241[/C][C]0.161942736962496[/C][C]0.323885473924993[/C][C]0.838057263037504[/C][/ROW]
[ROW][C]242[/C][C]0.202204672786614[/C][C]0.404409345573228[/C][C]0.797795327213386[/C][/ROW]
[ROW][C]243[/C][C]0.486233668052754[/C][C]0.972467336105508[/C][C]0.513766331947246[/C][/ROW]
[ROW][C]244[/C][C]0.680244484449621[/C][C]0.639511031100759[/C][C]0.319755515550379[/C][/ROW]
[ROW][C]245[/C][C]0.60416323186449[/C][C]0.79167353627102[/C][C]0.39583676813551[/C][/ROW]
[ROW][C]246[/C][C]0.533902085123438[/C][C]0.932195829753124[/C][C]0.466097914876562[/C][/ROW]
[ROW][C]247[/C][C]0.458896975912659[/C][C]0.917793951825317[/C][C]0.541103024087341[/C][/ROW]
[ROW][C]248[/C][C]0.393357509434676[/C][C]0.786715018869353[/C][C]0.606642490565324[/C][/ROW]
[ROW][C]249[/C][C]0.301859057482873[/C][C]0.603718114965747[/C][C]0.698140942517127[/C][/ROW]
[ROW][C]250[/C][C]0.244789407180571[/C][C]0.489578814361143[/C][C]0.755210592819429[/C][/ROW]
[ROW][C]251[/C][C]0.357006688460201[/C][C]0.714013376920402[/C][C]0.642993311539799[/C][/ROW]
[ROW][C]252[/C][C]0.580107019078214[/C][C]0.839785961843572[/C][C]0.419892980921786[/C][/ROW]
[ROW][C]253[/C][C]0.521626342371402[/C][C]0.956747315257196[/C][C]0.478373657628598[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225459&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225459&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
110.9917400519395890.01651989612082110.00825994806041056
120.9882951095422960.02340978091540780.0117048904577039
130.9759728976804370.0480542046391260.024027102319563
140.9752408171090850.04951836578182920.0247591828909146
150.9624995774682540.07500084506349110.0375004225317455
160.9493959258780920.1012081482438170.0506040741219083
170.9216209763593480.1567580472813030.0783790236406516
180.91823761957790.16352476084420.0817623804220999
190.9014248135589670.1971503728820660.0985751864410328
200.8613710645817570.2772578708364860.138628935418243
210.827180185067710.3456396298645810.17281981493229
220.7794014850705110.4411970298589780.220598514929489
230.7339987329623350.5320025340753290.266001267037665
240.6948524959311170.6102950081377660.305147504068883
250.6429952625660710.7140094748678570.357004737433929
260.641898228431640.716203543136720.35810177156836
270.6598734786793430.6802530426413150.340126521320657
280.670256866351810.659486267296380.32974313364819
290.6101757902177650.7796484195644690.389824209782235
300.562002338835180.8759953223296410.43799766116482
310.5116445526385720.9767108947228550.488355447361427
320.5278141532381080.9443716935237830.472185846761892
330.4672258522631090.9344517045262190.532774147736891
340.4121901741372350.824380348274470.587809825862765
350.3948283675685580.7896567351371160.605171632431442
360.3816487862295930.7632975724591870.618351213770407
370.3314455471976680.6628910943953360.668554452802332
380.3154668962070960.6309337924141930.684533103792904
390.2960560777718310.5921121555436630.703943922228169
400.2709085442533580.5418170885067150.729091455746642
410.2414900988542510.4829801977085020.758509901145749
420.2146007059660390.4292014119320790.785399294033961
430.2531674038701220.5063348077402440.746832596129878
440.2151924282617430.4303848565234860.784807571738257
450.1796092666193490.3592185332386980.820390733380651
460.2173217574056950.434643514811390.782678242594305
470.2363091945937910.4726183891875820.763690805406209
480.1995873464190010.3991746928380010.800412653580999
490.1887005874401450.3774011748802890.811299412559855
500.1744029061923010.3488058123846020.825597093807699
510.1816267131811670.3632534263623340.818373286818833
520.152043162018620.3040863240372410.84795683798138
530.1582466703229980.3164933406459950.841753329677002
540.1392495235548680.2784990471097350.860750476445132
550.210538417558370.421076835116740.78946158244163
560.4752608816498880.9505217632997770.524739118350112
570.4326038115737570.8652076231475140.567396188426243
580.390375563453650.7807511269073010.60962443654635
590.3500197283655690.7000394567311390.649980271634431
600.3461280147478340.6922560294956670.653871985252166
610.349946435200860.6998928704017190.65005356479914
620.311506110511190.623012221022380.68849388948881
630.3214195931282870.6428391862565740.678580406871713
640.2853650816414090.5707301632828170.714634918358591
650.2602465077151440.5204930154302870.739753492284856
660.2277912628075110.4555825256150220.772208737192489
670.209294114035420.418588228070840.79070588596458
680.1891531197239320.3783062394478640.810846880276068
690.1884309608765720.3768619217531450.811569039123428
700.1620310126815190.3240620253630380.837968987318481
710.1429063954593450.2858127909186890.857093604540655
720.1220290800953760.2440581601907510.877970919904624
730.1041748716512090.2083497433024190.895825128348791
740.08858688207858710.1771737641571740.911413117921413
750.07953685822612590.1590737164522520.920463141773874
760.1006380591814330.2012761183628660.899361940818567
770.09005323235715470.1801064647143090.909946767642845
780.0746894181990850.149378836398170.925310581800915
790.07993073706322060.1598614741264410.920069262936779
800.07671220736174690.1534244147234940.923287792638253
810.06367406489868820.1273481297973760.936325935101312
820.05263359917747930.1052671983549590.947366400822521
830.04578323375803670.09156646751607350.954216766241963
840.03722546133758570.07445092267517140.962774538662414
850.03410665578927720.06821331157855440.965893344210723
860.03880021478793150.0776004295758630.961199785212069
870.0314259937618740.0628519875237480.968574006238126
880.02561297555723570.05122595111447150.974387024442764
890.02173118524485960.04346237048971910.97826881475514
900.01819211826699520.03638423653399040.981807881733005
910.03000138411577170.06000276823154350.969998615884228
920.02487257719445790.04974515438891570.975127422805542
930.022694736677930.04538947335585990.97730526332207
940.02440790145749430.04881580291498850.975592098542506
950.0244150429551210.04883008591024190.975584957044879
960.02215597631574060.04431195263148120.977844023684259
970.02725748653913590.05451497307827180.972742513460864
980.02209154925461530.04418309850923070.977908450745385
990.01869517232496760.03739034464993520.981304827675032
1000.02186682754582140.04373365509164290.978133172454179
1010.01805295506518810.03610591013037610.981947044934812
1020.01532292740325710.03064585480651410.984677072596743
1030.0121638978320490.02432779566409790.987836102167951
1040.01075452574899560.02150905149799120.989245474251004
1050.01205946118985310.02411892237970610.987940538810147
1060.009432810835116110.01886562167023220.990567189164884
1070.007411170900151620.01482234180030320.992588829099848
1080.006076599498846430.01215319899769290.993923400501154
1090.008539393746025890.01707878749205180.991460606253974
1100.006654244821229960.01330848964245990.99334575517877
1110.007673857229834460.01534771445966890.992326142770166
1120.008027644244020070.01605528848804010.99197235575598
1130.006654806222229630.01330961244445930.99334519377777
1140.005377912657928650.01075582531585730.994622087342071
1150.004186606413287480.008373212826574960.995813393586713
1160.004925603303489430.009851206606978860.995074396696511
1170.00709666210175680.01419332420351360.992903337898243
1180.0059333670595070.0118667341190140.994066632940493
1190.004602445317382740.009204890634765470.995397554682617
1200.003862100068749310.007724200137498610.996137899931251
1210.00371453298773620.007429065975472410.996285467012264
1220.003740026396998720.007480052793997450.996259973603001
1230.004433005748305650.00886601149661130.995566994251694
1240.005072840772026160.01014568154405230.994927159227974
1250.009115853228457480.0182317064569150.990884146771543
1260.00758379504913240.01516759009826480.992416204950868
1270.006505672428707730.01301134485741550.993494327571292
1280.006762549459663080.01352509891932620.993237450540337
1290.006667205007772020.0133344100155440.993332794992228
1300.006666249272950910.01333249854590180.993333750727049
1310.00846975154845220.01693950309690440.991530248451548
1320.01718881483686840.03437762967373680.982811185163132
1330.01677553430097690.03355106860195380.983224465699023
1340.01570689301674720.03141378603349440.984293106983253
1350.01365338369721390.02730676739442780.986346616302786
1360.01111006801601620.02222013603203250.988889931983984
1370.008812592406728920.01762518481345780.991187407593271
1380.007903894355554950.01580778871110990.992096105644445
1390.00704431644801920.01408863289603840.992955683551981
1400.005720236109087250.01144047221817450.994279763890913
1410.01087722313486590.02175444626973180.989122776865134
1420.01273609062430450.02547218124860910.987263909375695
1430.01698008899752870.03396017799505740.983019911002471
1440.01358816734000090.02717633468000180.986411832659999
1450.01076191243117610.02152382486235220.989238087568824
1460.008721014410888480.0174420288217770.991278985589112
1470.009740066586133460.01948013317226690.990259933413867
1480.007848223874565050.01569644774913010.992151776125435
1490.006593307730659580.01318661546131920.99340669226934
1500.005954085490604310.01190817098120860.994045914509396
1510.006176191370567610.01235238274113520.993823808629432
1520.008288419567910850.01657683913582170.991711580432089
1530.05326916168797610.1065383233759520.946730838312024
1540.06052227891148020.121044557822960.93947772108852
1550.05064188732921610.1012837746584320.949358112670784
1560.07289170115334570.1457834023066910.927108298846654
1570.128092227817940.256184455635880.87190777218206
1580.1294473188422060.2588946376844110.870552681157794
1590.1125466959984170.2250933919968340.887453304001583
1600.1087985890066540.2175971780133090.891201410993346
1610.1079181233340550.2158362466681090.892081876665945
1620.09369091494632070.1873818298926410.906309085053679
1630.08436256652011430.1687251330402290.915637433479886
1640.08956176836300680.1791235367260140.910438231636993
1650.0811248802593420.1622497605186840.918875119740658
1660.06902468466592830.1380493693318570.930975315334072
1670.05871237228516990.117424744570340.94128762771483
1680.09761094033939460.1952218806787890.902389059660605
1690.09912031286536750.1982406257307350.900879687134633
1700.08622592946270860.1724518589254170.913774070537291
1710.1497438236515430.2994876473030850.850256176348457
1720.1299938515598180.2599877031196360.870006148440182
1730.114476634570170.228953269140340.88552336542983
1740.09844538242913350.1968907648582670.901554617570867
1750.1358831574203270.2717663148406540.864116842579673
1760.1177877684395250.235575536879050.882212231560475
1770.1058769088953780.2117538177907570.894123091104622
1780.09080545601618970.1816109120323790.90919454398381
1790.07670846417326670.1534169283465330.923291535826733
1800.06436200172338020.128724003446760.93563799827662
1810.05378805257581710.1075761051516340.946211947424183
1820.06151113737356640.1230222747471330.938488862626434
1830.06156140530572350.1231228106114470.938438594694276
1840.057055925031130.114111850062260.94294407496887
1850.2271332378080950.454266475616190.772866762191905
1860.2092598905461410.4185197810922820.790740109453859
1870.1874608391663140.3749216783326270.812539160833686
1880.1870414541690160.3740829083380310.812958545830984
1890.1738303903628130.3476607807256270.826169609637187
1900.2573562900826790.5147125801653570.742643709917321
1910.2624984646999650.5249969293999310.737501535300035
1920.2321679869063690.4643359738127370.767832013093631
1930.6079059033635280.7841881932729440.392094096636472
1940.5773203383323860.8453593233352270.422679661667614
1950.5406294609045090.9187410781909830.459370539095491
1960.5078896895482990.9842206209034020.492110310451701
1970.5225290098238640.9549419803522720.477470990176136
1980.4865201752016270.9730403504032540.513479824798373
1990.4603498173773330.9206996347546650.539650182622667
2000.4622564441866340.9245128883732690.537743555813366
2010.4361787891068220.8723575782136440.563821210893178
2020.4156463411626830.8312926823253660.584353658837317
2030.3938794173404390.7877588346808770.606120582659561
2040.4449689771443420.8899379542886850.555031022855658
2050.4790811696465360.9581623392930730.520918830353464
2060.4363010528699890.8726021057399790.563698947130011
2070.3961967779411880.7923935558823770.603803222058812
2080.356234653185150.7124693063702990.64376534681485
2090.3373579285397610.6747158570795220.662642071460239
2100.2997629491131240.5995258982262480.700237050886876
2110.3655918495740740.7311836991481480.634408150425926
2120.3825125395245590.7650250790491180.617487460475441
2130.3404106762193330.6808213524386660.659589323780667
2140.3613028237418090.7226056474836180.638697176258191
2150.325336700204340.650673400408680.67466329979566
2160.288896710373590.577793420747180.71110328962641
2170.2531511233830960.5063022467661910.746848876616904
2180.2163342259473290.4326684518946590.783665774052671
2190.2147516356745650.429503271349130.785248364325435
2200.1905690556174510.3811381112349020.809430944382549
2210.2333580770512440.4667161541024890.766641922948756
2220.197358306939970.394716613879940.80264169306003
2230.1894164190396720.3788328380793440.810583580960328
2240.1641752130524920.3283504261049830.835824786947508
2250.1357099456257680.2714198912515370.864290054374232
2260.1111135306832860.2222270613665710.888886469316714
2270.0894339688653740.1788679377307480.910566031134626
2280.07180101951755870.1436020390351170.928198980482441
2290.05497168135111710.1099433627022340.945028318648883
2300.04199268839688850.0839853767937770.958007311603111
2310.06143839493224750.1228767898644950.938561605067753
2320.07508720097714920.1501744019542980.924912799022851
2330.2750541013621390.5501082027242780.724945898637861
2340.2440763156559360.4881526313118720.755923684344064
2350.198723531487080.397447062974160.80127646851292
2360.1976422468113170.3952844936226340.802357753188683
2370.2355538423775220.4711076847550440.764446157622478
2380.2526364124305270.5052728248610530.747363587569473
2390.2439444410551090.4878888821102190.756055558944891
2400.1995149073762140.3990298147524290.800485092623786
2410.1619427369624960.3238854739249930.838057263037504
2420.2022046727866140.4044093455732280.797795327213386
2430.4862336680527540.9724673361055080.513766331947246
2440.6802444844496210.6395110311007590.319755515550379
2450.604163231864490.791673536271020.39583676813551
2460.5339020851234380.9321958297531240.466097914876562
2470.4588969759126590.9177939518253170.541103024087341
2480.3933575094346760.7867150188693530.606642490565324
2490.3018590574828730.6037181149657470.698140942517127
2500.2447894071805710.4895788143611430.755210592819429
2510.3570066884602010.7140133769204020.642993311539799
2520.5801070190782140.8397859618435720.419892980921786
2530.5216263423714020.9567473152571960.478373657628598






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level70.0288065843621399NOK
5% type I error level660.271604938271605NOK
10% type I error level760.312757201646091NOK

\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 & 7 & 0.0288065843621399 & NOK \tabularnewline
5% type I error level & 66 & 0.271604938271605 & NOK \tabularnewline
10% type I error level & 76 & 0.312757201646091 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225459&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]7[/C][C]0.0288065843621399[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]66[/C][C]0.271604938271605[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]76[/C][C]0.312757201646091[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225459&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225459&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 level70.0288065843621399NOK
5% type I error level660.271604938271605NOK
10% type I error level760.312757201646091NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
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')
}