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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 05 Nov 2012 06:37:02 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/05/t1352115435pg9l446es8veay3.htm/, Retrieved Wed, 01 Feb 2023 11:44:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185983, Retrieved Wed, 01 Feb 2023 11:44:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104
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]
-       [Multiple Regression] [mu lin reg] [2012-10-31 10:14:49] [2f324ead08cc3849e52bae5d3f3d905a]
-   P       [Multiple Regression] [mod3] [2012-11-05 11:37:02] [e357aba3893873b930815b56a53f1005] [Current]
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Dataseries X:
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




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 13 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185983&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185983&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185983&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 5.33462704912005 + 0.0334318102550329Connected[t] + 0.0429100015092721Separate[t] + 0.557382329522837Software[t] + 0.0707136347126803Happiness[t] -0.0289876371504571Depression[t] + 0.0235641874876029Belonging[t] -0.0252595092689673Belonging_Final[t] -0.0049379405910949t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  5.33462704912005 +  0.0334318102550329Connected[t] +  0.0429100015092721Separate[t] +  0.557382329522837Software[t] +  0.0707136347126803Happiness[t] -0.0289876371504571Depression[t] +  0.0235641874876029Belonging[t] -0.0252595092689673Belonging_Final[t] -0.0049379405910949t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185983&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  5.33462704912005 +  0.0334318102550329Connected[t] +  0.0429100015092721Separate[t] +  0.557382329522837Software[t] +  0.0707136347126803Happiness[t] -0.0289876371504571Depression[t] +  0.0235641874876029Belonging[t] -0.0252595092689673Belonging_Final[t] -0.0049379405910949t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185983&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185983&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 5.33462704912005 + 0.0334318102550329Connected[t] + 0.0429100015092721Separate[t] + 0.557382329522837Software[t] + 0.0707136347126803Happiness[t] -0.0289876371504571Depression[t] + 0.0235641874876029Belonging[t] -0.0252595092689673Belonging_Final[t] -0.0049379405910949t + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)5.334627049120051.9627922.71790.0070210.00351
Connected0.03343181025503290.034590.96650.3347060.167353
Separate0.04291000150927210.0351321.22140.2230680.111534
Software0.5573823295228370.05386410.347900
Happiness0.07071363471268030.0579091.22110.223170.111585
Depression-0.02898763715045710.042089-0.68870.491620.24581
Belonging0.02356418748760290.0373860.63030.5290610.264531
Belonging_Final-0.02525950926896730.05566-0.45380.6503470.325173
t-0.00493794059109490.001684-2.93260.0036670.001834

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 5.33462704912005 & 1.962792 & 2.7179 & 0.007021 & 0.00351 \tabularnewline
Connected & 0.0334318102550329 & 0.03459 & 0.9665 & 0.334706 & 0.167353 \tabularnewline
Separate & 0.0429100015092721 & 0.035132 & 1.2214 & 0.223068 & 0.111534 \tabularnewline
Software & 0.557382329522837 & 0.053864 & 10.3479 & 0 & 0 \tabularnewline
Happiness & 0.0707136347126803 & 0.057909 & 1.2211 & 0.22317 & 0.111585 \tabularnewline
Depression & -0.0289876371504571 & 0.042089 & -0.6887 & 0.49162 & 0.24581 \tabularnewline
Belonging & 0.0235641874876029 & 0.037386 & 0.6303 & 0.529061 & 0.264531 \tabularnewline
Belonging_Final & -0.0252595092689673 & 0.05566 & -0.4538 & 0.650347 & 0.325173 \tabularnewline
t & -0.0049379405910949 & 0.001684 & -2.9326 & 0.003667 & 0.001834 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185983&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]5.33462704912005[/C][C]1.962792[/C][C]2.7179[/C][C]0.007021[/C][C]0.00351[/C][/ROW]
[ROW][C]Connected[/C][C]0.0334318102550329[/C][C]0.03459[/C][C]0.9665[/C][C]0.334706[/C][C]0.167353[/C][/ROW]
[ROW][C]Separate[/C][C]0.0429100015092721[/C][C]0.035132[/C][C]1.2214[/C][C]0.223068[/C][C]0.111534[/C][/ROW]
[ROW][C]Software[/C][C]0.557382329522837[/C][C]0.053864[/C][C]10.3479[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0707136347126803[/C][C]0.057909[/C][C]1.2211[/C][C]0.22317[/C][C]0.111585[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0289876371504571[/C][C]0.042089[/C][C]-0.6887[/C][C]0.49162[/C][C]0.24581[/C][/ROW]
[ROW][C]Belonging[/C][C]0.0235641874876029[/C][C]0.037386[/C][C]0.6303[/C][C]0.529061[/C][C]0.264531[/C][/ROW]
[ROW][C]Belonging_Final[/C][C]-0.0252595092689673[/C][C]0.05566[/C][C]-0.4538[/C][C]0.650347[/C][C]0.325173[/C][/ROW]
[ROW][C]t[/C][C]-0.0049379405910949[/C][C]0.001684[/C][C]-2.9326[/C][C]0.003667[/C][C]0.001834[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185983&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185983&T=2

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)5.334627049120051.9627922.71790.0070210.00351
Connected0.03343181025503290.034590.96650.3347060.167353
Separate0.04291000150927210.0351321.22140.2230680.111534
Software0.5573823295228370.05386410.347900
Happiness0.07071363471268030.0579091.22110.223170.111585
Depression-0.02898763715045710.042089-0.68870.491620.24581
Belonging0.02356418748760290.0373860.63030.5290610.264531
Belonging_Final-0.02525950926896730.05566-0.45380.6503470.325173
t-0.00493794059109490.001684-2.93260.0036670.001834







Multiple Linear Regression - Regression Statistics
Multiple R0.667548376503906
R-squared0.445620834973
Adjusted R-squared0.428228547442742
F-TEST (value)25.6217495368402
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.85709761762755
Sum Squared Residuals879.446948156467

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.667548376503906 \tabularnewline
R-squared & 0.445620834973 \tabularnewline
Adjusted R-squared & 0.428228547442742 \tabularnewline
F-TEST (value) & 25.6217495368402 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 255 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.85709761762755 \tabularnewline
Sum Squared Residuals & 879.446948156467 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185983&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.667548376503906[/C][/ROW]
[ROW][C]R-squared[/C][C]0.445620834973[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.428228547442742[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]25.6217495368402[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]255[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]1.85709761762755[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]879.446948156467[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185983&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185983&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.667548376503906
R-squared0.445620834973
Adjusted R-squared0.428228547442742
F-TEST (value)25.6217495368402
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.85709761762755
Sum Squared Residuals879.446948156467







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11316.1022982210197-3.10229822101972
21615.7544914458590.245508554141014
31917.05171257728311.94828742271692
41512.15545808399312.84454191600689
51416.4318778324043-2.43187783240426
61314.8691295709112-1.86912957091122
71915.28926302854883.71073697145122
81517.0984636628673-2.09846366286726
91416.0620688662447-2.06206886624467
101514.45679219685380.543207803146187
111614.99086211027731.00913788972271
121616.1770052175893-0.177005217589299
131615.52150358046840.478496419531648
141615.49561571664570.504384283354324
151718.0065120508452-1.0065120508452
161515.4716004383729-0.471600438372882
171514.61597068211550.384029317884485
182016.42822369964333.57177630035666
191815.4790150935912.52098490640904
201615.55578939358740.444210606412555
211615.36504326547830.634956734521665
221615.1441458781390.855854121861016
231916.48248691524712.51751308475295
241615.08551849078250.914481509217452
251716.17302056026780.826979439732198
261716.26950718772830.730492812271699
271614.99779466763471.00220533236535
281516.760323977679-1.76032397767898
291615.75550082198770.244499178012286
301414.181416577811-0.181416577811048
311515.7546834756412-0.754683475641216
321212.8348155240329-0.83481552403293
331414.8118391627312-0.81183916273115
341615.93689538828060.063104611719357
351415.5703707644626-1.57037076446263
361013.005541434452-3.005541434452
371013.0747086953106-3.07470869531064
381415.7548997678586-1.75489976785859
391614.55679944677541.44320055322457
401614.4915065565451.508493443455
411614.72297955116161.27702044883837
421415.7500199860774-1.75001998607735
432017.46497876118732.53502123881265
441414.1623540255355-0.162354025535507
451414.4650019090832-0.465001909083171
461115.5278918457463-4.52789184574632
471416.537742048153-2.53774204815302
481515.1382184624629-0.13821846246294
491615.50816652908580.491833470914169
501415.6508961989038-1.65089619890381
511617.0132875529785-1.01328755297849
521414.1613795638325-0.161379563832531
531215.0533666119315-3.05336661193155
541615.82298904132590.177010958674083
55911.3977910266151-2.39779102661507
561412.38528848084141.61471151915857
571615.86618387038930.133816129610749
581615.48299395653070.517006043469343
591515.1489452458437-0.148945245843684
601614.2183106039861.78168939601395
611211.5660773045620.433922695437972
621615.6956016526540.304398347346031
631616.5680978968282-0.568097896828235
641414.7144975746602-0.71449757466022
651615.29190801662040.70809198337962
661716.04816805197450.9518319480255
671816.2919300000091.708069999991
681814.47683483939223.52316516060783
691215.9112854601582-3.9112854601582
701615.65524972471850.344750275281548
711013.3387945042165-3.33879450421647
721414.9127730431715-0.912773043171451
731816.96778958614221.03221041385776
741817.18866762534170.811332374658303
751615.26495057660350.73504942339646
761713.51214273064913.48785726935087
771616.4136496754081-0.413649675408144
781614.48856285174151.51143714825848
791315.2105291692642-2.21052916926418
801615.12101761165840.878982388341565
811615.71272550544860.287274494551398
821615.71228247054590.287717529454097
831515.6839662612022-0.683966261202235
841514.87785960985320.12214039014684
851614.16258228323441.83741771676558
861414.1848053547452-0.184805354745237
871615.36297274922020.637027250779809
881614.8546837895331.14531621046697
891514.5236197302540.476380269745968
901213.871340301249-1.871340301249
911716.74603962811350.253960371886512
921615.83471813772690.165281862273136
931515.1102677566366-0.110267756636619
941315.0707409807562-2.07074098075619
951614.79843885258911.20156114741089
961615.76991352865640.230086471343579
971613.7196072581862.28039274181401
981615.81472437926420.185275620735792
991414.4339411801958-0.433941180195834
1001617.0258101979206-1.02581019792061
1011614.67419689806771.32580310193225
1022017.45593524075252.54406475924747
1031514.18184572147880.818154278521223
1041615.00030285183710.999697148162855
1051314.8675061755119-1.86750617551193
1061715.6882876034181.31171239658197
1071615.7228503788020.277149621197993
1081614.34915442036331.6508455796367
1091212.275456137583-0.275456137582957
1101615.28627495238360.713725047616351
1111616.0176513153709-0.0176513153709174
1121715.02670004943551.97329995056449
1131314.5664542163355-1.56645421633551
1141214.5701172401542-2.57011724015419
1151816.15213910925081.84786089074916
1161415.8505123074627-1.85051230746266
1171413.14956200204310.850437997956938
1181314.7823871743341-1.78238717433406
1191615.53744910989060.462550890109423
1201314.416850974949-1.41685097494897
1211615.39116746860730.608832531392733
1221315.839724797741-2.83972479774098
1231616.8306547434266-0.830654743426562
1241515.8273961971164-0.827396197116446
1251616.8053227042767-0.805322704276728
1261514.66496503511640.335034964883577
1271715.52779081374431.47220918625569
1281513.96166165804181.03833834195822
1291214.6840500753593-2.68405007535926
1301613.96493721040612.03506278959389
1311013.7296991647035-3.72969916470354
1321613.49015315268122.50984684731883
1331214.1462272767885-2.14622727678853
1341415.5237533235708-1.52375332357078
1351515.0605941760137-0.0605941760136943
1361312.10965546061520.890344539384808
1371514.43567480268040.564325197319618
1381113.4342499906017-2.43424999060171
1391212.975933493865-0.97593349386503
1401113.3597071648791-2.35970716487914
1411612.83592450907493.16407549092506
1421513.6572528259221.34274717407804
1431716.82394622076220.17605377923783
1441614.14344326643051.85655673356948
1451013.2656605799341-3.26566057993405
1461815.47529379854222.52470620145776
1471314.9006435559371-1.90064355593709
1481614.82750401395541.1724959860446
1491312.80245414075330.197545859246742
1501012.8872795704569-2.88727957045692
1511515.9276356858023-0.927635685802293
1521613.87570950364352.12429049635646
1531611.85293459562684.14706540437316
1541412.38801931991511.61198068008492
1551012.4090361127589-2.40903611275887
1561716.42507348969230.574926510307681
1571311.68508634140941.31491365859057
1581513.81352344030891.18647655969106
1591614.5400470100071.45995298999296
1601212.7472156095952-0.747215609595171
1611312.5995854202710.400414579728982
1621312.607333415850.392666584149958
1631212.4465137428269-0.44651374282687
1641716.23554956792630.764450432073746
1651513.69968323331091.30031676668912
1661011.6136876844136-1.61368768441355
1671414.32787037191-0.327870371910013
1681114.2106862511466-3.21068625114663
1691314.7978730780644-1.7978730780644
1701614.47328508591021.52671491408983
1711210.47964211738431.52035788261573
1721615.33387404762030.666125952379726
1731213.8661216503701-1.86612165037008
174911.3520658851189-2.35206588511894
1751214.9038825751131-2.90388257511308
1761514.55339984393330.446600156066671
1771212.2615035985194-0.261503598519359
1781212.6794441470007-0.67944414700072
1791413.77585760877590.224142391224061
1801213.3751911004819-1.37519110048189
1811614.9877821756981.01221782430197
1821111.4391784414346-0.439178441434581
1831916.65278026436492.34721973563512
1841515.1309558411913-0.130955841191348
185814.5671696852632-6.5671696852632
1861614.76730802257471.23269197742529
1871714.44667794522112.5533220547789
1881212.3914638757077-0.391463875707659
1891111.4687344908835-0.468734490883497
1901110.4193121438550.580687856145011
1911414.7132415544436-0.713241554443631
1921615.41794942817460.58205057182538
193129.73051899235562.2694810076444
1941614.0050431456041.99495685439604
1951313.6285705973993-0.62857059739933
1961514.96172237137240.0382776286276256
1971612.93352546056753.06647453943252
1981615.00292920950330.997070790496686
1991412.42901937854211.57098062145789
2001614.52343599712241.47656400287756
2011613.97908670717962.02091329282044
2021413.32905127711680.670948722883167
2031113.405240124026-2.405240124026
2041214.4275103508537-2.42751035085371
2051512.69590076643662.30409923356338
2061514.4209957098240.579004290176027
2071614.45728455310891.54271544689108
2081614.84989333386971.1501066661303
2091113.5475210272528-2.54752102725284
2101513.92417721380331.07582278619673
2111214.1753816464544-2.17538164645442
2121215.6883077893975-3.68830778939753
2131514.09950263901920.900497360980815
2141512.06719267626822.93280732373177
2151614.48700152925181.51299847074822
2161413.03059344594540.969406554054561
2171714.57212859276482.42787140723524
2181413.8792322664080.120767733591951
2191311.8737260813111.12627391868899
2201515.087549793977-0.0875497939769591
2211314.5770127002136-1.57701270021358
2221413.99464097369080.0053590263092174
2231514.19797364513460.802026354865392
2241213.039494366232-1.03949436623199
2251312.56673983965890.433260160341059
226811.6951354167233-3.69513541672332
2271413.66064136571310.339358634286859
2281412.91383981710811.08616018289194
2291112.166321626068-1.16632162606804
2301212.8182182048195-0.81821820481955
2311311.19127599688971.80872400311032
2321013.1366805948245-3.13668059482447
2331611.31433517494254.6856648250575
2341815.73040732682792.26959267317212
2351313.7135684147306-0.713568414730565
2361113.2122088681183-2.21220886811834
237410.9165827014858-6.91658270148581
2381314.0971838894582-1.09718388945817
2391614.14151468531941.8584853146806
2401011.5906760659384-1.59067606593836
2411212.1730026807329-0.173002680732853
2421213.3478370561178-1.34783705611779
243108.8118266754651.188173324535
2441310.989824356332.01017564367
2451513.51422890906581.4857710909342
2461211.81345163629220.186548363707805
2471412.70373321441011.29626678558989
2481012.3306976778834-2.33069767788343
2491210.63808867440111.36191132559894
2501211.55272899351180.447271006488222
2511111.7356777720557-0.735677772055743
2521011.5456092216354-1.54560922163543
2531211.25415942360160.745840576398441
2541612.67558244171313.32441755828694
2551213.1490026491782-1.14900264917825
2561413.66082220342720.339177796572829
2571614.22078518151111.77921481848893
2581411.49444767618162.50555232381843
2591314.0518737366042-1.05187373660423
26049.29789121761609-5.29789121761609
2611513.55737498891741.44262501108259
2621114.7763139185647-3.77631391856475
2631111.1527836332774-0.152783633277424
2641412.6426960851831.35730391481695

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 16.1022982210197 & -3.10229822101972 \tabularnewline
2 & 16 & 15.754491445859 & 0.245508554141014 \tabularnewline
3 & 19 & 17.0517125772831 & 1.94828742271692 \tabularnewline
4 & 15 & 12.1554580839931 & 2.84454191600689 \tabularnewline
5 & 14 & 16.4318778324043 & -2.43187783240426 \tabularnewline
6 & 13 & 14.8691295709112 & -1.86912957091122 \tabularnewline
7 & 19 & 15.2892630285488 & 3.71073697145122 \tabularnewline
8 & 15 & 17.0984636628673 & -2.09846366286726 \tabularnewline
9 & 14 & 16.0620688662447 & -2.06206886624467 \tabularnewline
10 & 15 & 14.4567921968538 & 0.543207803146187 \tabularnewline
11 & 16 & 14.9908621102773 & 1.00913788972271 \tabularnewline
12 & 16 & 16.1770052175893 & -0.177005217589299 \tabularnewline
13 & 16 & 15.5215035804684 & 0.478496419531648 \tabularnewline
14 & 16 & 15.4956157166457 & 0.504384283354324 \tabularnewline
15 & 17 & 18.0065120508452 & -1.0065120508452 \tabularnewline
16 & 15 & 15.4716004383729 & -0.471600438372882 \tabularnewline
17 & 15 & 14.6159706821155 & 0.384029317884485 \tabularnewline
18 & 20 & 16.4282236996433 & 3.57177630035666 \tabularnewline
19 & 18 & 15.479015093591 & 2.52098490640904 \tabularnewline
20 & 16 & 15.5557893935874 & 0.444210606412555 \tabularnewline
21 & 16 & 15.3650432654783 & 0.634956734521665 \tabularnewline
22 & 16 & 15.144145878139 & 0.855854121861016 \tabularnewline
23 & 19 & 16.4824869152471 & 2.51751308475295 \tabularnewline
24 & 16 & 15.0855184907825 & 0.914481509217452 \tabularnewline
25 & 17 & 16.1730205602678 & 0.826979439732198 \tabularnewline
26 & 17 & 16.2695071877283 & 0.730492812271699 \tabularnewline
27 & 16 & 14.9977946676347 & 1.00220533236535 \tabularnewline
28 & 15 & 16.760323977679 & -1.76032397767898 \tabularnewline
29 & 16 & 15.7555008219877 & 0.244499178012286 \tabularnewline
30 & 14 & 14.181416577811 & -0.181416577811048 \tabularnewline
31 & 15 & 15.7546834756412 & -0.754683475641216 \tabularnewline
32 & 12 & 12.8348155240329 & -0.83481552403293 \tabularnewline
33 & 14 & 14.8118391627312 & -0.81183916273115 \tabularnewline
34 & 16 & 15.9368953882806 & 0.063104611719357 \tabularnewline
35 & 14 & 15.5703707644626 & -1.57037076446263 \tabularnewline
36 & 10 & 13.005541434452 & -3.005541434452 \tabularnewline
37 & 10 & 13.0747086953106 & -3.07470869531064 \tabularnewline
38 & 14 & 15.7548997678586 & -1.75489976785859 \tabularnewline
39 & 16 & 14.5567994467754 & 1.44320055322457 \tabularnewline
40 & 16 & 14.491506556545 & 1.508493443455 \tabularnewline
41 & 16 & 14.7229795511616 & 1.27702044883837 \tabularnewline
42 & 14 & 15.7500199860774 & -1.75001998607735 \tabularnewline
43 & 20 & 17.4649787611873 & 2.53502123881265 \tabularnewline
44 & 14 & 14.1623540255355 & -0.162354025535507 \tabularnewline
45 & 14 & 14.4650019090832 & -0.465001909083171 \tabularnewline
46 & 11 & 15.5278918457463 & -4.52789184574632 \tabularnewline
47 & 14 & 16.537742048153 & -2.53774204815302 \tabularnewline
48 & 15 & 15.1382184624629 & -0.13821846246294 \tabularnewline
49 & 16 & 15.5081665290858 & 0.491833470914169 \tabularnewline
50 & 14 & 15.6508961989038 & -1.65089619890381 \tabularnewline
51 & 16 & 17.0132875529785 & -1.01328755297849 \tabularnewline
52 & 14 & 14.1613795638325 & -0.161379563832531 \tabularnewline
53 & 12 & 15.0533666119315 & -3.05336661193155 \tabularnewline
54 & 16 & 15.8229890413259 & 0.177010958674083 \tabularnewline
55 & 9 & 11.3977910266151 & -2.39779102661507 \tabularnewline
56 & 14 & 12.3852884808414 & 1.61471151915857 \tabularnewline
57 & 16 & 15.8661838703893 & 0.133816129610749 \tabularnewline
58 & 16 & 15.4829939565307 & 0.517006043469343 \tabularnewline
59 & 15 & 15.1489452458437 & -0.148945245843684 \tabularnewline
60 & 16 & 14.218310603986 & 1.78168939601395 \tabularnewline
61 & 12 & 11.566077304562 & 0.433922695437972 \tabularnewline
62 & 16 & 15.695601652654 & 0.304398347346031 \tabularnewline
63 & 16 & 16.5680978968282 & -0.568097896828235 \tabularnewline
64 & 14 & 14.7144975746602 & -0.71449757466022 \tabularnewline
65 & 16 & 15.2919080166204 & 0.70809198337962 \tabularnewline
66 & 17 & 16.0481680519745 & 0.9518319480255 \tabularnewline
67 & 18 & 16.291930000009 & 1.708069999991 \tabularnewline
68 & 18 & 14.4768348393922 & 3.52316516060783 \tabularnewline
69 & 12 & 15.9112854601582 & -3.9112854601582 \tabularnewline
70 & 16 & 15.6552497247185 & 0.344750275281548 \tabularnewline
71 & 10 & 13.3387945042165 & -3.33879450421647 \tabularnewline
72 & 14 & 14.9127730431715 & -0.912773043171451 \tabularnewline
73 & 18 & 16.9677895861422 & 1.03221041385776 \tabularnewline
74 & 18 & 17.1886676253417 & 0.811332374658303 \tabularnewline
75 & 16 & 15.2649505766035 & 0.73504942339646 \tabularnewline
76 & 17 & 13.5121427306491 & 3.48785726935087 \tabularnewline
77 & 16 & 16.4136496754081 & -0.413649675408144 \tabularnewline
78 & 16 & 14.4885628517415 & 1.51143714825848 \tabularnewline
79 & 13 & 15.2105291692642 & -2.21052916926418 \tabularnewline
80 & 16 & 15.1210176116584 & 0.878982388341565 \tabularnewline
81 & 16 & 15.7127255054486 & 0.287274494551398 \tabularnewline
82 & 16 & 15.7122824705459 & 0.287717529454097 \tabularnewline
83 & 15 & 15.6839662612022 & -0.683966261202235 \tabularnewline
84 & 15 & 14.8778596098532 & 0.12214039014684 \tabularnewline
85 & 16 & 14.1625822832344 & 1.83741771676558 \tabularnewline
86 & 14 & 14.1848053547452 & -0.184805354745237 \tabularnewline
87 & 16 & 15.3629727492202 & 0.637027250779809 \tabularnewline
88 & 16 & 14.854683789533 & 1.14531621046697 \tabularnewline
89 & 15 & 14.523619730254 & 0.476380269745968 \tabularnewline
90 & 12 & 13.871340301249 & -1.871340301249 \tabularnewline
91 & 17 & 16.7460396281135 & 0.253960371886512 \tabularnewline
92 & 16 & 15.8347181377269 & 0.165281862273136 \tabularnewline
93 & 15 & 15.1102677566366 & -0.110267756636619 \tabularnewline
94 & 13 & 15.0707409807562 & -2.07074098075619 \tabularnewline
95 & 16 & 14.7984388525891 & 1.20156114741089 \tabularnewline
96 & 16 & 15.7699135286564 & 0.230086471343579 \tabularnewline
97 & 16 & 13.719607258186 & 2.28039274181401 \tabularnewline
98 & 16 & 15.8147243792642 & 0.185275620735792 \tabularnewline
99 & 14 & 14.4339411801958 & -0.433941180195834 \tabularnewline
100 & 16 & 17.0258101979206 & -1.02581019792061 \tabularnewline
101 & 16 & 14.6741968980677 & 1.32580310193225 \tabularnewline
102 & 20 & 17.4559352407525 & 2.54406475924747 \tabularnewline
103 & 15 & 14.1818457214788 & 0.818154278521223 \tabularnewline
104 & 16 & 15.0003028518371 & 0.999697148162855 \tabularnewline
105 & 13 & 14.8675061755119 & -1.86750617551193 \tabularnewline
106 & 17 & 15.688287603418 & 1.31171239658197 \tabularnewline
107 & 16 & 15.722850378802 & 0.277149621197993 \tabularnewline
108 & 16 & 14.3491544203633 & 1.6508455796367 \tabularnewline
109 & 12 & 12.275456137583 & -0.275456137582957 \tabularnewline
110 & 16 & 15.2862749523836 & 0.713725047616351 \tabularnewline
111 & 16 & 16.0176513153709 & -0.0176513153709174 \tabularnewline
112 & 17 & 15.0267000494355 & 1.97329995056449 \tabularnewline
113 & 13 & 14.5664542163355 & -1.56645421633551 \tabularnewline
114 & 12 & 14.5701172401542 & -2.57011724015419 \tabularnewline
115 & 18 & 16.1521391092508 & 1.84786089074916 \tabularnewline
116 & 14 & 15.8505123074627 & -1.85051230746266 \tabularnewline
117 & 14 & 13.1495620020431 & 0.850437997956938 \tabularnewline
118 & 13 & 14.7823871743341 & -1.78238717433406 \tabularnewline
119 & 16 & 15.5374491098906 & 0.462550890109423 \tabularnewline
120 & 13 & 14.416850974949 & -1.41685097494897 \tabularnewline
121 & 16 & 15.3911674686073 & 0.608832531392733 \tabularnewline
122 & 13 & 15.839724797741 & -2.83972479774098 \tabularnewline
123 & 16 & 16.8306547434266 & -0.830654743426562 \tabularnewline
124 & 15 & 15.8273961971164 & -0.827396197116446 \tabularnewline
125 & 16 & 16.8053227042767 & -0.805322704276728 \tabularnewline
126 & 15 & 14.6649650351164 & 0.335034964883577 \tabularnewline
127 & 17 & 15.5277908137443 & 1.47220918625569 \tabularnewline
128 & 15 & 13.9616616580418 & 1.03833834195822 \tabularnewline
129 & 12 & 14.6840500753593 & -2.68405007535926 \tabularnewline
130 & 16 & 13.9649372104061 & 2.03506278959389 \tabularnewline
131 & 10 & 13.7296991647035 & -3.72969916470354 \tabularnewline
132 & 16 & 13.4901531526812 & 2.50984684731883 \tabularnewline
133 & 12 & 14.1462272767885 & -2.14622727678853 \tabularnewline
134 & 14 & 15.5237533235708 & -1.52375332357078 \tabularnewline
135 & 15 & 15.0605941760137 & -0.0605941760136943 \tabularnewline
136 & 13 & 12.1096554606152 & 0.890344539384808 \tabularnewline
137 & 15 & 14.4356748026804 & 0.564325197319618 \tabularnewline
138 & 11 & 13.4342499906017 & -2.43424999060171 \tabularnewline
139 & 12 & 12.975933493865 & -0.97593349386503 \tabularnewline
140 & 11 & 13.3597071648791 & -2.35970716487914 \tabularnewline
141 & 16 & 12.8359245090749 & 3.16407549092506 \tabularnewline
142 & 15 & 13.657252825922 & 1.34274717407804 \tabularnewline
143 & 17 & 16.8239462207622 & 0.17605377923783 \tabularnewline
144 & 16 & 14.1434432664305 & 1.85655673356948 \tabularnewline
145 & 10 & 13.2656605799341 & -3.26566057993405 \tabularnewline
146 & 18 & 15.4752937985422 & 2.52470620145776 \tabularnewline
147 & 13 & 14.9006435559371 & -1.90064355593709 \tabularnewline
148 & 16 & 14.8275040139554 & 1.1724959860446 \tabularnewline
149 & 13 & 12.8024541407533 & 0.197545859246742 \tabularnewline
150 & 10 & 12.8872795704569 & -2.88727957045692 \tabularnewline
151 & 15 & 15.9276356858023 & -0.927635685802293 \tabularnewline
152 & 16 & 13.8757095036435 & 2.12429049635646 \tabularnewline
153 & 16 & 11.8529345956268 & 4.14706540437316 \tabularnewline
154 & 14 & 12.3880193199151 & 1.61198068008492 \tabularnewline
155 & 10 & 12.4090361127589 & -2.40903611275887 \tabularnewline
156 & 17 & 16.4250734896923 & 0.574926510307681 \tabularnewline
157 & 13 & 11.6850863414094 & 1.31491365859057 \tabularnewline
158 & 15 & 13.8135234403089 & 1.18647655969106 \tabularnewline
159 & 16 & 14.540047010007 & 1.45995298999296 \tabularnewline
160 & 12 & 12.7472156095952 & -0.747215609595171 \tabularnewline
161 & 13 & 12.599585420271 & 0.400414579728982 \tabularnewline
162 & 13 & 12.60733341585 & 0.392666584149958 \tabularnewline
163 & 12 & 12.4465137428269 & -0.44651374282687 \tabularnewline
164 & 17 & 16.2355495679263 & 0.764450432073746 \tabularnewline
165 & 15 & 13.6996832333109 & 1.30031676668912 \tabularnewline
166 & 10 & 11.6136876844136 & -1.61368768441355 \tabularnewline
167 & 14 & 14.32787037191 & -0.327870371910013 \tabularnewline
168 & 11 & 14.2106862511466 & -3.21068625114663 \tabularnewline
169 & 13 & 14.7978730780644 & -1.7978730780644 \tabularnewline
170 & 16 & 14.4732850859102 & 1.52671491408983 \tabularnewline
171 & 12 & 10.4796421173843 & 1.52035788261573 \tabularnewline
172 & 16 & 15.3338740476203 & 0.666125952379726 \tabularnewline
173 & 12 & 13.8661216503701 & -1.86612165037008 \tabularnewline
174 & 9 & 11.3520658851189 & -2.35206588511894 \tabularnewline
175 & 12 & 14.9038825751131 & -2.90388257511308 \tabularnewline
176 & 15 & 14.5533998439333 & 0.446600156066671 \tabularnewline
177 & 12 & 12.2615035985194 & -0.261503598519359 \tabularnewline
178 & 12 & 12.6794441470007 & -0.67944414700072 \tabularnewline
179 & 14 & 13.7758576087759 & 0.224142391224061 \tabularnewline
180 & 12 & 13.3751911004819 & -1.37519110048189 \tabularnewline
181 & 16 & 14.987782175698 & 1.01221782430197 \tabularnewline
182 & 11 & 11.4391784414346 & -0.439178441434581 \tabularnewline
183 & 19 & 16.6527802643649 & 2.34721973563512 \tabularnewline
184 & 15 & 15.1309558411913 & -0.130955841191348 \tabularnewline
185 & 8 & 14.5671696852632 & -6.5671696852632 \tabularnewline
186 & 16 & 14.7673080225747 & 1.23269197742529 \tabularnewline
187 & 17 & 14.4466779452211 & 2.5533220547789 \tabularnewline
188 & 12 & 12.3914638757077 & -0.391463875707659 \tabularnewline
189 & 11 & 11.4687344908835 & -0.468734490883497 \tabularnewline
190 & 11 & 10.419312143855 & 0.580687856145011 \tabularnewline
191 & 14 & 14.7132415544436 & -0.713241554443631 \tabularnewline
192 & 16 & 15.4179494281746 & 0.58205057182538 \tabularnewline
193 & 12 & 9.7305189923556 & 2.2694810076444 \tabularnewline
194 & 16 & 14.005043145604 & 1.99495685439604 \tabularnewline
195 & 13 & 13.6285705973993 & -0.62857059739933 \tabularnewline
196 & 15 & 14.9617223713724 & 0.0382776286276256 \tabularnewline
197 & 16 & 12.9335254605675 & 3.06647453943252 \tabularnewline
198 & 16 & 15.0029292095033 & 0.997070790496686 \tabularnewline
199 & 14 & 12.4290193785421 & 1.57098062145789 \tabularnewline
200 & 16 & 14.5234359971224 & 1.47656400287756 \tabularnewline
201 & 16 & 13.9790867071796 & 2.02091329282044 \tabularnewline
202 & 14 & 13.3290512771168 & 0.670948722883167 \tabularnewline
203 & 11 & 13.405240124026 & -2.405240124026 \tabularnewline
204 & 12 & 14.4275103508537 & -2.42751035085371 \tabularnewline
205 & 15 & 12.6959007664366 & 2.30409923356338 \tabularnewline
206 & 15 & 14.420995709824 & 0.579004290176027 \tabularnewline
207 & 16 & 14.4572845531089 & 1.54271544689108 \tabularnewline
208 & 16 & 14.8498933338697 & 1.1501066661303 \tabularnewline
209 & 11 & 13.5475210272528 & -2.54752102725284 \tabularnewline
210 & 15 & 13.9241772138033 & 1.07582278619673 \tabularnewline
211 & 12 & 14.1753816464544 & -2.17538164645442 \tabularnewline
212 & 12 & 15.6883077893975 & -3.68830778939753 \tabularnewline
213 & 15 & 14.0995026390192 & 0.900497360980815 \tabularnewline
214 & 15 & 12.0671926762682 & 2.93280732373177 \tabularnewline
215 & 16 & 14.4870015292518 & 1.51299847074822 \tabularnewline
216 & 14 & 13.0305934459454 & 0.969406554054561 \tabularnewline
217 & 17 & 14.5721285927648 & 2.42787140723524 \tabularnewline
218 & 14 & 13.879232266408 & 0.120767733591951 \tabularnewline
219 & 13 & 11.873726081311 & 1.12627391868899 \tabularnewline
220 & 15 & 15.087549793977 & -0.0875497939769591 \tabularnewline
221 & 13 & 14.5770127002136 & -1.57701270021358 \tabularnewline
222 & 14 & 13.9946409736908 & 0.0053590263092174 \tabularnewline
223 & 15 & 14.1979736451346 & 0.802026354865392 \tabularnewline
224 & 12 & 13.039494366232 & -1.03949436623199 \tabularnewline
225 & 13 & 12.5667398396589 & 0.433260160341059 \tabularnewline
226 & 8 & 11.6951354167233 & -3.69513541672332 \tabularnewline
227 & 14 & 13.6606413657131 & 0.339358634286859 \tabularnewline
228 & 14 & 12.9138398171081 & 1.08616018289194 \tabularnewline
229 & 11 & 12.166321626068 & -1.16632162606804 \tabularnewline
230 & 12 & 12.8182182048195 & -0.81821820481955 \tabularnewline
231 & 13 & 11.1912759968897 & 1.80872400311032 \tabularnewline
232 & 10 & 13.1366805948245 & -3.13668059482447 \tabularnewline
233 & 16 & 11.3143351749425 & 4.6856648250575 \tabularnewline
234 & 18 & 15.7304073268279 & 2.26959267317212 \tabularnewline
235 & 13 & 13.7135684147306 & -0.713568414730565 \tabularnewline
236 & 11 & 13.2122088681183 & -2.21220886811834 \tabularnewline
237 & 4 & 10.9165827014858 & -6.91658270148581 \tabularnewline
238 & 13 & 14.0971838894582 & -1.09718388945817 \tabularnewline
239 & 16 & 14.1415146853194 & 1.8584853146806 \tabularnewline
240 & 10 & 11.5906760659384 & -1.59067606593836 \tabularnewline
241 & 12 & 12.1730026807329 & -0.173002680732853 \tabularnewline
242 & 12 & 13.3478370561178 & -1.34783705611779 \tabularnewline
243 & 10 & 8.811826675465 & 1.188173324535 \tabularnewline
244 & 13 & 10.98982435633 & 2.01017564367 \tabularnewline
245 & 15 & 13.5142289090658 & 1.4857710909342 \tabularnewline
246 & 12 & 11.8134516362922 & 0.186548363707805 \tabularnewline
247 & 14 & 12.7037332144101 & 1.29626678558989 \tabularnewline
248 & 10 & 12.3306976778834 & -2.33069767788343 \tabularnewline
249 & 12 & 10.6380886744011 & 1.36191132559894 \tabularnewline
250 & 12 & 11.5527289935118 & 0.447271006488222 \tabularnewline
251 & 11 & 11.7356777720557 & -0.735677772055743 \tabularnewline
252 & 10 & 11.5456092216354 & -1.54560922163543 \tabularnewline
253 & 12 & 11.2541594236016 & 0.745840576398441 \tabularnewline
254 & 16 & 12.6755824417131 & 3.32441755828694 \tabularnewline
255 & 12 & 13.1490026491782 & -1.14900264917825 \tabularnewline
256 & 14 & 13.6608222034272 & 0.339177796572829 \tabularnewline
257 & 16 & 14.2207851815111 & 1.77921481848893 \tabularnewline
258 & 14 & 11.4944476761816 & 2.50555232381843 \tabularnewline
259 & 13 & 14.0518737366042 & -1.05187373660423 \tabularnewline
260 & 4 & 9.29789121761609 & -5.29789121761609 \tabularnewline
261 & 15 & 13.5573749889174 & 1.44262501108259 \tabularnewline
262 & 11 & 14.7763139185647 & -3.77631391856475 \tabularnewline
263 & 11 & 11.1527836332774 & -0.152783633277424 \tabularnewline
264 & 14 & 12.642696085183 & 1.35730391481695 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185983&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]13[/C][C]16.1022982210197[/C][C]-3.10229822101972[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.754491445859[/C][C]0.245508554141014[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]17.0517125772831[/C][C]1.94828742271692[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]12.1554580839931[/C][C]2.84454191600689[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.4318778324043[/C][C]-2.43187783240426[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.8691295709112[/C][C]-1.86912957091122[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.2892630285488[/C][C]3.71073697145122[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]17.0984636628673[/C][C]-2.09846366286726[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]16.0620688662447[/C][C]-2.06206886624467[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.4567921968538[/C][C]0.543207803146187[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.9908621102773[/C][C]1.00913788972271[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.1770052175893[/C][C]-0.177005217589299[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.5215035804684[/C][C]0.478496419531648[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.4956157166457[/C][C]0.504384283354324[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]18.0065120508452[/C][C]-1.0065120508452[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.4716004383729[/C][C]-0.471600438372882[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.6159706821155[/C][C]0.384029317884485[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.4282236996433[/C][C]3.57177630035666[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.479015093591[/C][C]2.52098490640904[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.5557893935874[/C][C]0.444210606412555[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.3650432654783[/C][C]0.634956734521665[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]15.144145878139[/C][C]0.855854121861016[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.4824869152471[/C][C]2.51751308475295[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]15.0855184907825[/C][C]0.914481509217452[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]16.1730205602678[/C][C]0.826979439732198[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.2695071877283[/C][C]0.730492812271699[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.9977946676347[/C][C]1.00220533236535[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.760323977679[/C][C]-1.76032397767898[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.7555008219877[/C][C]0.244499178012286[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.181416577811[/C][C]-0.181416577811048[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.7546834756412[/C][C]-0.754683475641216[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.8348155240329[/C][C]-0.83481552403293[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.8118391627312[/C][C]-0.81183916273115[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.9368953882806[/C][C]0.063104611719357[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.5703707644626[/C][C]-1.57037076446263[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]13.005541434452[/C][C]-3.005541434452[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]13.0747086953106[/C][C]-3.07470869531064[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.7548997678586[/C][C]-1.75489976785859[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.5567994467754[/C][C]1.44320055322457[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.491506556545[/C][C]1.508493443455[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.7229795511616[/C][C]1.27702044883837[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.7500199860774[/C][C]-1.75001998607735[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.4649787611873[/C][C]2.53502123881265[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.1623540255355[/C][C]-0.162354025535507[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.4650019090832[/C][C]-0.465001909083171[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.5278918457463[/C][C]-4.52789184574632[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.537742048153[/C][C]-2.53774204815302[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.1382184624629[/C][C]-0.13821846246294[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.5081665290858[/C][C]0.491833470914169[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.6508961989038[/C][C]-1.65089619890381[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]17.0132875529785[/C][C]-1.01328755297849[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.1613795638325[/C][C]-0.161379563832531[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]15.0533666119315[/C][C]-3.05336661193155[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.8229890413259[/C][C]0.177010958674083[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]11.3977910266151[/C][C]-2.39779102661507[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.3852884808414[/C][C]1.61471151915857[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.8661838703893[/C][C]0.133816129610749[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.4829939565307[/C][C]0.517006043469343[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]15.1489452458437[/C][C]-0.148945245843684[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.218310603986[/C][C]1.78168939601395[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.566077304562[/C][C]0.433922695437972[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.695601652654[/C][C]0.304398347346031[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.5680978968282[/C][C]-0.568097896828235[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.7144975746602[/C][C]-0.71449757466022[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.2919080166204[/C][C]0.70809198337962[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]16.0481680519745[/C][C]0.9518319480255[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.291930000009[/C][C]1.708069999991[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.4768348393922[/C][C]3.52316516060783[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.9112854601582[/C][C]-3.9112854601582[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.6552497247185[/C][C]0.344750275281548[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.3387945042165[/C][C]-3.33879450421647[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.9127730431715[/C][C]-0.912773043171451[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.9677895861422[/C][C]1.03221041385776[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.1886676253417[/C][C]0.811332374658303[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.2649505766035[/C][C]0.73504942339646[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.5121427306491[/C][C]3.48785726935087[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.4136496754081[/C][C]-0.413649675408144[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.4885628517415[/C][C]1.51143714825848[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]15.2105291692642[/C][C]-2.21052916926418[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.1210176116584[/C][C]0.878982388341565[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.7127255054486[/C][C]0.287274494551398[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.7122824705459[/C][C]0.287717529454097[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.6839662612022[/C][C]-0.683966261202235[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.8778596098532[/C][C]0.12214039014684[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]14.1625822832344[/C][C]1.83741771676558[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.1848053547452[/C][C]-0.184805354745237[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.3629727492202[/C][C]0.637027250779809[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.854683789533[/C][C]1.14531621046697[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.523619730254[/C][C]0.476380269745968[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.871340301249[/C][C]-1.871340301249[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.7460396281135[/C][C]0.253960371886512[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.8347181377269[/C][C]0.165281862273136[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.1102677566366[/C][C]-0.110267756636619[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]15.0707409807562[/C][C]-2.07074098075619[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.7984388525891[/C][C]1.20156114741089[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.7699135286564[/C][C]0.230086471343579[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.719607258186[/C][C]2.28039274181401[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.8147243792642[/C][C]0.185275620735792[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.4339411801958[/C][C]-0.433941180195834[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.0258101979206[/C][C]-1.02581019792061[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.6741968980677[/C][C]1.32580310193225[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.4559352407525[/C][C]2.54406475924747[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.1818457214788[/C][C]0.818154278521223[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]15.0003028518371[/C][C]0.999697148162855[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.8675061755119[/C][C]-1.86750617551193[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.688287603418[/C][C]1.31171239658197[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.722850378802[/C][C]0.277149621197993[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.3491544203633[/C][C]1.6508455796367[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.275456137583[/C][C]-0.275456137582957[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.2862749523836[/C][C]0.713725047616351[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]16.0176513153709[/C][C]-0.0176513153709174[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]15.0267000494355[/C][C]1.97329995056449[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.5664542163355[/C][C]-1.56645421633551[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.5701172401542[/C][C]-2.57011724015419[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.1521391092508[/C][C]1.84786089074916[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.8505123074627[/C][C]-1.85051230746266[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.1495620020431[/C][C]0.850437997956938[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.7823871743341[/C][C]-1.78238717433406[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.5374491098906[/C][C]0.462550890109423[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.416850974949[/C][C]-1.41685097494897[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.3911674686073[/C][C]0.608832531392733[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.839724797741[/C][C]-2.83972479774098[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]16.8306547434266[/C][C]-0.830654743426562[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.8273961971164[/C][C]-0.827396197116446[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.8053227042767[/C][C]-0.805322704276728[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.6649650351164[/C][C]0.335034964883577[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.5277908137443[/C][C]1.47220918625569[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]13.9616616580418[/C][C]1.03833834195822[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.6840500753593[/C][C]-2.68405007535926[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.9649372104061[/C][C]2.03506278959389[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.7296991647035[/C][C]-3.72969916470354[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4901531526812[/C][C]2.50984684731883[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.1462272767885[/C][C]-2.14622727678853[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.5237533235708[/C][C]-1.52375332357078[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.0605941760137[/C][C]-0.0605941760136943[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]12.1096554606152[/C][C]0.890344539384808[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.4356748026804[/C][C]0.564325197319618[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.4342499906017[/C][C]-2.43424999060171[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]12.975933493865[/C][C]-0.97593349386503[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.3597071648791[/C][C]-2.35970716487914[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8359245090749[/C][C]3.16407549092506[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.657252825922[/C][C]1.34274717407804[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]16.8239462207622[/C][C]0.17605377923783[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.1434432664305[/C][C]1.85655673356948[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.2656605799341[/C][C]-3.26566057993405[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.4752937985422[/C][C]2.52470620145776[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]14.9006435559371[/C][C]-1.90064355593709[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.8275040139554[/C][C]1.1724959860446[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.8024541407533[/C][C]0.197545859246742[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.8872795704569[/C][C]-2.88727957045692[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]15.9276356858023[/C][C]-0.927635685802293[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.8757095036435[/C][C]2.12429049635646[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.8529345956268[/C][C]4.14706540437316[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.3880193199151[/C][C]1.61198068008492[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.4090361127589[/C][C]-2.40903611275887[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.4250734896923[/C][C]0.574926510307681[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.6850863414094[/C][C]1.31491365859057[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]13.8135234403089[/C][C]1.18647655969106[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.540047010007[/C][C]1.45995298999296[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.7472156095952[/C][C]-0.747215609595171[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.599585420271[/C][C]0.400414579728982[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.60733341585[/C][C]0.392666584149958[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.4465137428269[/C][C]-0.44651374282687[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.2355495679263[/C][C]0.764450432073746[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.6996832333109[/C][C]1.30031676668912[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.6136876844136[/C][C]-1.61368768441355[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.32787037191[/C][C]-0.327870371910013[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.2106862511466[/C][C]-3.21068625114663[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.7978730780644[/C][C]-1.7978730780644[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.4732850859102[/C][C]1.52671491408983[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.4796421173843[/C][C]1.52035788261573[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.3338740476203[/C][C]0.666125952379726[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.8661216503701[/C][C]-1.86612165037008[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.3520658851189[/C][C]-2.35206588511894[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]14.9038825751131[/C][C]-2.90388257511308[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.5533998439333[/C][C]0.446600156066671[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.2615035985194[/C][C]-0.261503598519359[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.6794441470007[/C][C]-0.67944414700072[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.7758576087759[/C][C]0.224142391224061[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.3751911004819[/C][C]-1.37519110048189[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]14.987782175698[/C][C]1.01221782430197[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.4391784414346[/C][C]-0.439178441434581[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]16.6527802643649[/C][C]2.34721973563512[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.1309558411913[/C][C]-0.130955841191348[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.5671696852632[/C][C]-6.5671696852632[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.7673080225747[/C][C]1.23269197742529[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.4466779452211[/C][C]2.5533220547789[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.3914638757077[/C][C]-0.391463875707659[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.4687344908835[/C][C]-0.468734490883497[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.419312143855[/C][C]0.580687856145011[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14.7132415544436[/C][C]-0.713241554443631[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.4179494281746[/C][C]0.58205057182538[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.7305189923556[/C][C]2.2694810076444[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.005043145604[/C][C]1.99495685439604[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.6285705973993[/C][C]-0.62857059739933[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]14.9617223713724[/C][C]0.0382776286276256[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]12.9335254605675[/C][C]3.06647453943252[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.0029292095033[/C][C]0.997070790496686[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4290193785421[/C][C]1.57098062145789[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.5234359971224[/C][C]1.47656400287756[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]13.9790867071796[/C][C]2.02091329282044[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.3290512771168[/C][C]0.670948722883167[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.405240124026[/C][C]-2.405240124026[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.4275103508537[/C][C]-2.42751035085371[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.6959007664366[/C][C]2.30409923356338[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.420995709824[/C][C]0.579004290176027[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.4572845531089[/C][C]1.54271544689108[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]14.8498933338697[/C][C]1.1501066661303[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.5475210272528[/C][C]-2.54752102725284[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]13.9241772138033[/C][C]1.07582278619673[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.1753816464544[/C][C]-2.17538164645442[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]15.6883077893975[/C][C]-3.68830778939753[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.0995026390192[/C][C]0.900497360980815[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.0671926762682[/C][C]2.93280732373177[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.4870015292518[/C][C]1.51299847074822[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.0305934459454[/C][C]0.969406554054561[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.5721285927648[/C][C]2.42787140723524[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.879232266408[/C][C]0.120767733591951[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.873726081311[/C][C]1.12627391868899[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.087549793977[/C][C]-0.0875497939769591[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]14.5770127002136[/C][C]-1.57701270021358[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]13.9946409736908[/C][C]0.0053590263092174[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.1979736451346[/C][C]0.802026354865392[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.039494366232[/C][C]-1.03949436623199[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.5667398396589[/C][C]0.433260160341059[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.6951354167233[/C][C]-3.69513541672332[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]13.6606413657131[/C][C]0.339358634286859[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]12.9138398171081[/C][C]1.08616018289194[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.166321626068[/C][C]-1.16632162606804[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]12.8182182048195[/C][C]-0.81821820481955[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.1912759968897[/C][C]1.80872400311032[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.1366805948245[/C][C]-3.13668059482447[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.3143351749425[/C][C]4.6856648250575[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]15.7304073268279[/C][C]2.26959267317212[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]13.7135684147306[/C][C]-0.713568414730565[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.2122088681183[/C][C]-2.21220886811834[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]10.9165827014858[/C][C]-6.91658270148581[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.0971838894582[/C][C]-1.09718388945817[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.1415146853194[/C][C]1.8584853146806[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.5906760659384[/C][C]-1.59067606593836[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.1730026807329[/C][C]-0.173002680732853[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.3478370561178[/C][C]-1.34783705611779[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.811826675465[/C][C]1.188173324535[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]10.98982435633[/C][C]2.01017564367[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.5142289090658[/C][C]1.4857710909342[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]11.8134516362922[/C][C]0.186548363707805[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]12.7037332144101[/C][C]1.29626678558989[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.3306976778834[/C][C]-2.33069767788343[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.6380886744011[/C][C]1.36191132559894[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.5527289935118[/C][C]0.447271006488222[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.7356777720557[/C][C]-0.735677772055743[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.5456092216354[/C][C]-1.54560922163543[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.2541594236016[/C][C]0.745840576398441[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]12.6755824417131[/C][C]3.32441755828694[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.1490026491782[/C][C]-1.14900264917825[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.6608222034272[/C][C]0.339177796572829[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.2207851815111[/C][C]1.77921481848893[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.4944476761816[/C][C]2.50555232381843[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.0518737366042[/C][C]-1.05187373660423[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.29789121761609[/C][C]-5.29789121761609[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.5573749889174[/C][C]1.44262501108259[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]14.7763139185647[/C][C]-3.77631391856475[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.1527836332774[/C][C]-0.152783633277424[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]12.642696085183[/C][C]1.35730391481695[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185983&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185983&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11316.1022982210197-3.10229822101972
21615.7544914458590.245508554141014
31917.05171257728311.94828742271692
41512.15545808399312.84454191600689
51416.4318778324043-2.43187783240426
61314.8691295709112-1.86912957091122
71915.28926302854883.71073697145122
81517.0984636628673-2.09846366286726
91416.0620688662447-2.06206886624467
101514.45679219685380.543207803146187
111614.99086211027731.00913788972271
121616.1770052175893-0.177005217589299
131615.52150358046840.478496419531648
141615.49561571664570.504384283354324
151718.0065120508452-1.0065120508452
161515.4716004383729-0.471600438372882
171514.61597068211550.384029317884485
182016.42822369964333.57177630035666
191815.4790150935912.52098490640904
201615.55578939358740.444210606412555
211615.36504326547830.634956734521665
221615.1441458781390.855854121861016
231916.48248691524712.51751308475295
241615.08551849078250.914481509217452
251716.17302056026780.826979439732198
261716.26950718772830.730492812271699
271614.99779466763471.00220533236535
281516.760323977679-1.76032397767898
291615.75550082198770.244499178012286
301414.181416577811-0.181416577811048
311515.7546834756412-0.754683475641216
321212.8348155240329-0.83481552403293
331414.8118391627312-0.81183916273115
341615.93689538828060.063104611719357
351415.5703707644626-1.57037076446263
361013.005541434452-3.005541434452
371013.0747086953106-3.07470869531064
381415.7548997678586-1.75489976785859
391614.55679944677541.44320055322457
401614.4915065565451.508493443455
411614.72297955116161.27702044883837
421415.7500199860774-1.75001998607735
432017.46497876118732.53502123881265
441414.1623540255355-0.162354025535507
451414.4650019090832-0.465001909083171
461115.5278918457463-4.52789184574632
471416.537742048153-2.53774204815302
481515.1382184624629-0.13821846246294
491615.50816652908580.491833470914169
501415.6508961989038-1.65089619890381
511617.0132875529785-1.01328755297849
521414.1613795638325-0.161379563832531
531215.0533666119315-3.05336661193155
541615.82298904132590.177010958674083
55911.3977910266151-2.39779102661507
561412.38528848084141.61471151915857
571615.86618387038930.133816129610749
581615.48299395653070.517006043469343
591515.1489452458437-0.148945245843684
601614.2183106039861.78168939601395
611211.5660773045620.433922695437972
621615.6956016526540.304398347346031
631616.5680978968282-0.568097896828235
641414.7144975746602-0.71449757466022
651615.29190801662040.70809198337962
661716.04816805197450.9518319480255
671816.2919300000091.708069999991
681814.47683483939223.52316516060783
691215.9112854601582-3.9112854601582
701615.65524972471850.344750275281548
711013.3387945042165-3.33879450421647
721414.9127730431715-0.912773043171451
731816.96778958614221.03221041385776
741817.18866762534170.811332374658303
751615.26495057660350.73504942339646
761713.51214273064913.48785726935087
771616.4136496754081-0.413649675408144
781614.48856285174151.51143714825848
791315.2105291692642-2.21052916926418
801615.12101761165840.878982388341565
811615.71272550544860.287274494551398
821615.71228247054590.287717529454097
831515.6839662612022-0.683966261202235
841514.87785960985320.12214039014684
851614.16258228323441.83741771676558
861414.1848053547452-0.184805354745237
871615.36297274922020.637027250779809
881614.8546837895331.14531621046697
891514.5236197302540.476380269745968
901213.871340301249-1.871340301249
911716.74603962811350.253960371886512
921615.83471813772690.165281862273136
931515.1102677566366-0.110267756636619
941315.0707409807562-2.07074098075619
951614.79843885258911.20156114741089
961615.76991352865640.230086471343579
971613.7196072581862.28039274181401
981615.81472437926420.185275620735792
991414.4339411801958-0.433941180195834
1001617.0258101979206-1.02581019792061
1011614.67419689806771.32580310193225
1022017.45593524075252.54406475924747
1031514.18184572147880.818154278521223
1041615.00030285183710.999697148162855
1051314.8675061755119-1.86750617551193
1061715.6882876034181.31171239658197
1071615.7228503788020.277149621197993
1081614.34915442036331.6508455796367
1091212.275456137583-0.275456137582957
1101615.28627495238360.713725047616351
1111616.0176513153709-0.0176513153709174
1121715.02670004943551.97329995056449
1131314.5664542163355-1.56645421633551
1141214.5701172401542-2.57011724015419
1151816.15213910925081.84786089074916
1161415.8505123074627-1.85051230746266
1171413.14956200204310.850437997956938
1181314.7823871743341-1.78238717433406
1191615.53744910989060.462550890109423
1201314.416850974949-1.41685097494897
1211615.39116746860730.608832531392733
1221315.839724797741-2.83972479774098
1231616.8306547434266-0.830654743426562
1241515.8273961971164-0.827396197116446
1251616.8053227042767-0.805322704276728
1261514.66496503511640.335034964883577
1271715.52779081374431.47220918625569
1281513.96166165804181.03833834195822
1291214.6840500753593-2.68405007535926
1301613.96493721040612.03506278959389
1311013.7296991647035-3.72969916470354
1321613.49015315268122.50984684731883
1331214.1462272767885-2.14622727678853
1341415.5237533235708-1.52375332357078
1351515.0605941760137-0.0605941760136943
1361312.10965546061520.890344539384808
1371514.43567480268040.564325197319618
1381113.4342499906017-2.43424999060171
1391212.975933493865-0.97593349386503
1401113.3597071648791-2.35970716487914
1411612.83592450907493.16407549092506
1421513.6572528259221.34274717407804
1431716.82394622076220.17605377923783
1441614.14344326643051.85655673356948
1451013.2656605799341-3.26566057993405
1461815.47529379854222.52470620145776
1471314.9006435559371-1.90064355593709
1481614.82750401395541.1724959860446
1491312.80245414075330.197545859246742
1501012.8872795704569-2.88727957045692
1511515.9276356858023-0.927635685802293
1521613.87570950364352.12429049635646
1531611.85293459562684.14706540437316
1541412.38801931991511.61198068008492
1551012.4090361127589-2.40903611275887
1561716.42507348969230.574926510307681
1571311.68508634140941.31491365859057
1581513.81352344030891.18647655969106
1591614.5400470100071.45995298999296
1601212.7472156095952-0.747215609595171
1611312.5995854202710.400414579728982
1621312.607333415850.392666584149958
1631212.4465137428269-0.44651374282687
1641716.23554956792630.764450432073746
1651513.69968323331091.30031676668912
1661011.6136876844136-1.61368768441355
1671414.32787037191-0.327870371910013
1681114.2106862511466-3.21068625114663
1691314.7978730780644-1.7978730780644
1701614.47328508591021.52671491408983
1711210.47964211738431.52035788261573
1721615.33387404762030.666125952379726
1731213.8661216503701-1.86612165037008
174911.3520658851189-2.35206588511894
1751214.9038825751131-2.90388257511308
1761514.55339984393330.446600156066671
1771212.2615035985194-0.261503598519359
1781212.6794441470007-0.67944414700072
1791413.77585760877590.224142391224061
1801213.3751911004819-1.37519110048189
1811614.9877821756981.01221782430197
1821111.4391784414346-0.439178441434581
1831916.65278026436492.34721973563512
1841515.1309558411913-0.130955841191348
185814.5671696852632-6.5671696852632
1861614.76730802257471.23269197742529
1871714.44667794522112.5533220547789
1881212.3914638757077-0.391463875707659
1891111.4687344908835-0.468734490883497
1901110.4193121438550.580687856145011
1911414.7132415544436-0.713241554443631
1921615.41794942817460.58205057182538
193129.73051899235562.2694810076444
1941614.0050431456041.99495685439604
1951313.6285705973993-0.62857059739933
1961514.96172237137240.0382776286276256
1971612.93352546056753.06647453943252
1981615.00292920950330.997070790496686
1991412.42901937854211.57098062145789
2001614.52343599712241.47656400287756
2011613.97908670717962.02091329282044
2021413.32905127711680.670948722883167
2031113.405240124026-2.405240124026
2041214.4275103508537-2.42751035085371
2051512.69590076643662.30409923356338
2061514.4209957098240.579004290176027
2071614.45728455310891.54271544689108
2081614.84989333386971.1501066661303
2091113.5475210272528-2.54752102725284
2101513.92417721380331.07582278619673
2111214.1753816464544-2.17538164645442
2121215.6883077893975-3.68830778939753
2131514.09950263901920.900497360980815
2141512.06719267626822.93280732373177
2151614.48700152925181.51299847074822
2161413.03059344594540.969406554054561
2171714.57212859276482.42787140723524
2181413.8792322664080.120767733591951
2191311.8737260813111.12627391868899
2201515.087549793977-0.0875497939769591
2211314.5770127002136-1.57701270021358
2221413.99464097369080.0053590263092174
2231514.19797364513460.802026354865392
2241213.039494366232-1.03949436623199
2251312.56673983965890.433260160341059
226811.6951354167233-3.69513541672332
2271413.66064136571310.339358634286859
2281412.91383981710811.08616018289194
2291112.166321626068-1.16632162606804
2301212.8182182048195-0.81821820481955
2311311.19127599688971.80872400311032
2321013.1366805948245-3.13668059482447
2331611.31433517494254.6856648250575
2341815.73040732682792.26959267317212
2351313.7135684147306-0.713568414730565
2361113.2122088681183-2.21220886811834
237410.9165827014858-6.91658270148581
2381314.0971838894582-1.09718388945817
2391614.14151468531941.8584853146806
2401011.5906760659384-1.59067606593836
2411212.1730026807329-0.173002680732853
2421213.3478370561178-1.34783705611779
243108.8118266754651.188173324535
2441310.989824356332.01017564367
2451513.51422890906581.4857710909342
2461211.81345163629220.186548363707805
2471412.70373321441011.29626678558989
2481012.3306976778834-2.33069767788343
2491210.63808867440111.36191132559894
2501211.55272899351180.447271006488222
2511111.7356777720557-0.735677772055743
2521011.5456092216354-1.54560922163543
2531211.25415942360160.745840576398441
2541612.67558244171313.32441755828694
2551213.1490026491782-1.14900264917825
2561413.66082220342720.339177796572829
2571614.22078518151111.77921481848893
2581411.49444767618162.50555232381843
2591314.0518737366042-1.05187373660423
26049.29789121761609-5.29789121761609
2611513.55737498891741.44262501108259
2621114.7763139185647-3.77631391856475
2631111.1527836332774-0.152783633277424
2641412.6426960851831.35730391481695







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.09490693367178270.1898138673435650.905093066328217
130.1688210524404690.3376421048809370.831178947559531
140.178863827940670.3577276558813410.82113617205933
150.1021082218164460.2042164436328930.897891778183554
160.07842819714433640.1568563942886730.921571802855664
170.08702376605979080.1740475321195820.912976233940209
180.2132234398370970.4264468796741940.786776560162903
190.1758104644518980.3516209289037950.824189535548102
200.1394060419652330.2788120839304660.860593958034767
210.1076168728677320.2152337457354630.892383127132269
220.1314003163079110.2628006326158210.868599683692089
230.229848580090410.459697160180820.77015141990959
240.345400678188320.6908013563766390.65459932181168
250.2821587565081750.5643175130163490.717841243491825
260.2373233122401470.4746466244802940.762676687759853
270.2278962457384570.4557924914769140.772103754261543
280.3384850522129770.6769701044259540.661514947787023
290.2893254811346310.5786509622692620.710674518865369
300.3978828599366230.7957657198732450.602117140063377
310.3568902574880350.713780514976070.643109742511965
320.329416582090550.65883316418110.67058341790945
330.3141214600600360.6282429201200720.685878539939964
340.2782628951098780.5565257902197550.721737104890122
350.2368206844126130.4736413688252260.763179315587387
360.3669047636406810.7338095272813620.633095236359319
370.3956217287057510.7912434574115020.604378271294249
380.37157667251540.7431533450308010.6284233274846
390.416207602576150.83241520515230.58379239742385
400.3965466505621470.7930933011242930.603453349437853
410.3577995707434310.7155991414868630.642200429256569
420.319486473803070.6389729476061410.68051352619693
430.3384091031573870.6768182063147750.661590896842613
440.291402618208390.5828052364167810.70859738179161
450.264493101647080.528986203294160.73550689835292
460.4416124751845530.8832249503691070.558387524815447
470.5322670026109670.9354659947780670.467732997389033
480.4892016963859960.9784033927719920.510798303614004
490.5136426551357230.9727146897285540.486357344864277
500.4866219481787860.9732438963575720.513378051821214
510.4415572589751860.8831145179503720.558442741024814
520.4004250108969730.8008500217939450.599574989103027
530.3998641474306660.7997282948613320.600135852569334
540.3580805641964730.7161611283929460.641919435803527
550.3460959966995090.6921919933990180.653904003300491
560.3433011269468690.6866022538937380.656698873053131
570.3042398889216210.6084797778432420.695760111078379
580.2857200862422750.571440172484550.714279913757725
590.255885142827490.5117702856549790.74411485717251
600.2763078016978720.5526156033957430.723692198302128
610.2529929042034120.5059858084068250.747007095796588
620.228275085332220.4565501706644410.77172491466778
630.199677701775130.3993554035502610.80032229822487
640.1720118990507720.3440237981015430.827988100949228
650.1517815382386840.3035630764773680.848218461761316
660.1430713872026180.2861427744052370.856928612797382
670.1390475535876250.2780951071752490.860952446412375
680.2692032311029030.5384064622058060.730796768897097
690.3644951757875050.7289903515750090.635504824212495
700.3340009024832860.6680018049665710.665999097516714
710.4431017811684230.8862035623368450.556898218831578
720.4083901990131820.8167803980263650.591609800986818
730.4088932175450150.8177864350900310.591106782454984
740.3971357235217690.7942714470435380.602864276478231
750.3600340565442360.7200681130884710.639965943455764
760.4257931817071380.8515863634142770.574206818292862
770.3880424411457730.7760848822915470.611957558854227
780.3620947587099960.7241895174199930.637905241290004
790.3767932495497760.7535864990995520.623206750450224
800.3431168503060020.6862337006120050.656883149693998
810.3145228214193750.629045642838750.685477178580625
820.2808624843347370.5617249686694740.719137515665263
830.2532822022560530.5065644045121060.746717797743947
840.223423532033940.446847064067880.77657646796606
850.2172941130128580.4345882260257150.782705886987142
860.1898215960811270.3796431921622530.810178403918873
870.1674870500495880.3349741000991770.832512949950412
880.1551269114241020.3102538228482030.844873088575898
890.1336367401632070.2672734803264140.866363259836793
900.1322699266580860.2645398533161710.867730073341914
910.1131565212513720.2263130425027450.886843478748628
920.09888473584626070.1977694716925210.901115264153739
930.0841070314242160.1682140628484320.915892968575784
940.087387903163340.174775806326680.91261209683666
950.07905597610140650.1581119522028130.920944023898594
960.06615681562295230.1323136312459050.933843184377048
970.07087573047600050.1417514609520010.929124269524
980.05887246776282060.1177449355256410.941127532237179
990.04884884085961710.09769768171923420.951151159140383
1000.04292117224369980.08584234448739970.9570788277563
1010.03757442967993540.07514885935987080.962425570320065
1020.04346502184713560.08693004369427120.956534978152864
1030.03663580215437720.07327160430875440.963364197845623
1040.03285284634801090.06570569269602180.967147153651989
1050.03913920191121280.07827840382242550.960860798088787
1060.03405157097239640.06810314194479280.965948429027604
1070.02765164508836610.05530329017673220.972348354911634
1080.02678027064873750.05356054129747490.973219729351263
1090.02175499515892960.04350999031785920.97824500484107
1100.01772690060187320.03545380120374640.982273099398127
1110.01405453909611810.02810907819223610.985945460903882
1120.01419518124251680.02839036248503350.985804818757483
1130.01288849216904410.02577698433808820.987111507830956
1140.01886063958014740.03772127916029490.981139360419853
1150.0177299769212730.03545995384254610.982270023078727
1160.01723449623989080.03446899247978170.982765503760109
1170.01416276390975150.0283255278195030.985837236090249
1180.01425322643443670.02850645286887330.985746773565563
1190.01148841265526150.0229768253105230.988511587344739
1200.01028505431584560.02057010863169110.989714945684154
1210.008261909746838570.01652381949367710.991738090253161
1220.01251857842882640.02503715685765290.987481421571174
1230.01044720142890080.02089440285780160.989552798571099
1240.008973745364233480.0179474907284670.991026254635767
1250.007295191777116460.01459038355423290.992704808222884
1260.005773670024639530.01154734004927910.99422632997536
1270.005258363128513180.01051672625702640.994741636871487
1280.004250609199450490.008501218398900980.995749390800549
1290.006006641470327730.01201328294065550.993993358529672
1300.006603665812144640.01320733162428930.993396334187855
1310.01373860168122820.02747720336245640.986261398318772
1320.01641982605893550.03283965211787090.983580173941065
1330.01760203972465740.03520407944931480.982397960275343
1340.01669508230170530.03339016460341050.983304917698295
1350.01334414796471280.02668829592942560.986655852035287
1360.01122251727385520.02244503454771040.988777482726145
1370.008916657321749270.01783331464349850.991083342678251
1380.01115054210354870.02230108420709740.988849457896451
1390.009557227639701090.01911445527940220.990442772360299
1400.01131238699459740.02262477398919490.988687613005403
1410.01795907823722150.0359181564744430.982040921762778
1420.0165488861252270.0330977722504540.983451113874773
1430.01330585372132480.02661170744264960.986694146278675
1440.01369886080338960.02739772160677930.98630113919661
1450.02457946585901780.04915893171803560.975420534140982
1460.02983593984356710.05967187968713430.970164060156433
1470.03131752201670240.06263504403340470.968682477983298
1480.02771179376523080.05542358753046160.972288206234769
1490.02255240723186070.04510481446372140.977447592768139
1500.03149661579808850.06299323159617710.968503384201912
1510.0265998969757280.0531997939514560.973400103024272
1520.02894597497460320.05789194994920640.971054025025397
1530.05853760298865580.1170752059773120.941462397011344
1540.05640498581459260.1128099716291850.943595014185407
1550.06460824369310670.1292164873862130.935391756306893
1560.05493705281748810.1098741056349760.945062947182512
1570.04901887120467130.09803774240934270.950981128795329
1580.04268954235422440.08537908470844880.957310457645776
1590.04132954873613580.08265909747227170.958670451263864
1600.0354669898625970.0709339797251940.964533010137403
1610.0289564655703490.05791293114069790.971043534429651
1620.02363570823402070.04727141646804140.976364291765979
1630.01930963884510070.03861927769020140.980690361154899
1640.01632910977000030.03265821954000060.98367089023
1650.01445008337874660.02890016675749320.985549916621253
1660.01494861176131710.02989722352263430.985051388238683
1670.01188421738242430.02376843476484850.988115782617576
1680.01751327832294780.03502655664589560.982486721677052
1690.01763400818190620.03526801636381250.982365991818094
1700.01673538826347340.03347077652694680.983264611736527
1710.01545666162761660.03091332325523320.984543338372383
1720.01247237287750020.02494474575500040.9875276271225
1730.0120882121093150.024176424218630.987911787890685
1740.01377482855148940.02754965710297880.986225171448511
1750.0179335058427580.0358670116855160.982066494157242
1760.0143782154817520.0287564309635040.985621784518248
1770.01135238021117960.02270476042235910.98864761978882
1780.009545562620591690.01909112524118340.990454437379408
1790.007389758045191480.0147795160903830.992610241954809
1800.006509052142836590.01301810428567320.993490947857163
1810.00531052029528310.01062104059056620.994689479704717
1820.004086686884734920.008173373769469840.995913313115265
1830.004424692917154670.008849385834309340.995575307082845
1840.003352022920341060.006704045840682130.996647977079659
1850.09163270237506730.1832654047501350.908367297624933
1860.08192793360271330.1638558672054270.918072066397287
1870.09042000229711070.1808400045942210.909579997702889
1880.07590051292008580.1518010258401720.924099487079914
1890.06774692269210660.1354938453842130.932253077307893
1900.0565897118898440.1131794237796880.943410288110156
1910.052365079923280.104730159846560.94763492007672
1920.04325736088569910.08651472177139820.956742639114301
1930.04437521881991710.08875043763983430.955624781180083
1940.04485920517831940.08971841035663870.955140794821681
1950.03879136012260830.07758272024521650.961208639877392
1960.03121425287124310.06242850574248620.968785747128757
1970.03941489334589140.07882978669178270.960585106654109
1980.03218361130267320.06436722260534650.967816388697327
1990.02896427162907880.05792854325815750.971035728370921
2000.02485692046963590.04971384093927180.975143079530364
2010.02324626684405330.04649253368810650.976753733155947
2020.01965012261955380.03930024523910760.980349877380446
2030.02580615996018440.05161231992036870.974193840039816
2040.03005587198241490.06011174396482980.969944128017585
2050.03147735367449860.06295470734899710.968522646325501
2060.02467345405028220.04934690810056440.975326545949718
2070.02361957126079230.04723914252158450.976380428739208
2080.01930971781874440.03861943563748870.980690282181256
2090.02153171270348120.04306342540696230.978468287296519
2100.01715999382600610.03431998765201220.982840006173994
2110.01972006081024880.03944012162049760.980279939189751
2120.03198601436106650.06397202872213290.968013985638933
2130.02490099880834780.04980199761669570.975099001191652
2140.03219963344204030.06439926688408060.96780036655796
2150.02732320563832830.05464641127665650.972676794361672
2160.02113757479784180.04227514959568370.978862425202158
2170.02322055161677570.04644110323355140.976779448383224
2180.01957973264799160.03915946529598310.980420267352008
2190.01819143350512490.03638286701024980.981808566494875
2200.01391046527472530.02782093054945060.986089534725275
2210.01158463563075670.02316927126151330.988415364369243
2220.008318636450755210.01663727290151040.991681363549245
2230.006380203789997460.01276040757999490.993619796210003
2240.004809065882655540.009618131765311080.995190934117344
2250.004093750450760220.008187500901520440.99590624954924
2260.009466810057665290.01893362011533060.990533189942335
2270.007417951092789390.01483590218557880.992582048907211
2280.005488961457264570.01097792291452910.994511038542735
2290.003925896582777710.007851793165555420.996074103417222
2300.002890463416874660.005780926833749330.997109536583125
2310.002606181890285140.005212363780570270.997393818109715
2320.006137343094016580.01227468618803320.993862656905983
2330.02476496745693710.04952993491387430.975235032543063
2340.03774775795470850.0754955159094170.962252242045291
2350.02723109893689870.05446219787379750.972768901063101
2360.02282544908181220.04565089816362450.977174550918188
2370.197370721984520.394741443969040.80262927801548
2380.1556675216785840.3113350433571670.844332478321416
2390.1296071410199340.2592142820398670.870392858980066
2400.1005441980234880.2010883960469760.899455801976512
2410.08840818112546270.1768163622509250.911591818874537
2420.1379384942689970.2758769885379940.862061505731003
2430.1129598284016440.2259196568032870.887040171598356
2440.1182937307244960.2365874614489910.881706269275504
2450.09681983447441890.1936396689488380.903180165525581
2460.0821740101718720.1643480203437440.917825989828128
2470.05305608321626040.1061121664325210.94694391678374
2480.04520287298809690.09040574597619380.954797127011903
2490.0404519036819730.0809038073639460.959548096318027
2500.1154964621938520.2309929243877030.884503537806148
2510.09470384115353980.189407682307080.90529615884646
2520.4314389998356860.8628779996713710.568561000164314

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.0949069336717827 & 0.189813867343565 & 0.905093066328217 \tabularnewline
13 & 0.168821052440469 & 0.337642104880937 & 0.831178947559531 \tabularnewline
14 & 0.17886382794067 & 0.357727655881341 & 0.82113617205933 \tabularnewline
15 & 0.102108221816446 & 0.204216443632893 & 0.897891778183554 \tabularnewline
16 & 0.0784281971443364 & 0.156856394288673 & 0.921571802855664 \tabularnewline
17 & 0.0870237660597908 & 0.174047532119582 & 0.912976233940209 \tabularnewline
18 & 0.213223439837097 & 0.426446879674194 & 0.786776560162903 \tabularnewline
19 & 0.175810464451898 & 0.351620928903795 & 0.824189535548102 \tabularnewline
20 & 0.139406041965233 & 0.278812083930466 & 0.860593958034767 \tabularnewline
21 & 0.107616872867732 & 0.215233745735463 & 0.892383127132269 \tabularnewline
22 & 0.131400316307911 & 0.262800632615821 & 0.868599683692089 \tabularnewline
23 & 0.22984858009041 & 0.45969716018082 & 0.77015141990959 \tabularnewline
24 & 0.34540067818832 & 0.690801356376639 & 0.65459932181168 \tabularnewline
25 & 0.282158756508175 & 0.564317513016349 & 0.717841243491825 \tabularnewline
26 & 0.237323312240147 & 0.474646624480294 & 0.762676687759853 \tabularnewline
27 & 0.227896245738457 & 0.455792491476914 & 0.772103754261543 \tabularnewline
28 & 0.338485052212977 & 0.676970104425954 & 0.661514947787023 \tabularnewline
29 & 0.289325481134631 & 0.578650962269262 & 0.710674518865369 \tabularnewline
30 & 0.397882859936623 & 0.795765719873245 & 0.602117140063377 \tabularnewline
31 & 0.356890257488035 & 0.71378051497607 & 0.643109742511965 \tabularnewline
32 & 0.32941658209055 & 0.6588331641811 & 0.67058341790945 \tabularnewline
33 & 0.314121460060036 & 0.628242920120072 & 0.685878539939964 \tabularnewline
34 & 0.278262895109878 & 0.556525790219755 & 0.721737104890122 \tabularnewline
35 & 0.236820684412613 & 0.473641368825226 & 0.763179315587387 \tabularnewline
36 & 0.366904763640681 & 0.733809527281362 & 0.633095236359319 \tabularnewline
37 & 0.395621728705751 & 0.791243457411502 & 0.604378271294249 \tabularnewline
38 & 0.3715766725154 & 0.743153345030801 & 0.6284233274846 \tabularnewline
39 & 0.41620760257615 & 0.8324152051523 & 0.58379239742385 \tabularnewline
40 & 0.396546650562147 & 0.793093301124293 & 0.603453349437853 \tabularnewline
41 & 0.357799570743431 & 0.715599141486863 & 0.642200429256569 \tabularnewline
42 & 0.31948647380307 & 0.638972947606141 & 0.68051352619693 \tabularnewline
43 & 0.338409103157387 & 0.676818206314775 & 0.661590896842613 \tabularnewline
44 & 0.29140261820839 & 0.582805236416781 & 0.70859738179161 \tabularnewline
45 & 0.26449310164708 & 0.52898620329416 & 0.73550689835292 \tabularnewline
46 & 0.441612475184553 & 0.883224950369107 & 0.558387524815447 \tabularnewline
47 & 0.532267002610967 & 0.935465994778067 & 0.467732997389033 \tabularnewline
48 & 0.489201696385996 & 0.978403392771992 & 0.510798303614004 \tabularnewline
49 & 0.513642655135723 & 0.972714689728554 & 0.486357344864277 \tabularnewline
50 & 0.486621948178786 & 0.973243896357572 & 0.513378051821214 \tabularnewline
51 & 0.441557258975186 & 0.883114517950372 & 0.558442741024814 \tabularnewline
52 & 0.400425010896973 & 0.800850021793945 & 0.599574989103027 \tabularnewline
53 & 0.399864147430666 & 0.799728294861332 & 0.600135852569334 \tabularnewline
54 & 0.358080564196473 & 0.716161128392946 & 0.641919435803527 \tabularnewline
55 & 0.346095996699509 & 0.692191993399018 & 0.653904003300491 \tabularnewline
56 & 0.343301126946869 & 0.686602253893738 & 0.656698873053131 \tabularnewline
57 & 0.304239888921621 & 0.608479777843242 & 0.695760111078379 \tabularnewline
58 & 0.285720086242275 & 0.57144017248455 & 0.714279913757725 \tabularnewline
59 & 0.25588514282749 & 0.511770285654979 & 0.74411485717251 \tabularnewline
60 & 0.276307801697872 & 0.552615603395743 & 0.723692198302128 \tabularnewline
61 & 0.252992904203412 & 0.505985808406825 & 0.747007095796588 \tabularnewline
62 & 0.22827508533222 & 0.456550170664441 & 0.77172491466778 \tabularnewline
63 & 0.19967770177513 & 0.399355403550261 & 0.80032229822487 \tabularnewline
64 & 0.172011899050772 & 0.344023798101543 & 0.827988100949228 \tabularnewline
65 & 0.151781538238684 & 0.303563076477368 & 0.848218461761316 \tabularnewline
66 & 0.143071387202618 & 0.286142774405237 & 0.856928612797382 \tabularnewline
67 & 0.139047553587625 & 0.278095107175249 & 0.860952446412375 \tabularnewline
68 & 0.269203231102903 & 0.538406462205806 & 0.730796768897097 \tabularnewline
69 & 0.364495175787505 & 0.728990351575009 & 0.635504824212495 \tabularnewline
70 & 0.334000902483286 & 0.668001804966571 & 0.665999097516714 \tabularnewline
71 & 0.443101781168423 & 0.886203562336845 & 0.556898218831578 \tabularnewline
72 & 0.408390199013182 & 0.816780398026365 & 0.591609800986818 \tabularnewline
73 & 0.408893217545015 & 0.817786435090031 & 0.591106782454984 \tabularnewline
74 & 0.397135723521769 & 0.794271447043538 & 0.602864276478231 \tabularnewline
75 & 0.360034056544236 & 0.720068113088471 & 0.639965943455764 \tabularnewline
76 & 0.425793181707138 & 0.851586363414277 & 0.574206818292862 \tabularnewline
77 & 0.388042441145773 & 0.776084882291547 & 0.611957558854227 \tabularnewline
78 & 0.362094758709996 & 0.724189517419993 & 0.637905241290004 \tabularnewline
79 & 0.376793249549776 & 0.753586499099552 & 0.623206750450224 \tabularnewline
80 & 0.343116850306002 & 0.686233700612005 & 0.656883149693998 \tabularnewline
81 & 0.314522821419375 & 0.62904564283875 & 0.685477178580625 \tabularnewline
82 & 0.280862484334737 & 0.561724968669474 & 0.719137515665263 \tabularnewline
83 & 0.253282202256053 & 0.506564404512106 & 0.746717797743947 \tabularnewline
84 & 0.22342353203394 & 0.44684706406788 & 0.77657646796606 \tabularnewline
85 & 0.217294113012858 & 0.434588226025715 & 0.782705886987142 \tabularnewline
86 & 0.189821596081127 & 0.379643192162253 & 0.810178403918873 \tabularnewline
87 & 0.167487050049588 & 0.334974100099177 & 0.832512949950412 \tabularnewline
88 & 0.155126911424102 & 0.310253822848203 & 0.844873088575898 \tabularnewline
89 & 0.133636740163207 & 0.267273480326414 & 0.866363259836793 \tabularnewline
90 & 0.132269926658086 & 0.264539853316171 & 0.867730073341914 \tabularnewline
91 & 0.113156521251372 & 0.226313042502745 & 0.886843478748628 \tabularnewline
92 & 0.0988847358462607 & 0.197769471692521 & 0.901115264153739 \tabularnewline
93 & 0.084107031424216 & 0.168214062848432 & 0.915892968575784 \tabularnewline
94 & 0.08738790316334 & 0.17477580632668 & 0.91261209683666 \tabularnewline
95 & 0.0790559761014065 & 0.158111952202813 & 0.920944023898594 \tabularnewline
96 & 0.0661568156229523 & 0.132313631245905 & 0.933843184377048 \tabularnewline
97 & 0.0708757304760005 & 0.141751460952001 & 0.929124269524 \tabularnewline
98 & 0.0588724677628206 & 0.117744935525641 & 0.941127532237179 \tabularnewline
99 & 0.0488488408596171 & 0.0976976817192342 & 0.951151159140383 \tabularnewline
100 & 0.0429211722436998 & 0.0858423444873997 & 0.9570788277563 \tabularnewline
101 & 0.0375744296799354 & 0.0751488593598708 & 0.962425570320065 \tabularnewline
102 & 0.0434650218471356 & 0.0869300436942712 & 0.956534978152864 \tabularnewline
103 & 0.0366358021543772 & 0.0732716043087544 & 0.963364197845623 \tabularnewline
104 & 0.0328528463480109 & 0.0657056926960218 & 0.967147153651989 \tabularnewline
105 & 0.0391392019112128 & 0.0782784038224255 & 0.960860798088787 \tabularnewline
106 & 0.0340515709723964 & 0.0681031419447928 & 0.965948429027604 \tabularnewline
107 & 0.0276516450883661 & 0.0553032901767322 & 0.972348354911634 \tabularnewline
108 & 0.0267802706487375 & 0.0535605412974749 & 0.973219729351263 \tabularnewline
109 & 0.0217549951589296 & 0.0435099903178592 & 0.97824500484107 \tabularnewline
110 & 0.0177269006018732 & 0.0354538012037464 & 0.982273099398127 \tabularnewline
111 & 0.0140545390961181 & 0.0281090781922361 & 0.985945460903882 \tabularnewline
112 & 0.0141951812425168 & 0.0283903624850335 & 0.985804818757483 \tabularnewline
113 & 0.0128884921690441 & 0.0257769843380882 & 0.987111507830956 \tabularnewline
114 & 0.0188606395801474 & 0.0377212791602949 & 0.981139360419853 \tabularnewline
115 & 0.017729976921273 & 0.0354599538425461 & 0.982270023078727 \tabularnewline
116 & 0.0172344962398908 & 0.0344689924797817 & 0.982765503760109 \tabularnewline
117 & 0.0141627639097515 & 0.028325527819503 & 0.985837236090249 \tabularnewline
118 & 0.0142532264344367 & 0.0285064528688733 & 0.985746773565563 \tabularnewline
119 & 0.0114884126552615 & 0.022976825310523 & 0.988511587344739 \tabularnewline
120 & 0.0102850543158456 & 0.0205701086316911 & 0.989714945684154 \tabularnewline
121 & 0.00826190974683857 & 0.0165238194936771 & 0.991738090253161 \tabularnewline
122 & 0.0125185784288264 & 0.0250371568576529 & 0.987481421571174 \tabularnewline
123 & 0.0104472014289008 & 0.0208944028578016 & 0.989552798571099 \tabularnewline
124 & 0.00897374536423348 & 0.017947490728467 & 0.991026254635767 \tabularnewline
125 & 0.00729519177711646 & 0.0145903835542329 & 0.992704808222884 \tabularnewline
126 & 0.00577367002463953 & 0.0115473400492791 & 0.99422632997536 \tabularnewline
127 & 0.00525836312851318 & 0.0105167262570264 & 0.994741636871487 \tabularnewline
128 & 0.00425060919945049 & 0.00850121839890098 & 0.995749390800549 \tabularnewline
129 & 0.00600664147032773 & 0.0120132829406555 & 0.993993358529672 \tabularnewline
130 & 0.00660366581214464 & 0.0132073316242893 & 0.993396334187855 \tabularnewline
131 & 0.0137386016812282 & 0.0274772033624564 & 0.986261398318772 \tabularnewline
132 & 0.0164198260589355 & 0.0328396521178709 & 0.983580173941065 \tabularnewline
133 & 0.0176020397246574 & 0.0352040794493148 & 0.982397960275343 \tabularnewline
134 & 0.0166950823017053 & 0.0333901646034105 & 0.983304917698295 \tabularnewline
135 & 0.0133441479647128 & 0.0266882959294256 & 0.986655852035287 \tabularnewline
136 & 0.0112225172738552 & 0.0224450345477104 & 0.988777482726145 \tabularnewline
137 & 0.00891665732174927 & 0.0178333146434985 & 0.991083342678251 \tabularnewline
138 & 0.0111505421035487 & 0.0223010842070974 & 0.988849457896451 \tabularnewline
139 & 0.00955722763970109 & 0.0191144552794022 & 0.990442772360299 \tabularnewline
140 & 0.0113123869945974 & 0.0226247739891949 & 0.988687613005403 \tabularnewline
141 & 0.0179590782372215 & 0.035918156474443 & 0.982040921762778 \tabularnewline
142 & 0.016548886125227 & 0.033097772250454 & 0.983451113874773 \tabularnewline
143 & 0.0133058537213248 & 0.0266117074426496 & 0.986694146278675 \tabularnewline
144 & 0.0136988608033896 & 0.0273977216067793 & 0.98630113919661 \tabularnewline
145 & 0.0245794658590178 & 0.0491589317180356 & 0.975420534140982 \tabularnewline
146 & 0.0298359398435671 & 0.0596718796871343 & 0.970164060156433 \tabularnewline
147 & 0.0313175220167024 & 0.0626350440334047 & 0.968682477983298 \tabularnewline
148 & 0.0277117937652308 & 0.0554235875304616 & 0.972288206234769 \tabularnewline
149 & 0.0225524072318607 & 0.0451048144637214 & 0.977447592768139 \tabularnewline
150 & 0.0314966157980885 & 0.0629932315961771 & 0.968503384201912 \tabularnewline
151 & 0.026599896975728 & 0.053199793951456 & 0.973400103024272 \tabularnewline
152 & 0.0289459749746032 & 0.0578919499492064 & 0.971054025025397 \tabularnewline
153 & 0.0585376029886558 & 0.117075205977312 & 0.941462397011344 \tabularnewline
154 & 0.0564049858145926 & 0.112809971629185 & 0.943595014185407 \tabularnewline
155 & 0.0646082436931067 & 0.129216487386213 & 0.935391756306893 \tabularnewline
156 & 0.0549370528174881 & 0.109874105634976 & 0.945062947182512 \tabularnewline
157 & 0.0490188712046713 & 0.0980377424093427 & 0.950981128795329 \tabularnewline
158 & 0.0426895423542244 & 0.0853790847084488 & 0.957310457645776 \tabularnewline
159 & 0.0413295487361358 & 0.0826590974722717 & 0.958670451263864 \tabularnewline
160 & 0.035466989862597 & 0.070933979725194 & 0.964533010137403 \tabularnewline
161 & 0.028956465570349 & 0.0579129311406979 & 0.971043534429651 \tabularnewline
162 & 0.0236357082340207 & 0.0472714164680414 & 0.976364291765979 \tabularnewline
163 & 0.0193096388451007 & 0.0386192776902014 & 0.980690361154899 \tabularnewline
164 & 0.0163291097700003 & 0.0326582195400006 & 0.98367089023 \tabularnewline
165 & 0.0144500833787466 & 0.0289001667574932 & 0.985549916621253 \tabularnewline
166 & 0.0149486117613171 & 0.0298972235226343 & 0.985051388238683 \tabularnewline
167 & 0.0118842173824243 & 0.0237684347648485 & 0.988115782617576 \tabularnewline
168 & 0.0175132783229478 & 0.0350265566458956 & 0.982486721677052 \tabularnewline
169 & 0.0176340081819062 & 0.0352680163638125 & 0.982365991818094 \tabularnewline
170 & 0.0167353882634734 & 0.0334707765269468 & 0.983264611736527 \tabularnewline
171 & 0.0154566616276166 & 0.0309133232552332 & 0.984543338372383 \tabularnewline
172 & 0.0124723728775002 & 0.0249447457550004 & 0.9875276271225 \tabularnewline
173 & 0.012088212109315 & 0.02417642421863 & 0.987911787890685 \tabularnewline
174 & 0.0137748285514894 & 0.0275496571029788 & 0.986225171448511 \tabularnewline
175 & 0.017933505842758 & 0.035867011685516 & 0.982066494157242 \tabularnewline
176 & 0.014378215481752 & 0.028756430963504 & 0.985621784518248 \tabularnewline
177 & 0.0113523802111796 & 0.0227047604223591 & 0.98864761978882 \tabularnewline
178 & 0.00954556262059169 & 0.0190911252411834 & 0.990454437379408 \tabularnewline
179 & 0.00738975804519148 & 0.014779516090383 & 0.992610241954809 \tabularnewline
180 & 0.00650905214283659 & 0.0130181042856732 & 0.993490947857163 \tabularnewline
181 & 0.0053105202952831 & 0.0106210405905662 & 0.994689479704717 \tabularnewline
182 & 0.00408668688473492 & 0.00817337376946984 & 0.995913313115265 \tabularnewline
183 & 0.00442469291715467 & 0.00884938583430934 & 0.995575307082845 \tabularnewline
184 & 0.00335202292034106 & 0.00670404584068213 & 0.996647977079659 \tabularnewline
185 & 0.0916327023750673 & 0.183265404750135 & 0.908367297624933 \tabularnewline
186 & 0.0819279336027133 & 0.163855867205427 & 0.918072066397287 \tabularnewline
187 & 0.0904200022971107 & 0.180840004594221 & 0.909579997702889 \tabularnewline
188 & 0.0759005129200858 & 0.151801025840172 & 0.924099487079914 \tabularnewline
189 & 0.0677469226921066 & 0.135493845384213 & 0.932253077307893 \tabularnewline
190 & 0.056589711889844 & 0.113179423779688 & 0.943410288110156 \tabularnewline
191 & 0.05236507992328 & 0.10473015984656 & 0.94763492007672 \tabularnewline
192 & 0.0432573608856991 & 0.0865147217713982 & 0.956742639114301 \tabularnewline
193 & 0.0443752188199171 & 0.0887504376398343 & 0.955624781180083 \tabularnewline
194 & 0.0448592051783194 & 0.0897184103566387 & 0.955140794821681 \tabularnewline
195 & 0.0387913601226083 & 0.0775827202452165 & 0.961208639877392 \tabularnewline
196 & 0.0312142528712431 & 0.0624285057424862 & 0.968785747128757 \tabularnewline
197 & 0.0394148933458914 & 0.0788297866917827 & 0.960585106654109 \tabularnewline
198 & 0.0321836113026732 & 0.0643672226053465 & 0.967816388697327 \tabularnewline
199 & 0.0289642716290788 & 0.0579285432581575 & 0.971035728370921 \tabularnewline
200 & 0.0248569204696359 & 0.0497138409392718 & 0.975143079530364 \tabularnewline
201 & 0.0232462668440533 & 0.0464925336881065 & 0.976753733155947 \tabularnewline
202 & 0.0196501226195538 & 0.0393002452391076 & 0.980349877380446 \tabularnewline
203 & 0.0258061599601844 & 0.0516123199203687 & 0.974193840039816 \tabularnewline
204 & 0.0300558719824149 & 0.0601117439648298 & 0.969944128017585 \tabularnewline
205 & 0.0314773536744986 & 0.0629547073489971 & 0.968522646325501 \tabularnewline
206 & 0.0246734540502822 & 0.0493469081005644 & 0.975326545949718 \tabularnewline
207 & 0.0236195712607923 & 0.0472391425215845 & 0.976380428739208 \tabularnewline
208 & 0.0193097178187444 & 0.0386194356374887 & 0.980690282181256 \tabularnewline
209 & 0.0215317127034812 & 0.0430634254069623 & 0.978468287296519 \tabularnewline
210 & 0.0171599938260061 & 0.0343199876520122 & 0.982840006173994 \tabularnewline
211 & 0.0197200608102488 & 0.0394401216204976 & 0.980279939189751 \tabularnewline
212 & 0.0319860143610665 & 0.0639720287221329 & 0.968013985638933 \tabularnewline
213 & 0.0249009988083478 & 0.0498019976166957 & 0.975099001191652 \tabularnewline
214 & 0.0321996334420403 & 0.0643992668840806 & 0.96780036655796 \tabularnewline
215 & 0.0273232056383283 & 0.0546464112766565 & 0.972676794361672 \tabularnewline
216 & 0.0211375747978418 & 0.0422751495956837 & 0.978862425202158 \tabularnewline
217 & 0.0232205516167757 & 0.0464411032335514 & 0.976779448383224 \tabularnewline
218 & 0.0195797326479916 & 0.0391594652959831 & 0.980420267352008 \tabularnewline
219 & 0.0181914335051249 & 0.0363828670102498 & 0.981808566494875 \tabularnewline
220 & 0.0139104652747253 & 0.0278209305494506 & 0.986089534725275 \tabularnewline
221 & 0.0115846356307567 & 0.0231692712615133 & 0.988415364369243 \tabularnewline
222 & 0.00831863645075521 & 0.0166372729015104 & 0.991681363549245 \tabularnewline
223 & 0.00638020378999746 & 0.0127604075799949 & 0.993619796210003 \tabularnewline
224 & 0.00480906588265554 & 0.00961813176531108 & 0.995190934117344 \tabularnewline
225 & 0.00409375045076022 & 0.00818750090152044 & 0.99590624954924 \tabularnewline
226 & 0.00946681005766529 & 0.0189336201153306 & 0.990533189942335 \tabularnewline
227 & 0.00741795109278939 & 0.0148359021855788 & 0.992582048907211 \tabularnewline
228 & 0.00548896145726457 & 0.0109779229145291 & 0.994511038542735 \tabularnewline
229 & 0.00392589658277771 & 0.00785179316555542 & 0.996074103417222 \tabularnewline
230 & 0.00289046341687466 & 0.00578092683374933 & 0.997109536583125 \tabularnewline
231 & 0.00260618189028514 & 0.00521236378057027 & 0.997393818109715 \tabularnewline
232 & 0.00613734309401658 & 0.0122746861880332 & 0.993862656905983 \tabularnewline
233 & 0.0247649674569371 & 0.0495299349138743 & 0.975235032543063 \tabularnewline
234 & 0.0377477579547085 & 0.075495515909417 & 0.962252242045291 \tabularnewline
235 & 0.0272310989368987 & 0.0544621978737975 & 0.972768901063101 \tabularnewline
236 & 0.0228254490818122 & 0.0456508981636245 & 0.977174550918188 \tabularnewline
237 & 0.19737072198452 & 0.39474144396904 & 0.80262927801548 \tabularnewline
238 & 0.155667521678584 & 0.311335043357167 & 0.844332478321416 \tabularnewline
239 & 0.129607141019934 & 0.259214282039867 & 0.870392858980066 \tabularnewline
240 & 0.100544198023488 & 0.201088396046976 & 0.899455801976512 \tabularnewline
241 & 0.0884081811254627 & 0.176816362250925 & 0.911591818874537 \tabularnewline
242 & 0.137938494268997 & 0.275876988537994 & 0.862061505731003 \tabularnewline
243 & 0.112959828401644 & 0.225919656803287 & 0.887040171598356 \tabularnewline
244 & 0.118293730724496 & 0.236587461448991 & 0.881706269275504 \tabularnewline
245 & 0.0968198344744189 & 0.193639668948838 & 0.903180165525581 \tabularnewline
246 & 0.082174010171872 & 0.164348020343744 & 0.917825989828128 \tabularnewline
247 & 0.0530560832162604 & 0.106112166432521 & 0.94694391678374 \tabularnewline
248 & 0.0452028729880969 & 0.0904057459761938 & 0.954797127011903 \tabularnewline
249 & 0.040451903681973 & 0.080903807363946 & 0.959548096318027 \tabularnewline
250 & 0.115496462193852 & 0.230992924387703 & 0.884503537806148 \tabularnewline
251 & 0.0947038411535398 & 0.18940768230708 & 0.90529615884646 \tabularnewline
252 & 0.431438999835686 & 0.862877999671371 & 0.568561000164314 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185983&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]12[/C][C]0.0949069336717827[/C][C]0.189813867343565[/C][C]0.905093066328217[/C][/ROW]
[ROW][C]13[/C][C]0.168821052440469[/C][C]0.337642104880937[/C][C]0.831178947559531[/C][/ROW]
[ROW][C]14[/C][C]0.17886382794067[/C][C]0.357727655881341[/C][C]0.82113617205933[/C][/ROW]
[ROW][C]15[/C][C]0.102108221816446[/C][C]0.204216443632893[/C][C]0.897891778183554[/C][/ROW]
[ROW][C]16[/C][C]0.0784281971443364[/C][C]0.156856394288673[/C][C]0.921571802855664[/C][/ROW]
[ROW][C]17[/C][C]0.0870237660597908[/C][C]0.174047532119582[/C][C]0.912976233940209[/C][/ROW]
[ROW][C]18[/C][C]0.213223439837097[/C][C]0.426446879674194[/C][C]0.786776560162903[/C][/ROW]
[ROW][C]19[/C][C]0.175810464451898[/C][C]0.351620928903795[/C][C]0.824189535548102[/C][/ROW]
[ROW][C]20[/C][C]0.139406041965233[/C][C]0.278812083930466[/C][C]0.860593958034767[/C][/ROW]
[ROW][C]21[/C][C]0.107616872867732[/C][C]0.215233745735463[/C][C]0.892383127132269[/C][/ROW]
[ROW][C]22[/C][C]0.131400316307911[/C][C]0.262800632615821[/C][C]0.868599683692089[/C][/ROW]
[ROW][C]23[/C][C]0.22984858009041[/C][C]0.45969716018082[/C][C]0.77015141990959[/C][/ROW]
[ROW][C]24[/C][C]0.34540067818832[/C][C]0.690801356376639[/C][C]0.65459932181168[/C][/ROW]
[ROW][C]25[/C][C]0.282158756508175[/C][C]0.564317513016349[/C][C]0.717841243491825[/C][/ROW]
[ROW][C]26[/C][C]0.237323312240147[/C][C]0.474646624480294[/C][C]0.762676687759853[/C][/ROW]
[ROW][C]27[/C][C]0.227896245738457[/C][C]0.455792491476914[/C][C]0.772103754261543[/C][/ROW]
[ROW][C]28[/C][C]0.338485052212977[/C][C]0.676970104425954[/C][C]0.661514947787023[/C][/ROW]
[ROW][C]29[/C][C]0.289325481134631[/C][C]0.578650962269262[/C][C]0.710674518865369[/C][/ROW]
[ROW][C]30[/C][C]0.397882859936623[/C][C]0.795765719873245[/C][C]0.602117140063377[/C][/ROW]
[ROW][C]31[/C][C]0.356890257488035[/C][C]0.71378051497607[/C][C]0.643109742511965[/C][/ROW]
[ROW][C]32[/C][C]0.32941658209055[/C][C]0.6588331641811[/C][C]0.67058341790945[/C][/ROW]
[ROW][C]33[/C][C]0.314121460060036[/C][C]0.628242920120072[/C][C]0.685878539939964[/C][/ROW]
[ROW][C]34[/C][C]0.278262895109878[/C][C]0.556525790219755[/C][C]0.721737104890122[/C][/ROW]
[ROW][C]35[/C][C]0.236820684412613[/C][C]0.473641368825226[/C][C]0.763179315587387[/C][/ROW]
[ROW][C]36[/C][C]0.366904763640681[/C][C]0.733809527281362[/C][C]0.633095236359319[/C][/ROW]
[ROW][C]37[/C][C]0.395621728705751[/C][C]0.791243457411502[/C][C]0.604378271294249[/C][/ROW]
[ROW][C]38[/C][C]0.3715766725154[/C][C]0.743153345030801[/C][C]0.6284233274846[/C][/ROW]
[ROW][C]39[/C][C]0.41620760257615[/C][C]0.8324152051523[/C][C]0.58379239742385[/C][/ROW]
[ROW][C]40[/C][C]0.396546650562147[/C][C]0.793093301124293[/C][C]0.603453349437853[/C][/ROW]
[ROW][C]41[/C][C]0.357799570743431[/C][C]0.715599141486863[/C][C]0.642200429256569[/C][/ROW]
[ROW][C]42[/C][C]0.31948647380307[/C][C]0.638972947606141[/C][C]0.68051352619693[/C][/ROW]
[ROW][C]43[/C][C]0.338409103157387[/C][C]0.676818206314775[/C][C]0.661590896842613[/C][/ROW]
[ROW][C]44[/C][C]0.29140261820839[/C][C]0.582805236416781[/C][C]0.70859738179161[/C][/ROW]
[ROW][C]45[/C][C]0.26449310164708[/C][C]0.52898620329416[/C][C]0.73550689835292[/C][/ROW]
[ROW][C]46[/C][C]0.441612475184553[/C][C]0.883224950369107[/C][C]0.558387524815447[/C][/ROW]
[ROW][C]47[/C][C]0.532267002610967[/C][C]0.935465994778067[/C][C]0.467732997389033[/C][/ROW]
[ROW][C]48[/C][C]0.489201696385996[/C][C]0.978403392771992[/C][C]0.510798303614004[/C][/ROW]
[ROW][C]49[/C][C]0.513642655135723[/C][C]0.972714689728554[/C][C]0.486357344864277[/C][/ROW]
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[ROW][C]193[/C][C]0.0443752188199171[/C][C]0.0887504376398343[/C][C]0.955624781180083[/C][/ROW]
[ROW][C]194[/C][C]0.0448592051783194[/C][C]0.0897184103566387[/C][C]0.955140794821681[/C][/ROW]
[ROW][C]195[/C][C]0.0387913601226083[/C][C]0.0775827202452165[/C][C]0.961208639877392[/C][/ROW]
[ROW][C]196[/C][C]0.0312142528712431[/C][C]0.0624285057424862[/C][C]0.968785747128757[/C][/ROW]
[ROW][C]197[/C][C]0.0394148933458914[/C][C]0.0788297866917827[/C][C]0.960585106654109[/C][/ROW]
[ROW][C]198[/C][C]0.0321836113026732[/C][C]0.0643672226053465[/C][C]0.967816388697327[/C][/ROW]
[ROW][C]199[/C][C]0.0289642716290788[/C][C]0.0579285432581575[/C][C]0.971035728370921[/C][/ROW]
[ROW][C]200[/C][C]0.0248569204696359[/C][C]0.0497138409392718[/C][C]0.975143079530364[/C][/ROW]
[ROW][C]201[/C][C]0.0232462668440533[/C][C]0.0464925336881065[/C][C]0.976753733155947[/C][/ROW]
[ROW][C]202[/C][C]0.0196501226195538[/C][C]0.0393002452391076[/C][C]0.980349877380446[/C][/ROW]
[ROW][C]203[/C][C]0.0258061599601844[/C][C]0.0516123199203687[/C][C]0.974193840039816[/C][/ROW]
[ROW][C]204[/C][C]0.0300558719824149[/C][C]0.0601117439648298[/C][C]0.969944128017585[/C][/ROW]
[ROW][C]205[/C][C]0.0314773536744986[/C][C]0.0629547073489971[/C][C]0.968522646325501[/C][/ROW]
[ROW][C]206[/C][C]0.0246734540502822[/C][C]0.0493469081005644[/C][C]0.975326545949718[/C][/ROW]
[ROW][C]207[/C][C]0.0236195712607923[/C][C]0.0472391425215845[/C][C]0.976380428739208[/C][/ROW]
[ROW][C]208[/C][C]0.0193097178187444[/C][C]0.0386194356374887[/C][C]0.980690282181256[/C][/ROW]
[ROW][C]209[/C][C]0.0215317127034812[/C][C]0.0430634254069623[/C][C]0.978468287296519[/C][/ROW]
[ROW][C]210[/C][C]0.0171599938260061[/C][C]0.0343199876520122[/C][C]0.982840006173994[/C][/ROW]
[ROW][C]211[/C][C]0.0197200608102488[/C][C]0.0394401216204976[/C][C]0.980279939189751[/C][/ROW]
[ROW][C]212[/C][C]0.0319860143610665[/C][C]0.0639720287221329[/C][C]0.968013985638933[/C][/ROW]
[ROW][C]213[/C][C]0.0249009988083478[/C][C]0.0498019976166957[/C][C]0.975099001191652[/C][/ROW]
[ROW][C]214[/C][C]0.0321996334420403[/C][C]0.0643992668840806[/C][C]0.96780036655796[/C][/ROW]
[ROW][C]215[/C][C]0.0273232056383283[/C][C]0.0546464112766565[/C][C]0.972676794361672[/C][/ROW]
[ROW][C]216[/C][C]0.0211375747978418[/C][C]0.0422751495956837[/C][C]0.978862425202158[/C][/ROW]
[ROW][C]217[/C][C]0.0232205516167757[/C][C]0.0464411032335514[/C][C]0.976779448383224[/C][/ROW]
[ROW][C]218[/C][C]0.0195797326479916[/C][C]0.0391594652959831[/C][C]0.980420267352008[/C][/ROW]
[ROW][C]219[/C][C]0.0181914335051249[/C][C]0.0363828670102498[/C][C]0.981808566494875[/C][/ROW]
[ROW][C]220[/C][C]0.0139104652747253[/C][C]0.0278209305494506[/C][C]0.986089534725275[/C][/ROW]
[ROW][C]221[/C][C]0.0115846356307567[/C][C]0.0231692712615133[/C][C]0.988415364369243[/C][/ROW]
[ROW][C]222[/C][C]0.00831863645075521[/C][C]0.0166372729015104[/C][C]0.991681363549245[/C][/ROW]
[ROW][C]223[/C][C]0.00638020378999746[/C][C]0.0127604075799949[/C][C]0.993619796210003[/C][/ROW]
[ROW][C]224[/C][C]0.00480906588265554[/C][C]0.00961813176531108[/C][C]0.995190934117344[/C][/ROW]
[ROW][C]225[/C][C]0.00409375045076022[/C][C]0.00818750090152044[/C][C]0.99590624954924[/C][/ROW]
[ROW][C]226[/C][C]0.00946681005766529[/C][C]0.0189336201153306[/C][C]0.990533189942335[/C][/ROW]
[ROW][C]227[/C][C]0.00741795109278939[/C][C]0.0148359021855788[/C][C]0.992582048907211[/C][/ROW]
[ROW][C]228[/C][C]0.00548896145726457[/C][C]0.0109779229145291[/C][C]0.994511038542735[/C][/ROW]
[ROW][C]229[/C][C]0.00392589658277771[/C][C]0.00785179316555542[/C][C]0.996074103417222[/C][/ROW]
[ROW][C]230[/C][C]0.00289046341687466[/C][C]0.00578092683374933[/C][C]0.997109536583125[/C][/ROW]
[ROW][C]231[/C][C]0.00260618189028514[/C][C]0.00521236378057027[/C][C]0.997393818109715[/C][/ROW]
[ROW][C]232[/C][C]0.00613734309401658[/C][C]0.0122746861880332[/C][C]0.993862656905983[/C][/ROW]
[ROW][C]233[/C][C]0.0247649674569371[/C][C]0.0495299349138743[/C][C]0.975235032543063[/C][/ROW]
[ROW][C]234[/C][C]0.0377477579547085[/C][C]0.075495515909417[/C][C]0.962252242045291[/C][/ROW]
[ROW][C]235[/C][C]0.0272310989368987[/C][C]0.0544621978737975[/C][C]0.972768901063101[/C][/ROW]
[ROW][C]236[/C][C]0.0228254490818122[/C][C]0.0456508981636245[/C][C]0.977174550918188[/C][/ROW]
[ROW][C]237[/C][C]0.19737072198452[/C][C]0.39474144396904[/C][C]0.80262927801548[/C][/ROW]
[ROW][C]238[/C][C]0.155667521678584[/C][C]0.311335043357167[/C][C]0.844332478321416[/C][/ROW]
[ROW][C]239[/C][C]0.129607141019934[/C][C]0.259214282039867[/C][C]0.870392858980066[/C][/ROW]
[ROW][C]240[/C][C]0.100544198023488[/C][C]0.201088396046976[/C][C]0.899455801976512[/C][/ROW]
[ROW][C]241[/C][C]0.0884081811254627[/C][C]0.176816362250925[/C][C]0.911591818874537[/C][/ROW]
[ROW][C]242[/C][C]0.137938494268997[/C][C]0.275876988537994[/C][C]0.862061505731003[/C][/ROW]
[ROW][C]243[/C][C]0.112959828401644[/C][C]0.225919656803287[/C][C]0.887040171598356[/C][/ROW]
[ROW][C]244[/C][C]0.118293730724496[/C][C]0.236587461448991[/C][C]0.881706269275504[/C][/ROW]
[ROW][C]245[/C][C]0.0968198344744189[/C][C]0.193639668948838[/C][C]0.903180165525581[/C][/ROW]
[ROW][C]246[/C][C]0.082174010171872[/C][C]0.164348020343744[/C][C]0.917825989828128[/C][/ROW]
[ROW][C]247[/C][C]0.0530560832162604[/C][C]0.106112166432521[/C][C]0.94694391678374[/C][/ROW]
[ROW][C]248[/C][C]0.0452028729880969[/C][C]0.0904057459761938[/C][C]0.954797127011903[/C][/ROW]
[ROW][C]249[/C][C]0.040451903681973[/C][C]0.080903807363946[/C][C]0.959548096318027[/C][/ROW]
[ROW][C]250[/C][C]0.115496462193852[/C][C]0.230992924387703[/C][C]0.884503537806148[/C][/ROW]
[ROW][C]251[/C][C]0.0947038411535398[/C][C]0.18940768230708[/C][C]0.90529615884646[/C][/ROW]
[ROW][C]252[/C][C]0.431438999835686[/C][C]0.862877999671371[/C][C]0.568561000164314[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185983&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185983&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.09490693367178270.1898138673435650.905093066328217
130.1688210524404690.3376421048809370.831178947559531
140.178863827940670.3577276558813410.82113617205933
150.1021082218164460.2042164436328930.897891778183554
160.07842819714433640.1568563942886730.921571802855664
170.08702376605979080.1740475321195820.912976233940209
180.2132234398370970.4264468796741940.786776560162903
190.1758104644518980.3516209289037950.824189535548102
200.1394060419652330.2788120839304660.860593958034767
210.1076168728677320.2152337457354630.892383127132269
220.1314003163079110.2628006326158210.868599683692089
230.229848580090410.459697160180820.77015141990959
240.345400678188320.6908013563766390.65459932181168
250.2821587565081750.5643175130163490.717841243491825
260.2373233122401470.4746466244802940.762676687759853
270.2278962457384570.4557924914769140.772103754261543
280.3384850522129770.6769701044259540.661514947787023
290.2893254811346310.5786509622692620.710674518865369
300.3978828599366230.7957657198732450.602117140063377
310.3568902574880350.713780514976070.643109742511965
320.329416582090550.65883316418110.67058341790945
330.3141214600600360.6282429201200720.685878539939964
340.2782628951098780.5565257902197550.721737104890122
350.2368206844126130.4736413688252260.763179315587387
360.3669047636406810.7338095272813620.633095236359319
370.3956217287057510.7912434574115020.604378271294249
380.37157667251540.7431533450308010.6284233274846
390.416207602576150.83241520515230.58379239742385
400.3965466505621470.7930933011242930.603453349437853
410.3577995707434310.7155991414868630.642200429256569
420.319486473803070.6389729476061410.68051352619693
430.3384091031573870.6768182063147750.661590896842613
440.291402618208390.5828052364167810.70859738179161
450.264493101647080.528986203294160.73550689835292
460.4416124751845530.8832249503691070.558387524815447
470.5322670026109670.9354659947780670.467732997389033
480.4892016963859960.9784033927719920.510798303614004
490.5136426551357230.9727146897285540.486357344864277
500.4866219481787860.9732438963575720.513378051821214
510.4415572589751860.8831145179503720.558442741024814
520.4004250108969730.8008500217939450.599574989103027
530.3998641474306660.7997282948613320.600135852569334
540.3580805641964730.7161611283929460.641919435803527
550.3460959966995090.6921919933990180.653904003300491
560.3433011269468690.6866022538937380.656698873053131
570.3042398889216210.6084797778432420.695760111078379
580.2857200862422750.571440172484550.714279913757725
590.255885142827490.5117702856549790.74411485717251
600.2763078016978720.5526156033957430.723692198302128
610.2529929042034120.5059858084068250.747007095796588
620.228275085332220.4565501706644410.77172491466778
630.199677701775130.3993554035502610.80032229822487
640.1720118990507720.3440237981015430.827988100949228
650.1517815382386840.3035630764773680.848218461761316
660.1430713872026180.2861427744052370.856928612797382
670.1390475535876250.2780951071752490.860952446412375
680.2692032311029030.5384064622058060.730796768897097
690.3644951757875050.7289903515750090.635504824212495
700.3340009024832860.6680018049665710.665999097516714
710.4431017811684230.8862035623368450.556898218831578
720.4083901990131820.8167803980263650.591609800986818
730.4088932175450150.8177864350900310.591106782454984
740.3971357235217690.7942714470435380.602864276478231
750.3600340565442360.7200681130884710.639965943455764
760.4257931817071380.8515863634142770.574206818292862
770.3880424411457730.7760848822915470.611957558854227
780.3620947587099960.7241895174199930.637905241290004
790.3767932495497760.7535864990995520.623206750450224
800.3431168503060020.6862337006120050.656883149693998
810.3145228214193750.629045642838750.685477178580625
820.2808624843347370.5617249686694740.719137515665263
830.2532822022560530.5065644045121060.746717797743947
840.223423532033940.446847064067880.77657646796606
850.2172941130128580.4345882260257150.782705886987142
860.1898215960811270.3796431921622530.810178403918873
870.1674870500495880.3349741000991770.832512949950412
880.1551269114241020.3102538228482030.844873088575898
890.1336367401632070.2672734803264140.866363259836793
900.1322699266580860.2645398533161710.867730073341914
910.1131565212513720.2263130425027450.886843478748628
920.09888473584626070.1977694716925210.901115264153739
930.0841070314242160.1682140628484320.915892968575784
940.087387903163340.174775806326680.91261209683666
950.07905597610140650.1581119522028130.920944023898594
960.06615681562295230.1323136312459050.933843184377048
970.07087573047600050.1417514609520010.929124269524
980.05887246776282060.1177449355256410.941127532237179
990.04884884085961710.09769768171923420.951151159140383
1000.04292117224369980.08584234448739970.9570788277563
1010.03757442967993540.07514885935987080.962425570320065
1020.04346502184713560.08693004369427120.956534978152864
1030.03663580215437720.07327160430875440.963364197845623
1040.03285284634801090.06570569269602180.967147153651989
1050.03913920191121280.07827840382242550.960860798088787
1060.03405157097239640.06810314194479280.965948429027604
1070.02765164508836610.05530329017673220.972348354911634
1080.02678027064873750.05356054129747490.973219729351263
1090.02175499515892960.04350999031785920.97824500484107
1100.01772690060187320.03545380120374640.982273099398127
1110.01405453909611810.02810907819223610.985945460903882
1120.01419518124251680.02839036248503350.985804818757483
1130.01288849216904410.02577698433808820.987111507830956
1140.01886063958014740.03772127916029490.981139360419853
1150.0177299769212730.03545995384254610.982270023078727
1160.01723449623989080.03446899247978170.982765503760109
1170.01416276390975150.0283255278195030.985837236090249
1180.01425322643443670.02850645286887330.985746773565563
1190.01148841265526150.0229768253105230.988511587344739
1200.01028505431584560.02057010863169110.989714945684154
1210.008261909746838570.01652381949367710.991738090253161
1220.01251857842882640.02503715685765290.987481421571174
1230.01044720142890080.02089440285780160.989552798571099
1240.008973745364233480.0179474907284670.991026254635767
1250.007295191777116460.01459038355423290.992704808222884
1260.005773670024639530.01154734004927910.99422632997536
1270.005258363128513180.01051672625702640.994741636871487
1280.004250609199450490.008501218398900980.995749390800549
1290.006006641470327730.01201328294065550.993993358529672
1300.006603665812144640.01320733162428930.993396334187855
1310.01373860168122820.02747720336245640.986261398318772
1320.01641982605893550.03283965211787090.983580173941065
1330.01760203972465740.03520407944931480.982397960275343
1340.01669508230170530.03339016460341050.983304917698295
1350.01334414796471280.02668829592942560.986655852035287
1360.01122251727385520.02244503454771040.988777482726145
1370.008916657321749270.01783331464349850.991083342678251
1380.01115054210354870.02230108420709740.988849457896451
1390.009557227639701090.01911445527940220.990442772360299
1400.01131238699459740.02262477398919490.988687613005403
1410.01795907823722150.0359181564744430.982040921762778
1420.0165488861252270.0330977722504540.983451113874773
1430.01330585372132480.02661170744264960.986694146278675
1440.01369886080338960.02739772160677930.98630113919661
1450.02457946585901780.04915893171803560.975420534140982
1460.02983593984356710.05967187968713430.970164060156433
1470.03131752201670240.06263504403340470.968682477983298
1480.02771179376523080.05542358753046160.972288206234769
1490.02255240723186070.04510481446372140.977447592768139
1500.03149661579808850.06299323159617710.968503384201912
1510.0265998969757280.0531997939514560.973400103024272
1520.02894597497460320.05789194994920640.971054025025397
1530.05853760298865580.1170752059773120.941462397011344
1540.05640498581459260.1128099716291850.943595014185407
1550.06460824369310670.1292164873862130.935391756306893
1560.05493705281748810.1098741056349760.945062947182512
1570.04901887120467130.09803774240934270.950981128795329
1580.04268954235422440.08537908470844880.957310457645776
1590.04132954873613580.08265909747227170.958670451263864
1600.0354669898625970.0709339797251940.964533010137403
1610.0289564655703490.05791293114069790.971043534429651
1620.02363570823402070.04727141646804140.976364291765979
1630.01930963884510070.03861927769020140.980690361154899
1640.01632910977000030.03265821954000060.98367089023
1650.01445008337874660.02890016675749320.985549916621253
1660.01494861176131710.02989722352263430.985051388238683
1670.01188421738242430.02376843476484850.988115782617576
1680.01751327832294780.03502655664589560.982486721677052
1690.01763400818190620.03526801636381250.982365991818094
1700.01673538826347340.03347077652694680.983264611736527
1710.01545666162761660.03091332325523320.984543338372383
1720.01247237287750020.02494474575500040.9875276271225
1730.0120882121093150.024176424218630.987911787890685
1740.01377482855148940.02754965710297880.986225171448511
1750.0179335058427580.0358670116855160.982066494157242
1760.0143782154817520.0287564309635040.985621784518248
1770.01135238021117960.02270476042235910.98864761978882
1780.009545562620591690.01909112524118340.990454437379408
1790.007389758045191480.0147795160903830.992610241954809
1800.006509052142836590.01301810428567320.993490947857163
1810.00531052029528310.01062104059056620.994689479704717
1820.004086686884734920.008173373769469840.995913313115265
1830.004424692917154670.008849385834309340.995575307082845
1840.003352022920341060.006704045840682130.996647977079659
1850.09163270237506730.1832654047501350.908367297624933
1860.08192793360271330.1638558672054270.918072066397287
1870.09042000229711070.1808400045942210.909579997702889
1880.07590051292008580.1518010258401720.924099487079914
1890.06774692269210660.1354938453842130.932253077307893
1900.0565897118898440.1131794237796880.943410288110156
1910.052365079923280.104730159846560.94763492007672
1920.04325736088569910.08651472177139820.956742639114301
1930.04437521881991710.08875043763983430.955624781180083
1940.04485920517831940.08971841035663870.955140794821681
1950.03879136012260830.07758272024521650.961208639877392
1960.03121425287124310.06242850574248620.968785747128757
1970.03941489334589140.07882978669178270.960585106654109
1980.03218361130267320.06436722260534650.967816388697327
1990.02896427162907880.05792854325815750.971035728370921
2000.02485692046963590.04971384093927180.975143079530364
2010.02324626684405330.04649253368810650.976753733155947
2020.01965012261955380.03930024523910760.980349877380446
2030.02580615996018440.05161231992036870.974193840039816
2040.03005587198241490.06011174396482980.969944128017585
2050.03147735367449860.06295470734899710.968522646325501
2060.02467345405028220.04934690810056440.975326545949718
2070.02361957126079230.04723914252158450.976380428739208
2080.01930971781874440.03861943563748870.980690282181256
2090.02153171270348120.04306342540696230.978468287296519
2100.01715999382600610.03431998765201220.982840006173994
2110.01972006081024880.03944012162049760.980279939189751
2120.03198601436106650.06397202872213290.968013985638933
2130.02490099880834780.04980199761669570.975099001191652
2140.03219963344204030.06439926688408060.96780036655796
2150.02732320563832830.05464641127665650.972676794361672
2160.02113757479784180.04227514959568370.978862425202158
2170.02322055161677570.04644110323355140.976779448383224
2180.01957973264799160.03915946529598310.980420267352008
2190.01819143350512490.03638286701024980.981808566494875
2200.01391046527472530.02782093054945060.986089534725275
2210.01158463563075670.02316927126151330.988415364369243
2220.008318636450755210.01663727290151040.991681363549245
2230.006380203789997460.01276040757999490.993619796210003
2240.004809065882655540.009618131765311080.995190934117344
2250.004093750450760220.008187500901520440.99590624954924
2260.009466810057665290.01893362011533060.990533189942335
2270.007417951092789390.01483590218557880.992582048907211
2280.005488961457264570.01097792291452910.994511038542735
2290.003925896582777710.007851793165555420.996074103417222
2300.002890463416874660.005780926833749330.997109536583125
2310.002606181890285140.005212363780570270.997393818109715
2320.006137343094016580.01227468618803320.993862656905983
2330.02476496745693710.04952993491387430.975235032543063
2340.03774775795470850.0754955159094170.962252242045291
2350.02723109893689870.05446219787379750.972768901063101
2360.02282544908181220.04565089816362450.977174550918188
2370.197370721984520.394741443969040.80262927801548
2380.1556675216785840.3113350433571670.844332478321416
2390.1296071410199340.2592142820398670.870392858980066
2400.1005441980234880.2010883960469760.899455801976512
2410.08840818112546270.1768163622509250.911591818874537
2420.1379384942689970.2758769885379940.862061505731003
2430.1129598284016440.2259196568032870.887040171598356
2440.1182937307244960.2365874614489910.881706269275504
2450.09681983447441890.1936396689488380.903180165525581
2460.0821740101718720.1643480203437440.917825989828128
2470.05305608321626040.1061121664325210.94694391678374
2480.04520287298809690.09040574597619380.954797127011903
2490.0404519036819730.0809038073639460.959548096318027
2500.1154964621938520.2309929243877030.884503537806148
2510.09470384115353980.189407682307080.90529615884646
2520.4314389998356860.8628779996713710.568561000164314







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level90.037344398340249NOK
5% type I error level900.37344398340249NOK
10% type I error level1290.535269709543568NOK

\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 & 9 & 0.037344398340249 & NOK \tabularnewline
5% type I error level & 90 & 0.37344398340249 & NOK \tabularnewline
10% type I error level & 129 & 0.535269709543568 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185983&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]9[/C][C]0.037344398340249[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]90[/C][C]0.37344398340249[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]129[/C][C]0.535269709543568[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185983&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185983&T=6

As an alternative you can also use a QR Code:  

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 level90.037344398340249NOK
5% type I error level900.37344398340249NOK
10% type I error level1290.535269709543568NOK



Parameters (Session):
par1 = 3 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 3 ; par2 = Do not include Seasonal Dummies ; par3 = 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')
}