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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 computationFri, 21 Dec 2012 11:18:15 -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/Dec/21/t13561067588z93zfaabfht9sq.htm/, Retrieved Fri, 29 Mar 2024 11:17:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=203885, Retrieved Fri, 29 Mar 2024 11:17:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact70
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-11-17 09:14:55] [b98453cac15ba1066b407e146608df68]
-   P     [Multiple Regression] [Multiple Regressi...] [2012-12-21 16:18:15] [a641906195a0eb35087b0121beaccdc9] [Current]
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Dataseries X:
9	41	38	13	12	14	12	53	32
9	39	32	16	11	18	11	83	51
9	30	35	19	15	11	14	66	42
9	31	33	15	6	12	12	67	41
9	34	37	14	13	16	21	76	46
9	35	29	13	10	18	12	78	47
9	39	31	19	12	14	22	53	37
9	34	36	15	14	14	11	80	49
9	36	35	14	12	15	10	74	45
9	37	38	15	9	15	13	76	47
9	38	31	16	10	17	10	79	49
9	36	34	16	12	19	8	54	33
9	38	35	16	12	10	15	67	42
9	39	38	16	11	16	14	54	33
9	33	37	17	15	18	10	87	53
9	32	33	15	12	14	14	58	36
9	36	32	15	10	14	14	75	45
9	38	38	20	12	17	11	88	54
9	39	38	18	11	14	10	64	41
9	32	32	16	12	16	13	57	36
9	32	33	16	11	18	9.5	66	41
9	31	31	16	12	11	14	68	44
9	39	38	19	13	14	12	54	33
9	37	39	16	11	12	14	56	37
9	39	32	17	12	17	11	86	52
9	41	32	17	13	9	9	80	47
9	36	35	16	10	16	11	76	43
9	33	37	15	14	14	15	69	44
9	33	33	16	12	15	14	78	45
9	34	33	14	10	11	13	67	44
9	31	31	15	12	16	9	80	49
9	27	32	12	8	13	15	54	33
9	37	31	14	10	17	10	71	43
9	34	37	16	12	15	11	84	54
9	34	30	14	12	14	13	74	42
9	32	33	10	7	16	8	71	44
9	29	31	10	9	9	20	63	37
9	36	33	14	12	15	12	71	43
9	29	31	16	10	17	10	76	46
9	35	33	16	10	13	10	69	42
9	37	32	16	10	15	9	74	45
9	34	33	14	12	16	14	75	44
9	38	32	20	15	16	8	54	33
9	35	33	14	10	12	14	52	31
9	38	28	14	10	15	11	69	42
9	37	35	11	12	11	13	68	40
9	38	39	14	13	15	9	65	43
9	33	34	15	11	15	11	75	46
9	36	38	16	11	17	15	74	42
9	38	32	14	12	13	11	75	45
9	32	38	16	14	16	10	72	44
9	32	30	14	10	14	14	67	40
9	32	33	12	12	11	18	63	37
9	34	38	16	13	12	14	62	46
9	32	32	9	5	12	11	63	36
9	37	35	14	6	15	14.5	76	47
9	39	34	16	12	16	13	74	45
9	29	34	16	12	15	9	67	42
9	37	36	15	11	12	10	73	43
9	35	34	16	10	12	15	70	43
9	30	28	12	7	8	20	53	32
9	38	34	16	12	13	12	77	45
9	34	35	16	14	11	12	80	48
9	31	35	14	11	14	14	52	31
9	34	31	16	12	15	13	54	33
10	35	37	17	13	10	11	80	49
10	36	35	18	14	11	17	66	42
10	30	27	18	11	12	12	73	41
10	39	40	12	12	15	13	63	38
10	35	37	16	12	15	14	69	42
10	38	36	10	8	14	13	67	44
10	31	38	14	11	16	15	54	33
10	34	39	18	14	15	13	81	48
10	38	41	18	14	15	10	69	40
10	34	27	16	12	13	11	84	50
10	39	30	17	9	12	19	80	49
10	37	37	16	13	17	13	70	43
10	34	31	16	11	13	17	69	44
10	28	31	13	12	15	13	77	47
10	37	27	16	12	13	9	54	33
10	33	36	16	12	15	11	79	46
10	35	37	16	12	15	9	71	45
10	37	33	15	12	16	12	73	43
10	32	34	15	11	15	12	72	44
10	33	31	16	10	14	13	77	47
10	38	39	14	9	15	13	75	45
10	33	34	16	12	14	12	69	42
10	29	32	16	12	13	15	54	33
10	33	33	15	12	7	22	70	43
10	31	36	12	9	17	13	73	46
10	36	32	17	15	13	15	54	33
10	35	41	16	12	15	13	77	46
10	32	28	15	12	14	15	82	48
10	29	30	13	12	13	12.5	80	47
10	39	36	16	10	16	11	80	47
10	37	35	16	13	12	16	69	43
10	35	31	16	9	14	11	78	46
10	37	34	16	12	17	11	81	48
10	32	36	14	10	15	10	76	46
10	38	36	16	14	17	10	76	45
10	37	35	16	11	12	16	73	45
10	36	37	20	15	16	12	85	52
10	32	28	15	11	11	11	66	42
10	33	39	16	11	15	16	79	47
10	40	32	13	12	9	19	68	41
10	38	35	17	12	16	11	76	47
10	41	39	16	12	15	16	71	43
10	36	35	16	11	10	15	54	33
10	43	42	12	7	10	24	46	30
10	30	34	16	12	15	14	85	52
10	31	33	16	14	11	15	74	44
10	32	41	17	11	13	11	88	55
10	32	33	13	11	14	15	38	11
10	37	34	12	10	18	12	76	47
10	37	32	18	13	16	10	86	53
10	33	40	14	13	14	14	54	33
10	34	40	14	8	14	13	67	44
10	33	35	13	11	14	9	69	42
10	38	36	16	12	14	15	90	55
10	33	37	13	11	12	15	54	33
10	31	27	16	13	14	14	76	46
10	38	39	13	12	15	11	89	54
10	37	38	16	14	15	8	76	47
10	36	31	15	13	15	11	73	45
10	31	33	16	15	13	11	79	47
10	39	32	15	10	17	8	90	55
10	44	39	17	11	17	10	74	44
10	33	36	15	9	19	11	81	53
10	35	33	12	11	15	13	72	44
10	32	33	16	10	13	11	71	42
10	28	32	10	11	9	20	66	40
10	40	37	16	8	15	10	77	46
10	27	30	12	11	15	15	65	40
10	37	38	14	12	15	12	74	46
10	32	29	15	12	16	14	85	53
10	28	22	13	9	11	23	54	33
10	34	35	15	11	14	14	63	42
10	30	35	11	10	11	16	54	35
10	35	34	12	8	15	11	64	40
10	31	35	11	9	13	12	69	41
10	32	34	16	8	15	10	54	33
10	30	37	15	9	16	14	84	51
10	30	35	17	15	14	12	86	53
10	31	23	16	11	15	12	77	46
10	40	31	10	8	16	11	89	55
10	32	27	18	13	16	12	76	47
10	36	36	13	12	11	13	60	38
10	32	31	16	12	12	11	75	46
10	35	32	13	9	9	19	73	46
10	38	39	10	7	16	12	85	53
10	42	37	15	13	13	17	79	47
10	34	38	16	9	16	9	71	41
10	35	39	16	6	12	12	72	44
9	38	34	14	8	9	19	69	43
10	33	31	10	8	13	18	78	51
10	36	32	17	15	13	15	54	33
10	32	37	13	6	14	14	69	43
10	33	36	15	9	19	11	81	53
10	34	32	16	11	13	9	84	51
10	32	38	12	8	12	18	84	50
10	34	36	13	8	13	16	69	46
11	27	26	13	10	10	24	66	43
11	31	26	12	8	14	14	81	47
11	38	33	17	14	16	20	82	50
11	34	39	15	10	10	18	72	43
11	24	30	10	8	11	23	54	33
11	30	33	14	11	14	12	78	48
11	26	25	11	12	12	14	74	44
11	34	38	13	12	9	16	82	50
11	27	37	16	12	9	18	73	41
11	37	31	12	5	11	20	55	34
11	36	37	16	12	16	12	72	44
11	41	35	12	10	9	12	78	47
11	29	25	9	7	13	17	59	35
11	36	28	12	12	16	13	72	44
11	32	35	15	11	13	9	78	44
11	37	33	12	8	9	16	68	43
11	30	30	12	9	12	18	69	41
11	31	31	14	10	16	10	67	41
11	38	37	12	9	11	14	74	42
11	36	36	16	12	14	11	54	33
11	35	30	11	6	13	9	67	41
11	31	36	19	15	15	11	70	44
11	38	32	15	12	14	10	80	48
11	22	28	8	12	16	11	89	55
11	32	36	16	12	13	19	76	44
11	36	34	17	11	14	14	74	43
11	39	31	12	7	15	12	87	52
11	28	28	11	7	13	14	54	30
11	32	36	11	5	11	21	61	39
11	32	36	14	12	11	13	38	11
11	38	40	16	12	14	10	75	44
11	32	33	12	3	15	15	69	42
11	35	37	16	11	11	16	62	41
11	32	32	13	10	15	14	72	44
11	37	38	15	12	12	12	70	44
11	34	31	16	9	14	19	79	48
11	33	37	16	12	14	15	87	53
11	33	33	14	9	8	19	62	37
11	26	32	16	12	13	13	77	44
11	30	30	16	12	9	17	69	44
11	24	30	14	10	15	12	69	40
11	34	31	11	9	17	11	75	42
11	34	32	12	12	13	14	54	35
11	33	34	15	8	15	11	72	43
11	34	36	15	11	15	13	74	45
11	35	37	16	11	14	12	85	55
11	35	36	16	12	16	15	52	31
11	36	33	11	10	13	14	70	44
11	34	33	15	10	16	12	84	50
11	34	33	12	12	9	17	64	40
11	41	44	12	12	16	11	84	53
11	32	39	15	11	11	18	87	54
11	30	32	15	8	10	13	79	49
11	35	35	16	12	11	17	67	40
11	28	25	14	10	15	13	65	41
11	33	35	17	11	17	11	85	52
11	39	34	14	10	14	12	83	52
11	36	35	13	8	8	22	61	36
11	36	39	15	12	15	14	82	52
11	35	33	13	12	11	12	76	46
11	38	36	14	10	16	12	58	31
11	33	32	15	12	10	17	72	44
11	31	32	12	9	15	9	72	44
11	34	36	13	9	9	21	38	11
11	32	36	8	6	16	10	78	46
11	31	32	14	10	19	11	54	33
11	33	34	14	9	12	12	63	34
11	34	33	11	9	8	23	66	42
11	34	35	12	9	11	13	70	43
11	34	30	13	6	14	12	71	43
11	33	38	10	10	9	16	67	44
11	32	34	16	6	15	9	58	36
11	41	33	18	14	13	17	72	46
11	34	32	13	10	16	9	72	44
11	36	31	11	10	11	14	70	43
11	37	30	4	6	12	17	76	50
11	36	27	13	12	13	13	50	33
11	29	31	16	12	10	11	72	43
11	37	30	10	7	11	12	72	44
11	27	32	12	8	12	10	88	53
11	35	35	12	11	8	19	53	34
11	28	28	10	3	12	16	58	35
11	35	33	13	6	12	16	66	40
11	37	31	15	10	15	14	82	53
11	29	35	12	8	11	20	69	42
11	32	35	14	9	13	15	68	43
11	36	32	10	9	14	23	44	29
11	19	21	12	8	10	20	56	36
11	21	20	12	9	12	16	53	30
11	31	34	11	7	15	14	70	42
11	33	32	10	7	13	17	78	47
11	36	34	12	6	13	11	71	44
11	33	32	16	9	13	13	72	45
11	37	33	12	10	12	17	68	44
11	34	33	14	11	12	15	67	43
11	35	37	16	12	9	21	75	43
11	31	32	14	8	9	18	62	40
11	37	34	13	11	15	15	67	41
11	35	30	4	3	10	8	83	52
11	27	30	15	11	14	12	64	38
11	34	38	11	12	15	12	68	41
11	40	36	11	7	7	22	62	39
11	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 time17 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 & 17 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203885&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]17 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203885&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203885&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 time17 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Multiple Linear Regression - Estimated Regression Equation
month[t] = + 8.202389225477 -0.00346693163550728Connected[t] + 0.00135187598274539Separate[t] + 0.00380978730223924Learning[t] + 0.0193143069526706Software[t] + 0.00794756559353216Happiness[t] + 0.0123799910288668Depression[t] + 0.0153970637046628Belonging[t] -0.0210621657447992Belonging_Final[t] + 0.00978204440805615t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
month[t] =  +  8.202389225477 -0.00346693163550728Connected[t] +  0.00135187598274539Separate[t] +  0.00380978730223924Learning[t] +  0.0193143069526706Software[t] +  0.00794756559353216Happiness[t] +  0.0123799910288668Depression[t] +  0.0153970637046628Belonging[t] -0.0210621657447992Belonging_Final[t] +  0.00978204440805615t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203885&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]month[t] =  +  8.202389225477 -0.00346693163550728Connected[t] +  0.00135187598274539Separate[t] +  0.00380978730223924Learning[t] +  0.0193143069526706Software[t] +  0.00794756559353216Happiness[t] +  0.0123799910288668Depression[t] +  0.0153970637046628Belonging[t] -0.0210621657447992Belonging_Final[t] +  0.00978204440805615t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203885&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203885&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
month[t] = + 8.202389225477 -0.00346693163550728Connected[t] + 0.00135187598274539Separate[t] + 0.00380978730223924Learning[t] + 0.0193143069526706Software[t] + 0.00794756559353216Happiness[t] + 0.0123799910288668Depression[t] + 0.0153970637046628Belonging[t] -0.0210621657447992Belonging_Final[t] + 0.00978204440805615t + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.2023892254770.30605426.800400
Connected-0.003466931635507280.005327-0.65080.5157390.25787
Separate0.001351875982745390.0054160.24960.80310.40155
Learning0.003809787302239240.0096260.39580.6926040.346302
Software0.01931430695267060.0098661.95760.0513730.025686
Happiness0.007947565593532160.0089280.89020.3741890.187094
Depression0.01237999102886680.0064761.91170.0570350.028517
Belonging0.01539706370466280.0057512.67720.0079090.003954
Belonging_Final-0.02106216574479920.008559-2.46070.0145320.007266
t0.009782044408056150.00026337.171300

\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) & 8.202389225477 & 0.306054 & 26.8004 & 0 & 0 \tabularnewline
Connected & -0.00346693163550728 & 0.005327 & -0.6508 & 0.515739 & 0.25787 \tabularnewline
Separate & 0.00135187598274539 & 0.005416 & 0.2496 & 0.8031 & 0.40155 \tabularnewline
Learning & 0.00380978730223924 & 0.009626 & 0.3958 & 0.692604 & 0.346302 \tabularnewline
Software & 0.0193143069526706 & 0.009866 & 1.9576 & 0.051373 & 0.025686 \tabularnewline
Happiness & 0.00794756559353216 & 0.008928 & 0.8902 & 0.374189 & 0.187094 \tabularnewline
Depression & 0.0123799910288668 & 0.006476 & 1.9117 & 0.057035 & 0.028517 \tabularnewline
Belonging & 0.0153970637046628 & 0.005751 & 2.6772 & 0.007909 & 0.003954 \tabularnewline
Belonging_Final & -0.0210621657447992 & 0.008559 & -2.4607 & 0.014532 & 0.007266 \tabularnewline
t & 0.00978204440805615 & 0.000263 & 37.1713 & 0 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203885&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]8.202389225477[/C][C]0.306054[/C][C]26.8004[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Connected[/C][C]-0.00346693163550728[/C][C]0.005327[/C][C]-0.6508[/C][C]0.515739[/C][C]0.25787[/C][/ROW]
[ROW][C]Separate[/C][C]0.00135187598274539[/C][C]0.005416[/C][C]0.2496[/C][C]0.8031[/C][C]0.40155[/C][/ROW]
[ROW][C]Learning[/C][C]0.00380978730223924[/C][C]0.009626[/C][C]0.3958[/C][C]0.692604[/C][C]0.346302[/C][/ROW]
[ROW][C]Software[/C][C]0.0193143069526706[/C][C]0.009866[/C][C]1.9576[/C][C]0.051373[/C][C]0.025686[/C][/ROW]
[ROW][C]Happiness[/C][C]0.00794756559353216[/C][C]0.008928[/C][C]0.8902[/C][C]0.374189[/C][C]0.187094[/C][/ROW]
[ROW][C]Depression[/C][C]0.0123799910288668[/C][C]0.006476[/C][C]1.9117[/C][C]0.057035[/C][C]0.028517[/C][/ROW]
[ROW][C]Belonging[/C][C]0.0153970637046628[/C][C]0.005751[/C][C]2.6772[/C][C]0.007909[/C][C]0.003954[/C][/ROW]
[ROW][C]Belonging_Final[/C][C]-0.0210621657447992[/C][C]0.008559[/C][C]-2.4607[/C][C]0.014532[/C][C]0.007266[/C][/ROW]
[ROW][C]t[/C][C]0.00978204440805615[/C][C]0.000263[/C][C]37.1713[/C][C]0[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203885&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203885&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)8.2023892254770.30605426.800400
Connected-0.003466931635507280.005327-0.65080.5157390.25787
Separate0.001351875982745390.0054160.24960.80310.40155
Learning0.003809787302239240.0096260.39580.6926040.346302
Software0.01931430695267060.0098661.95760.0513730.025686
Happiness0.007947565593532160.0089280.89020.3741890.187094
Depression0.01237999102886680.0064761.91170.0570350.028517
Belonging0.01539706370466280.0057512.67720.0079090.003954
Belonging_Final-0.02106216574479920.008559-2.46070.0145320.007266
t0.009782044408056150.00026337.171300







Multiple Linear Regression - Regression Statistics
Multiple R0.934688985442669
R-squared0.873643499507846
Adjusted R-squared0.86916630067151
F-TEST (value)195.131717719908
F-TEST (DF numerator)9
F-TEST (DF denominator)254
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.285468350828087
Sum Squared Residuals20.6990135484249

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.934688985442669 \tabularnewline
R-squared & 0.873643499507846 \tabularnewline
Adjusted R-squared & 0.86916630067151 \tabularnewline
F-TEST (value) & 195.131717719908 \tabularnewline
F-TEST (DF numerator) & 9 \tabularnewline
F-TEST (DF denominator) & 254 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.285468350828087 \tabularnewline
Sum Squared Residuals & 20.6990135484249 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203885&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.934688985442669[/C][/ROW]
[ROW][C]R-squared[/C][C]0.873643499507846[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.86916630067151[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]195.131717719908[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]9[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]254[/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]0.285468350828087[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]20.6990135484249[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203885&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203885&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 R0.934688985442669
R-squared0.873643499507846
Adjusted R-squared0.86916630067151
F-TEST (value)195.131717719908
F-TEST (DF numerator)9
F-TEST (DF denominator)254
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.285468350828087
Sum Squared Residuals20.6990135484249







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
198.804578161704140.195421838295862
298.886438901774760.113561098225244
398.929481971223820.0705180287761851
498.763672233233140.236327766766859
599.07632427428401-0.0763242742840104
698.924278844626140.0757211553738652
798.902088964922390.0979110350776093
898.986149341888860.0138506581111349
998.932641101151470.0673588988485339
1098.914688477322810.0853115226771949
1198.91748657019590.0825134298040989
1298.92008992815810.0799100718419024
1398.950024168595590.0499758314044142
1498.96578366843860.0342163315613968
1599.12931739621936-0.129317396219364
1699.00086804483716-0.00086804483716005
1799.02899246409117-0.0289924640911752
1899.09493451169265-0.0949345116926459
1998.942371680869070.0576283191309349
2099.03057221024241-0.0305722102424131
2199.02821973088454-0.0282197308845436
2299.02576389256539-0.0257638925653906
2399.06322493067837-0.0632249306783694
2498.986645053828920.0133549461710757
2599.15173147719061-0.151731477190614
2699.09848190497035-0.098481904970355
2799.17095487671694-0.170954876716937
2899.17207212975641-0.172072129756413
2999.25470682579222-0.254706825792217
3099.02229796164546-0.0222979616454594
3199.16728431349094-0.167284313490941
3299.09070761569453-0.0907076156945306
3399.13173538903566-0.131735389035658
3499.17124053756616-0.171240537566156
3599.27952764384568-0.27952764384568
3699.05416814893982-0.0541681489398204
3799.22746143396222-0.227461433962217
3899.23430975945295-0.234309759452947
3999.23958150446145-0.239581504461448
4099.17594466569438-0.17594466569438
4199.19475493229579-0.19475493229579
4299.3536054370813-0.353605437081304
4399.26303506285771-0.263035062857705
4499.21895940745758-0.218959407457585
4599.22835026052586-0.228350260525865
4699.29795860791581-0.29795860791581
4799.213317503389-0.213317503389004
4899.31440012132773-0.314400121327731
4999.45726535663955-0.457265356639552
5099.33459735420898-0.334597354208983
5199.40587411321892-0.405874113218915
5299.36085252473413-0.360852524734133
5399.43297474614191-0.432974746141905
5499.23060680942451-0.230606809424511
5599.24690724253612-0.246907242536124
5699.3174241705282-0.317424170528202
5799.44313367513351-0.443133675133505
5899.38552455748939-0.385524557489393
5999.40700831725542-0.40700831725542
6099.42122471734891-0.421224717348914
6199.36709152695479-0.367091526954795
6299.50547933211382-0.505479332113818
6399.53621915564452-0.536219155644517
6499.46638121226596-0.466381212265963
6599.47152620987806-0.471526209878057
66109.507907867181040.492092132818961
67109.548747102358060.451252897641945
68109.585462029985820.414537970014183
69109.523510208586470.476489791413534
70109.578857211074920.421142788925081
71109.383524617448270.616475382551733
72109.565638113614310.434361886385693
73109.70663399536820.293366004631803
74109.651844653615560.348155346384446
75109.627139130261140.372860869738863
76109.620075284447670.37992471555233
77109.657562003731030.342437996268971
78109.612275445535670.38772455446433
79109.677109204277220.322890795722775
80109.537033481858860.462966518141135
81109.724623687832640.275376312167363
82109.601949419002190.398050580997813
83109.713586306485060.286413693514936
84109.678333783057740.321666216942263
85109.683319994955870.31668000504413
86109.678926277165010.321073722834991
87109.715322653683390.284677346316614
88109.72406461629430.2759353837057
89109.792226928308320.20777307169168
90109.694686611726010.305313388273991
91109.790894936230170.209105063769832
92109.826017547612380.173982452387625
93109.876489615346940.12351038465306
94109.843127127192310.156872872807695
95109.804424569380430.195575430619566
96109.822722176932880.177277823067118
97109.786155605020590.213844394979413
98109.878911891368860.121088108631137
99109.799348048160480.20065195183952
100109.910162602102520.0898373978974834
101109.852467708396870.147532291603126
102109.980516715926590.0194832840734114
103109.761653066772960.238346933227042
104109.975189819613030.0248101803869714
105109.905585028982180.0944149710178194
106109.894992259910740.105007740089257
107109.95718696004770.0428130399522962
108109.856335607221840.143664392778159
109109.810245791897820.189754208102179
1101010.0191493794531-0.019149379453078
1111010.0424605840101-0.0424605840100637
112109.955707806832890.0442921931671116
1131010.153785331417-0.153785331417049
114109.945961242627350.0540387573726526
1151010.0207837090744-0.0207837090743946
1161010.0021714479527-0.00217144795266387
117109.868013039900820.131986960099182
118109.952034264369880.0479657356301161
1191010.1003873247313-0.100387324731267
120109.991290456270870.00870954372912571
1211010.1129879669129-0.112987966912939
1221010.0864524275152-0.0864524275151553
1231010.0585408623544-0.0585408623544101
1241010.0722757257261-0.0722757257260563
1251010.178897501036-0.178897501036034
1261010.0547315583921-0.0547315583921199
1271010.0936667440349-0.0936667440349265
1281010.0377762964209-0.0377762964208847
1291010.1077237396531-0.107723739653146
1301010.1099035757641-0.109903575764148
1311010.1734257237227-0.17342572372268
1321010.0801599609288-0.0801599609288204
1331010.1717609415255-0.171760941525484
1341010.1596831647841-0.159683164784149
1351010.2330828590162-0.233082859016234
1361010.1973234339682-0.197323433968189
1371010.1115633240083-0.111563324008279
1381010.1104385109455-0.110438510945503
1391010.0852653101426-0.0852653101426025
1401010.1781794893462-0.178179489346182
1411010.1115538752123-0.111553875212293
1421010.2880903879325-0.288090387932529
1431010.3666887793705-0.366688779370525
1441010.2925235177024-0.292523517702369
1451010.1918893878988-0.191889387898802
1461010.3317647034678-0.331764703467846
1471010.2173312972045-0.217331297204509
1481010.2912972632949-0.291297263294932
1491010.2670612100555-0.267061210055494
1501010.2321502418192-0.232150241819204
1511010.4323434565515-0.432343456551516
1521010.3257646428991-0.325764642899088
1531010.2330489879791-0.233048987979107
154910.2943681119201-1.29436811192006
1551010.2916765560773-0.291676556077292
1561010.4267278227538-0.426727822753818
1571010.2839709345213-0.283970934521254
1581010.3312376286626-0.331237628662569
1591010.3904537856964-0.390453785696377
1601010.466633398616-0.46663339861602
1611010.3070679060349-0.307067906034863
1621110.45842086354010.541579136459895
1631110.46659442487480.533405575125243
1641110.63889150177120.36110849822877
1651110.50679487375070.493205126249333
1661110.48472383175450.515276168245522
1671110.49220182256770.507798177432324
1681110.5444467897330.455553210267034
1691110.54940814388280.450591856117224
1701110.66928209608230.330717903917683
1711110.39678739713560.603212602864361
1721110.56041325222130.439586747778672
1731110.46985204921090.530147950789087
1741110.49223822672030.507761773279667
1751110.57473334342070.425266656579302
1761110.6189810225360.381018977464039
1771110.46131357756240.538686422437629
1781110.6167468964560.383253103543997
1791110.55330397350230.446696026497684
1801110.61649428713680.383505712863209
1811110.5733613302040.426638669795982
1821110.44252122667480.557478773325154
1831110.70224912163770.297750878362258
1841110.65856748804430.341432511955671
1851110.71115795891810.288842041081853
1861110.83428321973350.16571678026648
1871110.74830491476830.251695085231703
1881110.64111429199290.358885708007061
1891110.64529656414350.354703435856521
1901110.60238203621060.397617963789422
1911110.89536183861020.104638161389755
1921110.75871198292890.241288017071137
1931110.61035404348720.389645956512759
1941110.6787688502170.321231149783024
1951110.75926306088710.240736939112936
1961110.72667308527620.27332691472378
1971110.84013963790770.159860362092292
1981110.88778850750360.112211492496405
1991110.78050318237270.219496817627329
2001110.92774304485980.0722569551401695
2011110.81550680286440.184493197135597
2021110.86987634997170.130123650028261
2031110.86937047604470.130629523955345
2041110.77170363772390.228296362276145
2051110.80923347865490.190766521345055
2061110.88962504222850.110374957771542
2071110.83952030496690.160479695033109
2081110.91768876023980.0823112397601546
2091110.82938699883970.170613001160302
2101110.94961066784710.0503893321529274
2111110.89553934359810.104460656401903
2121110.91140963476020.0885903652398076
2131111.0098008735317-0.00980087353172996
2141110.87139752682240.128602473177601
2151111.0112298130703-0.011229813070315
2161110.91592743569420.0840725643058146
2171111.0200298506413-0.0200298506413429
2181110.93465792723320.0653420727668339
2191110.98812800846460.01187199153541
2201111.0311310760237-0.0311310760237108
2211111.0060895893753-0.00608958937527957
2221111.0532308076777-0.0532308076776667
2231111.0733437063059-0.0733437063058886
2241110.9613852309570.0386147690430435
2251111.2424095740968-0.242409574096759
2261110.98029342936240.0197065706376484
2271111.028752166679-0.0287521666789969
2281111.0892482323002-0.0892482323001662
2291111.0648656112823-0.064865611282253
2301111.0217300705238-0.0217300705238197
2311110.99747937091880.00252062908123112
2321111.0145029363126-0.014502936312616
2331110.95889511340350.0411048865964949
2341111.1863389587963-0.18633895879625
2351111.0896585843875-0.0896585843874941
2361111.0959654804495-0.0959654804494586
2371110.98703773900740.0129622609925799
2381111.0625657773573-0.0625657773573427
2391111.1929642742679-0.192964274267908
2401111.05349412191-0.0534941219099727
2411111.167564227303-0.167564227302952
2421111.1525229438069-0.152522943806857
2431111.0655497896244-0.0655497896244464
2441111.1450606561757-0.145060656175714
2451111.2017094670775-0.201709467077504
2461111.2685881715198-0.268588171519788
2471111.2124392491717-0.212439249171739
2481111.2213870752203-0.221387075220322
2491111.2319409580552-0.23194095805524
2501111.2993085405886-0.299308540588611
2511111.258995939957-0.25899593995699
2521111.2944411046391-0.294441104639144
2531111.1659584788865-0.165958478886534
2541111.2757145163202-0.275714516320187
2551111.2781021773608-0.278102177360756
2561111.3061240182149-0.306124018214886
2571111.5183942755055-0.518394275505473
2581111.2762925601139-0.276292560113851
2591111.3885784734832-0.388578473483234
2601111.0993557668019-0.0993557668018904
2611111.4169317167682-0.416931716768193
2621111.4236847285112-0.42368472851116
2631111.3233512311794-0.323351231179362
2641111.4174750183926-0.417475018392563

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 9 & 8.80457816170414 & 0.195421838295862 \tabularnewline
2 & 9 & 8.88643890177476 & 0.113561098225244 \tabularnewline
3 & 9 & 8.92948197122382 & 0.0705180287761851 \tabularnewline
4 & 9 & 8.76367223323314 & 0.236327766766859 \tabularnewline
5 & 9 & 9.07632427428401 & -0.0763242742840104 \tabularnewline
6 & 9 & 8.92427884462614 & 0.0757211553738652 \tabularnewline
7 & 9 & 8.90208896492239 & 0.0979110350776093 \tabularnewline
8 & 9 & 8.98614934188886 & 0.0138506581111349 \tabularnewline
9 & 9 & 8.93264110115147 & 0.0673588988485339 \tabularnewline
10 & 9 & 8.91468847732281 & 0.0853115226771949 \tabularnewline
11 & 9 & 8.9174865701959 & 0.0825134298040989 \tabularnewline
12 & 9 & 8.9200899281581 & 0.0799100718419024 \tabularnewline
13 & 9 & 8.95002416859559 & 0.0499758314044142 \tabularnewline
14 & 9 & 8.9657836684386 & 0.0342163315613968 \tabularnewline
15 & 9 & 9.12931739621936 & -0.129317396219364 \tabularnewline
16 & 9 & 9.00086804483716 & -0.00086804483716005 \tabularnewline
17 & 9 & 9.02899246409117 & -0.0289924640911752 \tabularnewline
18 & 9 & 9.09493451169265 & -0.0949345116926459 \tabularnewline
19 & 9 & 8.94237168086907 & 0.0576283191309349 \tabularnewline
20 & 9 & 9.03057221024241 & -0.0305722102424131 \tabularnewline
21 & 9 & 9.02821973088454 & -0.0282197308845436 \tabularnewline
22 & 9 & 9.02576389256539 & -0.0257638925653906 \tabularnewline
23 & 9 & 9.06322493067837 & -0.0632249306783694 \tabularnewline
24 & 9 & 8.98664505382892 & 0.0133549461710757 \tabularnewline
25 & 9 & 9.15173147719061 & -0.151731477190614 \tabularnewline
26 & 9 & 9.09848190497035 & -0.098481904970355 \tabularnewline
27 & 9 & 9.17095487671694 & -0.170954876716937 \tabularnewline
28 & 9 & 9.17207212975641 & -0.172072129756413 \tabularnewline
29 & 9 & 9.25470682579222 & -0.254706825792217 \tabularnewline
30 & 9 & 9.02229796164546 & -0.0222979616454594 \tabularnewline
31 & 9 & 9.16728431349094 & -0.167284313490941 \tabularnewline
32 & 9 & 9.09070761569453 & -0.0907076156945306 \tabularnewline
33 & 9 & 9.13173538903566 & -0.131735389035658 \tabularnewline
34 & 9 & 9.17124053756616 & -0.171240537566156 \tabularnewline
35 & 9 & 9.27952764384568 & -0.27952764384568 \tabularnewline
36 & 9 & 9.05416814893982 & -0.0541681489398204 \tabularnewline
37 & 9 & 9.22746143396222 & -0.227461433962217 \tabularnewline
38 & 9 & 9.23430975945295 & -0.234309759452947 \tabularnewline
39 & 9 & 9.23958150446145 & -0.239581504461448 \tabularnewline
40 & 9 & 9.17594466569438 & -0.17594466569438 \tabularnewline
41 & 9 & 9.19475493229579 & -0.19475493229579 \tabularnewline
42 & 9 & 9.3536054370813 & -0.353605437081304 \tabularnewline
43 & 9 & 9.26303506285771 & -0.263035062857705 \tabularnewline
44 & 9 & 9.21895940745758 & -0.218959407457585 \tabularnewline
45 & 9 & 9.22835026052586 & -0.228350260525865 \tabularnewline
46 & 9 & 9.29795860791581 & -0.29795860791581 \tabularnewline
47 & 9 & 9.213317503389 & -0.213317503389004 \tabularnewline
48 & 9 & 9.31440012132773 & -0.314400121327731 \tabularnewline
49 & 9 & 9.45726535663955 & -0.457265356639552 \tabularnewline
50 & 9 & 9.33459735420898 & -0.334597354208983 \tabularnewline
51 & 9 & 9.40587411321892 & -0.405874113218915 \tabularnewline
52 & 9 & 9.36085252473413 & -0.360852524734133 \tabularnewline
53 & 9 & 9.43297474614191 & -0.432974746141905 \tabularnewline
54 & 9 & 9.23060680942451 & -0.230606809424511 \tabularnewline
55 & 9 & 9.24690724253612 & -0.246907242536124 \tabularnewline
56 & 9 & 9.3174241705282 & -0.317424170528202 \tabularnewline
57 & 9 & 9.44313367513351 & -0.443133675133505 \tabularnewline
58 & 9 & 9.38552455748939 & -0.385524557489393 \tabularnewline
59 & 9 & 9.40700831725542 & -0.40700831725542 \tabularnewline
60 & 9 & 9.42122471734891 & -0.421224717348914 \tabularnewline
61 & 9 & 9.36709152695479 & -0.367091526954795 \tabularnewline
62 & 9 & 9.50547933211382 & -0.505479332113818 \tabularnewline
63 & 9 & 9.53621915564452 & -0.536219155644517 \tabularnewline
64 & 9 & 9.46638121226596 & -0.466381212265963 \tabularnewline
65 & 9 & 9.47152620987806 & -0.471526209878057 \tabularnewline
66 & 10 & 9.50790786718104 & 0.492092132818961 \tabularnewline
67 & 10 & 9.54874710235806 & 0.451252897641945 \tabularnewline
68 & 10 & 9.58546202998582 & 0.414537970014183 \tabularnewline
69 & 10 & 9.52351020858647 & 0.476489791413534 \tabularnewline
70 & 10 & 9.57885721107492 & 0.421142788925081 \tabularnewline
71 & 10 & 9.38352461744827 & 0.616475382551733 \tabularnewline
72 & 10 & 9.56563811361431 & 0.434361886385693 \tabularnewline
73 & 10 & 9.7066339953682 & 0.293366004631803 \tabularnewline
74 & 10 & 9.65184465361556 & 0.348155346384446 \tabularnewline
75 & 10 & 9.62713913026114 & 0.372860869738863 \tabularnewline
76 & 10 & 9.62007528444767 & 0.37992471555233 \tabularnewline
77 & 10 & 9.65756200373103 & 0.342437996268971 \tabularnewline
78 & 10 & 9.61227544553567 & 0.38772455446433 \tabularnewline
79 & 10 & 9.67710920427722 & 0.322890795722775 \tabularnewline
80 & 10 & 9.53703348185886 & 0.462966518141135 \tabularnewline
81 & 10 & 9.72462368783264 & 0.275376312167363 \tabularnewline
82 & 10 & 9.60194941900219 & 0.398050580997813 \tabularnewline
83 & 10 & 9.71358630648506 & 0.286413693514936 \tabularnewline
84 & 10 & 9.67833378305774 & 0.321666216942263 \tabularnewline
85 & 10 & 9.68331999495587 & 0.31668000504413 \tabularnewline
86 & 10 & 9.67892627716501 & 0.321073722834991 \tabularnewline
87 & 10 & 9.71532265368339 & 0.284677346316614 \tabularnewline
88 & 10 & 9.7240646162943 & 0.2759353837057 \tabularnewline
89 & 10 & 9.79222692830832 & 0.20777307169168 \tabularnewline
90 & 10 & 9.69468661172601 & 0.305313388273991 \tabularnewline
91 & 10 & 9.79089493623017 & 0.209105063769832 \tabularnewline
92 & 10 & 9.82601754761238 & 0.173982452387625 \tabularnewline
93 & 10 & 9.87648961534694 & 0.12351038465306 \tabularnewline
94 & 10 & 9.84312712719231 & 0.156872872807695 \tabularnewline
95 & 10 & 9.80442456938043 & 0.195575430619566 \tabularnewline
96 & 10 & 9.82272217693288 & 0.177277823067118 \tabularnewline
97 & 10 & 9.78615560502059 & 0.213844394979413 \tabularnewline
98 & 10 & 9.87891189136886 & 0.121088108631137 \tabularnewline
99 & 10 & 9.79934804816048 & 0.20065195183952 \tabularnewline
100 & 10 & 9.91016260210252 & 0.0898373978974834 \tabularnewline
101 & 10 & 9.85246770839687 & 0.147532291603126 \tabularnewline
102 & 10 & 9.98051671592659 & 0.0194832840734114 \tabularnewline
103 & 10 & 9.76165306677296 & 0.238346933227042 \tabularnewline
104 & 10 & 9.97518981961303 & 0.0248101803869714 \tabularnewline
105 & 10 & 9.90558502898218 & 0.0944149710178194 \tabularnewline
106 & 10 & 9.89499225991074 & 0.105007740089257 \tabularnewline
107 & 10 & 9.9571869600477 & 0.0428130399522962 \tabularnewline
108 & 10 & 9.85633560722184 & 0.143664392778159 \tabularnewline
109 & 10 & 9.81024579189782 & 0.189754208102179 \tabularnewline
110 & 10 & 10.0191493794531 & -0.019149379453078 \tabularnewline
111 & 10 & 10.0424605840101 & -0.0424605840100637 \tabularnewline
112 & 10 & 9.95570780683289 & 0.0442921931671116 \tabularnewline
113 & 10 & 10.153785331417 & -0.153785331417049 \tabularnewline
114 & 10 & 9.94596124262735 & 0.0540387573726526 \tabularnewline
115 & 10 & 10.0207837090744 & -0.0207837090743946 \tabularnewline
116 & 10 & 10.0021714479527 & -0.00217144795266387 \tabularnewline
117 & 10 & 9.86801303990082 & 0.131986960099182 \tabularnewline
118 & 10 & 9.95203426436988 & 0.0479657356301161 \tabularnewline
119 & 10 & 10.1003873247313 & -0.100387324731267 \tabularnewline
120 & 10 & 9.99129045627087 & 0.00870954372912571 \tabularnewline
121 & 10 & 10.1129879669129 & -0.112987966912939 \tabularnewline
122 & 10 & 10.0864524275152 & -0.0864524275151553 \tabularnewline
123 & 10 & 10.0585408623544 & -0.0585408623544101 \tabularnewline
124 & 10 & 10.0722757257261 & -0.0722757257260563 \tabularnewline
125 & 10 & 10.178897501036 & -0.178897501036034 \tabularnewline
126 & 10 & 10.0547315583921 & -0.0547315583921199 \tabularnewline
127 & 10 & 10.0936667440349 & -0.0936667440349265 \tabularnewline
128 & 10 & 10.0377762964209 & -0.0377762964208847 \tabularnewline
129 & 10 & 10.1077237396531 & -0.107723739653146 \tabularnewline
130 & 10 & 10.1099035757641 & -0.109903575764148 \tabularnewline
131 & 10 & 10.1734257237227 & -0.17342572372268 \tabularnewline
132 & 10 & 10.0801599609288 & -0.0801599609288204 \tabularnewline
133 & 10 & 10.1717609415255 & -0.171760941525484 \tabularnewline
134 & 10 & 10.1596831647841 & -0.159683164784149 \tabularnewline
135 & 10 & 10.2330828590162 & -0.233082859016234 \tabularnewline
136 & 10 & 10.1973234339682 & -0.197323433968189 \tabularnewline
137 & 10 & 10.1115633240083 & -0.111563324008279 \tabularnewline
138 & 10 & 10.1104385109455 & -0.110438510945503 \tabularnewline
139 & 10 & 10.0852653101426 & -0.0852653101426025 \tabularnewline
140 & 10 & 10.1781794893462 & -0.178179489346182 \tabularnewline
141 & 10 & 10.1115538752123 & -0.111553875212293 \tabularnewline
142 & 10 & 10.2880903879325 & -0.288090387932529 \tabularnewline
143 & 10 & 10.3666887793705 & -0.366688779370525 \tabularnewline
144 & 10 & 10.2925235177024 & -0.292523517702369 \tabularnewline
145 & 10 & 10.1918893878988 & -0.191889387898802 \tabularnewline
146 & 10 & 10.3317647034678 & -0.331764703467846 \tabularnewline
147 & 10 & 10.2173312972045 & -0.217331297204509 \tabularnewline
148 & 10 & 10.2912972632949 & -0.291297263294932 \tabularnewline
149 & 10 & 10.2670612100555 & -0.267061210055494 \tabularnewline
150 & 10 & 10.2321502418192 & -0.232150241819204 \tabularnewline
151 & 10 & 10.4323434565515 & -0.432343456551516 \tabularnewline
152 & 10 & 10.3257646428991 & -0.325764642899088 \tabularnewline
153 & 10 & 10.2330489879791 & -0.233048987979107 \tabularnewline
154 & 9 & 10.2943681119201 & -1.29436811192006 \tabularnewline
155 & 10 & 10.2916765560773 & -0.291676556077292 \tabularnewline
156 & 10 & 10.4267278227538 & -0.426727822753818 \tabularnewline
157 & 10 & 10.2839709345213 & -0.283970934521254 \tabularnewline
158 & 10 & 10.3312376286626 & -0.331237628662569 \tabularnewline
159 & 10 & 10.3904537856964 & -0.390453785696377 \tabularnewline
160 & 10 & 10.466633398616 & -0.46663339861602 \tabularnewline
161 & 10 & 10.3070679060349 & -0.307067906034863 \tabularnewline
162 & 11 & 10.4584208635401 & 0.541579136459895 \tabularnewline
163 & 11 & 10.4665944248748 & 0.533405575125243 \tabularnewline
164 & 11 & 10.6388915017712 & 0.36110849822877 \tabularnewline
165 & 11 & 10.5067948737507 & 0.493205126249333 \tabularnewline
166 & 11 & 10.4847238317545 & 0.515276168245522 \tabularnewline
167 & 11 & 10.4922018225677 & 0.507798177432324 \tabularnewline
168 & 11 & 10.544446789733 & 0.455553210267034 \tabularnewline
169 & 11 & 10.5494081438828 & 0.450591856117224 \tabularnewline
170 & 11 & 10.6692820960823 & 0.330717903917683 \tabularnewline
171 & 11 & 10.3967873971356 & 0.603212602864361 \tabularnewline
172 & 11 & 10.5604132522213 & 0.439586747778672 \tabularnewline
173 & 11 & 10.4698520492109 & 0.530147950789087 \tabularnewline
174 & 11 & 10.4922382267203 & 0.507761773279667 \tabularnewline
175 & 11 & 10.5747333434207 & 0.425266656579302 \tabularnewline
176 & 11 & 10.618981022536 & 0.381018977464039 \tabularnewline
177 & 11 & 10.4613135775624 & 0.538686422437629 \tabularnewline
178 & 11 & 10.616746896456 & 0.383253103543997 \tabularnewline
179 & 11 & 10.5533039735023 & 0.446696026497684 \tabularnewline
180 & 11 & 10.6164942871368 & 0.383505712863209 \tabularnewline
181 & 11 & 10.573361330204 & 0.426638669795982 \tabularnewline
182 & 11 & 10.4425212266748 & 0.557478773325154 \tabularnewline
183 & 11 & 10.7022491216377 & 0.297750878362258 \tabularnewline
184 & 11 & 10.6585674880443 & 0.341432511955671 \tabularnewline
185 & 11 & 10.7111579589181 & 0.288842041081853 \tabularnewline
186 & 11 & 10.8342832197335 & 0.16571678026648 \tabularnewline
187 & 11 & 10.7483049147683 & 0.251695085231703 \tabularnewline
188 & 11 & 10.6411142919929 & 0.358885708007061 \tabularnewline
189 & 11 & 10.6452965641435 & 0.354703435856521 \tabularnewline
190 & 11 & 10.6023820362106 & 0.397617963789422 \tabularnewline
191 & 11 & 10.8953618386102 & 0.104638161389755 \tabularnewline
192 & 11 & 10.7587119829289 & 0.241288017071137 \tabularnewline
193 & 11 & 10.6103540434872 & 0.389645956512759 \tabularnewline
194 & 11 & 10.678768850217 & 0.321231149783024 \tabularnewline
195 & 11 & 10.7592630608871 & 0.240736939112936 \tabularnewline
196 & 11 & 10.7266730852762 & 0.27332691472378 \tabularnewline
197 & 11 & 10.8401396379077 & 0.159860362092292 \tabularnewline
198 & 11 & 10.8877885075036 & 0.112211492496405 \tabularnewline
199 & 11 & 10.7805031823727 & 0.219496817627329 \tabularnewline
200 & 11 & 10.9277430448598 & 0.0722569551401695 \tabularnewline
201 & 11 & 10.8155068028644 & 0.184493197135597 \tabularnewline
202 & 11 & 10.8698763499717 & 0.130123650028261 \tabularnewline
203 & 11 & 10.8693704760447 & 0.130629523955345 \tabularnewline
204 & 11 & 10.7717036377239 & 0.228296362276145 \tabularnewline
205 & 11 & 10.8092334786549 & 0.190766521345055 \tabularnewline
206 & 11 & 10.8896250422285 & 0.110374957771542 \tabularnewline
207 & 11 & 10.8395203049669 & 0.160479695033109 \tabularnewline
208 & 11 & 10.9176887602398 & 0.0823112397601546 \tabularnewline
209 & 11 & 10.8293869988397 & 0.170613001160302 \tabularnewline
210 & 11 & 10.9496106678471 & 0.0503893321529274 \tabularnewline
211 & 11 & 10.8955393435981 & 0.104460656401903 \tabularnewline
212 & 11 & 10.9114096347602 & 0.0885903652398076 \tabularnewline
213 & 11 & 11.0098008735317 & -0.00980087353172996 \tabularnewline
214 & 11 & 10.8713975268224 & 0.128602473177601 \tabularnewline
215 & 11 & 11.0112298130703 & -0.011229813070315 \tabularnewline
216 & 11 & 10.9159274356942 & 0.0840725643058146 \tabularnewline
217 & 11 & 11.0200298506413 & -0.0200298506413429 \tabularnewline
218 & 11 & 10.9346579272332 & 0.0653420727668339 \tabularnewline
219 & 11 & 10.9881280084646 & 0.01187199153541 \tabularnewline
220 & 11 & 11.0311310760237 & -0.0311310760237108 \tabularnewline
221 & 11 & 11.0060895893753 & -0.00608958937527957 \tabularnewline
222 & 11 & 11.0532308076777 & -0.0532308076776667 \tabularnewline
223 & 11 & 11.0733437063059 & -0.0733437063058886 \tabularnewline
224 & 11 & 10.961385230957 & 0.0386147690430435 \tabularnewline
225 & 11 & 11.2424095740968 & -0.242409574096759 \tabularnewline
226 & 11 & 10.9802934293624 & 0.0197065706376484 \tabularnewline
227 & 11 & 11.028752166679 & -0.0287521666789969 \tabularnewline
228 & 11 & 11.0892482323002 & -0.0892482323001662 \tabularnewline
229 & 11 & 11.0648656112823 & -0.064865611282253 \tabularnewline
230 & 11 & 11.0217300705238 & -0.0217300705238197 \tabularnewline
231 & 11 & 10.9974793709188 & 0.00252062908123112 \tabularnewline
232 & 11 & 11.0145029363126 & -0.014502936312616 \tabularnewline
233 & 11 & 10.9588951134035 & 0.0411048865964949 \tabularnewline
234 & 11 & 11.1863389587963 & -0.18633895879625 \tabularnewline
235 & 11 & 11.0896585843875 & -0.0896585843874941 \tabularnewline
236 & 11 & 11.0959654804495 & -0.0959654804494586 \tabularnewline
237 & 11 & 10.9870377390074 & 0.0129622609925799 \tabularnewline
238 & 11 & 11.0625657773573 & -0.0625657773573427 \tabularnewline
239 & 11 & 11.1929642742679 & -0.192964274267908 \tabularnewline
240 & 11 & 11.05349412191 & -0.0534941219099727 \tabularnewline
241 & 11 & 11.167564227303 & -0.167564227302952 \tabularnewline
242 & 11 & 11.1525229438069 & -0.152522943806857 \tabularnewline
243 & 11 & 11.0655497896244 & -0.0655497896244464 \tabularnewline
244 & 11 & 11.1450606561757 & -0.145060656175714 \tabularnewline
245 & 11 & 11.2017094670775 & -0.201709467077504 \tabularnewline
246 & 11 & 11.2685881715198 & -0.268588171519788 \tabularnewline
247 & 11 & 11.2124392491717 & -0.212439249171739 \tabularnewline
248 & 11 & 11.2213870752203 & -0.221387075220322 \tabularnewline
249 & 11 & 11.2319409580552 & -0.23194095805524 \tabularnewline
250 & 11 & 11.2993085405886 & -0.299308540588611 \tabularnewline
251 & 11 & 11.258995939957 & -0.25899593995699 \tabularnewline
252 & 11 & 11.2944411046391 & -0.294441104639144 \tabularnewline
253 & 11 & 11.1659584788865 & -0.165958478886534 \tabularnewline
254 & 11 & 11.2757145163202 & -0.275714516320187 \tabularnewline
255 & 11 & 11.2781021773608 & -0.278102177360756 \tabularnewline
256 & 11 & 11.3061240182149 & -0.306124018214886 \tabularnewline
257 & 11 & 11.5183942755055 & -0.518394275505473 \tabularnewline
258 & 11 & 11.2762925601139 & -0.276292560113851 \tabularnewline
259 & 11 & 11.3885784734832 & -0.388578473483234 \tabularnewline
260 & 11 & 11.0993557668019 & -0.0993557668018904 \tabularnewline
261 & 11 & 11.4169317167682 & -0.416931716768193 \tabularnewline
262 & 11 & 11.4236847285112 & -0.42368472851116 \tabularnewline
263 & 11 & 11.3233512311794 & -0.323351231179362 \tabularnewline
264 & 11 & 11.4174750183926 & -0.417475018392563 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203885&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]9[/C][C]8.80457816170414[/C][C]0.195421838295862[/C][/ROW]
[ROW][C]2[/C][C]9[/C][C]8.88643890177476[/C][C]0.113561098225244[/C][/ROW]
[ROW][C]3[/C][C]9[/C][C]8.92948197122382[/C][C]0.0705180287761851[/C][/ROW]
[ROW][C]4[/C][C]9[/C][C]8.76367223323314[/C][C]0.236327766766859[/C][/ROW]
[ROW][C]5[/C][C]9[/C][C]9.07632427428401[/C][C]-0.0763242742840104[/C][/ROW]
[ROW][C]6[/C][C]9[/C][C]8.92427884462614[/C][C]0.0757211553738652[/C][/ROW]
[ROW][C]7[/C][C]9[/C][C]8.90208896492239[/C][C]0.0979110350776093[/C][/ROW]
[ROW][C]8[/C][C]9[/C][C]8.98614934188886[/C][C]0.0138506581111349[/C][/ROW]
[ROW][C]9[/C][C]9[/C][C]8.93264110115147[/C][C]0.0673588988485339[/C][/ROW]
[ROW][C]10[/C][C]9[/C][C]8.91468847732281[/C][C]0.0853115226771949[/C][/ROW]
[ROW][C]11[/C][C]9[/C][C]8.9174865701959[/C][C]0.0825134298040989[/C][/ROW]
[ROW][C]12[/C][C]9[/C][C]8.9200899281581[/C][C]0.0799100718419024[/C][/ROW]
[ROW][C]13[/C][C]9[/C][C]8.95002416859559[/C][C]0.0499758314044142[/C][/ROW]
[ROW][C]14[/C][C]9[/C][C]8.9657836684386[/C][C]0.0342163315613968[/C][/ROW]
[ROW][C]15[/C][C]9[/C][C]9.12931739621936[/C][C]-0.129317396219364[/C][/ROW]
[ROW][C]16[/C][C]9[/C][C]9.00086804483716[/C][C]-0.00086804483716005[/C][/ROW]
[ROW][C]17[/C][C]9[/C][C]9.02899246409117[/C][C]-0.0289924640911752[/C][/ROW]
[ROW][C]18[/C][C]9[/C][C]9.09493451169265[/C][C]-0.0949345116926459[/C][/ROW]
[ROW][C]19[/C][C]9[/C][C]8.94237168086907[/C][C]0.0576283191309349[/C][/ROW]
[ROW][C]20[/C][C]9[/C][C]9.03057221024241[/C][C]-0.0305722102424131[/C][/ROW]
[ROW][C]21[/C][C]9[/C][C]9.02821973088454[/C][C]-0.0282197308845436[/C][/ROW]
[ROW][C]22[/C][C]9[/C][C]9.02576389256539[/C][C]-0.0257638925653906[/C][/ROW]
[ROW][C]23[/C][C]9[/C][C]9.06322493067837[/C][C]-0.0632249306783694[/C][/ROW]
[ROW][C]24[/C][C]9[/C][C]8.98664505382892[/C][C]0.0133549461710757[/C][/ROW]
[ROW][C]25[/C][C]9[/C][C]9.15173147719061[/C][C]-0.151731477190614[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]9.09848190497035[/C][C]-0.098481904970355[/C][/ROW]
[ROW][C]27[/C][C]9[/C][C]9.17095487671694[/C][C]-0.170954876716937[/C][/ROW]
[ROW][C]28[/C][C]9[/C][C]9.17207212975641[/C][C]-0.172072129756413[/C][/ROW]
[ROW][C]29[/C][C]9[/C][C]9.25470682579222[/C][C]-0.254706825792217[/C][/ROW]
[ROW][C]30[/C][C]9[/C][C]9.02229796164546[/C][C]-0.0222979616454594[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]9.16728431349094[/C][C]-0.167284313490941[/C][/ROW]
[ROW][C]32[/C][C]9[/C][C]9.09070761569453[/C][C]-0.0907076156945306[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]9.13173538903566[/C][C]-0.131735389035658[/C][/ROW]
[ROW][C]34[/C][C]9[/C][C]9.17124053756616[/C][C]-0.171240537566156[/C][/ROW]
[ROW][C]35[/C][C]9[/C][C]9.27952764384568[/C][C]-0.27952764384568[/C][/ROW]
[ROW][C]36[/C][C]9[/C][C]9.05416814893982[/C][C]-0.0541681489398204[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]9.22746143396222[/C][C]-0.227461433962217[/C][/ROW]
[ROW][C]38[/C][C]9[/C][C]9.23430975945295[/C][C]-0.234309759452947[/C][/ROW]
[ROW][C]39[/C][C]9[/C][C]9.23958150446145[/C][C]-0.239581504461448[/C][/ROW]
[ROW][C]40[/C][C]9[/C][C]9.17594466569438[/C][C]-0.17594466569438[/C][/ROW]
[ROW][C]41[/C][C]9[/C][C]9.19475493229579[/C][C]-0.19475493229579[/C][/ROW]
[ROW][C]42[/C][C]9[/C][C]9.3536054370813[/C][C]-0.353605437081304[/C][/ROW]
[ROW][C]43[/C][C]9[/C][C]9.26303506285771[/C][C]-0.263035062857705[/C][/ROW]
[ROW][C]44[/C][C]9[/C][C]9.21895940745758[/C][C]-0.218959407457585[/C][/ROW]
[ROW][C]45[/C][C]9[/C][C]9.22835026052586[/C][C]-0.228350260525865[/C][/ROW]
[ROW][C]46[/C][C]9[/C][C]9.29795860791581[/C][C]-0.29795860791581[/C][/ROW]
[ROW][C]47[/C][C]9[/C][C]9.213317503389[/C][C]-0.213317503389004[/C][/ROW]
[ROW][C]48[/C][C]9[/C][C]9.31440012132773[/C][C]-0.314400121327731[/C][/ROW]
[ROW][C]49[/C][C]9[/C][C]9.45726535663955[/C][C]-0.457265356639552[/C][/ROW]
[ROW][C]50[/C][C]9[/C][C]9.33459735420898[/C][C]-0.334597354208983[/C][/ROW]
[ROW][C]51[/C][C]9[/C][C]9.40587411321892[/C][C]-0.405874113218915[/C][/ROW]
[ROW][C]52[/C][C]9[/C][C]9.36085252473413[/C][C]-0.360852524734133[/C][/ROW]
[ROW][C]53[/C][C]9[/C][C]9.43297474614191[/C][C]-0.432974746141905[/C][/ROW]
[ROW][C]54[/C][C]9[/C][C]9.23060680942451[/C][C]-0.230606809424511[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]9.24690724253612[/C][C]-0.246907242536124[/C][/ROW]
[ROW][C]56[/C][C]9[/C][C]9.3174241705282[/C][C]-0.317424170528202[/C][/ROW]
[ROW][C]57[/C][C]9[/C][C]9.44313367513351[/C][C]-0.443133675133505[/C][/ROW]
[ROW][C]58[/C][C]9[/C][C]9.38552455748939[/C][C]-0.385524557489393[/C][/ROW]
[ROW][C]59[/C][C]9[/C][C]9.40700831725542[/C][C]-0.40700831725542[/C][/ROW]
[ROW][C]60[/C][C]9[/C][C]9.42122471734891[/C][C]-0.421224717348914[/C][/ROW]
[ROW][C]61[/C][C]9[/C][C]9.36709152695479[/C][C]-0.367091526954795[/C][/ROW]
[ROW][C]62[/C][C]9[/C][C]9.50547933211382[/C][C]-0.505479332113818[/C][/ROW]
[ROW][C]63[/C][C]9[/C][C]9.53621915564452[/C][C]-0.536219155644517[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]9.46638121226596[/C][C]-0.466381212265963[/C][/ROW]
[ROW][C]65[/C][C]9[/C][C]9.47152620987806[/C][C]-0.471526209878057[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]9.50790786718104[/C][C]0.492092132818961[/C][/ROW]
[ROW][C]67[/C][C]10[/C][C]9.54874710235806[/C][C]0.451252897641945[/C][/ROW]
[ROW][C]68[/C][C]10[/C][C]9.58546202998582[/C][C]0.414537970014183[/C][/ROW]
[ROW][C]69[/C][C]10[/C][C]9.52351020858647[/C][C]0.476489791413534[/C][/ROW]
[ROW][C]70[/C][C]10[/C][C]9.57885721107492[/C][C]0.421142788925081[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]9.38352461744827[/C][C]0.616475382551733[/C][/ROW]
[ROW][C]72[/C][C]10[/C][C]9.56563811361431[/C][C]0.434361886385693[/C][/ROW]
[ROW][C]73[/C][C]10[/C][C]9.7066339953682[/C][C]0.293366004631803[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]9.65184465361556[/C][C]0.348155346384446[/C][/ROW]
[ROW][C]75[/C][C]10[/C][C]9.62713913026114[/C][C]0.372860869738863[/C][/ROW]
[ROW][C]76[/C][C]10[/C][C]9.62007528444767[/C][C]0.37992471555233[/C][/ROW]
[ROW][C]77[/C][C]10[/C][C]9.65756200373103[/C][C]0.342437996268971[/C][/ROW]
[ROW][C]78[/C][C]10[/C][C]9.61227544553567[/C][C]0.38772455446433[/C][/ROW]
[ROW][C]79[/C][C]10[/C][C]9.67710920427722[/C][C]0.322890795722775[/C][/ROW]
[ROW][C]80[/C][C]10[/C][C]9.53703348185886[/C][C]0.462966518141135[/C][/ROW]
[ROW][C]81[/C][C]10[/C][C]9.72462368783264[/C][C]0.275376312167363[/C][/ROW]
[ROW][C]82[/C][C]10[/C][C]9.60194941900219[/C][C]0.398050580997813[/C][/ROW]
[ROW][C]83[/C][C]10[/C][C]9.71358630648506[/C][C]0.286413693514936[/C][/ROW]
[ROW][C]84[/C][C]10[/C][C]9.67833378305774[/C][C]0.321666216942263[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]9.68331999495587[/C][C]0.31668000504413[/C][/ROW]
[ROW][C]86[/C][C]10[/C][C]9.67892627716501[/C][C]0.321073722834991[/C][/ROW]
[ROW][C]87[/C][C]10[/C][C]9.71532265368339[/C][C]0.284677346316614[/C][/ROW]
[ROW][C]88[/C][C]10[/C][C]9.7240646162943[/C][C]0.2759353837057[/C][/ROW]
[ROW][C]89[/C][C]10[/C][C]9.79222692830832[/C][C]0.20777307169168[/C][/ROW]
[ROW][C]90[/C][C]10[/C][C]9.69468661172601[/C][C]0.305313388273991[/C][/ROW]
[ROW][C]91[/C][C]10[/C][C]9.79089493623017[/C][C]0.209105063769832[/C][/ROW]
[ROW][C]92[/C][C]10[/C][C]9.82601754761238[/C][C]0.173982452387625[/C][/ROW]
[ROW][C]93[/C][C]10[/C][C]9.87648961534694[/C][C]0.12351038465306[/C][/ROW]
[ROW][C]94[/C][C]10[/C][C]9.84312712719231[/C][C]0.156872872807695[/C][/ROW]
[ROW][C]95[/C][C]10[/C][C]9.80442456938043[/C][C]0.195575430619566[/C][/ROW]
[ROW][C]96[/C][C]10[/C][C]9.82272217693288[/C][C]0.177277823067118[/C][/ROW]
[ROW][C]97[/C][C]10[/C][C]9.78615560502059[/C][C]0.213844394979413[/C][/ROW]
[ROW][C]98[/C][C]10[/C][C]9.87891189136886[/C][C]0.121088108631137[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]9.79934804816048[/C][C]0.20065195183952[/C][/ROW]
[ROW][C]100[/C][C]10[/C][C]9.91016260210252[/C][C]0.0898373978974834[/C][/ROW]
[ROW][C]101[/C][C]10[/C][C]9.85246770839687[/C][C]0.147532291603126[/C][/ROW]
[ROW][C]102[/C][C]10[/C][C]9.98051671592659[/C][C]0.0194832840734114[/C][/ROW]
[ROW][C]103[/C][C]10[/C][C]9.76165306677296[/C][C]0.238346933227042[/C][/ROW]
[ROW][C]104[/C][C]10[/C][C]9.97518981961303[/C][C]0.0248101803869714[/C][/ROW]
[ROW][C]105[/C][C]10[/C][C]9.90558502898218[/C][C]0.0944149710178194[/C][/ROW]
[ROW][C]106[/C][C]10[/C][C]9.89499225991074[/C][C]0.105007740089257[/C][/ROW]
[ROW][C]107[/C][C]10[/C][C]9.9571869600477[/C][C]0.0428130399522962[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]9.85633560722184[/C][C]0.143664392778159[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.81024579189782[/C][C]0.189754208102179[/C][/ROW]
[ROW][C]110[/C][C]10[/C][C]10.0191493794531[/C][C]-0.019149379453078[/C][/ROW]
[ROW][C]111[/C][C]10[/C][C]10.0424605840101[/C][C]-0.0424605840100637[/C][/ROW]
[ROW][C]112[/C][C]10[/C][C]9.95570780683289[/C][C]0.0442921931671116[/C][/ROW]
[ROW][C]113[/C][C]10[/C][C]10.153785331417[/C][C]-0.153785331417049[/C][/ROW]
[ROW][C]114[/C][C]10[/C][C]9.94596124262735[/C][C]0.0540387573726526[/C][/ROW]
[ROW][C]115[/C][C]10[/C][C]10.0207837090744[/C][C]-0.0207837090743946[/C][/ROW]
[ROW][C]116[/C][C]10[/C][C]10.0021714479527[/C][C]-0.00217144795266387[/C][/ROW]
[ROW][C]117[/C][C]10[/C][C]9.86801303990082[/C][C]0.131986960099182[/C][/ROW]
[ROW][C]118[/C][C]10[/C][C]9.95203426436988[/C][C]0.0479657356301161[/C][/ROW]
[ROW][C]119[/C][C]10[/C][C]10.1003873247313[/C][C]-0.100387324731267[/C][/ROW]
[ROW][C]120[/C][C]10[/C][C]9.99129045627087[/C][C]0.00870954372912571[/C][/ROW]
[ROW][C]121[/C][C]10[/C][C]10.1129879669129[/C][C]-0.112987966912939[/C][/ROW]
[ROW][C]122[/C][C]10[/C][C]10.0864524275152[/C][C]-0.0864524275151553[/C][/ROW]
[ROW][C]123[/C][C]10[/C][C]10.0585408623544[/C][C]-0.0585408623544101[/C][/ROW]
[ROW][C]124[/C][C]10[/C][C]10.0722757257261[/C][C]-0.0722757257260563[/C][/ROW]
[ROW][C]125[/C][C]10[/C][C]10.178897501036[/C][C]-0.178897501036034[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]10.0547315583921[/C][C]-0.0547315583921199[/C][/ROW]
[ROW][C]127[/C][C]10[/C][C]10.0936667440349[/C][C]-0.0936667440349265[/C][/ROW]
[ROW][C]128[/C][C]10[/C][C]10.0377762964209[/C][C]-0.0377762964208847[/C][/ROW]
[ROW][C]129[/C][C]10[/C][C]10.1077237396531[/C][C]-0.107723739653146[/C][/ROW]
[ROW][C]130[/C][C]10[/C][C]10.1099035757641[/C][C]-0.109903575764148[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]10.1734257237227[/C][C]-0.17342572372268[/C][/ROW]
[ROW][C]132[/C][C]10[/C][C]10.0801599609288[/C][C]-0.0801599609288204[/C][/ROW]
[ROW][C]133[/C][C]10[/C][C]10.1717609415255[/C][C]-0.171760941525484[/C][/ROW]
[ROW][C]134[/C][C]10[/C][C]10.1596831647841[/C][C]-0.159683164784149[/C][/ROW]
[ROW][C]135[/C][C]10[/C][C]10.2330828590162[/C][C]-0.233082859016234[/C][/ROW]
[ROW][C]136[/C][C]10[/C][C]10.1973234339682[/C][C]-0.197323433968189[/C][/ROW]
[ROW][C]137[/C][C]10[/C][C]10.1115633240083[/C][C]-0.111563324008279[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]10.1104385109455[/C][C]-0.110438510945503[/C][/ROW]
[ROW][C]139[/C][C]10[/C][C]10.0852653101426[/C][C]-0.0852653101426025[/C][/ROW]
[ROW][C]140[/C][C]10[/C][C]10.1781794893462[/C][C]-0.178179489346182[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]10.1115538752123[/C][C]-0.111553875212293[/C][/ROW]
[ROW][C]142[/C][C]10[/C][C]10.2880903879325[/C][C]-0.288090387932529[/C][/ROW]
[ROW][C]143[/C][C]10[/C][C]10.3666887793705[/C][C]-0.366688779370525[/C][/ROW]
[ROW][C]144[/C][C]10[/C][C]10.2925235177024[/C][C]-0.292523517702369[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]10.1918893878988[/C][C]-0.191889387898802[/C][/ROW]
[ROW][C]146[/C][C]10[/C][C]10.3317647034678[/C][C]-0.331764703467846[/C][/ROW]
[ROW][C]147[/C][C]10[/C][C]10.2173312972045[/C][C]-0.217331297204509[/C][/ROW]
[ROW][C]148[/C][C]10[/C][C]10.2912972632949[/C][C]-0.291297263294932[/C][/ROW]
[ROW][C]149[/C][C]10[/C][C]10.2670612100555[/C][C]-0.267061210055494[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]10.2321502418192[/C][C]-0.232150241819204[/C][/ROW]
[ROW][C]151[/C][C]10[/C][C]10.4323434565515[/C][C]-0.432343456551516[/C][/ROW]
[ROW][C]152[/C][C]10[/C][C]10.3257646428991[/C][C]-0.325764642899088[/C][/ROW]
[ROW][C]153[/C][C]10[/C][C]10.2330489879791[/C][C]-0.233048987979107[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]10.2943681119201[/C][C]-1.29436811192006[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]10.2916765560773[/C][C]-0.291676556077292[/C][/ROW]
[ROW][C]156[/C][C]10[/C][C]10.4267278227538[/C][C]-0.426727822753818[/C][/ROW]
[ROW][C]157[/C][C]10[/C][C]10.2839709345213[/C][C]-0.283970934521254[/C][/ROW]
[ROW][C]158[/C][C]10[/C][C]10.3312376286626[/C][C]-0.331237628662569[/C][/ROW]
[ROW][C]159[/C][C]10[/C][C]10.3904537856964[/C][C]-0.390453785696377[/C][/ROW]
[ROW][C]160[/C][C]10[/C][C]10.466633398616[/C][C]-0.46663339861602[/C][/ROW]
[ROW][C]161[/C][C]10[/C][C]10.3070679060349[/C][C]-0.307067906034863[/C][/ROW]
[ROW][C]162[/C][C]11[/C][C]10.4584208635401[/C][C]0.541579136459895[/C][/ROW]
[ROW][C]163[/C][C]11[/C][C]10.4665944248748[/C][C]0.533405575125243[/C][/ROW]
[ROW][C]164[/C][C]11[/C][C]10.6388915017712[/C][C]0.36110849822877[/C][/ROW]
[ROW][C]165[/C][C]11[/C][C]10.5067948737507[/C][C]0.493205126249333[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]10.4847238317545[/C][C]0.515276168245522[/C][/ROW]
[ROW][C]167[/C][C]11[/C][C]10.4922018225677[/C][C]0.507798177432324[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]10.544446789733[/C][C]0.455553210267034[/C][/ROW]
[ROW][C]169[/C][C]11[/C][C]10.5494081438828[/C][C]0.450591856117224[/C][/ROW]
[ROW][C]170[/C][C]11[/C][C]10.6692820960823[/C][C]0.330717903917683[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.3967873971356[/C][C]0.603212602864361[/C][/ROW]
[ROW][C]172[/C][C]11[/C][C]10.5604132522213[/C][C]0.439586747778672[/C][/ROW]
[ROW][C]173[/C][C]11[/C][C]10.4698520492109[/C][C]0.530147950789087[/C][/ROW]
[ROW][C]174[/C][C]11[/C][C]10.4922382267203[/C][C]0.507761773279667[/C][/ROW]
[ROW][C]175[/C][C]11[/C][C]10.5747333434207[/C][C]0.425266656579302[/C][/ROW]
[ROW][C]176[/C][C]11[/C][C]10.618981022536[/C][C]0.381018977464039[/C][/ROW]
[ROW][C]177[/C][C]11[/C][C]10.4613135775624[/C][C]0.538686422437629[/C][/ROW]
[ROW][C]178[/C][C]11[/C][C]10.616746896456[/C][C]0.383253103543997[/C][/ROW]
[ROW][C]179[/C][C]11[/C][C]10.5533039735023[/C][C]0.446696026497684[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]10.6164942871368[/C][C]0.383505712863209[/C][/ROW]
[ROW][C]181[/C][C]11[/C][C]10.573361330204[/C][C]0.426638669795982[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]10.4425212266748[/C][C]0.557478773325154[/C][/ROW]
[ROW][C]183[/C][C]11[/C][C]10.7022491216377[/C][C]0.297750878362258[/C][/ROW]
[ROW][C]184[/C][C]11[/C][C]10.6585674880443[/C][C]0.341432511955671[/C][/ROW]
[ROW][C]185[/C][C]11[/C][C]10.7111579589181[/C][C]0.288842041081853[/C][/ROW]
[ROW][C]186[/C][C]11[/C][C]10.8342832197335[/C][C]0.16571678026648[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]10.7483049147683[/C][C]0.251695085231703[/C][/ROW]
[ROW][C]188[/C][C]11[/C][C]10.6411142919929[/C][C]0.358885708007061[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]10.6452965641435[/C][C]0.354703435856521[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.6023820362106[/C][C]0.397617963789422[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]10.8953618386102[/C][C]0.104638161389755[/C][/ROW]
[ROW][C]192[/C][C]11[/C][C]10.7587119829289[/C][C]0.241288017071137[/C][/ROW]
[ROW][C]193[/C][C]11[/C][C]10.6103540434872[/C][C]0.389645956512759[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]10.678768850217[/C][C]0.321231149783024[/C][/ROW]
[ROW][C]195[/C][C]11[/C][C]10.7592630608871[/C][C]0.240736939112936[/C][/ROW]
[ROW][C]196[/C][C]11[/C][C]10.7266730852762[/C][C]0.27332691472378[/C][/ROW]
[ROW][C]197[/C][C]11[/C][C]10.8401396379077[/C][C]0.159860362092292[/C][/ROW]
[ROW][C]198[/C][C]11[/C][C]10.8877885075036[/C][C]0.112211492496405[/C][/ROW]
[ROW][C]199[/C][C]11[/C][C]10.7805031823727[/C][C]0.219496817627329[/C][/ROW]
[ROW][C]200[/C][C]11[/C][C]10.9277430448598[/C][C]0.0722569551401695[/C][/ROW]
[ROW][C]201[/C][C]11[/C][C]10.8155068028644[/C][C]0.184493197135597[/C][/ROW]
[ROW][C]202[/C][C]11[/C][C]10.8698763499717[/C][C]0.130123650028261[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]10.8693704760447[/C][C]0.130629523955345[/C][/ROW]
[ROW][C]204[/C][C]11[/C][C]10.7717036377239[/C][C]0.228296362276145[/C][/ROW]
[ROW][C]205[/C][C]11[/C][C]10.8092334786549[/C][C]0.190766521345055[/C][/ROW]
[ROW][C]206[/C][C]11[/C][C]10.8896250422285[/C][C]0.110374957771542[/C][/ROW]
[ROW][C]207[/C][C]11[/C][C]10.8395203049669[/C][C]0.160479695033109[/C][/ROW]
[ROW][C]208[/C][C]11[/C][C]10.9176887602398[/C][C]0.0823112397601546[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]10.8293869988397[/C][C]0.170613001160302[/C][/ROW]
[ROW][C]210[/C][C]11[/C][C]10.9496106678471[/C][C]0.0503893321529274[/C][/ROW]
[ROW][C]211[/C][C]11[/C][C]10.8955393435981[/C][C]0.104460656401903[/C][/ROW]
[ROW][C]212[/C][C]11[/C][C]10.9114096347602[/C][C]0.0885903652398076[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]11.0098008735317[/C][C]-0.00980087353172996[/C][/ROW]
[ROW][C]214[/C][C]11[/C][C]10.8713975268224[/C][C]0.128602473177601[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]11.0112298130703[/C][C]-0.011229813070315[/C][/ROW]
[ROW][C]216[/C][C]11[/C][C]10.9159274356942[/C][C]0.0840725643058146[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]11.0200298506413[/C][C]-0.0200298506413429[/C][/ROW]
[ROW][C]218[/C][C]11[/C][C]10.9346579272332[/C][C]0.0653420727668339[/C][/ROW]
[ROW][C]219[/C][C]11[/C][C]10.9881280084646[/C][C]0.01187199153541[/C][/ROW]
[ROW][C]220[/C][C]11[/C][C]11.0311310760237[/C][C]-0.0311310760237108[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]11.0060895893753[/C][C]-0.00608958937527957[/C][/ROW]
[ROW][C]222[/C][C]11[/C][C]11.0532308076777[/C][C]-0.0532308076776667[/C][/ROW]
[ROW][C]223[/C][C]11[/C][C]11.0733437063059[/C][C]-0.0733437063058886[/C][/ROW]
[ROW][C]224[/C][C]11[/C][C]10.961385230957[/C][C]0.0386147690430435[/C][/ROW]
[ROW][C]225[/C][C]11[/C][C]11.2424095740968[/C][C]-0.242409574096759[/C][/ROW]
[ROW][C]226[/C][C]11[/C][C]10.9802934293624[/C][C]0.0197065706376484[/C][/ROW]
[ROW][C]227[/C][C]11[/C][C]11.028752166679[/C][C]-0.0287521666789969[/C][/ROW]
[ROW][C]228[/C][C]11[/C][C]11.0892482323002[/C][C]-0.0892482323001662[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]11.0648656112823[/C][C]-0.064865611282253[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]11.0217300705238[/C][C]-0.0217300705238197[/C][/ROW]
[ROW][C]231[/C][C]11[/C][C]10.9974793709188[/C][C]0.00252062908123112[/C][/ROW]
[ROW][C]232[/C][C]11[/C][C]11.0145029363126[/C][C]-0.014502936312616[/C][/ROW]
[ROW][C]233[/C][C]11[/C][C]10.9588951134035[/C][C]0.0411048865964949[/C][/ROW]
[ROW][C]234[/C][C]11[/C][C]11.1863389587963[/C][C]-0.18633895879625[/C][/ROW]
[ROW][C]235[/C][C]11[/C][C]11.0896585843875[/C][C]-0.0896585843874941[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]11.0959654804495[/C][C]-0.0959654804494586[/C][/ROW]
[ROW][C]237[/C][C]11[/C][C]10.9870377390074[/C][C]0.0129622609925799[/C][/ROW]
[ROW][C]238[/C][C]11[/C][C]11.0625657773573[/C][C]-0.0625657773573427[/C][/ROW]
[ROW][C]239[/C][C]11[/C][C]11.1929642742679[/C][C]-0.192964274267908[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]11.05349412191[/C][C]-0.0534941219099727[/C][/ROW]
[ROW][C]241[/C][C]11[/C][C]11.167564227303[/C][C]-0.167564227302952[/C][/ROW]
[ROW][C]242[/C][C]11[/C][C]11.1525229438069[/C][C]-0.152522943806857[/C][/ROW]
[ROW][C]243[/C][C]11[/C][C]11.0655497896244[/C][C]-0.0655497896244464[/C][/ROW]
[ROW][C]244[/C][C]11[/C][C]11.1450606561757[/C][C]-0.145060656175714[/C][/ROW]
[ROW][C]245[/C][C]11[/C][C]11.2017094670775[/C][C]-0.201709467077504[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]11.2685881715198[/C][C]-0.268588171519788[/C][/ROW]
[ROW][C]247[/C][C]11[/C][C]11.2124392491717[/C][C]-0.212439249171739[/C][/ROW]
[ROW][C]248[/C][C]11[/C][C]11.2213870752203[/C][C]-0.221387075220322[/C][/ROW]
[ROW][C]249[/C][C]11[/C][C]11.2319409580552[/C][C]-0.23194095805524[/C][/ROW]
[ROW][C]250[/C][C]11[/C][C]11.2993085405886[/C][C]-0.299308540588611[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.258995939957[/C][C]-0.25899593995699[/C][/ROW]
[ROW][C]252[/C][C]11[/C][C]11.2944411046391[/C][C]-0.294441104639144[/C][/ROW]
[ROW][C]253[/C][C]11[/C][C]11.1659584788865[/C][C]-0.165958478886534[/C][/ROW]
[ROW][C]254[/C][C]11[/C][C]11.2757145163202[/C][C]-0.275714516320187[/C][/ROW]
[ROW][C]255[/C][C]11[/C][C]11.2781021773608[/C][C]-0.278102177360756[/C][/ROW]
[ROW][C]256[/C][C]11[/C][C]11.3061240182149[/C][C]-0.306124018214886[/C][/ROW]
[ROW][C]257[/C][C]11[/C][C]11.5183942755055[/C][C]-0.518394275505473[/C][/ROW]
[ROW][C]258[/C][C]11[/C][C]11.2762925601139[/C][C]-0.276292560113851[/C][/ROW]
[ROW][C]259[/C][C]11[/C][C]11.3885784734832[/C][C]-0.388578473483234[/C][/ROW]
[ROW][C]260[/C][C]11[/C][C]11.0993557668019[/C][C]-0.0993557668018904[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]11.4169317167682[/C][C]-0.416931716768193[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]11.4236847285112[/C][C]-0.42368472851116[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.3233512311794[/C][C]-0.323351231179362[/C][/ROW]
[ROW][C]264[/C][C]11[/C][C]11.4174750183926[/C][C]-0.417475018392563[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203885&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203885&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
198.804578161704140.195421838295862
298.886438901774760.113561098225244
398.929481971223820.0705180287761851
498.763672233233140.236327766766859
599.07632427428401-0.0763242742840104
698.924278844626140.0757211553738652
798.902088964922390.0979110350776093
898.986149341888860.0138506581111349
998.932641101151470.0673588988485339
1098.914688477322810.0853115226771949
1198.91748657019590.0825134298040989
1298.92008992815810.0799100718419024
1398.950024168595590.0499758314044142
1498.96578366843860.0342163315613968
1599.12931739621936-0.129317396219364
1699.00086804483716-0.00086804483716005
1799.02899246409117-0.0289924640911752
1899.09493451169265-0.0949345116926459
1998.942371680869070.0576283191309349
2099.03057221024241-0.0305722102424131
2199.02821973088454-0.0282197308845436
2299.02576389256539-0.0257638925653906
2399.06322493067837-0.0632249306783694
2498.986645053828920.0133549461710757
2599.15173147719061-0.151731477190614
2699.09848190497035-0.098481904970355
2799.17095487671694-0.170954876716937
2899.17207212975641-0.172072129756413
2999.25470682579222-0.254706825792217
3099.02229796164546-0.0222979616454594
3199.16728431349094-0.167284313490941
3299.09070761569453-0.0907076156945306
3399.13173538903566-0.131735389035658
3499.17124053756616-0.171240537566156
3599.27952764384568-0.27952764384568
3699.05416814893982-0.0541681489398204
3799.22746143396222-0.227461433962217
3899.23430975945295-0.234309759452947
3999.23958150446145-0.239581504461448
4099.17594466569438-0.17594466569438
4199.19475493229579-0.19475493229579
4299.3536054370813-0.353605437081304
4399.26303506285771-0.263035062857705
4499.21895940745758-0.218959407457585
4599.22835026052586-0.228350260525865
4699.29795860791581-0.29795860791581
4799.213317503389-0.213317503389004
4899.31440012132773-0.314400121327731
4999.45726535663955-0.457265356639552
5099.33459735420898-0.334597354208983
5199.40587411321892-0.405874113218915
5299.36085252473413-0.360852524734133
5399.43297474614191-0.432974746141905
5499.23060680942451-0.230606809424511
5599.24690724253612-0.246907242536124
5699.3174241705282-0.317424170528202
5799.44313367513351-0.443133675133505
5899.38552455748939-0.385524557489393
5999.40700831725542-0.40700831725542
6099.42122471734891-0.421224717348914
6199.36709152695479-0.367091526954795
6299.50547933211382-0.505479332113818
6399.53621915564452-0.536219155644517
6499.46638121226596-0.466381212265963
6599.47152620987806-0.471526209878057
66109.507907867181040.492092132818961
67109.548747102358060.451252897641945
68109.585462029985820.414537970014183
69109.523510208586470.476489791413534
70109.578857211074920.421142788925081
71109.383524617448270.616475382551733
72109.565638113614310.434361886385693
73109.70663399536820.293366004631803
74109.651844653615560.348155346384446
75109.627139130261140.372860869738863
76109.620075284447670.37992471555233
77109.657562003731030.342437996268971
78109.612275445535670.38772455446433
79109.677109204277220.322890795722775
80109.537033481858860.462966518141135
81109.724623687832640.275376312167363
82109.601949419002190.398050580997813
83109.713586306485060.286413693514936
84109.678333783057740.321666216942263
85109.683319994955870.31668000504413
86109.678926277165010.321073722834991
87109.715322653683390.284677346316614
88109.72406461629430.2759353837057
89109.792226928308320.20777307169168
90109.694686611726010.305313388273991
91109.790894936230170.209105063769832
92109.826017547612380.173982452387625
93109.876489615346940.12351038465306
94109.843127127192310.156872872807695
95109.804424569380430.195575430619566
96109.822722176932880.177277823067118
97109.786155605020590.213844394979413
98109.878911891368860.121088108631137
99109.799348048160480.20065195183952
100109.910162602102520.0898373978974834
101109.852467708396870.147532291603126
102109.980516715926590.0194832840734114
103109.761653066772960.238346933227042
104109.975189819613030.0248101803869714
105109.905585028982180.0944149710178194
106109.894992259910740.105007740089257
107109.95718696004770.0428130399522962
108109.856335607221840.143664392778159
109109.810245791897820.189754208102179
1101010.0191493794531-0.019149379453078
1111010.0424605840101-0.0424605840100637
112109.955707806832890.0442921931671116
1131010.153785331417-0.153785331417049
114109.945961242627350.0540387573726526
1151010.0207837090744-0.0207837090743946
1161010.0021714479527-0.00217144795266387
117109.868013039900820.131986960099182
118109.952034264369880.0479657356301161
1191010.1003873247313-0.100387324731267
120109.991290456270870.00870954372912571
1211010.1129879669129-0.112987966912939
1221010.0864524275152-0.0864524275151553
1231010.0585408623544-0.0585408623544101
1241010.0722757257261-0.0722757257260563
1251010.178897501036-0.178897501036034
1261010.0547315583921-0.0547315583921199
1271010.0936667440349-0.0936667440349265
1281010.0377762964209-0.0377762964208847
1291010.1077237396531-0.107723739653146
1301010.1099035757641-0.109903575764148
1311010.1734257237227-0.17342572372268
1321010.0801599609288-0.0801599609288204
1331010.1717609415255-0.171760941525484
1341010.1596831647841-0.159683164784149
1351010.2330828590162-0.233082859016234
1361010.1973234339682-0.197323433968189
1371010.1115633240083-0.111563324008279
1381010.1104385109455-0.110438510945503
1391010.0852653101426-0.0852653101426025
1401010.1781794893462-0.178179489346182
1411010.1115538752123-0.111553875212293
1421010.2880903879325-0.288090387932529
1431010.3666887793705-0.366688779370525
1441010.2925235177024-0.292523517702369
1451010.1918893878988-0.191889387898802
1461010.3317647034678-0.331764703467846
1471010.2173312972045-0.217331297204509
1481010.2912972632949-0.291297263294932
1491010.2670612100555-0.267061210055494
1501010.2321502418192-0.232150241819204
1511010.4323434565515-0.432343456551516
1521010.3257646428991-0.325764642899088
1531010.2330489879791-0.233048987979107
154910.2943681119201-1.29436811192006
1551010.2916765560773-0.291676556077292
1561010.4267278227538-0.426727822753818
1571010.2839709345213-0.283970934521254
1581010.3312376286626-0.331237628662569
1591010.3904537856964-0.390453785696377
1601010.466633398616-0.46663339861602
1611010.3070679060349-0.307067906034863
1621110.45842086354010.541579136459895
1631110.46659442487480.533405575125243
1641110.63889150177120.36110849822877
1651110.50679487375070.493205126249333
1661110.48472383175450.515276168245522
1671110.49220182256770.507798177432324
1681110.5444467897330.455553210267034
1691110.54940814388280.450591856117224
1701110.66928209608230.330717903917683
1711110.39678739713560.603212602864361
1721110.56041325222130.439586747778672
1731110.46985204921090.530147950789087
1741110.49223822672030.507761773279667
1751110.57473334342070.425266656579302
1761110.6189810225360.381018977464039
1771110.46131357756240.538686422437629
1781110.6167468964560.383253103543997
1791110.55330397350230.446696026497684
1801110.61649428713680.383505712863209
1811110.5733613302040.426638669795982
1821110.44252122667480.557478773325154
1831110.70224912163770.297750878362258
1841110.65856748804430.341432511955671
1851110.71115795891810.288842041081853
1861110.83428321973350.16571678026648
1871110.74830491476830.251695085231703
1881110.64111429199290.358885708007061
1891110.64529656414350.354703435856521
1901110.60238203621060.397617963789422
1911110.89536183861020.104638161389755
1921110.75871198292890.241288017071137
1931110.61035404348720.389645956512759
1941110.6787688502170.321231149783024
1951110.75926306088710.240736939112936
1961110.72667308527620.27332691472378
1971110.84013963790770.159860362092292
1981110.88778850750360.112211492496405
1991110.78050318237270.219496817627329
2001110.92774304485980.0722569551401695
2011110.81550680286440.184493197135597
2021110.86987634997170.130123650028261
2031110.86937047604470.130629523955345
2041110.77170363772390.228296362276145
2051110.80923347865490.190766521345055
2061110.88962504222850.110374957771542
2071110.83952030496690.160479695033109
2081110.91768876023980.0823112397601546
2091110.82938699883970.170613001160302
2101110.94961066784710.0503893321529274
2111110.89553934359810.104460656401903
2121110.91140963476020.0885903652398076
2131111.0098008735317-0.00980087353172996
2141110.87139752682240.128602473177601
2151111.0112298130703-0.011229813070315
2161110.91592743569420.0840725643058146
2171111.0200298506413-0.0200298506413429
2181110.93465792723320.0653420727668339
2191110.98812800846460.01187199153541
2201111.0311310760237-0.0311310760237108
2211111.0060895893753-0.00608958937527957
2221111.0532308076777-0.0532308076776667
2231111.0733437063059-0.0733437063058886
2241110.9613852309570.0386147690430435
2251111.2424095740968-0.242409574096759
2261110.98029342936240.0197065706376484
2271111.028752166679-0.0287521666789969
2281111.0892482323002-0.0892482323001662
2291111.0648656112823-0.064865611282253
2301111.0217300705238-0.0217300705238197
2311110.99747937091880.00252062908123112
2321111.0145029363126-0.014502936312616
2331110.95889511340350.0411048865964949
2341111.1863389587963-0.18633895879625
2351111.0896585843875-0.0896585843874941
2361111.0959654804495-0.0959654804494586
2371110.98703773900740.0129622609925799
2381111.0625657773573-0.0625657773573427
2391111.1929642742679-0.192964274267908
2401111.05349412191-0.0534941219099727
2411111.167564227303-0.167564227302952
2421111.1525229438069-0.152522943806857
2431111.0655497896244-0.0655497896244464
2441111.1450606561757-0.145060656175714
2451111.2017094670775-0.201709467077504
2461111.2685881715198-0.268588171519788
2471111.2124392491717-0.212439249171739
2481111.2213870752203-0.221387075220322
2491111.2319409580552-0.23194095805524
2501111.2993085405886-0.299308540588611
2511111.258995939957-0.25899593995699
2521111.2944411046391-0.294441104639144
2531111.1659584788865-0.165958478886534
2541111.2757145163202-0.275714516320187
2551111.2781021773608-0.278102177360756
2561111.3061240182149-0.306124018214886
2571111.5183942755055-0.518394275505473
2581111.2762925601139-0.276292560113851
2591111.3885784734832-0.388578473483234
2601111.0993557668019-0.0993557668018904
2611111.4169317167682-0.416931716768193
2621111.4236847285112-0.42368472851116
2631111.3233512311794-0.323351231179362
2641111.4174750183926-0.417475018392563







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
132.28031440419649e-454.56062880839299e-451
143.52074781612403e-587.04149563224807e-581
151.37240212232936e-712.74480424465872e-711
16001
172.44661104114883e-1004.89322208229766e-1001
181.17462262798987e-1152.34924525597975e-1151
198.40628824171353e-1311.68125764834271e-1301
201.57362553166883e-1513.14725106333765e-1511
212.22491956742789e-1614.44983913485577e-1611
227.26087101488634e-1741.45217420297727e-1731
231.22564516113724e-1852.45129032227448e-1851
243.29210325268509e-2076.58420650537018e-2071
251.07995376533312e-2202.15990753066625e-2201
263.14753741916471e-2386.29507483832942e-2381
279.97277301117504e-2491.99455460223501e-2481
286.08178185605501e-2621.216356371211e-2611
295.66667736639293e-2861.13333547327859e-2851
302.55506510780961e-2835.11013021561921e-2831
311.49687044176093e-3062.99374088352186e-3061
324.94065645841247e-3249.88131291682493e-3241
33001
34001
35001
36001
37001
38001
39001
40001
41001
42001
43001
44001
45001
46001
47001
48001
49001
50001
51001
52001
53001
54001
55001
56001
57001
58001
59001
60001
61001
62001
63001
64001
65001
662.79218957877237e-105.58437915754474e-100.999999999720781
671.50029153100721e-053.00058306201442e-050.99998499708469
680.0009622505613959290.001924501122791860.999037749438604
690.0406235279789580.08124705595791610.959376472021042
700.1291981710683460.2583963421366930.870801828931653
710.3255281888962170.6510563777924340.674471811103783
720.4591951512500640.9183903025001280.540804848749936
730.5084725944018190.9830548111963620.491527405598181
740.5363217200594650.9273565598810690.463678279940535
750.6627445022021780.6745109955956440.337255497797822
760.6800624402950730.6398751194098530.319937559704927
770.6908001564173970.6183996871652060.309199843582603
780.7067529860924790.5864940278150430.293247013907521
790.7374427708684720.5251144582630550.262557229131528
800.7845008774871920.4309982450256170.215499122512808
810.7802859021598770.4394281956802460.219714097840123
820.7799333524214780.4401332951570440.220066647578522
830.7670617312310130.4658765375379750.232938268768987
840.7571911892361480.4856176215277030.242808810763851
850.7414311237096190.5171377525807630.258568876290381
860.7218094316441250.556381136711750.278190568355875
870.7014138248820160.5971723502359680.298586175117984
880.6822136178674460.6355727642651080.317786382132554
890.6515280217866710.6969439564266580.348471978213329
900.626228588106920.747542823786160.37377141189308
910.593294088324760.8134118233504810.40670591167524
920.5581900364367440.8836199271265120.441809963563256
930.5206998841326530.9586002317346950.479300115867347
940.4888525400643510.9777050801287010.511147459935649
950.4536815780509640.9073631561019280.546318421949036
960.4196268452925990.8392536905851990.580373154707401
970.3855904943330330.7711809886660660.614409505666967
980.3528487086652360.7056974173304720.647151291334764
990.3205756748899990.6411513497799980.679424325110001
1000.2905632524385580.5811265048771160.709436747561442
1010.2637477965524180.5274955931048360.736252203447582
1020.251769400684520.5035388013690410.74823059931548
1030.226208329648610.4524166592972210.77379167035139
1040.206601317011820.413202634023640.79339868298818
1050.1816647167624340.3633294335248670.818335283237566
1060.1644828933351340.3289657866702670.835517106664866
1070.1503890179500920.3007780359001840.849610982049908
1080.1309363360870440.2618726721740890.869063663912956
1090.1164672811968370.2329345623936730.883532718803163
1100.1061848893318130.2123697786636250.893815110668187
1110.09348153611173270.1869630722234650.906518463888267
1120.08304277805081010.166085556101620.91695722194919
1130.07652908207658540.1530581641531710.923470917923415
1140.06667663409431340.1333532681886270.933323365905687
1150.06159428988726090.1231885797745220.938405710112739
1160.05300993032364860.1060198606472970.946990069676351
1170.04589169014958850.0917833802991770.954108309850412
1180.03803925438202440.07607850876404880.961960745617976
1190.03634897971336310.07269795942672610.963651020286637
1200.03043474371975810.06086948743951630.969565256280242
1210.02826913048918180.05653826097836360.971730869510818
1220.02498119892407560.04996239784815130.975018801075924
1230.02183087118643030.04366174237286060.97816912881357
1240.01925683402960810.03851366805921630.980743165970392
1250.01823481819970060.03646963639940120.981765181800299
1260.01596975858914230.03193951717828450.984030241410858
1270.0148574711800910.02971494236018190.985142528819909
1280.01336318123634590.02672636247269180.986636818763654
1290.01177672928664520.02355345857329030.988223270713355
1300.01058660787442940.02117321574885890.989413392125571
1310.01013523054060980.02027046108121960.98986476945939
1320.008962043924997360.01792408784999470.991037956075003
1330.008623199121319740.01724639824263950.99137680087868
1340.008200125759508730.01640025151901750.991799874240491
1350.008796218400954150.01759243680190830.991203781599046
1360.009152507274934750.01830501454986950.990847492725065
1370.00835332490546570.01670664981093140.991646675094534
1380.007533502834262520.0150670056685250.992466497165737
1390.006555939717074250.01311187943414850.993444060282926
1400.006668329185795390.01333665837159080.993331670814205
1410.006147065028633020.0122941300572660.993852934971367
1420.00742399389220780.01484798778441560.992576006107792
1430.01118794514336280.02237589028672560.988812054856637
1440.01418061789838720.02836123579677430.985819382101613
1450.01520263983110.03040527966220.9847973601689
1460.02267361682849130.04534723365698250.977326383171509
1470.02684797913744760.05369595827489510.973152020862552
1480.03851900149865230.07703800299730460.961480998501348
1490.04975230908101420.09950461816202840.950247690918986
1500.05725779784831370.1145155956966270.942742202151686
1510.1080701974461610.2161403948923220.891929802553839
1520.1514500287795220.3029000575590430.848549971220478
1530.1762479989423160.3524959978846320.823752001057684
1540.9860929262529120.02781414749417560.0139070737470878
1550.9964338488930230.007132302213953320.00356615110697666
1560.99988569699340.0002286060132005820.000114303006600291
1570.9999915294566671.69410866668003e-058.47054333340017e-06
1580.9999999151374031.6972519444801e-078.48625972240048e-08
1590.9999999999990061.98744894469144e-129.93724472345721e-13
16016.22729547574856e-223.11364773787428e-22
161100
162100
163100
164100
165100
166100
167100
168100
169100
170100
171100
172100
173100
174100
175100
176100
177100
178100
179100
180100
181100
182100
183100
184100
185100
186100
187100
188100
189100
190100
191100
192100
193100
194100
195100
196100
197100
198100
199100
200100
201100
202100
203100
204100
205100
206100
207100
208100
209100
210100
211100
212100
213100
214100
215100
216100
217100
218100
219100
220100
221100
222100
223100
224100
225100
226100
227100
228100
229100
230100
23118.89318162514244e-3234.44659081257122e-323
232100
23311.42508847055468e-3017.12544235277339e-302
23416.58885218615726e-2823.29442609307863e-282
23514.53122932017209e-2782.26561466008605e-278
23618.18512046626044e-2554.09256023313022e-255
23713.30447112179486e-2461.65223556089743e-246
23814.40341240918453e-2292.20170620459226e-229
23912.7432485575654e-2101.3716242787827e-210
24015.99499665990184e-2132.99749832995092e-213
24111.12557542912217e-1915.62787714561084e-192
24215.58310623006506e-1702.79155311503253e-170
24313.8180489433327e-1651.90902447166635e-165
24412.6578638712862e-1501.3289319356431e-150
24513.76336200059293e-1301.88168100029647e-130
24616.16541862518434e-1263.08270931259217e-126
24718.4129529406902e-1014.2064764703451e-101
248100
24917.02966118217007e-733.51483059108504e-73
25011.13375144838089e-565.66875724190444e-57
25113.95062559713948e-471.97531279856974e-47

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 2.28031440419649e-45 & 4.56062880839299e-45 & 1 \tabularnewline
14 & 3.52074781612403e-58 & 7.04149563224807e-58 & 1 \tabularnewline
15 & 1.37240212232936e-71 & 2.74480424465872e-71 & 1 \tabularnewline
16 & 0 & 0 & 1 \tabularnewline
17 & 2.44661104114883e-100 & 4.89322208229766e-100 & 1 \tabularnewline
18 & 1.17462262798987e-115 & 2.34924525597975e-115 & 1 \tabularnewline
19 & 8.40628824171353e-131 & 1.68125764834271e-130 & 1 \tabularnewline
20 & 1.57362553166883e-151 & 3.14725106333765e-151 & 1 \tabularnewline
21 & 2.22491956742789e-161 & 4.44983913485577e-161 & 1 \tabularnewline
22 & 7.26087101488634e-174 & 1.45217420297727e-173 & 1 \tabularnewline
23 & 1.22564516113724e-185 & 2.45129032227448e-185 & 1 \tabularnewline
24 & 3.29210325268509e-207 & 6.58420650537018e-207 & 1 \tabularnewline
25 & 1.07995376533312e-220 & 2.15990753066625e-220 & 1 \tabularnewline
26 & 3.14753741916471e-238 & 6.29507483832942e-238 & 1 \tabularnewline
27 & 9.97277301117504e-249 & 1.99455460223501e-248 & 1 \tabularnewline
28 & 6.08178185605501e-262 & 1.216356371211e-261 & 1 \tabularnewline
29 & 5.66667736639293e-286 & 1.13333547327859e-285 & 1 \tabularnewline
30 & 2.55506510780961e-283 & 5.11013021561921e-283 & 1 \tabularnewline
31 & 1.49687044176093e-306 & 2.99374088352186e-306 & 1 \tabularnewline
32 & 4.94065645841247e-324 & 9.88131291682493e-324 & 1 \tabularnewline
33 & 0 & 0 & 1 \tabularnewline
34 & 0 & 0 & 1 \tabularnewline
35 & 0 & 0 & 1 \tabularnewline
36 & 0 & 0 & 1 \tabularnewline
37 & 0 & 0 & 1 \tabularnewline
38 & 0 & 0 & 1 \tabularnewline
39 & 0 & 0 & 1 \tabularnewline
40 & 0 & 0 & 1 \tabularnewline
41 & 0 & 0 & 1 \tabularnewline
42 & 0 & 0 & 1 \tabularnewline
43 & 0 & 0 & 1 \tabularnewline
44 & 0 & 0 & 1 \tabularnewline
45 & 0 & 0 & 1 \tabularnewline
46 & 0 & 0 & 1 \tabularnewline
47 & 0 & 0 & 1 \tabularnewline
48 & 0 & 0 & 1 \tabularnewline
49 & 0 & 0 & 1 \tabularnewline
50 & 0 & 0 & 1 \tabularnewline
51 & 0 & 0 & 1 \tabularnewline
52 & 0 & 0 & 1 \tabularnewline
53 & 0 & 0 & 1 \tabularnewline
54 & 0 & 0 & 1 \tabularnewline
55 & 0 & 0 & 1 \tabularnewline
56 & 0 & 0 & 1 \tabularnewline
57 & 0 & 0 & 1 \tabularnewline
58 & 0 & 0 & 1 \tabularnewline
59 & 0 & 0 & 1 \tabularnewline
60 & 0 & 0 & 1 \tabularnewline
61 & 0 & 0 & 1 \tabularnewline
62 & 0 & 0 & 1 \tabularnewline
63 & 0 & 0 & 1 \tabularnewline
64 & 0 & 0 & 1 \tabularnewline
65 & 0 & 0 & 1 \tabularnewline
66 & 2.79218957877237e-10 & 5.58437915754474e-10 & 0.999999999720781 \tabularnewline
67 & 1.50029153100721e-05 & 3.00058306201442e-05 & 0.99998499708469 \tabularnewline
68 & 0.000962250561395929 & 0.00192450112279186 & 0.999037749438604 \tabularnewline
69 & 0.040623527978958 & 0.0812470559579161 & 0.959376472021042 \tabularnewline
70 & 0.129198171068346 & 0.258396342136693 & 0.870801828931653 \tabularnewline
71 & 0.325528188896217 & 0.651056377792434 & 0.674471811103783 \tabularnewline
72 & 0.459195151250064 & 0.918390302500128 & 0.540804848749936 \tabularnewline
73 & 0.508472594401819 & 0.983054811196362 & 0.491527405598181 \tabularnewline
74 & 0.536321720059465 & 0.927356559881069 & 0.463678279940535 \tabularnewline
75 & 0.662744502202178 & 0.674510995595644 & 0.337255497797822 \tabularnewline
76 & 0.680062440295073 & 0.639875119409853 & 0.319937559704927 \tabularnewline
77 & 0.690800156417397 & 0.618399687165206 & 0.309199843582603 \tabularnewline
78 & 0.706752986092479 & 0.586494027815043 & 0.293247013907521 \tabularnewline
79 & 0.737442770868472 & 0.525114458263055 & 0.262557229131528 \tabularnewline
80 & 0.784500877487192 & 0.430998245025617 & 0.215499122512808 \tabularnewline
81 & 0.780285902159877 & 0.439428195680246 & 0.219714097840123 \tabularnewline
82 & 0.779933352421478 & 0.440133295157044 & 0.220066647578522 \tabularnewline
83 & 0.767061731231013 & 0.465876537537975 & 0.232938268768987 \tabularnewline
84 & 0.757191189236148 & 0.485617621527703 & 0.242808810763851 \tabularnewline
85 & 0.741431123709619 & 0.517137752580763 & 0.258568876290381 \tabularnewline
86 & 0.721809431644125 & 0.55638113671175 & 0.278190568355875 \tabularnewline
87 & 0.701413824882016 & 0.597172350235968 & 0.298586175117984 \tabularnewline
88 & 0.682213617867446 & 0.635572764265108 & 0.317786382132554 \tabularnewline
89 & 0.651528021786671 & 0.696943956426658 & 0.348471978213329 \tabularnewline
90 & 0.62622858810692 & 0.74754282378616 & 0.37377141189308 \tabularnewline
91 & 0.59329408832476 & 0.813411823350481 & 0.40670591167524 \tabularnewline
92 & 0.558190036436744 & 0.883619927126512 & 0.441809963563256 \tabularnewline
93 & 0.520699884132653 & 0.958600231734695 & 0.479300115867347 \tabularnewline
94 & 0.488852540064351 & 0.977705080128701 & 0.511147459935649 \tabularnewline
95 & 0.453681578050964 & 0.907363156101928 & 0.546318421949036 \tabularnewline
96 & 0.419626845292599 & 0.839253690585199 & 0.580373154707401 \tabularnewline
97 & 0.385590494333033 & 0.771180988666066 & 0.614409505666967 \tabularnewline
98 & 0.352848708665236 & 0.705697417330472 & 0.647151291334764 \tabularnewline
99 & 0.320575674889999 & 0.641151349779998 & 0.679424325110001 \tabularnewline
100 & 0.290563252438558 & 0.581126504877116 & 0.709436747561442 \tabularnewline
101 & 0.263747796552418 & 0.527495593104836 & 0.736252203447582 \tabularnewline
102 & 0.25176940068452 & 0.503538801369041 & 0.74823059931548 \tabularnewline
103 & 0.22620832964861 & 0.452416659297221 & 0.77379167035139 \tabularnewline
104 & 0.20660131701182 & 0.41320263402364 & 0.79339868298818 \tabularnewline
105 & 0.181664716762434 & 0.363329433524867 & 0.818335283237566 \tabularnewline
106 & 0.164482893335134 & 0.328965786670267 & 0.835517106664866 \tabularnewline
107 & 0.150389017950092 & 0.300778035900184 & 0.849610982049908 \tabularnewline
108 & 0.130936336087044 & 0.261872672174089 & 0.869063663912956 \tabularnewline
109 & 0.116467281196837 & 0.232934562393673 & 0.883532718803163 \tabularnewline
110 & 0.106184889331813 & 0.212369778663625 & 0.893815110668187 \tabularnewline
111 & 0.0934815361117327 & 0.186963072223465 & 0.906518463888267 \tabularnewline
112 & 0.0830427780508101 & 0.16608555610162 & 0.91695722194919 \tabularnewline
113 & 0.0765290820765854 & 0.153058164153171 & 0.923470917923415 \tabularnewline
114 & 0.0666766340943134 & 0.133353268188627 & 0.933323365905687 \tabularnewline
115 & 0.0615942898872609 & 0.123188579774522 & 0.938405710112739 \tabularnewline
116 & 0.0530099303236486 & 0.106019860647297 & 0.946990069676351 \tabularnewline
117 & 0.0458916901495885 & 0.091783380299177 & 0.954108309850412 \tabularnewline
118 & 0.0380392543820244 & 0.0760785087640488 & 0.961960745617976 \tabularnewline
119 & 0.0363489797133631 & 0.0726979594267261 & 0.963651020286637 \tabularnewline
120 & 0.0304347437197581 & 0.0608694874395163 & 0.969565256280242 \tabularnewline
121 & 0.0282691304891818 & 0.0565382609783636 & 0.971730869510818 \tabularnewline
122 & 0.0249811989240756 & 0.0499623978481513 & 0.975018801075924 \tabularnewline
123 & 0.0218308711864303 & 0.0436617423728606 & 0.97816912881357 \tabularnewline
124 & 0.0192568340296081 & 0.0385136680592163 & 0.980743165970392 \tabularnewline
125 & 0.0182348181997006 & 0.0364696363994012 & 0.981765181800299 \tabularnewline
126 & 0.0159697585891423 & 0.0319395171782845 & 0.984030241410858 \tabularnewline
127 & 0.014857471180091 & 0.0297149423601819 & 0.985142528819909 \tabularnewline
128 & 0.0133631812363459 & 0.0267263624726918 & 0.986636818763654 \tabularnewline
129 & 0.0117767292866452 & 0.0235534585732903 & 0.988223270713355 \tabularnewline
130 & 0.0105866078744294 & 0.0211732157488589 & 0.989413392125571 \tabularnewline
131 & 0.0101352305406098 & 0.0202704610812196 & 0.98986476945939 \tabularnewline
132 & 0.00896204392499736 & 0.0179240878499947 & 0.991037956075003 \tabularnewline
133 & 0.00862319912131974 & 0.0172463982426395 & 0.99137680087868 \tabularnewline
134 & 0.00820012575950873 & 0.0164002515190175 & 0.991799874240491 \tabularnewline
135 & 0.00879621840095415 & 0.0175924368019083 & 0.991203781599046 \tabularnewline
136 & 0.00915250727493475 & 0.0183050145498695 & 0.990847492725065 \tabularnewline
137 & 0.0083533249054657 & 0.0167066498109314 & 0.991646675094534 \tabularnewline
138 & 0.00753350283426252 & 0.015067005668525 & 0.992466497165737 \tabularnewline
139 & 0.00655593971707425 & 0.0131118794341485 & 0.993444060282926 \tabularnewline
140 & 0.00666832918579539 & 0.0133366583715908 & 0.993331670814205 \tabularnewline
141 & 0.00614706502863302 & 0.012294130057266 & 0.993852934971367 \tabularnewline
142 & 0.0074239938922078 & 0.0148479877844156 & 0.992576006107792 \tabularnewline
143 & 0.0111879451433628 & 0.0223758902867256 & 0.988812054856637 \tabularnewline
144 & 0.0141806178983872 & 0.0283612357967743 & 0.985819382101613 \tabularnewline
145 & 0.0152026398311 & 0.0304052796622 & 0.9847973601689 \tabularnewline
146 & 0.0226736168284913 & 0.0453472336569825 & 0.977326383171509 \tabularnewline
147 & 0.0268479791374476 & 0.0536959582748951 & 0.973152020862552 \tabularnewline
148 & 0.0385190014986523 & 0.0770380029973046 & 0.961480998501348 \tabularnewline
149 & 0.0497523090810142 & 0.0995046181620284 & 0.950247690918986 \tabularnewline
150 & 0.0572577978483137 & 0.114515595696627 & 0.942742202151686 \tabularnewline
151 & 0.108070197446161 & 0.216140394892322 & 0.891929802553839 \tabularnewline
152 & 0.151450028779522 & 0.302900057559043 & 0.848549971220478 \tabularnewline
153 & 0.176247998942316 & 0.352495997884632 & 0.823752001057684 \tabularnewline
154 & 0.986092926252912 & 0.0278141474941756 & 0.0139070737470878 \tabularnewline
155 & 0.996433848893023 & 0.00713230221395332 & 0.00356615110697666 \tabularnewline
156 & 0.9998856969934 & 0.000228606013200582 & 0.000114303006600291 \tabularnewline
157 & 0.999991529456667 & 1.69410866668003e-05 & 8.47054333340017e-06 \tabularnewline
158 & 0.999999915137403 & 1.6972519444801e-07 & 8.48625972240048e-08 \tabularnewline
159 & 0.999999999999006 & 1.98744894469144e-12 & 9.93724472345721e-13 \tabularnewline
160 & 1 & 6.22729547574856e-22 & 3.11364773787428e-22 \tabularnewline
161 & 1 & 0 & 0 \tabularnewline
162 & 1 & 0 & 0 \tabularnewline
163 & 1 & 0 & 0 \tabularnewline
164 & 1 & 0 & 0 \tabularnewline
165 & 1 & 0 & 0 \tabularnewline
166 & 1 & 0 & 0 \tabularnewline
167 & 1 & 0 & 0 \tabularnewline
168 & 1 & 0 & 0 \tabularnewline
169 & 1 & 0 & 0 \tabularnewline
170 & 1 & 0 & 0 \tabularnewline
171 & 1 & 0 & 0 \tabularnewline
172 & 1 & 0 & 0 \tabularnewline
173 & 1 & 0 & 0 \tabularnewline
174 & 1 & 0 & 0 \tabularnewline
175 & 1 & 0 & 0 \tabularnewline
176 & 1 & 0 & 0 \tabularnewline
177 & 1 & 0 & 0 \tabularnewline
178 & 1 & 0 & 0 \tabularnewline
179 & 1 & 0 & 0 \tabularnewline
180 & 1 & 0 & 0 \tabularnewline
181 & 1 & 0 & 0 \tabularnewline
182 & 1 & 0 & 0 \tabularnewline
183 & 1 & 0 & 0 \tabularnewline
184 & 1 & 0 & 0 \tabularnewline
185 & 1 & 0 & 0 \tabularnewline
186 & 1 & 0 & 0 \tabularnewline
187 & 1 & 0 & 0 \tabularnewline
188 & 1 & 0 & 0 \tabularnewline
189 & 1 & 0 & 0 \tabularnewline
190 & 1 & 0 & 0 \tabularnewline
191 & 1 & 0 & 0 \tabularnewline
192 & 1 & 0 & 0 \tabularnewline
193 & 1 & 0 & 0 \tabularnewline
194 & 1 & 0 & 0 \tabularnewline
195 & 1 & 0 & 0 \tabularnewline
196 & 1 & 0 & 0 \tabularnewline
197 & 1 & 0 & 0 \tabularnewline
198 & 1 & 0 & 0 \tabularnewline
199 & 1 & 0 & 0 \tabularnewline
200 & 1 & 0 & 0 \tabularnewline
201 & 1 & 0 & 0 \tabularnewline
202 & 1 & 0 & 0 \tabularnewline
203 & 1 & 0 & 0 \tabularnewline
204 & 1 & 0 & 0 \tabularnewline
205 & 1 & 0 & 0 \tabularnewline
206 & 1 & 0 & 0 \tabularnewline
207 & 1 & 0 & 0 \tabularnewline
208 & 1 & 0 & 0 \tabularnewline
209 & 1 & 0 & 0 \tabularnewline
210 & 1 & 0 & 0 \tabularnewline
211 & 1 & 0 & 0 \tabularnewline
212 & 1 & 0 & 0 \tabularnewline
213 & 1 & 0 & 0 \tabularnewline
214 & 1 & 0 & 0 \tabularnewline
215 & 1 & 0 & 0 \tabularnewline
216 & 1 & 0 & 0 \tabularnewline
217 & 1 & 0 & 0 \tabularnewline
218 & 1 & 0 & 0 \tabularnewline
219 & 1 & 0 & 0 \tabularnewline
220 & 1 & 0 & 0 \tabularnewline
221 & 1 & 0 & 0 \tabularnewline
222 & 1 & 0 & 0 \tabularnewline
223 & 1 & 0 & 0 \tabularnewline
224 & 1 & 0 & 0 \tabularnewline
225 & 1 & 0 & 0 \tabularnewline
226 & 1 & 0 & 0 \tabularnewline
227 & 1 & 0 & 0 \tabularnewline
228 & 1 & 0 & 0 \tabularnewline
229 & 1 & 0 & 0 \tabularnewline
230 & 1 & 0 & 0 \tabularnewline
231 & 1 & 8.89318162514244e-323 & 4.44659081257122e-323 \tabularnewline
232 & 1 & 0 & 0 \tabularnewline
233 & 1 & 1.42508847055468e-301 & 7.12544235277339e-302 \tabularnewline
234 & 1 & 6.58885218615726e-282 & 3.29442609307863e-282 \tabularnewline
235 & 1 & 4.53122932017209e-278 & 2.26561466008605e-278 \tabularnewline
236 & 1 & 8.18512046626044e-255 & 4.09256023313022e-255 \tabularnewline
237 & 1 & 3.30447112179486e-246 & 1.65223556089743e-246 \tabularnewline
238 & 1 & 4.40341240918453e-229 & 2.20170620459226e-229 \tabularnewline
239 & 1 & 2.7432485575654e-210 & 1.3716242787827e-210 \tabularnewline
240 & 1 & 5.99499665990184e-213 & 2.99749832995092e-213 \tabularnewline
241 & 1 & 1.12557542912217e-191 & 5.62787714561084e-192 \tabularnewline
242 & 1 & 5.58310623006506e-170 & 2.79155311503253e-170 \tabularnewline
243 & 1 & 3.8180489433327e-165 & 1.90902447166635e-165 \tabularnewline
244 & 1 & 2.6578638712862e-150 & 1.3289319356431e-150 \tabularnewline
245 & 1 & 3.76336200059293e-130 & 1.88168100029647e-130 \tabularnewline
246 & 1 & 6.16541862518434e-126 & 3.08270931259217e-126 \tabularnewline
247 & 1 & 8.4129529406902e-101 & 4.2064764703451e-101 \tabularnewline
248 & 1 & 0 & 0 \tabularnewline
249 & 1 & 7.02966118217007e-73 & 3.51483059108504e-73 \tabularnewline
250 & 1 & 1.13375144838089e-56 & 5.66875724190444e-57 \tabularnewline
251 & 1 & 3.95062559713948e-47 & 1.97531279856974e-47 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203885&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]13[/C][C]2.28031440419649e-45[/C][C]4.56062880839299e-45[/C][C]1[/C][/ROW]
[ROW][C]14[/C][C]3.52074781612403e-58[/C][C]7.04149563224807e-58[/C][C]1[/C][/ROW]
[ROW][C]15[/C][C]1.37240212232936e-71[/C][C]2.74480424465872e-71[/C][C]1[/C][/ROW]
[ROW][C]16[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]17[/C][C]2.44661104114883e-100[/C][C]4.89322208229766e-100[/C][C]1[/C][/ROW]
[ROW][C]18[/C][C]1.17462262798987e-115[/C][C]2.34924525597975e-115[/C][C]1[/C][/ROW]
[ROW][C]19[/C][C]8.40628824171353e-131[/C][C]1.68125764834271e-130[/C][C]1[/C][/ROW]
[ROW][C]20[/C][C]1.57362553166883e-151[/C][C]3.14725106333765e-151[/C][C]1[/C][/ROW]
[ROW][C]21[/C][C]2.22491956742789e-161[/C][C]4.44983913485577e-161[/C][C]1[/C][/ROW]
[ROW][C]22[/C][C]7.26087101488634e-174[/C][C]1.45217420297727e-173[/C][C]1[/C][/ROW]
[ROW][C]23[/C][C]1.22564516113724e-185[/C][C]2.45129032227448e-185[/C][C]1[/C][/ROW]
[ROW][C]24[/C][C]3.29210325268509e-207[/C][C]6.58420650537018e-207[/C][C]1[/C][/ROW]
[ROW][C]25[/C][C]1.07995376533312e-220[/C][C]2.15990753066625e-220[/C][C]1[/C][/ROW]
[ROW][C]26[/C][C]3.14753741916471e-238[/C][C]6.29507483832942e-238[/C][C]1[/C][/ROW]
[ROW][C]27[/C][C]9.97277301117504e-249[/C][C]1.99455460223501e-248[/C][C]1[/C][/ROW]
[ROW][C]28[/C][C]6.08178185605501e-262[/C][C]1.216356371211e-261[/C][C]1[/C][/ROW]
[ROW][C]29[/C][C]5.66667736639293e-286[/C][C]1.13333547327859e-285[/C][C]1[/C][/ROW]
[ROW][C]30[/C][C]2.55506510780961e-283[/C][C]5.11013021561921e-283[/C][C]1[/C][/ROW]
[ROW][C]31[/C][C]1.49687044176093e-306[/C][C]2.99374088352186e-306[/C][C]1[/C][/ROW]
[ROW][C]32[/C][C]4.94065645841247e-324[/C][C]9.88131291682493e-324[/C][C]1[/C][/ROW]
[ROW][C]33[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]34[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]35[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]36[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]37[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]38[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]39[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]42[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]44[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]45[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]46[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]47[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]48[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]49[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]50[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]51[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]54[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]55[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]56[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]58[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]60[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]61[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]63[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]64[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]65[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]66[/C][C]2.79218957877237e-10[/C][C]5.58437915754474e-10[/C][C]0.999999999720781[/C][/ROW]
[ROW][C]67[/C][C]1.50029153100721e-05[/C][C]3.00058306201442e-05[/C][C]0.99998499708469[/C][/ROW]
[ROW][C]68[/C][C]0.000962250561395929[/C][C]0.00192450112279186[/C][C]0.999037749438604[/C][/ROW]
[ROW][C]69[/C][C]0.040623527978958[/C][C]0.0812470559579161[/C][C]0.959376472021042[/C][/ROW]
[ROW][C]70[/C][C]0.129198171068346[/C][C]0.258396342136693[/C][C]0.870801828931653[/C][/ROW]
[ROW][C]71[/C][C]0.325528188896217[/C][C]0.651056377792434[/C][C]0.674471811103783[/C][/ROW]
[ROW][C]72[/C][C]0.459195151250064[/C][C]0.918390302500128[/C][C]0.540804848749936[/C][/ROW]
[ROW][C]73[/C][C]0.508472594401819[/C][C]0.983054811196362[/C][C]0.491527405598181[/C][/ROW]
[ROW][C]74[/C][C]0.536321720059465[/C][C]0.927356559881069[/C][C]0.463678279940535[/C][/ROW]
[ROW][C]75[/C][C]0.662744502202178[/C][C]0.674510995595644[/C][C]0.337255497797822[/C][/ROW]
[ROW][C]76[/C][C]0.680062440295073[/C][C]0.639875119409853[/C][C]0.319937559704927[/C][/ROW]
[ROW][C]77[/C][C]0.690800156417397[/C][C]0.618399687165206[/C][C]0.309199843582603[/C][/ROW]
[ROW][C]78[/C][C]0.706752986092479[/C][C]0.586494027815043[/C][C]0.293247013907521[/C][/ROW]
[ROW][C]79[/C][C]0.737442770868472[/C][C]0.525114458263055[/C][C]0.262557229131528[/C][/ROW]
[ROW][C]80[/C][C]0.784500877487192[/C][C]0.430998245025617[/C][C]0.215499122512808[/C][/ROW]
[ROW][C]81[/C][C]0.780285902159877[/C][C]0.439428195680246[/C][C]0.219714097840123[/C][/ROW]
[ROW][C]82[/C][C]0.779933352421478[/C][C]0.440133295157044[/C][C]0.220066647578522[/C][/ROW]
[ROW][C]83[/C][C]0.767061731231013[/C][C]0.465876537537975[/C][C]0.232938268768987[/C][/ROW]
[ROW][C]84[/C][C]0.757191189236148[/C][C]0.485617621527703[/C][C]0.242808810763851[/C][/ROW]
[ROW][C]85[/C][C]0.741431123709619[/C][C]0.517137752580763[/C][C]0.258568876290381[/C][/ROW]
[ROW][C]86[/C][C]0.721809431644125[/C][C]0.55638113671175[/C][C]0.278190568355875[/C][/ROW]
[ROW][C]87[/C][C]0.701413824882016[/C][C]0.597172350235968[/C][C]0.298586175117984[/C][/ROW]
[ROW][C]88[/C][C]0.682213617867446[/C][C]0.635572764265108[/C][C]0.317786382132554[/C][/ROW]
[ROW][C]89[/C][C]0.651528021786671[/C][C]0.696943956426658[/C][C]0.348471978213329[/C][/ROW]
[ROW][C]90[/C][C]0.62622858810692[/C][C]0.74754282378616[/C][C]0.37377141189308[/C][/ROW]
[ROW][C]91[/C][C]0.59329408832476[/C][C]0.813411823350481[/C][C]0.40670591167524[/C][/ROW]
[ROW][C]92[/C][C]0.558190036436744[/C][C]0.883619927126512[/C][C]0.441809963563256[/C][/ROW]
[ROW][C]93[/C][C]0.520699884132653[/C][C]0.958600231734695[/C][C]0.479300115867347[/C][/ROW]
[ROW][C]94[/C][C]0.488852540064351[/C][C]0.977705080128701[/C][C]0.511147459935649[/C][/ROW]
[ROW][C]95[/C][C]0.453681578050964[/C][C]0.907363156101928[/C][C]0.546318421949036[/C][/ROW]
[ROW][C]96[/C][C]0.419626845292599[/C][C]0.839253690585199[/C][C]0.580373154707401[/C][/ROW]
[ROW][C]97[/C][C]0.385590494333033[/C][C]0.771180988666066[/C][C]0.614409505666967[/C][/ROW]
[ROW][C]98[/C][C]0.352848708665236[/C][C]0.705697417330472[/C][C]0.647151291334764[/C][/ROW]
[ROW][C]99[/C][C]0.320575674889999[/C][C]0.641151349779998[/C][C]0.679424325110001[/C][/ROW]
[ROW][C]100[/C][C]0.290563252438558[/C][C]0.581126504877116[/C][C]0.709436747561442[/C][/ROW]
[ROW][C]101[/C][C]0.263747796552418[/C][C]0.527495593104836[/C][C]0.736252203447582[/C][/ROW]
[ROW][C]102[/C][C]0.25176940068452[/C][C]0.503538801369041[/C][C]0.74823059931548[/C][/ROW]
[ROW][C]103[/C][C]0.22620832964861[/C][C]0.452416659297221[/C][C]0.77379167035139[/C][/ROW]
[ROW][C]104[/C][C]0.20660131701182[/C][C]0.41320263402364[/C][C]0.79339868298818[/C][/ROW]
[ROW][C]105[/C][C]0.181664716762434[/C][C]0.363329433524867[/C][C]0.818335283237566[/C][/ROW]
[ROW][C]106[/C][C]0.164482893335134[/C][C]0.328965786670267[/C][C]0.835517106664866[/C][/ROW]
[ROW][C]107[/C][C]0.150389017950092[/C][C]0.300778035900184[/C][C]0.849610982049908[/C][/ROW]
[ROW][C]108[/C][C]0.130936336087044[/C][C]0.261872672174089[/C][C]0.869063663912956[/C][/ROW]
[ROW][C]109[/C][C]0.116467281196837[/C][C]0.232934562393673[/C][C]0.883532718803163[/C][/ROW]
[ROW][C]110[/C][C]0.106184889331813[/C][C]0.212369778663625[/C][C]0.893815110668187[/C][/ROW]
[ROW][C]111[/C][C]0.0934815361117327[/C][C]0.186963072223465[/C][C]0.906518463888267[/C][/ROW]
[ROW][C]112[/C][C]0.0830427780508101[/C][C]0.16608555610162[/C][C]0.91695722194919[/C][/ROW]
[ROW][C]113[/C][C]0.0765290820765854[/C][C]0.153058164153171[/C][C]0.923470917923415[/C][/ROW]
[ROW][C]114[/C][C]0.0666766340943134[/C][C]0.133353268188627[/C][C]0.933323365905687[/C][/ROW]
[ROW][C]115[/C][C]0.0615942898872609[/C][C]0.123188579774522[/C][C]0.938405710112739[/C][/ROW]
[ROW][C]116[/C][C]0.0530099303236486[/C][C]0.106019860647297[/C][C]0.946990069676351[/C][/ROW]
[ROW][C]117[/C][C]0.0458916901495885[/C][C]0.091783380299177[/C][C]0.954108309850412[/C][/ROW]
[ROW][C]118[/C][C]0.0380392543820244[/C][C]0.0760785087640488[/C][C]0.961960745617976[/C][/ROW]
[ROW][C]119[/C][C]0.0363489797133631[/C][C]0.0726979594267261[/C][C]0.963651020286637[/C][/ROW]
[ROW][C]120[/C][C]0.0304347437197581[/C][C]0.0608694874395163[/C][C]0.969565256280242[/C][/ROW]
[ROW][C]121[/C][C]0.0282691304891818[/C][C]0.0565382609783636[/C][C]0.971730869510818[/C][/ROW]
[ROW][C]122[/C][C]0.0249811989240756[/C][C]0.0499623978481513[/C][C]0.975018801075924[/C][/ROW]
[ROW][C]123[/C][C]0.0218308711864303[/C][C]0.0436617423728606[/C][C]0.97816912881357[/C][/ROW]
[ROW][C]124[/C][C]0.0192568340296081[/C][C]0.0385136680592163[/C][C]0.980743165970392[/C][/ROW]
[ROW][C]125[/C][C]0.0182348181997006[/C][C]0.0364696363994012[/C][C]0.981765181800299[/C][/ROW]
[ROW][C]126[/C][C]0.0159697585891423[/C][C]0.0319395171782845[/C][C]0.984030241410858[/C][/ROW]
[ROW][C]127[/C][C]0.014857471180091[/C][C]0.0297149423601819[/C][C]0.985142528819909[/C][/ROW]
[ROW][C]128[/C][C]0.0133631812363459[/C][C]0.0267263624726918[/C][C]0.986636818763654[/C][/ROW]
[ROW][C]129[/C][C]0.0117767292866452[/C][C]0.0235534585732903[/C][C]0.988223270713355[/C][/ROW]
[ROW][C]130[/C][C]0.0105866078744294[/C][C]0.0211732157488589[/C][C]0.989413392125571[/C][/ROW]
[ROW][C]131[/C][C]0.0101352305406098[/C][C]0.0202704610812196[/C][C]0.98986476945939[/C][/ROW]
[ROW][C]132[/C][C]0.00896204392499736[/C][C]0.0179240878499947[/C][C]0.991037956075003[/C][/ROW]
[ROW][C]133[/C][C]0.00862319912131974[/C][C]0.0172463982426395[/C][C]0.99137680087868[/C][/ROW]
[ROW][C]134[/C][C]0.00820012575950873[/C][C]0.0164002515190175[/C][C]0.991799874240491[/C][/ROW]
[ROW][C]135[/C][C]0.00879621840095415[/C][C]0.0175924368019083[/C][C]0.991203781599046[/C][/ROW]
[ROW][C]136[/C][C]0.00915250727493475[/C][C]0.0183050145498695[/C][C]0.990847492725065[/C][/ROW]
[ROW][C]137[/C][C]0.0083533249054657[/C][C]0.0167066498109314[/C][C]0.991646675094534[/C][/ROW]
[ROW][C]138[/C][C]0.00753350283426252[/C][C]0.015067005668525[/C][C]0.992466497165737[/C][/ROW]
[ROW][C]139[/C][C]0.00655593971707425[/C][C]0.0131118794341485[/C][C]0.993444060282926[/C][/ROW]
[ROW][C]140[/C][C]0.00666832918579539[/C][C]0.0133366583715908[/C][C]0.993331670814205[/C][/ROW]
[ROW][C]141[/C][C]0.00614706502863302[/C][C]0.012294130057266[/C][C]0.993852934971367[/C][/ROW]
[ROW][C]142[/C][C]0.0074239938922078[/C][C]0.0148479877844156[/C][C]0.992576006107792[/C][/ROW]
[ROW][C]143[/C][C]0.0111879451433628[/C][C]0.0223758902867256[/C][C]0.988812054856637[/C][/ROW]
[ROW][C]144[/C][C]0.0141806178983872[/C][C]0.0283612357967743[/C][C]0.985819382101613[/C][/ROW]
[ROW][C]145[/C][C]0.0152026398311[/C][C]0.0304052796622[/C][C]0.9847973601689[/C][/ROW]
[ROW][C]146[/C][C]0.0226736168284913[/C][C]0.0453472336569825[/C][C]0.977326383171509[/C][/ROW]
[ROW][C]147[/C][C]0.0268479791374476[/C][C]0.0536959582748951[/C][C]0.973152020862552[/C][/ROW]
[ROW][C]148[/C][C]0.0385190014986523[/C][C]0.0770380029973046[/C][C]0.961480998501348[/C][/ROW]
[ROW][C]149[/C][C]0.0497523090810142[/C][C]0.0995046181620284[/C][C]0.950247690918986[/C][/ROW]
[ROW][C]150[/C][C]0.0572577978483137[/C][C]0.114515595696627[/C][C]0.942742202151686[/C][/ROW]
[ROW][C]151[/C][C]0.108070197446161[/C][C]0.216140394892322[/C][C]0.891929802553839[/C][/ROW]
[ROW][C]152[/C][C]0.151450028779522[/C][C]0.302900057559043[/C][C]0.848549971220478[/C][/ROW]
[ROW][C]153[/C][C]0.176247998942316[/C][C]0.352495997884632[/C][C]0.823752001057684[/C][/ROW]
[ROW][C]154[/C][C]0.986092926252912[/C][C]0.0278141474941756[/C][C]0.0139070737470878[/C][/ROW]
[ROW][C]155[/C][C]0.996433848893023[/C][C]0.00713230221395332[/C][C]0.00356615110697666[/C][/ROW]
[ROW][C]156[/C][C]0.9998856969934[/C][C]0.000228606013200582[/C][C]0.000114303006600291[/C][/ROW]
[ROW][C]157[/C][C]0.999991529456667[/C][C]1.69410866668003e-05[/C][C]8.47054333340017e-06[/C][/ROW]
[ROW][C]158[/C][C]0.999999915137403[/C][C]1.6972519444801e-07[/C][C]8.48625972240048e-08[/C][/ROW]
[ROW][C]159[/C][C]0.999999999999006[/C][C]1.98744894469144e-12[/C][C]9.93724472345721e-13[/C][/ROW]
[ROW][C]160[/C][C]1[/C][C]6.22729547574856e-22[/C][C]3.11364773787428e-22[/C][/ROW]
[ROW][C]161[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]162[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]166[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]167[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]168[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]169[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]170[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]171[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]172[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]173[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]174[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]175[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]176[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]177[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]179[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]181[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]182[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]184[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]185[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]186[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]187[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]188[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]189[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]190[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]191[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]192[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]193[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]194[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]195[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]196[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]197[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]198[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]199[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]200[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]201[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]202[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]203[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]204[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]205[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]206[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]207[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]208[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]209[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]210[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]211[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]212[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]213[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]214[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]215[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]216[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]217[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]218[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]219[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]220[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]221[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]222[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]223[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]224[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]225[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]226[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]227[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]228[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]229[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]230[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]231[/C][C]1[/C][C]8.89318162514244e-323[/C][C]4.44659081257122e-323[/C][/ROW]
[ROW][C]232[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]233[/C][C]1[/C][C]1.42508847055468e-301[/C][C]7.12544235277339e-302[/C][/ROW]
[ROW][C]234[/C][C]1[/C][C]6.58885218615726e-282[/C][C]3.29442609307863e-282[/C][/ROW]
[ROW][C]235[/C][C]1[/C][C]4.53122932017209e-278[/C][C]2.26561466008605e-278[/C][/ROW]
[ROW][C]236[/C][C]1[/C][C]8.18512046626044e-255[/C][C]4.09256023313022e-255[/C][/ROW]
[ROW][C]237[/C][C]1[/C][C]3.30447112179486e-246[/C][C]1.65223556089743e-246[/C][/ROW]
[ROW][C]238[/C][C]1[/C][C]4.40341240918453e-229[/C][C]2.20170620459226e-229[/C][/ROW]
[ROW][C]239[/C][C]1[/C][C]2.7432485575654e-210[/C][C]1.3716242787827e-210[/C][/ROW]
[ROW][C]240[/C][C]1[/C][C]5.99499665990184e-213[/C][C]2.99749832995092e-213[/C][/ROW]
[ROW][C]241[/C][C]1[/C][C]1.12557542912217e-191[/C][C]5.62787714561084e-192[/C][/ROW]
[ROW][C]242[/C][C]1[/C][C]5.58310623006506e-170[/C][C]2.79155311503253e-170[/C][/ROW]
[ROW][C]243[/C][C]1[/C][C]3.8180489433327e-165[/C][C]1.90902447166635e-165[/C][/ROW]
[ROW][C]244[/C][C]1[/C][C]2.6578638712862e-150[/C][C]1.3289319356431e-150[/C][/ROW]
[ROW][C]245[/C][C]1[/C][C]3.76336200059293e-130[/C][C]1.88168100029647e-130[/C][/ROW]
[ROW][C]246[/C][C]1[/C][C]6.16541862518434e-126[/C][C]3.08270931259217e-126[/C][/ROW]
[ROW][C]247[/C][C]1[/C][C]8.4129529406902e-101[/C][C]4.2064764703451e-101[/C][/ROW]
[ROW][C]248[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]249[/C][C]1[/C][C]7.02966118217007e-73[/C][C]3.51483059108504e-73[/C][/ROW]
[ROW][C]250[/C][C]1[/C][C]1.13375144838089e-56[/C][C]5.66875724190444e-57[/C][/ROW]
[ROW][C]251[/C][C]1[/C][C]3.95062559713948e-47[/C][C]1.97531279856974e-47[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203885&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203885&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
132.28031440419649e-454.56062880839299e-451
143.52074781612403e-587.04149563224807e-581
151.37240212232936e-712.74480424465872e-711
16001
172.44661104114883e-1004.89322208229766e-1001
181.17462262798987e-1152.34924525597975e-1151
198.40628824171353e-1311.68125764834271e-1301
201.57362553166883e-1513.14725106333765e-1511
212.22491956742789e-1614.44983913485577e-1611
227.26087101488634e-1741.45217420297727e-1731
231.22564516113724e-1852.45129032227448e-1851
243.29210325268509e-2076.58420650537018e-2071
251.07995376533312e-2202.15990753066625e-2201
263.14753741916471e-2386.29507483832942e-2381
279.97277301117504e-2491.99455460223501e-2481
286.08178185605501e-2621.216356371211e-2611
295.66667736639293e-2861.13333547327859e-2851
302.55506510780961e-2835.11013021561921e-2831
311.49687044176093e-3062.99374088352186e-3061
324.94065645841247e-3249.88131291682493e-3241
33001
34001
35001
36001
37001
38001
39001
40001
41001
42001
43001
44001
45001
46001
47001
48001
49001
50001
51001
52001
53001
54001
55001
56001
57001
58001
59001
60001
61001
62001
63001
64001
65001
662.79218957877237e-105.58437915754474e-100.999999999720781
671.50029153100721e-053.00058306201442e-050.99998499708469
680.0009622505613959290.001924501122791860.999037749438604
690.0406235279789580.08124705595791610.959376472021042
700.1291981710683460.2583963421366930.870801828931653
710.3255281888962170.6510563777924340.674471811103783
720.4591951512500640.9183903025001280.540804848749936
730.5084725944018190.9830548111963620.491527405598181
740.5363217200594650.9273565598810690.463678279940535
750.6627445022021780.6745109955956440.337255497797822
760.6800624402950730.6398751194098530.319937559704927
770.6908001564173970.6183996871652060.309199843582603
780.7067529860924790.5864940278150430.293247013907521
790.7374427708684720.5251144582630550.262557229131528
800.7845008774871920.4309982450256170.215499122512808
810.7802859021598770.4394281956802460.219714097840123
820.7799333524214780.4401332951570440.220066647578522
830.7670617312310130.4658765375379750.232938268768987
840.7571911892361480.4856176215277030.242808810763851
850.7414311237096190.5171377525807630.258568876290381
860.7218094316441250.556381136711750.278190568355875
870.7014138248820160.5971723502359680.298586175117984
880.6822136178674460.6355727642651080.317786382132554
890.6515280217866710.6969439564266580.348471978213329
900.626228588106920.747542823786160.37377141189308
910.593294088324760.8134118233504810.40670591167524
920.5581900364367440.8836199271265120.441809963563256
930.5206998841326530.9586002317346950.479300115867347
940.4888525400643510.9777050801287010.511147459935649
950.4536815780509640.9073631561019280.546318421949036
960.4196268452925990.8392536905851990.580373154707401
970.3855904943330330.7711809886660660.614409505666967
980.3528487086652360.7056974173304720.647151291334764
990.3205756748899990.6411513497799980.679424325110001
1000.2905632524385580.5811265048771160.709436747561442
1010.2637477965524180.5274955931048360.736252203447582
1020.251769400684520.5035388013690410.74823059931548
1030.226208329648610.4524166592972210.77379167035139
1040.206601317011820.413202634023640.79339868298818
1050.1816647167624340.3633294335248670.818335283237566
1060.1644828933351340.3289657866702670.835517106664866
1070.1503890179500920.3007780359001840.849610982049908
1080.1309363360870440.2618726721740890.869063663912956
1090.1164672811968370.2329345623936730.883532718803163
1100.1061848893318130.2123697786636250.893815110668187
1110.09348153611173270.1869630722234650.906518463888267
1120.08304277805081010.166085556101620.91695722194919
1130.07652908207658540.1530581641531710.923470917923415
1140.06667663409431340.1333532681886270.933323365905687
1150.06159428988726090.1231885797745220.938405710112739
1160.05300993032364860.1060198606472970.946990069676351
1170.04589169014958850.0917833802991770.954108309850412
1180.03803925438202440.07607850876404880.961960745617976
1190.03634897971336310.07269795942672610.963651020286637
1200.03043474371975810.06086948743951630.969565256280242
1210.02826913048918180.05653826097836360.971730869510818
1220.02498119892407560.04996239784815130.975018801075924
1230.02183087118643030.04366174237286060.97816912881357
1240.01925683402960810.03851366805921630.980743165970392
1250.01823481819970060.03646963639940120.981765181800299
1260.01596975858914230.03193951717828450.984030241410858
1270.0148574711800910.02971494236018190.985142528819909
1280.01336318123634590.02672636247269180.986636818763654
1290.01177672928664520.02355345857329030.988223270713355
1300.01058660787442940.02117321574885890.989413392125571
1310.01013523054060980.02027046108121960.98986476945939
1320.008962043924997360.01792408784999470.991037956075003
1330.008623199121319740.01724639824263950.99137680087868
1340.008200125759508730.01640025151901750.991799874240491
1350.008796218400954150.01759243680190830.991203781599046
1360.009152507274934750.01830501454986950.990847492725065
1370.00835332490546570.01670664981093140.991646675094534
1380.007533502834262520.0150670056685250.992466497165737
1390.006555939717074250.01311187943414850.993444060282926
1400.006668329185795390.01333665837159080.993331670814205
1410.006147065028633020.0122941300572660.993852934971367
1420.00742399389220780.01484798778441560.992576006107792
1430.01118794514336280.02237589028672560.988812054856637
1440.01418061789838720.02836123579677430.985819382101613
1450.01520263983110.03040527966220.9847973601689
1460.02267361682849130.04534723365698250.977326383171509
1470.02684797913744760.05369595827489510.973152020862552
1480.03851900149865230.07703800299730460.961480998501348
1490.04975230908101420.09950461816202840.950247690918986
1500.05725779784831370.1145155956966270.942742202151686
1510.1080701974461610.2161403948923220.891929802553839
1520.1514500287795220.3029000575590430.848549971220478
1530.1762479989423160.3524959978846320.823752001057684
1540.9860929262529120.02781414749417560.0139070737470878
1550.9964338488930230.007132302213953320.00356615110697666
1560.99988569699340.0002286060132005820.000114303006600291
1570.9999915294566671.69410866668003e-058.47054333340017e-06
1580.9999999151374031.6972519444801e-078.48625972240048e-08
1590.9999999999990061.98744894469144e-129.93724472345721e-13
16016.22729547574856e-223.11364773787428e-22
161100
162100
163100
164100
165100
166100
167100
168100
169100
170100
171100
172100
173100
174100
175100
176100
177100
178100
179100
180100
181100
182100
183100
184100
185100
186100
187100
188100
189100
190100
191100
192100
193100
194100
195100
196100
197100
198100
199100
200100
201100
202100
203100
204100
205100
206100
207100
208100
209100
210100
211100
212100
213100
214100
215100
216100
217100
218100
219100
220100
221100
222100
223100
224100
225100
226100
227100
228100
229100
230100
23118.89318162514244e-3234.44659081257122e-323
232100
23311.42508847055468e-3017.12544235277339e-302
23416.58885218615726e-2823.29442609307863e-282
23514.53122932017209e-2782.26561466008605e-278
23618.18512046626044e-2554.09256023313022e-255
23713.30447112179486e-2461.65223556089743e-246
23814.40341240918453e-2292.20170620459226e-229
23912.7432485575654e-2101.3716242787827e-210
24015.99499665990184e-2132.99749832995092e-213
24111.12557542912217e-1915.62787714561084e-192
24215.58310623006506e-1702.79155311503253e-170
24313.8180489433327e-1651.90902447166635e-165
24412.6578638712862e-1501.3289319356431e-150
24513.76336200059293e-1301.88168100029647e-130
24616.16541862518434e-1263.08270931259217e-126
24718.4129529406902e-1014.2064764703451e-101
248100
24917.02966118217007e-733.51483059108504e-73
25011.13375144838089e-565.66875724190444e-57
25113.95062559713948e-471.97531279856974e-47







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1530.640167364016736NOK
5% type I error level1790.748953974895398NOK
10% type I error level1880.786610878661088NOK

\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 & 153 & 0.640167364016736 & NOK \tabularnewline
5% type I error level & 179 & 0.748953974895398 & NOK \tabularnewline
10% type I error level & 188 & 0.786610878661088 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203885&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]153[/C][C]0.640167364016736[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]179[/C][C]0.748953974895398[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]188[/C][C]0.786610878661088[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203885&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203885&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 level1530.640167364016736NOK
5% type I error level1790.748953974895398NOK
10% type I error level1880.786610878661088NOK



Parameters (Session):
par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; 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')
}