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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 17 Nov 2010 09:28:57 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/17/t1289986052iuu6wbiswsl22l0.htm/, Retrieved Fri, 26 Apr 2024 02:30:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=96551, Retrieved Fri, 26 Apr 2024 02:30:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact135

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2010-11-17 09:28:57] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	9	41	38	13	12	14	12	53
1	9	39	32	16	11	18	11	83
1	9	30	35	19	15	11	14	66
1	9	31	33	15	6	12	12	67
1	9	34	37	14	13	16	21	76
1	9	35	29	13	10	18	12	78
1	9	39	31	19	12	14	22	53
1	9	34	36	15	14	14	11	80
1	9	36	35	14	12	15	10	74
1	9	37	38	15	9	15	13	76
1	9	38	31	16	10	17	10	79
1	9	36	34	16	12	19	8	54
1	9	38	35	16	12	10	15	67
1	9	39	38	16	11	16	14	54
1	9	33	37	17	15	18	10	87
1	9	32	33	15	12	14	14	58
1	9	36	32	15	10	14	14	75
1	9	38	38	20	12	17	11	88
1	9	39	38	18	11	14	10	64
1	9	32	32	16	12	16	13	57
1	9	32	33	16	11	18	9.5	66
1	9	31	31	16	12	11	14	68
1	9	39	38	19	13	14	12	54
1	9	37	39	16	11	12	14	56
1	9	39	32	17	12	17	11	86
1	9	41	32	17	13	9	9	80
1	9	36	35	16	10	16	11	76
1	9	33	37	15	14	14	15	69
1	9	33	33	16	12	15	14	78
1	9	34	33	14	10	11	13	67
1	9	31	31	15	12	16	9	80
1	9	27	32	12	8	13	15	54
1	9	37	31	14	10	17	10	71
1	9	34	37	16	12	15	11	84
1	9	34	30	14	12	14	13	74
1	9	32	33	10	7	16	8	71
1	9	29	31	10	9	9	20	63
1	9	36	33	14	12	15	12	71
1	9	29	31	16	10	17	10	76
1	9	35	33	16	10	13	10	69
1	9	37	32	16	10	15	9	74
1	9	34	33	14	12	16	14	75
1	9	38	32	20	15	16	8	54
1	9	35	33	14	10	12	14	52
1	9	38	28	14	10	15	11	69
1	9	37	35	11	12	11	13	68
1	9	38	39	14	13	15	9	65
1	9	33	34	15	11	15	11	75
1	9	36	38	16	11	17	15	74
1	9	38	32	14	12	13	11	75
1	9	32	38	16	14	16	10	72
1	9	32	30	14	10	14	14	67
1	9	32	33	12	12	11	18	63
1	9	34	38	16	13	12	14	62
1	9	32	32	9	5	12	11	63
1	9	37	35	14	6	15	14.5	76
1	9	39	34	16	12	16	13	74
1	9	29	34	16	12	15	9	67
1	9	37	36	15	11	12	10	73
1	9	35	34	16	10	12	15	70
1	9	30	28	12	7	8	20	53
1	9	38	34	16	12	13	12	77
1	9	34	35	16	14	11	12	80
1	9	31	35	14	11	14	14	52
1	9	34	31	16	12	15	13	54
1	10	35	37	17	13	10	11	80
1	10	36	35	18	14	11	17	66
1	10	30	27	18	11	12	12	73
1	10	39	40	12	12	15	13	63
1	10	35	37	16	12	15	14	69
1	10	38	36	10	8	14	13	67
1	10	31	38	14	11	16	15	54
1	10	34	39	18	14	15	13	81
1	10	38	41	18	14	15	10	69
1	10	34	27	16	12	13	11	84
1	10	39	30	17	9	12	19	80
1	10	37	37	16	13	17	13	70
1	10	34	31	16	11	13	17	69
1	10	28	31	13	12	15	13	77
1	10	37	27	16	12	13	9	54
1	10	33	36	16	12	15	11	79
1	10	35	37	16	12	15	9	71
1	10	37	33	15	12	16	12	73
1	10	32	34	15	11	15	12	72
1	10	33	31	16	10	14	13	77
1	10	38	39	14	9	15	13	75
1	10	33	34	16	12	14	12	69
1	10	29	32	16	12	13	15	54
1	10	33	33	15	12	7	22	70
1	10	31	36	12	9	17	13	73
1	10	36	32	17	15	13	15	54
1	10	35	41	16	12	15	13	77
1	10	32	28	15	12	14	15	82
1	10	29	30	13	12	13	12.5	80
1	10	39	36	16	10	16	11	80
1	10	37	35	16	13	12	16	69
1	10	35	31	16	9	14	11	78
1	10	37	34	16	12	17	11	81
1	10	32	36	14	10	15	10	76
1	10	38	36	16	14	17	10	76
1	10	37	35	16	11	12	16	73
1	10	36	37	20	15	16	12	85
1	10	32	28	15	11	11	11	66
1	10	33	39	16	11	15	16	79
1	10	40	32	13	12	9	19	68
1	10	38	35	17	12	16	11	76
1	10	41	39	16	12	15	16	71
1	10	36	35	16	11	10	15	54
1	10	43	42	12	7	10	24	46
1	10	30	34	16	12	15	14	85
1	10	31	33	16	14	11	15	74
1	10	32	41	17	11	13	11	88
1	10	32	33	13	11	14	15	38
1	10	37	34	12	10	18	12	76
1	10	37	32	18	13	16	10	86
1	10	33	40	14	13	14	14	54
1	10	34	40	14	8	14	13	67
1	10	33	35	13	11	14	9	69
1	10	38	36	16	12	14	15	90
1	10	33	37	13	11	12	15	54
1	10	31	27	16	13	14	14	76
1	10	38	39	13	12	15	11	89
1	10	37	38	16	14	15	8	76
1	10	36	31	15	13	15	11	73
1	10	31	33	16	15	13	11	79
1	10	39	32	15	10	17	8	90
1	10	44	39	17	11	17	10	74
1	10	33	36	15	9	19	11	81
1	10	35	33	12	11	15	13	72
1	10	32	33	16	10	13	11	71
1	10	28	32	10	11	9	20	66
1	10	40	37	16	8	15	10	77
1	10	27	30	12	11	15	15	65
1	10	37	38	14	12	15	12	74
1	10	32	29	15	12	16	14	85
1	10	28	22	13	9	11	23	54
1	10	34	35	15	11	14	14	63
1	10	30	35	11	10	11	16	54
1	10	35	34	12	8	15	11	64
1	10	31	35	11	9	13	12	69
1	10	32	34	16	8	15	10	54
1	10	30	37	15	9	16	14	84
1	10	30	35	17	15	14	12	86
1	10	31	23	16	11	15	12	77
1	10	40	31	10	8	16	11	89
1	10	32	27	18	13	16	12	76
1	10	36	36	13	12	11	13	60
1	10	32	31	16	12	12	11	75
1	10	35	32	13	9	9	19	73
1	10	38	39	10	7	16	12	85
1	10	42	37	15	13	13	17	79
1	10	34	38	16	9	16	9	71
1	10	35	39	16	6	12	12	72
1	9	38	34	14	8	9	19	69
1	10	33	31	10	8	13	18	78
1	10	36	32	17	15	13	15	54
1	10	32	37	13	6	14	14	69
1	10	33	36	15	9	19	11	81
1	10	34	32	16	11	13	9	84
1	10	32	38	12	8	12	18	84
1	10	34	36	13	8	13	16	69
0	11	27	26	13	10	10	24	66
0	11	31	26	12	8	14	14	81
0	11	38	33	17	14	16	20	82
0	11	34	39	15	10	10	18	72
0	11	24	30	10	8	11	23	54
0	11	30	33	14	11	14	12	78
0	11	26	25	11	12	12	14	74
0	11	34	38	13	12	9	16	82
0	11	27	37	16	12	9	18	73
0	11	37	31	12	5	11	20	55
0	11	36	37	16	12	16	12	72
0	11	41	35	12	10	9	12	78
0	11	29	25	9	7	13	17	59
0	11	36	28	12	12	16	13	72
0	11	32	35	15	11	13	9	78
0	11	37	33	12	8	9	16	68
0	11	30	30	12	9	12	18	69
0	11	31	31	14	10	16	10	67
0	11	38	37	12	9	11	14	74
0	11	36	36	16	12	14	11	54
0	11	35	30	11	6	13	9	67
0	11	31	36	19	15	15	11	70
0	11	38	32	15	12	14	10	80
0	11	22	28	8	12	16	11	89
0	11	32	36	16	12	13	19	76
0	11	36	34	17	11	14	14	74
0	11	39	31	12	7	15	12	87
0	11	28	28	11	7	13	14	54
0	11	32	36	11	5	11	21	61
0	11	32	36	14	12	11	13	38
0	11	38	40	16	12	14	10	75
0	11	32	33	12	3	15	15	69
0	11	35	37	16	11	11	16	62
0	11	32	32	13	10	15	14	72
0	11	37	38	15	12	12	12	70
0	11	34	31	16	9	14	19	79
0	11	33	37	16	12	14	15	87
0	11	33	33	14	9	8	19	62
0	11	26	32	16	12	13	13	77
0	11	30	30	16	12	9	17	69
0	11	24	30	14	10	15	12	69
0	11	34	31	11	9	17	11	75
0	11	34	32	12	12	13	14	54
0	11	33	34	15	8	15	11	72
0	11	34	36	15	11	15	13	74
0	11	35	37	16	11	14	12	85
0	11	35	36	16	12	16	15	52
0	11	36	33	11	10	13	14	70
0	11	34	33	15	10	16	12	84
0	11	34	33	12	12	9	17	64
0	11	41	44	12	12	16	11	84
0	11	32	39	15	11	11	18	87
0	11	30	32	15	8	10	13	79
0	11	35	35	16	12	11	17	67
0	11	28	25	14	10	15	13	65
0	11	33	35	17	11	17	11	85
0	11	39	34	14	10	14	12	83
0	11	36	35	13	8	8	22	61
0	11	36	39	15	12	15	14	82
0	11	35	33	13	12	11	12	76
0	11	38	36	14	10	16	12	58
0	11	33	32	15	12	10	17	72
0	11	31	32	12	9	15	9	72
0	11	34	36	13	9	9	21	38
0	11	32	36	8	6	16	10	78
0	11	31	32	14	10	19	11	54
0	11	33	34	14	9	12	12	63
0	11	34	33	11	9	8	23	66
0	11	34	35	12	9	11	13	70
0	11	34	30	13	6	14	12	71
0	11	33	38	10	10	9	16	67
0	11	32	34	16	6	15	9	58
0	11	41	33	18	14	13	17	72
0	11	34	32	13	10	16	9	72
0	11	36	31	11	10	11	14	70
0	11	37	30	4	6	12	17	76
0	11	36	27	13	12	13	13	50
0	11	29	31	16	12	10	11	72
0	11	37	30	10	7	11	12	72
0	11	27	32	12	8	12	10	88
0	11	35	35	12	11	8	19	53
0	11	28	28	10	3	12	16	58
0	11	35	33	13	6	12	16	66
0	11	37	31	15	10	15	14	82
0	11	29	35	12	8	11	20	69
0	11	32	35	14	9	13	15	68
0	11	36	32	10	9	14	23	44
0	11	19	21	12	8	10	20	56
0	11	21	20	12	9	12	16	53
0	11	31	34	11	7	15	14	70
0	11	33	32	10	7	13	17	78
0	11	36	34	12	6	13	11	71
0	11	33	32	16	9	13	13	72
0	11	37	33	12	10	12	17	68
0	11	34	33	14	11	12	15	67
0	11	35	37	16	12	9	21	75
0	11	31	32	14	8	9	18	62
0	11	37	34	13	11	15	15	67
0	11	35	30	4	3	10	8	83
0	11	27	30	15	11	14	12	64
0	11	34	38	11	12	15	12	68
0	11	40	36	11	7	7	22	62
0	11	29	32	14	9	14	12	72

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 11 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96551&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]11 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96551&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96551&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 2.71036882048956 + 0.267704067574296Pop[t] + 0.298790977527051month[t] + 0.0331344672091642Connected[t] + 0.0409019846242882Separate[t] + 0.552243687717541Software[t] + 0.0669242791647773Happiness[t] -0.0340036411629706Depression[t] + 0.00642778731101736Belonging[t] -0.00640786153072009t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  2.71036882048956 +  0.267704067574296Pop[t] +  0.298790977527051month[t] +  0.0331344672091642Connected[t] +  0.0409019846242882Separate[t] +  0.552243687717541Software[t] +  0.0669242791647773Happiness[t] -0.0340036411629706Depression[t] +  0.00642778731101736Belonging[t] -0.00640786153072009t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96551&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  2.71036882048956 +  0.267704067574296Pop[t] +  0.298790977527051month[t] +  0.0331344672091642Connected[t] +  0.0409019846242882Separate[t] +  0.552243687717541Software[t] +  0.0669242791647773Happiness[t] -0.0340036411629706Depression[t] +  0.00642778731101736Belonging[t] -0.00640786153072009t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96551&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96551&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 2.71036882048956 + 0.267704067574296Pop[t] + 0.298790977527051month[t] + 0.0331344672091642Connected[t] + 0.0409019846242882Separate[t] + 0.552243687717541Software[t] + 0.0669242791647773Happiness[t] -0.0340036411629706Depression[t] + 0.00642778731101736Belonging[t] -0.00640786153072009t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)2.710368820489564.4750420.60570.5452790.27264
Pop0.2677040675742960.4986210.53690.5918140.295907
month0.2987909775270510.4551630.65640.512130.256065
Connected0.03313446720916420.0345720.95840.3387690.169384
Separate0.04090198462428820.0353111.15840.2478090.123905
Software0.5522436877175410.05477310.082400
Happiness0.06692427916477730.0581681.15050.2510070.125503
Depression-0.03400364116297060.042131-0.80710.4203630.210181
Belonging0.006427787311017360.0119980.53580.5925990.296299
t-0.006407861530720090.004338-1.47720.1408620.070431

\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) & 2.71036882048956 & 4.475042 & 0.6057 & 0.545279 & 0.27264 \tabularnewline
Pop & 0.267704067574296 & 0.498621 & 0.5369 & 0.591814 & 0.295907 \tabularnewline
month & 0.298790977527051 & 0.455163 & 0.6564 & 0.51213 & 0.256065 \tabularnewline
Connected & 0.0331344672091642 & 0.034572 & 0.9584 & 0.338769 & 0.169384 \tabularnewline
Separate & 0.0409019846242882 & 0.035311 & 1.1584 & 0.247809 & 0.123905 \tabularnewline
Software & 0.552243687717541 & 0.054773 & 10.0824 & 0 & 0 \tabularnewline
Happiness & 0.0669242791647773 & 0.058168 & 1.1505 & 0.251007 & 0.125503 \tabularnewline
Depression & -0.0340036411629706 & 0.042131 & -0.8071 & 0.420363 & 0.210181 \tabularnewline
Belonging & 0.00642778731101736 & 0.011998 & 0.5358 & 0.592599 & 0.296299 \tabularnewline
t & -0.00640786153072009 & 0.004338 & -1.4772 & 0.140862 & 0.070431 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96551&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]2.71036882048956[/C][C]4.475042[/C][C]0.6057[/C][C]0.545279[/C][C]0.27264[/C][/ROW]
[ROW][C]Pop[/C][C]0.267704067574296[/C][C]0.498621[/C][C]0.5369[/C][C]0.591814[/C][C]0.295907[/C][/ROW]
[ROW][C]month[/C][C]0.298790977527051[/C][C]0.455163[/C][C]0.6564[/C][C]0.51213[/C][C]0.256065[/C][/ROW]
[ROW][C]Connected[/C][C]0.0331344672091642[/C][C]0.034572[/C][C]0.9584[/C][C]0.338769[/C][C]0.169384[/C][/ROW]
[ROW][C]Separate[/C][C]0.0409019846242882[/C][C]0.035311[/C][C]1.1584[/C][C]0.247809[/C][C]0.123905[/C][/ROW]
[ROW][C]Software[/C][C]0.552243687717541[/C][C]0.054773[/C][C]10.0824[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0669242791647773[/C][C]0.058168[/C][C]1.1505[/C][C]0.251007[/C][C]0.125503[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0340036411629706[/C][C]0.042131[/C][C]-0.8071[/C][C]0.420363[/C][C]0.210181[/C][/ROW]
[ROW][C]Belonging[/C][C]0.00642778731101736[/C][C]0.011998[/C][C]0.5358[/C][C]0.592599[/C][C]0.296299[/C][/ROW]
[ROW][C]t[/C][C]-0.00640786153072009[/C][C]0.004338[/C][C]-1.4772[/C][C]0.140862[/C][C]0.070431[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96551&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96551&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)2.710368820489564.4750420.60570.5452790.27264
Pop0.2677040675742960.4986210.53690.5918140.295907
month0.2987909775270510.4551630.65640.512130.256065
Connected0.03313446720916420.0345720.95840.3387690.169384
Separate0.04090198462428820.0353111.15840.2478090.123905
Software0.5522436877175410.05477310.082400
Happiness0.06692427916477730.0581681.15050.2510070.125503
Depression-0.03400364116297060.042131-0.80710.4203630.210181
Belonging0.006427787311017360.0119980.53580.5925990.296299
t-0.006407861530720090.004338-1.47720.1408620.070431






Multiple Linear Regression - Regression Statistics
Multiple R0.66803004658921
R-squared0.446264143145982
Adjusted R-squared0.42664358128895
F-TEST (value)22.7447178321266
F-TEST (DF numerator)9
F-TEST (DF denominator)254
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.85966979909574
Sum Squared Residuals878.426427463874

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.66803004658921 \tabularnewline
R-squared & 0.446264143145982 \tabularnewline
Adjusted R-squared & 0.42664358128895 \tabularnewline
F-TEST (value) & 22.7447178321266 \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 & 1.85966979909574 \tabularnewline
Sum Squared Residuals & 878.426427463874 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96551&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.66803004658921[/C][/ROW]
[ROW][C]R-squared[/C][C]0.446264143145982[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.42664358128895[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]22.7447178321266[/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]1.85966979909574[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]878.426427463874[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96551&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96551&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Regression Statistics
Multiple R0.66803004658921
R-squared0.446264143145982
Adjusted R-squared0.42664358128895
F-TEST (value)22.7447178321266
F-TEST (DF numerator)9
F-TEST (DF denominator)254
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.85966979909574
Sum Squared Residuals878.426427463874






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11316.0700655900209-3.07006559002095
21615.69426757576120.305732424238781
31917.04157695216141.95842304783860
41512.15766574793512.84233425206487
51416.2994894725434-2.29948947254338
61314.7950060414932-1.79500604149322
71915.33899918241863.66100081758143
81517.0235065935887-2.02350659358869
91416.0003395028786-2.00033950287857
101514.40388565041040.596114349589618
111614.95168489518791.04831510481213
121616.1473625864268-0.147362586426829
131615.49134287835820.508657121641839
141615.44051983130030.559480168699663
151717.8853580370055-0.88535803700552
161515.4353591932854-0.435359193285363
171514.52537222481920.474627775180776
182016.32147757691413.67852242308589
191815.47492440307922.52507559692076
201615.53025017471970.469749825280298
211615.32321199829480.676788001705164
221615.14547862325910.854521376740856
231916.42149517695532.57850482304467
241615.09623272416200.903767275837978
251716.05148953104050.948510468959527
261716.15764061678720.842359383212759
271614.82628683251441.17371316748563
281516.6963966553163-1.69639665531634
291615.58067148598030.41932851401971
301414.1985115803063-0.198511580306322
311515.6695809188536-0.66958091885361
321212.7906452676818-0.79064526768175
331414.7261551758147-0.726155175814723
341615.88595223138800.114047768611978
351415.3940210428864-1.39402104288639
361012.9674151644339-2.96741516443386
371012.9563513608649-2.95635136086492
381415.6454169049801-1.64541690498012
391614.45477120551221.54522879448782
401614.41628248864881.58371751135121
411614.63523271295971.36476728704028
421415.5781446705218-1.57814467052182
432017.38914206980262.61085793019745
441414.0784398144220-0.0784398144219514
451414.3789815766678-0.378981576667822
461115.3881083294370-4.38810832943697
471416.5151148807080-2.51511488070805
481515.0303079753592-0.0303079753592149
491615.27831766031980.721682339680205
501415.519755748483-1.51975574848301
511616.8799334836024-0.879933483602363
521414.0353329346706-0.0353329346706483
531214.8936198510576-2.89361985105759
541615.90674559128980.093254408710175
55911.2791460966546-2.27914609665465
561412.27868154122731.72131845877269
571615.71617692208310.283823077916920
581615.40252016277070.597479837229299
591514.99453856565310.00546143434686897
601614.09851254499011.90148745500994
611211.47730166975390.522698330246092
621615.5035173128220.496482687177994
631616.3953957461175-0.395395746117497
641414.5856409302666-0.585640930266565
651615.18105571453350.818944285466491
661716.20473724979080.795262750209219
671816.47481698377091.52518301622910
681814.56759237499503.43240762500498
691216.0458555294013-4.04585552940125
701615.78876692786410.211233072135857
711013.5861095198426-3.58610951984262
721415.0685754612093-1.06857546120934
731817.03383730964170.966162690358343
741817.26664876195290.733351238047127
751615.37915248158310.620847518416886
761713.63972728910583.36027271089416
771616.5367045060885-0.536704506088515
781614.67085449112751.32914550887252
791315.3391689355289-2.33916893552889
801615.32169023855240.678309761447573
811615.77739832858270.222601671417309
821615.89474636993240.105253630067610
831515.7687684346207-0.768768434620745
841515.0119944674752-0.0119944674751563
851614.29498244779051.70501755220947
861414.2832878161251-0.283287816125141
871615.49194139671190.508058603288128
881615.00583968477700.99416031522303
891514.63614511055400.363854889445985
901214.0240021293728-2.02400212937277
911716.87528843380160.124711566198416
921615.89682785233660.103172147663437
931515.1564981641270-0.156498164126972
941315.1377201193380-2.13772011933795
951614.85535976144831.14464023855169
961615.89009106113240.109908938867559
971613.80654842575962.19345157424036
981615.86590271510010.134097284899881
991414.5391552576154-0.5391552576154
1001617.0743775085394-1.07437750853939
1011614.77927552728781.22072447271217
1022017.51135704770992.48864295229012
1031514.37257299128350.627427008716497
1041615.03046157371660.969538426283401
1051314.9476625190988-1.94766251909879
1061715.78961305896791.21038694103205
1071615.77713511602720.222864883972845
1081614.47931315328771.52068684671229
1091212.4247306347661-0.424730634766116
1101615.34691877369290.653081226307068
1111616.0648243519389-0.0648243519388998
1121715.12188791679471.87811208320529
1131314.3977845272317-1.39778452723171
1141214.6596712566202-2.65967125662023
1151816.22662708610011.77337291389988
1161415.9393449157931-1.93934491579306
1171413.322417959090.677582040910008
1181314.8839669096552-1.88396690965521
1191615.56733874306570.43266125693432
1201314.5186679408697-1.51866794086971
1211615.45072219444780.549277805552234
1221315.8673321688520-2.86733216885203
1231616.9098249193686-0.909824919368622
1241515.9104307251192-0.910430725119216
1251616.8293600377629-0.829360037762884
1261514.72632119126270.273678808737307
1271715.55329136656311.44670863343687
1281514.10005046476740.899949535232634
1291214.748138474433-2.74813847443299
1301614.01781446024261.9821855397574
1311013.7843416092875-3.78434160928755
1321613.53561396127522.46438603872483
1331214.2217235432609-2.22172354326086
1341415.5859809278217-1.58598092782170
1351515.1154055258866-0.115405525886594
1361312.19349926706440.806500732935584
1371514.58676707809970.413232921900267
1381113.5689474543954-2.56894745439539
1391213.0848157644353-1.08481576443525
1401113.4033024434723-2.40330244347227
1411612.94232240779913.05767759220089
1421513.66833858728391.33166141271611
1431716.84060318142830.159396818571737
1441614.17660541411071.82339458588930
1451013.3169539393641-3.3169539393641
1461815.52551596404442.47448403595558
1471314.9960505112883-1.99605051128828
1481614.88394322895541.11605677104456
1491312.87545214910370.124547850896257
1501012.9339030961619-2.93390309616189
1511515.8823334933492-0.882333493349214
1521613.86415679620932.13584320379074
1531611.91177407052244.08822592947764
1541412.14787439783751.85212560216245
1551012.5114300675364-2.51143006753643
1561716.45877743430480.541222565695222
1571311.75149316759401.24850683240602
1581513.90781461884581.09218538115424
1591614.56116563073251.43883436926753
1601212.704212629745-0.704212629745011
1611312.72078448520950.279215514790499
1621312.71690446362840.283095536371560
1631212.4426974334534-0.442697433453368
1641716.20426135972480.795738640275188
1651513.70393652046011.29606347953990
1661011.6747846515357-1.67478465153568
1671414.3757003960369-0.375700396036854
1681114.2342154864931-3.23421548649315
1691314.8072513414194-1.80725134141935
1701614.40214285667511.5978571433249
1711210.56610304987281.43389695012720
1721615.35360135231640.646398647683617
1731213.8966712518605-1.89667125186049
174911.4024498263592-2.40244982635922
1751214.9322562649427-2.93225626494266
1761514.50118919025140.498810809748587
1771212.3519181544552-0.351918154455236
1781212.6823000987845-0.682300098784452
1791413.82904304814560.170956951854436
1801213.3221032278085-1.32210322780853
1811615.03948352515070.960516474849282
1821111.5257114005642-0.525711400564246
1831916.68749540533712.31250459466286
1841515.1240470477292-0.124047047729155
185814.5815747753204-6.5815747753204
1861614.67736426103431.3226357389657
1871714.39353352173172.60646647826829
1881212.3733411536194-0.373341153619402
1891111.4657753769959-0.465775376995942
1901110.48775435056790.512245649432125
1911414.4712423242103-0.47124232421031
1921615.36786109592260.632138904077387
193129.764478698792842.23552130120716
1941614.09233641012791.90766358987211
1951313.6297538082259-0.629753808225923
1961514.99329643613140.00670356386858984
1971612.89811337343853.10188662656153
1981614.94815087873701.05184912126304
1991412.42314909314051.57685090685951
2001614.43568909214091.56431090785908
2011614.02488115039921.97511884960085
2021413.28674299098190.713257009018119
2031113.3067570218082-2.30675702180818
2041214.493290634375-2.49329063437499
2051512.67813717743032.32186282256971
2061514.38824710780600.61175289219397
2071614.49366072052811.50633927947185
2081614.81831521566771.18168478433225
2091113.5667794673052-2.5667794673052
2101513.85287181353071.14712818646934
2111214.1839074212464-2.18390742124639
2121215.6604102083986-3.6604102083986
2131514.04567500911480.95432499088521
2141512.08162488580502.91837511419496
2151614.42634633184391.57365366815615
2161413.06534608486000.934653915140025
2171714.51628568021132.48371431978866
2181413.86790689631440.132093103685559
2191311.81551683488471.18448316511532
2201515.0571742797099-0.0571742797098508
2211314.5339634850250-1.53396348502497
2221413.86409882778510.135901172214907
2231514.15132320869720.84867679130279
2241213.0285658747232-1.02856587472319
2251312.25703521579820.742964784201789
226811.6272488560834-3.62724885608335
2271413.64557564058340.354424359416577
2281412.79037348548481.20962651451519
2291112.1537442990202-1.15374429902023
2301212.7956608051062-0.795660805106198
2311311.16921622326971.83078377673027
2321013.1695174126745-3.16951741267448
2331611.33911347189764.66088652810242
2341815.69207466708632.30792533291370
2351313.6766507663951-0.676650766395077
2361113.1781146783976-2.17811467839762
237410.9584446281236-6.95844462812359
2381314.1454748455463-1.14547484554629
2391614.07937941772261.92062058227743
2401011.5688475086550-1.56884750865497
2411212.1029187904657-0.102918790465723
2421213.3423212406224-1.34232124062235
243108.801555691220241.19844430877976
2441310.93975238491592.06024761508412
2451513.49840895622161.50159104377838
2461211.73076572139950.269234278600498
2471412.67344392604721.32655607395279
2481012.3174962338769-2.31749623387687
2491210.65708416576771.34291583423234
2501211.47886670279690.521133297203091
2511111.6499964267704-0.649996426770351
2521011.4436163470791-1.44361634707906
2531211.22519950450760.774800495492435
2541612.63273584023853.36726415976152
2551213.1233615268255-1.12336152682551
2561413.63137344639980.368626553600234
2571614.02057929230891.97942070769111
2581411.48659857639562.51340142360441
2591313.9532280855537-0.953228085553718
26049.30524253866037-5.30524253866037
2611513.46126303429461.53873696570543
2621114.6588914363487-3.65889143634869
2631111.0942706014226-0.0942706014226423
2641412.53704727642241.46295272357763

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 16.0700655900209 & -3.07006559002095 \tabularnewline
2 & 16 & 15.6942675757612 & 0.305732424238781 \tabularnewline
3 & 19 & 17.0415769521614 & 1.95842304783860 \tabularnewline
4 & 15 & 12.1576657479351 & 2.84233425206487 \tabularnewline
5 & 14 & 16.2994894725434 & -2.29948947254338 \tabularnewline
6 & 13 & 14.7950060414932 & -1.79500604149322 \tabularnewline
7 & 19 & 15.3389991824186 & 3.66100081758143 \tabularnewline
8 & 15 & 17.0235065935887 & -2.02350659358869 \tabularnewline
9 & 14 & 16.0003395028786 & -2.00033950287857 \tabularnewline
10 & 15 & 14.4038856504104 & 0.596114349589618 \tabularnewline
11 & 16 & 14.9516848951879 & 1.04831510481213 \tabularnewline
12 & 16 & 16.1473625864268 & -0.147362586426829 \tabularnewline
13 & 16 & 15.4913428783582 & 0.508657121641839 \tabularnewline
14 & 16 & 15.4405198313003 & 0.559480168699663 \tabularnewline
15 & 17 & 17.8853580370055 & -0.88535803700552 \tabularnewline
16 & 15 & 15.4353591932854 & -0.435359193285363 \tabularnewline
17 & 15 & 14.5253722248192 & 0.474627775180776 \tabularnewline
18 & 20 & 16.3214775769141 & 3.67852242308589 \tabularnewline
19 & 18 & 15.4749244030792 & 2.52507559692076 \tabularnewline
20 & 16 & 15.5302501747197 & 0.469749825280298 \tabularnewline
21 & 16 & 15.3232119982948 & 0.676788001705164 \tabularnewline
22 & 16 & 15.1454786232591 & 0.854521376740856 \tabularnewline
23 & 19 & 16.4214951769553 & 2.57850482304467 \tabularnewline
24 & 16 & 15.0962327241620 & 0.903767275837978 \tabularnewline
25 & 17 & 16.0514895310405 & 0.948510468959527 \tabularnewline
26 & 17 & 16.1576406167872 & 0.842359383212759 \tabularnewline
27 & 16 & 14.8262868325144 & 1.17371316748563 \tabularnewline
28 & 15 & 16.6963966553163 & -1.69639665531634 \tabularnewline
29 & 16 & 15.5806714859803 & 0.41932851401971 \tabularnewline
30 & 14 & 14.1985115803063 & -0.198511580306322 \tabularnewline
31 & 15 & 15.6695809188536 & -0.66958091885361 \tabularnewline
32 & 12 & 12.7906452676818 & -0.79064526768175 \tabularnewline
33 & 14 & 14.7261551758147 & -0.726155175814723 \tabularnewline
34 & 16 & 15.8859522313880 & 0.114047768611978 \tabularnewline
35 & 14 & 15.3940210428864 & -1.39402104288639 \tabularnewline
36 & 10 & 12.9674151644339 & -2.96741516443386 \tabularnewline
37 & 10 & 12.9563513608649 & -2.95635136086492 \tabularnewline
38 & 14 & 15.6454169049801 & -1.64541690498012 \tabularnewline
39 & 16 & 14.4547712055122 & 1.54522879448782 \tabularnewline
40 & 16 & 14.4162824886488 & 1.58371751135121 \tabularnewline
41 & 16 & 14.6352327129597 & 1.36476728704028 \tabularnewline
42 & 14 & 15.5781446705218 & -1.57814467052182 \tabularnewline
43 & 20 & 17.3891420698026 & 2.61085793019745 \tabularnewline
44 & 14 & 14.0784398144220 & -0.0784398144219514 \tabularnewline
45 & 14 & 14.3789815766678 & -0.378981576667822 \tabularnewline
46 & 11 & 15.3881083294370 & -4.38810832943697 \tabularnewline
47 & 14 & 16.5151148807080 & -2.51511488070805 \tabularnewline
48 & 15 & 15.0303079753592 & -0.0303079753592149 \tabularnewline
49 & 16 & 15.2783176603198 & 0.721682339680205 \tabularnewline
50 & 14 & 15.519755748483 & -1.51975574848301 \tabularnewline
51 & 16 & 16.8799334836024 & -0.879933483602363 \tabularnewline
52 & 14 & 14.0353329346706 & -0.0353329346706483 \tabularnewline
53 & 12 & 14.8936198510576 & -2.89361985105759 \tabularnewline
54 & 16 & 15.9067455912898 & 0.093254408710175 \tabularnewline
55 & 9 & 11.2791460966546 & -2.27914609665465 \tabularnewline
56 & 14 & 12.2786815412273 & 1.72131845877269 \tabularnewline
57 & 16 & 15.7161769220831 & 0.283823077916920 \tabularnewline
58 & 16 & 15.4025201627707 & 0.597479837229299 \tabularnewline
59 & 15 & 14.9945385656531 & 0.00546143434686897 \tabularnewline
60 & 16 & 14.0985125449901 & 1.90148745500994 \tabularnewline
61 & 12 & 11.4773016697539 & 0.522698330246092 \tabularnewline
62 & 16 & 15.503517312822 & 0.496482687177994 \tabularnewline
63 & 16 & 16.3953957461175 & -0.395395746117497 \tabularnewline
64 & 14 & 14.5856409302666 & -0.585640930266565 \tabularnewline
65 & 16 & 15.1810557145335 & 0.818944285466491 \tabularnewline
66 & 17 & 16.2047372497908 & 0.795262750209219 \tabularnewline
67 & 18 & 16.4748169837709 & 1.52518301622910 \tabularnewline
68 & 18 & 14.5675923749950 & 3.43240762500498 \tabularnewline
69 & 12 & 16.0458555294013 & -4.04585552940125 \tabularnewline
70 & 16 & 15.7887669278641 & 0.211233072135857 \tabularnewline
71 & 10 & 13.5861095198426 & -3.58610951984262 \tabularnewline
72 & 14 & 15.0685754612093 & -1.06857546120934 \tabularnewline
73 & 18 & 17.0338373096417 & 0.966162690358343 \tabularnewline
74 & 18 & 17.2666487619529 & 0.733351238047127 \tabularnewline
75 & 16 & 15.3791524815831 & 0.620847518416886 \tabularnewline
76 & 17 & 13.6397272891058 & 3.36027271089416 \tabularnewline
77 & 16 & 16.5367045060885 & -0.536704506088515 \tabularnewline
78 & 16 & 14.6708544911275 & 1.32914550887252 \tabularnewline
79 & 13 & 15.3391689355289 & -2.33916893552889 \tabularnewline
80 & 16 & 15.3216902385524 & 0.678309761447573 \tabularnewline
81 & 16 & 15.7773983285827 & 0.222601671417309 \tabularnewline
82 & 16 & 15.8947463699324 & 0.105253630067610 \tabularnewline
83 & 15 & 15.7687684346207 & -0.768768434620745 \tabularnewline
84 & 15 & 15.0119944674752 & -0.0119944674751563 \tabularnewline
85 & 16 & 14.2949824477905 & 1.70501755220947 \tabularnewline
86 & 14 & 14.2832878161251 & -0.283287816125141 \tabularnewline
87 & 16 & 15.4919413967119 & 0.508058603288128 \tabularnewline
88 & 16 & 15.0058396847770 & 0.99416031522303 \tabularnewline
89 & 15 & 14.6361451105540 & 0.363854889445985 \tabularnewline
90 & 12 & 14.0240021293728 & -2.02400212937277 \tabularnewline
91 & 17 & 16.8752884338016 & 0.124711566198416 \tabularnewline
92 & 16 & 15.8968278523366 & 0.103172147663437 \tabularnewline
93 & 15 & 15.1564981641270 & -0.156498164126972 \tabularnewline
94 & 13 & 15.1377201193380 & -2.13772011933795 \tabularnewline
95 & 16 & 14.8553597614483 & 1.14464023855169 \tabularnewline
96 & 16 & 15.8900910611324 & 0.109908938867559 \tabularnewline
97 & 16 & 13.8065484257596 & 2.19345157424036 \tabularnewline
98 & 16 & 15.8659027151001 & 0.134097284899881 \tabularnewline
99 & 14 & 14.5391552576154 & -0.5391552576154 \tabularnewline
100 & 16 & 17.0743775085394 & -1.07437750853939 \tabularnewline
101 & 16 & 14.7792755272878 & 1.22072447271217 \tabularnewline
102 & 20 & 17.5113570477099 & 2.48864295229012 \tabularnewline
103 & 15 & 14.3725729912835 & 0.627427008716497 \tabularnewline
104 & 16 & 15.0304615737166 & 0.969538426283401 \tabularnewline
105 & 13 & 14.9476625190988 & -1.94766251909879 \tabularnewline
106 & 17 & 15.7896130589679 & 1.21038694103205 \tabularnewline
107 & 16 & 15.7771351160272 & 0.222864883972845 \tabularnewline
108 & 16 & 14.4793131532877 & 1.52068684671229 \tabularnewline
109 & 12 & 12.4247306347661 & -0.424730634766116 \tabularnewline
110 & 16 & 15.3469187736929 & 0.653081226307068 \tabularnewline
111 & 16 & 16.0648243519389 & -0.0648243519388998 \tabularnewline
112 & 17 & 15.1218879167947 & 1.87811208320529 \tabularnewline
113 & 13 & 14.3977845272317 & -1.39778452723171 \tabularnewline
114 & 12 & 14.6596712566202 & -2.65967125662023 \tabularnewline
115 & 18 & 16.2266270861001 & 1.77337291389988 \tabularnewline
116 & 14 & 15.9393449157931 & -1.93934491579306 \tabularnewline
117 & 14 & 13.32241795909 & 0.677582040910008 \tabularnewline
118 & 13 & 14.8839669096552 & -1.88396690965521 \tabularnewline
119 & 16 & 15.5673387430657 & 0.43266125693432 \tabularnewline
120 & 13 & 14.5186679408697 & -1.51866794086971 \tabularnewline
121 & 16 & 15.4507221944478 & 0.549277805552234 \tabularnewline
122 & 13 & 15.8673321688520 & -2.86733216885203 \tabularnewline
123 & 16 & 16.9098249193686 & -0.909824919368622 \tabularnewline
124 & 15 & 15.9104307251192 & -0.910430725119216 \tabularnewline
125 & 16 & 16.8293600377629 & -0.829360037762884 \tabularnewline
126 & 15 & 14.7263211912627 & 0.273678808737307 \tabularnewline
127 & 17 & 15.5532913665631 & 1.44670863343687 \tabularnewline
128 & 15 & 14.1000504647674 & 0.899949535232634 \tabularnewline
129 & 12 & 14.748138474433 & -2.74813847443299 \tabularnewline
130 & 16 & 14.0178144602426 & 1.9821855397574 \tabularnewline
131 & 10 & 13.7843416092875 & -3.78434160928755 \tabularnewline
132 & 16 & 13.5356139612752 & 2.46438603872483 \tabularnewline
133 & 12 & 14.2217235432609 & -2.22172354326086 \tabularnewline
134 & 14 & 15.5859809278217 & -1.58598092782170 \tabularnewline
135 & 15 & 15.1154055258866 & -0.115405525886594 \tabularnewline
136 & 13 & 12.1934992670644 & 0.806500732935584 \tabularnewline
137 & 15 & 14.5867670780997 & 0.413232921900267 \tabularnewline
138 & 11 & 13.5689474543954 & -2.56894745439539 \tabularnewline
139 & 12 & 13.0848157644353 & -1.08481576443525 \tabularnewline
140 & 11 & 13.4033024434723 & -2.40330244347227 \tabularnewline
141 & 16 & 12.9423224077991 & 3.05767759220089 \tabularnewline
142 & 15 & 13.6683385872839 & 1.33166141271611 \tabularnewline
143 & 17 & 16.8406031814283 & 0.159396818571737 \tabularnewline
144 & 16 & 14.1766054141107 & 1.82339458588930 \tabularnewline
145 & 10 & 13.3169539393641 & -3.3169539393641 \tabularnewline
146 & 18 & 15.5255159640444 & 2.47448403595558 \tabularnewline
147 & 13 & 14.9960505112883 & -1.99605051128828 \tabularnewline
148 & 16 & 14.8839432289554 & 1.11605677104456 \tabularnewline
149 & 13 & 12.8754521491037 & 0.124547850896257 \tabularnewline
150 & 10 & 12.9339030961619 & -2.93390309616189 \tabularnewline
151 & 15 & 15.8823334933492 & -0.882333493349214 \tabularnewline
152 & 16 & 13.8641567962093 & 2.13584320379074 \tabularnewline
153 & 16 & 11.9117740705224 & 4.08822592947764 \tabularnewline
154 & 14 & 12.1478743978375 & 1.85212560216245 \tabularnewline
155 & 10 & 12.5114300675364 & -2.51143006753643 \tabularnewline
156 & 17 & 16.4587774343048 & 0.541222565695222 \tabularnewline
157 & 13 & 11.7514931675940 & 1.24850683240602 \tabularnewline
158 & 15 & 13.9078146188458 & 1.09218538115424 \tabularnewline
159 & 16 & 14.5611656307325 & 1.43883436926753 \tabularnewline
160 & 12 & 12.704212629745 & -0.704212629745011 \tabularnewline
161 & 13 & 12.7207844852095 & 0.279215514790499 \tabularnewline
162 & 13 & 12.7169044636284 & 0.283095536371560 \tabularnewline
163 & 12 & 12.4426974334534 & -0.442697433453368 \tabularnewline
164 & 17 & 16.2042613597248 & 0.795738640275188 \tabularnewline
165 & 15 & 13.7039365204601 & 1.29606347953990 \tabularnewline
166 & 10 & 11.6747846515357 & -1.67478465153568 \tabularnewline
167 & 14 & 14.3757003960369 & -0.375700396036854 \tabularnewline
168 & 11 & 14.2342154864931 & -3.23421548649315 \tabularnewline
169 & 13 & 14.8072513414194 & -1.80725134141935 \tabularnewline
170 & 16 & 14.4021428566751 & 1.5978571433249 \tabularnewline
171 & 12 & 10.5661030498728 & 1.43389695012720 \tabularnewline
172 & 16 & 15.3536013523164 & 0.646398647683617 \tabularnewline
173 & 12 & 13.8966712518605 & -1.89667125186049 \tabularnewline
174 & 9 & 11.4024498263592 & -2.40244982635922 \tabularnewline
175 & 12 & 14.9322562649427 & -2.93225626494266 \tabularnewline
176 & 15 & 14.5011891902514 & 0.498810809748587 \tabularnewline
177 & 12 & 12.3519181544552 & -0.351918154455236 \tabularnewline
178 & 12 & 12.6823000987845 & -0.682300098784452 \tabularnewline
179 & 14 & 13.8290430481456 & 0.170956951854436 \tabularnewline
180 & 12 & 13.3221032278085 & -1.32210322780853 \tabularnewline
181 & 16 & 15.0394835251507 & 0.960516474849282 \tabularnewline
182 & 11 & 11.5257114005642 & -0.525711400564246 \tabularnewline
183 & 19 & 16.6874954053371 & 2.31250459466286 \tabularnewline
184 & 15 & 15.1240470477292 & -0.124047047729155 \tabularnewline
185 & 8 & 14.5815747753204 & -6.5815747753204 \tabularnewline
186 & 16 & 14.6773642610343 & 1.3226357389657 \tabularnewline
187 & 17 & 14.3935335217317 & 2.60646647826829 \tabularnewline
188 & 12 & 12.3733411536194 & -0.373341153619402 \tabularnewline
189 & 11 & 11.4657753769959 & -0.465775376995942 \tabularnewline
190 & 11 & 10.4877543505679 & 0.512245649432125 \tabularnewline
191 & 14 & 14.4712423242103 & -0.47124232421031 \tabularnewline
192 & 16 & 15.3678610959226 & 0.632138904077387 \tabularnewline
193 & 12 & 9.76447869879284 & 2.23552130120716 \tabularnewline
194 & 16 & 14.0923364101279 & 1.90766358987211 \tabularnewline
195 & 13 & 13.6297538082259 & -0.629753808225923 \tabularnewline
196 & 15 & 14.9932964361314 & 0.00670356386858984 \tabularnewline
197 & 16 & 12.8981133734385 & 3.10188662656153 \tabularnewline
198 & 16 & 14.9481508787370 & 1.05184912126304 \tabularnewline
199 & 14 & 12.4231490931405 & 1.57685090685951 \tabularnewline
200 & 16 & 14.4356890921409 & 1.56431090785908 \tabularnewline
201 & 16 & 14.0248811503992 & 1.97511884960085 \tabularnewline
202 & 14 & 13.2867429909819 & 0.713257009018119 \tabularnewline
203 & 11 & 13.3067570218082 & -2.30675702180818 \tabularnewline
204 & 12 & 14.493290634375 & -2.49329063437499 \tabularnewline
205 & 15 & 12.6781371774303 & 2.32186282256971 \tabularnewline
206 & 15 & 14.3882471078060 & 0.61175289219397 \tabularnewline
207 & 16 & 14.4936607205281 & 1.50633927947185 \tabularnewline
208 & 16 & 14.8183152156677 & 1.18168478433225 \tabularnewline
209 & 11 & 13.5667794673052 & -2.5667794673052 \tabularnewline
210 & 15 & 13.8528718135307 & 1.14712818646934 \tabularnewline
211 & 12 & 14.1839074212464 & -2.18390742124639 \tabularnewline
212 & 12 & 15.6604102083986 & -3.6604102083986 \tabularnewline
213 & 15 & 14.0456750091148 & 0.95432499088521 \tabularnewline
214 & 15 & 12.0816248858050 & 2.91837511419496 \tabularnewline
215 & 16 & 14.4263463318439 & 1.57365366815615 \tabularnewline
216 & 14 & 13.0653460848600 & 0.934653915140025 \tabularnewline
217 & 17 & 14.5162856802113 & 2.48371431978866 \tabularnewline
218 & 14 & 13.8679068963144 & 0.132093103685559 \tabularnewline
219 & 13 & 11.8155168348847 & 1.18448316511532 \tabularnewline
220 & 15 & 15.0571742797099 & -0.0571742797098508 \tabularnewline
221 & 13 & 14.5339634850250 & -1.53396348502497 \tabularnewline
222 & 14 & 13.8640988277851 & 0.135901172214907 \tabularnewline
223 & 15 & 14.1513232086972 & 0.84867679130279 \tabularnewline
224 & 12 & 13.0285658747232 & -1.02856587472319 \tabularnewline
225 & 13 & 12.2570352157982 & 0.742964784201789 \tabularnewline
226 & 8 & 11.6272488560834 & -3.62724885608335 \tabularnewline
227 & 14 & 13.6455756405834 & 0.354424359416577 \tabularnewline
228 & 14 & 12.7903734854848 & 1.20962651451519 \tabularnewline
229 & 11 & 12.1537442990202 & -1.15374429902023 \tabularnewline
230 & 12 & 12.7956608051062 & -0.795660805106198 \tabularnewline
231 & 13 & 11.1692162232697 & 1.83078377673027 \tabularnewline
232 & 10 & 13.1695174126745 & -3.16951741267448 \tabularnewline
233 & 16 & 11.3391134718976 & 4.66088652810242 \tabularnewline
234 & 18 & 15.6920746670863 & 2.30792533291370 \tabularnewline
235 & 13 & 13.6766507663951 & -0.676650766395077 \tabularnewline
236 & 11 & 13.1781146783976 & -2.17811467839762 \tabularnewline
237 & 4 & 10.9584446281236 & -6.95844462812359 \tabularnewline
238 & 13 & 14.1454748455463 & -1.14547484554629 \tabularnewline
239 & 16 & 14.0793794177226 & 1.92062058227743 \tabularnewline
240 & 10 & 11.5688475086550 & -1.56884750865497 \tabularnewline
241 & 12 & 12.1029187904657 & -0.102918790465723 \tabularnewline
242 & 12 & 13.3423212406224 & -1.34232124062235 \tabularnewline
243 & 10 & 8.80155569122024 & 1.19844430877976 \tabularnewline
244 & 13 & 10.9397523849159 & 2.06024761508412 \tabularnewline
245 & 15 & 13.4984089562216 & 1.50159104377838 \tabularnewline
246 & 12 & 11.7307657213995 & 0.269234278600498 \tabularnewline
247 & 14 & 12.6734439260472 & 1.32655607395279 \tabularnewline
248 & 10 & 12.3174962338769 & -2.31749623387687 \tabularnewline
249 & 12 & 10.6570841657677 & 1.34291583423234 \tabularnewline
250 & 12 & 11.4788667027969 & 0.521133297203091 \tabularnewline
251 & 11 & 11.6499964267704 & -0.649996426770351 \tabularnewline
252 & 10 & 11.4436163470791 & -1.44361634707906 \tabularnewline
253 & 12 & 11.2251995045076 & 0.774800495492435 \tabularnewline
254 & 16 & 12.6327358402385 & 3.36726415976152 \tabularnewline
255 & 12 & 13.1233615268255 & -1.12336152682551 \tabularnewline
256 & 14 & 13.6313734463998 & 0.368626553600234 \tabularnewline
257 & 16 & 14.0205792923089 & 1.97942070769111 \tabularnewline
258 & 14 & 11.4865985763956 & 2.51340142360441 \tabularnewline
259 & 13 & 13.9532280855537 & -0.953228085553718 \tabularnewline
260 & 4 & 9.30524253866037 & -5.30524253866037 \tabularnewline
261 & 15 & 13.4612630342946 & 1.53873696570543 \tabularnewline
262 & 11 & 14.6588914363487 & -3.65889143634869 \tabularnewline
263 & 11 & 11.0942706014226 & -0.0942706014226423 \tabularnewline
264 & 14 & 12.5370472764224 & 1.46295272357763 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96551&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]13[/C][C]16.0700655900209[/C][C]-3.07006559002095[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.6942675757612[/C][C]0.305732424238781[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]17.0415769521614[/C][C]1.95842304783860[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]12.1576657479351[/C][C]2.84233425206487[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.2994894725434[/C][C]-2.29948947254338[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.7950060414932[/C][C]-1.79500604149322[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.3389991824186[/C][C]3.66100081758143[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]17.0235065935887[/C][C]-2.02350659358869[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]16.0003395028786[/C][C]-2.00033950287857[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.4038856504104[/C][C]0.596114349589618[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.9516848951879[/C][C]1.04831510481213[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.1473625864268[/C][C]-0.147362586426829[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.4913428783582[/C][C]0.508657121641839[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.4405198313003[/C][C]0.559480168699663[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]17.8853580370055[/C][C]-0.88535803700552[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.4353591932854[/C][C]-0.435359193285363[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.5253722248192[/C][C]0.474627775180776[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.3214775769141[/C][C]3.67852242308589[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.4749244030792[/C][C]2.52507559692076[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.5302501747197[/C][C]0.469749825280298[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.3232119982948[/C][C]0.676788001705164[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]15.1454786232591[/C][C]0.854521376740856[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.4214951769553[/C][C]2.57850482304467[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]15.0962327241620[/C][C]0.903767275837978[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]16.0514895310405[/C][C]0.948510468959527[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.1576406167872[/C][C]0.842359383212759[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.8262868325144[/C][C]1.17371316748563[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.6963966553163[/C][C]-1.69639665531634[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.5806714859803[/C][C]0.41932851401971[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.1985115803063[/C][C]-0.198511580306322[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.6695809188536[/C][C]-0.66958091885361[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.7906452676818[/C][C]-0.79064526768175[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.7261551758147[/C][C]-0.726155175814723[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.8859522313880[/C][C]0.114047768611978[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.3940210428864[/C][C]-1.39402104288639[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.9674151644339[/C][C]-2.96741516443386[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]12.9563513608649[/C][C]-2.95635136086492[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.6454169049801[/C][C]-1.64541690498012[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.4547712055122[/C][C]1.54522879448782[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.4162824886488[/C][C]1.58371751135121[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.6352327129597[/C][C]1.36476728704028[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.5781446705218[/C][C]-1.57814467052182[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.3891420698026[/C][C]2.61085793019745[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.0784398144220[/C][C]-0.0784398144219514[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.3789815766678[/C][C]-0.378981576667822[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.3881083294370[/C][C]-4.38810832943697[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.5151148807080[/C][C]-2.51511488070805[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.0303079753592[/C][C]-0.0303079753592149[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.2783176603198[/C][C]0.721682339680205[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.519755748483[/C][C]-1.51975574848301[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]16.8799334836024[/C][C]-0.879933483602363[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.0353329346706[/C][C]-0.0353329346706483[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]14.8936198510576[/C][C]-2.89361985105759[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.9067455912898[/C][C]0.093254408710175[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]11.2791460966546[/C][C]-2.27914609665465[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.2786815412273[/C][C]1.72131845877269[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.7161769220831[/C][C]0.283823077916920[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.4025201627707[/C][C]0.597479837229299[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]14.9945385656531[/C][C]0.00546143434686897[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.0985125449901[/C][C]1.90148745500994[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.4773016697539[/C][C]0.522698330246092[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.503517312822[/C][C]0.496482687177994[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.3953957461175[/C][C]-0.395395746117497[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.5856409302666[/C][C]-0.585640930266565[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.1810557145335[/C][C]0.818944285466491[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]16.2047372497908[/C][C]0.795262750209219[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.4748169837709[/C][C]1.52518301622910[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.5675923749950[/C][C]3.43240762500498[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]16.0458555294013[/C][C]-4.04585552940125[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.7887669278641[/C][C]0.211233072135857[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.5861095198426[/C][C]-3.58610951984262[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]15.0685754612093[/C][C]-1.06857546120934[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]17.0338373096417[/C][C]0.966162690358343[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.2666487619529[/C][C]0.733351238047127[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.3791524815831[/C][C]0.620847518416886[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.6397272891058[/C][C]3.36027271089416[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.5367045060885[/C][C]-0.536704506088515[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.6708544911275[/C][C]1.32914550887252[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]15.3391689355289[/C][C]-2.33916893552889[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.3216902385524[/C][C]0.678309761447573[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.7773983285827[/C][C]0.222601671417309[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.8947463699324[/C][C]0.105253630067610[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.7687684346207[/C][C]-0.768768434620745[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]15.0119944674752[/C][C]-0.0119944674751563[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]14.2949824477905[/C][C]1.70501755220947[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.2832878161251[/C][C]-0.283287816125141[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.4919413967119[/C][C]0.508058603288128[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]15.0058396847770[/C][C]0.99416031522303[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.6361451105540[/C][C]0.363854889445985[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]14.0240021293728[/C][C]-2.02400212937277[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.8752884338016[/C][C]0.124711566198416[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.8968278523366[/C][C]0.103172147663437[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.1564981641270[/C][C]-0.156498164126972[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]15.1377201193380[/C][C]-2.13772011933795[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.8553597614483[/C][C]1.14464023855169[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.8900910611324[/C][C]0.109908938867559[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.8065484257596[/C][C]2.19345157424036[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.8659027151001[/C][C]0.134097284899881[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.5391552576154[/C][C]-0.5391552576154[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.0743775085394[/C][C]-1.07437750853939[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.7792755272878[/C][C]1.22072447271217[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.5113570477099[/C][C]2.48864295229012[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.3725729912835[/C][C]0.627427008716497[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]15.0304615737166[/C][C]0.969538426283401[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.9476625190988[/C][C]-1.94766251909879[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.7896130589679[/C][C]1.21038694103205[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.7771351160272[/C][C]0.222864883972845[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.4793131532877[/C][C]1.52068684671229[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.4247306347661[/C][C]-0.424730634766116[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.3469187736929[/C][C]0.653081226307068[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]16.0648243519389[/C][C]-0.0648243519388998[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]15.1218879167947[/C][C]1.87811208320529[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.3977845272317[/C][C]-1.39778452723171[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.6596712566202[/C][C]-2.65967125662023[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.2266270861001[/C][C]1.77337291389988[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.9393449157931[/C][C]-1.93934491579306[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.32241795909[/C][C]0.677582040910008[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.8839669096552[/C][C]-1.88396690965521[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.5673387430657[/C][C]0.43266125693432[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.5186679408697[/C][C]-1.51866794086971[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.4507221944478[/C][C]0.549277805552234[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.8673321688520[/C][C]-2.86733216885203[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]16.9098249193686[/C][C]-0.909824919368622[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.9104307251192[/C][C]-0.910430725119216[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.8293600377629[/C][C]-0.829360037762884[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.7263211912627[/C][C]0.273678808737307[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.5532913665631[/C][C]1.44670863343687[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]14.1000504647674[/C][C]0.899949535232634[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.748138474433[/C][C]-2.74813847443299[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]14.0178144602426[/C][C]1.9821855397574[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.7843416092875[/C][C]-3.78434160928755[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.5356139612752[/C][C]2.46438603872483[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.2217235432609[/C][C]-2.22172354326086[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.5859809278217[/C][C]-1.58598092782170[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.1154055258866[/C][C]-0.115405525886594[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]12.1934992670644[/C][C]0.806500732935584[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.5867670780997[/C][C]0.413232921900267[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.5689474543954[/C][C]-2.56894745439539[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]13.0848157644353[/C][C]-1.08481576443525[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.4033024434723[/C][C]-2.40330244347227[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.9423224077991[/C][C]3.05767759220089[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.6683385872839[/C][C]1.33166141271611[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]16.8406031814283[/C][C]0.159396818571737[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.1766054141107[/C][C]1.82339458588930[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.3169539393641[/C][C]-3.3169539393641[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.5255159640444[/C][C]2.47448403595558[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]14.9960505112883[/C][C]-1.99605051128828[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.8839432289554[/C][C]1.11605677104456[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.8754521491037[/C][C]0.124547850896257[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.9339030961619[/C][C]-2.93390309616189[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]15.8823334933492[/C][C]-0.882333493349214[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.8641567962093[/C][C]2.13584320379074[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.9117740705224[/C][C]4.08822592947764[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.1478743978375[/C][C]1.85212560216245[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.5114300675364[/C][C]-2.51143006753643[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.4587774343048[/C][C]0.541222565695222[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.7514931675940[/C][C]1.24850683240602[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]13.9078146188458[/C][C]1.09218538115424[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.5611656307325[/C][C]1.43883436926753[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.704212629745[/C][C]-0.704212629745011[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.7207844852095[/C][C]0.279215514790499[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.7169044636284[/C][C]0.283095536371560[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.4426974334534[/C][C]-0.442697433453368[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.2042613597248[/C][C]0.795738640275188[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.7039365204601[/C][C]1.29606347953990[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.6747846515357[/C][C]-1.67478465153568[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.3757003960369[/C][C]-0.375700396036854[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.2342154864931[/C][C]-3.23421548649315[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.8072513414194[/C][C]-1.80725134141935[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.4021428566751[/C][C]1.5978571433249[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.5661030498728[/C][C]1.43389695012720[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.3536013523164[/C][C]0.646398647683617[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.8966712518605[/C][C]-1.89667125186049[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.4024498263592[/C][C]-2.40244982635922[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]14.9322562649427[/C][C]-2.93225626494266[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.5011891902514[/C][C]0.498810809748587[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.3519181544552[/C][C]-0.351918154455236[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.6823000987845[/C][C]-0.682300098784452[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.8290430481456[/C][C]0.170956951854436[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.3221032278085[/C][C]-1.32210322780853[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]15.0394835251507[/C][C]0.960516474849282[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.5257114005642[/C][C]-0.525711400564246[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]16.6874954053371[/C][C]2.31250459466286[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.1240470477292[/C][C]-0.124047047729155[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.5815747753204[/C][C]-6.5815747753204[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.6773642610343[/C][C]1.3226357389657[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.3935335217317[/C][C]2.60646647826829[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.3733411536194[/C][C]-0.373341153619402[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.4657753769959[/C][C]-0.465775376995942[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.4877543505679[/C][C]0.512245649432125[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14.4712423242103[/C][C]-0.47124232421031[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.3678610959226[/C][C]0.632138904077387[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.76447869879284[/C][C]2.23552130120716[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.0923364101279[/C][C]1.90766358987211[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.6297538082259[/C][C]-0.629753808225923[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]14.9932964361314[/C][C]0.00670356386858984[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]12.8981133734385[/C][C]3.10188662656153[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]14.9481508787370[/C][C]1.05184912126304[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4231490931405[/C][C]1.57685090685951[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.4356890921409[/C][C]1.56431090785908[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]14.0248811503992[/C][C]1.97511884960085[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.2867429909819[/C][C]0.713257009018119[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.3067570218082[/C][C]-2.30675702180818[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.493290634375[/C][C]-2.49329063437499[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.6781371774303[/C][C]2.32186282256971[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.3882471078060[/C][C]0.61175289219397[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.4936607205281[/C][C]1.50633927947185[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]14.8183152156677[/C][C]1.18168478433225[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.5667794673052[/C][C]-2.5667794673052[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]13.8528718135307[/C][C]1.14712818646934[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.1839074212464[/C][C]-2.18390742124639[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]15.6604102083986[/C][C]-3.6604102083986[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.0456750091148[/C][C]0.95432499088521[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.0816248858050[/C][C]2.91837511419496[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.4263463318439[/C][C]1.57365366815615[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.0653460848600[/C][C]0.934653915140025[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.5162856802113[/C][C]2.48371431978866[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.8679068963144[/C][C]0.132093103685559[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.8155168348847[/C][C]1.18448316511532[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.0571742797099[/C][C]-0.0571742797098508[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]14.5339634850250[/C][C]-1.53396348502497[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]13.8640988277851[/C][C]0.135901172214907[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.1513232086972[/C][C]0.84867679130279[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.0285658747232[/C][C]-1.02856587472319[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.2570352157982[/C][C]0.742964784201789[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.6272488560834[/C][C]-3.62724885608335[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]13.6455756405834[/C][C]0.354424359416577[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]12.7903734854848[/C][C]1.20962651451519[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.1537442990202[/C][C]-1.15374429902023[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]12.7956608051062[/C][C]-0.795660805106198[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.1692162232697[/C][C]1.83078377673027[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.1695174126745[/C][C]-3.16951741267448[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.3391134718976[/C][C]4.66088652810242[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]15.6920746670863[/C][C]2.30792533291370[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]13.6766507663951[/C][C]-0.676650766395077[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.1781146783976[/C][C]-2.17811467839762[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]10.9584446281236[/C][C]-6.95844462812359[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.1454748455463[/C][C]-1.14547484554629[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.0793794177226[/C][C]1.92062058227743[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.5688475086550[/C][C]-1.56884750865497[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.1029187904657[/C][C]-0.102918790465723[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.3423212406224[/C][C]-1.34232124062235[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.80155569122024[/C][C]1.19844430877976[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]10.9397523849159[/C][C]2.06024761508412[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.4984089562216[/C][C]1.50159104377838[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]11.7307657213995[/C][C]0.269234278600498[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]12.6734439260472[/C][C]1.32655607395279[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.3174962338769[/C][C]-2.31749623387687[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.6570841657677[/C][C]1.34291583423234[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.4788667027969[/C][C]0.521133297203091[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.6499964267704[/C][C]-0.649996426770351[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.4436163470791[/C][C]-1.44361634707906[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.2251995045076[/C][C]0.774800495492435[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]12.6327358402385[/C][C]3.36726415976152[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.1233615268255[/C][C]-1.12336152682551[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.6313734463998[/C][C]0.368626553600234[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.0205792923089[/C][C]1.97942070769111[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.4865985763956[/C][C]2.51340142360441[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]13.9532280855537[/C][C]-0.953228085553718[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.30524253866037[/C][C]-5.30524253866037[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.4612630342946[/C][C]1.53873696570543[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]14.6588914363487[/C][C]-3.65889143634869[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.0942706014226[/C][C]-0.0942706014226423[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]12.5370472764224[/C][C]1.46295272357763[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96551&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96551&T=4

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11316.0700655900209-3.07006559002095
21615.69426757576120.305732424238781
31917.04157695216141.95842304783860
41512.15766574793512.84233425206487
51416.2994894725434-2.29948947254338
61314.7950060414932-1.79500604149322
71915.33899918241863.66100081758143
81517.0235065935887-2.02350659358869
91416.0003395028786-2.00033950287857
101514.40388565041040.596114349589618
111614.95168489518791.04831510481213
121616.1473625864268-0.147362586426829
131615.49134287835820.508657121641839
141615.44051983130030.559480168699663
151717.8853580370055-0.88535803700552
161515.4353591932854-0.435359193285363
171514.52537222481920.474627775180776
182016.32147757691413.67852242308589
191815.47492440307922.52507559692076
201615.53025017471970.469749825280298
211615.32321199829480.676788001705164
221615.14547862325910.854521376740856
231916.42149517695532.57850482304467
241615.09623272416200.903767275837978
251716.05148953104050.948510468959527
261716.15764061678720.842359383212759
271614.82628683251441.17371316748563
281516.6963966553163-1.69639665531634
291615.58067148598030.41932851401971
301414.1985115803063-0.198511580306322
311515.6695809188536-0.66958091885361
321212.7906452676818-0.79064526768175
331414.7261551758147-0.726155175814723
341615.88595223138800.114047768611978
351415.3940210428864-1.39402104288639
361012.9674151644339-2.96741516443386
371012.9563513608649-2.95635136086492
381415.6454169049801-1.64541690498012
391614.45477120551221.54522879448782
401614.41628248864881.58371751135121
411614.63523271295971.36476728704028
421415.5781446705218-1.57814467052182
432017.38914206980262.61085793019745
441414.0784398144220-0.0784398144219514
451414.3789815766678-0.378981576667822
461115.3881083294370-4.38810832943697
471416.5151148807080-2.51511488070805
481515.0303079753592-0.0303079753592149
491615.27831766031980.721682339680205
501415.519755748483-1.51975574848301
511616.8799334836024-0.879933483602363
521414.0353329346706-0.0353329346706483
531214.8936198510576-2.89361985105759
541615.90674559128980.093254408710175
55911.2791460966546-2.27914609665465
561412.27868154122731.72131845877269
571615.71617692208310.283823077916920
581615.40252016277070.597479837229299
591514.99453856565310.00546143434686897
601614.09851254499011.90148745500994
611211.47730166975390.522698330246092
621615.5035173128220.496482687177994
631616.3953957461175-0.395395746117497
641414.5856409302666-0.585640930266565
651615.18105571453350.818944285466491
661716.20473724979080.795262750209219
671816.47481698377091.52518301622910
681814.56759237499503.43240762500498
691216.0458555294013-4.04585552940125
701615.78876692786410.211233072135857
711013.5861095198426-3.58610951984262
721415.0685754612093-1.06857546120934
731817.03383730964170.966162690358343
741817.26664876195290.733351238047127
751615.37915248158310.620847518416886
761713.63972728910583.36027271089416
771616.5367045060885-0.536704506088515
781614.67085449112751.32914550887252
791315.3391689355289-2.33916893552889
801615.32169023855240.678309761447573
811615.77739832858270.222601671417309
821615.89474636993240.105253630067610
831515.7687684346207-0.768768434620745
841515.0119944674752-0.0119944674751563
851614.29498244779051.70501755220947
861414.2832878161251-0.283287816125141
871615.49194139671190.508058603288128
881615.00583968477700.99416031522303
891514.63614511055400.363854889445985
901214.0240021293728-2.02400212937277
911716.87528843380160.124711566198416
921615.89682785233660.103172147663437
931515.1564981641270-0.156498164126972
941315.1377201193380-2.13772011933795
951614.85535976144831.14464023855169
961615.89009106113240.109908938867559
971613.80654842575962.19345157424036
981615.86590271510010.134097284899881
991414.5391552576154-0.5391552576154
1001617.0743775085394-1.07437750853939
1011614.77927552728781.22072447271217
1022017.51135704770992.48864295229012
1031514.37257299128350.627427008716497
1041615.03046157371660.969538426283401
1051314.9476625190988-1.94766251909879
1061715.78961305896791.21038694103205
1071615.77713511602720.222864883972845
1081614.47931315328771.52068684671229
1091212.4247306347661-0.424730634766116
1101615.34691877369290.653081226307068
1111616.0648243519389-0.0648243519388998
1121715.12188791679471.87811208320529
1131314.3977845272317-1.39778452723171
1141214.6596712566202-2.65967125662023
1151816.22662708610011.77337291389988
1161415.9393449157931-1.93934491579306
1171413.322417959090.677582040910008
1181314.8839669096552-1.88396690965521
1191615.56733874306570.43266125693432
1201314.5186679408697-1.51866794086971
1211615.45072219444780.549277805552234
1221315.8673321688520-2.86733216885203
1231616.9098249193686-0.909824919368622
1241515.9104307251192-0.910430725119216
1251616.8293600377629-0.829360037762884
1261514.72632119126270.273678808737307
1271715.55329136656311.44670863343687
1281514.10005046476740.899949535232634
1291214.748138474433-2.74813847443299
1301614.01781446024261.9821855397574
1311013.7843416092875-3.78434160928755
1321613.53561396127522.46438603872483
1331214.2217235432609-2.22172354326086
1341415.5859809278217-1.58598092782170
1351515.1154055258866-0.115405525886594
1361312.19349926706440.806500732935584
1371514.58676707809970.413232921900267
1381113.5689474543954-2.56894745439539
1391213.0848157644353-1.08481576443525
1401113.4033024434723-2.40330244347227
1411612.94232240779913.05767759220089
1421513.66833858728391.33166141271611
1431716.84060318142830.159396818571737
1441614.17660541411071.82339458588930
1451013.3169539393641-3.3169539393641
1461815.52551596404442.47448403595558
1471314.9960505112883-1.99605051128828
1481614.88394322895541.11605677104456
1491312.87545214910370.124547850896257
1501012.9339030961619-2.93390309616189
1511515.8823334933492-0.882333493349214
1521613.86415679620932.13584320379074
1531611.91177407052244.08822592947764
1541412.14787439783751.85212560216245
1551012.5114300675364-2.51143006753643
1561716.45877743430480.541222565695222
1571311.75149316759401.24850683240602
1581513.90781461884581.09218538115424
1591614.56116563073251.43883436926753
1601212.704212629745-0.704212629745011
1611312.72078448520950.279215514790499
1621312.71690446362840.283095536371560
1631212.4426974334534-0.442697433453368
1641716.20426135972480.795738640275188
1651513.70393652046011.29606347953990
1661011.6747846515357-1.67478465153568
1671414.3757003960369-0.375700396036854
1681114.2342154864931-3.23421548649315
1691314.8072513414194-1.80725134141935
1701614.40214285667511.5978571433249
1711210.56610304987281.43389695012720
1721615.35360135231640.646398647683617
1731213.8966712518605-1.89667125186049
174911.4024498263592-2.40244982635922
1751214.9322562649427-2.93225626494266
1761514.50118919025140.498810809748587
1771212.3519181544552-0.351918154455236
1781212.6823000987845-0.682300098784452
1791413.82904304814560.170956951854436
1801213.3221032278085-1.32210322780853
1811615.03948352515070.960516474849282
1821111.5257114005642-0.525711400564246
1831916.68749540533712.31250459466286
1841515.1240470477292-0.124047047729155
185814.5815747753204-6.5815747753204
1861614.67736426103431.3226357389657
1871714.39353352173172.60646647826829
1881212.3733411536194-0.373341153619402
1891111.4657753769959-0.465775376995942
1901110.48775435056790.512245649432125
1911414.4712423242103-0.47124232421031
1921615.36786109592260.632138904077387
193129.764478698792842.23552130120716
1941614.09233641012791.90766358987211
1951313.6297538082259-0.629753808225923
1961514.99329643613140.00670356386858984
1971612.89811337343853.10188662656153
1981614.94815087873701.05184912126304
1991412.42314909314051.57685090685951
2001614.43568909214091.56431090785908
2011614.02488115039921.97511884960085
2021413.28674299098190.713257009018119
2031113.3067570218082-2.30675702180818
2041214.493290634375-2.49329063437499
2051512.67813717743032.32186282256971
2061514.38824710780600.61175289219397
2071614.49366072052811.50633927947185
2081614.81831521566771.18168478433225
2091113.5667794673052-2.5667794673052
2101513.85287181353071.14712818646934
2111214.1839074212464-2.18390742124639
2121215.6604102083986-3.6604102083986
2131514.04567500911480.95432499088521
2141512.08162488580502.91837511419496
2151614.42634633184391.57365366815615
2161413.06534608486000.934653915140025
2171714.51628568021132.48371431978866
2181413.86790689631440.132093103685559
2191311.81551683488471.18448316511532
2201515.0571742797099-0.0571742797098508
2211314.5339634850250-1.53396348502497
2221413.86409882778510.135901172214907
2231514.15132320869720.84867679130279
2241213.0285658747232-1.02856587472319
2251312.25703521579820.742964784201789
226811.6272488560834-3.62724885608335
2271413.64557564058340.354424359416577
2281412.79037348548481.20962651451519
2291112.1537442990202-1.15374429902023
2301212.7956608051062-0.795660805106198
2311311.16921622326971.83078377673027
2321013.1695174126745-3.16951741267448
2331611.33911347189764.66088652810242
2341815.69207466708632.30792533291370
2351313.6766507663951-0.676650766395077
2361113.1781146783976-2.17811467839762
237410.9584446281236-6.95844462812359
2381314.1454748455463-1.14547484554629
2391614.07937941772261.92062058227743
2401011.5688475086550-1.56884750865497
2411212.1029187904657-0.102918790465723
2421213.3423212406224-1.34232124062235
243108.801555691220241.19844430877976
2441310.93975238491592.06024761508412
2451513.49840895622161.50159104377838
2461211.73076572139950.269234278600498
2471412.67344392604721.32655607395279
2481012.3174962338769-2.31749623387687
2491210.65708416576771.34291583423234
2501211.47886670279690.521133297203091
2511111.6499964267704-0.649996426770351
2521011.4436163470791-1.44361634707906
2531211.22519950450760.774800495492435
2541612.63273584023853.36726415976152
2551213.1233615268255-1.12336152682551
2561413.63137344639980.368626553600234
2571614.02057929230891.97942070769111
2581411.48659857639562.51340142360441
2591313.9532280855537-0.953228085553718
26049.30524253866037-5.30524253866037
2611513.46126303429461.53873696570543
2621114.6588914363487-3.65889143634869
2631111.0942706014226-0.0942706014226423
2641412.53704727642241.46295272357763






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.9174031500106020.1651936999787970.0825968499893984
140.856823094396750.2863538112064990.143176905603249
150.8064556608230210.3870886783539570.193544339176979
160.8361648171242940.3276703657514120.163835182875706
170.7749024140490140.4501951719019730.225097585950986
180.9321377923487760.1357244153024490.0678622076512243
190.9133280210415010.1733439579169980.0866719789584989
200.8775061569640890.2449876860718230.122493843035911
210.8287166708518210.3425666582963570.171283329148179
220.79554605782840.40890788434320.2044539421716
230.7621641646750090.4756716706499830.237835835324991
240.731894807121850.5362103857562990.268105192878149
250.6735138624108230.6529722751783540.326486137589177
260.6247876890631590.7504246218736830.375212310936841
270.5649731442464640.8700537115070720.435026855753536
280.6114003397727810.7771993204544370.388599660227219
290.5504999355423020.8990001289153960.449500064457698
300.5566288696546380.8867422606907230.443371130345362
310.5045601095643910.9908797808712180.495439890435609
320.4968220253151970.9936440506303950.503177974684803
330.4740069835266210.9480139670532420.525993016473379
340.4125713587477270.8251427174954540.587428641252273
350.3968628233936090.7937256467872170.603137176606392
360.496170486778490.992340973556980.50382951322151
370.5721580696694730.8556838606610530.427841930330527
380.545605510838940.908788978322120.45439448916106
390.5907791848025920.8184416303948150.409220815197408
400.5713237921018860.8573524157962280.428676207898114
410.5358856025968670.9282287948062670.464114397403133
420.5026337733433340.9947324533133320.497366226656666
430.5202008822946910.9595982354106180.479799117705309
440.4710501663393880.9421003326787750.528949833660612
450.4293964114551620.8587928229103240.570603588544838
460.6453577064830040.7092845870339920.354642293516996
470.6587901131885790.6824197736228420.341209886811421
480.6210629359238070.7578741281523860.378937064076193
490.6080351347272080.7839297305455830.391964865272792
500.5794207300919790.8411585398160420.420579269908021
510.5342295181195860.9315409637608280.465770481880414
520.4914389717690370.9828779435380730.508561028230963
530.4977236230981510.9954472461963030.502276376901849
540.4667513745972050.933502749194410.533248625402795
550.466011255298170.932022510596340.53398874470183
560.4798038966876190.9596077933752380.520196103312381
570.4374139423601130.8748278847202260.562586057639887
580.4213043019546180.8426086039092360.578695698045382
590.3802173881952820.7604347763905650.619782611804718
600.4053723067413370.8107446134826740.594627693258663
610.3771299950584110.7542599901168220.622870004941589
620.3402752368525530.6805504737051070.659724763147447
630.3043359027697820.6086718055395630.695664097230218
640.2722235042209340.5444470084418680.727776495779066
650.2458327725745350.4916655451490690.754167227425465
660.2133745404919580.4267490809839160.786625459508042
670.1879617030857380.3759234061714760.812038296914262
680.2052032384243250.4104064768486490.794796761575675
690.4346312986486780.8692625972973570.565368701351322
700.3933734917529490.7867469835058980.606626508247051
710.5013012172404590.9973975655190830.498698782759541
720.4651852021656170.9303704043312340.534814797834383
730.4484637867890940.8969275735781880.551536213210906
740.4191948995838880.8383897991677760.580805100416112
750.3817146164998780.7634292329997560.618285383500122
760.4429381952571340.8858763905142680.557061804742866
770.4065606447728330.8131212895456650.593439355227167
780.3793935623142900.7587871246285790.62060643768571
790.4023633013412510.8047266026825030.597636698658749
800.3682630368567160.7365260737134320.631736963143284
810.3331574458083590.6663148916167170.666842554191641
820.298449480465750.59689896093150.70155051953425
830.2733370001211770.5466740002423540.726662999878823
840.2415581771199620.4831163542399230.758441822880038
850.2342078141481840.4684156282963670.765792185851816
860.2050013823169960.4100027646339910.794998617683004
870.1804070988852880.3608141977705770.819592901114712
880.1638748191348120.3277496382696240.836125180865188
890.141648301830060.283296603660120.85835169816994
900.138202987859570.276405975719140.86179701214043
910.1185274622219250.2370549244438490.881472537778075
920.1028042978011980.2056085956023950.897195702198802
930.0879845006217340.1759690012434680.912015499378266
940.09290780925431830.1858156185086370.907092190745682
950.08374494643187810.1674898928637560.916255053568122
960.06999374736015350.1399874947203070.930006252639846
970.07455962359840850.1491192471968170.925440376401592
980.06205976734718950.1241195346943790.93794023265281
990.05153734306604220.1030746861320840.948462656933958
1000.04504002548627710.09008005097255420.954959974513723
1010.04019333476138390.08038666952276780.959806665238616
1020.04954302515456560.09908605030913120.950456974845434
1030.04175105409943710.08350210819887420.958248945900563
1040.03767794126377230.07535588252754460.962322058736228
1050.04375318753796460.08750637507592910.956246812462035
1060.03902767731246640.07805535462493280.960972322687534
1070.03189153816964230.06378307633928470.968108461830358
1080.03063618225653030.06127236451306050.96936381774347
1090.02483561384987170.04967122769974350.975164386150128
1100.02075704203742060.04151408407484120.97924295796258
1110.01654005260934740.03308010521869490.983459947390653
1120.01785300851596470.03570601703192950.982146991484035
1130.01540713116155330.03081426232310660.984592868838447
1140.01973449854453170.03946899708906340.980265501455468
1150.01938094486179520.03876188972359040.980619055138205
1160.01865495893065620.03730991786131250.981345041069344
1170.01588505798601820.03177011597203630.984114942013982
1180.01558098104467770.03116196208935530.984419018955322
1190.01262208366050960.02524416732101920.98737791633949
1200.01121436852773250.02242873705546510.988785631472268
1210.009116782121600060.01823356424320010.9908832178784
1220.0126954953881350.025390990776270.987304504611865
1230.01038502072513720.02077004145027450.989614979274863
1240.008511951402339520.01702390280467900.99148804859766
1250.006809266869608970.01361853373921790.993190733130391
1260.005375740132009750.01075148026401950.99462425986799
1270.005069354891624550.01013870978324910.994930645108375
1280.004382793997600940.008765587995201890.995617206002399
1290.005649477260932630.01129895452186530.994350522739067
1300.006370792907184850.01274158581436970.993629207092815
1310.01220219968130140.02440439936260290.987797800318699
1320.01520814924769190.03041629849538380.984791850752308
1330.01587898414240190.03175796828480380.984121015857598
1340.01454066049727280.02908132099454560.985459339502727
1350.01152468664523120.02304937329046250.988475313354769
1360.01001366389900430.02002732779800870.989986336100996
1370.008227318984922720.01645463796984540.991772681015077
1380.01034934905626610.02069869811253210.989650650943734
1390.008801965152379050.01760393030475810.99119803484762
1400.01065418904762650.0213083780952530.989345810952374
1410.0171713962016540.0343427924033080.982828603798346
1420.0163468206869370.0326936413738740.983653179313063
1430.01356194522034430.02712389044068870.986438054779656
1440.01408002366543960.02816004733087910.98591997633456
1450.02291605058457230.04583210116914460.977083949415428
1460.02863857435558290.05727714871116590.971361425644417
1470.02997615636088530.05995231272177060.970023843639115
1480.02658661376562510.05317322753125030.973413386234375
1490.02159213586035250.0431842717207050.978407864139648
1500.02961818443544540.05923636887089080.970381815564555
1510.02492185111007820.04984370222015640.975078148889922
1520.02680161829166030.05360323658332060.97319838170834
1530.05462812593373470.1092562518674690.945371874066265
1540.05167636713317430.1033527342663490.948323632866826
1550.05943574763590560.1188714952718110.940564252364094
1560.0504050199016430.1008100398032860.949594980098357
1570.04461703683710920.08923407367421840.95538296316289
1580.03873117628170140.07746235256340280.961268823718299
1590.03788652521820450.0757730504364090.962113474781795
1600.03165398388197820.06330796776395630.968346016118022
1610.02580907659199100.05161815318398210.974190923408009
1620.02078059875145690.04156119750291380.979219401248543
1630.01728223957024990.03456447914049980.98271776042975
1640.01473602000337340.02947204000674690.985263979996627
1650.01244061148863620.02488122297727240.987559388511364
1660.01349200736510750.02698401473021500.986507992634893
1670.01074790676468550.02149581352937100.989252093235314
1680.01566394871566700.03132789743133410.984336051284333
1690.0153571699182490.0307143398364980.984642830081751
1700.01467101044083660.02934202088167310.985328989559163
1710.01342580969214390.02685161938428770.986574190307856
1720.01078860389621030.02157720779242070.98921139610379
1730.01033570025021920.02067140050043840.98966429974978
1740.01157651140434480.02315302280868960.988423488595655
1750.01402870295049750.02805740590099510.985971297049502
1760.01134205182168960.02268410364337920.98865794817831
1770.008814623604540050.01762924720908010.99118537639546
1780.00731173299058070.01462346598116140.99268826700942
1790.005692231167673290.01138446233534660.994307768832327
1800.00482866455373710.00965732910747420.995171335446263
1810.004003999065621010.008007998131242020.99599600093438
1820.003022345831752460.006044691663504910.996977654168248
1830.003405047614760520.006810095229521040.99659495238524
1840.002556436883933270.005112873767866540.997443563116067
1850.07245747224464380.1449149444892880.927542527755356
1860.0654080203115880.1308160406231760.934591979688412
1870.07562701898484830.1512540379696970.924372981015152
1880.0628367424399570.1256734848799140.937163257560043
1890.05554130822890880.1110826164578180.944458691771091
1900.04675181829933910.09350363659867830.95324818170066
1910.04005892017442970.08011784034885940.95994107982557
1920.03314862335281230.06629724670562470.966851376647188
1930.03366726822108640.06733453644217280.966332731778914
1940.03216375306092830.06432750612185660.967836246939072
1950.02761922547764790.05523845095529580.972380774522352
1960.02171201857721110.04342403715442220.978287981422789
1970.02916679711845130.05833359423690250.970833202881549
1980.02372836617301670.04745673234603350.976271633826983
1990.02121618960772980.04243237921545970.97878381039227
2000.01795966546282950.03591933092565890.98204033453717
2010.01638919684649660.03277839369299310.983610803153503
2020.01357534583868630.02715069167737260.986424654161314
2030.01500026759805040.03000053519610070.98499973240195
2040.01984674344131630.03969348688263250.980153256558684
2050.02096859095247390.04193718190494790.979031409047526
2060.01617388213145570.03234776426291150.983826117868544
2070.01431230540898230.02862461081796470.985687694591018
2080.01130453386399030.02260906772798070.98869546613601
2090.01309188152387800.02618376304775600.986908118476122
2100.01071293175945570.02142586351891140.989287068240544
2110.01309101702181740.02618203404363490.986908982978183
2120.02308789984641130.04617579969282270.976912100153589
2130.01778461084100960.03556922168201920.98221538915899
2140.02226457370744890.04452914741489780.977735426292551
2150.01873149191322610.03746298382645230.981268508086774
2160.01426379609671830.02852759219343650.985736203903282
2170.01596069154060030.03192138308120060.9840393084594
2180.01329666828356290.02659333656712590.986703331716437
2190.01226965916253910.02453931832507820.98773034083746
2200.009004208928150340.01800841785630070.99099579107185
2210.007304318884684750.01460863776936950.992695681115315
2220.005193191901060940.01038638380212190.99480680809894
2230.003925993928176160.007851987856352320.996074006071824
2240.002931169826585560.005862339653171110.997068830173414
2250.001996579463873350.00399315892774670.998003420536127
2260.004162431243562730.008324862487125450.995837568756437
2270.003236731904821690.006473463809643380.996763268095178
2280.002297808837789650.004595617675579290.99770219116221
2290.001576222135455670.003152444270911350.998423777864544
2300.001077293940849130.002154587881698260.99892270605915
2310.001164089994363040.002328179988726080.998835910005637
2320.004142608361277800.008285216722555610.995857391638722
2330.01680643790976090.03361287581952180.98319356209024
2340.02626001313866740.05252002627733480.973739986861333
2350.01849741501433500.03699483002866990.981502584985665
2360.01455609506978610.02911219013957210.985443904930214
2370.1577479892498280.3154959784996570.842252010750172
2380.1212096039362030.2424192078724050.878790396063797
2390.09862671298740160.1972534259748030.901373287012598
2400.07464536724944630.1492907344988930.925354632750554
2410.06425555395170690.1285111079034140.935744446048293
2420.1012610679507750.202522135901550.898738932049225
2430.08106380816007560.1621276163201510.918936191839924
2440.07919179485587910.1583835897117580.92080820514412
2450.06552186515272680.1310437303054540.934478134847273
2460.05366711595153520.1073342319030700.946332884048465
2470.03244867939591730.06489735879183470.967551320604083
2480.02623108749021210.05246217498042410.973768912509788
2490.01740480564527200.03480961129054410.982595194354728
2500.044724685955690.089449371911380.95527531404431
2510.02996643274143760.05993286548287530.970033567258562

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.917403150010602 & 0.165193699978797 & 0.0825968499893984 \tabularnewline
14 & 0.85682309439675 & 0.286353811206499 & 0.143176905603249 \tabularnewline
15 & 0.806455660823021 & 0.387088678353957 & 0.193544339176979 \tabularnewline
16 & 0.836164817124294 & 0.327670365751412 & 0.163835182875706 \tabularnewline
17 & 0.774902414049014 & 0.450195171901973 & 0.225097585950986 \tabularnewline
18 & 0.932137792348776 & 0.135724415302449 & 0.0678622076512243 \tabularnewline
19 & 0.913328021041501 & 0.173343957916998 & 0.0866719789584989 \tabularnewline
20 & 0.877506156964089 & 0.244987686071823 & 0.122493843035911 \tabularnewline
21 & 0.828716670851821 & 0.342566658296357 & 0.171283329148179 \tabularnewline
22 & 0.7955460578284 & 0.4089078843432 & 0.2044539421716 \tabularnewline
23 & 0.762164164675009 & 0.475671670649983 & 0.237835835324991 \tabularnewline
24 & 0.73189480712185 & 0.536210385756299 & 0.268105192878149 \tabularnewline
25 & 0.673513862410823 & 0.652972275178354 & 0.326486137589177 \tabularnewline
26 & 0.624787689063159 & 0.750424621873683 & 0.375212310936841 \tabularnewline
27 & 0.564973144246464 & 0.870053711507072 & 0.435026855753536 \tabularnewline
28 & 0.611400339772781 & 0.777199320454437 & 0.388599660227219 \tabularnewline
29 & 0.550499935542302 & 0.899000128915396 & 0.449500064457698 \tabularnewline
30 & 0.556628869654638 & 0.886742260690723 & 0.443371130345362 \tabularnewline
31 & 0.504560109564391 & 0.990879780871218 & 0.495439890435609 \tabularnewline
32 & 0.496822025315197 & 0.993644050630395 & 0.503177974684803 \tabularnewline
33 & 0.474006983526621 & 0.948013967053242 & 0.525993016473379 \tabularnewline
34 & 0.412571358747727 & 0.825142717495454 & 0.587428641252273 \tabularnewline
35 & 0.396862823393609 & 0.793725646787217 & 0.603137176606392 \tabularnewline
36 & 0.49617048677849 & 0.99234097355698 & 0.50382951322151 \tabularnewline
37 & 0.572158069669473 & 0.855683860661053 & 0.427841930330527 \tabularnewline
38 & 0.54560551083894 & 0.90878897832212 & 0.45439448916106 \tabularnewline
39 & 0.590779184802592 & 0.818441630394815 & 0.409220815197408 \tabularnewline
40 & 0.571323792101886 & 0.857352415796228 & 0.428676207898114 \tabularnewline
41 & 0.535885602596867 & 0.928228794806267 & 0.464114397403133 \tabularnewline
42 & 0.502633773343334 & 0.994732453313332 & 0.497366226656666 \tabularnewline
43 & 0.520200882294691 & 0.959598235410618 & 0.479799117705309 \tabularnewline
44 & 0.471050166339388 & 0.942100332678775 & 0.528949833660612 \tabularnewline
45 & 0.429396411455162 & 0.858792822910324 & 0.570603588544838 \tabularnewline
46 & 0.645357706483004 & 0.709284587033992 & 0.354642293516996 \tabularnewline
47 & 0.658790113188579 & 0.682419773622842 & 0.341209886811421 \tabularnewline
48 & 0.621062935923807 & 0.757874128152386 & 0.378937064076193 \tabularnewline
49 & 0.608035134727208 & 0.783929730545583 & 0.391964865272792 \tabularnewline
50 & 0.579420730091979 & 0.841158539816042 & 0.420579269908021 \tabularnewline
51 & 0.534229518119586 & 0.931540963760828 & 0.465770481880414 \tabularnewline
52 & 0.491438971769037 & 0.982877943538073 & 0.508561028230963 \tabularnewline
53 & 0.497723623098151 & 0.995447246196303 & 0.502276376901849 \tabularnewline
54 & 0.466751374597205 & 0.93350274919441 & 0.533248625402795 \tabularnewline
55 & 0.46601125529817 & 0.93202251059634 & 0.53398874470183 \tabularnewline
56 & 0.479803896687619 & 0.959607793375238 & 0.520196103312381 \tabularnewline
57 & 0.437413942360113 & 0.874827884720226 & 0.562586057639887 \tabularnewline
58 & 0.421304301954618 & 0.842608603909236 & 0.578695698045382 \tabularnewline
59 & 0.380217388195282 & 0.760434776390565 & 0.619782611804718 \tabularnewline
60 & 0.405372306741337 & 0.810744613482674 & 0.594627693258663 \tabularnewline
61 & 0.377129995058411 & 0.754259990116822 & 0.622870004941589 \tabularnewline
62 & 0.340275236852553 & 0.680550473705107 & 0.659724763147447 \tabularnewline
63 & 0.304335902769782 & 0.608671805539563 & 0.695664097230218 \tabularnewline
64 & 0.272223504220934 & 0.544447008441868 & 0.727776495779066 \tabularnewline
65 & 0.245832772574535 & 0.491665545149069 & 0.754167227425465 \tabularnewline
66 & 0.213374540491958 & 0.426749080983916 & 0.786625459508042 \tabularnewline
67 & 0.187961703085738 & 0.375923406171476 & 0.812038296914262 \tabularnewline
68 & 0.205203238424325 & 0.410406476848649 & 0.794796761575675 \tabularnewline
69 & 0.434631298648678 & 0.869262597297357 & 0.565368701351322 \tabularnewline
70 & 0.393373491752949 & 0.786746983505898 & 0.606626508247051 \tabularnewline
71 & 0.501301217240459 & 0.997397565519083 & 0.498698782759541 \tabularnewline
72 & 0.465185202165617 & 0.930370404331234 & 0.534814797834383 \tabularnewline
73 & 0.448463786789094 & 0.896927573578188 & 0.551536213210906 \tabularnewline
74 & 0.419194899583888 & 0.838389799167776 & 0.580805100416112 \tabularnewline
75 & 0.381714616499878 & 0.763429232999756 & 0.618285383500122 \tabularnewline
76 & 0.442938195257134 & 0.885876390514268 & 0.557061804742866 \tabularnewline
77 & 0.406560644772833 & 0.813121289545665 & 0.593439355227167 \tabularnewline
78 & 0.379393562314290 & 0.758787124628579 & 0.62060643768571 \tabularnewline
79 & 0.402363301341251 & 0.804726602682503 & 0.597636698658749 \tabularnewline
80 & 0.368263036856716 & 0.736526073713432 & 0.631736963143284 \tabularnewline
81 & 0.333157445808359 & 0.666314891616717 & 0.666842554191641 \tabularnewline
82 & 0.29844948046575 & 0.5968989609315 & 0.70155051953425 \tabularnewline
83 & 0.273337000121177 & 0.546674000242354 & 0.726662999878823 \tabularnewline
84 & 0.241558177119962 & 0.483116354239923 & 0.758441822880038 \tabularnewline
85 & 0.234207814148184 & 0.468415628296367 & 0.765792185851816 \tabularnewline
86 & 0.205001382316996 & 0.410002764633991 & 0.794998617683004 \tabularnewline
87 & 0.180407098885288 & 0.360814197770577 & 0.819592901114712 \tabularnewline
88 & 0.163874819134812 & 0.327749638269624 & 0.836125180865188 \tabularnewline
89 & 0.14164830183006 & 0.28329660366012 & 0.85835169816994 \tabularnewline
90 & 0.13820298785957 & 0.27640597571914 & 0.86179701214043 \tabularnewline
91 & 0.118527462221925 & 0.237054924443849 & 0.881472537778075 \tabularnewline
92 & 0.102804297801198 & 0.205608595602395 & 0.897195702198802 \tabularnewline
93 & 0.087984500621734 & 0.175969001243468 & 0.912015499378266 \tabularnewline
94 & 0.0929078092543183 & 0.185815618508637 & 0.907092190745682 \tabularnewline
95 & 0.0837449464318781 & 0.167489892863756 & 0.916255053568122 \tabularnewline
96 & 0.0699937473601535 & 0.139987494720307 & 0.930006252639846 \tabularnewline
97 & 0.0745596235984085 & 0.149119247196817 & 0.925440376401592 \tabularnewline
98 & 0.0620597673471895 & 0.124119534694379 & 0.93794023265281 \tabularnewline
99 & 0.0515373430660422 & 0.103074686132084 & 0.948462656933958 \tabularnewline
100 & 0.0450400254862771 & 0.0900800509725542 & 0.954959974513723 \tabularnewline
101 & 0.0401933347613839 & 0.0803866695227678 & 0.959806665238616 \tabularnewline
102 & 0.0495430251545656 & 0.0990860503091312 & 0.950456974845434 \tabularnewline
103 & 0.0417510540994371 & 0.0835021081988742 & 0.958248945900563 \tabularnewline
104 & 0.0376779412637723 & 0.0753558825275446 & 0.962322058736228 \tabularnewline
105 & 0.0437531875379646 & 0.0875063750759291 & 0.956246812462035 \tabularnewline
106 & 0.0390276773124664 & 0.0780553546249328 & 0.960972322687534 \tabularnewline
107 & 0.0318915381696423 & 0.0637830763392847 & 0.968108461830358 \tabularnewline
108 & 0.0306361822565303 & 0.0612723645130605 & 0.96936381774347 \tabularnewline
109 & 0.0248356138498717 & 0.0496712276997435 & 0.975164386150128 \tabularnewline
110 & 0.0207570420374206 & 0.0415140840748412 & 0.97924295796258 \tabularnewline
111 & 0.0165400526093474 & 0.0330801052186949 & 0.983459947390653 \tabularnewline
112 & 0.0178530085159647 & 0.0357060170319295 & 0.982146991484035 \tabularnewline
113 & 0.0154071311615533 & 0.0308142623231066 & 0.984592868838447 \tabularnewline
114 & 0.0197344985445317 & 0.0394689970890634 & 0.980265501455468 \tabularnewline
115 & 0.0193809448617952 & 0.0387618897235904 & 0.980619055138205 \tabularnewline
116 & 0.0186549589306562 & 0.0373099178613125 & 0.981345041069344 \tabularnewline
117 & 0.0158850579860182 & 0.0317701159720363 & 0.984114942013982 \tabularnewline
118 & 0.0155809810446777 & 0.0311619620893553 & 0.984419018955322 \tabularnewline
119 & 0.0126220836605096 & 0.0252441673210192 & 0.98737791633949 \tabularnewline
120 & 0.0112143685277325 & 0.0224287370554651 & 0.988785631472268 \tabularnewline
121 & 0.00911678212160006 & 0.0182335642432001 & 0.9908832178784 \tabularnewline
122 & 0.012695495388135 & 0.02539099077627 & 0.987304504611865 \tabularnewline
123 & 0.0103850207251372 & 0.0207700414502745 & 0.989614979274863 \tabularnewline
124 & 0.00851195140233952 & 0.0170239028046790 & 0.99148804859766 \tabularnewline
125 & 0.00680926686960897 & 0.0136185337392179 & 0.993190733130391 \tabularnewline
126 & 0.00537574013200975 & 0.0107514802640195 & 0.99462425986799 \tabularnewline
127 & 0.00506935489162455 & 0.0101387097832491 & 0.994930645108375 \tabularnewline
128 & 0.00438279399760094 & 0.00876558799520189 & 0.995617206002399 \tabularnewline
129 & 0.00564947726093263 & 0.0112989545218653 & 0.994350522739067 \tabularnewline
130 & 0.00637079290718485 & 0.0127415858143697 & 0.993629207092815 \tabularnewline
131 & 0.0122021996813014 & 0.0244043993626029 & 0.987797800318699 \tabularnewline
132 & 0.0152081492476919 & 0.0304162984953838 & 0.984791850752308 \tabularnewline
133 & 0.0158789841424019 & 0.0317579682848038 & 0.984121015857598 \tabularnewline
134 & 0.0145406604972728 & 0.0290813209945456 & 0.985459339502727 \tabularnewline
135 & 0.0115246866452312 & 0.0230493732904625 & 0.988475313354769 \tabularnewline
136 & 0.0100136638990043 & 0.0200273277980087 & 0.989986336100996 \tabularnewline
137 & 0.00822731898492272 & 0.0164546379698454 & 0.991772681015077 \tabularnewline
138 & 0.0103493490562661 & 0.0206986981125321 & 0.989650650943734 \tabularnewline
139 & 0.00880196515237905 & 0.0176039303047581 & 0.99119803484762 \tabularnewline
140 & 0.0106541890476265 & 0.021308378095253 & 0.989345810952374 \tabularnewline
141 & 0.017171396201654 & 0.034342792403308 & 0.982828603798346 \tabularnewline
142 & 0.016346820686937 & 0.032693641373874 & 0.983653179313063 \tabularnewline
143 & 0.0135619452203443 & 0.0271238904406887 & 0.986438054779656 \tabularnewline
144 & 0.0140800236654396 & 0.0281600473308791 & 0.98591997633456 \tabularnewline
145 & 0.0229160505845723 & 0.0458321011691446 & 0.977083949415428 \tabularnewline
146 & 0.0286385743555829 & 0.0572771487111659 & 0.971361425644417 \tabularnewline
147 & 0.0299761563608853 & 0.0599523127217706 & 0.970023843639115 \tabularnewline
148 & 0.0265866137656251 & 0.0531732275312503 & 0.973413386234375 \tabularnewline
149 & 0.0215921358603525 & 0.043184271720705 & 0.978407864139648 \tabularnewline
150 & 0.0296181844354454 & 0.0592363688708908 & 0.970381815564555 \tabularnewline
151 & 0.0249218511100782 & 0.0498437022201564 & 0.975078148889922 \tabularnewline
152 & 0.0268016182916603 & 0.0536032365833206 & 0.97319838170834 \tabularnewline
153 & 0.0546281259337347 & 0.109256251867469 & 0.945371874066265 \tabularnewline
154 & 0.0516763671331743 & 0.103352734266349 & 0.948323632866826 \tabularnewline
155 & 0.0594357476359056 & 0.118871495271811 & 0.940564252364094 \tabularnewline
156 & 0.050405019901643 & 0.100810039803286 & 0.949594980098357 \tabularnewline
157 & 0.0446170368371092 & 0.0892340736742184 & 0.95538296316289 \tabularnewline
158 & 0.0387311762817014 & 0.0774623525634028 & 0.961268823718299 \tabularnewline
159 & 0.0378865252182045 & 0.075773050436409 & 0.962113474781795 \tabularnewline
160 & 0.0316539838819782 & 0.0633079677639563 & 0.968346016118022 \tabularnewline
161 & 0.0258090765919910 & 0.0516181531839821 & 0.974190923408009 \tabularnewline
162 & 0.0207805987514569 & 0.0415611975029138 & 0.979219401248543 \tabularnewline
163 & 0.0172822395702499 & 0.0345644791404998 & 0.98271776042975 \tabularnewline
164 & 0.0147360200033734 & 0.0294720400067469 & 0.985263979996627 \tabularnewline
165 & 0.0124406114886362 & 0.0248812229772724 & 0.987559388511364 \tabularnewline
166 & 0.0134920073651075 & 0.0269840147302150 & 0.986507992634893 \tabularnewline
167 & 0.0107479067646855 & 0.0214958135293710 & 0.989252093235314 \tabularnewline
168 & 0.0156639487156670 & 0.0313278974313341 & 0.984336051284333 \tabularnewline
169 & 0.015357169918249 & 0.030714339836498 & 0.984642830081751 \tabularnewline
170 & 0.0146710104408366 & 0.0293420208816731 & 0.985328989559163 \tabularnewline
171 & 0.0134258096921439 & 0.0268516193842877 & 0.986574190307856 \tabularnewline
172 & 0.0107886038962103 & 0.0215772077924207 & 0.98921139610379 \tabularnewline
173 & 0.0103357002502192 & 0.0206714005004384 & 0.98966429974978 \tabularnewline
174 & 0.0115765114043448 & 0.0231530228086896 & 0.988423488595655 \tabularnewline
175 & 0.0140287029504975 & 0.0280574059009951 & 0.985971297049502 \tabularnewline
176 & 0.0113420518216896 & 0.0226841036433792 & 0.98865794817831 \tabularnewline
177 & 0.00881462360454005 & 0.0176292472090801 & 0.99118537639546 \tabularnewline
178 & 0.0073117329905807 & 0.0146234659811614 & 0.99268826700942 \tabularnewline
179 & 0.00569223116767329 & 0.0113844623353466 & 0.994307768832327 \tabularnewline
180 & 0.0048286645537371 & 0.0096573291074742 & 0.995171335446263 \tabularnewline
181 & 0.00400399906562101 & 0.00800799813124202 & 0.99599600093438 \tabularnewline
182 & 0.00302234583175246 & 0.00604469166350491 & 0.996977654168248 \tabularnewline
183 & 0.00340504761476052 & 0.00681009522952104 & 0.99659495238524 \tabularnewline
184 & 0.00255643688393327 & 0.00511287376786654 & 0.997443563116067 \tabularnewline
185 & 0.0724574722446438 & 0.144914944489288 & 0.927542527755356 \tabularnewline
186 & 0.065408020311588 & 0.130816040623176 & 0.934591979688412 \tabularnewline
187 & 0.0756270189848483 & 0.151254037969697 & 0.924372981015152 \tabularnewline
188 & 0.062836742439957 & 0.125673484879914 & 0.937163257560043 \tabularnewline
189 & 0.0555413082289088 & 0.111082616457818 & 0.944458691771091 \tabularnewline
190 & 0.0467518182993391 & 0.0935036365986783 & 0.95324818170066 \tabularnewline
191 & 0.0400589201744297 & 0.0801178403488594 & 0.95994107982557 \tabularnewline
192 & 0.0331486233528123 & 0.0662972467056247 & 0.966851376647188 \tabularnewline
193 & 0.0336672682210864 & 0.0673345364421728 & 0.966332731778914 \tabularnewline
194 & 0.0321637530609283 & 0.0643275061218566 & 0.967836246939072 \tabularnewline
195 & 0.0276192254776479 & 0.0552384509552958 & 0.972380774522352 \tabularnewline
196 & 0.0217120185772111 & 0.0434240371544222 & 0.978287981422789 \tabularnewline
197 & 0.0291667971184513 & 0.0583335942369025 & 0.970833202881549 \tabularnewline
198 & 0.0237283661730167 & 0.0474567323460335 & 0.976271633826983 \tabularnewline
199 & 0.0212161896077298 & 0.0424323792154597 & 0.97878381039227 \tabularnewline
200 & 0.0179596654628295 & 0.0359193309256589 & 0.98204033453717 \tabularnewline
201 & 0.0163891968464966 & 0.0327783936929931 & 0.983610803153503 \tabularnewline
202 & 0.0135753458386863 & 0.0271506916773726 & 0.986424654161314 \tabularnewline
203 & 0.0150002675980504 & 0.0300005351961007 & 0.98499973240195 \tabularnewline
204 & 0.0198467434413163 & 0.0396934868826325 & 0.980153256558684 \tabularnewline
205 & 0.0209685909524739 & 0.0419371819049479 & 0.979031409047526 \tabularnewline
206 & 0.0161738821314557 & 0.0323477642629115 & 0.983826117868544 \tabularnewline
207 & 0.0143123054089823 & 0.0286246108179647 & 0.985687694591018 \tabularnewline
208 & 0.0113045338639903 & 0.0226090677279807 & 0.98869546613601 \tabularnewline
209 & 0.0130918815238780 & 0.0261837630477560 & 0.986908118476122 \tabularnewline
210 & 0.0107129317594557 & 0.0214258635189114 & 0.989287068240544 \tabularnewline
211 & 0.0130910170218174 & 0.0261820340436349 & 0.986908982978183 \tabularnewline
212 & 0.0230878998464113 & 0.0461757996928227 & 0.976912100153589 \tabularnewline
213 & 0.0177846108410096 & 0.0355692216820192 & 0.98221538915899 \tabularnewline
214 & 0.0222645737074489 & 0.0445291474148978 & 0.977735426292551 \tabularnewline
215 & 0.0187314919132261 & 0.0374629838264523 & 0.981268508086774 \tabularnewline
216 & 0.0142637960967183 & 0.0285275921934365 & 0.985736203903282 \tabularnewline
217 & 0.0159606915406003 & 0.0319213830812006 & 0.9840393084594 \tabularnewline
218 & 0.0132966682835629 & 0.0265933365671259 & 0.986703331716437 \tabularnewline
219 & 0.0122696591625391 & 0.0245393183250782 & 0.98773034083746 \tabularnewline
220 & 0.00900420892815034 & 0.0180084178563007 & 0.99099579107185 \tabularnewline
221 & 0.00730431888468475 & 0.0146086377693695 & 0.992695681115315 \tabularnewline
222 & 0.00519319190106094 & 0.0103863838021219 & 0.99480680809894 \tabularnewline
223 & 0.00392599392817616 & 0.00785198785635232 & 0.996074006071824 \tabularnewline
224 & 0.00293116982658556 & 0.00586233965317111 & 0.997068830173414 \tabularnewline
225 & 0.00199657946387335 & 0.0039931589277467 & 0.998003420536127 \tabularnewline
226 & 0.00416243124356273 & 0.00832486248712545 & 0.995837568756437 \tabularnewline
227 & 0.00323673190482169 & 0.00647346380964338 & 0.996763268095178 \tabularnewline
228 & 0.00229780883778965 & 0.00459561767557929 & 0.99770219116221 \tabularnewline
229 & 0.00157622213545567 & 0.00315244427091135 & 0.998423777864544 \tabularnewline
230 & 0.00107729394084913 & 0.00215458788169826 & 0.99892270605915 \tabularnewline
231 & 0.00116408999436304 & 0.00232817998872608 & 0.998835910005637 \tabularnewline
232 & 0.00414260836127780 & 0.00828521672255561 & 0.995857391638722 \tabularnewline
233 & 0.0168064379097609 & 0.0336128758195218 & 0.98319356209024 \tabularnewline
234 & 0.0262600131386674 & 0.0525200262773348 & 0.973739986861333 \tabularnewline
235 & 0.0184974150143350 & 0.0369948300286699 & 0.981502584985665 \tabularnewline
236 & 0.0145560950697861 & 0.0291121901395721 & 0.985443904930214 \tabularnewline
237 & 0.157747989249828 & 0.315495978499657 & 0.842252010750172 \tabularnewline
238 & 0.121209603936203 & 0.242419207872405 & 0.878790396063797 \tabularnewline
239 & 0.0986267129874016 & 0.197253425974803 & 0.901373287012598 \tabularnewline
240 & 0.0746453672494463 & 0.149290734498893 & 0.925354632750554 \tabularnewline
241 & 0.0642555539517069 & 0.128511107903414 & 0.935744446048293 \tabularnewline
242 & 0.101261067950775 & 0.20252213590155 & 0.898738932049225 \tabularnewline
243 & 0.0810638081600756 & 0.162127616320151 & 0.918936191839924 \tabularnewline
244 & 0.0791917948558791 & 0.158383589711758 & 0.92080820514412 \tabularnewline
245 & 0.0655218651527268 & 0.131043730305454 & 0.934478134847273 \tabularnewline
246 & 0.0536671159515352 & 0.107334231903070 & 0.946332884048465 \tabularnewline
247 & 0.0324486793959173 & 0.0648973587918347 & 0.967551320604083 \tabularnewline
248 & 0.0262310874902121 & 0.0524621749804241 & 0.973768912509788 \tabularnewline
249 & 0.0174048056452720 & 0.0348096112905441 & 0.982595194354728 \tabularnewline
250 & 0.04472468595569 & 0.08944937191138 & 0.95527531404431 \tabularnewline
251 & 0.0299664327414376 & 0.0599328654828753 & 0.970033567258562 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96551&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]0.917403150010602[/C][C]0.165193699978797[/C][C]0.0825968499893984[/C][/ROW]
[ROW][C]14[/C][C]0.85682309439675[/C][C]0.286353811206499[/C][C]0.143176905603249[/C][/ROW]
[ROW][C]15[/C][C]0.806455660823021[/C][C]0.387088678353957[/C][C]0.193544339176979[/C][/ROW]
[ROW][C]16[/C][C]0.836164817124294[/C][C]0.327670365751412[/C][C]0.163835182875706[/C][/ROW]
[ROW][C]17[/C][C]0.774902414049014[/C][C]0.450195171901973[/C][C]0.225097585950986[/C][/ROW]
[ROW][C]18[/C][C]0.932137792348776[/C][C]0.135724415302449[/C][C]0.0678622076512243[/C][/ROW]
[ROW][C]19[/C][C]0.913328021041501[/C][C]0.173343957916998[/C][C]0.0866719789584989[/C][/ROW]
[ROW][C]20[/C][C]0.877506156964089[/C][C]0.244987686071823[/C][C]0.122493843035911[/C][/ROW]
[ROW][C]21[/C][C]0.828716670851821[/C][C]0.342566658296357[/C][C]0.171283329148179[/C][/ROW]
[ROW][C]22[/C][C]0.7955460578284[/C][C]0.4089078843432[/C][C]0.2044539421716[/C][/ROW]
[ROW][C]23[/C][C]0.762164164675009[/C][C]0.475671670649983[/C][C]0.237835835324991[/C][/ROW]
[ROW][C]24[/C][C]0.73189480712185[/C][C]0.536210385756299[/C][C]0.268105192878149[/C][/ROW]
[ROW][C]25[/C][C]0.673513862410823[/C][C]0.652972275178354[/C][C]0.326486137589177[/C][/ROW]
[ROW][C]26[/C][C]0.624787689063159[/C][C]0.750424621873683[/C][C]0.375212310936841[/C][/ROW]
[ROW][C]27[/C][C]0.564973144246464[/C][C]0.870053711507072[/C][C]0.435026855753536[/C][/ROW]
[ROW][C]28[/C][C]0.611400339772781[/C][C]0.777199320454437[/C][C]0.388599660227219[/C][/ROW]
[ROW][C]29[/C][C]0.550499935542302[/C][C]0.899000128915396[/C][C]0.449500064457698[/C][/ROW]
[ROW][C]30[/C][C]0.556628869654638[/C][C]0.886742260690723[/C][C]0.443371130345362[/C][/ROW]
[ROW][C]31[/C][C]0.504560109564391[/C][C]0.990879780871218[/C][C]0.495439890435609[/C][/ROW]
[ROW][C]32[/C][C]0.496822025315197[/C][C]0.993644050630395[/C][C]0.503177974684803[/C][/ROW]
[ROW][C]33[/C][C]0.474006983526621[/C][C]0.948013967053242[/C][C]0.525993016473379[/C][/ROW]
[ROW][C]34[/C][C]0.412571358747727[/C][C]0.825142717495454[/C][C]0.587428641252273[/C][/ROW]
[ROW][C]35[/C][C]0.396862823393609[/C][C]0.793725646787217[/C][C]0.603137176606392[/C][/ROW]
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[ROW][C]182[/C][C]0.00302234583175246[/C][C]0.00604469166350491[/C][C]0.996977654168248[/C][/ROW]
[ROW][C]183[/C][C]0.00340504761476052[/C][C]0.00681009522952104[/C][C]0.99659495238524[/C][/ROW]
[ROW][C]184[/C][C]0.00255643688393327[/C][C]0.00511287376786654[/C][C]0.997443563116067[/C][/ROW]
[ROW][C]185[/C][C]0.0724574722446438[/C][C]0.144914944489288[/C][C]0.927542527755356[/C][/ROW]
[ROW][C]186[/C][C]0.065408020311588[/C][C]0.130816040623176[/C][C]0.934591979688412[/C][/ROW]
[ROW][C]187[/C][C]0.0756270189848483[/C][C]0.151254037969697[/C][C]0.924372981015152[/C][/ROW]
[ROW][C]188[/C][C]0.062836742439957[/C][C]0.125673484879914[/C][C]0.937163257560043[/C][/ROW]
[ROW][C]189[/C][C]0.0555413082289088[/C][C]0.111082616457818[/C][C]0.944458691771091[/C][/ROW]
[ROW][C]190[/C][C]0.0467518182993391[/C][C]0.0935036365986783[/C][C]0.95324818170066[/C][/ROW]
[ROW][C]191[/C][C]0.0400589201744297[/C][C]0.0801178403488594[/C][C]0.95994107982557[/C][/ROW]
[ROW][C]192[/C][C]0.0331486233528123[/C][C]0.0662972467056247[/C][C]0.966851376647188[/C][/ROW]
[ROW][C]193[/C][C]0.0336672682210864[/C][C]0.0673345364421728[/C][C]0.966332731778914[/C][/ROW]
[ROW][C]194[/C][C]0.0321637530609283[/C][C]0.0643275061218566[/C][C]0.967836246939072[/C][/ROW]
[ROW][C]195[/C][C]0.0276192254776479[/C][C]0.0552384509552958[/C][C]0.972380774522352[/C][/ROW]
[ROW][C]196[/C][C]0.0217120185772111[/C][C]0.0434240371544222[/C][C]0.978287981422789[/C][/ROW]
[ROW][C]197[/C][C]0.0291667971184513[/C][C]0.0583335942369025[/C][C]0.970833202881549[/C][/ROW]
[ROW][C]198[/C][C]0.0237283661730167[/C][C]0.0474567323460335[/C][C]0.976271633826983[/C][/ROW]
[ROW][C]199[/C][C]0.0212161896077298[/C][C]0.0424323792154597[/C][C]0.97878381039227[/C][/ROW]
[ROW][C]200[/C][C]0.0179596654628295[/C][C]0.0359193309256589[/C][C]0.98204033453717[/C][/ROW]
[ROW][C]201[/C][C]0.0163891968464966[/C][C]0.0327783936929931[/C][C]0.983610803153503[/C][/ROW]
[ROW][C]202[/C][C]0.0135753458386863[/C][C]0.0271506916773726[/C][C]0.986424654161314[/C][/ROW]
[ROW][C]203[/C][C]0.0150002675980504[/C][C]0.0300005351961007[/C][C]0.98499973240195[/C][/ROW]
[ROW][C]204[/C][C]0.0198467434413163[/C][C]0.0396934868826325[/C][C]0.980153256558684[/C][/ROW]
[ROW][C]205[/C][C]0.0209685909524739[/C][C]0.0419371819049479[/C][C]0.979031409047526[/C][/ROW]
[ROW][C]206[/C][C]0.0161738821314557[/C][C]0.0323477642629115[/C][C]0.983826117868544[/C][/ROW]
[ROW][C]207[/C][C]0.0143123054089823[/C][C]0.0286246108179647[/C][C]0.985687694591018[/C][/ROW]
[ROW][C]208[/C][C]0.0113045338639903[/C][C]0.0226090677279807[/C][C]0.98869546613601[/C][/ROW]
[ROW][C]209[/C][C]0.0130918815238780[/C][C]0.0261837630477560[/C][C]0.986908118476122[/C][/ROW]
[ROW][C]210[/C][C]0.0107129317594557[/C][C]0.0214258635189114[/C][C]0.989287068240544[/C][/ROW]
[ROW][C]211[/C][C]0.0130910170218174[/C][C]0.0261820340436349[/C][C]0.986908982978183[/C][/ROW]
[ROW][C]212[/C][C]0.0230878998464113[/C][C]0.0461757996928227[/C][C]0.976912100153589[/C][/ROW]
[ROW][C]213[/C][C]0.0177846108410096[/C][C]0.0355692216820192[/C][C]0.98221538915899[/C][/ROW]
[ROW][C]214[/C][C]0.0222645737074489[/C][C]0.0445291474148978[/C][C]0.977735426292551[/C][/ROW]
[ROW][C]215[/C][C]0.0187314919132261[/C][C]0.0374629838264523[/C][C]0.981268508086774[/C][/ROW]
[ROW][C]216[/C][C]0.0142637960967183[/C][C]0.0285275921934365[/C][C]0.985736203903282[/C][/ROW]
[ROW][C]217[/C][C]0.0159606915406003[/C][C]0.0319213830812006[/C][C]0.9840393084594[/C][/ROW]
[ROW][C]218[/C][C]0.0132966682835629[/C][C]0.0265933365671259[/C][C]0.986703331716437[/C][/ROW]
[ROW][C]219[/C][C]0.0122696591625391[/C][C]0.0245393183250782[/C][C]0.98773034083746[/C][/ROW]
[ROW][C]220[/C][C]0.00900420892815034[/C][C]0.0180084178563007[/C][C]0.99099579107185[/C][/ROW]
[ROW][C]221[/C][C]0.00730431888468475[/C][C]0.0146086377693695[/C][C]0.992695681115315[/C][/ROW]
[ROW][C]222[/C][C]0.00519319190106094[/C][C]0.0103863838021219[/C][C]0.99480680809894[/C][/ROW]
[ROW][C]223[/C][C]0.00392599392817616[/C][C]0.00785198785635232[/C][C]0.996074006071824[/C][/ROW]
[ROW][C]224[/C][C]0.00293116982658556[/C][C]0.00586233965317111[/C][C]0.997068830173414[/C][/ROW]
[ROW][C]225[/C][C]0.00199657946387335[/C][C]0.0039931589277467[/C][C]0.998003420536127[/C][/ROW]
[ROW][C]226[/C][C]0.00416243124356273[/C][C]0.00832486248712545[/C][C]0.995837568756437[/C][/ROW]
[ROW][C]227[/C][C]0.00323673190482169[/C][C]0.00647346380964338[/C][C]0.996763268095178[/C][/ROW]
[ROW][C]228[/C][C]0.00229780883778965[/C][C]0.00459561767557929[/C][C]0.99770219116221[/C][/ROW]
[ROW][C]229[/C][C]0.00157622213545567[/C][C]0.00315244427091135[/C][C]0.998423777864544[/C][/ROW]
[ROW][C]230[/C][C]0.00107729394084913[/C][C]0.00215458788169826[/C][C]0.99892270605915[/C][/ROW]
[ROW][C]231[/C][C]0.00116408999436304[/C][C]0.00232817998872608[/C][C]0.998835910005637[/C][/ROW]
[ROW][C]232[/C][C]0.00414260836127780[/C][C]0.00828521672255561[/C][C]0.995857391638722[/C][/ROW]
[ROW][C]233[/C][C]0.0168064379097609[/C][C]0.0336128758195218[/C][C]0.98319356209024[/C][/ROW]
[ROW][C]234[/C][C]0.0262600131386674[/C][C]0.0525200262773348[/C][C]0.973739986861333[/C][/ROW]
[ROW][C]235[/C][C]0.0184974150143350[/C][C]0.0369948300286699[/C][C]0.981502584985665[/C][/ROW]
[ROW][C]236[/C][C]0.0145560950697861[/C][C]0.0291121901395721[/C][C]0.985443904930214[/C][/ROW]
[ROW][C]237[/C][C]0.157747989249828[/C][C]0.315495978499657[/C][C]0.842252010750172[/C][/ROW]
[ROW][C]238[/C][C]0.121209603936203[/C][C]0.242419207872405[/C][C]0.878790396063797[/C][/ROW]
[ROW][C]239[/C][C]0.0986267129874016[/C][C]0.197253425974803[/C][C]0.901373287012598[/C][/ROW]
[ROW][C]240[/C][C]0.0746453672494463[/C][C]0.149290734498893[/C][C]0.925354632750554[/C][/ROW]
[ROW][C]241[/C][C]0.0642555539517069[/C][C]0.128511107903414[/C][C]0.935744446048293[/C][/ROW]
[ROW][C]242[/C][C]0.101261067950775[/C][C]0.20252213590155[/C][C]0.898738932049225[/C][/ROW]
[ROW][C]243[/C][C]0.0810638081600756[/C][C]0.162127616320151[/C][C]0.918936191839924[/C][/ROW]
[ROW][C]244[/C][C]0.0791917948558791[/C][C]0.158383589711758[/C][C]0.92080820514412[/C][/ROW]
[ROW][C]245[/C][C]0.0655218651527268[/C][C]0.131043730305454[/C][C]0.934478134847273[/C][/ROW]
[ROW][C]246[/C][C]0.0536671159515352[/C][C]0.107334231903070[/C][C]0.946332884048465[/C][/ROW]
[ROW][C]247[/C][C]0.0324486793959173[/C][C]0.0648973587918347[/C][C]0.967551320604083[/C][/ROW]
[ROW][C]248[/C][C]0.0262310874902121[/C][C]0.0524621749804241[/C][C]0.973768912509788[/C][/ROW]
[ROW][C]249[/C][C]0.0174048056452720[/C][C]0.0348096112905441[/C][C]0.982595194354728[/C][/ROW]
[ROW][C]250[/C][C]0.04472468595569[/C][C]0.08944937191138[/C][C]0.95527531404431[/C][/ROW]
[ROW][C]251[/C][C]0.0299664327414376[/C][C]0.0599328654828753[/C][C]0.970033567258562[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96551&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96551&T=5

As an alternative you can also use a QR Code:  
QR Code


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.9174031500106020.1651936999787970.0825968499893984
140.856823094396750.2863538112064990.143176905603249
150.8064556608230210.3870886783539570.193544339176979
160.8361648171242940.3276703657514120.163835182875706
170.7749024140490140.4501951719019730.225097585950986
180.9321377923487760.1357244153024490.0678622076512243
190.9133280210415010.1733439579169980.0866719789584989
200.8775061569640890.2449876860718230.122493843035911
210.8287166708518210.3425666582963570.171283329148179
220.79554605782840.40890788434320.2044539421716
230.7621641646750090.4756716706499830.237835835324991
240.731894807121850.5362103857562990.268105192878149
250.6735138624108230.6529722751783540.326486137589177
260.6247876890631590.7504246218736830.375212310936841
270.5649731442464640.8700537115070720.435026855753536
280.6114003397727810.7771993204544370.388599660227219
290.5504999355423020.8990001289153960.449500064457698
300.5566288696546380.8867422606907230.443371130345362
310.5045601095643910.9908797808712180.495439890435609
320.4968220253151970.9936440506303950.503177974684803
330.4740069835266210.9480139670532420.525993016473379
340.4125713587477270.8251427174954540.587428641252273
350.3968628233936090.7937256467872170.603137176606392
360.496170486778490.992340973556980.50382951322151
370.5721580696694730.8556838606610530.427841930330527
380.545605510838940.908788978322120.45439448916106
390.5907791848025920.8184416303948150.409220815197408
400.5713237921018860.8573524157962280.428676207898114
410.5358856025968670.9282287948062670.464114397403133
420.5026337733433340.9947324533133320.497366226656666
430.5202008822946910.9595982354106180.479799117705309
440.4710501663393880.9421003326787750.528949833660612
450.4293964114551620.8587928229103240.570603588544838
460.6453577064830040.7092845870339920.354642293516996
470.6587901131885790.6824197736228420.341209886811421
480.6210629359238070.7578741281523860.378937064076193
490.6080351347272080.7839297305455830.391964865272792
500.5794207300919790.8411585398160420.420579269908021
510.5342295181195860.9315409637608280.465770481880414
520.4914389717690370.9828779435380730.508561028230963
530.4977236230981510.9954472461963030.502276376901849
540.4667513745972050.933502749194410.533248625402795
550.466011255298170.932022510596340.53398874470183
560.4798038966876190.9596077933752380.520196103312381
570.4374139423601130.8748278847202260.562586057639887
580.4213043019546180.8426086039092360.578695698045382
590.3802173881952820.7604347763905650.619782611804718
600.4053723067413370.8107446134826740.594627693258663
610.3771299950584110.7542599901168220.622870004941589
620.3402752368525530.6805504737051070.659724763147447
630.3043359027697820.6086718055395630.695664097230218
640.2722235042209340.5444470084418680.727776495779066
650.2458327725745350.4916655451490690.754167227425465
660.2133745404919580.4267490809839160.786625459508042
670.1879617030857380.3759234061714760.812038296914262
680.2052032384243250.4104064768486490.794796761575675
690.4346312986486780.8692625972973570.565368701351322
700.3933734917529490.7867469835058980.606626508247051
710.5013012172404590.9973975655190830.498698782759541
720.4651852021656170.9303704043312340.534814797834383
730.4484637867890940.8969275735781880.551536213210906
740.4191948995838880.8383897991677760.580805100416112
750.3817146164998780.7634292329997560.618285383500122
760.4429381952571340.8858763905142680.557061804742866
770.4065606447728330.8131212895456650.593439355227167
780.3793935623142900.7587871246285790.62060643768571
790.4023633013412510.8047266026825030.597636698658749
800.3682630368567160.7365260737134320.631736963143284
810.3331574458083590.6663148916167170.666842554191641
820.298449480465750.59689896093150.70155051953425
830.2733370001211770.5466740002423540.726662999878823
840.2415581771199620.4831163542399230.758441822880038
850.2342078141481840.4684156282963670.765792185851816
860.2050013823169960.4100027646339910.794998617683004
870.1804070988852880.3608141977705770.819592901114712
880.1638748191348120.3277496382696240.836125180865188
890.141648301830060.283296603660120.85835169816994
900.138202987859570.276405975719140.86179701214043
910.1185274622219250.2370549244438490.881472537778075
920.1028042978011980.2056085956023950.897195702198802
930.0879845006217340.1759690012434680.912015499378266
940.09290780925431830.1858156185086370.907092190745682
950.08374494643187810.1674898928637560.916255053568122
960.06999374736015350.1399874947203070.930006252639846
970.07455962359840850.1491192471968170.925440376401592
980.06205976734718950.1241195346943790.93794023265281
990.05153734306604220.1030746861320840.948462656933958
1000.04504002548627710.09008005097255420.954959974513723
1010.04019333476138390.08038666952276780.959806665238616
1020.04954302515456560.09908605030913120.950456974845434
1030.04175105409943710.08350210819887420.958248945900563
1040.03767794126377230.07535588252754460.962322058736228
1050.04375318753796460.08750637507592910.956246812462035
1060.03902767731246640.07805535462493280.960972322687534
1070.03189153816964230.06378307633928470.968108461830358
1080.03063618225653030.06127236451306050.96936381774347
1090.02483561384987170.04967122769974350.975164386150128
1100.02075704203742060.04151408407484120.97924295796258
1110.01654005260934740.03308010521869490.983459947390653
1120.01785300851596470.03570601703192950.982146991484035
1130.01540713116155330.03081426232310660.984592868838447
1140.01973449854453170.03946899708906340.980265501455468
1150.01938094486179520.03876188972359040.980619055138205
1160.01865495893065620.03730991786131250.981345041069344
1170.01588505798601820.03177011597203630.984114942013982
1180.01558098104467770.03116196208935530.984419018955322
1190.01262208366050960.02524416732101920.98737791633949
1200.01121436852773250.02242873705546510.988785631472268
1210.009116782121600060.01823356424320010.9908832178784
1220.0126954953881350.025390990776270.987304504611865
1230.01038502072513720.02077004145027450.989614979274863
1240.008511951402339520.01702390280467900.99148804859766
1250.006809266869608970.01361853373921790.993190733130391
1260.005375740132009750.01075148026401950.99462425986799
1270.005069354891624550.01013870978324910.994930645108375
1280.004382793997600940.008765587995201890.995617206002399
1290.005649477260932630.01129895452186530.994350522739067
1300.006370792907184850.01274158581436970.993629207092815
1310.01220219968130140.02440439936260290.987797800318699
1320.01520814924769190.03041629849538380.984791850752308
1330.01587898414240190.03175796828480380.984121015857598
1340.01454066049727280.02908132099454560.985459339502727
1350.01152468664523120.02304937329046250.988475313354769
1360.01001366389900430.02002732779800870.989986336100996
1370.008227318984922720.01645463796984540.991772681015077
1380.01034934905626610.02069869811253210.989650650943734
1390.008801965152379050.01760393030475810.99119803484762
1400.01065418904762650.0213083780952530.989345810952374
1410.0171713962016540.0343427924033080.982828603798346
1420.0163468206869370.0326936413738740.983653179313063
1430.01356194522034430.02712389044068870.986438054779656
1440.01408002366543960.02816004733087910.98591997633456
1450.02291605058457230.04583210116914460.977083949415428
1460.02863857435558290.05727714871116590.971361425644417
1470.02997615636088530.05995231272177060.970023843639115
1480.02658661376562510.05317322753125030.973413386234375
1490.02159213586035250.0431842717207050.978407864139648
1500.02961818443544540.05923636887089080.970381815564555
1510.02492185111007820.04984370222015640.975078148889922
1520.02680161829166030.05360323658332060.97319838170834
1530.05462812593373470.1092562518674690.945371874066265
1540.05167636713317430.1033527342663490.948323632866826
1550.05943574763590560.1188714952718110.940564252364094
1560.0504050199016430.1008100398032860.949594980098357
1570.04461703683710920.08923407367421840.95538296316289
1580.03873117628170140.07746235256340280.961268823718299
1590.03788652521820450.0757730504364090.962113474781795
1600.03165398388197820.06330796776395630.968346016118022
1610.02580907659199100.05161815318398210.974190923408009
1620.02078059875145690.04156119750291380.979219401248543
1630.01728223957024990.03456447914049980.98271776042975
1640.01473602000337340.02947204000674690.985263979996627
1650.01244061148863620.02488122297727240.987559388511364
1660.01349200736510750.02698401473021500.986507992634893
1670.01074790676468550.02149581352937100.989252093235314
1680.01566394871566700.03132789743133410.984336051284333
1690.0153571699182490.0307143398364980.984642830081751
1700.01467101044083660.02934202088167310.985328989559163
1710.01342580969214390.02685161938428770.986574190307856
1720.01078860389621030.02157720779242070.98921139610379
1730.01033570025021920.02067140050043840.98966429974978
1740.01157651140434480.02315302280868960.988423488595655
1750.01402870295049750.02805740590099510.985971297049502
1760.01134205182168960.02268410364337920.98865794817831
1770.008814623604540050.01762924720908010.99118537639546
1780.00731173299058070.01462346598116140.99268826700942
1790.005692231167673290.01138446233534660.994307768832327
1800.00482866455373710.00965732910747420.995171335446263
1810.004003999065621010.008007998131242020.99599600093438
1820.003022345831752460.006044691663504910.996977654168248
1830.003405047614760520.006810095229521040.99659495238524
1840.002556436883933270.005112873767866540.997443563116067
1850.07245747224464380.1449149444892880.927542527755356
1860.0654080203115880.1308160406231760.934591979688412
1870.07562701898484830.1512540379696970.924372981015152
1880.0628367424399570.1256734848799140.937163257560043
1890.05554130822890880.1110826164578180.944458691771091
1900.04675181829933910.09350363659867830.95324818170066
1910.04005892017442970.08011784034885940.95994107982557
1920.03314862335281230.06629724670562470.966851376647188
1930.03366726822108640.06733453644217280.966332731778914
1940.03216375306092830.06432750612185660.967836246939072
1950.02761922547764790.05523845095529580.972380774522352
1960.02171201857721110.04342403715442220.978287981422789
1970.02916679711845130.05833359423690250.970833202881549
1980.02372836617301670.04745673234603350.976271633826983
1990.02121618960772980.04243237921545970.97878381039227
2000.01795966546282950.03591933092565890.98204033453717
2010.01638919684649660.03277839369299310.983610803153503
2020.01357534583868630.02715069167737260.986424654161314
2030.01500026759805040.03000053519610070.98499973240195
2040.01984674344131630.03969348688263250.980153256558684
2050.02096859095247390.04193718190494790.979031409047526
2060.01617388213145570.03234776426291150.983826117868544
2070.01431230540898230.02862461081796470.985687694591018
2080.01130453386399030.02260906772798070.98869546613601
2090.01309188152387800.02618376304775600.986908118476122
2100.01071293175945570.02142586351891140.989287068240544
2110.01309101702181740.02618203404363490.986908982978183
2120.02308789984641130.04617579969282270.976912100153589
2130.01778461084100960.03556922168201920.98221538915899
2140.02226457370744890.04452914741489780.977735426292551
2150.01873149191322610.03746298382645230.981268508086774
2160.01426379609671830.02852759219343650.985736203903282
2170.01596069154060030.03192138308120060.9840393084594
2180.01329666828356290.02659333656712590.986703331716437
2190.01226965916253910.02453931832507820.98773034083746
2200.009004208928150340.01800841785630070.99099579107185
2210.007304318884684750.01460863776936950.992695681115315
2220.005193191901060940.01038638380212190.99480680809894
2230.003925993928176160.007851987856352320.996074006071824
2240.002931169826585560.005862339653171110.997068830173414
2250.001996579463873350.00399315892774670.998003420536127
2260.004162431243562730.008324862487125450.995837568756437
2270.003236731904821690.006473463809643380.996763268095178
2280.002297808837789650.004595617675579290.99770219116221
2290.001576222135455670.003152444270911350.998423777864544
2300.001077293940849130.002154587881698260.99892270605915
2310.001164089994363040.002328179988726080.998835910005637
2320.004142608361277800.008285216722555610.995857391638722
2330.01680643790976090.03361287581952180.98319356209024
2340.02626001313866740.05252002627733480.973739986861333
2350.01849741501433500.03699483002866990.981502584985665
2360.01455609506978610.02911219013957210.985443904930214
2370.1577479892498280.3154959784996570.842252010750172
2380.1212096039362030.2424192078724050.878790396063797
2390.09862671298740160.1972534259748030.901373287012598
2400.07464536724944630.1492907344988930.925354632750554
2410.06425555395170690.1285111079034140.935744446048293
2420.1012610679507750.202522135901550.898738932049225
2430.08106380816007560.1621276163201510.918936191839924
2440.07919179485587910.1583835897117580.92080820514412
2450.06552186515272680.1310437303054540.934478134847273
2460.05366711595153520.1073342319030700.946332884048465
2470.03244867939591730.06489735879183470.967551320604083
2480.02623108749021210.05246217498042410.973768912509788
2490.01740480564527200.03480961129054410.982595194354728
2500.044724685955690.089449371911380.95527531404431
2510.02996643274143760.05993286548287530.970033567258562






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level160.0669456066945607NOK
5% type I error level1020.426778242677824NOK
10% type I error level1330.556485355648536NOK

\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 & 16 & 0.0669456066945607 & NOK \tabularnewline
5% type I error level & 102 & 0.426778242677824 & NOK \tabularnewline
10% type I error level & 133 & 0.556485355648536 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96551&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]16[/C][C]0.0669456066945607[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]102[/C][C]0.426778242677824[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]133[/C][C]0.556485355648536[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96551&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96551&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level160.0669456066945607NOK
5% type I error level1020.426778242677824NOK
10% type I error level1330.556485355648536NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 5 ; 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')
}