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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 computationSun, 18 Nov 2012 12:35:21 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/18/t1353260468m0l79rv99fccvt0.htm/, Retrieved Mon, 29 Apr 2024 18:16:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=190281, Retrieved Mon, 29 Apr 2024 18:16:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact105

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Decreasing Compet...] [2010-11-17 09:04:39] [b98453cac15ba1066b407e146608df68]
- R     [Multiple Regression] [ws 7 berekening 2] [2012-11-18 17:27:26] [4d16aec667f4ecb2462f7b90319797ea]
-           [Multiple Regression] [ws 7 berekening 3] [2012-11-18 17:35:21] [5948b95c00a54abd73f88aac58cf0e09] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9	41	38	13	12	14	12	53	32
9	39	32	16	11	18	11	83	51
9	30	35	19	15	11	14	66	42
9	31	33	15	6	12	12	67	41
9	34	37	14	13	16	21	76	46
9	35	29	13	10	18	12	78	47
9	39	31	19	12	14	22	53	37
9	34	36	15	14	14	11	80	49
9	36	35	14	12	15	10	74	45
9	37	38	15	9	15	13	76	47
9	38	31	16	10	17	10	79	49
9	36	34	16	12	19	8	54	33
9	38	35	16	12	10	15	67	42
9	39	38	16	11	16	14	54	33
9	33	37	17	15	18	10	87	53
9	32	33	15	12	14	14	58	36
9	36	32	15	10	14	14	75	45
9	38	38	20	12	17	11	88	54
9	39	38	18	11	14	10	64	41
9	32	32	16	12	16	13	57	36
9	32	33	16	11	18	9.5	66	41
9	31	31	16	12	11	14	68	44
9	39	38	19	13	14	12	54	33
9	37	39	16	11	12	14	56	37
9	39	32	17	12	17	11	86	52
9	41	32	17	13	9	9	80	47
9	36	35	16	10	16	11	76	43
9	33	37	15	14	14	15	69	44
9	33	33	16	12	15	14	78	45
9	34	33	14	10	11	13	67	44
9	31	31	15	12	16	9	80	49
9	27	32	12	8	13	15	54	33
9	37	31	14	10	17	10	71	43
9	34	37	16	12	15	11	84	54
9	34	30	14	12	14	13	74	42
9	32	33	10	7	16	8	71	44
9	29	31	10	9	9	20	63	37
9	36	33	14	12	15	12	71	43
9	29	31	16	10	17	10	76	46
9	35	33	16	10	13	10	69	42
9	37	32	16	10	15	9	74	45
9	34	33	14	12	16	14	75	44
9	38	32	20	15	16	8	54	33
9	35	33	14	10	12	14	52	31
9	38	28	14	10	15	11	69	42
9	37	35	11	12	11	13	68	40
9	38	39	14	13	15	9	65	43
9	33	34	15	11	15	11	75	46
9	36	38	16	11	17	15	74	42
9	38	32	14	12	13	11	75	45
9	32	38	16	14	16	10	72	44
9	32	30	14	10	14	14	67	40
9	32	33	12	12	11	18	63	37
9	34	38	16	13	12	14	62	46
9	32	32	9	5	12	11	63	36
9	37	35	14	6	15	14.5	76	47
9	39	34	16	12	16	13	74	45
9	29	34	16	12	15	9	67	42
9	37	36	15	11	12	10	73	43
9	35	34	16	10	12	15	70	43
9	30	28	12	7	8	20	53	32
9	38	34	16	12	13	12	77	45
9	34	35	16	14	11	12	80	48
9	31	35	14	11	14	14	52	31
9	34	31	16	12	15	13	54	33
10	35	37	17	13	10	11	80	49
10	36	35	18	14	11	17	66	42
10	30	27	18	11	12	12	73	41
10	39	40	12	12	15	13	63	38
10	35	37	16	12	15	14	69	42
10	38	36	10	8	14	13	67	44
10	31	38	14	11	16	15	54	33
10	34	39	18	14	15	13	81	48
10	38	41	18	14	15	10	69	40
10	34	27	16	12	13	11	84	50
10	39	30	17	9	12	19	80	49
10	37	37	16	13	17	13	70	43
10	34	31	16	11	13	17	69	44
10	28	31	13	12	15	13	77	47
10	37	27	16	12	13	9	54	33
10	33	36	16	12	15	11	79	46
10	35	37	16	12	15	9	71	45
10	37	33	15	12	16	12	73	43
10	32	34	15	11	15	12	72	44
10	33	31	16	10	14	13	77	47
10	38	39	14	9	15	13	75	45
10	33	34	16	12	14	12	69	42
10	29	32	16	12	13	15	54	33
10	33	33	15	12	7	22	70	43
10	31	36	12	9	17	13	73	46
10	36	32	17	15	13	15	54	33
10	35	41	16	12	15	13	77	46
10	32	28	15	12	14	15	82	48
10	29	30	13	12	13	12.5	80	47
10	39	36	16	10	16	11	80	47
10	37	35	16	13	12	16	69	43
10	35	31	16	9	14	11	78	46
10	37	34	16	12	17	11	81	48
10	32	36	14	10	15	10	76	46
10	38	36	16	14	17	10	76	45
10	37	35	16	11	12	16	73	45
10	36	37	20	15	16	12	85	52
10	32	28	15	11	11	11	66	42
10	33	39	16	11	15	16	79	47
10	40	32	13	12	9	19	68	41
10	38	35	17	12	16	11	76	47
10	41	39	16	12	15	16	71	43
10	36	35	16	11	10	15	54	33
10	43	42	12	7	10	24	46	30
10	30	34	16	12	15	14	85	52
10	31	33	16	14	11	15	74	44
10	32	41	17	11	13	11	88	55
10	32	33	13	11	14	15	38	11
10	37	34	12	10	18	12	76	47
10	37	32	18	13	16	10	86	53
10	33	40	14	13	14	14	54	33
10	34	40	14	8	14	13	67	44
10	33	35	13	11	14	9	69	42
10	38	36	16	12	14	15	90	55
10	33	37	13	11	12	15	54	33
10	31	27	16	13	14	14	76	46
10	38	39	13	12	15	11	89	54
10	37	38	16	14	15	8	76	47
10	36	31	15	13	15	11	73	45
10	31	33	16	15	13	11	79	47
10	39	32	15	10	17	8	90	55
10	44	39	17	11	17	10	74	44
10	33	36	15	9	19	11	81	53
10	35	33	12	11	15	13	72	44
10	32	33	16	10	13	11	71	42
10	28	32	10	11	9	20	66	40
10	40	37	16	8	15	10	77	46
10	27	30	12	11	15	15	65	40
10	37	38	14	12	15	12	74	46
10	32	29	15	12	16	14	85	53
10	28	22	13	9	11	23	54	33
10	34	35	15	11	14	14	63	42
10	30	35	11	10	11	16	54	35
10	35	34	12	8	15	11	64	40
10	31	35	11	9	13	12	69	41
10	32	34	16	8	15	10	54	33
10	30	37	15	9	16	14	84	51
10	30	35	17	15	14	12	86	53
10	31	23	16	11	15	12	77	46
10	40	31	10	8	16	11	89	55
10	32	27	18	13	16	12	76	47
10	36	36	13	12	11	13	60	38
10	32	31	16	12	12	11	75	46
10	35	32	13	9	9	19	73	46
10	38	39	10	7	16	12	85	53
10	42	37	15	13	13	17	79	47
10	34	38	16	9	16	9	71	41
10	35	39	16	6	12	12	72	44
9	38	34	14	8	9	19	69	43
10	33	31	10	8	13	18	78	51
10	36	32	17	15	13	15	54	33
10	32	37	13	6	14	14	69	43
10	33	36	15	9	19	11	81	53
10	34	32	16	11	13	9	84	51
10	32	38	12	8	12	18	84	50
10	34	36	13	8	13	16	69	46
11	27	26	13	10	10	24	66	43
11	31	26	12	8	14	14	81	47
11	38	33	17	14	16	20	82	50
11	34	39	15	10	10	18	72	43
11	24	30	10	8	11	23	54	33
11	30	33	14	11	14	12	78	48
11	26	25	11	12	12	14	74	44
11	34	38	13	12	9	16	82	50
11	27	37	16	12	9	18	73	41
11	37	31	12	5	11	20	55	34
11	36	37	16	12	16	12	72	44
11	41	35	12	10	9	12	78	47
11	29	25	9	7	13	17	59	35
11	36	28	12	12	16	13	72	44
11	32	35	15	11	13	9	78	44
11	37	33	12	8	9	16	68	43
11	30	30	12	9	12	18	69	41
11	31	31	14	10	16	10	67	41
11	38	37	12	9	11	14	74	42
11	36	36	16	12	14	11	54	33
11	35	30	11	6	13	9	67	41
11	31	36	19	15	15	11	70	44
11	38	32	15	12	14	10	80	48
11	22	28	8	12	16	11	89	55
11	32	36	16	12	13	19	76	44
11	36	34	17	11	14	14	74	43
11	39	31	12	7	15	12	87	52
11	28	28	11	7	13	14	54	30
11	32	36	11	5	11	21	61	39
11	32	36	14	12	11	13	38	11
11	38	40	16	12	14	10	75	44
11	32	33	12	3	15	15	69	42
11	35	37	16	11	11	16	62	41
11	32	32	13	10	15	14	72	44
11	37	38	15	12	12	12	70	44
11	34	31	16	9	14	19	79	48
11	33	37	16	12	14	15	87	53
11	33	33	14	9	8	19	62	37
11	26	32	16	12	13	13	77	44
11	30	30	16	12	9	17	69	44
11	24	30	14	10	15	12	69	40
11	34	31	11	9	17	11	75	42
11	34	32	12	12	13	14	54	35
11	33	34	15	8	15	11	72	43
11	34	36	15	11	15	13	74	45
11	35	37	16	11	14	12	85	55
11	35	36	16	12	16	15	52	31
11	36	33	11	10	13	14	70	44
11	34	33	15	10	16	12	84	50
11	34	33	12	12	9	17	64	40
11	41	44	12	12	16	11	84	53
11	32	39	15	11	11	18	87	54
11	30	32	15	8	10	13	79	49
11	35	35	16	12	11	17	67	40
11	28	25	14	10	15	13	65	41
11	33	35	17	11	17	11	85	52
11	39	34	14	10	14	12	83	52
11	36	35	13	8	8	22	61	36
11	36	39	15	12	15	14	82	52
11	35	33	13	12	11	12	76	46
11	38	36	14	10	16	12	58	31
11	33	32	15	12	10	17	72	44
11	31	32	12	9	15	9	72	44
11	34	36	13	9	9	21	38	11
11	32	36	8	6	16	10	78	46
11	31	32	14	10	19	11	54	33
11	33	34	14	9	12	12	63	34
11	34	33	11	9	8	23	66	42
11	34	35	12	9	11	13	70	43
11	34	30	13	6	14	12	71	43
11	33	38	10	10	9	16	67	44
11	32	34	16	6	15	9	58	36
11	41	33	18	14	13	17	72	46
11	34	32	13	10	16	9	72	44
11	36	31	11	10	11	14	70	43
11	37	30	4	6	12	17	76	50
11	36	27	13	12	13	13	50	33
11	29	31	16	12	10	11	72	43
11	37	30	10	7	11	12	72	44
11	27	32	12	8	12	10	88	53
11	35	35	12	11	8	19	53	34
11	28	28	10	3	12	16	58	35
11	35	33	13	6	12	16	66	40
11	37	31	15	10	15	14	82	53
11	29	35	12	8	11	20	69	42
11	32	35	14	9	13	15	68	43
11	36	32	10	9	14	23	44	29
11	19	21	12	8	10	20	56	36
11	21	20	12	9	12	16	53	30
11	31	34	11	7	15	14	70	42
11	33	32	10	7	13	17	78	47
11	36	34	12	6	13	11	71	44
11	33	32	16	9	13	13	72	45
11	37	33	12	10	12	17	68	44
11	34	33	14	11	12	15	67	43
11	35	37	16	12	9	21	75	43
11	31	32	14	8	9	18	62	40
11	37	34	13	11	15	15	67	41
11	35	30	4	3	10	8	83	52
11	27	30	15	11	14	12	64	38
11	34	38	11	12	15	12	68	41
11	40	36	11	7	7	22	62	39
11	29	32	14	9	14	12	72	43

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 15 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190281&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]15 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190281&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190281&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 time15 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Software[t] = -3.58404048669344 + 0.76953516038212month[t] -0.0179428824621839Connected[t] + 0.0369197456089638Separate[t] + 0.519756244301807Learning[t] -0.0332102096938587Happiness[t] -0.0115326014852726Depression[t] + 0.00810469831161155Belonging[t] -0.003066058865331Belonging_Final[t] -0.011814834728254t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Software[t] =  -3.58404048669344 +  0.76953516038212month[t] -0.0179428824621839Connected[t] +  0.0369197456089638Separate[t] +  0.519756244301807Learning[t] -0.0332102096938587Happiness[t] -0.0115326014852726Depression[t] +  0.00810469831161155Belonging[t] -0.003066058865331Belonging_Final[t] -0.011814834728254t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190281&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Software[t] =  -3.58404048669344 +  0.76953516038212month[t] -0.0179428824621839Connected[t] +  0.0369197456089638Separate[t] +  0.519756244301807Learning[t] -0.0332102096938587Happiness[t] -0.0115326014852726Depression[t] +  0.00810469831161155Belonging[t] -0.003066058865331Belonging_Final[t] -0.011814834728254t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190281&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190281&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Software[t] = -3.58404048669344 + 0.76953516038212month[t] -0.0179428824621839Connected[t] + 0.0369197456089638Separate[t] + 0.519756244301807Learning[t] -0.0332102096938587Happiness[t] -0.0115326014852726Depression[t] + 0.00810469831161155Belonging[t] -0.003066058865331Belonging_Final[t] -0.011814834728254t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-3.584040486693443.772925-0.94990.3430470.171524
month0.769535160382120.3931031.95760.0513730.025686
Connected-0.01794288246218390.033633-0.53350.5941610.29708
Separate0.03691974560896380.0341131.08230.280160.14008
Learning0.5197562443018070.0512910.133700
Happiness-0.03321020969385870.056401-0.58880.5565060.278253
Depression-0.01153260148527260.041162-0.28020.7795730.389787
Belonging0.008104698311611550.0368080.22020.8259010.41295
Belonging_Final-0.0030660588653310.054668-0.05610.9553180.477659
t-0.0118148347282540.00415-2.84720.0047710.002386

\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) & -3.58404048669344 & 3.772925 & -0.9499 & 0.343047 & 0.171524 \tabularnewline
month & 0.76953516038212 & 0.393103 & 1.9576 & 0.051373 & 0.025686 \tabularnewline
Connected & -0.0179428824621839 & 0.033633 & -0.5335 & 0.594161 & 0.29708 \tabularnewline
Separate & 0.0369197456089638 & 0.034113 & 1.0823 & 0.28016 & 0.14008 \tabularnewline
Learning & 0.519756244301807 & 0.05129 & 10.1337 & 0 & 0 \tabularnewline
Happiness & -0.0332102096938587 & 0.056401 & -0.5888 & 0.556506 & 0.278253 \tabularnewline
Depression & -0.0115326014852726 & 0.041162 & -0.2802 & 0.779573 & 0.389787 \tabularnewline
Belonging & 0.00810469831161155 & 0.036808 & 0.2202 & 0.825901 & 0.41295 \tabularnewline
Belonging_Final & -0.003066058865331 & 0.054668 & -0.0561 & 0.955318 & 0.477659 \tabularnewline
t & -0.011814834728254 & 0.00415 & -2.8472 & 0.004771 & 0.002386 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190281&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]-3.58404048669344[/C][C]3.772925[/C][C]-0.9499[/C][C]0.343047[/C][C]0.171524[/C][/ROW]
[ROW][C]month[/C][C]0.76953516038212[/C][C]0.393103[/C][C]1.9576[/C][C]0.051373[/C][C]0.025686[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0179428824621839[/C][C]0.033633[/C][C]-0.5335[/C][C]0.594161[/C][C]0.29708[/C][/ROW]
[ROW][C]Separate[/C][C]0.0369197456089638[/C][C]0.034113[/C][C]1.0823[/C][C]0.28016[/C][C]0.14008[/C][/ROW]
[ROW][C]Learning[/C][C]0.519756244301807[/C][C]0.05129[/C][C]10.1337[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.0332102096938587[/C][C]0.056401[/C][C]-0.5888[/C][C]0.556506[/C][C]0.278253[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0115326014852726[/C][C]0.041162[/C][C]-0.2802[/C][C]0.779573[/C][C]0.389787[/C][/ROW]
[ROW][C]Belonging[/C][C]0.00810469831161155[/C][C]0.036808[/C][C]0.2202[/C][C]0.825901[/C][C]0.41295[/C][/ROW]
[ROW][C]Belonging_Final[/C][C]-0.003066058865331[/C][C]0.054668[/C][C]-0.0561[/C][C]0.955318[/C][C]0.477659[/C][/ROW]
[ROW][C]t[/C][C]-0.011814834728254[/C][C]0.00415[/C][C]-2.8472[/C][C]0.004771[/C][C]0.002386[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190281&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190281&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)-3.584040486693443.772925-0.94990.3430470.171524
month0.769535160382120.3931031.95760.0513730.025686
Connected-0.01794288246218390.033633-0.53350.5941610.29708
Separate0.03691974560896380.0341131.08230.280160.14008
Learning0.5197562443018070.0512910.133700
Happiness-0.03321020969385870.056401-0.58880.5565060.278253
Depression-0.01153260148527260.041162-0.28020.7795730.389787
Belonging0.008104698311611550.0368080.22020.8259010.41295
Belonging_Final-0.0030660588653310.054668-0.05610.9553180.477659
t-0.0118148347282540.00415-2.84720.0047710.002386






Multiple Linear Regression - Regression Statistics
Multiple R0.646084274787135
R-squared0.417424890127218
Adjusted R-squared0.396782464974246
F-TEST (value)20.2216981306146
F-TEST (DF numerator)9
F-TEST (DF denominator)254
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.80190809101452
Sum Squared Residuals824.705683189756

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.646084274787135 \tabularnewline
R-squared & 0.417424890127218 \tabularnewline
Adjusted R-squared & 0.396782464974246 \tabularnewline
F-TEST (value) & 20.2216981306146 \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 & 1.80190809101452 \tabularnewline
Sum Squared Residuals & 824.705683189756 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190281&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.646084274787135[/C][/ROW]
[ROW][C]R-squared[/C][C]0.417424890127218[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.396782464974246[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]20.2216981306146[/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]1.80190809101452[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]824.705683189756[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190281&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190281&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 R0.646084274787135
R-squared0.417424890127218
Adjusted R-squared0.396782464974246
F-TEST (value)20.2216981306146
F-TEST (DF numerator)9
F-TEST (DF denominator)254
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.80190809101452
Sum Squared Residuals824.705683189756






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11210.48218542341951.51781457658049
21111.9075842064841-0.907584206484133
31513.81497160553961.18502839446038
4611.6333751703777-5.63337517037766
51311.01663216473191.98336783526813
61010.2222765701055-0.222276570105538
71213.176625117343-1.17662511734304
81411.66899121013082.33100878986916
91211.00657305795050.993426942049482
10911.5828102963255-2.58281029632552
111011.8007299664464-1.80072996644642
121211.73864440110730.261355598892743
131212.0237937721744-0.0237937721743902
141111.83930008687-0.839300086869993
151512.60382289913762.39617710086238
161211.32655665834030.673443341659683
171011.3162358896638-1.31623588966378
181214.1015687088112-2.10156870881119
191112.9888077393546-1.98880773935461
201211.69914130190610.300858698093912
211111.7558018890754-0.755801889075384
221211.87567642679190.1243235732081
231313.3817209295794-0.38172092957939
241111.9307432500581-0.930743250058119
251212.2100574977995-0.210057497799463
261312.41780588312520.582194116874759
271011.8110172246203-1.81101722462031
281411.36760535059472.63239464940525
291211.7760663954630.223933604536968
301010.7650840073673-0.765084007367292
311211.22312471430560.776875285694439
3289.62950222804292-1.62950222804292
331010.4727927629825-0.472792762982493
341211.90235978633290.0976402136670583
351210.55848497372951.4415150262705
3678.57508653891843-1.57508653891843
3798.593965935956960.406034064043041
381210.54885617943851.45114382056149
391011.6162846178761-1.61628461787612
401011.6590241656482-1.65902416564817
411011.5508413174462-1.5508413174462
421210.51055992716661.48944007283343
431513.44131487467791.55868512532211
441010.4552789181056-0.455278918105551
451010.2440571070989-0.244057107098923
46129.057157696414122.94284230358588
471310.61412499019982.38587500980021
481111.075965687589-0.0759656875890157
491111.5693661440328-0.569366144032777
501210.43851234855491.5614876514451
511411.68603970719132.31396029280866
521010.3313851763377-0.331385176337656
53129.421096696322712.57890330367729
541311.61424077006981.38575922993022
5557.8518626079202-2.8518626079202
56610.3915135154692-4.39151351546923
571211.32041707245270.679582927547251
581211.5198369663960.480163033604005
591111.052222477487-0.0522224774870326
601011.4402330584058-1.44023305840583
6179.1887137926978-2.1887137926978
621211.41476310677530.585236893224654
631411.59317588523142.40682411476865
641110.29817282521940.701827174780583
651211.11276251995630.887237480043656
661312.94459614680010.0554038531999405
671413.16634599978280.833654000217238
681113.051082239735-2.05108223973502
691210.05618865286581.94381134713417
701212.1092424412897-0.109242441289716
7188.91054304458035-0.910543044580353
721111.016072802622-0.0160728026219689
731413.29548542742130.704514572578696
741413.24760844970140.752391550298631
751211.89697392161610.103026078383948
76912.3375568191361-3.33755681913614
771311.94080365481141.05919634518859
781111.8368386694733-0.836838669473322
791210.4087617930631.59123820693698
801211.61611835492110.383881645078944
811212.0816258307049-0.0816258307049354
821212.0321386520043-0.0321386520042612
831211.27153632581820.728463674181814
841111.4083951015267-0.408395101526732
851011.8406373149819-1.84063731498186
86910.9516660556244-1.95166605562436
871211.88979219167130.110207808328722
881211.78054585592570.219454144074321
891211.43167062475460.568329375245435
9099.79403929363986-0.794039293639859
911512.13925741880742.86074258119256
921212.0611010122208-0.0611010122208251
931211.14793826821150.852061731788505
941210.27317745913331.72682254086674
951011.7803892794887-1.7803892794887
961311.76583084945851.23416915054148
97911.6972094934659-2.69720949346593
981211.67881947876280.321180521237202
991010.8346077060054-0.834607706005373
1001411.69129370458522.30870629541476
1011111.733043351333-0.733043351333031
1021513.88111940233981.11888059766021
1031111.0642721361578-0.0642721361578231
1041111.8599148024903-0.859914802490292
105129.998700963830182.00129903616982
1061212.1187866853865-0.118786685386485
1071211.62835388757650.37164611242351
1081111.6290388500338-0.629038850033779
10979.51160425686141-2.51160425686141
1101211.71461881197610.28538118802394
1111411.70462637596172.29537362403826
1121112.5494319833421-1.54943198334211
113119.813565265393961.18643473460604
114109.328556902031650.67144309796835
1151312.51357629417870.4864237058213
1161310.61212682174532.38787317825466
117810.6655361365725-2.66553613657249
1181110.03578113225480.964218867745233
1191211.59158465411290.408415345887119
120119.989239819606071.01076018039393
1211311.28693880632171.71306119367832
1221210.11551221065051.88448778934946
1231411.59468838414312.40531161585689
1241310.76984218665252.2301578133475
1251511.55025399128163.44974600871838
1261010.8046002831306-0.80460028313059
1271111.8820080155201-0.882008015520087
128910.8684784999657-1.86847849996566
129119.21517781136911.78482218863091
1301011.4237296430119-1.42372964301193
131118.32288517829322.6771148217068
132811.3857120327997-3.38571203279971
133119.133168439636161.86683156036384
1341210.36593896982971.63406103017028
1351210.64273093793951.35726906206047
13699.27707008994215-0.27707008994215
1371110.72657768126330.273422318736661
138108.732594952540441.26740504745956
13989.1044410616345-1.1044410616345
14098.773906508657310.226093491342694
141811.1656130471982-3.16561304719824
142910.8892982440569-1.88929824405688
1431511.94271930796513.05728069203487
1441110.86547831672430.134521683275723
14587.916982280640010.0830177193599868
1461311.96671626897431.03328373102575
147129.669064197155122.33093580284488
1481211.19058789416440.809412105835587
14999.59375584532932-0.593755845329324
15078.15133255979377-1.15133255979376
1511310.60442371048542.39557628951459
152911.2390168748651-2.2390168748651
153611.3433284593189-5.34332845931886
15489.28169298278866-1.28169298278866
15587.866449083311020.133550916688975
1561511.37129316147093.62870683852907
15769.60605588524128-3.60605588524128
158910.514033458118-1.51403345811804
1591111.1091256765928-0.109125676592751
16089.20817295842716-1.20817295842716
16189.48693786592225-1.48693786592225
162109.993314811582320.00668518841767825
16389.48176361799367-1.48176361799367
1641412.06485854021821.93514145978183
1651011.4695631104637-1.46956311046372
16688.50002097029168-0.500020970291678
1671110.74608291857960.253917081420426
168128.974613574554983.02538642544503
1691210.46173152106131.53826847893867
1701212.0294528928777-0.0294528928777491
17159.32375800275669-4.32375800275669
1721211.66375854740860.336241452591394
173109.681266313074970.318733686925034
17477.64859947115942-0.648599471159415
175129.205478754050672.79452124594933
1761111.2775316262317-0.277531626231655
17789.51702585919688-1.51702585919688
17899.41159294886717-0.41159294886717
1791010.4014780423728-0.401478042372832
18099.61965648730361-0.619656487303614
1811211.4863003880280.51369961197202
18268.8092367603918-2.8092367603918
1831513.17439217956111.8256078204389
1841210.92379876678841.0762012332116
185127.386624210780784.61337578921922
1861211.58452385738390.415476142616064
1871111.9581637058654-0.958163705865438
18879.25060130695437-2.25060130695437
18978.64899616535271-1.64899616535271
19058.87559833303154-3.87559833303154
1911210.41475463015311.58524536984691
1921211.61613504203910.383864957960852
19339.2411450163548-6.2411450163548
1941111.4698469018573-0.469846901857283
195109.730066424280580.269933575719425
1961210.99605457492771.0039454250723
197911.2129158321836-2.21291583218361
1981211.53620005167860.463799948321352
199910.336764082188-1.33676408218799
2001211.45639479074890.543605209251125
2011211.32084178129540.679158218704589
2021010.2478377374612-0.247837737461182
20398.521853345051190.478146654948805
204129.016221282066812.9837787179332
205810.7449910376785-2.74499103767854
2061110.7760848876280.223915112371953
2071111.4062370643019-0.406237064301928
2081211.06261462860590.937385371394063
209108.540505488006131.45949451199387
2101010.662105392469-0.662105392469014
211129.134396907687072.86560309231293
212129.362058439459682.63794156054032
2131110.99297042589360.00702957410642848
214810.7999690617809-2.79996906178092
2151211.17995283028410.820047169715862
216109.779042339775020.220957660224979
2171111.6909913840273-0.690991384027324
2181010.0472194069847-0.0472194069846633
21989.56108554325039-1.56108554325039
2201210.71739324628531.28260675371468
221129.588164536830152.41183546316985
222109.88709180074570.112908199254296
2231210.55227390204441.44772609795563
22498.943285862747950.0567141372520499
22599.43156784767182-0.431567847671817
22666.96812057701776-0.968120577017763
227109.679289883330450.320710116669546
22899.99624386720667-0.996243867206671
22998.376065517951470.623934482048527
23099.00289453889522-0.00289453889521819
23169.24624389113926-3.24624389113926
232108.072896961255911.92710303874409
233610.8829366307167-4.88293663071672
2341411.76919339203822.23080660796175
235109.246040067958550.753959932041448
236108.217151937378391.78284806262161
23764.471538528129021.52846147187098
238128.899034578608283.10096542139172
2391210.99010624271081.00989375728915
24077.63148226682086-0.631482266820859
24189.00438387301048-1.00438387301048
242118.763423318354512.23657668164549
24337.51847235136829-4.51847235136829
24469.17443209252123-3.17443209252123
2451010.1056554718797-0.105655471879743
24688.81780474571089-0.817804745710885
24799.7717455830614-0.771745583061396
24897.221316047510211.7786839524898
24988.39115811245736-0.391158112457362
25098.28033001200630.719669987993699
25178.11062828568229-1.11062828568229
25277.55066185760807-0.55066185760807
25368.62003125264115-2.62003125264115
254910.6492039877645-1.64920398776448
255108.481239460960891.51876053903911
256119.580792325747061.41920767425294
2571210.83349868625891.16650131374108
25889.60777906773184-1.60777906773183
259118.915184164131992.08481583586801
26034.45649769750934-1.45649769750934
2611110.01550892127590.984491078724085
262128.084437303933453.91556269606655
26377.9989852737733-0.998985273773303
26499.54776919124914-0.547769191249143

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 10.4821854234195 & 1.51781457658049 \tabularnewline
2 & 11 & 11.9075842064841 & -0.907584206484133 \tabularnewline
3 & 15 & 13.8149716055396 & 1.18502839446038 \tabularnewline
4 & 6 & 11.6333751703777 & -5.63337517037766 \tabularnewline
5 & 13 & 11.0166321647319 & 1.98336783526813 \tabularnewline
6 & 10 & 10.2222765701055 & -0.222276570105538 \tabularnewline
7 & 12 & 13.176625117343 & -1.17662511734304 \tabularnewline
8 & 14 & 11.6689912101308 & 2.33100878986916 \tabularnewline
9 & 12 & 11.0065730579505 & 0.993426942049482 \tabularnewline
10 & 9 & 11.5828102963255 & -2.58281029632552 \tabularnewline
11 & 10 & 11.8007299664464 & -1.80072996644642 \tabularnewline
12 & 12 & 11.7386444011073 & 0.261355598892743 \tabularnewline
13 & 12 & 12.0237937721744 & -0.0237937721743902 \tabularnewline
14 & 11 & 11.83930008687 & -0.839300086869993 \tabularnewline
15 & 15 & 12.6038228991376 & 2.39617710086238 \tabularnewline
16 & 12 & 11.3265566583403 & 0.673443341659683 \tabularnewline
17 & 10 & 11.3162358896638 & -1.31623588966378 \tabularnewline
18 & 12 & 14.1015687088112 & -2.10156870881119 \tabularnewline
19 & 11 & 12.9888077393546 & -1.98880773935461 \tabularnewline
20 & 12 & 11.6991413019061 & 0.300858698093912 \tabularnewline
21 & 11 & 11.7558018890754 & -0.755801889075384 \tabularnewline
22 & 12 & 11.8756764267919 & 0.1243235732081 \tabularnewline
23 & 13 & 13.3817209295794 & -0.38172092957939 \tabularnewline
24 & 11 & 11.9307432500581 & -0.930743250058119 \tabularnewline
25 & 12 & 12.2100574977995 & -0.210057497799463 \tabularnewline
26 & 13 & 12.4178058831252 & 0.582194116874759 \tabularnewline
27 & 10 & 11.8110172246203 & -1.81101722462031 \tabularnewline
28 & 14 & 11.3676053505947 & 2.63239464940525 \tabularnewline
29 & 12 & 11.776066395463 & 0.223933604536968 \tabularnewline
30 & 10 & 10.7650840073673 & -0.765084007367292 \tabularnewline
31 & 12 & 11.2231247143056 & 0.776875285694439 \tabularnewline
32 & 8 & 9.62950222804292 & -1.62950222804292 \tabularnewline
33 & 10 & 10.4727927629825 & -0.472792762982493 \tabularnewline
34 & 12 & 11.9023597863329 & 0.0976402136670583 \tabularnewline
35 & 12 & 10.5584849737295 & 1.4415150262705 \tabularnewline
36 & 7 & 8.57508653891843 & -1.57508653891843 \tabularnewline
37 & 9 & 8.59396593595696 & 0.406034064043041 \tabularnewline
38 & 12 & 10.5488561794385 & 1.45114382056149 \tabularnewline
39 & 10 & 11.6162846178761 & -1.61628461787612 \tabularnewline
40 & 10 & 11.6590241656482 & -1.65902416564817 \tabularnewline
41 & 10 & 11.5508413174462 & -1.5508413174462 \tabularnewline
42 & 12 & 10.5105599271666 & 1.48944007283343 \tabularnewline
43 & 15 & 13.4413148746779 & 1.55868512532211 \tabularnewline
44 & 10 & 10.4552789181056 & -0.455278918105551 \tabularnewline
45 & 10 & 10.2440571070989 & -0.244057107098923 \tabularnewline
46 & 12 & 9.05715769641412 & 2.94284230358588 \tabularnewline
47 & 13 & 10.6141249901998 & 2.38587500980021 \tabularnewline
48 & 11 & 11.075965687589 & -0.0759656875890157 \tabularnewline
49 & 11 & 11.5693661440328 & -0.569366144032777 \tabularnewline
50 & 12 & 10.4385123485549 & 1.5614876514451 \tabularnewline
51 & 14 & 11.6860397071913 & 2.31396029280866 \tabularnewline
52 & 10 & 10.3313851763377 & -0.331385176337656 \tabularnewline
53 & 12 & 9.42109669632271 & 2.57890330367729 \tabularnewline
54 & 13 & 11.6142407700698 & 1.38575922993022 \tabularnewline
55 & 5 & 7.8518626079202 & -2.8518626079202 \tabularnewline
56 & 6 & 10.3915135154692 & -4.39151351546923 \tabularnewline
57 & 12 & 11.3204170724527 & 0.679582927547251 \tabularnewline
58 & 12 & 11.519836966396 & 0.480163033604005 \tabularnewline
59 & 11 & 11.052222477487 & -0.0522224774870326 \tabularnewline
60 & 10 & 11.4402330584058 & -1.44023305840583 \tabularnewline
61 & 7 & 9.1887137926978 & -2.1887137926978 \tabularnewline
62 & 12 & 11.4147631067753 & 0.585236893224654 \tabularnewline
63 & 14 & 11.5931758852314 & 2.40682411476865 \tabularnewline
64 & 11 & 10.2981728252194 & 0.701827174780583 \tabularnewline
65 & 12 & 11.1127625199563 & 0.887237480043656 \tabularnewline
66 & 13 & 12.9445961468001 & 0.0554038531999405 \tabularnewline
67 & 14 & 13.1663459997828 & 0.833654000217238 \tabularnewline
68 & 11 & 13.051082239735 & -2.05108223973502 \tabularnewline
69 & 12 & 10.0561886528658 & 1.94381134713417 \tabularnewline
70 & 12 & 12.1092424412897 & -0.109242441289716 \tabularnewline
71 & 8 & 8.91054304458035 & -0.910543044580353 \tabularnewline
72 & 11 & 11.016072802622 & -0.0160728026219689 \tabularnewline
73 & 14 & 13.2954854274213 & 0.704514572578696 \tabularnewline
74 & 14 & 13.2476084497014 & 0.752391550298631 \tabularnewline
75 & 12 & 11.8969739216161 & 0.103026078383948 \tabularnewline
76 & 9 & 12.3375568191361 & -3.33755681913614 \tabularnewline
77 & 13 & 11.9408036548114 & 1.05919634518859 \tabularnewline
78 & 11 & 11.8368386694733 & -0.836838669473322 \tabularnewline
79 & 12 & 10.408761793063 & 1.59123820693698 \tabularnewline
80 & 12 & 11.6161183549211 & 0.383881645078944 \tabularnewline
81 & 12 & 12.0816258307049 & -0.0816258307049354 \tabularnewline
82 & 12 & 12.0321386520043 & -0.0321386520042612 \tabularnewline
83 & 12 & 11.2715363258182 & 0.728463674181814 \tabularnewline
84 & 11 & 11.4083951015267 & -0.408395101526732 \tabularnewline
85 & 10 & 11.8406373149819 & -1.84063731498186 \tabularnewline
86 & 9 & 10.9516660556244 & -1.95166605562436 \tabularnewline
87 & 12 & 11.8897921916713 & 0.110207808328722 \tabularnewline
88 & 12 & 11.7805458559257 & 0.219454144074321 \tabularnewline
89 & 12 & 11.4316706247546 & 0.568329375245435 \tabularnewline
90 & 9 & 9.79403929363986 & -0.794039293639859 \tabularnewline
91 & 15 & 12.1392574188074 & 2.86074258119256 \tabularnewline
92 & 12 & 12.0611010122208 & -0.0611010122208251 \tabularnewline
93 & 12 & 11.1479382682115 & 0.852061731788505 \tabularnewline
94 & 12 & 10.2731774591333 & 1.72682254086674 \tabularnewline
95 & 10 & 11.7803892794887 & -1.7803892794887 \tabularnewline
96 & 13 & 11.7658308494585 & 1.23416915054148 \tabularnewline
97 & 9 & 11.6972094934659 & -2.69720949346593 \tabularnewline
98 & 12 & 11.6788194787628 & 0.321180521237202 \tabularnewline
99 & 10 & 10.8346077060054 & -0.834607706005373 \tabularnewline
100 & 14 & 11.6912937045852 & 2.30870629541476 \tabularnewline
101 & 11 & 11.733043351333 & -0.733043351333031 \tabularnewline
102 & 15 & 13.8811194023398 & 1.11888059766021 \tabularnewline
103 & 11 & 11.0642721361578 & -0.0642721361578231 \tabularnewline
104 & 11 & 11.8599148024903 & -0.859914802490292 \tabularnewline
105 & 12 & 9.99870096383018 & 2.00129903616982 \tabularnewline
106 & 12 & 12.1187866853865 & -0.118786685386485 \tabularnewline
107 & 12 & 11.6283538875765 & 0.37164611242351 \tabularnewline
108 & 11 & 11.6290388500338 & -0.629038850033779 \tabularnewline
109 & 7 & 9.51160425686141 & -2.51160425686141 \tabularnewline
110 & 12 & 11.7146188119761 & 0.28538118802394 \tabularnewline
111 & 14 & 11.7046263759617 & 2.29537362403826 \tabularnewline
112 & 11 & 12.5494319833421 & -1.54943198334211 \tabularnewline
113 & 11 & 9.81356526539396 & 1.18643473460604 \tabularnewline
114 & 10 & 9.32855690203165 & 0.67144309796835 \tabularnewline
115 & 13 & 12.5135762941787 & 0.4864237058213 \tabularnewline
116 & 13 & 10.6121268217453 & 2.38787317825466 \tabularnewline
117 & 8 & 10.6655361365725 & -2.66553613657249 \tabularnewline
118 & 11 & 10.0357811322548 & 0.964218867745233 \tabularnewline
119 & 12 & 11.5915846541129 & 0.408415345887119 \tabularnewline
120 & 11 & 9.98923981960607 & 1.01076018039393 \tabularnewline
121 & 13 & 11.2869388063217 & 1.71306119367832 \tabularnewline
122 & 12 & 10.1155122106505 & 1.88448778934946 \tabularnewline
123 & 14 & 11.5946883841431 & 2.40531161585689 \tabularnewline
124 & 13 & 10.7698421866525 & 2.2301578133475 \tabularnewline
125 & 15 & 11.5502539912816 & 3.44974600871838 \tabularnewline
126 & 10 & 10.8046002831306 & -0.80460028313059 \tabularnewline
127 & 11 & 11.8820080155201 & -0.882008015520087 \tabularnewline
128 & 9 & 10.8684784999657 & -1.86847849996566 \tabularnewline
129 & 11 & 9.2151778113691 & 1.78482218863091 \tabularnewline
130 & 10 & 11.4237296430119 & -1.42372964301193 \tabularnewline
131 & 11 & 8.3228851782932 & 2.6771148217068 \tabularnewline
132 & 8 & 11.3857120327997 & -3.38571203279971 \tabularnewline
133 & 11 & 9.13316843963616 & 1.86683156036384 \tabularnewline
134 & 12 & 10.3659389698297 & 1.63406103017028 \tabularnewline
135 & 12 & 10.6427309379395 & 1.35726906206047 \tabularnewline
136 & 9 & 9.27707008994215 & -0.27707008994215 \tabularnewline
137 & 11 & 10.7265776812633 & 0.273422318736661 \tabularnewline
138 & 10 & 8.73259495254044 & 1.26740504745956 \tabularnewline
139 & 8 & 9.1044410616345 & -1.1044410616345 \tabularnewline
140 & 9 & 8.77390650865731 & 0.226093491342694 \tabularnewline
141 & 8 & 11.1656130471982 & -3.16561304719824 \tabularnewline
142 & 9 & 10.8892982440569 & -1.88929824405688 \tabularnewline
143 & 15 & 11.9427193079651 & 3.05728069203487 \tabularnewline
144 & 11 & 10.8654783167243 & 0.134521683275723 \tabularnewline
145 & 8 & 7.91698228064001 & 0.0830177193599868 \tabularnewline
146 & 13 & 11.9667162689743 & 1.03328373102575 \tabularnewline
147 & 12 & 9.66906419715512 & 2.33093580284488 \tabularnewline
148 & 12 & 11.1905878941644 & 0.809412105835587 \tabularnewline
149 & 9 & 9.59375584532932 & -0.593755845329324 \tabularnewline
150 & 7 & 8.15133255979377 & -1.15133255979376 \tabularnewline
151 & 13 & 10.6044237104854 & 2.39557628951459 \tabularnewline
152 & 9 & 11.2390168748651 & -2.2390168748651 \tabularnewline
153 & 6 & 11.3433284593189 & -5.34332845931886 \tabularnewline
154 & 8 & 9.28169298278866 & -1.28169298278866 \tabularnewline
155 & 8 & 7.86644908331102 & 0.133550916688975 \tabularnewline
156 & 15 & 11.3712931614709 & 3.62870683852907 \tabularnewline
157 & 6 & 9.60605588524128 & -3.60605588524128 \tabularnewline
158 & 9 & 10.514033458118 & -1.51403345811804 \tabularnewline
159 & 11 & 11.1091256765928 & -0.109125676592751 \tabularnewline
160 & 8 & 9.20817295842716 & -1.20817295842716 \tabularnewline
161 & 8 & 9.48693786592225 & -1.48693786592225 \tabularnewline
162 & 10 & 9.99331481158232 & 0.00668518841767825 \tabularnewline
163 & 8 & 9.48176361799367 & -1.48176361799367 \tabularnewline
164 & 14 & 12.0648585402182 & 1.93514145978183 \tabularnewline
165 & 10 & 11.4695631104637 & -1.46956311046372 \tabularnewline
166 & 8 & 8.50002097029168 & -0.500020970291678 \tabularnewline
167 & 11 & 10.7460829185796 & 0.253917081420426 \tabularnewline
168 & 12 & 8.97461357455498 & 3.02538642544503 \tabularnewline
169 & 12 & 10.4617315210613 & 1.53826847893867 \tabularnewline
170 & 12 & 12.0294528928777 & -0.0294528928777491 \tabularnewline
171 & 5 & 9.32375800275669 & -4.32375800275669 \tabularnewline
172 & 12 & 11.6637585474086 & 0.336241452591394 \tabularnewline
173 & 10 & 9.68126631307497 & 0.318733686925034 \tabularnewline
174 & 7 & 7.64859947115942 & -0.648599471159415 \tabularnewline
175 & 12 & 9.20547875405067 & 2.79452124594933 \tabularnewline
176 & 11 & 11.2775316262317 & -0.277531626231655 \tabularnewline
177 & 8 & 9.51702585919688 & -1.51702585919688 \tabularnewline
178 & 9 & 9.41159294886717 & -0.41159294886717 \tabularnewline
179 & 10 & 10.4014780423728 & -0.401478042372832 \tabularnewline
180 & 9 & 9.61965648730361 & -0.619656487303614 \tabularnewline
181 & 12 & 11.486300388028 & 0.51369961197202 \tabularnewline
182 & 6 & 8.8092367603918 & -2.8092367603918 \tabularnewline
183 & 15 & 13.1743921795611 & 1.8256078204389 \tabularnewline
184 & 12 & 10.9237987667884 & 1.0762012332116 \tabularnewline
185 & 12 & 7.38662421078078 & 4.61337578921922 \tabularnewline
186 & 12 & 11.5845238573839 & 0.415476142616064 \tabularnewline
187 & 11 & 11.9581637058654 & -0.958163705865438 \tabularnewline
188 & 7 & 9.25060130695437 & -2.25060130695437 \tabularnewline
189 & 7 & 8.64899616535271 & -1.64899616535271 \tabularnewline
190 & 5 & 8.87559833303154 & -3.87559833303154 \tabularnewline
191 & 12 & 10.4147546301531 & 1.58524536984691 \tabularnewline
192 & 12 & 11.6161350420391 & 0.383864957960852 \tabularnewline
193 & 3 & 9.2411450163548 & -6.2411450163548 \tabularnewline
194 & 11 & 11.4698469018573 & -0.469846901857283 \tabularnewline
195 & 10 & 9.73006642428058 & 0.269933575719425 \tabularnewline
196 & 12 & 10.9960545749277 & 1.0039454250723 \tabularnewline
197 & 9 & 11.2129158321836 & -2.21291583218361 \tabularnewline
198 & 12 & 11.5362000516786 & 0.463799948321352 \tabularnewline
199 & 9 & 10.336764082188 & -1.33676408218799 \tabularnewline
200 & 12 & 11.4563947907489 & 0.543605209251125 \tabularnewline
201 & 12 & 11.3208417812954 & 0.679158218704589 \tabularnewline
202 & 10 & 10.2478377374612 & -0.247837737461182 \tabularnewline
203 & 9 & 8.52185334505119 & 0.478146654948805 \tabularnewline
204 & 12 & 9.01622128206681 & 2.9837787179332 \tabularnewline
205 & 8 & 10.7449910376785 & -2.74499103767854 \tabularnewline
206 & 11 & 10.776084887628 & 0.223915112371953 \tabularnewline
207 & 11 & 11.4062370643019 & -0.406237064301928 \tabularnewline
208 & 12 & 11.0626146286059 & 0.937385371394063 \tabularnewline
209 & 10 & 8.54050548800613 & 1.45949451199387 \tabularnewline
210 & 10 & 10.662105392469 & -0.662105392469014 \tabularnewline
211 & 12 & 9.13439690768707 & 2.86560309231293 \tabularnewline
212 & 12 & 9.36205843945968 & 2.63794156054032 \tabularnewline
213 & 11 & 10.9929704258936 & 0.00702957410642848 \tabularnewline
214 & 8 & 10.7999690617809 & -2.79996906178092 \tabularnewline
215 & 12 & 11.1799528302841 & 0.820047169715862 \tabularnewline
216 & 10 & 9.77904233977502 & 0.220957660224979 \tabularnewline
217 & 11 & 11.6909913840273 & -0.690991384027324 \tabularnewline
218 & 10 & 10.0472194069847 & -0.0472194069846633 \tabularnewline
219 & 8 & 9.56108554325039 & -1.56108554325039 \tabularnewline
220 & 12 & 10.7173932462853 & 1.28260675371468 \tabularnewline
221 & 12 & 9.58816453683015 & 2.41183546316985 \tabularnewline
222 & 10 & 9.8870918007457 & 0.112908199254296 \tabularnewline
223 & 12 & 10.5522739020444 & 1.44772609795563 \tabularnewline
224 & 9 & 8.94328586274795 & 0.0567141372520499 \tabularnewline
225 & 9 & 9.43156784767182 & -0.431567847671817 \tabularnewline
226 & 6 & 6.96812057701776 & -0.968120577017763 \tabularnewline
227 & 10 & 9.67928988333045 & 0.320710116669546 \tabularnewline
228 & 9 & 9.99624386720667 & -0.996243867206671 \tabularnewline
229 & 9 & 8.37606551795147 & 0.623934482048527 \tabularnewline
230 & 9 & 9.00289453889522 & -0.00289453889521819 \tabularnewline
231 & 6 & 9.24624389113926 & -3.24624389113926 \tabularnewline
232 & 10 & 8.07289696125591 & 1.92710303874409 \tabularnewline
233 & 6 & 10.8829366307167 & -4.88293663071672 \tabularnewline
234 & 14 & 11.7691933920382 & 2.23080660796175 \tabularnewline
235 & 10 & 9.24604006795855 & 0.753959932041448 \tabularnewline
236 & 10 & 8.21715193737839 & 1.78284806262161 \tabularnewline
237 & 6 & 4.47153852812902 & 1.52846147187098 \tabularnewline
238 & 12 & 8.89903457860828 & 3.10096542139172 \tabularnewline
239 & 12 & 10.9901062427108 & 1.00989375728915 \tabularnewline
240 & 7 & 7.63148226682086 & -0.631482266820859 \tabularnewline
241 & 8 & 9.00438387301048 & -1.00438387301048 \tabularnewline
242 & 11 & 8.76342331835451 & 2.23657668164549 \tabularnewline
243 & 3 & 7.51847235136829 & -4.51847235136829 \tabularnewline
244 & 6 & 9.17443209252123 & -3.17443209252123 \tabularnewline
245 & 10 & 10.1056554718797 & -0.105655471879743 \tabularnewline
246 & 8 & 8.81780474571089 & -0.817804745710885 \tabularnewline
247 & 9 & 9.7717455830614 & -0.771745583061396 \tabularnewline
248 & 9 & 7.22131604751021 & 1.7786839524898 \tabularnewline
249 & 8 & 8.39115811245736 & -0.391158112457362 \tabularnewline
250 & 9 & 8.2803300120063 & 0.719669987993699 \tabularnewline
251 & 7 & 8.11062828568229 & -1.11062828568229 \tabularnewline
252 & 7 & 7.55066185760807 & -0.55066185760807 \tabularnewline
253 & 6 & 8.62003125264115 & -2.62003125264115 \tabularnewline
254 & 9 & 10.6492039877645 & -1.64920398776448 \tabularnewline
255 & 10 & 8.48123946096089 & 1.51876053903911 \tabularnewline
256 & 11 & 9.58079232574706 & 1.41920767425294 \tabularnewline
257 & 12 & 10.8334986862589 & 1.16650131374108 \tabularnewline
258 & 8 & 9.60777906773184 & -1.60777906773183 \tabularnewline
259 & 11 & 8.91518416413199 & 2.08481583586801 \tabularnewline
260 & 3 & 4.45649769750934 & -1.45649769750934 \tabularnewline
261 & 11 & 10.0155089212759 & 0.984491078724085 \tabularnewline
262 & 12 & 8.08443730393345 & 3.91556269606655 \tabularnewline
263 & 7 & 7.9989852737733 & -0.998985273773303 \tabularnewline
264 & 9 & 9.54776919124914 & -0.547769191249143 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190281&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12[/C][C]10.4821854234195[/C][C]1.51781457658049[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]11.9075842064841[/C][C]-0.907584206484133[/C][/ROW]
[ROW][C]3[/C][C]15[/C][C]13.8149716055396[/C][C]1.18502839446038[/C][/ROW]
[ROW][C]4[/C][C]6[/C][C]11.6333751703777[/C][C]-5.63337517037766[/C][/ROW]
[ROW][C]5[/C][C]13[/C][C]11.0166321647319[/C][C]1.98336783526813[/C][/ROW]
[ROW][C]6[/C][C]10[/C][C]10.2222765701055[/C][C]-0.222276570105538[/C][/ROW]
[ROW][C]7[/C][C]12[/C][C]13.176625117343[/C][C]-1.17662511734304[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]11.6689912101308[/C][C]2.33100878986916[/C][/ROW]
[ROW][C]9[/C][C]12[/C][C]11.0065730579505[/C][C]0.993426942049482[/C][/ROW]
[ROW][C]10[/C][C]9[/C][C]11.5828102963255[/C][C]-2.58281029632552[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]11.8007299664464[/C][C]-1.80072996644642[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]11.7386444011073[/C][C]0.261355598892743[/C][/ROW]
[ROW][C]13[/C][C]12[/C][C]12.0237937721744[/C][C]-0.0237937721743902[/C][/ROW]
[ROW][C]14[/C][C]11[/C][C]11.83930008687[/C][C]-0.839300086869993[/C][/ROW]
[ROW][C]15[/C][C]15[/C][C]12.6038228991376[/C][C]2.39617710086238[/C][/ROW]
[ROW][C]16[/C][C]12[/C][C]11.3265566583403[/C][C]0.673443341659683[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]11.3162358896638[/C][C]-1.31623588966378[/C][/ROW]
[ROW][C]18[/C][C]12[/C][C]14.1015687088112[/C][C]-2.10156870881119[/C][/ROW]
[ROW][C]19[/C][C]11[/C][C]12.9888077393546[/C][C]-1.98880773935461[/C][/ROW]
[ROW][C]20[/C][C]12[/C][C]11.6991413019061[/C][C]0.300858698093912[/C][/ROW]
[ROW][C]21[/C][C]11[/C][C]11.7558018890754[/C][C]-0.755801889075384[/C][/ROW]
[ROW][C]22[/C][C]12[/C][C]11.8756764267919[/C][C]0.1243235732081[/C][/ROW]
[ROW][C]23[/C][C]13[/C][C]13.3817209295794[/C][C]-0.38172092957939[/C][/ROW]
[ROW][C]24[/C][C]11[/C][C]11.9307432500581[/C][C]-0.930743250058119[/C][/ROW]
[ROW][C]25[/C][C]12[/C][C]12.2100574977995[/C][C]-0.210057497799463[/C][/ROW]
[ROW][C]26[/C][C]13[/C][C]12.4178058831252[/C][C]0.582194116874759[/C][/ROW]
[ROW][C]27[/C][C]10[/C][C]11.8110172246203[/C][C]-1.81101722462031[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]11.3676053505947[/C][C]2.63239464940525[/C][/ROW]
[ROW][C]29[/C][C]12[/C][C]11.776066395463[/C][C]0.223933604536968[/C][/ROW]
[ROW][C]30[/C][C]10[/C][C]10.7650840073673[/C][C]-0.765084007367292[/C][/ROW]
[ROW][C]31[/C][C]12[/C][C]11.2231247143056[/C][C]0.776875285694439[/C][/ROW]
[ROW][C]32[/C][C]8[/C][C]9.62950222804292[/C][C]-1.62950222804292[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.4727927629825[/C][C]-0.472792762982493[/C][/ROW]
[ROW][C]34[/C][C]12[/C][C]11.9023597863329[/C][C]0.0976402136670583[/C][/ROW]
[ROW][C]35[/C][C]12[/C][C]10.5584849737295[/C][C]1.4415150262705[/C][/ROW]
[ROW][C]36[/C][C]7[/C][C]8.57508653891843[/C][C]-1.57508653891843[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]8.59396593595696[/C][C]0.406034064043041[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]10.5488561794385[/C][C]1.45114382056149[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]11.6162846178761[/C][C]-1.61628461787612[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]11.6590241656482[/C][C]-1.65902416564817[/C][/ROW]
[ROW][C]41[/C][C]10[/C][C]11.5508413174462[/C][C]-1.5508413174462[/C][/ROW]
[ROW][C]42[/C][C]12[/C][C]10.5105599271666[/C][C]1.48944007283343[/C][/ROW]
[ROW][C]43[/C][C]15[/C][C]13.4413148746779[/C][C]1.55868512532211[/C][/ROW]
[ROW][C]44[/C][C]10[/C][C]10.4552789181056[/C][C]-0.455278918105551[/C][/ROW]
[ROW][C]45[/C][C]10[/C][C]10.2440571070989[/C][C]-0.244057107098923[/C][/ROW]
[ROW][C]46[/C][C]12[/C][C]9.05715769641412[/C][C]2.94284230358588[/C][/ROW]
[ROW][C]47[/C][C]13[/C][C]10.6141249901998[/C][C]2.38587500980021[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]11.075965687589[/C][C]-0.0759656875890157[/C][/ROW]
[ROW][C]49[/C][C]11[/C][C]11.5693661440328[/C][C]-0.569366144032777[/C][/ROW]
[ROW][C]50[/C][C]12[/C][C]10.4385123485549[/C][C]1.5614876514451[/C][/ROW]
[ROW][C]51[/C][C]14[/C][C]11.6860397071913[/C][C]2.31396029280866[/C][/ROW]
[ROW][C]52[/C][C]10[/C][C]10.3313851763377[/C][C]-0.331385176337656[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]9.42109669632271[/C][C]2.57890330367729[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]11.6142407700698[/C][C]1.38575922993022[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]7.8518626079202[/C][C]-2.8518626079202[/C][/ROW]
[ROW][C]56[/C][C]6[/C][C]10.3915135154692[/C][C]-4.39151351546923[/C][/ROW]
[ROW][C]57[/C][C]12[/C][C]11.3204170724527[/C][C]0.679582927547251[/C][/ROW]
[ROW][C]58[/C][C]12[/C][C]11.519836966396[/C][C]0.480163033604005[/C][/ROW]
[ROW][C]59[/C][C]11[/C][C]11.052222477487[/C][C]-0.0522224774870326[/C][/ROW]
[ROW][C]60[/C][C]10[/C][C]11.4402330584058[/C][C]-1.44023305840583[/C][/ROW]
[ROW][C]61[/C][C]7[/C][C]9.1887137926978[/C][C]-2.1887137926978[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]11.4147631067753[/C][C]0.585236893224654[/C][/ROW]
[ROW][C]63[/C][C]14[/C][C]11.5931758852314[/C][C]2.40682411476865[/C][/ROW]
[ROW][C]64[/C][C]11[/C][C]10.2981728252194[/C][C]0.701827174780583[/C][/ROW]
[ROW][C]65[/C][C]12[/C][C]11.1127625199563[/C][C]0.887237480043656[/C][/ROW]
[ROW][C]66[/C][C]13[/C][C]12.9445961468001[/C][C]0.0554038531999405[/C][/ROW]
[ROW][C]67[/C][C]14[/C][C]13.1663459997828[/C][C]0.833654000217238[/C][/ROW]
[ROW][C]68[/C][C]11[/C][C]13.051082239735[/C][C]-2.05108223973502[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]10.0561886528658[/C][C]1.94381134713417[/C][/ROW]
[ROW][C]70[/C][C]12[/C][C]12.1092424412897[/C][C]-0.109242441289716[/C][/ROW]
[ROW][C]71[/C][C]8[/C][C]8.91054304458035[/C][C]-0.910543044580353[/C][/ROW]
[ROW][C]72[/C][C]11[/C][C]11.016072802622[/C][C]-0.0160728026219689[/C][/ROW]
[ROW][C]73[/C][C]14[/C][C]13.2954854274213[/C][C]0.704514572578696[/C][/ROW]
[ROW][C]74[/C][C]14[/C][C]13.2476084497014[/C][C]0.752391550298631[/C][/ROW]
[ROW][C]75[/C][C]12[/C][C]11.8969739216161[/C][C]0.103026078383948[/C][/ROW]
[ROW][C]76[/C][C]9[/C][C]12.3375568191361[/C][C]-3.33755681913614[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.9408036548114[/C][C]1.05919634518859[/C][/ROW]
[ROW][C]78[/C][C]11[/C][C]11.8368386694733[/C][C]-0.836838669473322[/C][/ROW]
[ROW][C]79[/C][C]12[/C][C]10.408761793063[/C][C]1.59123820693698[/C][/ROW]
[ROW][C]80[/C][C]12[/C][C]11.6161183549211[/C][C]0.383881645078944[/C][/ROW]
[ROW][C]81[/C][C]12[/C][C]12.0816258307049[/C][C]-0.0816258307049354[/C][/ROW]
[ROW][C]82[/C][C]12[/C][C]12.0321386520043[/C][C]-0.0321386520042612[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]11.2715363258182[/C][C]0.728463674181814[/C][/ROW]
[ROW][C]84[/C][C]11[/C][C]11.4083951015267[/C][C]-0.408395101526732[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]11.8406373149819[/C][C]-1.84063731498186[/C][/ROW]
[ROW][C]86[/C][C]9[/C][C]10.9516660556244[/C][C]-1.95166605562436[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]11.8897921916713[/C][C]0.110207808328722[/C][/ROW]
[ROW][C]88[/C][C]12[/C][C]11.7805458559257[/C][C]0.219454144074321[/C][/ROW]
[ROW][C]89[/C][C]12[/C][C]11.4316706247546[/C][C]0.568329375245435[/C][/ROW]
[ROW][C]90[/C][C]9[/C][C]9.79403929363986[/C][C]-0.794039293639859[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]12.1392574188074[/C][C]2.86074258119256[/C][/ROW]
[ROW][C]92[/C][C]12[/C][C]12.0611010122208[/C][C]-0.0611010122208251[/C][/ROW]
[ROW][C]93[/C][C]12[/C][C]11.1479382682115[/C][C]0.852061731788505[/C][/ROW]
[ROW][C]94[/C][C]12[/C][C]10.2731774591333[/C][C]1.72682254086674[/C][/ROW]
[ROW][C]95[/C][C]10[/C][C]11.7803892794887[/C][C]-1.7803892794887[/C][/ROW]
[ROW][C]96[/C][C]13[/C][C]11.7658308494585[/C][C]1.23416915054148[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]11.6972094934659[/C][C]-2.69720949346593[/C][/ROW]
[ROW][C]98[/C][C]12[/C][C]11.6788194787628[/C][C]0.321180521237202[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]10.8346077060054[/C][C]-0.834607706005373[/C][/ROW]
[ROW][C]100[/C][C]14[/C][C]11.6912937045852[/C][C]2.30870629541476[/C][/ROW]
[ROW][C]101[/C][C]11[/C][C]11.733043351333[/C][C]-0.733043351333031[/C][/ROW]
[ROW][C]102[/C][C]15[/C][C]13.8811194023398[/C][C]1.11888059766021[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]11.0642721361578[/C][C]-0.0642721361578231[/C][/ROW]
[ROW][C]104[/C][C]11[/C][C]11.8599148024903[/C][C]-0.859914802490292[/C][/ROW]
[ROW][C]105[/C][C]12[/C][C]9.99870096383018[/C][C]2.00129903616982[/C][/ROW]
[ROW][C]106[/C][C]12[/C][C]12.1187866853865[/C][C]-0.118786685386485[/C][/ROW]
[ROW][C]107[/C][C]12[/C][C]11.6283538875765[/C][C]0.37164611242351[/C][/ROW]
[ROW][C]108[/C][C]11[/C][C]11.6290388500338[/C][C]-0.629038850033779[/C][/ROW]
[ROW][C]109[/C][C]7[/C][C]9.51160425686141[/C][C]-2.51160425686141[/C][/ROW]
[ROW][C]110[/C][C]12[/C][C]11.7146188119761[/C][C]0.28538118802394[/C][/ROW]
[ROW][C]111[/C][C]14[/C][C]11.7046263759617[/C][C]2.29537362403826[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]12.5494319833421[/C][C]-1.54943198334211[/C][/ROW]
[ROW][C]113[/C][C]11[/C][C]9.81356526539396[/C][C]1.18643473460604[/C][/ROW]
[ROW][C]114[/C][C]10[/C][C]9.32855690203165[/C][C]0.67144309796835[/C][/ROW]
[ROW][C]115[/C][C]13[/C][C]12.5135762941787[/C][C]0.4864237058213[/C][/ROW]
[ROW][C]116[/C][C]13[/C][C]10.6121268217453[/C][C]2.38787317825466[/C][/ROW]
[ROW][C]117[/C][C]8[/C][C]10.6655361365725[/C][C]-2.66553613657249[/C][/ROW]
[ROW][C]118[/C][C]11[/C][C]10.0357811322548[/C][C]0.964218867745233[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]11.5915846541129[/C][C]0.408415345887119[/C][/ROW]
[ROW][C]120[/C][C]11[/C][C]9.98923981960607[/C][C]1.01076018039393[/C][/ROW]
[ROW][C]121[/C][C]13[/C][C]11.2869388063217[/C][C]1.71306119367832[/C][/ROW]
[ROW][C]122[/C][C]12[/C][C]10.1155122106505[/C][C]1.88448778934946[/C][/ROW]
[ROW][C]123[/C][C]14[/C][C]11.5946883841431[/C][C]2.40531161585689[/C][/ROW]
[ROW][C]124[/C][C]13[/C][C]10.7698421866525[/C][C]2.2301578133475[/C][/ROW]
[ROW][C]125[/C][C]15[/C][C]11.5502539912816[/C][C]3.44974600871838[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]10.8046002831306[/C][C]-0.80460028313059[/C][/ROW]
[ROW][C]127[/C][C]11[/C][C]11.8820080155201[/C][C]-0.882008015520087[/C][/ROW]
[ROW][C]128[/C][C]9[/C][C]10.8684784999657[/C][C]-1.86847849996566[/C][/ROW]
[ROW][C]129[/C][C]11[/C][C]9.2151778113691[/C][C]1.78482218863091[/C][/ROW]
[ROW][C]130[/C][C]10[/C][C]11.4237296430119[/C][C]-1.42372964301193[/C][/ROW]
[ROW][C]131[/C][C]11[/C][C]8.3228851782932[/C][C]2.6771148217068[/C][/ROW]
[ROW][C]132[/C][C]8[/C][C]11.3857120327997[/C][C]-3.38571203279971[/C][/ROW]
[ROW][C]133[/C][C]11[/C][C]9.13316843963616[/C][C]1.86683156036384[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]10.3659389698297[/C][C]1.63406103017028[/C][/ROW]
[ROW][C]135[/C][C]12[/C][C]10.6427309379395[/C][C]1.35726906206047[/C][/ROW]
[ROW][C]136[/C][C]9[/C][C]9.27707008994215[/C][C]-0.27707008994215[/C][/ROW]
[ROW][C]137[/C][C]11[/C][C]10.7265776812633[/C][C]0.273422318736661[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]8.73259495254044[/C][C]1.26740504745956[/C][/ROW]
[ROW][C]139[/C][C]8[/C][C]9.1044410616345[/C][C]-1.1044410616345[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]8.77390650865731[/C][C]0.226093491342694[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]11.1656130471982[/C][C]-3.16561304719824[/C][/ROW]
[ROW][C]142[/C][C]9[/C][C]10.8892982440569[/C][C]-1.88929824405688[/C][/ROW]
[ROW][C]143[/C][C]15[/C][C]11.9427193079651[/C][C]3.05728069203487[/C][/ROW]
[ROW][C]144[/C][C]11[/C][C]10.8654783167243[/C][C]0.134521683275723[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]7.91698228064001[/C][C]0.0830177193599868[/C][/ROW]
[ROW][C]146[/C][C]13[/C][C]11.9667162689743[/C][C]1.03328373102575[/C][/ROW]
[ROW][C]147[/C][C]12[/C][C]9.66906419715512[/C][C]2.33093580284488[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]11.1905878941644[/C][C]0.809412105835587[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]9.59375584532932[/C][C]-0.593755845329324[/C][/ROW]
[ROW][C]150[/C][C]7[/C][C]8.15133255979377[/C][C]-1.15133255979376[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]10.6044237104854[/C][C]2.39557628951459[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.2390168748651[/C][C]-2.2390168748651[/C][/ROW]
[ROW][C]153[/C][C]6[/C][C]11.3433284593189[/C][C]-5.34332845931886[/C][/ROW]
[ROW][C]154[/C][C]8[/C][C]9.28169298278866[/C][C]-1.28169298278866[/C][/ROW]
[ROW][C]155[/C][C]8[/C][C]7.86644908331102[/C][C]0.133550916688975[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]11.3712931614709[/C][C]3.62870683852907[/C][/ROW]
[ROW][C]157[/C][C]6[/C][C]9.60605588524128[/C][C]-3.60605588524128[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]10.514033458118[/C][C]-1.51403345811804[/C][/ROW]
[ROW][C]159[/C][C]11[/C][C]11.1091256765928[/C][C]-0.109125676592751[/C][/ROW]
[ROW][C]160[/C][C]8[/C][C]9.20817295842716[/C][C]-1.20817295842716[/C][/ROW]
[ROW][C]161[/C][C]8[/C][C]9.48693786592225[/C][C]-1.48693786592225[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.99331481158232[/C][C]0.00668518841767825[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]9.48176361799367[/C][C]-1.48176361799367[/C][/ROW]
[ROW][C]164[/C][C]14[/C][C]12.0648585402182[/C][C]1.93514145978183[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.4695631104637[/C][C]-1.46956311046372[/C][/ROW]
[ROW][C]166[/C][C]8[/C][C]8.50002097029168[/C][C]-0.500020970291678[/C][/ROW]
[ROW][C]167[/C][C]11[/C][C]10.7460829185796[/C][C]0.253917081420426[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]8.97461357455498[/C][C]3.02538642544503[/C][/ROW]
[ROW][C]169[/C][C]12[/C][C]10.4617315210613[/C][C]1.53826847893867[/C][/ROW]
[ROW][C]170[/C][C]12[/C][C]12.0294528928777[/C][C]-0.0294528928777491[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]9.32375800275669[/C][C]-4.32375800275669[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.6637585474086[/C][C]0.336241452591394[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]9.68126631307497[/C][C]0.318733686925034[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]7.64859947115942[/C][C]-0.648599471159415[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]9.20547875405067[/C][C]2.79452124594933[/C][/ROW]
[ROW][C]176[/C][C]11[/C][C]11.2775316262317[/C][C]-0.277531626231655[/C][/ROW]
[ROW][C]177[/C][C]8[/C][C]9.51702585919688[/C][C]-1.51702585919688[/C][/ROW]
[ROW][C]178[/C][C]9[/C][C]9.41159294886717[/C][C]-0.41159294886717[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]10.4014780423728[/C][C]-0.401478042372832[/C][/ROW]
[ROW][C]180[/C][C]9[/C][C]9.61965648730361[/C][C]-0.619656487303614[/C][/ROW]
[ROW][C]181[/C][C]12[/C][C]11.486300388028[/C][C]0.51369961197202[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]8.8092367603918[/C][C]-2.8092367603918[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]13.1743921795611[/C][C]1.8256078204389[/C][/ROW]
[ROW][C]184[/C][C]12[/C][C]10.9237987667884[/C][C]1.0762012332116[/C][/ROW]
[ROW][C]185[/C][C]12[/C][C]7.38662421078078[/C][C]4.61337578921922[/C][/ROW]
[ROW][C]186[/C][C]12[/C][C]11.5845238573839[/C][C]0.415476142616064[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]11.9581637058654[/C][C]-0.958163705865438[/C][/ROW]
[ROW][C]188[/C][C]7[/C][C]9.25060130695437[/C][C]-2.25060130695437[/C][/ROW]
[ROW][C]189[/C][C]7[/C][C]8.64899616535271[/C][C]-1.64899616535271[/C][/ROW]
[ROW][C]190[/C][C]5[/C][C]8.87559833303154[/C][C]-3.87559833303154[/C][/ROW]
[ROW][C]191[/C][C]12[/C][C]10.4147546301531[/C][C]1.58524536984691[/C][/ROW]
[ROW][C]192[/C][C]12[/C][C]11.6161350420391[/C][C]0.383864957960852[/C][/ROW]
[ROW][C]193[/C][C]3[/C][C]9.2411450163548[/C][C]-6.2411450163548[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]11.4698469018573[/C][C]-0.469846901857283[/C][/ROW]
[ROW][C]195[/C][C]10[/C][C]9.73006642428058[/C][C]0.269933575719425[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]10.9960545749277[/C][C]1.0039454250723[/C][/ROW]
[ROW][C]197[/C][C]9[/C][C]11.2129158321836[/C][C]-2.21291583218361[/C][/ROW]
[ROW][C]198[/C][C]12[/C][C]11.5362000516786[/C][C]0.463799948321352[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]10.336764082188[/C][C]-1.33676408218799[/C][/ROW]
[ROW][C]200[/C][C]12[/C][C]11.4563947907489[/C][C]0.543605209251125[/C][/ROW]
[ROW][C]201[/C][C]12[/C][C]11.3208417812954[/C][C]0.679158218704589[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]10.2478377374612[/C][C]-0.247837737461182[/C][/ROW]
[ROW][C]203[/C][C]9[/C][C]8.52185334505119[/C][C]0.478146654948805[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]9.01622128206681[/C][C]2.9837787179332[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]10.7449910376785[/C][C]-2.74499103767854[/C][/ROW]
[ROW][C]206[/C][C]11[/C][C]10.776084887628[/C][C]0.223915112371953[/C][/ROW]
[ROW][C]207[/C][C]11[/C][C]11.4062370643019[/C][C]-0.406237064301928[/C][/ROW]
[ROW][C]208[/C][C]12[/C][C]11.0626146286059[/C][C]0.937385371394063[/C][/ROW]
[ROW][C]209[/C][C]10[/C][C]8.54050548800613[/C][C]1.45949451199387[/C][/ROW]
[ROW][C]210[/C][C]10[/C][C]10.662105392469[/C][C]-0.662105392469014[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]9.13439690768707[/C][C]2.86560309231293[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]9.36205843945968[/C][C]2.63794156054032[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]10.9929704258936[/C][C]0.00702957410642848[/C][/ROW]
[ROW][C]214[/C][C]8[/C][C]10.7999690617809[/C][C]-2.79996906178092[/C][/ROW]
[ROW][C]215[/C][C]12[/C][C]11.1799528302841[/C][C]0.820047169715862[/C][/ROW]
[ROW][C]216[/C][C]10[/C][C]9.77904233977502[/C][C]0.220957660224979[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]11.6909913840273[/C][C]-0.690991384027324[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]10.0472194069847[/C][C]-0.0472194069846633[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.56108554325039[/C][C]-1.56108554325039[/C][/ROW]
[ROW][C]220[/C][C]12[/C][C]10.7173932462853[/C][C]1.28260675371468[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]9.58816453683015[/C][C]2.41183546316985[/C][/ROW]
[ROW][C]222[/C][C]10[/C][C]9.8870918007457[/C][C]0.112908199254296[/C][/ROW]
[ROW][C]223[/C][C]12[/C][C]10.5522739020444[/C][C]1.44772609795563[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]8.94328586274795[/C][C]0.0567141372520499[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.43156784767182[/C][C]-0.431567847671817[/C][/ROW]
[ROW][C]226[/C][C]6[/C][C]6.96812057701776[/C][C]-0.968120577017763[/C][/ROW]
[ROW][C]227[/C][C]10[/C][C]9.67928988333045[/C][C]0.320710116669546[/C][/ROW]
[ROW][C]228[/C][C]9[/C][C]9.99624386720667[/C][C]-0.996243867206671[/C][/ROW]
[ROW][C]229[/C][C]9[/C][C]8.37606551795147[/C][C]0.623934482048527[/C][/ROW]
[ROW][C]230[/C][C]9[/C][C]9.00289453889522[/C][C]-0.00289453889521819[/C][/ROW]
[ROW][C]231[/C][C]6[/C][C]9.24624389113926[/C][C]-3.24624389113926[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]8.07289696125591[/C][C]1.92710303874409[/C][/ROW]
[ROW][C]233[/C][C]6[/C][C]10.8829366307167[/C][C]-4.88293663071672[/C][/ROW]
[ROW][C]234[/C][C]14[/C][C]11.7691933920382[/C][C]2.23080660796175[/C][/ROW]
[ROW][C]235[/C][C]10[/C][C]9.24604006795855[/C][C]0.753959932041448[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]8.21715193737839[/C][C]1.78284806262161[/C][/ROW]
[ROW][C]237[/C][C]6[/C][C]4.47153852812902[/C][C]1.52846147187098[/C][/ROW]
[ROW][C]238[/C][C]12[/C][C]8.89903457860828[/C][C]3.10096542139172[/C][/ROW]
[ROW][C]239[/C][C]12[/C][C]10.9901062427108[/C][C]1.00989375728915[/C][/ROW]
[ROW][C]240[/C][C]7[/C][C]7.63148226682086[/C][C]-0.631482266820859[/C][/ROW]
[ROW][C]241[/C][C]8[/C][C]9.00438387301048[/C][C]-1.00438387301048[/C][/ROW]
[ROW][C]242[/C][C]11[/C][C]8.76342331835451[/C][C]2.23657668164549[/C][/ROW]
[ROW][C]243[/C][C]3[/C][C]7.51847235136829[/C][C]-4.51847235136829[/C][/ROW]
[ROW][C]244[/C][C]6[/C][C]9.17443209252123[/C][C]-3.17443209252123[/C][/ROW]
[ROW][C]245[/C][C]10[/C][C]10.1056554718797[/C][C]-0.105655471879743[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]8.81780474571089[/C][C]-0.817804745710885[/C][/ROW]
[ROW][C]247[/C][C]9[/C][C]9.7717455830614[/C][C]-0.771745583061396[/C][/ROW]
[ROW][C]248[/C][C]9[/C][C]7.22131604751021[/C][C]1.7786839524898[/C][/ROW]
[ROW][C]249[/C][C]8[/C][C]8.39115811245736[/C][C]-0.391158112457362[/C][/ROW]
[ROW][C]250[/C][C]9[/C][C]8.2803300120063[/C][C]0.719669987993699[/C][/ROW]
[ROW][C]251[/C][C]7[/C][C]8.11062828568229[/C][C]-1.11062828568229[/C][/ROW]
[ROW][C]252[/C][C]7[/C][C]7.55066185760807[/C][C]-0.55066185760807[/C][/ROW]
[ROW][C]253[/C][C]6[/C][C]8.62003125264115[/C][C]-2.62003125264115[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]10.6492039877645[/C][C]-1.64920398776448[/C][/ROW]
[ROW][C]255[/C][C]10[/C][C]8.48123946096089[/C][C]1.51876053903911[/C][/ROW]
[ROW][C]256[/C][C]11[/C][C]9.58079232574706[/C][C]1.41920767425294[/C][/ROW]
[ROW][C]257[/C][C]12[/C][C]10.8334986862589[/C][C]1.16650131374108[/C][/ROW]
[ROW][C]258[/C][C]8[/C][C]9.60777906773184[/C][C]-1.60777906773183[/C][/ROW]
[ROW][C]259[/C][C]11[/C][C]8.91518416413199[/C][C]2.08481583586801[/C][/ROW]
[ROW][C]260[/C][C]3[/C][C]4.45649769750934[/C][C]-1.45649769750934[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]10.0155089212759[/C][C]0.984491078724085[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]8.08443730393345[/C][C]3.91556269606655[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]7.9989852737733[/C][C]-0.998985273773303[/C][/ROW]
[ROW][C]264[/C][C]9[/C][C]9.54776919124914[/C][C]-0.547769191249143[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190281&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190281&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
11210.48218542341951.51781457658049
21111.9075842064841-0.907584206484133
31513.81497160553961.18502839446038
4611.6333751703777-5.63337517037766
51311.01663216473191.98336783526813
61010.2222765701055-0.222276570105538
71213.176625117343-1.17662511734304
81411.66899121013082.33100878986916
91211.00657305795050.993426942049482
10911.5828102963255-2.58281029632552
111011.8007299664464-1.80072996644642
121211.73864440110730.261355598892743
131212.0237937721744-0.0237937721743902
141111.83930008687-0.839300086869993
151512.60382289913762.39617710086238
161211.32655665834030.673443341659683
171011.3162358896638-1.31623588966378
181214.1015687088112-2.10156870881119
191112.9888077393546-1.98880773935461
201211.69914130190610.300858698093912
211111.7558018890754-0.755801889075384
221211.87567642679190.1243235732081
231313.3817209295794-0.38172092957939
241111.9307432500581-0.930743250058119
251212.2100574977995-0.210057497799463
261312.41780588312520.582194116874759
271011.8110172246203-1.81101722462031
281411.36760535059472.63239464940525
291211.7760663954630.223933604536968
301010.7650840073673-0.765084007367292
311211.22312471430560.776875285694439
3289.62950222804292-1.62950222804292
331010.4727927629825-0.472792762982493
341211.90235978633290.0976402136670583
351210.55848497372951.4415150262705
3678.57508653891843-1.57508653891843
3798.593965935956960.406034064043041
381210.54885617943851.45114382056149
391011.6162846178761-1.61628461787612
401011.6590241656482-1.65902416564817
411011.5508413174462-1.5508413174462
421210.51055992716661.48944007283343
431513.44131487467791.55868512532211
441010.4552789181056-0.455278918105551
451010.2440571070989-0.244057107098923
46129.057157696414122.94284230358588
471310.61412499019982.38587500980021
481111.075965687589-0.0759656875890157
491111.5693661440328-0.569366144032777
501210.43851234855491.5614876514451
511411.68603970719132.31396029280866
521010.3313851763377-0.331385176337656
53129.421096696322712.57890330367729
541311.61424077006981.38575922993022
5557.8518626079202-2.8518626079202
56610.3915135154692-4.39151351546923
571211.32041707245270.679582927547251
581211.5198369663960.480163033604005
591111.052222477487-0.0522224774870326
601011.4402330584058-1.44023305840583
6179.1887137926978-2.1887137926978
621211.41476310677530.585236893224654
631411.59317588523142.40682411476865
641110.29817282521940.701827174780583
651211.11276251995630.887237480043656
661312.94459614680010.0554038531999405
671413.16634599978280.833654000217238
681113.051082239735-2.05108223973502
691210.05618865286581.94381134713417
701212.1092424412897-0.109242441289716
7188.91054304458035-0.910543044580353
721111.016072802622-0.0160728026219689
731413.29548542742130.704514572578696
741413.24760844970140.752391550298631
751211.89697392161610.103026078383948
76912.3375568191361-3.33755681913614
771311.94080365481141.05919634518859
781111.8368386694733-0.836838669473322
791210.4087617930631.59123820693698
801211.61611835492110.383881645078944
811212.0816258307049-0.0816258307049354
821212.0321386520043-0.0321386520042612
831211.27153632581820.728463674181814
841111.4083951015267-0.408395101526732
851011.8406373149819-1.84063731498186
86910.9516660556244-1.95166605562436
871211.88979219167130.110207808328722
881211.78054585592570.219454144074321
891211.43167062475460.568329375245435
9099.79403929363986-0.794039293639859
911512.13925741880742.86074258119256
921212.0611010122208-0.0611010122208251
931211.14793826821150.852061731788505
941210.27317745913331.72682254086674
951011.7803892794887-1.7803892794887
961311.76583084945851.23416915054148
97911.6972094934659-2.69720949346593
981211.67881947876280.321180521237202
991010.8346077060054-0.834607706005373
1001411.69129370458522.30870629541476
1011111.733043351333-0.733043351333031
1021513.88111940233981.11888059766021
1031111.0642721361578-0.0642721361578231
1041111.8599148024903-0.859914802490292
105129.998700963830182.00129903616982
1061212.1187866853865-0.118786685386485
1071211.62835388757650.37164611242351
1081111.6290388500338-0.629038850033779
10979.51160425686141-2.51160425686141
1101211.71461881197610.28538118802394
1111411.70462637596172.29537362403826
1121112.5494319833421-1.54943198334211
113119.813565265393961.18643473460604
114109.328556902031650.67144309796835
1151312.51357629417870.4864237058213
1161310.61212682174532.38787317825466
117810.6655361365725-2.66553613657249
1181110.03578113225480.964218867745233
1191211.59158465411290.408415345887119
120119.989239819606071.01076018039393
1211311.28693880632171.71306119367832
1221210.11551221065051.88448778934946
1231411.59468838414312.40531161585689
1241310.76984218665252.2301578133475
1251511.55025399128163.44974600871838
1261010.8046002831306-0.80460028313059
1271111.8820080155201-0.882008015520087
128910.8684784999657-1.86847849996566
129119.21517781136911.78482218863091
1301011.4237296430119-1.42372964301193
131118.32288517829322.6771148217068
132811.3857120327997-3.38571203279971
133119.133168439636161.86683156036384
1341210.36593896982971.63406103017028
1351210.64273093793951.35726906206047
13699.27707008994215-0.27707008994215
1371110.72657768126330.273422318736661
138108.732594952540441.26740504745956
13989.1044410616345-1.1044410616345
14098.773906508657310.226093491342694
141811.1656130471982-3.16561304719824
142910.8892982440569-1.88929824405688
1431511.94271930796513.05728069203487
1441110.86547831672430.134521683275723
14587.916982280640010.0830177193599868
1461311.96671626897431.03328373102575
147129.669064197155122.33093580284488
1481211.19058789416440.809412105835587
14999.59375584532932-0.593755845329324
15078.15133255979377-1.15133255979376
1511310.60442371048542.39557628951459
152911.2390168748651-2.2390168748651
153611.3433284593189-5.34332845931886
15489.28169298278866-1.28169298278866
15587.866449083311020.133550916688975
1561511.37129316147093.62870683852907
15769.60605588524128-3.60605588524128
158910.514033458118-1.51403345811804
1591111.1091256765928-0.109125676592751
16089.20817295842716-1.20817295842716
16189.48693786592225-1.48693786592225
162109.993314811582320.00668518841767825
16389.48176361799367-1.48176361799367
1641412.06485854021821.93514145978183
1651011.4695631104637-1.46956311046372
16688.50002097029168-0.500020970291678
1671110.74608291857960.253917081420426
168128.974613574554983.02538642544503
1691210.46173152106131.53826847893867
1701212.0294528928777-0.0294528928777491
17159.32375800275669-4.32375800275669
1721211.66375854740860.336241452591394
173109.681266313074970.318733686925034
17477.64859947115942-0.648599471159415
175129.205478754050672.79452124594933
1761111.2775316262317-0.277531626231655
17789.51702585919688-1.51702585919688
17899.41159294886717-0.41159294886717
1791010.4014780423728-0.401478042372832
18099.61965648730361-0.619656487303614
1811211.4863003880280.51369961197202
18268.8092367603918-2.8092367603918
1831513.17439217956111.8256078204389
1841210.92379876678841.0762012332116
185127.386624210780784.61337578921922
1861211.58452385738390.415476142616064
1871111.9581637058654-0.958163705865438
18879.25060130695437-2.25060130695437
18978.64899616535271-1.64899616535271
19058.87559833303154-3.87559833303154
1911210.41475463015311.58524536984691
1921211.61613504203910.383864957960852
19339.2411450163548-6.2411450163548
1941111.4698469018573-0.469846901857283
195109.730066424280580.269933575719425
1961210.99605457492771.0039454250723
197911.2129158321836-2.21291583218361
1981211.53620005167860.463799948321352
199910.336764082188-1.33676408218799
2001211.45639479074890.543605209251125
2011211.32084178129540.679158218704589
2021010.2478377374612-0.247837737461182
20398.521853345051190.478146654948805
204129.016221282066812.9837787179332
205810.7449910376785-2.74499103767854
2061110.7760848876280.223915112371953
2071111.4062370643019-0.406237064301928
2081211.06261462860590.937385371394063
209108.540505488006131.45949451199387
2101010.662105392469-0.662105392469014
211129.134396907687072.86560309231293
212129.362058439459682.63794156054032
2131110.99297042589360.00702957410642848
214810.7999690617809-2.79996906178092
2151211.17995283028410.820047169715862
216109.779042339775020.220957660224979
2171111.6909913840273-0.690991384027324
2181010.0472194069847-0.0472194069846633
21989.56108554325039-1.56108554325039
2201210.71739324628531.28260675371468
221129.588164536830152.41183546316985
222109.88709180074570.112908199254296
2231210.55227390204441.44772609795563
22498.943285862747950.0567141372520499
22599.43156784767182-0.431567847671817
22666.96812057701776-0.968120577017763
227109.679289883330450.320710116669546
22899.99624386720667-0.996243867206671
22998.376065517951470.623934482048527
23099.00289453889522-0.00289453889521819
23169.24624389113926-3.24624389113926
232108.072896961255911.92710303874409
233610.8829366307167-4.88293663071672
2341411.76919339203822.23080660796175
235109.246040067958550.753959932041448
236108.217151937378391.78284806262161
23764.471538528129021.52846147187098
238128.899034578608283.10096542139172
2391210.99010624271081.00989375728915
24077.63148226682086-0.631482266820859
24189.00438387301048-1.00438387301048
242118.763423318354512.23657668164549
24337.51847235136829-4.51847235136829
24469.17443209252123-3.17443209252123
2451010.1056554718797-0.105655471879743
24688.81780474571089-0.817804745710885
24799.7717455830614-0.771745583061396
24897.221316047510211.7786839524898
24988.39115811245736-0.391158112457362
25098.28033001200630.719669987993699
25178.11062828568229-1.11062828568229
25277.55066185760807-0.55066185760807
25368.62003125264115-2.62003125264115
254910.6492039877645-1.64920398776448
255108.481239460960891.51876053903911
256119.580792325747061.41920767425294
2571210.83349868625891.16650131374108
25889.60777906773184-1.60777906773183
259118.915184164131992.08481583586801
26034.45649769750934-1.45649769750934
2611110.01550892127590.984491078724085
262128.084437303933453.91556269606655
26377.9989852737733-0.998985273773303
26499.54776919124914-0.547769191249143






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.9960700858905130.007859828218974610.0039299141094873
140.99441043961650.01117912076699960.00558956038349982
150.9903571010938350.01928579781233010.00964289890616503
160.9859049238213730.02819015235725480.0140950761786274
170.9747043472748830.05059130545023450.0252956527251172
180.9720648450622830.05587030987543420.0279351549377171
190.9620698755081280.07586024898374420.0379301244918721
200.9412833147255130.1174333705489750.0587166852744875
210.9180282696921770.1639434606156460.0819717303078231
220.8910817795780130.2178364408439750.108918220421987
230.8619454743433410.2761090513133180.138054525656659
240.8293393954823190.3413212090353630.170660604517681
250.7939460784316610.4121078431366790.206053921568339
260.7906489483497880.4187021033004250.209351051650212
270.802159469804090.3956810603918190.19784053019591
280.8037635106229720.3924729787540560.196236489377028
290.7540011107436930.4919977785126140.245998889256307
300.717802053007530.564395893984940.28219794699247
310.669155772342910.661688455314180.33084422765709
320.6862948268153930.6274103463692140.313705173184607
330.6297748203757070.7404503592485860.370225179624293
340.5729709244327180.8540581511345640.427029075567282
350.554508209566730.890983580866540.44549179043327
360.5413792943169720.9172414113660550.458620705683028
370.4839716181378720.9679432362757440.516028381862128
380.4654574562625440.9309149125250870.534542543737456
390.4435039330129860.8870078660259730.556496066987014
400.4127317036800260.8254634073600520.587268296319974
410.3746171322378040.7492342644756080.625382867762196
420.3439107326184430.6878214652368850.656089267381557
430.3925529192474690.7851058384949370.607447080752531
440.3466457187980110.6932914375960230.653354281201988
450.3002877932781620.6005755865563240.699712206721838
460.3363562129353750.672712425870750.663643787064625
470.3384418939548480.6768837879096960.661558106045152
480.29697897853580.5939579570716010.7030210214642
490.2970177336797920.5940354673595840.702982266320208
500.2722469987578640.5444939975157280.727753001242136
510.2694528344340030.5389056688680070.730547165565997
520.2343198725637540.4686397451275080.765680127436246
530.2311090197655580.4622180395311160.768890980234442
540.1993816973531210.3987633947062410.800618302646879
550.3010577377628560.6021154755257130.698942262237144
560.6199972469806850.760005506038630.380002753019315
570.5776188920438390.8447622159123230.422381107956162
580.5337063644144850.9325872711710290.466293635585514
590.4911986560913410.9823973121826820.508801343908659
600.4872184607435890.9744369214871780.512781539256411
610.4958985349063670.9917970698127340.504101465093633
620.4541515688154010.9083031376308020.545848431184599
630.4655077811331010.9310155622662030.534492218866899
640.423959828294980.847919656589960.57604017170502
650.393913530857660.7878270617153190.60608646914234
660.3525323282026670.7050646564053330.647467671797334
670.3191733807592710.6383467615185410.680826619240729
680.3058334012071030.6116668024142050.694166598792897
690.2861729568334560.5723459136669130.713827043166544
700.2549437593270950.5098875186541890.745056240672905
710.2357991695234940.4715983390469890.764200830476506
720.2056236842088760.4112473684177530.794376315791124
730.1779337450613770.3558674901227540.822066254938623
740.1529543248325970.3059086496651940.847045675167403
750.1369173777413520.2738347554827040.863082622258648
760.1800480144684540.3600960289369090.819951985531546
770.1607181417304250.3214362834608490.839281858269575
780.1393574045962290.2787148091924580.860642595403771
790.1394959174433440.2789918348866890.860504082556656
800.1289477271954190.2578954543908380.871052272804581
810.1102399018828830.2204798037657660.889760098117117
820.09347606461981090.1869521292396220.906523935380189
830.07987403718700420.1597480743740080.920125962812996
840.06738524025006540.1347704805001310.932614759749935
850.06661914325757070.1332382865151410.933380856742429
860.07905328469629190.1581065693925840.920946715303708
870.06542029044894120.1308405808978820.934579709551059
880.05402154606395530.1080430921279110.945978453936045
890.04573985672791060.09147971345582110.954260143272089
900.03981252106835170.07962504213670340.960187478931648
910.05621487790438690.1124297558087740.943785122095613
920.04764507380081790.09529014760163570.952354926199182
930.04253608744003440.08507217488006890.957463912559966
940.04217343181185380.08434686362370770.957826568188146
950.04483319050441370.08966638100882730.955166809495586
960.03923509214308720.07847018428617450.960764907856913
970.05180449249994760.1036089849998950.948195507500052
980.04263503011081350.0852700602216270.957364969889187
990.03757811401772840.07515622803545670.962421885982272
1000.04079625618535450.08159251237070890.959203743814646
1010.03514970201206520.07029940402413050.964850297987935
1020.02974425594974620.05948851189949240.970255744050254
1030.02409370297369330.04818740594738650.975906297026307
1040.0219165255936230.0438330511872460.978083474406377
1050.02244270070938240.04488540141876480.977557299290618
1060.01801071855893510.03602143711787020.981989281441065
1070.01429881792881750.0285976358576350.985701182071183
1080.01222549389145750.02445098778291490.987774506108543
1090.01835067846132730.03670135692265450.981649321538673
1100.01452924868566420.02905849737132850.985470751314336
1110.01561665770966290.03123331541932580.984383342290337
1120.01660346650743920.03320693301487840.983396533492561
1130.01366713150330630.02733426300661260.986332868496694
1140.01103742361960320.02207484723920640.988962576380397
1150.008708057810490870.01741611562098170.991291942189509
1160.009331829118965060.01866365823793010.990668170881035
1170.01415253040110680.02830506080221370.985847469598893
1180.01160586126081670.02321172252163340.988394138739183
1190.009146854906295510.0182937098125910.990853145093704
1200.007444903372427230.01488980674485450.992555096627573
1210.006996317629577110.01399263525915420.993003682370423
1220.006792382623116130.01358476524623230.993207617376884
1230.007457950344223910.01491590068844780.992542049655776
1240.007881190382914680.01576238076582940.992118809617085
1250.01298453707697870.02596907415395740.987015462923021
1260.01127197074535570.02254394149071130.988728029254644
1270.01004892557129620.02009785114259240.989951074428704
1280.01095801560008730.02191603120017470.989041984399913
1290.01049951219877740.02099902439755470.989500487801223
1300.01073711672843050.0214742334568610.98926288327157
1310.01333240213015330.02666480426030660.986667597869847
1320.0262862449487780.05257248989755590.973713755051222
1330.0257879976990390.0515759953980780.974212002300961
1340.02429055158746980.04858110317493950.97570944841253
1350.02155406495882740.04310812991765480.978445935041173
1360.01781517604839840.03563035209679680.982184823951602
1370.01435088093000610.02870176186001230.985649119069994
1380.01314590113767230.02629180227534460.986854098862328
1390.01182765164017150.02365530328034310.988172348359828
1400.009964917123203660.01992983424640730.990035082876796
1410.01722163207843250.03444326415686490.982778367921567
1420.01851571615136520.03703143230273040.981484283848635
1430.02747219849493650.05494439698987290.972527801505064
1440.02226519136148930.04453038272297860.977734808638511
1450.01790119003848880.03580238007697770.982098809961511
1460.01540344379099340.03080688758198690.984596556209007
1470.01872521927118290.03745043854236590.981274780728817
1480.01648682377017560.03297364754035120.983513176229824
1490.01379657654401820.02759315308803640.986203423455982
1500.01201512468902070.02403024937804130.987984875310979
1510.01521413725636830.03042827451273670.984785862743632
1520.01714349066379240.03428698132758480.982856509336208
1530.07001920085877380.1400384017175480.929980799141226
1540.06179522146383120.1235904429276620.938204778536169
1550.05257083533111770.1051416706622350.947429164668882
1560.1088451616130310.2176903232260630.891154838386969
1570.1437791667364250.2875583334728490.856220833263575
1580.1306962381917780.2613924763835560.869303761808222
1590.1163625428731130.2327250857462260.883637457126887
1600.1040417126853970.2080834253707940.895958287314603
1610.09184155443062540.1836831088612510.908158445569375
1620.07808121275462010.156162425509240.92191878724538
1630.07379482848401210.1475896569680240.926205171515988
1640.07484684176867170.1496936835373430.925153158231328
1650.07104174117488440.1420834823497690.928958258825116
1660.0604969939671920.1209939879343840.939503006032808
1670.05019510303342170.1003902060668430.949804896966578
1680.07363886656574150.1472777331314830.926361133434259
1690.07009394084089970.1401878816817990.9299060591591
1700.05953254238383190.1190650847676640.940467457616168
1710.1252368765918390.2504737531836770.874763123408161
1720.1070109688237860.2140219376475710.892989031176214
1730.09133732512950410.1826746502590080.908662674870496
1740.07809218477288580.1561843695457720.921907815227114
1750.1014041877784350.2028083755568710.898595812221565
1760.08648331997676550.1729666399535310.913516680023234
1770.08025092813184060.1605018562636810.919749071868159
1780.06746477628541520.134929552570830.932535223714585
1790.05622358838546540.1124471767709310.943776411614535
1800.04682733030526360.09365466061052720.953172669694736
1810.03836439650186650.0767287930037330.961635603498133
1820.04916665073902330.09833330147804660.950833349260977
1830.04776696996501710.09553393993003430.952233030034983
1840.04244373192533270.08488746385066540.957556268074667
1850.1671574844645630.3343149689291270.832842515535437
1860.1517016111872480.3034032223744950.848298388812752
1870.1331384578598820.2662769157197630.866861542140118
1880.1338554455888310.2677108911776610.866144554411169
1890.1232904829391690.2465809658783380.876709517060831
1900.2052823288293760.4105646576587530.794717671170624
1910.2048127682542910.4096255365085820.795187231745709
1920.1779042187188130.3558084374376260.822095781281187
1930.5824492941397360.8351014117205280.417550705860264
1940.5661077871819490.8677844256361030.433892212818051
1950.5245012648154010.9509974703691980.475498735184599
1960.4878362713924830.9756725427849660.512163728607517
1970.5204493152376270.9591013695247470.479550684762373
1980.4793666357308920.9587332714617850.520633364269107
1990.4749258294133540.9498516588267070.525074170586646
2000.4563823165067780.9127646330135560.543617683493222
2010.4169563038950670.8339126077901340.583043696104933
2020.3810773666253350.762154733250670.618922633374665
2030.3480643976946470.6961287953892940.651935602305353
2040.3776973644399980.7553947288799970.622302635560002
2050.4226262366476760.8452524732953520.577373763352324
2060.3791250581743980.7582501163487960.620874941825602
2070.3447958140970590.6895916281941180.655204185902941
2080.307171397543020.614342795086040.69282860245698
2090.280607709613160.5612154192263210.71939229038684
2100.2455611052878280.4911222105756560.754438894712172
2110.2856269313349830.5712538626699650.714373068665017
2120.2972479639312280.5944959278624570.702752036068772
2130.2576162531225540.5152325062451090.742383746877446
2140.2825137806706590.5650275613413190.717486219329341
2150.2473442191723810.4946884383447620.752655780827619
2160.2117207647466240.4234415294932480.788279235253376
2170.1812161682717150.3624323365434310.818783831728285
2180.1522372037718390.3044744075436780.847762796228161
2190.1610425940984840.3220851881969670.838957405901516
2200.1367106948247460.2734213896494920.863289305175254
2210.1609342376121190.3218684752242380.839065762387881
2220.131412000866390.2628240017327790.868587999133611
2230.1222914819571580.2445829639143170.877708518042842
2240.1023597458057320.2047194916114640.897640254194268
2250.0810692204962170.1621384409924340.918930779503783
2260.06355626201412540.1271125240282510.936443737985875
2270.04932539135814370.09865078271628740.950674608641856
2280.03755290108115740.07510580216231470.962447098918843
2290.0277364355412780.05547287108255610.972263564458722
2300.02041655225769220.04083310451538450.979583447742308
2310.02949405475724830.05898810951449650.970505945242752
2320.03788781971082280.07577563942164570.962112180289177
2330.1700048727066290.3400097454132590.829995127293371
2340.1467513087941440.2935026175882880.853248691205856
2350.1133636468093480.2267272936186970.886636353190652
2360.1091058461294790.2182116922589590.890894153870521
2370.1372115161846810.2744230323693620.862788483815319
2380.1620320967219450.324064193443890.837967903278055
2390.1814297632286110.3628595264572220.818570236771389
2400.1681078836134240.3362157672268480.831892116386576
2410.1704880372743350.3409760745486690.829511962725665
2420.6099553146555370.7800893706889260.390044685344463
2430.6672431821680.6655136356640.332756817832
2440.6324520255037210.7350959489925580.367547974496279
2450.5603629084771190.8792741830457620.439637091522881
2460.4580005912747740.9160011825495480.541999408725226
2470.3622911575431260.7245823150862530.637708842456874
2480.2758787984365560.5517575968731120.724121201563444
2490.1883467821487510.3766935642975020.811653217851249
2500.2340091006420010.4680182012840030.765990899357999
2510.1686580925255870.3373161850511740.831341907474413

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.996070085890513 & 0.00785982821897461 & 0.0039299141094873 \tabularnewline
14 & 0.9944104396165 & 0.0111791207669996 & 0.00558956038349982 \tabularnewline
15 & 0.990357101093835 & 0.0192857978123301 & 0.00964289890616503 \tabularnewline
16 & 0.985904923821373 & 0.0281901523572548 & 0.0140950761786274 \tabularnewline
17 & 0.974704347274883 & 0.0505913054502345 & 0.0252956527251172 \tabularnewline
18 & 0.972064845062283 & 0.0558703098754342 & 0.0279351549377171 \tabularnewline
19 & 0.962069875508128 & 0.0758602489837442 & 0.0379301244918721 \tabularnewline
20 & 0.941283314725513 & 0.117433370548975 & 0.0587166852744875 \tabularnewline
21 & 0.918028269692177 & 0.163943460615646 & 0.0819717303078231 \tabularnewline
22 & 0.891081779578013 & 0.217836440843975 & 0.108918220421987 \tabularnewline
23 & 0.861945474343341 & 0.276109051313318 & 0.138054525656659 \tabularnewline
24 & 0.829339395482319 & 0.341321209035363 & 0.170660604517681 \tabularnewline
25 & 0.793946078431661 & 0.412107843136679 & 0.206053921568339 \tabularnewline
26 & 0.790648948349788 & 0.418702103300425 & 0.209351051650212 \tabularnewline
27 & 0.80215946980409 & 0.395681060391819 & 0.19784053019591 \tabularnewline
28 & 0.803763510622972 & 0.392472978754056 & 0.196236489377028 \tabularnewline
29 & 0.754001110743693 & 0.491997778512614 & 0.245998889256307 \tabularnewline
30 & 0.71780205300753 & 0.56439589398494 & 0.28219794699247 \tabularnewline
31 & 0.66915577234291 & 0.66168845531418 & 0.33084422765709 \tabularnewline
32 & 0.686294826815393 & 0.627410346369214 & 0.313705173184607 \tabularnewline
33 & 0.629774820375707 & 0.740450359248586 & 0.370225179624293 \tabularnewline
34 & 0.572970924432718 & 0.854058151134564 & 0.427029075567282 \tabularnewline
35 & 0.55450820956673 & 0.89098358086654 & 0.44549179043327 \tabularnewline
36 & 0.541379294316972 & 0.917241411366055 & 0.458620705683028 \tabularnewline
37 & 0.483971618137872 & 0.967943236275744 & 0.516028381862128 \tabularnewline
38 & 0.465457456262544 & 0.930914912525087 & 0.534542543737456 \tabularnewline
39 & 0.443503933012986 & 0.887007866025973 & 0.556496066987014 \tabularnewline
40 & 0.412731703680026 & 0.825463407360052 & 0.587268296319974 \tabularnewline
41 & 0.374617132237804 & 0.749234264475608 & 0.625382867762196 \tabularnewline
42 & 0.343910732618443 & 0.687821465236885 & 0.656089267381557 \tabularnewline
43 & 0.392552919247469 & 0.785105838494937 & 0.607447080752531 \tabularnewline
44 & 0.346645718798011 & 0.693291437596023 & 0.653354281201988 \tabularnewline
45 & 0.300287793278162 & 0.600575586556324 & 0.699712206721838 \tabularnewline
46 & 0.336356212935375 & 0.67271242587075 & 0.663643787064625 \tabularnewline
47 & 0.338441893954848 & 0.676883787909696 & 0.661558106045152 \tabularnewline
48 & 0.2969789785358 & 0.593957957071601 & 0.7030210214642 \tabularnewline
49 & 0.297017733679792 & 0.594035467359584 & 0.702982266320208 \tabularnewline
50 & 0.272246998757864 & 0.544493997515728 & 0.727753001242136 \tabularnewline
51 & 0.269452834434003 & 0.538905668868007 & 0.730547165565997 \tabularnewline
52 & 0.234319872563754 & 0.468639745127508 & 0.765680127436246 \tabularnewline
53 & 0.231109019765558 & 0.462218039531116 & 0.768890980234442 \tabularnewline
54 & 0.199381697353121 & 0.398763394706241 & 0.800618302646879 \tabularnewline
55 & 0.301057737762856 & 0.602115475525713 & 0.698942262237144 \tabularnewline
56 & 0.619997246980685 & 0.76000550603863 & 0.380002753019315 \tabularnewline
57 & 0.577618892043839 & 0.844762215912323 & 0.422381107956162 \tabularnewline
58 & 0.533706364414485 & 0.932587271171029 & 0.466293635585514 \tabularnewline
59 & 0.491198656091341 & 0.982397312182682 & 0.508801343908659 \tabularnewline
60 & 0.487218460743589 & 0.974436921487178 & 0.512781539256411 \tabularnewline
61 & 0.495898534906367 & 0.991797069812734 & 0.504101465093633 \tabularnewline
62 & 0.454151568815401 & 0.908303137630802 & 0.545848431184599 \tabularnewline
63 & 0.465507781133101 & 0.931015562266203 & 0.534492218866899 \tabularnewline
64 & 0.42395982829498 & 0.84791965658996 & 0.57604017170502 \tabularnewline
65 & 0.39391353085766 & 0.787827061715319 & 0.60608646914234 \tabularnewline
66 & 0.352532328202667 & 0.705064656405333 & 0.647467671797334 \tabularnewline
67 & 0.319173380759271 & 0.638346761518541 & 0.680826619240729 \tabularnewline
68 & 0.305833401207103 & 0.611666802414205 & 0.694166598792897 \tabularnewline
69 & 0.286172956833456 & 0.572345913666913 & 0.713827043166544 \tabularnewline
70 & 0.254943759327095 & 0.509887518654189 & 0.745056240672905 \tabularnewline
71 & 0.235799169523494 & 0.471598339046989 & 0.764200830476506 \tabularnewline
72 & 0.205623684208876 & 0.411247368417753 & 0.794376315791124 \tabularnewline
73 & 0.177933745061377 & 0.355867490122754 & 0.822066254938623 \tabularnewline
74 & 0.152954324832597 & 0.305908649665194 & 0.847045675167403 \tabularnewline
75 & 0.136917377741352 & 0.273834755482704 & 0.863082622258648 \tabularnewline
76 & 0.180048014468454 & 0.360096028936909 & 0.819951985531546 \tabularnewline
77 & 0.160718141730425 & 0.321436283460849 & 0.839281858269575 \tabularnewline
78 & 0.139357404596229 & 0.278714809192458 & 0.860642595403771 \tabularnewline
79 & 0.139495917443344 & 0.278991834886689 & 0.860504082556656 \tabularnewline
80 & 0.128947727195419 & 0.257895454390838 & 0.871052272804581 \tabularnewline
81 & 0.110239901882883 & 0.220479803765766 & 0.889760098117117 \tabularnewline
82 & 0.0934760646198109 & 0.186952129239622 & 0.906523935380189 \tabularnewline
83 & 0.0798740371870042 & 0.159748074374008 & 0.920125962812996 \tabularnewline
84 & 0.0673852402500654 & 0.134770480500131 & 0.932614759749935 \tabularnewline
85 & 0.0666191432575707 & 0.133238286515141 & 0.933380856742429 \tabularnewline
86 & 0.0790532846962919 & 0.158106569392584 & 0.920946715303708 \tabularnewline
87 & 0.0654202904489412 & 0.130840580897882 & 0.934579709551059 \tabularnewline
88 & 0.0540215460639553 & 0.108043092127911 & 0.945978453936045 \tabularnewline
89 & 0.0457398567279106 & 0.0914797134558211 & 0.954260143272089 \tabularnewline
90 & 0.0398125210683517 & 0.0796250421367034 & 0.960187478931648 \tabularnewline
91 & 0.0562148779043869 & 0.112429755808774 & 0.943785122095613 \tabularnewline
92 & 0.0476450738008179 & 0.0952901476016357 & 0.952354926199182 \tabularnewline
93 & 0.0425360874400344 & 0.0850721748800689 & 0.957463912559966 \tabularnewline
94 & 0.0421734318118538 & 0.0843468636237077 & 0.957826568188146 \tabularnewline
95 & 0.0448331905044137 & 0.0896663810088273 & 0.955166809495586 \tabularnewline
96 & 0.0392350921430872 & 0.0784701842861745 & 0.960764907856913 \tabularnewline
97 & 0.0518044924999476 & 0.103608984999895 & 0.948195507500052 \tabularnewline
98 & 0.0426350301108135 & 0.085270060221627 & 0.957364969889187 \tabularnewline
99 & 0.0375781140177284 & 0.0751562280354567 & 0.962421885982272 \tabularnewline
100 & 0.0407962561853545 & 0.0815925123707089 & 0.959203743814646 \tabularnewline
101 & 0.0351497020120652 & 0.0702994040241305 & 0.964850297987935 \tabularnewline
102 & 0.0297442559497462 & 0.0594885118994924 & 0.970255744050254 \tabularnewline
103 & 0.0240937029736933 & 0.0481874059473865 & 0.975906297026307 \tabularnewline
104 & 0.021916525593623 & 0.043833051187246 & 0.978083474406377 \tabularnewline
105 & 0.0224427007093824 & 0.0448854014187648 & 0.977557299290618 \tabularnewline
106 & 0.0180107185589351 & 0.0360214371178702 & 0.981989281441065 \tabularnewline
107 & 0.0142988179288175 & 0.028597635857635 & 0.985701182071183 \tabularnewline
108 & 0.0122254938914575 & 0.0244509877829149 & 0.987774506108543 \tabularnewline
109 & 0.0183506784613273 & 0.0367013569226545 & 0.981649321538673 \tabularnewline
110 & 0.0145292486856642 & 0.0290584973713285 & 0.985470751314336 \tabularnewline
111 & 0.0156166577096629 & 0.0312333154193258 & 0.984383342290337 \tabularnewline
112 & 0.0166034665074392 & 0.0332069330148784 & 0.983396533492561 \tabularnewline
113 & 0.0136671315033063 & 0.0273342630066126 & 0.986332868496694 \tabularnewline
114 & 0.0110374236196032 & 0.0220748472392064 & 0.988962576380397 \tabularnewline
115 & 0.00870805781049087 & 0.0174161156209817 & 0.991291942189509 \tabularnewline
116 & 0.00933182911896506 & 0.0186636582379301 & 0.990668170881035 \tabularnewline
117 & 0.0141525304011068 & 0.0283050608022137 & 0.985847469598893 \tabularnewline
118 & 0.0116058612608167 & 0.0232117225216334 & 0.988394138739183 \tabularnewline
119 & 0.00914685490629551 & 0.018293709812591 & 0.990853145093704 \tabularnewline
120 & 0.00744490337242723 & 0.0148898067448545 & 0.992555096627573 \tabularnewline
121 & 0.00699631762957711 & 0.0139926352591542 & 0.993003682370423 \tabularnewline
122 & 0.00679238262311613 & 0.0135847652462323 & 0.993207617376884 \tabularnewline
123 & 0.00745795034422391 & 0.0149159006884478 & 0.992542049655776 \tabularnewline
124 & 0.00788119038291468 & 0.0157623807658294 & 0.992118809617085 \tabularnewline
125 & 0.0129845370769787 & 0.0259690741539574 & 0.987015462923021 \tabularnewline
126 & 0.0112719707453557 & 0.0225439414907113 & 0.988728029254644 \tabularnewline
127 & 0.0100489255712962 & 0.0200978511425924 & 0.989951074428704 \tabularnewline
128 & 0.0109580156000873 & 0.0219160312001747 & 0.989041984399913 \tabularnewline
129 & 0.0104995121987774 & 0.0209990243975547 & 0.989500487801223 \tabularnewline
130 & 0.0107371167284305 & 0.021474233456861 & 0.98926288327157 \tabularnewline
131 & 0.0133324021301533 & 0.0266648042603066 & 0.986667597869847 \tabularnewline
132 & 0.026286244948778 & 0.0525724898975559 & 0.973713755051222 \tabularnewline
133 & 0.025787997699039 & 0.051575995398078 & 0.974212002300961 \tabularnewline
134 & 0.0242905515874698 & 0.0485811031749395 & 0.97570944841253 \tabularnewline
135 & 0.0215540649588274 & 0.0431081299176548 & 0.978445935041173 \tabularnewline
136 & 0.0178151760483984 & 0.0356303520967968 & 0.982184823951602 \tabularnewline
137 & 0.0143508809300061 & 0.0287017618600123 & 0.985649119069994 \tabularnewline
138 & 0.0131459011376723 & 0.0262918022753446 & 0.986854098862328 \tabularnewline
139 & 0.0118276516401715 & 0.0236553032803431 & 0.988172348359828 \tabularnewline
140 & 0.00996491712320366 & 0.0199298342464073 & 0.990035082876796 \tabularnewline
141 & 0.0172216320784325 & 0.0344432641568649 & 0.982778367921567 \tabularnewline
142 & 0.0185157161513652 & 0.0370314323027304 & 0.981484283848635 \tabularnewline
143 & 0.0274721984949365 & 0.0549443969898729 & 0.972527801505064 \tabularnewline
144 & 0.0222651913614893 & 0.0445303827229786 & 0.977734808638511 \tabularnewline
145 & 0.0179011900384888 & 0.0358023800769777 & 0.982098809961511 \tabularnewline
146 & 0.0154034437909934 & 0.0308068875819869 & 0.984596556209007 \tabularnewline
147 & 0.0187252192711829 & 0.0374504385423659 & 0.981274780728817 \tabularnewline
148 & 0.0164868237701756 & 0.0329736475403512 & 0.983513176229824 \tabularnewline
149 & 0.0137965765440182 & 0.0275931530880364 & 0.986203423455982 \tabularnewline
150 & 0.0120151246890207 & 0.0240302493780413 & 0.987984875310979 \tabularnewline
151 & 0.0152141372563683 & 0.0304282745127367 & 0.984785862743632 \tabularnewline
152 & 0.0171434906637924 & 0.0342869813275848 & 0.982856509336208 \tabularnewline
153 & 0.0700192008587738 & 0.140038401717548 & 0.929980799141226 \tabularnewline
154 & 0.0617952214638312 & 0.123590442927662 & 0.938204778536169 \tabularnewline
155 & 0.0525708353311177 & 0.105141670662235 & 0.947429164668882 \tabularnewline
156 & 0.108845161613031 & 0.217690323226063 & 0.891154838386969 \tabularnewline
157 & 0.143779166736425 & 0.287558333472849 & 0.856220833263575 \tabularnewline
158 & 0.130696238191778 & 0.261392476383556 & 0.869303761808222 \tabularnewline
159 & 0.116362542873113 & 0.232725085746226 & 0.883637457126887 \tabularnewline
160 & 0.104041712685397 & 0.208083425370794 & 0.895958287314603 \tabularnewline
161 & 0.0918415544306254 & 0.183683108861251 & 0.908158445569375 \tabularnewline
162 & 0.0780812127546201 & 0.15616242550924 & 0.92191878724538 \tabularnewline
163 & 0.0737948284840121 & 0.147589656968024 & 0.926205171515988 \tabularnewline
164 & 0.0748468417686717 & 0.149693683537343 & 0.925153158231328 \tabularnewline
165 & 0.0710417411748844 & 0.142083482349769 & 0.928958258825116 \tabularnewline
166 & 0.060496993967192 & 0.120993987934384 & 0.939503006032808 \tabularnewline
167 & 0.0501951030334217 & 0.100390206066843 & 0.949804896966578 \tabularnewline
168 & 0.0736388665657415 & 0.147277733131483 & 0.926361133434259 \tabularnewline
169 & 0.0700939408408997 & 0.140187881681799 & 0.9299060591591 \tabularnewline
170 & 0.0595325423838319 & 0.119065084767664 & 0.940467457616168 \tabularnewline
171 & 0.125236876591839 & 0.250473753183677 & 0.874763123408161 \tabularnewline
172 & 0.107010968823786 & 0.214021937647571 & 0.892989031176214 \tabularnewline
173 & 0.0913373251295041 & 0.182674650259008 & 0.908662674870496 \tabularnewline
174 & 0.0780921847728858 & 0.156184369545772 & 0.921907815227114 \tabularnewline
175 & 0.101404187778435 & 0.202808375556871 & 0.898595812221565 \tabularnewline
176 & 0.0864833199767655 & 0.172966639953531 & 0.913516680023234 \tabularnewline
177 & 0.0802509281318406 & 0.160501856263681 & 0.919749071868159 \tabularnewline
178 & 0.0674647762854152 & 0.13492955257083 & 0.932535223714585 \tabularnewline
179 & 0.0562235883854654 & 0.112447176770931 & 0.943776411614535 \tabularnewline
180 & 0.0468273303052636 & 0.0936546606105272 & 0.953172669694736 \tabularnewline
181 & 0.0383643965018665 & 0.076728793003733 & 0.961635603498133 \tabularnewline
182 & 0.0491666507390233 & 0.0983333014780466 & 0.950833349260977 \tabularnewline
183 & 0.0477669699650171 & 0.0955339399300343 & 0.952233030034983 \tabularnewline
184 & 0.0424437319253327 & 0.0848874638506654 & 0.957556268074667 \tabularnewline
185 & 0.167157484464563 & 0.334314968929127 & 0.832842515535437 \tabularnewline
186 & 0.151701611187248 & 0.303403222374495 & 0.848298388812752 \tabularnewline
187 & 0.133138457859882 & 0.266276915719763 & 0.866861542140118 \tabularnewline
188 & 0.133855445588831 & 0.267710891177661 & 0.866144554411169 \tabularnewline
189 & 0.123290482939169 & 0.246580965878338 & 0.876709517060831 \tabularnewline
190 & 0.205282328829376 & 0.410564657658753 & 0.794717671170624 \tabularnewline
191 & 0.204812768254291 & 0.409625536508582 & 0.795187231745709 \tabularnewline
192 & 0.177904218718813 & 0.355808437437626 & 0.822095781281187 \tabularnewline
193 & 0.582449294139736 & 0.835101411720528 & 0.417550705860264 \tabularnewline
194 & 0.566107787181949 & 0.867784425636103 & 0.433892212818051 \tabularnewline
195 & 0.524501264815401 & 0.950997470369198 & 0.475498735184599 \tabularnewline
196 & 0.487836271392483 & 0.975672542784966 & 0.512163728607517 \tabularnewline
197 & 0.520449315237627 & 0.959101369524747 & 0.479550684762373 \tabularnewline
198 & 0.479366635730892 & 0.958733271461785 & 0.520633364269107 \tabularnewline
199 & 0.474925829413354 & 0.949851658826707 & 0.525074170586646 \tabularnewline
200 & 0.456382316506778 & 0.912764633013556 & 0.543617683493222 \tabularnewline
201 & 0.416956303895067 & 0.833912607790134 & 0.583043696104933 \tabularnewline
202 & 0.381077366625335 & 0.76215473325067 & 0.618922633374665 \tabularnewline
203 & 0.348064397694647 & 0.696128795389294 & 0.651935602305353 \tabularnewline
204 & 0.377697364439998 & 0.755394728879997 & 0.622302635560002 \tabularnewline
205 & 0.422626236647676 & 0.845252473295352 & 0.577373763352324 \tabularnewline
206 & 0.379125058174398 & 0.758250116348796 & 0.620874941825602 \tabularnewline
207 & 0.344795814097059 & 0.689591628194118 & 0.655204185902941 \tabularnewline
208 & 0.30717139754302 & 0.61434279508604 & 0.69282860245698 \tabularnewline
209 & 0.28060770961316 & 0.561215419226321 & 0.71939229038684 \tabularnewline
210 & 0.245561105287828 & 0.491122210575656 & 0.754438894712172 \tabularnewline
211 & 0.285626931334983 & 0.571253862669965 & 0.714373068665017 \tabularnewline
212 & 0.297247963931228 & 0.594495927862457 & 0.702752036068772 \tabularnewline
213 & 0.257616253122554 & 0.515232506245109 & 0.742383746877446 \tabularnewline
214 & 0.282513780670659 & 0.565027561341319 & 0.717486219329341 \tabularnewline
215 & 0.247344219172381 & 0.494688438344762 & 0.752655780827619 \tabularnewline
216 & 0.211720764746624 & 0.423441529493248 & 0.788279235253376 \tabularnewline
217 & 0.181216168271715 & 0.362432336543431 & 0.818783831728285 \tabularnewline
218 & 0.152237203771839 & 0.304474407543678 & 0.847762796228161 \tabularnewline
219 & 0.161042594098484 & 0.322085188196967 & 0.838957405901516 \tabularnewline
220 & 0.136710694824746 & 0.273421389649492 & 0.863289305175254 \tabularnewline
221 & 0.160934237612119 & 0.321868475224238 & 0.839065762387881 \tabularnewline
222 & 0.13141200086639 & 0.262824001732779 & 0.868587999133611 \tabularnewline
223 & 0.122291481957158 & 0.244582963914317 & 0.877708518042842 \tabularnewline
224 & 0.102359745805732 & 0.204719491611464 & 0.897640254194268 \tabularnewline
225 & 0.081069220496217 & 0.162138440992434 & 0.918930779503783 \tabularnewline
226 & 0.0635562620141254 & 0.127112524028251 & 0.936443737985875 \tabularnewline
227 & 0.0493253913581437 & 0.0986507827162874 & 0.950674608641856 \tabularnewline
228 & 0.0375529010811574 & 0.0751058021623147 & 0.962447098918843 \tabularnewline
229 & 0.027736435541278 & 0.0554728710825561 & 0.972263564458722 \tabularnewline
230 & 0.0204165522576922 & 0.0408331045153845 & 0.979583447742308 \tabularnewline
231 & 0.0294940547572483 & 0.0589881095144965 & 0.970505945242752 \tabularnewline
232 & 0.0378878197108228 & 0.0757756394216457 & 0.962112180289177 \tabularnewline
233 & 0.170004872706629 & 0.340009745413259 & 0.829995127293371 \tabularnewline
234 & 0.146751308794144 & 0.293502617588288 & 0.853248691205856 \tabularnewline
235 & 0.113363646809348 & 0.226727293618697 & 0.886636353190652 \tabularnewline
236 & 0.109105846129479 & 0.218211692258959 & 0.890894153870521 \tabularnewline
237 & 0.137211516184681 & 0.274423032369362 & 0.862788483815319 \tabularnewline
238 & 0.162032096721945 & 0.32406419344389 & 0.837967903278055 \tabularnewline
239 & 0.181429763228611 & 0.362859526457222 & 0.818570236771389 \tabularnewline
240 & 0.168107883613424 & 0.336215767226848 & 0.831892116386576 \tabularnewline
241 & 0.170488037274335 & 0.340976074548669 & 0.829511962725665 \tabularnewline
242 & 0.609955314655537 & 0.780089370688926 & 0.390044685344463 \tabularnewline
243 & 0.667243182168 & 0.665513635664 & 0.332756817832 \tabularnewline
244 & 0.632452025503721 & 0.735095948992558 & 0.367547974496279 \tabularnewline
245 & 0.560362908477119 & 0.879274183045762 & 0.439637091522881 \tabularnewline
246 & 0.458000591274774 & 0.916001182549548 & 0.541999408725226 \tabularnewline
247 & 0.362291157543126 & 0.724582315086253 & 0.637708842456874 \tabularnewline
248 & 0.275878798436556 & 0.551757596873112 & 0.724121201563444 \tabularnewline
249 & 0.188346782148751 & 0.376693564297502 & 0.811653217851249 \tabularnewline
250 & 0.234009100642001 & 0.468018201284003 & 0.765990899357999 \tabularnewline
251 & 0.168658092525587 & 0.337316185051174 & 0.831341907474413 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190281&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]0.996070085890513[/C][C]0.00785982821897461[/C][C]0.0039299141094873[/C][/ROW]
[ROW][C]14[/C][C]0.9944104396165[/C][C]0.0111791207669996[/C][C]0.00558956038349982[/C][/ROW]
[ROW][C]15[/C][C]0.990357101093835[/C][C]0.0192857978123301[/C][C]0.00964289890616503[/C][/ROW]
[ROW][C]16[/C][C]0.985904923821373[/C][C]0.0281901523572548[/C][C]0.0140950761786274[/C][/ROW]
[ROW][C]17[/C][C]0.974704347274883[/C][C]0.0505913054502345[/C][C]0.0252956527251172[/C][/ROW]
[ROW][C]18[/C][C]0.972064845062283[/C][C]0.0558703098754342[/C][C]0.0279351549377171[/C][/ROW]
[ROW][C]19[/C][C]0.962069875508128[/C][C]0.0758602489837442[/C][C]0.0379301244918721[/C][/ROW]
[ROW][C]20[/C][C]0.941283314725513[/C][C]0.117433370548975[/C][C]0.0587166852744875[/C][/ROW]
[ROW][C]21[/C][C]0.918028269692177[/C][C]0.163943460615646[/C][C]0.0819717303078231[/C][/ROW]
[ROW][C]22[/C][C]0.891081779578013[/C][C]0.217836440843975[/C][C]0.108918220421987[/C][/ROW]
[ROW][C]23[/C][C]0.861945474343341[/C][C]0.276109051313318[/C][C]0.138054525656659[/C][/ROW]
[ROW][C]24[/C][C]0.829339395482319[/C][C]0.341321209035363[/C][C]0.170660604517681[/C][/ROW]
[ROW][C]25[/C][C]0.793946078431661[/C][C]0.412107843136679[/C][C]0.206053921568339[/C][/ROW]
[ROW][C]26[/C][C]0.790648948349788[/C][C]0.418702103300425[/C][C]0.209351051650212[/C][/ROW]
[ROW][C]27[/C][C]0.80215946980409[/C][C]0.395681060391819[/C][C]0.19784053019591[/C][/ROW]
[ROW][C]28[/C][C]0.803763510622972[/C][C]0.392472978754056[/C][C]0.196236489377028[/C][/ROW]
[ROW][C]29[/C][C]0.754001110743693[/C][C]0.491997778512614[/C][C]0.245998889256307[/C][/ROW]
[ROW][C]30[/C][C]0.71780205300753[/C][C]0.56439589398494[/C][C]0.28219794699247[/C][/ROW]
[ROW][C]31[/C][C]0.66915577234291[/C][C]0.66168845531418[/C][C]0.33084422765709[/C][/ROW]
[ROW][C]32[/C][C]0.686294826815393[/C][C]0.627410346369214[/C][C]0.313705173184607[/C][/ROW]
[ROW][C]33[/C][C]0.629774820375707[/C][C]0.740450359248586[/C][C]0.370225179624293[/C][/ROW]
[ROW][C]34[/C][C]0.572970924432718[/C][C]0.854058151134564[/C][C]0.427029075567282[/C][/ROW]
[ROW][C]35[/C][C]0.55450820956673[/C][C]0.89098358086654[/C][C]0.44549179043327[/C][/ROW]
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[ROW][C]37[/C][C]0.483971618137872[/C][C]0.967943236275744[/C][C]0.516028381862128[/C][/ROW]
[ROW][C]38[/C][C]0.465457456262544[/C][C]0.930914912525087[/C][C]0.534542543737456[/C][/ROW]
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[ROW][C]110[/C][C]0.0145292486856642[/C][C]0.0290584973713285[/C][C]0.985470751314336[/C][/ROW]
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[ROW][C]112[/C][C]0.0166034665074392[/C][C]0.0332069330148784[/C][C]0.983396533492561[/C][/ROW]
[ROW][C]113[/C][C]0.0136671315033063[/C][C]0.0273342630066126[/C][C]0.986332868496694[/C][/ROW]
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[ROW][C]115[/C][C]0.00870805781049087[/C][C]0.0174161156209817[/C][C]0.991291942189509[/C][/ROW]
[ROW][C]116[/C][C]0.00933182911896506[/C][C]0.0186636582379301[/C][C]0.990668170881035[/C][/ROW]
[ROW][C]117[/C][C]0.0141525304011068[/C][C]0.0283050608022137[/C][C]0.985847469598893[/C][/ROW]
[ROW][C]118[/C][C]0.0116058612608167[/C][C]0.0232117225216334[/C][C]0.988394138739183[/C][/ROW]
[ROW][C]119[/C][C]0.00914685490629551[/C][C]0.018293709812591[/C][C]0.990853145093704[/C][/ROW]
[ROW][C]120[/C][C]0.00744490337242723[/C][C]0.0148898067448545[/C][C]0.992555096627573[/C][/ROW]
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[ROW][C]124[/C][C]0.00788119038291468[/C][C]0.0157623807658294[/C][C]0.992118809617085[/C][/ROW]
[ROW][C]125[/C][C]0.0129845370769787[/C][C]0.0259690741539574[/C][C]0.987015462923021[/C][/ROW]
[ROW][C]126[/C][C]0.0112719707453557[/C][C]0.0225439414907113[/C][C]0.988728029254644[/C][/ROW]
[ROW][C]127[/C][C]0.0100489255712962[/C][C]0.0200978511425924[/C][C]0.989951074428704[/C][/ROW]
[ROW][C]128[/C][C]0.0109580156000873[/C][C]0.0219160312001747[/C][C]0.989041984399913[/C][/ROW]
[ROW][C]129[/C][C]0.0104995121987774[/C][C]0.0209990243975547[/C][C]0.989500487801223[/C][/ROW]
[ROW][C]130[/C][C]0.0107371167284305[/C][C]0.021474233456861[/C][C]0.98926288327157[/C][/ROW]
[ROW][C]131[/C][C]0.0133324021301533[/C][C]0.0266648042603066[/C][C]0.986667597869847[/C][/ROW]
[ROW][C]132[/C][C]0.026286244948778[/C][C]0.0525724898975559[/C][C]0.973713755051222[/C][/ROW]
[ROW][C]133[/C][C]0.025787997699039[/C][C]0.051575995398078[/C][C]0.974212002300961[/C][/ROW]
[ROW][C]134[/C][C]0.0242905515874698[/C][C]0.0485811031749395[/C][C]0.97570944841253[/C][/ROW]
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[ROW][C]137[/C][C]0.0143508809300061[/C][C]0.0287017618600123[/C][C]0.985649119069994[/C][/ROW]
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[ROW][C]162[/C][C]0.0780812127546201[/C][C]0.15616242550924[/C][C]0.92191878724538[/C][/ROW]
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[ROW][C]164[/C][C]0.0748468417686717[/C][C]0.149693683537343[/C][C]0.925153158231328[/C][/ROW]
[ROW][C]165[/C][C]0.0710417411748844[/C][C]0.142083482349769[/C][C]0.928958258825116[/C][/ROW]
[ROW][C]166[/C][C]0.060496993967192[/C][C]0.120993987934384[/C][C]0.939503006032808[/C][/ROW]
[ROW][C]167[/C][C]0.0501951030334217[/C][C]0.100390206066843[/C][C]0.949804896966578[/C][/ROW]
[ROW][C]168[/C][C]0.0736388665657415[/C][C]0.147277733131483[/C][C]0.926361133434259[/C][/ROW]
[ROW][C]169[/C][C]0.0700939408408997[/C][C]0.140187881681799[/C][C]0.9299060591591[/C][/ROW]
[ROW][C]170[/C][C]0.0595325423838319[/C][C]0.119065084767664[/C][C]0.940467457616168[/C][/ROW]
[ROW][C]171[/C][C]0.125236876591839[/C][C]0.250473753183677[/C][C]0.874763123408161[/C][/ROW]
[ROW][C]172[/C][C]0.107010968823786[/C][C]0.214021937647571[/C][C]0.892989031176214[/C][/ROW]
[ROW][C]173[/C][C]0.0913373251295041[/C][C]0.182674650259008[/C][C]0.908662674870496[/C][/ROW]
[ROW][C]174[/C][C]0.0780921847728858[/C][C]0.156184369545772[/C][C]0.921907815227114[/C][/ROW]
[ROW][C]175[/C][C]0.101404187778435[/C][C]0.202808375556871[/C][C]0.898595812221565[/C][/ROW]
[ROW][C]176[/C][C]0.0864833199767655[/C][C]0.172966639953531[/C][C]0.913516680023234[/C][/ROW]
[ROW][C]177[/C][C]0.0802509281318406[/C][C]0.160501856263681[/C][C]0.919749071868159[/C][/ROW]
[ROW][C]178[/C][C]0.0674647762854152[/C][C]0.13492955257083[/C][C]0.932535223714585[/C][/ROW]
[ROW][C]179[/C][C]0.0562235883854654[/C][C]0.112447176770931[/C][C]0.943776411614535[/C][/ROW]
[ROW][C]180[/C][C]0.0468273303052636[/C][C]0.0936546606105272[/C][C]0.953172669694736[/C][/ROW]
[ROW][C]181[/C][C]0.0383643965018665[/C][C]0.076728793003733[/C][C]0.961635603498133[/C][/ROW]
[ROW][C]182[/C][C]0.0491666507390233[/C][C]0.0983333014780466[/C][C]0.950833349260977[/C][/ROW]
[ROW][C]183[/C][C]0.0477669699650171[/C][C]0.0955339399300343[/C][C]0.952233030034983[/C][/ROW]
[ROW][C]184[/C][C]0.0424437319253327[/C][C]0.0848874638506654[/C][C]0.957556268074667[/C][/ROW]
[ROW][C]185[/C][C]0.167157484464563[/C][C]0.334314968929127[/C][C]0.832842515535437[/C][/ROW]
[ROW][C]186[/C][C]0.151701611187248[/C][C]0.303403222374495[/C][C]0.848298388812752[/C][/ROW]
[ROW][C]187[/C][C]0.133138457859882[/C][C]0.266276915719763[/C][C]0.866861542140118[/C][/ROW]
[ROW][C]188[/C][C]0.133855445588831[/C][C]0.267710891177661[/C][C]0.866144554411169[/C][/ROW]
[ROW][C]189[/C][C]0.123290482939169[/C][C]0.246580965878338[/C][C]0.876709517060831[/C][/ROW]
[ROW][C]190[/C][C]0.205282328829376[/C][C]0.410564657658753[/C][C]0.794717671170624[/C][/ROW]
[ROW][C]191[/C][C]0.204812768254291[/C][C]0.409625536508582[/C][C]0.795187231745709[/C][/ROW]
[ROW][C]192[/C][C]0.177904218718813[/C][C]0.355808437437626[/C][C]0.822095781281187[/C][/ROW]
[ROW][C]193[/C][C]0.582449294139736[/C][C]0.835101411720528[/C][C]0.417550705860264[/C][/ROW]
[ROW][C]194[/C][C]0.566107787181949[/C][C]0.867784425636103[/C][C]0.433892212818051[/C][/ROW]
[ROW][C]195[/C][C]0.524501264815401[/C][C]0.950997470369198[/C][C]0.475498735184599[/C][/ROW]
[ROW][C]196[/C][C]0.487836271392483[/C][C]0.975672542784966[/C][C]0.512163728607517[/C][/ROW]
[ROW][C]197[/C][C]0.520449315237627[/C][C]0.959101369524747[/C][C]0.479550684762373[/C][/ROW]
[ROW][C]198[/C][C]0.479366635730892[/C][C]0.958733271461785[/C][C]0.520633364269107[/C][/ROW]
[ROW][C]199[/C][C]0.474925829413354[/C][C]0.949851658826707[/C][C]0.525074170586646[/C][/ROW]
[ROW][C]200[/C][C]0.456382316506778[/C][C]0.912764633013556[/C][C]0.543617683493222[/C][/ROW]
[ROW][C]201[/C][C]0.416956303895067[/C][C]0.833912607790134[/C][C]0.583043696104933[/C][/ROW]
[ROW][C]202[/C][C]0.381077366625335[/C][C]0.76215473325067[/C][C]0.618922633374665[/C][/ROW]
[ROW][C]203[/C][C]0.348064397694647[/C][C]0.696128795389294[/C][C]0.651935602305353[/C][/ROW]
[ROW][C]204[/C][C]0.377697364439998[/C][C]0.755394728879997[/C][C]0.622302635560002[/C][/ROW]
[ROW][C]205[/C][C]0.422626236647676[/C][C]0.845252473295352[/C][C]0.577373763352324[/C][/ROW]
[ROW][C]206[/C][C]0.379125058174398[/C][C]0.758250116348796[/C][C]0.620874941825602[/C][/ROW]
[ROW][C]207[/C][C]0.344795814097059[/C][C]0.689591628194118[/C][C]0.655204185902941[/C][/ROW]
[ROW][C]208[/C][C]0.30717139754302[/C][C]0.61434279508604[/C][C]0.69282860245698[/C][/ROW]
[ROW][C]209[/C][C]0.28060770961316[/C][C]0.561215419226321[/C][C]0.71939229038684[/C][/ROW]
[ROW][C]210[/C][C]0.245561105287828[/C][C]0.491122210575656[/C][C]0.754438894712172[/C][/ROW]
[ROW][C]211[/C][C]0.285626931334983[/C][C]0.571253862669965[/C][C]0.714373068665017[/C][/ROW]
[ROW][C]212[/C][C]0.297247963931228[/C][C]0.594495927862457[/C][C]0.702752036068772[/C][/ROW]
[ROW][C]213[/C][C]0.257616253122554[/C][C]0.515232506245109[/C][C]0.742383746877446[/C][/ROW]
[ROW][C]214[/C][C]0.282513780670659[/C][C]0.565027561341319[/C][C]0.717486219329341[/C][/ROW]
[ROW][C]215[/C][C]0.247344219172381[/C][C]0.494688438344762[/C][C]0.752655780827619[/C][/ROW]
[ROW][C]216[/C][C]0.211720764746624[/C][C]0.423441529493248[/C][C]0.788279235253376[/C][/ROW]
[ROW][C]217[/C][C]0.181216168271715[/C][C]0.362432336543431[/C][C]0.818783831728285[/C][/ROW]
[ROW][C]218[/C][C]0.152237203771839[/C][C]0.304474407543678[/C][C]0.847762796228161[/C][/ROW]
[ROW][C]219[/C][C]0.161042594098484[/C][C]0.322085188196967[/C][C]0.838957405901516[/C][/ROW]
[ROW][C]220[/C][C]0.136710694824746[/C][C]0.273421389649492[/C][C]0.863289305175254[/C][/ROW]
[ROW][C]221[/C][C]0.160934237612119[/C][C]0.321868475224238[/C][C]0.839065762387881[/C][/ROW]
[ROW][C]222[/C][C]0.13141200086639[/C][C]0.262824001732779[/C][C]0.868587999133611[/C][/ROW]
[ROW][C]223[/C][C]0.122291481957158[/C][C]0.244582963914317[/C][C]0.877708518042842[/C][/ROW]
[ROW][C]224[/C][C]0.102359745805732[/C][C]0.204719491611464[/C][C]0.897640254194268[/C][/ROW]
[ROW][C]225[/C][C]0.081069220496217[/C][C]0.162138440992434[/C][C]0.918930779503783[/C][/ROW]
[ROW][C]226[/C][C]0.0635562620141254[/C][C]0.127112524028251[/C][C]0.936443737985875[/C][/ROW]
[ROW][C]227[/C][C]0.0493253913581437[/C][C]0.0986507827162874[/C][C]0.950674608641856[/C][/ROW]
[ROW][C]228[/C][C]0.0375529010811574[/C][C]0.0751058021623147[/C][C]0.962447098918843[/C][/ROW]
[ROW][C]229[/C][C]0.027736435541278[/C][C]0.0554728710825561[/C][C]0.972263564458722[/C][/ROW]
[ROW][C]230[/C][C]0.0204165522576922[/C][C]0.0408331045153845[/C][C]0.979583447742308[/C][/ROW]
[ROW][C]231[/C][C]0.0294940547572483[/C][C]0.0589881095144965[/C][C]0.970505945242752[/C][/ROW]
[ROW][C]232[/C][C]0.0378878197108228[/C][C]0.0757756394216457[/C][C]0.962112180289177[/C][/ROW]
[ROW][C]233[/C][C]0.170004872706629[/C][C]0.340009745413259[/C][C]0.829995127293371[/C][/ROW]
[ROW][C]234[/C][C]0.146751308794144[/C][C]0.293502617588288[/C][C]0.853248691205856[/C][/ROW]
[ROW][C]235[/C][C]0.113363646809348[/C][C]0.226727293618697[/C][C]0.886636353190652[/C][/ROW]
[ROW][C]236[/C][C]0.109105846129479[/C][C]0.218211692258959[/C][C]0.890894153870521[/C][/ROW]
[ROW][C]237[/C][C]0.137211516184681[/C][C]0.274423032369362[/C][C]0.862788483815319[/C][/ROW]
[ROW][C]238[/C][C]0.162032096721945[/C][C]0.32406419344389[/C][C]0.837967903278055[/C][/ROW]
[ROW][C]239[/C][C]0.181429763228611[/C][C]0.362859526457222[/C][C]0.818570236771389[/C][/ROW]
[ROW][C]240[/C][C]0.168107883613424[/C][C]0.336215767226848[/C][C]0.831892116386576[/C][/ROW]
[ROW][C]241[/C][C]0.170488037274335[/C][C]0.340976074548669[/C][C]0.829511962725665[/C][/ROW]
[ROW][C]242[/C][C]0.609955314655537[/C][C]0.780089370688926[/C][C]0.390044685344463[/C][/ROW]
[ROW][C]243[/C][C]0.667243182168[/C][C]0.665513635664[/C][C]0.332756817832[/C][/ROW]
[ROW][C]244[/C][C]0.632452025503721[/C][C]0.735095948992558[/C][C]0.367547974496279[/C][/ROW]
[ROW][C]245[/C][C]0.560362908477119[/C][C]0.879274183045762[/C][C]0.439637091522881[/C][/ROW]
[ROW][C]246[/C][C]0.458000591274774[/C][C]0.916001182549548[/C][C]0.541999408725226[/C][/ROW]
[ROW][C]247[/C][C]0.362291157543126[/C][C]0.724582315086253[/C][C]0.637708842456874[/C][/ROW]
[ROW][C]248[/C][C]0.275878798436556[/C][C]0.551757596873112[/C][C]0.724121201563444[/C][/ROW]
[ROW][C]249[/C][C]0.188346782148751[/C][C]0.376693564297502[/C][C]0.811653217851249[/C][/ROW]
[ROW][C]250[/C][C]0.234009100642001[/C][C]0.468018201284003[/C][C]0.765990899357999[/C][/ROW]
[ROW][C]251[/C][C]0.168658092525587[/C][C]0.337316185051174[/C][C]0.831341907474413[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190281&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190281&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
130.9960700858905130.007859828218974610.0039299141094873
140.99441043961650.01117912076699960.00558956038349982
150.9903571010938350.01928579781233010.00964289890616503
160.9859049238213730.02819015235725480.0140950761786274
170.9747043472748830.05059130545023450.0252956527251172
180.9720648450622830.05587030987543420.0279351549377171
190.9620698755081280.07586024898374420.0379301244918721
200.9412833147255130.1174333705489750.0587166852744875
210.9180282696921770.1639434606156460.0819717303078231
220.8910817795780130.2178364408439750.108918220421987
230.8619454743433410.2761090513133180.138054525656659
240.8293393954823190.3413212090353630.170660604517681
250.7939460784316610.4121078431366790.206053921568339
260.7906489483497880.4187021033004250.209351051650212
270.802159469804090.3956810603918190.19784053019591
280.8037635106229720.3924729787540560.196236489377028
290.7540011107436930.4919977785126140.245998889256307
300.717802053007530.564395893984940.28219794699247
310.669155772342910.661688455314180.33084422765709
320.6862948268153930.6274103463692140.313705173184607
330.6297748203757070.7404503592485860.370225179624293
340.5729709244327180.8540581511345640.427029075567282
350.554508209566730.890983580866540.44549179043327
360.5413792943169720.9172414113660550.458620705683028
370.4839716181378720.9679432362757440.516028381862128
380.4654574562625440.9309149125250870.534542543737456
390.4435039330129860.8870078660259730.556496066987014
400.4127317036800260.8254634073600520.587268296319974
410.3746171322378040.7492342644756080.625382867762196
420.3439107326184430.6878214652368850.656089267381557
430.3925529192474690.7851058384949370.607447080752531
440.3466457187980110.6932914375960230.653354281201988
450.3002877932781620.6005755865563240.699712206721838
460.3363562129353750.672712425870750.663643787064625
470.3384418939548480.6768837879096960.661558106045152
480.29697897853580.5939579570716010.7030210214642
490.2970177336797920.5940354673595840.702982266320208
500.2722469987578640.5444939975157280.727753001242136
510.2694528344340030.5389056688680070.730547165565997
520.2343198725637540.4686397451275080.765680127436246
530.2311090197655580.4622180395311160.768890980234442
540.1993816973531210.3987633947062410.800618302646879
550.3010577377628560.6021154755257130.698942262237144
560.6199972469806850.760005506038630.380002753019315
570.5776188920438390.8447622159123230.422381107956162
580.5337063644144850.9325872711710290.466293635585514
590.4911986560913410.9823973121826820.508801343908659
600.4872184607435890.9744369214871780.512781539256411
610.4958985349063670.9917970698127340.504101465093633
620.4541515688154010.9083031376308020.545848431184599
630.4655077811331010.9310155622662030.534492218866899
640.423959828294980.847919656589960.57604017170502
650.393913530857660.7878270617153190.60608646914234
660.3525323282026670.7050646564053330.647467671797334
670.3191733807592710.6383467615185410.680826619240729
680.3058334012071030.6116668024142050.694166598792897
690.2861729568334560.5723459136669130.713827043166544
700.2549437593270950.5098875186541890.745056240672905
710.2357991695234940.4715983390469890.764200830476506
720.2056236842088760.4112473684177530.794376315791124
730.1779337450613770.3558674901227540.822066254938623
740.1529543248325970.3059086496651940.847045675167403
750.1369173777413520.2738347554827040.863082622258648
760.1800480144684540.3600960289369090.819951985531546
770.1607181417304250.3214362834608490.839281858269575
780.1393574045962290.2787148091924580.860642595403771
790.1394959174433440.2789918348866890.860504082556656
800.1289477271954190.2578954543908380.871052272804581
810.1102399018828830.2204798037657660.889760098117117
820.09347606461981090.1869521292396220.906523935380189
830.07987403718700420.1597480743740080.920125962812996
840.06738524025006540.1347704805001310.932614759749935
850.06661914325757070.1332382865151410.933380856742429
860.07905328469629190.1581065693925840.920946715303708
870.06542029044894120.1308405808978820.934579709551059
880.05402154606395530.1080430921279110.945978453936045
890.04573985672791060.09147971345582110.954260143272089
900.03981252106835170.07962504213670340.960187478931648
910.05621487790438690.1124297558087740.943785122095613
920.04764507380081790.09529014760163570.952354926199182
930.04253608744003440.08507217488006890.957463912559966
940.04217343181185380.08434686362370770.957826568188146
950.04483319050441370.08966638100882730.955166809495586
960.03923509214308720.07847018428617450.960764907856913
970.05180449249994760.1036089849998950.948195507500052
980.04263503011081350.0852700602216270.957364969889187
990.03757811401772840.07515622803545670.962421885982272
1000.04079625618535450.08159251237070890.959203743814646
1010.03514970201206520.07029940402413050.964850297987935
1020.02974425594974620.05948851189949240.970255744050254
1030.02409370297369330.04818740594738650.975906297026307
1040.0219165255936230.0438330511872460.978083474406377
1050.02244270070938240.04488540141876480.977557299290618
1060.01801071855893510.03602143711787020.981989281441065
1070.01429881792881750.0285976358576350.985701182071183
1080.01222549389145750.02445098778291490.987774506108543
1090.01835067846132730.03670135692265450.981649321538673
1100.01452924868566420.02905849737132850.985470751314336
1110.01561665770966290.03123331541932580.984383342290337
1120.01660346650743920.03320693301487840.983396533492561
1130.01366713150330630.02733426300661260.986332868496694
1140.01103742361960320.02207484723920640.988962576380397
1150.008708057810490870.01741611562098170.991291942189509
1160.009331829118965060.01866365823793010.990668170881035
1170.01415253040110680.02830506080221370.985847469598893
1180.01160586126081670.02321172252163340.988394138739183
1190.009146854906295510.0182937098125910.990853145093704
1200.007444903372427230.01488980674485450.992555096627573
1210.006996317629577110.01399263525915420.993003682370423
1220.006792382623116130.01358476524623230.993207617376884
1230.007457950344223910.01491590068844780.992542049655776
1240.007881190382914680.01576238076582940.992118809617085
1250.01298453707697870.02596907415395740.987015462923021
1260.01127197074535570.02254394149071130.988728029254644
1270.01004892557129620.02009785114259240.989951074428704
1280.01095801560008730.02191603120017470.989041984399913
1290.01049951219877740.02099902439755470.989500487801223
1300.01073711672843050.0214742334568610.98926288327157
1310.01333240213015330.02666480426030660.986667597869847
1320.0262862449487780.05257248989755590.973713755051222
1330.0257879976990390.0515759953980780.974212002300961
1340.02429055158746980.04858110317493950.97570944841253
1350.02155406495882740.04310812991765480.978445935041173
1360.01781517604839840.03563035209679680.982184823951602
1370.01435088093000610.02870176186001230.985649119069994
1380.01314590113767230.02629180227534460.986854098862328
1390.01182765164017150.02365530328034310.988172348359828
1400.009964917123203660.01992983424640730.990035082876796
1410.01722163207843250.03444326415686490.982778367921567
1420.01851571615136520.03703143230273040.981484283848635
1430.02747219849493650.05494439698987290.972527801505064
1440.02226519136148930.04453038272297860.977734808638511
1450.01790119003848880.03580238007697770.982098809961511
1460.01540344379099340.03080688758198690.984596556209007
1470.01872521927118290.03745043854236590.981274780728817
1480.01648682377017560.03297364754035120.983513176229824
1490.01379657654401820.02759315308803640.986203423455982
1500.01201512468902070.02403024937804130.987984875310979
1510.01521413725636830.03042827451273670.984785862743632
1520.01714349066379240.03428698132758480.982856509336208
1530.07001920085877380.1400384017175480.929980799141226
1540.06179522146383120.1235904429276620.938204778536169
1550.05257083533111770.1051416706622350.947429164668882
1560.1088451616130310.2176903232260630.891154838386969
1570.1437791667364250.2875583334728490.856220833263575
1580.1306962381917780.2613924763835560.869303761808222
1590.1163625428731130.2327250857462260.883637457126887
1600.1040417126853970.2080834253707940.895958287314603
1610.09184155443062540.1836831088612510.908158445569375
1620.07808121275462010.156162425509240.92191878724538
1630.07379482848401210.1475896569680240.926205171515988
1640.07484684176867170.1496936835373430.925153158231328
1650.07104174117488440.1420834823497690.928958258825116
1660.0604969939671920.1209939879343840.939503006032808
1670.05019510303342170.1003902060668430.949804896966578
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1730.09133732512950410.1826746502590080.908662674870496
1740.07809218477288580.1561843695457720.921907815227114
1750.1014041877784350.2028083755568710.898595812221565
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1770.08025092813184060.1605018562636810.919749071868159
1780.06746477628541520.134929552570830.932535223714585
1790.05622358838546540.1124471767709310.943776411614535
1800.04682733030526360.09365466061052720.953172669694736
1810.03836439650186650.0767287930037330.961635603498133
1820.04916665073902330.09833330147804660.950833349260977
1830.04776696996501710.09553393993003430.952233030034983
1840.04244373192533270.08488746385066540.957556268074667
1850.1671574844645630.3343149689291270.832842515535437
1860.1517016111872480.3034032223744950.848298388812752
1870.1331384578598820.2662769157197630.866861542140118
1880.1338554455888310.2677108911776610.866144554411169
1890.1232904829391690.2465809658783380.876709517060831
1900.2052823288293760.4105646576587530.794717671170624
1910.2048127682542910.4096255365085820.795187231745709
1920.1779042187188130.3558084374376260.822095781281187
1930.5824492941397360.8351014117205280.417550705860264
1940.5661077871819490.8677844256361030.433892212818051
1950.5245012648154010.9509974703691980.475498735184599
1960.4878362713924830.9756725427849660.512163728607517
1970.5204493152376270.9591013695247470.479550684762373
1980.4793666357308920.9587332714617850.520633364269107
1990.4749258294133540.9498516588267070.525074170586646
2000.4563823165067780.9127646330135560.543617683493222
2010.4169563038950670.8339126077901340.583043696104933
2020.3810773666253350.762154733250670.618922633374665
2030.3480643976946470.6961287953892940.651935602305353
2040.3776973644399980.7553947288799970.622302635560002
2050.4226262366476760.8452524732953520.577373763352324
2060.3791250581743980.7582501163487960.620874941825602
2070.3447958140970590.6895916281941180.655204185902941
2080.307171397543020.614342795086040.69282860245698
2090.280607709613160.5612154192263210.71939229038684
2100.2455611052878280.4911222105756560.754438894712172
2110.2856269313349830.5712538626699650.714373068665017
2120.2972479639312280.5944959278624570.702752036068772
2130.2576162531225540.5152325062451090.742383746877446
2140.2825137806706590.5650275613413190.717486219329341
2150.2473442191723810.4946884383447620.752655780827619
2160.2117207647466240.4234415294932480.788279235253376
2170.1812161682717150.3624323365434310.818783831728285
2180.1522372037718390.3044744075436780.847762796228161
2190.1610425940984840.3220851881969670.838957405901516
2200.1367106948247460.2734213896494920.863289305175254
2210.1609342376121190.3218684752242380.839065762387881
2220.131412000866390.2628240017327790.868587999133611
2230.1222914819571580.2445829639143170.877708518042842
2240.1023597458057320.2047194916114640.897640254194268
2250.0810692204962170.1621384409924340.918930779503783
2260.06355626201412540.1271125240282510.936443737985875
2270.04932539135814370.09865078271628740.950674608641856
2280.03755290108115740.07510580216231470.962447098918843
2290.0277364355412780.05547287108255610.972263564458722
2300.02041655225769220.04083310451538450.979583447742308
2310.02949405475724830.05898810951449650.970505945242752
2320.03788781971082280.07577563942164570.962112180289177
2330.1700048727066290.3400097454132590.829995127293371
2340.1467513087941440.2935026175882880.853248691205856
2350.1133636468093480.2267272936186970.886636353190652
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2390.1814297632286110.3628595264572220.818570236771389
2400.1681078836134240.3362157672268480.831892116386576
2410.1704880372743350.3409760745486690.829511962725665
2420.6099553146555370.7800893706889260.390044685344463
2430.6672431821680.6655136356640.332756817832
2440.6324520255037210.7350959489925580.367547974496279
2450.5603629084771190.8792741830457620.439637091522881
2460.4580005912747740.9160011825495480.541999408725226
2470.3622911575431260.7245823150862530.637708842456874
2480.2758787984365560.5517575968731120.724121201563444
2490.1883467821487510.3766935642975020.811653217851249
2500.2340091006420010.4680182012840030.765990899357999
2510.1686580925255870.3373161850511740.831341907474413






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level10.00418410041841004OK
5% type I error level520.217573221757322NOK
10% type I error level800.334728033472803NOK

\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 & 1 & 0.00418410041841004 & OK \tabularnewline
5% type I error level & 52 & 0.217573221757322 & NOK \tabularnewline
10% type I error level & 80 & 0.334728033472803 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190281&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]1[/C][C]0.00418410041841004[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]52[/C][C]0.217573221757322[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]80[/C][C]0.334728033472803[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190281&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190281&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 level10.00418410041841004OK
5% type I error level520.217573221757322NOK
10% type I error level800.334728033472803NOK


Figures (Output of Computation)

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Figure 10
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Input Parameters & R Code

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