Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 05 Nov 2012 17:15:49 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/05/t13521537711awr40a6udi6lzh.htm/, Retrieved Wed, 01 Feb 2023 15:50:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=186332, Retrieved Wed, 01 Feb 2023 15:50:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact66
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]
-   P     [Multiple Regression] [] [2012-11-05 22:15:49] [e8c322125b0cf2de4bdab96981906a22] [Current]
- RMPD      [Univariate Explorative Data Analysis] [] [2012-12-20 15:32:48] [43bd65bee76289cab2ce37423d405966]
- R P         [Univariate Explorative Data Analysis] [] [2012-12-22 16:39:07] [8c6900b6affe5ced50ee5724b2e31c80]
Feedback Forum

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




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 15 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186332&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186332&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186332&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 18.2331269218713 -0.317163421864344month[t] + 0.00399972397395324Connected[t] + 0.0118355009158621Separate[t] + 0.0926299065733013Learning[t] -0.0199196273577166Software[t] -0.363549781226373Depression[t] + 0.0165414616732836Belonging[t] + 0.0147119347288411Belonging_Final[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  18.2331269218713 -0.317163421864344month[t] +  0.00399972397395324Connected[t] +  0.0118355009158621Separate[t] +  0.0926299065733013Learning[t] -0.0199196273577166Software[t] -0.363549781226373Depression[t] +  0.0165414616732836Belonging[t] +  0.0147119347288411Belonging_Final[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186332&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  18.2331269218713 -0.317163421864344month[t] +  0.00399972397395324Connected[t] +  0.0118355009158621Separate[t] +  0.0926299065733013Learning[t] -0.0199196273577166Software[t] -0.363549781226373Depression[t] +  0.0165414616732836Belonging[t] +  0.0147119347288411Belonging_Final[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186332&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186332&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 18.2331269218713 -0.317163421864344month[t] + 0.00399972397395324Connected[t] + 0.0118355009158621Separate[t] + 0.0926299065733013Learning[t] -0.0199196273577166Software[t] -0.363549781226373Depression[t] + 0.0165414616732836Belonging[t] + 0.0147119347288411Belonging_Final[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)18.23312692187132.6423096.900500
month-0.3171634218643440.173074-1.83250.0680390.03402
Connected0.003999723973953240.037560.10650.9152790.45764
Separate0.01183550091586210.0381580.31020.7566850.378342
Learning0.09262990657330130.0672951.37650.1698790.08494
Software-0.01991962735771660.068935-0.2890.7728460.386423
Depression-0.3635497812263730.039748-9.146500
Belonging0.01654146167328360.0407660.40580.6852570.342628
Belonging_Final0.01471193472884110.060540.2430.8081910.404096

\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) & 18.2331269218713 & 2.642309 & 6.9005 & 0 & 0 \tabularnewline
month & -0.317163421864344 & 0.173074 & -1.8325 & 0.068039 & 0.03402 \tabularnewline
Connected & 0.00399972397395324 & 0.03756 & 0.1065 & 0.915279 & 0.45764 \tabularnewline
Separate & 0.0118355009158621 & 0.038158 & 0.3102 & 0.756685 & 0.378342 \tabularnewline
Learning & 0.0926299065733013 & 0.067295 & 1.3765 & 0.169879 & 0.08494 \tabularnewline
Software & -0.0199196273577166 & 0.068935 & -0.289 & 0.772846 & 0.386423 \tabularnewline
Depression & -0.363549781226373 & 0.039748 & -9.1465 & 0 & 0 \tabularnewline
Belonging & 0.0165414616732836 & 0.040766 & 0.4058 & 0.685257 & 0.342628 \tabularnewline
Belonging_Final & 0.0147119347288411 & 0.06054 & 0.243 & 0.808191 & 0.404096 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186332&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]18.2331269218713[/C][C]2.642309[/C][C]6.9005[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]month[/C][C]-0.317163421864344[/C][C]0.173074[/C][C]-1.8325[/C][C]0.068039[/C][C]0.03402[/C][/ROW]
[ROW][C]Connected[/C][C]0.00399972397395324[/C][C]0.03756[/C][C]0.1065[/C][C]0.915279[/C][C]0.45764[/C][/ROW]
[ROW][C]Separate[/C][C]0.0118355009158621[/C][C]0.038158[/C][C]0.3102[/C][C]0.756685[/C][C]0.378342[/C][/ROW]
[ROW][C]Learning[/C][C]0.0926299065733013[/C][C]0.067295[/C][C]1.3765[/C][C]0.169879[/C][C]0.08494[/C][/ROW]
[ROW][C]Software[/C][C]-0.0199196273577166[/C][C]0.068935[/C][C]-0.289[/C][C]0.772846[/C][C]0.386423[/C][/ROW]
[ROW][C]Depression[/C][C]-0.363549781226373[/C][C]0.039748[/C][C]-9.1465[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Belonging[/C][C]0.0165414616732836[/C][C]0.040766[/C][C]0.4058[/C][C]0.685257[/C][C]0.342628[/C][/ROW]
[ROW][C]Belonging_Final[/C][C]0.0147119347288411[/C][C]0.06054[/C][C]0.243[/C][C]0.808191[/C][C]0.404096[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186332&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186332&T=2

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)18.23312692187132.6423096.900500
month-0.3171634218643440.173074-1.83250.0680390.03402
Connected0.003999723973953240.037560.10650.9152790.45764
Separate0.01183550091586210.0381580.31020.7566850.378342
Learning0.09262990657330130.0672951.37650.1698790.08494
Software-0.01991962735771660.068935-0.2890.7728460.386423
Depression-0.3635497812263730.039748-9.146500
Belonging0.01654146167328360.0407660.40580.6852570.342628
Belonging_Final0.01471193472884110.060540.2430.8081910.404096







Multiple Linear Regression - Regression Statistics
Multiple R0.609698323645421
R-squared0.371732045856037
Adjusted R-squared0.352021678667207
F-TEST (value)18.8597220079541
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.01133509701029
Sum Squared Residuals1031.59456247868

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.609698323645421 \tabularnewline
R-squared & 0.371732045856037 \tabularnewline
Adjusted R-squared & 0.352021678667207 \tabularnewline
F-TEST (value) & 18.8597220079541 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 255 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.01133509701029 \tabularnewline
Sum Squared Residuals & 1031.59456247868 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186332&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.609698323645421[/C][/ROW]
[ROW][C]R-squared[/C][C]0.371732045856037[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.352021678667207[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]18.8597220079541[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]255[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.01133509701029[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1031.59456247868[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186332&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186332&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.609698323645421
R-squared0.371732045856037
Adjusted R-squared0.352021678667207
F-TEST (value)18.8597220079541
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.01133509701029
Sum Squared Residuals1031.59456247868







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11413.94242910527780.0575708947222239
21815.30054639018522.69945360981481
31113.9940049827717-2.99400498277173
41214.5120198142374-2.51201981423739
51611.28977848941184.71022151058822
61814.48596607067143.51403392932855
71410.84542245173913.15457754826088
81415.0964527308549-1.09645273085489
91515.2452792983004-0.245279298300373
101514.40903176279350.590968237206507
111715.57259085772861.42740914227135
121915.63843072277213.3615692772279
131013.4608636173635-3.46086361736351
141613.53639283835692.46360716164312
151815.80781644544042.19218355455959
161413.44696938290850.553030617091464
171413.90458429360930.0954157063906888
181715.84500278319481.15499721680516
191415.4589618709725-1.45896187097254
201613.87477210811912.12522789188094
211815.40138429938872.59861570061129
221113.7950386582397-2.79503865823973
231414.5015428658141-0.501542865814098
241213.6321595535868-1.63215955358677
251715.43759298914951.56240701085053
26915.9799639285085-6.9799639285085
271615.11048763882490.889512361175079
281413.3945736308410.60542636915902
291514.0068356594810.993164340518967
301114.0322965931152-3.03229659311523
311615.79221487152190.2077851284781
321312.74307261972780.256927380272161
331715.16272801884881.83727198115122
341515.3804829133968-0.380482913396826
351414.0433171979075-0.0433171979075127
361615.59745115377230.40254884622773
37910.9240291140986-1.92402911409861
381514.41546047953840.584539520461631
391715.44283315275671.5571668472433
401315.3158645278038-2.31586452780379
411515.8024213686151-0.80242136861515
421613.76123925055972.23876074944031
431615.93351991310830.0664800868916651
441213.2333694592886-1.23336945928862
451514.71987660077340.280123399226636
461113.7079315151914-2.70793151519139
471515.4659538792632-0.465953879263151
481515.0016977745694-0.00169777456942071
491713.62408053123393.37591946876611
501314.8707639239476-1.8707639239476
511615.36241260550790.637587394492092
521413.5663931222780.433606877722001
531111.8122997813784-0.812299781378398
541213.8001418086329-1.80014180863288
551214.1921484861024-2.19214848610242
561513.79532956370621.20467043629381
571614.34005343877391.65994656122615
581515.5943292880403-0.594329288040307
591215.3276987259902-3.32769872599024
601213.5412045189899-1.54120451898991
61810.87864711281-2.87864711280997
621314.7492278810461-1.74922788104612
631114.7989854205571-3.79898542055711
641413.22112193786680.778878062133185
651513.77717586594471.22282413405526
661015.0003039743847-5.00030397438468
671112.5374802818564-1.5374802818564
681214.3973840158749-2.39738401587494
691513.43844377460351.56155622539653
701513.5520047299821.44799527001803
711413.43595819831650.564041801683487
721612.63842203032793.36157796967207
731514.36741549594970.632584504050268
741515.1815417194463-0.181541719446257
751314.8861167434585-1.8861167434585
761212.1047346234893-0.104734623489337
771713.93488772820073.06511227179934
781312.43568615364910.564313846350879
791513.74454508520611.25545491479393
801314.8788687372443-1.8788687372443
811514.84708148044550.15291851955448
821515.4469723636469-0.446972363646926
831614.22800961156781.77199038843215
841514.23793659302720.762063406972782
851414.0822726795112-0.0822726795111701
861513.96910832811471.0308916718853
871414.2355983417392-0.235598341739223
881312.72474976267370.275250237326259
89710.5268885183884-3.52688851838845
901713.70197295578513.29802704421489
911312.78561885499160.214381145008435
921514.15407594717340.845924052826577
931413.28061697214340.719383027856592
941313.9681085838972-0.968108583897196
951614.94217247540681.0578275245932
961212.8040259210165-0.804025921016528
971414.839120844214-0.839120844213983
981714.90191616731392.09808383268614
991515.0115865942469-0.0115865942469205
1001715.12645430707751.87354569292246
1011212.9394548918828-0.939454891882777
1021615.00564749468970.994352505310327
1031114.401800729261-3.40180072926104
1041513.09947063914781.9005293608522
105911.3859338230185-2.38593382301853
1061614.91296205568171.08703794431828
1071512.92036937128012.07963062871993
1081012.8081739605967-2.80817396059672
109109.179763889352930.820236110647068
1101513.90828234142561.09171765857444
1111113.197405972305-2.197405972305
1121315.296089362601-2.29608936260102
1131411.90228839234222.09771160765777
1141814.11026677141453.88973322858555
1151615.5634021145080.436597885491982
1161412.99380300661851.0061969933815
1171413.83782093237740.162179067622646
1181415.080113093972-1.08011309397202
1191413.72724446637550.272755533624518
1201212.5419560707867-0.541956070786677
1211413.57236916819820.427630831801833
1221514.90780697790650.0921930220934662
1231515.9026490168457-0.902649016845736
1241514.57339290908850.426607090911491
1251314.7585285824057-1.75852858240572
1261716.17596000341270.824039996587266
1271715.29055308423991.70944691576012
1281914.95027692239384.04972307760617
1291513.59666076308691.40333923691306
1301314.6562350761378-1.65623507613778
131910.6686224036671-1.66862240366712
1321515.2970604164897-0.297060416489728
1331512.62741893546662.37258106453337
1341514.25523447543370.744765524566336
1351613.77918631294972.2208136870503
136119.475865942083431.52413405791658
1371413.3523749549210.647625045078995
1381112.0068197994755-1.00681979947552
1391514.20417527622710.795824723772937
1401313.821331809185-0.82133180918498
1411514.65784735199010.342152648009941
1421613.87966442327092.12033557672913
1431414.7113418256964-0.71134182569645
1441514.30850744337620.691492556623817
1451614.63762314296731.36237685703265
1461614.50344020250031.49655979749969
1471113.4221081205716-2.42210812057161
1481214.7177384051991-2.71773840519912
149911.5819610672325-2.58196106723253
1501614.28508783232691.71491216767314
1511312.61577821056650.384221789433456
1521615.45571928374660.544280716253379
1531214.5013413128903-2.50134131289027
154911.9370425459018-2.93704254590182
1551311.82397278924361.17602721075642
1561312.78561885499160.214381145008435
1571413.39634553721530.603654462784655
1581914.95027692239384.04972307760617
1591315.7070253725771-2.70702537257711
1601212.1726182201381-0.17261822013812
1611312.66970647126570.330293528734267
162109.16419227869230.8358077213077
1631413.06986799900860.930132000991402
1641611.40372492045914.59627507954092
1651011.8118591289607-1.81185912896073
166118.979417539287982.02058246071202
1671413.96640482468090.0335951753191299
1681212.7057994263193-0.705799426319294
169912.5704222824703-3.5704222824703
170911.8000983033848-2.8000983033848
1711110.41017088716620.58982911283377
1721614.04498884902191.95501115097814
173913.8540206697084-4.85402066970835
1741311.16095824054521.83904175945481
1751613.20439993325952.79560006674048
1761315.1225067857976-2.12250678579756
177912.1757285461426-3.17572854614255
1781211.35232237798240.647677622017567
1791614.40881311512561.59118688487444
1801113.0187870441858-2.01878704418585
1811413.9371255371960.0628744628039876
1821314.5783150810428-1.57831508104284
1831514.56175242376280.43824757623721
1841414.8194598805715-0.819459880571533
1851613.94801986424682.05198013575321
1861311.53847183031871.4615281696813
1871413.41330330637030.586696693629732
1881514.08087092887390.919129071126095
1891312.31210719413390.687892805866077
1901110.165978527760.834021472239995
1911112.4204413148938-1.42044131489381
1921414.8652187471899-0.865218747189949
1931512.62070737123222.37929262876781
1941112.3971592065808-1.39715920658077
1951513.00466242108951.99533757891048
1961213.9351112439918-1.9351112439918
1971411.65552477969572.34447522030434
1981413.32286967107970.677130328920298
199811.0469001139438-3.04690011394376
2001313.6649716318431-0.664971631843059
201912.0707687076154-3.07076870761539
2021513.6602509725571.339749027443
2031713.9463360415743.05366395842604
2041312.450038985070.549961014929986
2051514.33336962370750.666630376292491
2061513.63668869779151.36331130220846
2071414.4377790361756-0.43777903617556
2081612.41641989551233.58358010448768
2091312.8141540814080.185845918591978
2101614.22362589400511.77637410599492
211911.6101994326838-2.6101994326838
2121614.47177108287481.5282289171252
2131112.1938932607716-1.19389326077161
2141013.7746617275872-3.77466172758721
2151112.0580141698025-1.05801416980253
2161513.20206867068281.79793132931717
2171714.81815247000912.18184752999092
2181414.1757125160018-0.17571251600181
21989.88795726840051-1.88795726840051
2201513.53204047639111.4679595236089
2211113.8113471178154-2.81134711781537
2221613.47289662272182.52710337727817
2231012.0634333598155-2.06343335981552
2241514.74570132403180.254298675968154
22599.48717148853057-0.487171488530575
2261614.25140516572021.7485948342798
2271913.72436435523165.27563564476837
2281213.575989740931-1.575989740931
22989.45853651362965-1.45853651362965
2301113.2912130157204-2.29121301572039
2311413.76451554268720.235484457312813
232911.9919785600196-2.99197856001957
2331514.85437461694720.14562538305282
2341312.37474098698520.62525901301484
2351614.83041077516931.16958922483071
2361112.7757711448475-1.77577114484746
2371211.31078750078580.689212499214227
2381312.75945090008750.240549099912532
2391014.2948156222065-4.29481562220655
2401113.5099587639336-2.50995876393355
2411214.7831430735995-2.78314307359948
242810.6604625366153-2.66046253661528
2431211.71178175487610.28821824512392
2441212.2229795319503-0.222979531950292
2451513.49590738248241.50409261751757
2461110.71503215822160.284967841778399
2471312.70829089511980.291709104880228
248148.806903245801225.19309675419878
2491010.2060272955343-0.206027295534266
2501211.49857474672120.50142525327881
2511512.83632597506962.16367402493041
2521311.84326653796381.15673346203618
2531314.1054888036805-1.10548880368046
2541313.6847332080963-0.684733208096305
2551211.78705144492960.212948555070412
2561212.6362386248472-0.636238624847237
257910.8039535443016-1.80395354430155
258911.4546703778506-2.4546703778506
2591512.5380195216542.46198047834603
2601014.779709067119-4.77970906711905
2611413.63282924587030.367170754129656
2621513.47537371824361.52462628175635
26379.81112874528311-2.81112874528311
2641413.81760041082260.182399589177419

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 13.9424291052778 & 0.0575708947222239 \tabularnewline
2 & 18 & 15.3005463901852 & 2.69945360981481 \tabularnewline
3 & 11 & 13.9940049827717 & -2.99400498277173 \tabularnewline
4 & 12 & 14.5120198142374 & -2.51201981423739 \tabularnewline
5 & 16 & 11.2897784894118 & 4.71022151058822 \tabularnewline
6 & 18 & 14.4859660706714 & 3.51403392932855 \tabularnewline
7 & 14 & 10.8454224517391 & 3.15457754826088 \tabularnewline
8 & 14 & 15.0964527308549 & -1.09645273085489 \tabularnewline
9 & 15 & 15.2452792983004 & -0.245279298300373 \tabularnewline
10 & 15 & 14.4090317627935 & 0.590968237206507 \tabularnewline
11 & 17 & 15.5725908577286 & 1.42740914227135 \tabularnewline
12 & 19 & 15.6384307227721 & 3.3615692772279 \tabularnewline
13 & 10 & 13.4608636173635 & -3.46086361736351 \tabularnewline
14 & 16 & 13.5363928383569 & 2.46360716164312 \tabularnewline
15 & 18 & 15.8078164454404 & 2.19218355455959 \tabularnewline
16 & 14 & 13.4469693829085 & 0.553030617091464 \tabularnewline
17 & 14 & 13.9045842936093 & 0.0954157063906888 \tabularnewline
18 & 17 & 15.8450027831948 & 1.15499721680516 \tabularnewline
19 & 14 & 15.4589618709725 & -1.45896187097254 \tabularnewline
20 & 16 & 13.8747721081191 & 2.12522789188094 \tabularnewline
21 & 18 & 15.4013842993887 & 2.59861570061129 \tabularnewline
22 & 11 & 13.7950386582397 & -2.79503865823973 \tabularnewline
23 & 14 & 14.5015428658141 & -0.501542865814098 \tabularnewline
24 & 12 & 13.6321595535868 & -1.63215955358677 \tabularnewline
25 & 17 & 15.4375929891495 & 1.56240701085053 \tabularnewline
26 & 9 & 15.9799639285085 & -6.9799639285085 \tabularnewline
27 & 16 & 15.1104876388249 & 0.889512361175079 \tabularnewline
28 & 14 & 13.394573630841 & 0.60542636915902 \tabularnewline
29 & 15 & 14.006835659481 & 0.993164340518967 \tabularnewline
30 & 11 & 14.0322965931152 & -3.03229659311523 \tabularnewline
31 & 16 & 15.7922148715219 & 0.2077851284781 \tabularnewline
32 & 13 & 12.7430726197278 & 0.256927380272161 \tabularnewline
33 & 17 & 15.1627280188488 & 1.83727198115122 \tabularnewline
34 & 15 & 15.3804829133968 & -0.380482913396826 \tabularnewline
35 & 14 & 14.0433171979075 & -0.0433171979075127 \tabularnewline
36 & 16 & 15.5974511537723 & 0.40254884622773 \tabularnewline
37 & 9 & 10.9240291140986 & -1.92402911409861 \tabularnewline
38 & 15 & 14.4154604795384 & 0.584539520461631 \tabularnewline
39 & 17 & 15.4428331527567 & 1.5571668472433 \tabularnewline
40 & 13 & 15.3158645278038 & -2.31586452780379 \tabularnewline
41 & 15 & 15.8024213686151 & -0.80242136861515 \tabularnewline
42 & 16 & 13.7612392505597 & 2.23876074944031 \tabularnewline
43 & 16 & 15.9335199131083 & 0.0664800868916651 \tabularnewline
44 & 12 & 13.2333694592886 & -1.23336945928862 \tabularnewline
45 & 15 & 14.7198766007734 & 0.280123399226636 \tabularnewline
46 & 11 & 13.7079315151914 & -2.70793151519139 \tabularnewline
47 & 15 & 15.4659538792632 & -0.465953879263151 \tabularnewline
48 & 15 & 15.0016977745694 & -0.00169777456942071 \tabularnewline
49 & 17 & 13.6240805312339 & 3.37591946876611 \tabularnewline
50 & 13 & 14.8707639239476 & -1.8707639239476 \tabularnewline
51 & 16 & 15.3624126055079 & 0.637587394492092 \tabularnewline
52 & 14 & 13.566393122278 & 0.433606877722001 \tabularnewline
53 & 11 & 11.8122997813784 & -0.812299781378398 \tabularnewline
54 & 12 & 13.8001418086329 & -1.80014180863288 \tabularnewline
55 & 12 & 14.1921484861024 & -2.19214848610242 \tabularnewline
56 & 15 & 13.7953295637062 & 1.20467043629381 \tabularnewline
57 & 16 & 14.3400534387739 & 1.65994656122615 \tabularnewline
58 & 15 & 15.5943292880403 & -0.594329288040307 \tabularnewline
59 & 12 & 15.3276987259902 & -3.32769872599024 \tabularnewline
60 & 12 & 13.5412045189899 & -1.54120451898991 \tabularnewline
61 & 8 & 10.87864711281 & -2.87864711280997 \tabularnewline
62 & 13 & 14.7492278810461 & -1.74922788104612 \tabularnewline
63 & 11 & 14.7989854205571 & -3.79898542055711 \tabularnewline
64 & 14 & 13.2211219378668 & 0.778878062133185 \tabularnewline
65 & 15 & 13.7771758659447 & 1.22282413405526 \tabularnewline
66 & 10 & 15.0003039743847 & -5.00030397438468 \tabularnewline
67 & 11 & 12.5374802818564 & -1.5374802818564 \tabularnewline
68 & 12 & 14.3973840158749 & -2.39738401587494 \tabularnewline
69 & 15 & 13.4384437746035 & 1.56155622539653 \tabularnewline
70 & 15 & 13.552004729982 & 1.44799527001803 \tabularnewline
71 & 14 & 13.4359581983165 & 0.564041801683487 \tabularnewline
72 & 16 & 12.6384220303279 & 3.36157796967207 \tabularnewline
73 & 15 & 14.3674154959497 & 0.632584504050268 \tabularnewline
74 & 15 & 15.1815417194463 & -0.181541719446257 \tabularnewline
75 & 13 & 14.8861167434585 & -1.8861167434585 \tabularnewline
76 & 12 & 12.1047346234893 & -0.104734623489337 \tabularnewline
77 & 17 & 13.9348877282007 & 3.06511227179934 \tabularnewline
78 & 13 & 12.4356861536491 & 0.564313846350879 \tabularnewline
79 & 15 & 13.7445450852061 & 1.25545491479393 \tabularnewline
80 & 13 & 14.8788687372443 & -1.8788687372443 \tabularnewline
81 & 15 & 14.8470814804455 & 0.15291851955448 \tabularnewline
82 & 15 & 15.4469723636469 & -0.446972363646926 \tabularnewline
83 & 16 & 14.2280096115678 & 1.77199038843215 \tabularnewline
84 & 15 & 14.2379365930272 & 0.762063406972782 \tabularnewline
85 & 14 & 14.0822726795112 & -0.0822726795111701 \tabularnewline
86 & 15 & 13.9691083281147 & 1.0308916718853 \tabularnewline
87 & 14 & 14.2355983417392 & -0.235598341739223 \tabularnewline
88 & 13 & 12.7247497626737 & 0.275250237326259 \tabularnewline
89 & 7 & 10.5268885183884 & -3.52688851838845 \tabularnewline
90 & 17 & 13.7019729557851 & 3.29802704421489 \tabularnewline
91 & 13 & 12.7856188549916 & 0.214381145008435 \tabularnewline
92 & 15 & 14.1540759471734 & 0.845924052826577 \tabularnewline
93 & 14 & 13.2806169721434 & 0.719383027856592 \tabularnewline
94 & 13 & 13.9681085838972 & -0.968108583897196 \tabularnewline
95 & 16 & 14.9421724754068 & 1.0578275245932 \tabularnewline
96 & 12 & 12.8040259210165 & -0.804025921016528 \tabularnewline
97 & 14 & 14.839120844214 & -0.839120844213983 \tabularnewline
98 & 17 & 14.9019161673139 & 2.09808383268614 \tabularnewline
99 & 15 & 15.0115865942469 & -0.0115865942469205 \tabularnewline
100 & 17 & 15.1264543070775 & 1.87354569292246 \tabularnewline
101 & 12 & 12.9394548918828 & -0.939454891882777 \tabularnewline
102 & 16 & 15.0056474946897 & 0.994352505310327 \tabularnewline
103 & 11 & 14.401800729261 & -3.40180072926104 \tabularnewline
104 & 15 & 13.0994706391478 & 1.9005293608522 \tabularnewline
105 & 9 & 11.3859338230185 & -2.38593382301853 \tabularnewline
106 & 16 & 14.9129620556817 & 1.08703794431828 \tabularnewline
107 & 15 & 12.9203693712801 & 2.07963062871993 \tabularnewline
108 & 10 & 12.8081739605967 & -2.80817396059672 \tabularnewline
109 & 10 & 9.17976388935293 & 0.820236110647068 \tabularnewline
110 & 15 & 13.9082823414256 & 1.09171765857444 \tabularnewline
111 & 11 & 13.197405972305 & -2.197405972305 \tabularnewline
112 & 13 & 15.296089362601 & -2.29608936260102 \tabularnewline
113 & 14 & 11.9022883923422 & 2.09771160765777 \tabularnewline
114 & 18 & 14.1102667714145 & 3.88973322858555 \tabularnewline
115 & 16 & 15.563402114508 & 0.436597885491982 \tabularnewline
116 & 14 & 12.9938030066185 & 1.0061969933815 \tabularnewline
117 & 14 & 13.8378209323774 & 0.162179067622646 \tabularnewline
118 & 14 & 15.080113093972 & -1.08011309397202 \tabularnewline
119 & 14 & 13.7272444663755 & 0.272755533624518 \tabularnewline
120 & 12 & 12.5419560707867 & -0.541956070786677 \tabularnewline
121 & 14 & 13.5723691681982 & 0.427630831801833 \tabularnewline
122 & 15 & 14.9078069779065 & 0.0921930220934662 \tabularnewline
123 & 15 & 15.9026490168457 & -0.902649016845736 \tabularnewline
124 & 15 & 14.5733929090885 & 0.426607090911491 \tabularnewline
125 & 13 & 14.7585285824057 & -1.75852858240572 \tabularnewline
126 & 17 & 16.1759600034127 & 0.824039996587266 \tabularnewline
127 & 17 & 15.2905530842399 & 1.70944691576012 \tabularnewline
128 & 19 & 14.9502769223938 & 4.04972307760617 \tabularnewline
129 & 15 & 13.5966607630869 & 1.40333923691306 \tabularnewline
130 & 13 & 14.6562350761378 & -1.65623507613778 \tabularnewline
131 & 9 & 10.6686224036671 & -1.66862240366712 \tabularnewline
132 & 15 & 15.2970604164897 & -0.297060416489728 \tabularnewline
133 & 15 & 12.6274189354666 & 2.37258106453337 \tabularnewline
134 & 15 & 14.2552344754337 & 0.744765524566336 \tabularnewline
135 & 16 & 13.7791863129497 & 2.2208136870503 \tabularnewline
136 & 11 & 9.47586594208343 & 1.52413405791658 \tabularnewline
137 & 14 & 13.352374954921 & 0.647625045078995 \tabularnewline
138 & 11 & 12.0068197994755 & -1.00681979947552 \tabularnewline
139 & 15 & 14.2041752762271 & 0.795824723772937 \tabularnewline
140 & 13 & 13.821331809185 & -0.82133180918498 \tabularnewline
141 & 15 & 14.6578473519901 & 0.342152648009941 \tabularnewline
142 & 16 & 13.8796644232709 & 2.12033557672913 \tabularnewline
143 & 14 & 14.7113418256964 & -0.71134182569645 \tabularnewline
144 & 15 & 14.3085074433762 & 0.691492556623817 \tabularnewline
145 & 16 & 14.6376231429673 & 1.36237685703265 \tabularnewline
146 & 16 & 14.5034402025003 & 1.49655979749969 \tabularnewline
147 & 11 & 13.4221081205716 & -2.42210812057161 \tabularnewline
148 & 12 & 14.7177384051991 & -2.71773840519912 \tabularnewline
149 & 9 & 11.5819610672325 & -2.58196106723253 \tabularnewline
150 & 16 & 14.2850878323269 & 1.71491216767314 \tabularnewline
151 & 13 & 12.6157782105665 & 0.384221789433456 \tabularnewline
152 & 16 & 15.4557192837466 & 0.544280716253379 \tabularnewline
153 & 12 & 14.5013413128903 & -2.50134131289027 \tabularnewline
154 & 9 & 11.9370425459018 & -2.93704254590182 \tabularnewline
155 & 13 & 11.8239727892436 & 1.17602721075642 \tabularnewline
156 & 13 & 12.7856188549916 & 0.214381145008435 \tabularnewline
157 & 14 & 13.3963455372153 & 0.603654462784655 \tabularnewline
158 & 19 & 14.9502769223938 & 4.04972307760617 \tabularnewline
159 & 13 & 15.7070253725771 & -2.70702537257711 \tabularnewline
160 & 12 & 12.1726182201381 & -0.17261822013812 \tabularnewline
161 & 13 & 12.6697064712657 & 0.330293528734267 \tabularnewline
162 & 10 & 9.1641922786923 & 0.8358077213077 \tabularnewline
163 & 14 & 13.0698679990086 & 0.930132000991402 \tabularnewline
164 & 16 & 11.4037249204591 & 4.59627507954092 \tabularnewline
165 & 10 & 11.8118591289607 & -1.81185912896073 \tabularnewline
166 & 11 & 8.97941753928798 & 2.02058246071202 \tabularnewline
167 & 14 & 13.9664048246809 & 0.0335951753191299 \tabularnewline
168 & 12 & 12.7057994263193 & -0.705799426319294 \tabularnewline
169 & 9 & 12.5704222824703 & -3.5704222824703 \tabularnewline
170 & 9 & 11.8000983033848 & -2.8000983033848 \tabularnewline
171 & 11 & 10.4101708871662 & 0.58982911283377 \tabularnewline
172 & 16 & 14.0449888490219 & 1.95501115097814 \tabularnewline
173 & 9 & 13.8540206697084 & -4.85402066970835 \tabularnewline
174 & 13 & 11.1609582405452 & 1.83904175945481 \tabularnewline
175 & 16 & 13.2043999332595 & 2.79560006674048 \tabularnewline
176 & 13 & 15.1225067857976 & -2.12250678579756 \tabularnewline
177 & 9 & 12.1757285461426 & -3.17572854614255 \tabularnewline
178 & 12 & 11.3523223779824 & 0.647677622017567 \tabularnewline
179 & 16 & 14.4088131151256 & 1.59118688487444 \tabularnewline
180 & 11 & 13.0187870441858 & -2.01878704418585 \tabularnewline
181 & 14 & 13.937125537196 & 0.0628744628039876 \tabularnewline
182 & 13 & 14.5783150810428 & -1.57831508104284 \tabularnewline
183 & 15 & 14.5617524237628 & 0.43824757623721 \tabularnewline
184 & 14 & 14.8194598805715 & -0.819459880571533 \tabularnewline
185 & 16 & 13.9480198642468 & 2.05198013575321 \tabularnewline
186 & 13 & 11.5384718303187 & 1.4615281696813 \tabularnewline
187 & 14 & 13.4133033063703 & 0.586696693629732 \tabularnewline
188 & 15 & 14.0808709288739 & 0.919129071126095 \tabularnewline
189 & 13 & 12.3121071941339 & 0.687892805866077 \tabularnewline
190 & 11 & 10.16597852776 & 0.834021472239995 \tabularnewline
191 & 11 & 12.4204413148938 & -1.42044131489381 \tabularnewline
192 & 14 & 14.8652187471899 & -0.865218747189949 \tabularnewline
193 & 15 & 12.6207073712322 & 2.37929262876781 \tabularnewline
194 & 11 & 12.3971592065808 & -1.39715920658077 \tabularnewline
195 & 15 & 13.0046624210895 & 1.99533757891048 \tabularnewline
196 & 12 & 13.9351112439918 & -1.9351112439918 \tabularnewline
197 & 14 & 11.6555247796957 & 2.34447522030434 \tabularnewline
198 & 14 & 13.3228696710797 & 0.677130328920298 \tabularnewline
199 & 8 & 11.0469001139438 & -3.04690011394376 \tabularnewline
200 & 13 & 13.6649716318431 & -0.664971631843059 \tabularnewline
201 & 9 & 12.0707687076154 & -3.07076870761539 \tabularnewline
202 & 15 & 13.660250972557 & 1.339749027443 \tabularnewline
203 & 17 & 13.946336041574 & 3.05366395842604 \tabularnewline
204 & 13 & 12.45003898507 & 0.549961014929986 \tabularnewline
205 & 15 & 14.3333696237075 & 0.666630376292491 \tabularnewline
206 & 15 & 13.6366886977915 & 1.36331130220846 \tabularnewline
207 & 14 & 14.4377790361756 & -0.43777903617556 \tabularnewline
208 & 16 & 12.4164198955123 & 3.58358010448768 \tabularnewline
209 & 13 & 12.814154081408 & 0.185845918591978 \tabularnewline
210 & 16 & 14.2236258940051 & 1.77637410599492 \tabularnewline
211 & 9 & 11.6101994326838 & -2.6101994326838 \tabularnewline
212 & 16 & 14.4717710828748 & 1.5282289171252 \tabularnewline
213 & 11 & 12.1938932607716 & -1.19389326077161 \tabularnewline
214 & 10 & 13.7746617275872 & -3.77466172758721 \tabularnewline
215 & 11 & 12.0580141698025 & -1.05801416980253 \tabularnewline
216 & 15 & 13.2020686706828 & 1.79793132931717 \tabularnewline
217 & 17 & 14.8181524700091 & 2.18184752999092 \tabularnewline
218 & 14 & 14.1757125160018 & -0.17571251600181 \tabularnewline
219 & 8 & 9.88795726840051 & -1.88795726840051 \tabularnewline
220 & 15 & 13.5320404763911 & 1.4679595236089 \tabularnewline
221 & 11 & 13.8113471178154 & -2.81134711781537 \tabularnewline
222 & 16 & 13.4728966227218 & 2.52710337727817 \tabularnewline
223 & 10 & 12.0634333598155 & -2.06343335981552 \tabularnewline
224 & 15 & 14.7457013240318 & 0.254298675968154 \tabularnewline
225 & 9 & 9.48717148853057 & -0.487171488530575 \tabularnewline
226 & 16 & 14.2514051657202 & 1.7485948342798 \tabularnewline
227 & 19 & 13.7243643552316 & 5.27563564476837 \tabularnewline
228 & 12 & 13.575989740931 & -1.575989740931 \tabularnewline
229 & 8 & 9.45853651362965 & -1.45853651362965 \tabularnewline
230 & 11 & 13.2912130157204 & -2.29121301572039 \tabularnewline
231 & 14 & 13.7645155426872 & 0.235484457312813 \tabularnewline
232 & 9 & 11.9919785600196 & -2.99197856001957 \tabularnewline
233 & 15 & 14.8543746169472 & 0.14562538305282 \tabularnewline
234 & 13 & 12.3747409869852 & 0.62525901301484 \tabularnewline
235 & 16 & 14.8304107751693 & 1.16958922483071 \tabularnewline
236 & 11 & 12.7757711448475 & -1.77577114484746 \tabularnewline
237 & 12 & 11.3107875007858 & 0.689212499214227 \tabularnewline
238 & 13 & 12.7594509000875 & 0.240549099912532 \tabularnewline
239 & 10 & 14.2948156222065 & -4.29481562220655 \tabularnewline
240 & 11 & 13.5099587639336 & -2.50995876393355 \tabularnewline
241 & 12 & 14.7831430735995 & -2.78314307359948 \tabularnewline
242 & 8 & 10.6604625366153 & -2.66046253661528 \tabularnewline
243 & 12 & 11.7117817548761 & 0.28821824512392 \tabularnewline
244 & 12 & 12.2229795319503 & -0.222979531950292 \tabularnewline
245 & 15 & 13.4959073824824 & 1.50409261751757 \tabularnewline
246 & 11 & 10.7150321582216 & 0.284967841778399 \tabularnewline
247 & 13 & 12.7082908951198 & 0.291709104880228 \tabularnewline
248 & 14 & 8.80690324580122 & 5.19309675419878 \tabularnewline
249 & 10 & 10.2060272955343 & -0.206027295534266 \tabularnewline
250 & 12 & 11.4985747467212 & 0.50142525327881 \tabularnewline
251 & 15 & 12.8363259750696 & 2.16367402493041 \tabularnewline
252 & 13 & 11.8432665379638 & 1.15673346203618 \tabularnewline
253 & 13 & 14.1054888036805 & -1.10548880368046 \tabularnewline
254 & 13 & 13.6847332080963 & -0.684733208096305 \tabularnewline
255 & 12 & 11.7870514449296 & 0.212948555070412 \tabularnewline
256 & 12 & 12.6362386248472 & -0.636238624847237 \tabularnewline
257 & 9 & 10.8039535443016 & -1.80395354430155 \tabularnewline
258 & 9 & 11.4546703778506 & -2.4546703778506 \tabularnewline
259 & 15 & 12.538019521654 & 2.46198047834603 \tabularnewline
260 & 10 & 14.779709067119 & -4.77970906711905 \tabularnewline
261 & 14 & 13.6328292458703 & 0.367170754129656 \tabularnewline
262 & 15 & 13.4753737182436 & 1.52462628175635 \tabularnewline
263 & 7 & 9.81112874528311 & -2.81112874528311 \tabularnewline
264 & 14 & 13.8176004108226 & 0.182399589177419 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186332&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]14[/C][C]13.9424291052778[/C][C]0.0575708947222239[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]15.3005463901852[/C][C]2.69945360981481[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]13.9940049827717[/C][C]-2.99400498277173[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.5120198142374[/C][C]-2.51201981423739[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]11.2897784894118[/C][C]4.71022151058822[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.4859660706714[/C][C]3.51403392932855[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.8454224517391[/C][C]3.15457754826088[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]15.0964527308549[/C][C]-1.09645273085489[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]15.2452792983004[/C][C]-0.245279298300373[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.4090317627935[/C][C]0.590968237206507[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.5725908577286[/C][C]1.42740914227135[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.6384307227721[/C][C]3.3615692772279[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.4608636173635[/C][C]-3.46086361736351[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.5363928383569[/C][C]2.46360716164312[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.8078164454404[/C][C]2.19218355455959[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.4469693829085[/C][C]0.553030617091464[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.9045842936093[/C][C]0.0954157063906888[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.8450027831948[/C][C]1.15499721680516[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.4589618709725[/C][C]-1.45896187097254[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.8747721081191[/C][C]2.12522789188094[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.4013842993887[/C][C]2.59861570061129[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.7950386582397[/C][C]-2.79503865823973[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.5015428658141[/C][C]-0.501542865814098[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.6321595535868[/C][C]-1.63215955358677[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.4375929891495[/C][C]1.56240701085053[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.9799639285085[/C][C]-6.9799639285085[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]15.1104876388249[/C][C]0.889512361175079[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.394573630841[/C][C]0.60542636915902[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]14.006835659481[/C][C]0.993164340518967[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]14.0322965931152[/C][C]-3.03229659311523[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.7922148715219[/C][C]0.2077851284781[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.7430726197278[/C][C]0.256927380272161[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]15.1627280188488[/C][C]1.83727198115122[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.3804829133968[/C][C]-0.380482913396826[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]14.0433171979075[/C][C]-0.0433171979075127[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.5974511537723[/C][C]0.40254884622773[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.9240291140986[/C][C]-1.92402911409861[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.4154604795384[/C][C]0.584539520461631[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.4428331527567[/C][C]1.5571668472433[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.3158645278038[/C][C]-2.31586452780379[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.8024213686151[/C][C]-0.80242136861515[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.7612392505597[/C][C]2.23876074944031[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]15.9335199131083[/C][C]0.0664800868916651[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.2333694592886[/C][C]-1.23336945928862[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.7198766007734[/C][C]0.280123399226636[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.7079315151914[/C][C]-2.70793151519139[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.4659538792632[/C][C]-0.465953879263151[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.0016977745694[/C][C]-0.00169777456942071[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.6240805312339[/C][C]3.37591946876611[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.8707639239476[/C][C]-1.8707639239476[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.3624126055079[/C][C]0.637587394492092[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.566393122278[/C][C]0.433606877722001[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.8122997813784[/C][C]-0.812299781378398[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.8001418086329[/C][C]-1.80014180863288[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]14.1921484861024[/C][C]-2.19214848610242[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.7953295637062[/C][C]1.20467043629381[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.3400534387739[/C][C]1.65994656122615[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.5943292880403[/C][C]-0.594329288040307[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.3276987259902[/C][C]-3.32769872599024[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.5412045189899[/C][C]-1.54120451898991[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.87864711281[/C][C]-2.87864711280997[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.7492278810461[/C][C]-1.74922788104612[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.7989854205571[/C][C]-3.79898542055711[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.2211219378668[/C][C]0.778878062133185[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.7771758659447[/C][C]1.22282413405526[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]15.0003039743847[/C][C]-5.00030397438468[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.5374802818564[/C][C]-1.5374802818564[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.3973840158749[/C][C]-2.39738401587494[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.4384437746035[/C][C]1.56155622539653[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.552004729982[/C][C]1.44799527001803[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.4359581983165[/C][C]0.564041801683487[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.6384220303279[/C][C]3.36157796967207[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.3674154959497[/C][C]0.632584504050268[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.1815417194463[/C][C]-0.181541719446257[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.8861167434585[/C][C]-1.8861167434585[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]12.1047346234893[/C][C]-0.104734623489337[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]13.9348877282007[/C][C]3.06511227179934[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.4356861536491[/C][C]0.564313846350879[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.7445450852061[/C][C]1.25545491479393[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]14.8788687372443[/C][C]-1.8788687372443[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.8470814804455[/C][C]0.15291851955448[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.4469723636469[/C][C]-0.446972363646926[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.2280096115678[/C][C]1.77199038843215[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.2379365930272[/C][C]0.762063406972782[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.0822726795112[/C][C]-0.0822726795111701[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.9691083281147[/C][C]1.0308916718853[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.2355983417392[/C][C]-0.235598341739223[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.7247497626737[/C][C]0.275250237326259[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.5268885183884[/C][C]-3.52688851838845[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.7019729557851[/C][C]3.29802704421489[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]12.7856188549916[/C][C]0.214381145008435[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.1540759471734[/C][C]0.845924052826577[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.2806169721434[/C][C]0.719383027856592[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.9681085838972[/C][C]-0.968108583897196[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.9421724754068[/C][C]1.0578275245932[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.8040259210165[/C][C]-0.804025921016528[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.839120844214[/C][C]-0.839120844213983[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.9019161673139[/C][C]2.09808383268614[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]15.0115865942469[/C][C]-0.0115865942469205[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.1264543070775[/C][C]1.87354569292246[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]12.9394548918828[/C][C]-0.939454891882777[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]15.0056474946897[/C][C]0.994352505310327[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.401800729261[/C][C]-3.40180072926104[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]13.0994706391478[/C][C]1.9005293608522[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.3859338230185[/C][C]-2.38593382301853[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.9129620556817[/C][C]1.08703794431828[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.9203693712801[/C][C]2.07963062871993[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.8081739605967[/C][C]-2.80817396059672[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.17976388935293[/C][C]0.820236110647068[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.9082823414256[/C][C]1.09171765857444[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.197405972305[/C][C]-2.197405972305[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.296089362601[/C][C]-2.29608936260102[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]11.9022883923422[/C][C]2.09771160765777[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.1102667714145[/C][C]3.88973322858555[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.563402114508[/C][C]0.436597885491982[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]12.9938030066185[/C][C]1.0061969933815[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.8378209323774[/C][C]0.162179067622646[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.080113093972[/C][C]-1.08011309397202[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.7272444663755[/C][C]0.272755533624518[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.5419560707867[/C][C]-0.541956070786677[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.5723691681982[/C][C]0.427630831801833[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.9078069779065[/C][C]0.0921930220934662[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]15.9026490168457[/C][C]-0.902649016845736[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.5733929090885[/C][C]0.426607090911491[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.7585285824057[/C][C]-1.75852858240572[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.1759600034127[/C][C]0.824039996587266[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.2905530842399[/C][C]1.70944691576012[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.9502769223938[/C][C]4.04972307760617[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.5966607630869[/C][C]1.40333923691306[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.6562350761378[/C][C]-1.65623507613778[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.6686224036671[/C][C]-1.66862240366712[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.2970604164897[/C][C]-0.297060416489728[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.6274189354666[/C][C]2.37258106453337[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.2552344754337[/C][C]0.744765524566336[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.7791863129497[/C][C]2.2208136870503[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.47586594208343[/C][C]1.52413405791658[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.352374954921[/C][C]0.647625045078995[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]12.0068197994755[/C][C]-1.00681979947552[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.2041752762271[/C][C]0.795824723772937[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.821331809185[/C][C]-0.82133180918498[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.6578473519901[/C][C]0.342152648009941[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.8796644232709[/C][C]2.12033557672913[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.7113418256964[/C][C]-0.71134182569645[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.3085074433762[/C][C]0.691492556623817[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.6376231429673[/C][C]1.36237685703265[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.5034402025003[/C][C]1.49655979749969[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.4221081205716[/C][C]-2.42210812057161[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.7177384051991[/C][C]-2.71773840519912[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.5819610672325[/C][C]-2.58196106723253[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]14.2850878323269[/C][C]1.71491216767314[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.6157782105665[/C][C]0.384221789433456[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.4557192837466[/C][C]0.544280716253379[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.5013413128903[/C][C]-2.50134131289027[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.9370425459018[/C][C]-2.93704254590182[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.8239727892436[/C][C]1.17602721075642[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.7856188549916[/C][C]0.214381145008435[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.3963455372153[/C][C]0.603654462784655[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.9502769223938[/C][C]4.04972307760617[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.7070253725771[/C][C]-2.70702537257711[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.1726182201381[/C][C]-0.17261822013812[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.6697064712657[/C][C]0.330293528734267[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.1641922786923[/C][C]0.8358077213077[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.0698679990086[/C][C]0.930132000991402[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.4037249204591[/C][C]4.59627507954092[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.8118591289607[/C][C]-1.81185912896073[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]8.97941753928798[/C][C]2.02058246071202[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]13.9664048246809[/C][C]0.0335951753191299[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]12.7057994263193[/C][C]-0.705799426319294[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.5704222824703[/C][C]-3.5704222824703[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.8000983033848[/C][C]-2.8000983033848[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.4101708871662[/C][C]0.58982911283377[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.0449888490219[/C][C]1.95501115097814[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]13.8540206697084[/C][C]-4.85402066970835[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.1609582405452[/C][C]1.83904175945481[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.2043999332595[/C][C]2.79560006674048[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.1225067857976[/C][C]-2.12250678579756[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.1757285461426[/C][C]-3.17572854614255[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.3523223779824[/C][C]0.647677622017567[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.4088131151256[/C][C]1.59118688487444[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.0187870441858[/C][C]-2.01878704418585[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]13.937125537196[/C][C]0.0628744628039876[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.5783150810428[/C][C]-1.57831508104284[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]14.5617524237628[/C][C]0.43824757623721[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]14.8194598805715[/C][C]-0.819459880571533[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]13.9480198642468[/C][C]2.05198013575321[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.5384718303187[/C][C]1.4615281696813[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.4133033063703[/C][C]0.586696693629732[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.0808709288739[/C][C]0.919129071126095[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.3121071941339[/C][C]0.687892805866077[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.16597852776[/C][C]0.834021472239995[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]12.4204413148938[/C][C]-1.42044131489381[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]14.8652187471899[/C][C]-0.865218747189949[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.6207073712322[/C][C]2.37929262876781[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.3971592065808[/C][C]-1.39715920658077[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]13.0046624210895[/C][C]1.99533757891048[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]13.9351112439918[/C][C]-1.9351112439918[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.6555247796957[/C][C]2.34447522030434[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.3228696710797[/C][C]0.677130328920298[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.0469001139438[/C][C]-3.04690011394376[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.6649716318431[/C][C]-0.664971631843059[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]12.0707687076154[/C][C]-3.07076870761539[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.660250972557[/C][C]1.339749027443[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]13.946336041574[/C][C]3.05366395842604[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.45003898507[/C][C]0.549961014929986[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.3333696237075[/C][C]0.666630376292491[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.6366886977915[/C][C]1.36331130220846[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.4377790361756[/C][C]-0.43777903617556[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.4164198955123[/C][C]3.58358010448768[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]12.814154081408[/C][C]0.185845918591978[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.2236258940051[/C][C]1.77637410599492[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.6101994326838[/C][C]-2.6101994326838[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.4717710828748[/C][C]1.5282289171252[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.1938932607716[/C][C]-1.19389326077161[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.7746617275872[/C][C]-3.77466172758721[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]12.0580141698025[/C][C]-1.05801416980253[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.2020686706828[/C][C]1.79793132931717[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.8181524700091[/C][C]2.18184752999092[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.1757125160018[/C][C]-0.17571251600181[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.88795726840051[/C][C]-1.88795726840051[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.5320404763911[/C][C]1.4679595236089[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]13.8113471178154[/C][C]-2.81134711781537[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]13.4728966227218[/C][C]2.52710337727817[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]12.0634333598155[/C][C]-2.06343335981552[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]14.7457013240318[/C][C]0.254298675968154[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.48717148853057[/C][C]-0.487171488530575[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.2514051657202[/C][C]1.7485948342798[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]13.7243643552316[/C][C]5.27563564476837[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.575989740931[/C][C]-1.575989740931[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.45853651362965[/C][C]-1.45853651362965[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.2912130157204[/C][C]-2.29121301572039[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.7645155426872[/C][C]0.235484457312813[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]11.9919785600196[/C][C]-2.99197856001957[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]14.8543746169472[/C][C]0.14562538305282[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.3747409869852[/C][C]0.62525901301484[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]14.8304107751693[/C][C]1.16958922483071[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.7757711448475[/C][C]-1.77577114484746[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.3107875007858[/C][C]0.689212499214227[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]12.7594509000875[/C][C]0.240549099912532[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.2948156222065[/C][C]-4.29481562220655[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.5099587639336[/C][C]-2.50995876393355[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.7831430735995[/C][C]-2.78314307359948[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.6604625366153[/C][C]-2.66046253661528[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.7117817548761[/C][C]0.28821824512392[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.2229795319503[/C][C]-0.222979531950292[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.4959073824824[/C][C]1.50409261751757[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.7150321582216[/C][C]0.284967841778399[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.7082908951198[/C][C]0.291709104880228[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]8.80690324580122[/C][C]5.19309675419878[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]10.2060272955343[/C][C]-0.206027295534266[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.4985747467212[/C][C]0.50142525327881[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.8363259750696[/C][C]2.16367402493041[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.8432665379638[/C][C]1.15673346203618[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.1054888036805[/C][C]-1.10548880368046[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.6847332080963[/C][C]-0.684733208096305[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]11.7870514449296[/C][C]0.212948555070412[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.6362386248472[/C][C]-0.636238624847237[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.8039535443016[/C][C]-1.80395354430155[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.4546703778506[/C][C]-2.4546703778506[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.538019521654[/C][C]2.46198047834603[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.779709067119[/C][C]-4.77970906711905[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.6328292458703[/C][C]0.367170754129656[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.4753737182436[/C][C]1.52462628175635[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.81112874528311[/C][C]-2.81112874528311[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.8176004108226[/C][C]0.182399589177419[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186332&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186332&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11413.94242910527780.0575708947222239
21815.30054639018522.69945360981481
31113.9940049827717-2.99400498277173
41214.5120198142374-2.51201981423739
51611.28977848941184.71022151058822
61814.48596607067143.51403392932855
71410.84542245173913.15457754826088
81415.0964527308549-1.09645273085489
91515.2452792983004-0.245279298300373
101514.40903176279350.590968237206507
111715.57259085772861.42740914227135
121915.63843072277213.3615692772279
131013.4608636173635-3.46086361736351
141613.53639283835692.46360716164312
151815.80781644544042.19218355455959
161413.44696938290850.553030617091464
171413.90458429360930.0954157063906888
181715.84500278319481.15499721680516
191415.4589618709725-1.45896187097254
201613.87477210811912.12522789188094
211815.40138429938872.59861570061129
221113.7950386582397-2.79503865823973
231414.5015428658141-0.501542865814098
241213.6321595535868-1.63215955358677
251715.43759298914951.56240701085053
26915.9799639285085-6.9799639285085
271615.11048763882490.889512361175079
281413.3945736308410.60542636915902
291514.0068356594810.993164340518967
301114.0322965931152-3.03229659311523
311615.79221487152190.2077851284781
321312.74307261972780.256927380272161
331715.16272801884881.83727198115122
341515.3804829133968-0.380482913396826
351414.0433171979075-0.0433171979075127
361615.59745115377230.40254884622773
37910.9240291140986-1.92402911409861
381514.41546047953840.584539520461631
391715.44283315275671.5571668472433
401315.3158645278038-2.31586452780379
411515.8024213686151-0.80242136861515
421613.76123925055972.23876074944031
431615.93351991310830.0664800868916651
441213.2333694592886-1.23336945928862
451514.71987660077340.280123399226636
461113.7079315151914-2.70793151519139
471515.4659538792632-0.465953879263151
481515.0016977745694-0.00169777456942071
491713.62408053123393.37591946876611
501314.8707639239476-1.8707639239476
511615.36241260550790.637587394492092
521413.5663931222780.433606877722001
531111.8122997813784-0.812299781378398
541213.8001418086329-1.80014180863288
551214.1921484861024-2.19214848610242
561513.79532956370621.20467043629381
571614.34005343877391.65994656122615
581515.5943292880403-0.594329288040307
591215.3276987259902-3.32769872599024
601213.5412045189899-1.54120451898991
61810.87864711281-2.87864711280997
621314.7492278810461-1.74922788104612
631114.7989854205571-3.79898542055711
641413.22112193786680.778878062133185
651513.77717586594471.22282413405526
661015.0003039743847-5.00030397438468
671112.5374802818564-1.5374802818564
681214.3973840158749-2.39738401587494
691513.43844377460351.56155622539653
701513.5520047299821.44799527001803
711413.43595819831650.564041801683487
721612.63842203032793.36157796967207
731514.36741549594970.632584504050268
741515.1815417194463-0.181541719446257
751314.8861167434585-1.8861167434585
761212.1047346234893-0.104734623489337
771713.93488772820073.06511227179934
781312.43568615364910.564313846350879
791513.74454508520611.25545491479393
801314.8788687372443-1.8788687372443
811514.84708148044550.15291851955448
821515.4469723636469-0.446972363646926
831614.22800961156781.77199038843215
841514.23793659302720.762063406972782
851414.0822726795112-0.0822726795111701
861513.96910832811471.0308916718853
871414.2355983417392-0.235598341739223
881312.72474976267370.275250237326259
89710.5268885183884-3.52688851838845
901713.70197295578513.29802704421489
911312.78561885499160.214381145008435
921514.15407594717340.845924052826577
931413.28061697214340.719383027856592
941313.9681085838972-0.968108583897196
951614.94217247540681.0578275245932
961212.8040259210165-0.804025921016528
971414.839120844214-0.839120844213983
981714.90191616731392.09808383268614
991515.0115865942469-0.0115865942469205
1001715.12645430707751.87354569292246
1011212.9394548918828-0.939454891882777
1021615.00564749468970.994352505310327
1031114.401800729261-3.40180072926104
1041513.09947063914781.9005293608522
105911.3859338230185-2.38593382301853
1061614.91296205568171.08703794431828
1071512.92036937128012.07963062871993
1081012.8081739605967-2.80817396059672
109109.179763889352930.820236110647068
1101513.90828234142561.09171765857444
1111113.197405972305-2.197405972305
1121315.296089362601-2.29608936260102
1131411.90228839234222.09771160765777
1141814.11026677141453.88973322858555
1151615.5634021145080.436597885491982
1161412.99380300661851.0061969933815
1171413.83782093237740.162179067622646
1181415.080113093972-1.08011309397202
1191413.72724446637550.272755533624518
1201212.5419560707867-0.541956070786677
1211413.57236916819820.427630831801833
1221514.90780697790650.0921930220934662
1231515.9026490168457-0.902649016845736
1241514.57339290908850.426607090911491
1251314.7585285824057-1.75852858240572
1261716.17596000341270.824039996587266
1271715.29055308423991.70944691576012
1281914.95027692239384.04972307760617
1291513.59666076308691.40333923691306
1301314.6562350761378-1.65623507613778
131910.6686224036671-1.66862240366712
1321515.2970604164897-0.297060416489728
1331512.62741893546662.37258106453337
1341514.25523447543370.744765524566336
1351613.77918631294972.2208136870503
136119.475865942083431.52413405791658
1371413.3523749549210.647625045078995
1381112.0068197994755-1.00681979947552
1391514.20417527622710.795824723772937
1401313.821331809185-0.82133180918498
1411514.65784735199010.342152648009941
1421613.87966442327092.12033557672913
1431414.7113418256964-0.71134182569645
1441514.30850744337620.691492556623817
1451614.63762314296731.36237685703265
1461614.50344020250031.49655979749969
1471113.4221081205716-2.42210812057161
1481214.7177384051991-2.71773840519912
149911.5819610672325-2.58196106723253
1501614.28508783232691.71491216767314
1511312.61577821056650.384221789433456
1521615.45571928374660.544280716253379
1531214.5013413128903-2.50134131289027
154911.9370425459018-2.93704254590182
1551311.82397278924361.17602721075642
1561312.78561885499160.214381145008435
1571413.39634553721530.603654462784655
1581914.95027692239384.04972307760617
1591315.7070253725771-2.70702537257711
1601212.1726182201381-0.17261822013812
1611312.66970647126570.330293528734267
162109.16419227869230.8358077213077
1631413.06986799900860.930132000991402
1641611.40372492045914.59627507954092
1651011.8118591289607-1.81185912896073
166118.979417539287982.02058246071202
1671413.96640482468090.0335951753191299
1681212.7057994263193-0.705799426319294
169912.5704222824703-3.5704222824703
170911.8000983033848-2.8000983033848
1711110.41017088716620.58982911283377
1721614.04498884902191.95501115097814
173913.8540206697084-4.85402066970835
1741311.16095824054521.83904175945481
1751613.20439993325952.79560006674048
1761315.1225067857976-2.12250678579756
177912.1757285461426-3.17572854614255
1781211.35232237798240.647677622017567
1791614.40881311512561.59118688487444
1801113.0187870441858-2.01878704418585
1811413.9371255371960.0628744628039876
1821314.5783150810428-1.57831508104284
1831514.56175242376280.43824757623721
1841414.8194598805715-0.819459880571533
1851613.94801986424682.05198013575321
1861311.53847183031871.4615281696813
1871413.41330330637030.586696693629732
1881514.08087092887390.919129071126095
1891312.31210719413390.687892805866077
1901110.165978527760.834021472239995
1911112.4204413148938-1.42044131489381
1921414.8652187471899-0.865218747189949
1931512.62070737123222.37929262876781
1941112.3971592065808-1.39715920658077
1951513.00466242108951.99533757891048
1961213.9351112439918-1.9351112439918
1971411.65552477969572.34447522030434
1981413.32286967107970.677130328920298
199811.0469001139438-3.04690011394376
2001313.6649716318431-0.664971631843059
201912.0707687076154-3.07076870761539
2021513.6602509725571.339749027443
2031713.9463360415743.05366395842604
2041312.450038985070.549961014929986
2051514.33336962370750.666630376292491
2061513.63668869779151.36331130220846
2071414.4377790361756-0.43777903617556
2081612.41641989551233.58358010448768
2091312.8141540814080.185845918591978
2101614.22362589400511.77637410599492
211911.6101994326838-2.6101994326838
2121614.47177108287481.5282289171252
2131112.1938932607716-1.19389326077161
2141013.7746617275872-3.77466172758721
2151112.0580141698025-1.05801416980253
2161513.20206867068281.79793132931717
2171714.81815247000912.18184752999092
2181414.1757125160018-0.17571251600181
21989.88795726840051-1.88795726840051
2201513.53204047639111.4679595236089
2211113.8113471178154-2.81134711781537
2221613.47289662272182.52710337727817
2231012.0634333598155-2.06343335981552
2241514.74570132403180.254298675968154
22599.48717148853057-0.487171488530575
2261614.25140516572021.7485948342798
2271913.72436435523165.27563564476837
2281213.575989740931-1.575989740931
22989.45853651362965-1.45853651362965
2301113.2912130157204-2.29121301572039
2311413.76451554268720.235484457312813
232911.9919785600196-2.99197856001957
2331514.85437461694720.14562538305282
2341312.37474098698520.62525901301484
2351614.83041077516931.16958922483071
2361112.7757711448475-1.77577114484746
2371211.31078750078580.689212499214227
2381312.75945090008750.240549099912532
2391014.2948156222065-4.29481562220655
2401113.5099587639336-2.50995876393355
2411214.7831430735995-2.78314307359948
242810.6604625366153-2.66046253661528
2431211.71178175487610.28821824512392
2441212.2229795319503-0.222979531950292
2451513.49590738248241.50409261751757
2461110.71503215822160.284967841778399
2471312.70829089511980.291709104880228
248148.806903245801225.19309675419878
2491010.2060272955343-0.206027295534266
2501211.49857474672120.50142525327881
2511512.83632597506962.16367402493041
2521311.84326653796381.15673346203618
2531314.1054888036805-1.10548880368046
2541313.6847332080963-0.684733208096305
2551211.78705144492960.212948555070412
2561212.6362386248472-0.636238624847237
257910.8039535443016-1.80395354430155
258911.4546703778506-2.4546703778506
2591512.5380195216542.46198047834603
2601014.779709067119-4.77970906711905
2611413.63282924587030.367170754129656
2621513.47537371824361.52462628175635
26379.81112874528311-2.81112874528311
2641413.81760041082260.182399589177419







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.824602542649830.350794914700340.17539745735017
130.981778694293190.03644261141361960.0182213057068098
140.9650414803473790.06991703930524250.0349585196526213
150.9654156884901910.06916862301961780.0345843115098089
160.9429828863923190.1140342272153610.0570171136076807
170.966857298638730.0662854027225390.0331427013612695
180.9467112021378590.1065775957242820.0532887978621411
190.9191384441376690.1617231117246630.0808615558623314
200.9153086631965360.1693826736069270.0846913368034635
210.9374245394737220.1251509210525550.0625754605262776
220.9350616472460310.1298767055079370.0649383527539687
230.9350480906318570.1299038187362860.0649519093681428
240.9112744763297450.177451047340510.0887255236702548
250.89091390484640.21817219030720.1090860951536
260.9993054628773450.00138907424531030.000694537122655151
270.9988675316225490.002264936754902670.00113246837745134
280.9981580100119660.003683979976068710.00184198998803436
290.9971098941454120.005780211709175610.00289010585458781
300.9980494003810540.003901199237891250.00195059961894562
310.9969845530356010.006030893928797740.00301544696439887
320.9955757706820550.008848458635889740.00442422931794487
330.9945482763956850.01090344720863080.00545172360431541
340.99200536018060.01598927963880030.00799463981940013
350.9900161407538940.01996771849221290.00998385924610647
360.9859340535550380.02813189288992290.0140659464449615
370.9905733722837960.01885325543240710.00942662771620356
380.9867889108217570.02642217835648690.0132110891782435
390.9846131832785750.03077363344284990.015386816721425
400.9849598797891060.03008024042178870.0150401202108943
410.9801320034692570.03973599306148610.0198679965307431
420.9777202961300140.04455940773997220.0222797038699861
430.9703716419802390.05925671603952290.0296283580197615
440.965038166228220.06992366754356010.03496183377178
450.9545403302084530.09091933958309360.0454596697915468
460.9629168469020180.07416630619596420.0370831530979821
470.9523810506926610.09523789861467770.0476189493073388
480.9392687441595580.1214625116808840.0607312558404422
490.9478157413772130.1043685172455750.0521842586227873
500.9446170388435070.1107659223129850.0553829611564927
510.9317375912723670.1365248174552660.068262408727633
520.9155391405322360.1689217189355280.0844608594677638
530.9028653644327690.1942692711344620.0971346355672311
540.8879376710649880.2241246578700240.112062328935012
550.8828114675481890.2343770649036210.117188532451811
560.8644378525198070.2711242949603870.135562147480193
570.8505108098920650.298978380215870.149489190107935
580.8237208337282020.3525583325435970.176279166271798
590.8652140153713240.2695719692573530.134785984628676
600.8622152563391520.2755694873216970.137784743660848
610.8828827287303490.2342345425393030.117117271269651
620.8837586238753820.2324827522492360.116241376124618
630.9316622493233440.1366755013533120.0683377506766561
640.9201595902730380.1596808194539250.0798404097269624
650.9097637619642020.1804724760715960.0902362380357978
660.9208391159170380.1583217681659250.0791608840829624
670.9200248495856070.1599503008287850.0799751504143927
680.9112333829815990.1775332340368030.0887666170184015
690.9419334892476920.1161330215046160.0580665107523081
700.9463850286728780.1072299426542430.0536149713271216
710.9410903117011440.1178193765977130.0589096882988564
720.9610685993721080.07786280125578430.0389314006278922
730.9525882934521930.0948234130956140.047411706547807
740.9419988848268330.1160022303463340.0580011151731672
750.9351435406471360.1297129187057280.0648564593528642
760.9215827283161820.1568345433676360.0784172716838182
770.9376191050019120.1247617899961760.062380894998088
780.9260443131059370.1479113737881250.0739556868940626
790.9196729316375490.1606541367249010.0803270683624506
800.9129940485133820.1740119029732370.0870059514866183
810.8964426778225830.2071146443548340.103557322177417
820.878486239475080.2430275210498390.12151376052492
830.8729402074762950.254119585047410.127059792523705
840.85461548487850.2907690302430010.1453845151215
850.8315743477394250.3368513045211510.168425652260575
860.8089793535819460.3820412928361080.191020646418054
870.782155084002830.4356898319943410.21784491599717
880.7531750843135770.4936498313728450.246824915686423
890.8216600239044590.3566799521910820.178339976095541
900.8525552990290930.2948894019418140.147444700970907
910.8304485324048980.3391029351902040.169551467595102
920.8076856884305410.3846286231389180.192314311569459
930.7855125738005840.4289748523988310.214487426199416
940.7629786572706580.4740426854586840.237021342729342
950.7373131007499810.5253737985000370.262686899250018
960.7127450716168620.5745098567662760.287254928383138
970.6866165178930390.6267669642139220.313383482106961
980.6844393831964760.6311212336070480.315560616803524
990.6509307035796140.6981385928407730.349069296420386
1000.6402802233186530.7194395533626940.359719776681347
1010.6166552358468490.7666895283063020.383344764153151
1020.5869787733655160.8260424532689680.413021226634484
1030.63776445222010.72447109555980.3622355477799
1040.6232515253359980.7534969493280030.376748474664001
1050.6406184043804810.7187631912390380.359381595619519
1060.6139059610730240.7721880778539510.386094038926976
1070.6038050955426750.792389808914650.396194904457325
1080.6444252206269760.7111495587460480.355574779373024
1090.6135763786821540.7728472426356920.386423621317846
1100.5865528837687230.8268942324625550.413447116231277
1110.594182240658490.8116355186830190.40581775934151
1120.6216039283088350.756792143382330.378396071691165
1130.6094306696165190.7811386607669610.390569330383481
1140.6962027419160570.6075945161678850.303797258083943
1150.666377513424770.667244973150460.33362248657523
1160.6396917442259350.7206165115481290.360308255774065
1170.6057963367177180.7884073265645650.394203663282282
1180.5818410025598140.8363179948803720.418158997440186
1190.5467664915094260.9064670169811490.453233508490574
1200.5147750653643710.9704498692712580.485224934635629
1210.485557683339740.971115366679480.51444231666026
1220.4526752348959430.9053504697918860.547324765104057
1230.4255573844951980.8511147689903960.574442615504802
1240.3936193206894210.7872386413788420.606380679310579
1250.385307080076110.770614160152220.61469291992389
1260.3556514833808990.7113029667617990.644348516619101
1270.3394173324743540.6788346649487090.660582667525646
1280.4413203963592380.8826407927184750.558679603640762
1290.4219599171849860.8439198343699720.578040082815014
1300.4123350283436240.8246700566872470.587664971656376
1310.4002157958906950.800431591781390.599784204109305
1320.3710175039066770.7420350078133540.628982496093323
1330.3881900577568240.7763801155136480.611809942243176
1340.358790956430760.7175819128615210.64120904356924
1350.3679911969083560.7359823938167130.632008803091644
1360.3564304781079510.7128609562159020.643569521892049
1370.3266032482224650.6532064964449290.673396751777535
1380.3029969825388620.6059939650777250.697003017461138
1390.2763368341512690.5526736683025390.723663165848731
1400.2530762052489930.5061524104979850.746923794751007
1410.225734704916720.451469409833440.77426529508328
1420.2295534369013910.4591068738027820.770446563098609
1430.2050451965217390.4100903930434780.794954803478261
1440.1845740534315290.3691481068630590.815425946568471
1450.1724349721289250.344869944257850.827565027871075
1460.1651669547514530.3303339095029060.834833045248547
1470.1727366632416320.3454733264832650.827263336758368
1480.1901569661308620.3803139322617250.809843033869138
1490.2096525467786260.4193050935572520.790347453221374
1500.2062888768365880.4125777536731770.793711123163412
1510.184599718531020.369199437062040.81540028146898
1520.1650015217944860.3300030435889720.834998478205514
1530.1784311045572890.3568622091145780.821568895442711
1540.2141099602417420.4282199204834840.785890039758258
1550.192741633501910.3854832670038190.80725836649809
1560.17266804540080.3453360908016010.8273319545992
1570.1505634424938780.3011268849877550.849436557506122
1580.2204375626723140.4408751253446280.779562437327686
1590.2462644289238180.4925288578476370.753735571076182
1600.2206639057116520.4413278114233030.779336094288348
1610.1942107192365050.3884214384730110.805789280763495
1620.1717107775267910.3434215550535830.828289222473209
1630.1517180536005210.3034361072010420.848281946399479
1640.2549861601847720.5099723203695450.745013839815228
1650.2517756648163370.5035513296326730.748224335183663
1660.2475902730703010.4951805461406020.752409726929699
1670.2197228229996330.4394456459992670.780277177000367
1680.197981063776220.3959621275524390.80201893622378
1690.2518548714735910.5037097429471810.748145128526409
1700.2741967238195930.5483934476391860.725803276180407
1710.2470321915239890.4940643830479770.752967808476012
1720.2434023665011640.4868047330023270.756597633498836
1730.3970396666899010.7940793333798020.602960333310099
1740.3854990678503170.7709981357006340.614500932149683
1750.4108125572404740.8216251144809480.589187442759526
1760.4165598393404750.833119678680950.583440160659525
1770.4676120497333540.9352240994667080.532387950266646
1780.4345039752203570.8690079504407130.565496024779643
1790.4147880357253230.8295760714506450.585211964274677
1800.4106070350411410.8212140700822810.589392964958859
1810.3735847744812970.7471695489625930.626415225518703
1820.3628926197727660.7257852395455320.637107380227234
1830.3273771634324430.6547543268648870.672622836567557
1840.2994867802110880.5989735604221760.700513219788912
1850.3151793410752440.6303586821504870.684820658924756
1860.3091116572688820.6182233145377640.690888342731118
1870.2768253767499160.5536507534998330.723174623250084
1880.2515654067364810.5031308134729610.748434593263519
1890.2228533639525960.4457067279051920.777146636047404
1900.2016452156539430.4032904313078850.798354784346057
1910.2041603372245270.4083206744490550.795839662775473
1920.1857674460715830.3715348921431660.814232553928417
1930.2038206196729670.4076412393459340.796179380327033
1940.1901276967195720.3802553934391450.809872303280428
1950.1909504085150640.3819008170301290.809049591484936
1960.1984250248339120.3968500496678230.801574975166088
1970.2436983755793150.487396751158630.756301624420685
1980.2264933759012680.4529867518025360.773506624098732
1990.2545526712013020.5091053424026030.745447328798698
2000.2228832229270510.4457664458541010.777116777072949
2010.2531556261620890.5063112523241790.746844373837911
2020.2341571897875990.4683143795751990.765842810212401
2030.2944763846035510.5889527692071010.705523615396449
2040.2610279214360.5220558428719990.738972078564
2050.2293372923506260.4586745847012520.770662707649374
2060.2103620716838270.4207241433676540.789637928316173
2070.1804222224348760.3608444448697520.819577777565124
2080.201874707627470.403749415254940.79812529237253
2090.1720505099442660.3441010198885320.827949490055734
2100.1878747564404240.3757495128808480.812125243559576
2110.2113668245277440.4227336490554870.788633175472256
2120.1973057646166280.3946115292332570.802694235383372
2130.1713029832724760.3426059665449530.828697016727524
2140.2135029488033120.4270058976066230.786497051196688
2150.1872639114271580.3745278228543160.812736088572842
2160.176294270546370.352588541092740.82370572945363
2170.2072521895522490.4145043791044980.792747810447751
2180.1785209800246890.3570419600493790.821479019975311
2190.1647657231028260.3295314462056520.835234276897174
2200.1717878310211760.3435756620423520.828212168978824
2210.1767013009497220.3534026018994430.823298699050278
2220.1790197438448080.3580394876896160.820980256155192
2230.1630871488708270.3261742977416550.836912851129173
2240.1345194990116310.2690389980232610.865480500988369
2250.1205513326062940.2411026652125880.879448667393706
2260.1453517615123380.2907035230246770.854648238487662
2270.3235967928077370.6471935856154730.676403207192263
2280.2997899800964010.5995799601928020.700210019903599
2290.2732574510577910.5465149021155830.726742548942209
2300.2570740867107210.5141481734214420.742925913289279
2310.2174474026629380.4348948053258750.782552597337063
2320.250767425512950.5015348510258990.74923257448705
2330.2094739901235950.4189479802471910.790526009876405
2340.172361110736720.344722221473440.82763888926328
2350.171193389272290.342386778544580.82880661072771
2360.148734723918950.29746944783790.85126527608105
2370.1220284053152760.2440568106305520.877971594684724
2380.09261159435332490.185223188706650.907388405646675
2390.1870825958248880.3741651916497750.812917404175112
2400.1808893362733320.3617786725466650.819110663726668
2410.1521372467964330.3042744935928650.847862753203567
2420.3229730912479790.6459461824959590.677026908752021
2430.2805913401666420.5611826803332840.719408659833358
2440.2256335505048060.4512671010096120.774366449495194
2450.3382818923844680.6765637847689370.661718107615532
2460.2589168191725340.5178336383450680.741083180827466
2470.1904925699464830.3809851398929650.809507430053517
2480.3093072274135070.6186144548270140.690692772586493
2490.2234956728859870.4469913457719730.776504327114013
2500.1481990714849920.2963981429699830.851800928515008
2510.2358895996966610.4717791993933220.764110400303339
2520.7436685821612590.5126628356774830.256331417838741

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.82460254264983 & 0.35079491470034 & 0.17539745735017 \tabularnewline
13 & 0.98177869429319 & 0.0364426114136196 & 0.0182213057068098 \tabularnewline
14 & 0.965041480347379 & 0.0699170393052425 & 0.0349585196526213 \tabularnewline
15 & 0.965415688490191 & 0.0691686230196178 & 0.0345843115098089 \tabularnewline
16 & 0.942982886392319 & 0.114034227215361 & 0.0570171136076807 \tabularnewline
17 & 0.96685729863873 & 0.066285402722539 & 0.0331427013612695 \tabularnewline
18 & 0.946711202137859 & 0.106577595724282 & 0.0532887978621411 \tabularnewline
19 & 0.919138444137669 & 0.161723111724663 & 0.0808615558623314 \tabularnewline
20 & 0.915308663196536 & 0.169382673606927 & 0.0846913368034635 \tabularnewline
21 & 0.937424539473722 & 0.125150921052555 & 0.0625754605262776 \tabularnewline
22 & 0.935061647246031 & 0.129876705507937 & 0.0649383527539687 \tabularnewline
23 & 0.935048090631857 & 0.129903818736286 & 0.0649519093681428 \tabularnewline
24 & 0.911274476329745 & 0.17745104734051 & 0.0887255236702548 \tabularnewline
25 & 0.8909139048464 & 0.2181721903072 & 0.1090860951536 \tabularnewline
26 & 0.999305462877345 & 0.0013890742453103 & 0.000694537122655151 \tabularnewline
27 & 0.998867531622549 & 0.00226493675490267 & 0.00113246837745134 \tabularnewline
28 & 0.998158010011966 & 0.00368397997606871 & 0.00184198998803436 \tabularnewline
29 & 0.997109894145412 & 0.00578021170917561 & 0.00289010585458781 \tabularnewline
30 & 0.998049400381054 & 0.00390119923789125 & 0.00195059961894562 \tabularnewline
31 & 0.996984553035601 & 0.00603089392879774 & 0.00301544696439887 \tabularnewline
32 & 0.995575770682055 & 0.00884845863588974 & 0.00442422931794487 \tabularnewline
33 & 0.994548276395685 & 0.0109034472086308 & 0.00545172360431541 \tabularnewline
34 & 0.9920053601806 & 0.0159892796388003 & 0.00799463981940013 \tabularnewline
35 & 0.990016140753894 & 0.0199677184922129 & 0.00998385924610647 \tabularnewline
36 & 0.985934053555038 & 0.0281318928899229 & 0.0140659464449615 \tabularnewline
37 & 0.990573372283796 & 0.0188532554324071 & 0.00942662771620356 \tabularnewline
38 & 0.986788910821757 & 0.0264221783564869 & 0.0132110891782435 \tabularnewline
39 & 0.984613183278575 & 0.0307736334428499 & 0.015386816721425 \tabularnewline
40 & 0.984959879789106 & 0.0300802404217887 & 0.0150401202108943 \tabularnewline
41 & 0.980132003469257 & 0.0397359930614861 & 0.0198679965307431 \tabularnewline
42 & 0.977720296130014 & 0.0445594077399722 & 0.0222797038699861 \tabularnewline
43 & 0.970371641980239 & 0.0592567160395229 & 0.0296283580197615 \tabularnewline
44 & 0.96503816622822 & 0.0699236675435601 & 0.03496183377178 \tabularnewline
45 & 0.954540330208453 & 0.0909193395830936 & 0.0454596697915468 \tabularnewline
46 & 0.962916846902018 & 0.0741663061959642 & 0.0370831530979821 \tabularnewline
47 & 0.952381050692661 & 0.0952378986146777 & 0.0476189493073388 \tabularnewline
48 & 0.939268744159558 & 0.121462511680884 & 0.0607312558404422 \tabularnewline
49 & 0.947815741377213 & 0.104368517245575 & 0.0521842586227873 \tabularnewline
50 & 0.944617038843507 & 0.110765922312985 & 0.0553829611564927 \tabularnewline
51 & 0.931737591272367 & 0.136524817455266 & 0.068262408727633 \tabularnewline
52 & 0.915539140532236 & 0.168921718935528 & 0.0844608594677638 \tabularnewline
53 & 0.902865364432769 & 0.194269271134462 & 0.0971346355672311 \tabularnewline
54 & 0.887937671064988 & 0.224124657870024 & 0.112062328935012 \tabularnewline
55 & 0.882811467548189 & 0.234377064903621 & 0.117188532451811 \tabularnewline
56 & 0.864437852519807 & 0.271124294960387 & 0.135562147480193 \tabularnewline
57 & 0.850510809892065 & 0.29897838021587 & 0.149489190107935 \tabularnewline
58 & 0.823720833728202 & 0.352558332543597 & 0.176279166271798 \tabularnewline
59 & 0.865214015371324 & 0.269571969257353 & 0.134785984628676 \tabularnewline
60 & 0.862215256339152 & 0.275569487321697 & 0.137784743660848 \tabularnewline
61 & 0.882882728730349 & 0.234234542539303 & 0.117117271269651 \tabularnewline
62 & 0.883758623875382 & 0.232482752249236 & 0.116241376124618 \tabularnewline
63 & 0.931662249323344 & 0.136675501353312 & 0.0683377506766561 \tabularnewline
64 & 0.920159590273038 & 0.159680819453925 & 0.0798404097269624 \tabularnewline
65 & 0.909763761964202 & 0.180472476071596 & 0.0902362380357978 \tabularnewline
66 & 0.920839115917038 & 0.158321768165925 & 0.0791608840829624 \tabularnewline
67 & 0.920024849585607 & 0.159950300828785 & 0.0799751504143927 \tabularnewline
68 & 0.911233382981599 & 0.177533234036803 & 0.0887666170184015 \tabularnewline
69 & 0.941933489247692 & 0.116133021504616 & 0.0580665107523081 \tabularnewline
70 & 0.946385028672878 & 0.107229942654243 & 0.0536149713271216 \tabularnewline
71 & 0.941090311701144 & 0.117819376597713 & 0.0589096882988564 \tabularnewline
72 & 0.961068599372108 & 0.0778628012557843 & 0.0389314006278922 \tabularnewline
73 & 0.952588293452193 & 0.094823413095614 & 0.047411706547807 \tabularnewline
74 & 0.941998884826833 & 0.116002230346334 & 0.0580011151731672 \tabularnewline
75 & 0.935143540647136 & 0.129712918705728 & 0.0648564593528642 \tabularnewline
76 & 0.921582728316182 & 0.156834543367636 & 0.0784172716838182 \tabularnewline
77 & 0.937619105001912 & 0.124761789996176 & 0.062380894998088 \tabularnewline
78 & 0.926044313105937 & 0.147911373788125 & 0.0739556868940626 \tabularnewline
79 & 0.919672931637549 & 0.160654136724901 & 0.0803270683624506 \tabularnewline
80 & 0.912994048513382 & 0.174011902973237 & 0.0870059514866183 \tabularnewline
81 & 0.896442677822583 & 0.207114644354834 & 0.103557322177417 \tabularnewline
82 & 0.87848623947508 & 0.243027521049839 & 0.12151376052492 \tabularnewline
83 & 0.872940207476295 & 0.25411958504741 & 0.127059792523705 \tabularnewline
84 & 0.8546154848785 & 0.290769030243001 & 0.1453845151215 \tabularnewline
85 & 0.831574347739425 & 0.336851304521151 & 0.168425652260575 \tabularnewline
86 & 0.808979353581946 & 0.382041292836108 & 0.191020646418054 \tabularnewline
87 & 0.78215508400283 & 0.435689831994341 & 0.21784491599717 \tabularnewline
88 & 0.753175084313577 & 0.493649831372845 & 0.246824915686423 \tabularnewline
89 & 0.821660023904459 & 0.356679952191082 & 0.178339976095541 \tabularnewline
90 & 0.852555299029093 & 0.294889401941814 & 0.147444700970907 \tabularnewline
91 & 0.830448532404898 & 0.339102935190204 & 0.169551467595102 \tabularnewline
92 & 0.807685688430541 & 0.384628623138918 & 0.192314311569459 \tabularnewline
93 & 0.785512573800584 & 0.428974852398831 & 0.214487426199416 \tabularnewline
94 & 0.762978657270658 & 0.474042685458684 & 0.237021342729342 \tabularnewline
95 & 0.737313100749981 & 0.525373798500037 & 0.262686899250018 \tabularnewline
96 & 0.712745071616862 & 0.574509856766276 & 0.287254928383138 \tabularnewline
97 & 0.686616517893039 & 0.626766964213922 & 0.313383482106961 \tabularnewline
98 & 0.684439383196476 & 0.631121233607048 & 0.315560616803524 \tabularnewline
99 & 0.650930703579614 & 0.698138592840773 & 0.349069296420386 \tabularnewline
100 & 0.640280223318653 & 0.719439553362694 & 0.359719776681347 \tabularnewline
101 & 0.616655235846849 & 0.766689528306302 & 0.383344764153151 \tabularnewline
102 & 0.586978773365516 & 0.826042453268968 & 0.413021226634484 \tabularnewline
103 & 0.6377644522201 & 0.7244710955598 & 0.3622355477799 \tabularnewline
104 & 0.623251525335998 & 0.753496949328003 & 0.376748474664001 \tabularnewline
105 & 0.640618404380481 & 0.718763191239038 & 0.359381595619519 \tabularnewline
106 & 0.613905961073024 & 0.772188077853951 & 0.386094038926976 \tabularnewline
107 & 0.603805095542675 & 0.79238980891465 & 0.396194904457325 \tabularnewline
108 & 0.644425220626976 & 0.711149558746048 & 0.355574779373024 \tabularnewline
109 & 0.613576378682154 & 0.772847242635692 & 0.386423621317846 \tabularnewline
110 & 0.586552883768723 & 0.826894232462555 & 0.413447116231277 \tabularnewline
111 & 0.59418224065849 & 0.811635518683019 & 0.40581775934151 \tabularnewline
112 & 0.621603928308835 & 0.75679214338233 & 0.378396071691165 \tabularnewline
113 & 0.609430669616519 & 0.781138660766961 & 0.390569330383481 \tabularnewline
114 & 0.696202741916057 & 0.607594516167885 & 0.303797258083943 \tabularnewline
115 & 0.66637751342477 & 0.66724497315046 & 0.33362248657523 \tabularnewline
116 & 0.639691744225935 & 0.720616511548129 & 0.360308255774065 \tabularnewline
117 & 0.605796336717718 & 0.788407326564565 & 0.394203663282282 \tabularnewline
118 & 0.581841002559814 & 0.836317994880372 & 0.418158997440186 \tabularnewline
119 & 0.546766491509426 & 0.906467016981149 & 0.453233508490574 \tabularnewline
120 & 0.514775065364371 & 0.970449869271258 & 0.485224934635629 \tabularnewline
121 & 0.48555768333974 & 0.97111536667948 & 0.51444231666026 \tabularnewline
122 & 0.452675234895943 & 0.905350469791886 & 0.547324765104057 \tabularnewline
123 & 0.425557384495198 & 0.851114768990396 & 0.574442615504802 \tabularnewline
124 & 0.393619320689421 & 0.787238641378842 & 0.606380679310579 \tabularnewline
125 & 0.38530708007611 & 0.77061416015222 & 0.61469291992389 \tabularnewline
126 & 0.355651483380899 & 0.711302966761799 & 0.644348516619101 \tabularnewline
127 & 0.339417332474354 & 0.678834664948709 & 0.660582667525646 \tabularnewline
128 & 0.441320396359238 & 0.882640792718475 & 0.558679603640762 \tabularnewline
129 & 0.421959917184986 & 0.843919834369972 & 0.578040082815014 \tabularnewline
130 & 0.412335028343624 & 0.824670056687247 & 0.587664971656376 \tabularnewline
131 & 0.400215795890695 & 0.80043159178139 & 0.599784204109305 \tabularnewline
132 & 0.371017503906677 & 0.742035007813354 & 0.628982496093323 \tabularnewline
133 & 0.388190057756824 & 0.776380115513648 & 0.611809942243176 \tabularnewline
134 & 0.35879095643076 & 0.717581912861521 & 0.64120904356924 \tabularnewline
135 & 0.367991196908356 & 0.735982393816713 & 0.632008803091644 \tabularnewline
136 & 0.356430478107951 & 0.712860956215902 & 0.643569521892049 \tabularnewline
137 & 0.326603248222465 & 0.653206496444929 & 0.673396751777535 \tabularnewline
138 & 0.302996982538862 & 0.605993965077725 & 0.697003017461138 \tabularnewline
139 & 0.276336834151269 & 0.552673668302539 & 0.723663165848731 \tabularnewline
140 & 0.253076205248993 & 0.506152410497985 & 0.746923794751007 \tabularnewline
141 & 0.22573470491672 & 0.45146940983344 & 0.77426529508328 \tabularnewline
142 & 0.229553436901391 & 0.459106873802782 & 0.770446563098609 \tabularnewline
143 & 0.205045196521739 & 0.410090393043478 & 0.794954803478261 \tabularnewline
144 & 0.184574053431529 & 0.369148106863059 & 0.815425946568471 \tabularnewline
145 & 0.172434972128925 & 0.34486994425785 & 0.827565027871075 \tabularnewline
146 & 0.165166954751453 & 0.330333909502906 & 0.834833045248547 \tabularnewline
147 & 0.172736663241632 & 0.345473326483265 & 0.827263336758368 \tabularnewline
148 & 0.190156966130862 & 0.380313932261725 & 0.809843033869138 \tabularnewline
149 & 0.209652546778626 & 0.419305093557252 & 0.790347453221374 \tabularnewline
150 & 0.206288876836588 & 0.412577753673177 & 0.793711123163412 \tabularnewline
151 & 0.18459971853102 & 0.36919943706204 & 0.81540028146898 \tabularnewline
152 & 0.165001521794486 & 0.330003043588972 & 0.834998478205514 \tabularnewline
153 & 0.178431104557289 & 0.356862209114578 & 0.821568895442711 \tabularnewline
154 & 0.214109960241742 & 0.428219920483484 & 0.785890039758258 \tabularnewline
155 & 0.19274163350191 & 0.385483267003819 & 0.80725836649809 \tabularnewline
156 & 0.1726680454008 & 0.345336090801601 & 0.8273319545992 \tabularnewline
157 & 0.150563442493878 & 0.301126884987755 & 0.849436557506122 \tabularnewline
158 & 0.220437562672314 & 0.440875125344628 & 0.779562437327686 \tabularnewline
159 & 0.246264428923818 & 0.492528857847637 & 0.753735571076182 \tabularnewline
160 & 0.220663905711652 & 0.441327811423303 & 0.779336094288348 \tabularnewline
161 & 0.194210719236505 & 0.388421438473011 & 0.805789280763495 \tabularnewline
162 & 0.171710777526791 & 0.343421555053583 & 0.828289222473209 \tabularnewline
163 & 0.151718053600521 & 0.303436107201042 & 0.848281946399479 \tabularnewline
164 & 0.254986160184772 & 0.509972320369545 & 0.745013839815228 \tabularnewline
165 & 0.251775664816337 & 0.503551329632673 & 0.748224335183663 \tabularnewline
166 & 0.247590273070301 & 0.495180546140602 & 0.752409726929699 \tabularnewline
167 & 0.219722822999633 & 0.439445645999267 & 0.780277177000367 \tabularnewline
168 & 0.19798106377622 & 0.395962127552439 & 0.80201893622378 \tabularnewline
169 & 0.251854871473591 & 0.503709742947181 & 0.748145128526409 \tabularnewline
170 & 0.274196723819593 & 0.548393447639186 & 0.725803276180407 \tabularnewline
171 & 0.247032191523989 & 0.494064383047977 & 0.752967808476012 \tabularnewline
172 & 0.243402366501164 & 0.486804733002327 & 0.756597633498836 \tabularnewline
173 & 0.397039666689901 & 0.794079333379802 & 0.602960333310099 \tabularnewline
174 & 0.385499067850317 & 0.770998135700634 & 0.614500932149683 \tabularnewline
175 & 0.410812557240474 & 0.821625114480948 & 0.589187442759526 \tabularnewline
176 & 0.416559839340475 & 0.83311967868095 & 0.583440160659525 \tabularnewline
177 & 0.467612049733354 & 0.935224099466708 & 0.532387950266646 \tabularnewline
178 & 0.434503975220357 & 0.869007950440713 & 0.565496024779643 \tabularnewline
179 & 0.414788035725323 & 0.829576071450645 & 0.585211964274677 \tabularnewline
180 & 0.410607035041141 & 0.821214070082281 & 0.589392964958859 \tabularnewline
181 & 0.373584774481297 & 0.747169548962593 & 0.626415225518703 \tabularnewline
182 & 0.362892619772766 & 0.725785239545532 & 0.637107380227234 \tabularnewline
183 & 0.327377163432443 & 0.654754326864887 & 0.672622836567557 \tabularnewline
184 & 0.299486780211088 & 0.598973560422176 & 0.700513219788912 \tabularnewline
185 & 0.315179341075244 & 0.630358682150487 & 0.684820658924756 \tabularnewline
186 & 0.309111657268882 & 0.618223314537764 & 0.690888342731118 \tabularnewline
187 & 0.276825376749916 & 0.553650753499833 & 0.723174623250084 \tabularnewline
188 & 0.251565406736481 & 0.503130813472961 & 0.748434593263519 \tabularnewline
189 & 0.222853363952596 & 0.445706727905192 & 0.777146636047404 \tabularnewline
190 & 0.201645215653943 & 0.403290431307885 & 0.798354784346057 \tabularnewline
191 & 0.204160337224527 & 0.408320674449055 & 0.795839662775473 \tabularnewline
192 & 0.185767446071583 & 0.371534892143166 & 0.814232553928417 \tabularnewline
193 & 0.203820619672967 & 0.407641239345934 & 0.796179380327033 \tabularnewline
194 & 0.190127696719572 & 0.380255393439145 & 0.809872303280428 \tabularnewline
195 & 0.190950408515064 & 0.381900817030129 & 0.809049591484936 \tabularnewline
196 & 0.198425024833912 & 0.396850049667823 & 0.801574975166088 \tabularnewline
197 & 0.243698375579315 & 0.48739675115863 & 0.756301624420685 \tabularnewline
198 & 0.226493375901268 & 0.452986751802536 & 0.773506624098732 \tabularnewline
199 & 0.254552671201302 & 0.509105342402603 & 0.745447328798698 \tabularnewline
200 & 0.222883222927051 & 0.445766445854101 & 0.777116777072949 \tabularnewline
201 & 0.253155626162089 & 0.506311252324179 & 0.746844373837911 \tabularnewline
202 & 0.234157189787599 & 0.468314379575199 & 0.765842810212401 \tabularnewline
203 & 0.294476384603551 & 0.588952769207101 & 0.705523615396449 \tabularnewline
204 & 0.261027921436 & 0.522055842871999 & 0.738972078564 \tabularnewline
205 & 0.229337292350626 & 0.458674584701252 & 0.770662707649374 \tabularnewline
206 & 0.210362071683827 & 0.420724143367654 & 0.789637928316173 \tabularnewline
207 & 0.180422222434876 & 0.360844444869752 & 0.819577777565124 \tabularnewline
208 & 0.20187470762747 & 0.40374941525494 & 0.79812529237253 \tabularnewline
209 & 0.172050509944266 & 0.344101019888532 & 0.827949490055734 \tabularnewline
210 & 0.187874756440424 & 0.375749512880848 & 0.812125243559576 \tabularnewline
211 & 0.211366824527744 & 0.422733649055487 & 0.788633175472256 \tabularnewline
212 & 0.197305764616628 & 0.394611529233257 & 0.802694235383372 \tabularnewline
213 & 0.171302983272476 & 0.342605966544953 & 0.828697016727524 \tabularnewline
214 & 0.213502948803312 & 0.427005897606623 & 0.786497051196688 \tabularnewline
215 & 0.187263911427158 & 0.374527822854316 & 0.812736088572842 \tabularnewline
216 & 0.17629427054637 & 0.35258854109274 & 0.82370572945363 \tabularnewline
217 & 0.207252189552249 & 0.414504379104498 & 0.792747810447751 \tabularnewline
218 & 0.178520980024689 & 0.357041960049379 & 0.821479019975311 \tabularnewline
219 & 0.164765723102826 & 0.329531446205652 & 0.835234276897174 \tabularnewline
220 & 0.171787831021176 & 0.343575662042352 & 0.828212168978824 \tabularnewline
221 & 0.176701300949722 & 0.353402601899443 & 0.823298699050278 \tabularnewline
222 & 0.179019743844808 & 0.358039487689616 & 0.820980256155192 \tabularnewline
223 & 0.163087148870827 & 0.326174297741655 & 0.836912851129173 \tabularnewline
224 & 0.134519499011631 & 0.269038998023261 & 0.865480500988369 \tabularnewline
225 & 0.120551332606294 & 0.241102665212588 & 0.879448667393706 \tabularnewline
226 & 0.145351761512338 & 0.290703523024677 & 0.854648238487662 \tabularnewline
227 & 0.323596792807737 & 0.647193585615473 & 0.676403207192263 \tabularnewline
228 & 0.299789980096401 & 0.599579960192802 & 0.700210019903599 \tabularnewline
229 & 0.273257451057791 & 0.546514902115583 & 0.726742548942209 \tabularnewline
230 & 0.257074086710721 & 0.514148173421442 & 0.742925913289279 \tabularnewline
231 & 0.217447402662938 & 0.434894805325875 & 0.782552597337063 \tabularnewline
232 & 0.25076742551295 & 0.501534851025899 & 0.74923257448705 \tabularnewline
233 & 0.209473990123595 & 0.418947980247191 & 0.790526009876405 \tabularnewline
234 & 0.17236111073672 & 0.34472222147344 & 0.82763888926328 \tabularnewline
235 & 0.17119338927229 & 0.34238677854458 & 0.82880661072771 \tabularnewline
236 & 0.14873472391895 & 0.2974694478379 & 0.85126527608105 \tabularnewline
237 & 0.122028405315276 & 0.244056810630552 & 0.877971594684724 \tabularnewline
238 & 0.0926115943533249 & 0.18522318870665 & 0.907388405646675 \tabularnewline
239 & 0.187082595824888 & 0.374165191649775 & 0.812917404175112 \tabularnewline
240 & 0.180889336273332 & 0.361778672546665 & 0.819110663726668 \tabularnewline
241 & 0.152137246796433 & 0.304274493592865 & 0.847862753203567 \tabularnewline
242 & 0.322973091247979 & 0.645946182495959 & 0.677026908752021 \tabularnewline
243 & 0.280591340166642 & 0.561182680333284 & 0.719408659833358 \tabularnewline
244 & 0.225633550504806 & 0.451267101009612 & 0.774366449495194 \tabularnewline
245 & 0.338281892384468 & 0.676563784768937 & 0.661718107615532 \tabularnewline
246 & 0.258916819172534 & 0.517833638345068 & 0.741083180827466 \tabularnewline
247 & 0.190492569946483 & 0.380985139892965 & 0.809507430053517 \tabularnewline
248 & 0.309307227413507 & 0.618614454827014 & 0.690692772586493 \tabularnewline
249 & 0.223495672885987 & 0.446991345771973 & 0.776504327114013 \tabularnewline
250 & 0.148199071484992 & 0.296398142969983 & 0.851800928515008 \tabularnewline
251 & 0.235889599696661 & 0.471779199393322 & 0.764110400303339 \tabularnewline
252 & 0.743668582161259 & 0.512662835677483 & 0.256331417838741 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186332&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]12[/C][C]0.82460254264983[/C][C]0.35079491470034[/C][C]0.17539745735017[/C][/ROW]
[ROW][C]13[/C][C]0.98177869429319[/C][C]0.0364426114136196[/C][C]0.0182213057068098[/C][/ROW]
[ROW][C]14[/C][C]0.965041480347379[/C][C]0.0699170393052425[/C][C]0.0349585196526213[/C][/ROW]
[ROW][C]15[/C][C]0.965415688490191[/C][C]0.0691686230196178[/C][C]0.0345843115098089[/C][/ROW]
[ROW][C]16[/C][C]0.942982886392319[/C][C]0.114034227215361[/C][C]0.0570171136076807[/C][/ROW]
[ROW][C]17[/C][C]0.96685729863873[/C][C]0.066285402722539[/C][C]0.0331427013612695[/C][/ROW]
[ROW][C]18[/C][C]0.946711202137859[/C][C]0.106577595724282[/C][C]0.0532887978621411[/C][/ROW]
[ROW][C]19[/C][C]0.919138444137669[/C][C]0.161723111724663[/C][C]0.0808615558623314[/C][/ROW]
[ROW][C]20[/C][C]0.915308663196536[/C][C]0.169382673606927[/C][C]0.0846913368034635[/C][/ROW]
[ROW][C]21[/C][C]0.937424539473722[/C][C]0.125150921052555[/C][C]0.0625754605262776[/C][/ROW]
[ROW][C]22[/C][C]0.935061647246031[/C][C]0.129876705507937[/C][C]0.0649383527539687[/C][/ROW]
[ROW][C]23[/C][C]0.935048090631857[/C][C]0.129903818736286[/C][C]0.0649519093681428[/C][/ROW]
[ROW][C]24[/C][C]0.911274476329745[/C][C]0.17745104734051[/C][C]0.0887255236702548[/C][/ROW]
[ROW][C]25[/C][C]0.8909139048464[/C][C]0.2181721903072[/C][C]0.1090860951536[/C][/ROW]
[ROW][C]26[/C][C]0.999305462877345[/C][C]0.0013890742453103[/C][C]0.000694537122655151[/C][/ROW]
[ROW][C]27[/C][C]0.998867531622549[/C][C]0.00226493675490267[/C][C]0.00113246837745134[/C][/ROW]
[ROW][C]28[/C][C]0.998158010011966[/C][C]0.00368397997606871[/C][C]0.00184198998803436[/C][/ROW]
[ROW][C]29[/C][C]0.997109894145412[/C][C]0.00578021170917561[/C][C]0.00289010585458781[/C][/ROW]
[ROW][C]30[/C][C]0.998049400381054[/C][C]0.00390119923789125[/C][C]0.00195059961894562[/C][/ROW]
[ROW][C]31[/C][C]0.996984553035601[/C][C]0.00603089392879774[/C][C]0.00301544696439887[/C][/ROW]
[ROW][C]32[/C][C]0.995575770682055[/C][C]0.00884845863588974[/C][C]0.00442422931794487[/C][/ROW]
[ROW][C]33[/C][C]0.994548276395685[/C][C]0.0109034472086308[/C][C]0.00545172360431541[/C][/ROW]
[ROW][C]34[/C][C]0.9920053601806[/C][C]0.0159892796388003[/C][C]0.00799463981940013[/C][/ROW]
[ROW][C]35[/C][C]0.990016140753894[/C][C]0.0199677184922129[/C][C]0.00998385924610647[/C][/ROW]
[ROW][C]36[/C][C]0.985934053555038[/C][C]0.0281318928899229[/C][C]0.0140659464449615[/C][/ROW]
[ROW][C]37[/C][C]0.990573372283796[/C][C]0.0188532554324071[/C][C]0.00942662771620356[/C][/ROW]
[ROW][C]38[/C][C]0.986788910821757[/C][C]0.0264221783564869[/C][C]0.0132110891782435[/C][/ROW]
[ROW][C]39[/C][C]0.984613183278575[/C][C]0.0307736334428499[/C][C]0.015386816721425[/C][/ROW]
[ROW][C]40[/C][C]0.984959879789106[/C][C]0.0300802404217887[/C][C]0.0150401202108943[/C][/ROW]
[ROW][C]41[/C][C]0.980132003469257[/C][C]0.0397359930614861[/C][C]0.0198679965307431[/C][/ROW]
[ROW][C]42[/C][C]0.977720296130014[/C][C]0.0445594077399722[/C][C]0.0222797038699861[/C][/ROW]
[ROW][C]43[/C][C]0.970371641980239[/C][C]0.0592567160395229[/C][C]0.0296283580197615[/C][/ROW]
[ROW][C]44[/C][C]0.96503816622822[/C][C]0.0699236675435601[/C][C]0.03496183377178[/C][/ROW]
[ROW][C]45[/C][C]0.954540330208453[/C][C]0.0909193395830936[/C][C]0.0454596697915468[/C][/ROW]
[ROW][C]46[/C][C]0.962916846902018[/C][C]0.0741663061959642[/C][C]0.0370831530979821[/C][/ROW]
[ROW][C]47[/C][C]0.952381050692661[/C][C]0.0952378986146777[/C][C]0.0476189493073388[/C][/ROW]
[ROW][C]48[/C][C]0.939268744159558[/C][C]0.121462511680884[/C][C]0.0607312558404422[/C][/ROW]
[ROW][C]49[/C][C]0.947815741377213[/C][C]0.104368517245575[/C][C]0.0521842586227873[/C][/ROW]
[ROW][C]50[/C][C]0.944617038843507[/C][C]0.110765922312985[/C][C]0.0553829611564927[/C][/ROW]
[ROW][C]51[/C][C]0.931737591272367[/C][C]0.136524817455266[/C][C]0.068262408727633[/C][/ROW]
[ROW][C]52[/C][C]0.915539140532236[/C][C]0.168921718935528[/C][C]0.0844608594677638[/C][/ROW]
[ROW][C]53[/C][C]0.902865364432769[/C][C]0.194269271134462[/C][C]0.0971346355672311[/C][/ROW]
[ROW][C]54[/C][C]0.887937671064988[/C][C]0.224124657870024[/C][C]0.112062328935012[/C][/ROW]
[ROW][C]55[/C][C]0.882811467548189[/C][C]0.234377064903621[/C][C]0.117188532451811[/C][/ROW]
[ROW][C]56[/C][C]0.864437852519807[/C][C]0.271124294960387[/C][C]0.135562147480193[/C][/ROW]
[ROW][C]57[/C][C]0.850510809892065[/C][C]0.29897838021587[/C][C]0.149489190107935[/C][/ROW]
[ROW][C]58[/C][C]0.823720833728202[/C][C]0.352558332543597[/C][C]0.176279166271798[/C][/ROW]
[ROW][C]59[/C][C]0.865214015371324[/C][C]0.269571969257353[/C][C]0.134785984628676[/C][/ROW]
[ROW][C]60[/C][C]0.862215256339152[/C][C]0.275569487321697[/C][C]0.137784743660848[/C][/ROW]
[ROW][C]61[/C][C]0.882882728730349[/C][C]0.234234542539303[/C][C]0.117117271269651[/C][/ROW]
[ROW][C]62[/C][C]0.883758623875382[/C][C]0.232482752249236[/C][C]0.116241376124618[/C][/ROW]
[ROW][C]63[/C][C]0.931662249323344[/C][C]0.136675501353312[/C][C]0.0683377506766561[/C][/ROW]
[ROW][C]64[/C][C]0.920159590273038[/C][C]0.159680819453925[/C][C]0.0798404097269624[/C][/ROW]
[ROW][C]65[/C][C]0.909763761964202[/C][C]0.180472476071596[/C][C]0.0902362380357978[/C][/ROW]
[ROW][C]66[/C][C]0.920839115917038[/C][C]0.158321768165925[/C][C]0.0791608840829624[/C][/ROW]
[ROW][C]67[/C][C]0.920024849585607[/C][C]0.159950300828785[/C][C]0.0799751504143927[/C][/ROW]
[ROW][C]68[/C][C]0.911233382981599[/C][C]0.177533234036803[/C][C]0.0887666170184015[/C][/ROW]
[ROW][C]69[/C][C]0.941933489247692[/C][C]0.116133021504616[/C][C]0.0580665107523081[/C][/ROW]
[ROW][C]70[/C][C]0.946385028672878[/C][C]0.107229942654243[/C][C]0.0536149713271216[/C][/ROW]
[ROW][C]71[/C][C]0.941090311701144[/C][C]0.117819376597713[/C][C]0.0589096882988564[/C][/ROW]
[ROW][C]72[/C][C]0.961068599372108[/C][C]0.0778628012557843[/C][C]0.0389314006278922[/C][/ROW]
[ROW][C]73[/C][C]0.952588293452193[/C][C]0.094823413095614[/C][C]0.047411706547807[/C][/ROW]
[ROW][C]74[/C][C]0.941998884826833[/C][C]0.116002230346334[/C][C]0.0580011151731672[/C][/ROW]
[ROW][C]75[/C][C]0.935143540647136[/C][C]0.129712918705728[/C][C]0.0648564593528642[/C][/ROW]
[ROW][C]76[/C][C]0.921582728316182[/C][C]0.156834543367636[/C][C]0.0784172716838182[/C][/ROW]
[ROW][C]77[/C][C]0.937619105001912[/C][C]0.124761789996176[/C][C]0.062380894998088[/C][/ROW]
[ROW][C]78[/C][C]0.926044313105937[/C][C]0.147911373788125[/C][C]0.0739556868940626[/C][/ROW]
[ROW][C]79[/C][C]0.919672931637549[/C][C]0.160654136724901[/C][C]0.0803270683624506[/C][/ROW]
[ROW][C]80[/C][C]0.912994048513382[/C][C]0.174011902973237[/C][C]0.0870059514866183[/C][/ROW]
[ROW][C]81[/C][C]0.896442677822583[/C][C]0.207114644354834[/C][C]0.103557322177417[/C][/ROW]
[ROW][C]82[/C][C]0.87848623947508[/C][C]0.243027521049839[/C][C]0.12151376052492[/C][/ROW]
[ROW][C]83[/C][C]0.872940207476295[/C][C]0.25411958504741[/C][C]0.127059792523705[/C][/ROW]
[ROW][C]84[/C][C]0.8546154848785[/C][C]0.290769030243001[/C][C]0.1453845151215[/C][/ROW]
[ROW][C]85[/C][C]0.831574347739425[/C][C]0.336851304521151[/C][C]0.168425652260575[/C][/ROW]
[ROW][C]86[/C][C]0.808979353581946[/C][C]0.382041292836108[/C][C]0.191020646418054[/C][/ROW]
[ROW][C]87[/C][C]0.78215508400283[/C][C]0.435689831994341[/C][C]0.21784491599717[/C][/ROW]
[ROW][C]88[/C][C]0.753175084313577[/C][C]0.493649831372845[/C][C]0.246824915686423[/C][/ROW]
[ROW][C]89[/C][C]0.821660023904459[/C][C]0.356679952191082[/C][C]0.178339976095541[/C][/ROW]
[ROW][C]90[/C][C]0.852555299029093[/C][C]0.294889401941814[/C][C]0.147444700970907[/C][/ROW]
[ROW][C]91[/C][C]0.830448532404898[/C][C]0.339102935190204[/C][C]0.169551467595102[/C][/ROW]
[ROW][C]92[/C][C]0.807685688430541[/C][C]0.384628623138918[/C][C]0.192314311569459[/C][/ROW]
[ROW][C]93[/C][C]0.785512573800584[/C][C]0.428974852398831[/C][C]0.214487426199416[/C][/ROW]
[ROW][C]94[/C][C]0.762978657270658[/C][C]0.474042685458684[/C][C]0.237021342729342[/C][/ROW]
[ROW][C]95[/C][C]0.737313100749981[/C][C]0.525373798500037[/C][C]0.262686899250018[/C][/ROW]
[ROW][C]96[/C][C]0.712745071616862[/C][C]0.574509856766276[/C][C]0.287254928383138[/C][/ROW]
[ROW][C]97[/C][C]0.686616517893039[/C][C]0.626766964213922[/C][C]0.313383482106961[/C][/ROW]
[ROW][C]98[/C][C]0.684439383196476[/C][C]0.631121233607048[/C][C]0.315560616803524[/C][/ROW]
[ROW][C]99[/C][C]0.650930703579614[/C][C]0.698138592840773[/C][C]0.349069296420386[/C][/ROW]
[ROW][C]100[/C][C]0.640280223318653[/C][C]0.719439553362694[/C][C]0.359719776681347[/C][/ROW]
[ROW][C]101[/C][C]0.616655235846849[/C][C]0.766689528306302[/C][C]0.383344764153151[/C][/ROW]
[ROW][C]102[/C][C]0.586978773365516[/C][C]0.826042453268968[/C][C]0.413021226634484[/C][/ROW]
[ROW][C]103[/C][C]0.6377644522201[/C][C]0.7244710955598[/C][C]0.3622355477799[/C][/ROW]
[ROW][C]104[/C][C]0.623251525335998[/C][C]0.753496949328003[/C][C]0.376748474664001[/C][/ROW]
[ROW][C]105[/C][C]0.640618404380481[/C][C]0.718763191239038[/C][C]0.359381595619519[/C][/ROW]
[ROW][C]106[/C][C]0.613905961073024[/C][C]0.772188077853951[/C][C]0.386094038926976[/C][/ROW]
[ROW][C]107[/C][C]0.603805095542675[/C][C]0.79238980891465[/C][C]0.396194904457325[/C][/ROW]
[ROW][C]108[/C][C]0.644425220626976[/C][C]0.711149558746048[/C][C]0.355574779373024[/C][/ROW]
[ROW][C]109[/C][C]0.613576378682154[/C][C]0.772847242635692[/C][C]0.386423621317846[/C][/ROW]
[ROW][C]110[/C][C]0.586552883768723[/C][C]0.826894232462555[/C][C]0.413447116231277[/C][/ROW]
[ROW][C]111[/C][C]0.59418224065849[/C][C]0.811635518683019[/C][C]0.40581775934151[/C][/ROW]
[ROW][C]112[/C][C]0.621603928308835[/C][C]0.75679214338233[/C][C]0.378396071691165[/C][/ROW]
[ROW][C]113[/C][C]0.609430669616519[/C][C]0.781138660766961[/C][C]0.390569330383481[/C][/ROW]
[ROW][C]114[/C][C]0.696202741916057[/C][C]0.607594516167885[/C][C]0.303797258083943[/C][/ROW]
[ROW][C]115[/C][C]0.66637751342477[/C][C]0.66724497315046[/C][C]0.33362248657523[/C][/ROW]
[ROW][C]116[/C][C]0.639691744225935[/C][C]0.720616511548129[/C][C]0.360308255774065[/C][/ROW]
[ROW][C]117[/C][C]0.605796336717718[/C][C]0.788407326564565[/C][C]0.394203663282282[/C][/ROW]
[ROW][C]118[/C][C]0.581841002559814[/C][C]0.836317994880372[/C][C]0.418158997440186[/C][/ROW]
[ROW][C]119[/C][C]0.546766491509426[/C][C]0.906467016981149[/C][C]0.453233508490574[/C][/ROW]
[ROW][C]120[/C][C]0.514775065364371[/C][C]0.970449869271258[/C][C]0.485224934635629[/C][/ROW]
[ROW][C]121[/C][C]0.48555768333974[/C][C]0.97111536667948[/C][C]0.51444231666026[/C][/ROW]
[ROW][C]122[/C][C]0.452675234895943[/C][C]0.905350469791886[/C][C]0.547324765104057[/C][/ROW]
[ROW][C]123[/C][C]0.425557384495198[/C][C]0.851114768990396[/C][C]0.574442615504802[/C][/ROW]
[ROW][C]124[/C][C]0.393619320689421[/C][C]0.787238641378842[/C][C]0.606380679310579[/C][/ROW]
[ROW][C]125[/C][C]0.38530708007611[/C][C]0.77061416015222[/C][C]0.61469291992389[/C][/ROW]
[ROW][C]126[/C][C]0.355651483380899[/C][C]0.711302966761799[/C][C]0.644348516619101[/C][/ROW]
[ROW][C]127[/C][C]0.339417332474354[/C][C]0.678834664948709[/C][C]0.660582667525646[/C][/ROW]
[ROW][C]128[/C][C]0.441320396359238[/C][C]0.882640792718475[/C][C]0.558679603640762[/C][/ROW]
[ROW][C]129[/C][C]0.421959917184986[/C][C]0.843919834369972[/C][C]0.578040082815014[/C][/ROW]
[ROW][C]130[/C][C]0.412335028343624[/C][C]0.824670056687247[/C][C]0.587664971656376[/C][/ROW]
[ROW][C]131[/C][C]0.400215795890695[/C][C]0.80043159178139[/C][C]0.599784204109305[/C][/ROW]
[ROW][C]132[/C][C]0.371017503906677[/C][C]0.742035007813354[/C][C]0.628982496093323[/C][/ROW]
[ROW][C]133[/C][C]0.388190057756824[/C][C]0.776380115513648[/C][C]0.611809942243176[/C][/ROW]
[ROW][C]134[/C][C]0.35879095643076[/C][C]0.717581912861521[/C][C]0.64120904356924[/C][/ROW]
[ROW][C]135[/C][C]0.367991196908356[/C][C]0.735982393816713[/C][C]0.632008803091644[/C][/ROW]
[ROW][C]136[/C][C]0.356430478107951[/C][C]0.712860956215902[/C][C]0.643569521892049[/C][/ROW]
[ROW][C]137[/C][C]0.326603248222465[/C][C]0.653206496444929[/C][C]0.673396751777535[/C][/ROW]
[ROW][C]138[/C][C]0.302996982538862[/C][C]0.605993965077725[/C][C]0.697003017461138[/C][/ROW]
[ROW][C]139[/C][C]0.276336834151269[/C][C]0.552673668302539[/C][C]0.723663165848731[/C][/ROW]
[ROW][C]140[/C][C]0.253076205248993[/C][C]0.506152410497985[/C][C]0.746923794751007[/C][/ROW]
[ROW][C]141[/C][C]0.22573470491672[/C][C]0.45146940983344[/C][C]0.77426529508328[/C][/ROW]
[ROW][C]142[/C][C]0.229553436901391[/C][C]0.459106873802782[/C][C]0.770446563098609[/C][/ROW]
[ROW][C]143[/C][C]0.205045196521739[/C][C]0.410090393043478[/C][C]0.794954803478261[/C][/ROW]
[ROW][C]144[/C][C]0.184574053431529[/C][C]0.369148106863059[/C][C]0.815425946568471[/C][/ROW]
[ROW][C]145[/C][C]0.172434972128925[/C][C]0.34486994425785[/C][C]0.827565027871075[/C][/ROW]
[ROW][C]146[/C][C]0.165166954751453[/C][C]0.330333909502906[/C][C]0.834833045248547[/C][/ROW]
[ROW][C]147[/C][C]0.172736663241632[/C][C]0.345473326483265[/C][C]0.827263336758368[/C][/ROW]
[ROW][C]148[/C][C]0.190156966130862[/C][C]0.380313932261725[/C][C]0.809843033869138[/C][/ROW]
[ROW][C]149[/C][C]0.209652546778626[/C][C]0.419305093557252[/C][C]0.790347453221374[/C][/ROW]
[ROW][C]150[/C][C]0.206288876836588[/C][C]0.412577753673177[/C][C]0.793711123163412[/C][/ROW]
[ROW][C]151[/C][C]0.18459971853102[/C][C]0.36919943706204[/C][C]0.81540028146898[/C][/ROW]
[ROW][C]152[/C][C]0.165001521794486[/C][C]0.330003043588972[/C][C]0.834998478205514[/C][/ROW]
[ROW][C]153[/C][C]0.178431104557289[/C][C]0.356862209114578[/C][C]0.821568895442711[/C][/ROW]
[ROW][C]154[/C][C]0.214109960241742[/C][C]0.428219920483484[/C][C]0.785890039758258[/C][/ROW]
[ROW][C]155[/C][C]0.19274163350191[/C][C]0.385483267003819[/C][C]0.80725836649809[/C][/ROW]
[ROW][C]156[/C][C]0.1726680454008[/C][C]0.345336090801601[/C][C]0.8273319545992[/C][/ROW]
[ROW][C]157[/C][C]0.150563442493878[/C][C]0.301126884987755[/C][C]0.849436557506122[/C][/ROW]
[ROW][C]158[/C][C]0.220437562672314[/C][C]0.440875125344628[/C][C]0.779562437327686[/C][/ROW]
[ROW][C]159[/C][C]0.246264428923818[/C][C]0.492528857847637[/C][C]0.753735571076182[/C][/ROW]
[ROW][C]160[/C][C]0.220663905711652[/C][C]0.441327811423303[/C][C]0.779336094288348[/C][/ROW]
[ROW][C]161[/C][C]0.194210719236505[/C][C]0.388421438473011[/C][C]0.805789280763495[/C][/ROW]
[ROW][C]162[/C][C]0.171710777526791[/C][C]0.343421555053583[/C][C]0.828289222473209[/C][/ROW]
[ROW][C]163[/C][C]0.151718053600521[/C][C]0.303436107201042[/C][C]0.848281946399479[/C][/ROW]
[ROW][C]164[/C][C]0.254986160184772[/C][C]0.509972320369545[/C][C]0.745013839815228[/C][/ROW]
[ROW][C]165[/C][C]0.251775664816337[/C][C]0.503551329632673[/C][C]0.748224335183663[/C][/ROW]
[ROW][C]166[/C][C]0.247590273070301[/C][C]0.495180546140602[/C][C]0.752409726929699[/C][/ROW]
[ROW][C]167[/C][C]0.219722822999633[/C][C]0.439445645999267[/C][C]0.780277177000367[/C][/ROW]
[ROW][C]168[/C][C]0.19798106377622[/C][C]0.395962127552439[/C][C]0.80201893622378[/C][/ROW]
[ROW][C]169[/C][C]0.251854871473591[/C][C]0.503709742947181[/C][C]0.748145128526409[/C][/ROW]
[ROW][C]170[/C][C]0.274196723819593[/C][C]0.548393447639186[/C][C]0.725803276180407[/C][/ROW]
[ROW][C]171[/C][C]0.247032191523989[/C][C]0.494064383047977[/C][C]0.752967808476012[/C][/ROW]
[ROW][C]172[/C][C]0.243402366501164[/C][C]0.486804733002327[/C][C]0.756597633498836[/C][/ROW]
[ROW][C]173[/C][C]0.397039666689901[/C][C]0.794079333379802[/C][C]0.602960333310099[/C][/ROW]
[ROW][C]174[/C][C]0.385499067850317[/C][C]0.770998135700634[/C][C]0.614500932149683[/C][/ROW]
[ROW][C]175[/C][C]0.410812557240474[/C][C]0.821625114480948[/C][C]0.589187442759526[/C][/ROW]
[ROW][C]176[/C][C]0.416559839340475[/C][C]0.83311967868095[/C][C]0.583440160659525[/C][/ROW]
[ROW][C]177[/C][C]0.467612049733354[/C][C]0.935224099466708[/C][C]0.532387950266646[/C][/ROW]
[ROW][C]178[/C][C]0.434503975220357[/C][C]0.869007950440713[/C][C]0.565496024779643[/C][/ROW]
[ROW][C]179[/C][C]0.414788035725323[/C][C]0.829576071450645[/C][C]0.585211964274677[/C][/ROW]
[ROW][C]180[/C][C]0.410607035041141[/C][C]0.821214070082281[/C][C]0.589392964958859[/C][/ROW]
[ROW][C]181[/C][C]0.373584774481297[/C][C]0.747169548962593[/C][C]0.626415225518703[/C][/ROW]
[ROW][C]182[/C][C]0.362892619772766[/C][C]0.725785239545532[/C][C]0.637107380227234[/C][/ROW]
[ROW][C]183[/C][C]0.327377163432443[/C][C]0.654754326864887[/C][C]0.672622836567557[/C][/ROW]
[ROW][C]184[/C][C]0.299486780211088[/C][C]0.598973560422176[/C][C]0.700513219788912[/C][/ROW]
[ROW][C]185[/C][C]0.315179341075244[/C][C]0.630358682150487[/C][C]0.684820658924756[/C][/ROW]
[ROW][C]186[/C][C]0.309111657268882[/C][C]0.618223314537764[/C][C]0.690888342731118[/C][/ROW]
[ROW][C]187[/C][C]0.276825376749916[/C][C]0.553650753499833[/C][C]0.723174623250084[/C][/ROW]
[ROW][C]188[/C][C]0.251565406736481[/C][C]0.503130813472961[/C][C]0.748434593263519[/C][/ROW]
[ROW][C]189[/C][C]0.222853363952596[/C][C]0.445706727905192[/C][C]0.777146636047404[/C][/ROW]
[ROW][C]190[/C][C]0.201645215653943[/C][C]0.403290431307885[/C][C]0.798354784346057[/C][/ROW]
[ROW][C]191[/C][C]0.204160337224527[/C][C]0.408320674449055[/C][C]0.795839662775473[/C][/ROW]
[ROW][C]192[/C][C]0.185767446071583[/C][C]0.371534892143166[/C][C]0.814232553928417[/C][/ROW]
[ROW][C]193[/C][C]0.203820619672967[/C][C]0.407641239345934[/C][C]0.796179380327033[/C][/ROW]
[ROW][C]194[/C][C]0.190127696719572[/C][C]0.380255393439145[/C][C]0.809872303280428[/C][/ROW]
[ROW][C]195[/C][C]0.190950408515064[/C][C]0.381900817030129[/C][C]0.809049591484936[/C][/ROW]
[ROW][C]196[/C][C]0.198425024833912[/C][C]0.396850049667823[/C][C]0.801574975166088[/C][/ROW]
[ROW][C]197[/C][C]0.243698375579315[/C][C]0.48739675115863[/C][C]0.756301624420685[/C][/ROW]
[ROW][C]198[/C][C]0.226493375901268[/C][C]0.452986751802536[/C][C]0.773506624098732[/C][/ROW]
[ROW][C]199[/C][C]0.254552671201302[/C][C]0.509105342402603[/C][C]0.745447328798698[/C][/ROW]
[ROW][C]200[/C][C]0.222883222927051[/C][C]0.445766445854101[/C][C]0.777116777072949[/C][/ROW]
[ROW][C]201[/C][C]0.253155626162089[/C][C]0.506311252324179[/C][C]0.746844373837911[/C][/ROW]
[ROW][C]202[/C][C]0.234157189787599[/C][C]0.468314379575199[/C][C]0.765842810212401[/C][/ROW]
[ROW][C]203[/C][C]0.294476384603551[/C][C]0.588952769207101[/C][C]0.705523615396449[/C][/ROW]
[ROW][C]204[/C][C]0.261027921436[/C][C]0.522055842871999[/C][C]0.738972078564[/C][/ROW]
[ROW][C]205[/C][C]0.229337292350626[/C][C]0.458674584701252[/C][C]0.770662707649374[/C][/ROW]
[ROW][C]206[/C][C]0.210362071683827[/C][C]0.420724143367654[/C][C]0.789637928316173[/C][/ROW]
[ROW][C]207[/C][C]0.180422222434876[/C][C]0.360844444869752[/C][C]0.819577777565124[/C][/ROW]
[ROW][C]208[/C][C]0.20187470762747[/C][C]0.40374941525494[/C][C]0.79812529237253[/C][/ROW]
[ROW][C]209[/C][C]0.172050509944266[/C][C]0.344101019888532[/C][C]0.827949490055734[/C][/ROW]
[ROW][C]210[/C][C]0.187874756440424[/C][C]0.375749512880848[/C][C]0.812125243559576[/C][/ROW]
[ROW][C]211[/C][C]0.211366824527744[/C][C]0.422733649055487[/C][C]0.788633175472256[/C][/ROW]
[ROW][C]212[/C][C]0.197305764616628[/C][C]0.394611529233257[/C][C]0.802694235383372[/C][/ROW]
[ROW][C]213[/C][C]0.171302983272476[/C][C]0.342605966544953[/C][C]0.828697016727524[/C][/ROW]
[ROW][C]214[/C][C]0.213502948803312[/C][C]0.427005897606623[/C][C]0.786497051196688[/C][/ROW]
[ROW][C]215[/C][C]0.187263911427158[/C][C]0.374527822854316[/C][C]0.812736088572842[/C][/ROW]
[ROW][C]216[/C][C]0.17629427054637[/C][C]0.35258854109274[/C][C]0.82370572945363[/C][/ROW]
[ROW][C]217[/C][C]0.207252189552249[/C][C]0.414504379104498[/C][C]0.792747810447751[/C][/ROW]
[ROW][C]218[/C][C]0.178520980024689[/C][C]0.357041960049379[/C][C]0.821479019975311[/C][/ROW]
[ROW][C]219[/C][C]0.164765723102826[/C][C]0.329531446205652[/C][C]0.835234276897174[/C][/ROW]
[ROW][C]220[/C][C]0.171787831021176[/C][C]0.343575662042352[/C][C]0.828212168978824[/C][/ROW]
[ROW][C]221[/C][C]0.176701300949722[/C][C]0.353402601899443[/C][C]0.823298699050278[/C][/ROW]
[ROW][C]222[/C][C]0.179019743844808[/C][C]0.358039487689616[/C][C]0.820980256155192[/C][/ROW]
[ROW][C]223[/C][C]0.163087148870827[/C][C]0.326174297741655[/C][C]0.836912851129173[/C][/ROW]
[ROW][C]224[/C][C]0.134519499011631[/C][C]0.269038998023261[/C][C]0.865480500988369[/C][/ROW]
[ROW][C]225[/C][C]0.120551332606294[/C][C]0.241102665212588[/C][C]0.879448667393706[/C][/ROW]
[ROW][C]226[/C][C]0.145351761512338[/C][C]0.290703523024677[/C][C]0.854648238487662[/C][/ROW]
[ROW][C]227[/C][C]0.323596792807737[/C][C]0.647193585615473[/C][C]0.676403207192263[/C][/ROW]
[ROW][C]228[/C][C]0.299789980096401[/C][C]0.599579960192802[/C][C]0.700210019903599[/C][/ROW]
[ROW][C]229[/C][C]0.273257451057791[/C][C]0.546514902115583[/C][C]0.726742548942209[/C][/ROW]
[ROW][C]230[/C][C]0.257074086710721[/C][C]0.514148173421442[/C][C]0.742925913289279[/C][/ROW]
[ROW][C]231[/C][C]0.217447402662938[/C][C]0.434894805325875[/C][C]0.782552597337063[/C][/ROW]
[ROW][C]232[/C][C]0.25076742551295[/C][C]0.501534851025899[/C][C]0.74923257448705[/C][/ROW]
[ROW][C]233[/C][C]0.209473990123595[/C][C]0.418947980247191[/C][C]0.790526009876405[/C][/ROW]
[ROW][C]234[/C][C]0.17236111073672[/C][C]0.34472222147344[/C][C]0.82763888926328[/C][/ROW]
[ROW][C]235[/C][C]0.17119338927229[/C][C]0.34238677854458[/C][C]0.82880661072771[/C][/ROW]
[ROW][C]236[/C][C]0.14873472391895[/C][C]0.2974694478379[/C][C]0.85126527608105[/C][/ROW]
[ROW][C]237[/C][C]0.122028405315276[/C][C]0.244056810630552[/C][C]0.877971594684724[/C][/ROW]
[ROW][C]238[/C][C]0.0926115943533249[/C][C]0.18522318870665[/C][C]0.907388405646675[/C][/ROW]
[ROW][C]239[/C][C]0.187082595824888[/C][C]0.374165191649775[/C][C]0.812917404175112[/C][/ROW]
[ROW][C]240[/C][C]0.180889336273332[/C][C]0.361778672546665[/C][C]0.819110663726668[/C][/ROW]
[ROW][C]241[/C][C]0.152137246796433[/C][C]0.304274493592865[/C][C]0.847862753203567[/C][/ROW]
[ROW][C]242[/C][C]0.322973091247979[/C][C]0.645946182495959[/C][C]0.677026908752021[/C][/ROW]
[ROW][C]243[/C][C]0.280591340166642[/C][C]0.561182680333284[/C][C]0.719408659833358[/C][/ROW]
[ROW][C]244[/C][C]0.225633550504806[/C][C]0.451267101009612[/C][C]0.774366449495194[/C][/ROW]
[ROW][C]245[/C][C]0.338281892384468[/C][C]0.676563784768937[/C][C]0.661718107615532[/C][/ROW]
[ROW][C]246[/C][C]0.258916819172534[/C][C]0.517833638345068[/C][C]0.741083180827466[/C][/ROW]
[ROW][C]247[/C][C]0.190492569946483[/C][C]0.380985139892965[/C][C]0.809507430053517[/C][/ROW]
[ROW][C]248[/C][C]0.309307227413507[/C][C]0.618614454827014[/C][C]0.690692772586493[/C][/ROW]
[ROW][C]249[/C][C]0.223495672885987[/C][C]0.446991345771973[/C][C]0.776504327114013[/C][/ROW]
[ROW][C]250[/C][C]0.148199071484992[/C][C]0.296398142969983[/C][C]0.851800928515008[/C][/ROW]
[ROW][C]251[/C][C]0.235889599696661[/C][C]0.471779199393322[/C][C]0.764110400303339[/C][/ROW]
[ROW][C]252[/C][C]0.743668582161259[/C][C]0.512662835677483[/C][C]0.256331417838741[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186332&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186332&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.824602542649830.350794914700340.17539745735017
130.981778694293190.03644261141361960.0182213057068098
140.9650414803473790.06991703930524250.0349585196526213
150.9654156884901910.06916862301961780.0345843115098089
160.9429828863923190.1140342272153610.0570171136076807
170.966857298638730.0662854027225390.0331427013612695
180.9467112021378590.1065775957242820.0532887978621411
190.9191384441376690.1617231117246630.0808615558623314
200.9153086631965360.1693826736069270.0846913368034635
210.9374245394737220.1251509210525550.0625754605262776
220.9350616472460310.1298767055079370.0649383527539687
230.9350480906318570.1299038187362860.0649519093681428
240.9112744763297450.177451047340510.0887255236702548
250.89091390484640.21817219030720.1090860951536
260.9993054628773450.00138907424531030.000694537122655151
270.9988675316225490.002264936754902670.00113246837745134
280.9981580100119660.003683979976068710.00184198998803436
290.9971098941454120.005780211709175610.00289010585458781
300.9980494003810540.003901199237891250.00195059961894562
310.9969845530356010.006030893928797740.00301544696439887
320.9955757706820550.008848458635889740.00442422931794487
330.9945482763956850.01090344720863080.00545172360431541
340.99200536018060.01598927963880030.00799463981940013
350.9900161407538940.01996771849221290.00998385924610647
360.9859340535550380.02813189288992290.0140659464449615
370.9905733722837960.01885325543240710.00942662771620356
380.9867889108217570.02642217835648690.0132110891782435
390.9846131832785750.03077363344284990.015386816721425
400.9849598797891060.03008024042178870.0150401202108943
410.9801320034692570.03973599306148610.0198679965307431
420.9777202961300140.04455940773997220.0222797038699861
430.9703716419802390.05925671603952290.0296283580197615
440.965038166228220.06992366754356010.03496183377178
450.9545403302084530.09091933958309360.0454596697915468
460.9629168469020180.07416630619596420.0370831530979821
470.9523810506926610.09523789861467770.0476189493073388
480.9392687441595580.1214625116808840.0607312558404422
490.9478157413772130.1043685172455750.0521842586227873
500.9446170388435070.1107659223129850.0553829611564927
510.9317375912723670.1365248174552660.068262408727633
520.9155391405322360.1689217189355280.0844608594677638
530.9028653644327690.1942692711344620.0971346355672311
540.8879376710649880.2241246578700240.112062328935012
550.8828114675481890.2343770649036210.117188532451811
560.8644378525198070.2711242949603870.135562147480193
570.8505108098920650.298978380215870.149489190107935
580.8237208337282020.3525583325435970.176279166271798
590.8652140153713240.2695719692573530.134785984628676
600.8622152563391520.2755694873216970.137784743660848
610.8828827287303490.2342345425393030.117117271269651
620.8837586238753820.2324827522492360.116241376124618
630.9316622493233440.1366755013533120.0683377506766561
640.9201595902730380.1596808194539250.0798404097269624
650.9097637619642020.1804724760715960.0902362380357978
660.9208391159170380.1583217681659250.0791608840829624
670.9200248495856070.1599503008287850.0799751504143927
680.9112333829815990.1775332340368030.0887666170184015
690.9419334892476920.1161330215046160.0580665107523081
700.9463850286728780.1072299426542430.0536149713271216
710.9410903117011440.1178193765977130.0589096882988564
720.9610685993721080.07786280125578430.0389314006278922
730.9525882934521930.0948234130956140.047411706547807
740.9419988848268330.1160022303463340.0580011151731672
750.9351435406471360.1297129187057280.0648564593528642
760.9215827283161820.1568345433676360.0784172716838182
770.9376191050019120.1247617899961760.062380894998088
780.9260443131059370.1479113737881250.0739556868940626
790.9196729316375490.1606541367249010.0803270683624506
800.9129940485133820.1740119029732370.0870059514866183
810.8964426778225830.2071146443548340.103557322177417
820.878486239475080.2430275210498390.12151376052492
830.8729402074762950.254119585047410.127059792523705
840.85461548487850.2907690302430010.1453845151215
850.8315743477394250.3368513045211510.168425652260575
860.8089793535819460.3820412928361080.191020646418054
870.782155084002830.4356898319943410.21784491599717
880.7531750843135770.4936498313728450.246824915686423
890.8216600239044590.3566799521910820.178339976095541
900.8525552990290930.2948894019418140.147444700970907
910.8304485324048980.3391029351902040.169551467595102
920.8076856884305410.3846286231389180.192314311569459
930.7855125738005840.4289748523988310.214487426199416
940.7629786572706580.4740426854586840.237021342729342
950.7373131007499810.5253737985000370.262686899250018
960.7127450716168620.5745098567662760.287254928383138
970.6866165178930390.6267669642139220.313383482106961
980.6844393831964760.6311212336070480.315560616803524
990.6509307035796140.6981385928407730.349069296420386
1000.6402802233186530.7194395533626940.359719776681347
1010.6166552358468490.7666895283063020.383344764153151
1020.5869787733655160.8260424532689680.413021226634484
1030.63776445222010.72447109555980.3622355477799
1040.6232515253359980.7534969493280030.376748474664001
1050.6406184043804810.7187631912390380.359381595619519
1060.6139059610730240.7721880778539510.386094038926976
1070.6038050955426750.792389808914650.396194904457325
1080.6444252206269760.7111495587460480.355574779373024
1090.6135763786821540.7728472426356920.386423621317846
1100.5865528837687230.8268942324625550.413447116231277
1110.594182240658490.8116355186830190.40581775934151
1120.6216039283088350.756792143382330.378396071691165
1130.6094306696165190.7811386607669610.390569330383481
1140.6962027419160570.6075945161678850.303797258083943
1150.666377513424770.667244973150460.33362248657523
1160.6396917442259350.7206165115481290.360308255774065
1170.6057963367177180.7884073265645650.394203663282282
1180.5818410025598140.8363179948803720.418158997440186
1190.5467664915094260.9064670169811490.453233508490574
1200.5147750653643710.9704498692712580.485224934635629
1210.485557683339740.971115366679480.51444231666026
1220.4526752348959430.9053504697918860.547324765104057
1230.4255573844951980.8511147689903960.574442615504802
1240.3936193206894210.7872386413788420.606380679310579
1250.385307080076110.770614160152220.61469291992389
1260.3556514833808990.7113029667617990.644348516619101
1270.3394173324743540.6788346649487090.660582667525646
1280.4413203963592380.8826407927184750.558679603640762
1290.4219599171849860.8439198343699720.578040082815014
1300.4123350283436240.8246700566872470.587664971656376
1310.4002157958906950.800431591781390.599784204109305
1320.3710175039066770.7420350078133540.628982496093323
1330.3881900577568240.7763801155136480.611809942243176
1340.358790956430760.7175819128615210.64120904356924
1350.3679911969083560.7359823938167130.632008803091644
1360.3564304781079510.7128609562159020.643569521892049
1370.3266032482224650.6532064964449290.673396751777535
1380.3029969825388620.6059939650777250.697003017461138
1390.2763368341512690.5526736683025390.723663165848731
1400.2530762052489930.5061524104979850.746923794751007
1410.225734704916720.451469409833440.77426529508328
1420.2295534369013910.4591068738027820.770446563098609
1430.2050451965217390.4100903930434780.794954803478261
1440.1845740534315290.3691481068630590.815425946568471
1450.1724349721289250.344869944257850.827565027871075
1460.1651669547514530.3303339095029060.834833045248547
1470.1727366632416320.3454733264832650.827263336758368
1480.1901569661308620.3803139322617250.809843033869138
1490.2096525467786260.4193050935572520.790347453221374
1500.2062888768365880.4125777536731770.793711123163412
1510.184599718531020.369199437062040.81540028146898
1520.1650015217944860.3300030435889720.834998478205514
1530.1784311045572890.3568622091145780.821568895442711
1540.2141099602417420.4282199204834840.785890039758258
1550.192741633501910.3854832670038190.80725836649809
1560.17266804540080.3453360908016010.8273319545992
1570.1505634424938780.3011268849877550.849436557506122
1580.2204375626723140.4408751253446280.779562437327686
1590.2462644289238180.4925288578476370.753735571076182
1600.2206639057116520.4413278114233030.779336094288348
1610.1942107192365050.3884214384730110.805789280763495
1620.1717107775267910.3434215550535830.828289222473209
1630.1517180536005210.3034361072010420.848281946399479
1640.2549861601847720.5099723203695450.745013839815228
1650.2517756648163370.5035513296326730.748224335183663
1660.2475902730703010.4951805461406020.752409726929699
1670.2197228229996330.4394456459992670.780277177000367
1680.197981063776220.3959621275524390.80201893622378
1690.2518548714735910.5037097429471810.748145128526409
1700.2741967238195930.5483934476391860.725803276180407
1710.2470321915239890.4940643830479770.752967808476012
1720.2434023665011640.4868047330023270.756597633498836
1730.3970396666899010.7940793333798020.602960333310099
1740.3854990678503170.7709981357006340.614500932149683
1750.4108125572404740.8216251144809480.589187442759526
1760.4165598393404750.833119678680950.583440160659525
1770.4676120497333540.9352240994667080.532387950266646
1780.4345039752203570.8690079504407130.565496024779643
1790.4147880357253230.8295760714506450.585211964274677
1800.4106070350411410.8212140700822810.589392964958859
1810.3735847744812970.7471695489625930.626415225518703
1820.3628926197727660.7257852395455320.637107380227234
1830.3273771634324430.6547543268648870.672622836567557
1840.2994867802110880.5989735604221760.700513219788912
1850.3151793410752440.6303586821504870.684820658924756
1860.3091116572688820.6182233145377640.690888342731118
1870.2768253767499160.5536507534998330.723174623250084
1880.2515654067364810.5031308134729610.748434593263519
1890.2228533639525960.4457067279051920.777146636047404
1900.2016452156539430.4032904313078850.798354784346057
1910.2041603372245270.4083206744490550.795839662775473
1920.1857674460715830.3715348921431660.814232553928417
1930.2038206196729670.4076412393459340.796179380327033
1940.1901276967195720.3802553934391450.809872303280428
1950.1909504085150640.3819008170301290.809049591484936
1960.1984250248339120.3968500496678230.801574975166088
1970.2436983755793150.487396751158630.756301624420685
1980.2264933759012680.4529867518025360.773506624098732
1990.2545526712013020.5091053424026030.745447328798698
2000.2228832229270510.4457664458541010.777116777072949
2010.2531556261620890.5063112523241790.746844373837911
2020.2341571897875990.4683143795751990.765842810212401
2030.2944763846035510.5889527692071010.705523615396449
2040.2610279214360.5220558428719990.738972078564
2050.2293372923506260.4586745847012520.770662707649374
2060.2103620716838270.4207241433676540.789637928316173
2070.1804222224348760.3608444448697520.819577777565124
2080.201874707627470.403749415254940.79812529237253
2090.1720505099442660.3441010198885320.827949490055734
2100.1878747564404240.3757495128808480.812125243559576
2110.2113668245277440.4227336490554870.788633175472256
2120.1973057646166280.3946115292332570.802694235383372
2130.1713029832724760.3426059665449530.828697016727524
2140.2135029488033120.4270058976066230.786497051196688
2150.1872639114271580.3745278228543160.812736088572842
2160.176294270546370.352588541092740.82370572945363
2170.2072521895522490.4145043791044980.792747810447751
2180.1785209800246890.3570419600493790.821479019975311
2190.1647657231028260.3295314462056520.835234276897174
2200.1717878310211760.3435756620423520.828212168978824
2210.1767013009497220.3534026018994430.823298699050278
2220.1790197438448080.3580394876896160.820980256155192
2230.1630871488708270.3261742977416550.836912851129173
2240.1345194990116310.2690389980232610.865480500988369
2250.1205513326062940.2411026652125880.879448667393706
2260.1453517615123380.2907035230246770.854648238487662
2270.3235967928077370.6471935856154730.676403207192263
2280.2997899800964010.5995799601928020.700210019903599
2290.2732574510577910.5465149021155830.726742548942209
2300.2570740867107210.5141481734214420.742925913289279
2310.2174474026629380.4348948053258750.782552597337063
2320.250767425512950.5015348510258990.74923257448705
2330.2094739901235950.4189479802471910.790526009876405
2340.172361110736720.344722221473440.82763888926328
2350.171193389272290.342386778544580.82880661072771
2360.148734723918950.29746944783790.85126527608105
2370.1220284053152760.2440568106305520.877971594684724
2380.09261159435332490.185223188706650.907388405646675
2390.1870825958248880.3741651916497750.812917404175112
2400.1808893362733320.3617786725466650.819110663726668
2410.1521372467964330.3042744935928650.847862753203567
2420.3229730912479790.6459461824959590.677026908752021
2430.2805913401666420.5611826803332840.719408659833358
2440.2256335505048060.4512671010096120.774366449495194
2450.3382818923844680.6765637847689370.661718107615532
2460.2589168191725340.5178336383450680.741083180827466
2470.1904925699464830.3809851398929650.809507430053517
2480.3093072274135070.6186144548270140.690692772586493
2490.2234956728859870.4469913457719730.776504327114013
2500.1481990714849920.2963981429699830.851800928515008
2510.2358895996966610.4717791993933220.764110400303339
2520.7436685821612590.5126628356774830.256331417838741







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level70.029045643153527NOK
5% type I error level180.0746887966804979NOK
10% type I error level280.116182572614108NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 7 & 0.029045643153527 & NOK \tabularnewline
5% type I error level & 18 & 0.0746887966804979 & NOK \tabularnewline
10% type I error level & 28 & 0.116182572614108 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186332&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]7[/C][C]0.029045643153527[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]18[/C][C]0.0746887966804979[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]28[/C][C]0.116182572614108[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186332&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186332&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level70.029045643153527NOK
5% type I error level180.0746887966804979NOK
10% type I error level280.116182572614108NOK



Parameters (Session):
par1 = 6 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 6 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}