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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 15 Dec 2014 21:20:37 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t1418678507e98al4gue9j87yq.htm/, Retrieved Thu, 16 May 2024 18:54:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269042, Retrieved Thu, 16 May 2024 18:54:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2014-12-12 13:12:51] [fa1b8827d7de91b8b87087311d3d9fa1]
- R  D  [Multiple Regression] [] [2014-12-13 11:13:21] [bb1b6762b7e5624d262776d3f7139d34]
-    D    [Multiple Regression] [] [2014-12-15 08:53:53] [7b576ab45e161dc8fb6fe50455a3800c]
-           [Multiple Regression] [] [2014-12-15 10:02:37] [7b576ab45e161dc8fb6fe50455a3800c]
-    D          [Multiple Regression] [Multiple Linear R...] [2014-12-15 21:20:37] [abae100319030711995379e8f3c2e274] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
26	50	4	2011	1	0	0	0	0	7.5
57	62	4	2011	1	1	57	62	4	6
37	54	5	2011	1	0	0	0	0	6.5
67	71	4	2011	1	1	67	71	4	1
43	54	4	2011	1	1	43	54	4	1
52	65	9	2011	1	1	52	65	9	5.5
52	73	8	2011	1	0	0	0	0	8.5
43	52	11	2011	1	1	43	52	11	6.5
84	84	4	2011	1	1	84	84	4	4.5
67	42	4	2011	1	1	67	42	4	2
49	66	6	2011	1	1	49	66	6	5
70	65	4	2011	1	1	70	65	4	0.5
52	78	8	2011	1	1	52	78	8	5
58	73	4	2011	1	0	0	0	0	5
68	75	4	2011	1	0	0	0	0	2.5
62	72	11	2011	0	0	0	0	0	5
43	66	4	2011	1	1	43	66	4	5.5
56	70	4	2011	1	0	0	0	0	3.5
56	61	6	2011	0	1	56	61	6	3
74	81	6	2011	1	0	0	0	0	4
65	71	4	2011	1	1	65	71	4	0.5
63	69	8	2011	1	1	63	69	8	6.5
58	71	5	2011	1	0	0	0	0	4.5
57	72	4	2011	1	1	57	72	4	7.5
63	68	9	2011	1	1	63	68	9	5.5
53	70	4	2011	1	1	53	70	4	4
57	68	7	2011	0	1	57	68	7	7.5
51	61	10	2011	0	0	0	0	0	7
64	67	4	2011	1	1	64	67	4	4
53	76	4	2011	1	0	0	0	0	5.5
29	70	7	2011	1	0	0	0	0	2.5
54	60	12	2011	1	0	0	0	0	5.5
58	72	7	2011	1	1	58	72	7	3.5
43	69	5	2011	1	1	43	69	5	2.5
51	71	8	2011	1	1	51	71	8	4.5
53	62	5	2011	1	1	53	62	5	4.5
54	70	4	2011	1	0	0	0	0	4.5
56	64	9	2011	0	1	56	64	9	6
61	58	7	2011	1	1	61	58	7	2.5
47	76	4	2011	1	0	0	0	0	5
39	52	4	2011	1	1	39	52	4	0
48	59	4	2011	1	1	48	59	4	5
50	68	4	2011	1	1	50	68	4	6.5
35	76	4	2011	1	1	35	76	4	5
30	65	7	2011	0	1	30	65	7	6
68	67	4	2011	1	0	0	0	0	4.5
49	59	7	2011	1	1	49	59	7	5.5
61	69	4	2011	0	1	61	69	4	1
67	76	4	2011	1	0	0	0	0	7.5
47	63	4	2011	0	1	47	63	4	6
56	75	4	2011	0	1	56	75	4	5
50	63	8	2011	0	1	50	63	8	1
43	60	4	2011	1	1	43	60	4	5
67	73	4	2011	0	1	67	73	4	6.5
62	63	4	2011	1	1	62	63	4	7
57	70	4	2011	1	1	57	70	4	4.5
41	75	7	2011	0	0	0	0	0	0
54	66	12	2011	1	1	54	66	12	8.5
45	63	4	2011	0	0	0	0	0	3.5
48	63	4	2011	0	1	48	63	4	7.5
61	64	4	2011	1	1	61	64	4	3.5
56	70	5	2011	1	0	0	0	0	6
41	75	15	2011	1	0	0	0	0	1.5
43	61	5	2011	1	1	43	61	5	9
53	60	10	2011	1	0	0	0	0	3.5
44	62	9	2011	0	1	44	62	9	3.5
66	73	8	2011	1	0	0	0	0	4
58	61	4	2011	1	1	58	61	4	6.5
46	66	5	2011	1	1	46	66	5	7.5
37	64	4	2011	0	0	0	0	0	6
51	59	9	2011	1	0	0	0	0	5
51	64	4	2011	1	0	0	0	0	5.5
56	60	10	2011	0	0	0	0	0	3.5
66	56	4	2011	0	1	66	56	4	7.5
37	78	4	2011	1	0	0	0	0	6.5
42	67	7	2011	1	0	0	0	0	6.5
38	59	5	2011	0	1	38	59	5	6.5
66	66	4	2011	1	0	0	0	0	7
34	68	4	2011	0	0	0	0	0	3.5
53	71	4	2011	1	1	53	71	4	1.5
49	66	4	2011	0	0	0	0	0	4
55	73	4	2011	0	0	0	0	0	7.5
49	72	4	2011	0	0	0	0	0	4.5
59	71	6	2011	0	1	59	71	6	0
40	59	10	2011	0	0	0	0	0	3.5
58	64	7	2011	0	1	58	64	7	5.5
60	66	4	2011	0	1	60	66	4	5
63	78	4	2011	0	0	0	0	0	4.5
56	68	7	2011	0	0	0	0	0	2.5
54	73	4	2011	0	0	0	0	0	7.5
52	62	8	2011	0	1	52	62	8	7
34	65	11	2011	0	1	34	65	11	0
69	68	6	2011	0	1	69	68	6	4.5
32	65	14	2011	0	0	0	0	0	3
48	60	5	2011	0	1	48	60	5	1.5
67	71	4	2011	0	0	0	0	0	3.5
58	65	8	2011	0	1	58	65	8	2.5
57	68	9	2011	0	1	57	68	9	5.5
42	64	4	2011	0	1	42	64	4	8
64	74	4	2011	0	1	64	74	4	1
58	69	5	2011	0	1	58	69	5	5
66	76	4	2011	0	0	0	0	0	4.5
26	68	5	2011	0	1	26	68	5	3
61	72	4	2011	0	1	61	72	4	3
52	67	4	2011	0	1	52	67	4	8
51	63	7	2011	0	0	0	0	0	2.5
55	59	10	2011	0	0	0	0	0	7
50	73	4	2011	0	0	0	0	0	0
60	66	5	2011	0	0	0	0	0	1
56	62	4	2011	0	0	0	0	0	3.5
63	69	4	2011	0	0	0	0	0	5.5
61	66	4	2011	0	1	61	66	4	5.5
52	51	6	2012	1	1	52	51	6	0.5
16	56	4	2012	1	1	16	56	4	7.5
46	67	8	2012	1	1	46	67	8	9
56	69	5	2012	1	1	56	69	5	9.5
52	57	4	2012	0	0	0	0	0	8.5
55	56	17	2012	0	1	55	56	17	7
50	55	4	2012	1	1	50	55	4	8
59	63	4	2012	1	0	0	0	0	10
60	67	8	2012	1	1	60	67	8	7
52	65	4	2012	1	0	0	0	0	8.5
44	47	7	2012	1	0	0	0	0	9
67	76	4	2012	1	1	67	76	4	9.5
52	64	4	2012	1	1	52	64	4	4
55	68	5	2012	1	1	55	68	5	6
37	64	7	2012	1	1	37	64	7	8
54	65	4	2012	1	1	54	65	4	5.5
72	71	4	2012	0	1	72	71	4	9.5
51	63	7	2012	1	1	51	63	7	7.5
48	60	11	2012	1	1	48	60	11	7
60	68	7	2012	1	0	0	0	0	7.5
50	72	4	2012	1	1	50	72	4	8
63	70	4	2012	1	1	63	70	4	7
33	61	4	2012	1	1	33	61	4	7
67	61	4	2012	1	1	67	61	4	6
46	62	4	2012	1	1	46	62	4	10
54	71	4	2012	1	1	54	71	4	2.5
59	71	6	2012	1	0	0	0	0	9
61	51	8	2012	1	1	61	51	8	8
33	56	23	2012	0	1	33	56	23	6
47	70	4	2012	1	1	47	70	4	8.5
69	73	8	2012	1	1	69	73	8	6
52	76	6	2012	1	1	52	76	6	9
55	68	4	2012	1	0	0	0	0	8
41	48	7	2012	1	0	0	0	0	9
73	52	4	2012	1	1	73	52	4	5.5
52	60	4	2012	1	0	0	0	0	7
50	59	4	2012	1	0	0	0	0	5.5
51	57	10	2012	1	1	51	57	10	9
60	79	6	2012	1	0	0	0	0	2
56	60	5	2012	1	1	56	60	5	8.5
56	60	5	2012	1	1	56	60	5	9
29	59	4	2012	1	0	0	0	0	8.5
66	62	4	2012	0	1	66	62	4	9
66	59	5	2012	0	1	66	59	5	7.5
73	61	5	2012	1	1	73	61	5	10
55	71	5	2012	1	0	0	0	0	9
64	57	5	2012	0	0	0	0	0	7.5
40	66	4	2012	0	0	0	0	0	6
46	63	6	2012	0	0	0	0	0	10.5
58	69	4	2012	0	1	58	69	4	8.5
43	58	4	2012	1	0	0	0	0	8
61	59	4	2012	1	1	61	59	4	10
51	48	9	2012	0	0	0	0	0	10.5
50	66	18	2012	0	1	50	66	18	6.5
52	73	6	2012	0	0	0	0	0	9.5
54	67	5	2012	0	1	54	67	5	8.5
66	61	4	2012	0	0	0	0	0	7.5
61	68	11	2012	0	0	0	0	0	5
80	75	4	2012	0	1	80	75	4	8
51	62	10	2012	0	0	0	0	0	10
56	69	6	2012	0	1	56	69	6	7
56	58	8	2012	1	1	56	58	8	7.5
56	60	8	2012	1	1	56	60	8	7.5
53	74	6	2012	0	1	53	74	6	9.5
47	55	8	2012	1	1	47	55	8	6
25	62	4	2012	1	0	0	0	0	10
47	63	4	2012	0	1	47	63	4	7
46	69	9	2012	1	0	0	0	0	3
50	58	9	2012	0	0	0	0	0	6
39	58	5	2012	0	0	0	0	0	7
51	68	4	2012	1	1	51	68	4	10
58	72	4	2012	0	0	0	0	0	7
35	62	15	2012	0	1	35	62	15	3.5
58	62	10	2012	0	0	0	0	0	8
60	65	9	2012	0	0	0	0	0	10
62	69	7	2012	0	0	0	0	0	5.5
63	66	9	2012	0	0	0	0	0	6
53	72	6	2012	0	1	53	72	6	6.5
46	62	4	2012	0	1	46	62	4	6.5
67	75	7	2012	0	1	67	75	7	8.5
59	58	4	2012	0	1	59	58	4	4
64	66	7	2012	0	0	0	0	0	9.5
38	55	4	2012	0	0	0	0	0	8
50	47	15	2012	0	1	50	47	15	8.5
48	72	4	2012	1	0	0	0	0	5.5
48	62	9	2012	0	0	0	0	0	7
47	64	4	2012	0	0	0	0	0	9
66	64	4	2012	0	0	0	0	0	8
47	19	28	2012	1	1	47	19	28	10
63	50	4	2012	0	1	63	50	4	8
58	68	4	2012	1	0	0	0	0	6
44	70	4	2012	0	0	0	0	0	8
51	79	5	2012	1	1	51	79	5	5
43	69	4	2012	0	0	0	0	0	9
55	71	4	2012	1	1	55	71	4	4.5
38	48	12	2012	0	1	38	48	12	8.5
45	73	4	2012	0	0	0	0	0	9.5
50	74	6	2012	0	1	50	74	6	8.5
54	66	6	2012	0	1	54	66	6	7.5
57	71	5	2012	1	1	57	71	5	7.5
60	74	4	2012	1	0	0	0	0	5
55	78	4	2012	0	0	0	0	0	7
56	75	4	2012	1	0	0	0	0	8
49	53	10	2012	1	1	49	53	10	5.5
37	60	7	2012	0	1	37	60	7	8.5
59	70	4	2012	1	1	59	70	4	9.5
46	69	7	2012	0	1	46	69	7	7
51	65	4	2012	0	0	0	0	0	8
58	78	4	2012	1	0	0	0	0	8.5
64	78	12	2012	0	0	0	0	0	3.5
53	59	5	2012	1	1	53	59	5	6.5
48	72	8	2012	1	1	48	72	8	6.5
51	70	6	2012	1	0	0	0	0	10.5
47	63	17	2012	0	0	0	0	0	8.5
59	63	4	2012	1	0	0	0	0	8
62	71	5	2012	0	1	62	71	5	10
62	74	4	2012	1	1	62	74	4	10
51	67	5	2012	1	0	0	0	0	9.5
64	66	5	2012	1	0	0	0	0	9
52	62	6	2012	1	0	0	0	0	10
67	80	4	2012	0	1	67	80	4	7.5
50	73	4	2012	1	1	50	73	4	4.5
54	67	4	2012	1	1	54	67	4	4.5
58	61	6	2012	1	1	58	61	6	0.5
56	73	8	2012	0	0	0	0	0	6.5
63	74	10	2012	1	1	63	74	10	4.5
31	32	4	2012	1	1	31	32	4	5.5
65	69	5	2012	0	1	65	69	5	5
71	69	4	2012	1	0	0	0	0	6
50	84	4	2012	0	0	0	0	0	4
57	64	4	2012	0	1	57	64	4	8
47	58	16	2012	0	0	0	0	0	10.5
47	59	7	2012	0	1	47	59	7	6.5
57	78	4	2012	0	1	57	78	4	8
43	57	4	2012	1	0	0	0	0	8.5
41	60	14	2012	1	1	41	60	14	5.5
63	68	5	2012	1	0	0	0	0	7
63	68	5	2012	1	1	63	68	5	5
56	73	5	2012	1	1	56	73	5	3.5
51	69	5	2012	1	0	0	0	0	5
50	67	7	2012	0	1	50	67	7	9
22	60	19	2012	0	0	0	0	0	8.5
41	65	16	2012	1	1	41	65	16	5
59	66	4	2012	0	0	0	0	0	9.5
56	74	4	2012	0	1	56	74	4	3
66	81	7	2012	1	0	0	0	0	1.5
53	72	9	2012	0	0	0	0	0	6
42	55	5	2012	0	1	42	55	5	0.5
52	49	14	2012	0	1	52	49	14	6.5
54	74	4	2012	0	0	0	0	0	7.5
44	53	16	2012	0	1	44	53	16	4.5
62	64	10	2012	0	1	62	64	10	8
53	65	5	2012	0	0	0	0	0	9
50	57	6	2012	0	1	50	57	6	7.5
36	51	4	2012	0	0	0	0	0	8.5
76	80	4	2012	0	0	0	0	0	7
66	67	4	2012	0	1	66	67	4	9.5
62	70	5	2012	0	1	62	70	5	6.5
59	74	4	2012	0	0	0	0	0	9.5
47	75	4	2012	0	1	47	75	4	6
55	70	5	2012	0	0	0	0	0	8
58	69	4	2012	0	0	0	0	0	9.5
60	65	4	2012	0	1	60	65	4	8
44	55	5	2012	1	0	0	0	0	8
57	71	8	2012	0	0	0	0	0	9
45	65	15	2012	0	1	45	65	15	5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 10 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269042&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]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269042&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269042&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Multiple Linear Regression - Estimated Regression Equation
Tot[t] = -5245.24 + 0.00148167AMS.I[t] -0.0987234AMS.E[t] -0.0920137AMS.A[t] + 2.61425Academiejaar[t] -0.0927568Type_Opleiding_Binair[t] -8.32148gender[t] + 0.0102542AMS.I_GES[t] + 0.101007AMS.E_GES[t] + 0.0902903AMS.A_GES[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Tot[t] =  -5245.24 +  0.00148167AMS.I[t] -0.0987234AMS.E[t] -0.0920137AMS.A[t] +  2.61425Academiejaar[t] -0.0927568Type_Opleiding_Binair[t] -8.32148gender[t] +  0.0102542AMS.I_GES[t] +  0.101007AMS.E_GES[t] +  0.0902903AMS.A_GES[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269042&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Tot[t] =  -5245.24 +  0.00148167AMS.I[t] -0.0987234AMS.E[t] -0.0920137AMS.A[t] +  2.61425Academiejaar[t] -0.0927568Type_Opleiding_Binair[t] -8.32148gender[t] +  0.0102542AMS.I_GES[t] +  0.101007AMS.E_GES[t] +  0.0902903AMS.A_GES[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269042&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269042&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Tot[t] = -5245.24 + 0.00148167AMS.I[t] -0.0987234AMS.E[t] -0.0920137AMS.A[t] + 2.61425Academiejaar[t] -0.0927568Type_Opleiding_Binair[t] -8.32148gender[t] + 0.0102542AMS.I_GES[t] + 0.101007AMS.E_GES[t] + 0.0902903AMS.A_GES[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-5245.24529.997-9.8976.94507e-203.47253e-20
AMS.I0.001481670.02089340.070920.9435180.471759
AMS.E-0.09872340.0292312-3.3770.0008405390.000420269
AMS.A-0.09201370.0650936-1.4140.1586520.0793259
Academiejaar2.614250.263389.9265.61351e-202.80675e-20
Type_Opleiding_Binair-0.09275680.259028-0.35810.7205540.360277
gender-8.321482.57422-3.2330.001380080.000690038
AMS.I_GES0.01025420.02730210.37560.7075230.353762
AMS.E_GES0.1010070.03679042.7450.006451130.00322556
AMS.A_GES0.09029030.08207331.10.2722680.136134

\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) & -5245.24 & 529.997 & -9.897 & 6.94507e-20 & 3.47253e-20 \tabularnewline
AMS.I & 0.00148167 & 0.0208934 & 0.07092 & 0.943518 & 0.471759 \tabularnewline
AMS.E & -0.0987234 & 0.0292312 & -3.377 & 0.000840539 & 0.000420269 \tabularnewline
AMS.A & -0.0920137 & 0.0650936 & -1.414 & 0.158652 & 0.0793259 \tabularnewline
Academiejaar & 2.61425 & 0.26338 & 9.926 & 5.61351e-20 & 2.80675e-20 \tabularnewline
Type_Opleiding_Binair & -0.0927568 & 0.259028 & -0.3581 & 0.720554 & 0.360277 \tabularnewline
gender & -8.32148 & 2.57422 & -3.233 & 0.00138008 & 0.000690038 \tabularnewline
AMS.I_GES & 0.0102542 & 0.0273021 & 0.3756 & 0.707523 & 0.353762 \tabularnewline
AMS.E_GES & 0.101007 & 0.0367904 & 2.745 & 0.00645113 & 0.00322556 \tabularnewline
AMS.A_GES & 0.0902903 & 0.0820733 & 1.1 & 0.272268 & 0.136134 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269042&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]-5245.24[/C][C]529.997[/C][C]-9.897[/C][C]6.94507e-20[/C][C]3.47253e-20[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.00148167[/C][C]0.0208934[/C][C]0.07092[/C][C]0.943518[/C][C]0.471759[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0987234[/C][C]0.0292312[/C][C]-3.377[/C][C]0.000840539[/C][C]0.000420269[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0920137[/C][C]0.0650936[/C][C]-1.414[/C][C]0.158652[/C][C]0.0793259[/C][/ROW]
[ROW][C]Academiejaar[/C][C]2.61425[/C][C]0.26338[/C][C]9.926[/C][C]5.61351e-20[/C][C]2.80675e-20[/C][/ROW]
[ROW][C]Type_Opleiding_Binair[/C][C]-0.0927568[/C][C]0.259028[/C][C]-0.3581[/C][C]0.720554[/C][C]0.360277[/C][/ROW]
[ROW][C]gender[/C][C]-8.32148[/C][C]2.57422[/C][C]-3.233[/C][C]0.00138008[/C][C]0.000690038[/C][/ROW]
[ROW][C]AMS.I_GES[/C][C]0.0102542[/C][C]0.0273021[/C][C]0.3756[/C][C]0.707523[/C][C]0.353762[/C][/ROW]
[ROW][C]AMS.E_GES[/C][C]0.101007[/C][C]0.0367904[/C][C]2.745[/C][C]0.00645113[/C][C]0.00322556[/C][/ROW]
[ROW][C]AMS.A_GES[/C][C]0.0902903[/C][C]0.0820733[/C][C]1.1[/C][C]0.272268[/C][C]0.136134[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269042&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269042&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-5245.24529.997-9.8976.94507e-203.47253e-20
AMS.I0.001481670.02089340.070920.9435180.471759
AMS.E-0.09872340.0292312-3.3770.0008405390.000420269
AMS.A-0.09201370.0650936-1.4140.1586520.0793259
Academiejaar2.614250.263389.9265.61351e-202.80675e-20
Type_Opleiding_Binair-0.09275680.259028-0.35810.7205540.360277
gender-8.321482.57422-3.2330.001380080.000690038
AMS.I_GES0.01025420.02730210.37560.7075230.353762
AMS.E_GES0.1010070.03679042.7450.006451130.00322556
AMS.A_GES0.09029030.08207331.10.2722680.136134






Multiple Linear Regression - Regression Statistics
Multiple R0.569918
R-squared0.324807
Adjusted R-squared0.302132
F-TEST (value)14.3248
F-TEST (DF numerator)9
F-TEST (DF denominator)268
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.11656
Sum Squared Residuals1200.59

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.569918 \tabularnewline
R-squared & 0.324807 \tabularnewline
Adjusted R-squared & 0.302132 \tabularnewline
F-TEST (value) & 14.3248 \tabularnewline
F-TEST (DF numerator) & 9 \tabularnewline
F-TEST (DF denominator) & 268 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.11656 \tabularnewline
Sum Squared Residuals & 1200.59 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269042&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.569918[/C][/ROW]
[ROW][C]R-squared[/C][C]0.324807[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.302132[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]14.3248[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]9[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]268[/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]2.11656[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1200.59[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269042&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269042&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.569918
R-squared0.324807
Adjusted R-squared0.302132
F-TEST (value)14.3248
F-TEST (DF numerator)9
F-TEST (DF denominator)268
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.11656
Sum Squared Residuals1200.59






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.56.665240.834759
264.413121.58688
36.56.194630.305368
414.55103-3.55103
514.23054-3.23054
65.54.352671.14733
78.54.065074.43493
86.54.213912.28609
94.54.78023-0.28023
1024.4848-2.4848
1154.324920.675082
120.54.57253-4.07253
1354.384080.615916
1454.442020.557983
152.54.25939-1.75939
1653.995331.00467
175.54.257951.24205
183.54.73522-1.23522
1934.48841-1.48841
2043.491910.50809
210.54.52756-4.02756
226.54.492622.00738
234.54.54745-0.0474503
247.54.435953.06405
255.54.488621.01138
2644.38444-0.384443
277.54.514412.98559
2875.1571.843
2944.50669-0.506687
305.54.138441.36156
312.54.41918-1.91918
325.54.983380.516615
333.54.44252-0.94252
342.54.26308-1.76308
354.54.356360.143638
364.54.364450.135551
374.54.73226-0.232261
3864.490091.50991
392.54.44575-1.94575
4054.129550.870451
4104.17903-4.17903
4254.300640.699358
436.54.344672.15533
4454.18690.8131
4564.190681.80932
464.55.04917-0.549174
475.54.307211.19279
4814.5688-3.5688
497.54.159183.34082
5064.39081.6092
5154.523830.476173
5214.41911-3.41911
5354.244250.755754
546.54.648351.85165
5574.474082.52592
564.54.431390.0686131
5704.0361-4.0361
588.54.373264.12674
593.55.50275-2.00275
607.54.402533.09747
613.54.46463-0.964628
6264.643211.35679
631.53.20723-1.70723
6494.244814.75519
653.55.16593-1.66593
663.54.34469-0.844689
6744.08582-0.0858157
686.54.422572.07743
697.54.291433.20857
7065.392170.607831
7155.3537-0.353704
725.55.320160.179844
733.55.26313-1.76313
747.54.597792.90221
756.53.917292.58271
766.54.734611.76539
776.54.274322.22568
7875.144931.85507
793.54.99283-1.49283
801.54.38673-2.88673
8145.2125-1.2125
827.54.530332.96967
834.54.62016-0.120162
8404.54645-4.54645
853.55.33815-1.83815
865.54.517010.982994
8754.550220.449784
884.54.048570.451434
892.54.74939-2.24939
907.54.528852.97115
9174.44032.5597
9204.23073-4.23073
934.54.65696-0.15696
9434.3659-1.3659
951.54.39396-2.89396
963.54.74556-1.24556
972.54.51757-2.01757
985.54.510960.989041
9984.33443.6656
10014.61543-3.61543
10154.531870.468128
1024.54.250460.249543
10334.15404-1.15404
10434.57566-1.57566
10584.458613.54139
1062.55.23559-2.73559
10775.360371.63963
10804.52292-4.52292
10915.13679-4.13679
1103.55.61777-2.11777
1115.54.937080.562924
1125.54.561950.938048
1130.56.94012-6.44012
1147.56.53250.967505
11596.90282.0972
1169.57.02992.4701
1178.58.71971-0.219712
11877.06055-0.0605475
11986.929231.07077
120108.044991.95501
12177.0671-0.0671033
1228.57.837170.662832
12399.32629-0.326294
1249.57.17672.3233
12546.97326-2.97326
12667.01588-1.01588
12786.792051.20795
1285.56.99901-1.49901
1299.57.316722.18328
1307.56.954070.545932
13176.905120.0948847
1327.57.276810.22319
13386.968061.03194
13477.11606-0.116056
13576.743420.256575
13667.14245-1.14245
137106.898283.10172
1382.57.01272-4.51272
13997.071171.92883
14087.04230.957702
14166.79202-0.792017
1428.56.928281.57172
14367.18643-1.18643
14496.997222.00278
14587.545440.454557
14699.22313-0.223126
1475.57.19231-1.69231
14878.33078-1.33078
1495.58.42654-2.92654
15096.935192.06481
15126.28287-4.28287
1528.57.009341.49066
15397.009341.99066
1548.58.395430.10457
15597.225751.77425
1567.57.217180.282825
157107.211142.78886
15897.157261.84274
1597.58.64548-1.14548
16067.81342-1.81342
16110.57.934452.56555
1628.57.147851.35215
16388.5149-0.514897
164107.067462.93254
16510.59.146671.35333
1666.57.02298-0.522983
1679.56.956112.54389
1688.57.094611.40539
1697.58.34556-0.845562
17057.00299-2.00299
17187.419740.580257
172107.672532.32747
17377.12093-0.120931
1747.56.999610.500395
1757.57.004170.495827
1769.57.097142.40286
17766.88713-0.88713
178108.093331.90667
17977.00505-0.00505166
18036.97332-3.97332
18168.15796-2.15796
18278.50971-1.50971
183106.970663.02934
18477.24775-0.247751
1853.56.84298-3.34298
18687.68290.317097
187107.481712.51829
1885.57.27381-1.77381
18967.38743-1.38743
1906.57.09257-0.592575
1916.56.99103-0.491032
1928.57.262011.23799
19347.13446-3.13446
1949.57.572941.92706
19588.89642-0.896415
1968.56.984761.51524
1975.57.14018-1.64018
19877.7601-0.7601
19998.021240.97876
20088.04939-0.0493915
201106.770443.22956
20287.163140.836864
20367.54989-1.54989
20487.424450.575545
20556.99406-1.99406
20697.52171.4783
2074.57.02445-2.52445
2088.56.851381.64862
2099.57.129772.37023
2108.57.061931.43807
2117.57.090610.409392
2127.57.04620.453799
21356.96051-1.96051
21476.650970.349034
21586.855861.14414
2165.56.90259-1.40259
2178.56.875671.62433
2189.57.069112.43089
21977.00185-0.00184854
22087.928440.0715569
2218.56.562651.93735
2223.55.92819-2.42819
2236.56.97185-0.471852
2246.56.93769-0.437692
22510.57.158043.34196
2268.56.923781.57622
22788.04499-0.0449864
228107.197642.80236
229107.113462.88654
2309.57.546231.95377
23197.664211.33579
232107.949312.05069
2337.57.27860.221405
2344.56.97034-2.47034
2354.57.00358-2.50358
2360.57.03338-6.53338
2376.56.77801-0.27801
2384.57.11485-2.61485
2395.56.65372-1.15372
24057.22828-2.22828
24167.47043-1.47043
24246.05122-2.05122
24387.124690.875305
24410.57.509422.99058
2456.56.99075-0.490746
24687.156670.843332
2478.58.61362-0.11362
2485.56.81779-1.31779
24977.46528-0.465283
25057.10977-2.10977
2513.57.03903-3.53903
25257.34878-2.34878
25397.044221.95578
2548.56.998891.50111
25556.82577-1.82577
2569.57.841571.65843
25737.1358-4.1358
2581.56.0023-4.5023
25966.78027-0.780274
2600.56.92638-6.42638
2616.57.01452-0.514523
2627.57.044380.455622
2634.56.92632-2.42632
26487.173030.826967
26597.839391.16061
2667.57.023110.476891
2678.59.28835-0.788345
26876.484630.515366
2699.57.237172.26283
2706.57.19535-0.695354
2719.57.051792.44821
27267.03246-1.03246
27387.348740.651261
2749.57.543921.95608
27587.162190.837814
27688.72053-0.720535
27796.976942.02306
27856.96719-1.96719

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 6.66524 & 0.834759 \tabularnewline
2 & 6 & 4.41312 & 1.58688 \tabularnewline
3 & 6.5 & 6.19463 & 0.305368 \tabularnewline
4 & 1 & 4.55103 & -3.55103 \tabularnewline
5 & 1 & 4.23054 & -3.23054 \tabularnewline
6 & 5.5 & 4.35267 & 1.14733 \tabularnewline
7 & 8.5 & 4.06507 & 4.43493 \tabularnewline
8 & 6.5 & 4.21391 & 2.28609 \tabularnewline
9 & 4.5 & 4.78023 & -0.28023 \tabularnewline
10 & 2 & 4.4848 & -2.4848 \tabularnewline
11 & 5 & 4.32492 & 0.675082 \tabularnewline
12 & 0.5 & 4.57253 & -4.07253 \tabularnewline
13 & 5 & 4.38408 & 0.615916 \tabularnewline
14 & 5 & 4.44202 & 0.557983 \tabularnewline
15 & 2.5 & 4.25939 & -1.75939 \tabularnewline
16 & 5 & 3.99533 & 1.00467 \tabularnewline
17 & 5.5 & 4.25795 & 1.24205 \tabularnewline
18 & 3.5 & 4.73522 & -1.23522 \tabularnewline
19 & 3 & 4.48841 & -1.48841 \tabularnewline
20 & 4 & 3.49191 & 0.50809 \tabularnewline
21 & 0.5 & 4.52756 & -4.02756 \tabularnewline
22 & 6.5 & 4.49262 & 2.00738 \tabularnewline
23 & 4.5 & 4.54745 & -0.0474503 \tabularnewline
24 & 7.5 & 4.43595 & 3.06405 \tabularnewline
25 & 5.5 & 4.48862 & 1.01138 \tabularnewline
26 & 4 & 4.38444 & -0.384443 \tabularnewline
27 & 7.5 & 4.51441 & 2.98559 \tabularnewline
28 & 7 & 5.157 & 1.843 \tabularnewline
29 & 4 & 4.50669 & -0.506687 \tabularnewline
30 & 5.5 & 4.13844 & 1.36156 \tabularnewline
31 & 2.5 & 4.41918 & -1.91918 \tabularnewline
32 & 5.5 & 4.98338 & 0.516615 \tabularnewline
33 & 3.5 & 4.44252 & -0.94252 \tabularnewline
34 & 2.5 & 4.26308 & -1.76308 \tabularnewline
35 & 4.5 & 4.35636 & 0.143638 \tabularnewline
36 & 4.5 & 4.36445 & 0.135551 \tabularnewline
37 & 4.5 & 4.73226 & -0.232261 \tabularnewline
38 & 6 & 4.49009 & 1.50991 \tabularnewline
39 & 2.5 & 4.44575 & -1.94575 \tabularnewline
40 & 5 & 4.12955 & 0.870451 \tabularnewline
41 & 0 & 4.17903 & -4.17903 \tabularnewline
42 & 5 & 4.30064 & 0.699358 \tabularnewline
43 & 6.5 & 4.34467 & 2.15533 \tabularnewline
44 & 5 & 4.1869 & 0.8131 \tabularnewline
45 & 6 & 4.19068 & 1.80932 \tabularnewline
46 & 4.5 & 5.04917 & -0.549174 \tabularnewline
47 & 5.5 & 4.30721 & 1.19279 \tabularnewline
48 & 1 & 4.5688 & -3.5688 \tabularnewline
49 & 7.5 & 4.15918 & 3.34082 \tabularnewline
50 & 6 & 4.3908 & 1.6092 \tabularnewline
51 & 5 & 4.52383 & 0.476173 \tabularnewline
52 & 1 & 4.41911 & -3.41911 \tabularnewline
53 & 5 & 4.24425 & 0.755754 \tabularnewline
54 & 6.5 & 4.64835 & 1.85165 \tabularnewline
55 & 7 & 4.47408 & 2.52592 \tabularnewline
56 & 4.5 & 4.43139 & 0.0686131 \tabularnewline
57 & 0 & 4.0361 & -4.0361 \tabularnewline
58 & 8.5 & 4.37326 & 4.12674 \tabularnewline
59 & 3.5 & 5.50275 & -2.00275 \tabularnewline
60 & 7.5 & 4.40253 & 3.09747 \tabularnewline
61 & 3.5 & 4.46463 & -0.964628 \tabularnewline
62 & 6 & 4.64321 & 1.35679 \tabularnewline
63 & 1.5 & 3.20723 & -1.70723 \tabularnewline
64 & 9 & 4.24481 & 4.75519 \tabularnewline
65 & 3.5 & 5.16593 & -1.66593 \tabularnewline
66 & 3.5 & 4.34469 & -0.844689 \tabularnewline
67 & 4 & 4.08582 & -0.0858157 \tabularnewline
68 & 6.5 & 4.42257 & 2.07743 \tabularnewline
69 & 7.5 & 4.29143 & 3.20857 \tabularnewline
70 & 6 & 5.39217 & 0.607831 \tabularnewline
71 & 5 & 5.3537 & -0.353704 \tabularnewline
72 & 5.5 & 5.32016 & 0.179844 \tabularnewline
73 & 3.5 & 5.26313 & -1.76313 \tabularnewline
74 & 7.5 & 4.59779 & 2.90221 \tabularnewline
75 & 6.5 & 3.91729 & 2.58271 \tabularnewline
76 & 6.5 & 4.73461 & 1.76539 \tabularnewline
77 & 6.5 & 4.27432 & 2.22568 \tabularnewline
78 & 7 & 5.14493 & 1.85507 \tabularnewline
79 & 3.5 & 4.99283 & -1.49283 \tabularnewline
80 & 1.5 & 4.38673 & -2.88673 \tabularnewline
81 & 4 & 5.2125 & -1.2125 \tabularnewline
82 & 7.5 & 4.53033 & 2.96967 \tabularnewline
83 & 4.5 & 4.62016 & -0.120162 \tabularnewline
84 & 0 & 4.54645 & -4.54645 \tabularnewline
85 & 3.5 & 5.33815 & -1.83815 \tabularnewline
86 & 5.5 & 4.51701 & 0.982994 \tabularnewline
87 & 5 & 4.55022 & 0.449784 \tabularnewline
88 & 4.5 & 4.04857 & 0.451434 \tabularnewline
89 & 2.5 & 4.74939 & -2.24939 \tabularnewline
90 & 7.5 & 4.52885 & 2.97115 \tabularnewline
91 & 7 & 4.4403 & 2.5597 \tabularnewline
92 & 0 & 4.23073 & -4.23073 \tabularnewline
93 & 4.5 & 4.65696 & -0.15696 \tabularnewline
94 & 3 & 4.3659 & -1.3659 \tabularnewline
95 & 1.5 & 4.39396 & -2.89396 \tabularnewline
96 & 3.5 & 4.74556 & -1.24556 \tabularnewline
97 & 2.5 & 4.51757 & -2.01757 \tabularnewline
98 & 5.5 & 4.51096 & 0.989041 \tabularnewline
99 & 8 & 4.3344 & 3.6656 \tabularnewline
100 & 1 & 4.61543 & -3.61543 \tabularnewline
101 & 5 & 4.53187 & 0.468128 \tabularnewline
102 & 4.5 & 4.25046 & 0.249543 \tabularnewline
103 & 3 & 4.15404 & -1.15404 \tabularnewline
104 & 3 & 4.57566 & -1.57566 \tabularnewline
105 & 8 & 4.45861 & 3.54139 \tabularnewline
106 & 2.5 & 5.23559 & -2.73559 \tabularnewline
107 & 7 & 5.36037 & 1.63963 \tabularnewline
108 & 0 & 4.52292 & -4.52292 \tabularnewline
109 & 1 & 5.13679 & -4.13679 \tabularnewline
110 & 3.5 & 5.61777 & -2.11777 \tabularnewline
111 & 5.5 & 4.93708 & 0.562924 \tabularnewline
112 & 5.5 & 4.56195 & 0.938048 \tabularnewline
113 & 0.5 & 6.94012 & -6.44012 \tabularnewline
114 & 7.5 & 6.5325 & 0.967505 \tabularnewline
115 & 9 & 6.9028 & 2.0972 \tabularnewline
116 & 9.5 & 7.0299 & 2.4701 \tabularnewline
117 & 8.5 & 8.71971 & -0.219712 \tabularnewline
118 & 7 & 7.06055 & -0.0605475 \tabularnewline
119 & 8 & 6.92923 & 1.07077 \tabularnewline
120 & 10 & 8.04499 & 1.95501 \tabularnewline
121 & 7 & 7.0671 & -0.0671033 \tabularnewline
122 & 8.5 & 7.83717 & 0.662832 \tabularnewline
123 & 9 & 9.32629 & -0.326294 \tabularnewline
124 & 9.5 & 7.1767 & 2.3233 \tabularnewline
125 & 4 & 6.97326 & -2.97326 \tabularnewline
126 & 6 & 7.01588 & -1.01588 \tabularnewline
127 & 8 & 6.79205 & 1.20795 \tabularnewline
128 & 5.5 & 6.99901 & -1.49901 \tabularnewline
129 & 9.5 & 7.31672 & 2.18328 \tabularnewline
130 & 7.5 & 6.95407 & 0.545932 \tabularnewline
131 & 7 & 6.90512 & 0.0948847 \tabularnewline
132 & 7.5 & 7.27681 & 0.22319 \tabularnewline
133 & 8 & 6.96806 & 1.03194 \tabularnewline
134 & 7 & 7.11606 & -0.116056 \tabularnewline
135 & 7 & 6.74342 & 0.256575 \tabularnewline
136 & 6 & 7.14245 & -1.14245 \tabularnewline
137 & 10 & 6.89828 & 3.10172 \tabularnewline
138 & 2.5 & 7.01272 & -4.51272 \tabularnewline
139 & 9 & 7.07117 & 1.92883 \tabularnewline
140 & 8 & 7.0423 & 0.957702 \tabularnewline
141 & 6 & 6.79202 & -0.792017 \tabularnewline
142 & 8.5 & 6.92828 & 1.57172 \tabularnewline
143 & 6 & 7.18643 & -1.18643 \tabularnewline
144 & 9 & 6.99722 & 2.00278 \tabularnewline
145 & 8 & 7.54544 & 0.454557 \tabularnewline
146 & 9 & 9.22313 & -0.223126 \tabularnewline
147 & 5.5 & 7.19231 & -1.69231 \tabularnewline
148 & 7 & 8.33078 & -1.33078 \tabularnewline
149 & 5.5 & 8.42654 & -2.92654 \tabularnewline
150 & 9 & 6.93519 & 2.06481 \tabularnewline
151 & 2 & 6.28287 & -4.28287 \tabularnewline
152 & 8.5 & 7.00934 & 1.49066 \tabularnewline
153 & 9 & 7.00934 & 1.99066 \tabularnewline
154 & 8.5 & 8.39543 & 0.10457 \tabularnewline
155 & 9 & 7.22575 & 1.77425 \tabularnewline
156 & 7.5 & 7.21718 & 0.282825 \tabularnewline
157 & 10 & 7.21114 & 2.78886 \tabularnewline
158 & 9 & 7.15726 & 1.84274 \tabularnewline
159 & 7.5 & 8.64548 & -1.14548 \tabularnewline
160 & 6 & 7.81342 & -1.81342 \tabularnewline
161 & 10.5 & 7.93445 & 2.56555 \tabularnewline
162 & 8.5 & 7.14785 & 1.35215 \tabularnewline
163 & 8 & 8.5149 & -0.514897 \tabularnewline
164 & 10 & 7.06746 & 2.93254 \tabularnewline
165 & 10.5 & 9.14667 & 1.35333 \tabularnewline
166 & 6.5 & 7.02298 & -0.522983 \tabularnewline
167 & 9.5 & 6.95611 & 2.54389 \tabularnewline
168 & 8.5 & 7.09461 & 1.40539 \tabularnewline
169 & 7.5 & 8.34556 & -0.845562 \tabularnewline
170 & 5 & 7.00299 & -2.00299 \tabularnewline
171 & 8 & 7.41974 & 0.580257 \tabularnewline
172 & 10 & 7.67253 & 2.32747 \tabularnewline
173 & 7 & 7.12093 & -0.120931 \tabularnewline
174 & 7.5 & 6.99961 & 0.500395 \tabularnewline
175 & 7.5 & 7.00417 & 0.495827 \tabularnewline
176 & 9.5 & 7.09714 & 2.40286 \tabularnewline
177 & 6 & 6.88713 & -0.88713 \tabularnewline
178 & 10 & 8.09333 & 1.90667 \tabularnewline
179 & 7 & 7.00505 & -0.00505166 \tabularnewline
180 & 3 & 6.97332 & -3.97332 \tabularnewline
181 & 6 & 8.15796 & -2.15796 \tabularnewline
182 & 7 & 8.50971 & -1.50971 \tabularnewline
183 & 10 & 6.97066 & 3.02934 \tabularnewline
184 & 7 & 7.24775 & -0.247751 \tabularnewline
185 & 3.5 & 6.84298 & -3.34298 \tabularnewline
186 & 8 & 7.6829 & 0.317097 \tabularnewline
187 & 10 & 7.48171 & 2.51829 \tabularnewline
188 & 5.5 & 7.27381 & -1.77381 \tabularnewline
189 & 6 & 7.38743 & -1.38743 \tabularnewline
190 & 6.5 & 7.09257 & -0.592575 \tabularnewline
191 & 6.5 & 6.99103 & -0.491032 \tabularnewline
192 & 8.5 & 7.26201 & 1.23799 \tabularnewline
193 & 4 & 7.13446 & -3.13446 \tabularnewline
194 & 9.5 & 7.57294 & 1.92706 \tabularnewline
195 & 8 & 8.89642 & -0.896415 \tabularnewline
196 & 8.5 & 6.98476 & 1.51524 \tabularnewline
197 & 5.5 & 7.14018 & -1.64018 \tabularnewline
198 & 7 & 7.7601 & -0.7601 \tabularnewline
199 & 9 & 8.02124 & 0.97876 \tabularnewline
200 & 8 & 8.04939 & -0.0493915 \tabularnewline
201 & 10 & 6.77044 & 3.22956 \tabularnewline
202 & 8 & 7.16314 & 0.836864 \tabularnewline
203 & 6 & 7.54989 & -1.54989 \tabularnewline
204 & 8 & 7.42445 & 0.575545 \tabularnewline
205 & 5 & 6.99406 & -1.99406 \tabularnewline
206 & 9 & 7.5217 & 1.4783 \tabularnewline
207 & 4.5 & 7.02445 & -2.52445 \tabularnewline
208 & 8.5 & 6.85138 & 1.64862 \tabularnewline
209 & 9.5 & 7.12977 & 2.37023 \tabularnewline
210 & 8.5 & 7.06193 & 1.43807 \tabularnewline
211 & 7.5 & 7.09061 & 0.409392 \tabularnewline
212 & 7.5 & 7.0462 & 0.453799 \tabularnewline
213 & 5 & 6.96051 & -1.96051 \tabularnewline
214 & 7 & 6.65097 & 0.349034 \tabularnewline
215 & 8 & 6.85586 & 1.14414 \tabularnewline
216 & 5.5 & 6.90259 & -1.40259 \tabularnewline
217 & 8.5 & 6.87567 & 1.62433 \tabularnewline
218 & 9.5 & 7.06911 & 2.43089 \tabularnewline
219 & 7 & 7.00185 & -0.00184854 \tabularnewline
220 & 8 & 7.92844 & 0.0715569 \tabularnewline
221 & 8.5 & 6.56265 & 1.93735 \tabularnewline
222 & 3.5 & 5.92819 & -2.42819 \tabularnewline
223 & 6.5 & 6.97185 & -0.471852 \tabularnewline
224 & 6.5 & 6.93769 & -0.437692 \tabularnewline
225 & 10.5 & 7.15804 & 3.34196 \tabularnewline
226 & 8.5 & 6.92378 & 1.57622 \tabularnewline
227 & 8 & 8.04499 & -0.0449864 \tabularnewline
228 & 10 & 7.19764 & 2.80236 \tabularnewline
229 & 10 & 7.11346 & 2.88654 \tabularnewline
230 & 9.5 & 7.54623 & 1.95377 \tabularnewline
231 & 9 & 7.66421 & 1.33579 \tabularnewline
232 & 10 & 7.94931 & 2.05069 \tabularnewline
233 & 7.5 & 7.2786 & 0.221405 \tabularnewline
234 & 4.5 & 6.97034 & -2.47034 \tabularnewline
235 & 4.5 & 7.00358 & -2.50358 \tabularnewline
236 & 0.5 & 7.03338 & -6.53338 \tabularnewline
237 & 6.5 & 6.77801 & -0.27801 \tabularnewline
238 & 4.5 & 7.11485 & -2.61485 \tabularnewline
239 & 5.5 & 6.65372 & -1.15372 \tabularnewline
240 & 5 & 7.22828 & -2.22828 \tabularnewline
241 & 6 & 7.47043 & -1.47043 \tabularnewline
242 & 4 & 6.05122 & -2.05122 \tabularnewline
243 & 8 & 7.12469 & 0.875305 \tabularnewline
244 & 10.5 & 7.50942 & 2.99058 \tabularnewline
245 & 6.5 & 6.99075 & -0.490746 \tabularnewline
246 & 8 & 7.15667 & 0.843332 \tabularnewline
247 & 8.5 & 8.61362 & -0.11362 \tabularnewline
248 & 5.5 & 6.81779 & -1.31779 \tabularnewline
249 & 7 & 7.46528 & -0.465283 \tabularnewline
250 & 5 & 7.10977 & -2.10977 \tabularnewline
251 & 3.5 & 7.03903 & -3.53903 \tabularnewline
252 & 5 & 7.34878 & -2.34878 \tabularnewline
253 & 9 & 7.04422 & 1.95578 \tabularnewline
254 & 8.5 & 6.99889 & 1.50111 \tabularnewline
255 & 5 & 6.82577 & -1.82577 \tabularnewline
256 & 9.5 & 7.84157 & 1.65843 \tabularnewline
257 & 3 & 7.1358 & -4.1358 \tabularnewline
258 & 1.5 & 6.0023 & -4.5023 \tabularnewline
259 & 6 & 6.78027 & -0.780274 \tabularnewline
260 & 0.5 & 6.92638 & -6.42638 \tabularnewline
261 & 6.5 & 7.01452 & -0.514523 \tabularnewline
262 & 7.5 & 7.04438 & 0.455622 \tabularnewline
263 & 4.5 & 6.92632 & -2.42632 \tabularnewline
264 & 8 & 7.17303 & 0.826967 \tabularnewline
265 & 9 & 7.83939 & 1.16061 \tabularnewline
266 & 7.5 & 7.02311 & 0.476891 \tabularnewline
267 & 8.5 & 9.28835 & -0.788345 \tabularnewline
268 & 7 & 6.48463 & 0.515366 \tabularnewline
269 & 9.5 & 7.23717 & 2.26283 \tabularnewline
270 & 6.5 & 7.19535 & -0.695354 \tabularnewline
271 & 9.5 & 7.05179 & 2.44821 \tabularnewline
272 & 6 & 7.03246 & -1.03246 \tabularnewline
273 & 8 & 7.34874 & 0.651261 \tabularnewline
274 & 9.5 & 7.54392 & 1.95608 \tabularnewline
275 & 8 & 7.16219 & 0.837814 \tabularnewline
276 & 8 & 8.72053 & -0.720535 \tabularnewline
277 & 9 & 6.97694 & 2.02306 \tabularnewline
278 & 5 & 6.96719 & -1.96719 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269042&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]7.5[/C][C]6.66524[/C][C]0.834759[/C][/ROW]
[ROW][C]2[/C][C]6[/C][C]4.41312[/C][C]1.58688[/C][/ROW]
[ROW][C]3[/C][C]6.5[/C][C]6.19463[/C][C]0.305368[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]4.55103[/C][C]-3.55103[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]4.23054[/C][C]-3.23054[/C][/ROW]
[ROW][C]6[/C][C]5.5[/C][C]4.35267[/C][C]1.14733[/C][/ROW]
[ROW][C]7[/C][C]8.5[/C][C]4.06507[/C][C]4.43493[/C][/ROW]
[ROW][C]8[/C][C]6.5[/C][C]4.21391[/C][C]2.28609[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]4.78023[/C][C]-0.28023[/C][/ROW]
[ROW][C]10[/C][C]2[/C][C]4.4848[/C][C]-2.4848[/C][/ROW]
[ROW][C]11[/C][C]5[/C][C]4.32492[/C][C]0.675082[/C][/ROW]
[ROW][C]12[/C][C]0.5[/C][C]4.57253[/C][C]-4.07253[/C][/ROW]
[ROW][C]13[/C][C]5[/C][C]4.38408[/C][C]0.615916[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]4.44202[/C][C]0.557983[/C][/ROW]
[ROW][C]15[/C][C]2.5[/C][C]4.25939[/C][C]-1.75939[/C][/ROW]
[ROW][C]16[/C][C]5[/C][C]3.99533[/C][C]1.00467[/C][/ROW]
[ROW][C]17[/C][C]5.5[/C][C]4.25795[/C][C]1.24205[/C][/ROW]
[ROW][C]18[/C][C]3.5[/C][C]4.73522[/C][C]-1.23522[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]4.48841[/C][C]-1.48841[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]3.49191[/C][C]0.50809[/C][/ROW]
[ROW][C]21[/C][C]0.5[/C][C]4.52756[/C][C]-4.02756[/C][/ROW]
[ROW][C]22[/C][C]6.5[/C][C]4.49262[/C][C]2.00738[/C][/ROW]
[ROW][C]23[/C][C]4.5[/C][C]4.54745[/C][C]-0.0474503[/C][/ROW]
[ROW][C]24[/C][C]7.5[/C][C]4.43595[/C][C]3.06405[/C][/ROW]
[ROW][C]25[/C][C]5.5[/C][C]4.48862[/C][C]1.01138[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]4.38444[/C][C]-0.384443[/C][/ROW]
[ROW][C]27[/C][C]7.5[/C][C]4.51441[/C][C]2.98559[/C][/ROW]
[ROW][C]28[/C][C]7[/C][C]5.157[/C][C]1.843[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]4.50669[/C][C]-0.506687[/C][/ROW]
[ROW][C]30[/C][C]5.5[/C][C]4.13844[/C][C]1.36156[/C][/ROW]
[ROW][C]31[/C][C]2.5[/C][C]4.41918[/C][C]-1.91918[/C][/ROW]
[ROW][C]32[/C][C]5.5[/C][C]4.98338[/C][C]0.516615[/C][/ROW]
[ROW][C]33[/C][C]3.5[/C][C]4.44252[/C][C]-0.94252[/C][/ROW]
[ROW][C]34[/C][C]2.5[/C][C]4.26308[/C][C]-1.76308[/C][/ROW]
[ROW][C]35[/C][C]4.5[/C][C]4.35636[/C][C]0.143638[/C][/ROW]
[ROW][C]36[/C][C]4.5[/C][C]4.36445[/C][C]0.135551[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]4.73226[/C][C]-0.232261[/C][/ROW]
[ROW][C]38[/C][C]6[/C][C]4.49009[/C][C]1.50991[/C][/ROW]
[ROW][C]39[/C][C]2.5[/C][C]4.44575[/C][C]-1.94575[/C][/ROW]
[ROW][C]40[/C][C]5[/C][C]4.12955[/C][C]0.870451[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]4.17903[/C][C]-4.17903[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]4.30064[/C][C]0.699358[/C][/ROW]
[ROW][C]43[/C][C]6.5[/C][C]4.34467[/C][C]2.15533[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]4.1869[/C][C]0.8131[/C][/ROW]
[ROW][C]45[/C][C]6[/C][C]4.19068[/C][C]1.80932[/C][/ROW]
[ROW][C]46[/C][C]4.5[/C][C]5.04917[/C][C]-0.549174[/C][/ROW]
[ROW][C]47[/C][C]5.5[/C][C]4.30721[/C][C]1.19279[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]4.5688[/C][C]-3.5688[/C][/ROW]
[ROW][C]49[/C][C]7.5[/C][C]4.15918[/C][C]3.34082[/C][/ROW]
[ROW][C]50[/C][C]6[/C][C]4.3908[/C][C]1.6092[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]4.52383[/C][C]0.476173[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]4.41911[/C][C]-3.41911[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]4.24425[/C][C]0.755754[/C][/ROW]
[ROW][C]54[/C][C]6.5[/C][C]4.64835[/C][C]1.85165[/C][/ROW]
[ROW][C]55[/C][C]7[/C][C]4.47408[/C][C]2.52592[/C][/ROW]
[ROW][C]56[/C][C]4.5[/C][C]4.43139[/C][C]0.0686131[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]4.0361[/C][C]-4.0361[/C][/ROW]
[ROW][C]58[/C][C]8.5[/C][C]4.37326[/C][C]4.12674[/C][/ROW]
[ROW][C]59[/C][C]3.5[/C][C]5.50275[/C][C]-2.00275[/C][/ROW]
[ROW][C]60[/C][C]7.5[/C][C]4.40253[/C][C]3.09747[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]4.46463[/C][C]-0.964628[/C][/ROW]
[ROW][C]62[/C][C]6[/C][C]4.64321[/C][C]1.35679[/C][/ROW]
[ROW][C]63[/C][C]1.5[/C][C]3.20723[/C][C]-1.70723[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]4.24481[/C][C]4.75519[/C][/ROW]
[ROW][C]65[/C][C]3.5[/C][C]5.16593[/C][C]-1.66593[/C][/ROW]
[ROW][C]66[/C][C]3.5[/C][C]4.34469[/C][C]-0.844689[/C][/ROW]
[ROW][C]67[/C][C]4[/C][C]4.08582[/C][C]-0.0858157[/C][/ROW]
[ROW][C]68[/C][C]6.5[/C][C]4.42257[/C][C]2.07743[/C][/ROW]
[ROW][C]69[/C][C]7.5[/C][C]4.29143[/C][C]3.20857[/C][/ROW]
[ROW][C]70[/C][C]6[/C][C]5.39217[/C][C]0.607831[/C][/ROW]
[ROW][C]71[/C][C]5[/C][C]5.3537[/C][C]-0.353704[/C][/ROW]
[ROW][C]72[/C][C]5.5[/C][C]5.32016[/C][C]0.179844[/C][/ROW]
[ROW][C]73[/C][C]3.5[/C][C]5.26313[/C][C]-1.76313[/C][/ROW]
[ROW][C]74[/C][C]7.5[/C][C]4.59779[/C][C]2.90221[/C][/ROW]
[ROW][C]75[/C][C]6.5[/C][C]3.91729[/C][C]2.58271[/C][/ROW]
[ROW][C]76[/C][C]6.5[/C][C]4.73461[/C][C]1.76539[/C][/ROW]
[ROW][C]77[/C][C]6.5[/C][C]4.27432[/C][C]2.22568[/C][/ROW]
[ROW][C]78[/C][C]7[/C][C]5.14493[/C][C]1.85507[/C][/ROW]
[ROW][C]79[/C][C]3.5[/C][C]4.99283[/C][C]-1.49283[/C][/ROW]
[ROW][C]80[/C][C]1.5[/C][C]4.38673[/C][C]-2.88673[/C][/ROW]
[ROW][C]81[/C][C]4[/C][C]5.2125[/C][C]-1.2125[/C][/ROW]
[ROW][C]82[/C][C]7.5[/C][C]4.53033[/C][C]2.96967[/C][/ROW]
[ROW][C]83[/C][C]4.5[/C][C]4.62016[/C][C]-0.120162[/C][/ROW]
[ROW][C]84[/C][C]0[/C][C]4.54645[/C][C]-4.54645[/C][/ROW]
[ROW][C]85[/C][C]3.5[/C][C]5.33815[/C][C]-1.83815[/C][/ROW]
[ROW][C]86[/C][C]5.5[/C][C]4.51701[/C][C]0.982994[/C][/ROW]
[ROW][C]87[/C][C]5[/C][C]4.55022[/C][C]0.449784[/C][/ROW]
[ROW][C]88[/C][C]4.5[/C][C]4.04857[/C][C]0.451434[/C][/ROW]
[ROW][C]89[/C][C]2.5[/C][C]4.74939[/C][C]-2.24939[/C][/ROW]
[ROW][C]90[/C][C]7.5[/C][C]4.52885[/C][C]2.97115[/C][/ROW]
[ROW][C]91[/C][C]7[/C][C]4.4403[/C][C]2.5597[/C][/ROW]
[ROW][C]92[/C][C]0[/C][C]4.23073[/C][C]-4.23073[/C][/ROW]
[ROW][C]93[/C][C]4.5[/C][C]4.65696[/C][C]-0.15696[/C][/ROW]
[ROW][C]94[/C][C]3[/C][C]4.3659[/C][C]-1.3659[/C][/ROW]
[ROW][C]95[/C][C]1.5[/C][C]4.39396[/C][C]-2.89396[/C][/ROW]
[ROW][C]96[/C][C]3.5[/C][C]4.74556[/C][C]-1.24556[/C][/ROW]
[ROW][C]97[/C][C]2.5[/C][C]4.51757[/C][C]-2.01757[/C][/ROW]
[ROW][C]98[/C][C]5.5[/C][C]4.51096[/C][C]0.989041[/C][/ROW]
[ROW][C]99[/C][C]8[/C][C]4.3344[/C][C]3.6656[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]4.61543[/C][C]-3.61543[/C][/ROW]
[ROW][C]101[/C][C]5[/C][C]4.53187[/C][C]0.468128[/C][/ROW]
[ROW][C]102[/C][C]4.5[/C][C]4.25046[/C][C]0.249543[/C][/ROW]
[ROW][C]103[/C][C]3[/C][C]4.15404[/C][C]-1.15404[/C][/ROW]
[ROW][C]104[/C][C]3[/C][C]4.57566[/C][C]-1.57566[/C][/ROW]
[ROW][C]105[/C][C]8[/C][C]4.45861[/C][C]3.54139[/C][/ROW]
[ROW][C]106[/C][C]2.5[/C][C]5.23559[/C][C]-2.73559[/C][/ROW]
[ROW][C]107[/C][C]7[/C][C]5.36037[/C][C]1.63963[/C][/ROW]
[ROW][C]108[/C][C]0[/C][C]4.52292[/C][C]-4.52292[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]5.13679[/C][C]-4.13679[/C][/ROW]
[ROW][C]110[/C][C]3.5[/C][C]5.61777[/C][C]-2.11777[/C][/ROW]
[ROW][C]111[/C][C]5.5[/C][C]4.93708[/C][C]0.562924[/C][/ROW]
[ROW][C]112[/C][C]5.5[/C][C]4.56195[/C][C]0.938048[/C][/ROW]
[ROW][C]113[/C][C]0.5[/C][C]6.94012[/C][C]-6.44012[/C][/ROW]
[ROW][C]114[/C][C]7.5[/C][C]6.5325[/C][C]0.967505[/C][/ROW]
[ROW][C]115[/C][C]9[/C][C]6.9028[/C][C]2.0972[/C][/ROW]
[ROW][C]116[/C][C]9.5[/C][C]7.0299[/C][C]2.4701[/C][/ROW]
[ROW][C]117[/C][C]8.5[/C][C]8.71971[/C][C]-0.219712[/C][/ROW]
[ROW][C]118[/C][C]7[/C][C]7.06055[/C][C]-0.0605475[/C][/ROW]
[ROW][C]119[/C][C]8[/C][C]6.92923[/C][C]1.07077[/C][/ROW]
[ROW][C]120[/C][C]10[/C][C]8.04499[/C][C]1.95501[/C][/ROW]
[ROW][C]121[/C][C]7[/C][C]7.0671[/C][C]-0.0671033[/C][/ROW]
[ROW][C]122[/C][C]8.5[/C][C]7.83717[/C][C]0.662832[/C][/ROW]
[ROW][C]123[/C][C]9[/C][C]9.32629[/C][C]-0.326294[/C][/ROW]
[ROW][C]124[/C][C]9.5[/C][C]7.1767[/C][C]2.3233[/C][/ROW]
[ROW][C]125[/C][C]4[/C][C]6.97326[/C][C]-2.97326[/C][/ROW]
[ROW][C]126[/C][C]6[/C][C]7.01588[/C][C]-1.01588[/C][/ROW]
[ROW][C]127[/C][C]8[/C][C]6.79205[/C][C]1.20795[/C][/ROW]
[ROW][C]128[/C][C]5.5[/C][C]6.99901[/C][C]-1.49901[/C][/ROW]
[ROW][C]129[/C][C]9.5[/C][C]7.31672[/C][C]2.18328[/C][/ROW]
[ROW][C]130[/C][C]7.5[/C][C]6.95407[/C][C]0.545932[/C][/ROW]
[ROW][C]131[/C][C]7[/C][C]6.90512[/C][C]0.0948847[/C][/ROW]
[ROW][C]132[/C][C]7.5[/C][C]7.27681[/C][C]0.22319[/C][/ROW]
[ROW][C]133[/C][C]8[/C][C]6.96806[/C][C]1.03194[/C][/ROW]
[ROW][C]134[/C][C]7[/C][C]7.11606[/C][C]-0.116056[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]6.74342[/C][C]0.256575[/C][/ROW]
[ROW][C]136[/C][C]6[/C][C]7.14245[/C][C]-1.14245[/C][/ROW]
[ROW][C]137[/C][C]10[/C][C]6.89828[/C][C]3.10172[/C][/ROW]
[ROW][C]138[/C][C]2.5[/C][C]7.01272[/C][C]-4.51272[/C][/ROW]
[ROW][C]139[/C][C]9[/C][C]7.07117[/C][C]1.92883[/C][/ROW]
[ROW][C]140[/C][C]8[/C][C]7.0423[/C][C]0.957702[/C][/ROW]
[ROW][C]141[/C][C]6[/C][C]6.79202[/C][C]-0.792017[/C][/ROW]
[ROW][C]142[/C][C]8.5[/C][C]6.92828[/C][C]1.57172[/C][/ROW]
[ROW][C]143[/C][C]6[/C][C]7.18643[/C][C]-1.18643[/C][/ROW]
[ROW][C]144[/C][C]9[/C][C]6.99722[/C][C]2.00278[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]7.54544[/C][C]0.454557[/C][/ROW]
[ROW][C]146[/C][C]9[/C][C]9.22313[/C][C]-0.223126[/C][/ROW]
[ROW][C]147[/C][C]5.5[/C][C]7.19231[/C][C]-1.69231[/C][/ROW]
[ROW][C]148[/C][C]7[/C][C]8.33078[/C][C]-1.33078[/C][/ROW]
[ROW][C]149[/C][C]5.5[/C][C]8.42654[/C][C]-2.92654[/C][/ROW]
[ROW][C]150[/C][C]9[/C][C]6.93519[/C][C]2.06481[/C][/ROW]
[ROW][C]151[/C][C]2[/C][C]6.28287[/C][C]-4.28287[/C][/ROW]
[ROW][C]152[/C][C]8.5[/C][C]7.00934[/C][C]1.49066[/C][/ROW]
[ROW][C]153[/C][C]9[/C][C]7.00934[/C][C]1.99066[/C][/ROW]
[ROW][C]154[/C][C]8.5[/C][C]8.39543[/C][C]0.10457[/C][/ROW]
[ROW][C]155[/C][C]9[/C][C]7.22575[/C][C]1.77425[/C][/ROW]
[ROW][C]156[/C][C]7.5[/C][C]7.21718[/C][C]0.282825[/C][/ROW]
[ROW][C]157[/C][C]10[/C][C]7.21114[/C][C]2.78886[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]7.15726[/C][C]1.84274[/C][/ROW]
[ROW][C]159[/C][C]7.5[/C][C]8.64548[/C][C]-1.14548[/C][/ROW]
[ROW][C]160[/C][C]6[/C][C]7.81342[/C][C]-1.81342[/C][/ROW]
[ROW][C]161[/C][C]10.5[/C][C]7.93445[/C][C]2.56555[/C][/ROW]
[ROW][C]162[/C][C]8.5[/C][C]7.14785[/C][C]1.35215[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]8.5149[/C][C]-0.514897[/C][/ROW]
[ROW][C]164[/C][C]10[/C][C]7.06746[/C][C]2.93254[/C][/ROW]
[ROW][C]165[/C][C]10.5[/C][C]9.14667[/C][C]1.35333[/C][/ROW]
[ROW][C]166[/C][C]6.5[/C][C]7.02298[/C][C]-0.522983[/C][/ROW]
[ROW][C]167[/C][C]9.5[/C][C]6.95611[/C][C]2.54389[/C][/ROW]
[ROW][C]168[/C][C]8.5[/C][C]7.09461[/C][C]1.40539[/C][/ROW]
[ROW][C]169[/C][C]7.5[/C][C]8.34556[/C][C]-0.845562[/C][/ROW]
[ROW][C]170[/C][C]5[/C][C]7.00299[/C][C]-2.00299[/C][/ROW]
[ROW][C]171[/C][C]8[/C][C]7.41974[/C][C]0.580257[/C][/ROW]
[ROW][C]172[/C][C]10[/C][C]7.67253[/C][C]2.32747[/C][/ROW]
[ROW][C]173[/C][C]7[/C][C]7.12093[/C][C]-0.120931[/C][/ROW]
[ROW][C]174[/C][C]7.5[/C][C]6.99961[/C][C]0.500395[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]7.00417[/C][C]0.495827[/C][/ROW]
[ROW][C]176[/C][C]9.5[/C][C]7.09714[/C][C]2.40286[/C][/ROW]
[ROW][C]177[/C][C]6[/C][C]6.88713[/C][C]-0.88713[/C][/ROW]
[ROW][C]178[/C][C]10[/C][C]8.09333[/C][C]1.90667[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]7.00505[/C][C]-0.00505166[/C][/ROW]
[ROW][C]180[/C][C]3[/C][C]6.97332[/C][C]-3.97332[/C][/ROW]
[ROW][C]181[/C][C]6[/C][C]8.15796[/C][C]-2.15796[/C][/ROW]
[ROW][C]182[/C][C]7[/C][C]8.50971[/C][C]-1.50971[/C][/ROW]
[ROW][C]183[/C][C]10[/C][C]6.97066[/C][C]3.02934[/C][/ROW]
[ROW][C]184[/C][C]7[/C][C]7.24775[/C][C]-0.247751[/C][/ROW]
[ROW][C]185[/C][C]3.5[/C][C]6.84298[/C][C]-3.34298[/C][/ROW]
[ROW][C]186[/C][C]8[/C][C]7.6829[/C][C]0.317097[/C][/ROW]
[ROW][C]187[/C][C]10[/C][C]7.48171[/C][C]2.51829[/C][/ROW]
[ROW][C]188[/C][C]5.5[/C][C]7.27381[/C][C]-1.77381[/C][/ROW]
[ROW][C]189[/C][C]6[/C][C]7.38743[/C][C]-1.38743[/C][/ROW]
[ROW][C]190[/C][C]6.5[/C][C]7.09257[/C][C]-0.592575[/C][/ROW]
[ROW][C]191[/C][C]6.5[/C][C]6.99103[/C][C]-0.491032[/C][/ROW]
[ROW][C]192[/C][C]8.5[/C][C]7.26201[/C][C]1.23799[/C][/ROW]
[ROW][C]193[/C][C]4[/C][C]7.13446[/C][C]-3.13446[/C][/ROW]
[ROW][C]194[/C][C]9.5[/C][C]7.57294[/C][C]1.92706[/C][/ROW]
[ROW][C]195[/C][C]8[/C][C]8.89642[/C][C]-0.896415[/C][/ROW]
[ROW][C]196[/C][C]8.5[/C][C]6.98476[/C][C]1.51524[/C][/ROW]
[ROW][C]197[/C][C]5.5[/C][C]7.14018[/C][C]-1.64018[/C][/ROW]
[ROW][C]198[/C][C]7[/C][C]7.7601[/C][C]-0.7601[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]8.02124[/C][C]0.97876[/C][/ROW]
[ROW][C]200[/C][C]8[/C][C]8.04939[/C][C]-0.0493915[/C][/ROW]
[ROW][C]201[/C][C]10[/C][C]6.77044[/C][C]3.22956[/C][/ROW]
[ROW][C]202[/C][C]8[/C][C]7.16314[/C][C]0.836864[/C][/ROW]
[ROW][C]203[/C][C]6[/C][C]7.54989[/C][C]-1.54989[/C][/ROW]
[ROW][C]204[/C][C]8[/C][C]7.42445[/C][C]0.575545[/C][/ROW]
[ROW][C]205[/C][C]5[/C][C]6.99406[/C][C]-1.99406[/C][/ROW]
[ROW][C]206[/C][C]9[/C][C]7.5217[/C][C]1.4783[/C][/ROW]
[ROW][C]207[/C][C]4.5[/C][C]7.02445[/C][C]-2.52445[/C][/ROW]
[ROW][C]208[/C][C]8.5[/C][C]6.85138[/C][C]1.64862[/C][/ROW]
[ROW][C]209[/C][C]9.5[/C][C]7.12977[/C][C]2.37023[/C][/ROW]
[ROW][C]210[/C][C]8.5[/C][C]7.06193[/C][C]1.43807[/C][/ROW]
[ROW][C]211[/C][C]7.5[/C][C]7.09061[/C][C]0.409392[/C][/ROW]
[ROW][C]212[/C][C]7.5[/C][C]7.0462[/C][C]0.453799[/C][/ROW]
[ROW][C]213[/C][C]5[/C][C]6.96051[/C][C]-1.96051[/C][/ROW]
[ROW][C]214[/C][C]7[/C][C]6.65097[/C][C]0.349034[/C][/ROW]
[ROW][C]215[/C][C]8[/C][C]6.85586[/C][C]1.14414[/C][/ROW]
[ROW][C]216[/C][C]5.5[/C][C]6.90259[/C][C]-1.40259[/C][/ROW]
[ROW][C]217[/C][C]8.5[/C][C]6.87567[/C][C]1.62433[/C][/ROW]
[ROW][C]218[/C][C]9.5[/C][C]7.06911[/C][C]2.43089[/C][/ROW]
[ROW][C]219[/C][C]7[/C][C]7.00185[/C][C]-0.00184854[/C][/ROW]
[ROW][C]220[/C][C]8[/C][C]7.92844[/C][C]0.0715569[/C][/ROW]
[ROW][C]221[/C][C]8.5[/C][C]6.56265[/C][C]1.93735[/C][/ROW]
[ROW][C]222[/C][C]3.5[/C][C]5.92819[/C][C]-2.42819[/C][/ROW]
[ROW][C]223[/C][C]6.5[/C][C]6.97185[/C][C]-0.471852[/C][/ROW]
[ROW][C]224[/C][C]6.5[/C][C]6.93769[/C][C]-0.437692[/C][/ROW]
[ROW][C]225[/C][C]10.5[/C][C]7.15804[/C][C]3.34196[/C][/ROW]
[ROW][C]226[/C][C]8.5[/C][C]6.92378[/C][C]1.57622[/C][/ROW]
[ROW][C]227[/C][C]8[/C][C]8.04499[/C][C]-0.0449864[/C][/ROW]
[ROW][C]228[/C][C]10[/C][C]7.19764[/C][C]2.80236[/C][/ROW]
[ROW][C]229[/C][C]10[/C][C]7.11346[/C][C]2.88654[/C][/ROW]
[ROW][C]230[/C][C]9.5[/C][C]7.54623[/C][C]1.95377[/C][/ROW]
[ROW][C]231[/C][C]9[/C][C]7.66421[/C][C]1.33579[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]7.94931[/C][C]2.05069[/C][/ROW]
[ROW][C]233[/C][C]7.5[/C][C]7.2786[/C][C]0.221405[/C][/ROW]
[ROW][C]234[/C][C]4.5[/C][C]6.97034[/C][C]-2.47034[/C][/ROW]
[ROW][C]235[/C][C]4.5[/C][C]7.00358[/C][C]-2.50358[/C][/ROW]
[ROW][C]236[/C][C]0.5[/C][C]7.03338[/C][C]-6.53338[/C][/ROW]
[ROW][C]237[/C][C]6.5[/C][C]6.77801[/C][C]-0.27801[/C][/ROW]
[ROW][C]238[/C][C]4.5[/C][C]7.11485[/C][C]-2.61485[/C][/ROW]
[ROW][C]239[/C][C]5.5[/C][C]6.65372[/C][C]-1.15372[/C][/ROW]
[ROW][C]240[/C][C]5[/C][C]7.22828[/C][C]-2.22828[/C][/ROW]
[ROW][C]241[/C][C]6[/C][C]7.47043[/C][C]-1.47043[/C][/ROW]
[ROW][C]242[/C][C]4[/C][C]6.05122[/C][C]-2.05122[/C][/ROW]
[ROW][C]243[/C][C]8[/C][C]7.12469[/C][C]0.875305[/C][/ROW]
[ROW][C]244[/C][C]10.5[/C][C]7.50942[/C][C]2.99058[/C][/ROW]
[ROW][C]245[/C][C]6.5[/C][C]6.99075[/C][C]-0.490746[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]7.15667[/C][C]0.843332[/C][/ROW]
[ROW][C]247[/C][C]8.5[/C][C]8.61362[/C][C]-0.11362[/C][/ROW]
[ROW][C]248[/C][C]5.5[/C][C]6.81779[/C][C]-1.31779[/C][/ROW]
[ROW][C]249[/C][C]7[/C][C]7.46528[/C][C]-0.465283[/C][/ROW]
[ROW][C]250[/C][C]5[/C][C]7.10977[/C][C]-2.10977[/C][/ROW]
[ROW][C]251[/C][C]3.5[/C][C]7.03903[/C][C]-3.53903[/C][/ROW]
[ROW][C]252[/C][C]5[/C][C]7.34878[/C][C]-2.34878[/C][/ROW]
[ROW][C]253[/C][C]9[/C][C]7.04422[/C][C]1.95578[/C][/ROW]
[ROW][C]254[/C][C]8.5[/C][C]6.99889[/C][C]1.50111[/C][/ROW]
[ROW][C]255[/C][C]5[/C][C]6.82577[/C][C]-1.82577[/C][/ROW]
[ROW][C]256[/C][C]9.5[/C][C]7.84157[/C][C]1.65843[/C][/ROW]
[ROW][C]257[/C][C]3[/C][C]7.1358[/C][C]-4.1358[/C][/ROW]
[ROW][C]258[/C][C]1.5[/C][C]6.0023[/C][C]-4.5023[/C][/ROW]
[ROW][C]259[/C][C]6[/C][C]6.78027[/C][C]-0.780274[/C][/ROW]
[ROW][C]260[/C][C]0.5[/C][C]6.92638[/C][C]-6.42638[/C][/ROW]
[ROW][C]261[/C][C]6.5[/C][C]7.01452[/C][C]-0.514523[/C][/ROW]
[ROW][C]262[/C][C]7.5[/C][C]7.04438[/C][C]0.455622[/C][/ROW]
[ROW][C]263[/C][C]4.5[/C][C]6.92632[/C][C]-2.42632[/C][/ROW]
[ROW][C]264[/C][C]8[/C][C]7.17303[/C][C]0.826967[/C][/ROW]
[ROW][C]265[/C][C]9[/C][C]7.83939[/C][C]1.16061[/C][/ROW]
[ROW][C]266[/C][C]7.5[/C][C]7.02311[/C][C]0.476891[/C][/ROW]
[ROW][C]267[/C][C]8.5[/C][C]9.28835[/C][C]-0.788345[/C][/ROW]
[ROW][C]268[/C][C]7[/C][C]6.48463[/C][C]0.515366[/C][/ROW]
[ROW][C]269[/C][C]9.5[/C][C]7.23717[/C][C]2.26283[/C][/ROW]
[ROW][C]270[/C][C]6.5[/C][C]7.19535[/C][C]-0.695354[/C][/ROW]
[ROW][C]271[/C][C]9.5[/C][C]7.05179[/C][C]2.44821[/C][/ROW]
[ROW][C]272[/C][C]6[/C][C]7.03246[/C][C]-1.03246[/C][/ROW]
[ROW][C]273[/C][C]8[/C][C]7.34874[/C][C]0.651261[/C][/ROW]
[ROW][C]274[/C][C]9.5[/C][C]7.54392[/C][C]1.95608[/C][/ROW]
[ROW][C]275[/C][C]8[/C][C]7.16219[/C][C]0.837814[/C][/ROW]
[ROW][C]276[/C][C]8[/C][C]8.72053[/C][C]-0.720535[/C][/ROW]
[ROW][C]277[/C][C]9[/C][C]6.97694[/C][C]2.02306[/C][/ROW]
[ROW][C]278[/C][C]5[/C][C]6.96719[/C][C]-1.96719[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269042&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269042&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.56.665240.834759
264.413121.58688
36.56.194630.305368
414.55103-3.55103
514.23054-3.23054
65.54.352671.14733
78.54.065074.43493
86.54.213912.28609
94.54.78023-0.28023
1024.4848-2.4848
1154.324920.675082
120.54.57253-4.07253
1354.384080.615916
1454.442020.557983
152.54.25939-1.75939
1653.995331.00467
175.54.257951.24205
183.54.73522-1.23522
1934.48841-1.48841
2043.491910.50809
210.54.52756-4.02756
226.54.492622.00738
234.54.54745-0.0474503
247.54.435953.06405
255.54.488621.01138
2644.38444-0.384443
277.54.514412.98559
2875.1571.843
2944.50669-0.506687
305.54.138441.36156
312.54.41918-1.91918
325.54.983380.516615
333.54.44252-0.94252
342.54.26308-1.76308
354.54.356360.143638
364.54.364450.135551
374.54.73226-0.232261
3864.490091.50991
392.54.44575-1.94575
4054.129550.870451
4104.17903-4.17903
4254.300640.699358
436.54.344672.15533
4454.18690.8131
4564.190681.80932
464.55.04917-0.549174
475.54.307211.19279
4814.5688-3.5688
497.54.159183.34082
5064.39081.6092
5154.523830.476173
5214.41911-3.41911
5354.244250.755754
546.54.648351.85165
5574.474082.52592
564.54.431390.0686131
5704.0361-4.0361
588.54.373264.12674
593.55.50275-2.00275
607.54.402533.09747
613.54.46463-0.964628
6264.643211.35679
631.53.20723-1.70723
6494.244814.75519
653.55.16593-1.66593
663.54.34469-0.844689
6744.08582-0.0858157
686.54.422572.07743
697.54.291433.20857
7065.392170.607831
7155.3537-0.353704
725.55.320160.179844
733.55.26313-1.76313
747.54.597792.90221
756.53.917292.58271
766.54.734611.76539
776.54.274322.22568
7875.144931.85507
793.54.99283-1.49283
801.54.38673-2.88673
8145.2125-1.2125
827.54.530332.96967
834.54.62016-0.120162
8404.54645-4.54645
853.55.33815-1.83815
865.54.517010.982994
8754.550220.449784
884.54.048570.451434
892.54.74939-2.24939
907.54.528852.97115
9174.44032.5597
9204.23073-4.23073
934.54.65696-0.15696
9434.3659-1.3659
951.54.39396-2.89396
963.54.74556-1.24556
972.54.51757-2.01757
985.54.510960.989041
9984.33443.6656
10014.61543-3.61543
10154.531870.468128
1024.54.250460.249543
10334.15404-1.15404
10434.57566-1.57566
10584.458613.54139
1062.55.23559-2.73559
10775.360371.63963
10804.52292-4.52292
10915.13679-4.13679
1103.55.61777-2.11777
1115.54.937080.562924
1125.54.561950.938048
1130.56.94012-6.44012
1147.56.53250.967505
11596.90282.0972
1169.57.02992.4701
1178.58.71971-0.219712
11877.06055-0.0605475
11986.929231.07077
120108.044991.95501
12177.0671-0.0671033
1228.57.837170.662832
12399.32629-0.326294
1249.57.17672.3233
12546.97326-2.97326
12667.01588-1.01588
12786.792051.20795
1285.56.99901-1.49901
1299.57.316722.18328
1307.56.954070.545932
13176.905120.0948847
1327.57.276810.22319
13386.968061.03194
13477.11606-0.116056
13576.743420.256575
13667.14245-1.14245
137106.898283.10172
1382.57.01272-4.51272
13997.071171.92883
14087.04230.957702
14166.79202-0.792017
1428.56.928281.57172
14367.18643-1.18643
14496.997222.00278
14587.545440.454557
14699.22313-0.223126
1475.57.19231-1.69231
14878.33078-1.33078
1495.58.42654-2.92654
15096.935192.06481
15126.28287-4.28287
1528.57.009341.49066
15397.009341.99066
1548.58.395430.10457
15597.225751.77425
1567.57.217180.282825
157107.211142.78886
15897.157261.84274
1597.58.64548-1.14548
16067.81342-1.81342
16110.57.934452.56555
1628.57.147851.35215
16388.5149-0.514897
164107.067462.93254
16510.59.146671.35333
1666.57.02298-0.522983
1679.56.956112.54389
1688.57.094611.40539
1697.58.34556-0.845562
17057.00299-2.00299
17187.419740.580257
172107.672532.32747
17377.12093-0.120931
1747.56.999610.500395
1757.57.004170.495827
1769.57.097142.40286
17766.88713-0.88713
178108.093331.90667
17977.00505-0.00505166
18036.97332-3.97332
18168.15796-2.15796
18278.50971-1.50971
183106.970663.02934
18477.24775-0.247751
1853.56.84298-3.34298
18687.68290.317097
187107.481712.51829
1885.57.27381-1.77381
18967.38743-1.38743
1906.57.09257-0.592575
1916.56.99103-0.491032
1928.57.262011.23799
19347.13446-3.13446
1949.57.572941.92706
19588.89642-0.896415
1968.56.984761.51524
1975.57.14018-1.64018
19877.7601-0.7601
19998.021240.97876
20088.04939-0.0493915
201106.770443.22956
20287.163140.836864
20367.54989-1.54989
20487.424450.575545
20556.99406-1.99406
20697.52171.4783
2074.57.02445-2.52445
2088.56.851381.64862
2099.57.129772.37023
2108.57.061931.43807
2117.57.090610.409392
2127.57.04620.453799
21356.96051-1.96051
21476.650970.349034
21586.855861.14414
2165.56.90259-1.40259
2178.56.875671.62433
2189.57.069112.43089
21977.00185-0.00184854
22087.928440.0715569
2218.56.562651.93735
2223.55.92819-2.42819
2236.56.97185-0.471852
2246.56.93769-0.437692
22510.57.158043.34196
2268.56.923781.57622
22788.04499-0.0449864
228107.197642.80236
229107.113462.88654
2309.57.546231.95377
23197.664211.33579
232107.949312.05069
2337.57.27860.221405
2344.56.97034-2.47034
2354.57.00358-2.50358
2360.57.03338-6.53338
2376.56.77801-0.27801
2384.57.11485-2.61485
2395.56.65372-1.15372
24057.22828-2.22828
24167.47043-1.47043
24246.05122-2.05122
24387.124690.875305
24410.57.509422.99058
2456.56.99075-0.490746
24687.156670.843332
2478.58.61362-0.11362
2485.56.81779-1.31779
24977.46528-0.465283
25057.10977-2.10977
2513.57.03903-3.53903
25257.34878-2.34878
25397.044221.95578
2548.56.998891.50111
25556.82577-1.82577
2569.57.841571.65843
25737.1358-4.1358
2581.56.0023-4.5023
25966.78027-0.780274
2600.56.92638-6.42638
2616.57.01452-0.514523
2627.57.044380.455622
2634.56.92632-2.42632
26487.173030.826967
26597.839391.16061
2667.57.023110.476891
2678.59.28835-0.788345
26876.484630.515366
2699.57.237172.26283
2706.57.19535-0.695354
2719.57.051792.44821
27267.03246-1.03246
27387.348740.651261
2749.57.543921.95608
27587.162190.837814
27688.72053-0.720535
27796.976942.02306
27856.96719-1.96719






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.8634970.2730060.136503
140.7626190.4747620.237381
150.6488450.7023090.351155
160.5253820.9492350.474618
170.5150560.9698870.484944
180.4273060.8546120.572694
190.3389520.6779040.661048
200.2641220.5282440.735878
210.3251480.6502970.674852
220.2946970.5893940.705303
230.2242810.4485610.775719
240.4194260.8388530.580574
250.3442690.6885380.655731
260.2757420.5514850.724258
270.3427110.6854210.657289
280.302620.6052410.69738
290.2524330.5048670.747567
300.2131670.4263340.786833
310.4425270.8850540.557473
320.3990280.7980560.600972
330.3776010.7552010.622399
340.3806050.7612110.619395
350.3376980.6753960.662302
360.2925850.585170.707415
370.2437650.487530.756235
380.2017770.4035530.798223
390.1838180.3676370.816182
400.1525620.3051240.847438
410.1921530.3843070.807847
420.1950420.3900840.804958
430.2274470.4548950.772553
440.1897840.3795670.810216
450.1598260.3196520.840174
460.1305990.2611980.869401
470.1133620.2267230.886638
480.1456160.2912330.854384
490.1938410.3876810.806159
500.1967050.3934110.803295
510.16530.3306010.8347
520.2822850.564570.717715
530.2573030.5146060.742697
540.2784790.5569570.721521
550.3603980.7207960.639602
560.3186480.6372960.681352
570.4430460.8860920.556954
580.4700690.9401380.529931
590.4529230.9058470.547077
600.5434220.9131570.456578
610.5010680.9978630.498932
620.4710720.9421440.528928
630.4531120.9062240.546888
640.6150210.7699580.384979
650.6160920.7678160.383908
660.6075970.7848060.392403
670.5700870.8598260.429913
680.5937210.8125580.406279
690.6286580.7426840.371342
700.6001630.7996730.399837
710.5628080.8743840.437192
720.5229550.9540890.477045
730.5058130.9883740.494187
740.6086070.7827850.391393
750.6342560.7314880.365744
760.6296160.7407690.370384
770.6270660.7458680.372934
780.6189840.7620320.381016
790.5961980.8076040.403802
800.6281210.7437570.371879
810.6021970.7956060.397803
820.6358340.7283310.364166
830.6005150.7989690.399485
840.7218410.5563180.278159
850.6993610.6012780.300639
860.6744630.6510740.325537
870.6467680.7064630.353232
880.6150550.769890.384945
890.6118420.7763150.388158
900.6506940.6986120.349306
910.6649720.6700570.335028
920.8113560.3772870.188644
930.7855380.4289250.214462
940.7597570.4804850.240243
950.7740280.4519430.225972
960.7567710.4864570.243229
970.7486830.5026340.251317
980.7274420.5451150.272558
990.7981120.4037770.201888
1000.8231950.3536110.176805
1010.8034510.3930980.196549
1020.7820820.4358360.217918
1030.7684610.4630780.231539
1040.7450120.5099770.254988
1050.8235120.3529760.176488
1060.8203030.3593950.179697
1070.8332040.3335930.166796
1080.8813230.2373540.118677
1090.9126740.1746530.0873263
1100.9105510.1788990.0894494
1110.8964530.2070940.103547
1120.8846780.2306440.115322
1130.9315110.1369770.0684886
1140.948280.1034410.0517203
1150.9612750.07744950.0387248
1160.9694990.06100280.0305014
1170.9641350.0717310.0358655
1180.9566430.08671420.0433571
1190.9520290.09594220.0479711
1200.951450.09710030.0485501
1210.9419890.1160230.0580114
1220.932230.1355410.0677705
1230.920160.1596790.0798397
1240.9216390.1567220.0783608
1250.9329860.1340280.0670142
1260.9235270.1529470.0764733
1270.9177530.1644930.0822465
1280.909210.1815810.0907904
1290.9130650.1738690.0869347
1300.8999140.2001710.100086
1310.8847110.2305770.115289
1320.86730.2653990.1327
1330.8553280.2893440.144672
1340.8344070.3311860.165593
1350.8174180.3651650.182582
1360.8005980.3988040.199402
1370.8398010.3203970.160199
1380.900660.1986810.0993404
1390.9004480.1991030.0995516
1400.8880080.2239840.111992
1410.8764410.2471180.123559
1420.8761480.2477040.123852
1430.8652710.2694570.134729
1440.8722340.2555330.127766
1450.8549190.2901610.145081
1460.8342360.3315270.165764
1470.8400780.3198440.159922
1480.8257520.3484950.174248
1490.8447560.3104880.155244
1500.8484970.3030050.151503
1510.9006650.198670.099335
1520.8949830.2100340.105017
1530.8967130.2065750.103287
1540.8805540.2388930.119446
1550.8749370.2501270.125063
1560.8592030.2815950.140797
1570.8659530.2680940.134047
1580.8644540.2710910.135546
1590.851540.2969190.14846
1600.8530850.2938290.146915
1610.8606040.2787910.139396
1620.8484610.3030790.151539
1630.8280630.3438740.171937
1640.8523590.2952810.147641
1650.8389910.3220180.161009
1660.8182950.3634090.181705
1670.8247330.3505340.175267
1680.8129940.3740120.187006
1690.7943760.4112480.205624
1700.7949460.4101080.205054
1710.7701530.4596950.229847
1720.7708050.458390.229195
1730.7424380.5151230.257562
1740.7163260.5673480.283674
1750.689860.620280.31014
1760.7083220.5833550.291678
1770.6799320.6401360.320068
1780.6737140.6525730.326286
1790.6426290.7147420.357371
1800.7213310.5573380.278669
1810.7384370.5231250.261563
1820.7400460.5199080.259954
1830.8160640.3678720.183936
1840.7916290.4167420.208371
1850.817050.3659010.18295
1860.7927090.4145810.207291
1870.7957170.4085660.204283
1880.7970210.4059570.202979
1890.7932620.4134760.206738
1900.766360.4672810.23364
1910.7372950.5254090.262705
1920.7116430.5767130.288357
1930.7559080.4881840.244092
1940.7401720.5196560.259828
1950.738630.522740.26137
1960.718180.563640.28182
1970.701670.596660.29833
1980.6889510.6220980.311049
1990.6560970.6878060.343903
2000.6248380.7503240.375162
2010.687720.624560.31228
2020.6560850.6878290.343915
2030.6378980.7242050.362102
2040.6011170.7977660.398883
2050.5786860.8426290.421314
2060.5457890.9084210.454211
2070.5375870.9248260.462413
2080.5560340.8879330.443966
2090.5525630.8948750.447437
2100.5358010.9283980.464199
2110.4976660.9953330.502334
2120.4715130.9430260.528487
2130.4565410.9130820.543459
2140.4145570.8291130.585443
2150.3970320.7940650.602968
2160.3637020.7274040.636298
2170.3890740.7781480.610926
2180.4518010.9036030.548199
2190.4176380.8352760.582362
2200.3811560.7623120.618844
2210.4206860.8413710.579314
2220.4506530.9013070.549347
2230.4216050.843210.578395
2240.4063010.8126030.593699
2250.5461210.9077590.453879
2260.5104760.9790490.489524
2270.4627260.9254520.537274
2280.5073930.9852150.492607
2290.7094880.5810230.290512
2300.7616590.4766830.238341
2310.7436890.5126220.256311
2320.7759510.4480980.224049
2330.7379240.5241510.262076
2340.7107770.5784450.289223
2350.6781380.6437240.321862
2360.8475650.3048710.152435
2370.8169720.3660550.183028
2380.787690.4246190.21231
2390.8433110.3133780.156689
2400.8839840.2320330.116016
2410.8617310.2765380.138269
2420.829640.3407210.17036
2430.8121620.3756770.187838
2440.7776010.4447980.222399
2450.7530810.4938380.246919
2460.7123830.5752330.287617
2470.6674110.6651780.332589
2480.7120740.5758510.287926
2490.6610180.6779640.338982
2500.5992940.8014110.400706
2510.5464460.9071080.453554
2520.4799040.9598080.520096
2530.6007920.7984160.399208
2540.5828670.8342660.417133
2550.6836230.6327540.316377
2560.6054770.7890470.394523
2570.7660050.467990.233995
2580.8250960.3498080.174904
2590.8282920.3434160.171708
2600.9854970.02900550.0145027
2610.9681570.0636870.0318435
2620.9658140.06837180.0341859
2630.9454680.1090640.0545318
2640.884270.231460.11573
2650.7754940.4490130.224506

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.863497 & 0.273006 & 0.136503 \tabularnewline
14 & 0.762619 & 0.474762 & 0.237381 \tabularnewline
15 & 0.648845 & 0.702309 & 0.351155 \tabularnewline
16 & 0.525382 & 0.949235 & 0.474618 \tabularnewline
17 & 0.515056 & 0.969887 & 0.484944 \tabularnewline
18 & 0.427306 & 0.854612 & 0.572694 \tabularnewline
19 & 0.338952 & 0.677904 & 0.661048 \tabularnewline
20 & 0.264122 & 0.528244 & 0.735878 \tabularnewline
21 & 0.325148 & 0.650297 & 0.674852 \tabularnewline
22 & 0.294697 & 0.589394 & 0.705303 \tabularnewline
23 & 0.224281 & 0.448561 & 0.775719 \tabularnewline
24 & 0.419426 & 0.838853 & 0.580574 \tabularnewline
25 & 0.344269 & 0.688538 & 0.655731 \tabularnewline
26 & 0.275742 & 0.551485 & 0.724258 \tabularnewline
27 & 0.342711 & 0.685421 & 0.657289 \tabularnewline
28 & 0.30262 & 0.605241 & 0.69738 \tabularnewline
29 & 0.252433 & 0.504867 & 0.747567 \tabularnewline
30 & 0.213167 & 0.426334 & 0.786833 \tabularnewline
31 & 0.442527 & 0.885054 & 0.557473 \tabularnewline
32 & 0.399028 & 0.798056 & 0.600972 \tabularnewline
33 & 0.377601 & 0.755201 & 0.622399 \tabularnewline
34 & 0.380605 & 0.761211 & 0.619395 \tabularnewline
35 & 0.337698 & 0.675396 & 0.662302 \tabularnewline
36 & 0.292585 & 0.58517 & 0.707415 \tabularnewline
37 & 0.243765 & 0.48753 & 0.756235 \tabularnewline
38 & 0.201777 & 0.403553 & 0.798223 \tabularnewline
39 & 0.183818 & 0.367637 & 0.816182 \tabularnewline
40 & 0.152562 & 0.305124 & 0.847438 \tabularnewline
41 & 0.192153 & 0.384307 & 0.807847 \tabularnewline
42 & 0.195042 & 0.390084 & 0.804958 \tabularnewline
43 & 0.227447 & 0.454895 & 0.772553 \tabularnewline
44 & 0.189784 & 0.379567 & 0.810216 \tabularnewline
45 & 0.159826 & 0.319652 & 0.840174 \tabularnewline
46 & 0.130599 & 0.261198 & 0.869401 \tabularnewline
47 & 0.113362 & 0.226723 & 0.886638 \tabularnewline
48 & 0.145616 & 0.291233 & 0.854384 \tabularnewline
49 & 0.193841 & 0.387681 & 0.806159 \tabularnewline
50 & 0.196705 & 0.393411 & 0.803295 \tabularnewline
51 & 0.1653 & 0.330601 & 0.8347 \tabularnewline
52 & 0.282285 & 0.56457 & 0.717715 \tabularnewline
53 & 0.257303 & 0.514606 & 0.742697 \tabularnewline
54 & 0.278479 & 0.556957 & 0.721521 \tabularnewline
55 & 0.360398 & 0.720796 & 0.639602 \tabularnewline
56 & 0.318648 & 0.637296 & 0.681352 \tabularnewline
57 & 0.443046 & 0.886092 & 0.556954 \tabularnewline
58 & 0.470069 & 0.940138 & 0.529931 \tabularnewline
59 & 0.452923 & 0.905847 & 0.547077 \tabularnewline
60 & 0.543422 & 0.913157 & 0.456578 \tabularnewline
61 & 0.501068 & 0.997863 & 0.498932 \tabularnewline
62 & 0.471072 & 0.942144 & 0.528928 \tabularnewline
63 & 0.453112 & 0.906224 & 0.546888 \tabularnewline
64 & 0.615021 & 0.769958 & 0.384979 \tabularnewline
65 & 0.616092 & 0.767816 & 0.383908 \tabularnewline
66 & 0.607597 & 0.784806 & 0.392403 \tabularnewline
67 & 0.570087 & 0.859826 & 0.429913 \tabularnewline
68 & 0.593721 & 0.812558 & 0.406279 \tabularnewline
69 & 0.628658 & 0.742684 & 0.371342 \tabularnewline
70 & 0.600163 & 0.799673 & 0.399837 \tabularnewline
71 & 0.562808 & 0.874384 & 0.437192 \tabularnewline
72 & 0.522955 & 0.954089 & 0.477045 \tabularnewline
73 & 0.505813 & 0.988374 & 0.494187 \tabularnewline
74 & 0.608607 & 0.782785 & 0.391393 \tabularnewline
75 & 0.634256 & 0.731488 & 0.365744 \tabularnewline
76 & 0.629616 & 0.740769 & 0.370384 \tabularnewline
77 & 0.627066 & 0.745868 & 0.372934 \tabularnewline
78 & 0.618984 & 0.762032 & 0.381016 \tabularnewline
79 & 0.596198 & 0.807604 & 0.403802 \tabularnewline
80 & 0.628121 & 0.743757 & 0.371879 \tabularnewline
81 & 0.602197 & 0.795606 & 0.397803 \tabularnewline
82 & 0.635834 & 0.728331 & 0.364166 \tabularnewline
83 & 0.600515 & 0.798969 & 0.399485 \tabularnewline
84 & 0.721841 & 0.556318 & 0.278159 \tabularnewline
85 & 0.699361 & 0.601278 & 0.300639 \tabularnewline
86 & 0.674463 & 0.651074 & 0.325537 \tabularnewline
87 & 0.646768 & 0.706463 & 0.353232 \tabularnewline
88 & 0.615055 & 0.76989 & 0.384945 \tabularnewline
89 & 0.611842 & 0.776315 & 0.388158 \tabularnewline
90 & 0.650694 & 0.698612 & 0.349306 \tabularnewline
91 & 0.664972 & 0.670057 & 0.335028 \tabularnewline
92 & 0.811356 & 0.377287 & 0.188644 \tabularnewline
93 & 0.785538 & 0.428925 & 0.214462 \tabularnewline
94 & 0.759757 & 0.480485 & 0.240243 \tabularnewline
95 & 0.774028 & 0.451943 & 0.225972 \tabularnewline
96 & 0.756771 & 0.486457 & 0.243229 \tabularnewline
97 & 0.748683 & 0.502634 & 0.251317 \tabularnewline
98 & 0.727442 & 0.545115 & 0.272558 \tabularnewline
99 & 0.798112 & 0.403777 & 0.201888 \tabularnewline
100 & 0.823195 & 0.353611 & 0.176805 \tabularnewline
101 & 0.803451 & 0.393098 & 0.196549 \tabularnewline
102 & 0.782082 & 0.435836 & 0.217918 \tabularnewline
103 & 0.768461 & 0.463078 & 0.231539 \tabularnewline
104 & 0.745012 & 0.509977 & 0.254988 \tabularnewline
105 & 0.823512 & 0.352976 & 0.176488 \tabularnewline
106 & 0.820303 & 0.359395 & 0.179697 \tabularnewline
107 & 0.833204 & 0.333593 & 0.166796 \tabularnewline
108 & 0.881323 & 0.237354 & 0.118677 \tabularnewline
109 & 0.912674 & 0.174653 & 0.0873263 \tabularnewline
110 & 0.910551 & 0.178899 & 0.0894494 \tabularnewline
111 & 0.896453 & 0.207094 & 0.103547 \tabularnewline
112 & 0.884678 & 0.230644 & 0.115322 \tabularnewline
113 & 0.931511 & 0.136977 & 0.0684886 \tabularnewline
114 & 0.94828 & 0.103441 & 0.0517203 \tabularnewline
115 & 0.961275 & 0.0774495 & 0.0387248 \tabularnewline
116 & 0.969499 & 0.0610028 & 0.0305014 \tabularnewline
117 & 0.964135 & 0.071731 & 0.0358655 \tabularnewline
118 & 0.956643 & 0.0867142 & 0.0433571 \tabularnewline
119 & 0.952029 & 0.0959422 & 0.0479711 \tabularnewline
120 & 0.95145 & 0.0971003 & 0.0485501 \tabularnewline
121 & 0.941989 & 0.116023 & 0.0580114 \tabularnewline
122 & 0.93223 & 0.135541 & 0.0677705 \tabularnewline
123 & 0.92016 & 0.159679 & 0.0798397 \tabularnewline
124 & 0.921639 & 0.156722 & 0.0783608 \tabularnewline
125 & 0.932986 & 0.134028 & 0.0670142 \tabularnewline
126 & 0.923527 & 0.152947 & 0.0764733 \tabularnewline
127 & 0.917753 & 0.164493 & 0.0822465 \tabularnewline
128 & 0.90921 & 0.181581 & 0.0907904 \tabularnewline
129 & 0.913065 & 0.173869 & 0.0869347 \tabularnewline
130 & 0.899914 & 0.200171 & 0.100086 \tabularnewline
131 & 0.884711 & 0.230577 & 0.115289 \tabularnewline
132 & 0.8673 & 0.265399 & 0.1327 \tabularnewline
133 & 0.855328 & 0.289344 & 0.144672 \tabularnewline
134 & 0.834407 & 0.331186 & 0.165593 \tabularnewline
135 & 0.817418 & 0.365165 & 0.182582 \tabularnewline
136 & 0.800598 & 0.398804 & 0.199402 \tabularnewline
137 & 0.839801 & 0.320397 & 0.160199 \tabularnewline
138 & 0.90066 & 0.198681 & 0.0993404 \tabularnewline
139 & 0.900448 & 0.199103 & 0.0995516 \tabularnewline
140 & 0.888008 & 0.223984 & 0.111992 \tabularnewline
141 & 0.876441 & 0.247118 & 0.123559 \tabularnewline
142 & 0.876148 & 0.247704 & 0.123852 \tabularnewline
143 & 0.865271 & 0.269457 & 0.134729 \tabularnewline
144 & 0.872234 & 0.255533 & 0.127766 \tabularnewline
145 & 0.854919 & 0.290161 & 0.145081 \tabularnewline
146 & 0.834236 & 0.331527 & 0.165764 \tabularnewline
147 & 0.840078 & 0.319844 & 0.159922 \tabularnewline
148 & 0.825752 & 0.348495 & 0.174248 \tabularnewline
149 & 0.844756 & 0.310488 & 0.155244 \tabularnewline
150 & 0.848497 & 0.303005 & 0.151503 \tabularnewline
151 & 0.900665 & 0.19867 & 0.099335 \tabularnewline
152 & 0.894983 & 0.210034 & 0.105017 \tabularnewline
153 & 0.896713 & 0.206575 & 0.103287 \tabularnewline
154 & 0.880554 & 0.238893 & 0.119446 \tabularnewline
155 & 0.874937 & 0.250127 & 0.125063 \tabularnewline
156 & 0.859203 & 0.281595 & 0.140797 \tabularnewline
157 & 0.865953 & 0.268094 & 0.134047 \tabularnewline
158 & 0.864454 & 0.271091 & 0.135546 \tabularnewline
159 & 0.85154 & 0.296919 & 0.14846 \tabularnewline
160 & 0.853085 & 0.293829 & 0.146915 \tabularnewline
161 & 0.860604 & 0.278791 & 0.139396 \tabularnewline
162 & 0.848461 & 0.303079 & 0.151539 \tabularnewline
163 & 0.828063 & 0.343874 & 0.171937 \tabularnewline
164 & 0.852359 & 0.295281 & 0.147641 \tabularnewline
165 & 0.838991 & 0.322018 & 0.161009 \tabularnewline
166 & 0.818295 & 0.363409 & 0.181705 \tabularnewline
167 & 0.824733 & 0.350534 & 0.175267 \tabularnewline
168 & 0.812994 & 0.374012 & 0.187006 \tabularnewline
169 & 0.794376 & 0.411248 & 0.205624 \tabularnewline
170 & 0.794946 & 0.410108 & 0.205054 \tabularnewline
171 & 0.770153 & 0.459695 & 0.229847 \tabularnewline
172 & 0.770805 & 0.45839 & 0.229195 \tabularnewline
173 & 0.742438 & 0.515123 & 0.257562 \tabularnewline
174 & 0.716326 & 0.567348 & 0.283674 \tabularnewline
175 & 0.68986 & 0.62028 & 0.31014 \tabularnewline
176 & 0.708322 & 0.583355 & 0.291678 \tabularnewline
177 & 0.679932 & 0.640136 & 0.320068 \tabularnewline
178 & 0.673714 & 0.652573 & 0.326286 \tabularnewline
179 & 0.642629 & 0.714742 & 0.357371 \tabularnewline
180 & 0.721331 & 0.557338 & 0.278669 \tabularnewline
181 & 0.738437 & 0.523125 & 0.261563 \tabularnewline
182 & 0.740046 & 0.519908 & 0.259954 \tabularnewline
183 & 0.816064 & 0.367872 & 0.183936 \tabularnewline
184 & 0.791629 & 0.416742 & 0.208371 \tabularnewline
185 & 0.81705 & 0.365901 & 0.18295 \tabularnewline
186 & 0.792709 & 0.414581 & 0.207291 \tabularnewline
187 & 0.795717 & 0.408566 & 0.204283 \tabularnewline
188 & 0.797021 & 0.405957 & 0.202979 \tabularnewline
189 & 0.793262 & 0.413476 & 0.206738 \tabularnewline
190 & 0.76636 & 0.467281 & 0.23364 \tabularnewline
191 & 0.737295 & 0.525409 & 0.262705 \tabularnewline
192 & 0.711643 & 0.576713 & 0.288357 \tabularnewline
193 & 0.755908 & 0.488184 & 0.244092 \tabularnewline
194 & 0.740172 & 0.519656 & 0.259828 \tabularnewline
195 & 0.73863 & 0.52274 & 0.26137 \tabularnewline
196 & 0.71818 & 0.56364 & 0.28182 \tabularnewline
197 & 0.70167 & 0.59666 & 0.29833 \tabularnewline
198 & 0.688951 & 0.622098 & 0.311049 \tabularnewline
199 & 0.656097 & 0.687806 & 0.343903 \tabularnewline
200 & 0.624838 & 0.750324 & 0.375162 \tabularnewline
201 & 0.68772 & 0.62456 & 0.31228 \tabularnewline
202 & 0.656085 & 0.687829 & 0.343915 \tabularnewline
203 & 0.637898 & 0.724205 & 0.362102 \tabularnewline
204 & 0.601117 & 0.797766 & 0.398883 \tabularnewline
205 & 0.578686 & 0.842629 & 0.421314 \tabularnewline
206 & 0.545789 & 0.908421 & 0.454211 \tabularnewline
207 & 0.537587 & 0.924826 & 0.462413 \tabularnewline
208 & 0.556034 & 0.887933 & 0.443966 \tabularnewline
209 & 0.552563 & 0.894875 & 0.447437 \tabularnewline
210 & 0.535801 & 0.928398 & 0.464199 \tabularnewline
211 & 0.497666 & 0.995333 & 0.502334 \tabularnewline
212 & 0.471513 & 0.943026 & 0.528487 \tabularnewline
213 & 0.456541 & 0.913082 & 0.543459 \tabularnewline
214 & 0.414557 & 0.829113 & 0.585443 \tabularnewline
215 & 0.397032 & 0.794065 & 0.602968 \tabularnewline
216 & 0.363702 & 0.727404 & 0.636298 \tabularnewline
217 & 0.389074 & 0.778148 & 0.610926 \tabularnewline
218 & 0.451801 & 0.903603 & 0.548199 \tabularnewline
219 & 0.417638 & 0.835276 & 0.582362 \tabularnewline
220 & 0.381156 & 0.762312 & 0.618844 \tabularnewline
221 & 0.420686 & 0.841371 & 0.579314 \tabularnewline
222 & 0.450653 & 0.901307 & 0.549347 \tabularnewline
223 & 0.421605 & 0.84321 & 0.578395 \tabularnewline
224 & 0.406301 & 0.812603 & 0.593699 \tabularnewline
225 & 0.546121 & 0.907759 & 0.453879 \tabularnewline
226 & 0.510476 & 0.979049 & 0.489524 \tabularnewline
227 & 0.462726 & 0.925452 & 0.537274 \tabularnewline
228 & 0.507393 & 0.985215 & 0.492607 \tabularnewline
229 & 0.709488 & 0.581023 & 0.290512 \tabularnewline
230 & 0.761659 & 0.476683 & 0.238341 \tabularnewline
231 & 0.743689 & 0.512622 & 0.256311 \tabularnewline
232 & 0.775951 & 0.448098 & 0.224049 \tabularnewline
233 & 0.737924 & 0.524151 & 0.262076 \tabularnewline
234 & 0.710777 & 0.578445 & 0.289223 \tabularnewline
235 & 0.678138 & 0.643724 & 0.321862 \tabularnewline
236 & 0.847565 & 0.304871 & 0.152435 \tabularnewline
237 & 0.816972 & 0.366055 & 0.183028 \tabularnewline
238 & 0.78769 & 0.424619 & 0.21231 \tabularnewline
239 & 0.843311 & 0.313378 & 0.156689 \tabularnewline
240 & 0.883984 & 0.232033 & 0.116016 \tabularnewline
241 & 0.861731 & 0.276538 & 0.138269 \tabularnewline
242 & 0.82964 & 0.340721 & 0.17036 \tabularnewline
243 & 0.812162 & 0.375677 & 0.187838 \tabularnewline
244 & 0.777601 & 0.444798 & 0.222399 \tabularnewline
245 & 0.753081 & 0.493838 & 0.246919 \tabularnewline
246 & 0.712383 & 0.575233 & 0.287617 \tabularnewline
247 & 0.667411 & 0.665178 & 0.332589 \tabularnewline
248 & 0.712074 & 0.575851 & 0.287926 \tabularnewline
249 & 0.661018 & 0.677964 & 0.338982 \tabularnewline
250 & 0.599294 & 0.801411 & 0.400706 \tabularnewline
251 & 0.546446 & 0.907108 & 0.453554 \tabularnewline
252 & 0.479904 & 0.959808 & 0.520096 \tabularnewline
253 & 0.600792 & 0.798416 & 0.399208 \tabularnewline
254 & 0.582867 & 0.834266 & 0.417133 \tabularnewline
255 & 0.683623 & 0.632754 & 0.316377 \tabularnewline
256 & 0.605477 & 0.789047 & 0.394523 \tabularnewline
257 & 0.766005 & 0.46799 & 0.233995 \tabularnewline
258 & 0.825096 & 0.349808 & 0.174904 \tabularnewline
259 & 0.828292 & 0.343416 & 0.171708 \tabularnewline
260 & 0.985497 & 0.0290055 & 0.0145027 \tabularnewline
261 & 0.968157 & 0.063687 & 0.0318435 \tabularnewline
262 & 0.965814 & 0.0683718 & 0.0341859 \tabularnewline
263 & 0.945468 & 0.109064 & 0.0545318 \tabularnewline
264 & 0.88427 & 0.23146 & 0.11573 \tabularnewline
265 & 0.775494 & 0.449013 & 0.224506 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269042&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]13[/C][C]0.863497[/C][C]0.273006[/C][C]0.136503[/C][/ROW]
[ROW][C]14[/C][C]0.762619[/C][C]0.474762[/C][C]0.237381[/C][/ROW]
[ROW][C]15[/C][C]0.648845[/C][C]0.702309[/C][C]0.351155[/C][/ROW]
[ROW][C]16[/C][C]0.525382[/C][C]0.949235[/C][C]0.474618[/C][/ROW]
[ROW][C]17[/C][C]0.515056[/C][C]0.969887[/C][C]0.484944[/C][/ROW]
[ROW][C]18[/C][C]0.427306[/C][C]0.854612[/C][C]0.572694[/C][/ROW]
[ROW][C]19[/C][C]0.338952[/C][C]0.677904[/C][C]0.661048[/C][/ROW]
[ROW][C]20[/C][C]0.264122[/C][C]0.528244[/C][C]0.735878[/C][/ROW]
[ROW][C]21[/C][C]0.325148[/C][C]0.650297[/C][C]0.674852[/C][/ROW]
[ROW][C]22[/C][C]0.294697[/C][C]0.589394[/C][C]0.705303[/C][/ROW]
[ROW][C]23[/C][C]0.224281[/C][C]0.448561[/C][C]0.775719[/C][/ROW]
[ROW][C]24[/C][C]0.419426[/C][C]0.838853[/C][C]0.580574[/C][/ROW]
[ROW][C]25[/C][C]0.344269[/C][C]0.688538[/C][C]0.655731[/C][/ROW]
[ROW][C]26[/C][C]0.275742[/C][C]0.551485[/C][C]0.724258[/C][/ROW]
[ROW][C]27[/C][C]0.342711[/C][C]0.685421[/C][C]0.657289[/C][/ROW]
[ROW][C]28[/C][C]0.30262[/C][C]0.605241[/C][C]0.69738[/C][/ROW]
[ROW][C]29[/C][C]0.252433[/C][C]0.504867[/C][C]0.747567[/C][/ROW]
[ROW][C]30[/C][C]0.213167[/C][C]0.426334[/C][C]0.786833[/C][/ROW]
[ROW][C]31[/C][C]0.442527[/C][C]0.885054[/C][C]0.557473[/C][/ROW]
[ROW][C]32[/C][C]0.399028[/C][C]0.798056[/C][C]0.600972[/C][/ROW]
[ROW][C]33[/C][C]0.377601[/C][C]0.755201[/C][C]0.622399[/C][/ROW]
[ROW][C]34[/C][C]0.380605[/C][C]0.761211[/C][C]0.619395[/C][/ROW]
[ROW][C]35[/C][C]0.337698[/C][C]0.675396[/C][C]0.662302[/C][/ROW]
[ROW][C]36[/C][C]0.292585[/C][C]0.58517[/C][C]0.707415[/C][/ROW]
[ROW][C]37[/C][C]0.243765[/C][C]0.48753[/C][C]0.756235[/C][/ROW]
[ROW][C]38[/C][C]0.201777[/C][C]0.403553[/C][C]0.798223[/C][/ROW]
[ROW][C]39[/C][C]0.183818[/C][C]0.367637[/C][C]0.816182[/C][/ROW]
[ROW][C]40[/C][C]0.152562[/C][C]0.305124[/C][C]0.847438[/C][/ROW]
[ROW][C]41[/C][C]0.192153[/C][C]0.384307[/C][C]0.807847[/C][/ROW]
[ROW][C]42[/C][C]0.195042[/C][C]0.390084[/C][C]0.804958[/C][/ROW]
[ROW][C]43[/C][C]0.227447[/C][C]0.454895[/C][C]0.772553[/C][/ROW]
[ROW][C]44[/C][C]0.189784[/C][C]0.379567[/C][C]0.810216[/C][/ROW]
[ROW][C]45[/C][C]0.159826[/C][C]0.319652[/C][C]0.840174[/C][/ROW]
[ROW][C]46[/C][C]0.130599[/C][C]0.261198[/C][C]0.869401[/C][/ROW]
[ROW][C]47[/C][C]0.113362[/C][C]0.226723[/C][C]0.886638[/C][/ROW]
[ROW][C]48[/C][C]0.145616[/C][C]0.291233[/C][C]0.854384[/C][/ROW]
[ROW][C]49[/C][C]0.193841[/C][C]0.387681[/C][C]0.806159[/C][/ROW]
[ROW][C]50[/C][C]0.196705[/C][C]0.393411[/C][C]0.803295[/C][/ROW]
[ROW][C]51[/C][C]0.1653[/C][C]0.330601[/C][C]0.8347[/C][/ROW]
[ROW][C]52[/C][C]0.282285[/C][C]0.56457[/C][C]0.717715[/C][/ROW]
[ROW][C]53[/C][C]0.257303[/C][C]0.514606[/C][C]0.742697[/C][/ROW]
[ROW][C]54[/C][C]0.278479[/C][C]0.556957[/C][C]0.721521[/C][/ROW]
[ROW][C]55[/C][C]0.360398[/C][C]0.720796[/C][C]0.639602[/C][/ROW]
[ROW][C]56[/C][C]0.318648[/C][C]0.637296[/C][C]0.681352[/C][/ROW]
[ROW][C]57[/C][C]0.443046[/C][C]0.886092[/C][C]0.556954[/C][/ROW]
[ROW][C]58[/C][C]0.470069[/C][C]0.940138[/C][C]0.529931[/C][/ROW]
[ROW][C]59[/C][C]0.452923[/C][C]0.905847[/C][C]0.547077[/C][/ROW]
[ROW][C]60[/C][C]0.543422[/C][C]0.913157[/C][C]0.456578[/C][/ROW]
[ROW][C]61[/C][C]0.501068[/C][C]0.997863[/C][C]0.498932[/C][/ROW]
[ROW][C]62[/C][C]0.471072[/C][C]0.942144[/C][C]0.528928[/C][/ROW]
[ROW][C]63[/C][C]0.453112[/C][C]0.906224[/C][C]0.546888[/C][/ROW]
[ROW][C]64[/C][C]0.615021[/C][C]0.769958[/C][C]0.384979[/C][/ROW]
[ROW][C]65[/C][C]0.616092[/C][C]0.767816[/C][C]0.383908[/C][/ROW]
[ROW][C]66[/C][C]0.607597[/C][C]0.784806[/C][C]0.392403[/C][/ROW]
[ROW][C]67[/C][C]0.570087[/C][C]0.859826[/C][C]0.429913[/C][/ROW]
[ROW][C]68[/C][C]0.593721[/C][C]0.812558[/C][C]0.406279[/C][/ROW]
[ROW][C]69[/C][C]0.628658[/C][C]0.742684[/C][C]0.371342[/C][/ROW]
[ROW][C]70[/C][C]0.600163[/C][C]0.799673[/C][C]0.399837[/C][/ROW]
[ROW][C]71[/C][C]0.562808[/C][C]0.874384[/C][C]0.437192[/C][/ROW]
[ROW][C]72[/C][C]0.522955[/C][C]0.954089[/C][C]0.477045[/C][/ROW]
[ROW][C]73[/C][C]0.505813[/C][C]0.988374[/C][C]0.494187[/C][/ROW]
[ROW][C]74[/C][C]0.608607[/C][C]0.782785[/C][C]0.391393[/C][/ROW]
[ROW][C]75[/C][C]0.634256[/C][C]0.731488[/C][C]0.365744[/C][/ROW]
[ROW][C]76[/C][C]0.629616[/C][C]0.740769[/C][C]0.370384[/C][/ROW]
[ROW][C]77[/C][C]0.627066[/C][C]0.745868[/C][C]0.372934[/C][/ROW]
[ROW][C]78[/C][C]0.618984[/C][C]0.762032[/C][C]0.381016[/C][/ROW]
[ROW][C]79[/C][C]0.596198[/C][C]0.807604[/C][C]0.403802[/C][/ROW]
[ROW][C]80[/C][C]0.628121[/C][C]0.743757[/C][C]0.371879[/C][/ROW]
[ROW][C]81[/C][C]0.602197[/C][C]0.795606[/C][C]0.397803[/C][/ROW]
[ROW][C]82[/C][C]0.635834[/C][C]0.728331[/C][C]0.364166[/C][/ROW]
[ROW][C]83[/C][C]0.600515[/C][C]0.798969[/C][C]0.399485[/C][/ROW]
[ROW][C]84[/C][C]0.721841[/C][C]0.556318[/C][C]0.278159[/C][/ROW]
[ROW][C]85[/C][C]0.699361[/C][C]0.601278[/C][C]0.300639[/C][/ROW]
[ROW][C]86[/C][C]0.674463[/C][C]0.651074[/C][C]0.325537[/C][/ROW]
[ROW][C]87[/C][C]0.646768[/C][C]0.706463[/C][C]0.353232[/C][/ROW]
[ROW][C]88[/C][C]0.615055[/C][C]0.76989[/C][C]0.384945[/C][/ROW]
[ROW][C]89[/C][C]0.611842[/C][C]0.776315[/C][C]0.388158[/C][/ROW]
[ROW][C]90[/C][C]0.650694[/C][C]0.698612[/C][C]0.349306[/C][/ROW]
[ROW][C]91[/C][C]0.664972[/C][C]0.670057[/C][C]0.335028[/C][/ROW]
[ROW][C]92[/C][C]0.811356[/C][C]0.377287[/C][C]0.188644[/C][/ROW]
[ROW][C]93[/C][C]0.785538[/C][C]0.428925[/C][C]0.214462[/C][/ROW]
[ROW][C]94[/C][C]0.759757[/C][C]0.480485[/C][C]0.240243[/C][/ROW]
[ROW][C]95[/C][C]0.774028[/C][C]0.451943[/C][C]0.225972[/C][/ROW]
[ROW][C]96[/C][C]0.756771[/C][C]0.486457[/C][C]0.243229[/C][/ROW]
[ROW][C]97[/C][C]0.748683[/C][C]0.502634[/C][C]0.251317[/C][/ROW]
[ROW][C]98[/C][C]0.727442[/C][C]0.545115[/C][C]0.272558[/C][/ROW]
[ROW][C]99[/C][C]0.798112[/C][C]0.403777[/C][C]0.201888[/C][/ROW]
[ROW][C]100[/C][C]0.823195[/C][C]0.353611[/C][C]0.176805[/C][/ROW]
[ROW][C]101[/C][C]0.803451[/C][C]0.393098[/C][C]0.196549[/C][/ROW]
[ROW][C]102[/C][C]0.782082[/C][C]0.435836[/C][C]0.217918[/C][/ROW]
[ROW][C]103[/C][C]0.768461[/C][C]0.463078[/C][C]0.231539[/C][/ROW]
[ROW][C]104[/C][C]0.745012[/C][C]0.509977[/C][C]0.254988[/C][/ROW]
[ROW][C]105[/C][C]0.823512[/C][C]0.352976[/C][C]0.176488[/C][/ROW]
[ROW][C]106[/C][C]0.820303[/C][C]0.359395[/C][C]0.179697[/C][/ROW]
[ROW][C]107[/C][C]0.833204[/C][C]0.333593[/C][C]0.166796[/C][/ROW]
[ROW][C]108[/C][C]0.881323[/C][C]0.237354[/C][C]0.118677[/C][/ROW]
[ROW][C]109[/C][C]0.912674[/C][C]0.174653[/C][C]0.0873263[/C][/ROW]
[ROW][C]110[/C][C]0.910551[/C][C]0.178899[/C][C]0.0894494[/C][/ROW]
[ROW][C]111[/C][C]0.896453[/C][C]0.207094[/C][C]0.103547[/C][/ROW]
[ROW][C]112[/C][C]0.884678[/C][C]0.230644[/C][C]0.115322[/C][/ROW]
[ROW][C]113[/C][C]0.931511[/C][C]0.136977[/C][C]0.0684886[/C][/ROW]
[ROW][C]114[/C][C]0.94828[/C][C]0.103441[/C][C]0.0517203[/C][/ROW]
[ROW][C]115[/C][C]0.961275[/C][C]0.0774495[/C][C]0.0387248[/C][/ROW]
[ROW][C]116[/C][C]0.969499[/C][C]0.0610028[/C][C]0.0305014[/C][/ROW]
[ROW][C]117[/C][C]0.964135[/C][C]0.071731[/C][C]0.0358655[/C][/ROW]
[ROW][C]118[/C][C]0.956643[/C][C]0.0867142[/C][C]0.0433571[/C][/ROW]
[ROW][C]119[/C][C]0.952029[/C][C]0.0959422[/C][C]0.0479711[/C][/ROW]
[ROW][C]120[/C][C]0.95145[/C][C]0.0971003[/C][C]0.0485501[/C][/ROW]
[ROW][C]121[/C][C]0.941989[/C][C]0.116023[/C][C]0.0580114[/C][/ROW]
[ROW][C]122[/C][C]0.93223[/C][C]0.135541[/C][C]0.0677705[/C][/ROW]
[ROW][C]123[/C][C]0.92016[/C][C]0.159679[/C][C]0.0798397[/C][/ROW]
[ROW][C]124[/C][C]0.921639[/C][C]0.156722[/C][C]0.0783608[/C][/ROW]
[ROW][C]125[/C][C]0.932986[/C][C]0.134028[/C][C]0.0670142[/C][/ROW]
[ROW][C]126[/C][C]0.923527[/C][C]0.152947[/C][C]0.0764733[/C][/ROW]
[ROW][C]127[/C][C]0.917753[/C][C]0.164493[/C][C]0.0822465[/C][/ROW]
[ROW][C]128[/C][C]0.90921[/C][C]0.181581[/C][C]0.0907904[/C][/ROW]
[ROW][C]129[/C][C]0.913065[/C][C]0.173869[/C][C]0.0869347[/C][/ROW]
[ROW][C]130[/C][C]0.899914[/C][C]0.200171[/C][C]0.100086[/C][/ROW]
[ROW][C]131[/C][C]0.884711[/C][C]0.230577[/C][C]0.115289[/C][/ROW]
[ROW][C]132[/C][C]0.8673[/C][C]0.265399[/C][C]0.1327[/C][/ROW]
[ROW][C]133[/C][C]0.855328[/C][C]0.289344[/C][C]0.144672[/C][/ROW]
[ROW][C]134[/C][C]0.834407[/C][C]0.331186[/C][C]0.165593[/C][/ROW]
[ROW][C]135[/C][C]0.817418[/C][C]0.365165[/C][C]0.182582[/C][/ROW]
[ROW][C]136[/C][C]0.800598[/C][C]0.398804[/C][C]0.199402[/C][/ROW]
[ROW][C]137[/C][C]0.839801[/C][C]0.320397[/C][C]0.160199[/C][/ROW]
[ROW][C]138[/C][C]0.90066[/C][C]0.198681[/C][C]0.0993404[/C][/ROW]
[ROW][C]139[/C][C]0.900448[/C][C]0.199103[/C][C]0.0995516[/C][/ROW]
[ROW][C]140[/C][C]0.888008[/C][C]0.223984[/C][C]0.111992[/C][/ROW]
[ROW][C]141[/C][C]0.876441[/C][C]0.247118[/C][C]0.123559[/C][/ROW]
[ROW][C]142[/C][C]0.876148[/C][C]0.247704[/C][C]0.123852[/C][/ROW]
[ROW][C]143[/C][C]0.865271[/C][C]0.269457[/C][C]0.134729[/C][/ROW]
[ROW][C]144[/C][C]0.872234[/C][C]0.255533[/C][C]0.127766[/C][/ROW]
[ROW][C]145[/C][C]0.854919[/C][C]0.290161[/C][C]0.145081[/C][/ROW]
[ROW][C]146[/C][C]0.834236[/C][C]0.331527[/C][C]0.165764[/C][/ROW]
[ROW][C]147[/C][C]0.840078[/C][C]0.319844[/C][C]0.159922[/C][/ROW]
[ROW][C]148[/C][C]0.825752[/C][C]0.348495[/C][C]0.174248[/C][/ROW]
[ROW][C]149[/C][C]0.844756[/C][C]0.310488[/C][C]0.155244[/C][/ROW]
[ROW][C]150[/C][C]0.848497[/C][C]0.303005[/C][C]0.151503[/C][/ROW]
[ROW][C]151[/C][C]0.900665[/C][C]0.19867[/C][C]0.099335[/C][/ROW]
[ROW][C]152[/C][C]0.894983[/C][C]0.210034[/C][C]0.105017[/C][/ROW]
[ROW][C]153[/C][C]0.896713[/C][C]0.206575[/C][C]0.103287[/C][/ROW]
[ROW][C]154[/C][C]0.880554[/C][C]0.238893[/C][C]0.119446[/C][/ROW]
[ROW][C]155[/C][C]0.874937[/C][C]0.250127[/C][C]0.125063[/C][/ROW]
[ROW][C]156[/C][C]0.859203[/C][C]0.281595[/C][C]0.140797[/C][/ROW]
[ROW][C]157[/C][C]0.865953[/C][C]0.268094[/C][C]0.134047[/C][/ROW]
[ROW][C]158[/C][C]0.864454[/C][C]0.271091[/C][C]0.135546[/C][/ROW]
[ROW][C]159[/C][C]0.85154[/C][C]0.296919[/C][C]0.14846[/C][/ROW]
[ROW][C]160[/C][C]0.853085[/C][C]0.293829[/C][C]0.146915[/C][/ROW]
[ROW][C]161[/C][C]0.860604[/C][C]0.278791[/C][C]0.139396[/C][/ROW]
[ROW][C]162[/C][C]0.848461[/C][C]0.303079[/C][C]0.151539[/C][/ROW]
[ROW][C]163[/C][C]0.828063[/C][C]0.343874[/C][C]0.171937[/C][/ROW]
[ROW][C]164[/C][C]0.852359[/C][C]0.295281[/C][C]0.147641[/C][/ROW]
[ROW][C]165[/C][C]0.838991[/C][C]0.322018[/C][C]0.161009[/C][/ROW]
[ROW][C]166[/C][C]0.818295[/C][C]0.363409[/C][C]0.181705[/C][/ROW]
[ROW][C]167[/C][C]0.824733[/C][C]0.350534[/C][C]0.175267[/C][/ROW]
[ROW][C]168[/C][C]0.812994[/C][C]0.374012[/C][C]0.187006[/C][/ROW]
[ROW][C]169[/C][C]0.794376[/C][C]0.411248[/C][C]0.205624[/C][/ROW]
[ROW][C]170[/C][C]0.794946[/C][C]0.410108[/C][C]0.205054[/C][/ROW]
[ROW][C]171[/C][C]0.770153[/C][C]0.459695[/C][C]0.229847[/C][/ROW]
[ROW][C]172[/C][C]0.770805[/C][C]0.45839[/C][C]0.229195[/C][/ROW]
[ROW][C]173[/C][C]0.742438[/C][C]0.515123[/C][C]0.257562[/C][/ROW]
[ROW][C]174[/C][C]0.716326[/C][C]0.567348[/C][C]0.283674[/C][/ROW]
[ROW][C]175[/C][C]0.68986[/C][C]0.62028[/C][C]0.31014[/C][/ROW]
[ROW][C]176[/C][C]0.708322[/C][C]0.583355[/C][C]0.291678[/C][/ROW]
[ROW][C]177[/C][C]0.679932[/C][C]0.640136[/C][C]0.320068[/C][/ROW]
[ROW][C]178[/C][C]0.673714[/C][C]0.652573[/C][C]0.326286[/C][/ROW]
[ROW][C]179[/C][C]0.642629[/C][C]0.714742[/C][C]0.357371[/C][/ROW]
[ROW][C]180[/C][C]0.721331[/C][C]0.557338[/C][C]0.278669[/C][/ROW]
[ROW][C]181[/C][C]0.738437[/C][C]0.523125[/C][C]0.261563[/C][/ROW]
[ROW][C]182[/C][C]0.740046[/C][C]0.519908[/C][C]0.259954[/C][/ROW]
[ROW][C]183[/C][C]0.816064[/C][C]0.367872[/C][C]0.183936[/C][/ROW]
[ROW][C]184[/C][C]0.791629[/C][C]0.416742[/C][C]0.208371[/C][/ROW]
[ROW][C]185[/C][C]0.81705[/C][C]0.365901[/C][C]0.18295[/C][/ROW]
[ROW][C]186[/C][C]0.792709[/C][C]0.414581[/C][C]0.207291[/C][/ROW]
[ROW][C]187[/C][C]0.795717[/C][C]0.408566[/C][C]0.204283[/C][/ROW]
[ROW][C]188[/C][C]0.797021[/C][C]0.405957[/C][C]0.202979[/C][/ROW]
[ROW][C]189[/C][C]0.793262[/C][C]0.413476[/C][C]0.206738[/C][/ROW]
[ROW][C]190[/C][C]0.76636[/C][C]0.467281[/C][C]0.23364[/C][/ROW]
[ROW][C]191[/C][C]0.737295[/C][C]0.525409[/C][C]0.262705[/C][/ROW]
[ROW][C]192[/C][C]0.711643[/C][C]0.576713[/C][C]0.288357[/C][/ROW]
[ROW][C]193[/C][C]0.755908[/C][C]0.488184[/C][C]0.244092[/C][/ROW]
[ROW][C]194[/C][C]0.740172[/C][C]0.519656[/C][C]0.259828[/C][/ROW]
[ROW][C]195[/C][C]0.73863[/C][C]0.52274[/C][C]0.26137[/C][/ROW]
[ROW][C]196[/C][C]0.71818[/C][C]0.56364[/C][C]0.28182[/C][/ROW]
[ROW][C]197[/C][C]0.70167[/C][C]0.59666[/C][C]0.29833[/C][/ROW]
[ROW][C]198[/C][C]0.688951[/C][C]0.622098[/C][C]0.311049[/C][/ROW]
[ROW][C]199[/C][C]0.656097[/C][C]0.687806[/C][C]0.343903[/C][/ROW]
[ROW][C]200[/C][C]0.624838[/C][C]0.750324[/C][C]0.375162[/C][/ROW]
[ROW][C]201[/C][C]0.68772[/C][C]0.62456[/C][C]0.31228[/C][/ROW]
[ROW][C]202[/C][C]0.656085[/C][C]0.687829[/C][C]0.343915[/C][/ROW]
[ROW][C]203[/C][C]0.637898[/C][C]0.724205[/C][C]0.362102[/C][/ROW]
[ROW][C]204[/C][C]0.601117[/C][C]0.797766[/C][C]0.398883[/C][/ROW]
[ROW][C]205[/C][C]0.578686[/C][C]0.842629[/C][C]0.421314[/C][/ROW]
[ROW][C]206[/C][C]0.545789[/C][C]0.908421[/C][C]0.454211[/C][/ROW]
[ROW][C]207[/C][C]0.537587[/C][C]0.924826[/C][C]0.462413[/C][/ROW]
[ROW][C]208[/C][C]0.556034[/C][C]0.887933[/C][C]0.443966[/C][/ROW]
[ROW][C]209[/C][C]0.552563[/C][C]0.894875[/C][C]0.447437[/C][/ROW]
[ROW][C]210[/C][C]0.535801[/C][C]0.928398[/C][C]0.464199[/C][/ROW]
[ROW][C]211[/C][C]0.497666[/C][C]0.995333[/C][C]0.502334[/C][/ROW]
[ROW][C]212[/C][C]0.471513[/C][C]0.943026[/C][C]0.528487[/C][/ROW]
[ROW][C]213[/C][C]0.456541[/C][C]0.913082[/C][C]0.543459[/C][/ROW]
[ROW][C]214[/C][C]0.414557[/C][C]0.829113[/C][C]0.585443[/C][/ROW]
[ROW][C]215[/C][C]0.397032[/C][C]0.794065[/C][C]0.602968[/C][/ROW]
[ROW][C]216[/C][C]0.363702[/C][C]0.727404[/C][C]0.636298[/C][/ROW]
[ROW][C]217[/C][C]0.389074[/C][C]0.778148[/C][C]0.610926[/C][/ROW]
[ROW][C]218[/C][C]0.451801[/C][C]0.903603[/C][C]0.548199[/C][/ROW]
[ROW][C]219[/C][C]0.417638[/C][C]0.835276[/C][C]0.582362[/C][/ROW]
[ROW][C]220[/C][C]0.381156[/C][C]0.762312[/C][C]0.618844[/C][/ROW]
[ROW][C]221[/C][C]0.420686[/C][C]0.841371[/C][C]0.579314[/C][/ROW]
[ROW][C]222[/C][C]0.450653[/C][C]0.901307[/C][C]0.549347[/C][/ROW]
[ROW][C]223[/C][C]0.421605[/C][C]0.84321[/C][C]0.578395[/C][/ROW]
[ROW][C]224[/C][C]0.406301[/C][C]0.812603[/C][C]0.593699[/C][/ROW]
[ROW][C]225[/C][C]0.546121[/C][C]0.907759[/C][C]0.453879[/C][/ROW]
[ROW][C]226[/C][C]0.510476[/C][C]0.979049[/C][C]0.489524[/C][/ROW]
[ROW][C]227[/C][C]0.462726[/C][C]0.925452[/C][C]0.537274[/C][/ROW]
[ROW][C]228[/C][C]0.507393[/C][C]0.985215[/C][C]0.492607[/C][/ROW]
[ROW][C]229[/C][C]0.709488[/C][C]0.581023[/C][C]0.290512[/C][/ROW]
[ROW][C]230[/C][C]0.761659[/C][C]0.476683[/C][C]0.238341[/C][/ROW]
[ROW][C]231[/C][C]0.743689[/C][C]0.512622[/C][C]0.256311[/C][/ROW]
[ROW][C]232[/C][C]0.775951[/C][C]0.448098[/C][C]0.224049[/C][/ROW]
[ROW][C]233[/C][C]0.737924[/C][C]0.524151[/C][C]0.262076[/C][/ROW]
[ROW][C]234[/C][C]0.710777[/C][C]0.578445[/C][C]0.289223[/C][/ROW]
[ROW][C]235[/C][C]0.678138[/C][C]0.643724[/C][C]0.321862[/C][/ROW]
[ROW][C]236[/C][C]0.847565[/C][C]0.304871[/C][C]0.152435[/C][/ROW]
[ROW][C]237[/C][C]0.816972[/C][C]0.366055[/C][C]0.183028[/C][/ROW]
[ROW][C]238[/C][C]0.78769[/C][C]0.424619[/C][C]0.21231[/C][/ROW]
[ROW][C]239[/C][C]0.843311[/C][C]0.313378[/C][C]0.156689[/C][/ROW]
[ROW][C]240[/C][C]0.883984[/C][C]0.232033[/C][C]0.116016[/C][/ROW]
[ROW][C]241[/C][C]0.861731[/C][C]0.276538[/C][C]0.138269[/C][/ROW]
[ROW][C]242[/C][C]0.82964[/C][C]0.340721[/C][C]0.17036[/C][/ROW]
[ROW][C]243[/C][C]0.812162[/C][C]0.375677[/C][C]0.187838[/C][/ROW]
[ROW][C]244[/C][C]0.777601[/C][C]0.444798[/C][C]0.222399[/C][/ROW]
[ROW][C]245[/C][C]0.753081[/C][C]0.493838[/C][C]0.246919[/C][/ROW]
[ROW][C]246[/C][C]0.712383[/C][C]0.575233[/C][C]0.287617[/C][/ROW]
[ROW][C]247[/C][C]0.667411[/C][C]0.665178[/C][C]0.332589[/C][/ROW]
[ROW][C]248[/C][C]0.712074[/C][C]0.575851[/C][C]0.287926[/C][/ROW]
[ROW][C]249[/C][C]0.661018[/C][C]0.677964[/C][C]0.338982[/C][/ROW]
[ROW][C]250[/C][C]0.599294[/C][C]0.801411[/C][C]0.400706[/C][/ROW]
[ROW][C]251[/C][C]0.546446[/C][C]0.907108[/C][C]0.453554[/C][/ROW]
[ROW][C]252[/C][C]0.479904[/C][C]0.959808[/C][C]0.520096[/C][/ROW]
[ROW][C]253[/C][C]0.600792[/C][C]0.798416[/C][C]0.399208[/C][/ROW]
[ROW][C]254[/C][C]0.582867[/C][C]0.834266[/C][C]0.417133[/C][/ROW]
[ROW][C]255[/C][C]0.683623[/C][C]0.632754[/C][C]0.316377[/C][/ROW]
[ROW][C]256[/C][C]0.605477[/C][C]0.789047[/C][C]0.394523[/C][/ROW]
[ROW][C]257[/C][C]0.766005[/C][C]0.46799[/C][C]0.233995[/C][/ROW]
[ROW][C]258[/C][C]0.825096[/C][C]0.349808[/C][C]0.174904[/C][/ROW]
[ROW][C]259[/C][C]0.828292[/C][C]0.343416[/C][C]0.171708[/C][/ROW]
[ROW][C]260[/C][C]0.985497[/C][C]0.0290055[/C][C]0.0145027[/C][/ROW]
[ROW][C]261[/C][C]0.968157[/C][C]0.063687[/C][C]0.0318435[/C][/ROW]
[ROW][C]262[/C][C]0.965814[/C][C]0.0683718[/C][C]0.0341859[/C][/ROW]
[ROW][C]263[/C][C]0.945468[/C][C]0.109064[/C][C]0.0545318[/C][/ROW]
[ROW][C]264[/C][C]0.88427[/C][C]0.23146[/C][C]0.11573[/C][/ROW]
[ROW][C]265[/C][C]0.775494[/C][C]0.449013[/C][C]0.224506[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269042&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269042&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.8634970.2730060.136503
140.7626190.4747620.237381
150.6488450.7023090.351155
160.5253820.9492350.474618
170.5150560.9698870.484944
180.4273060.8546120.572694
190.3389520.6779040.661048
200.2641220.5282440.735878
210.3251480.6502970.674852
220.2946970.5893940.705303
230.2242810.4485610.775719
240.4194260.8388530.580574
250.3442690.6885380.655731
260.2757420.5514850.724258
270.3427110.6854210.657289
280.302620.6052410.69738
290.2524330.5048670.747567
300.2131670.4263340.786833
310.4425270.8850540.557473
320.3990280.7980560.600972
330.3776010.7552010.622399
340.3806050.7612110.619395
350.3376980.6753960.662302
360.2925850.585170.707415
370.2437650.487530.756235
380.2017770.4035530.798223
390.1838180.3676370.816182
400.1525620.3051240.847438
410.1921530.3843070.807847
420.1950420.3900840.804958
430.2274470.4548950.772553
440.1897840.3795670.810216
450.1598260.3196520.840174
460.1305990.2611980.869401
470.1133620.2267230.886638
480.1456160.2912330.854384
490.1938410.3876810.806159
500.1967050.3934110.803295
510.16530.3306010.8347
520.2822850.564570.717715
530.2573030.5146060.742697
540.2784790.5569570.721521
550.3603980.7207960.639602
560.3186480.6372960.681352
570.4430460.8860920.556954
580.4700690.9401380.529931
590.4529230.9058470.547077
600.5434220.9131570.456578
610.5010680.9978630.498932
620.4710720.9421440.528928
630.4531120.9062240.546888
640.6150210.7699580.384979
650.6160920.7678160.383908
660.6075970.7848060.392403
670.5700870.8598260.429913
680.5937210.8125580.406279
690.6286580.7426840.371342
700.6001630.7996730.399837
710.5628080.8743840.437192
720.5229550.9540890.477045
730.5058130.9883740.494187
740.6086070.7827850.391393
750.6342560.7314880.365744
760.6296160.7407690.370384
770.6270660.7458680.372934
780.6189840.7620320.381016
790.5961980.8076040.403802
800.6281210.7437570.371879
810.6021970.7956060.397803
820.6358340.7283310.364166
830.6005150.7989690.399485
840.7218410.5563180.278159
850.6993610.6012780.300639
860.6744630.6510740.325537
870.6467680.7064630.353232
880.6150550.769890.384945
890.6118420.7763150.388158
900.6506940.6986120.349306
910.6649720.6700570.335028
920.8113560.3772870.188644
930.7855380.4289250.214462
940.7597570.4804850.240243
950.7740280.4519430.225972
960.7567710.4864570.243229
970.7486830.5026340.251317
980.7274420.5451150.272558
990.7981120.4037770.201888
1000.8231950.3536110.176805
1010.8034510.3930980.196549
1020.7820820.4358360.217918
1030.7684610.4630780.231539
1040.7450120.5099770.254988
1050.8235120.3529760.176488
1060.8203030.3593950.179697
1070.8332040.3335930.166796
1080.8813230.2373540.118677
1090.9126740.1746530.0873263
1100.9105510.1788990.0894494
1110.8964530.2070940.103547
1120.8846780.2306440.115322
1130.9315110.1369770.0684886
1140.948280.1034410.0517203
1150.9612750.07744950.0387248
1160.9694990.06100280.0305014
1170.9641350.0717310.0358655
1180.9566430.08671420.0433571
1190.9520290.09594220.0479711
1200.951450.09710030.0485501
1210.9419890.1160230.0580114
1220.932230.1355410.0677705
1230.920160.1596790.0798397
1240.9216390.1567220.0783608
1250.9329860.1340280.0670142
1260.9235270.1529470.0764733
1270.9177530.1644930.0822465
1280.909210.1815810.0907904
1290.9130650.1738690.0869347
1300.8999140.2001710.100086
1310.8847110.2305770.115289
1320.86730.2653990.1327
1330.8553280.2893440.144672
1340.8344070.3311860.165593
1350.8174180.3651650.182582
1360.8005980.3988040.199402
1370.8398010.3203970.160199
1380.900660.1986810.0993404
1390.9004480.1991030.0995516
1400.8880080.2239840.111992
1410.8764410.2471180.123559
1420.8761480.2477040.123852
1430.8652710.2694570.134729
1440.8722340.2555330.127766
1450.8549190.2901610.145081
1460.8342360.3315270.165764
1470.8400780.3198440.159922
1480.8257520.3484950.174248
1490.8447560.3104880.155244
1500.8484970.3030050.151503
1510.9006650.198670.099335
1520.8949830.2100340.105017
1530.8967130.2065750.103287
1540.8805540.2388930.119446
1550.8749370.2501270.125063
1560.8592030.2815950.140797
1570.8659530.2680940.134047
1580.8644540.2710910.135546
1590.851540.2969190.14846
1600.8530850.2938290.146915
1610.8606040.2787910.139396
1620.8484610.3030790.151539
1630.8280630.3438740.171937
1640.8523590.2952810.147641
1650.8389910.3220180.161009
1660.8182950.3634090.181705
1670.8247330.3505340.175267
1680.8129940.3740120.187006
1690.7943760.4112480.205624
1700.7949460.4101080.205054
1710.7701530.4596950.229847
1720.7708050.458390.229195
1730.7424380.5151230.257562
1740.7163260.5673480.283674
1750.689860.620280.31014
1760.7083220.5833550.291678
1770.6799320.6401360.320068
1780.6737140.6525730.326286
1790.6426290.7147420.357371
1800.7213310.5573380.278669
1810.7384370.5231250.261563
1820.7400460.5199080.259954
1830.8160640.3678720.183936
1840.7916290.4167420.208371
1850.817050.3659010.18295
1860.7927090.4145810.207291
1870.7957170.4085660.204283
1880.7970210.4059570.202979
1890.7932620.4134760.206738
1900.766360.4672810.23364
1910.7372950.5254090.262705
1920.7116430.5767130.288357
1930.7559080.4881840.244092
1940.7401720.5196560.259828
1950.738630.522740.26137
1960.718180.563640.28182
1970.701670.596660.29833
1980.6889510.6220980.311049
1990.6560970.6878060.343903
2000.6248380.7503240.375162
2010.687720.624560.31228
2020.6560850.6878290.343915
2030.6378980.7242050.362102
2040.6011170.7977660.398883
2050.5786860.8426290.421314
2060.5457890.9084210.454211
2070.5375870.9248260.462413
2080.5560340.8879330.443966
2090.5525630.8948750.447437
2100.5358010.9283980.464199
2110.4976660.9953330.502334
2120.4715130.9430260.528487
2130.4565410.9130820.543459
2140.4145570.8291130.585443
2150.3970320.7940650.602968
2160.3637020.7274040.636298
2170.3890740.7781480.610926
2180.4518010.9036030.548199
2190.4176380.8352760.582362
2200.3811560.7623120.618844
2210.4206860.8413710.579314
2220.4506530.9013070.549347
2230.4216050.843210.578395
2240.4063010.8126030.593699
2250.5461210.9077590.453879
2260.5104760.9790490.489524
2270.4627260.9254520.537274
2280.5073930.9852150.492607
2290.7094880.5810230.290512
2300.7616590.4766830.238341
2310.7436890.5126220.256311
2320.7759510.4480980.224049
2330.7379240.5241510.262076
2340.7107770.5784450.289223
2350.6781380.6437240.321862
2360.8475650.3048710.152435
2370.8169720.3660550.183028
2380.787690.4246190.21231
2390.8433110.3133780.156689
2400.8839840.2320330.116016
2410.8617310.2765380.138269
2420.829640.3407210.17036
2430.8121620.3756770.187838
2440.7776010.4447980.222399
2450.7530810.4938380.246919
2460.7123830.5752330.287617
2470.6674110.6651780.332589
2480.7120740.5758510.287926
2490.6610180.6779640.338982
2500.5992940.8014110.400706
2510.5464460.9071080.453554
2520.4799040.9598080.520096
2530.6007920.7984160.399208
2540.5828670.8342660.417133
2550.6836230.6327540.316377
2560.6054770.7890470.394523
2570.7660050.467990.233995
2580.8250960.3498080.174904
2590.8282920.3434160.171708
2600.9854970.02900550.0145027
2610.9681570.0636870.0318435
2620.9658140.06837180.0341859
2630.9454680.1090640.0545318
2640.884270.231460.11573
2650.7754940.4490130.224506






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level10.00395257OK
10% type I error level90.0355731OK

\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 & 0 & 0 & OK \tabularnewline
5% type I error level & 1 & 0.00395257 & OK \tabularnewline
10% type I error level & 9 & 0.0355731 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269042&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]1[/C][C]0.00395257[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]9[/C][C]0.0355731[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269042&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269042&T=6

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level10.00395257OK
10% type I error level90.0355731OK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 10 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 10 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- '10'
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$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), 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,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
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, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
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,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
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,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
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,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
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,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
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')
}