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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 15 Dec 2014 08:53:53 +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/t1418633650pj195n74a1usjnm.htm/, Retrieved Thu, 31 Oct 2024 23:16:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267961, Retrieved Thu, 31 Oct 2024 23:16:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact178
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] [efc983391fe36da4845de855ec76c3b2] [Current]
-             [Multiple Regression] [] [2014-12-15 10:02:37] [7b576ab45e161dc8fb6fe50455a3800c]
-    D          [Multiple Regression] [Multiple Linear R...] [2014-12-15 21:20:37] [508ad00fbaced7ad8e80ddb3167ea0fd]
- RMPD        [Skewness and Kurtosis Test] [] [2014-12-15 11:37:38] [7b576ab45e161dc8fb6fe50455a3800c]
- RMPD        [Central Tendency] [] [2014-12-15 15:18:37] [7b576ab45e161dc8fb6fe50455a3800c]
- RMPD        [Skewness and Kurtosis Test] [] [2014-12-15 15:27:27] [7b576ab45e161dc8fb6fe50455a3800c]
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Dataseries X:
26	50	4	2011	1	0	0	0	0	12.9
57	62	4	2011	1	1	57	62	4	12.2
37	54	5	2011	1	0	0	0	0	12.8
67	71	4	2011	1	1	67	71	4	7.4
43	54	4	2011	1	1	43	54	4	6.7
52	65	9	2011	1	1	52	65	9	12.6
52	73	8	2011	1	0	0	0	0	14.8
43	52	11	2011	1	1	43	52	11	13.3
84	84	4	2011	1	1	84	84	4	11.1
67	42	4	2011	1	1	67	42	4	8.2
49	66	6	2011	1	1	49	66	6	11.4
70	65	4	2011	1	1	70	65	4	6.4
52	78	8	2011	1	1	52	78	8	10.6
58	73	4	2011	1	0	0	0	0	12.0
68	75	4	2011	1	0	0	0	0	6.3
62	72	11	2011	0	0	0	0	0	11.3
43	66	4	2011	1	1	43	66	4	11.9
56	70	4	2011	1	0	0	0	0	9.3
56	61	6	2011	0	1	56	61	6	9.6
74	81	6	2011	1	0	0	0	0	10.0
65	71	4	2011	1	1	65	71	4	6.4
63	69	8	2011	1	1	63	69	8	13.8
58	71	5	2011	1	0	0	0	0	10.8
57	72	4	2011	1	1	57	72	4	13.8
63	68	9	2011	1	1	63	68	9	11.7
53	70	4	2011	1	1	53	70	4	10.9
57	68	7	2011	0	1	57	68	7	16.1
51	61	10	2011	0	0	0	0	0	13.4
64	67	4	2011	1	1	64	67	4	9.9
53	76	4	2011	1	0	0	0	0	11.5
29	70	7	2011	1	0	0	0	0	8.3
54	60	12	2011	1	0	0	0	0	11.7
58	72	7	2011	1	1	58	72	7	9.0
43	69	5	2011	1	1	43	69	5	9.7
51	71	8	2011	1	1	51	71	8	10.8
53	62	5	2011	1	1	53	62	5	10.3
54	70	4	2011	1	0	0	0	0	10.4
56	64	9	2011	0	1	56	64	9	12.7
61	58	7	2011	1	1	61	58	7	9.3
47	76	4	2011	1	0	0	0	0	11.8
39	52	4	2011	1	1	39	52	4	5.9
48	59	4	2011	1	1	48	59	4	11.4
50	68	4	2011	1	1	50	68	4	13.0
35	76	4	2011	1	1	35	76	4	10.8
30	65	7	2011	0	1	30	65	7	12.3
68	67	4	2011	1	0	0	0	0	11.3
49	59	7	2011	1	1	49	59	7	11.8
61	69	4	2011	0	1	61	69	4	7.9
67	76	4	2011	1	0	0	0	0	12.7
47	63	4	2011	0	1	47	63	4	12.3
56	75	4	2011	0	1	56	75	4	11.6
50	63	8	2011	0	1	50	63	8	6.7
43	60	4	2011	1	1	43	60	4	10.9
67	73	4	2011	0	1	67	73	4	12.1
62	63	4	2011	1	1	62	63	4	13.3
57	70	4	2011	1	1	57	70	4	10.1
41	75	7	2011	0	0	0	0	0	5.7
54	66	12	2011	1	1	54	66	12	14.3
45	63	4	2011	0	0	0	0	0	8.0
48	63	4	2011	0	1	48	63	4	13.3
61	64	4	2011	1	1	61	64	4	9.3
56	70	5	2011	1	0	0	0	0	12.5
41	75	15	2011	1	0	0	0	0	7.6
43	61	5	2011	1	1	43	61	5	15.9
53	60	10	2011	1	0	0	0	0	9.2
44	62	9	2011	0	1	44	62	9	9.1
66	73	8	2011	1	0	0	0	0	11.1
58	61	4	2011	1	1	58	61	4	13.0
46	66	5	2011	1	1	46	66	5	14.5
37	64	4	2011	0	0	0	0	0	12.2
51	59	9	2011	1	0	0	0	0	12.3
51	64	4	2011	1	0	0	0	0	11.4
56	60	10	2011	0	0	0	0	0	8.8
66	56	4	2011	0	1	66	56	4	14.6
37	78	4	2011	1	0	0	0	0	12.6
42	67	7	2011	1	0	0	0	0	13.0
38	59	5	2011	0	1	38	59	5	12.6
66	66	4	2011	1	0	0	0	0	13.2
34	68	4	2011	0	0	0	0	0	9.9
53	71	4	2011	1	1	53	71	4	7.7
49	66	4	2011	0	0	0	0	0	10.5
55	73	4	2011	0	0	0	0	0	13.4
49	72	4	2011	0	0	0	0	0	10.9
59	71	6	2011	0	1	59	71	6	4.3
40	59	10	2011	0	0	0	0	0	10.3
58	64	7	2011	0	1	58	64	7	11.8
60	66	4	2011	0	1	60	66	4	11.2
63	78	4	2011	0	0	0	0	0	11.4
56	68	7	2011	0	0	0	0	0	8.6
54	73	4	2011	0	0	0	0	0	13.2
52	62	8	2011	0	1	52	62	8	12.6
34	65	11	2011	0	1	34	65	11	5.6
69	68	6	2011	0	1	69	68	6	9.9
32	65	14	2011	0	0	0	0	0	8.8
48	60	5	2011	0	1	48	60	5	7.7
67	71	4	2011	0	0	0	0	0	9.0
58	65	8	2011	0	1	58	65	8	7.3
57	68	9	2011	0	1	57	68	9	11.4
42	64	4	2011	0	1	42	64	4	13.6
64	74	4	2011	0	1	64	74	4	7.9
58	69	5	2011	0	1	58	69	5	10.7
66	76	4	2011	0	0	0	0	0	10.3
26	68	5	2011	0	1	26	68	5	8.3
61	72	4	2011	0	1	61	72	4	9.6
52	67	4	2011	0	1	52	67	4	14.2
51	63	7	2011	0	0	0	0	0	8.5
55	59	10	2011	0	0	0	0	0	13.5
50	73	4	2011	0	0	0	0	0	4.9
60	66	5	2011	0	0	0	0	0	6.4
56	62	4	2011	0	0	0	0	0	9.6
63	69	4	2011	0	0	0	0	0	11.6
61	66	4	2011	0	1	61	66	4	11.1
52	51	6	2012	1	1	52	51	6	4.35
16	56	4	2012	1	1	16	56	4	12.7
46	67	8	2012	1	1	46	67	8	18.1
56	69	5	2012	1	1	56	69	5	17.85
52	57	4	2012	0	0	0	0	0	16.6
55	56	17	2012	0	1	55	56	17	12.6
50	55	4	2012	1	1	50	55	4	17.1
59	63	4	2012	1	0	0	0	0	19.1
60	67	8	2012	1	1	60	67	8	16.1
52	65	4	2012	1	0	0	0	0	13.35
44	47	7	2012	1	0	0	0	0	18.4
67	76	4	2012	1	1	67	76	4	14.7
52	64	4	2012	1	1	52	64	4	10.6
55	68	5	2012	1	1	55	68	5	12.6
37	64	7	2012	1	1	37	64	7	16.2
54	65	4	2012	1	1	54	65	4	13.6
72	71	4	2012	0	1	72	71	4	18.9
51	63	7	2012	1	1	51	63	7	14.1
48	60	11	2012	1	1	48	60	11	14.5
60	68	7	2012	1	0	0	0	0	16.15
50	72	4	2012	1	1	50	72	4	14.75
63	70	4	2012	1	1	63	70	4	14.8
33	61	4	2012	1	1	33	61	4	12.45
67	61	4	2012	1	1	67	61	4	12.65
46	62	4	2012	1	1	46	62	4	17.35
54	71	4	2012	1	1	54	71	4	8.6
59	71	6	2012	1	0	0	0	0	18.4
61	51	8	2012	1	1	61	51	8	16.1
33	56	23	2012	0	1	33	56	23	11.6
47	70	4	2012	1	1	47	70	4	17.75
69	73	8	2012	1	1	69	73	8	15.25
52	76	6	2012	1	1	52	76	6	17.65
55	68	4	2012	1	0	0	0	0	16.35
41	48	7	2012	1	0	0	0	0	17.65
73	52	4	2012	1	1	73	52	4	13.6
52	60	4	2012	1	0	0	0	0	14.35
50	59	4	2012	1	0	0	0	0	14.75
51	57	10	2012	1	1	51	57	10	18.25
60	79	6	2012	1	0	0	0	0	9.9
56	60	5	2012	1	1	56	60	5	16
56	60	5	2012	1	1	56	60	5	18.25
29	59	4	2012	1	0	0	0	0	16.85
66	62	4	2012	0	1	66	62	4	14.6
66	59	5	2012	0	1	66	59	5	13.85
73	61	5	2012	1	1	73	61	5	18.95
55	71	5	2012	1	0	0	0	0	15.6
64	57	5	2012	0	0	0	0	0	14.85
40	66	4	2012	0	0	0	0	0	11.75
46	63	6	2012	0	0	0	0	0	18.45
58	69	4	2012	0	1	58	69	4	15.9
43	58	4	2012	1	0	0	0	0	17.1
61	59	4	2012	1	1	61	59	4	16.1
51	48	9	2012	0	0	0	0	0	19.9
50	66	18	2012	0	1	50	66	18	10.95
52	73	6	2012	0	0	0	0	0	18.45
54	67	5	2012	0	1	54	67	5	15.1
66	61	4	2012	0	0	0	0	0	15
61	68	11	2012	0	0	0	0	0	11.35
80	75	4	2012	0	1	80	75	4	15.95
51	62	10	2012	0	0	0	0	0	18.1
56	69	6	2012	0	1	56	69	6	14.6
56	58	8	2012	1	1	56	58	8	15.4
56	60	8	2012	1	1	56	60	8	15.4
53	74	6	2012	0	1	53	74	6	17.6
47	55	8	2012	1	1	47	55	8	13.35
25	62	4	2012	1	0	0	0	0	19.1
47	63	4	2012	0	1	47	63	4	15.35
46	69	9	2012	1	0	0	0	0	7.6
50	58	9	2012	0	0	0	0	0	13.4
39	58	5	2012	0	0	0	0	0	13.9
51	68	4	2012	1	1	51	68	4	19.1
58	72	4	2012	0	0	0	0	0	15.25
35	62	15	2012	0	1	35	62	15	12.9
58	62	10	2012	0	0	0	0	0	16.1
60	65	9	2012	0	0	0	0	0	17.35
62	69	7	2012	0	0	0	0	0	13.15
63	66	9	2012	0	0	0	0	0	12.15
53	72	6	2012	0	1	53	72	6	12.6
46	62	4	2012	0	1	46	62	4	10.35
67	75	7	2012	0	1	67	75	7	15.4
59	58	4	2012	0	1	59	58	4	9.6
64	66	7	2012	0	0	0	0	0	18.2
38	55	4	2012	0	0	0	0	0	13.6
50	47	15	2012	0	1	50	47	15	14.85
48	72	4	2012	1	0	0	0	0	14.75
48	62	9	2012	0	0	0	0	0	14.1
47	64	4	2012	0	0	0	0	0	14.9
66	64	4	2012	0	0	0	0	0	16.25
47	19	28	2012	1	1	47	19	28	19.25
63	50	4	2012	0	1	63	50	4	13.6
58	68	4	2012	1	0	0	0	0	13.6
44	70	4	2012	0	0	0	0	0	15.65
51	79	5	2012	1	1	51	79	5	12.75
43	69	4	2012	0	0	0	0	0	14.6
55	71	4	2012	1	1	55	71	4	9.85
38	48	12	2012	0	1	38	48	12	12.65
45	73	4	2012	0	0	0	0	0	19.2
50	74	6	2012	0	1	50	74	6	16.6
54	66	6	2012	0	1	54	66	6	11.2
57	71	5	2012	1	1	57	71	5	15.25
60	74	4	2012	1	0	0	0	0	11.9
55	78	4	2012	0	0	0	0	0	13.2
56	75	4	2012	1	0	0	0	0	16.35
49	53	10	2012	1	1	49	53	10	12.4
37	60	7	2012	0	1	37	60	7	15.85
59	70	4	2012	1	1	59	70	4	18.15
46	69	7	2012	0	1	46	69	7	11.15
51	65	4	2012	0	0	0	0	0	15.65
58	78	4	2012	1	0	0	0	0	17.75
64	78	12	2012	0	0	0	0	0	7.65
53	59	5	2012	1	1	53	59	5	12.35
48	72	8	2012	1	1	48	72	8	15.6
51	70	6	2012	1	0	0	0	0	19.3
47	63	17	2012	0	0	0	0	0	15.2
59	63	4	2012	1	0	0	0	0	17.1
62	71	5	2012	0	1	62	71	5	15.6
62	74	4	2012	1	1	62	74	4	18.4
51	67	5	2012	1	0	0	0	0	19.05
64	66	5	2012	1	0	0	0	0	18.55
52	62	6	2012	1	0	0	0	0	19.1
67	80	4	2012	0	1	67	80	4	13.1
50	73	4	2012	1	1	50	73	4	12.85
54	67	4	2012	1	1	54	67	4	9.5
58	61	6	2012	1	1	58	61	6	4.5
56	73	8	2012	0	0	0	0	0	11.85
63	74	10	2012	1	1	63	74	10	13.6
31	32	4	2012	1	1	31	32	4	11.7
65	69	5	2012	0	1	65	69	5	12.4
71	69	4	2012	1	0	0	0	0	13.35
50	84	4	2012	0	0	0	0	0	11.4
57	64	4	2012	0	1	57	64	4	14.9
47	58	16	2012	0	0	0	0	0	19.9
47	59	7	2012	0	1	47	59	7	11.2
57	78	4	2012	0	1	57	78	4	14.6
43	57	4	2012	1	0	0	0	0	17.6
41	60	14	2012	1	1	41	60	14	14.05
63	68	5	2012	1	0	0	0	0	16.1
63	68	5	2012	1	1	63	68	5	13.35
56	73	5	2012	1	1	56	73	5	11.85
51	69	5	2012	1	0	0	0	0	11.95
50	67	7	2012	0	1	50	67	7	14.75
22	60	19	2012	0	0	0	0	0	15.15
41	65	16	2012	1	1	41	65	16	13.2
59	66	4	2012	0	0	0	0	0	16.85
56	74	4	2012	0	1	56	74	4	7.85
66	81	7	2012	1	0	0	0	0	7.7
53	72	9	2012	0	0	0	0	0	12.6
42	55	5	2012	0	1	42	55	5	7.85
52	49	14	2012	0	1	52	49	14	10.95
54	74	4	2012	0	0	0	0	0	12.35
44	53	16	2012	0	1	44	53	16	9.95
62	64	10	2012	0	1	62	64	10	14.9
53	65	5	2012	0	0	0	0	0	16.65
50	57	6	2012	0	1	50	57	6	13.4
36	51	4	2012	0	0	0	0	0	13.95
76	80	4	2012	0	0	0	0	0	15.7
66	67	4	2012	0	1	66	67	4	16.85
62	70	5	2012	0	1	62	70	5	10.95
59	74	4	2012	0	0	0	0	0	15.35
47	75	4	2012	0	1	47	75	4	12.2
55	70	5	2012	0	0	0	0	0	15.1
58	69	4	2012	0	0	0	0	0	17.75
60	65	4	2012	0	1	60	65	4	15.2
44	55	5	2012	1	0	0	0	0	14.6
57	71	8	2012	0	0	0	0	0	16.65
45	65	15	2012	0	1	45	65	15	8.1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267961&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267961&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267961&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'George Udny Yule' @ yule.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Tot[t] = -7435.53 + 0.0164837AMS.I[t] -0.138326AMS.E[t] -0.103108AMS.A[t] + 3.70734Academiejaar[t] + 0.697448Type_Opleiding_Binair[t] -12.6607gender[t] + 0.0103167AMS.I_GES[t] + 0.156984AMS.I1_GES[t] + 0.120528AMS.A_GES[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Tot[t] =  -7435.53 +  0.0164837AMS.I[t] -0.138326AMS.E[t] -0.103108AMS.A[t] +  3.70734Academiejaar[t] +  0.697448Type_Opleiding_Binair[t] -12.6607gender[t] +  0.0103167AMS.I_GES[t] +  0.156984AMS.I1_GES[t] +  0.120528AMS.A_GES[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267961&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Tot[t] =  -7435.53 +  0.0164837AMS.I[t] -0.138326AMS.E[t] -0.103108AMS.A[t] +  3.70734Academiejaar[t] +  0.697448Type_Opleiding_Binair[t] -12.6607gender[t] +  0.0103167AMS.I_GES[t] +  0.156984AMS.I1_GES[t] +  0.120528AMS.A_GES[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267961&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267961&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
Tot[t] = -7435.53 + 0.0164837AMS.I[t] -0.138326AMS.E[t] -0.103108AMS.A[t] + 3.70734Academiejaar[t] + 0.697448Type_Opleiding_Binair[t] -12.6607gender[t] + 0.0103167AMS.I_GES[t] + 0.156984AMS.I1_GES[t] + 0.120528AMS.A_GES[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-7435.53684.279-10.874.98019e-232.49009e-23
AMS.I0.01648370.02697540.61110.5416760.270838
AMS.E-0.1383260.0377404-3.6650.0002979240.000148962
AMS.A-0.1031080.0840424-1.2270.2209520.110476
Academiejaar3.707340.3400510.93.78315e-231.89157e-23
Type_Opleiding_Binair0.6974480.3344312.0850.03797230.0189862
gender-12.66073.32357-3.8090.0001727998.63996e-05
AMS.I_GES0.01031670.03524970.29270.7699970.384998
AMS.I1_GES0.1569840.04750013.3050.001079530.000539764
AMS.A_GES0.1205280.1059651.1370.2563730.128187

\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) & -7435.53 & 684.279 & -10.87 & 4.98019e-23 & 2.49009e-23 \tabularnewline
AMS.I & 0.0164837 & 0.0269754 & 0.6111 & 0.541676 & 0.270838 \tabularnewline
AMS.E & -0.138326 & 0.0377404 & -3.665 & 0.000297924 & 0.000148962 \tabularnewline
AMS.A & -0.103108 & 0.0840424 & -1.227 & 0.220952 & 0.110476 \tabularnewline
Academiejaar & 3.70734 & 0.34005 & 10.9 & 3.78315e-23 & 1.89157e-23 \tabularnewline
Type_Opleiding_Binair & 0.697448 & 0.334431 & 2.085 & 0.0379723 & 0.0189862 \tabularnewline
gender & -12.6607 & 3.32357 & -3.809 & 0.000172799 & 8.63996e-05 \tabularnewline
AMS.I_GES & 0.0103167 & 0.0352497 & 0.2927 & 0.769997 & 0.384998 \tabularnewline
AMS.I1_GES & 0.156984 & 0.0475001 & 3.305 & 0.00107953 & 0.000539764 \tabularnewline
AMS.A_GES & 0.120528 & 0.105965 & 1.137 & 0.256373 & 0.128187 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267961&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]-7435.53[/C][C]684.279[/C][C]-10.87[/C][C]4.98019e-23[/C][C]2.49009e-23[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.0164837[/C][C]0.0269754[/C][C]0.6111[/C][C]0.541676[/C][C]0.270838[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.138326[/C][C]0.0377404[/C][C]-3.665[/C][C]0.000297924[/C][C]0.000148962[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.103108[/C][C]0.0840424[/C][C]-1.227[/C][C]0.220952[/C][C]0.110476[/C][/ROW]
[ROW][C]Academiejaar[/C][C]3.70734[/C][C]0.34005[/C][C]10.9[/C][C]3.78315e-23[/C][C]1.89157e-23[/C][/ROW]
[ROW][C]Type_Opleiding_Binair[/C][C]0.697448[/C][C]0.334431[/C][C]2.085[/C][C]0.0379723[/C][C]0.0189862[/C][/ROW]
[ROW][C]gender[/C][C]-12.6607[/C][C]3.32357[/C][C]-3.809[/C][C]0.000172799[/C][C]8.63996e-05[/C][/ROW]
[ROW][C]AMS.I_GES[/C][C]0.0103167[/C][C]0.0352497[/C][C]0.2927[/C][C]0.769997[/C][C]0.384998[/C][/ROW]
[ROW][C]AMS.I1_GES[/C][C]0.156984[/C][C]0.0475001[/C][C]3.305[/C][C]0.00107953[/C][C]0.000539764[/C][/ROW]
[ROW][C]AMS.A_GES[/C][C]0.120528[/C][C]0.105965[/C][C]1.137[/C][C]0.256373[/C][C]0.128187[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267961&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267961&T=2

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-7435.53684.279-10.874.98019e-232.49009e-23
AMS.I0.01648370.02697540.61110.5416760.270838
AMS.E-0.1383260.0377404-3.6650.0002979240.000148962
AMS.A-0.1031080.0840424-1.2270.2209520.110476
Academiejaar3.707340.3400510.93.78315e-231.89157e-23
Type_Opleiding_Binair0.6974480.3344312.0850.03797230.0189862
gender-12.66073.32357-3.8090.0001727998.63996e-05
AMS.I_GES0.01031670.03524970.29270.7699970.384998
AMS.I1_GES0.1569840.04750013.3050.001079530.000539764
AMS.A_GES0.1205280.1059651.1370.2563730.128187







Multiple Linear Regression - Regression Statistics
Multiple R0.610676
R-squared0.372925
Adjusted R-squared0.351867
F-TEST (value)17.709
F-TEST (DF numerator)9
F-TEST (DF denominator)268
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.73269
Sum Squared Residuals2001.31

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.610676 \tabularnewline
R-squared & 0.372925 \tabularnewline
Adjusted R-squared & 0.351867 \tabularnewline
F-TEST (value) & 17.709 \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 & 2.73269 \tabularnewline
Sum Squared Residuals & 2001.31 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267961&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.610676[/C][/ROW]
[ROW][C]R-squared[/C][C]0.372925[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.351867[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]17.709[/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]2.73269[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2001.31[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267961&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267961&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.610676
R-squared0.372925
Adjusted R-squared0.351867
F-TEST (value)17.709
F-TEST (DF numerator)9
F-TEST (DF denominator)268
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.73269
Sum Squared Residuals2001.31







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.7262-0.826184
212.210.71971.48029
312.813.2511-0.451093
47.411.1556-3.75564
56.710.1952-3.49524
612.610.72881.87121
714.810.56084.23916
813.310.27993.02014
911.111.8538-0.753813
108.210.6145-2.41454
1111.410.61480.785215
126.411.1241-4.72409
1310.610.9539-0.353929
141211.07220.927829
156.310.9604-4.66036
1611.39.857231.44277
1711.910.41911.48086
189.311.4542-2.15418
199.610.0116-0.411647
201010.0231-0.0230883
216.411.102-4.70204
2213.811.08082.71919
2310.811.2457-0.445714
2413.810.90632.8937
2511.711.07960.620433
2610.910.76180.138219
2716.110.18655.91352
2813.411.30062.0994
299.911.0006-1.10061
3011.510.57480.925224
318.310.6998-2.3998
3211.711.9796-0.279605
33910.9854-1.98536
349.710.4925-0.792539
3510.810.79650.00348174
3610.310.6299-0.329932
3710.411.4212-1.02121
3812.710.11992.58012
399.310.8045-1.50454
4011.810.47591.32413
415.910.0507-4.15072
4211.410.42250.977466
431310.64412.35594
4410.810.39130.408674
4512.39.406892.89311
4611.312.067-0.766961
4711.810.50161.29841
487.910.2601-2.36008
4912.710.80551.89445
5012.39.772922.52708
5111.610.2381.36197
526.79.923-3.223
5310.910.30720.592809
5412.110.49551.60449
5513.310.87242.42763
5610.110.869-0.768983
575.79.50853-3.80853
5814.310.85333.44669
59811.5437-3.54369
6013.39.799723.50028
619.310.8642-1.56423
6212.511.35111.14893
637.69.38111-1.78111
6415.910.34335.55673
659.212.1693-2.96934
669.19.76096-0.66096
6711.110.79160.308392
681310.72792.27214
6914.510.5173.98304
7012.211.27350.926503
7112.312.3778-0.0778038
7211.412.2017-0.801716
738.811.5213-2.72134
7414.610.15154.44848
7512.610.03442.56561
761311.32911.67094
7712.69.47453.1255
7813.212.17231.02768
799.910.6707-0.770744
807.710.7804-3.08044
8110.511.1947-0.69465
8213.410.32533.07473
8310.910.36470.535304
844.310.2786-5.97863
8510.311.3959-1.09593
8611.810.13861.66136
8711.210.17731.0227
8811.49.765511.63449
898.610.7241-2.12406
9013.210.30882.89121
9112.69.957942.64206
925.69.58377-3.98377
939.910.4907-0.590662
948.810.0217-1.22167
957.79.76117-2.06117
96910.7997-1.79973
977.310.1747-2.87472
9811.410.22131.17868
9913.69.657583.94242
1007.910.4338-2.53377
10110.710.19710.502903
10210.310.09160.208384
1038.39.32083-1.02083
1049.610.3161-0.716054
10514.29.981564.21844
1068.511.3333-2.83327
10713.511.64321.85682
1084.910.2429-5.34285
1096.411.2729-4.87286
1109.611.8633-2.26334
11111.611.01040.589556
11211.110.20410.895898
1134.3514.1226-9.77264
11412.713.2163-0.516283
11518.114.29523.80478
11617.8514.54833.30172
11716.616.19640.403631
11812.613.7905-1.19051
11917.114.10882.99116
12019.116.17922.92075
12116.114.67041.42958
12213.3515.7872-2.43721
12318.417.83590.564121
12414.714.9563-0.256275
12510.614.3304-3.73037
12612.614.5028-1.90282
12716.213.98062.21938
12813.614.4026-0.802625
12918.914.29954.60046
13014.114.3372-0.237167
13114.514.27050.229531
13216.1515.19480.955221
13314.7514.4260.323966
13414.814.73710.0628781
13512.4513.7652-1.31518
13612.6514.6764-2.0264
13717.3514.13223.21775
1388.614.5146-5.91458
13918.414.86643.53357
14016.114.39871.70131
14111.613.3054-1.70542
14217.7514.30833.44168
14315.2515.02360.226421
14417.6514.58913.06089
14516.3515.42170.928315
14617.6517.64810.00189747
14713.614.6693-1.06927
14814.3516.4788-2.12884
14914.7516.5842-1.8342
15018.2514.27753.97253
1519.913.7763-3.87631
1521614.38041.61965
15318.2514.38043.86965
15416.8516.2380.611959
15514.613.97080.629194
15613.8513.9323-0.0822504
15718.9514.85464.09538
15815.614.90360.6964
15914.8516.2911-1.44106
16011.7514.7536-3.00363
16118.4515.06133.3887
16215.913.8872.01299
16317.116.60710.492862
16416.114.47831.62172
16519.916.90932.99072
16610.9513.8605-2.91051
16718.4513.77694.67306
16815.113.75991.34009
1691515.8738-0.873837
17011.3514.1014-2.75138
17115.9514.58861.36143
17218.114.86963.23039
17314.613.86830.731747
17415.414.39531.0047
17515.414.43260.967388
17617.613.88113.71886
17713.3514.0981-0.748116
17819.115.75713.34287
17915.3513.48031.86974
1807.614.6195-7.01947
18113.415.5095-2.10954
18213.915.7406-1.84065
18319.114.37824.7218
18415.2514.22041.02961
18512.913.3316-0.431613
18616.114.9851.11501
18717.3514.70612.64391
18813.1514.392-1.24197
18912.1514.6172-2.46722
19012.613.8438-1.24383
19110.3513.4348-3.0848
19215.414.29241.10757
1939.613.7086-4.10857
19418.214.83993.36008
19513.616.2422-2.64225
19614.8513.45371.39626
19714.7514.753-0.00299733
19814.114.9233-0.823265
19914.915.1457-0.245671
20016.2515.45890.79114
20119.2513.77485.4752
20213.613.6665-0.0665018
20313.615.4711-1.87114
20415.6514.26631.38373
20512.7514.6009-1.85086
20614.614.38810.211892
2079.8514.5414-4.69138
20812.6513.0985-0.448534
20919.213.86785.33223
21016.613.80072.79926
21111.213.7587-2.55868
21215.2514.61240.637602
21311.914.6741-2.77415
21413.213.341-0.140981
21516.3514.46991.88011
21612.414.1492-1.74924
21715.8513.20852.64146
21818.1514.62993.52008
21911.1513.6177-2.46767
22015.6515.07330.57672
22117.7514.08793.66212
2227.6512.6645-5.01447
22312.3514.2813-1.93129
22415.614.44211.15789
22519.314.87294.42712
22615.213.94361.25641
22717.116.17920.920752
22815.614.0491.55105
22918.414.7853.61504
23019.0515.3913.65903
23118.5515.74362.80642
23219.115.9963.10403
23313.114.3335-1.23346
23412.8514.4447-1.59469
2359.514.4399-4.93994
2364.514.47-9.97003
23711.8513.6367-1.78666
23813.614.9163-1.31628
23911.713.1705-1.47048
24012.414.092-1.69204
24113.3515.5471-2.1971
24211.412.4286-1.02861
24314.913.76691.13308
24419.914.73835.16167
24511.213.4579-2.25788
24614.614.02810.571859
24717.616.74550.854536
24814.0514.1351-0.0851257
24916.115.45040.649553
25013.3514.7172-1.36722
25111.8514.6229-2.77292
25211.9515.1143-3.16432
25314.7513.68761.06245
25415.1513.74031.40974
25513.214.2633-1.06326
25616.8515.06681.78318
2577.8513.9267-6.07671
2587.713.4954-5.79545
25912.613.6224-1.02243
2607.8513.2144-5.36441
26110.9513.5272-2.57724
26212.3513.8778-1.5278
2639.9513.4223-3.47231
26414.914.00540.894559
26516.6515.00311.64686
26613.413.4835-0.0835469
26713.9516.7626-2.81258
26815.713.41052.28951
26916.8514.06412.7859
27010.9514.0303-3.08029
27115.3513.96021.38978
27212.213.7042-1.50416
27315.114.34450.755522
27417.7514.63543.11464
27515.213.8661.33402
27614.616.9355-2.33549
27716.6513.92982.7202
2788.113.6556-5.55559

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.7262 & -0.826184 \tabularnewline
2 & 12.2 & 10.7197 & 1.48029 \tabularnewline
3 & 12.8 & 13.2511 & -0.451093 \tabularnewline
4 & 7.4 & 11.1556 & -3.75564 \tabularnewline
5 & 6.7 & 10.1952 & -3.49524 \tabularnewline
6 & 12.6 & 10.7288 & 1.87121 \tabularnewline
7 & 14.8 & 10.5608 & 4.23916 \tabularnewline
8 & 13.3 & 10.2799 & 3.02014 \tabularnewline
9 & 11.1 & 11.8538 & -0.753813 \tabularnewline
10 & 8.2 & 10.6145 & -2.41454 \tabularnewline
11 & 11.4 & 10.6148 & 0.785215 \tabularnewline
12 & 6.4 & 11.1241 & -4.72409 \tabularnewline
13 & 10.6 & 10.9539 & -0.353929 \tabularnewline
14 & 12 & 11.0722 & 0.927829 \tabularnewline
15 & 6.3 & 10.9604 & -4.66036 \tabularnewline
16 & 11.3 & 9.85723 & 1.44277 \tabularnewline
17 & 11.9 & 10.4191 & 1.48086 \tabularnewline
18 & 9.3 & 11.4542 & -2.15418 \tabularnewline
19 & 9.6 & 10.0116 & -0.411647 \tabularnewline
20 & 10 & 10.0231 & -0.0230883 \tabularnewline
21 & 6.4 & 11.102 & -4.70204 \tabularnewline
22 & 13.8 & 11.0808 & 2.71919 \tabularnewline
23 & 10.8 & 11.2457 & -0.445714 \tabularnewline
24 & 13.8 & 10.9063 & 2.8937 \tabularnewline
25 & 11.7 & 11.0796 & 0.620433 \tabularnewline
26 & 10.9 & 10.7618 & 0.138219 \tabularnewline
27 & 16.1 & 10.1865 & 5.91352 \tabularnewline
28 & 13.4 & 11.3006 & 2.0994 \tabularnewline
29 & 9.9 & 11.0006 & -1.10061 \tabularnewline
30 & 11.5 & 10.5748 & 0.925224 \tabularnewline
31 & 8.3 & 10.6998 & -2.3998 \tabularnewline
32 & 11.7 & 11.9796 & -0.279605 \tabularnewline
33 & 9 & 10.9854 & -1.98536 \tabularnewline
34 & 9.7 & 10.4925 & -0.792539 \tabularnewline
35 & 10.8 & 10.7965 & 0.00348174 \tabularnewline
36 & 10.3 & 10.6299 & -0.329932 \tabularnewline
37 & 10.4 & 11.4212 & -1.02121 \tabularnewline
38 & 12.7 & 10.1199 & 2.58012 \tabularnewline
39 & 9.3 & 10.8045 & -1.50454 \tabularnewline
40 & 11.8 & 10.4759 & 1.32413 \tabularnewline
41 & 5.9 & 10.0507 & -4.15072 \tabularnewline
42 & 11.4 & 10.4225 & 0.977466 \tabularnewline
43 & 13 & 10.6441 & 2.35594 \tabularnewline
44 & 10.8 & 10.3913 & 0.408674 \tabularnewline
45 & 12.3 & 9.40689 & 2.89311 \tabularnewline
46 & 11.3 & 12.067 & -0.766961 \tabularnewline
47 & 11.8 & 10.5016 & 1.29841 \tabularnewline
48 & 7.9 & 10.2601 & -2.36008 \tabularnewline
49 & 12.7 & 10.8055 & 1.89445 \tabularnewline
50 & 12.3 & 9.77292 & 2.52708 \tabularnewline
51 & 11.6 & 10.238 & 1.36197 \tabularnewline
52 & 6.7 & 9.923 & -3.223 \tabularnewline
53 & 10.9 & 10.3072 & 0.592809 \tabularnewline
54 & 12.1 & 10.4955 & 1.60449 \tabularnewline
55 & 13.3 & 10.8724 & 2.42763 \tabularnewline
56 & 10.1 & 10.869 & -0.768983 \tabularnewline
57 & 5.7 & 9.50853 & -3.80853 \tabularnewline
58 & 14.3 & 10.8533 & 3.44669 \tabularnewline
59 & 8 & 11.5437 & -3.54369 \tabularnewline
60 & 13.3 & 9.79972 & 3.50028 \tabularnewline
61 & 9.3 & 10.8642 & -1.56423 \tabularnewline
62 & 12.5 & 11.3511 & 1.14893 \tabularnewline
63 & 7.6 & 9.38111 & -1.78111 \tabularnewline
64 & 15.9 & 10.3433 & 5.55673 \tabularnewline
65 & 9.2 & 12.1693 & -2.96934 \tabularnewline
66 & 9.1 & 9.76096 & -0.66096 \tabularnewline
67 & 11.1 & 10.7916 & 0.308392 \tabularnewline
68 & 13 & 10.7279 & 2.27214 \tabularnewline
69 & 14.5 & 10.517 & 3.98304 \tabularnewline
70 & 12.2 & 11.2735 & 0.926503 \tabularnewline
71 & 12.3 & 12.3778 & -0.0778038 \tabularnewline
72 & 11.4 & 12.2017 & -0.801716 \tabularnewline
73 & 8.8 & 11.5213 & -2.72134 \tabularnewline
74 & 14.6 & 10.1515 & 4.44848 \tabularnewline
75 & 12.6 & 10.0344 & 2.56561 \tabularnewline
76 & 13 & 11.3291 & 1.67094 \tabularnewline
77 & 12.6 & 9.4745 & 3.1255 \tabularnewline
78 & 13.2 & 12.1723 & 1.02768 \tabularnewline
79 & 9.9 & 10.6707 & -0.770744 \tabularnewline
80 & 7.7 & 10.7804 & -3.08044 \tabularnewline
81 & 10.5 & 11.1947 & -0.69465 \tabularnewline
82 & 13.4 & 10.3253 & 3.07473 \tabularnewline
83 & 10.9 & 10.3647 & 0.535304 \tabularnewline
84 & 4.3 & 10.2786 & -5.97863 \tabularnewline
85 & 10.3 & 11.3959 & -1.09593 \tabularnewline
86 & 11.8 & 10.1386 & 1.66136 \tabularnewline
87 & 11.2 & 10.1773 & 1.0227 \tabularnewline
88 & 11.4 & 9.76551 & 1.63449 \tabularnewline
89 & 8.6 & 10.7241 & -2.12406 \tabularnewline
90 & 13.2 & 10.3088 & 2.89121 \tabularnewline
91 & 12.6 & 9.95794 & 2.64206 \tabularnewline
92 & 5.6 & 9.58377 & -3.98377 \tabularnewline
93 & 9.9 & 10.4907 & -0.590662 \tabularnewline
94 & 8.8 & 10.0217 & -1.22167 \tabularnewline
95 & 7.7 & 9.76117 & -2.06117 \tabularnewline
96 & 9 & 10.7997 & -1.79973 \tabularnewline
97 & 7.3 & 10.1747 & -2.87472 \tabularnewline
98 & 11.4 & 10.2213 & 1.17868 \tabularnewline
99 & 13.6 & 9.65758 & 3.94242 \tabularnewline
100 & 7.9 & 10.4338 & -2.53377 \tabularnewline
101 & 10.7 & 10.1971 & 0.502903 \tabularnewline
102 & 10.3 & 10.0916 & 0.208384 \tabularnewline
103 & 8.3 & 9.32083 & -1.02083 \tabularnewline
104 & 9.6 & 10.3161 & -0.716054 \tabularnewline
105 & 14.2 & 9.98156 & 4.21844 \tabularnewline
106 & 8.5 & 11.3333 & -2.83327 \tabularnewline
107 & 13.5 & 11.6432 & 1.85682 \tabularnewline
108 & 4.9 & 10.2429 & -5.34285 \tabularnewline
109 & 6.4 & 11.2729 & -4.87286 \tabularnewline
110 & 9.6 & 11.8633 & -2.26334 \tabularnewline
111 & 11.6 & 11.0104 & 0.589556 \tabularnewline
112 & 11.1 & 10.2041 & 0.895898 \tabularnewline
113 & 4.35 & 14.1226 & -9.77264 \tabularnewline
114 & 12.7 & 13.2163 & -0.516283 \tabularnewline
115 & 18.1 & 14.2952 & 3.80478 \tabularnewline
116 & 17.85 & 14.5483 & 3.30172 \tabularnewline
117 & 16.6 & 16.1964 & 0.403631 \tabularnewline
118 & 12.6 & 13.7905 & -1.19051 \tabularnewline
119 & 17.1 & 14.1088 & 2.99116 \tabularnewline
120 & 19.1 & 16.1792 & 2.92075 \tabularnewline
121 & 16.1 & 14.6704 & 1.42958 \tabularnewline
122 & 13.35 & 15.7872 & -2.43721 \tabularnewline
123 & 18.4 & 17.8359 & 0.564121 \tabularnewline
124 & 14.7 & 14.9563 & -0.256275 \tabularnewline
125 & 10.6 & 14.3304 & -3.73037 \tabularnewline
126 & 12.6 & 14.5028 & -1.90282 \tabularnewline
127 & 16.2 & 13.9806 & 2.21938 \tabularnewline
128 & 13.6 & 14.4026 & -0.802625 \tabularnewline
129 & 18.9 & 14.2995 & 4.60046 \tabularnewline
130 & 14.1 & 14.3372 & -0.237167 \tabularnewline
131 & 14.5 & 14.2705 & 0.229531 \tabularnewline
132 & 16.15 & 15.1948 & 0.955221 \tabularnewline
133 & 14.75 & 14.426 & 0.323966 \tabularnewline
134 & 14.8 & 14.7371 & 0.0628781 \tabularnewline
135 & 12.45 & 13.7652 & -1.31518 \tabularnewline
136 & 12.65 & 14.6764 & -2.0264 \tabularnewline
137 & 17.35 & 14.1322 & 3.21775 \tabularnewline
138 & 8.6 & 14.5146 & -5.91458 \tabularnewline
139 & 18.4 & 14.8664 & 3.53357 \tabularnewline
140 & 16.1 & 14.3987 & 1.70131 \tabularnewline
141 & 11.6 & 13.3054 & -1.70542 \tabularnewline
142 & 17.75 & 14.3083 & 3.44168 \tabularnewline
143 & 15.25 & 15.0236 & 0.226421 \tabularnewline
144 & 17.65 & 14.5891 & 3.06089 \tabularnewline
145 & 16.35 & 15.4217 & 0.928315 \tabularnewline
146 & 17.65 & 17.6481 & 0.00189747 \tabularnewline
147 & 13.6 & 14.6693 & -1.06927 \tabularnewline
148 & 14.35 & 16.4788 & -2.12884 \tabularnewline
149 & 14.75 & 16.5842 & -1.8342 \tabularnewline
150 & 18.25 & 14.2775 & 3.97253 \tabularnewline
151 & 9.9 & 13.7763 & -3.87631 \tabularnewline
152 & 16 & 14.3804 & 1.61965 \tabularnewline
153 & 18.25 & 14.3804 & 3.86965 \tabularnewline
154 & 16.85 & 16.238 & 0.611959 \tabularnewline
155 & 14.6 & 13.9708 & 0.629194 \tabularnewline
156 & 13.85 & 13.9323 & -0.0822504 \tabularnewline
157 & 18.95 & 14.8546 & 4.09538 \tabularnewline
158 & 15.6 & 14.9036 & 0.6964 \tabularnewline
159 & 14.85 & 16.2911 & -1.44106 \tabularnewline
160 & 11.75 & 14.7536 & -3.00363 \tabularnewline
161 & 18.45 & 15.0613 & 3.3887 \tabularnewline
162 & 15.9 & 13.887 & 2.01299 \tabularnewline
163 & 17.1 & 16.6071 & 0.492862 \tabularnewline
164 & 16.1 & 14.4783 & 1.62172 \tabularnewline
165 & 19.9 & 16.9093 & 2.99072 \tabularnewline
166 & 10.95 & 13.8605 & -2.91051 \tabularnewline
167 & 18.45 & 13.7769 & 4.67306 \tabularnewline
168 & 15.1 & 13.7599 & 1.34009 \tabularnewline
169 & 15 & 15.8738 & -0.873837 \tabularnewline
170 & 11.35 & 14.1014 & -2.75138 \tabularnewline
171 & 15.95 & 14.5886 & 1.36143 \tabularnewline
172 & 18.1 & 14.8696 & 3.23039 \tabularnewline
173 & 14.6 & 13.8683 & 0.731747 \tabularnewline
174 & 15.4 & 14.3953 & 1.0047 \tabularnewline
175 & 15.4 & 14.4326 & 0.967388 \tabularnewline
176 & 17.6 & 13.8811 & 3.71886 \tabularnewline
177 & 13.35 & 14.0981 & -0.748116 \tabularnewline
178 & 19.1 & 15.7571 & 3.34287 \tabularnewline
179 & 15.35 & 13.4803 & 1.86974 \tabularnewline
180 & 7.6 & 14.6195 & -7.01947 \tabularnewline
181 & 13.4 & 15.5095 & -2.10954 \tabularnewline
182 & 13.9 & 15.7406 & -1.84065 \tabularnewline
183 & 19.1 & 14.3782 & 4.7218 \tabularnewline
184 & 15.25 & 14.2204 & 1.02961 \tabularnewline
185 & 12.9 & 13.3316 & -0.431613 \tabularnewline
186 & 16.1 & 14.985 & 1.11501 \tabularnewline
187 & 17.35 & 14.7061 & 2.64391 \tabularnewline
188 & 13.15 & 14.392 & -1.24197 \tabularnewline
189 & 12.15 & 14.6172 & -2.46722 \tabularnewline
190 & 12.6 & 13.8438 & -1.24383 \tabularnewline
191 & 10.35 & 13.4348 & -3.0848 \tabularnewline
192 & 15.4 & 14.2924 & 1.10757 \tabularnewline
193 & 9.6 & 13.7086 & -4.10857 \tabularnewline
194 & 18.2 & 14.8399 & 3.36008 \tabularnewline
195 & 13.6 & 16.2422 & -2.64225 \tabularnewline
196 & 14.85 & 13.4537 & 1.39626 \tabularnewline
197 & 14.75 & 14.753 & -0.00299733 \tabularnewline
198 & 14.1 & 14.9233 & -0.823265 \tabularnewline
199 & 14.9 & 15.1457 & -0.245671 \tabularnewline
200 & 16.25 & 15.4589 & 0.79114 \tabularnewline
201 & 19.25 & 13.7748 & 5.4752 \tabularnewline
202 & 13.6 & 13.6665 & -0.0665018 \tabularnewline
203 & 13.6 & 15.4711 & -1.87114 \tabularnewline
204 & 15.65 & 14.2663 & 1.38373 \tabularnewline
205 & 12.75 & 14.6009 & -1.85086 \tabularnewline
206 & 14.6 & 14.3881 & 0.211892 \tabularnewline
207 & 9.85 & 14.5414 & -4.69138 \tabularnewline
208 & 12.65 & 13.0985 & -0.448534 \tabularnewline
209 & 19.2 & 13.8678 & 5.33223 \tabularnewline
210 & 16.6 & 13.8007 & 2.79926 \tabularnewline
211 & 11.2 & 13.7587 & -2.55868 \tabularnewline
212 & 15.25 & 14.6124 & 0.637602 \tabularnewline
213 & 11.9 & 14.6741 & -2.77415 \tabularnewline
214 & 13.2 & 13.341 & -0.140981 \tabularnewline
215 & 16.35 & 14.4699 & 1.88011 \tabularnewline
216 & 12.4 & 14.1492 & -1.74924 \tabularnewline
217 & 15.85 & 13.2085 & 2.64146 \tabularnewline
218 & 18.15 & 14.6299 & 3.52008 \tabularnewline
219 & 11.15 & 13.6177 & -2.46767 \tabularnewline
220 & 15.65 & 15.0733 & 0.57672 \tabularnewline
221 & 17.75 & 14.0879 & 3.66212 \tabularnewline
222 & 7.65 & 12.6645 & -5.01447 \tabularnewline
223 & 12.35 & 14.2813 & -1.93129 \tabularnewline
224 & 15.6 & 14.4421 & 1.15789 \tabularnewline
225 & 19.3 & 14.8729 & 4.42712 \tabularnewline
226 & 15.2 & 13.9436 & 1.25641 \tabularnewline
227 & 17.1 & 16.1792 & 0.920752 \tabularnewline
228 & 15.6 & 14.049 & 1.55105 \tabularnewline
229 & 18.4 & 14.785 & 3.61504 \tabularnewline
230 & 19.05 & 15.391 & 3.65903 \tabularnewline
231 & 18.55 & 15.7436 & 2.80642 \tabularnewline
232 & 19.1 & 15.996 & 3.10403 \tabularnewline
233 & 13.1 & 14.3335 & -1.23346 \tabularnewline
234 & 12.85 & 14.4447 & -1.59469 \tabularnewline
235 & 9.5 & 14.4399 & -4.93994 \tabularnewline
236 & 4.5 & 14.47 & -9.97003 \tabularnewline
237 & 11.85 & 13.6367 & -1.78666 \tabularnewline
238 & 13.6 & 14.9163 & -1.31628 \tabularnewline
239 & 11.7 & 13.1705 & -1.47048 \tabularnewline
240 & 12.4 & 14.092 & -1.69204 \tabularnewline
241 & 13.35 & 15.5471 & -2.1971 \tabularnewline
242 & 11.4 & 12.4286 & -1.02861 \tabularnewline
243 & 14.9 & 13.7669 & 1.13308 \tabularnewline
244 & 19.9 & 14.7383 & 5.16167 \tabularnewline
245 & 11.2 & 13.4579 & -2.25788 \tabularnewline
246 & 14.6 & 14.0281 & 0.571859 \tabularnewline
247 & 17.6 & 16.7455 & 0.854536 \tabularnewline
248 & 14.05 & 14.1351 & -0.0851257 \tabularnewline
249 & 16.1 & 15.4504 & 0.649553 \tabularnewline
250 & 13.35 & 14.7172 & -1.36722 \tabularnewline
251 & 11.85 & 14.6229 & -2.77292 \tabularnewline
252 & 11.95 & 15.1143 & -3.16432 \tabularnewline
253 & 14.75 & 13.6876 & 1.06245 \tabularnewline
254 & 15.15 & 13.7403 & 1.40974 \tabularnewline
255 & 13.2 & 14.2633 & -1.06326 \tabularnewline
256 & 16.85 & 15.0668 & 1.78318 \tabularnewline
257 & 7.85 & 13.9267 & -6.07671 \tabularnewline
258 & 7.7 & 13.4954 & -5.79545 \tabularnewline
259 & 12.6 & 13.6224 & -1.02243 \tabularnewline
260 & 7.85 & 13.2144 & -5.36441 \tabularnewline
261 & 10.95 & 13.5272 & -2.57724 \tabularnewline
262 & 12.35 & 13.8778 & -1.5278 \tabularnewline
263 & 9.95 & 13.4223 & -3.47231 \tabularnewline
264 & 14.9 & 14.0054 & 0.894559 \tabularnewline
265 & 16.65 & 15.0031 & 1.64686 \tabularnewline
266 & 13.4 & 13.4835 & -0.0835469 \tabularnewline
267 & 13.95 & 16.7626 & -2.81258 \tabularnewline
268 & 15.7 & 13.4105 & 2.28951 \tabularnewline
269 & 16.85 & 14.0641 & 2.7859 \tabularnewline
270 & 10.95 & 14.0303 & -3.08029 \tabularnewline
271 & 15.35 & 13.9602 & 1.38978 \tabularnewline
272 & 12.2 & 13.7042 & -1.50416 \tabularnewline
273 & 15.1 & 14.3445 & 0.755522 \tabularnewline
274 & 17.75 & 14.6354 & 3.11464 \tabularnewline
275 & 15.2 & 13.866 & 1.33402 \tabularnewline
276 & 14.6 & 16.9355 & -2.33549 \tabularnewline
277 & 16.65 & 13.9298 & 2.7202 \tabularnewline
278 & 8.1 & 13.6556 & -5.55559 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267961&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]13.7262[/C][C]-0.826184[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]10.7197[/C][C]1.48029[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]13.2511[/C][C]-0.451093[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]11.1556[/C][C]-3.75564[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]10.1952[/C][C]-3.49524[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]10.7288[/C][C]1.87121[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]10.5608[/C][C]4.23916[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]10.2799[/C][C]3.02014[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]11.8538[/C][C]-0.753813[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]10.6145[/C][C]-2.41454[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]10.6148[/C][C]0.785215[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]11.1241[/C][C]-4.72409[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]10.9539[/C][C]-0.353929[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]11.0722[/C][C]0.927829[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]10.9604[/C][C]-4.66036[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]9.85723[/C][C]1.44277[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]10.4191[/C][C]1.48086[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]11.4542[/C][C]-2.15418[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]10.0116[/C][C]-0.411647[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]10.0231[/C][C]-0.0230883[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]11.102[/C][C]-4.70204[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]11.0808[/C][C]2.71919[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]11.2457[/C][C]-0.445714[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]10.9063[/C][C]2.8937[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]11.0796[/C][C]0.620433[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]10.7618[/C][C]0.138219[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]10.1865[/C][C]5.91352[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]11.3006[/C][C]2.0994[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.0006[/C][C]-1.10061[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]10.5748[/C][C]0.925224[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]10.6998[/C][C]-2.3998[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]11.9796[/C][C]-0.279605[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]10.9854[/C][C]-1.98536[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]10.4925[/C][C]-0.792539[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]10.7965[/C][C]0.00348174[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]10.6299[/C][C]-0.329932[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]11.4212[/C][C]-1.02121[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]10.1199[/C][C]2.58012[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]10.8045[/C][C]-1.50454[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]10.4759[/C][C]1.32413[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]10.0507[/C][C]-4.15072[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]10.4225[/C][C]0.977466[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]10.6441[/C][C]2.35594[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]10.3913[/C][C]0.408674[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]9.40689[/C][C]2.89311[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]12.067[/C][C]-0.766961[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]10.5016[/C][C]1.29841[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]10.2601[/C][C]-2.36008[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]10.8055[/C][C]1.89445[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]9.77292[/C][C]2.52708[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]10.238[/C][C]1.36197[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]9.923[/C][C]-3.223[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]10.3072[/C][C]0.592809[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]10.4955[/C][C]1.60449[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]10.8724[/C][C]2.42763[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]10.869[/C][C]-0.768983[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]9.50853[/C][C]-3.80853[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]10.8533[/C][C]3.44669[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]11.5437[/C][C]-3.54369[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]9.79972[/C][C]3.50028[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]10.8642[/C][C]-1.56423[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.3511[/C][C]1.14893[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]9.38111[/C][C]-1.78111[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]10.3433[/C][C]5.55673[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]12.1693[/C][C]-2.96934[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]9.76096[/C][C]-0.66096[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]10.7916[/C][C]0.308392[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]10.7279[/C][C]2.27214[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]10.517[/C][C]3.98304[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]11.2735[/C][C]0.926503[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]12.3778[/C][C]-0.0778038[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]12.2017[/C][C]-0.801716[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]11.5213[/C][C]-2.72134[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]10.1515[/C][C]4.44848[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]10.0344[/C][C]2.56561[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]11.3291[/C][C]1.67094[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]9.4745[/C][C]3.1255[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]12.1723[/C][C]1.02768[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]10.6707[/C][C]-0.770744[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]10.7804[/C][C]-3.08044[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]11.1947[/C][C]-0.69465[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]10.3253[/C][C]3.07473[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]10.3647[/C][C]0.535304[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]10.2786[/C][C]-5.97863[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]11.3959[/C][C]-1.09593[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]10.1386[/C][C]1.66136[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]10.1773[/C][C]1.0227[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]9.76551[/C][C]1.63449[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]10.7241[/C][C]-2.12406[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]10.3088[/C][C]2.89121[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]9.95794[/C][C]2.64206[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]9.58377[/C][C]-3.98377[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]10.4907[/C][C]-0.590662[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]10.0217[/C][C]-1.22167[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]9.76117[/C][C]-2.06117[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]10.7997[/C][C]-1.79973[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]10.1747[/C][C]-2.87472[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]10.2213[/C][C]1.17868[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]9.65758[/C][C]3.94242[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]10.4338[/C][C]-2.53377[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]10.1971[/C][C]0.502903[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]10.0916[/C][C]0.208384[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]9.32083[/C][C]-1.02083[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]10.3161[/C][C]-0.716054[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]9.98156[/C][C]4.21844[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]11.3333[/C][C]-2.83327[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]11.6432[/C][C]1.85682[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]10.2429[/C][C]-5.34285[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]11.2729[/C][C]-4.87286[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]11.8633[/C][C]-2.26334[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]11.0104[/C][C]0.589556[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]10.2041[/C][C]0.895898[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]14.1226[/C][C]-9.77264[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]13.2163[/C][C]-0.516283[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]14.2952[/C][C]3.80478[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]14.5483[/C][C]3.30172[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]16.1964[/C][C]0.403631[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]13.7905[/C][C]-1.19051[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]14.1088[/C][C]2.99116[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]16.1792[/C][C]2.92075[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]14.6704[/C][C]1.42958[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]15.7872[/C][C]-2.43721[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]17.8359[/C][C]0.564121[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]14.9563[/C][C]-0.256275[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]14.3304[/C][C]-3.73037[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]14.5028[/C][C]-1.90282[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]13.9806[/C][C]2.21938[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]14.4026[/C][C]-0.802625[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]14.2995[/C][C]4.60046[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]14.3372[/C][C]-0.237167[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]14.2705[/C][C]0.229531[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]15.1948[/C][C]0.955221[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]14.426[/C][C]0.323966[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]14.7371[/C][C]0.0628781[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]13.7652[/C][C]-1.31518[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]14.6764[/C][C]-2.0264[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]14.1322[/C][C]3.21775[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]14.5146[/C][C]-5.91458[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]14.8664[/C][C]3.53357[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]14.3987[/C][C]1.70131[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]13.3054[/C][C]-1.70542[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]14.3083[/C][C]3.44168[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]15.0236[/C][C]0.226421[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]14.5891[/C][C]3.06089[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]15.4217[/C][C]0.928315[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]17.6481[/C][C]0.00189747[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]14.6693[/C][C]-1.06927[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]16.4788[/C][C]-2.12884[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]16.5842[/C][C]-1.8342[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]14.2775[/C][C]3.97253[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]13.7763[/C][C]-3.87631[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]14.3804[/C][C]1.61965[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]14.3804[/C][C]3.86965[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]16.238[/C][C]0.611959[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]13.9708[/C][C]0.629194[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]13.9323[/C][C]-0.0822504[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]14.8546[/C][C]4.09538[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]14.9036[/C][C]0.6964[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]16.2911[/C][C]-1.44106[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]14.7536[/C][C]-3.00363[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]15.0613[/C][C]3.3887[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]13.887[/C][C]2.01299[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]16.6071[/C][C]0.492862[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]14.4783[/C][C]1.62172[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]16.9093[/C][C]2.99072[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]13.8605[/C][C]-2.91051[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]13.7769[/C][C]4.67306[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]13.7599[/C][C]1.34009[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]15.8738[/C][C]-0.873837[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]14.1014[/C][C]-2.75138[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]14.5886[/C][C]1.36143[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]14.8696[/C][C]3.23039[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]13.8683[/C][C]0.731747[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]14.3953[/C][C]1.0047[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]14.4326[/C][C]0.967388[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]13.8811[/C][C]3.71886[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]14.0981[/C][C]-0.748116[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]15.7571[/C][C]3.34287[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]13.4803[/C][C]1.86974[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]14.6195[/C][C]-7.01947[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]15.5095[/C][C]-2.10954[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]15.7406[/C][C]-1.84065[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]14.3782[/C][C]4.7218[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]14.2204[/C][C]1.02961[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]13.3316[/C][C]-0.431613[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]14.985[/C][C]1.11501[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]14.7061[/C][C]2.64391[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]14.392[/C][C]-1.24197[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]14.6172[/C][C]-2.46722[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]13.8438[/C][C]-1.24383[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]13.4348[/C][C]-3.0848[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]14.2924[/C][C]1.10757[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]13.7086[/C][C]-4.10857[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]14.8399[/C][C]3.36008[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]16.2422[/C][C]-2.64225[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]13.4537[/C][C]1.39626[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]14.753[/C][C]-0.00299733[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]14.9233[/C][C]-0.823265[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]15.1457[/C][C]-0.245671[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]15.4589[/C][C]0.79114[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]13.7748[/C][C]5.4752[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]13.6665[/C][C]-0.0665018[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]15.4711[/C][C]-1.87114[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]14.2663[/C][C]1.38373[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]14.6009[/C][C]-1.85086[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]14.3881[/C][C]0.211892[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]14.5414[/C][C]-4.69138[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]13.0985[/C][C]-0.448534[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]13.8678[/C][C]5.33223[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]13.8007[/C][C]2.79926[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]13.7587[/C][C]-2.55868[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]14.6124[/C][C]0.637602[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]14.6741[/C][C]-2.77415[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]13.341[/C][C]-0.140981[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]14.4699[/C][C]1.88011[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]14.1492[/C][C]-1.74924[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]13.2085[/C][C]2.64146[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]14.6299[/C][C]3.52008[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]13.6177[/C][C]-2.46767[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]15.0733[/C][C]0.57672[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]14.0879[/C][C]3.66212[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]12.6645[/C][C]-5.01447[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]14.2813[/C][C]-1.93129[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]14.4421[/C][C]1.15789[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]14.8729[/C][C]4.42712[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]13.9436[/C][C]1.25641[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]16.1792[/C][C]0.920752[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]14.049[/C][C]1.55105[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]14.785[/C][C]3.61504[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]15.391[/C][C]3.65903[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]15.7436[/C][C]2.80642[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]15.996[/C][C]3.10403[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]14.3335[/C][C]-1.23346[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]14.4447[/C][C]-1.59469[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]14.4399[/C][C]-4.93994[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]14.47[/C][C]-9.97003[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]13.6367[/C][C]-1.78666[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]14.9163[/C][C]-1.31628[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]13.1705[/C][C]-1.47048[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]14.092[/C][C]-1.69204[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]15.5471[/C][C]-2.1971[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]12.4286[/C][C]-1.02861[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]13.7669[/C][C]1.13308[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]14.7383[/C][C]5.16167[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]13.4579[/C][C]-2.25788[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]14.0281[/C][C]0.571859[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]16.7455[/C][C]0.854536[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]14.1351[/C][C]-0.0851257[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]15.4504[/C][C]0.649553[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]14.7172[/C][C]-1.36722[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]14.6229[/C][C]-2.77292[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]15.1143[/C][C]-3.16432[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]13.6876[/C][C]1.06245[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]13.7403[/C][C]1.40974[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]14.2633[/C][C]-1.06326[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]15.0668[/C][C]1.78318[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]13.9267[/C][C]-6.07671[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]13.4954[/C][C]-5.79545[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]13.6224[/C][C]-1.02243[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]13.2144[/C][C]-5.36441[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]13.5272[/C][C]-2.57724[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]13.8778[/C][C]-1.5278[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]13.4223[/C][C]-3.47231[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]14.0054[/C][C]0.894559[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]15.0031[/C][C]1.64686[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]13.4835[/C][C]-0.0835469[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]16.7626[/C][C]-2.81258[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]13.4105[/C][C]2.28951[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]14.0641[/C][C]2.7859[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]14.0303[/C][C]-3.08029[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]13.9602[/C][C]1.38978[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]13.7042[/C][C]-1.50416[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]14.3445[/C][C]0.755522[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]14.6354[/C][C]3.11464[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]13.866[/C][C]1.33402[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]16.9355[/C][C]-2.33549[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]13.9298[/C][C]2.7202[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]13.6556[/C][C]-5.55559[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267961&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267961&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.7262-0.826184
212.210.71971.48029
312.813.2511-0.451093
47.411.1556-3.75564
56.710.1952-3.49524
612.610.72881.87121
714.810.56084.23916
813.310.27993.02014
911.111.8538-0.753813
108.210.6145-2.41454
1111.410.61480.785215
126.411.1241-4.72409
1310.610.9539-0.353929
141211.07220.927829
156.310.9604-4.66036
1611.39.857231.44277
1711.910.41911.48086
189.311.4542-2.15418
199.610.0116-0.411647
201010.0231-0.0230883
216.411.102-4.70204
2213.811.08082.71919
2310.811.2457-0.445714
2413.810.90632.8937
2511.711.07960.620433
2610.910.76180.138219
2716.110.18655.91352
2813.411.30062.0994
299.911.0006-1.10061
3011.510.57480.925224
318.310.6998-2.3998
3211.711.9796-0.279605
33910.9854-1.98536
349.710.4925-0.792539
3510.810.79650.00348174
3610.310.6299-0.329932
3710.411.4212-1.02121
3812.710.11992.58012
399.310.8045-1.50454
4011.810.47591.32413
415.910.0507-4.15072
4211.410.42250.977466
431310.64412.35594
4410.810.39130.408674
4512.39.406892.89311
4611.312.067-0.766961
4711.810.50161.29841
487.910.2601-2.36008
4912.710.80551.89445
5012.39.772922.52708
5111.610.2381.36197
526.79.923-3.223
5310.910.30720.592809
5412.110.49551.60449
5513.310.87242.42763
5610.110.869-0.768983
575.79.50853-3.80853
5814.310.85333.44669
59811.5437-3.54369
6013.39.799723.50028
619.310.8642-1.56423
6212.511.35111.14893
637.69.38111-1.78111
6415.910.34335.55673
659.212.1693-2.96934
669.19.76096-0.66096
6711.110.79160.308392
681310.72792.27214
6914.510.5173.98304
7012.211.27350.926503
7112.312.3778-0.0778038
7211.412.2017-0.801716
738.811.5213-2.72134
7414.610.15154.44848
7512.610.03442.56561
761311.32911.67094
7712.69.47453.1255
7813.212.17231.02768
799.910.6707-0.770744
807.710.7804-3.08044
8110.511.1947-0.69465
8213.410.32533.07473
8310.910.36470.535304
844.310.2786-5.97863
8510.311.3959-1.09593
8611.810.13861.66136
8711.210.17731.0227
8811.49.765511.63449
898.610.7241-2.12406
9013.210.30882.89121
9112.69.957942.64206
925.69.58377-3.98377
939.910.4907-0.590662
948.810.0217-1.22167
957.79.76117-2.06117
96910.7997-1.79973
977.310.1747-2.87472
9811.410.22131.17868
9913.69.657583.94242
1007.910.4338-2.53377
10110.710.19710.502903
10210.310.09160.208384
1038.39.32083-1.02083
1049.610.3161-0.716054
10514.29.981564.21844
1068.511.3333-2.83327
10713.511.64321.85682
1084.910.2429-5.34285
1096.411.2729-4.87286
1109.611.8633-2.26334
11111.611.01040.589556
11211.110.20410.895898
1134.3514.1226-9.77264
11412.713.2163-0.516283
11518.114.29523.80478
11617.8514.54833.30172
11716.616.19640.403631
11812.613.7905-1.19051
11917.114.10882.99116
12019.116.17922.92075
12116.114.67041.42958
12213.3515.7872-2.43721
12318.417.83590.564121
12414.714.9563-0.256275
12510.614.3304-3.73037
12612.614.5028-1.90282
12716.213.98062.21938
12813.614.4026-0.802625
12918.914.29954.60046
13014.114.3372-0.237167
13114.514.27050.229531
13216.1515.19480.955221
13314.7514.4260.323966
13414.814.73710.0628781
13512.4513.7652-1.31518
13612.6514.6764-2.0264
13717.3514.13223.21775
1388.614.5146-5.91458
13918.414.86643.53357
14016.114.39871.70131
14111.613.3054-1.70542
14217.7514.30833.44168
14315.2515.02360.226421
14417.6514.58913.06089
14516.3515.42170.928315
14617.6517.64810.00189747
14713.614.6693-1.06927
14814.3516.4788-2.12884
14914.7516.5842-1.8342
15018.2514.27753.97253
1519.913.7763-3.87631
1521614.38041.61965
15318.2514.38043.86965
15416.8516.2380.611959
15514.613.97080.629194
15613.8513.9323-0.0822504
15718.9514.85464.09538
15815.614.90360.6964
15914.8516.2911-1.44106
16011.7514.7536-3.00363
16118.4515.06133.3887
16215.913.8872.01299
16317.116.60710.492862
16416.114.47831.62172
16519.916.90932.99072
16610.9513.8605-2.91051
16718.4513.77694.67306
16815.113.75991.34009
1691515.8738-0.873837
17011.3514.1014-2.75138
17115.9514.58861.36143
17218.114.86963.23039
17314.613.86830.731747
17415.414.39531.0047
17515.414.43260.967388
17617.613.88113.71886
17713.3514.0981-0.748116
17819.115.75713.34287
17915.3513.48031.86974
1807.614.6195-7.01947
18113.415.5095-2.10954
18213.915.7406-1.84065
18319.114.37824.7218
18415.2514.22041.02961
18512.913.3316-0.431613
18616.114.9851.11501
18717.3514.70612.64391
18813.1514.392-1.24197
18912.1514.6172-2.46722
19012.613.8438-1.24383
19110.3513.4348-3.0848
19215.414.29241.10757
1939.613.7086-4.10857
19418.214.83993.36008
19513.616.2422-2.64225
19614.8513.45371.39626
19714.7514.753-0.00299733
19814.114.9233-0.823265
19914.915.1457-0.245671
20016.2515.45890.79114
20119.2513.77485.4752
20213.613.6665-0.0665018
20313.615.4711-1.87114
20415.6514.26631.38373
20512.7514.6009-1.85086
20614.614.38810.211892
2079.8514.5414-4.69138
20812.6513.0985-0.448534
20919.213.86785.33223
21016.613.80072.79926
21111.213.7587-2.55868
21215.2514.61240.637602
21311.914.6741-2.77415
21413.213.341-0.140981
21516.3514.46991.88011
21612.414.1492-1.74924
21715.8513.20852.64146
21818.1514.62993.52008
21911.1513.6177-2.46767
22015.6515.07330.57672
22117.7514.08793.66212
2227.6512.6645-5.01447
22312.3514.2813-1.93129
22415.614.44211.15789
22519.314.87294.42712
22615.213.94361.25641
22717.116.17920.920752
22815.614.0491.55105
22918.414.7853.61504
23019.0515.3913.65903
23118.5515.74362.80642
23219.115.9963.10403
23313.114.3335-1.23346
23412.8514.4447-1.59469
2359.514.4399-4.93994
2364.514.47-9.97003
23711.8513.6367-1.78666
23813.614.9163-1.31628
23911.713.1705-1.47048
24012.414.092-1.69204
24113.3515.5471-2.1971
24211.412.4286-1.02861
24314.913.76691.13308
24419.914.73835.16167
24511.213.4579-2.25788
24614.614.02810.571859
24717.616.74550.854536
24814.0514.1351-0.0851257
24916.115.45040.649553
25013.3514.7172-1.36722
25111.8514.6229-2.77292
25211.9515.1143-3.16432
25314.7513.68761.06245
25415.1513.74031.40974
25513.214.2633-1.06326
25616.8515.06681.78318
2577.8513.9267-6.07671
2587.713.4954-5.79545
25912.613.6224-1.02243
2607.8513.2144-5.36441
26110.9513.5272-2.57724
26212.3513.8778-1.5278
2639.9513.4223-3.47231
26414.914.00540.894559
26516.6515.00311.64686
26613.413.4835-0.0835469
26713.9516.7626-2.81258
26815.713.41052.28951
26916.8514.06412.7859
27010.9514.0303-3.08029
27115.3513.96021.38978
27212.213.7042-1.50416
27315.114.34450.755522
27417.7514.63543.11464
27515.213.8661.33402
27614.616.9355-2.33549
27716.6513.92982.7202
2788.113.6556-5.55559







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.7312070.5375860.268793
140.5840320.8319370.415968
150.5469560.9060880.453044
160.4172360.8344720.582764
170.4116760.8233530.588324
180.3163150.632630.683685
190.2273520.4547040.772648
200.1763620.3527230.823638
210.2021610.4043220.797839
220.1893180.3786360.810682
230.1354390.2708780.864561
240.2280070.4560140.771993
250.1730690.3461380.826931
260.1296920.2593840.870308
270.2255920.4511830.774408
280.192880.3857610.80712
290.1489530.2979050.851047
300.1273060.2546130.872694
310.2961880.5923770.703812
320.2445570.4891140.755443
330.2483180.4966360.751682
340.2109670.4219340.789033
350.179010.3580210.82099
360.1420280.2840560.857972
370.1108620.2217230.889138
380.08842520.176850.911575
390.07038560.1407710.929614
400.05806680.1161340.941933
410.06813310.1362660.931867
420.06537690.1307540.934623
430.07281720.1456340.927183
440.05619430.1123890.943806
450.04566210.09132420.954338
460.03496010.06992030.96504
470.02743120.05486230.972569
480.0294110.05882210.970589
490.02867310.05734620.971327
500.02529270.05058550.974707
510.01886190.03772380.981138
520.05084670.1016930.949153
530.04100890.08201780.958991
540.03506950.07013910.96493
550.04672780.09345560.953272
560.03616790.07233580.963832
570.06387990.127760.93612
580.0559340.1118680.944066
590.06309620.1261920.936904
600.07399530.1479910.926005
610.06065730.1213150.939343
620.0527130.1054260.947287
630.04778240.09556490.952218
640.09471260.1894250.905287
650.0972970.1945940.902703
660.0991560.1983120.900844
670.08147510.162950.918525
680.08535790.1707160.914642
690.09967670.1993530.900323
700.08793220.1758640.912068
710.07234840.1446970.927652
720.05899520.117990.941005
730.05908290.1181660.940917
740.09932230.1986450.900678
750.1013320.2026640.898668
760.09520690.1904140.904793
770.09097390.1819480.909026
780.08023740.1604750.919763
790.0675570.1351140.932443
800.0729480.1458960.927052
810.06084130.1216830.939159
820.06186140.1237230.938139
830.05085570.1017110.949144
840.1262550.252510.873745
850.1078790.2157570.892121
860.09448210.1889640.905518
870.0815830.1631660.918417
880.07081840.1416370.929182
890.06609750.1321950.933902
900.06637690.1327540.933623
910.06167340.1233470.938327
920.1199170.2398340.880083
930.102390.204780.89761
940.08717010.174340.91283
950.08487330.1697470.915127
960.07785530.1557110.922145
970.08270340.1654070.917297
980.07107810.1421560.928922
990.0848390.1696780.915161
1000.07995980.159920.92004
1010.0679140.1358280.932086
1020.05724310.1144860.942757
1030.05406910.1081380.945931
1040.0447890.08957810.955211
1050.06598360.1319670.934016
1060.06108880.1221780.938911
1070.06407450.1281490.935926
1080.09642220.1928440.903578
1090.1229950.245990.877005
1100.113750.22750.88625
1110.09874610.1974920.901254
1120.08514360.1702870.914856
1130.1484920.2969840.851508
1140.1842210.3684430.815779
1150.3224520.6449030.677548
1160.3870290.7740590.612971
1170.3711170.7422340.628883
1180.3436030.6872060.656397
1190.3664780.7329550.633522
1200.3805890.7611780.619411
1210.3535730.7071460.646427
1220.3452920.6905840.654708
1230.3204880.6409760.679512
1240.2901110.5802220.709889
1250.3145610.6291220.685439
1260.2965760.5931530.703424
1270.290530.5810610.70947
1280.2621390.5242790.737861
1290.319940.6398790.68006
1300.2895980.5791970.710402
1310.2606610.5213210.739339
1320.2365890.4731790.763411
1330.211910.423820.78809
1340.1871810.3743620.812819
1350.1705360.3410720.829464
1360.1602530.3205060.839747
1370.1735760.3471530.826424
1380.2649460.5298920.735054
1390.2862030.5724060.713797
1400.268160.536320.73184
1410.2566190.5132370.743381
1420.2798870.5597730.720113
1430.2511830.5023660.748817
1440.26190.5237990.7381
1450.2370890.4741780.762911
1460.2127210.4254420.787279
1470.1976110.3952220.802389
1480.188270.376540.81173
1490.1762260.3524530.823774
1500.2042940.4085870.795706
1510.2319330.4638660.768067
1520.2154020.4308050.784598
1530.2443530.4887060.755647
1540.2198090.4396170.780191
1550.1950170.3900330.804983
1560.1721810.3443610.827819
1570.1923030.3846060.807697
1580.170080.3401610.82992
1590.1559950.311990.844005
1600.1655430.3310860.834457
1610.1734710.3469430.826529
1620.1637650.3275290.836235
1630.1436270.2872550.856373
1640.1316960.2633910.868304
1650.1321640.2643270.867836
1660.1385650.277130.861435
1670.1703610.3407230.829639
1680.1557430.3114870.844257
1690.138750.2775010.86125
1700.142340.2846790.85766
1710.1248140.2496270.875186
1720.1271950.254390.872805
1730.1116960.2233920.888304
1740.09865270.1973050.901347
1750.0868270.1736540.913173
1760.1028680.2057350.897132
1770.08871210.1774240.911288
1780.09414180.1882840.905858
1790.09263140.1852630.907369
1800.2149120.4298240.785088
1810.2100830.4201650.789917
1820.2019880.4039750.798012
1830.2963730.5927460.703627
1840.2667610.5335220.733239
1850.2393890.4787780.760611
1860.2134010.4268020.786599
1870.2050890.4101780.794911
1880.1877060.3754130.812294
1890.1917630.3835250.808237
1900.1726530.3453070.827347
1910.1695320.3390650.830468
1920.1504130.3008250.849587
1930.1711180.3422370.828882
1940.1743620.3487250.825638
1950.18790.37580.8121
1960.169010.338020.83099
1970.1457810.2915620.854219
1980.1308740.2617470.869126
1990.1139940.2279880.886006
2000.09647070.1929410.903529
2010.1710080.3420160.828992
2020.1498520.2997050.850148
2030.1404840.2809680.859516
2040.1212390.2424770.878761
2050.10780.2155990.8922
2060.09116630.1823330.908834
2070.1135970.2271930.886403
2080.1019060.2038110.898094
2090.149690.299380.85031
2100.1577590.3155180.842241
2110.1464480.2928970.853552
2120.1287010.2574010.871299
2130.129790.259580.87021
2140.1088410.2176820.891159
2150.09863150.1972630.901369
2160.08444810.1688960.915552
2170.1062650.212530.893735
2180.1346320.2692640.865368
2190.1197010.2394030.880299
2200.0992990.1985980.900701
2210.1268560.2537130.873144
2220.2086060.4172110.791394
2230.1818540.3637070.818146
2240.1864010.3728020.813599
2250.2627710.5255410.737229
2260.2396760.4793530.760324
2270.2054770.4109540.794523
2280.1914070.3828130.808593
2290.2956150.591230.704385
2300.3806310.7612620.619369
2310.3724290.7448580.627571
2320.4103220.8206440.589678
2330.3653860.7307720.634614
2340.3395660.6791310.660434
2350.3345340.6690670.665466
2360.7393070.5213860.260693
2370.7286690.5426630.271331
2380.6866640.6266730.313336
2390.672460.6550790.32754
2400.6479350.704130.352065
2410.6509380.6981240.349062
2420.6483460.7033080.351654
2430.622530.7549390.37747
2440.5849190.8301610.415081
2450.5281990.9436030.471801
2460.4820810.9641630.517919
2470.4659480.9318960.534052
2480.5640650.8718710.435935
2490.4992810.9985630.500719
2500.4390240.8780470.560976
2510.382320.7646410.61768
2520.32220.64440.6778
2530.3353440.6706890.664656
2540.3308280.6616570.669172
2550.7331750.5336510.266825
2560.666540.6669190.33346
2570.8322720.3354550.167728
2580.8527120.2945770.147288
2590.8401010.3197980.159899
2600.8902430.2195130.109757
2610.8473310.3053380.152669
2620.8077650.384470.192235
2630.7012390.5975220.298761
2640.654750.6905010.34525
2650.5071080.9857850.492892

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.731207 & 0.537586 & 0.268793 \tabularnewline
14 & 0.584032 & 0.831937 & 0.415968 \tabularnewline
15 & 0.546956 & 0.906088 & 0.453044 \tabularnewline
16 & 0.417236 & 0.834472 & 0.582764 \tabularnewline
17 & 0.411676 & 0.823353 & 0.588324 \tabularnewline
18 & 0.316315 & 0.63263 & 0.683685 \tabularnewline
19 & 0.227352 & 0.454704 & 0.772648 \tabularnewline
20 & 0.176362 & 0.352723 & 0.823638 \tabularnewline
21 & 0.202161 & 0.404322 & 0.797839 \tabularnewline
22 & 0.189318 & 0.378636 & 0.810682 \tabularnewline
23 & 0.135439 & 0.270878 & 0.864561 \tabularnewline
24 & 0.228007 & 0.456014 & 0.771993 \tabularnewline
25 & 0.173069 & 0.346138 & 0.826931 \tabularnewline
26 & 0.129692 & 0.259384 & 0.870308 \tabularnewline
27 & 0.225592 & 0.451183 & 0.774408 \tabularnewline
28 & 0.19288 & 0.385761 & 0.80712 \tabularnewline
29 & 0.148953 & 0.297905 & 0.851047 \tabularnewline
30 & 0.127306 & 0.254613 & 0.872694 \tabularnewline
31 & 0.296188 & 0.592377 & 0.703812 \tabularnewline
32 & 0.244557 & 0.489114 & 0.755443 \tabularnewline
33 & 0.248318 & 0.496636 & 0.751682 \tabularnewline
34 & 0.210967 & 0.421934 & 0.789033 \tabularnewline
35 & 0.17901 & 0.358021 & 0.82099 \tabularnewline
36 & 0.142028 & 0.284056 & 0.857972 \tabularnewline
37 & 0.110862 & 0.221723 & 0.889138 \tabularnewline
38 & 0.0884252 & 0.17685 & 0.911575 \tabularnewline
39 & 0.0703856 & 0.140771 & 0.929614 \tabularnewline
40 & 0.0580668 & 0.116134 & 0.941933 \tabularnewline
41 & 0.0681331 & 0.136266 & 0.931867 \tabularnewline
42 & 0.0653769 & 0.130754 & 0.934623 \tabularnewline
43 & 0.0728172 & 0.145634 & 0.927183 \tabularnewline
44 & 0.0561943 & 0.112389 & 0.943806 \tabularnewline
45 & 0.0456621 & 0.0913242 & 0.954338 \tabularnewline
46 & 0.0349601 & 0.0699203 & 0.96504 \tabularnewline
47 & 0.0274312 & 0.0548623 & 0.972569 \tabularnewline
48 & 0.029411 & 0.0588221 & 0.970589 \tabularnewline
49 & 0.0286731 & 0.0573462 & 0.971327 \tabularnewline
50 & 0.0252927 & 0.0505855 & 0.974707 \tabularnewline
51 & 0.0188619 & 0.0377238 & 0.981138 \tabularnewline
52 & 0.0508467 & 0.101693 & 0.949153 \tabularnewline
53 & 0.0410089 & 0.0820178 & 0.958991 \tabularnewline
54 & 0.0350695 & 0.0701391 & 0.96493 \tabularnewline
55 & 0.0467278 & 0.0934556 & 0.953272 \tabularnewline
56 & 0.0361679 & 0.0723358 & 0.963832 \tabularnewline
57 & 0.0638799 & 0.12776 & 0.93612 \tabularnewline
58 & 0.055934 & 0.111868 & 0.944066 \tabularnewline
59 & 0.0630962 & 0.126192 & 0.936904 \tabularnewline
60 & 0.0739953 & 0.147991 & 0.926005 \tabularnewline
61 & 0.0606573 & 0.121315 & 0.939343 \tabularnewline
62 & 0.052713 & 0.105426 & 0.947287 \tabularnewline
63 & 0.0477824 & 0.0955649 & 0.952218 \tabularnewline
64 & 0.0947126 & 0.189425 & 0.905287 \tabularnewline
65 & 0.097297 & 0.194594 & 0.902703 \tabularnewline
66 & 0.099156 & 0.198312 & 0.900844 \tabularnewline
67 & 0.0814751 & 0.16295 & 0.918525 \tabularnewline
68 & 0.0853579 & 0.170716 & 0.914642 \tabularnewline
69 & 0.0996767 & 0.199353 & 0.900323 \tabularnewline
70 & 0.0879322 & 0.175864 & 0.912068 \tabularnewline
71 & 0.0723484 & 0.144697 & 0.927652 \tabularnewline
72 & 0.0589952 & 0.11799 & 0.941005 \tabularnewline
73 & 0.0590829 & 0.118166 & 0.940917 \tabularnewline
74 & 0.0993223 & 0.198645 & 0.900678 \tabularnewline
75 & 0.101332 & 0.202664 & 0.898668 \tabularnewline
76 & 0.0952069 & 0.190414 & 0.904793 \tabularnewline
77 & 0.0909739 & 0.181948 & 0.909026 \tabularnewline
78 & 0.0802374 & 0.160475 & 0.919763 \tabularnewline
79 & 0.067557 & 0.135114 & 0.932443 \tabularnewline
80 & 0.072948 & 0.145896 & 0.927052 \tabularnewline
81 & 0.0608413 & 0.121683 & 0.939159 \tabularnewline
82 & 0.0618614 & 0.123723 & 0.938139 \tabularnewline
83 & 0.0508557 & 0.101711 & 0.949144 \tabularnewline
84 & 0.126255 & 0.25251 & 0.873745 \tabularnewline
85 & 0.107879 & 0.215757 & 0.892121 \tabularnewline
86 & 0.0944821 & 0.188964 & 0.905518 \tabularnewline
87 & 0.081583 & 0.163166 & 0.918417 \tabularnewline
88 & 0.0708184 & 0.141637 & 0.929182 \tabularnewline
89 & 0.0660975 & 0.132195 & 0.933902 \tabularnewline
90 & 0.0663769 & 0.132754 & 0.933623 \tabularnewline
91 & 0.0616734 & 0.123347 & 0.938327 \tabularnewline
92 & 0.119917 & 0.239834 & 0.880083 \tabularnewline
93 & 0.10239 & 0.20478 & 0.89761 \tabularnewline
94 & 0.0871701 & 0.17434 & 0.91283 \tabularnewline
95 & 0.0848733 & 0.169747 & 0.915127 \tabularnewline
96 & 0.0778553 & 0.155711 & 0.922145 \tabularnewline
97 & 0.0827034 & 0.165407 & 0.917297 \tabularnewline
98 & 0.0710781 & 0.142156 & 0.928922 \tabularnewline
99 & 0.084839 & 0.169678 & 0.915161 \tabularnewline
100 & 0.0799598 & 0.15992 & 0.92004 \tabularnewline
101 & 0.067914 & 0.135828 & 0.932086 \tabularnewline
102 & 0.0572431 & 0.114486 & 0.942757 \tabularnewline
103 & 0.0540691 & 0.108138 & 0.945931 \tabularnewline
104 & 0.044789 & 0.0895781 & 0.955211 \tabularnewline
105 & 0.0659836 & 0.131967 & 0.934016 \tabularnewline
106 & 0.0610888 & 0.122178 & 0.938911 \tabularnewline
107 & 0.0640745 & 0.128149 & 0.935926 \tabularnewline
108 & 0.0964222 & 0.192844 & 0.903578 \tabularnewline
109 & 0.122995 & 0.24599 & 0.877005 \tabularnewline
110 & 0.11375 & 0.2275 & 0.88625 \tabularnewline
111 & 0.0987461 & 0.197492 & 0.901254 \tabularnewline
112 & 0.0851436 & 0.170287 & 0.914856 \tabularnewline
113 & 0.148492 & 0.296984 & 0.851508 \tabularnewline
114 & 0.184221 & 0.368443 & 0.815779 \tabularnewline
115 & 0.322452 & 0.644903 & 0.677548 \tabularnewline
116 & 0.387029 & 0.774059 & 0.612971 \tabularnewline
117 & 0.371117 & 0.742234 & 0.628883 \tabularnewline
118 & 0.343603 & 0.687206 & 0.656397 \tabularnewline
119 & 0.366478 & 0.732955 & 0.633522 \tabularnewline
120 & 0.380589 & 0.761178 & 0.619411 \tabularnewline
121 & 0.353573 & 0.707146 & 0.646427 \tabularnewline
122 & 0.345292 & 0.690584 & 0.654708 \tabularnewline
123 & 0.320488 & 0.640976 & 0.679512 \tabularnewline
124 & 0.290111 & 0.580222 & 0.709889 \tabularnewline
125 & 0.314561 & 0.629122 & 0.685439 \tabularnewline
126 & 0.296576 & 0.593153 & 0.703424 \tabularnewline
127 & 0.29053 & 0.581061 & 0.70947 \tabularnewline
128 & 0.262139 & 0.524279 & 0.737861 \tabularnewline
129 & 0.31994 & 0.639879 & 0.68006 \tabularnewline
130 & 0.289598 & 0.579197 & 0.710402 \tabularnewline
131 & 0.260661 & 0.521321 & 0.739339 \tabularnewline
132 & 0.236589 & 0.473179 & 0.763411 \tabularnewline
133 & 0.21191 & 0.42382 & 0.78809 \tabularnewline
134 & 0.187181 & 0.374362 & 0.812819 \tabularnewline
135 & 0.170536 & 0.341072 & 0.829464 \tabularnewline
136 & 0.160253 & 0.320506 & 0.839747 \tabularnewline
137 & 0.173576 & 0.347153 & 0.826424 \tabularnewline
138 & 0.264946 & 0.529892 & 0.735054 \tabularnewline
139 & 0.286203 & 0.572406 & 0.713797 \tabularnewline
140 & 0.26816 & 0.53632 & 0.73184 \tabularnewline
141 & 0.256619 & 0.513237 & 0.743381 \tabularnewline
142 & 0.279887 & 0.559773 & 0.720113 \tabularnewline
143 & 0.251183 & 0.502366 & 0.748817 \tabularnewline
144 & 0.2619 & 0.523799 & 0.7381 \tabularnewline
145 & 0.237089 & 0.474178 & 0.762911 \tabularnewline
146 & 0.212721 & 0.425442 & 0.787279 \tabularnewline
147 & 0.197611 & 0.395222 & 0.802389 \tabularnewline
148 & 0.18827 & 0.37654 & 0.81173 \tabularnewline
149 & 0.176226 & 0.352453 & 0.823774 \tabularnewline
150 & 0.204294 & 0.408587 & 0.795706 \tabularnewline
151 & 0.231933 & 0.463866 & 0.768067 \tabularnewline
152 & 0.215402 & 0.430805 & 0.784598 \tabularnewline
153 & 0.244353 & 0.488706 & 0.755647 \tabularnewline
154 & 0.219809 & 0.439617 & 0.780191 \tabularnewline
155 & 0.195017 & 0.390033 & 0.804983 \tabularnewline
156 & 0.172181 & 0.344361 & 0.827819 \tabularnewline
157 & 0.192303 & 0.384606 & 0.807697 \tabularnewline
158 & 0.17008 & 0.340161 & 0.82992 \tabularnewline
159 & 0.155995 & 0.31199 & 0.844005 \tabularnewline
160 & 0.165543 & 0.331086 & 0.834457 \tabularnewline
161 & 0.173471 & 0.346943 & 0.826529 \tabularnewline
162 & 0.163765 & 0.327529 & 0.836235 \tabularnewline
163 & 0.143627 & 0.287255 & 0.856373 \tabularnewline
164 & 0.131696 & 0.263391 & 0.868304 \tabularnewline
165 & 0.132164 & 0.264327 & 0.867836 \tabularnewline
166 & 0.138565 & 0.27713 & 0.861435 \tabularnewline
167 & 0.170361 & 0.340723 & 0.829639 \tabularnewline
168 & 0.155743 & 0.311487 & 0.844257 \tabularnewline
169 & 0.13875 & 0.277501 & 0.86125 \tabularnewline
170 & 0.14234 & 0.284679 & 0.85766 \tabularnewline
171 & 0.124814 & 0.249627 & 0.875186 \tabularnewline
172 & 0.127195 & 0.25439 & 0.872805 \tabularnewline
173 & 0.111696 & 0.223392 & 0.888304 \tabularnewline
174 & 0.0986527 & 0.197305 & 0.901347 \tabularnewline
175 & 0.086827 & 0.173654 & 0.913173 \tabularnewline
176 & 0.102868 & 0.205735 & 0.897132 \tabularnewline
177 & 0.0887121 & 0.177424 & 0.911288 \tabularnewline
178 & 0.0941418 & 0.188284 & 0.905858 \tabularnewline
179 & 0.0926314 & 0.185263 & 0.907369 \tabularnewline
180 & 0.214912 & 0.429824 & 0.785088 \tabularnewline
181 & 0.210083 & 0.420165 & 0.789917 \tabularnewline
182 & 0.201988 & 0.403975 & 0.798012 \tabularnewline
183 & 0.296373 & 0.592746 & 0.703627 \tabularnewline
184 & 0.266761 & 0.533522 & 0.733239 \tabularnewline
185 & 0.239389 & 0.478778 & 0.760611 \tabularnewline
186 & 0.213401 & 0.426802 & 0.786599 \tabularnewline
187 & 0.205089 & 0.410178 & 0.794911 \tabularnewline
188 & 0.187706 & 0.375413 & 0.812294 \tabularnewline
189 & 0.191763 & 0.383525 & 0.808237 \tabularnewline
190 & 0.172653 & 0.345307 & 0.827347 \tabularnewline
191 & 0.169532 & 0.339065 & 0.830468 \tabularnewline
192 & 0.150413 & 0.300825 & 0.849587 \tabularnewline
193 & 0.171118 & 0.342237 & 0.828882 \tabularnewline
194 & 0.174362 & 0.348725 & 0.825638 \tabularnewline
195 & 0.1879 & 0.3758 & 0.8121 \tabularnewline
196 & 0.16901 & 0.33802 & 0.83099 \tabularnewline
197 & 0.145781 & 0.291562 & 0.854219 \tabularnewline
198 & 0.130874 & 0.261747 & 0.869126 \tabularnewline
199 & 0.113994 & 0.227988 & 0.886006 \tabularnewline
200 & 0.0964707 & 0.192941 & 0.903529 \tabularnewline
201 & 0.171008 & 0.342016 & 0.828992 \tabularnewline
202 & 0.149852 & 0.299705 & 0.850148 \tabularnewline
203 & 0.140484 & 0.280968 & 0.859516 \tabularnewline
204 & 0.121239 & 0.242477 & 0.878761 \tabularnewline
205 & 0.1078 & 0.215599 & 0.8922 \tabularnewline
206 & 0.0911663 & 0.182333 & 0.908834 \tabularnewline
207 & 0.113597 & 0.227193 & 0.886403 \tabularnewline
208 & 0.101906 & 0.203811 & 0.898094 \tabularnewline
209 & 0.14969 & 0.29938 & 0.85031 \tabularnewline
210 & 0.157759 & 0.315518 & 0.842241 \tabularnewline
211 & 0.146448 & 0.292897 & 0.853552 \tabularnewline
212 & 0.128701 & 0.257401 & 0.871299 \tabularnewline
213 & 0.12979 & 0.25958 & 0.87021 \tabularnewline
214 & 0.108841 & 0.217682 & 0.891159 \tabularnewline
215 & 0.0986315 & 0.197263 & 0.901369 \tabularnewline
216 & 0.0844481 & 0.168896 & 0.915552 \tabularnewline
217 & 0.106265 & 0.21253 & 0.893735 \tabularnewline
218 & 0.134632 & 0.269264 & 0.865368 \tabularnewline
219 & 0.119701 & 0.239403 & 0.880299 \tabularnewline
220 & 0.099299 & 0.198598 & 0.900701 \tabularnewline
221 & 0.126856 & 0.253713 & 0.873144 \tabularnewline
222 & 0.208606 & 0.417211 & 0.791394 \tabularnewline
223 & 0.181854 & 0.363707 & 0.818146 \tabularnewline
224 & 0.186401 & 0.372802 & 0.813599 \tabularnewline
225 & 0.262771 & 0.525541 & 0.737229 \tabularnewline
226 & 0.239676 & 0.479353 & 0.760324 \tabularnewline
227 & 0.205477 & 0.410954 & 0.794523 \tabularnewline
228 & 0.191407 & 0.382813 & 0.808593 \tabularnewline
229 & 0.295615 & 0.59123 & 0.704385 \tabularnewline
230 & 0.380631 & 0.761262 & 0.619369 \tabularnewline
231 & 0.372429 & 0.744858 & 0.627571 \tabularnewline
232 & 0.410322 & 0.820644 & 0.589678 \tabularnewline
233 & 0.365386 & 0.730772 & 0.634614 \tabularnewline
234 & 0.339566 & 0.679131 & 0.660434 \tabularnewline
235 & 0.334534 & 0.669067 & 0.665466 \tabularnewline
236 & 0.739307 & 0.521386 & 0.260693 \tabularnewline
237 & 0.728669 & 0.542663 & 0.271331 \tabularnewline
238 & 0.686664 & 0.626673 & 0.313336 \tabularnewline
239 & 0.67246 & 0.655079 & 0.32754 \tabularnewline
240 & 0.647935 & 0.70413 & 0.352065 \tabularnewline
241 & 0.650938 & 0.698124 & 0.349062 \tabularnewline
242 & 0.648346 & 0.703308 & 0.351654 \tabularnewline
243 & 0.62253 & 0.754939 & 0.37747 \tabularnewline
244 & 0.584919 & 0.830161 & 0.415081 \tabularnewline
245 & 0.528199 & 0.943603 & 0.471801 \tabularnewline
246 & 0.482081 & 0.964163 & 0.517919 \tabularnewline
247 & 0.465948 & 0.931896 & 0.534052 \tabularnewline
248 & 0.564065 & 0.871871 & 0.435935 \tabularnewline
249 & 0.499281 & 0.998563 & 0.500719 \tabularnewline
250 & 0.439024 & 0.878047 & 0.560976 \tabularnewline
251 & 0.38232 & 0.764641 & 0.61768 \tabularnewline
252 & 0.3222 & 0.6444 & 0.6778 \tabularnewline
253 & 0.335344 & 0.670689 & 0.664656 \tabularnewline
254 & 0.330828 & 0.661657 & 0.669172 \tabularnewline
255 & 0.733175 & 0.533651 & 0.266825 \tabularnewline
256 & 0.66654 & 0.666919 & 0.33346 \tabularnewline
257 & 0.832272 & 0.335455 & 0.167728 \tabularnewline
258 & 0.852712 & 0.294577 & 0.147288 \tabularnewline
259 & 0.840101 & 0.319798 & 0.159899 \tabularnewline
260 & 0.890243 & 0.219513 & 0.109757 \tabularnewline
261 & 0.847331 & 0.305338 & 0.152669 \tabularnewline
262 & 0.807765 & 0.38447 & 0.192235 \tabularnewline
263 & 0.701239 & 0.597522 & 0.298761 \tabularnewline
264 & 0.65475 & 0.690501 & 0.34525 \tabularnewline
265 & 0.507108 & 0.985785 & 0.492892 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267961&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]0.731207[/C][C]0.537586[/C][C]0.268793[/C][/ROW]
[ROW][C]14[/C][C]0.584032[/C][C]0.831937[/C][C]0.415968[/C][/ROW]
[ROW][C]15[/C][C]0.546956[/C][C]0.906088[/C][C]0.453044[/C][/ROW]
[ROW][C]16[/C][C]0.417236[/C][C]0.834472[/C][C]0.582764[/C][/ROW]
[ROW][C]17[/C][C]0.411676[/C][C]0.823353[/C][C]0.588324[/C][/ROW]
[ROW][C]18[/C][C]0.316315[/C][C]0.63263[/C][C]0.683685[/C][/ROW]
[ROW][C]19[/C][C]0.227352[/C][C]0.454704[/C][C]0.772648[/C][/ROW]
[ROW][C]20[/C][C]0.176362[/C][C]0.352723[/C][C]0.823638[/C][/ROW]
[ROW][C]21[/C][C]0.202161[/C][C]0.404322[/C][C]0.797839[/C][/ROW]
[ROW][C]22[/C][C]0.189318[/C][C]0.378636[/C][C]0.810682[/C][/ROW]
[ROW][C]23[/C][C]0.135439[/C][C]0.270878[/C][C]0.864561[/C][/ROW]
[ROW][C]24[/C][C]0.228007[/C][C]0.456014[/C][C]0.771993[/C][/ROW]
[ROW][C]25[/C][C]0.173069[/C][C]0.346138[/C][C]0.826931[/C][/ROW]
[ROW][C]26[/C][C]0.129692[/C][C]0.259384[/C][C]0.870308[/C][/ROW]
[ROW][C]27[/C][C]0.225592[/C][C]0.451183[/C][C]0.774408[/C][/ROW]
[ROW][C]28[/C][C]0.19288[/C][C]0.385761[/C][C]0.80712[/C][/ROW]
[ROW][C]29[/C][C]0.148953[/C][C]0.297905[/C][C]0.851047[/C][/ROW]
[ROW][C]30[/C][C]0.127306[/C][C]0.254613[/C][C]0.872694[/C][/ROW]
[ROW][C]31[/C][C]0.296188[/C][C]0.592377[/C][C]0.703812[/C][/ROW]
[ROW][C]32[/C][C]0.244557[/C][C]0.489114[/C][C]0.755443[/C][/ROW]
[ROW][C]33[/C][C]0.248318[/C][C]0.496636[/C][C]0.751682[/C][/ROW]
[ROW][C]34[/C][C]0.210967[/C][C]0.421934[/C][C]0.789033[/C][/ROW]
[ROW][C]35[/C][C]0.17901[/C][C]0.358021[/C][C]0.82099[/C][/ROW]
[ROW][C]36[/C][C]0.142028[/C][C]0.284056[/C][C]0.857972[/C][/ROW]
[ROW][C]37[/C][C]0.110862[/C][C]0.221723[/C][C]0.889138[/C][/ROW]
[ROW][C]38[/C][C]0.0884252[/C][C]0.17685[/C][C]0.911575[/C][/ROW]
[ROW][C]39[/C][C]0.0703856[/C][C]0.140771[/C][C]0.929614[/C][/ROW]
[ROW][C]40[/C][C]0.0580668[/C][C]0.116134[/C][C]0.941933[/C][/ROW]
[ROW][C]41[/C][C]0.0681331[/C][C]0.136266[/C][C]0.931867[/C][/ROW]
[ROW][C]42[/C][C]0.0653769[/C][C]0.130754[/C][C]0.934623[/C][/ROW]
[ROW][C]43[/C][C]0.0728172[/C][C]0.145634[/C][C]0.927183[/C][/ROW]
[ROW][C]44[/C][C]0.0561943[/C][C]0.112389[/C][C]0.943806[/C][/ROW]
[ROW][C]45[/C][C]0.0456621[/C][C]0.0913242[/C][C]0.954338[/C][/ROW]
[ROW][C]46[/C][C]0.0349601[/C][C]0.0699203[/C][C]0.96504[/C][/ROW]
[ROW][C]47[/C][C]0.0274312[/C][C]0.0548623[/C][C]0.972569[/C][/ROW]
[ROW][C]48[/C][C]0.029411[/C][C]0.0588221[/C][C]0.970589[/C][/ROW]
[ROW][C]49[/C][C]0.0286731[/C][C]0.0573462[/C][C]0.971327[/C][/ROW]
[ROW][C]50[/C][C]0.0252927[/C][C]0.0505855[/C][C]0.974707[/C][/ROW]
[ROW][C]51[/C][C]0.0188619[/C][C]0.0377238[/C][C]0.981138[/C][/ROW]
[ROW][C]52[/C][C]0.0508467[/C][C]0.101693[/C][C]0.949153[/C][/ROW]
[ROW][C]53[/C][C]0.0410089[/C][C]0.0820178[/C][C]0.958991[/C][/ROW]
[ROW][C]54[/C][C]0.0350695[/C][C]0.0701391[/C][C]0.96493[/C][/ROW]
[ROW][C]55[/C][C]0.0467278[/C][C]0.0934556[/C][C]0.953272[/C][/ROW]
[ROW][C]56[/C][C]0.0361679[/C][C]0.0723358[/C][C]0.963832[/C][/ROW]
[ROW][C]57[/C][C]0.0638799[/C][C]0.12776[/C][C]0.93612[/C][/ROW]
[ROW][C]58[/C][C]0.055934[/C][C]0.111868[/C][C]0.944066[/C][/ROW]
[ROW][C]59[/C][C]0.0630962[/C][C]0.126192[/C][C]0.936904[/C][/ROW]
[ROW][C]60[/C][C]0.0739953[/C][C]0.147991[/C][C]0.926005[/C][/ROW]
[ROW][C]61[/C][C]0.0606573[/C][C]0.121315[/C][C]0.939343[/C][/ROW]
[ROW][C]62[/C][C]0.052713[/C][C]0.105426[/C][C]0.947287[/C][/ROW]
[ROW][C]63[/C][C]0.0477824[/C][C]0.0955649[/C][C]0.952218[/C][/ROW]
[ROW][C]64[/C][C]0.0947126[/C][C]0.189425[/C][C]0.905287[/C][/ROW]
[ROW][C]65[/C][C]0.097297[/C][C]0.194594[/C][C]0.902703[/C][/ROW]
[ROW][C]66[/C][C]0.099156[/C][C]0.198312[/C][C]0.900844[/C][/ROW]
[ROW][C]67[/C][C]0.0814751[/C][C]0.16295[/C][C]0.918525[/C][/ROW]
[ROW][C]68[/C][C]0.0853579[/C][C]0.170716[/C][C]0.914642[/C][/ROW]
[ROW][C]69[/C][C]0.0996767[/C][C]0.199353[/C][C]0.900323[/C][/ROW]
[ROW][C]70[/C][C]0.0879322[/C][C]0.175864[/C][C]0.912068[/C][/ROW]
[ROW][C]71[/C][C]0.0723484[/C][C]0.144697[/C][C]0.927652[/C][/ROW]
[ROW][C]72[/C][C]0.0589952[/C][C]0.11799[/C][C]0.941005[/C][/ROW]
[ROW][C]73[/C][C]0.0590829[/C][C]0.118166[/C][C]0.940917[/C][/ROW]
[ROW][C]74[/C][C]0.0993223[/C][C]0.198645[/C][C]0.900678[/C][/ROW]
[ROW][C]75[/C][C]0.101332[/C][C]0.202664[/C][C]0.898668[/C][/ROW]
[ROW][C]76[/C][C]0.0952069[/C][C]0.190414[/C][C]0.904793[/C][/ROW]
[ROW][C]77[/C][C]0.0909739[/C][C]0.181948[/C][C]0.909026[/C][/ROW]
[ROW][C]78[/C][C]0.0802374[/C][C]0.160475[/C][C]0.919763[/C][/ROW]
[ROW][C]79[/C][C]0.067557[/C][C]0.135114[/C][C]0.932443[/C][/ROW]
[ROW][C]80[/C][C]0.072948[/C][C]0.145896[/C][C]0.927052[/C][/ROW]
[ROW][C]81[/C][C]0.0608413[/C][C]0.121683[/C][C]0.939159[/C][/ROW]
[ROW][C]82[/C][C]0.0618614[/C][C]0.123723[/C][C]0.938139[/C][/ROW]
[ROW][C]83[/C][C]0.0508557[/C][C]0.101711[/C][C]0.949144[/C][/ROW]
[ROW][C]84[/C][C]0.126255[/C][C]0.25251[/C][C]0.873745[/C][/ROW]
[ROW][C]85[/C][C]0.107879[/C][C]0.215757[/C][C]0.892121[/C][/ROW]
[ROW][C]86[/C][C]0.0944821[/C][C]0.188964[/C][C]0.905518[/C][/ROW]
[ROW][C]87[/C][C]0.081583[/C][C]0.163166[/C][C]0.918417[/C][/ROW]
[ROW][C]88[/C][C]0.0708184[/C][C]0.141637[/C][C]0.929182[/C][/ROW]
[ROW][C]89[/C][C]0.0660975[/C][C]0.132195[/C][C]0.933902[/C][/ROW]
[ROW][C]90[/C][C]0.0663769[/C][C]0.132754[/C][C]0.933623[/C][/ROW]
[ROW][C]91[/C][C]0.0616734[/C][C]0.123347[/C][C]0.938327[/C][/ROW]
[ROW][C]92[/C][C]0.119917[/C][C]0.239834[/C][C]0.880083[/C][/ROW]
[ROW][C]93[/C][C]0.10239[/C][C]0.20478[/C][C]0.89761[/C][/ROW]
[ROW][C]94[/C][C]0.0871701[/C][C]0.17434[/C][C]0.91283[/C][/ROW]
[ROW][C]95[/C][C]0.0848733[/C][C]0.169747[/C][C]0.915127[/C][/ROW]
[ROW][C]96[/C][C]0.0778553[/C][C]0.155711[/C][C]0.922145[/C][/ROW]
[ROW][C]97[/C][C]0.0827034[/C][C]0.165407[/C][C]0.917297[/C][/ROW]
[ROW][C]98[/C][C]0.0710781[/C][C]0.142156[/C][C]0.928922[/C][/ROW]
[ROW][C]99[/C][C]0.084839[/C][C]0.169678[/C][C]0.915161[/C][/ROW]
[ROW][C]100[/C][C]0.0799598[/C][C]0.15992[/C][C]0.92004[/C][/ROW]
[ROW][C]101[/C][C]0.067914[/C][C]0.135828[/C][C]0.932086[/C][/ROW]
[ROW][C]102[/C][C]0.0572431[/C][C]0.114486[/C][C]0.942757[/C][/ROW]
[ROW][C]103[/C][C]0.0540691[/C][C]0.108138[/C][C]0.945931[/C][/ROW]
[ROW][C]104[/C][C]0.044789[/C][C]0.0895781[/C][C]0.955211[/C][/ROW]
[ROW][C]105[/C][C]0.0659836[/C][C]0.131967[/C][C]0.934016[/C][/ROW]
[ROW][C]106[/C][C]0.0610888[/C][C]0.122178[/C][C]0.938911[/C][/ROW]
[ROW][C]107[/C][C]0.0640745[/C][C]0.128149[/C][C]0.935926[/C][/ROW]
[ROW][C]108[/C][C]0.0964222[/C][C]0.192844[/C][C]0.903578[/C][/ROW]
[ROW][C]109[/C][C]0.122995[/C][C]0.24599[/C][C]0.877005[/C][/ROW]
[ROW][C]110[/C][C]0.11375[/C][C]0.2275[/C][C]0.88625[/C][/ROW]
[ROW][C]111[/C][C]0.0987461[/C][C]0.197492[/C][C]0.901254[/C][/ROW]
[ROW][C]112[/C][C]0.0851436[/C][C]0.170287[/C][C]0.914856[/C][/ROW]
[ROW][C]113[/C][C]0.148492[/C][C]0.296984[/C][C]0.851508[/C][/ROW]
[ROW][C]114[/C][C]0.184221[/C][C]0.368443[/C][C]0.815779[/C][/ROW]
[ROW][C]115[/C][C]0.322452[/C][C]0.644903[/C][C]0.677548[/C][/ROW]
[ROW][C]116[/C][C]0.387029[/C][C]0.774059[/C][C]0.612971[/C][/ROW]
[ROW][C]117[/C][C]0.371117[/C][C]0.742234[/C][C]0.628883[/C][/ROW]
[ROW][C]118[/C][C]0.343603[/C][C]0.687206[/C][C]0.656397[/C][/ROW]
[ROW][C]119[/C][C]0.366478[/C][C]0.732955[/C][C]0.633522[/C][/ROW]
[ROW][C]120[/C][C]0.380589[/C][C]0.761178[/C][C]0.619411[/C][/ROW]
[ROW][C]121[/C][C]0.353573[/C][C]0.707146[/C][C]0.646427[/C][/ROW]
[ROW][C]122[/C][C]0.345292[/C][C]0.690584[/C][C]0.654708[/C][/ROW]
[ROW][C]123[/C][C]0.320488[/C][C]0.640976[/C][C]0.679512[/C][/ROW]
[ROW][C]124[/C][C]0.290111[/C][C]0.580222[/C][C]0.709889[/C][/ROW]
[ROW][C]125[/C][C]0.314561[/C][C]0.629122[/C][C]0.685439[/C][/ROW]
[ROW][C]126[/C][C]0.296576[/C][C]0.593153[/C][C]0.703424[/C][/ROW]
[ROW][C]127[/C][C]0.29053[/C][C]0.581061[/C][C]0.70947[/C][/ROW]
[ROW][C]128[/C][C]0.262139[/C][C]0.524279[/C][C]0.737861[/C][/ROW]
[ROW][C]129[/C][C]0.31994[/C][C]0.639879[/C][C]0.68006[/C][/ROW]
[ROW][C]130[/C][C]0.289598[/C][C]0.579197[/C][C]0.710402[/C][/ROW]
[ROW][C]131[/C][C]0.260661[/C][C]0.521321[/C][C]0.739339[/C][/ROW]
[ROW][C]132[/C][C]0.236589[/C][C]0.473179[/C][C]0.763411[/C][/ROW]
[ROW][C]133[/C][C]0.21191[/C][C]0.42382[/C][C]0.78809[/C][/ROW]
[ROW][C]134[/C][C]0.187181[/C][C]0.374362[/C][C]0.812819[/C][/ROW]
[ROW][C]135[/C][C]0.170536[/C][C]0.341072[/C][C]0.829464[/C][/ROW]
[ROW][C]136[/C][C]0.160253[/C][C]0.320506[/C][C]0.839747[/C][/ROW]
[ROW][C]137[/C][C]0.173576[/C][C]0.347153[/C][C]0.826424[/C][/ROW]
[ROW][C]138[/C][C]0.264946[/C][C]0.529892[/C][C]0.735054[/C][/ROW]
[ROW][C]139[/C][C]0.286203[/C][C]0.572406[/C][C]0.713797[/C][/ROW]
[ROW][C]140[/C][C]0.26816[/C][C]0.53632[/C][C]0.73184[/C][/ROW]
[ROW][C]141[/C][C]0.256619[/C][C]0.513237[/C][C]0.743381[/C][/ROW]
[ROW][C]142[/C][C]0.279887[/C][C]0.559773[/C][C]0.720113[/C][/ROW]
[ROW][C]143[/C][C]0.251183[/C][C]0.502366[/C][C]0.748817[/C][/ROW]
[ROW][C]144[/C][C]0.2619[/C][C]0.523799[/C][C]0.7381[/C][/ROW]
[ROW][C]145[/C][C]0.237089[/C][C]0.474178[/C][C]0.762911[/C][/ROW]
[ROW][C]146[/C][C]0.212721[/C][C]0.425442[/C][C]0.787279[/C][/ROW]
[ROW][C]147[/C][C]0.197611[/C][C]0.395222[/C][C]0.802389[/C][/ROW]
[ROW][C]148[/C][C]0.18827[/C][C]0.37654[/C][C]0.81173[/C][/ROW]
[ROW][C]149[/C][C]0.176226[/C][C]0.352453[/C][C]0.823774[/C][/ROW]
[ROW][C]150[/C][C]0.204294[/C][C]0.408587[/C][C]0.795706[/C][/ROW]
[ROW][C]151[/C][C]0.231933[/C][C]0.463866[/C][C]0.768067[/C][/ROW]
[ROW][C]152[/C][C]0.215402[/C][C]0.430805[/C][C]0.784598[/C][/ROW]
[ROW][C]153[/C][C]0.244353[/C][C]0.488706[/C][C]0.755647[/C][/ROW]
[ROW][C]154[/C][C]0.219809[/C][C]0.439617[/C][C]0.780191[/C][/ROW]
[ROW][C]155[/C][C]0.195017[/C][C]0.390033[/C][C]0.804983[/C][/ROW]
[ROW][C]156[/C][C]0.172181[/C][C]0.344361[/C][C]0.827819[/C][/ROW]
[ROW][C]157[/C][C]0.192303[/C][C]0.384606[/C][C]0.807697[/C][/ROW]
[ROW][C]158[/C][C]0.17008[/C][C]0.340161[/C][C]0.82992[/C][/ROW]
[ROW][C]159[/C][C]0.155995[/C][C]0.31199[/C][C]0.844005[/C][/ROW]
[ROW][C]160[/C][C]0.165543[/C][C]0.331086[/C][C]0.834457[/C][/ROW]
[ROW][C]161[/C][C]0.173471[/C][C]0.346943[/C][C]0.826529[/C][/ROW]
[ROW][C]162[/C][C]0.163765[/C][C]0.327529[/C][C]0.836235[/C][/ROW]
[ROW][C]163[/C][C]0.143627[/C][C]0.287255[/C][C]0.856373[/C][/ROW]
[ROW][C]164[/C][C]0.131696[/C][C]0.263391[/C][C]0.868304[/C][/ROW]
[ROW][C]165[/C][C]0.132164[/C][C]0.264327[/C][C]0.867836[/C][/ROW]
[ROW][C]166[/C][C]0.138565[/C][C]0.27713[/C][C]0.861435[/C][/ROW]
[ROW][C]167[/C][C]0.170361[/C][C]0.340723[/C][C]0.829639[/C][/ROW]
[ROW][C]168[/C][C]0.155743[/C][C]0.311487[/C][C]0.844257[/C][/ROW]
[ROW][C]169[/C][C]0.13875[/C][C]0.277501[/C][C]0.86125[/C][/ROW]
[ROW][C]170[/C][C]0.14234[/C][C]0.284679[/C][C]0.85766[/C][/ROW]
[ROW][C]171[/C][C]0.124814[/C][C]0.249627[/C][C]0.875186[/C][/ROW]
[ROW][C]172[/C][C]0.127195[/C][C]0.25439[/C][C]0.872805[/C][/ROW]
[ROW][C]173[/C][C]0.111696[/C][C]0.223392[/C][C]0.888304[/C][/ROW]
[ROW][C]174[/C][C]0.0986527[/C][C]0.197305[/C][C]0.901347[/C][/ROW]
[ROW][C]175[/C][C]0.086827[/C][C]0.173654[/C][C]0.913173[/C][/ROW]
[ROW][C]176[/C][C]0.102868[/C][C]0.205735[/C][C]0.897132[/C][/ROW]
[ROW][C]177[/C][C]0.0887121[/C][C]0.177424[/C][C]0.911288[/C][/ROW]
[ROW][C]178[/C][C]0.0941418[/C][C]0.188284[/C][C]0.905858[/C][/ROW]
[ROW][C]179[/C][C]0.0926314[/C][C]0.185263[/C][C]0.907369[/C][/ROW]
[ROW][C]180[/C][C]0.214912[/C][C]0.429824[/C][C]0.785088[/C][/ROW]
[ROW][C]181[/C][C]0.210083[/C][C]0.420165[/C][C]0.789917[/C][/ROW]
[ROW][C]182[/C][C]0.201988[/C][C]0.403975[/C][C]0.798012[/C][/ROW]
[ROW][C]183[/C][C]0.296373[/C][C]0.592746[/C][C]0.703627[/C][/ROW]
[ROW][C]184[/C][C]0.266761[/C][C]0.533522[/C][C]0.733239[/C][/ROW]
[ROW][C]185[/C][C]0.239389[/C][C]0.478778[/C][C]0.760611[/C][/ROW]
[ROW][C]186[/C][C]0.213401[/C][C]0.426802[/C][C]0.786599[/C][/ROW]
[ROW][C]187[/C][C]0.205089[/C][C]0.410178[/C][C]0.794911[/C][/ROW]
[ROW][C]188[/C][C]0.187706[/C][C]0.375413[/C][C]0.812294[/C][/ROW]
[ROW][C]189[/C][C]0.191763[/C][C]0.383525[/C][C]0.808237[/C][/ROW]
[ROW][C]190[/C][C]0.172653[/C][C]0.345307[/C][C]0.827347[/C][/ROW]
[ROW][C]191[/C][C]0.169532[/C][C]0.339065[/C][C]0.830468[/C][/ROW]
[ROW][C]192[/C][C]0.150413[/C][C]0.300825[/C][C]0.849587[/C][/ROW]
[ROW][C]193[/C][C]0.171118[/C][C]0.342237[/C][C]0.828882[/C][/ROW]
[ROW][C]194[/C][C]0.174362[/C][C]0.348725[/C][C]0.825638[/C][/ROW]
[ROW][C]195[/C][C]0.1879[/C][C]0.3758[/C][C]0.8121[/C][/ROW]
[ROW][C]196[/C][C]0.16901[/C][C]0.33802[/C][C]0.83099[/C][/ROW]
[ROW][C]197[/C][C]0.145781[/C][C]0.291562[/C][C]0.854219[/C][/ROW]
[ROW][C]198[/C][C]0.130874[/C][C]0.261747[/C][C]0.869126[/C][/ROW]
[ROW][C]199[/C][C]0.113994[/C][C]0.227988[/C][C]0.886006[/C][/ROW]
[ROW][C]200[/C][C]0.0964707[/C][C]0.192941[/C][C]0.903529[/C][/ROW]
[ROW][C]201[/C][C]0.171008[/C][C]0.342016[/C][C]0.828992[/C][/ROW]
[ROW][C]202[/C][C]0.149852[/C][C]0.299705[/C][C]0.850148[/C][/ROW]
[ROW][C]203[/C][C]0.140484[/C][C]0.280968[/C][C]0.859516[/C][/ROW]
[ROW][C]204[/C][C]0.121239[/C][C]0.242477[/C][C]0.878761[/C][/ROW]
[ROW][C]205[/C][C]0.1078[/C][C]0.215599[/C][C]0.8922[/C][/ROW]
[ROW][C]206[/C][C]0.0911663[/C][C]0.182333[/C][C]0.908834[/C][/ROW]
[ROW][C]207[/C][C]0.113597[/C][C]0.227193[/C][C]0.886403[/C][/ROW]
[ROW][C]208[/C][C]0.101906[/C][C]0.203811[/C][C]0.898094[/C][/ROW]
[ROW][C]209[/C][C]0.14969[/C][C]0.29938[/C][C]0.85031[/C][/ROW]
[ROW][C]210[/C][C]0.157759[/C][C]0.315518[/C][C]0.842241[/C][/ROW]
[ROW][C]211[/C][C]0.146448[/C][C]0.292897[/C][C]0.853552[/C][/ROW]
[ROW][C]212[/C][C]0.128701[/C][C]0.257401[/C][C]0.871299[/C][/ROW]
[ROW][C]213[/C][C]0.12979[/C][C]0.25958[/C][C]0.87021[/C][/ROW]
[ROW][C]214[/C][C]0.108841[/C][C]0.217682[/C][C]0.891159[/C][/ROW]
[ROW][C]215[/C][C]0.0986315[/C][C]0.197263[/C][C]0.901369[/C][/ROW]
[ROW][C]216[/C][C]0.0844481[/C][C]0.168896[/C][C]0.915552[/C][/ROW]
[ROW][C]217[/C][C]0.106265[/C][C]0.21253[/C][C]0.893735[/C][/ROW]
[ROW][C]218[/C][C]0.134632[/C][C]0.269264[/C][C]0.865368[/C][/ROW]
[ROW][C]219[/C][C]0.119701[/C][C]0.239403[/C][C]0.880299[/C][/ROW]
[ROW][C]220[/C][C]0.099299[/C][C]0.198598[/C][C]0.900701[/C][/ROW]
[ROW][C]221[/C][C]0.126856[/C][C]0.253713[/C][C]0.873144[/C][/ROW]
[ROW][C]222[/C][C]0.208606[/C][C]0.417211[/C][C]0.791394[/C][/ROW]
[ROW][C]223[/C][C]0.181854[/C][C]0.363707[/C][C]0.818146[/C][/ROW]
[ROW][C]224[/C][C]0.186401[/C][C]0.372802[/C][C]0.813599[/C][/ROW]
[ROW][C]225[/C][C]0.262771[/C][C]0.525541[/C][C]0.737229[/C][/ROW]
[ROW][C]226[/C][C]0.239676[/C][C]0.479353[/C][C]0.760324[/C][/ROW]
[ROW][C]227[/C][C]0.205477[/C][C]0.410954[/C][C]0.794523[/C][/ROW]
[ROW][C]228[/C][C]0.191407[/C][C]0.382813[/C][C]0.808593[/C][/ROW]
[ROW][C]229[/C][C]0.295615[/C][C]0.59123[/C][C]0.704385[/C][/ROW]
[ROW][C]230[/C][C]0.380631[/C][C]0.761262[/C][C]0.619369[/C][/ROW]
[ROW][C]231[/C][C]0.372429[/C][C]0.744858[/C][C]0.627571[/C][/ROW]
[ROW][C]232[/C][C]0.410322[/C][C]0.820644[/C][C]0.589678[/C][/ROW]
[ROW][C]233[/C][C]0.365386[/C][C]0.730772[/C][C]0.634614[/C][/ROW]
[ROW][C]234[/C][C]0.339566[/C][C]0.679131[/C][C]0.660434[/C][/ROW]
[ROW][C]235[/C][C]0.334534[/C][C]0.669067[/C][C]0.665466[/C][/ROW]
[ROW][C]236[/C][C]0.739307[/C][C]0.521386[/C][C]0.260693[/C][/ROW]
[ROW][C]237[/C][C]0.728669[/C][C]0.542663[/C][C]0.271331[/C][/ROW]
[ROW][C]238[/C][C]0.686664[/C][C]0.626673[/C][C]0.313336[/C][/ROW]
[ROW][C]239[/C][C]0.67246[/C][C]0.655079[/C][C]0.32754[/C][/ROW]
[ROW][C]240[/C][C]0.647935[/C][C]0.70413[/C][C]0.352065[/C][/ROW]
[ROW][C]241[/C][C]0.650938[/C][C]0.698124[/C][C]0.349062[/C][/ROW]
[ROW][C]242[/C][C]0.648346[/C][C]0.703308[/C][C]0.351654[/C][/ROW]
[ROW][C]243[/C][C]0.62253[/C][C]0.754939[/C][C]0.37747[/C][/ROW]
[ROW][C]244[/C][C]0.584919[/C][C]0.830161[/C][C]0.415081[/C][/ROW]
[ROW][C]245[/C][C]0.528199[/C][C]0.943603[/C][C]0.471801[/C][/ROW]
[ROW][C]246[/C][C]0.482081[/C][C]0.964163[/C][C]0.517919[/C][/ROW]
[ROW][C]247[/C][C]0.465948[/C][C]0.931896[/C][C]0.534052[/C][/ROW]
[ROW][C]248[/C][C]0.564065[/C][C]0.871871[/C][C]0.435935[/C][/ROW]
[ROW][C]249[/C][C]0.499281[/C][C]0.998563[/C][C]0.500719[/C][/ROW]
[ROW][C]250[/C][C]0.439024[/C][C]0.878047[/C][C]0.560976[/C][/ROW]
[ROW][C]251[/C][C]0.38232[/C][C]0.764641[/C][C]0.61768[/C][/ROW]
[ROW][C]252[/C][C]0.3222[/C][C]0.6444[/C][C]0.6778[/C][/ROW]
[ROW][C]253[/C][C]0.335344[/C][C]0.670689[/C][C]0.664656[/C][/ROW]
[ROW][C]254[/C][C]0.330828[/C][C]0.661657[/C][C]0.669172[/C][/ROW]
[ROW][C]255[/C][C]0.733175[/C][C]0.533651[/C][C]0.266825[/C][/ROW]
[ROW][C]256[/C][C]0.66654[/C][C]0.666919[/C][C]0.33346[/C][/ROW]
[ROW][C]257[/C][C]0.832272[/C][C]0.335455[/C][C]0.167728[/C][/ROW]
[ROW][C]258[/C][C]0.852712[/C][C]0.294577[/C][C]0.147288[/C][/ROW]
[ROW][C]259[/C][C]0.840101[/C][C]0.319798[/C][C]0.159899[/C][/ROW]
[ROW][C]260[/C][C]0.890243[/C][C]0.219513[/C][C]0.109757[/C][/ROW]
[ROW][C]261[/C][C]0.847331[/C][C]0.305338[/C][C]0.152669[/C][/ROW]
[ROW][C]262[/C][C]0.807765[/C][C]0.38447[/C][C]0.192235[/C][/ROW]
[ROW][C]263[/C][C]0.701239[/C][C]0.597522[/C][C]0.298761[/C][/ROW]
[ROW][C]264[/C][C]0.65475[/C][C]0.690501[/C][C]0.34525[/C][/ROW]
[ROW][C]265[/C][C]0.507108[/C][C]0.985785[/C][C]0.492892[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267961&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267961&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.7312070.5375860.268793
140.5840320.8319370.415968
150.5469560.9060880.453044
160.4172360.8344720.582764
170.4116760.8233530.588324
180.3163150.632630.683685
190.2273520.4547040.772648
200.1763620.3527230.823638
210.2021610.4043220.797839
220.1893180.3786360.810682
230.1354390.2708780.864561
240.2280070.4560140.771993
250.1730690.3461380.826931
260.1296920.2593840.870308
270.2255920.4511830.774408
280.192880.3857610.80712
290.1489530.2979050.851047
300.1273060.2546130.872694
310.2961880.5923770.703812
320.2445570.4891140.755443
330.2483180.4966360.751682
340.2109670.4219340.789033
350.179010.3580210.82099
360.1420280.2840560.857972
370.1108620.2217230.889138
380.08842520.176850.911575
390.07038560.1407710.929614
400.05806680.1161340.941933
410.06813310.1362660.931867
420.06537690.1307540.934623
430.07281720.1456340.927183
440.05619430.1123890.943806
450.04566210.09132420.954338
460.03496010.06992030.96504
470.02743120.05486230.972569
480.0294110.05882210.970589
490.02867310.05734620.971327
500.02529270.05058550.974707
510.01886190.03772380.981138
520.05084670.1016930.949153
530.04100890.08201780.958991
540.03506950.07013910.96493
550.04672780.09345560.953272
560.03616790.07233580.963832
570.06387990.127760.93612
580.0559340.1118680.944066
590.06309620.1261920.936904
600.07399530.1479910.926005
610.06065730.1213150.939343
620.0527130.1054260.947287
630.04778240.09556490.952218
640.09471260.1894250.905287
650.0972970.1945940.902703
660.0991560.1983120.900844
670.08147510.162950.918525
680.08535790.1707160.914642
690.09967670.1993530.900323
700.08793220.1758640.912068
710.07234840.1446970.927652
720.05899520.117990.941005
730.05908290.1181660.940917
740.09932230.1986450.900678
750.1013320.2026640.898668
760.09520690.1904140.904793
770.09097390.1819480.909026
780.08023740.1604750.919763
790.0675570.1351140.932443
800.0729480.1458960.927052
810.06084130.1216830.939159
820.06186140.1237230.938139
830.05085570.1017110.949144
840.1262550.252510.873745
850.1078790.2157570.892121
860.09448210.1889640.905518
870.0815830.1631660.918417
880.07081840.1416370.929182
890.06609750.1321950.933902
900.06637690.1327540.933623
910.06167340.1233470.938327
920.1199170.2398340.880083
930.102390.204780.89761
940.08717010.174340.91283
950.08487330.1697470.915127
960.07785530.1557110.922145
970.08270340.1654070.917297
980.07107810.1421560.928922
990.0848390.1696780.915161
1000.07995980.159920.92004
1010.0679140.1358280.932086
1020.05724310.1144860.942757
1030.05406910.1081380.945931
1040.0447890.08957810.955211
1050.06598360.1319670.934016
1060.06108880.1221780.938911
1070.06407450.1281490.935926
1080.09642220.1928440.903578
1090.1229950.245990.877005
1100.113750.22750.88625
1110.09874610.1974920.901254
1120.08514360.1702870.914856
1130.1484920.2969840.851508
1140.1842210.3684430.815779
1150.3224520.6449030.677548
1160.3870290.7740590.612971
1170.3711170.7422340.628883
1180.3436030.6872060.656397
1190.3664780.7329550.633522
1200.3805890.7611780.619411
1210.3535730.7071460.646427
1220.3452920.6905840.654708
1230.3204880.6409760.679512
1240.2901110.5802220.709889
1250.3145610.6291220.685439
1260.2965760.5931530.703424
1270.290530.5810610.70947
1280.2621390.5242790.737861
1290.319940.6398790.68006
1300.2895980.5791970.710402
1310.2606610.5213210.739339
1320.2365890.4731790.763411
1330.211910.423820.78809
1340.1871810.3743620.812819
1350.1705360.3410720.829464
1360.1602530.3205060.839747
1370.1735760.3471530.826424
1380.2649460.5298920.735054
1390.2862030.5724060.713797
1400.268160.536320.73184
1410.2566190.5132370.743381
1420.2798870.5597730.720113
1430.2511830.5023660.748817
1440.26190.5237990.7381
1450.2370890.4741780.762911
1460.2127210.4254420.787279
1470.1976110.3952220.802389
1480.188270.376540.81173
1490.1762260.3524530.823774
1500.2042940.4085870.795706
1510.2319330.4638660.768067
1520.2154020.4308050.784598
1530.2443530.4887060.755647
1540.2198090.4396170.780191
1550.1950170.3900330.804983
1560.1721810.3443610.827819
1570.1923030.3846060.807697
1580.170080.3401610.82992
1590.1559950.311990.844005
1600.1655430.3310860.834457
1610.1734710.3469430.826529
1620.1637650.3275290.836235
1630.1436270.2872550.856373
1640.1316960.2633910.868304
1650.1321640.2643270.867836
1660.1385650.277130.861435
1670.1703610.3407230.829639
1680.1557430.3114870.844257
1690.138750.2775010.86125
1700.142340.2846790.85766
1710.1248140.2496270.875186
1720.1271950.254390.872805
1730.1116960.2233920.888304
1740.09865270.1973050.901347
1750.0868270.1736540.913173
1760.1028680.2057350.897132
1770.08871210.1774240.911288
1780.09414180.1882840.905858
1790.09263140.1852630.907369
1800.2149120.4298240.785088
1810.2100830.4201650.789917
1820.2019880.4039750.798012
1830.2963730.5927460.703627
1840.2667610.5335220.733239
1850.2393890.4787780.760611
1860.2134010.4268020.786599
1870.2050890.4101780.794911
1880.1877060.3754130.812294
1890.1917630.3835250.808237
1900.1726530.3453070.827347
1910.1695320.3390650.830468
1920.1504130.3008250.849587
1930.1711180.3422370.828882
1940.1743620.3487250.825638
1950.18790.37580.8121
1960.169010.338020.83099
1970.1457810.2915620.854219
1980.1308740.2617470.869126
1990.1139940.2279880.886006
2000.09647070.1929410.903529
2010.1710080.3420160.828992
2020.1498520.2997050.850148
2030.1404840.2809680.859516
2040.1212390.2424770.878761
2050.10780.2155990.8922
2060.09116630.1823330.908834
2070.1135970.2271930.886403
2080.1019060.2038110.898094
2090.149690.299380.85031
2100.1577590.3155180.842241
2110.1464480.2928970.853552
2120.1287010.2574010.871299
2130.129790.259580.87021
2140.1088410.2176820.891159
2150.09863150.1972630.901369
2160.08444810.1688960.915552
2170.1062650.212530.893735
2180.1346320.2692640.865368
2190.1197010.2394030.880299
2200.0992990.1985980.900701
2210.1268560.2537130.873144
2220.2086060.4172110.791394
2230.1818540.3637070.818146
2240.1864010.3728020.813599
2250.2627710.5255410.737229
2260.2396760.4793530.760324
2270.2054770.4109540.794523
2280.1914070.3828130.808593
2290.2956150.591230.704385
2300.3806310.7612620.619369
2310.3724290.7448580.627571
2320.4103220.8206440.589678
2330.3653860.7307720.634614
2340.3395660.6791310.660434
2350.3345340.6690670.665466
2360.7393070.5213860.260693
2370.7286690.5426630.271331
2380.6866640.6266730.313336
2390.672460.6550790.32754
2400.6479350.704130.352065
2410.6509380.6981240.349062
2420.6483460.7033080.351654
2430.622530.7549390.37747
2440.5849190.8301610.415081
2450.5281990.9436030.471801
2460.4820810.9641630.517919
2470.4659480.9318960.534052
2480.5640650.8718710.435935
2490.4992810.9985630.500719
2500.4390240.8780470.560976
2510.382320.7646410.61768
2520.32220.64440.6778
2530.3353440.6706890.664656
2540.3308280.6616570.669172
2550.7331750.5336510.266825
2560.666540.6669190.33346
2570.8322720.3354550.167728
2580.8527120.2945770.147288
2590.8401010.3197980.159899
2600.8902430.2195130.109757
2610.8473310.3053380.152669
2620.8077650.384470.192235
2630.7012390.5975220.298761
2640.654750.6905010.34525
2650.5071080.9857850.492892







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 level130.0513834OK

\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 & 13 & 0.0513834 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267961&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]13[/C][C]0.0513834[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267961&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267961&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level10.00395257OK
10% type I error level130.0513834OK



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')
}