Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 17 Nov 2010 07:43:53 +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/2010/Nov/17/t128998342128i6qsjxv676vga.htm/, Retrieved Thu, 06 Oct 2022 23:03:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=96530, Retrieved Thu, 06 Oct 2022 23:03:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact795
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
- R PD    [Multiple Regression] [WS7 Tutorial] [2010-11-18 16:04:53] [afe9379cca749d06b3d6872e02cc47ed]
-    D      [Multiple Regression] [WS7 Tutorial Popu...] [2010-11-22 10:41:15] [afe9379cca749d06b3d6872e02cc47ed]
- R  D        [Multiple Regression] [] [2010-12-02 15:03:12] [11b6443b23f19c2dbda3ee0ee9d024b2]
- RMPD        [Univariate Explorative Data Analysis] [] [2010-12-02 15:42:43] [11b6443b23f19c2dbda3ee0ee9d024b2]
- R  D          [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2010-12-02 19:58:40] [69c775ce4d55db2aa75a88e773e8d700]
- R PD        [Multiple Regression] [] [2010-12-02 16:12:01] [11b6443b23f19c2dbda3ee0ee9d024b2]
-             [Multiple Regression] [WS 4: Personality...] [2010-12-02 16:43:36] [4f1a20f787b3465111b61213cdeef1a9]
- RMPD        [] [Multiple regressi...] [-0001-11-30 00:00:00] [74be16979710d4c4e7c6647856088456]
- RMPD        [] [Multiple regressi...] [-0001-11-30 00:00:00] [74be16979710d4c4e7c6647856088456]
- R PD        [Multiple Regression] [] [2010-12-02 17:36:13] [11b6443b23f19c2dbda3ee0ee9d024b2]
- RMPD        [] [Multiple regressi...] [-0001-11-30 00:00:00] [74be16979710d4c4e7c6647856088456]
- RMPD        [] [Multiple regressi...] [-0001-11-30 00:00:00] [74be16979710d4c4e7c6647856088456]
- R PD        [Multiple Regression] [] [2010-12-02 18:02:49] [94f4aa1c01e87d8321fffb341ed4df07]
- R             [Multiple Regression] [] [2011-11-25 00:47:59] [74be16979710d4c4e7c6647856088456]
- R P             [Multiple Regression] [] [2011-11-27 17:03:35] [3931071255a6f7f4a767409781cc5f7d]
- RMPD        [Univariate Explorative Data Analysis] [EDA - assignment ...] [2010-12-02 18:07:45] [74be16979710d4c4e7c6647856088456]
-             [Multiple Regression] [] [2010-12-02 18:37:01] [f47feae0308dca73181bb669fbad1c56]
- RM            [Multiple Regression] [] [2012-11-20 16:54:06] [74be16979710d4c4e7c6647856088456]
- R             [Multiple Regression] [W7 ] [2012-11-20 19:29:08] [783d8509970888a6ec44a5a7a0d2a339]
- RM            [Multiple Regression] [Workshop 7] [2012-11-20 19:35:01] [74be16979710d4c4e7c6647856088456]
- R PD        [Multiple Regression] [] [2010-12-02 23:03:05] [d67ce207bd02ca41b9162077ae11c874]
-   PD        [Multiple Regression] [Tutorial1] [2010-12-03 19:28:18] [a7c91bc614e4e21e8b9c8593f39a36f1]
- R  D        [Multiple Regression] [WS 7 Mini-tutorial] [2011-11-20 14:29:34] [f5fdea4413921432bb019d1f20c4f2ec]
- R  D          [Multiple Regression] [WS 7 Mini-tutorial] [2011-11-20 14:47:41] [f5fdea4413921432bb019d1f20c4f2ec]
-    D            [Multiple Regression] [Ws 7 Mini-tutoria...] [2011-11-20 15:44:07] [f5fdea4413921432bb019d1f20c4f2ec]
-   P               [Multiple Regression] [Ws 7 Mini-tutoria...] [2011-11-20 15:51:02] [f5fdea4413921432bb019d1f20c4f2ec]
- RMP             [Kendall tau Correlation Matrix] [workshop 10 a] [2012-12-07 13:55:33] [dbae308bdff61c0f4902cc85498d0d35]
- R P               [Kendall tau Correlation Matrix] [workshop 10 b] [2012-12-07 14:31:15] [dbae308bdff61c0f4902cc85498d0d35]
- RMP               [Multiple Regression] [workshop 10 c] [2012-12-07 14:38:23] [dbae308bdff61c0f4902cc85498d0d35]
- RMP               [Recursive Partitioning (Regression Trees)] [workshop 10 d] [2012-12-07 14:46:54] [dbae308bdff61c0f4902cc85498d0d35]
-   P                 [Recursive Partitioning (Regression Trees)] [WS 10 recursive p...] [2012-12-10 17:38:57] [8c30f4dd45e15fd207e4faf2fdf6253e]
-                   [Kendall tau Correlation Matrix] [WS 10 Pearson cor...] [2012-12-10 15:35:41] [8c30f4dd45e15fd207e4faf2fdf6253e]
- R P               [Kendall tau Correlation Matrix] [WS 10 Kendall] [2012-12-10 15:49:57] [8c30f4dd45e15fd207e4faf2fdf6253e]
- RMP               [Multiple Regression] [WS 10 multiple re...] [2012-12-10 15:57:07] [8c30f4dd45e15fd207e4faf2fdf6253e]
- R PD        [Multiple Regression] [] [2011-11-21 16:29:10] [bdca8f3e7c3554be8c1291e54f61d441]
- R PD        [Multiple Regression] [] [2011-11-21 21:29:21] [bdca8f3e7c3554be8c1291e54f61d441]
- R PD        [Multiple Regression] [] [2011-11-21 21:29:21] [bdca8f3e7c3554be8c1291e54f61d441]
- R PD        [Multiple Regression] [] [2011-11-21 21:29:21] [bdca8f3e7c3554be8c1291e54f61d441]
- R PD        [Multiple Regression] [] [2011-11-22 00:46:31] [bdca8f3e7c3554be8c1291e54f61d441]
- R             [Multiple Regression] [] [2011-12-19 20:06:55] [74be16979710d4c4e7c6647856088456]
- RM            [Multiple Regression] [WS7] [2012-11-20 16:38:51] [bdca8f3e7c3554be8c1291e54f61d441]
- RM            [Multiple Regression] [] [2012-11-20 18:17:58] [10b150b957285d7c50cf113330698f19]
- RM            [Multiple Regression] [] [2012-11-20 18:19:47] [10b150b957285d7c50cf113330698f19]
- RM            [Multiple Regression] [] [2012-11-20 18:21:00] [10b150b957285d7c50cf113330698f19]
- RM            [Multiple Regression] [] [2012-12-21 15:52:30] [74be16979710d4c4e7c6647856088456]
- R  D        [Multiple Regression] [ws7-1] [2011-11-22 10:24:02] [f7a862281046b7153543b12c78921b36]
-    D          [Multiple Regression] [ws7-1] [2011-11-22 10:38:43] [f7a862281046b7153543b12c78921b36]
- R  D            [Multiple Regression] [ws7-3] [2011-11-22 17:14:48] [f7a862281046b7153543b12c78921b36]

[Truncated]
Feedback Forum

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




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 16 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96530&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]16 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96530&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96530&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 time16 seconds
R Server'George Udny Yule' @ 72.249.76.132







Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 3.77956658273111 + 0.0469437389403786Connected[t] + 0.0419978310517143Separate[t] + 0.607405158110716Software[t] + 0.098631079258643Happiness[t] -0.0393791266630193Depression[t] + 0.0158660592613680Belonging[t] -0.0194154193631033Belonging_Final[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  3.77956658273111 +  0.0469437389403786Connected[t] +  0.0419978310517143Separate[t] +  0.607405158110716Software[t] +  0.098631079258643Happiness[t] -0.0393791266630193Depression[t] +  0.0158660592613680Belonging[t] -0.0194154193631033Belonging_Final[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96530&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  3.77956658273111 +  0.0469437389403786Connected[t] +  0.0419978310517143Separate[t] +  0.607405158110716Software[t] +  0.098631079258643Happiness[t] -0.0393791266630193Depression[t] +  0.0158660592613680Belonging[t] -0.0194154193631033Belonging_Final[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96530&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96530&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
Learning[t] = + 3.77956658273111 + 0.0469437389403786Connected[t] + 0.0419978310517143Separate[t] + 0.607405158110716Software[t] + 0.098631079258643Happiness[t] -0.0393791266630193Depression[t] + 0.0158660592613680Belonging[t] -0.0194154193631033Belonging_Final[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)3.779566582731111.9176521.97090.0498090.024904
Connected0.04694373894037860.0347871.34950.1783840.089192
Separate0.04199783105171430.0356481.17810.2398470.119923
Software0.6074051581107160.05184511.715800
Happiness0.0986310792586430.0579631.70160.090040.04502
Depression-0.03937912666301930.042557-0.92530.355670.177835
Belonging0.01586605926136800.0378430.41930.6753760.337688
Belonging_Final-0.01941541936310330.056444-0.3440.7311470.365573

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 3.77956658273111 & 1.917652 & 1.9709 & 0.049809 & 0.024904 \tabularnewline
Connected & 0.0469437389403786 & 0.034787 & 1.3495 & 0.178384 & 0.089192 \tabularnewline
Separate & 0.0419978310517143 & 0.035648 & 1.1781 & 0.239847 & 0.119923 \tabularnewline
Software & 0.607405158110716 & 0.051845 & 11.7158 & 0 & 0 \tabularnewline
Happiness & 0.098631079258643 & 0.057963 & 1.7016 & 0.09004 & 0.04502 \tabularnewline
Depression & -0.0393791266630193 & 0.042557 & -0.9253 & 0.35567 & 0.177835 \tabularnewline
Belonging & 0.0158660592613680 & 0.037843 & 0.4193 & 0.675376 & 0.337688 \tabularnewline
Belonging_Final & -0.0194154193631033 & 0.056444 & -0.344 & 0.731147 & 0.365573 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96530&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]3.77956658273111[/C][C]1.917652[/C][C]1.9709[/C][C]0.049809[/C][C]0.024904[/C][/ROW]
[ROW][C]Connected[/C][C]0.0469437389403786[/C][C]0.034787[/C][C]1.3495[/C][C]0.178384[/C][C]0.089192[/C][/ROW]
[ROW][C]Separate[/C][C]0.0419978310517143[/C][C]0.035648[/C][C]1.1781[/C][C]0.239847[/C][C]0.119923[/C][/ROW]
[ROW][C]Software[/C][C]0.607405158110716[/C][C]0.051845[/C][C]11.7158[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Happiness[/C][C]0.098631079258643[/C][C]0.057963[/C][C]1.7016[/C][C]0.09004[/C][C]0.04502[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0393791266630193[/C][C]0.042557[/C][C]-0.9253[/C][C]0.35567[/C][C]0.177835[/C][/ROW]
[ROW][C]Belonging[/C][C]0.0158660592613680[/C][C]0.037843[/C][C]0.4193[/C][C]0.675376[/C][C]0.337688[/C][/ROW]
[ROW][C]Belonging_Final[/C][C]-0.0194154193631033[/C][C]0.056444[/C][C]-0.344[/C][C]0.731147[/C][C]0.365573[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96530&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96530&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)3.779566582731111.9176521.97090.0498090.024904
Connected0.04694373894037860.0347871.34950.1783840.089192
Separate0.04199783105171430.0356481.17810.2398470.119923
Software0.6074051581107160.05184511.715800
Happiness0.0986310792586430.0579631.70160.090040.04502
Depression-0.03937912666301930.042557-0.92530.355670.177835
Belonging0.01586605926136800.0378430.41930.6753760.337688
Belonging_Final-0.01941541936310330.056444-0.3440.7311470.365573







Multiple Linear Regression - Regression Statistics
Multiple R0.653394258005351
R-squared0.426924056394364
Adjusted R-squared0.411254011061397
F-TEST (value)27.2445961273770
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.88446241278468
Sum Squared Residuals909.106837810756

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.653394258005351 \tabularnewline
R-squared & 0.426924056394364 \tabularnewline
Adjusted R-squared & 0.411254011061397 \tabularnewline
F-TEST (value) & 27.2445961273770 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 256 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.88446241278468 \tabularnewline
Sum Squared Residuals & 909.106837810756 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96530&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.653394258005351[/C][/ROW]
[ROW][C]R-squared[/C][C]0.426924056394364[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.411254011061397[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]27.2445961273770[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]256[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]1.88446241278468[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]909.106837810756[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96530&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96530&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 R0.653394258005351
R-squared0.426924056394364
Adjusted R-squared0.411254011061397
F-TEST (value)27.2445961273770
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.88446241278468
Sum Squared Residuals909.106837810756







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11315.7169326674778-2.71693266747778
21615.30464529881620.695354701183782
31916.53422660597592.46577339402406
41511.24319907102563.7568009289744
51415.8896873324328-1.88968733243279
61314.3424239462714-1.34242394627140
71914.83819200878984.16180799121016
81516.6568417465609-1.65684174656087
91415.6143966049743-1.61439660497434
101513.83988226254521.16011773745481
111614.52441321979851.47558678020148
121615.96134519141310.0386548085868819
131614.96541689650651.03458310349348
141615.13059457657630.86940542342365
151717.7266051778577-0.726605177857671
161515.0073602272847-0.00736022728472072
171514.03331126894840.966688731051586
182016.03954666325573.96045333674427
191815.094186162422.90581383758001
201615.18613762215190.813862377848057
211615.00153683346760.99846316653241
221614.58386482617381.41613517382616
231916.22690098760652.77309901239347
241614.63825105378311.36174894621694
251715.84160213608931.15839786391071
261715.83448513258501.16551486741503
271614.52940119859751.47059880140252
281516.4169297769606-1.41692977696059
291615.29551745644320.704482543556828
301413.61739445627860.382605543721379
311515.3672314701030-0.367231470103049
321212.1577948842104-0.157794884210425
331414.4670335229458-0.467033522945819
341615.54904748087970.450952519120254
351415.1519977706766-1.15199777067662
361012.4548067707195-2.4548067707195
371012.2908025947004-2.29080259470041
381415.4428753504870-1.44287535048698
391614.11256764964031.88743235035968
401614.05030069097431.94969930902571
411614.35991566120121.64008433879884
421415.4129095162212-1.41290951622119
432017.49755924374672.50244075625334
441413.73799971061440.262000289385554
451414.1390257843911-0.139025784391116
461115.1505593881384-4.1505593881384
471416.4190959972096-2.41909599720959
481514.78123391222600.218766087773978
491615.19159772331030.80840227668973
501415.3615153637810-1.36151536378102
511616.8537398386884-0.853739838688414
521413.73168927380800.268310726191956
531214.6138653598004-2.61386535980045
541615.59068990343190.409310096568081
55910.7137318072366-1.71373180723661
561411.83260460506342.16739539493663
571615.69372369001330.306276309986652
581615.23035557126270.769644428737268
591514.82300455854460.176995441455372
601613.79322244935052.20677755064947
611210.83672794920741.16327205079259
621615.43786401774420.562135982255836
631616.2989869704333-0.298986970433305
641414.4388877335844-0.438887733584363
651615.15004427002750.849955729972452
661715.74385384140771.25614615859233
671816.09034650151841.90965349848157
681814.07649049189673.92350950810328
691215.8084608807317-3.80846088073167
701615.47284798326780.527152016732215
711013.0122458267498-3.01224582674977
721414.7156655383903-0.715665538390303
731816.83798954427311.16201045572692
741817.19282818589550.807171814104506
751615.00946868929770.990531310702272
761713.09025249257743.90974750742255
771616.4072325443378-0.407232544337829
781614.21228172267391.78771827732615
791314.9614853283133-1.96148532831330
801615.08313851077660.916861489223383
811615.53609896948560.463901030514361
821615.64322947701630.356770522983692
831515.6201822872087-0.620182287208735
841514.68614370756470.313856292435273
851613.88276262753512.11723737246489
861413.95178861200210.0482113879978810
871615.23309418629930.76690581370072
881614.68130299453401.31869700546595
891514.10333817370510.896661826294864
901213.6433035668958-1.64330356689577
911716.83212464144880.167875358551157
921615.72948523077620.270514769223806
931514.90579233527870.0942076647212783
941314.8364568188003-1.83645681880029
951614.69803280606341.30196719393662
961615.69607804669080.303921953309242
971613.48328467925572.51671532074434
981615.83004170145750.169958298542461
991414.2661258632027-0.266125863202743
1001617.1940865071683-1.19408650716827
1011614.50590112878861.49409887121141
1022017.57909928367582.42090071632415
1031514.02264601404090.977353985959115
1041614.83837625185191.16162374814813
1051314.7124447739459-1.71244477394589
1061715.76043731524731.23956268475275
1071615.77206452484710.227935475152921
1081614.23260426438521.76739573561481
1091212.0024802659182-0.00248026591817174
1101615.17183854996160.828161450038395
1111615.93848803340390.0615119665961127
1121714.86253282826022.13746717173979
1131314.5286402413612-1.52864024136121
1141214.614568460888-2.61456846088799
1151816.27645244436051.72354755563947
1161415.9504759627417-1.95047596274165
1171412.99246219519511.00753780480488
1181314.7858242392293-1.78582423922934
1191615.51445795588390.48554204411607
1201314.3730308681848-1.37303086818477
1211615.40726953321840.592730466781637
1221315.9001483950515-2.90014839505153
1231617.0738036864139-1.07380368641386
1241515.9985652529538-0.998565252953813
1251616.9217558949015-0.921755894901497
1261514.75014717881310.249852821186918
1271715.76721026047391.23278973952610
1281514.00423199516910.995768004830924
1291214.7455979666711-2.74559796667113
1301613.90182246601292.09817753398713
1311013.4900189227280-3.49001892272798
1321613.48472934881742.51527065118258
1331214.1318955712898-2.13189557128976
1341415.6891601643807-1.68916016438072
1351515.1349525324793-0.134952532479329
1361311.87987029892291.12012970107707
1371514.54067598928640.459324010713589
1381113.3639577865016-2.36395778650162
1391212.9948717800782-0.994871780078202
1401113.2797734052426-2.27977340524255
1411612.87066703284813.12933296715187
1421513.57779700814501.42220299185502
1431717.0126296693111-0.0126296693111276
1441614.21772328463611.78227671536388
1451013.3076482519712-3.30764825197124
1461815.71081826463902.28918173536104
1471315.057515844885-2.05751584488500
1481614.91980860046531.08019139953471
1491312.63776380440320.362236195596831
1501012.8783257394112-2.8783257394112
1511516.1550432712530-1.15504327125297
1521613.99236085150662.00763914849345
1531611.70404505131494.29595494868507
1541412.24996754626091.75003245373915
1551012.3106299805489-2.31062998054890
1561716.83212464144880.167875358551157
1571311.56953931916061.43046068083939
1581514.00423199516910.995768004830924
1591614.67139552040851.32860447959148
1601212.5736517546432-0.573651754643187
1611312.60060369153710.39939630846291
1621312.46655135388390.53344864611615
1631212.3881607885568-0.388160788556804
1641716.57378992687700.42621007312302
1651513.67260044568511.32739955431489
1661011.4206728334644-1.42067283346442
1671414.4691619974894-0.469161997489407
1681114.2909865799885-3.29098657998851
1691314.8482927619942-1.84829276199418
1701614.43087474594941.56912525405060
1711210.36531181629621.63468818370377
1721615.70594839385070.294051606149257
1731213.9883936528962-1.98839365289617
174911.3120335908731-2.31203359087306
1751215.2885887877223-3.28858878772229
1761514.74421311565640.255786884343579
1771212.2632972969965-0.263297296996452
1781212.6879346718068-0.68793467180684
1791414.0621066117256-0.0621066117256398
1801213.4762697050290-1.47626970502904
1811615.43404807723430.565951922765726
1821111.5217489928797-0.521748992879665
1831917.16046327131091.83953672868908
1841515.5206096079202-0.520609607920211
185814.7662880903322-6.76628809033216
1861614.96809271966591.03190728033408
1871714.74767686862742.2523231313726
1881212.5418032885651-0.541803288565062
1891111.5269675255856-0.526967525585558
1901110.29932240894260.700677591057419
1911415.0449039081772-1.04490390817718
1921615.85492363747950.145076362520500
193129.657999892580332.34200010741967
1941614.30051325933001.69948674067001
1951313.9159846340245-0.915984634024543
1961515.3686335282855-0.368633528285528
1971613.09834314754632.90165685245371
1981615.31296975317590.687030246824146
1991412.48745520070841.51254479929164
2001614.77057978105631.22942021894372
2011614.19538977693681.80461022306323
2021413.56526081339240.434739186607567
2031113.7622976777595-2.76229767775952
2041214.9165699771728-2.91656997717275
2051512.96966651819912.03033348180092
2061514.83696442004550.163035579954474
2071614.8470264956861.15297350431399
2081615.43394871036260.566051289637426
2091113.9167631437977-2.91676314379775
2101514.30315947049950.696840529500508
2111214.507489606999-2.507489606999
2121216.2896849694461-4.28968496944614
2131514.30917048110010.690829518899902
2141512.16749588830622.83250411169378
2151614.88328934434421.11671065565580
2161413.42078783082380.57921216917622
2171715.06266197823011.93733802176992
2181414.3279169397482-0.327916939748238
2191311.99028890163491.00971109836511
2201515.6158919610783-0.615891961078344
2211315.0224913327296-2.02249133272956
2221414.5733033465195-0.573303346519544
2231514.56644591290410.43355408709592
2241213.4585313702885-1.45853137028855
2251312.80428073990430.195719260095656
226811.9668684285413-3.96686842854126
2271414.3096831383973-0.309683138397306
2281413.27374355278650.726256447213536
2291112.3432695732266-1.34326957322662
2301213.1609985574185-1.16099855741854
2311311.47993235152811.52006764847186
2321013.4650403340905-3.46504033409047
2331611.70045382224594.29954617775412
2341816.45586637075001.54413362925002
2351314.3053988244790-1.30539882447904
2361113.6549207425401-2.65492074254014
237411.1700281372820-7.17002813728201
2381314.8152140281387-1.81521402813869
2391614.59236330543211.40763669456793
2401011.9287261285823-1.92872612858232
2411212.4071970658913-0.407197065891325
2421213.7956003816510-1.79560038165098
243108.886344700787971.11365529921203
2441311.27700688023681.72299311976323
2451514.09262731602050.907372683979529
2461212.0467701780665-0.0467701780665329
2471413.15388286620630.846117133793704
2481012.8902928435778-2.89029284357777
2491210.80096582046091.19903417953906
2501211.88393362896460.116066371035425
2511112.1379198030589-1.13791980305892
2521011.8622634576053-1.86226345760533
2531211.66314378165700.336856218342975
2541613.17822476363682.82177523636317
2551213.7152063049677-1.71520630496769
2561414.2640878596850-0.264087859685045
2571614.68118855727991.31881144272010
2581411.82392868149752.17607131850247
2591314.7816409840600-1.78164098406003
26049.48330674262236-5.48330674262236
2611514.1743666514850.825633348514991
2621115.5502096888069-4.55020968880690
2631111.4716452522508-0.471645252250818
2641413.16729085252320.83270914747681

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 15.7169326674778 & -2.71693266747778 \tabularnewline
2 & 16 & 15.3046452988162 & 0.695354701183782 \tabularnewline
3 & 19 & 16.5342266059759 & 2.46577339402406 \tabularnewline
4 & 15 & 11.2431990710256 & 3.7568009289744 \tabularnewline
5 & 14 & 15.8896873324328 & -1.88968733243279 \tabularnewline
6 & 13 & 14.3424239462714 & -1.34242394627140 \tabularnewline
7 & 19 & 14.8381920087898 & 4.16180799121016 \tabularnewline
8 & 15 & 16.6568417465609 & -1.65684174656087 \tabularnewline
9 & 14 & 15.6143966049743 & -1.61439660497434 \tabularnewline
10 & 15 & 13.8398822625452 & 1.16011773745481 \tabularnewline
11 & 16 & 14.5244132197985 & 1.47558678020148 \tabularnewline
12 & 16 & 15.9613451914131 & 0.0386548085868819 \tabularnewline
13 & 16 & 14.9654168965065 & 1.03458310349348 \tabularnewline
14 & 16 & 15.1305945765763 & 0.86940542342365 \tabularnewline
15 & 17 & 17.7266051778577 & -0.726605177857671 \tabularnewline
16 & 15 & 15.0073602272847 & -0.00736022728472072 \tabularnewline
17 & 15 & 14.0333112689484 & 0.966688731051586 \tabularnewline
18 & 20 & 16.0395466632557 & 3.96045333674427 \tabularnewline
19 & 18 & 15.09418616242 & 2.90581383758001 \tabularnewline
20 & 16 & 15.1861376221519 & 0.813862377848057 \tabularnewline
21 & 16 & 15.0015368334676 & 0.99846316653241 \tabularnewline
22 & 16 & 14.5838648261738 & 1.41613517382616 \tabularnewline
23 & 19 & 16.2269009876065 & 2.77309901239347 \tabularnewline
24 & 16 & 14.6382510537831 & 1.36174894621694 \tabularnewline
25 & 17 & 15.8416021360893 & 1.15839786391071 \tabularnewline
26 & 17 & 15.8344851325850 & 1.16551486741503 \tabularnewline
27 & 16 & 14.5294011985975 & 1.47059880140252 \tabularnewline
28 & 15 & 16.4169297769606 & -1.41692977696059 \tabularnewline
29 & 16 & 15.2955174564432 & 0.704482543556828 \tabularnewline
30 & 14 & 13.6173944562786 & 0.382605543721379 \tabularnewline
31 & 15 & 15.3672314701030 & -0.367231470103049 \tabularnewline
32 & 12 & 12.1577948842104 & -0.157794884210425 \tabularnewline
33 & 14 & 14.4670335229458 & -0.467033522945819 \tabularnewline
34 & 16 & 15.5490474808797 & 0.450952519120254 \tabularnewline
35 & 14 & 15.1519977706766 & -1.15199777067662 \tabularnewline
36 & 10 & 12.4548067707195 & -2.4548067707195 \tabularnewline
37 & 10 & 12.2908025947004 & -2.29080259470041 \tabularnewline
38 & 14 & 15.4428753504870 & -1.44287535048698 \tabularnewline
39 & 16 & 14.1125676496403 & 1.88743235035968 \tabularnewline
40 & 16 & 14.0503006909743 & 1.94969930902571 \tabularnewline
41 & 16 & 14.3599156612012 & 1.64008433879884 \tabularnewline
42 & 14 & 15.4129095162212 & -1.41290951622119 \tabularnewline
43 & 20 & 17.4975592437467 & 2.50244075625334 \tabularnewline
44 & 14 & 13.7379997106144 & 0.262000289385554 \tabularnewline
45 & 14 & 14.1390257843911 & -0.139025784391116 \tabularnewline
46 & 11 & 15.1505593881384 & -4.1505593881384 \tabularnewline
47 & 14 & 16.4190959972096 & -2.41909599720959 \tabularnewline
48 & 15 & 14.7812339122260 & 0.218766087773978 \tabularnewline
49 & 16 & 15.1915977233103 & 0.80840227668973 \tabularnewline
50 & 14 & 15.3615153637810 & -1.36151536378102 \tabularnewline
51 & 16 & 16.8537398386884 & -0.853739838688414 \tabularnewline
52 & 14 & 13.7316892738080 & 0.268310726191956 \tabularnewline
53 & 12 & 14.6138653598004 & -2.61386535980045 \tabularnewline
54 & 16 & 15.5906899034319 & 0.409310096568081 \tabularnewline
55 & 9 & 10.7137318072366 & -1.71373180723661 \tabularnewline
56 & 14 & 11.8326046050634 & 2.16739539493663 \tabularnewline
57 & 16 & 15.6937236900133 & 0.306276309986652 \tabularnewline
58 & 16 & 15.2303555712627 & 0.769644428737268 \tabularnewline
59 & 15 & 14.8230045585446 & 0.176995441455372 \tabularnewline
60 & 16 & 13.7932224493505 & 2.20677755064947 \tabularnewline
61 & 12 & 10.8367279492074 & 1.16327205079259 \tabularnewline
62 & 16 & 15.4378640177442 & 0.562135982255836 \tabularnewline
63 & 16 & 16.2989869704333 & -0.298986970433305 \tabularnewline
64 & 14 & 14.4388877335844 & -0.438887733584363 \tabularnewline
65 & 16 & 15.1500442700275 & 0.849955729972452 \tabularnewline
66 & 17 & 15.7438538414077 & 1.25614615859233 \tabularnewline
67 & 18 & 16.0903465015184 & 1.90965349848157 \tabularnewline
68 & 18 & 14.0764904918967 & 3.92350950810328 \tabularnewline
69 & 12 & 15.8084608807317 & -3.80846088073167 \tabularnewline
70 & 16 & 15.4728479832678 & 0.527152016732215 \tabularnewline
71 & 10 & 13.0122458267498 & -3.01224582674977 \tabularnewline
72 & 14 & 14.7156655383903 & -0.715665538390303 \tabularnewline
73 & 18 & 16.8379895442731 & 1.16201045572692 \tabularnewline
74 & 18 & 17.1928281858955 & 0.807171814104506 \tabularnewline
75 & 16 & 15.0094686892977 & 0.990531310702272 \tabularnewline
76 & 17 & 13.0902524925774 & 3.90974750742255 \tabularnewline
77 & 16 & 16.4072325443378 & -0.407232544337829 \tabularnewline
78 & 16 & 14.2122817226739 & 1.78771827732615 \tabularnewline
79 & 13 & 14.9614853283133 & -1.96148532831330 \tabularnewline
80 & 16 & 15.0831385107766 & 0.916861489223383 \tabularnewline
81 & 16 & 15.5360989694856 & 0.463901030514361 \tabularnewline
82 & 16 & 15.6432294770163 & 0.356770522983692 \tabularnewline
83 & 15 & 15.6201822872087 & -0.620182287208735 \tabularnewline
84 & 15 & 14.6861437075647 & 0.313856292435273 \tabularnewline
85 & 16 & 13.8827626275351 & 2.11723737246489 \tabularnewline
86 & 14 & 13.9517886120021 & 0.0482113879978810 \tabularnewline
87 & 16 & 15.2330941862993 & 0.76690581370072 \tabularnewline
88 & 16 & 14.6813029945340 & 1.31869700546595 \tabularnewline
89 & 15 & 14.1033381737051 & 0.896661826294864 \tabularnewline
90 & 12 & 13.6433035668958 & -1.64330356689577 \tabularnewline
91 & 17 & 16.8321246414488 & 0.167875358551157 \tabularnewline
92 & 16 & 15.7294852307762 & 0.270514769223806 \tabularnewline
93 & 15 & 14.9057923352787 & 0.0942076647212783 \tabularnewline
94 & 13 & 14.8364568188003 & -1.83645681880029 \tabularnewline
95 & 16 & 14.6980328060634 & 1.30196719393662 \tabularnewline
96 & 16 & 15.6960780466908 & 0.303921953309242 \tabularnewline
97 & 16 & 13.4832846792557 & 2.51671532074434 \tabularnewline
98 & 16 & 15.8300417014575 & 0.169958298542461 \tabularnewline
99 & 14 & 14.2661258632027 & -0.266125863202743 \tabularnewline
100 & 16 & 17.1940865071683 & -1.19408650716827 \tabularnewline
101 & 16 & 14.5059011287886 & 1.49409887121141 \tabularnewline
102 & 20 & 17.5790992836758 & 2.42090071632415 \tabularnewline
103 & 15 & 14.0226460140409 & 0.977353985959115 \tabularnewline
104 & 16 & 14.8383762518519 & 1.16162374814813 \tabularnewline
105 & 13 & 14.7124447739459 & -1.71244477394589 \tabularnewline
106 & 17 & 15.7604373152473 & 1.23956268475275 \tabularnewline
107 & 16 & 15.7720645248471 & 0.227935475152921 \tabularnewline
108 & 16 & 14.2326042643852 & 1.76739573561481 \tabularnewline
109 & 12 & 12.0024802659182 & -0.00248026591817174 \tabularnewline
110 & 16 & 15.1718385499616 & 0.828161450038395 \tabularnewline
111 & 16 & 15.9384880334039 & 0.0615119665961127 \tabularnewline
112 & 17 & 14.8625328282602 & 2.13746717173979 \tabularnewline
113 & 13 & 14.5286402413612 & -1.52864024136121 \tabularnewline
114 & 12 & 14.614568460888 & -2.61456846088799 \tabularnewline
115 & 18 & 16.2764524443605 & 1.72354755563947 \tabularnewline
116 & 14 & 15.9504759627417 & -1.95047596274165 \tabularnewline
117 & 14 & 12.9924621951951 & 1.00753780480488 \tabularnewline
118 & 13 & 14.7858242392293 & -1.78582423922934 \tabularnewline
119 & 16 & 15.5144579558839 & 0.48554204411607 \tabularnewline
120 & 13 & 14.3730308681848 & -1.37303086818477 \tabularnewline
121 & 16 & 15.4072695332184 & 0.592730466781637 \tabularnewline
122 & 13 & 15.9001483950515 & -2.90014839505153 \tabularnewline
123 & 16 & 17.0738036864139 & -1.07380368641386 \tabularnewline
124 & 15 & 15.9985652529538 & -0.998565252953813 \tabularnewline
125 & 16 & 16.9217558949015 & -0.921755894901497 \tabularnewline
126 & 15 & 14.7501471788131 & 0.249852821186918 \tabularnewline
127 & 17 & 15.7672102604739 & 1.23278973952610 \tabularnewline
128 & 15 & 14.0042319951691 & 0.995768004830924 \tabularnewline
129 & 12 & 14.7455979666711 & -2.74559796667113 \tabularnewline
130 & 16 & 13.9018224660129 & 2.09817753398713 \tabularnewline
131 & 10 & 13.4900189227280 & -3.49001892272798 \tabularnewline
132 & 16 & 13.4847293488174 & 2.51527065118258 \tabularnewline
133 & 12 & 14.1318955712898 & -2.13189557128976 \tabularnewline
134 & 14 & 15.6891601643807 & -1.68916016438072 \tabularnewline
135 & 15 & 15.1349525324793 & -0.134952532479329 \tabularnewline
136 & 13 & 11.8798702989229 & 1.12012970107707 \tabularnewline
137 & 15 & 14.5406759892864 & 0.459324010713589 \tabularnewline
138 & 11 & 13.3639577865016 & -2.36395778650162 \tabularnewline
139 & 12 & 12.9948717800782 & -0.994871780078202 \tabularnewline
140 & 11 & 13.2797734052426 & -2.27977340524255 \tabularnewline
141 & 16 & 12.8706670328481 & 3.12933296715187 \tabularnewline
142 & 15 & 13.5777970081450 & 1.42220299185502 \tabularnewline
143 & 17 & 17.0126296693111 & -0.0126296693111276 \tabularnewline
144 & 16 & 14.2177232846361 & 1.78227671536388 \tabularnewline
145 & 10 & 13.3076482519712 & -3.30764825197124 \tabularnewline
146 & 18 & 15.7108182646390 & 2.28918173536104 \tabularnewline
147 & 13 & 15.057515844885 & -2.05751584488500 \tabularnewline
148 & 16 & 14.9198086004653 & 1.08019139953471 \tabularnewline
149 & 13 & 12.6377638044032 & 0.362236195596831 \tabularnewline
150 & 10 & 12.8783257394112 & -2.8783257394112 \tabularnewline
151 & 15 & 16.1550432712530 & -1.15504327125297 \tabularnewline
152 & 16 & 13.9923608515066 & 2.00763914849345 \tabularnewline
153 & 16 & 11.7040450513149 & 4.29595494868507 \tabularnewline
154 & 14 & 12.2499675462609 & 1.75003245373915 \tabularnewline
155 & 10 & 12.3106299805489 & -2.31062998054890 \tabularnewline
156 & 17 & 16.8321246414488 & 0.167875358551157 \tabularnewline
157 & 13 & 11.5695393191606 & 1.43046068083939 \tabularnewline
158 & 15 & 14.0042319951691 & 0.995768004830924 \tabularnewline
159 & 16 & 14.6713955204085 & 1.32860447959148 \tabularnewline
160 & 12 & 12.5736517546432 & -0.573651754643187 \tabularnewline
161 & 13 & 12.6006036915371 & 0.39939630846291 \tabularnewline
162 & 13 & 12.4665513538839 & 0.53344864611615 \tabularnewline
163 & 12 & 12.3881607885568 & -0.388160788556804 \tabularnewline
164 & 17 & 16.5737899268770 & 0.42621007312302 \tabularnewline
165 & 15 & 13.6726004456851 & 1.32739955431489 \tabularnewline
166 & 10 & 11.4206728334644 & -1.42067283346442 \tabularnewline
167 & 14 & 14.4691619974894 & -0.469161997489407 \tabularnewline
168 & 11 & 14.2909865799885 & -3.29098657998851 \tabularnewline
169 & 13 & 14.8482927619942 & -1.84829276199418 \tabularnewline
170 & 16 & 14.4308747459494 & 1.56912525405060 \tabularnewline
171 & 12 & 10.3653118162962 & 1.63468818370377 \tabularnewline
172 & 16 & 15.7059483938507 & 0.294051606149257 \tabularnewline
173 & 12 & 13.9883936528962 & -1.98839365289617 \tabularnewline
174 & 9 & 11.3120335908731 & -2.31203359087306 \tabularnewline
175 & 12 & 15.2885887877223 & -3.28858878772229 \tabularnewline
176 & 15 & 14.7442131156564 & 0.255786884343579 \tabularnewline
177 & 12 & 12.2632972969965 & -0.263297296996452 \tabularnewline
178 & 12 & 12.6879346718068 & -0.68793467180684 \tabularnewline
179 & 14 & 14.0621066117256 & -0.0621066117256398 \tabularnewline
180 & 12 & 13.4762697050290 & -1.47626970502904 \tabularnewline
181 & 16 & 15.4340480772343 & 0.565951922765726 \tabularnewline
182 & 11 & 11.5217489928797 & -0.521748992879665 \tabularnewline
183 & 19 & 17.1604632713109 & 1.83953672868908 \tabularnewline
184 & 15 & 15.5206096079202 & -0.520609607920211 \tabularnewline
185 & 8 & 14.7662880903322 & -6.76628809033216 \tabularnewline
186 & 16 & 14.9680927196659 & 1.03190728033408 \tabularnewline
187 & 17 & 14.7476768686274 & 2.2523231313726 \tabularnewline
188 & 12 & 12.5418032885651 & -0.541803288565062 \tabularnewline
189 & 11 & 11.5269675255856 & -0.526967525585558 \tabularnewline
190 & 11 & 10.2993224089426 & 0.700677591057419 \tabularnewline
191 & 14 & 15.0449039081772 & -1.04490390817718 \tabularnewline
192 & 16 & 15.8549236374795 & 0.145076362520500 \tabularnewline
193 & 12 & 9.65799989258033 & 2.34200010741967 \tabularnewline
194 & 16 & 14.3005132593300 & 1.69948674067001 \tabularnewline
195 & 13 & 13.9159846340245 & -0.915984634024543 \tabularnewline
196 & 15 & 15.3686335282855 & -0.368633528285528 \tabularnewline
197 & 16 & 13.0983431475463 & 2.90165685245371 \tabularnewline
198 & 16 & 15.3129697531759 & 0.687030246824146 \tabularnewline
199 & 14 & 12.4874552007084 & 1.51254479929164 \tabularnewline
200 & 16 & 14.7705797810563 & 1.22942021894372 \tabularnewline
201 & 16 & 14.1953897769368 & 1.80461022306323 \tabularnewline
202 & 14 & 13.5652608133924 & 0.434739186607567 \tabularnewline
203 & 11 & 13.7622976777595 & -2.76229767775952 \tabularnewline
204 & 12 & 14.9165699771728 & -2.91656997717275 \tabularnewline
205 & 15 & 12.9696665181991 & 2.03033348180092 \tabularnewline
206 & 15 & 14.8369644200455 & 0.163035579954474 \tabularnewline
207 & 16 & 14.847026495686 & 1.15297350431399 \tabularnewline
208 & 16 & 15.4339487103626 & 0.566051289637426 \tabularnewline
209 & 11 & 13.9167631437977 & -2.91676314379775 \tabularnewline
210 & 15 & 14.3031594704995 & 0.696840529500508 \tabularnewline
211 & 12 & 14.507489606999 & -2.507489606999 \tabularnewline
212 & 12 & 16.2896849694461 & -4.28968496944614 \tabularnewline
213 & 15 & 14.3091704811001 & 0.690829518899902 \tabularnewline
214 & 15 & 12.1674958883062 & 2.83250411169378 \tabularnewline
215 & 16 & 14.8832893443442 & 1.11671065565580 \tabularnewline
216 & 14 & 13.4207878308238 & 0.57921216917622 \tabularnewline
217 & 17 & 15.0626619782301 & 1.93733802176992 \tabularnewline
218 & 14 & 14.3279169397482 & -0.327916939748238 \tabularnewline
219 & 13 & 11.9902889016349 & 1.00971109836511 \tabularnewline
220 & 15 & 15.6158919610783 & -0.615891961078344 \tabularnewline
221 & 13 & 15.0224913327296 & -2.02249133272956 \tabularnewline
222 & 14 & 14.5733033465195 & -0.573303346519544 \tabularnewline
223 & 15 & 14.5664459129041 & 0.43355408709592 \tabularnewline
224 & 12 & 13.4585313702885 & -1.45853137028855 \tabularnewline
225 & 13 & 12.8042807399043 & 0.195719260095656 \tabularnewline
226 & 8 & 11.9668684285413 & -3.96686842854126 \tabularnewline
227 & 14 & 14.3096831383973 & -0.309683138397306 \tabularnewline
228 & 14 & 13.2737435527865 & 0.726256447213536 \tabularnewline
229 & 11 & 12.3432695732266 & -1.34326957322662 \tabularnewline
230 & 12 & 13.1609985574185 & -1.16099855741854 \tabularnewline
231 & 13 & 11.4799323515281 & 1.52006764847186 \tabularnewline
232 & 10 & 13.4650403340905 & -3.46504033409047 \tabularnewline
233 & 16 & 11.7004538222459 & 4.29954617775412 \tabularnewline
234 & 18 & 16.4558663707500 & 1.54413362925002 \tabularnewline
235 & 13 & 14.3053988244790 & -1.30539882447904 \tabularnewline
236 & 11 & 13.6549207425401 & -2.65492074254014 \tabularnewline
237 & 4 & 11.1700281372820 & -7.17002813728201 \tabularnewline
238 & 13 & 14.8152140281387 & -1.81521402813869 \tabularnewline
239 & 16 & 14.5923633054321 & 1.40763669456793 \tabularnewline
240 & 10 & 11.9287261285823 & -1.92872612858232 \tabularnewline
241 & 12 & 12.4071970658913 & -0.407197065891325 \tabularnewline
242 & 12 & 13.7956003816510 & -1.79560038165098 \tabularnewline
243 & 10 & 8.88634470078797 & 1.11365529921203 \tabularnewline
244 & 13 & 11.2770068802368 & 1.72299311976323 \tabularnewline
245 & 15 & 14.0926273160205 & 0.907372683979529 \tabularnewline
246 & 12 & 12.0467701780665 & -0.0467701780665329 \tabularnewline
247 & 14 & 13.1538828662063 & 0.846117133793704 \tabularnewline
248 & 10 & 12.8902928435778 & -2.89029284357777 \tabularnewline
249 & 12 & 10.8009658204609 & 1.19903417953906 \tabularnewline
250 & 12 & 11.8839336289646 & 0.116066371035425 \tabularnewline
251 & 11 & 12.1379198030589 & -1.13791980305892 \tabularnewline
252 & 10 & 11.8622634576053 & -1.86226345760533 \tabularnewline
253 & 12 & 11.6631437816570 & 0.336856218342975 \tabularnewline
254 & 16 & 13.1782247636368 & 2.82177523636317 \tabularnewline
255 & 12 & 13.7152063049677 & -1.71520630496769 \tabularnewline
256 & 14 & 14.2640878596850 & -0.264087859685045 \tabularnewline
257 & 16 & 14.6811885572799 & 1.31881144272010 \tabularnewline
258 & 14 & 11.8239286814975 & 2.17607131850247 \tabularnewline
259 & 13 & 14.7816409840600 & -1.78164098406003 \tabularnewline
260 & 4 & 9.48330674262236 & -5.48330674262236 \tabularnewline
261 & 15 & 14.174366651485 & 0.825633348514991 \tabularnewline
262 & 11 & 15.5502096888069 & -4.55020968880690 \tabularnewline
263 & 11 & 11.4716452522508 & -0.471645252250818 \tabularnewline
264 & 14 & 13.1672908525232 & 0.83270914747681 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96530&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]13[/C][C]15.7169326674778[/C][C]-2.71693266747778[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.3046452988162[/C][C]0.695354701183782[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]16.5342266059759[/C][C]2.46577339402406[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]11.2431990710256[/C][C]3.7568009289744[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]15.8896873324328[/C][C]-1.88968733243279[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.3424239462714[/C][C]-1.34242394627140[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]14.8381920087898[/C][C]4.16180799121016[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]16.6568417465609[/C][C]-1.65684174656087[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]15.6143966049743[/C][C]-1.61439660497434[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]13.8398822625452[/C][C]1.16011773745481[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.5244132197985[/C][C]1.47558678020148[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]15.9613451914131[/C][C]0.0386548085868819[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]14.9654168965065[/C][C]1.03458310349348[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.1305945765763[/C][C]0.86940542342365[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]17.7266051778577[/C][C]-0.726605177857671[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.0073602272847[/C][C]-0.00736022728472072[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.0333112689484[/C][C]0.966688731051586[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.0395466632557[/C][C]3.96045333674427[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.09418616242[/C][C]2.90581383758001[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.1861376221519[/C][C]0.813862377848057[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.0015368334676[/C][C]0.99846316653241[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]14.5838648261738[/C][C]1.41613517382616[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.2269009876065[/C][C]2.77309901239347[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]14.6382510537831[/C][C]1.36174894621694[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.8416021360893[/C][C]1.15839786391071[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]15.8344851325850[/C][C]1.16551486741503[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.5294011985975[/C][C]1.47059880140252[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.4169297769606[/C][C]-1.41692977696059[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.2955174564432[/C][C]0.704482543556828[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]13.6173944562786[/C][C]0.382605543721379[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.3672314701030[/C][C]-0.367231470103049[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.1577948842104[/C][C]-0.157794884210425[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.4670335229458[/C][C]-0.467033522945819[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.5490474808797[/C][C]0.450952519120254[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.1519977706766[/C][C]-1.15199777067662[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.4548067707195[/C][C]-2.4548067707195[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]12.2908025947004[/C][C]-2.29080259470041[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.4428753504870[/C][C]-1.44287535048698[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.1125676496403[/C][C]1.88743235035968[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.0503006909743[/C][C]1.94969930902571[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.3599156612012[/C][C]1.64008433879884[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.4129095162212[/C][C]-1.41290951622119[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.4975592437467[/C][C]2.50244075625334[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]13.7379997106144[/C][C]0.262000289385554[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.1390257843911[/C][C]-0.139025784391116[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.1505593881384[/C][C]-4.1505593881384[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.4190959972096[/C][C]-2.41909599720959[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.7812339122260[/C][C]0.218766087773978[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.1915977233103[/C][C]0.80840227668973[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.3615153637810[/C][C]-1.36151536378102[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]16.8537398386884[/C][C]-0.853739838688414[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.7316892738080[/C][C]0.268310726191956[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]14.6138653598004[/C][C]-2.61386535980045[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.5906899034319[/C][C]0.409310096568081[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]10.7137318072366[/C][C]-1.71373180723661[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]11.8326046050634[/C][C]2.16739539493663[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.6937236900133[/C][C]0.306276309986652[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.2303555712627[/C][C]0.769644428737268[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]14.8230045585446[/C][C]0.176995441455372[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]13.7932224493505[/C][C]2.20677755064947[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]10.8367279492074[/C][C]1.16327205079259[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.4378640177442[/C][C]0.562135982255836[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.2989869704333[/C][C]-0.298986970433305[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.4388877335844[/C][C]-0.438887733584363[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.1500442700275[/C][C]0.849955729972452[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]15.7438538414077[/C][C]1.25614615859233[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.0903465015184[/C][C]1.90965349848157[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.0764904918967[/C][C]3.92350950810328[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.8084608807317[/C][C]-3.80846088073167[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.4728479832678[/C][C]0.527152016732215[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.0122458267498[/C][C]-3.01224582674977[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.7156655383903[/C][C]-0.715665538390303[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.8379895442731[/C][C]1.16201045572692[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.1928281858955[/C][C]0.807171814104506[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.0094686892977[/C][C]0.990531310702272[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.0902524925774[/C][C]3.90974750742255[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.4072325443378[/C][C]-0.407232544337829[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.2122817226739[/C][C]1.78771827732615[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]14.9614853283133[/C][C]-1.96148532831330[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.0831385107766[/C][C]0.916861489223383[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.5360989694856[/C][C]0.463901030514361[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.6432294770163[/C][C]0.356770522983692[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.6201822872087[/C][C]-0.620182287208735[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.6861437075647[/C][C]0.313856292435273[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]13.8827626275351[/C][C]2.11723737246489[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]13.9517886120021[/C][C]0.0482113879978810[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.2330941862993[/C][C]0.76690581370072[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.6813029945340[/C][C]1.31869700546595[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.1033381737051[/C][C]0.896661826294864[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.6433035668958[/C][C]-1.64330356689577[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.8321246414488[/C][C]0.167875358551157[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.7294852307762[/C][C]0.270514769223806[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]14.9057923352787[/C][C]0.0942076647212783[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.8364568188003[/C][C]-1.83645681880029[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.6980328060634[/C][C]1.30196719393662[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.6960780466908[/C][C]0.303921953309242[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.4832846792557[/C][C]2.51671532074434[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.8300417014575[/C][C]0.169958298542461[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.2661258632027[/C][C]-0.266125863202743[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.1940865071683[/C][C]-1.19408650716827[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.5059011287886[/C][C]1.49409887121141[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.5790992836758[/C][C]2.42090071632415[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.0226460140409[/C][C]0.977353985959115[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]14.8383762518519[/C][C]1.16162374814813[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.7124447739459[/C][C]-1.71244477394589[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.7604373152473[/C][C]1.23956268475275[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.7720645248471[/C][C]0.227935475152921[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.2326042643852[/C][C]1.76739573561481[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.0024802659182[/C][C]-0.00248026591817174[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.1718385499616[/C][C]0.828161450038395[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]15.9384880334039[/C][C]0.0615119665961127[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]14.8625328282602[/C][C]2.13746717173979[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.5286402413612[/C][C]-1.52864024136121[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.614568460888[/C][C]-2.61456846088799[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.2764524443605[/C][C]1.72354755563947[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.9504759627417[/C][C]-1.95047596274165[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]12.9924621951951[/C][C]1.00753780480488[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.7858242392293[/C][C]-1.78582423922934[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.5144579558839[/C][C]0.48554204411607[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.3730308681848[/C][C]-1.37303086818477[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.4072695332184[/C][C]0.592730466781637[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.9001483950515[/C][C]-2.90014839505153[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]17.0738036864139[/C][C]-1.07380368641386[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.9985652529538[/C][C]-0.998565252953813[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.9217558949015[/C][C]-0.921755894901497[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.7501471788131[/C][C]0.249852821186918[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.7672102604739[/C][C]1.23278973952610[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]14.0042319951691[/C][C]0.995768004830924[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.7455979666711[/C][C]-2.74559796667113[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.9018224660129[/C][C]2.09817753398713[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.4900189227280[/C][C]-3.49001892272798[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4847293488174[/C][C]2.51527065118258[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.1318955712898[/C][C]-2.13189557128976[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.6891601643807[/C][C]-1.68916016438072[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.1349525324793[/C][C]-0.134952532479329[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]11.8798702989229[/C][C]1.12012970107707[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.5406759892864[/C][C]0.459324010713589[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.3639577865016[/C][C]-2.36395778650162[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]12.9948717800782[/C][C]-0.994871780078202[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.2797734052426[/C][C]-2.27977340524255[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8706670328481[/C][C]3.12933296715187[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.5777970081450[/C][C]1.42220299185502[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]17.0126296693111[/C][C]-0.0126296693111276[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.2177232846361[/C][C]1.78227671536388[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.3076482519712[/C][C]-3.30764825197124[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.7108182646390[/C][C]2.28918173536104[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.057515844885[/C][C]-2.05751584488500[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.9198086004653[/C][C]1.08019139953471[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.6377638044032[/C][C]0.362236195596831[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.8783257394112[/C][C]-2.8783257394112[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]16.1550432712530[/C][C]-1.15504327125297[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.9923608515066[/C][C]2.00763914849345[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.7040450513149[/C][C]4.29595494868507[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.2499675462609[/C][C]1.75003245373915[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.3106299805489[/C][C]-2.31062998054890[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.8321246414488[/C][C]0.167875358551157[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.5695393191606[/C][C]1.43046068083939[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]14.0042319951691[/C][C]0.995768004830924[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.6713955204085[/C][C]1.32860447959148[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.5736517546432[/C][C]-0.573651754643187[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.6006036915371[/C][C]0.39939630846291[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.4665513538839[/C][C]0.53344864611615[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.3881607885568[/C][C]-0.388160788556804[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.5737899268770[/C][C]0.42621007312302[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.6726004456851[/C][C]1.32739955431489[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.4206728334644[/C][C]-1.42067283346442[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.4691619974894[/C][C]-0.469161997489407[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.2909865799885[/C][C]-3.29098657998851[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.8482927619942[/C][C]-1.84829276199418[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.4308747459494[/C][C]1.56912525405060[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.3653118162962[/C][C]1.63468818370377[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.7059483938507[/C][C]0.294051606149257[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.9883936528962[/C][C]-1.98839365289617[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.3120335908731[/C][C]-2.31203359087306[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]15.2885887877223[/C][C]-3.28858878772229[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.7442131156564[/C][C]0.255786884343579[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.2632972969965[/C][C]-0.263297296996452[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.6879346718068[/C][C]-0.68793467180684[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]14.0621066117256[/C][C]-0.0621066117256398[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.4762697050290[/C][C]-1.47626970502904[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]15.4340480772343[/C][C]0.565951922765726[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.5217489928797[/C][C]-0.521748992879665[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]17.1604632713109[/C][C]1.83953672868908[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.5206096079202[/C][C]-0.520609607920211[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.7662880903322[/C][C]-6.76628809033216[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.9680927196659[/C][C]1.03190728033408[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.7476768686274[/C][C]2.2523231313726[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.5418032885651[/C][C]-0.541803288565062[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.5269675255856[/C][C]-0.526967525585558[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.2993224089426[/C][C]0.700677591057419[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]15.0449039081772[/C][C]-1.04490390817718[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.8549236374795[/C][C]0.145076362520500[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.65799989258033[/C][C]2.34200010741967[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.3005132593300[/C][C]1.69948674067001[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.9159846340245[/C][C]-0.915984634024543[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]15.3686335282855[/C][C]-0.368633528285528[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]13.0983431475463[/C][C]2.90165685245371[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.3129697531759[/C][C]0.687030246824146[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4874552007084[/C][C]1.51254479929164[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.7705797810563[/C][C]1.22942021894372[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]14.1953897769368[/C][C]1.80461022306323[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.5652608133924[/C][C]0.434739186607567[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.7622976777595[/C][C]-2.76229767775952[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.9165699771728[/C][C]-2.91656997717275[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.9696665181991[/C][C]2.03033348180092[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.8369644200455[/C][C]0.163035579954474[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.847026495686[/C][C]1.15297350431399[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]15.4339487103626[/C][C]0.566051289637426[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.9167631437977[/C][C]-2.91676314379775[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]14.3031594704995[/C][C]0.696840529500508[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.507489606999[/C][C]-2.507489606999[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]16.2896849694461[/C][C]-4.28968496944614[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.3091704811001[/C][C]0.690829518899902[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.1674958883062[/C][C]2.83250411169378[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.8832893443442[/C][C]1.11671065565580[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.4207878308238[/C][C]0.57921216917622[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]15.0626619782301[/C][C]1.93733802176992[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.3279169397482[/C][C]-0.327916939748238[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.9902889016349[/C][C]1.00971109836511[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.6158919610783[/C][C]-0.615891961078344[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]15.0224913327296[/C][C]-2.02249133272956[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]14.5733033465195[/C][C]-0.573303346519544[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.5664459129041[/C][C]0.43355408709592[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.4585313702885[/C][C]-1.45853137028855[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.8042807399043[/C][C]0.195719260095656[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.9668684285413[/C][C]-3.96686842854126[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]14.3096831383973[/C][C]-0.309683138397306[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]13.2737435527865[/C][C]0.726256447213536[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.3432695732266[/C][C]-1.34326957322662[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]13.1609985574185[/C][C]-1.16099855741854[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.4799323515281[/C][C]1.52006764847186[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.4650403340905[/C][C]-3.46504033409047[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.7004538222459[/C][C]4.29954617775412[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]16.4558663707500[/C][C]1.54413362925002[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]14.3053988244790[/C][C]-1.30539882447904[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.6549207425401[/C][C]-2.65492074254014[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]11.1700281372820[/C][C]-7.17002813728201[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.8152140281387[/C][C]-1.81521402813869[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.5923633054321[/C][C]1.40763669456793[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.9287261285823[/C][C]-1.92872612858232[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.4071970658913[/C][C]-0.407197065891325[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.7956003816510[/C][C]-1.79560038165098[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.88634470078797[/C][C]1.11365529921203[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]11.2770068802368[/C][C]1.72299311976323[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]14.0926273160205[/C][C]0.907372683979529[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]12.0467701780665[/C][C]-0.0467701780665329[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]13.1538828662063[/C][C]0.846117133793704[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.8902928435778[/C][C]-2.89029284357777[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.8009658204609[/C][C]1.19903417953906[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.8839336289646[/C][C]0.116066371035425[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]12.1379198030589[/C][C]-1.13791980305892[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.8622634576053[/C][C]-1.86226345760533[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.6631437816570[/C][C]0.336856218342975[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]13.1782247636368[/C][C]2.82177523636317[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.7152063049677[/C][C]-1.71520630496769[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]14.2640878596850[/C][C]-0.264087859685045[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.6811885572799[/C][C]1.31881144272010[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.8239286814975[/C][C]2.17607131850247[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.7816409840600[/C][C]-1.78164098406003[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.48330674262236[/C][C]-5.48330674262236[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]14.174366651485[/C][C]0.825633348514991[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]15.5502096888069[/C][C]-4.55020968880690[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.4716452522508[/C][C]-0.471645252250818[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.1672908525232[/C][C]0.83270914747681[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96530&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96530&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
11315.7169326674778-2.71693266747778
21615.30464529881620.695354701183782
31916.53422660597592.46577339402406
41511.24319907102563.7568009289744
51415.8896873324328-1.88968733243279
61314.3424239462714-1.34242394627140
71914.83819200878984.16180799121016
81516.6568417465609-1.65684174656087
91415.6143966049743-1.61439660497434
101513.83988226254521.16011773745481
111614.52441321979851.47558678020148
121615.96134519141310.0386548085868819
131614.96541689650651.03458310349348
141615.13059457657630.86940542342365
151717.7266051778577-0.726605177857671
161515.0073602272847-0.00736022728472072
171514.03331126894840.966688731051586
182016.03954666325573.96045333674427
191815.094186162422.90581383758001
201615.18613762215190.813862377848057
211615.00153683346760.99846316653241
221614.58386482617381.41613517382616
231916.22690098760652.77309901239347
241614.63825105378311.36174894621694
251715.84160213608931.15839786391071
261715.83448513258501.16551486741503
271614.52940119859751.47059880140252
281516.4169297769606-1.41692977696059
291615.29551745644320.704482543556828
301413.61739445627860.382605543721379
311515.3672314701030-0.367231470103049
321212.1577948842104-0.157794884210425
331414.4670335229458-0.467033522945819
341615.54904748087970.450952519120254
351415.1519977706766-1.15199777067662
361012.4548067707195-2.4548067707195
371012.2908025947004-2.29080259470041
381415.4428753504870-1.44287535048698
391614.11256764964031.88743235035968
401614.05030069097431.94969930902571
411614.35991566120121.64008433879884
421415.4129095162212-1.41290951622119
432017.49755924374672.50244075625334
441413.73799971061440.262000289385554
451414.1390257843911-0.139025784391116
461115.1505593881384-4.1505593881384
471416.4190959972096-2.41909599720959
481514.78123391222600.218766087773978
491615.19159772331030.80840227668973
501415.3615153637810-1.36151536378102
511616.8537398386884-0.853739838688414
521413.73168927380800.268310726191956
531214.6138653598004-2.61386535980045
541615.59068990343190.409310096568081
55910.7137318072366-1.71373180723661
561411.83260460506342.16739539493663
571615.69372369001330.306276309986652
581615.23035557126270.769644428737268
591514.82300455854460.176995441455372
601613.79322244935052.20677755064947
611210.83672794920741.16327205079259
621615.43786401774420.562135982255836
631616.2989869704333-0.298986970433305
641414.4388877335844-0.438887733584363
651615.15004427002750.849955729972452
661715.74385384140771.25614615859233
671816.09034650151841.90965349848157
681814.07649049189673.92350950810328
691215.8084608807317-3.80846088073167
701615.47284798326780.527152016732215
711013.0122458267498-3.01224582674977
721414.7156655383903-0.715665538390303
731816.83798954427311.16201045572692
741817.19282818589550.807171814104506
751615.00946868929770.990531310702272
761713.09025249257743.90974750742255
771616.4072325443378-0.407232544337829
781614.21228172267391.78771827732615
791314.9614853283133-1.96148532831330
801615.08313851077660.916861489223383
811615.53609896948560.463901030514361
821615.64322947701630.356770522983692
831515.6201822872087-0.620182287208735
841514.68614370756470.313856292435273
851613.88276262753512.11723737246489
861413.95178861200210.0482113879978810
871615.23309418629930.76690581370072
881614.68130299453401.31869700546595
891514.10333817370510.896661826294864
901213.6433035668958-1.64330356689577
911716.83212464144880.167875358551157
921615.72948523077620.270514769223806
931514.90579233527870.0942076647212783
941314.8364568188003-1.83645681880029
951614.69803280606341.30196719393662
961615.69607804669080.303921953309242
971613.48328467925572.51671532074434
981615.83004170145750.169958298542461
991414.2661258632027-0.266125863202743
1001617.1940865071683-1.19408650716827
1011614.50590112878861.49409887121141
1022017.57909928367582.42090071632415
1031514.02264601404090.977353985959115
1041614.83837625185191.16162374814813
1051314.7124447739459-1.71244477394589
1061715.76043731524731.23956268475275
1071615.77206452484710.227935475152921
1081614.23260426438521.76739573561481
1091212.0024802659182-0.00248026591817174
1101615.17183854996160.828161450038395
1111615.93848803340390.0615119665961127
1121714.86253282826022.13746717173979
1131314.5286402413612-1.52864024136121
1141214.614568460888-2.61456846088799
1151816.27645244436051.72354755563947
1161415.9504759627417-1.95047596274165
1171412.99246219519511.00753780480488
1181314.7858242392293-1.78582423922934
1191615.51445795588390.48554204411607
1201314.3730308681848-1.37303086818477
1211615.40726953321840.592730466781637
1221315.9001483950515-2.90014839505153
1231617.0738036864139-1.07380368641386
1241515.9985652529538-0.998565252953813
1251616.9217558949015-0.921755894901497
1261514.75014717881310.249852821186918
1271715.76721026047391.23278973952610
1281514.00423199516910.995768004830924
1291214.7455979666711-2.74559796667113
1301613.90182246601292.09817753398713
1311013.4900189227280-3.49001892272798
1321613.48472934881742.51527065118258
1331214.1318955712898-2.13189557128976
1341415.6891601643807-1.68916016438072
1351515.1349525324793-0.134952532479329
1361311.87987029892291.12012970107707
1371514.54067598928640.459324010713589
1381113.3639577865016-2.36395778650162
1391212.9948717800782-0.994871780078202
1401113.2797734052426-2.27977340524255
1411612.87066703284813.12933296715187
1421513.57779700814501.42220299185502
1431717.0126296693111-0.0126296693111276
1441614.21772328463611.78227671536388
1451013.3076482519712-3.30764825197124
1461815.71081826463902.28918173536104
1471315.057515844885-2.05751584488500
1481614.91980860046531.08019139953471
1491312.63776380440320.362236195596831
1501012.8783257394112-2.8783257394112
1511516.1550432712530-1.15504327125297
1521613.99236085150662.00763914849345
1531611.70404505131494.29595494868507
1541412.24996754626091.75003245373915
1551012.3106299805489-2.31062998054890
1561716.83212464144880.167875358551157
1571311.56953931916061.43046068083939
1581514.00423199516910.995768004830924
1591614.67139552040851.32860447959148
1601212.5736517546432-0.573651754643187
1611312.60060369153710.39939630846291
1621312.46655135388390.53344864611615
1631212.3881607885568-0.388160788556804
1641716.57378992687700.42621007312302
1651513.67260044568511.32739955431489
1661011.4206728334644-1.42067283346442
1671414.4691619974894-0.469161997489407
1681114.2909865799885-3.29098657998851
1691314.8482927619942-1.84829276199418
1701614.43087474594941.56912525405060
1711210.36531181629621.63468818370377
1721615.70594839385070.294051606149257
1731213.9883936528962-1.98839365289617
174911.3120335908731-2.31203359087306
1751215.2885887877223-3.28858878772229
1761514.74421311565640.255786884343579
1771212.2632972969965-0.263297296996452
1781212.6879346718068-0.68793467180684
1791414.0621066117256-0.0621066117256398
1801213.4762697050290-1.47626970502904
1811615.43404807723430.565951922765726
1821111.5217489928797-0.521748992879665
1831917.16046327131091.83953672868908
1841515.5206096079202-0.520609607920211
185814.7662880903322-6.76628809033216
1861614.96809271966591.03190728033408
1871714.74767686862742.2523231313726
1881212.5418032885651-0.541803288565062
1891111.5269675255856-0.526967525585558
1901110.29932240894260.700677591057419
1911415.0449039081772-1.04490390817718
1921615.85492363747950.145076362520500
193129.657999892580332.34200010741967
1941614.30051325933001.69948674067001
1951313.9159846340245-0.915984634024543
1961515.3686335282855-0.368633528285528
1971613.09834314754632.90165685245371
1981615.31296975317590.687030246824146
1991412.48745520070841.51254479929164
2001614.77057978105631.22942021894372
2011614.19538977693681.80461022306323
2021413.56526081339240.434739186607567
2031113.7622976777595-2.76229767775952
2041214.9165699771728-2.91656997717275
2051512.96966651819912.03033348180092
2061514.83696442004550.163035579954474
2071614.8470264956861.15297350431399
2081615.43394871036260.566051289637426
2091113.9167631437977-2.91676314379775
2101514.30315947049950.696840529500508
2111214.507489606999-2.507489606999
2121216.2896849694461-4.28968496944614
2131514.30917048110010.690829518899902
2141512.16749588830622.83250411169378
2151614.88328934434421.11671065565580
2161413.42078783082380.57921216917622
2171715.06266197823011.93733802176992
2181414.3279169397482-0.327916939748238
2191311.99028890163491.00971109836511
2201515.6158919610783-0.615891961078344
2211315.0224913327296-2.02249133272956
2221414.5733033465195-0.573303346519544
2231514.56644591290410.43355408709592
2241213.4585313702885-1.45853137028855
2251312.80428073990430.195719260095656
226811.9668684285413-3.96686842854126
2271414.3096831383973-0.309683138397306
2281413.27374355278650.726256447213536
2291112.3432695732266-1.34326957322662
2301213.1609985574185-1.16099855741854
2311311.47993235152811.52006764847186
2321013.4650403340905-3.46504033409047
2331611.70045382224594.29954617775412
2341816.45586637075001.54413362925002
2351314.3053988244790-1.30539882447904
2361113.6549207425401-2.65492074254014
237411.1700281372820-7.17002813728201
2381314.8152140281387-1.81521402813869
2391614.59236330543211.40763669456793
2401011.9287261285823-1.92872612858232
2411212.4071970658913-0.407197065891325
2421213.7956003816510-1.79560038165098
243108.886344700787971.11365529921203
2441311.27700688023681.72299311976323
2451514.09262731602050.907372683979529
2461212.0467701780665-0.0467701780665329
2471413.15388286620630.846117133793704
2481012.8902928435778-2.89029284357777
2491210.80096582046091.19903417953906
2501211.88393362896460.116066371035425
2511112.1379198030589-1.13791980305892
2521011.8622634576053-1.86226345760533
2531211.66314378165700.336856218342975
2541613.17822476363682.82177523636317
2551213.7152063049677-1.71520630496769
2561414.2640878596850-0.264087859685045
2571614.68118855727991.31881144272010
2581411.82392868149752.17607131850247
2591314.7816409840600-1.78164098406003
26049.48330674262236-5.48330674262236
2611514.1743666514850.825633348514991
2621115.5502096888069-4.55020968880690
2631111.4716452522508-0.471645252250818
2641413.16729085252320.83270914747681







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.2344495241033230.4688990482066470.765550475896677
120.1202935178405570.2405870356811130.879706482159443
130.08155415734578020.1631083146915600.91844584265422
140.1028747764979180.2057495529958360.897125223502082
150.05875197565155020.1175039513031000.94124802434845
160.03916866759316340.07833733518632680.960831332406837
170.06301911844417490.1260382368883500.936980881555825
180.255864327935310.511728655870620.74413567206469
190.1942166329001510.3884332658003010.80578336709985
200.1377648833346390.2755297666692780.862235116665361
210.09860626155137020.1972125231027400.90139373844863
220.09685339904277270.1937067980855450.903146600957227
230.2570543779111390.5141087558222780.742945622088861
240.3214954184239470.6429908368478930.678504581576054
250.2948695385950190.5897390771900380.705130461404981
260.2774478577119770.5548957154239540.722552142288023
270.3520988888725580.7041977777451160.647901111127442
280.3638496488593420.7276992977186840.636150351140658
290.3467855921475900.6935711842951810.65321440785241
300.3808983862722670.7617967725445330.619101613727733
310.3286758031111610.6573516062223230.671324196888839
320.2894928679699320.5789857359398640.710507132030068
330.2624907774068980.5249815548137960.737509222593102
340.2263044170330470.4526088340660930.773695582966953
350.1878805418145860.3757610836291730.812119458185414
360.3049298148882160.6098596297764330.695070185111784
370.3349710741511980.6699421483023970.665028925848802
380.3259636225842430.6519272451684870.674036377415757
390.356022739855430.712045479710860.64397726014457
400.3342094491346500.6684188982693010.66579055086535
410.2980013652937390.5960027305874780.701998634706261
420.2638357288282340.5276714576564680.736164271171766
430.2782742652114290.5565485304228570.721725734788571
440.2365365213239350.473073042647870.763463478676065
450.2144422801981490.4288845603962980.78555771980185
460.3926897177725710.7853794355451420.607310282227429
470.5455190334856540.9089619330286920.454480966514346
480.4965487764023290.9930975528046580.503451223597671
490.4832161607247480.9664323214494970.516783839275252
500.4683902306446510.9367804612893030.531609769355349
510.423671720349910.847343440699820.57632827965009
520.3781691975725310.7563383951450610.621830802427469
530.3866036095760970.7732072191521930.613396390423903
540.3697095512825990.7394191025651980.630290448717401
550.3609375571723190.7218751143446380.639062442827681
560.3393852385237370.6787704770474740.660614761476263
570.2997777542626480.5995555085252950.700222245737352
580.2711577202394290.5423154404788580.728842279760571
590.236694269796530.473388539593060.76330573020347
600.2424586147505530.4849172295011070.757541385249447
610.2186501591049580.4373003182099170.781349840895042
620.1917356708049260.3834713416098510.808264329195074
630.1637320578437630.3274641156875260.836267942156237
640.137978888894910.275957777789820.86202111110509
650.1190738662615490.2381477325230970.880926133738452
660.1102288514213880.2204577028427760.889771148578612
670.1059861502412980.2119723004825950.894013849758702
680.2230586793560410.4461173587120830.776941320643959
690.3130388526634780.6260777053269570.686961147336522
700.2821425098269310.5642850196538630.717857490173069
710.3979023773212310.7958047546424620.602097622678769
720.3598978352378190.7197956704756380.640102164762181
730.3515646464888900.7031292929777790.64843535351111
740.3361970271152240.6723940542304480.663802972884776
750.3040241548740810.6080483097481620.695975845125919
760.3695447255589490.7390894511178980.630455274441051
770.3338177811756490.6676355623512990.66618221882435
780.312977052653640.625954105307280.68702294734636
790.3260565689197130.6521131378394270.673943431080287
800.2984783473115510.5969566946231030.701521652688449
810.2703419068908420.5406838137816850.729658093109158
820.2394460425874990.4788920851749970.760553957412501
830.2151396628227040.4302793256454080.784860337177296
840.1879137227384090.3758274454768190.81208627726159
850.1846071916740810.3692143833481620.815392808325919
860.15957251204160.31914502408320.8404274879584
870.1403225373613210.2806450747226420.859677462638679
880.1307388017647960.2614776035295920.869261198235204
890.1129764378758910.2259528757517820.887023562124109
900.1102031142192690.2204062284385380.889796885780731
910.09429193694486640.1885838738897330.905708063055134
920.08142409060866280.1628481812173260.918575909391337
930.06916220468658730.1383244093731750.930837795313413
940.07105056196411580.1421011239282320.928949438035884
950.06420477509781160.1284095501956230.935795224902188
960.05379758650354240.1075951730070850.946202413496458
970.05943151463996810.1188630292799360.940568485360032
980.04922705113043840.09845410226087680.950772948869562
990.0403637971239430.0807275942478860.959636202876057
1000.03531497706865640.07062995413731280.964685022931344
1010.03133001394681710.06266002789363430.968669986053183
1020.03688207108464570.07376414216929150.963117928915354
1030.03165139025063830.06330278050127660.968348609749362
1040.02858591411915220.05717182823830440.971414085880848
1050.0338171358137690.0676342716275380.966182864186231
1060.02971708786873170.05943417573746340.970282912131268
1070.02413307862849510.04826615725699010.975866921371505
1080.02400791135008460.04801582270016930.975992088649915
1090.01945150490639040.03890300981278080.98054849509361
1100.01591366614214870.03182733228429730.984086333857851
1110.01261465227192150.02522930454384290.987385347728079
1120.01303812775868150.02607625551736290.986961872241318
1130.01164521464788090.02329042929576170.98835478535212
1140.01672065608724730.03344131217449460.983279343912753
1150.01597102344518570.03194204689037130.984028976554814
1160.01528119780168540.03056239560337090.984718802198315
1170.01263902994539360.02527805989078720.987360970054606
1180.01262195624937530.02524391249875060.987378043750625
1190.01026120162714520.02052240325429040.989738798372855
1200.009038025678921760.01807605135784350.990961974321078
1210.007353567803015460.01470713560603090.992646432196985
1220.01131955121710510.02263910243421010.988680448782895
1230.009538495994803950.01907699198960790.990461504005196
1240.008473116391724320.01694623278344860.991526883608276
1250.006935559729241560.01387111945848310.993064440270758
1260.005650421037164760.01130084207432950.994349578962835
1270.005087164012794030.01017432802558810.994912835987206
1280.004098793520274390.008197587040548790.995901206479726
1290.00604886982758740.01209773965517480.993951130172413
1300.00655323802881230.01310647605762460.993446761971188
1310.01354029438996440.02708058877992880.986459705610036
1320.01629872750422810.03259745500845620.983701272495772
1330.01758236498167110.03516472996334230.982417635018329
1340.016983344991950.03396668998390.98301665500805
1350.01388037447347760.02776074894695520.986119625526522
1360.01171233869970190.02342467739940380.988287661300298
1370.009374643338209990.01874928667642000.99062535666179
1380.01141690215884600.02283380431769210.988583097841154
1390.009937139879518860.01987427975903770.990062860120481
1400.01129281549976420.02258563099952850.988707184500236
1410.01751656482001290.03503312964002580.982483435179987
1420.01592895790096370.03185791580192740.984071042099036
1430.01268316359323370.02536632718646740.987316836406766
1440.01344583330598290.02689166661196590.986554166694017
1450.02564031348952430.05128062697904860.974359686510476
1460.03141841095330070.06283682190660140.9685815890467
1470.03297957803633630.06595915607267260.967020421963664
1480.02977342271015380.05954684542030760.970226577289846
1490.02481272874093830.04962545748187650.975187271259062
1500.03443623206436970.06887246412873930.96556376793563
1510.02971241893936230.05942483787872460.970287581060638
1520.03128065816489960.06256131632979920.9687193418351
1530.0638804329782790.1277608659565580.936119567021721
1540.06276143572712750.1255228714542550.937238564272872
1550.07217477719129780.1443495543825960.927825222808702
1560.0617478574339070.1234957148678140.938252142566093
1570.05516287941602640.1103257588320530.944837120583974
1580.04827041228233670.09654082456467340.951729587717663
1590.04722610868202180.09445221736404370.952773891317978
1600.04049302819331120.08098605638662240.959506971806689
1610.03341243056971770.06682486113943530.966587569430282
1620.02746679527600310.05493359055200620.972533204723997
1630.02287565330103750.04575130660207490.977124346698963
1640.01929641328181650.03859282656363310.980703586718183
1650.01693535633760500.03387071267521000.983064643662395
1660.01718430506346230.03436861012692460.982815694936538
1670.01380762438724050.0276152487744810.98619237561276
1680.02037358612615630.04074717225231270.979626413873844
1690.02019288594577390.04038577189154770.979807114054226
1700.01885801717267540.03771603434535090.981141982827325
1710.01813496534063030.03626993068126060.98186503465937
1720.01469419658669680.02938839317339370.985305803413303
1730.01474229074869430.02948458149738860.985257709251306
1740.01642261616407210.03284523232814420.983577383835928
1750.02194945967986900.04389891935973790.978050540320131
1760.01765315232126240.03530630464252490.982346847678738
1770.01438269225106920.02876538450213840.98561730774893
1780.01174274283847600.02348548567695210.988257257161524
1790.009192159794017360.01838431958803470.990807840205983
1800.008005361728639250.01601072345727850.99199463827136
1810.006603604186685790.01320720837337160.993396395813314
1820.005345217149551780.01069043429910360.994654782850448
1830.005609366225755130.01121873245151030.994390633774245
1840.004436472950335140.008872945900670280.995563527049665
1850.0940865399009810.1881730798019620.905913460099019
1860.08168458117218880.1633691623443780.918315418827811
1870.09284398026744080.1856879605348820.90715601973256
1880.08021271356467170.1604254271293430.919787286435328
1890.06795963394561480.1359192678912300.932040366054385
1900.05635614350327240.1127122870065450.943643856496728
1910.04971116188416230.09942232376832470.950288838115838
1920.04196119331522320.08392238663044650.958038806684777
1930.04871552798395660.09743105596791320.951284472016043
1940.05228906663103670.1045781332620730.947710933368963
1950.04438117382695380.08876234765390760.955618826173046
1960.03702632821723780.07405265643447560.962973671782762
1970.04831570611723910.09663141223447820.95168429388276
1980.03958629462185330.07917258924370660.960413705378147
1990.03670115629514820.07340231259029640.963298843704852
2000.03103986761341950.0620797352268390.96896013238658
2010.02922197249448440.05844394498896880.970778027505516
2020.02438057070672690.04876114141345380.975619429293273
2030.03130536910662940.06261073821325880.96869463089337
2040.03568031777393860.07136063554787720.964319682226061
2050.03890633637672090.07781267275344190.96109366362328
2060.03087915454207750.06175830908415510.969120845457922
2070.03034222282480830.06068444564961660.969657777175192
2080.0249498727311470.0498997454622940.975050127268853
2090.02786814120547170.05573628241094340.972131858794528
2100.02254174262108960.04508348524217930.97745825737891
2110.02497753329313890.04995506658627770.975022466706861
2120.03997350874229910.07994701748459810.960026491257701
2130.03158710624416680.06317421248833350.968412893755833
2140.04415894259894010.08831788519788010.95584105740106
2150.03805930928693680.07611861857387350.961940690713063
2160.02975082592105540.05950165184211090.970249174078945
2170.03219553127290580.06439106254581150.967804468727094
2180.02752949098226420.05505898196452840.972470509017736
2190.02474180700445470.04948361400890930.975258192995545
2200.01896337737057080.03792675474114150.98103662262943
2210.01689473392096630.03378946784193260.983105266079034
2220.01242064858491550.02484129716983090.987579351415085
2230.00931174186201640.01862348372403280.990688258137984
2240.007502118543976970.01500423708795390.992497881456023
2250.006547056161290640.01309411232258130.99345294383871
2260.01499519031446590.02999038062893190.985004809685534
2270.01154161843724630.02308323687449270.988458381562754
2280.008350318923407890.01670063784681580.991649681076592
2290.00609683424321090.01219366848642180.993903165756789
2300.004410362517329970.008820725034659950.99558963748267
2310.004394614579941070.008789229159882140.99560538542006
2320.008144979571466430.01628995914293290.991855020428534
2330.03775654421187840.07551308842375680.962243455788122
2340.05429422005691060.1085884401138210.94570577994309
2350.04050658575470100.08101317150940210.959493414245299
2360.03611011259517660.07222022519035330.963889887404823
2370.2465057005701980.4930114011403950.753494299429802
2380.2007821309639780.4015642619279570.799217869036022
2390.1800444054680330.3600888109360670.819955594531967
2400.1421285353331370.2842570706662750.857871464666863
2410.1137073431033520.2274146862067050.886292656896648
2420.09453010324073070.1890602064814610.90546989675927
2430.08790231871979330.1758046374395870.912097681280207
2440.1535504342222440.3071008684444880.846449565777756
2450.1376303397172540.2752606794345080.862369660282746
2460.1101093305386860.2202186610773730.889890669461314
2470.07777060082222380.1555412016444480.922229399177776
2480.06669484702562380.1333896940512480.933305152974376
2490.06248882703230130.1249776540646030.937511172967699
2500.07738099305396050.1547619861079210.92261900694604
2510.04605497640822600.09210995281645210.953945023591774
2520.1122856641622780.2245713283245560.887714335837722
2530.2349985110953940.4699970221907870.765001488904606

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.234449524103323 & 0.468899048206647 & 0.765550475896677 \tabularnewline
12 & 0.120293517840557 & 0.240587035681113 & 0.879706482159443 \tabularnewline
13 & 0.0815541573457802 & 0.163108314691560 & 0.91844584265422 \tabularnewline
14 & 0.102874776497918 & 0.205749552995836 & 0.897125223502082 \tabularnewline
15 & 0.0587519756515502 & 0.117503951303100 & 0.94124802434845 \tabularnewline
16 & 0.0391686675931634 & 0.0783373351863268 & 0.960831332406837 \tabularnewline
17 & 0.0630191184441749 & 0.126038236888350 & 0.936980881555825 \tabularnewline
18 & 0.25586432793531 & 0.51172865587062 & 0.74413567206469 \tabularnewline
19 & 0.194216632900151 & 0.388433265800301 & 0.80578336709985 \tabularnewline
20 & 0.137764883334639 & 0.275529766669278 & 0.862235116665361 \tabularnewline
21 & 0.0986062615513702 & 0.197212523102740 & 0.90139373844863 \tabularnewline
22 & 0.0968533990427727 & 0.193706798085545 & 0.903146600957227 \tabularnewline
23 & 0.257054377911139 & 0.514108755822278 & 0.742945622088861 \tabularnewline
24 & 0.321495418423947 & 0.642990836847893 & 0.678504581576054 \tabularnewline
25 & 0.294869538595019 & 0.589739077190038 & 0.705130461404981 \tabularnewline
26 & 0.277447857711977 & 0.554895715423954 & 0.722552142288023 \tabularnewline
27 & 0.352098888872558 & 0.704197777745116 & 0.647901111127442 \tabularnewline
28 & 0.363849648859342 & 0.727699297718684 & 0.636150351140658 \tabularnewline
29 & 0.346785592147590 & 0.693571184295181 & 0.65321440785241 \tabularnewline
30 & 0.380898386272267 & 0.761796772544533 & 0.619101613727733 \tabularnewline
31 & 0.328675803111161 & 0.657351606222323 & 0.671324196888839 \tabularnewline
32 & 0.289492867969932 & 0.578985735939864 & 0.710507132030068 \tabularnewline
33 & 0.262490777406898 & 0.524981554813796 & 0.737509222593102 \tabularnewline
34 & 0.226304417033047 & 0.452608834066093 & 0.773695582966953 \tabularnewline
35 & 0.187880541814586 & 0.375761083629173 & 0.812119458185414 \tabularnewline
36 & 0.304929814888216 & 0.609859629776433 & 0.695070185111784 \tabularnewline
37 & 0.334971074151198 & 0.669942148302397 & 0.665028925848802 \tabularnewline
38 & 0.325963622584243 & 0.651927245168487 & 0.674036377415757 \tabularnewline
39 & 0.35602273985543 & 0.71204547971086 & 0.64397726014457 \tabularnewline
40 & 0.334209449134650 & 0.668418898269301 & 0.66579055086535 \tabularnewline
41 & 0.298001365293739 & 0.596002730587478 & 0.701998634706261 \tabularnewline
42 & 0.263835728828234 & 0.527671457656468 & 0.736164271171766 \tabularnewline
43 & 0.278274265211429 & 0.556548530422857 & 0.721725734788571 \tabularnewline
44 & 0.236536521323935 & 0.47307304264787 & 0.763463478676065 \tabularnewline
45 & 0.214442280198149 & 0.428884560396298 & 0.78555771980185 \tabularnewline
46 & 0.392689717772571 & 0.785379435545142 & 0.607310282227429 \tabularnewline
47 & 0.545519033485654 & 0.908961933028692 & 0.454480966514346 \tabularnewline
48 & 0.496548776402329 & 0.993097552804658 & 0.503451223597671 \tabularnewline
49 & 0.483216160724748 & 0.966432321449497 & 0.516783839275252 \tabularnewline
50 & 0.468390230644651 & 0.936780461289303 & 0.531609769355349 \tabularnewline
51 & 0.42367172034991 & 0.84734344069982 & 0.57632827965009 \tabularnewline
52 & 0.378169197572531 & 0.756338395145061 & 0.621830802427469 \tabularnewline
53 & 0.386603609576097 & 0.773207219152193 & 0.613396390423903 \tabularnewline
54 & 0.369709551282599 & 0.739419102565198 & 0.630290448717401 \tabularnewline
55 & 0.360937557172319 & 0.721875114344638 & 0.639062442827681 \tabularnewline
56 & 0.339385238523737 & 0.678770477047474 & 0.660614761476263 \tabularnewline
57 & 0.299777754262648 & 0.599555508525295 & 0.700222245737352 \tabularnewline
58 & 0.271157720239429 & 0.542315440478858 & 0.728842279760571 \tabularnewline
59 & 0.23669426979653 & 0.47338853959306 & 0.76330573020347 \tabularnewline
60 & 0.242458614750553 & 0.484917229501107 & 0.757541385249447 \tabularnewline
61 & 0.218650159104958 & 0.437300318209917 & 0.781349840895042 \tabularnewline
62 & 0.191735670804926 & 0.383471341609851 & 0.808264329195074 \tabularnewline
63 & 0.163732057843763 & 0.327464115687526 & 0.836267942156237 \tabularnewline
64 & 0.13797888889491 & 0.27595777778982 & 0.86202111110509 \tabularnewline
65 & 0.119073866261549 & 0.238147732523097 & 0.880926133738452 \tabularnewline
66 & 0.110228851421388 & 0.220457702842776 & 0.889771148578612 \tabularnewline
67 & 0.105986150241298 & 0.211972300482595 & 0.894013849758702 \tabularnewline
68 & 0.223058679356041 & 0.446117358712083 & 0.776941320643959 \tabularnewline
69 & 0.313038852663478 & 0.626077705326957 & 0.686961147336522 \tabularnewline
70 & 0.282142509826931 & 0.564285019653863 & 0.717857490173069 \tabularnewline
71 & 0.397902377321231 & 0.795804754642462 & 0.602097622678769 \tabularnewline
72 & 0.359897835237819 & 0.719795670475638 & 0.640102164762181 \tabularnewline
73 & 0.351564646488890 & 0.703129292977779 & 0.64843535351111 \tabularnewline
74 & 0.336197027115224 & 0.672394054230448 & 0.663802972884776 \tabularnewline
75 & 0.304024154874081 & 0.608048309748162 & 0.695975845125919 \tabularnewline
76 & 0.369544725558949 & 0.739089451117898 & 0.630455274441051 \tabularnewline
77 & 0.333817781175649 & 0.667635562351299 & 0.66618221882435 \tabularnewline
78 & 0.31297705265364 & 0.62595410530728 & 0.68702294734636 \tabularnewline
79 & 0.326056568919713 & 0.652113137839427 & 0.673943431080287 \tabularnewline
80 & 0.298478347311551 & 0.596956694623103 & 0.701521652688449 \tabularnewline
81 & 0.270341906890842 & 0.540683813781685 & 0.729658093109158 \tabularnewline
82 & 0.239446042587499 & 0.478892085174997 & 0.760553957412501 \tabularnewline
83 & 0.215139662822704 & 0.430279325645408 & 0.784860337177296 \tabularnewline
84 & 0.187913722738409 & 0.375827445476819 & 0.81208627726159 \tabularnewline
85 & 0.184607191674081 & 0.369214383348162 & 0.815392808325919 \tabularnewline
86 & 0.1595725120416 & 0.3191450240832 & 0.8404274879584 \tabularnewline
87 & 0.140322537361321 & 0.280645074722642 & 0.859677462638679 \tabularnewline
88 & 0.130738801764796 & 0.261477603529592 & 0.869261198235204 \tabularnewline
89 & 0.112976437875891 & 0.225952875751782 & 0.887023562124109 \tabularnewline
90 & 0.110203114219269 & 0.220406228438538 & 0.889796885780731 \tabularnewline
91 & 0.0942919369448664 & 0.188583873889733 & 0.905708063055134 \tabularnewline
92 & 0.0814240906086628 & 0.162848181217326 & 0.918575909391337 \tabularnewline
93 & 0.0691622046865873 & 0.138324409373175 & 0.930837795313413 \tabularnewline
94 & 0.0710505619641158 & 0.142101123928232 & 0.928949438035884 \tabularnewline
95 & 0.0642047750978116 & 0.128409550195623 & 0.935795224902188 \tabularnewline
96 & 0.0537975865035424 & 0.107595173007085 & 0.946202413496458 \tabularnewline
97 & 0.0594315146399681 & 0.118863029279936 & 0.940568485360032 \tabularnewline
98 & 0.0492270511304384 & 0.0984541022608768 & 0.950772948869562 \tabularnewline
99 & 0.040363797123943 & 0.080727594247886 & 0.959636202876057 \tabularnewline
100 & 0.0353149770686564 & 0.0706299541373128 & 0.964685022931344 \tabularnewline
101 & 0.0313300139468171 & 0.0626600278936343 & 0.968669986053183 \tabularnewline
102 & 0.0368820710846457 & 0.0737641421692915 & 0.963117928915354 \tabularnewline
103 & 0.0316513902506383 & 0.0633027805012766 & 0.968348609749362 \tabularnewline
104 & 0.0285859141191522 & 0.0571718282383044 & 0.971414085880848 \tabularnewline
105 & 0.033817135813769 & 0.067634271627538 & 0.966182864186231 \tabularnewline
106 & 0.0297170878687317 & 0.0594341757374634 & 0.970282912131268 \tabularnewline
107 & 0.0241330786284951 & 0.0482661572569901 & 0.975866921371505 \tabularnewline
108 & 0.0240079113500846 & 0.0480158227001693 & 0.975992088649915 \tabularnewline
109 & 0.0194515049063904 & 0.0389030098127808 & 0.98054849509361 \tabularnewline
110 & 0.0159136661421487 & 0.0318273322842973 & 0.984086333857851 \tabularnewline
111 & 0.0126146522719215 & 0.0252293045438429 & 0.987385347728079 \tabularnewline
112 & 0.0130381277586815 & 0.0260762555173629 & 0.986961872241318 \tabularnewline
113 & 0.0116452146478809 & 0.0232904292957617 & 0.98835478535212 \tabularnewline
114 & 0.0167206560872473 & 0.0334413121744946 & 0.983279343912753 \tabularnewline
115 & 0.0159710234451857 & 0.0319420468903713 & 0.984028976554814 \tabularnewline
116 & 0.0152811978016854 & 0.0305623956033709 & 0.984718802198315 \tabularnewline
117 & 0.0126390299453936 & 0.0252780598907872 & 0.987360970054606 \tabularnewline
118 & 0.0126219562493753 & 0.0252439124987506 & 0.987378043750625 \tabularnewline
119 & 0.0102612016271452 & 0.0205224032542904 & 0.989738798372855 \tabularnewline
120 & 0.00903802567892176 & 0.0180760513578435 & 0.990961974321078 \tabularnewline
121 & 0.00735356780301546 & 0.0147071356060309 & 0.992646432196985 \tabularnewline
122 & 0.0113195512171051 & 0.0226391024342101 & 0.988680448782895 \tabularnewline
123 & 0.00953849599480395 & 0.0190769919896079 & 0.990461504005196 \tabularnewline
124 & 0.00847311639172432 & 0.0169462327834486 & 0.991526883608276 \tabularnewline
125 & 0.00693555972924156 & 0.0138711194584831 & 0.993064440270758 \tabularnewline
126 & 0.00565042103716476 & 0.0113008420743295 & 0.994349578962835 \tabularnewline
127 & 0.00508716401279403 & 0.0101743280255881 & 0.994912835987206 \tabularnewline
128 & 0.00409879352027439 & 0.00819758704054879 & 0.995901206479726 \tabularnewline
129 & 0.0060488698275874 & 0.0120977396551748 & 0.993951130172413 \tabularnewline
130 & 0.0065532380288123 & 0.0131064760576246 & 0.993446761971188 \tabularnewline
131 & 0.0135402943899644 & 0.0270805887799288 & 0.986459705610036 \tabularnewline
132 & 0.0162987275042281 & 0.0325974550084562 & 0.983701272495772 \tabularnewline
133 & 0.0175823649816711 & 0.0351647299633423 & 0.982417635018329 \tabularnewline
134 & 0.01698334499195 & 0.0339666899839 & 0.98301665500805 \tabularnewline
135 & 0.0138803744734776 & 0.0277607489469552 & 0.986119625526522 \tabularnewline
136 & 0.0117123386997019 & 0.0234246773994038 & 0.988287661300298 \tabularnewline
137 & 0.00937464333820999 & 0.0187492866764200 & 0.99062535666179 \tabularnewline
138 & 0.0114169021588460 & 0.0228338043176921 & 0.988583097841154 \tabularnewline
139 & 0.00993713987951886 & 0.0198742797590377 & 0.990062860120481 \tabularnewline
140 & 0.0112928154997642 & 0.0225856309995285 & 0.988707184500236 \tabularnewline
141 & 0.0175165648200129 & 0.0350331296400258 & 0.982483435179987 \tabularnewline
142 & 0.0159289579009637 & 0.0318579158019274 & 0.984071042099036 \tabularnewline
143 & 0.0126831635932337 & 0.0253663271864674 & 0.987316836406766 \tabularnewline
144 & 0.0134458333059829 & 0.0268916666119659 & 0.986554166694017 \tabularnewline
145 & 0.0256403134895243 & 0.0512806269790486 & 0.974359686510476 \tabularnewline
146 & 0.0314184109533007 & 0.0628368219066014 & 0.9685815890467 \tabularnewline
147 & 0.0329795780363363 & 0.0659591560726726 & 0.967020421963664 \tabularnewline
148 & 0.0297734227101538 & 0.0595468454203076 & 0.970226577289846 \tabularnewline
149 & 0.0248127287409383 & 0.0496254574818765 & 0.975187271259062 \tabularnewline
150 & 0.0344362320643697 & 0.0688724641287393 & 0.96556376793563 \tabularnewline
151 & 0.0297124189393623 & 0.0594248378787246 & 0.970287581060638 \tabularnewline
152 & 0.0312806581648996 & 0.0625613163297992 & 0.9687193418351 \tabularnewline
153 & 0.063880432978279 & 0.127760865956558 & 0.936119567021721 \tabularnewline
154 & 0.0627614357271275 & 0.125522871454255 & 0.937238564272872 \tabularnewline
155 & 0.0721747771912978 & 0.144349554382596 & 0.927825222808702 \tabularnewline
156 & 0.061747857433907 & 0.123495714867814 & 0.938252142566093 \tabularnewline
157 & 0.0551628794160264 & 0.110325758832053 & 0.944837120583974 \tabularnewline
158 & 0.0482704122823367 & 0.0965408245646734 & 0.951729587717663 \tabularnewline
159 & 0.0472261086820218 & 0.0944522173640437 & 0.952773891317978 \tabularnewline
160 & 0.0404930281933112 & 0.0809860563866224 & 0.959506971806689 \tabularnewline
161 & 0.0334124305697177 & 0.0668248611394353 & 0.966587569430282 \tabularnewline
162 & 0.0274667952760031 & 0.0549335905520062 & 0.972533204723997 \tabularnewline
163 & 0.0228756533010375 & 0.0457513066020749 & 0.977124346698963 \tabularnewline
164 & 0.0192964132818165 & 0.0385928265636331 & 0.980703586718183 \tabularnewline
165 & 0.0169353563376050 & 0.0338707126752100 & 0.983064643662395 \tabularnewline
166 & 0.0171843050634623 & 0.0343686101269246 & 0.982815694936538 \tabularnewline
167 & 0.0138076243872405 & 0.027615248774481 & 0.98619237561276 \tabularnewline
168 & 0.0203735861261563 & 0.0407471722523127 & 0.979626413873844 \tabularnewline
169 & 0.0201928859457739 & 0.0403857718915477 & 0.979807114054226 \tabularnewline
170 & 0.0188580171726754 & 0.0377160343453509 & 0.981141982827325 \tabularnewline
171 & 0.0181349653406303 & 0.0362699306812606 & 0.98186503465937 \tabularnewline
172 & 0.0146941965866968 & 0.0293883931733937 & 0.985305803413303 \tabularnewline
173 & 0.0147422907486943 & 0.0294845814973886 & 0.985257709251306 \tabularnewline
174 & 0.0164226161640721 & 0.0328452323281442 & 0.983577383835928 \tabularnewline
175 & 0.0219494596798690 & 0.0438989193597379 & 0.978050540320131 \tabularnewline
176 & 0.0176531523212624 & 0.0353063046425249 & 0.982346847678738 \tabularnewline
177 & 0.0143826922510692 & 0.0287653845021384 & 0.98561730774893 \tabularnewline
178 & 0.0117427428384760 & 0.0234854856769521 & 0.988257257161524 \tabularnewline
179 & 0.00919215979401736 & 0.0183843195880347 & 0.990807840205983 \tabularnewline
180 & 0.00800536172863925 & 0.0160107234572785 & 0.99199463827136 \tabularnewline
181 & 0.00660360418668579 & 0.0132072083733716 & 0.993396395813314 \tabularnewline
182 & 0.00534521714955178 & 0.0106904342991036 & 0.994654782850448 \tabularnewline
183 & 0.00560936622575513 & 0.0112187324515103 & 0.994390633774245 \tabularnewline
184 & 0.00443647295033514 & 0.00887294590067028 & 0.995563527049665 \tabularnewline
185 & 0.094086539900981 & 0.188173079801962 & 0.905913460099019 \tabularnewline
186 & 0.0816845811721888 & 0.163369162344378 & 0.918315418827811 \tabularnewline
187 & 0.0928439802674408 & 0.185687960534882 & 0.90715601973256 \tabularnewline
188 & 0.0802127135646717 & 0.160425427129343 & 0.919787286435328 \tabularnewline
189 & 0.0679596339456148 & 0.135919267891230 & 0.932040366054385 \tabularnewline
190 & 0.0563561435032724 & 0.112712287006545 & 0.943643856496728 \tabularnewline
191 & 0.0497111618841623 & 0.0994223237683247 & 0.950288838115838 \tabularnewline
192 & 0.0419611933152232 & 0.0839223866304465 & 0.958038806684777 \tabularnewline
193 & 0.0487155279839566 & 0.0974310559679132 & 0.951284472016043 \tabularnewline
194 & 0.0522890666310367 & 0.104578133262073 & 0.947710933368963 \tabularnewline
195 & 0.0443811738269538 & 0.0887623476539076 & 0.955618826173046 \tabularnewline
196 & 0.0370263282172378 & 0.0740526564344756 & 0.962973671782762 \tabularnewline
197 & 0.0483157061172391 & 0.0966314122344782 & 0.95168429388276 \tabularnewline
198 & 0.0395862946218533 & 0.0791725892437066 & 0.960413705378147 \tabularnewline
199 & 0.0367011562951482 & 0.0734023125902964 & 0.963298843704852 \tabularnewline
200 & 0.0310398676134195 & 0.062079735226839 & 0.96896013238658 \tabularnewline
201 & 0.0292219724944844 & 0.0584439449889688 & 0.970778027505516 \tabularnewline
202 & 0.0243805707067269 & 0.0487611414134538 & 0.975619429293273 \tabularnewline
203 & 0.0313053691066294 & 0.0626107382132588 & 0.96869463089337 \tabularnewline
204 & 0.0356803177739386 & 0.0713606355478772 & 0.964319682226061 \tabularnewline
205 & 0.0389063363767209 & 0.0778126727534419 & 0.96109366362328 \tabularnewline
206 & 0.0308791545420775 & 0.0617583090841551 & 0.969120845457922 \tabularnewline
207 & 0.0303422228248083 & 0.0606844456496166 & 0.969657777175192 \tabularnewline
208 & 0.024949872731147 & 0.049899745462294 & 0.975050127268853 \tabularnewline
209 & 0.0278681412054717 & 0.0557362824109434 & 0.972131858794528 \tabularnewline
210 & 0.0225417426210896 & 0.0450834852421793 & 0.97745825737891 \tabularnewline
211 & 0.0249775332931389 & 0.0499550665862777 & 0.975022466706861 \tabularnewline
212 & 0.0399735087422991 & 0.0799470174845981 & 0.960026491257701 \tabularnewline
213 & 0.0315871062441668 & 0.0631742124883335 & 0.968412893755833 \tabularnewline
214 & 0.0441589425989401 & 0.0883178851978801 & 0.95584105740106 \tabularnewline
215 & 0.0380593092869368 & 0.0761186185738735 & 0.961940690713063 \tabularnewline
216 & 0.0297508259210554 & 0.0595016518421109 & 0.970249174078945 \tabularnewline
217 & 0.0321955312729058 & 0.0643910625458115 & 0.967804468727094 \tabularnewline
218 & 0.0275294909822642 & 0.0550589819645284 & 0.972470509017736 \tabularnewline
219 & 0.0247418070044547 & 0.0494836140089093 & 0.975258192995545 \tabularnewline
220 & 0.0189633773705708 & 0.0379267547411415 & 0.98103662262943 \tabularnewline
221 & 0.0168947339209663 & 0.0337894678419326 & 0.983105266079034 \tabularnewline
222 & 0.0124206485849155 & 0.0248412971698309 & 0.987579351415085 \tabularnewline
223 & 0.0093117418620164 & 0.0186234837240328 & 0.990688258137984 \tabularnewline
224 & 0.00750211854397697 & 0.0150042370879539 & 0.992497881456023 \tabularnewline
225 & 0.00654705616129064 & 0.0130941123225813 & 0.99345294383871 \tabularnewline
226 & 0.0149951903144659 & 0.0299903806289319 & 0.985004809685534 \tabularnewline
227 & 0.0115416184372463 & 0.0230832368744927 & 0.988458381562754 \tabularnewline
228 & 0.00835031892340789 & 0.0167006378468158 & 0.991649681076592 \tabularnewline
229 & 0.0060968342432109 & 0.0121936684864218 & 0.993903165756789 \tabularnewline
230 & 0.00441036251732997 & 0.00882072503465995 & 0.99558963748267 \tabularnewline
231 & 0.00439461457994107 & 0.00878922915988214 & 0.99560538542006 \tabularnewline
232 & 0.00814497957146643 & 0.0162899591429329 & 0.991855020428534 \tabularnewline
233 & 0.0377565442118784 & 0.0755130884237568 & 0.962243455788122 \tabularnewline
234 & 0.0542942200569106 & 0.108588440113821 & 0.94570577994309 \tabularnewline
235 & 0.0405065857547010 & 0.0810131715094021 & 0.959493414245299 \tabularnewline
236 & 0.0361101125951766 & 0.0722202251903533 & 0.963889887404823 \tabularnewline
237 & 0.246505700570198 & 0.493011401140395 & 0.753494299429802 \tabularnewline
238 & 0.200782130963978 & 0.401564261927957 & 0.799217869036022 \tabularnewline
239 & 0.180044405468033 & 0.360088810936067 & 0.819955594531967 \tabularnewline
240 & 0.142128535333137 & 0.284257070666275 & 0.857871464666863 \tabularnewline
241 & 0.113707343103352 & 0.227414686206705 & 0.886292656896648 \tabularnewline
242 & 0.0945301032407307 & 0.189060206481461 & 0.90546989675927 \tabularnewline
243 & 0.0879023187197933 & 0.175804637439587 & 0.912097681280207 \tabularnewline
244 & 0.153550434222244 & 0.307100868444488 & 0.846449565777756 \tabularnewline
245 & 0.137630339717254 & 0.275260679434508 & 0.862369660282746 \tabularnewline
246 & 0.110109330538686 & 0.220218661077373 & 0.889890669461314 \tabularnewline
247 & 0.0777706008222238 & 0.155541201644448 & 0.922229399177776 \tabularnewline
248 & 0.0666948470256238 & 0.133389694051248 & 0.933305152974376 \tabularnewline
249 & 0.0624888270323013 & 0.124977654064603 & 0.937511172967699 \tabularnewline
250 & 0.0773809930539605 & 0.154761986107921 & 0.92261900694604 \tabularnewline
251 & 0.0460549764082260 & 0.0921099528164521 & 0.953945023591774 \tabularnewline
252 & 0.112285664162278 & 0.224571328324556 & 0.887714335837722 \tabularnewline
253 & 0.234998511095394 & 0.469997022190787 & 0.765001488904606 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96530&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]11[/C][C]0.234449524103323[/C][C]0.468899048206647[/C][C]0.765550475896677[/C][/ROW]
[ROW][C]12[/C][C]0.120293517840557[/C][C]0.240587035681113[/C][C]0.879706482159443[/C][/ROW]
[ROW][C]13[/C][C]0.0815541573457802[/C][C]0.163108314691560[/C][C]0.91844584265422[/C][/ROW]
[ROW][C]14[/C][C]0.102874776497918[/C][C]0.205749552995836[/C][C]0.897125223502082[/C][/ROW]
[ROW][C]15[/C][C]0.0587519756515502[/C][C]0.117503951303100[/C][C]0.94124802434845[/C][/ROW]
[ROW][C]16[/C][C]0.0391686675931634[/C][C]0.0783373351863268[/C][C]0.960831332406837[/C][/ROW]
[ROW][C]17[/C][C]0.0630191184441749[/C][C]0.126038236888350[/C][C]0.936980881555825[/C][/ROW]
[ROW][C]18[/C][C]0.25586432793531[/C][C]0.51172865587062[/C][C]0.74413567206469[/C][/ROW]
[ROW][C]19[/C][C]0.194216632900151[/C][C]0.388433265800301[/C][C]0.80578336709985[/C][/ROW]
[ROW][C]20[/C][C]0.137764883334639[/C][C]0.275529766669278[/C][C]0.862235116665361[/C][/ROW]
[ROW][C]21[/C][C]0.0986062615513702[/C][C]0.197212523102740[/C][C]0.90139373844863[/C][/ROW]
[ROW][C]22[/C][C]0.0968533990427727[/C][C]0.193706798085545[/C][C]0.903146600957227[/C][/ROW]
[ROW][C]23[/C][C]0.257054377911139[/C][C]0.514108755822278[/C][C]0.742945622088861[/C][/ROW]
[ROW][C]24[/C][C]0.321495418423947[/C][C]0.642990836847893[/C][C]0.678504581576054[/C][/ROW]
[ROW][C]25[/C][C]0.294869538595019[/C][C]0.589739077190038[/C][C]0.705130461404981[/C][/ROW]
[ROW][C]26[/C][C]0.277447857711977[/C][C]0.554895715423954[/C][C]0.722552142288023[/C][/ROW]
[ROW][C]27[/C][C]0.352098888872558[/C][C]0.704197777745116[/C][C]0.647901111127442[/C][/ROW]
[ROW][C]28[/C][C]0.363849648859342[/C][C]0.727699297718684[/C][C]0.636150351140658[/C][/ROW]
[ROW][C]29[/C][C]0.346785592147590[/C][C]0.693571184295181[/C][C]0.65321440785241[/C][/ROW]
[ROW][C]30[/C][C]0.380898386272267[/C][C]0.761796772544533[/C][C]0.619101613727733[/C][/ROW]
[ROW][C]31[/C][C]0.328675803111161[/C][C]0.657351606222323[/C][C]0.671324196888839[/C][/ROW]
[ROW][C]32[/C][C]0.289492867969932[/C][C]0.578985735939864[/C][C]0.710507132030068[/C][/ROW]
[ROW][C]33[/C][C]0.262490777406898[/C][C]0.524981554813796[/C][C]0.737509222593102[/C][/ROW]
[ROW][C]34[/C][C]0.226304417033047[/C][C]0.452608834066093[/C][C]0.773695582966953[/C][/ROW]
[ROW][C]35[/C][C]0.187880541814586[/C][C]0.375761083629173[/C][C]0.812119458185414[/C][/ROW]
[ROW][C]36[/C][C]0.304929814888216[/C][C]0.609859629776433[/C][C]0.695070185111784[/C][/ROW]
[ROW][C]37[/C][C]0.334971074151198[/C][C]0.669942148302397[/C][C]0.665028925848802[/C][/ROW]
[ROW][C]38[/C][C]0.325963622584243[/C][C]0.651927245168487[/C][C]0.674036377415757[/C][/ROW]
[ROW][C]39[/C][C]0.35602273985543[/C][C]0.71204547971086[/C][C]0.64397726014457[/C][/ROW]
[ROW][C]40[/C][C]0.334209449134650[/C][C]0.668418898269301[/C][C]0.66579055086535[/C][/ROW]
[ROW][C]41[/C][C]0.298001365293739[/C][C]0.596002730587478[/C][C]0.701998634706261[/C][/ROW]
[ROW][C]42[/C][C]0.263835728828234[/C][C]0.527671457656468[/C][C]0.736164271171766[/C][/ROW]
[ROW][C]43[/C][C]0.278274265211429[/C][C]0.556548530422857[/C][C]0.721725734788571[/C][/ROW]
[ROW][C]44[/C][C]0.236536521323935[/C][C]0.47307304264787[/C][C]0.763463478676065[/C][/ROW]
[ROW][C]45[/C][C]0.214442280198149[/C][C]0.428884560396298[/C][C]0.78555771980185[/C][/ROW]
[ROW][C]46[/C][C]0.392689717772571[/C][C]0.785379435545142[/C][C]0.607310282227429[/C][/ROW]
[ROW][C]47[/C][C]0.545519033485654[/C][C]0.908961933028692[/C][C]0.454480966514346[/C][/ROW]
[ROW][C]48[/C][C]0.496548776402329[/C][C]0.993097552804658[/C][C]0.503451223597671[/C][/ROW]
[ROW][C]49[/C][C]0.483216160724748[/C][C]0.966432321449497[/C][C]0.516783839275252[/C][/ROW]
[ROW][C]50[/C][C]0.468390230644651[/C][C]0.936780461289303[/C][C]0.531609769355349[/C][/ROW]
[ROW][C]51[/C][C]0.42367172034991[/C][C]0.84734344069982[/C][C]0.57632827965009[/C][/ROW]
[ROW][C]52[/C][C]0.378169197572531[/C][C]0.756338395145061[/C][C]0.621830802427469[/C][/ROW]
[ROW][C]53[/C][C]0.386603609576097[/C][C]0.773207219152193[/C][C]0.613396390423903[/C][/ROW]
[ROW][C]54[/C][C]0.369709551282599[/C][C]0.739419102565198[/C][C]0.630290448717401[/C][/ROW]
[ROW][C]55[/C][C]0.360937557172319[/C][C]0.721875114344638[/C][C]0.639062442827681[/C][/ROW]
[ROW][C]56[/C][C]0.339385238523737[/C][C]0.678770477047474[/C][C]0.660614761476263[/C][/ROW]
[ROW][C]57[/C][C]0.299777754262648[/C][C]0.599555508525295[/C][C]0.700222245737352[/C][/ROW]
[ROW][C]58[/C][C]0.271157720239429[/C][C]0.542315440478858[/C][C]0.728842279760571[/C][/ROW]
[ROW][C]59[/C][C]0.23669426979653[/C][C]0.47338853959306[/C][C]0.76330573020347[/C][/ROW]
[ROW][C]60[/C][C]0.242458614750553[/C][C]0.484917229501107[/C][C]0.757541385249447[/C][/ROW]
[ROW][C]61[/C][C]0.218650159104958[/C][C]0.437300318209917[/C][C]0.781349840895042[/C][/ROW]
[ROW][C]62[/C][C]0.191735670804926[/C][C]0.383471341609851[/C][C]0.808264329195074[/C][/ROW]
[ROW][C]63[/C][C]0.163732057843763[/C][C]0.327464115687526[/C][C]0.836267942156237[/C][/ROW]
[ROW][C]64[/C][C]0.13797888889491[/C][C]0.27595777778982[/C][C]0.86202111110509[/C][/ROW]
[ROW][C]65[/C][C]0.119073866261549[/C][C]0.238147732523097[/C][C]0.880926133738452[/C][/ROW]
[ROW][C]66[/C][C]0.110228851421388[/C][C]0.220457702842776[/C][C]0.889771148578612[/C][/ROW]
[ROW][C]67[/C][C]0.105986150241298[/C][C]0.211972300482595[/C][C]0.894013849758702[/C][/ROW]
[ROW][C]68[/C][C]0.223058679356041[/C][C]0.446117358712083[/C][C]0.776941320643959[/C][/ROW]
[ROW][C]69[/C][C]0.313038852663478[/C][C]0.626077705326957[/C][C]0.686961147336522[/C][/ROW]
[ROW][C]70[/C][C]0.282142509826931[/C][C]0.564285019653863[/C][C]0.717857490173069[/C][/ROW]
[ROW][C]71[/C][C]0.397902377321231[/C][C]0.795804754642462[/C][C]0.602097622678769[/C][/ROW]
[ROW][C]72[/C][C]0.359897835237819[/C][C]0.719795670475638[/C][C]0.640102164762181[/C][/ROW]
[ROW][C]73[/C][C]0.351564646488890[/C][C]0.703129292977779[/C][C]0.64843535351111[/C][/ROW]
[ROW][C]74[/C][C]0.336197027115224[/C][C]0.672394054230448[/C][C]0.663802972884776[/C][/ROW]
[ROW][C]75[/C][C]0.304024154874081[/C][C]0.608048309748162[/C][C]0.695975845125919[/C][/ROW]
[ROW][C]76[/C][C]0.369544725558949[/C][C]0.739089451117898[/C][C]0.630455274441051[/C][/ROW]
[ROW][C]77[/C][C]0.333817781175649[/C][C]0.667635562351299[/C][C]0.66618221882435[/C][/ROW]
[ROW][C]78[/C][C]0.31297705265364[/C][C]0.62595410530728[/C][C]0.68702294734636[/C][/ROW]
[ROW][C]79[/C][C]0.326056568919713[/C][C]0.652113137839427[/C][C]0.673943431080287[/C][/ROW]
[ROW][C]80[/C][C]0.298478347311551[/C][C]0.596956694623103[/C][C]0.701521652688449[/C][/ROW]
[ROW][C]81[/C][C]0.270341906890842[/C][C]0.540683813781685[/C][C]0.729658093109158[/C][/ROW]
[ROW][C]82[/C][C]0.239446042587499[/C][C]0.478892085174997[/C][C]0.760553957412501[/C][/ROW]
[ROW][C]83[/C][C]0.215139662822704[/C][C]0.430279325645408[/C][C]0.784860337177296[/C][/ROW]
[ROW][C]84[/C][C]0.187913722738409[/C][C]0.375827445476819[/C][C]0.81208627726159[/C][/ROW]
[ROW][C]85[/C][C]0.184607191674081[/C][C]0.369214383348162[/C][C]0.815392808325919[/C][/ROW]
[ROW][C]86[/C][C]0.1595725120416[/C][C]0.3191450240832[/C][C]0.8404274879584[/C][/ROW]
[ROW][C]87[/C][C]0.140322537361321[/C][C]0.280645074722642[/C][C]0.859677462638679[/C][/ROW]
[ROW][C]88[/C][C]0.130738801764796[/C][C]0.261477603529592[/C][C]0.869261198235204[/C][/ROW]
[ROW][C]89[/C][C]0.112976437875891[/C][C]0.225952875751782[/C][C]0.887023562124109[/C][/ROW]
[ROW][C]90[/C][C]0.110203114219269[/C][C]0.220406228438538[/C][C]0.889796885780731[/C][/ROW]
[ROW][C]91[/C][C]0.0942919369448664[/C][C]0.188583873889733[/C][C]0.905708063055134[/C][/ROW]
[ROW][C]92[/C][C]0.0814240906086628[/C][C]0.162848181217326[/C][C]0.918575909391337[/C][/ROW]
[ROW][C]93[/C][C]0.0691622046865873[/C][C]0.138324409373175[/C][C]0.930837795313413[/C][/ROW]
[ROW][C]94[/C][C]0.0710505619641158[/C][C]0.142101123928232[/C][C]0.928949438035884[/C][/ROW]
[ROW][C]95[/C][C]0.0642047750978116[/C][C]0.128409550195623[/C][C]0.935795224902188[/C][/ROW]
[ROW][C]96[/C][C]0.0537975865035424[/C][C]0.107595173007085[/C][C]0.946202413496458[/C][/ROW]
[ROW][C]97[/C][C]0.0594315146399681[/C][C]0.118863029279936[/C][C]0.940568485360032[/C][/ROW]
[ROW][C]98[/C][C]0.0492270511304384[/C][C]0.0984541022608768[/C][C]0.950772948869562[/C][/ROW]
[ROW][C]99[/C][C]0.040363797123943[/C][C]0.080727594247886[/C][C]0.959636202876057[/C][/ROW]
[ROW][C]100[/C][C]0.0353149770686564[/C][C]0.0706299541373128[/C][C]0.964685022931344[/C][/ROW]
[ROW][C]101[/C][C]0.0313300139468171[/C][C]0.0626600278936343[/C][C]0.968669986053183[/C][/ROW]
[ROW][C]102[/C][C]0.0368820710846457[/C][C]0.0737641421692915[/C][C]0.963117928915354[/C][/ROW]
[ROW][C]103[/C][C]0.0316513902506383[/C][C]0.0633027805012766[/C][C]0.968348609749362[/C][/ROW]
[ROW][C]104[/C][C]0.0285859141191522[/C][C]0.0571718282383044[/C][C]0.971414085880848[/C][/ROW]
[ROW][C]105[/C][C]0.033817135813769[/C][C]0.067634271627538[/C][C]0.966182864186231[/C][/ROW]
[ROW][C]106[/C][C]0.0297170878687317[/C][C]0.0594341757374634[/C][C]0.970282912131268[/C][/ROW]
[ROW][C]107[/C][C]0.0241330786284951[/C][C]0.0482661572569901[/C][C]0.975866921371505[/C][/ROW]
[ROW][C]108[/C][C]0.0240079113500846[/C][C]0.0480158227001693[/C][C]0.975992088649915[/C][/ROW]
[ROW][C]109[/C][C]0.0194515049063904[/C][C]0.0389030098127808[/C][C]0.98054849509361[/C][/ROW]
[ROW][C]110[/C][C]0.0159136661421487[/C][C]0.0318273322842973[/C][C]0.984086333857851[/C][/ROW]
[ROW][C]111[/C][C]0.0126146522719215[/C][C]0.0252293045438429[/C][C]0.987385347728079[/C][/ROW]
[ROW][C]112[/C][C]0.0130381277586815[/C][C]0.0260762555173629[/C][C]0.986961872241318[/C][/ROW]
[ROW][C]113[/C][C]0.0116452146478809[/C][C]0.0232904292957617[/C][C]0.98835478535212[/C][/ROW]
[ROW][C]114[/C][C]0.0167206560872473[/C][C]0.0334413121744946[/C][C]0.983279343912753[/C][/ROW]
[ROW][C]115[/C][C]0.0159710234451857[/C][C]0.0319420468903713[/C][C]0.984028976554814[/C][/ROW]
[ROW][C]116[/C][C]0.0152811978016854[/C][C]0.0305623956033709[/C][C]0.984718802198315[/C][/ROW]
[ROW][C]117[/C][C]0.0126390299453936[/C][C]0.0252780598907872[/C][C]0.987360970054606[/C][/ROW]
[ROW][C]118[/C][C]0.0126219562493753[/C][C]0.0252439124987506[/C][C]0.987378043750625[/C][/ROW]
[ROW][C]119[/C][C]0.0102612016271452[/C][C]0.0205224032542904[/C][C]0.989738798372855[/C][/ROW]
[ROW][C]120[/C][C]0.00903802567892176[/C][C]0.0180760513578435[/C][C]0.990961974321078[/C][/ROW]
[ROW][C]121[/C][C]0.00735356780301546[/C][C]0.0147071356060309[/C][C]0.992646432196985[/C][/ROW]
[ROW][C]122[/C][C]0.0113195512171051[/C][C]0.0226391024342101[/C][C]0.988680448782895[/C][/ROW]
[ROW][C]123[/C][C]0.00953849599480395[/C][C]0.0190769919896079[/C][C]0.990461504005196[/C][/ROW]
[ROW][C]124[/C][C]0.00847311639172432[/C][C]0.0169462327834486[/C][C]0.991526883608276[/C][/ROW]
[ROW][C]125[/C][C]0.00693555972924156[/C][C]0.0138711194584831[/C][C]0.993064440270758[/C][/ROW]
[ROW][C]126[/C][C]0.00565042103716476[/C][C]0.0113008420743295[/C][C]0.994349578962835[/C][/ROW]
[ROW][C]127[/C][C]0.00508716401279403[/C][C]0.0101743280255881[/C][C]0.994912835987206[/C][/ROW]
[ROW][C]128[/C][C]0.00409879352027439[/C][C]0.00819758704054879[/C][C]0.995901206479726[/C][/ROW]
[ROW][C]129[/C][C]0.0060488698275874[/C][C]0.0120977396551748[/C][C]0.993951130172413[/C][/ROW]
[ROW][C]130[/C][C]0.0065532380288123[/C][C]0.0131064760576246[/C][C]0.993446761971188[/C][/ROW]
[ROW][C]131[/C][C]0.0135402943899644[/C][C]0.0270805887799288[/C][C]0.986459705610036[/C][/ROW]
[ROW][C]132[/C][C]0.0162987275042281[/C][C]0.0325974550084562[/C][C]0.983701272495772[/C][/ROW]
[ROW][C]133[/C][C]0.0175823649816711[/C][C]0.0351647299633423[/C][C]0.982417635018329[/C][/ROW]
[ROW][C]134[/C][C]0.01698334499195[/C][C]0.0339666899839[/C][C]0.98301665500805[/C][/ROW]
[ROW][C]135[/C][C]0.0138803744734776[/C][C]0.0277607489469552[/C][C]0.986119625526522[/C][/ROW]
[ROW][C]136[/C][C]0.0117123386997019[/C][C]0.0234246773994038[/C][C]0.988287661300298[/C][/ROW]
[ROW][C]137[/C][C]0.00937464333820999[/C][C]0.0187492866764200[/C][C]0.99062535666179[/C][/ROW]
[ROW][C]138[/C][C]0.0114169021588460[/C][C]0.0228338043176921[/C][C]0.988583097841154[/C][/ROW]
[ROW][C]139[/C][C]0.00993713987951886[/C][C]0.0198742797590377[/C][C]0.990062860120481[/C][/ROW]
[ROW][C]140[/C][C]0.0112928154997642[/C][C]0.0225856309995285[/C][C]0.988707184500236[/C][/ROW]
[ROW][C]141[/C][C]0.0175165648200129[/C][C]0.0350331296400258[/C][C]0.982483435179987[/C][/ROW]
[ROW][C]142[/C][C]0.0159289579009637[/C][C]0.0318579158019274[/C][C]0.984071042099036[/C][/ROW]
[ROW][C]143[/C][C]0.0126831635932337[/C][C]0.0253663271864674[/C][C]0.987316836406766[/C][/ROW]
[ROW][C]144[/C][C]0.0134458333059829[/C][C]0.0268916666119659[/C][C]0.986554166694017[/C][/ROW]
[ROW][C]145[/C][C]0.0256403134895243[/C][C]0.0512806269790486[/C][C]0.974359686510476[/C][/ROW]
[ROW][C]146[/C][C]0.0314184109533007[/C][C]0.0628368219066014[/C][C]0.9685815890467[/C][/ROW]
[ROW][C]147[/C][C]0.0329795780363363[/C][C]0.0659591560726726[/C][C]0.967020421963664[/C][/ROW]
[ROW][C]148[/C][C]0.0297734227101538[/C][C]0.0595468454203076[/C][C]0.970226577289846[/C][/ROW]
[ROW][C]149[/C][C]0.0248127287409383[/C][C]0.0496254574818765[/C][C]0.975187271259062[/C][/ROW]
[ROW][C]150[/C][C]0.0344362320643697[/C][C]0.0688724641287393[/C][C]0.96556376793563[/C][/ROW]
[ROW][C]151[/C][C]0.0297124189393623[/C][C]0.0594248378787246[/C][C]0.970287581060638[/C][/ROW]
[ROW][C]152[/C][C]0.0312806581648996[/C][C]0.0625613163297992[/C][C]0.9687193418351[/C][/ROW]
[ROW][C]153[/C][C]0.063880432978279[/C][C]0.127760865956558[/C][C]0.936119567021721[/C][/ROW]
[ROW][C]154[/C][C]0.0627614357271275[/C][C]0.125522871454255[/C][C]0.937238564272872[/C][/ROW]
[ROW][C]155[/C][C]0.0721747771912978[/C][C]0.144349554382596[/C][C]0.927825222808702[/C][/ROW]
[ROW][C]156[/C][C]0.061747857433907[/C][C]0.123495714867814[/C][C]0.938252142566093[/C][/ROW]
[ROW][C]157[/C][C]0.0551628794160264[/C][C]0.110325758832053[/C][C]0.944837120583974[/C][/ROW]
[ROW][C]158[/C][C]0.0482704122823367[/C][C]0.0965408245646734[/C][C]0.951729587717663[/C][/ROW]
[ROW][C]159[/C][C]0.0472261086820218[/C][C]0.0944522173640437[/C][C]0.952773891317978[/C][/ROW]
[ROW][C]160[/C][C]0.0404930281933112[/C][C]0.0809860563866224[/C][C]0.959506971806689[/C][/ROW]
[ROW][C]161[/C][C]0.0334124305697177[/C][C]0.0668248611394353[/C][C]0.966587569430282[/C][/ROW]
[ROW][C]162[/C][C]0.0274667952760031[/C][C]0.0549335905520062[/C][C]0.972533204723997[/C][/ROW]
[ROW][C]163[/C][C]0.0228756533010375[/C][C]0.0457513066020749[/C][C]0.977124346698963[/C][/ROW]
[ROW][C]164[/C][C]0.0192964132818165[/C][C]0.0385928265636331[/C][C]0.980703586718183[/C][/ROW]
[ROW][C]165[/C][C]0.0169353563376050[/C][C]0.0338707126752100[/C][C]0.983064643662395[/C][/ROW]
[ROW][C]166[/C][C]0.0171843050634623[/C][C]0.0343686101269246[/C][C]0.982815694936538[/C][/ROW]
[ROW][C]167[/C][C]0.0138076243872405[/C][C]0.027615248774481[/C][C]0.98619237561276[/C][/ROW]
[ROW][C]168[/C][C]0.0203735861261563[/C][C]0.0407471722523127[/C][C]0.979626413873844[/C][/ROW]
[ROW][C]169[/C][C]0.0201928859457739[/C][C]0.0403857718915477[/C][C]0.979807114054226[/C][/ROW]
[ROW][C]170[/C][C]0.0188580171726754[/C][C]0.0377160343453509[/C][C]0.981141982827325[/C][/ROW]
[ROW][C]171[/C][C]0.0181349653406303[/C][C]0.0362699306812606[/C][C]0.98186503465937[/C][/ROW]
[ROW][C]172[/C][C]0.0146941965866968[/C][C]0.0293883931733937[/C][C]0.985305803413303[/C][/ROW]
[ROW][C]173[/C][C]0.0147422907486943[/C][C]0.0294845814973886[/C][C]0.985257709251306[/C][/ROW]
[ROW][C]174[/C][C]0.0164226161640721[/C][C]0.0328452323281442[/C][C]0.983577383835928[/C][/ROW]
[ROW][C]175[/C][C]0.0219494596798690[/C][C]0.0438989193597379[/C][C]0.978050540320131[/C][/ROW]
[ROW][C]176[/C][C]0.0176531523212624[/C][C]0.0353063046425249[/C][C]0.982346847678738[/C][/ROW]
[ROW][C]177[/C][C]0.0143826922510692[/C][C]0.0287653845021384[/C][C]0.98561730774893[/C][/ROW]
[ROW][C]178[/C][C]0.0117427428384760[/C][C]0.0234854856769521[/C][C]0.988257257161524[/C][/ROW]
[ROW][C]179[/C][C]0.00919215979401736[/C][C]0.0183843195880347[/C][C]0.990807840205983[/C][/ROW]
[ROW][C]180[/C][C]0.00800536172863925[/C][C]0.0160107234572785[/C][C]0.99199463827136[/C][/ROW]
[ROW][C]181[/C][C]0.00660360418668579[/C][C]0.0132072083733716[/C][C]0.993396395813314[/C][/ROW]
[ROW][C]182[/C][C]0.00534521714955178[/C][C]0.0106904342991036[/C][C]0.994654782850448[/C][/ROW]
[ROW][C]183[/C][C]0.00560936622575513[/C][C]0.0112187324515103[/C][C]0.994390633774245[/C][/ROW]
[ROW][C]184[/C][C]0.00443647295033514[/C][C]0.00887294590067028[/C][C]0.995563527049665[/C][/ROW]
[ROW][C]185[/C][C]0.094086539900981[/C][C]0.188173079801962[/C][C]0.905913460099019[/C][/ROW]
[ROW][C]186[/C][C]0.0816845811721888[/C][C]0.163369162344378[/C][C]0.918315418827811[/C][/ROW]
[ROW][C]187[/C][C]0.0928439802674408[/C][C]0.185687960534882[/C][C]0.90715601973256[/C][/ROW]
[ROW][C]188[/C][C]0.0802127135646717[/C][C]0.160425427129343[/C][C]0.919787286435328[/C][/ROW]
[ROW][C]189[/C][C]0.0679596339456148[/C][C]0.135919267891230[/C][C]0.932040366054385[/C][/ROW]
[ROW][C]190[/C][C]0.0563561435032724[/C][C]0.112712287006545[/C][C]0.943643856496728[/C][/ROW]
[ROW][C]191[/C][C]0.0497111618841623[/C][C]0.0994223237683247[/C][C]0.950288838115838[/C][/ROW]
[ROW][C]192[/C][C]0.0419611933152232[/C][C]0.0839223866304465[/C][C]0.958038806684777[/C][/ROW]
[ROW][C]193[/C][C]0.0487155279839566[/C][C]0.0974310559679132[/C][C]0.951284472016043[/C][/ROW]
[ROW][C]194[/C][C]0.0522890666310367[/C][C]0.104578133262073[/C][C]0.947710933368963[/C][/ROW]
[ROW][C]195[/C][C]0.0443811738269538[/C][C]0.0887623476539076[/C][C]0.955618826173046[/C][/ROW]
[ROW][C]196[/C][C]0.0370263282172378[/C][C]0.0740526564344756[/C][C]0.962973671782762[/C][/ROW]
[ROW][C]197[/C][C]0.0483157061172391[/C][C]0.0966314122344782[/C][C]0.95168429388276[/C][/ROW]
[ROW][C]198[/C][C]0.0395862946218533[/C][C]0.0791725892437066[/C][C]0.960413705378147[/C][/ROW]
[ROW][C]199[/C][C]0.0367011562951482[/C][C]0.0734023125902964[/C][C]0.963298843704852[/C][/ROW]
[ROW][C]200[/C][C]0.0310398676134195[/C][C]0.062079735226839[/C][C]0.96896013238658[/C][/ROW]
[ROW][C]201[/C][C]0.0292219724944844[/C][C]0.0584439449889688[/C][C]0.970778027505516[/C][/ROW]
[ROW][C]202[/C][C]0.0243805707067269[/C][C]0.0487611414134538[/C][C]0.975619429293273[/C][/ROW]
[ROW][C]203[/C][C]0.0313053691066294[/C][C]0.0626107382132588[/C][C]0.96869463089337[/C][/ROW]
[ROW][C]204[/C][C]0.0356803177739386[/C][C]0.0713606355478772[/C][C]0.964319682226061[/C][/ROW]
[ROW][C]205[/C][C]0.0389063363767209[/C][C]0.0778126727534419[/C][C]0.96109366362328[/C][/ROW]
[ROW][C]206[/C][C]0.0308791545420775[/C][C]0.0617583090841551[/C][C]0.969120845457922[/C][/ROW]
[ROW][C]207[/C][C]0.0303422228248083[/C][C]0.0606844456496166[/C][C]0.969657777175192[/C][/ROW]
[ROW][C]208[/C][C]0.024949872731147[/C][C]0.049899745462294[/C][C]0.975050127268853[/C][/ROW]
[ROW][C]209[/C][C]0.0278681412054717[/C][C]0.0557362824109434[/C][C]0.972131858794528[/C][/ROW]
[ROW][C]210[/C][C]0.0225417426210896[/C][C]0.0450834852421793[/C][C]0.97745825737891[/C][/ROW]
[ROW][C]211[/C][C]0.0249775332931389[/C][C]0.0499550665862777[/C][C]0.975022466706861[/C][/ROW]
[ROW][C]212[/C][C]0.0399735087422991[/C][C]0.0799470174845981[/C][C]0.960026491257701[/C][/ROW]
[ROW][C]213[/C][C]0.0315871062441668[/C][C]0.0631742124883335[/C][C]0.968412893755833[/C][/ROW]
[ROW][C]214[/C][C]0.0441589425989401[/C][C]0.0883178851978801[/C][C]0.95584105740106[/C][/ROW]
[ROW][C]215[/C][C]0.0380593092869368[/C][C]0.0761186185738735[/C][C]0.961940690713063[/C][/ROW]
[ROW][C]216[/C][C]0.0297508259210554[/C][C]0.0595016518421109[/C][C]0.970249174078945[/C][/ROW]
[ROW][C]217[/C][C]0.0321955312729058[/C][C]0.0643910625458115[/C][C]0.967804468727094[/C][/ROW]
[ROW][C]218[/C][C]0.0275294909822642[/C][C]0.0550589819645284[/C][C]0.972470509017736[/C][/ROW]
[ROW][C]219[/C][C]0.0247418070044547[/C][C]0.0494836140089093[/C][C]0.975258192995545[/C][/ROW]
[ROW][C]220[/C][C]0.0189633773705708[/C][C]0.0379267547411415[/C][C]0.98103662262943[/C][/ROW]
[ROW][C]221[/C][C]0.0168947339209663[/C][C]0.0337894678419326[/C][C]0.983105266079034[/C][/ROW]
[ROW][C]222[/C][C]0.0124206485849155[/C][C]0.0248412971698309[/C][C]0.987579351415085[/C][/ROW]
[ROW][C]223[/C][C]0.0093117418620164[/C][C]0.0186234837240328[/C][C]0.990688258137984[/C][/ROW]
[ROW][C]224[/C][C]0.00750211854397697[/C][C]0.0150042370879539[/C][C]0.992497881456023[/C][/ROW]
[ROW][C]225[/C][C]0.00654705616129064[/C][C]0.0130941123225813[/C][C]0.99345294383871[/C][/ROW]
[ROW][C]226[/C][C]0.0149951903144659[/C][C]0.0299903806289319[/C][C]0.985004809685534[/C][/ROW]
[ROW][C]227[/C][C]0.0115416184372463[/C][C]0.0230832368744927[/C][C]0.988458381562754[/C][/ROW]
[ROW][C]228[/C][C]0.00835031892340789[/C][C]0.0167006378468158[/C][C]0.991649681076592[/C][/ROW]
[ROW][C]229[/C][C]0.0060968342432109[/C][C]0.0121936684864218[/C][C]0.993903165756789[/C][/ROW]
[ROW][C]230[/C][C]0.00441036251732997[/C][C]0.00882072503465995[/C][C]0.99558963748267[/C][/ROW]
[ROW][C]231[/C][C]0.00439461457994107[/C][C]0.00878922915988214[/C][C]0.99560538542006[/C][/ROW]
[ROW][C]232[/C][C]0.00814497957146643[/C][C]0.0162899591429329[/C][C]0.991855020428534[/C][/ROW]
[ROW][C]233[/C][C]0.0377565442118784[/C][C]0.0755130884237568[/C][C]0.962243455788122[/C][/ROW]
[ROW][C]234[/C][C]0.0542942200569106[/C][C]0.108588440113821[/C][C]0.94570577994309[/C][/ROW]
[ROW][C]235[/C][C]0.0405065857547010[/C][C]0.0810131715094021[/C][C]0.959493414245299[/C][/ROW]
[ROW][C]236[/C][C]0.0361101125951766[/C][C]0.0722202251903533[/C][C]0.963889887404823[/C][/ROW]
[ROW][C]237[/C][C]0.246505700570198[/C][C]0.493011401140395[/C][C]0.753494299429802[/C][/ROW]
[ROW][C]238[/C][C]0.200782130963978[/C][C]0.401564261927957[/C][C]0.799217869036022[/C][/ROW]
[ROW][C]239[/C][C]0.180044405468033[/C][C]0.360088810936067[/C][C]0.819955594531967[/C][/ROW]
[ROW][C]240[/C][C]0.142128535333137[/C][C]0.284257070666275[/C][C]0.857871464666863[/C][/ROW]
[ROW][C]241[/C][C]0.113707343103352[/C][C]0.227414686206705[/C][C]0.886292656896648[/C][/ROW]
[ROW][C]242[/C][C]0.0945301032407307[/C][C]0.189060206481461[/C][C]0.90546989675927[/C][/ROW]
[ROW][C]243[/C][C]0.0879023187197933[/C][C]0.175804637439587[/C][C]0.912097681280207[/C][/ROW]
[ROW][C]244[/C][C]0.153550434222244[/C][C]0.307100868444488[/C][C]0.846449565777756[/C][/ROW]
[ROW][C]245[/C][C]0.137630339717254[/C][C]0.275260679434508[/C][C]0.862369660282746[/C][/ROW]
[ROW][C]246[/C][C]0.110109330538686[/C][C]0.220218661077373[/C][C]0.889890669461314[/C][/ROW]
[ROW][C]247[/C][C]0.0777706008222238[/C][C]0.155541201644448[/C][C]0.922229399177776[/C][/ROW]
[ROW][C]248[/C][C]0.0666948470256238[/C][C]0.133389694051248[/C][C]0.933305152974376[/C][/ROW]
[ROW][C]249[/C][C]0.0624888270323013[/C][C]0.124977654064603[/C][C]0.937511172967699[/C][/ROW]
[ROW][C]250[/C][C]0.0773809930539605[/C][C]0.154761986107921[/C][C]0.92261900694604[/C][/ROW]
[ROW][C]251[/C][C]0.0460549764082260[/C][C]0.0921099528164521[/C][C]0.953945023591774[/C][/ROW]
[ROW][C]252[/C][C]0.112285664162278[/C][C]0.224571328324556[/C][C]0.887714335837722[/C][/ROW]
[ROW][C]253[/C][C]0.234998511095394[/C][C]0.469997022190787[/C][C]0.765001488904606[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96530&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96530&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
110.2344495241033230.4688990482066470.765550475896677
120.1202935178405570.2405870356811130.879706482159443
130.08155415734578020.1631083146915600.91844584265422
140.1028747764979180.2057495529958360.897125223502082
150.05875197565155020.1175039513031000.94124802434845
160.03916866759316340.07833733518632680.960831332406837
170.06301911844417490.1260382368883500.936980881555825
180.255864327935310.511728655870620.74413567206469
190.1942166329001510.3884332658003010.80578336709985
200.1377648833346390.2755297666692780.862235116665361
210.09860626155137020.1972125231027400.90139373844863
220.09685339904277270.1937067980855450.903146600957227
230.2570543779111390.5141087558222780.742945622088861
240.3214954184239470.6429908368478930.678504581576054
250.2948695385950190.5897390771900380.705130461404981
260.2774478577119770.5548957154239540.722552142288023
270.3520988888725580.7041977777451160.647901111127442
280.3638496488593420.7276992977186840.636150351140658
290.3467855921475900.6935711842951810.65321440785241
300.3808983862722670.7617967725445330.619101613727733
310.3286758031111610.6573516062223230.671324196888839
320.2894928679699320.5789857359398640.710507132030068
330.2624907774068980.5249815548137960.737509222593102
340.2263044170330470.4526088340660930.773695582966953
350.1878805418145860.3757610836291730.812119458185414
360.3049298148882160.6098596297764330.695070185111784
370.3349710741511980.6699421483023970.665028925848802
380.3259636225842430.6519272451684870.674036377415757
390.356022739855430.712045479710860.64397726014457
400.3342094491346500.6684188982693010.66579055086535
410.2980013652937390.5960027305874780.701998634706261
420.2638357288282340.5276714576564680.736164271171766
430.2782742652114290.5565485304228570.721725734788571
440.2365365213239350.473073042647870.763463478676065
450.2144422801981490.4288845603962980.78555771980185
460.3926897177725710.7853794355451420.607310282227429
470.5455190334856540.9089619330286920.454480966514346
480.4965487764023290.9930975528046580.503451223597671
490.4832161607247480.9664323214494970.516783839275252
500.4683902306446510.9367804612893030.531609769355349
510.423671720349910.847343440699820.57632827965009
520.3781691975725310.7563383951450610.621830802427469
530.3866036095760970.7732072191521930.613396390423903
540.3697095512825990.7394191025651980.630290448717401
550.3609375571723190.7218751143446380.639062442827681
560.3393852385237370.6787704770474740.660614761476263
570.2997777542626480.5995555085252950.700222245737352
580.2711577202394290.5423154404788580.728842279760571
590.236694269796530.473388539593060.76330573020347
600.2424586147505530.4849172295011070.757541385249447
610.2186501591049580.4373003182099170.781349840895042
620.1917356708049260.3834713416098510.808264329195074
630.1637320578437630.3274641156875260.836267942156237
640.137978888894910.275957777789820.86202111110509
650.1190738662615490.2381477325230970.880926133738452
660.1102288514213880.2204577028427760.889771148578612
670.1059861502412980.2119723004825950.894013849758702
680.2230586793560410.4461173587120830.776941320643959
690.3130388526634780.6260777053269570.686961147336522
700.2821425098269310.5642850196538630.717857490173069
710.3979023773212310.7958047546424620.602097622678769
720.3598978352378190.7197956704756380.640102164762181
730.3515646464888900.7031292929777790.64843535351111
740.3361970271152240.6723940542304480.663802972884776
750.3040241548740810.6080483097481620.695975845125919
760.3695447255589490.7390894511178980.630455274441051
770.3338177811756490.6676355623512990.66618221882435
780.312977052653640.625954105307280.68702294734636
790.3260565689197130.6521131378394270.673943431080287
800.2984783473115510.5969566946231030.701521652688449
810.2703419068908420.5406838137816850.729658093109158
820.2394460425874990.4788920851749970.760553957412501
830.2151396628227040.4302793256454080.784860337177296
840.1879137227384090.3758274454768190.81208627726159
850.1846071916740810.3692143833481620.815392808325919
860.15957251204160.31914502408320.8404274879584
870.1403225373613210.2806450747226420.859677462638679
880.1307388017647960.2614776035295920.869261198235204
890.1129764378758910.2259528757517820.887023562124109
900.1102031142192690.2204062284385380.889796885780731
910.09429193694486640.1885838738897330.905708063055134
920.08142409060866280.1628481812173260.918575909391337
930.06916220468658730.1383244093731750.930837795313413
940.07105056196411580.1421011239282320.928949438035884
950.06420477509781160.1284095501956230.935795224902188
960.05379758650354240.1075951730070850.946202413496458
970.05943151463996810.1188630292799360.940568485360032
980.04922705113043840.09845410226087680.950772948869562
990.0403637971239430.0807275942478860.959636202876057
1000.03531497706865640.07062995413731280.964685022931344
1010.03133001394681710.06266002789363430.968669986053183
1020.03688207108464570.07376414216929150.963117928915354
1030.03165139025063830.06330278050127660.968348609749362
1040.02858591411915220.05717182823830440.971414085880848
1050.0338171358137690.0676342716275380.966182864186231
1060.02971708786873170.05943417573746340.970282912131268
1070.02413307862849510.04826615725699010.975866921371505
1080.02400791135008460.04801582270016930.975992088649915
1090.01945150490639040.03890300981278080.98054849509361
1100.01591366614214870.03182733228429730.984086333857851
1110.01261465227192150.02522930454384290.987385347728079
1120.01303812775868150.02607625551736290.986961872241318
1130.01164521464788090.02329042929576170.98835478535212
1140.01672065608724730.03344131217449460.983279343912753
1150.01597102344518570.03194204689037130.984028976554814
1160.01528119780168540.03056239560337090.984718802198315
1170.01263902994539360.02527805989078720.987360970054606
1180.01262195624937530.02524391249875060.987378043750625
1190.01026120162714520.02052240325429040.989738798372855
1200.009038025678921760.01807605135784350.990961974321078
1210.007353567803015460.01470713560603090.992646432196985
1220.01131955121710510.02263910243421010.988680448782895
1230.009538495994803950.01907699198960790.990461504005196
1240.008473116391724320.01694623278344860.991526883608276
1250.006935559729241560.01387111945848310.993064440270758
1260.005650421037164760.01130084207432950.994349578962835
1270.005087164012794030.01017432802558810.994912835987206
1280.004098793520274390.008197587040548790.995901206479726
1290.00604886982758740.01209773965517480.993951130172413
1300.00655323802881230.01310647605762460.993446761971188
1310.01354029438996440.02708058877992880.986459705610036
1320.01629872750422810.03259745500845620.983701272495772
1330.01758236498167110.03516472996334230.982417635018329
1340.016983344991950.03396668998390.98301665500805
1350.01388037447347760.02776074894695520.986119625526522
1360.01171233869970190.02342467739940380.988287661300298
1370.009374643338209990.01874928667642000.99062535666179
1380.01141690215884600.02283380431769210.988583097841154
1390.009937139879518860.01987427975903770.990062860120481
1400.01129281549976420.02258563099952850.988707184500236
1410.01751656482001290.03503312964002580.982483435179987
1420.01592895790096370.03185791580192740.984071042099036
1430.01268316359323370.02536632718646740.987316836406766
1440.01344583330598290.02689166661196590.986554166694017
1450.02564031348952430.05128062697904860.974359686510476
1460.03141841095330070.06283682190660140.9685815890467
1470.03297957803633630.06595915607267260.967020421963664
1480.02977342271015380.05954684542030760.970226577289846
1490.02481272874093830.04962545748187650.975187271259062
1500.03443623206436970.06887246412873930.96556376793563
1510.02971241893936230.05942483787872460.970287581060638
1520.03128065816489960.06256131632979920.9687193418351
1530.0638804329782790.1277608659565580.936119567021721
1540.06276143572712750.1255228714542550.937238564272872
1550.07217477719129780.1443495543825960.927825222808702
1560.0617478574339070.1234957148678140.938252142566093
1570.05516287941602640.1103257588320530.944837120583974
1580.04827041228233670.09654082456467340.951729587717663
1590.04722610868202180.09445221736404370.952773891317978
1600.04049302819331120.08098605638662240.959506971806689
1610.03341243056971770.06682486113943530.966587569430282
1620.02746679527600310.05493359055200620.972533204723997
1630.02287565330103750.04575130660207490.977124346698963
1640.01929641328181650.03859282656363310.980703586718183
1650.01693535633760500.03387071267521000.983064643662395
1660.01718430506346230.03436861012692460.982815694936538
1670.01380762438724050.0276152487744810.98619237561276
1680.02037358612615630.04074717225231270.979626413873844
1690.02019288594577390.04038577189154770.979807114054226
1700.01885801717267540.03771603434535090.981141982827325
1710.01813496534063030.03626993068126060.98186503465937
1720.01469419658669680.02938839317339370.985305803413303
1730.01474229074869430.02948458149738860.985257709251306
1740.01642261616407210.03284523232814420.983577383835928
1750.02194945967986900.04389891935973790.978050540320131
1760.01765315232126240.03530630464252490.982346847678738
1770.01438269225106920.02876538450213840.98561730774893
1780.01174274283847600.02348548567695210.988257257161524
1790.009192159794017360.01838431958803470.990807840205983
1800.008005361728639250.01601072345727850.99199463827136
1810.006603604186685790.01320720837337160.993396395813314
1820.005345217149551780.01069043429910360.994654782850448
1830.005609366225755130.01121873245151030.994390633774245
1840.004436472950335140.008872945900670280.995563527049665
1850.0940865399009810.1881730798019620.905913460099019
1860.08168458117218880.1633691623443780.918315418827811
1870.09284398026744080.1856879605348820.90715601973256
1880.08021271356467170.1604254271293430.919787286435328
1890.06795963394561480.1359192678912300.932040366054385
1900.05635614350327240.1127122870065450.943643856496728
1910.04971116188416230.09942232376832470.950288838115838
1920.04196119331522320.08392238663044650.958038806684777
1930.04871552798395660.09743105596791320.951284472016043
1940.05228906663103670.1045781332620730.947710933368963
1950.04438117382695380.08876234765390760.955618826173046
1960.03702632821723780.07405265643447560.962973671782762
1970.04831570611723910.09663141223447820.95168429388276
1980.03958629462185330.07917258924370660.960413705378147
1990.03670115629514820.07340231259029640.963298843704852
2000.03103986761341950.0620797352268390.96896013238658
2010.02922197249448440.05844394498896880.970778027505516
2020.02438057070672690.04876114141345380.975619429293273
2030.03130536910662940.06261073821325880.96869463089337
2040.03568031777393860.07136063554787720.964319682226061
2050.03890633637672090.07781267275344190.96109366362328
2060.03087915454207750.06175830908415510.969120845457922
2070.03034222282480830.06068444564961660.969657777175192
2080.0249498727311470.0498997454622940.975050127268853
2090.02786814120547170.05573628241094340.972131858794528
2100.02254174262108960.04508348524217930.97745825737891
2110.02497753329313890.04995506658627770.975022466706861
2120.03997350874229910.07994701748459810.960026491257701
2130.03158710624416680.06317421248833350.968412893755833
2140.04415894259894010.08831788519788010.95584105740106
2150.03805930928693680.07611861857387350.961940690713063
2160.02975082592105540.05950165184211090.970249174078945
2170.03219553127290580.06439106254581150.967804468727094
2180.02752949098226420.05505898196452840.972470509017736
2190.02474180700445470.04948361400890930.975258192995545
2200.01896337737057080.03792675474114150.98103662262943
2210.01689473392096630.03378946784193260.983105266079034
2220.01242064858491550.02484129716983090.987579351415085
2230.00931174186201640.01862348372403280.990688258137984
2240.007502118543976970.01500423708795390.992497881456023
2250.006547056161290640.01309411232258130.99345294383871
2260.01499519031446590.02999038062893190.985004809685534
2270.01154161843724630.02308323687449270.988458381562754
2280.008350318923407890.01670063784681580.991649681076592
2290.00609683424321090.01219366848642180.993903165756789
2300.004410362517329970.008820725034659950.99558963748267
2310.004394614579941070.008789229159882140.99560538542006
2320.008144979571466430.01628995914293290.991855020428534
2330.03775654421187840.07551308842375680.962243455788122
2340.05429422005691060.1085884401138210.94570577994309
2350.04050658575470100.08101317150940210.959493414245299
2360.03611011259517660.07222022519035330.963889887404823
2370.2465057005701980.4930114011403950.753494299429802
2380.2007821309639780.4015642619279570.799217869036022
2390.1800444054680330.3600888109360670.819955594531967
2400.1421285353331370.2842570706662750.857871464666863
2410.1137073431033520.2274146862067050.886292656896648
2420.09453010324073070.1890602064814610.90546989675927
2430.08790231871979330.1758046374395870.912097681280207
2440.1535504342222440.3071008684444880.846449565777756
2450.1376303397172540.2752606794345080.862369660282746
2460.1101093305386860.2202186610773730.889890669461314
2470.07777060082222380.1555412016444480.922229399177776
2480.06669484702562380.1333896940512480.933305152974376
2490.06248882703230130.1249776540646030.937511172967699
2500.07738099305396050.1547619861079210.92261900694604
2510.04605497640822600.09210995281645210.953945023591774
2520.1122856641622780.2245713283245560.887714335837722
2530.2349985110953940.4699970221907870.765001488904606







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level40.0164609053497942NOK
5% type I error level790.325102880658436NOK
10% type I error level1280.526748971193416NOK

\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 & 4 & 0.0164609053497942 & NOK \tabularnewline
5% type I error level & 79 & 0.325102880658436 & NOK \tabularnewline
10% type I error level & 128 & 0.526748971193416 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96530&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]4[/C][C]0.0164609053497942[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]79[/C][C]0.325102880658436[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]128[/C][C]0.526748971193416[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96530&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96530&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 level40.0164609053497942NOK
5% type I error level790.325102880658436NOK
10% type I error level1280.526748971193416NOK



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