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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of 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 Wed, 30 Apr 2025 20:40:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=96530, Retrieved Wed, 30 Apr 2025 20:40:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact1076

Tree of Dependent Computations

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]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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

Tables (Output of Computation)





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:  
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:  
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:  
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:  
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:  
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
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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:  
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
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1060.02971708786873170.05943417573746340.970282912131268
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1080.02400791135008460.04801582270016930.975992088649915
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1100.01591366614214870.03182733228429730.984086333857851
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1120.01303812775868150.02607625551736290.986961872241318
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1200.009038025678921760.01807605135784350.990961974321078
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1330.01758236498167110.03516472996334230.982417635018329
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1350.01388037447347760.02776074894695520.986119625526522
1360.01171233869970190.02342467739940380.988287661300298
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1390.009937139879518860.01987427975903770.990062860120481
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1480.02977342271015380.05954684542030760.970226577289846
1490.02481272874093830.04962545748187650.975187271259062
1500.03443623206436970.06887246412873930.96556376793563
1510.02971241893936230.05942483787872460.970287581060638
1520.03128065816489960.06256131632979920.9687193418351
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1600.04049302819331120.08098605638662240.959506971806689
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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
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2360.03611011259517660.07222022519035330.963889887404823
2370.2465057005701980.4930114011403950.753494299429802
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2420.09453010324073070.1890602064814610.90546989675927
2430.08790231871979330.1758046374395870.912097681280207
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2450.1376303397172540.2752606794345080.862369660282746
2460.1101093305386860.2202186610773730.889890669461314
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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:  
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The GUIDs for individual cells are displayed in the table below:

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


Figures (Output of Computation)

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Figure 10
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Input Parameters & R Code

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')
}